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At least 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Dependence of simulated radiation damage on crystal structure and atomic misfit in metals

This study investigates the evolution of radiation damage in three metals in the low temperature and high radiant flux regime using molecular statics and a Frenkel pair accumulation method to simulate up to 2.0 displacements per atom. The metals considered include Fe, equiatomic CrCoNi, and a fictitious metal with similar bulk properties to the CrCoNi composed of a single atom type referred to as an A-atom. CrCoNi is found to sustain higher concentrations of dislocations than either the Fe or A-atom systems and more stacking faults than the A-atom system. The results suggest that the difference between the concentrations of vacancies and interstitials is substantially smaller for CrCoNi than the A-atom system, perhaps reflecting that the sink capture radius is smaller in CrCoNi due to the roughened potential energy landscape. A model that partitions the major contributions from defects to the stored energy is described, and serves to highlight a general need for higher fidelity approaches to point defect identification.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Anomalies in the space of coupling constants and their dynamical applications I

It is customary to couple a quantum system to external classical fields. One application is to couple the global symmetries of the system (including the Poincaré symmetry) to background gauge fields (and a metric for the Poincaré symmetry). Failure of gauge invariance of the partition function under gauge transformations of these fields reflects ’t Hooft anomalies. It is also common to view the ordinary (scalar) coupling constants as background fields, i.e. to study the theory when they are spacetime dependent. We will show that the notion of ’t Hooft anomalies can be extended naturally to include these scalar background fields. Just as ordinary ’t Hooft anomalies allow us to deduce dynamical consequences about the phases of the theory and its defects, the same is true for these generalized ’t Hooft anomalies. Specifically, since the coupling constants vary, we can learn that certain phase transitions must be present. We will demonstrate these anomalies and their applications in simple pedagogical examples in one dimension (quantum mechanics) and in some two, three, and four-dimensional quantum field theories. An anomaly is an example of an invertible field theory, which can be described as an object in (generalized) differential cohomology. We give an introduction to this perspective. Also, we use Quillen’s superconnections to derive the anomaly for a free spinor field with variable mass. In a companion paper we will study four-dimensional gauge theories showing how our view unifies and extends many recently obtained results.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1993

The stability of hibonite and other aluminous phases in silicate melts: Implications for the origin of hibonite-bearing inclusions

Phase fields in which hibonite (Hib) and silicate melt coexist with spinel (Sp), CaAl4O7 (CA2), gehlenitic melilite (Mel), anorthite (An), or corundum (Cor) in the system CaO-MgO-Al203-SiO2-TiO2 (CMAST) were determined and activity models developed for Mel and Hib solid solutions. Experimentally determined partition coefficients for Ti between Hib and coexisting melt, D sub t, vary from 0.8 to 2.1 and generally decrease with increasing TiO2 content in the liquid (L). Based on Ti partioning between Hib and melt, bulk inclusion compositions and Hib-saturated liquid use phase diagrams, the Hib in Fluffy Type A inclusions (FTA's) from Allende and at least some of the Hib from Hib-rich inclusions is relict; much of the Hib from Hib-glass spherules probably crystallized from a melt under nonequilibrium conditions. Bulk compositions for all of these Ca-Al-rich inclusions (CAI's) are consistent with an origin as Mel + Hib + Sp + perovskite (Pv) proto-inclusions in which Mel was partially altered. In some cases, the proto-inclusion was partially or completely melted with vaporization occurring over a period of time sufficient to remove any Na introduced by the alteration process but frequently insufficient to dissolve all of the original hibonite. If equilibration temperatures based on Hib-bearing CAI's reflect condensation in a cooling gas of solar composition, then Hib + Cor condensed at approximately 1260 C (referenced to 10 exp -3 atm) and Hib + Sp + Mel at approximately 1215 +/- 10 C. Simple thermochemical models for the substitution of trace elements into the Ca-site of meteoritic Hib suggest that virtually all Eu is divalent in early condensate Hibs but that Eu(2+)/Eu(3+) decreases by a factor of 20 or more during the course of condensation, primarily because the ratio is proportional to the partial pressure of Al, which decreases dramatically as aluminous phases condense. The relative sizes of Eu and Yb anomalies in meteoritic Hibs and CAI's may be influenced by this effect.

