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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Heterogeneous phase transformation pathways in additively manufactured Al-Ce-Mn alloys

Heat treatment of additively manufactured Al-Ce based multicomponent alloys leads to complex microstructure evolution. In this research, the ability to extend the phase transformation theories involving nucleation of a product phase from a heterogeneous multi-phase microstructure typical to that of additively manufactured samples is explored. The Al-10Ce-8Mn (wt%) was used as a model alloy system. Under additive manufacturing conditions different solidification microstructures were obtained due to spatial and temporal variations of thermal gradients (G) and liquid-solid interface velocities (R) within a given melt pool. Near the melt pool boundary (high G and low R, referred as MPB region), initially, Al 20 Mn 2 Ce forms from the liquid followed by a eutectic of FCC Al and Al 11 Ce 3 . In the melt pool interiors (low G and high R referred as ES region) a eutectic structure between FCC Al and Al 20 Mn 2 Ce is observed. During subsequent heat treatments, the MPB and ES regions transform into different sets of microstructures. In the MPB region, a fine globular microstructure containing FCC Al, Al 11 Ce 3 , Al 6 Mn, and Al 12 Mn results from the decomposition of Al 20 Mn 2 Ce. In the ES region a faceted Al 51 Mn 7 Ce 4 plate phase results from the decomposition of Al 20 Mn 2 Ce. The formation of the Al 51 Mn 7 Ce 4 phase within the eutectic microstructure at the boundaries of FCC Al and Al 20 Mn 2 Ce has not been reported in the literature. Further, these two distinct phase transformation pathways are rationalized based on the role of driving force on the nucleation of (Al 6 Mn) and/or metastable intermetallic (Al 51 Mn 7 Ce 4 ) phases at the interface of aluminum (FCC) and the non-equilibrium intermetallic (Al 20 Mn 2 Ce) phases.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Excitons in strained and suspended monolayer WSe 2

Here, we study suspended membranes of atomically thin WSe 2 as hosts of excitons. We perform optical reflectance measurements to probe the exciton physics and obtain the peak energies for the 1$s$, 2$s$, and 3$s$ states of the $A$ exciton in suspended WSe 2 and consider supported membranes as a reference. We find that elimination of the influence of the dielectric environment enables a strong electron–hole interaction and a concomitant increase in the exciton binding energy in suspended monolayer (1L) WSe 2 . Based on the experimental results, we calculate the excitonic binding energies by employing the recently developed quantum electrostatic heterostructure model and the commonly employed Rytova–Keldysh potential model. We see that the binding energy of the ground state $A$ exciton increases from about 0.3 eV (on a substrate) to above 0.4 eV (suspended). We also exploit the tunability of the excitons in suspended samples via mechanical strain. By applying external gas pressure of 2.72 atm to a 1L suspended over a circular hole of 8 μm diameter, we strain the WSe 2 and obtain a reversible 0.15 eV redshift in the exciton resonance. The linewidth of the $A$ exciton decreases by more than half, from about 50 to 20 meV under 1.5% biaxial strain at room temperature. This line narrowing is due to the suppression of intervalley exciton–phonon scattering. By making use of the observed strain-dependent optical signatures, we infer the two-dimensional (2D) elastic moduli of 1L and 2L WSe 2 . Our results exemplify the use of suspended 2D materials as novel systems for fundamental studies, as well as for strong and dynamic tuning of their optical properties.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Comprehensive Material Characterization and Simultaneous Model Calibration for Improved Computational Simulation Credibility

Computational simulation is increasingly relied upon for high-consequence engineering decisions, and a foundational element to solid mechanics simulations is a credible material model. Our ultimate vision is to interlace material characterization and model calibration in a real-time feedback loop, where the current model calibration results will drive the experiment to load regimes that add the most useful information to reduce parameter uncertainty. The current work investigated one key step to this Interlaced Characterization and Calibration (ICC) paradigm, using a finite load-path tree to incorporate history/path dependency of nonlinear material models into a network of surrogate models that replace computationally-expensive finite-element analyses. Our reference simulation was an elastoplastic material point subject to biaxial deformation with a Hill anisotropic yield criterion. Training data was generated using either a space-filling or adaptive sampling method, and surrogates were built using either Gaussian process or polynomial chaos expansion methods. Surrogate error was evaluated to be on the order of 10 ⁻5 and 10 ⁻3 percent for the space-filling and adaptive sampling training data, respectively. Direct Bayesian inference was performed with the surrogate network and with the reference material point simulator, and results agreed to within 3 significant figures for the mean parameter values, with a reduction in computational cost over 5 orders of magnitude. These results bought down risk regarding the surrogate network and facilitated a successful FY22-24 full LDRD proposal to research and develop the complete ICC paradigm.

