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DOE OSTI2020

Impact of uranium oxide (UO 2 ) fuel with molybdenum (Mo) inserts on pressurized water reactor performance and safety

This work investigates nuclear reactor performance and safety characteristics of UO 2 with high thermal conductivity Mo insert structures by using multiphysics modeling techniques. Additionally, the purpose of this study is to use scoping analyses to quantify the impact of using Mo inserts from neutronic and heat transfer standpoints. Attention is given to reactor performance parameters, such as cycle length, maximum fuel temperature, temperature gradients in the fuel, and stored energy in the fuel. The finite-element code BISON and the Monte Carlo particle transport code Serpent were used to perform sensitivity analyses on the Mo insert geometry to optimize the insert design and inform larger scale modeling that required the homogenization of the UO 2 and Mo. Although BISON is often used as a fuel performance analysis tool, it is used in this context for heat transfer analysis only. Fuel performance optimization is outside the scope of the current study, but would be important for future work focused on this concept. The results showed that the insert had little impact on neutronic performance and that homogenizing the UO 2 and Mo was acceptable for reactor physics calculations. Reactivity temperature coefficients calculated using homogeneous UO 2 -Mo were shown to be relatively similar to UO 2 , but higher Mo content and 235 U enrichment can reduce the worth of soluble boron and control rods. The effect of insert geometry on heat transfer was much greater, and an approximately 15–20% difference in maximum fuel temperature was predicted between the best and worst performing heat transfer geometries. Furthermore, thermal conductivity calibration based on the finite element analysis results was performed to improve the accuracy of temperature predictions in reactor analysis models that homogenized the UO 2 -Mo fuel. Compared with UO 2 in a pressurized water reactor (PWR), the optimized UO 2 -Mo design increased the margin to fuel melt by 13–32% across the fuel cycle, but it requires the 235U enrichment to exceed 5% to match the cycle length of conventional UO 2 .

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS2015

The Effects of Sweeping Jet Actuator Parameters on Flow Separation Control

A parametric experimental study was performed with sweeping jet actuators (fluidic oscillators) to determine their effectiveness in controlling flow separation on an adverse pressure gradient ramp. Actuator parameters that were investigated include blowing coefficients, operation mode, pitch and spreading angles, streamwise location, aspect ratio, and scale. Surface pressure measurements and surface oil flow visualization were used to characterize the effects of these parameters on the actuator performance. 2D Particle Image Velocimetry measurements of the flow field over the ramp and hot-wire measurements of the actuator's jet flow were also obtained for selective cases. In addition, the sweeping jet actuators were compared to other well-known flow control techniques such as micro-vortex generators, steady blowing, and steady vortex-generating jets. The results confirm that the sweeping jet actuators are more effective than steady blowing and steady vortex-generating jets. The results also suggest that an actuator with a larger spreading angle placed closer to the location where the flow separates provides better performance. For the cases tested, an actuator with an aspect ratio, which is the width/depth of the actuator throat, of 2 was found to be optimal. For a fixed momentum coefficient, decreasing the aspect ratio to 1 produced weaker vortices while increasing the aspect ratio to 4 reduced coverage area. Although scaling down the actuator (based on the throat dimensions) from 0.25 inch x 0.125 inch to 0.15 inch x 0.075 inch resulted in similar flow control performance, scaling down the actuator further to 0.075 inch x 0.0375 inch reduced the actuator efficiency by reducing the coverage area and the amount of mixing in the near-wall region. The results of this study provide insight that can be used to design and select the optimal sweeping jet actuator configuration for flow control applications.

