Effect of Copper Oxide, Titanium Dioxide, and Lithium Fluoride on the Thermal Behavior and Decomposition Kinetics of Ammonium Nitrate

NASA Astrophysics Data System (ADS)

Vargeese, Anuj A.; Mija, S. J.; Muralidharan, Krishnamurthi

2014-07-01

Ammonium nitrate (AN) is crystallized along with copper oxide, titanium dioxide, and lithium fluoride. Thermal kinetic constants for the decomposition reaction of the samples were calculated by model-free (Friedman's differential and Vyzovkins nonlinear integral) and model-fitting (Coats-Redfern) methods. To determine the decomposition mechanisms, 12 solid-state mechanisms were tested using the Coats-Redfern method. The results of the Coats-Redfern method show that the decomposition mechanism for all samples is the contracting cylinder mechanism. The phase behavior of the obtained samples was evaluated by differential scanning calorimetry (DSC), and structural properties were determined by X-ray powder diffraction (XRPD). The results indicate that copper oxide modifies the phase transition behavior and can catalyze AN decomposition, whereas LiF inhibits AN decomposition, and TiO2 shows no influence on the rate of decomposition. Possible explanations for these results are discussed. Supplementary materials are available for this article. Go to the publisher's online edition of the Journal of Energetic Materials to view the free supplemental file.

Semi-empirical modelling for forest above ground biomass estimation using hybrid and fully PolSAR data

NASA Astrophysics Data System (ADS)

Tomar, Kiledar S.; Kumar, Shashi; Tolpekin, Valentyn A.; Joshi, Sushil K.

2016-05-01

Forests act as sink of carbon and as a result maintains carbon cycle in atmosphere. Deforestation leads to imbalance in global carbon cycle and changes in climate. Hence estimation of forest biophysical parameter like biomass becomes a necessity. PolSAR has the ability to discriminate the share of scattering element like surface, double bounce and volume scattering in a single SAR resolution cell. Studies have shown that volume scattering is a significant parameter for forest biophysical characterization which mainly occurred from vegetation due to randomly oriented structures. This random orientation of forest structure causes shift in orientation angle of polarization ellipse which ultimately disturbs the radar signature and shows overestimation of volume scattering and underestimation of double bounce scattering after decomposition of fully PolSAR data. Hybrid polarimetry has the advantage of zero POA shift due to rotational symmetry followed by the circular transmission of electromagnetic waves. The prime objective of this study was to extract the potential of Hybrid PolSAR and fully PolSAR data for AGB estimation using Extended Water Cloud model. Validation was performed using field biomass. The study site chosen was Barkot Forest, Uttarakhand, India. To obtain the decomposition components, m-alpha and Yamaguchi decomposition modelling for Hybrid and fully PolSAR data were implied respectively. The RGB composite image for both the decomposition techniques has generated. The contribution of all scattering from each plot for m-alpha and Yamaguchi decomposition modelling were extracted. The R2 value for modelled AGB and field biomass from Hybrid PolSAR and fully PolSAR data were found 0.5127 and 0.4625 respectively. The RMSE for Hybrid and fully PolSAR between modelled AGB and field biomass were 63.156 (t ha-1) and 73.424 (t ha-1) respectively. On the basis of RMSE and R2 value, this study suggests Hybrid PolSAR decomposition modelling to retrieve scattering element for AGB estimation from forest.

Study on Influencing Factors of Carbon Emissions from Energy Consumption of Shandong Province of China from 1995 to 2012

PubMed Central

Song, Jiekun; Song, Qing; Zhang, Dong; Lu, Youyou; Luan, Long

2014-01-01

Carbon emissions from energy consumption of Shandong province from 1995 to 2012 are calculated. Three zero-residual decomposition models (LMDI, MRCI and Shapley value models) are introduced for decomposing carbon emissions. Based on the results, Kendall coordination coefficient method is employed for testing their compatibility, and an optimal weighted combination decomposition model is constructed for improving the objectivity of decomposition. STIRPAT model is applied to evaluate the impact of each factor on carbon emissions. The results show that, using 1995 as the base year, the cumulative effects of population, per capita GDP, energy consumption intensity, and energy consumption structure of Shandong province in 2012 are positive, while the cumulative effect of industrial structure is negative. Per capita GDP is the largest driver of the increasing carbon emissions and has a great impact on carbon emissions; energy consumption intensity is a weak driver and has certain impact on carbon emissions; population plays a weak driving role, but it has the most significant impact on carbon emissions; energy consumption structure is a weak driver of the increasing carbon emissions and has a weak impact on carbon emissions; industrial structure has played a weak inhibitory role, and its impact on carbon emissions is great. PMID:24977216

Young Children's Thinking About Decomposition: Early Modeling Entrees to Complex Ideas in Science

NASA Astrophysics Data System (ADS)

Ero-Tolliver, Isi; Lucas, Deborah; Schauble, Leona

2013-10-01

This study was part of a multi-year project on the development of elementary students' modeling approaches to understanding the life sciences. Twenty-three first grade students conducted a series of coordinated observations and investigations on decomposition, a topic that is rarely addressed in the early grades. The instruction included in-class observations of different types of soil and soil profiling, visits to the school's compost bin, structured observations of decaying organic matter of various kinds, study of organisms that live in the soil, and models of environmental conditions that affect rates of decomposition. Both before and after instruction, students completed a written performance assessment that asked them to reason about the process of decomposition. Additional information was gathered through one-on-one interviews with six focus students who represented variability of performance across the class. During instruction, researchers collected video of classroom activity, student science journal entries, and charts and illustrations produced by the teacher. After instruction, the first-grade students showed a more nuanced understanding of the composition and variability of soils, the role of visible organisms in decomposition, and environmental factors that influence rates of decomposition. Through a variety of representational devices, including drawings, narrative records, and physical models, students came to regard decomposition as a process, rather than simply as an end state that does not require explanation.

A Subspace Approach to the Structural Decomposition and Identification of Ankle Joint Dynamic Stiffness.

PubMed

Jalaleddini, Kian; Tehrani, Ehsan Sobhani; Kearney, Robert E

2017-06-01

The purpose of this paper is to present a structural decomposition subspace (SDSS) method for decomposition of the joint torque to intrinsic, reflexive, and voluntary torques and identification of joint dynamic stiffness. First, it formulates a novel state-space representation for the joint dynamic stiffness modeled by a parallel-cascade structure with a concise parameter set that provides a direct link between the state-space representation matrices and the parallel-cascade parameters. Second, it presents a subspace method for the identification of the new state-space model that involves two steps: 1) the decomposition of the intrinsic and reflex pathways and 2) the identification of an impulse response model of the intrinsic pathway and a Hammerstein model of the reflex pathway. Extensive simulation studies demonstrate that SDSS has significant performance advantages over some other methods. Thus, SDSS was more robust under high noise conditions, converging where others failed; it was more accurate, giving estimates with lower bias and random errors. The method also worked well in practice and yielded high-quality estimates of intrinsic and reflex stiffnesses when applied to experimental data at three muscle activation levels. The simulation and experimental results demonstrate that SDSS accurately decomposes the intrinsic and reflex torques and provides accurate estimates of physiologically meaningful parameters. SDSS will be a valuable tool for studying joint stiffness under functionally important conditions. It has important clinical implications for the diagnosis, assessment, objective quantification, and monitoring of neuromuscular diseases that change the muscle tone.

Modal characteristics of a simplified brake rotor model using semi-analytical Rayleigh Ritz method

NASA Astrophysics Data System (ADS)

Zhang, F.; Cheng, L.; Yam, L. H.; Zhou, L. M.

2006-10-01

Emphasis of this paper is given to the modal characteristics of a brake rotor which is utilized in automotive disc brake system. The brake rotor is modeled as a combined structure comprising an annular plate connected to a segment of cylindrical shell by distributed artificial springs. Modal analysis shows the existence of three types of modes for the combined structure, depending on the involvement of each substructure. A decomposition technique is proposed, allowing each mode of the combined structure to be decomposed into a linear combination of the individual substructure modes. It is shown that the decomposition coefficients provide a direct and systematic means to carry out modal classification and quantification.

Microbial decomposition of keratin in nature-a new hypothesis of industrial relevance.

PubMed

Lange, Lene; Huang, Yuhong; Busk, Peter Kamp

2016-03-01

Discovery of keratin-degrading enzymes from fungi and bacteria has primarily focused on finding one protease with efficient keratinase activity. Recently, an investigation was conducted of all keratinases secreted from a fungus known to grow on keratinaceous materials, such as feather, horn, and hooves. The study demonstrated that a minimum of three keratinases is needed to break down keratin, an endo-acting, an exo-acting, and an oligopeptide-acting keratinase. Further, several studies have documented that disruption of sulfur bridges of the keratin structure acts synergistically with the keratinases to loosen the molecular structure, thus giving the enzymes access to their substrate, the protein structure. With such complexity, it is relevant to compare microbial keratin decomposition with the microbial decomposition of well-studied polymers such as cellulose and chitin. Interestingly, it was recently shown that the specialized enzymes, lytic polysaccharide monoxygenases (LPMOs), shown to be important for breaking the recalcitrance of cellulose and chitin, are also found in keratin-degrading fungi. A holistic view of the complex molecular self-assembling structure of keratin and knowledge about enzymatic and boosting factors needed for keratin breakdown have been used to formulate a hypothesis for mode of action of the LPMOs in keratin decomposition and for a model for degradation of keratin in nature. Testing such hypotheses and models still needs to be done. Even now, the hypothesis can serve as an inspiration for designing industrial processes for keratin decomposition for conversion of unexploited waste streams, chicken feather, and pig bristles into bioaccessible animal feed.

[Decomposition model of energy-related carbon emissions in tertiary industry for China].

PubMed

Lu, Yuan-Qing; Shi, Jun

2012-07-01

Tertiary industry has been developed in recent years. And it is very important to find the factors influenced the energy-related carbon emissions in tertiary industry. A decomposition model of energy-related carbon emissions for China is set up by adopting logarithmic mean weight Divisia method based on the identity of carbon emissions. The model is adopted to analyze the influence of energy structure, energy efficiency, tertiary industry structure and economic output to energy-related carbon emissions in China from 2000 to 2009. Results show that the contribution rate of economic output and energy structure to energy-related carbon emissions increases year by year. Either is the contribution rate of energy efficiency or the tertiary industry restraining to energy-related carbon emissions. However, the restrain effect is weakening.

Root chemistry and soil fauna, but not soil abiotic conditions explain the effects of plant diversity on root decomposition.

PubMed

Chen, Hongmei; Oram, Natalie J; Barry, Kathryn E; Mommer, Liesje; van Ruijven, Jasper; de Kroon, Hans; Ebeling, Anne; Eisenhauer, Nico; Fischer, Christine; Gleixner, Gerd; Gessler, Arthur; González Macé, Odette; Hacker, Nina; Hildebrandt, Anke; Lange, Markus; Scherer-Lorenzen, Michael; Scheu, Stefan; Oelmann, Yvonne; Wagg, Cameron; Wilcke, Wolfgang; Wirth, Christian; Weigelt, Alexandra

2017-11-01

Plant diversity influences many ecosystem functions including root decomposition. However, due to the presence of multiple pathways via which plant diversity may affect root decomposition, our mechanistic understanding of their relationships is limited. In a grassland biodiversity experiment, we simultaneously assessed the effects of three pathways-root litter quality, soil biota, and soil abiotic conditions-on the relationships between plant diversity (in terms of species richness and the presence/absence of grasses and legumes) and root decomposition using structural equation modeling. Our final structural equation model explained 70% of the variation in root mass loss. However, different measures of plant diversity included in our model operated via different pathways to alter root mass loss. Plant species richness had a negative effect on root mass loss. This was partially due to increased Oribatida abundance, but was weakened by enhanced root potassium (K) concentration in more diverse mixtures. Equally, grass presence negatively affected root mass loss. This effect of grasses was mostly mediated via increased root lignin concentration and supported via increased Oribatida abundance and decreased root K concentration. In contrast, legume presence showed a net positive effect on root mass loss via decreased root lignin concentration and increased root magnesium concentration, both of which led to enhanced root mass loss. Overall, the different measures of plant diversity had contrasting effects on root decomposition. Furthermore, we found that root chemistry and soil biota but not root morphology or soil abiotic conditions mediated these effects of plant diversity on root decomposition.

Structure and thermal decomposition of sulfated β-cyclodextrin intercalated in a layered double hydroxide

NASA Astrophysics Data System (ADS)

Wang, Ji; Wei, Min; Rao, Guoying; Evans, David G.; Duan, Xue

2004-01-01

The sodium salt of hexasulfated β-cyclodextrin has been synthesized and intercalated into a magnesium-aluminum layered double hydroxide by ion exchange. The structure, composition and thermal decomposition behavior of the intercalated material have been studied by variable temperature X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), inductively coupled plasma emission spectroscopy (ICP), and thermal analysis (TG-DTA) and a model for the structure has been proposed. The thermal stability of the intercalated sulfated β-cyclodextrin is significantly enhanced compared with the pure form before intercalation.

Mode decomposition and Lagrangian structures of the flow dynamics in orbitally shaken bioreactors

NASA Astrophysics Data System (ADS)

Weheliye, Weheliye Hashi; Cagney, Neil; Rodriguez, Gregorio; Micheletti, Martina; Ducci, Andrea

2018-03-01

In this study, two mode decomposition techniques were applied and compared to assess the flow dynamics in an orbital shaken bioreactor (OSB) of cylindrical geometry and flat bottom: proper orthogonal decomposition and dynamic mode decomposition. Particle Image Velocimetry (PIV) experiments were carried out for different operating conditions including fluid height, h, and shaker rotational speed, N. A detailed flow analysis is provided for conditions when the fluid and vessel motions are in-phase (Fr = 0.23) and out-of-phase (Fr = 0.47). PIV measurements in vertical and horizontal planes were combined to reconstruct low order models of the full 3D flow and to determine its Finite-Time Lyapunov Exponent (FTLE) within OSBs. The combined results from the mode decomposition and the FTLE fields provide a useful insight into the flow dynamics and Lagrangian coherent structures in OSBs and offer a valuable tool to optimise bioprocess design in terms of mixing and cell suspension.

X-Ray Thomson Scattering Without the Chihara Decomposition

NASA Astrophysics Data System (ADS)

Magyar, Rudolph; Baczewski, Andrew; Shulenburger, Luke; Hansen, Stephanie B.; Desjarlais, Michael P.; Sandia National Laboratories Collaboration

X-Ray Thomson Scattering is an important experimental technique used in dynamic compression experiments to measure the properties of warm dense matter. The fundamental property probed in these experiments is the electronic dynamic structure factor that is typically modeled using an empirical three-term decomposition (Chihara, J. Phys. F, 1987). One of the crucial assumptions of this decomposition is that the system's electrons can be either classified as bound to ions or free. This decomposition may not be accurate for materials in the warm dense regime. We present unambiguous first principles calculations of the dynamic structure factor independent of the Chihara decomposition that can be used to benchmark these assumptions. Results are generated using a finite-temperature real-time time-dependent density functional theory applied for the first time in these conditions. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Security Administration under contract DE-AC04-94AL85000.

FAST TRACK COMMUNICATION: \\ {P}\\ {T}-symmetry, Cartan decompositions, Lie triple systems and Krein space-related Clifford algebras

NASA Astrophysics Data System (ADS)

Günther, Uwe; Kuzhel, Sergii

2010-10-01

Gauged \\ {P}\\ {T} quantum mechanics (PTQM) and corresponding Krein space setups are studied. For models with constant non-Abelian gauge potentials and extended parity inversions compact and noncompact Lie group components are analyzed via Cartan decompositions. A Lie-triple structure is found and an interpretation as \\ {P}\\ {T}-symmetrically generalized Jaynes-Cummings model is possible with close relation to recently studied cavity QED setups with transmon states in multilevel artificial atoms. For models with Abelian gauge potentials a hidden Clifford algebra structure is found and used to obtain the fundamental symmetry of Krein space-related J-self-adjoint extensions for PTQM setups with ultra-localized potentials.

Adequacy assessment of mathematical models in the dynamics of litter decomposition in a tropical forest Mosaic Atlantic, in southeastern Brazil.

PubMed

Nunes, F P; Garcia, Q S

2015-05-01

The study of litter decomposition and nutrient cycling is essential to know native forests structure and functioning. Mathematical models can help to understand the local and temporal litter fall variations and their environmental variables relationships. The objective of this study was test the adequacy of mathematical models for leaf litter decomposition in the Atlantic Forest in southeastern Brazil. We study four native forest sites in Parque Estadual do Rio Doce, a Biosphere Reserve of the Atlantic, which were installed 200 bags of litter decomposing with 20 × 20 cm nylon screen of 2 mm, with 10 grams of litter. Monthly from 09/2007 to 04/2009, 10 litterbags were removed for determination of the mass loss. We compared 3 nonlinear models: 1 - Olson Exponential Model (1963), which considers the constant K, 2 - Model proposed by Fountain and Schowalter (2004), 3 - Model proposed by Coelho and Borges (2005), which considers the variable K through QMR, SQR, SQTC, DMA and Test F. The Fountain and Schowalter (2004) model was inappropriate for this study by overestimating decomposition rate. The decay curve analysis showed that the model with the variable K was more appropriate, although the values of QMR and DMA revealed no significant difference (p > 0.05) between the models. The analysis showed a better adjustment of DMA using K variable, reinforced by the values of the adjustment coefficient (R2). However, convergence problems were observed in this model for estimate study areas outliers, which did not occur with K constant model. This problem can be related to the non-linear fit of mass/time values to K variable generated. The model with K constant shown to be adequate to describe curve decomposition for separately areas and best adjustability without convergence problems. The results demonstrated the adequacy of Olson model to estimate tropical forest litter decomposition. Although use of reduced number of parameters equaling the steps of the decomposition process, no difficulties of convergence were observed in Olson model. So, this model can be used to describe decomposition curves in different types of environments, estimating K appropriately.

Matching multiple rigid domain decompositions of proteins

PubMed Central

Flynn, Emily; Streinu, Ileana

2017-01-01

We describe efficient methods for consistently coloring and visualizing collections of rigid cluster decompositions obtained from variations of a protein structure, and lay the foundation for more complex setups that may involve different computational and experimental methods. The focus here is on three biological applications: the conceptually simpler problems of visualizing results of dilution and mutation analyses, and the more complex task of matching decompositions of multiple NMR models of the same protein. Implemented into the KINARI web server application, the improved visualization techniques give useful information about protein folding cores, help examining the effect of mutations on protein flexibility and function, and provide insights into the structural motions of PDB proteins solved with solution NMR. These tools have been developed with the goal of improving and validating rigidity analysis as a credible coarse-grained model capturing essential information about a protein’s slow motions near the native state. PMID:28141528

Improving Distributed Diagnosis Through Structural Model Decomposition

NASA Technical Reports Server (NTRS)

Bregon, Anibal; Daigle, Matthew John; Roychoudhury, Indranil; Biswas, Gautam; Koutsoukos, Xenofon; Pulido, Belarmino

2011-01-01

Complex engineering systems require efficient fault diagnosis methodologies, but centralized approaches do not scale well, and this motivates the development of distributed solutions. This work presents an event-based approach for distributed diagnosis of abrupt parametric faults in continuous systems, by using the structural model decomposition capabilities provided by Possible Conflicts. We develop a distributed diagnosis algorithm that uses residuals computed by extending Possible Conflicts to build local event-based diagnosers based on global diagnosability analysis. The proposed approach is applied to a multitank system, and results demonstrate an improvement in the design of local diagnosers. Since local diagnosers use only a subset of the residuals, and use subsystem models to compute residuals (instead of the global system model), the local diagnosers are more efficient than previously developed distributed approaches.

In silico local structure approach: a case study on outer membrane proteins.

PubMed

Martin, Juliette; de Brevern, Alexandre G; Camproux, Anne-Claude

2008-04-01

The detection of Outer Membrane Proteins (OMP) in whole genomes is an actual question, their sequence characteristics have thus been intensively studied. This class of protein displays a common beta-barrel architecture, formed by adjacent antiparallel strands. However, due to the lack of available structures, few structural studies have been made on this class of proteins. Here we propose a novel OMP local structure investigation, based on a structural alphabet approach, i.e., the decomposition of 3D structures using a library of four-residue protein fragments. The optimal decomposition of structures using hidden Markov model results in a specific structural alphabet of 20 fragments, six of them dedicated to the decomposition of beta-strands. This optimal alphabet, called SA20-OMP, is analyzed in details, in terms of local structures and transitions between fragments. It highlights a particular and strong organization of beta-strands as series of regular canonical structural fragments. The comparison with alphabets learned on globular structures indicates that the internal organization of OMP structures is more constrained than in globular structures. The analysis of OMP structures using SA20-OMP reveals some recurrent structural patterns. The preferred location of fragments in the distinct regions of the membrane is investigated. The study of pairwise specificity of fragments reveals that some contacts between structural fragments in beta-sheets are clearly favored whereas others are avoided. This contact specificity is stronger in OMP than in globular structures. Moreover, SA20-OMP also captured sequential information. This can be integrated in a scoring function for structural model ranking with very promising results. (c) 2007 Wiley-Liss, Inc.