36 MATERIALS SCIENCE↗
NASA NTRS1995

Investigation of air transportation technology at Ohio University: 1993-1994

The Joint University Program (JUP) offers students, faculty, and staff of the Avionics Engineering Center the opportunity to conduct basic research relating to the safety and efficiency of the National Airspace System. During the 1993-1994 year research was continued in a variety of GPS-related technologies and also in a hybrid data uplink system. (1) Processing techniques developed for the GPS attitude determination have been applied to centimeter-level kinematic GPS aircraft positioning for flight reference systems and aircraft autoland and taxiing operations. This resulted in the first real-time kinematic GPS autoland. (2) The fault detection and isolation (FDI) algorithm developed under the Joint University Program has been fully adopted by RTCA Special Committee 159 as the baseline algorithm for sole-means navigation of GPS integrated with GLONASS, LORAN-C, or baro-altimeter. (3) A Satellite Coverage Research Analysis Model (SCRAM) has been developed which provides outage areas, outage dynamics, and availability information for satellite-based navigation systems. RTCA Special Committee 159 has adopted this model for use in their work. (4) A basic receiver structure has been simulated and tested for use with the hybrid data uplink. This uplink utilizes the phase of an existing AM carrier to transmit digital data, thus both amplitude and phase modulation are applied, resulting in a hybrid carrier. The receiver simulation is directly applicable to real-time implementation as a result of the development platform.

Lilley, Robert W.↗
NASA NTRS1996

Visualizing Infrared (IR) Spectroscopy with Computer Animation

IR Tutor, an interactive, animated infrared (IR) spectroscopy tutorial has been developed for Macintosh and IBM-compatible computers. Using unique color animation, complicated vibrational modes can be introduced to beginning students. Rules governing the appearance of IR absorption bands become obvious because the vibrational modes can be visualized. Each peak in the IR spectrum is highlighted, and the animation of the corresponding normal mode can be shown. Students can study each spectrum stepwise, or click on any individual peak to see its assignment. Important regions of each spectrum can be expanded and spectra can be overlaid for comparison. An introduction to the theory of IR spectroscopy is included, making the program a complete instructional package. Our own success in using this software for teaching and research in both academic and industrial environments will be described. IR Tutor consists of three sections: (1) The 'Introduction' is a review of basic principles of spectroscopy. (2) 'Theory' begins with the classical model of a simple diatomic molecule and is expanded to include larger molecules by introducing normal modes and group frequencies. (3) 'Interpretation' is the heart of the tutorial. Thirteen IR spectra are analyzed in detail, covering the most important functional groups. This section features color animation of each normal mode, full interactivity, overlay of related spectra, and expansion of important regions. This section can also be used as a reference.

Charles B. Abrams↗
NASA NTRS2000

Factors Contributing to Pilot Valve Fuel Seal Extrusion in Orbiter PRCS Thrusters