Koklu, Mehti↗

DOE OSTI2026

Ionic Liquids for Direct Air Capture of CO 2 using Electric‐Field‐Mediated Moisture Gradient Process (Final Technical Report)

The final report provides executive summary, a list of publications, and information on training graduate students and postdoctoral researchers. We carried out computational and experimental research on understanding molecular-level mechanism of how CO 2 is absorbed in a solution containing ethylene glycol as the solvent and KOH as the salt in the presence of ionic liquids and under the influence of electric field. In doing so, we developed an automated high-throughput method which allowed us to measure the solubility of CO 2 in a large number of ionic liquids, considerably speeding up the CO 2 solubility measurement. We also demonstrated how varying the concentration of ionic liquids in ethylene glycol can result in a maximum in ionic conductivity. Reaction of CO 2 and subsequent release results in a 50% reduction when the process is operated at an ionic liquid-ethylene glycol concentration yielding maximum ionic conductivity amongst all the ionic liquid-ethylene glycol combinations studied as a part of this research. We utilized machine learning models to identify unique ionic liquid-solvent combinations with ionic conductivity much higher than that measured for ionic liquid-ethylene glycol combinations. We demonstrated that the rate of CO 2 reaction with KOH in ethylene glycol can be optimized with the type of ionic liquid and its concentration. Overall, the research led to publication of 10 peer-reviewed research articles and several presentations at national conferences. We are also in the process of developing additional manuscripts based on the research carried out as a part of this project. Two graduate students and two postdoctoral researchers were supported on the funding.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Cryogenic System Preliminary Design for a 0.5m-Long, Conduction-Cooled Nb3Sn Undulator Magnet Prototype

There are several NbTi superconducting undulator (SCU) magnets currently in operation at the Advanced Photon Source (APS) at Argonne National Laboratory (ANL). The development on Nb3Sn-based superconducting undulator magnets at APS is underway due to the potential to further enhance the performance of the SCUs. Superconducting undulator magnets need to keep temperature gradients minimized in order to retain thermal and operating current margin. We have designed the thermal links for efficient heat conduction using 3D finite element analysis (FEA) simulation in COMSOL Multiphysics software, which was later used for the calculation of the temperature distribution across a 0.5 m long, conduction-cooled, Nb3Sn undulator magnet prototype that includes both conductive heat transfer and radiative heating components. We have modelled the evolution of the thermal properties of the magnet winding as well as other cold parts during cool-down from ambient temperature with the operation of a SHI RDK-415D cryocooler to examine the estimated time that is needed for the cooldown as well as the baseline temperature we could achieve. A key result was that a maximum coil delta T = 0.11 K along the designed thermal links and a temperature range of 3.42 K-3.53 K for the winding were predicted at steady state. A pair of G10 support rods for carrying the magnet as well as a pair of current leads made of metals were also designed and optimized for the testing system, targeting for an operation temperature of 4 K and a coil current of 950 A DC.

Zhang, Danlu↗

DOE OSTI2025

TropiRoot 1.0: Database of tropical root characteristics across environments

Tropical ecosystems contain the world's largest biodiversity of vascular plants. Yet, our understanding of tropical functional diversity and its contribution to global diversity patterns is constrained by data availability. This discrepancy underscores an urgent need to bridge data gaps by incorporating comprehensive tropical root data into global datasets. Here, we provide a database of tropical root characteristics. This new database, TropiRoot 1.0, will be instrumental in evaluating an array of hypotheses pertaining to root functional ecology and plant biogeography, both within the tropics and relative to other global biomes. The data compilation was conducted by the TropiRoot Initiative, in partnership with the Fine-Root Ecology Database (FRED) and the Global Root Trait (GRooT) database, Colorado State University (CSU) and the Smithsonian Tropical Research Institute (STRI). Literature search and data extraction were conducted between 2020 and 2024. Literature was identified using Web of Science, Scopus, and complemented using the expert knowledge of members of TropiRoot. To provide broad environmental and geographical distributions, literature searches included root characteristics (traits) across global change drivers, natural gradients, and from different continents. We adopted FRED standardized data columns and streamlined the format to enhance accessibility for data extraction across various user groups. This optimized framework resulted in a smaller, yet comprehensive datasheet. To make the database compatible with other global root trait initiatives, column identification was standardized following the codes provided by FRED. These efforts culminated in data extracted from 104 new sources, resulting in more than 8000 rows of data (either species or community data). Most of the data in TropiRoot 1.0 include root characteristics such as root biomass, morphology, root dynamics, mass fraction, architecture, anatomy, physiology, and root chemistry. This initiative represents a 30% increase in the currently available data for tropical roots in FRED. TropiRoot 1.0 contains root characteristics from 25 different countries, where seven are located in Asia, six in South America, five in Central America and the Caribbean, four in Africa, two in North America, and 1 in Oceania. Due to the volume of data, when ancillary data were available, including soil data, these data were either extracted and included in the database or its availability was recorded in an additional column. Multiple contributors checked the entries for outliers during the collation process to ensure data quality. For text-based observations, we examined all cells to ensure that their content relates to their specific categories. For numerical observations, we ordered each numerical value from least to greatest and plotted the values, checking apparent outliers against the data in their respective sources and correcting or removing incorrect or impossible values. Some data (soil and aboveground) have different columns for the same variable presented in different units, including originally published units, but root characteristics data had units converted to match those reported in FRED. By filling a gap from global databases, TropiRoot 1.0 expands our knowledge of otherwise so far underrepresented regions and our ability to assess global trends. This advancement can be used to improve tropical forest representation in vegetation models. The data are freely available and should be cited when used.