Beckett, J. R.↗
NASA NTRS1994

The stability of hibonite, melilite and other aluminous phases in silicate melts: Implications for the origin of hibonite-bearing inclusions from carbonaceous chondrites

Phase fields in which hibonite and silicate melt coexist with spinel CaAl4O7, gehlenitic melilite, anorthite or corundum at 1 bar in the system CaO-MgO-Al2O3-SiO2-TiO2 were determined. The hibonites contain up to 1.7 wt% SiO2. For TiO2, the experimentally determined partition coefficients between hibonite and coexisting melt D(sub i)(sup Hib/L), vary from 0.8 to 2.1 and generally decrease with increasing TiO2 in the liquid. Based on Ti partitioning between hibonite and melt, bulk inclusion compositions and hibonite-saturated liquidus phase diagrams, the hibonite in hibonite-poor fluffy Type A inclusions from Allende and at least some hibonite from hibonite-rich inclusions is relict, although much of the hibonite from hibonite-glass spherules probably crystallized metasably from a melt. Bulk compositions for all of these CAIs are consistent with an origin as melite + hibonite + spinel + perovskite phase assembalges that were partially altered and in some cases partially or completely melted. The duration of the melting event was sufficient to remove any Na introduced by the alteration process but frequently insufficient to dissolve all of the original hibonite. Simple thermochemical models developed for meteoritic melilite and hibonite solid solutions were used to obtain equilibration temperatures of hibonite-bearing phase assemblages with vapor. Referenced to 10(exp -3) atm, hibonite + corundum + vapor equilibrated at approximately 1260 C and hibonite + spinel +/- melilite + vapor at 1215 +/- 10 C. If these temperatures reflect condensation in a cooling gas of solar composition, then hibonite +/- corundum condensed first, followed by spinel and then melilite. The position of perovskite within this sequence is uncertain, but it probably began to condense before spinel. This sequence of phase appearances and relative temperatures is generally consistent with observed textures but differs from expectations based on classical condensation calculations in that equilibration temperatures are generally lower than predicted and melilite initially condenses with or even after spinel. Simple thermochemical modes for the substitution of trace elements into the Ca site of meteoritic hibonites suggest that virtually all Eu is divalent in early condensate hibonites but that Eu(2+)/Eu(#+) decreases by a factor of 20 or more during the course of condensation primarily because the ratio is proportional to the partial pressure of Al, which decreases dramatically as aluminous phase condense. The relative sizes of Eu and Yb anomalies in meteoritic hibonites and inclusions may be partly due to this effect.

Beckett, J. R.↗
NASA NTRS2007

Method for Constructing Composite Response Surfaces by Combining Neural Networks with Polynominal Interpolation or Estimation Techniques

A method and system for data modeling that incorporates the advantages of both traditional response surface methodology (RSM) and neural networks is disclosed. The invention partitions the parameters into a first set of s simple parameters, where observable data are expressible as low order polynomials, and c complex parameters that reflect more complicated variation of the observed data. Variation of the data with the simple parameters is modeled using polynomials; and variation of the data with the complex parameters at each vertex is analyzed using a neural network. Variations with the simple parameters and with the complex parameters are expressed using a first sequence of shape functions and a second sequence of neural network functions. The first and second sequences are multiplicatively combined to form a composite response surface, dependent upon the parameter values, that can be used to identify an accurate mode

Rai, Man Mohan↗
NASA NTRS2010

Multiscale Simulations of Magnetic Island Coalescence

We describe a new interactive parallel Adaptive Mesh Refinement (AMR) framework written in the Python programming language. This new framework, PyAMR, hides the details of parallel AMR data structures and algorithms (e.g., domain decomposition, grid partition, and inter-process communication), allowing the user to focus on the development of algorithms for advancing the solution of a systems of partial differential equations on a single uniform mesh. We demonstrate the use of PyAMR by simulating the pairwise coalescence of magnetic islands using the resistive Hall MHD equations. Techniques for coupling different physics models on different levels of the AMR grid hierarchy are discussed.

Dorelli, John C.↗
NASA NTRS2014

UAS Conflict-Avoidance Using Multiagent RL with Abstract Strategy Type Communication

The use of unmanned aerial systems (UAS) in the national airspace is of growing interest to the research community. Safety and scalability of control algorithms are key to the successful integration of autonomous system into a human-populated airspace. In order to ensure safety while still maintaining efficient paths of travel, these algorithms must also accommodate heterogeneity of path strategies of its neighbors. We show that, using multiagent RL, we can improve the speed with which conflicts are resolved in cases with up to 80 aircraft within a section of the airspace. In addition, we show that the introduction of abstract agent strategy types to partition the state space is helpful in resolving conflicts, particularly in high congestion.