Extrusion of the polytetrafluoroethylene (PTFE) pilot seal used in the monomethylhydrazine (fuel) valve of the Orbiter Primary Reaction Control System (PRCS) thrusters has been implicated in numerous on-orbit thruster failures and on-ground valve failures. Two extrusion mechanisms have been proposed, one or both may be occurring. The first mechanism is attributed to thermal expansion mismatch between adjacent PTFE and metal parts used in the fuel valve, and is referred to as thermal extrusion. The second mechanism is attributed to nitrogen tetroxide (oxidizer) leakage from the adjacent oxidizer valve on the same thruster during ground turnaround, and is referred to as oxidizer-induced extrusion. Model calculations of PTFE pilot seal in an exact pilot valve configuration show that extrusion can be caused by differential thermal expansion, without the intervening influence of oxidizer. Experimental data on semitrapped PTFE and TFM (modified PTFE) specimens simulating a fuel pilot valve configuration show that thermal extrusion 1) is incremental and irreversible, 2) increases with the size of the thermal excursion, 3) decreases with successive thermal cycling, and 4) is accompanied by gap formation. Both PTFE and TFM exhibit a higher affinity for oxidizer than fuel. The property changes associated with oxidizer uptake may explain why oxidizer seals do not exhibit extrusion. Impression replicas of fuel pilot seals removed from the Orbiter fleet show two types of extrusion: extrusion of the entire seal (loaded extrusion), or extrusion of non-sealing surface (unloaded extrusion). Both extrusion types may arise from differences in service history, rather than in failure mechanism. The plausibility oxidizer-induced extrusion was evaluated. Preliminary calculations suggest that enough energy, heat, or gas may be liberated under certain operational scenarios to cause catastrophic extrusion. However, given the lack of supporting data, conclusions implicating oxidizer leakage as a factor in extrusion must be made with caution.

Waller, J.M.↗
NASA NTRS2022

Assessment of ICESat-2’s Horizontal Accuracy Using Precisely Surveyed Terrains in McMurdo Dry Valleys, Antarctica

This article presents an assessment of the horizontal accuracy and precision of the laser altimetry observations collected by NASA’s Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) mission. We selected the terrain-matching method to determine the position of laser altimeter profiles within a precisely known surface, represented by a digital elevation model (DEM). We took this classical approach a step further, approximated the DEM by planar surfaces, and calculated the optimal position of the laser profile by minimizing the square sum of the elevation differences between reference DEMs and ICESat-2 profiles. We found the highly accurate DEMs of the McMurdo Dry Valleys (DV), Antarctica, ideal for this research because of their stable landscape and rugged topography. We computed the 3-D shift parameters of 379 different laser altimeter profiles along two reference ground tracks collected within the first two years of the mission. Analyzing these results revealed a total geolocation error (mean +1 σ ) of 4.93 m for version 3 and 4.66 m for version 4 data. These numbers are the averages of the six beams, expressed as mean +1 σ and lie well within the mission requirement of 6.5 m.

calibration↗
DOE OSTI2016

Nuclear Forensics for Irradiated Materials using Kernel Regression Models

The ultimate purpose of nuclear forensics is to locate the origin of nuclear and other radioactive materials out of regulatory control used in nuclear security events such as classical forensics. For this purpose, some specific characteristics of interdicted materials (referred to as 'signatures') should be defined to compare the known sample database. In some cases, involved with irradiated material, the signatures could be specific amount of fission product inventory depending on reactor operational histories such as reactor type, initial enrichment, burn up rate of nuclear fuel and cooling period after irradiation in the reactor. In order to make inference model for irradiated material for nuclear forensics, we suggested 3 ways as follows; (i) analyzing ORIGEN produced nuclear substances for the fission product inventory, (ii) classifying the range of reactor type, (iii) predicting the operational history from the fission product inventory. In terms of nuclear substance analysis, the construction of spent fuel database has been internationally carried out since ITWG (Nuclear Smuggling International Technical Working Group) was established in 1995. However, enough sample data cannot be obtained in Korea to determine reactor type and operational histories because analyzing nuclear substances have been limited due to the international regulation. Thus, this study does not mention how to obtain mass or ratios of nuclides for the spent fuel. We just have generated simulation sample data as a fission product inventory using ORIGEN to construct spent fuel database. When unidentified radioactive materials are discovered, it is assumed that mass or ratios of the nuclides are analyzed by certain methods which are available in Korea as well as other countries. Then, a reactor type is determined, and finally, regression model can locate the origin or source of the radioactive materials by inferring operational histories using the fission product inventory. There are some studies on the classification of reactor type using statistical methods. As a part of predicting the operational history, this paper focuses on the development of spent fuel inference algorithm for nuclear forensics to estimate reactor operational histories that reflect characteristics of a reactor from the fission product inventory. The spent fuel inference algorithm for nuclear forensics has been developed on the basis of Kernel Regression (KR) which can conditionally generate the estimated output data by giving weight depending on geometric distance between sample data and input data. Also the KR which comprises Auto-Associative KR and Inferential KR have some benefits that can estimate only using data without assumption for specific physical model and re-learning process. Auto-associative KR (AAKR) was used to sort out outliers of input data and Inferential KR (IKR) was carried out to predict the operational histories for spent fuel. All of regression algorithms were performed in R programming tool. From the validation of both AAKR and IKR, it is expected that kernel regression has enough accuracy to be applied to nuclear forensics for spent fuel. Once the nuclear substance is measured to fill the fission product inventory with a certain reactor type, this kernel regression algorithm would predict the operational histories of spent fuel with high accuracy. Finally, this information is expected to be useful to find the origin of irradiated materials. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Artificial Intelligence Application to D and D - 20492