Jammed Limit of Bijel Structure Formation

DOE PAGES

Welch, P. M.; Lee, M. N.; Parra-Vasquez, A. N. G.; ...

2017-11-02

Over the past decade, methods to control microstructure in heterogeneous mixtures by arresting spinodal decomposition via the addition of colloidal particles have led to an entirely new class of bicontinuous materials known as bijels. We present a new model for the development of these materials that yields to both numerical and analytical evaluation. This model reveals that a single dimensionless parameter that captures both chemical and environmental variables dictates the dynamics and ultimate structure formed in bijels. We also demonstrate that this parameter must fall within a fixed range in order for jamming to occur during spinodal decomposition, as wellmore » as show that known experimental trends for the characteristic domain sizes and time scales for formation are recovered by this model.« less

Simultaneous Tensor Decomposition and Completion Using Factor Priors.

PubMed

Chen, Yi-Lei; Hsu, Chiou-Ting Candy; Liao, Hong-Yuan Mark

2013-08-27

Tensor completion, which is a high-order extension of matrix completion, has generated a great deal of research interest in recent years. Given a tensor with incomplete entries, existing methods use either factorization or completion schemes to recover the missing parts. However, as the number of missing entries increases, factorization schemes may overfit the model because of incorrectly predefined ranks, while completion schemes may fail to interpret the model factors. In this paper, we introduce a novel concept: complete the missing entries and simultaneously capture the underlying model structure. To this end, we propose a method called Simultaneous Tensor Decomposition and Completion (STDC) that combines a rank minimization technique with Tucker model decomposition. Moreover, as the model structure is implicitly included in the Tucker model, we use factor priors, which are usually known a priori in real-world tensor objects, to characterize the underlying joint-manifold drawn from the model factors. We conducted experiments to empirically verify the convergence of our algorithm on synthetic data, and evaluate its effectiveness on various kinds of real-world data. The results demonstrate the efficacy of the proposed method and its potential usage in tensor-based applications. It also outperforms state-of-the-art methods on multilinear model analysis and visual data completion tasks.

A CATALOG OF BULGE+DISK DECOMPOSITIONS AND UPDATED PHOTOMETRY FOR 1.12 MILLION GALAXIES IN THE SLOAN DIGITAL SKY SURVEY

DOE Office of Scientific and Technical Information (OSTI.GOV)

Simard, Luc; McConnachie, Alan W.; Trevor Mendel, J.

We perform two-dimensional, point-spread-function-convolved, bulge+disk decompositions in the g and r bandpasses on a sample of 1,123,718 galaxies from the Legacy area of the Sloan Digital Sky Survey Data Release Seven. Four different decomposition procedures are investigated which make improvements to sky background determinations and object deblending over the standard SDSS procedures that lead to more robust structural parameters and integrated galaxy magnitudes and colors, especially in crowded environments. We use a set of science-based quality assurance metrics, namely, the disk luminosity-size relation, the galaxy color-magnitude diagram, and the galaxy central (fiber) colors to show the robustness of our structuralmore » parameters. The best procedure utilizes simultaneous, two-bandpass decompositions. Bulge and disk photometric errors remain below 0.1 mag down to bulge and disk magnitudes of g {approx_equal} 19 and r {approx_equal} 18.5. We also use and compare three different galaxy fitting models: a pure Sersic model, an n{sub b} = 4 bulge + disk model, and a Sersic (free n{sub b}) bulge + disk model. The most appropriate model for a given galaxy is determined by the F-test probability. All three catalogs of measured structural parameters, rest-frame magnitudes, and colors are publicly released here. These catalogs should provide an extensive comparison set for a wide range of observational and theoretical studies of galaxies.« less

Characterizing Feedback Control Mechanisms in Nonlinear Microbial Models of Soil Organic Matter Decomposition by Stability Analysis

NASA Astrophysics Data System (ADS)

Georgiou, K.; Tang, J.; Riley, W. J.; Torn, M. S.

2014-12-01

Soil organic matter (SOM) decomposition is regulated by biotic and abiotic processes. Feedback interactions between such processes may act to dampen oscillatory responses to perturbations from equilibrium. Indeed, although biological oscillations have been observed in small-scale laboratory incubations, the overlying behavior at the plot-scale exhibits a relatively stable response to disturbances in input rates and temperature. Recent studies have demonstrated the ability of microbial models to capture nonlinear feedbacks in SOM decomposition that linear Century-type models are unable to reproduce, such as soil priming in response to increased carbon input. However, these microbial models often exhibit strong oscillatory behavior that is deemed unrealistic. The inherently nonlinear dynamics of SOM decomposition have important implications for global climate-carbon and carbon-concentration feedbacks. It is therefore imperative to represent these dynamics in Earth System Models (ESMs) by introducing sub-models that accurately represent microbial and abiotic processes. In the present study we explore, both analytically and numerically, four microbe-enabled model structures of varying levels of complexity. The most complex model combines microbial physiology, a non-linear mineral sorption isotherm, and enzyme dynamics. Based on detailed stability analysis of the nonlinear dynamics, we calculate the system modes as functions of model parameters. This dependence provides insight into the source of state oscillations. We find that feedback mechanisms that emerge from careful representation of enzyme and mineral interactions, with parameter values in a prescribed range, are critical for both maintaining system stability and capturing realistic responses to disturbances. Corroborating and expanding upon the results of recent studies, we explain the emergence of oscillatory responses and discuss the appropriate microbe-enabled model structure for inclusion in ESMs.

Performance of tensor decomposition-based modal identification under nonstationary vibration

NASA Astrophysics Data System (ADS)

Friesen, P.; Sadhu, A.

2017-03-01

Health monitoring of civil engineering structures is of paramount importance when they are subjected to natural hazards or extreme climatic events like earthquake, strong wind gusts or man-made excitations. Most of the traditional modal identification methods are reliant on stationarity assumption of the vibration response and posed difficulty while analyzing nonstationary vibration (e.g. earthquake or human-induced vibration). Recently tensor decomposition based methods are emerged as powerful and yet generic blind (i.e. without requiring a knowledge of input characteristics) signal decomposition tool for structural modal identification. In this paper, a tensor decomposition based system identification method is further explored to estimate modal parameters using nonstationary vibration generated due to either earthquake or pedestrian induced excitation in a structure. The effects of lag parameters and sensor densities on tensor decomposition are studied with respect to the extent of nonstationarity of the responses characterized by the stationary duration and peak ground acceleration of the earthquake. A suite of more than 1400 earthquakes is used to investigate the performance of the proposed method under a wide variety of ground motions utilizing both complete and partial measurements of a high-rise building model. Apart from the earthquake, human-induced nonstationary vibration of a real-life pedestrian bridge is also used to verify the accuracy of the proposed method.

Investigation of automated task learning, decomposition and scheduling

NASA Technical Reports Server (NTRS)

Livingston, David L.; Serpen, Gursel; Masti, Chandrashekar L.

1990-01-01

The details and results of research conducted in the application of neural networks to task planning and decomposition are presented. Task planning and decomposition are operations that humans perform in a reasonably efficient manner. Without the use of good heuristics and usually much human interaction, automatic planners and decomposers generally do not perform well due to the intractable nature of the problems under consideration. The human-like performance of neural networks has shown promise for generating acceptable solutions to intractable problems such as planning and decomposition. This was the primary reasoning behind attempting the study. The basis for the work is the use of state machines to model tasks. State machine models provide a useful means for examining the structure of tasks since many formal techniques have been developed for their analysis and synthesis. It is the approach to integrate the strong algebraic foundations of state machines with the heretofore trial-and-error approach to neural network synthesis.

Preliminary application of Structure from Motion and GIS to document decomposition and taphonomic processes.

PubMed

Carlton, Connor D; Mitchell, Samantha; Lewis, Patrick

2018-01-01

Over the past decade, Structure from Motion (SfM) has increasingly been used as a means of digital preservation and for documenting archaeological excavations, architecture, and cultural material. However, few studies have tapped the potential of using SfM to document and analyze taphonomic processes affecting burials for forensic sciences purposes. This project utilizes SfM models to elucidate specific post-depositional events that affected a series of three human cadavers deposited at the South East Texas Applied Forensic Science Facility (STAFS). The aim of this research was to test the ability for untrained researchers to employ spatial software and photogrammetry for data collection purposes. For a series of three months a single lens reflex (SLR) camera was used to capture a series of overlapping images at periodic stages in the decomposition process of each cadaver. These images are processed through photogrammetric software that creates a 3D model that can be measured, manipulated, and viewed. This project used photogrammetric and geospatial software to map changes in decomposition and movement of the body from original deposition points. Project results indicate SfM and GIS as a useful tool for documenting decomposition and taphonomic processes. Results indicate photogrammetry is an efficient, relatively simple, and affordable tool for the documentation of decomposition. Copyright © 2017 Elsevier B.V. All rights reserved.

The implications of microbial and substrate limitation for the fates of carbon in different organic soil horizon types of boreal forest ecosystems: a mechanistically based model analysis

USGS Publications Warehouse

He, Y.; Zhuang, Q.; Harden, Jennifer W.; McGuire, A. David; Fan, Z.; Liu, Y.; Wickland, Kimberly P.

2014-01-01

The large amount of soil carbon in boreal forest ecosystems has the potential to influence the climate system if released in large quantities in response to warming. Thus, there is a need to better understand and represent the environmental sensitivity of soil carbon decomposition. Most soil carbon decomposition models rely on empirical relationships omitting key biogeochemical mechanisms and their response to climate change is highly uncertain. In this study, we developed a multi-layer microbial explicit soil decomposition model framework for boreal forest ecosystems. A thorough sensitivity analysis was conducted to identify dominating biogeochemical processes and to highlight structural limitations. Our results indicate that substrate availability (limited by soil water diffusion and substrate quality) is likely to be a major constraint on soil decomposition in the fibrous horizon (40–60% of soil organic carbon (SOC) pool size variation), while energy limited microbial activity in the amorphous horizon exerts a predominant control on soil decomposition (>70% of SOC pool size variation). Elevated temperature alleviated the energy constraint of microbial activity most notably in amorphous soils, whereas moisture only exhibited a marginal effect on dissolved substrate supply and microbial activity. Our study highlights the different decomposition properties and underlying mechanisms of soil dynamics between fibrous and amorphous soil horizons. Soil decomposition models should consider explicitly representing different boreal soil horizons and soil–microbial interactions to better characterize biogeochemical processes in boreal forest ecosystems. A more comprehensive representation of critical biogeochemical mechanisms of soil moisture effects may be required to improve the performance of the soil model we analyzed in this study.

A Type-2 Block-Component-Decomposition Based 2D AOA Estimation Algorithm for an Electromagnetic Vector Sensor Array

PubMed Central

Gao, Yu-Fei; Gui, Guan; Xie, Wei; Zou, Yan-Bin; Yang, Yue; Wan, Qun

2017-01-01

This paper investigates a two-dimensional angle of arrival (2D AOA) estimation algorithm for the electromagnetic vector sensor (EMVS) array based on Type-2 block component decomposition (BCD) tensor modeling. Such a tensor decomposition method can take full advantage of the multidimensional structural information of electromagnetic signals to accomplish blind estimation for array parameters with higher resolution. However, existing tensor decomposition methods encounter many restrictions in applications of the EMVS array, such as the strict requirement for uniqueness conditions of decomposition, the inability to handle partially-polarized signals, etc. To solve these problems, this paper investigates tensor modeling for partially-polarized signals of an L-shaped EMVS array. The 2D AOA estimation algorithm based on rank-(L1,L2,·) BCD is developed, and the uniqueness condition of decomposition is analyzed. By means of the estimated steering matrix, the proposed algorithm can automatically achieve angle pair-matching. Numerical experiments demonstrate that the present algorithm has the advantages of both accuracy and robustness of parameter estimation. Even under the conditions of lower SNR, small angular separation and limited snapshots, the proposed algorithm still possesses better performance than subspace methods and the canonical polyadic decomposition (CPD) method. PMID:28448431

A Type-2 Block-Component-Decomposition Based 2D AOA Estimation Algorithm for an Electromagnetic Vector Sensor Array.

PubMed

Gao, Yu-Fei; Gui, Guan; Xie, Wei; Zou, Yan-Bin; Yang, Yue; Wan, Qun

2017-04-27

This paper investigates a two-dimensional angle of arrival (2D AOA) estimation algorithm for the electromagnetic vector sensor (EMVS) array based on Type-2 block component decomposition (BCD) tensor modeling. Such a tensor decomposition method can take full advantage of the multidimensional structural information of electromagnetic signals to accomplish blind estimation for array parameters with higher resolution. However, existing tensor decomposition methods encounter many restrictions in applications of the EMVS array, such as the strict requirement for uniqueness conditions of decomposition, the inability to handle partially-polarized signals, etc. To solve these problems, this paper investigates tensor modeling for partially-polarized signals of an L-shaped EMVS array. The 2D AOA estimation algorithm based on rank- ( L 1 , L 2 , · ) BCD is developed, and the uniqueness condition of decomposition is analyzed. By means of the estimated steering matrix, the proposed algorithm can automatically achieve angle pair-matching. Numerical experiments demonstrate that the present algorithm has the advantages of both accuracy and robustness of parameter estimation. Even under the conditions of lower SNR, small angular separation and limited snapshots, the proposed algorithm still possesses better performance than subspace methods and the canonical polyadic decomposition (CPD) method.

Using FT-IR Spectroscopy to Elucidate the Structures of Ablative Polymers

NASA Technical Reports Server (NTRS)

Fan, Wendy

2011-01-01

The composition and structure of an ablative polymer has a multifaceted influence on its thermal, mechanical and ablative properties. Understanding the molecular level information is critical to the optimization of material performance because it helps to establish correlations with the macroscopic properties of the material, the so-called structure-property relationship. Moreover, accurate information of molecular structures is also essential to predict the thermal decomposition pathways as well as to identify decomposition species that are fundamentally important to modeling work. In this presentation, I will describe the use of infrared transmission spectroscopy (FT-IR) as a convenient tool to aid the discovery and development of thermal protection system materials.

Revealing driving factors of China's PM2.5 pollution

NASA Astrophysics Data System (ADS)

Zheng, Y.; Zhao, H.; Zhang, Q.; Geng, G.; Tong, D.; Peng, L.; He, K.

2017-12-01

China's rapid economic development and intensive energy consumption are deteriorating the air quality significantly. Understanding the key driving factors behind China's growing emissions of air pollutants and the accompanying PM2.5 pollution is critical for the development of China's clean air policies and also provides insight into how other emerging economies may develop a clear sky future. Here we reveal the socioeconomic drivers of the variations of China's PM2.5 concentrations during 2002-2012 by using an interdisciplinary framework that integrates an emission inventory model, an index decomposition analysis model, and a regional air quality model. The decomposition results demostrate that the improvements in emission efficiency and energy efficiency failed to offset the increased emissions of both primary PM2.5 and gaseous PM2.5 precursors (including SO2 NOx, and volatile organic compounds) triggered by the surging economic growth during 2002-2012. During the same time, the effects of energy structure, production structure and population growth were relatively less significant to all pollutants, which indicates the potential of large emission abatements through energy structure and production structure adjustment. Sensitivity simulations by the air quality model based on the provincial decomposition results also show that the economic growth have outpaced efficiency improvements in the increments of PM2.5 concentrations during the study years. As China continues to develop rapidly, future policies should promote further improvements in efficiency and accelerate the adjustments toward clean energy and production structures, which are critical for reducing China's emissions and alleviating the severe PM2.5 pollution.

Modeling of methanol decomposition on Pt/CeO2/ZrO2 catalyst in a packed bed microreactor

NASA Astrophysics Data System (ADS)

Pohar, Andrej; Belavič, Darko; Dolanc, Gregor; Hočevar, Stanko

2014-06-01

Methanol decomposition on Pt/CeO2/ZrO2 catalyst is studied inside a packed bed microreactor in the temperature range of 300-380 °C. The microreactor is fabricated using low-temperature co-fired ceramic (LTCC) technology, which is well suited for the production of relatively complex three-dimensional structures. It is packed with 2 wt% Pt-CeO2 catalyst, which is deposited onto ZrO2 spherical particles. A 1D mathematical model, which incorporates diffusion, convection and mass transfer through the boundary layer to the catalyst particles, as well as a 3D computational fluid dynamics model, are developed to describe the methanol decomposition process inside the packed bed. The microreactor exhibits reliable operation and no catalyst deactivation was observed during three months of experimentation. A comparison between the 1D mathematical model and the 3D model, considering the full 3D geometry of the microreactor is made and the differences between the models are identified and evaluated.

An effective hierarchical model for the biomolecular covalent bond: an approach integrating artificial chemistry and an actual terrestrial life system.

PubMed

Oohashi, Tsutomu; Ueno, Osamu; Maekawa, Tadao; Kawai, Norie; Nishina, Emi; Honda, Manabu

2009-01-01

Under the AChem paradigm and the programmed self-decomposition (PSD) model, we propose a hierarchical model for the biomolecular covalent bond (HBCB model). This model assumes that terrestrial organisms arrange their biomolecules in a hierarchical structure according to the energy strength of their covalent bonds. It also assumes that they have evolutionarily selected the PSD mechanism of turning biological polymers (BPs) into biological monomers (BMs) as an efficient biomolecular recycling strategy We have examined the validity and effectiveness of the HBCB model by coordinating two complementary approaches: biological experiments using existent terrestrial life, and simulation experiments using an AChem system. Biological experiments have shown that terrestrial life possesses a PSD mechanism as an endergonic, genetically regulated process and that hydrolysis, which decomposes a BP into BMs, is one of the main processes of such a mechanism. In simulation experiments, we compared different virtual self-decomposition processes. The virtual species in which the self-decomposition process mainly involved covalent bond cleavage from a BP to BMs showed evolutionary superiority over other species in which the self-decomposition process involved cleavage from BP to classes lower than BM. These converging findings strongly support the existence of PSD and the validity and effectiveness of the HBCB model.

A molecular dynamics study of model SI clathrate hydrates: the effect of guest size and guest-water interaction on decomposition kinetics.

PubMed

Das, Subhadip; Baghel, Vikesh Singh; Roy, Sudip; Kumar, Rajnish

2015-04-14

One of the options suggested for methane recovery from natural gas hydrates is molecular replacement of methane by suitable guests like CO2 and N2. This approach has been found to be feasible through many experimental and molecular dynamics simulation studies. However, the long term stability of the resultant hydrate needs to be evaluated; the decomposition rate of these hydrates is expected to depend on the interaction between these guest and water molecules. In this work, molecular dynamics simulation has been performed to illustrate the effect of guest molecules with different sizes and interaction strengths with water on structure I (SI) hydrate decomposition and hence the stability. The van der Waals interaction between water of hydrate cages and guest molecules is defined by Lennard Jones potential parameters. A wide range of parameter spaces has been scanned by changing the guest molecules in the SI hydrate, which acts as a model gas for occupying the small and large cages of the SI hydrate. All atomistic simulation results show that the stability of the hydrate is sensitive to the size and interaction of the guest molecules with hydrate water. The increase in the interaction of guest molecules with water stabilizes the hydrate, which in turn shows a slower rate of hydrate decomposition. Similarly guest molecules with a reasonably small (similar to Helium) or large size increase the decomposition rate. The results were also analyzed by calculating the structural order parameter to understand the dynamics of crystal structure and correlated with the release rate of guest molecules from the solid hydrate phase. The results have been explained based on the calculation of potential energies felt by guest molecules in amorphous water, hydrate bulk and hydrate-water interface regions.

Fourier imaging of non-linear structure formation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brandbyge, Jacob; Hannestad, Steen, E-mail: jacobb@phys.au.dk, E-mail: sth@phys.au.dk

We perform a Fourier space decomposition of the dynamics of non-linear cosmological structure formation in ΛCDM models. From N -body simulations involving only cold dark matter we calculate 3-dimensional non-linear density, velocity divergence and vorticity Fourier realizations, and use these to calculate the fully non-linear mode coupling integrals in the corresponding fluid equations. Our approach allows for a reconstruction of the amount of mode coupling between any two wavenumbers as a function of redshift. With our Fourier decomposition method we identify the transfer of power from larger to smaller scales, the stable clustering regime, the scale where vorticity becomes important,more » and the suppression of the non-linear divergence power spectrum as compared to linear theory. Our results can be used to improve and calibrate semi-analytical structure formation models.« less

Flash nano-precipitation of polymer blends: a role for fluid flow?

NASA Astrophysics Data System (ADS)

Grundy, Lorena; Mason, Lachlan; Chergui, Jalel; Juric, Damir; Craster, Richard V.; Lee, Victoria; Prudhomme, Robert; Priestley, Rodney; Matar, Omar K.

