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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Decorrelating the errors of the galaxy correlation function with compact transformation matrices

Abstract Covariance matrix estimation is a persistent challenge for cosmology, often requiring a large number of synthetic mock catalogues. The off-diagonal components of the covariance matrix also make it difficult to show representative error bars on the 2-point correlation function (2PCF) since errors computed from the diagonal values of the covariance matrix greatly underestimate the uncertainties. We develop a routine for decorrelating the projected and anisotropic 2PCF with simple and scale-compact transformations on the 2PCF. These transformation matrices are modelled after the Cholesky decomposition and the symmetric square root of the Fisher matrix. Using mock catalogues, we show that the transformed projected and anisotropic 2PCF recover the same structure as the original 2PCF while producing largely decorrelated error bars. Specifically, we propose simple Cholesky-based transformation matrices that suppress the off-diagonal covariances on the projected 2PCF by ${\sim } 95{{\ \rm per\ cent}}$ and that on the anisotropic 2PCF by ${\sim } 87{{\ \rm per\ cent}}$. These transformations also serve as highly regularized models of the Fisher matrix, compressing the degrees of freedom so that one can fit for the Fisher matrix with a much smaller number of mocks.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

B/PS bulges in DESI Legacy edge-on galaxies – I. Sample building

ABSTRACT We present the biggest up-to-date sample of edge-on galaxies with boxy/peanut-shaped (B/PS) bulges and X-structures. The sample was prepared using images from the Dark Energy Spectroscopic Instrument (DESI) Legacy catalogue and contains about 2000 galaxies. To find suitable candidates in catalogue, we made the assumption that the residues (original images minus model) of galaxies with B/PS bulges should exhibit a characteristic X-shape. Galaxies with such features were selected by eye and then used as input data for a neural network training, which was applied to a bigger sample of edge-on galaxies. Using the available data and the photometric models from the literature, we investigated the observational and statistical properties of the sample created. Comparing the B/D ratios for galaxies with and without B/PS bulges, we found that the B/D ratio for galaxies from our sample is statistically higher, with typical values in the range ≈0.2–0.5 depending on the decomposition procedure. We studied how the opening angles φ of the X-structure and the length of its rays are distributed in the formed sample and found them to be consistent with previous measurements and predictions from N-body models, e.g. $\varphi \gtrsim 25{^\circ }$, but measured here for a much larger number of galaxies. We found a sharp increase in the B/PS bulge fraction for stellar masses log M⋆ ≳ 10.4, but for edge-on galaxies, which complements the results of previous works. The sample can be used in future work to test various bar models and their relationship with B/PS bulges, as well as to study their stability and evolution.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2018

International Space Station Future Correlation Analysis Improvements

Ongoing modal analyses and model correlation are performed on different configurations of the International Space Station (ISS). These analyses utilize on-orbit dynamic measurements collected using four main ISS instrumentation systems: External Wireless Instrumentation System (EWIS), Internal Wireless Instrumentation System (IWIS), Space Acceleration Measurement System (SAMS), and Structural Dynamic Measurement System (SDMS). Remote Sensor Units (RSUs) are network relay stations that acquire flight data from sensors. Measured data is stored in the Remote Sensor Unit (RSU) until it receives a command to download data via RF to the Network Control Unit (NCU). Since each RSU has its own clock, it is necessary to synchronize measurements before analysis. Imprecise synchronization impacts analysis results. A study was performed to evaluate three different synchronization techniques: (i) measurements visually aligned to analytical time-response data using model comparison, (ii) Frequency Domain Decomposition (FDD), and (iii) lag from cross-correlation to align measurements. This paper presents the results of this study.