As aging facilities across the DOE complex await decommissioning, there is an ongoing need to understand any changes in the structural conditions. Many of these facilities were built over 50 years ago and, in some cases, these facilities have gone beyond the expected operational lifetime. Many facilities have been placed in a state of 'cold and dark,' sitting unused and awaiting decommissioning. Especially challenging are the aging facilities that provide unique operational/production capabilities to support critical DOE missions and cannot be shut down. In any of these scenarios, the structural integrity of these facilities may become compromised as time passes. It is critical that adequate inspections be performed on a continual basis and that the data collected undergoes sufficient analysis to support timely identification of any new or worsening structural issues as well as prompt needed maintenance and repairs to maintain the facilities in a safe condition. In recent days, Artificial Intelligence (AI) [1] and its application to various domains are growing at fast speed. FIU is performing research in this area and exploring the associated technologies to solve nuclear decommissioning problems. Artificial intelligence refers to the capability of a program to autonomously act, react and adapt to the working environment. AI enables the machine to behave like humans and perform the cognitive functions such as 'learning' and 'problem solving'. AI systems gradually moving from traditional approaches (algorithms and expert systems) towards more efficient and advanced technologies (machine learning [1] and deep learning [2] [3]). AI is the study of algorithms and statistical models that is being used by computers to perform specific tasks without using explicit instructions. FIU is working to develop a pilot-scale infrastructure to implement structural health monitoring using AI technologies with focus on machine learning, deep learning. This research is focused on Computer Vision/Image Classification area of AI applications. This can also be expanded to other areas of AI related to Object Recognition and Character Recognition in images. In addition to utilizing existing data sets, FIU will collect and investigate image and video data using FIU test-bed mockups to monitor structural health of the facility. Resulting data will be processed and analyzed using machine learning/deep learning technologies. The proposed pilot system is intended to serve as a starting point to engage the DOE field sites on related data sets and their decision making needs. It is anticipated that proposed machine learning/deep learning technologies can be effectively employed using anomaly detection to solve EM challenges in surveillance and maintenance of the D and D facilities. FIU will work with research stakeholders to identify applications at various sites and other DOE facilities. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Using an Absolute Cavity Pyrgeometer to Validate the Calibration of a Secondary Standard Pyrgeometer Outdoors, Independent from the Reference Value of the Atmospheric Longwave Irradiance

Accurate measurements of broadband outdoor longwave irradiance are important for renewable energy applications and the study of the atmosphere and climate change. A unique method of pyrgeometer calibration has been developed to improve the measurement uncertainty [1]. The results of this method yielded irradiance values within ±3 W/m 2 of those traceable to the World InfraRed Standard Group (WISG). This article describes a technique for validating this pyrgeometer calibration method using two Absolute Cavity Pyrgeometers (ACPs). The ACPs and pyrgeometer model PIR were deployed outdoors and the irradiance measured by the PIR was compared against the average irradiance measured by the two ACPs. The irradiance measured by the PIR was calculated using two equations, NREL equation and the Physikalisch Meteorologisches Observatorium Davos (PMOD) equation. The uncertainty with 95% confidence level ( U 95 ) of the irradiance measured by the PIR using NREL equation equaled ±3.51 W/m 2 with respect to SI and using PMOD equation U 95 equaled ±2.99 W/m 2 with respect to SI. These results suggest that the PIR calibration method might be useful in addressing the international need for a secondary standard pyrgeometer traceable to SI.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

SU-E-T-03: 3D GPU-Accelerated Secondary Checks of Radiation Therapy Treatment Plans