2017-11-01

Porous structures can be formed by the controlled precipitation of polymer blends; ranging from porous matrices, with applications in membrane filtration, to porous nano-particles, with applications in catalysis, targeted drug delivery and emulsion stabilisation. Under a diffusive exchange of solvent for non-solvent, prevailing conditions favour the decomposition of polymer blends into multiple phases. Interestingly, dynamic structures can be `trapped' via vitrification prior to thermodynamic equilibrium. A promising mechanism for large-scale polymer processing is flash nano-precipitation (FNP). FNP particle formation has recently been modelled using spinodal decomposition theory, however the influence of fluid flow on structure formation is yet to be clarified. In this study, we couple a Navier-Stokes equation to a Cahn-Hilliard model of spinodal decomposition. The framework is implemented using Code BLUE, a massively scalable fluid dynamics solver, and applied to flows within confined impinging jet mixers. The present method is valid for a wide range of mixing timescales spanning FNP and conventional immersion precipitation processes. Results aid in the fabrication of nano-scale polymer particles with tuneable internal porosities. EPSRC, UK, MEMPHIS program Grant (EP/K003976/1), RAEng Research Chair (OKM), PETRONAS.

3D tensor-based blind multispectral image decomposition for tumor demarcation

NASA Astrophysics Data System (ADS)

Kopriva, Ivica; Peršin, Antun

2010-03-01

Blind decomposition of multi-spectral fluorescent image for tumor demarcation is formulated exploiting tensorial structure of the image. First contribution of the paper is identification of the matrix of spectral responses and 3D tensor of spatial distributions of the materials present in the image from Tucker3 or PARAFAC models of 3D image tensor. Second contribution of the paper is clustering based estimation of the number of the materials present in the image as well as matrix of their spectral profiles. 3D tensor of the spatial distributions of the materials is recovered through 3-mode multiplication of the multi-spectral image tensor and inverse of the matrix of spectral profiles. Tensor representation of the multi-spectral image preserves its local spatial structure that is lost, due to vectorization process, when matrix factorization-based decomposition methods (such as non-negative matrix factorization and independent component analysis) are used. Superior performance of the tensor-based image decomposition over matrix factorization-based decompositions is demonstrated on experimental red-green-blue (RGB) image with known ground truth as well as on RGB fluorescent images of the skin tumor (basal cell carcinoma).

Factors affecting regional per-capita carbon emissions in China based on an LMDI factor decomposition model.

PubMed

Dong, Feng; Long, Ruyin; Chen, Hong; Li, Xiaohui; Yang, Qingliang

2013-01-01

China is considered to be the main carbon producer in the world. The per-capita carbon emissions indicator is an important measure of the regional carbon emissions situation. This study used the LMDI factor decomposition model-panel co-integration test two-step method to analyze the factors that affect per-capita carbon emissions. The main results are as follows. (1) During 1997, Eastern China, Central China, and Western China ranked first, second, and third in the per-capita carbon emissions, while in 2009 the pecking order changed to Eastern China, Western China, and Central China. (2) According to the LMDI decomposition results, the key driver boosting the per-capita carbon emissions in the three economic regions of China between 1997 and 2009 was economic development, and the energy efficiency was much greater than the energy structure after considering their effect on restraining increased per-capita carbon emissions. (3) Based on the decomposition, the factors that affected per-capita carbon emissions in the panel co-integration test showed that Central China had the best energy structure elasticity in its regional per-capita carbon emissions. Thus, Central China was ranked first for energy efficiency elasticity, while Western China was ranked first for economic development elasticity.

A Structured Model for Software Documentation.

ERIC Educational Resources Information Center

Swigger, Keith

The concept of "structured programming" was developed to facilitate software production, but it has not carried over to documentation design. Two concepts of structure are relevant to user documentation for computer programs. The first is based on programming techniques that emphasize decomposition of tasks into discrete modules, while the second…

Modal decomposition of turbulent supersonic cavity

NASA Astrophysics Data System (ADS)

Soni, R. K.; Arya, N.; De, A.

2018-06-01

Self-sustained oscillations in a Mach 3 supersonic cavity with a length-to-depth ratio of three are investigated using wall-modeled large eddy simulation methodology for ReD = 3.39× 105 . The unsteady data obtained through computation are utilized to investigate the spatial and temporal evolution of the flow field, especially the second invariant of the velocity tensor, while the phase-averaged data are analyzed over a feedback cycle to study the spatial structures. This analysis is accompanied by the proper orthogonal decomposition (POD) data, which reveals the presence of discrete vortices along the shear layer. The POD analysis is performed in both the spanwise and streamwise planes to extract the coherence in flow structures. Finally, dynamic mode decomposition is performed on the data sequence to obtain the dynamic information and deeper insight into the self-sustained mechanism.

Automatic decomposition of kinetic models of signaling networks minimizing the retroactivity among modules.

PubMed

Saez-Rodriguez, Julio; Gayer, Stefan; Ginkel, Martin; Gilles, Ernst Dieter

2008-08-15

The modularity of biochemical networks in general, and signaling networks in particular, has been extensively studied over the past few years. It has been proposed to be a useful property to analyze signaling networks: by decomposing the network into subsystems, more manageable units are obtained that are easier to analyze. While many powerful algorithms are available to identify modules in protein interaction networks, less attention has been paid to signaling networks de.ned as chemical systems. Such a decomposition would be very useful as most quantitative models are de.ned using the latter, more detailed formalism. Here, we introduce a novel method to decompose biochemical networks into modules so that the bidirectional (retroactive) couplings among the modules are minimized. Our approach adapts a method to detect community structures, and applies it to the so-called retroactivity matrix that characterizes the couplings of the network. Only the structure of the network, e.g. in SBML format, is required. Furthermore, the modularized models can be loaded into ProMoT, a modeling tool which supports modular modeling. This allows visualization of the models, exploiting their modularity and easy generation of models of one or several modules for further analysis. The method is applied to several relevant cases, including an entangled model of the EGF-induced MAPK cascade and a comprehensive model of EGF signaling, demonstrating its ability to uncover meaningful modules. Our approach can thus help to analyze large networks, especially when little a priori knowledge on the structure of the network is available. The decomposition algorithms implemented in MATLAB (Mathworks, Inc.) are freely available upon request. ProMoT is freely available at http://www.mpi-magdeburg.mpg.de/projects/promot. Supplementary data are available at Bioinformatics online.

An investigation of the use of temporal decomposition in space mission scheduling

NASA Technical Reports Server (NTRS)

Bullington, Stanley E.; Narayanan, Venkat

1994-01-01

This research involves an examination of techniques for solving scheduling problems in long-duration space missions. The mission timeline is broken up into several time segments, which are then scheduled incrementally. Three methods are presented for identifying the activities that are to be attempted within these segments. The first method is a mathematical model, which is presented primarily to illustrate the structure of the temporal decomposition problem. Since the mathematical model is bound to be computationally prohibitive for realistic problems, two heuristic assignment procedures are also presented. The first heuristic method is based on dispatching rules for activity selection, and the second heuristic assigns performances of a model evenly over timeline segments. These heuristics are tested using a sample Space Station mission and a Spacelab mission. The results are compared with those obtained by scheduling the missions without any problem decomposition. The applicability of this approach to large-scale mission scheduling problems is also discussed.

Direct observation of nanowire growth and decomposition.

PubMed

Rackauskas, Simas; Shandakov, Sergey D; Jiang, Hua; Wagner, Jakob B; Nasibulin, Albert G

2017-09-26

Fundamental concepts of the crystal formation suggest that the growth and decomposition are determined by simultaneous embedding and removal of the atoms. Apparently, by changing the crystal formation conditions one can switch the regimes from the growth to decomposition. To the best of our knowledge, so far this has been only postulated, but never observed at the atomic level. By means of in situ environmental transmission electron microscopy we monitored and examined the atomic layer transformation at the conditions of the crystal growth and its decomposition using CuO nanowires selected as a model object. The atomic layer growth/decomposition was studied by varying an O 2 partial pressure. Three distinct regimes of the atomic layer evolution were experimentally observed: growth, transition and decomposition. The transition regime, at which atomic layer growth/decomposition switch takes place, is characterised by random nucleation of the atomic layers on the growing {111} surface. The decomposition starts on the side of the nanowire by removing the atomic layers without altering the overall crystal structure, which besides the fundamental importance offers new possibilities for the nanowire manipulation. Understanding of the crystal growth kinetics and nucleation at the atomic level is essential for the precise control of 1D crystal formation.

CT Image Sequence Restoration Based on Sparse and Low-Rank Decomposition

PubMed Central

Gou, Shuiping; Wang, Yueyue; Wang, Zhilong; Peng, Yong; Zhang, Xiaopeng; Jiao, Licheng; Wu, Jianshe

2013-01-01

Blurry organ boundaries and soft tissue structures present a major challenge in biomedical image restoration. In this paper, we propose a low-rank decomposition-based method for computed tomography (CT) image sequence restoration, where the CT image sequence is decomposed into a sparse component and a low-rank component. A new point spread function of Weiner filter is employed to efficiently remove blur in the sparse component; a wiener filtering with the Gaussian PSF is used to recover the average image of the low-rank component. And then we get the recovered CT image sequence by combining the recovery low-rank image with all recovery sparse image sequence. Our method achieves restoration results with higher contrast, sharper organ boundaries and richer soft tissue structure information, compared with existing CT image restoration methods. The robustness of our method was assessed with numerical experiments using three different low-rank models: Robust Principle Component Analysis (RPCA), Linearized Alternating Direction Method with Adaptive Penalty (LADMAP) and Go Decomposition (GoDec). Experimental results demonstrated that the RPCA model was the most suitable for the small noise CT images whereas the GoDec model was the best for the large noisy CT images. PMID:24023764

Simultaneous tensor decomposition and completion using factor priors.

PubMed

Chen, Yi-Lei; Hsu, Chiou-Ting; Liao, Hong-Yuan Mark

2014-03-01

The success of research on matrix completion is evident in a variety of real-world applications. Tensor completion, which is a high-order extension of matrix completion, has also generated a great deal of research interest in recent years. Given a tensor with incomplete entries, existing methods use either factorization or completion schemes to recover the missing parts. However, as the number of missing entries increases, factorization schemes may overfit the model because of incorrectly predefined ranks, while completion schemes may fail to interpret the model factors. In this paper, we introduce a novel concept: complete the missing entries and simultaneously capture the underlying model structure. To this end, we propose a method called simultaneous tensor decomposition and completion (STDC) that combines a rank minimization technique with Tucker model decomposition. Moreover, as the model structure is implicitly included in the Tucker model, we use factor priors, which are usually known a priori in real-world tensor objects, to characterize the underlying joint-manifold drawn from the model factors. By exploiting this auxiliary information, our method leverages two classic schemes and accurately estimates the model factors and missing entries. We conducted experiments to empirically verify the convergence of our algorithm on synthetic data and evaluate its effectiveness on various kinds of real-world data. The results demonstrate the efficacy of the proposed method and its potential usage in tensor-based applications. It also outperforms state-of-the-art methods on multilinear model analysis and visual data completion tasks.

Importance of vegetation dynamics for future terrestrial carbon cycling

NASA Astrophysics Data System (ADS)

Ahlström, Anders; Xia, Jianyang; Arneth, Almut; Luo, Yiqi; Smith, Benjamin

2015-05-01

Terrestrial ecosystems currently sequester about one third of anthropogenic CO2 emissions each year, an important ecosystem service that dampens climate change. The future fate of this net uptake of CO2 by land based ecosystems is highly uncertain. Most ecosystem models used to predict the future terrestrial carbon cycle share a common architecture, whereby carbon that enters the system as net primary production (NPP) is distributed to plant compartments, transferred to litter and soil through vegetation turnover and then re-emitted to the atmosphere in conjunction with soil decomposition. However, while all models represent the processes of NPP and soil decomposition, they vary greatly in their representations of vegetation turnover and the associated processes governing mortality, disturbance and biome shifts. Here we used a detailed second generation dynamic global vegetation model with advanced representation of vegetation growth and mortality, and the associated turnover. We apply an emulator that describes the carbon flows and pools exactly as in simulations with the full model. The emulator simulates ecosystem dynamics in response to 13 different climate or Earth system model simulations from the Coupled Model Intercomparison Project Phase 5 ensemble under RCP8.5 radiative forcing. By exchanging carbon cycle processes between these 13 simulations we quantified the relative roles of three main driving processes of the carbon cycle; (I) NPP, (II) vegetation dynamics and turnover and (III) soil decomposition, in terms of their contribution to future carbon (C) uptake uncertainties among the ensemble of climate change scenarios. We found that NPP, vegetation turnover (including structural shifts, wild fires and mortality) and soil decomposition rates explained 49%, 17% and 33%, respectively, of uncertainties in modelled global C-uptake. Uncertainty due to vegetation turnover was further partitioned into stand-clearing disturbances (16%), wild fires (0%), stand dynamics (7%), reproduction (10%) and biome shifts (67%) globally. We conclude that while NPP and soil decomposition rates jointly account for 83% of future climate induced C-uptake uncertainties, vegetation turnover and structure, dominated by biome shifts, represent a significant fraction globally and regionally (tropical forests: 40%), strongly motivating their representation and analysis in future C-cycle studies.

Search for memory effects in methane hydrate: structure of water before hydrate formation and after hydrate decomposition.

PubMed

Buchanan, Piers; Soper, Alan K; Thompson, Helen; Westacott, Robin E; Creek, Jefferson L; Hobson, Greg; Koh, Carolyn A

2005-10-22

Neutron diffraction with HD isotope substitution has been used to study the formation and decomposition of the methane clathrate hydrate. Using this atomistic technique coupled with simultaneous gas consumption measurements, we have successfully tracked the formation of the sI methane hydrate from a water/gas mixture and then the subsequent decomposition of the hydrate from initiation to completion. These studies demonstrate that the application of neutron diffraction with simultaneous gas consumption measurements provides a powerful method for studying the clathrate hydrate crystal growth and decomposition. We have also used neutron diffraction to examine the water structure before the hydrate growth and after the hydrate decomposition. From the neutron-scattering curves and the empirical potential structure refinement analysis of the data, we find that there is no significant difference between the structure of water before the hydrate formation and the structure of water after the hydrate decomposition. Nor is there any significant change to the methane hydration shell. These results are discussed in the context of widely held views on the existence of memory effects after the hydrate decomposition.

Qualitative Fault Isolation of Hybrid Systems: A Structural Model Decomposition-Based Approach

NASA Technical Reports Server (NTRS)

Bregon, Anibal; Daigle, Matthew; Roychoudhury, Indranil

2016-01-01

Quick and robust fault diagnosis is critical to ensuring safe operation of complex engineering systems. A large number of techniques are available to provide fault diagnosis in systems with continuous dynamics. However, many systems in aerospace and industrial environments are best represented as hybrid systems that consist of discrete behavioral modes, each with its own continuous dynamics. These hybrid dynamics make the on-line fault diagnosis task computationally more complex due to the large number of possible system modes and the existence of autonomous mode transitions. This paper presents a qualitative fault isolation framework for hybrid systems based on structural model decomposition. The fault isolation is performed by analyzing the qualitative information of the residual deviations. However, in hybrid systems this process becomes complex due to possible existence of observation delays, which can cause observed deviations to be inconsistent with the expected deviations for the current mode in the system. The great advantage of structural model decomposition is that (i) it allows to design residuals that respond to only a subset of the faults, and (ii) every time a mode change occurs, only a subset of the residuals will need to be reconfigured, thus reducing the complexity of the reasoning process for isolation purposes. To demonstrate and test the validity of our approach, we use an electric circuit simulation as the case study.

Zero-Sum Matrix Game with Payoffs of Dempster-Shafer Belief Structures and Its Applications on Sensors

PubMed Central

Deng, Xinyang; Jiang, Wen; Zhang, Jiandong

2017-01-01

The zero-sum matrix game is one of the most classic game models, and it is widely used in many scientific and engineering fields. In the real world, due to the complexity of the decision-making environment, sometimes the payoffs received by players may be inexact or uncertain, which requires that the model of matrix games has the ability to represent and deal with imprecise payoffs. To meet such a requirement, this paper develops a zero-sum matrix game model with Dempster–Shafer belief structure payoffs, which effectively represents the ambiguity involved in payoffs of a game. Then, a decomposition method is proposed to calculate the value of such a game, which is also expressed with belief structures. Moreover, for the possible computation-intensive issue in the proposed decomposition method, as an alternative solution, a Monte Carlo simulation approach is presented, as well. Finally, the proposed zero-sum matrix games with payoffs of Dempster–Shafer belief structures is illustratively applied to the sensor selection and intrusion detection of sensor networks, which shows its effectiveness and application process. PMID:28430156

The interacting effects of temperature and food chain length on trophic abundance and ecosystem function.

PubMed

Beveridge, Oliver S; Humphries, Stuart; Petchey, Owen L

2010-05-01

1. While much is known about the independent effects of trophic structure and temperature on density and ecosystem processes, less is known about the interaction(s) between the two. 2. We manipulated the temperature of laboratory-based bacteria-protist communities that contained communities with one, two, or three trophic levels, and recorded species' densities and bacterial decomposition. 3. Temperature, food chain length and their interaction produced significant responses in microbial density and bacterial decomposition. Prey and resource density expressed different patterns of temperature dependency during different phases of population dynamics. The addition of a predator altered the temperature-density relationship of prey, from a unimodal trend to a negative one. Bacterial decomposition was greatest in the presence of consumers at higher temperatures. 4. These results are qualitatively consistent with a recent model of direct and indirect temperature effects on resource-consumer population dynamics. Results highlight and reinforce the importance of indirect effects of temperature mediated through trophic interactions. Understanding and predicting the consequences of environmental change will require that indirect effects, trophic structure, and individual species' tolerances be incorporated into theory and models.

Aeroelastic System Development Using Proper Orthogonal Decomposition and Volterra Theory

NASA Technical Reports Server (NTRS)

Lucia, David J.; Beran, Philip S.; Silva, Walter A.

2003-01-01

This research combines Volterra theory and proper orthogonal decomposition (POD) into a hybrid methodology for reduced-order modeling of aeroelastic systems. The out-come of the method is a set of linear ordinary differential equations (ODEs) describing the modal amplitudes associated with both the structural modes and the POD basis functions for the uid. For this research, the structural modes are sine waves of varying frequency, and the Volterra-POD approach is applied to the fluid dynamics equations. The structural modes are treated as forcing terms which are impulsed as part of the uid model realization. Using this approach, structural and uid operators are coupled into a single aeroelastic operator. This coupling converts a free boundary uid problem into an initial value problem, while preserving the parameter (or parameters) of interest for sensitivity analysis. The approach is applied to an elastic panel in supersonic cross ow. The hybrid Volterra-POD approach provides a low-order uid model in state-space form. The linear uid model is tightly coupled with a nonlinear panel model using an implicit integration scheme. The resulting aeroelastic model provides correct limit-cycle oscillation prediction over a wide range of panel dynamic pressure values. Time integration of the reduced-order aeroelastic model is four orders of magnitude faster than the high-order solution procedure developed for this research using traditional uid and structural solvers.

Signal decomposition for surrogate modeling of a constrained ultrasonic design space

NASA Astrophysics Data System (ADS)

Homa, Laura; Sparkman, Daniel; Wertz, John; Welter, John; Aldrin, John C.

2018-04-01

The U.S. Air Force seeks to improve the methods and measures by which the lifecycle of composite structures are managed. Nondestructive evaluation of damage - particularly internal damage resulting from impact - represents a significant input to that improvement. Conventional ultrasound can detect this damage; however, full 3D characterization has not been demonstrated. A proposed approach for robust characterization uses model-based inversion through fitting of simulated results to experimental data. One challenge with this approach is the high computational expense of the forward model to simulate the ultrasonic B-scans for each damage scenario. A potential solution is to construct a surrogate model using a subset of simulated ultrasonic scans built using a highly accurate, computationally expensive forward model. However, the dimensionality of these simulated B-scans makes interpolating between them a difficult and potentially infeasible problem. Thus, we propose using the chirplet decomposition to reduce the dimensionality of the data, and allow for interpolation in the chirplet parameter space. By applying the chirplet decomposition, we are able to extract the salient features in the data and construct a surrogate forward model.

Hierarchical coordinate systems for understanding complexity and its evolution, with applications to genetic regulatory networks.

PubMed

Egri-Nagy, Attila; Nehaniv, Chrystopher L

2008-01-01

Beyond complexity measures, sometimes it is worthwhile in addition to investigate how complexity changes structurally, especially in artificial systems where we have complete knowledge about the evolutionary process. Hierarchical decomposition is a useful way of assessing structural complexity changes of organisms modeled as automata, and we show how recently developed computational tools can be used for this purpose, by computing holonomy decompositions and holonomy complexity. To gain insight into the evolution of complexity, we investigate the smoothness of the landscape structure of complexity under minimal transitions. As a proof of concept, we illustrate how the hierarchical complexity analysis reveals symmetries and irreversible structure in biological networks by applying the methods to the lac operon mechanism in the genetic regulatory network of Escherichia coli.