FRED↗

DOE OSTI2020

Atomic-Level Understanding of Surface Reconstruction Based on Li[Ni x Mn y Co 1–x–y ]O 2 Single-Crystal Studies

The stability of cathode particle surfaces that are directly exposed to the electrolyte is one of the most crucial and determining factors for cathode performance at high operating voltages. Theory has predicted a strong dependence of surface stability on chemical compositions as well as surface facets of layered oxides, yet conflicting results on the correlations exist as most experimental studies focus on cycled secondary particles recovered from composite electrodes. Here, we synthesize well-formed Li[Ni x Mn y Co 1–x–y ]O 2 (NMC) single-crystal samples, carefully define pristine surface properties, and then monitor their evolution with cycling. Atomic-resolution scanning transmission electron microscopy (STEM) imaging and electron energy loss spectroscopy (EELS) analysis show the formation of a surface reconstruction layer (SRL) as well as an extended surface reduction layer on pristine, Li-permeable non-(001) surfaces, even before cycling. We reveal a transition region with chemical gradient, in which the layered structure gradually densifies and eventually transforms into the SRL on the top surface. Contrary to these observations, no SRL is observed on pristine, Li-impermeable (001) surfaces, revealing the facet-dependent nature of surface reconstructions during particle synthesis. Upon electrochemical cycling, significant composition-and facet-dependent SRL growth is observed. The driving force and mechanism for surface reconstruction are further discussed. The present study provides insights into the origin as well as the nature of SRLs, highlighting the significance of surface engineering in cathode material optimization.

25 ENERGY STORAGE↗

DOE OSTI2025

Reducing heat load density with asymmetric and inclined double-crystal monochromators: principles and requirements revisited

Asymmetric double-crystal monochromators (aDCMs) and inclined DCMs (iDCMs) can significantly expand the X-ray beam footprint and consequently reduce the heat load density and gradient. Based on rigorous dynamical theory calculations, the major principles and properties of aDCMs and iDCMs are presented to guide their design and development, particularly for fourth-generation synchrotrons. In addition to the large beam footprint, aDCMs have very large bandwidths (up to ∼10 eV) and angular acceptance, but the narrow angular acceptance of the second crystal requires precise control of the relative orientations and strains. Based on Fourier coupled-wave diffraction theory calculations, it is rigorously proved that the iDCM has almost the same properties as the conventional symmetric DCM, including the efficiency, angular acceptance, bandwidth, tuning energy range and sensitivity to misalignment. The exception is that, for the extremely inclined geometry that can achieve very large footprint expansion, the iDCM has (beneficially) a larger bandwidth and wider angular acceptance. Inclined diffraction has the `rho-kick effect' that can be cancelled by the second reflection of the iDCM (even with misalignment), except that inhomogeneous strains may cause non-uniform rho-kick angles. At present, fabrication/mounting-induced strains pose low risk since they can be controlled to <0.5 µrad over large areas. The only uncertain challenge is the thermally induced strains, yet it is estimated that these strains are naturally lowered by the large footprint and may be further mitigated by optimized cryogenic cooling to the 1–2 µrad level. Overall, aDCMs and iDCMs have more stringent requirements than normal DCMs, but they are feasible schemes in practice.