Unmanned Autonomous Systems↗
DOE OSTI2021

Electrochemical Manipulation and Radiolytic Evaluation of Organic Phase Neptunium

Presentation for Seed LDRD proposal presentation: This Seed LDRD research proposes to test an innovative approach to precisely control the oxidation state distribution of neptunium (Np) under used nuclear fuel (UNF) reprocessing conditions using novel electrochemical methods. Current UNF reprocessing technologies are not financially viable in the US, requiring significant scientific and technological innovation to improve cost efficiency. Reducing the number of process cycles is one avenue for increasing cost efficiency, of which resolving the challenge associated with isolating Np is critical. Under envisioned process conditions, Np is present in a mixture of extractable (Np(IV) and Np(VI)) and inextractable (Np(V)) oxidation states, the distribution of which is dependent on several factors, including ionizing radiation dose, that change throughout a reprocessing scheme. Consequently, Np unintentionally partitions into various UNF reprocessing phases and product streams, ultimately increasing the number of process cycles to isolate UNF components. Here, we propose to employ novel, high surface area, optically transparent, Ligand Modified tin-doped indium oxide Electrodes (LMES). These LMEs bind Np, and therefore enable concurrent generation and spectroscopic characterization of Np oxidation states in organic solutions. These proof-of-concept experiments will: (i) facilitate optimization of the proposed electrochemical system conditions for Np oxidation state manipulation; (ii) identify the accessible electrochemical window for Np complexes in the organic phase; (iii) report characteristic optical spectra for each accessible complexed Np oxidation state; and (iv) determine the lifetime and partitioning of a given atypical Np oxidation state in the organic phase in the presence and absence of ionizing radiation fields. The data gathered by this Seed LDRD will provide support for the design of an electrochemical process concept for the precise manipulation of Np oxidation states in UNF reprocessing solvent systems, with the intention of providing advanced control over Np mass transfer, and thus greater process efficiency and economy.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
NASA NTRS2000

Reliability Modeling of Microelectromechanical Systems Using Neural Networks

Microelectromechanical systems (MEMS) are a broad and rapidly expanding field that is currently receiving a great deal of attention because of the potential to significantly improve the ability to sense, analyze, and control a variety of processes, such as heating and ventilation systems, automobiles, medicine, aeronautical flight, military surveillance, weather forecasting, and space exploration. MEMS are very small and are a blend of electrical and mechanical components, with electrical and mechanical systems on one chip. This research establishes reliability estimation and prediction for MEMS devices at the conceptual design phase using neural networks. At the conceptual design phase, before devices are built and tested, traditional methods of quantifying reliability are inadequate because the device is not in existence and cannot be tested to establish the reliability distributions. A novel approach using neural networks is created to predict the overall reliability of a MEMS device based on its components and each component's attributes. The methodology begins with collecting attribute data (fabrication process, physical specifications, operating environment, property characteristics, packaging, etc.) and reliability data for many types of microengines. The data are partitioned into training data (the majority) and validation data (the remainder). A neural network is applied to the training data (both attribute and reliability); the attributes become the system inputs and reliability data (cycles to failure), the system output. After the neural network is trained with sufficient data. the validation data are used to verify the neural networks provided accurate reliability estimates. Now, the reliability of a new proposed MEMS device can be estimated by using the appropriate trained neural networks developed in this work.

Perera. J. Sebastian↗
DOE OSTI2020

Niche Partitioning of Microbial Communities at an Ancient Vitrified Hillfort: Implications for Vitrified Radioactive Waste Disposal

A pre-Viking era vitrified hillfort, Broborg, provides a habitat analogue for disposed radioactive waste glass and shows strong niche partitioning among the organisms involved in glass alteration. Microbes cannot be eliminated from radioactive waste disposal facilities and the consequences of bio-colonization must be understood. We use Broborg as a model system to inform what microbial processes might influence long-term radioactive waste glass durability by examining anthropogenic glass that has been subjected to bio-colonization for over 1,500 years. Scanning electron microscopy (SEM) images reveal the surficial biofilm structure, and chemical/mineralogy analysis in combination with deoxyribonucleic acid (DNA) sequencing of samples from the vitrified substrate, the adjacent soil, and the general topsoil provide insight into niche partitioning. The ancient glass niche supports a unique microbial community of bacteria, fungi, and protists that manifests the species response to local geochemical and mineralogical conditions. Communities from the geochemical niche associated with the glass are distinct and less diverse than soil communities. The microbiome of the glass and adjacent soil are dominated by lichens, lichen-associated microorganisms, and other epilithic, endolithic, and epigeic organisms. Pseudomonads dominate the prokaryotic communities on the vitrified material, but not the adjacent soil. In contrast, the general topsoil communities are enriched in plant rhizosphere organisms. Taxa associated with vitrification have bio-corrosive properties that could be detrimental to glass durability, including silicate mineral dissolution, extraction of essential elements, secretion of geochemically reactive organic acids, and dissolution induced by improved water retention. However, these stable long-term biofilms also possess a homeostatic function that could limit glass alteration. Overall, this study demonstrates the potential impacts that microbial colonization and niche partitioning can have on glass alteration and subsequent release of radionuclides from a disposal facility for vitrified radioactive waste.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Deforestation reshapes land-surface energy-flux partitioning