time synchronization↗
DOE OSTI2018

A generalized framework for reduced-order modeling of a wind turbine wake

A reduced-order model for a wind turbine wake is sought from large eddy simulation data. Fluctuating velocity fields are combined in the correlation tensor to form the kernel of the proper orthogonal decomposition (POD). Proper orthogonal decomposition modes resulting from the decomposition represent the spatially coherent turbulence structures in the wind turbine wake; eigenvalues delineate the relative amount of turbulent kinetic energy associated with each mode. Back-projecting the POD modes onto the velocity snapshots produces dynamic coefficients that express the amplitude of each mode in time. A reduced-order model of the wind turbine wake (wakeROM) is defined through a series of polynomial parameters that quantify mode interaction and the evolution of each POD mode coefficients. The resulting system of ordinary differential equations models the wind turbine wake composed only of the large-scale turbulent dynamics identified by the POD. Tikhonov regularization is used to recalibrate the dynamical system by adding additional constraints to the minimization seeking polynomial parameters, reducing error in the modeled mode coefficients. The wakeROM is periodically reinitialized with new initial conditions found by relating the incoming turbulent velocity to the POD mode coefficients through a series of open-loop transfer functions. The wakeROM reproduces mode coefficients to within 25.2%, quantified through the normalized root-mean-square error. Furthermore, a high-level view of the modeling approach is provided as a platform to discuss promising research directions, alternate processes that could benefit stability and efficiency, and desired extensions of the wakeROM.

17 WIND ENERGY↗
DOE OSTI2020

Microwave-induced selective decomposition of cellulose: Computational and experimental mechanistic study

Understanding microwave-material interactions will help facilitate the utilization of microwave technology in gasification and renewable energy production. In this study, cellulose was used as a model compound to simulate the organic matter in biomass, and its catalytic decomposition under a microwave (MW) field was studied to identify structural changes from the reaction. The study was conducted using a MW source coupled to a fixed-bed gas-flow reactor, mass spectroscopic, and Fourier transform infrared spectroscopy post-reaction analysis. Zeolite 13X was chosen as a microwave absorber to study the catalytic enhancement of the decomposition of cellulose. Density functional theory (DFT) was used to gain insights into the molecular transformations occurring in the presence of a static electric field, which was used to simulate the electric field component of the microwave electromagnetic radiation. Theoretical calculations demonstrated that both the positive and negative portion of the electric field interact with the permanent dipoles of the cellulose effecting the decomposition through the glycosidic bond breaking mechanism. The theoretical result was verified using infrared spectroscopic analysis of the pure cellulose during microwave heating. The theoretical calculations suggest only the positive electric field component may be active for the cellulose decomposition in the presence of Zeolite 13X. Physically mixing Zeolite 13X with the cellulose led to a significant enhancement in the decomposition rate of the glycosidic bond. Zeolite 13X enhanced the glycosidic O-C decomposition at lower MW power (lower temperatures), whereas the O-H functional group required higher MW power (higher temperature) for its decomposition. The DFT study coupled with the reaction studies revealed that the electric field polarizability is dependent upon both the direction and the orientation of the cellulose. Gas products revealed that applying 250 W of MW power led to the production of CO, H 2 , along with some CO 2 , CH 4 , and benzene at 305 °C. Finally, reaction under 500, 750, and 1000 W of power at constant temperature (305 °C) revealed that higher power led to the complete decomposition of cellulose to mostly CO, H 2 , and CO 2 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Pseudo-Polymorphism in Layered FeS Intercalates: A Competition between Charged and Neutral Guest Species

Systematic synthesis studies of the formation of tetrahedral FeS-ethylenediamine intercalates resulted in the synthesis of a new compound, [Fe 9.4(2) S 10 ][Fe(en) 3 ] 0.6(1) ·en 0.9 ( 3 ). The composition and complex crystal structure were determined based on a synergistic combination of elemental composition, decomposition behavior, high-resolution synchrotron X-ray diffraction and total scattering, 57 Fe Mössbauer spectroscopy, and electron diffraction. The structural model was derived based on a systematic comparison to the previously reported structures [Fe 8 S 10 ][Fe(en) 3 ] 1 ·en 0.5 and tetragonal FeS. The new compound has flat Fe 9.4 S 10 layers, analogous to those in superconducting binary FeS. In the crystal structure of [Fe 9.4 S 10 ][Fe(en) 3 ] 0.6 ·en 0.9 , the interlayer space is occupied by [Fe(en) 3 ] 2+ complexes and neutral ethylenediamine molecules in a ~2:3 ratio. Interlayer species are not randomly oriented but ordered as evidenced by superstructural diffraction peaks in both high-resolution X-ray diffraction and electron diffraction patterns. Magnetic studies reveal no superconducting transition down to 2 K, indicating that the presence of minute amounts (~6%) of iron vacancies at the Fe-S layer in [Fe 9.4 S 10 ][Fe(en) 3 ] 0.6 ·en 0.9 is still sufficient to shift the position of the Fermi level resulting in an adjustment of the properties. Here, our work shows the importance of detailed characterization of the crystal structure of intercalated compounds to understand the origin of the observed properties and develop proper structure–property relationships.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