asymmetric monochromator↗

DOE OSTI2025

A Novel LDPP-MADDPG Approach for Distributed Power Allocation in mmWave Cellular Networks

This paper considers the problem of distributed beam scheduling and power allocation problem in millimeter- Wave (mmWave) cellular networks, in which multiple Base Stations (BSs) operate as individual operators over a shared spectrum. We propose a novel learning-aided approach that integrates the Lyapunov Drift-Plus-Penalty (LDPP) framework and Multi-agent Deep Deterministic Policy Gradient (MADDPG) reinforcement learning algorithms. This offers a powerful approach to learning stable and constraint-aware policies, reaping the joint benefit of both LDPP and MADDPG, in complex multiagent environments. The major challenge for this approach is to integrate these two approaches in a meaningful and effective manner. The key idea to solve this problem is to introduce a novel feature of local observation that incorporates potential negative value of the reward function due to the stochastic constraints introduced by the LDPP framework. Empirical results demonstrate that our proposed scheme outperforms the baseline methods under various conditions.

99 - GENERAL AND MISCELLANEOUS↗

NASA NTRS2007

Norbornene-Based Polymer Electrolytes for Lithium Cells

Norbornene-based polymers have shown promise as solid electrolytes for lithium-based rechargeable electrochemical cells. These polymers are characterized as single-ion conductors. Single-ion-conducting polymers that can be used in lithium cells have long been sought. Single-ion conductors are preferred to multiple-ion conductors as solid electrolytes because concentration gradients associated with multiple-ion conduction lead to concentration polarization. By minimizing concentration polarization, one can enhance charge and discharge rates. Norbornene sulfonic acid esters have been synthesized by a ring-opening metathesis polymerization technique, using ruthenium-based catalysts. The resulting polymer structures (see figure) include sulfonate ionomers attached to the backbones of the polymer molecules. These molecules are single-ion conductors in that they conduct mobile Li+ ions only; the SO3 anions in these polymers, being tethered to the backbones, do not contribute to ionic conduction. This molecular system is especially attractive in that it is highly amenable to modification through functionalization of the backbone or copolymerization with various monomers. Polymers of this type have been blended with poly(ethylene oxide) to lend mechanical integrity to free-standing films, and the films have been fabricated into solid polymer electrolytes. These electrolytes have been demonstrated to exhibit conductivity of 2 10(exp -5)S/cm (which is high, relative to the conductivities of other solid electrolytes) at ambient temperature, plus acceptably high stability. This type of norbornene-based polymeric solid electrolyte is in the early stages of development. Inasmuch as the method of synthesis of these polymers is inherently flexible and techniques for the fabrication of the polymers into solid electrolytes are amenable to optimization, there is reason to anticipate further improvements.

Cheung, Iris↗

NASA NTRS2004

Method Developed for Improving the Thermomechanical Properties of Silicon Carbide Matrix Composites

Today, a major thrust for achieving engine components with improved thermal capability is the development of fiber-reinforced silicon-carbide (SiC) matrix composites. These materials are not only lighter and capable of higher use temperatures than state-of-the-art metallic alloys and oxide matrix composites (approx. 1100 C), but they can provide significantly better static and dynamic toughness than unreinforced silicon-based monolithic ceramics. However, for successful application in advanced engine systems, the SiC matrix composites should be able to withstand component service stresses and temperatures for the desired component lifetime. Since the high-temperature structural life of ceramic materials is typically controlled by creep-induced flaw growth, a key composite property requirement is the ability to display high creep resistance under these conditions. Also, because of the possibility of severe thermal gradients in the components, the composites should provide maximum thermal conductivity to minimize the development of thermal stresses. State-of-the-art SiC matrix composites are typically fabricated via a three-step process: (1) fabrication of a component-shaped architectural preform reinforced by high-performance fibers, (2) chemical vapor infiltration of a fiber coating material such as boron nitride (BN) into the preform, and (3) infiltration of a SiC matrix into the remaining porous areas in the preform. Generally, the highest performing composites have matrices fabricated by the CVI process, which produces a SiC matrix typically more thermally stable and denser than matrices formed by other approaches. As such, the CVI SiC matrix is able to provide better environmental protection to the coated fibers, plus provide the composite with better resistance to crack propagation. Also, the denser CVI SiC matrix should provide optimal creep resistance and thermal conductivity to the composite. However, for adequate preform infiltration, the CVI SiC matrix process typically has to be conducted at temperatures below 1100 C, which results in a SiC matrix that is fairly dense, but contains metastable atomic defects and is nonstoichiometric because of a small amount of excess silicon. Because these defects typically exist at the matrix grain boundaries, they can scatter thermal phonons and degrade matrix creep resistance by enhancing grain-boundary sliding. To eliminate these defects and improve the thermomechanical properties of ceramic composites with CVI SiC matrices, researchers at the NASA Glenn Research Center developed a high-temperature treatment process that can be used after the CVI SiC matrix is deposited into the fiber preform.