Frequency Domain Decomposition performed on the strain data obtained from the aluminium model of an offshore support structure

NASA Astrophysics Data System (ADS)

Mieloszyk, M.; Opoka, S.; Ostachowicz, W.

2015-07-01

This paper presents an application of Fibre Bragg Grating (FBG) sensors for Structural Health Monitoring (SHM) of offshore wind energy support structure model. The analysed structure is a tripod equipped with 16 FBG sensors. From a wide variety of Operational Modal Analysis (OMA) methods Frequency Domain Decomposition (FDD) technique is used in this paper under assumption that the input loading is similar to a white noise excitation. The FDD method can be applied using different sets of sensors, i.e. the one which contains all FBG sensors and the other set of sensors localised only on a particular tripod's leg. The cases considered during investigation were as follows: damaged and undamaged scenarios, different support conditions. The damage was simulated as an dismantled flange on an upper brace in one of the tripod legs. First the model was fixed to an antishaker table and investigated in the air under impulse excitations. Next the tripod was submerged into water basin in order to check the quality of the measurement set-up in different environmental condition. In this case the model was excited by regular waves.

F4 , E6 and G2 exceptional gauge groups in the vacuum domain structure model

NASA Astrophysics Data System (ADS)

Shahlaei, Amir; Rafibakhsh, Shahnoosh

2018-03-01

Using a vacuum domain structure model, we calculate trivial static potentials in various representations of F4 , E6, and G2 exceptional groups by means of the unit center element. Due to the absence of the nontrivial center elements, the potential of every representation is screened at far distances. However, the linear part is observed at intermediate quark separations and is investigated by the decomposition of the exceptional group to its maximal subgroups. Comparing the group factor of the supergroup with the corresponding one obtained from the nontrivial center elements of S U (3 ) subgroup shows that S U (3 ) is not the direct cause of temporary confinement in any of the exceptional groups. However, the trivial potential obtained from the group decomposition into the S U (3 ) subgroup is the same as the potential of the supergroup itself. In addition, any regular or singular decomposition into the S U (2 ) subgroup that produces the Cartan generator with the same elements as h1, in any exceptional group, leads to the linear intermediate potential of the exceptional gauge groups. The other S U (2 ) decompositions with the Cartan generator different from h1 are still able to describe the linear potential if the number of S U (2 ) nontrivial center elements that emerge in the decompositions is the same. As a result, it is the center vortices quantized in terms of nontrivial center elements of the S U (2 ) subgroup that give rise to the intermediate confinement in the static potentials.

Multi-scale structure and topological anomaly detection via a new network statistic: The onion decomposition.

PubMed

Hébert-Dufresne, Laurent; Grochow, Joshua A; Allard, Antoine

2016-08-18

We introduce a network statistic that measures structural properties at the micro-, meso-, and macroscopic scales, while still being easy to compute and interpretable at a glance. Our statistic, the onion spectrum, is based on the onion decomposition, which refines the k-core decomposition, a standard network fingerprinting method. The onion spectrum is exactly as easy to compute as the k-cores: It is based on the stages at which each vertex gets removed from a graph in the standard algorithm for computing the k-cores. Yet, the onion spectrum reveals much more information about a network, and at multiple scales; for example, it can be used to quantify node heterogeneity, degree correlations, centrality, and tree- or lattice-likeness. Furthermore, unlike the k-core decomposition, the combined degree-onion spectrum immediately gives a clear local picture of the network around each node which allows the detection of interesting subgraphs whose topological structure differs from the global network organization. This local description can also be leveraged to easily generate samples from the ensemble of networks with a given joint degree-onion distribution. We demonstrate the utility of the onion spectrum for understanding both static and dynamic properties on several standard graph models and on many real-world networks.

Towards reduced order modelling for predicting the dynamics of coherent vorticity structures within wind turbine wakes

NASA Astrophysics Data System (ADS)

Debnath, M.; Santoni, C.; Leonardi, S.; Iungo, G. V.

2017-03-01

The dynamics of the velocity field resulting from the interaction between the atmospheric boundary layer and a wind turbine array can affect significantly the performance of a wind power plant and the durability of wind turbines. In this work, dynamics in wind turbine wakes and instabilities of helicoidal tip vortices are detected and characterized through modal decomposition techniques. The dataset under examination consists of snapshots of the velocity field obtained from large-eddy simulations (LES) of an isolated wind turbine, for which aerodynamic forcing exerted by the turbine blades on the atmospheric boundary layer is mimicked through the actuator line model. Particular attention is paid to the interaction between the downstream evolution of the helicoidal tip vortices and the alternate vortex shedding from the turbine tower. The LES dataset is interrogated through different modal decomposition techniques, such as proper orthogonal decomposition and dynamic mode decomposition. The dominant wake dynamics are selected for the formulation of a reduced order model, which consists in a linear time-marching algorithm where temporal evolution of flow dynamics is obtained from the previous temporal realization multiplied by a time-invariant operator. This article is part of the themed issue 'Wind energy in complex terrains'.

Interrelationships among shrub encroachment, land management, and litter decomposition in a semidesert grassland.

PubMed

Throop, Heather L; Archer, Steven R

2007-09-01

Encroachment of woody plants into grasslands, and subsequent brush management, are among the most prominent changes to occur in arid and semiarid systems over the past century. Despite the resulting widespread changes in landcover, substantial uncertainty about the biogeochemical impacts of woody proliferation and brush management exists. We explored the role of shrub encroachment and brush management on leaf litter decomposition in a semidesert grassland where velvet mesquite (Prosopis velutina) abundance has increased over the past 100 years. This change in physiognomy may affect decomposition directly, through altered litter quality or quantity, and indirectly through altered canopy structure. To assess the direct and indirect impacts of shrubs on decomposition, we quantified changes in mass, nitrogen, and carbon in litterbags deployed under mesquite canopies and in intercanopy zones. Litterbags contained foliage from mesquite and Lehmann lovegrass (Eragrostis lehmanniana), a widespread, nonnative grass in southern Arizona. To explore short- and long-term influences of brush management on the initial stages of decomposition, litterbags were deployed at sites where mesquite canopies were removed three weeks, 45 years, or 70 years prior to study initiation. Mesquite litter decomposed more rapidly than lovegrass, but negative indirect influences of mesquite canopies counteracted positive direct effects. Decomposition was positively correlated with soil infiltration into litterbags, which varied with microsite placement, and was lowest under canopies. Low under-canopy decomposition was ostensibly due to decreased soil movement associated with high under-canopy herbaceous biomass. Decomposition rates where canopies were removed three weeks prior to study initiation were comparable to those beneath intact canopies, suggesting that decomposition was driven by mesquite legacy effects on herbaceous cover-soil movement linkages. Decomposition rates where shrubs were removed 45 and 70 years prior to study initiation were comparable to intercanopy rates, suggesting that legacy effects persist less than 45 years. Accurate decomposition modeling has proved challenging in arid and semiarid systems but is critical to understanding biogeochemical responses to woody encroachment and brush management. Predicting brush-management effects on decomposition will require information on shrub-grass interactions and herbaceous biomass influences on soil movement at decadal timescales. Inclusion of microsite factors controlling soil accumulation on litter would improve the predictive capability of decomposition models.

Physical soil architectural traits are functionally linked to carbon decomposition and bacterial diversity.

PubMed

Rabbi, S M F; Daniel, H; Lockwood, P V; Macdonald, C; Pereg, L; Tighe, M; Wilson, B R; Young, I M

2016-09-12

Aggregates play a key role in protecting soil organic carbon (SOC) from microbial decomposition. The objectives of this study were to investigate the influence of pore geometry on the organic carbon decomposition rate and bacterial diversity in both macro- (250-2000 μm) and micro-aggregates (53-250 μm) using field samples. Four sites of contrasting land use on Alfisols (i.e. native pasture, crop/pasture rotation, woodland) were investigated. 3D Pore geometry of the micro-aggregates and macro-aggregates were examined by X-ray computed tomography (μCT). The occluded particulate organic carbon (oPOC) of aggregates was measured by size and density fractionation methods. Micro-aggregates had 54% less μCT observed porosity but 64% more oPOC compared with macro-aggregates. In addition, the pore connectivity in micro-aggregates was lower than macro-aggregates. Despite both lower μCT observed porosity and pore connectivity in micro-aggregates, the organic carbon decomposition rate constant (Ksoc) was similar in both aggregate size ranges. Structural equation modelling showed a strong positive relationship of the concentration of oPOC with bacterial diversity in aggregates. We use these findings to propose a conceptual model that illustrates the dynamic links between substrate, bacterial diversity, and pore geometry that suggests a structural explanation for differences in bacterial diversity across aggregate sizes.

Physical soil architectural traits are functionally linked to carbon decomposition and bacterial diversity

PubMed Central

Rabbi, S. M. F.; Daniel, H.; Lockwood, P. V.; Macdonald, C.; Pereg, L.; Tighe, M.; Wilson, B. R.; Young, I. M.

2016-01-01

Aggregates play a key role in protecting soil organic carbon (SOC) from microbial decomposition. The objectives of this study were to investigate the influence of pore geometry on the organic carbon decomposition rate and bacterial diversity in both macro- (250–2000 μm) and micro-aggregates (53–250 μm) using field samples. Four sites of contrasting land use on Alfisols (i.e. native pasture, crop/pasture rotation, woodland) were investigated. 3D Pore geometry of the micro-aggregates and macro-aggregates were examined by X-ray computed tomography (μCT). The occluded particulate organic carbon (oPOC) of aggregates was measured by size and density fractionation methods. Micro-aggregates had 54% less μCT observed porosity but 64% more oPOC compared with macro-aggregates. In addition, the pore connectivity in micro-aggregates was lower than macro-aggregates. Despite both lower μCT observed porosity and pore connectivity in micro-aggregates, the organic carbon decomposition rate constant (Ksoc) was similar in both aggregate size ranges. Structural equation modelling showed a strong positive relationship of the concentration of oPOC with bacterial diversity in aggregates. We use these findings to propose a conceptual model that illustrates the dynamic links between substrate, bacterial diversity, and pore geometry that suggests a structural explanation for differences in bacterial diversity across aggregate sizes. PMID:27615807

Nonequilibrium adiabatic molecular dynamics simulations of methane clathrate hydrate decomposition

NASA Astrophysics Data System (ADS)

Alavi, Saman; Ripmeester, J. A.

2010-04-01

Nonequilibrium, constant energy, constant volume (NVE) molecular dynamics simulations are used to study the decomposition of methane clathrate hydrate in contact with water. Under adiabatic conditions, the rate of methane clathrate decomposition is affected by heat and mass transfer arising from the breakup of the clathrate hydrate framework and release of the methane gas at the solid-liquid interface and diffusion of methane through water. We observe that temperature gradients are established between the clathrate and solution phases as a result of the endothermic clathrate decomposition process and this factor must be considered when modeling the decomposition process. Additionally we observe that clathrate decomposition does not occur gradually with breakup of individual cages, but rather in a concerted fashion with rows of structure I cages parallel to the interface decomposing simultaneously. Due to the concerted breakup of layers of the hydrate, large amounts of methane gas are released near the surface which can form bubbles that will greatly affect the rate of mass transfer near the surface of the clathrate phase. The effects of these phenomena on the rate of methane hydrate decomposition are determined and implications on hydrate dissociation in natural methane hydrate reservoirs are discussed.

Nonequilibrium adiabatic molecular dynamics simulations of methane clathrate hydrate decomposition.

PubMed

Alavi, Saman; Ripmeester, J A

2010-04-14

Nonequilibrium, constant energy, constant volume (NVE) molecular dynamics simulations are used to study the decomposition of methane clathrate hydrate in contact with water. Under adiabatic conditions, the rate of methane clathrate decomposition is affected by heat and mass transfer arising from the breakup of the clathrate hydrate framework and release of the methane gas at the solid-liquid interface and diffusion of methane through water. We observe that temperature gradients are established between the clathrate and solution phases as a result of the endothermic clathrate decomposition process and this factor must be considered when modeling the decomposition process. Additionally we observe that clathrate decomposition does not occur gradually with breakup of individual cages, but rather in a concerted fashion with rows of structure I cages parallel to the interface decomposing simultaneously. Due to the concerted breakup of layers of the hydrate, large amounts of methane gas are released near the surface which can form bubbles that will greatly affect the rate of mass transfer near the surface of the clathrate phase. The effects of these phenomena on the rate of methane hydrate decomposition are determined and implications on hydrate dissociation in natural methane hydrate reservoirs are discussed.

Temperature responses of individual soil organic matter components

NASA Astrophysics Data System (ADS)

Feng, Xiaojuan; Simpson, Myrna J.

2008-09-01

Temperature responses of soil organic matter (SOM) remain unclear partly due to its chemical and compositional heterogeneity. In this study, the decomposition of SOM from two grassland soils was investigated in a 1-year laboratory incubation at six different temperatures. SOM was separated into solvent extractable compounds, suberin- and cutin-derived compounds, and lignin-derived monomers by solvent extraction, base hydrolysis, and CuO oxidation, respectively. These SOM components have distinct chemical structures and stabilities and their decomposition patterns over the course of the experiment were fitted with a two-pool exponential decay model. The stability of SOM components was also assessed using geochemical parameters and kinetic parameters derived from model fitting. Compared with the solvent extractable compounds, a low percentage of lignin monomers partitioned into the labile SOM pool. Suberin- and cutin-derived compounds were poorly fitted by the decay model, and their recalcitrance was shown by the geochemical degradation parameter (ω - C16/∑C16), which was observed to stabilize during the incubation. The temperature sensitivity of decomposition, expressed as Q10, was derived from the relationship between temperature and SOM decay rates. SOM components exhibited varying temperature responses and the decomposition of lignin monomers exhibited higher Q10 values than the decomposition of solvent extractable compounds. Our study shows that Q10 values derived from soil respiration measurements may not be reliable indicators of temperature responses of individual SOM components.

Blurred Palmprint Recognition Based on Stable-Feature Extraction Using a Vese–Osher Decomposition Model

PubMed Central

Hong, Danfeng; Su, Jian; Hong, Qinggen; Pan, Zhenkuan; Wang, Guodong

2014-01-01

As palmprints are captured using non-contact devices, image blur is inevitably generated because of the defocused status. This degrades the recognition performance of the system. To solve this problem, we propose a stable-feature extraction method based on a Vese–Osher (VO) decomposition model to recognize blurred palmprints effectively. A Gaussian defocus degradation model is first established to simulate image blur. With different degrees of blurring, stable features are found to exist in the image which can be investigated by analyzing the blur theoretically. Then, a VO decomposition model is used to obtain structure and texture layers of the blurred palmprint images. The structure layer is stable for different degrees of blurring (this is a theoretical conclusion that needs to be further proved via experiment). Next, an algorithm based on weighted robustness histogram of oriented gradients (WRHOG) is designed to extract the stable features from the structure layer of the blurred palmprint image. Finally, a normalized correlation coefficient is introduced to measure the similarity in the palmprint features. We also designed and performed a series of experiments to show the benefits of the proposed method. The experimental results are used to demonstrate the theoretical conclusion that the structure layer is stable for different blurring scales. The WRHOG method also proves to be an advanced and robust method of distinguishing blurred palmprints. The recognition results obtained using the proposed method and data from two palmprint databases (PolyU and Blurred–PolyU) are stable and superior in comparison to previous high-performance methods (the equal error rate is only 0.132%). In addition, the authentication time is less than 1.3 s, which is fast enough to meet real-time demands. Therefore, the proposed method is a feasible way of implementing blurred palmprint recognition. PMID:24992328

Blurred palmprint recognition based on stable-feature extraction using a Vese-Osher decomposition model.

PubMed

Hong, Danfeng; Su, Jian; Hong, Qinggen; Pan, Zhenkuan; Wang, Guodong

2014-01-01

As palmprints are captured using non-contact devices, image blur is inevitably generated because of the defocused status. This degrades the recognition performance of the system. To solve this problem, we propose a stable-feature extraction method based on a Vese-Osher (VO) decomposition model to recognize blurred palmprints effectively. A Gaussian defocus degradation model is first established to simulate image blur. With different degrees of blurring, stable features are found to exist in the image which can be investigated by analyzing the blur theoretically. Then, a VO decomposition model is used to obtain structure and texture layers of the blurred palmprint images. The structure layer is stable for different degrees of blurring (this is a theoretical conclusion that needs to be further proved via experiment). Next, an algorithm based on weighted robustness histogram of oriented gradients (WRHOG) is designed to extract the stable features from the structure layer of the blurred palmprint image. Finally, a normalized correlation coefficient is introduced to measure the similarity in the palmprint features. We also designed and performed a series of experiments to show the benefits of the proposed method. The experimental results are used to demonstrate the theoretical conclusion that the structure layer is stable for different blurring scales. The WRHOG method also proves to be an advanced and robust method of distinguishing blurred palmprints. The recognition results obtained using the proposed method and data from two palmprint databases (PolyU and Blurred-PolyU) are stable and superior in comparison to previous high-performance methods (the equal error rate is only 0.132%). In addition, the authentication time is less than 1.3 s, which is fast enough to meet real-time demands. Therefore, the proposed method is a feasible way of implementing blurred palmprint recognition.

Kinetics of the cellular decomposition of supersaturated solid solutions

NASA Astrophysics Data System (ADS)

Ivanov, M. A.; Naumuk, A. Yu.

2014-09-01

A consistent description of the kinetics of the cellular decomposition of supersaturated solid solutions with the development of a spatially periodic structure of lamellar (platelike) type, which consists of alternating phases of precipitates on the basis of the impurity component and depleted initial solid solution, is given. One of the equations, which determines the relationship between the parameters that describe the process of decomposition, has been obtained from a comparison of two approaches in order to determine the rate of change in the free energy of the system. The other kinetic parameters can be described with the use of a variational method, namely, by the maximum velocity of motion of the decomposition boundary at a given temperature. It is shown that the mutual directions of growth of the lamellae of different phases are determined by the minimum value of the interphase surface energy. To determine the parameters of the decomposition, a simple thermodynamic model of states with a parabolic dependence of the free energy on the concentrations has been used. As a result, expressions that describe the decomposition rate, interlamellar distance, and the concentration of impurities in the phase that remain after the decomposition have been derived. This concentration proves to be equal to the half-sum of the initial concentration and the equilibrium concentration corresponding to the decomposition temperature.

A model for finite-deformation nonlinear thermomechanical response of single crystal copper under shock conditions

NASA Astrophysics Data System (ADS)

Luscher, Darby J.; Bronkhorst, Curt A.; Alleman, Coleman N.; Addessio, Francis L.

2013-09-01

A physically consistent framework for combining pressure-volume-temperature equations of state with crystal plasticity models is developed for the application of modeling the response of single and polycrystals under shock conditions. The particular model is developed for copper, thus the approach focuses on crystals of cubic symmetry although many of the concepts in the approach are applicable to crystals of lower symmetry. We employ a multiplicative decomposition of the deformation gradient into isochoric elastic, thermoelastic dilation, and plastic parts leading to a definition of isochoric elastic Green-Lagrange strain. This finite deformation kinematic decomposition enables a decomposition of Helmholtz free-energy into terms reflecting dilatational thermoelasticity, strain energy due to long-range isochoric elastic deformation of the lattice and a term reflecting energy stored in short range elastic lattice deformation due to evolving defect structures. A model for the single crystal response of copper is implemented consistent with the framework into a three-dimensional Lagrangian finite element code. Simulations exhibit favorable agreement with single and bicrystal experimental data for shock pressures ranging from 3 to 110 GPa.

(A)biotic processes control soil carbon dynamics: quantitative assessment of model complexity, stability and response to perturbations for improving ESMs

NASA Astrophysics Data System (ADS)

Georgiou, K.; Abramoff, R. Z.; Harte, J.; Riley, W. J.; Torn, M. S.

2016-12-01

As global temperatures and atmospheric CO2 concentrations continue to increase, soil microbial activity and decomposition of soil organic matter (SOM) are expected to follow suit, potentially limiting soil carbon storage. Traditional global- and ecosystem-scale models simulate SOM decomposition using linear kinetics, which are inherently unable to reproduce carbon-concentration feedbacks, such as priming of native SOM at elevated CO2 concentrations. Recent studies using nonlinear microbial models of SOM decomposition seek to capture these interactions, and several groups are currently integrating these microbial models into Earth System Models (ESMs). However, despite their widespread ability to exhibit nonlinear responses, these models vary tremendously in complexity and, consequently, dynamics. In this study, we explore, both analytically and numerically, the emergent oscillatory behavior and insensitivity of SOM stocks to carbon inputs that have been deemed `unrealistic' in recent microbial models. We discuss the sources of instability in four models of varying complexity, by sequentially reducing complexity of a detailed model that includes microbial physiology, a mineral sorption isotherm, and enzyme dynamics. We also present an alternative representation of microbial turnover that limits population sizes and, thus, reduces oscillations. We compare these models to several long-term carbon input manipulations, including the Detritus Input and Removal Treatment (DIRT) experiments, to show that there are clear metrics that can be used to distinguish and validate the inherent dynamics of each model structure. We find that traditional linear and nonlinear models cannot readily capture the range of long-term responses observed across the DIRT experiments as a direct consequence of their model structures, and that modifying microbial turnover results in more realistic predictions. Finally, we discuss our findings in the context of improving microbial model behavior for inclusion in ESMs.