Land-use and land-cover change significantly modify local land-surface characteristics and water/energy exchanges, which can lead to atmospheric circulation and regional climate changes. In particular, deforestation accounts for a large portion of global land-use changes, which transforms forests into other land cover types, such as croplands and grazing lands. Many previous efforts have focused on observing and modeling land–atmosphere–water/energy fluxes to investigate land–atmosphere coupling induced by deforestation. However, interpreting land–atmosphere–water/energy-flux responses to deforestation is often complicated by the concurrent impacts from shifts in land-surface properties versus background atmospheric forcings. In this study, we used 29 paired FLUXNET sites, to improve understanding of how deforested land surfaces drive changes in surface-energy-flux partitioning. Each paired sites included an intact forested and non-forested site that had similar background climate. We employed transfer entropy, a method based on information theory, to diagnose directional controls between coupling variables, and identify nonlinear cause–effect relationships. Transfer entropy is a powerful tool to detective causal relationships in nonlinear and asynchronous systems. The paired eddy covariance flux measurements showed consistent and strong information flows from vegetation activity (gross primary productivity (GPP)) and physical climate (e.g. shortwave radiation, air temperature) to evaporative fraction (EF) over both non-forested and forested land surfaces. More importantly, the information transfers from radiation, precipitation, and GPP to EF were significantly reduced at non-forested sites, compared to forested sites. We then applied these observationally constrained metrics as benchmarks to evaluate the Energy Exascale Earth System Model (E3SM) land model (ELM). ELM predicted vegetation controls on EF relatively well, but underpredicted climate factors on EF, indicating model deficiencies in describing the relationships between atmospheric state and surface fluxes. Moreover, changes in controls on surface energy flux partitioning due to deforestation were not detected in the model. We highlight the need for benchmarking model simulated surface-energy fluxes and the corresponding causal relationships against those of observations, to improve our understanding of model predictability on how deforestation reshapes land surface energy fluxes.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1988

Multi-time-step integration using nodal partitioning

An algorithm is presented which integrates different groups of nodes of a finite element mesh with different time steps and different integrators. Since the nodal groups are updated independently no unsymmetric systems need be solved. Stability is demonstrated by showing that an energy norm of the solution decreases after every update if the time step is less than a given critical value. The element eigenvalue inequality theorem is used to give the critical time step in terms of element eigenvalues.

Smolinski, P.↗
DOE OSTI2020

Mantle–melt partitioning of the highly siderophile elements: New results and application to Mars

Trace elements and extant and extinct isotopic attributes in Martian meteorites have been used to argue that Mars accreted quickly, differentiated into core and mantle, and established several mantle reservoirs, possibly within 10 Ma of T0. The partitioning of trace elements in the deep mantle has been relatively unstudied, despite the need for such knowledge in understanding magma ocean crystallization and the origin of depleted and enriched mantle reservoirs. The siderophile element composition of the Martian mantle and lithophile isotopic systems such as Sr, Hf, and Nd are thought to record evidence for early metal–silicate equilibrium and deep magma ocean at an intermediate depth and pressure of 800 km or 14 GPa. We have carried out experiments across this pressure range to better understand the mineral/melt partitioning of a wide range of elements. These new data are used to evaluate differentiation models for Mars and to help interpret the available isotopic data. The relatively incompatible nature of Re compared to mildly compatible Os means that the crystallization of a deep magma ocean will lead to residual liquids with superchondritic Re/Os, and solids with subchondritic Re/Os. Such material available in the mantle could be the source of enriched isotopic reservoir that produced shergottites with +γOs values. Slightly subchondritic Re/Os ratios in the crystallizing solids would provide a reservoir that could produce -γOs values. Finally, melting of mixtures of these two enriched and depleted endmembers could explain the Nd-Os isotopic correlations and systematics of shergottites.