Bhatt, Ramakrishna T.↗

DOE OSTI2022

A feasibility assessment for co-locating and powering offshore aquaculture with wave energy in the United States

Offshore aquaculture and marine renewable energy (energy from waves, tides, currents, and ocean gradients) are two developing ocean-based industries. Aquaculture, an industry that has typically relied on diesel for power, is expected to grow globally, presenting an opportunity to reduce greenhouse gas emissions by switching to renewable sources as it expands. As the industry moves further offshore and is situated in more energetic environments, the prospect to co-locate offshore aquaculture with wave energy increases. To improve understanding of this potential, a feasibility assessment was completed to estimate the energy needs and wave resource required to power offshore finfish aquaculture operations. The study found it is possible to power offshore aquaculture operations entirely with wave energy. A spatial analysis was then performed to assess the suitability of co-locating offshore finfish aquaculture and wave energy off California and Hawaii. Suitable locations were identified offshore of O’ahu, Hawaii, and northern California. Southern California was also assessed, using a lower wave resource, based on study areas evaluated by the National Oceanic and Atmospheric Administration to identify Aquaculture Opportunity Areas, and while limited there are suitable locations that may warrant further evaluation. This study presents an analysis into the potential to pair wave energy with offshore aquaculture, and how various factors can help determine suitable areas for co-location. The analyses developed in this study will support future identification of potential sites for development and decision-making to optimize the success of co-locating wave energy resources and offshore finfish aquaculture.

16 TIDAL AND WAVE POWER↗

NASA NTRS2015

Space Synthetic Biology Project

Synthetic biology is an effort to make genetic engineering more useful by standardizing sections of genetic code. By standardizing genetic components, biological engineering will become much more similar to traditional fields of engineering, in which well-defined components and subsystems are readily available in markets. Specifications of the behavior of those components and subsystems can be used to model a system which incorporates them. Then, the behavior of the novel system can be simulated and optimized. Finally, the components and subsystems can be purchased and assembled to create the optimized system, which most often will exhibit behavior similar to that indicated by the model. The Space Synthetic Biology project began in 2012 as a multi-Center effort. The purpose of this project was to harness Synthetic Biology principals to enable NASA's missions. A central target for application was to Environmental Control & Life Support (ECLS). Engineers from NASA Marshall Space Flight Center's (MSFC's) ECLS Systems Development Branch (ES62) were brought into the project to contribute expertise in operational ECLS systems. Project lead scientists chose to pursue the development of bioelectrochemical technologies to spacecraft life support. Therefore, the ECLS element of the project became essentially an effort to develop a bioelectrochemical ECLS subsystem. Bioelectrochemical systems exploit the ability of many microorganisms to drive their metabolisms by direct or indirect utilization of electrical potential gradients. Whereas many microorganisms are capable of deriving the energy required for the processes of interest (such as carbon dioxide (CO2) fixation) from sunlight, it is believed that subsystems utilizing electrotrophs will exhibit smaller mass, volume, and power requirements than those that derive their energy from sunlight. In the first 2 years of the project, MSFC personnel conducted modeling, simulation, and conceptual design efforts to assist the project in selecting the best approaches to the application of bioelectrochemical technologies to ECLS. Figure 1 shows results of simulation of charge transport in an experimental system. Figure 2 shows one of five conceptual designs for ECLS subsystems based on bioelectrochemical reactors. Also during the first 2 years, some work was undertaken to gather fundamental data (conductivities, overpotentials) relevant to the modeling efforts.