Assessing the effect of different treatments on decomposition rate of dairy manure.

PubMed

Khalil, Tariq M; Higgins, Stewart S; Ndegwa, Pius M; Frear, Craig S; Stöckle, Claudio O

2016-11-01

Confined animal feeding operations (CAFOs) contribute to greenhouse gas emission, but the magnitude of these emissions as a function of operation size, infrastructure, and manure management are difficult to assess. Modeling is a viable option to estimate gaseous emission and nutrient flows from CAFOs. These models use a decomposition rate constant for carbon mineralization. However, this constant is usually determined assuming a homogenous mix of manure, ignoring the effects of emerging manure treatments. The aim of this study was to measure and compare the decomposition rate constants of dairy manure in single and three-pool decomposition models, and to develop an empirical model based on chemical composition of manure for prediction of a decomposition rate constant. Decomposition rate constants of manure before and after an anaerobic digester (AD), following coarse fiber separation, and fine solids removal were determined under anaerobic conditions for single and three-pool decomposition models. The decomposition rates of treated manure effluents differed significantly from untreated manure for both single and three-pool decomposition models. In the single-pool decomposition model, AD effluent containing only suspended solids had a relatively high decomposition rate of 0.060 d(-1), while liquid with coarse fiber and fine solids removed had the lowest rate of 0.013 d(-1). In the three-pool decomposition model, fast and slow decomposition rate constants (0.25 d(-1) and 0.016 d(-1) respectively) of untreated AD influent were also significantly different from treated manure fractions. A regression model to predict the decomposition rate of treated dairy manure fitted well (R(2) = 0.83) to observed data. Copyright © 2016 Elsevier Ltd. All rights reserved.

Gibbsian Stationary Non-equilibrium States

NASA Astrophysics Data System (ADS)

De Carlo, Leonardo; Gabrielli, Davide

2017-09-01

We study the structure of stationary non-equilibrium states for interacting particle systems from a microscopic viewpoint. In particular we discuss two different discrete geometric constructions. We apply both of them to determine non reversible transition rates corresponding to a fixed invariant measure. The first one uses the equivalence of this problem with the construction of divergence free flows on the transition graph. Since divergence free flows are characterized by cyclic decompositions we can generate families of models from elementary cycles on the configuration space. The second construction is a functional discrete Hodge decomposition for translational covariant discrete vector fields. According to this, for example, the instantaneous current of any interacting particle system on a finite torus can be canonically decomposed in a gradient part, a circulation term and an harmonic component. All the three components are associated with functions on the configuration space. This decomposition is unique and constructive. The stationary condition can be interpreted as an orthogonality condition with respect to an harmonic discrete vector field and we use this decomposition to construct models having a fixed invariant measure.

A reduced-order model for compressible flows with buffeting condition using higher order dynamic mode decomposition with a mode selection criterion

NASA Astrophysics Data System (ADS)

Kou, Jiaqing; Le Clainche, Soledad; Zhang, Weiwei

2018-01-01

This study proposes an improvement in the performance of reduced-order models (ROMs) based on dynamic mode decomposition to model the flow dynamics of the attractor from a transient solution. By combining higher order dynamic mode decomposition (HODMD) with an efficient mode selection criterion, the HODMD with criterion (HODMDc) ROM is able to identify dominant flow patterns with high accuracy. This helps us to develop a more parsimonious ROM structure, allowing better predictions of the attractor dynamics. The method is tested in the solution of a NACA0012 airfoil buffeting in a transonic flow, and its good performance in both the reconstruction of the original solution and the prediction of the permanent dynamics is shown. In addition, the robustness of the method has been successfully tested using different types of parameters, indicating that the proposed ROM approach is a tool promising for using in both numerical simulations and experimental data.

Studying Turbulence Using Numerical Simulation Databases. Proceedings of the 1987 Summer Program

NASA Technical Reports Server (NTRS)

Moin, Parviz (Editor); Reynolds, William C. (Editor); Kim, John (Editor)

1987-01-01

The focus was on the use of databases obtained from direct numerical simulations of turbulent flows, for study of turbulence physics and modeling. Topics addressed included: stochastic decomposition/chaos/bifurcation; two-point closure (or k-space) modeling; scalar transport/reacting flows; Reynolds stress modeling; and structure of turbulent boundary layers.

An Efficient Model-based Diagnosis Engine for Hybrid Systems Using Structural Model Decomposition

NASA Technical Reports Server (NTRS)

Bregon, Anibal; Narasimhan, Sriram; Roychoudhury, Indranil; Daigle, Matthew; Pulido, Belarmino

2013-01-01

Complex hybrid systems are present in a large range of engineering applications, like mechanical systems, electrical circuits, or embedded computation systems. The behavior of these systems is made up of continuous and discrete event dynamics that increase the difficulties for accurate and timely online fault diagnosis. The Hybrid Diagnosis Engine (HyDE) offers flexibility to the diagnosis application designer to choose the modeling paradigm and the reasoning algorithms. The HyDE architecture supports the use of multiple modeling paradigms at the component and system level. However, HyDE faces some problems regarding performance in terms of complexity and time. Our focus in this paper is on developing efficient model-based methodologies for online fault diagnosis in complex hybrid systems. To do this, we propose a diagnosis framework where structural model decomposition is integrated within the HyDE diagnosis framework to reduce the computational complexity associated with the fault diagnosis of hybrid systems. As a case study, we apply our approach to a diagnostic testbed, the Advanced Diagnostics and Prognostics Testbed (ADAPT), using real data.

On the Structure Sensitivity of Formic Acid Decomposition on Cu Catalysts

DOE PAGES

Li, Sha; Scaranto, Jessica; Mavrikakis, Manos

2016-08-03

Catalytic decomposition of formic acid (HCOOH) has attracted substantial attention since HCOOH is a major by-product in biomass reforming, a promising hydrogen carrier, and also a potential low temperature fuel cell feed. Despite the abundance of experimental studies for vapor-phase HCOOH decomposition on Cu catalysts, the reaction mechanism and its structure sensitivity is still under debate. In this work, self-consistent, periodic density functional theory calculations were performed on three model surfaces of copper—Cu(111), Cu(100) and Cu(211), and both the HCOO (formate)-mediated and COOH (carboxyl)-mediated pathways were investigated for HCOOH decomposition. The energetics of both pathways suggest that the HCOO-mediated routemore » is more favorable than the COOH-mediated route on all three surfaces, and that HCOOH decomposition proceeds through two consecutive dehydrogenation steps via the HCOO intermediate followed by the recombinative desorption of H 2. On all three surfaces, HCOO dehydrogenation is the likely rate determining step since it has the highest transition state energy and also the highest activation energy among the three catalytic steps in the HCOO pathway. The reaction is structure sensitive on Cu catalysts since the examined three Cu facets have dramatically different binding strengths for the key intermediate HCOO and varied barriers for the likely rate determining step—HCOO dehydrogenation. Cu(100) and Cu(211) bind HCOO much more strongly than Cu(111), and they are also characterized by potential energy surfaces that are lower in energy than that for the Cu(111) facet. Coadsorbed HCOO and H represents the most stable state along the reaction coordinate, indicating that, under reaction conditions, there might be a substantial surface coverage of the HCOO intermediate, especially at under-coordinated step, corner or defect sites. Therefore, under reaction conditions, HCOOH decomposition is predicted to occur most readily on the terrace sites of Cu nanoparticles. Finally, as a result, we hereby present an example of a fundamentally structure-sensitive reaction, which may present itself as structure-insensitive in typical varied particle-size experiments.« less

Shoot litter breakdown and zinc dynamics of an aquatic plant, Schoenoplectus californicus.

PubMed

Arreghini, Silvana; de Cabo, Laura; Serafini, Roberto José María; Fabrizio de Iorio, Alicia

2018-07-03

Decomposition of plant debris is an important process in determining the structure and function of aquatic ecosystems. The aims were to find a mathematic model fitting the decomposition process of Schoenoplectus californicus shoots containing different Zn concentrations; compare the decomposition rates; and assess metal accumulation/mobilization during decomposition. A litterbag technique was applied with shoots containing three levels of Zn: collected from an unpolluted river (RIV) and from experimental populations at low (LoZn) and high (HiZn) Zn supply. The double exponential model explained S. californicus shoot decomposition, at first, higher initial proportion of refractory fraction in RIV detritus determined a lower decay rate and until 68 days, RIV and LoZn detritus behaved like a source of metal, releasing soluble/weakly bound zinc into the water; after 68 days, they became like a sink. However, HiZn detritus showed rapid release into the water during the first 8 days, changing to the sink condition up to 68 days, and then returning to the source condition up to 369 days. The knowledge of the role of detritus (sink/source) will allow defining a correct management of the vegetation used for zinc removal and providing a valuable tool for environmental remediation and rehabilitation planning.

Evaluating litter decomposition and soil organic matter dynamics in earth system models: contrasting analysis of long-term litter decomposition and steady-state soil carbon

NASA Astrophysics Data System (ADS)

Bonan, G. B.; Wieder, W. R.

2012-12-01

Decomposition is a large term in the global carbon budget, but models of the earth system that simulate carbon cycle-climate feedbacks are largely untested with respect to litter decomposition. Here, we demonstrate a protocol to document model performance with respect to both long-term (10 year) litter decomposition and steady-state soil carbon stocks. First, we test the soil organic matter parameterization of the Community Land Model version 4 (CLM4), the terrestrial component of the Community Earth System Model, with data from the Long-term Intersite Decomposition Experiment Team (LIDET). The LIDET dataset is a 10-year study of litter decomposition at multiple sites across North America and Central America. We show results for 10-year litter decomposition simulations compared with LIDET for 9 litter types and 20 sites in tundra, grassland, and boreal, conifer, deciduous, and tropical forest biomes. We show additional simulations with DAYCENT, a version of the CENTURY model, to ask how well an established ecosystem model matches the observations. The results reveal large discrepancy between the laboratory microcosm studies used to parameterize the CLM4 litter decomposition and the LIDET field study. Simulated carbon loss is more rapid than the observations across all sites, despite using the LIDET-provided climatic decomposition index to constrain temperature and moisture effects on decomposition. Nitrogen immobilization is similarly biased high. Closer agreement with the observations requires much lower decomposition rates, obtained with the assumption that nitrogen severely limits decomposition. DAYCENT better replicates the observations, for both carbon mass remaining and nitrogen, without requirement for nitrogen limitation of decomposition. Second, we compare global observationally-based datasets of soil carbon with simulated steady-state soil carbon stocks for both models. The models simulations were forced with observationally-based estimates of annual litterfall and model-derived climatic decomposition index. While comparison with the LIDET 10-year litterbag study reveals sharp contrasts between CLM4 and DAYCENT, simulations of steady-state soil carbon show less difference between models. Both CLM4 and DAYCENT significantly underestimate soil carbon. Sensitivity analyses highlight causes of the low soil carbon bias. The terrestrial biogeochemistry of earth system models must be critically tested with observations, and the consequences of particular model choices must be documented. Long-term litter decomposition experiments such as LIDET provide a real-world process-oriented benchmark to evaluate models and can critically inform model development. Analysis of steady-state soil carbon estimates reveal additional, but here different, inferences about model performance.

Untangling climatic and autogenic signals in peat records

NASA Astrophysics Data System (ADS)

Morris, Paul J.; Baird, Andrew J.; Young, Dylan M.; Swindles, Graeme T.

2016-04-01

Raised bogs contain potentially valuable information about Holocene climate change. However, autogenic processes may disconnect peatland hydrological behaviour from climate, and overwrite and degrade climatic signals in peat records. How can genuine climate signals be separated from autogenic changes? What level of detail of climatic information should we expect to be able to recover from peat-based reconstructions? We used an updated version of the DigiBog model to simulate peatland development and response to reconstructed Holocene rainfall and temperature reconstructions. The model represents key processes that are influential in peatland development and climate signal preservation, and includes a network of feedbacks between peat accumulation, decomposition, hydraulic structure and hydrological processes. It also incorporates the effects of temperature upon evapotranspiration, plant (litter) productivity and peat decomposition. Negative feedbacks in the model cause simulated water-table depths and peat humification records to exhibit homeostatic recovery from prescribed changes in rainfall, chiefly through changes in drainage. However, the simulated bogs show less resilience to changes in temperature, which cause lasting alterations to peatland structure and function and may therefore be more readily detectable in peat records. The network of feedbacks represented in DigiBog also provide both high- and low-pass filters for climatic information, meaning that the fidelity with which climate signals are preserved in simulated peatlands is determined by both the magnitude and the rate of climate change. Large-magnitude climatic events of an intermediate frequency (i.e., multi-decadal to centennial) are best preserved in the simulated bogs. We found that simulated humification records are further degraded by a phenomenon known as secondary decomposition. Decomposition signals are consistently offset from the climatic events that generate them, and decomposition records of dry-wet-dry climate sequences appear to be particularly vulnerable to overwriting. Our findings have direct implications not only for the interpretation of peat-based records of past climates, but also for understanding the likely vulnerability of peatland ecosystems and carbon stocks to future climate change.

Temporal structure of neuronal population oscillations with empirical model decomposition

NASA Astrophysics Data System (ADS)

Li, Xiaoli

2006-08-01

Frequency analysis of neuronal oscillation is very important for understanding the neural information processing and mechanism of disorder in the brain. This Letter addresses a new method to analyze the neuronal population oscillations with empirical mode decomposition (EMD). Following EMD of neuronal oscillation, a series of intrinsic mode functions (IMFs) are obtained, then Hilbert transform of IMFs can be used to extract the instantaneous time frequency structure of neuronal oscillation. The method is applied to analyze the neuronal oscillation in the hippocampus of epileptic rats in vivo, the results show the neuronal oscillations have different descriptions during the pre-ictal, seizure onset and ictal periods of the epileptic EEG at the different frequency band. This new method is very helpful to provide a view for the temporal structure of neural oscillation.

Decomposition and extraction: a new framework for visual classification.

PubMed

Fang, Yuqiang; Chen, Qiang; Sun, Lin; Dai, Bin; Yan, Shuicheng

2014-08-01

In this paper, we present a novel framework for visual classification based on hierarchical image decomposition and hybrid midlevel feature extraction. Unlike most midlevel feature learning methods, which focus on the process of coding or pooling, we emphasize that the mechanism of image composition also strongly influences the feature extraction. To effectively explore the image content for the feature extraction, we model a multiplicity feature representation mechanism through meaningful hierarchical image decomposition followed by a fusion step. In particularly, we first propose a new hierarchical image decomposition approach in which each image is decomposed into a series of hierarchical semantical components, i.e, the structure and texture images. Then, different feature extraction schemes can be adopted to match the decomposed structure and texture processes in a dissociative manner. Here, two schemes are explored to produce property related feature representations. One is based on a single-stage network over hand-crafted features and the other is based on a multistage network, which can learn features from raw pixels automatically. Finally, those multiple midlevel features are incorporated by solving a multiple kernel learning task. Extensive experiments are conducted on several challenging data sets for visual classification, and experimental results demonstrate the effectiveness of the proposed method.

Azole energetic materials: Initial mechanisms for the energy release from electronical excited nitropyrazoles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yuan, Bing; Yu, Zijun; Bernstein, Elliot R., E-mail: erb@lamar.Colostate.edu

2014-01-21

Decomposition of energetic material 3,4-dinitropyrazole (DNP) and two model molecules 4-nitropyrazole and 1-nitropyrazole is investigated both theoretically and experimentally. The initial decomposition mechanisms for these three nitropyrazoles are explored with complete active space self-consistent field (CASSCF) level. The NO molecule is observed as an initial decomposition product from all three materials subsequent to UV excitation. Observed NO products are rotationally cold (<50 K) for all three systems. The vibrational temperature of the NO product from DNP is (3850 ± 50) K, 1350 K hotter than that of the two model species. Potential energy surface calculations at the CASSCF(12,8)/6-31+G(d) level illustratemore » that conical intersections plays an essential role in the decomposition mechanism. Electronically excited S{sub 2} nitropyraozles can nonradiatively relax to lower electronic states through (S{sub 2}/S{sub 1}){sub CI} and (S{sub 1}/S{sub 0}){sub CI} conical intersection and undergo a nitro-nitrite isomerization to generate NO product either in the S{sub 1} state or S{sub 0} state. In model systems, NO is generated in the S{sub 1} state, while in the energetic material DNP, NO is produced on the ground state surface, as the S{sub 1} decomposition pathway is energetically unavailable. The theoretically predicted mechanism is consistent with the experimental results, as DNP decomposes in a lower electronic state than do the model systems and thus the vibrational energy in the NO product from DNP should be hotter than from the model systems. The observed rotational energy distributions for NO are consistent with the final structures of the respective transition states for each molecule.« less

Low-dimensional representation of near-wall dynamics in shear flows, with implications to wall-models.

PubMed

Schmid, P J; Sayadi, T

2017-03-13

The dynamics of coherent structures near the wall of a turbulent boundary layer is investigated with the aim of a low-dimensional representation of its essential features. Based on a triple decomposition into mean, coherent and incoherent motion and a dynamic mode decomposition to recover statistical information about the incoherent part of the flow field, a driven linear system coupling first- and second-order moments of the coherent structures is derived and analysed. The transfer function for this system, evaluated for a wall-parallel plane, confirms a strong bias towards streamwise elongated structures, and is proposed as an 'impedance' boundary condition which replaces the bulk of the transport between the coherent velocity field and the coherent Reynolds stresses, thus acting as a wall model for large-eddy simulations (LES). It is interesting to note that the boundary condition is non-local in space and time. The extracted model is capable of reproducing the principal Reynolds stress components for the pretransitional, transitional and fully turbulent boundary layer.This article is part of the themed issue 'Toward the development of high-fidelity models of wall turbulence at large Reynolds number'. © 2017 The Author(s).

Projection decomposition algorithm for dual-energy computed tomography via deep neural network.

PubMed

Xu, Yifu; Yan, Bin; Chen, Jian; Zeng, Lei; Li, Lei

2018-03-15

Dual-energy computed tomography (DECT) has been widely used to improve identification of substances from different spectral information. Decomposition of the mixed test samples into two materials relies on a well-calibrated material decomposition function. This work aims to establish and validate a data-driven algorithm for estimation of the decomposition function. A deep neural network (DNN) consisting of two sub-nets is proposed to solve the projection decomposition problem. The compressing sub-net, substantially a stack auto-encoder (SAE), learns a compact representation of energy spectrum. The decomposing sub-net with a two-layer structure fits the nonlinear transform between energy projection and basic material thickness. The proposed DNN not only delivers image with lower standard deviation and higher quality in both simulated and real data, and also yields the best performance in cases mixed with photon noise. Moreover, DNN costs only 0.4 s to generate a decomposition solution of 360 × 512 size scale, which is about 200 times faster than the competing algorithms. The DNN model is applicable to the decomposition tasks with different dual energies. Experimental results demonstrated the strong function fitting ability of DNN. Thus, the Deep learning paradigm provides a promising approach to solve the nonlinear problem in DECT.

Reactivity continuum modeling of leaf, root, and wood decomposition across biomes

NASA Astrophysics Data System (ADS)

Koehler, Birgit; Tranvik, Lars J.

2015-07-01

Large carbon dioxide amounts are released to the atmosphere during organic matter decomposition. Yet the large-scale and long-term regulation of this critical process in global carbon cycling by litter chemistry and climate remains poorly understood. We used reactivity continuum (RC) modeling to analyze the decadal data set of the "Long-term Intersite Decomposition Experiment," in which fine litter and wood decomposition was studied in eight biome types (224 time series). In 32 and 46% of all sites the litter content of the acid-unhydrolyzable residue (AUR, formerly referred to as lignin) and the AUR/nitrogen ratio, respectively, retarded initial decomposition rates. This initial rate-retarding effect generally disappeared within the first year of decomposition, and rate-stimulating effects of nutrients and a rate-retarding effect of the carbon/nitrogen ratio became more prevalent. For needles and leaves/grasses, the influence of climate on decomposition decreased over time. For fine roots, the climatic influence was initially smaller but increased toward later-stage decomposition. The climate decomposition index was the strongest climatic predictor of decomposition. The similar variability in initial decomposition rates across litter categories as across biome types suggested that future changes in decomposition may be dominated by warming-induced changes in plant community composition. In general, the RC model parameters successfully predicted independent decomposition data for the different litter-biome combinations (196 time series). We argue that parameterization of large-scale decomposition models with RC model parameters, as opposed to the currently common discrete multiexponential models, could significantly improve their mechanistic foundation and predictive accuracy across climate zones and litter categories.