Purpose: Redundant treatment verifications in conformal and intensity-modulated radiation therapy techniques are traditionally performed with single point calculations. New solutions can replace these checks with 3D treatment plan verifications. This work describes a software tool (Mobius3D, Mobius Medical Systems) that uses a GPU-accelerated collapsed cone algorithm to perform 3D independent verifications of TPS calculations. Methods: Mobius3D comes with reference beam models for common linear accelerators. The system uses an independently developed collapsed cone algorithm updated with recent enhancements. 144 isotropically-spaced cones are used for each voxel for calculations. These complex calculations can be sped up by using GPUs. Mobius3D calculate dose using DICOM information coming from TPS (CT, RT Struct, RT Plan RT Dose). DVH-metrics and 3D gamma tests can be used to compare both TPS and secondary calculations. 170 patients treated with all common techniques as 3DCFRT (including wedged), static and dynamic IMRT and VMAT have been successfully verified with this solution. Results: Calculation times are between 3–5 minutes for 3DCFRT treatments and 15–20 for most complex dMLC and VMAT plans. For all PTVs mean dose and 90% coverage differences are (1.12±0.97)% and (0.68±1.19)%, respectively. Mean dose discrepancies for all OARs is (0.64±1.00)%. 3D gamma (global, 3%/3 mm) analysis shows a mean passing rate of (97.8 ± 3.0)% for PTVs and (99.0±3.0)% for OARs. 3D gamma pasing rate for all voxels in CT has a mean value of (98.5±1.6)%. Conclusion: Mobius3D is a powerful tool to verify all modalities of radiation therapy treatments. Dose discrepancies calculated by this system are in good agreement with TPS. The use of reference beam data results in time savings and can be used to avoid the propagation of errors in original beam data into our QA system. GPU calculations permit enhanced collapsed cone calculations with reasonable calculation times.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Communication: Orientational self-ordering of spin-labeled cholesterol analogs in lipid bilayers in diluted conditions

Lipid-cholesterol interactions are responsible for different properties of biological membranes including those determining formation in the membrane of spatial inhomogeneities (lipid rafts). To get new information on these interactions, electron spin echo (ESE) spectroscopy, which is a pulsed version of electron paramagnetic resonance (EPR), was applied to study 3β-doxyl-5α-cholestane (DCh), a spin-labeled analog of cholesterol, in phospholipid bilayer consisted of equimolecular mixture of 1,2-dipalmitoyl-sn-glycero-3-phosphocholine and 1,2-dioleoyl-sn-glycero-3-phosphocholine. DCh concentration in the bilayer was between 0.1 mol.% and 4 mol.%. For comparison, a reference system containing a spin-labeled 5-doxyl-stearic acid (5-DSA) instead of DCh was studied as well. The effects of “instantaneous diffusion” in ESE decay and in echo-detected (ED) EPR spectra were explored for both systems. The reference system showed good agreement with the theoretical prediction for the model of spin labels of randomly distributed orientations, but the DCh system demonstrated remarkably smaller effects. The results were explained by assuming that neighboring DCh molecules are oriented in a correlative way. However, this correlation does not imply the formation of clusters of cholesterol molecules, because conventional continuous wave EPR spectra did not show the typical broadening due to aggregation of spin labels and the observed ESE decay was not faster than in the reference system. So the obtained data evidence that cholesterol molecules at low concentrations in biological membranes can interact via large distances of several nanometers which results in their orientational self-ordering.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Utah FORGE: Seismic Velocity Models, February 2021