Howard, David↗

DOE OSTI2025

Pathway to tune sputter coated Nb$_3$Sn with Zr

Superconducting radio frequency (SRF) cavities are essential elements of many modern-day particle accelerators such as, European XFEL (DESY), LCLS II-HE (SLAC) and PIP II (Fermilab). Nb$_3$Sn superconducting material promises significant potential to exceed the performance of conventional niobium based SRF cavities. We aim to advance the ongoing R$&$D efforts to achieve Nb$_3$Sn coated cavities with high material quality. In this work, we have developed to achieve a route for effectively reducing the intrinsic defects in magnetron sputter coated Nb$_3$Sn SRF cavities and eventually improve the overall RF performance. We have observed that Zr is mainly being incorporated as ZrO$_2$ precipitates of average dimensions ranging from 20-100nm. By increasing the concentration of Zr, we have three major effects in the physical properties. Firstly, we noted that the density of the surface and bulk voids as well as their average dimensions are dramatically reduced on increasing the Zr content in Nb$_3$Sn. These surface voids are believed to be detrimental to cavity applications due to increase the local dissipation of electric and magnetic fields. These results indicate that inclusion of Zr in Nb$_3$Sn sputtered coating will improve the material quality and might help to reduce the overall RF power dissipation. Secondly, we observed that increasing Zr concentration from 0 to 2.4% substantially improves both superconducting transition temperature (Tc) and upper critical magnetic field (Hc2). However, on further increasing the Zr concentration to 24%, we noticed a small decrement in the Hc2 value. These results infer that the increase in Zr concentration up to an optimal concentration will be beneficial to enhance the superconducting properties. Increase in Tc promises lesser RF losses and improvement in accelerating gradient, whereas the increase in Hc2 suggests more efficient flux pinning which could give rise to high quality factors in presence of multi-Tesla magnetic field. Additionally, we also observed that increasing Zr concentration possibly prevents the oxygen diffusion and leads to thinner formation of primary surface oxide (Nb$_2$O$_5$ and SnO). This study gives a route to tune Zr fraction in Nb3Sn to modify the physical properties that control the high field performance of Nb3Sn RF cavities.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRSDate not supplied

Predicting Airport Runway Configurations for Decision-Support Using Supervised Learning

One of the most challenging tasks for air traffic controllers is runway configuration management (RCM). It deals with the optimal selection of runways to operate on (for arrivals and departures) based on traffic, surface wind speed, wind direction, other environmental variables, noise constraints, and several other airport-specific factors. It affects the efficiency of the National Airspace System (NAS) and both surface and airspace operations can benefit from better understanding future runway configurations. In this paper, we present a comprehensive implementation of predictive models for runway configuration estimation from large volumes of historical data. Specifically, operational data from two full years (2018 and 2019) is collected, analyzed, and fused together to build the data product used in this work. The data set differs from prior work in the field in terms of its scope, resolution, and variety of factors collected and considered. Meteorological data is collected from two different sources – current weather conditions from METAR (Meteorological Terminal Aviation Routine Weather Report) and forecast weather conditions from Localized Aviation MOS Program (LAMP). Operational data from the Federal Aviation Administration (FAA) Aviation System Performance Metrics (ASPM) related to scheduled and actual number of arrivals and departures, average taxi times, etc. are collected. NASA’s Sherlock Data Warehouse is used to identify critical information such as go-arounds, and other events that might impact RCM decision-making. All data is collected and aggregated over 15-minute intervals throughout the two years. This provides a resolution like the timescales that might be necessary for runway configuration management decision-making. A variety of supervised learning algorithms are tested including Support Vector Machine, Random Forest, Gradient Boosting, etc. including tuning of the model hyperparameters. The modeling process is applied and presented on two representative U.S. airports – Charlotte Douglas International Airport (KCLT) and Denver International Airport (KDEN). The two airports present different levels of complexity in terms of the total number of configurations used and provide a balanced perspective on the generalizability of the developed approach to other airports in the NAS. Initial results are promising (F1 score of 0.91 at KCLT and 0.83 at KDEN) for data in the test set. The final paper will contain a comprehensive comparison between different models and model building strategies as well as further refined results. Most important predictors for each airport will be identified along with a discussion and recommendations on adapting the framework to other scenarios.