From deep TLS validation to ensembles of atomic models built from elemental motions

Procedures are described for extracting the vibration and libration parameters corresponding to a given set of TLS matrices and their simultaneous validation. Knowledge of these parameters allows the generation of structural ensembles corresponding to these matrices. The translation–libration–screw model first introduced by Cruickshank, Schomaker and Trueblood describes the concerted motions of atomic groups. Using TLS models can improve the agreement between calculated and experimental diffraction data. Because the T, L and S matrices describe a combination of atomic vibrations and librations, TLS models can also potentially shed light on molecular mechanisms involving correlated motions. However, this use of TLS models in mechanistic studies is hampered by the difficulties in translating the results of refinement into molecular movement or a structural ensemble. To convert the matrices into a constituent molecular movement, the matrix elements must satisfy several conditions. Refining the T, L and S matrix elements as independent parameters without taking these conditions into account may result in matrices that do not represent concerted molecular movements. Here, a mathematical framework and the computational tools to analyze TLS matrices, resulting in either explicit decomposition into descriptions of the underlying motions or a report of broken conditions, are described. The description of valid underlying motions can then be output as a structural ensemble. All methods are implemented as part of the PHENIX project.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1989

Low dimensional models of the wall region of a turbulent boundary layer, and the possibility of control

A method of identification of coherent structures in a random turbulent flow is outlined with emphasis on the structure best correlated with a random energy-integrable field and application of the proper orthogonal decomposition to the shear flow of the wall region. The wall region of a pipe flow with almost pure glycerine is investigated experimentally, dynamic equations are obtained, and an energy-transfer model is employed. Numerical solutions are obtained, implications for the flow in the wall region are discussed with focus placed on the sets of solutions exhibiting intermittency. The most significant finding of the study is considered to be the suggestion of the etiology of the bursting phenomenon; presuming that abrupt transitions from one fixed point to the other can be identified with a burst, these bursts appear to be produced autonomously by the wall region, but be triggered by pressure signals from the outer layer.

Lumley, John L.↗
DOE OSTI2021

Increasing temperatures reduce invertebrate abundance and slow decomposition

Decomposition is an essential ecosystem service driven by interacting biotic and abiotic factors. Increasing temperatures due to climate change can affect soil moisture, soil fauna, and subsequently, decomposition. Understanding how projected climate change scenarios will affect decomposition is of vital importance for predicting nutrient cycling and ecosystem health. In this study, we experimentally addressed the question of how the early stages of decomposition would vary along a gradient of projected climate change scenarios. Given the importance of biodiversity for ecosystem service provisioning, we measured the effect of invertebrate exclusion on red maple ( Acer rubrum ) leaf litter breakdown along a temperature gradient using litterbags in warming chambers over a period of five weeks. Leaf litter decomposed more slowly in the warmer chambers and in the litterbag treatment that minimized invertebrate access. Moreover, increasing air temperature reduced invertebrate abundance and richness, and altered the community composition, independent of exclusion treatment. Using structural equation models, we were able to disentangle the effects of average air temperature on leaf litter loss, finding a direct negative effect of warming on the early stages of decomposition, independent of invertebrate abundance. This result indicates that not only can climate change affect the invertebrate community, but may also directly influence how the remaining organisms interact with their environment and their effectiveness at provisioning ecosystem services. Overall, our study highlights the role of biodiversity in maintaining ecosystem services and contributes to our understanding of how climate change could disrupt nutrient cycling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Low-Temperature Non-Oxidative Coupling of Methane on Atomically Dispersed Titanium–Aluminum–Boron Nanopowder