Decomposition analysis of water footprint changes in a water-limited river basin: a case study of the Haihe River basin, China

NASA Astrophysics Data System (ADS)

Zhi, Y.; Yang, Z. F.; Yin, X. A.

2014-05-01

Decomposition analysis of water footprint (WF) changes, or assessing the changes in WF and identifying the contributions of factors leading to the changes, is important to water resource management. Instead of focusing on WF from the perspective of administrative regions, we built a framework in which the input-output (IO) model, the structural decomposition analysis (SDA) model and the generating regional IO tables (GRIT) method are combined to implement decomposition analysis for WF in a river basin. This framework is illustrated in the WF in Haihe River basin (HRB) from 2002 to 2007, which is a typical water-limited river basin. It shows that the total WF in the HRB increased from 4.3 × 1010 m3 in 2002 to 5.6 × 1010 m3 in 2007, and the agriculture sector makes the dominant contribution to the increase. Both the WF of domestic products (internal) and the WF of imported products (external) increased, and the proportion of external WF rose from 29.1 to 34.4%. The technological effect was the dominant contributor to offsetting the increase of WF. However, the growth of WF caused by the economic structural effect and the scale effect was greater, so the total WF increased. This study provides insights about water challenges in the HRB and proposes possible strategies for the future, and serves as a reference for WF management and policy-making in other water-limited river basins.

Towards reduced order modelling for predicting the dynamics of coherent vorticity structures within wind turbine wakes.

PubMed

Debnath, M; Santoni, C; Leonardi, S; Iungo, G V

2017-04-13

The dynamics of the velocity field resulting from the interaction between the atmospheric boundary layer and a wind turbine array can affect significantly the performance of a wind power plant and the durability of wind turbines. In this work, dynamics in wind turbine wakes and instabilities of helicoidal tip vortices are detected and characterized through modal decomposition techniques. The dataset under examination consists of snapshots of the velocity field obtained from large-eddy simulations (LES) of an isolated wind turbine, for which aerodynamic forcing exerted by the turbine blades on the atmospheric boundary layer is mimicked through the actuator line model. Particular attention is paid to the interaction between the downstream evolution of the helicoidal tip vortices and the alternate vortex shedding from the turbine tower. The LES dataset is interrogated through different modal decomposition techniques, such as proper orthogonal decomposition and dynamic mode decomposition. The dominant wake dynamics are selected for the formulation of a reduced order model, which consists in a linear time-marching algorithm where temporal evolution of flow dynamics is obtained from the previous temporal realization multiplied by a time-invariant operator.This article is part of the themed issue 'Wind energy in complex terrains'. © 2017 The Author(s).

Atomic decomposition of the protein solvation free energy and its application to amyloid-beta protein in water

NASA Astrophysics Data System (ADS)

Chong, Song-Ho; Ham, Sihyun

2011-07-01

We report the development of an atomic decomposition method of the protein solvation free energy in water, which ascribes global change in the solvation free energy to local changes in protein conformation as well as in hydration structure. So far, empirical decomposition analyses based on simple continuum solvation models have prevailed in the study of protein-protein interactions, protein-ligand interactions, as well as in developing scoring functions for computer-aided drug design. However, the use of continuum solvation model suffers serious drawbacks since it yields the protein free energy landscape which is quite different from that of the explicit solvent model and since it does not properly account for the non-polar hydrophobic effects which play a crucial role in biological processes in water. Herein, we develop an exact and general decomposition method of the solvation free energy that overcomes these hindrances. We then apply this method to elucidate the molecular origin for the solvation free energy change upon the conformational transitions of 42-residue amyloid-beta protein (Aβ42) in water, whose aggregation has been implicated as a primary cause of Alzheimer's disease. We address why Aβ42 protein exhibits a great propensity to aggregate when transferred from organic phase to aqueous phase.

Temporal dynamics of phosphorus during aquatic and terrestrial litter decomposition in an alpine forest.

PubMed

Peng, Yan; Yang, Wanqin; Yue, Kai; Tan, Bo; Huang, Chunping; Xu, Zhenfeng; Ni, Xiangyin; Zhang, Li; Wu, Fuzhong

2018-06-17

Plant litter decomposition in forested soil and watershed is an important source of phosphorus (P) for plants in forest ecosystems. Understanding P dynamics during litter decomposition in forested aquatic and terrestrial ecosystems will be of great importance for better understanding nutrient cycling across forest landscape. However, despite massive studies addressing litter decomposition have been carried out, generalizations across aquatic and terrestrial ecosystems regarding the temporal dynamics of P loss during litter decomposition remain elusive. We conducted a two-year field experiment using litterbag method in both aquatic (streams and riparian zones) and terrestrial (forest floors) ecosystems in an alpine forest on the eastern Tibetan Plateau. By using multigroup comparisons of structural equation modeling (SEM) method with different litter mass-loss intervals, we explicitly assessed the direct and indirect effects of several biotic and abiotic drivers on P loss across different decomposition stages. The results suggested that (1) P concentration in decomposing litter showed similar patterns of early increase and later decrease across different species and ecosystems types; (2) P loss shared a common hierarchy of drivers across different ecosystems types, with litter chemical dynamics mainly having direct effects but environment and initial litter quality having both direct and indirect effects; (3) when assessing at the temporal scale, the effects of initial litter quality appeared to increase in late decomposition stages, while litter chemical dynamics showed consistent significant effects almost in all decomposition stages across aquatic and terrestrial ecosystems; (4) microbial diversity showed significant effects on P loss, but its effects were lower compared with other drivers. Our results highlight the importance of including spatiotemporal variations and indicate the possibility of integrating aquatic and terrestrial decomposition into a common framework for future construction of models that account for the temporal dynamics of P in decomposing litter. Copyright © 2018 Elsevier B.V. All rights reserved.

Temperature Responses of Soil Organic Matter Components With Varying Recalcitrance

NASA Astrophysics Data System (ADS)

Simpson, M. J.; Feng, X.

2007-12-01

The response of soil organic matter (SOM) to global warming remains unclear partly due to the chemical heterogeneity of SOM composition. In this study, the decomposition of SOM from two grassland soils was investigated in a one-year laboratory incubation at six different temperatures. SOM was separated into solvent- extractable compounds, suberin- and cutin-derived compounds, and lignin monomers by solvent extraction, base hydrolysis, and CuO oxidation, respectively. These SOM components had distinct chemical structures and recalcitrance, and their decomposition was fitted by a two-pool exponential decay model. The stability of SOM components was assessed using geochemical parameters and kinetic parameters derived from model fitting. Lignin monomers exhibited much lower decay rates than solvent-extractable compounds and a relatively low percentage of lignin monomers partitioned into the labile SOM pool, which confirmed the generally accepted recalcitrance of lignin compounds. Suberin- and cutin-derived compounds had a poor fitting for the exponential decay model, and their recalcitrance was shown by the geochemical degradation parameter which stabilized during the incubation. The aliphatic components of suberin degraded faster than cutin-derived compounds, suggesting that cutin-derived compounds in the soil may be at a higher stage of degradation than suberin- derived compounds. The temperature sensitivity of decomposition, expressed as Q10, was derived from the relationship between temperature and SOM decay rates. SOM components exhibited varying temperature responses and the decomposition of the recalcitrant lignin monomers had much higher Q10 values than soil respiration or the solvent-extractable compounds decomposition. Our study shows that the decomposition of recalcitrant SOM is highly sensitive to temperature, more so than bulk soil mineralization. This observation suggests a potential acceleration in the degradation of the recalcitrant SOM pool with global warming.

Molecular C dynamics downstream: the biochemical decomposition sequence and its impact on soil organic matter structure and function.

PubMed

Grandy, A Stuart; Neff, Jason C

2008-10-15

Advances in spectroscopic and other chemical methods have greatly enhanced our ability to characterize soil organic matter chemistry. As a result, the molecular characteristics of soil C are now known for a range of ecosystems, soil types, and management intensities. Placing this knowledge into a broader ecological and management context is difficult, however, and remains one of the fundamental challenges of soil organic matter research. Here we present a conceptual model of molecular soil C dynamics to stimulate inter-disciplinary research into the ecological implications of molecular C turnover and its management- and process-level controls. Our model describes three properties of soil C dynamics: 1) soil size fractions have unique molecular patterns that reflect varying degrees of biological and physical control over decomposition; 2) there is a common decomposition sequence independent of plant inputs or other ecosystem properties; and 3) molecular decomposition sequences, although consistent, are not uniform and can be altered by processes that accelerate or slow the microbial transformation of specific molecules. The consequences of this model include several key points. First, lignin presents a constraint to decomposition of plant litter and particulate C (>53 microm) but exerts little influence on more stable mineral-associated soil fractions <53 microm. Second, carbon stabilized onto mineral fractions has a distinct composition related more to microbially processed organic matter than to plant-related compounds. Third, disturbances, such as N fertilization and tillage, which alter decomposition rates, can have "downstream effects"; that is, a disturbance that directly alters the molecular dynamics of particulate C may have a series of indirect effects on C stabilization in silt and clay fractions.

Self-similar pyramidal structures and signal reconstruction

NASA Astrophysics Data System (ADS)

Benedetto, John J.; Leon, Manuel; Saliani, Sandra

1998-03-01

Pyramidal structures are defined which are locally a combination of low and highpass filtering. The structures are analogous to but different from wavelet packet structures. In particular, new frequency decompositions are obtained; and these decompositions can be parameterized to establish a correspondence with a large class of Cantor sets. Further correspondences are then established to relate such frequency decompositions with more general self- similarities. The role of the filters in defining these pyramidal structures gives rise to signal reconstruction algorithms, and these, in turn, are used in the analysis of speech data.

Decomposition of metabolic network into functional modules based on the global connectivity structure of reaction graph.

PubMed

Ma, Hong-Wu; Zhao, Xue-Ming; Yuan, Ying-Jin; Zeng, An-Ping

2004-08-12

Metabolic networks are organized in a modular, hierarchical manner. Methods for a rational decomposition of the metabolic network into relatively independent functional subsets are essential to better understand the modularity and organization principle of a large-scale, genome-wide network. Network decomposition is also necessary for functional analysis of metabolism by pathway analysis methods that are often hampered by the problem of combinatorial explosion due to the complexity of metabolic network. Decomposition methods proposed in literature are mainly based on the connection degree of metabolites. To obtain a more reasonable decomposition, the global connectivity structure of metabolic networks should be taken into account. In this work, we use a reaction graph representation of a metabolic network for the identification of its global connectivity structure and for decomposition. A bow-tie connectivity structure similar to that previously discovered for metabolite graph is found also to exist in the reaction graph. Based on this bow-tie structure, a new decomposition method is proposed, which uses a distance definition derived from the path length between two reactions. An hierarchical classification tree is first constructed from the distance matrix among the reactions in the giant strong component of the bow-tie structure. These reactions are then grouped into different subsets based on the hierarchical tree. Reactions in the IN and OUT subsets of the bow-tie structure are subsequently placed in the corresponding subsets according to a 'majority rule'. Compared with the decomposition methods proposed in literature, ours is based on combined properties of the global network structure and local reaction connectivity rather than, primarily, on the connection degree of metabolites. The method is applied to decompose the metabolic network of Escherichia coli. Eleven subsets are obtained. More detailed investigations of the subsets show that reactions in the same subset are really functionally related. The rational decomposition of metabolic networks, and subsequent studies of the subsets, make it more amenable to understand the inherent organization and functionality of metabolic networks at the modular level. http://genome.gbf.de/bioinformatics/

Structure and information in spatial segregation

PubMed Central

2017-01-01

Ethnoracial residential segregation is a complex, multiscalar phenomenon with immense moral and economic costs. Modeling the structure and dynamics of segregation is a pressing problem for sociology and urban planning, but existing methods have limitations. In this paper, we develop a suite of methods, grounded in information theory, for studying the spatial structure of segregation. We first advance existing profile and decomposition methods by posing two related regionalization methods, which allow for profile curves with nonconstant spatial scale and decomposition analysis with nonarbitrary areal units. We then formulate a measure of local spatial scale, which may be used for both detailed, within-city analysis and intercity comparisons. These methods highlight detailed insights in the structure and dynamics of urban segregation that would be otherwise easy to miss or difficult to quantify. They are computationally efficient, applicable to a broad range of study questions, and freely available in open source software. PMID:29078323

Structure and information in spatial segregation.

PubMed

Chodrow, Philip S

2017-10-31

Ethnoracial residential segregation is a complex, multiscalar phenomenon with immense moral and economic costs. Modeling the structure and dynamics of segregation is a pressing problem for sociology and urban planning, but existing methods have limitations. In this paper, we develop a suite of methods, grounded in information theory, for studying the spatial structure of segregation. We first advance existing profile and decomposition methods by posing two related regionalization methods, which allow for profile curves with nonconstant spatial scale and decomposition analysis with nonarbitrary areal units. We then formulate a measure of local spatial scale, which may be used for both detailed, within-city analysis and intercity comparisons. These methods highlight detailed insights in the structure and dynamics of urban segregation that would be otherwise easy to miss or difficult to quantify. They are computationally efficient, applicable to a broad range of study questions, and freely available in open source software. Published under the PNAS license.

Long-term power generation expansion planning with short-term demand response: Model, algorithms, implementation, and electricity policies

NASA Astrophysics Data System (ADS)

Lohmann, Timo

Electric sector models are powerful tools that guide policy makers and stakeholders. Long-term power generation expansion planning models are a prominent example and determine a capacity expansion for an existing power system over a long planning horizon. With the changes in the power industry away from monopolies and regulation, the focus of these models has shifted to competing electric companies maximizing their profit in a deregulated electricity market. In recent years, consumers have started to participate in demand response programs, actively influencing electricity load and price in the power system. We introduce a model that features investment and retirement decisions over a long planning horizon of more than 20 years, as well as an hourly representation of day-ahead electricity markets in which sellers of electricity face buyers. This combination makes our model both unique and challenging to solve. Decomposition algorithms, and especially Benders decomposition, can exploit the model structure. We present a novel method that can be seen as an alternative to generalized Benders decomposition and relies on dynamic linear overestimation. We prove its finite convergence and present computational results, demonstrating its superiority over traditional approaches. In certain special cases of our model, all necessary solution values in the decomposition algorithms can be directly calculated and solving mathematical programming problems becomes entirely obsolete. This leads to highly efficient algorithms that drastically outperform their programming problem-based counterparts. Furthermore, we discuss the implementation of all tailored algorithms and the challenges from a modeling software developer's standpoint, providing an insider's look into the modeling language GAMS. Finally, we apply our model to the Texas power system and design two electricity policies motivated by the U.S. Environment Protection Agency's recently proposed CO2 emissions targets for the power sector.

Heterogeneous Tensor Decomposition for Clustering via Manifold Optimization.

PubMed

Sun, Yanfeng; Gao, Junbin; Hong, Xia; Mishra, Bamdev; Yin, Baocai

2016-03-01

Tensor clustering is an important tool that exploits intrinsically rich structures in real-world multiarray or Tensor datasets. Often in dealing with those datasets, standard practice is to use subspace clustering that is based on vectorizing multiarray data. However, vectorization of tensorial data does not exploit complete structure information. In this paper, we propose a subspace clustering algorithm without adopting any vectorization process. Our approach is based on a novel heterogeneous Tucker decomposition model taking into account cluster membership information. We propose a new clustering algorithm that alternates between different modes of the proposed heterogeneous tensor model. All but the last mode have closed-form updates. Updating the last mode reduces to optimizing over the multinomial manifold for which we investigate second order Riemannian geometry and propose a trust-region algorithm. Numerical experiments show that our proposed algorithm compete effectively with state-of-the-art clustering algorithms that are based on tensor factorization.

Ground cross-modal impedance as a tool for analyzing ground/plate interaction and ground wave propagation.

PubMed

Grau, L; Laulagnet, B

2015-05-01

An analytical approach is investigated to model ground-plate interaction based on modal decomposition and the two-dimensional Fourier transform. A finite rectangular plate subjected to flexural vibration is coupled with the ground and modeled with the Kirchhoff hypothesis. A Navier equation represents the stratified ground, assumed infinite in the x- and y-directions and free at the top surface. To obtain an analytical solution, modal decomposition is applied to the structure and a Fourier Transform is applied to the ground. The result is a new tool for analyzing ground-plate interaction to resolve this problem: ground cross-modal impedance. It allows quantifying the added-stiffness, added-mass, and added-damping from the ground to the structure. Similarity with the parallel acoustic problem is highlighted. A comparison between the theory and the experiment shows good matching. Finally, specific cases are investigated, notably the influence of layer depth on plate vibration.

Generalized neurofuzzy network modeling algorithms using Bézier-Bernstein polynomial functions and additive decomposition.

PubMed

Hong, X; Harris, C J

2000-01-01

This paper introduces a new neurofuzzy model construction algorithm for nonlinear dynamic systems based upon basis functions that are Bézier-Bernstein polynomial functions. This paper is generalized in that it copes with n-dimensional inputs by utilising an additive decomposition construction to overcome the curse of dimensionality associated with high n. This new construction algorithm also introduces univariate Bézier-Bernstein polynomial functions for the completeness of the generalized procedure. Like the B-spline expansion based neurofuzzy systems, Bézier-Bernstein polynomial function based neurofuzzy networks hold desirable properties such as nonnegativity of the basis functions, unity of support, and interpretability of basis function as fuzzy membership functions, moreover with the additional advantages of structural parsimony and Delaunay input space partition, essentially overcoming the curse of dimensionality associated with conventional fuzzy and RBF networks. This new modeling network is based on additive decomposition approach together with two separate basis function formation approaches for both univariate and bivariate Bézier-Bernstein polynomial functions used in model construction. The overall network weights are then learnt using conventional least squares methods. Numerical examples are included to demonstrate the effectiveness of this new data based modeling approach.

Neurocomputing strategies in decomposition based structural design

NASA Technical Reports Server (NTRS)

Szewczyk, Z.; Hajela, P.

1993-01-01

The present paper explores the applicability of neurocomputing strategies in decomposition based structural optimization problems. It is shown that the modeling capability of a backpropagation neural network can be used to detect weak couplings in a system, and to effectively decompose it into smaller, more tractable, subsystems. When such partitioning of a design space is possible, parallel optimization can be performed in each subsystem, with a penalty term added to its objective function to account for constraint violations in all other subsystems. Dependencies among subsystems are represented in terms of global design variables, and a neural network is used to map the relations between these variables and all subsystem constraints. A vector quantization technique, referred to as a z-Network, can effectively be used for this purpose. The approach is illustrated with applications to minimum weight sizing of truss structures with multiple design constraints.

Large herbivores affect forest ecosystem functions by altering the structure of dung beetle communities

NASA Astrophysics Data System (ADS)

Iida, Taichi; Soga, Masashi; Koike, Shinsuke

2018-04-01

Dramatic increases in populations of large mammalian herbivores have become a major ecological issue, particularly in the northern hemisphere, due to their substantial impacts on both animal and plant communities through processes such as grazing, browsing, and trampling. However, little is known about the consequences of these population explosions on ecosystem functions. Here, we experimentally investigated how the population density of sika deer (Cervus nippon) in temperate deciduous forest areas in Japan affected the decomposition of mammal dung by dung beetles, which is a key process in forest ecosystems. We measured a range of environmental variables (e.g., vegetation cover, soil hardness) and the dung decomposition rate, measured as the amount of deer dung decomposed during one week, and sampled dung beetles at 16 study sites with three different deer densities (high/intermediate/low). We then used structural equation modeling to investigate the relationships between deer density, environmental variables, the biomass of dung beetles (classified into small or large species), and the dung decomposition rate. We found that the biomass of small species increased with increasing deer density, whereas that of large species was not related to deer density. Furthermore, the dung decomposition rate was positively related to the biomass of small species but unrelated to that of large species. Overall, our results showed that an increase in deer density affects the decomposition rate of mammal dung by changing the structure of dung beetle communities (i.e., increasing the number of small dung beetles). Such an understanding of how increases in large herbivore populations affect ecosystem functions is important for accurately evaluating the ecological consequences of their overabundance and ultimately managing their populations appropriately.

Application of Lanczos vectors to control design of flexible structures

NASA Technical Reports Server (NTRS)

Craig, Roy R., Jr.; Su, Tzu-Jeng

1990-01-01

This report covers research conducted during the first year of the two-year grant. The research, entitled 'Application of Lanczos Vectors to Control Design of Flexible Structures' concerns various ways to obtain reduced-order mathematical models for use in dynamic response analyses and in control design studies. This report summarizes research described in several reports and papers that were written under this contract. Extended abstracts are presented for technical papers covering the following topics: controller reduction by preserving impulse response energy; substructuring decomposition and controller synthesis; model reduction methods for structural control design; and recent literature on structural modeling, identification, and analysis.

A test of the hierarchical model of litter decomposition.