Tejas G Puranik↗

DOE OSTI2023

Controlling Molecular Structure and Spin with Multiconfigurational Quantum Chemistry (Final Technical Report)

For many first-row transition metal complexes, structure-property relationships can be obtained from high-level molecular geometry optimizations and subsequent electronic structure studies. The project funded under this award utilized newly implemented fully internally contracted (FIC) nuclear gradients for extended multi-state (XMS) complete active space second-order multireference perturbation theory (CASPT2) to explore geometry changes in first-row transition metal coordination complexes. At the start of the project, only one full geometry optimization using FIC-CASPT2 analytical gradients had been reported (J. Chem. Theory Comput., 2016, 12 (8), 3781), and many open-questions regarding the performance and achievable accuracy in applying such computations to larger complexes persisted. Key deliverables in the report include the implementation of the numerical Hessian and subsequent vibrational analysis in the BAGEL program package. This includes both full Hessian vibrational analysis (FHVA) and a partial Hessian vibrational analysis (PHVA). The latter of which allows us to reduce the significant cost of computing the vibrational frequencies in a large molecule by focusing on the modes of highest interest. The gradient code also proved useful in the development of an approach to improve the Hubbard-U correction by removing bias in predicting spin-splitting in Fe(II) complexes via plane-wave density functional theory (DFT). Finally, we showed for three families of complexes (spin-crossover (SCO) complexes, metallocorroles complexes, and those with metal-metal bonds) that CASPT2 can result in good molecular geometries and established best practices in undertaking this work. We are now using this approach in collaborative projects with experimental groups, which would not have been possible at the start of this project. A common theme also arose through this work that static and dynamic correlation must be recovered in a balanced way to yield quantitative results. By systematically varying how both effects were included, we were able to make key chemical insights. This work supported the training of two postdoctoral scholars, one graduate student, and one undergraduate student in applying high-level wavefunction based methods to challenging systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1992

Deformation mechanisms of NiAl cyclicly deformed near the brittle-to-ductile transformation temperature

One of the ongoing challenges of the aerospace industry is to develop more efficient turbine engines. Greater efficiency entails reduced specific strength and larger temperature gradients, the latter of which means higher operating temperatures and increased thermal conductivity. Continued development of nickel-based superalloys has provided steady increases in engine efficiency and the limits of superalloys have probably not been realized. However, other material systems are under intense investigation for possible use in high temperature engines. Ceramic, intermetallic, and various composite systems are being explored in an effort to exploit the much higher melting temperatures of these systems. NiAl is considered a potential alternative to conventional superalloys due to its excellent oxidation resistance, low density, and high melting temperature. The fact that NiAl is the most common coating for current superalloy turbine blades is a tribute to its oxidation resistance. Its density is one-third that of typical superalloys and in most temperature ranges its thermal conductivity is twice that of common superalloys. Despite these many advantages, NiAl requires more investigation before it is ready to be used in engines. Binary NiAl in general has poor high-temperature strength and low-temperature ductility. On-going research in alloy design continues to make improvements in the high-temperature strength of NiAl. The factors controlling low temperature ductility have been identified in the last few years. Small, but reproducible ductility can now be achieved at room temperature through careful control of chemical purity and processing. But the mechanisms controlling the transition from brittle to ductile behavior are not fully understood. Research in the area of fatigue deformation can aid the development of the NiAl system in two ways. Fatigue properties must be documented and optimized before NiAl can be applied to engineering systems. More importantly though, probing the deformation mechanisms operating in fatigue will lead to a better understanding of NiAl's unique characteristics. Low cycle fatigue properties have been reported on binary NiAl in the past year, yet those studies were limited to two temperature ranges: room temperature and near 1000 K. Eventually, fatigue property data will be needed for a wide range of temperatures and compositions. The intermediate temperature range near the brittle-to-ductile transition was chosen for this study to ascertain whether the sharp change occurring in monotonic behavior also occurs under cyclic conditions. An effort was made to characterize the dislocation structures which evolved during fatigue testing and comment on their role in the deformation process.