58 GEOSCIENCES↗
NASA NTRS2020

Mantle-melt Partitioning of the Highly Siderophile Elements: New Results and Application to Mars

Trace elements and extant and extinct isotopic attributes in martian meteorites have been used to argue that Mars accreted quickly, differentiated into core and mantle, and established several mantle reservoirs, possibly within 10 Ma of T0. The partitioning of trace elements in the deep mantle has been relatively unstudied, despite the need for such knowledge in understanding magma ocean crystallization and the origin of depleted and enriched mantle reservoirs. The siderophile element composition of the martian mantle, and lithophile isotopic systems such as Sr, Hf, and Nd, are thought to record evidence for early metal-silicate equilibrium and deep magma ocean at an intermediate depth and pressure of 800 km or 14 GPa. We have carried out experiments across this pressure range to better understand the mineral/melt partitioning of a wide range of elements. These new data are used to evaluate differentiation models for Mars and to help interpret the available isotopic data. The relatively incompatible nature of Re compared to mildly compatible Os means that the crystallization of a deep magma ocean will lead to residual liquids with super chondritic Re/Os, and solids with sub-chondritic Re/Os. Such material available in the mantle could be the source of enriched isotopic reservoir that produced shergottites with + Os values. On the other hand, slightly sub-chondritic Re/Os ratios in the crystallizing solids would provide a reservoir that could produce - Os values. Melting of mixtures of these two enriched and depleted end members could explain the Nd-Os isotopic correlations and systematics of shergottites.

K Righter↗
NASA NTRS2000

An Approach to Experimental Design for the Computer Analysis of Complex Phenomenon

The ability to make credible system assessments, predictions and design decisions related to engineered systems and other complex phenomenon is key to a successful program for many large-scale investigations in government and industry. Recently, many of these large-scale analyses have turned to computational simulation to provide much of the required information. Addressing specific goals in the computer analysis of these complex phenomenon is often accomplished through the use of performance measures that are based on system response models. The response models are constructed using computer-generated responses together with physical test results where possible. They are often based on probabilistically defined inputs and generally require estimation of a set of response modeling parameters. As a consequence, the performance measures are themselves distributed quantities reflecting these variabilities and uncertainties. Uncertainty in the values of the performance measures leads to uncertainties in predicted performance and can cloud the decisions required of the analysis. A specific goal of this research has been to develop methodology that will reduce this uncertainty in an analysis environment where limited resources and system complexity together restrict the number of simulations that can be performed. An approach has been developed that is based on evaluation of the potential information provided for each "intelligently selected" candidate set of computer runs. Each candidate is evaluated by partitioning the performance measure uncertainty into two components - one component that could be explained through the additional computational simulation runs and a second that would remain uncertain. The portion explained is estimated using a probabilistic evaluation of likely results for the additional computational analyses based on what is currently known about the system. The set of runs indicating the largest potential reduction in uncertainty is then selected and the computational simulations are performed. Examples are provided to demonstrate this approach on small scale problems. These examples give encouraging results. Directions for further research are indicated.

Rutherford, Brian↗
DOE OSTI2025

Efficient shallow Ritz method for 1D diffusion problems

This paper studies the shallow Ritz method for solving the one-dimensional diffusion problem. It is shown that the shallow Ritz method improves the order of approximation dramatically for non-smooth problems. To realize this optimal or nearly optimal order of the shallow Ritz approximation, we develop a damped block Newton (dBN) method that alternates between updates of the linear and non-linear parameters. Per each iteration, the linear and the non-linear parameters are updated by exact inversion and one step of a modified, damped Newton method applied to a reduced non-linear system, respectively. The computational cost of each dBN iteration is $\mathcal{O}$(n). Starting with the non-linear parameters as a uniform partition of the interval, numerical experiments show that the dBN is capable of efficiently moving mesh points to nearly optimal locations. In conclusion, to improve the efficiency of the dBN further, we propose an adaptive damped block Newton (AdBN) method by combining the dBN with the adaptive neuron enhancement (ANE) method [28].

Diffusion problems↗
NASA NTRS1977

Lie theoretic aspects of the Riccati equation

Various features of the application of Lie theory to matrix Riccati equations, of basic importance in control and system theories, are discussed. Particular consideration is given to centralizer foliation, the Cartan decomposition, matrix Riccati equations as Lie systems on Grassmanians, local analysis near a zero point of a vector field, linearization in homogeneous space, the tangent bundle in terms of partitioned matrices, and stability properties of fixed points of Riccati vector fields.

Hermann, R.↗