This dataset contains a map, showing the Utah FORGE seismic stations, and seismic velocity model data. There are 61 1-D velocity models which are in a compressed TAR file. A paper is referenced at the end of this description which discusses the use of these data in 3D modelling. The paper summary follows: We expand the application of spatial autocorrelation (SPAC) from typical 1-D Vs profiles to quasi-3-D imaging via Bayesian Monte Carlo inversion (BMCI) using a dense nodal array (49 nodes) located at the Utah Frontier Observatory for Research in Geothermal Energy (FORGE) site. Combinations of 4 and 9 geophones in subarrays provide for 36 and 25 1-D Vs profiles, respectively. Profiles with error bars are determined by calculating coherency functions that fit observations in a frequency range of 0.2-5 Hz. Thus, a high-resolution quasi-3-D Vs model from the surface to 2.0 km depth is derived and shows that surface-parallel sedimentary strata deepen to the west, consistent with a 3-D seismic reflection survey. Moreover, the resulting Vs profile is consistent with a Vs profile derived from distributed acoustic sensing (DAS) data located in a borehole at the FORGE site. The quasi-3-D velocity model shows that the base of the basin dips ~22 degrees to the west and topography on the basement interface coincident with the Mag Lee Wash suggests that the bedrock interface is an unconformity. Reference: Zhang, H. and K. L. Pankow (2021). High-resolution Bayesian spatial auto-correlation (SPAC) pseudo-3D Vs model of Utah FORGE site with a dense geophone array, Geophys. Res. Int, https://doi.org/10.1093/gji/ggab049

15 GEOTHERMAL ENERGY↗
NASA NTRS2004

Finite Element Modeling Used to Study Stress Distribution on the Foot

A method to study the stress distribution inside the forefoot during walking was developed at the Cleveland Clinic Foundation by a researcher from the NASA Glenn Research Center. In this method, a semiautomated process was outlined to create a three-dimensional, patient-specific, finite element model (FEM) of the forefoot using magnetic resonance images (MRI). The images were processed in Matlab using the k-nearest neighbor (k-NN) classification algorithm and Sobel edge detection to separate the different tissue types: bone, skin, fat, and muscle. This information was used to create curves and surfaces that were exported to an FEM preprocessor known as Truegrid. In Truegrid, eight-noded or brick elements were created by using surface mapping. The FEM was processed and postprocessed in Abaqus. Material properties of the models were obtained from past experiments such as fat pad confined compression, skin axial and biaxial tests, muscle in vivo compressive tests, and reference literature (bone properties). Nonlinear (hyperelastic) material models were used for the skin (epidermis and dermis), fat, and muscles; and a linear elastic model was used for the bones. Muscle activation during walking yielded uncertainties in the muscle material model since contracted muscles are stiffer than relaxed muscles. These uncertainties were resolved by performing a sensitivity analysis of the muscle material properties. The original properties were multiplied by arbitrary factors of 2, 3, 0.5, and 0.33. The strain and stress distributions, as well as the locations of peak values, were similar in all cases. The peak contact pressure P obtained for each case varied with respect to the applied factor f as follows:

Morales, Nelson↗
NASA NTRS2009

Analytic Shielding Optimization to Reduce Crew Exposure to Ionizing Radiation Inside Space Vehicles

A sustainable lunar architecture provides capabilities for leveraging out-of-service components for alternate uses. Discarded architecture elements may be used to provide ionizing radiation shielding to the crew habitat in case of a Solar Particle Event. The specific location relative to the vehicle where the additional shielding mass is placed, as corroborated with particularities of the vehicle design, has a large influence on protection gain. This effect is caused by the exponential- like decrease of radiation exposure with shielding mass thickness, which in turn determines that the most benefit from a given amount of shielding mass is obtained by placing it so that it preferentially augments protection in under-shielded areas of the vehicle exposed to the radiation environment. A novel analytic technique to derive an optimal shielding configuration was developed by Lockheed Martin during Design Analysis Cycle 3 (DAC-3) of the Orion Crew Exploration Vehicle (CEV). [1] Based on a detailed Computer Aided Design (CAD) model of the vehicle including a specific crew positioning scenario, a set of under-shielded vehicle regions can be identified as candidates for placement of additional shielding. Analytic tools are available to allow capturing an idealized supplemental shielding distribution in the CAD environment, which in turn is used as a reference for deriving a realistic shielding configuration from available vehicle components. While the analysis referenced in this communication applies particularly to the Orion vehicle, the general method can be applied to a large range of space exploration vehicles, including but not limited to lunar and Mars architecture components. In addition, the method can be immediately applied for optimization of radiation shielding provided to sensitive electronic components.