Antolovich, Stephen D.↗

NASA NTRS2019

Accelerated Simulation of Air Pollution Using NVIDIA RAPIDS

Atmospheric chemistry models are a central tool to study and forecast the impact of air pollution on the environment, vegetation, and human health. However, the numerical simulation of chemical kinetics is computationally expensive due to the stiffness of the system of ordinary differential equations that describes atmospheric chemistry. Here we present an alternative approach to the computation of atmospheric chemistry based on machine learning. Our training data set is produced using the NASA Goddard Earth Observing System (GEOS) model with GEOS-Chem chemistry, run on the NASA Center for Climate Simulation (NCCS) Discover supercomputing cluster on 384 Intel Xeon Haswell cores. This model spends more than 50% of total run time on solving atmospheric chemistry. The data set contains as input features the air pollution concentrations before solving the differential equations, together with some key physical parameters such as temperature and sun intensity. As target variables we define the air pollution concentrations after solving the differential equations. Using Dask-cuDF and Dask-XGBoost on the NVIDIA RAPIDS platform on 8 Tesla V100 GPUs, we generate from this training set gradient boosted decision tree models that can reproduce the simulation of chemical kinetics. We do this on the NCCS Advanced Data Analytics Platform (ADAPT) science cloud environment. Our application takes full advantage of recent advances in Dask-XGBoost, such as multi-node and multi-GPU scaling for distributed training with large data sets. The increase in training data size enabled by this is critical to capture the full range of chemical environments encountered across the globe and all annual seasons.The boosted tree models offer good predictability and show many of the features of the full chemistry reference simulation. Further improvements can be achieved through mass balance considerations and by accounting for error correlations. We incorporate the boosted tree models into the GEOS reference model using XGBoost's C API. This enables a seamless integration of the GPU trained models into GEOS-Chem, which is written in Fortran and optimized for use in a massively parallel CPU environment. We show the benefits of this approach and discuss the potential speedup of this machine learning accelerated atmospheric chemistry model.

Keller, Christoph A.↗

NASA NTRS1996

A Proof of Concept Experiment for Reducing Skin Friction by Using a Micro-Blowing Technique

A proof of concept experiment for reducing skin friction has been conducted in the Advanced Nozzle and Engine Components Test Facility at the NASA Lewis Research Center. In this unique concept, called the micro-blowing technique (MBT), an extremely small amount of air was blown vertically through very small holes to reduce the surface roughness and to control the gradient of the flow velocity profile on the surface thereby reducing skin friction. Research revealed that the skin was the most important factor to make this concept achievable. The proposed skin consisted of two layers. The inner layer was a low permeable porous skin for distributing the blowing air evenly while the outer layer with small holes controlled the vertical or nearly vertical blowing air. Preliminary experimental results showed that the MBT has the potential of a very large reduction in skin friction below the skin friction of a nonporous plain flat plate. Of the skins tested, three have been identified as the MBT skins. They provided very low unblown skin friction such that a large skin friction reduction, below a flat plate value, was achieved with very small amounts of blowing air. The reduction in skin friction of 55 percent was achieved at the Mach number of 0.3 for the exhaust pressure of 0.85 atm, and 60 percent reduction was obtained for the exhaust pressure of 0.24 atm (corresponding to 10 700-m altitude) at the same Mach number. A significant reduction in skin friction of over 25 percent was achieved for the exhaust pressure of 0.24 atm at the Mach number of 0.7. This implied that the MBT could be applied to a wide range of flight conditions. It is also believed that additional 10 percent reduction could be obtained by eliminating the gap between the inner layer and the outer layer. The aspect ratio of the vertical small holes for the outer layer of the MBT skin should be larger than 4 based on the preliminary conclusion from this test. Many experiments are needed to find out the optimal MBT skin. The penalty associated with the MBT needs to be assessed. However, preliminary results indicated that the MBT could provide a 25 to 35 percent reduction for real-world application. The concept can be applied to not only an airplane, but also a missile, a submarine (micro-blow water instead of air), and an ocean liner.

Hwang, Danny P.↗