Nonoxidative coupling of methane represents a long-standing challenge in heterogeneous catalysis, as it requires activation of the carbon–hydrogen (C–H) bond, controlled carbon–carbon (C–C) bond formation, and effective hydrogen management without relying on oxidants. Here, we report a low-temperature C–H activation and nonoxidative C–C coupling of methane over atomically dispersed titanium–aluminum–boron nanopowder (Ti–Al–B NP) utilizing a catalytic microreactor coupled to synchrotron single-photon photoionization reflectron time-of-flight mass spectrometry. The soft-ionization, in situ probing method detects the nascent reaction products and radical intermediates under operando conditions, including methyl radical, C2 hydrocarbons, and molecular hydrogen. Methane activation is initiated at 800 K, approximately 700 K below the gas-phase decomposition threshold, leading predominantly to ethylene formation with selectivity reaching up to 78% among the C–C coupled products. Electronic structure calculations on model Ti–Al–B clusters elucidate a cooperative catalytic mechanism in which titanium enables methane adsorption and C–H activation, boron acts as a reversible hydrogen reservoir, and aluminum stabilizes methylene intermediates, thereby facilitating selective C–C coupling and dehydrogenation. These findings establish a distinct catalyst architecture for nonoxidative methane coupling based on earth abundant elements alternative to expensive platinum and other noble metal-containing conventional catalysts and provide molecular-level design principles for controlling dehydrogenation and subsequent C–C bond formation in challenging light alkane conversions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Reduced order modeling for flow and transport problems with Barlow Twins self-supervised learning

Abstract We propose a unified data-driven reduced order model (ROM) that bridges the performance gap between linear and nonlinear manifold approaches. Deep learning ROM (DL-ROM) using deep-convolutional autoencoders (DC–AE) has been shown to capture nonlinear solution manifolds but fails to perform adequately when linear subspace approaches such as proper orthogonal decomposition (POD) would be optimal. Besides, most DL-ROM models rely on convolutional layers, which might limit its application to only a structured mesh. The proposed framework in this study relies on the combination of an autoencoder (AE) and Barlow Twins (BT) self-supervised learning, where BT maximizes the information content of the embedding with the latent space through a joint embedding architecture. Through a series of benchmark problems of natural convection in porous media, BT–AE performs better than the previous DL-ROM framework by providing comparable results to POD-based approaches for problems where the solution lies within a linear subspace as well as DL-ROM autoencoder-based techniques where the solution lies on a nonlinear manifold; consequently, bridges the gap between linear and nonlinear reduced manifolds. We illustrate that a proficient construction of the latent space is key to achieving these results, enabling us to map these latent spaces using regression models. The proposed framework achieves a relative error of 2% on average and 12% in the worst-case scenario (i.e., the training data is small, but the parameter space is large.). We also show that our framework provides a speed-up of $$7 \times 10^{6}$$ 7 × 10 6 times, in the best case, and $$7 \times 10^{3}$$ 7 × 10 3 times on average compared to a finite element solver. Furthermore, this BT–AE framework can operate on unstructured meshes, which provides flexibility in its application to standard numerical solvers, on-site measurements, experimental data, or a combination of these sources.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Transport of fast electrons in a nanowire array with collisional effects included

The transport of picosecond laser generated fast electrons in a nanowire array is studied with two-dimensional particle-in-cell simulations. Our simulations show that a fast electron beam is initially guided and collimated by strong magnetic filaments in the array. Subsequently, after the decomposition of the structure of nanowire array due to plasma expansion, the beam is still collimated by the resistive magnetic field. An analytical model is established to give a criterion for long-term beam collimation in a nanowire array; it indicates that the nanowire cell should be wide enough to keep the beam collimated in picosecond scale.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

pyDRESCALk

Modern data scientists are tasked to analyze ever-growing data sets with increasingly complex relationships. Tensor decompositions have come to play a central role in identifying underlying latent structures in higher-order data. The problem of fitting tensor models to different distributions is complicated by the combinations of size, dimensionality, and sparsity present in real world data. The situation demands efficient algorithms designed for shared-memory and distributed systems. This work will present new research that tackles these challenges on several different fronts, leveraging optimizations in numerical algorithms and sparse tensor representations in heterogeneous high performance computing environments.

Bhattarai, Manish↗
DOE OSTI2017

Combustion energy frontier research center (CEFRC) final report (August 1, 2009 – July 31, 2016)