PubMed

Bradford, Mark A; Veen, G F Ciska; Bonis, Anne; Bradford, Ella M; Classen, Aimee T; Cornelissen, J Hans C; Crowther, Thomas W; De Long, Jonathan R; Freschet, Gregoire T; Kardol, Paul; Manrubia-Freixa, Marta; Maynard, Daniel S; Newman, Gregory S; Logtestijn, Richard S P; Viketoft, Maria; Wardle, David A; Wieder, William R; Wood, Stephen A; van der Putten, Wim H

2017-12-01

Our basic understanding of plant litter decomposition informs the assumptions underlying widely applied soil biogeochemical models, including those embedded in Earth system models. Confidence in projected carbon cycle-climate feedbacks therefore depends on accurate knowledge about the controls regulating the rate at which plant biomass is decomposed into products such as CO 2 . Here we test underlying assumptions of the dominant conceptual model of litter decomposition. The model posits that a primary control on the rate of decomposition at regional to global scales is climate (temperature and moisture), with the controlling effects of decomposers negligible at such broad spatial scales. Using a regional-scale litter decomposition experiment at six sites spanning from northern Sweden to southern France-and capturing both within and among site variation in putative controls-we find that contrary to predictions from the hierarchical model, decomposer (microbial) biomass strongly regulates decomposition at regional scales. Furthermore, the size of the microbial biomass dictates the absolute change in decomposition rates with changing climate variables. Our findings suggest the need for revision of the hierarchical model, with decomposers acting as both local- and broad-scale controls on litter decomposition rates, necessitating their explicit consideration in global biogeochemical models.

Scoring of Decomposition: A Proposed Amendment to the Method When Using a Pig Model for Human Studies.

PubMed

Keough, Natalie; Myburgh, Jolandie; Steyn, Maryna

2017-07-01

Decomposition studies often use pigs as proxies for human cadavers. However, differences in decomposition sequences/rates relative to humans have not been scientifically examined. Descriptions of five main decomposition stages (humans) were developed and refined by Galloway and later by Megyesi. However, whether these changes/processes are alike in pigs is unclear. Any differences can have significant effects when pig models are used for human PMI estimation. This study compared human decomposition models to the changes observed in pigs. Twenty pigs (50-90 kg) were decomposed over five months and decompositional features recorded. Total body scores (TBS) were calculated. Significant differences were observed during early decomposition between pigs and humans. An amended scoring system to be used in future studies was developed. Standards for PMI estimation derived from porcine models may not directly apply to humans and may need adjustment. Porcine models, however, remain valuable to study variables influencing decomposition. © 2016 American Academy of Forensic Sciences.

Matching-centrality decomposition and the forecasting of new links in networks.

PubMed

Rohr, Rudolf P; Naisbit, Russell E; Mazza, Christian; Bersier, Louis-Félix

2016-02-10

Networks play a prominent role in the study of complex systems of interacting entities in biology, sociology, and economics. Despite this diversity, we demonstrate here that a statistical model decomposing networks into matching and centrality components provides a comprehensive and unifying quantification of their architecture. The matching term quantifies the assortative structure in which node makes links with which other node, whereas the centrality term quantifies the number of links that nodes make. We show, for a diverse set of networks, that this decomposition can provide a tight fit to observed networks. Then we provide three applications. First, we show that the model allows very accurate prediction of missing links in partially known networks. Second, when node characteristics are known, we show how the matching-centrality decomposition can be related to this external information. Consequently, it offers us a simple and versatile tool to explore how node characteristics explain network architecture. Finally, we demonstrate the efficiency and flexibility of the model to forecast the links that a novel node would create if it were to join an existing network. © 2016 The Author(s).

Matching–centrality decomposition and the forecasting of new links in networks

PubMed Central

Rohr, Rudolf P.; Naisbit, Russell E.; Mazza, Christian; Bersier, Louis-Félix

2016-01-01

Networks play a prominent role in the study of complex systems of interacting entities in biology, sociology, and economics. Despite this diversity, we demonstrate here that a statistical model decomposing networks into matching and centrality components provides a comprehensive and unifying quantification of their architecture. The matching term quantifies the assortative structure in which node makes links with which other node, whereas the centrality term quantifies the number of links that nodes make. We show, for a diverse set of networks, that this decomposition can provide a tight fit to observed networks. Then we provide three applications. First, we show that the model allows very accurate prediction of missing links in partially known networks. Second, when node characteristics are known, we show how the matching–centrality decomposition can be related to this external information. Consequently, it offers us a simple and versatile tool to explore how node characteristics explain network architecture. Finally, we demonstrate the efficiency and flexibility of the model to forecast the links that a novel node would create if it were to join an existing network. PMID:26842568

Automated analysis of biological oscillator models using mode decomposition.

PubMed

Konopka, Tomasz

2011-04-01

Oscillating signals produced by biological systems have shapes, described by their Fourier spectra, that can potentially reveal the mechanisms that generate them. Extracting this information from measured signals is interesting for the validation of theoretical models, discovery and classification of interaction types, and for optimal experiment design. An automated workflow is described for the analysis of oscillating signals. A software package is developed to match signal shapes to hundreds of a priori viable model structures defined by a class of first-order differential equations. The package computes parameter values for each model by exploiting the mode decomposition of oscillating signals and formulating the matching problem in terms of systems of simultaneous polynomial equations. On the basis of the computed parameter values, the software returns a list of models consistent with the data. In validation tests with synthetic datasets, it not only shortlists those model structures used to generate the data but also shows that excellent fits can sometimes be achieved with alternative equations. The listing of all consistent equations is indicative of how further invalidation might be achieved with additional information. When applied to data from a microarray experiment on mice, the procedure finds several candidate model structures to describe interactions related to the circadian rhythm. This shows that experimental data on oscillators is indeed rich in information about gene regulation mechanisms. The software package is available at http://babylone.ulb.ac.be/autoosc/.

ORCHIMIC (v1.0), a microbe-mediated model for soil organic matter decomposition

NASA Astrophysics Data System (ADS)

Huang, Ye; Guenet, Bertrand; Ciais, Philippe; Janssens, Ivan A.; Soong, Jennifer L.; Wang, Yilong; Goll, Daniel; Blagodatskaya, Evgenia; Huang, Yuanyuan

2018-06-01

The role of soil microorganisms in regulating soil organic matter (SOM) decomposition is of primary importance in the carbon cycle, in particular in the context of global change. Modeling soil microbial community dynamics to simulate its impact on soil gaseous carbon (C) emissions and nitrogen (N) mineralization at large spatial scales is a recent research field with the potential to improve predictions of SOM responses to global climate change. In this study we present a SOM model called ORCHIMIC, which utilizes input data that are consistent with those of global vegetation models. ORCHIMIC simulates the decomposition of SOM by explicitly accounting for enzyme production and distinguishing three different microbial functional groups: fresh organic matter (FOM) specialists, SOM specialists, and generalists, while also implicitly accounting for microbes that do not produce extracellular enzymes, i.e., cheaters. ORCHIMIC and two other organic matter decomposition models, CENTURY (based on first-order kinetics and representative of the structure of most current global soil carbon models) and PRIM (with FOM accelerating the decomposition rate of SOM), were calibrated to reproduce the observed respiration fluxes of FOM and SOM from the incubation experiments of Blagodatskaya et al. (2014). Among the three models, ORCHIMIC was the only one that effectively captured both the temporal dynamics of the respiratory fluxes and the magnitude of the priming effect observed during the incubation experiment. ORCHIMIC also effectively reproduced the temporal dynamics of microbial biomass. We then applied different idealized changes to the model input data, i.e., a 5 K stepwise increase of temperature and/or a doubling of plant litter inputs. Under 5 K warming conditions, ORCHIMIC predicted a 0.002 K-1 decrease in the C use efficiency (defined as the ratio of C allocated to microbial growth to the sum of C allocated to growth and respiration) and a 3 % loss of SOC. Under the double litter input scenario, ORCHIMIC predicted a doubling of microbial biomass, while SOC stock increased by less than 1 % due to the priming effect. This limited increase in SOC stock contrasted with the proportional increase in SOC stock as modeled by the conventional SOC decomposition model (CENTURY), which can not reproduce the priming effect. If temperature increased by 5 K and litter input was doubled, ORCHIMIC predicted almost the same loss of SOC as when only temperature was increased. These tests suggest that the responses of SOC stock to warming and increasing input may differ considerably from those simulated by conventional SOC decomposition models when microbial dynamics are included. The next step is to incorporate the ORCHIMIC model into a global vegetation model to perform simulations for representative sites and future scenarios.

First determination of volume changes and enthalpies of the high-pressure decomposition reaction of the structure H methane hydrate to the cubic structure I methane hydrate and fluid methane.

PubMed

Ogienko, Andrey G; Tkacz, Marek; Manakov, Andrey Yu; Lipkowski, Janusz

2007-11-08

Pressure-temperature (P-T) conditions of the decomposition reaction of the structure H high-pressure methane hydrate to the cubic structure I methane hydrate and fluid methane were studied with a piston-cylinder apparatus at room temperature. For the first time, volume changes accompanying this reaction were determined. With the use of the Clausius-Clapeyron equation the enthalpies of the decomposition reaction of the structure H high-pressure methane hydrate to the cubic structure I methane hydrate and fluid methane have been calculated.

Integrated control/structure optimization by multilevel decomposition

NASA Technical Reports Server (NTRS)

Zeiler, Thomas A.; Gilbert, Michael G.

1990-01-01

A method for integrated control/structure optimization by multilevel decomposition is presented. It is shown that several previously reported methods were actually partial decompositions wherein only the control was decomposed into a subsystem design. One of these partially decomposed problems was selected as a benchmark example for comparison. The system is fully decomposed into structural and control subsystem designs and an improved design is produced. Theory, implementation, and results for the method are presented and compared with the benchmark example.

Distributed Damage Estimation for Prognostics based on Structural Model Decomposition

NASA Technical Reports Server (NTRS)

Daigle, Matthew; Bregon, Anibal; Roychoudhury, Indranil

2011-01-01

Model-based prognostics approaches capture system knowledge in the form of physics-based models of components, and how they fail. These methods consist of a damage estimation phase, in which the health state of a component is estimated, and a prediction phase, in which the health state is projected forward in time to determine end of life. However, the damage estimation problem is often multi-dimensional and computationally intensive. We propose a model decomposition approach adapted from the diagnosis community, called possible conflicts, in order to both improve the computational efficiency of damage estimation, and formulate a damage estimation approach that is inherently distributed. Local state estimates are combined into a global state estimate from which prediction is performed. Using a centrifugal pump as a case study, we perform a number of simulation-based experiments to demonstrate the approach.

Phase decomposition and ordering in Ni-11.3 at.% Ti studied with atom probe tomography.

PubMed

Al-Kassab, T; Kompatscher, M; Kirchheim, R; Kostorz, G; Schönfeld, B

2014-09-01

The decomposition behavior of Ni-rich Ni-Ti was reassessed using Tomographic Atom Probe (TAP) and Laser Assisted Wide Angle Tomographic Atom Probe. Single crystalline specimens of Ni-11.3 at.% Ti were investigated, the states selected from the decomposition path were the metastable γ″ and γ' states introduced on the basis of small-angle neutron scattering (SANS) and the two-phase model for evaluation. The composition values of the precipitates in these states could not be confirmed by APT data as the interface of the ordered precipitates may not be neglected. The present results rather suggest to apply a three-phase model for the interpretation of SANS measurements, in which the width of the interface remains nearly unchanged and the L12 structure close to 3:1 stoichiometry is maintained in the core of the precipitates from the γ″ to the γ' state. Copyright © 2014 Elsevier Ltd. All rights reserved.

Molecular Theory of Detonation Initiation: Insight from First Principles Modeling of the Decomposition Mechanisms of Organic Nitro Energetic Materials.

PubMed

Tsyshevsky, Roman V; Sharia, Onise; Kuklja, Maija M

2016-02-19

This review presents a concept, which assumes that thermal decomposition processes play a major role in defining the sensitivity of organic energetic materials to detonation initiation. As a science and engineering community we are still far away from having a comprehensive molecular detonation initiation theory in a widely agreed upon form. However, recent advances in experimental and theoretical methods allow for a constructive and rigorous approach to design and test the theory or at least some of its fundamental building blocks. In this review, we analyzed a set of select experimental and theoretical articles, which were augmented by our own first principles modeling and simulations, to reveal new trends in energetic materials and to refine known existing correlations between their structures, properties, and functions. Our consideration is intentionally limited to the processes of thermally stimulated chemical reactions at the earliest stage of decomposition of molecules and materials containing defects.

Molecular Theory of Detonation Initiation: Insight from First Principles Modeling of the Decomposition Mechanisms of Organic Nitro Energetic Materials

DOE PAGES

Tsyshevsky, Roman; Sharia, Onise; Kuklja, Maija

2016-02-19

Our review presents a concept, which assumes that thermal decomposition processes play a major role in defining the sensitivity of organic energetic materials to detonation initiation. As a science and engineering community we are still far away from having a comprehensive molecular detonation initiation theory in a widely agreed upon form. However, recent advances in experimental and theoretical methods allow for a constructive and rigorous approach to design and test the theory or at least some of its fundamental building blocks. In this review, we analyzed a set of select experimental and theoretical articles, which were augmented by our ownmore » first principles modeling and simulations, to reveal new trends in energetic materials and to refine known existing correlations between their structures, properties, and functions. Lastly, our consideration is intentionally limited to the processes of thermally stimulated chemical reactions at the earliest stage of decomposition of molecules and materials containing defects.« less

Factors Affecting Regional Per-Capita Carbon Emissions in China Based on an LMDI Factor Decomposition Model

PubMed Central

Dong, Feng; Long, Ruyin; Chen, Hong; Li, Xiaohui; Yang, Qingliang

2013-01-01

China is considered to be the main carbon producer in the world. The per-capita carbon emissions indicator is an important measure of the regional carbon emissions situation. This study used the LMDI factor decomposition model–panel co-integration test two-step method to analyze the factors that affect per-capita carbon emissions. The main results are as follows. (1) During 1997, Eastern China, Central China, and Western China ranked first, second, and third in the per-capita carbon emissions, while in 2009 the pecking order changed to Eastern China, Western China, and Central China. (2) According to the LMDI decomposition results, the key driver boosting the per-capita carbon emissions in the three economic regions of China between 1997 and 2009 was economic development, and the energy efficiency was much greater than the energy structure after considering their effect on restraining increased per-capita carbon emissions. (3) Based on the decomposition, the factors that affected per-capita carbon emissions in the panel co-integration test showed that Central China had the best energy structure elasticity in its regional per-capita carbon emissions. Thus, Central China was ranked first for energy efficiency elasticity, while Western China was ranked first for economic development elasticity. PMID:24353753

The generalized Hill model: A kinematic approach towards active muscle contraction

NASA Astrophysics Data System (ADS)

Göktepe, Serdar; Menzel, Andreas; Kuhl, Ellen

2014-12-01

Excitation-contraction coupling is the physiological process of converting an electrical stimulus into a mechanical response. In muscle, the electrical stimulus is an action potential and the mechanical response is active contraction. The classical Hill model characterizes muscle contraction though one contractile element, activated by electrical excitation, and two non-linear springs, one in series and one in parallel. This rheology translates into an additive decomposition of the total stress into a passive and an active part. Here we supplement this additive decomposition of the stress by a multiplicative decomposition of the deformation gradient into a passive and an active part. We generalize the one-dimensional Hill model to the three-dimensional setting and constitutively define the passive stress as a function of the total deformation gradient and the active stress as a function of both the total deformation gradient and its active part. We show that this novel approach combines the features of both the classical stress-based Hill model and the recent active-strain models. While the notion of active stress is rather phenomenological in nature, active strain is micro-structurally motivated, physically measurable, and straightforward to calibrate. We demonstrate that our model is capable of simulating excitation-contraction coupling in cardiac muscle with its characteristic features of wall thickening, apical lift, and ventricular torsion.

Exploring Patterns of Soil Organic Matter Decomposition with Students through the Global Decomposition Project (GDP) and the Interactive Model of Leaf Decomposition (IMOLD)

NASA Astrophysics Data System (ADS)

Steiner, S. M.; Wood, J. H.

2015-12-01

As decomposition rates are affected by climate change, understanding crucial soil interactions that affect plant growth and decomposition becomes a vital part of contributing to the students' knowledge base. The Global Decomposition Project (GDP) is designed to introduce and educate students about soil organic matter and decomposition through a standardized protocol for collecting, reporting, and sharing data. The Interactive Model of Leaf Decomposition (IMOLD) utilizes animations and modeling to learn about the carbon cycle, leaf anatomy, and the role of microbes in decomposition. Paired together, IMOLD teaches the background information and allows simulation of numerous scenarios, and the GDP is a data collection protocol that allows students to gather usable measurements of decomposition in the field. Our presentation will detail how the GDP protocol works, how to obtain or make the materials needed, and how results will be shared. We will also highlight learning objectives from the three animations of IMOLD, and demonstrate how students can experiment with different climates and litter types using the interactive model to explore a variety of decomposition scenarios. The GDP demonstrates how scientific methods can be extended to educate broader audiences, and data collected by students can provide new insight into global patterns of soil decomposition. Using IMOLD, students will gain a better understanding of carbon cycling in the context of litter decomposition, as well as learn to pose questions they can answer with an authentic computer model. Using the GDP protocols and IMOLD provide a pathway for scientists and educators to interact and reach meaningful education and research goals.

A novel hybrid decomposition-and-ensemble model based on CEEMD and GWO for short-term PM2.5 concentration forecasting

NASA Astrophysics Data System (ADS)

Niu, Mingfei; Wang, Yufang; Sun, Shaolong; Li, Yongwu

2016-06-01

To enhance prediction reliability and accuracy, a hybrid model based on the promising principle of "decomposition and ensemble" and a recently proposed meta-heuristic called grey wolf optimizer (GWO) is introduced for daily PM2.5 concentration forecasting. Compared with existing PM2.5 forecasting methods, this proposed model has improved the prediction accuracy and hit rates of directional prediction. The proposed model involves three main steps, i.e., decomposing the original PM2.5 series into several intrinsic mode functions (IMFs) via complementary ensemble empirical mode decomposition (CEEMD) for simplifying the complex data; individually predicting each IMF with support vector regression (SVR) optimized by GWO; integrating all predicted IMFs for the ensemble result as the final prediction by another SVR optimized by GWO. Seven benchmark models, including single artificial intelligence (AI) models, other decomposition-ensemble models with different decomposition methods and models with the same decomposition-ensemble method but optimized by different algorithms, are considered to verify the superiority of the proposed hybrid model. The empirical study indicates that the proposed hybrid decomposition-ensemble model is remarkably superior to all considered benchmark models for its higher prediction accuracy and hit rates of directional prediction.

Intrinsic Decomposition of The Stretch Tensor for Fibrous Media

NASA Astrophysics Data System (ADS)

Kellermann, David C.

2010-05-01

This paper presents a novel mechanism for the description of fibre reorientation based on the decomposition of the stretch tensor according to a given material's intrinsic constitutive properties. This approach avoids the necessity for fibre directors, structural tensors or specialised model such as the ideal fibre reinforced model, which are commonly applied to the analysis of fibre kinematics in the finite deformation of fibrous media for biomechanical problems. The proposed approach uses Intrinsic-Field Tensors (IFTs) that build upon the linear orthotropic theory presented in a previous paper entitled Strongly orthotropic continuum mechanics and finite element treatment. The intrinsic decomposition of the stretch tensor therein provides superior capacity to represent the intermediary kinematics driven by finite orthotropic ratios, where the benefits are predominantly expressed in cases of large deformation as is typical in the biomechanical studies. Satisfaction of requirements such as Material Frame-Indifference (MFI) and Euclidean objectivity are demonstrated here—these factors being necessary for the proposed IFTs to be valid tensorial quantities. The resultant tensors, initially for the simplest case of linear elasticity, are able to describe the same fibre reorientation as would the contemporary approaches such as with use of structural tensors and the like, while additionally being capable of showing results intermediary to classical isotropy and the infinitely orthotropic representations. This intermediary case is previously unreported.

Computer simulation of formation and decomposition of Au13 nanoparticles

NASA Astrophysics Data System (ADS)

Stishenko, P.; Svalova, A.

2017-08-01

To study the Ostwald ripening process of Au13 nanoparticles a two-scale model is constructed: analytical approximation of average nanoparticle energy as function of nanoparticle size and structural motive, and the Monte Carlo model of 1000 particles ensemble. Simulation results show different behavior of particles of different structural motives. The change of the distributions of atom coordination numbers during the Ostwald ripening process was observed. The nanoparticles of the equal size and shape with the face-centered cubic structure of the largest sizes appeared to be the most stable.