Gaza, Razvan↗
DOE OSTI2021

Assessment of CMIP6 Performance and Projected Temperature and Precipitation Changes Over South America

We evaluate the performance of a large ensemble of Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) over South America for a recent past reference period and examine their projections of twenty-first century precipitation and temperature changes. The future changes are computed for two time slices (2040–2059 and 2080–2099) relative to the reference period (1995–2014) under four Shared Socioeconomic Pathways (SSPs, SSP1–2.6, SSP2–4.5, SSP3–7.0 and SSP5–8.5). The CMIP6 GCMs successfully capture the main climate characteristics across South America. However, they exhibit varying skill in the spatiotemporal distribution of precipitation and temperature at the sub-regional scale, particularly over high latitudes and altitudes. Future precipitation exhibits a decrease over the east of the northern Andes in tropical South America and the southern Andes in Chile and Amazonia, and an increase over southeastern South America and the northern Andes—a result generally consistent with earlier CMIP (3 and 5) projections. However, most of these changes remain within the range of variability of the reference period. In contrast, temperature increases are robust in terms of magnitude even under the SSP1–2.6. Future changes mostly progress monotonically from the weakest to the strongest forcing scenario, and from the mid-century to late-century projection period. There is an increase in the seasonality of the intra-annual precipitation distribution, as the wetter part of the year contributes relatively more to the annual total. Furthermore, an increasingly heavy-tailed precipitation distribution and a rightward shifted temperature distribution provide strong indications of a more intense hydrological cycle as greenhouse gas emissions increase. The relative distance of an individual GCM from the ensemble mean does not substantially vary across different scenarios. We found no clear systematic linkage between model spread about the mean in the reference period and the magnitude of simulated sub-regional climate change in the future period. Overall, these results could be useful for regional climate change impact assessments across South America.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Exotic edge states of C 3 high-fold fermions in honeycomb lattices

A generalization of the graphene honeycomb model to the case where each site in the honeycomb lattice contains a n -fold degenerate set of eigenstates of the C 3 symmetry has been recently proposed to describe several systems, including triangulene crystals and photonic lattices. These generalized honeycomb models are defined by ( n a , n b ) , the number of C 3 eigenstates in the a and b sites of the unit cell, resulting in n a + n b bands. Thus, the (1,1) case gives the coventional honeycomb model that describes the two low-energy bands in graphene. Generalizations, such as (2,1), (2,2), and (3,3) display several nontrivial features, such as coexisting graphenelike Dirac cones with flat bands, both at zero and finite energy, as well as robust degeneracy points where a flat band and a parabolic band meet at the Γ point. Here we explore the edge states of this class of crystals, using as reference triangulene crystals, and we find several types of edge states absent in the conventional (1,1) honeycomb case, associated to the nontrivial features of the two-dimensional bands of the high-fold case. First, we find dispersive edge states associated to the finite-energy flat bands, that occur both at the armchair and zigzag termination. Second, in the case of noncentrosymmetric triangulene crystals that lead to a S = 1 Dirac band, we have a bonding-antibonding pair of dispersive edge states, localized in the same edge so that their energy splitting is reduced as their localization increases, opposite to the conventional behavior of pairs of states localized in opposite edges. Third, for the (3,3) case, that hosts a gap separating a pair of flat conduction and valence bands, we find nondispersive edge states with E = 0 in all edge terminations. Published by the American Physical Society 2024

Madail, L. (ORCID:0000000208457748)↗
NASA NTRS1995

Spectral analyses, climatology, and interannual variability of Nimbus-7 TOMS version 6 total column ozone

This reference publication presents selected results from space-time spectral analyses of 13 years of version 6 daily global ozone fields from the Total Ozone Mapping Spectrometer (TOMS). One purpose is to illustrate more quantitatively the well-known richness of structure and variation in total ozone. A second purpose is to provide, for use by modelers and for comparison with other analysts' work, quantitative measures of zonal waves 1, 2, 3, and medium-scale waves 4-7 in total ozone. Their variations throughout the year and at a variety of latitudes are presented, from equatorial to polar regions. The 13-year averages are given, along with selected individual years which illustrate year-to-year variability. The largest long wave amplitudes occur in the polar winters and early springs of each hemisphere, and are related to strong wave amplification during major warning events. In low attitudes total ozone wave amplitudes are an order of magnitude smaller than at high latitudes. However, TOMS fields contain a number of equatorial dynamical features, including Rossby-gravity and Kelvin waves.

Stanford, J. L.↗