The Combustion Energy Frontier Research Center (CEFRC) was established to tackle the single overarching grand challenge of energy sustainability, energy security and global warming: to develop a “validated, predictive, multi-scale, combustion modeling capability to optimize the design and operation of evolving fuels in advanced engines for transportation applications,” as identified in the DOE report on “Basic Energy Needs for Clean and Efficient Combustion of 21st Century Transportation Fuels”. The challenge is particularly daunting since energy conversion efficiencies and exhaust emissions are governed by coupled chemical and transport processes at multiple length scales ranging from electron excitation to molecular rearrangements to nanoscale particulate formation to turbulent fuel/air mixing. To tackle this challenge, the CEFRC assembled a world-class team of 15 principal investigators, with the objectives to: 1) develop and test theoretical models to predict elementary reaction rates, molecule thermalization rates, chemical bond dissociation energies, and nonequilibrium transport properties using quantum chemistry calculations that account for strong electron correlation and multiple electronic potential energy surfaces; 2) develop automated kinetic mechanism generation, reduction, and error control methods for predicting alternative fuel including biofuel oxidation, fuel droplet decomposition, and NOx and particulate formation; 3) validate and improve the predictions of these models by measuring ignition delay times, species profiles, flame structures, burning limits, turbulence-kinetic coupling, and NOx and soot emissions at high-pressures and near-limit conditions, by using advanced experimental diagnostic techniques including multiple laser techniques, molecular beam sampling and synchrotron photoionization, and by conducting the measurements in high-pressure shock tubes, jet-stirred and flow reactors, flame bombs, counterflow flames, and advanced-design rapid compression ignition instruments; and 4) develop a suite of validated petascale high-fidelity simulation and modeling capabilities to understand and predict chemistry-turbulence-radiation coupling for new fuels in new regimes, including the high pressure, low-temperature combustion in advanced engine and turbine designs, and 5) establish a knowledge highway between researchers and engineers in academia, national laboratories, and industry to facilitate the dissemination and exchange of knowledge on national and international levels, and enrich the talent pool and capabilities of the next generation of combustion scientists and engineers. The technical activities of the CEFRC were conducted through three Disciplinary Working Groups – Chemistry Theory, Experiment and Mechanism, and Reacting Flows, which coordinated the Center’s research on the development of combustion chemistry of Foundation Fuels (C0–C4 hydrocarbons), Alcohols, and Biodiesel through three corresponding Mechanism Thrust Groups. Such a two-dimensional coordinated and tightly interwoven research structure has been proven to be highly effective in assuring the interplay between the developments of the fundamentals of combustion science and the utilization of the various categories of fuels. The Center has accomplished the above goals over the five year period (August 1, 2009 – July 31, 2014) with appropriated funding, followed by two additional no-cost-extension (NCE) years. The research results are documented in 230 journal publications, with six legacy review papers on the study of combustion chemistry using shock tubes, flow reactors, rapid compression machines, and flames, on uncertainty quantification, and on theoretical reaction dynamics and chemical modeling of combustion. A robust outreach program complemented these PI-led research activities, consisting of: 1) a roving post-doc program comprised of a corps of Center-appointed, co- or multi-sponsored post-doctoral fellows with rotating assignments to conduct seed projects initiated by at least two PIs, in residence with these sponsoring PIs, to rapidly pursue new and high-risk, high-payoff interdisciplinary ideas; 2) an annual summer school on combustion heavily attended (~200) by senior graduate students and practicing researchers covering advanced topics on chemical kinetics, fluid mechanics, turbulent combustion, engine combustion, new technologies, etc.; 3) a robust open web-site providing Center and community information as well as the lecture videos and notes of the summer school; and 4) widely distributed biannual newsletters.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

Mechanisms of interfacial reactivity in near surface and extreme environments

The local water structure surrounding ions in aqueous solutions greatly affects their chemical properties such as reaction rates, ion association, and proton and electron transport. These properties result in the behavior of ions in natural aqueous environments. For example ore transport is facilitated by chloride ion pair formation and the reaction of ions in an interface is strongly dependent on the dehydration of the ion hydration shell. We are developing the use of high-­resolution XAFS observations and 1st principles based MD-­XAFS analysis (spectra simulated using 1st principle methods with no adjustable parameters, AIMD) to interpret the solution properties of strongly interacting aqueous solutes under arbitrary pressure and temperature conditions. In the 1st principle MD-­XAFS method density functional theory (DFT) based MD simulations(Car and Parrinello, 1985) are used to generate a large ensemble of structural snap shots of the hydration region. These are then used to generate scattering intensities. I emphasize three points about this novel approach to analyzing XAFS data. 1st: As illustrated in Figure 1, the level of agreement between the calculated and observed intensities is considerably higher than has been obtained by any XAFS analysis to date (note 2nd shell region, R> 2 Å). 2nd: This result was obtained from a parameter free simulation with no fitting of the interaction potentials to any data. This supports the use of these methods for more difficult environments and more complex solutes (polyions). 3rd: New information about the shell structure (Figure 1) is now available because of this more detailed agreement. We note also that both multiple scattering and second shell features are well represented in the analysis. As far as we know this is the 1st analysis of second shell structure and multiple scattering. Excellent agreement has been obtained for most of the third row metal ions: Ca 2+ , Zn 2+ , Cu 2+ , Ni 2+ , Co 2+ , Mn 2+ , Fe 3+ , Cr 3+ . Calculations on these systems are demanding because of their open electronic shells, and high ionic charge. Principal Investigator: Professor John Weare (University of California, San Diego) The prediction of the interactions of geochemical fluids with minerals, nanoparticles, and colloids under extreme near surface conditions of temperature (T) and pressure (P) is a grand challenge research need in geosciences (U.S. DOE 2007, Basic Research Needs for Geosciences: Facilitating the 21st Energy Systems.). To evaluate the impact of these processes on energy production and management strategies it is necessary to have a high level of understanding of the interaction between complex natural fluids and mineral formations. This program emphasizes 1st principle parameter free simulations of complex chemical processes in solutions, in the mineral phase, and in the interfaces between these phases The development of new computational tools (with emphasis on oxide materials and reaction dynamics) tailored to treat wide range of conditions and time scales experienced in such geochemical applications is has been developed. Because of the sensitivity of the interaction in these systems to electronic structure and local bonding environments, and of the need to describe bond breaking/formation, our simulations are based on interactions calculated at the electronic structure level (ab-initio molecular dynamics, AIMD). The progress in the computational aspects of program may be summarized in terms of the following themes (objectives); Development of efficient parameter free dynamical simulation technology based on 1st principles force and energy calculations especially adapted for geochemical applications (e.g., mineral, interfaces and aqueous solutions) (continuing program); Calculation of the dynamics of water structure of in the surface-water interface of transition metal oxides and oxihydroxides; and Development of improved (beyond DFT+GGA) electronic structure calculations for minerals and the interface region that more accurately calculate electron correlation, spin density, and localization. The focus of the program is also on the iron oxide and oxihydroxide minerals and Fe 2+ (aq)/Fe 3+ (cr) oxidation in the mineral solution interface region. These methods included the development of model Hamilitonian methods that can be solved to near convergence for single site models (DMFT) and many-body perturbation methods (MP2, GW); Development of time decomposition methods to extend time scales of molecular dynamics (MD) simulations and support the use of high complexity electronic structure calculations (MP2, CCSD(T)) of forces for use in dynamical simulations where very high chemical accuracy is required (microsolvated reactions in absorbed surface layers); and The development of a new linear scaling finite element solver for eigenvalue problem that supports solution of quantum problems with unusual potential and boundary values. Application progress of the above new simulation technology to problems of geochemical interests includes; The prediction of metal oxide surface structure and the reduction/oxidation of Fe 3+ (cr)/Fe 2+ (aq) in metal oxide (hematite, goethite)/solution interfaces. Result: water interacts strongly with the 001 Hematite surface; interaction of water with the 100 goethite is weak; The study of ion solvation and the composition of ion hydration shells under extreme conditions (focus on Fe 3+/2+ , Al 3+ and Mg 2+ and their hydroxide speciation). Result: Ion association in water solutions can be calculated from 1st principle methods. Efficient sampling of the free energy requires more development; The continued development of new high resolution analysis of XAFS scattering of disordered systems (particularly Al, Mg) and of XANES calculations for aqueous ions. Result: EXAFS spectra can be calculated to high accuracy with DFT level dynamic simulations; The exploration of electron localization and electron transport in metal oxides (highly correlated materials). Result: Proper description of electron localization requires levels of calculation beyond DFT; and Localization of electrons in DFT type Hamiltonians was studied. Result: For very Dirac high exchange new solutions (New unphysical bifrucations) to the eigenvalue problem are found. The program was highly collaborative involving faculty and students in mathematics, physics and computer science departments as well as coworkers at the Pacific Northwest National Laboratories (PNNL). The students in this program had the opportunity to develop skills in the development of methods, the implementation of method on high performance parallel computers and the application of these methods to problem in geochemical science. Much of the software that was developed was incorporated in the NWchem software package maintained by PNNL.

58 GEOSCIENCES↗
DOE OSTI2014

TH-C-18A-02: Machine Learning and STAPLE Based Simultaneous Longitudinal Segmentation of Bone and Marrow Structures From Dual Energy CT

Purpose: To develop a fully-automatic longitudinal bone and marrow segmentation method in the pelvic region from dual energy computed tomography (DECT). Methods: We developed a two-step automatic bone and marrow segmentation method for simultaneous longitudinal evaluation of patients with metastatic bone disease using dual energy CT (DECT). Our approach transforms the DECT images into a multi-material decomposition (MMD) model that represents the voxels as a mixture of multiple materials. A support vector machine (SVM) was trained using a single scan. In the first step of the longitudinal segmentation the trained SVM model detects bone and marrow structures on all available longitudinal scans. Segmentation is further refined through active contour segmentation. In the second step, the segmentations from the individual scans are merged by employing the simultaneous truth and performance level estimation (STAPLE) algorithm. The scans are registered using affine and deformable registration. We found that our approach improves the segmentation in all the scans under reliable registration performance between the same scans. Improving registration was not under the scope of this work. Results: We applied our approach to segment bone and marrow in DECT scans in the pelvic regions for multiple patients. Each patient had three to five follow up scans. All the patients in the analysis had artificial metal prostheses which introduced challenges for the registration. Our algorithm achieved reasonable accurate segmentation despite the presence of metal artifacts and high-density oral contrast in neighboring structures. Our approach obtained an overall segmentation accuracy of 80% using DICE metric. Conclusion: We developed a two-step automatic longitudinal segmentation technique for bone and marrow region structures in the pelvic areas from dual energy CT. Our approach achieves robust segmentation despite the presence of confounding structures with similar intensities as the bone and marrow regions due to uptake of oral contrast and metal artifacts.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1990

A decentralized linear quadratic control design method for flexible structures

A decentralized suboptimal linear quadratic control design procedure which combines substructural synthesis, model reduction, decentralized control design, subcontroller synthesis, and controller reduction is proposed for the design of reduced-order controllers for flexible structures. The procedure starts with a definition of the continuum structure to be controlled. An evaluation model of finite dimension is obtained by the finite element method. Then, the finite element model is decomposed into several substructures by using a natural decomposition called substructuring decomposition. Each substructure, at this point, still has too large a dimension and must be reduced to a size that is Riccati-solvable. Model reduction of each substructure can be performed by using any existing model reduction method, e.g., modal truncation, balanced reduction, Krylov model reduction, or mixed-mode method. Then, based on the reduced substructure model, a subcontroller is designed by an LQ optimal control method for each substructure independently. After all subcontrollers are designed, a controller synthesis method called substructural controller synthesis is employed to synthesize all subcontrollers into a global controller. The assembling scheme used is the same as that employed for the structure matrices. Finally, a controller reduction scheme, called the equivalent impulse response energy controller (EIREC) reduction algorithm, is used to reduce the global controller to a reasonable size for implementation. The EIREC reduced controller preserves the impulse response energy of the full-order controller and has the property of matching low-frequency moments and low-frequency power moments. An advantage of the substructural controller synthesis method is that it relieves the computational burden associated with dimensionality. Besides that, the SCS design scheme is also a highly adaptable controller synthesis method for structures with varying configuration, or varying mass and stiffness properties.

Su, Tzu-Jeng↗
DOE OSTI2019

On the role of soil water retention characteristic on aerobic microbial respiration

Soil water status is one of the most important environmental factors that control microbial activity and rate of soil organic matter (SOM) decomposition. Its effect can be partitioned into effect of water energy status (water potential) on cellular activity, effect of water volume on cellular motility, and aqueous diffusion of substrate and nutrients, as well as the effect of air content and gas-diffusion pathways on concentration of dissolved oxygen. Nonetheless,moisture functions widely used in SOM decomposition models are often based on empirical functions rather than robust physical foundations that account for these disparate impacts of soil water. The contributions of soil water content and water potential varyfrom soil to soil according to the soil water characteristic (SWC), which in turn is strongly dependent on soil texture and structure. The overall goal of this study is to introduce a physically based modeling framework of aerobic microbial respiration that incorporates the role of SWC under arbitrary soil moisture status. The model was tested by contrasting it with published data sets of SOM decomposition under laboratory conditions.

54 ENVIRONMENTAL SCIENCES↗