Studies in turbulence

NASA Technical Reports Server (NTRS)

Gatski, Thomas B. (Editor); Sarkar, Sutanu (Editor); Speziale, Charles G. (Editor)

1992-01-01

Various papers on turbulence are presented. Individual topics addressed include: modeling the dissipation rate in rotating turbulent flows, mapping closures for turbulent mixing and reaction, understanding turbulence in vortex dynamics, models for the structure and dynamics of near-wall turbulence, complexity of turbulence near a wall, proper orthogonal decomposition, propagating structures in wall-bounded turbulence flows. Also discussed are: constitutive relation in compressible turbulence, compressible turbulence and shock waves, direct simulation of compressible turbulence in a shear flow, structural genesis in wall-bounded turbulence flows, vortex lattice structure of turbulent shear slows, etiology of shear layer vortices, trilinear coordinates in fluid mechanics.

Integrated control/structure optimization by multilevel decomposition

NASA Technical Reports Server (NTRS)

Zeiler, Thomas A.; Gilbert, Michael G.

1990-01-01

A method for integrated control/structure optimization by multilevel decomposition is presented. It is shown that several previously reported methods were actually partial decompositions wherein only the control was decomposed into a subsystem design. One of these partially decomposed problems was selected as a benchmark example for comparison. The present paper fully decomposes the system into structural and control subsystem designs and produces an improved design. Theory, implementation, and results for the method are presented and compared with the benchmark example.

Active sites and mechanisms for H2O2 decomposition over Pd catalysts

PubMed Central

Plauck, Anthony; Stangland, Eric E.; Dumesic, James A.; Mavrikakis, Manos

2016-01-01

A combination of periodic, self-consistent density functional theory (DFT-GGA-PW91) calculations, reaction kinetics experiments on a SiO2-supported Pd catalyst, and mean-field microkinetic modeling are used to probe key aspects of H2O2 decomposition on Pd in the absence of cofeeding H2. We conclude that both Pd(111) and OH-partially covered Pd(100) surfaces represent the nature of the active site for H2O2 decomposition on the supported Pd catalyst reasonably well. Furthermore, all reaction flux in the closed catalytic cycle is predicted to flow through an O–O bond scission step in either H2O2 or OOH, followed by rapid H-transfer steps to produce the H2O and O2 products. The barrier for O–O bond scission is sensitive to Pd surface structure and is concluded to be the central parameter governing H2O2 decomposition activity. PMID:27006504

Analysis of Decomposition for Structure I Methane Hydrate by Molecular Dynamics Simulation

NASA Astrophysics Data System (ADS)

Wei, Na; Sun, Wan-Tong; Meng, Ying-Feng; Liu, An-Qi; Zhou, Shou-Wei; Guo, Ping; Fu, Qiang; Lv, Xin

2018-05-01

Under multi-nodes of temperatures and pressures, microscopic decomposition mechanisms of structure I methane hydrate in contact with bulk water molecules have been studied through LAMMPS software by molecular dynamics simulation. Simulation system consists of 482 methane molecules in hydrate and 3027 randomly distributed bulk water molecules. Through analyses of simulation results, decomposition number of hydrate cages, density of methane molecules, radial distribution function for oxygen atoms, mean square displacement and coefficient of diffusion of methane molecules have been studied. A significant result shows that structure I methane hydrate decomposes from hydrate-bulk water interface to hydrate interior. As temperature rises and pressure drops, the stabilization of hydrate will weaken, decomposition extent will go deep, and mean square displacement and coefficient of diffusion of methane molecules will increase. The studies can provide important meanings for the microscopic decomposition mechanisms analyses of methane hydrate.

Modeling diffusion control on organic matter decomposition in unsaturated soil pore space

NASA Astrophysics Data System (ADS)

Vogel, Laure; Pot, Valérie; Garnier, Patricia; Vieublé-Gonod, Laure; Nunan, Naoise; Raynaud, Xavier; Chenu, Claire

2014-05-01

Soil Organic Matter decomposition is affected by soil structure and water content, but field and laboratory studies about this issue conclude to highly variable outcomes. Variability could be explained by the discrepancy between the scale at which key processes occur and the measurements scale. We think that physical and biological interactions driving carbon transformation dynamics can be best understood at the pore scale. Because of the spatial disconnection between carbon sources and decomposers, the latter rely on nutrient transport unless they can actively move. In hydrostatic case, diffusion in soil pore space is thus thought to regulate biological activity. In unsaturated conditions, the heterogeneous distribution of water modifies diffusion pathways and rates, thus affects diffusion control on decomposition. Innovative imaging and modeling tools offer new means to address these effects. We have developed a new model based on the association between a 3D Lattice-Boltzmann Model and an adimensional decomposition module. We designed scenarios to study the impact of physical (geometry, saturation, decomposers position) and biological properties on decomposition. The model was applied on porous media with various morphologies. We selected three cubic images of 100 voxels side from µCT-scanned images of an undisturbed soil sample at 68µm resolution. We used LBM to perform phase separation and obtained water phase distributions at equilibrium for different saturation indices. We then simulated the diffusion of a simple soluble substrate (glucose) and its consumption by bacteria. The same mass of glucose was added as a pulse at the beginning of all simulations. Bacteria were placed in few voxels either regularly spaced or concentrated close to or far from the glucose source. We modulated physiological features of decomposers in order to weight them against abiotic conditions. We could evidence several effects creating unequal substrate access conditions for decomposers, hence inducing contrasted decomposition kinetics: position of bacteria relative to the substrate diffusion pathways, diffusion rate and hydraulic connectivity between bacteria and substrate source, local substrate enrichment due to restricted mass transfer. Physiological characteristics had a strong impact on decomposition only when glucose diffused easily but not when diffusion limitation prevailed. This suggests that carbon dynamics should not be considered to derive from decomposers' physiology alone but rather from the interactions of biological and physical processes at the microscale.

Structural Technology Evaluation and Analysis Program (STEAP). Delivery Order 0046: Multiscale Modeling of Composite Structures Subjected to Cyclic Loading

DTIC Science & Technology

2012-09-01

on transformation field analysis [19], proper orthogonal decomposition [63], eigenstrains [23], and others [1, 29, 39] have brought significant...commercial finite element software (Abaqus) along with the user material subroutine utility ( UMAT ) is employed to solve these problems. In this section...Symmetric Coefficients TFA: Transformation Field Analysis UMAT : User Material Subroutine

In situ Low-temperature Pair Distribution Function (PDF) Analysis of CH4 and CO2 Hydrates

NASA Astrophysics Data System (ADS)

Cladek, B.; Everett, M.; McDonnell, M.; Tucker, M.; Keffer, D.; Rawn, C.

2017-12-01

Gas hydrates occur in ocean floor and sub-surface permafrost deposits and are stable at moderate to high pressures and low temperatures. They are a clathrate structure composed of hydrogen bonded water cages that accommodate a wide variety of guest molecules. CO2 and CH4 hydrates both crystallize as the cubic sI hydrate and can form a solid solution. Natural gas hydrates are interesting as a potential methane source and for CO2 sequestration. Long-range diffraction studies on gas hydrates give valuable structural information but do not provide a detailed understanding of the disordered gas molecule interactions with the host lattice. In-situ low temperature total scattering experiments combined with pair distribution function (PDF) analysis are used to investigate the gas molecule motions and guest-cage interactions. CO2 and methane hydrates exhibit different decomposition behavior, and CO2 hydrate has a smaller lattice parameter despite it being a relatively larger molecule. Total scattering studies characterizing both the short- and long-range order simultaneously help to elucidate the structural source of these phenomena. Low temperature neutron total scattering data were collected using the Nanoscale Ordered MAterials Diffractometer (NOMAD) beamline at the Spallation Neutron Source (SNS) on CO2 and CH4 hydrates synthesized with D2O. Guest molecule motion within cages and interactions between gases and cages are investigated through the hydrate stability and decomposition regions. Data were collected from 2-80 K at a pressure of 55 mbar on CO2 and CH4 hydrates, and from 80-270 K at 25 bar on CH4 hydrate. The hydrate systems were modeled with classical molecular dynamic (MD) simulations to provide an analysis of the total energy into guest-guest, guest-host and host-host contributions. Combined Reitveld and Reverse Monte Carlo (RMC) structure refinement were used to fit models of the data. This combined modeling and simulation characterizes the effects of CO2 and CH4 as guest molecules on the structure and decomposition of gas hydrates. Structure and thermodynamic studies will provide a more comprehensive understanding of CO2-CH4 solid solutions, exchange kinetics, and implications on hydrate structure.

Canonical Structure and Orthogonality of Forces and Currents in Irreversible Markov Chains

NASA Astrophysics Data System (ADS)

Kaiser, Marcus; Jack, Robert L.; Zimmer, Johannes

2018-03-01

We discuss a canonical structure that provides a unifying description of dynamical large deviations for irreversible finite state Markov chains (continuous time), Onsager theory, and Macroscopic Fluctuation Theory (MFT). For Markov chains, this theory involves a non-linear relation between probability currents and their conjugate forces. Within this framework, we show how the forces can be split into two components, which are orthogonal to each other, in a generalised sense. This splitting allows a decomposition of the pathwise rate function into three terms, which have physical interpretations in terms of dissipation and convergence to equilibrium. Similar decompositions hold for rate functions at level 2 and level 2.5. These results clarify how bounds on entropy production and fluctuation theorems emerge from the underlying dynamical rules. We discuss how these results for Markov chains are related to similar structures within MFT, which describes hydrodynamic limits of such microscopic models.

A decentralized linear quadratic control design method for flexible structures

NASA Technical Reports Server (NTRS)

Su, Tzu-Jeng; Craig, Roy R., Jr.

1990-01-01

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.

Block matrix based LU decomposition to analyze kinetic damping in active plasma resonance spectroscopy

NASA Astrophysics Data System (ADS)

Roehl, Jan Hendrik; Oberrath, Jens

2016-09-01

``Active plasma resonance spectroscopy'' (APRS) is a widely used diagnostic method to measure plasma parameter like electron density. Measurements with APRS probes in plasmas of a few Pa typically show a broadening of the spectrum due to kinetic effects. To analyze the broadening a general kinetic model in electrostatic approximation based on functional analytic methods has been presented [ 1 ] . One of the main results is, that the system response function Y(ω) is given in terms of the matrix elements of the resolvent of the dynamic operator evaluated for values on the imaginary axis. To determine the response function of a specific probe the resolvent has to be approximated by a huge matrix which is given by a banded block structure. Due to this structure a block based LU decomposition can be implemented. It leads to a solution of Y(ω) which is given only by products of matrices of the inner block size. This LU decomposition allows to analyze the influence of kinetic effects on the broadening and saves memory and calculation time. Gratitude is expressed to the internal funding of Leuphana University.

Hidden discriminative features extraction for supervised high-order time series modeling.

PubMed

Nguyen, Ngoc Anh Thi; Yang, Hyung-Jeong; Kim, Sunhee

2016-11-01

In this paper, an orthogonal Tucker-decomposition-based extraction of high-order discriminative subspaces from a tensor-based time series data structure is presented, named as Tensor Discriminative Feature Extraction (TDFE). TDFE relies on the employment of category information for the maximization of the between-class scatter and the minimization of the within-class scatter to extract optimal hidden discriminative feature subspaces that are simultaneously spanned by every modality for supervised tensor modeling. In this context, the proposed tensor-decomposition method provides the following benefits: i) reduces dimensionality while robustly mining the underlying discriminative features, ii) results in effective interpretable features that lead to an improved classification and visualization, and iii) reduces the processing time during the training stage and the filtering of the projection by solving the generalized eigenvalue issue at each alternation step. Two real third-order tensor-structures of time series datasets (an epilepsy electroencephalogram (EEG) that is modeled as channel×frequency bin×time frame and a microarray data that is modeled as gene×sample×time) were used for the evaluation of the TDFE. The experiment results corroborate the advantages of the proposed method with averages of 98.26% and 89.63% for the classification accuracies of the epilepsy dataset and the microarray dataset, respectively. These performance averages represent an improvement on those of the matrix-based algorithms and recent tensor-based, discriminant-decomposition approaches; this is especially the case considering the small number of samples that are used in practice. Copyright © 2016 Elsevier Ltd. All rights reserved.

Decomposition of Fuzzy Soft Sets with Finite Value Spaces

PubMed Central

Jun, Young Bae

2014-01-01

The notion of fuzzy soft sets is a hybrid soft computing model that integrates both gradualness and parameterization methods in harmony to deal with uncertainty. The decomposition of fuzzy soft sets is of great importance in both theory and practical applications with regard to decision making under uncertainty. This study aims to explore decomposition of fuzzy soft sets with finite value spaces. Scalar uni-product and int-product operations of fuzzy soft sets are introduced and some related properties are investigated. Using t-level soft sets, we define level equivalent relations and show that the quotient structure of the unit interval induced by level equivalent relations is isomorphic to the lattice consisting of all t-level soft sets of a given fuzzy soft set. We also introduce the concepts of crucial threshold values and complete threshold sets. Finally, some decomposition theorems for fuzzy soft sets with finite value spaces are established, illustrated by an example concerning the classification and rating of multimedia cell phones. The obtained results extend some classical decomposition theorems of fuzzy sets, since every fuzzy set can be viewed as a fuzzy soft set with a single parameter. PMID:24558342

Decomposition of fuzzy soft sets with finite value spaces.

PubMed

Feng, Feng; Fujita, Hamido; Jun, Young Bae; Khan, Madad

2014-01-01

The notion of fuzzy soft sets is a hybrid soft computing model that integrates both gradualness and parameterization methods in harmony to deal with uncertainty. The decomposition of fuzzy soft sets is of great importance in both theory and practical applications with regard to decision making under uncertainty. This study aims to explore decomposition of fuzzy soft sets with finite value spaces. Scalar uni-product and int-product operations of fuzzy soft sets are introduced and some related properties are investigated. Using t-level soft sets, we define level equivalent relations and show that the quotient structure of the unit interval induced by level equivalent relations is isomorphic to the lattice consisting of all t-level soft sets of a given fuzzy soft set. We also introduce the concepts of crucial threshold values and complete threshold sets. Finally, some decomposition theorems for fuzzy soft sets with finite value spaces are established, illustrated by an example concerning the classification and rating of multimedia cell phones. The obtained results extend some classical decomposition theorems of fuzzy sets, since every fuzzy set can be viewed as a fuzzy soft set with a single parameter.

Urban-area extraction from polarimetric SAR image using combination of target decomposition and orientation angle

NASA Astrophysics Data System (ADS)

Zou, Bin; Lu, Da; Wu, Zhilu; Qiao, Zhijun G.

2016-05-01

The results of model-based target decomposition are the main features used to discriminate urban and non-urban area in polarimetric synthetic aperture radar (PolSAR) application. Traditional urban-area extraction methods based on modelbased target decomposition usually misclassified ground-trunk structure as urban-area or misclassified rotated urbanarea as forest. This paper introduces another feature named orientation angle to improve urban-area extraction scheme for the accurate mapping in urban by PolSAR image. The proposed method takes randomness of orientation angle into account for restriction of urban area first and, subsequently, implements rotation angle to improve results that oriented urban areas are recognized as double-bounce objects from volume scattering. ESAR L-band PolSAR data of the Oberpfaffenhofen Test Site Area was used to validate the proposed algorithm.

Modelling Behaviour of a Carbon Epoxy Composite Exposed to Fire: Part I-Characterisation of Thermophysical Properties.

PubMed

Tranchard, Pauline; Samyn, Fabienne; Duquesne, Sophie; Estèbe, Bruno; Bourbigot, Serge

2017-05-04

Thermophysical properties of a carbon-reinforced epoxy composite laminate (T700/M21 composite for aircraft structures) were evaluated using different innovative characterisation methods. Thermogravimetric Analysis (TGA), Simultaneous Thermal analysis (STA), Laser Flash analysis (LFA), and Fourier Transform Infrared (FTIR) analysis were used for measuring the thermal decomposition, the specific heat capacity, the anisotropic thermal conductivity of the composite, the heats of decomposition and the specific heat capacity of released gases. It permits to get input data to feed a three-dimensional (3D) model given the temperature profile and the mass loss obtained during well-defined fire scenarios (model presented in Part II of this paper). The measurements were optimised to get accurate data. The data also permit to create a public database on an aeronautical carbon fibre/epoxy composite for fire safety engineering.

Isospin decomposition of γ N → N * transitions within a dynamical coupled-channels model

DOE PAGES

Kamano, Hiroyuki; Nakamura, S. X.; Lee, T. -S. H.; ...

2016-07-07

Here, by extending the dynamical coupled-channels analysis performed in our previous work to include the available data of photoproduction of pi mesons off neutrons, the transition amplitudes for the photoexcitation of the neutron-to-nucleon resonances, γn → N*, at the resonance pole positions are determined. The combined fits to the data for both the proton- and neutron-target reactions also revise our results for the resonance pole positions and the γp → N* transition amplitudes. Our results allow an isospin decomposition of the γN → N* transition amplitudes for the isospin I = 1/2 N* resonances, which is necessary for testing hadronmore » structure models and gives crucial inputs for constructing models of neutrino-induced reactions in the nucleon resonance region.« less

Management intensity alters decomposition via biological pathways

USGS Publications Warehouse

Wickings, Kyle; Grandy, A. Stuart; Reed, Sasha; Cleveland, Cory

2011-01-01

Current conceptual models predict that changes in plant litter chemistry during decomposition are primarily regulated by both initial litter chemistry and the stage-or extent-of mass loss. Far less is known about how variations in decomposer community structure (e.g., resulting from different ecosystem management types) could influence litter chemistry during decomposition. Given the recent agricultural intensification occurring globally and the importance of litter chemistry in regulating soil organic matter storage, our objectives were to determine the potential effects of agricultural management on plant litter chemistry and decomposition rates, and to investigate possible links between ecosystem management, litter chemistry and decomposition, and decomposer community composition and activity. We measured decomposition rates, changes in litter chemistry, extracellular enzyme activity, microarthropod communities, and bacterial versus fungal relative abundance in replicated conventional-till, no-till, and old field agricultural sites for both corn and grass litter. After one growing season, litter decomposition under conventional-till was 20% greater than in old field communities. However, decomposition rates in no-till were not significantly different from those in old field or conventional-till sites. After decomposition, grass residue in both conventional- and no-till systems was enriched in total polysaccharides relative to initial litter, while grass litter decomposed in old fields was enriched in nitrogen-bearing compounds and lipids. These differences corresponded with differences in decomposer communities, which also exhibited strong responses to both litter and management type. Overall, our results indicate that agricultural intensification can increase litter decomposition rates, alter decomposer communities, and influence litter chemistry in ways that could have important and long-term effects on soil organic matter dynamics. We suggest that future efforts to more accurately predict soil carbon dynamics under different management regimes may need to explicitly consider how changes in litter chemistry during decomposition are influenced by the specific metabolic capabilities of the extant decomposer communities.

Lumley's PODT definition of large eddies and a trio of numerical procedures. [Proper Orthogonal Decomposition Theorem

NASA Technical Reports Server (NTRS)

Payne, Fred R.

1992-01-01

Lumley's 1967 Moscow paper provided, for the first time, a completely rational definition of the physically-useful term 'large eddy', popular for a half-century. The numerical procedures based upon his results are: (1) PODT (Proper Orthogonal Decomposition Theorem), which extracts the Large Eddy structure of stochastic processes from physical or computer simulation two-point covariances, and 2) LEIM (Large-Eddy Interaction Model), a predictive scheme for the dynamical large eddies based upon higher order turbulence modeling. Earlier Lumley's work (1964) forms the basis for the final member of the triad of numerical procedures: this predicts the global neutral modes of turbulence which have surprising agreement with both structural eigenmodes and those obtained from the dynamical equations. The ultimate goal of improved engineering design tools for turbulence may be near at hand, partly due to the power and storage of 'supermicrocomputer' workstations finally becoming adequate for the demanding numerics of these procedures.

A prototype computer-aided modelling tool for life-support system models

NASA Technical Reports Server (NTRS)

Preisig, H. A.; Lee, Tae-Yeong; Little, Frank

1990-01-01

Based on the canonical decomposition of physical-chemical-biological systems, a prototype kernel has been developed to efficiently model alternative life-support systems. It supports (1) the work in an interdisciplinary group through an easy-to-use mostly graphical interface, (2) modularized object-oriented model representation, (3) reuse of models, (4) inheritance of structures from model object to model object, and (5) model data base. The kernel is implemented in Modula-II and presently operates on an IBM PC.

A Four-Stage Hybrid Model for Hydrological Time Series Forecasting

PubMed Central

Di, Chongli; Yang, Xiaohua; Wang, Xiaochao

2014-01-01

Hydrological time series forecasting remains a difficult task due to its complicated nonlinear, non-stationary and multi-scale characteristics. To solve this difficulty and improve the prediction accuracy, a novel four-stage hybrid model is proposed for hydrological time series forecasting based on the principle of ‘denoising, decomposition and ensemble’. The proposed model has four stages, i.e., denoising, decomposition, components prediction and ensemble. In the denoising stage, the empirical mode decomposition (EMD) method is utilized to reduce the noises in the hydrological time series. Then, an improved method of EMD, the ensemble empirical mode decomposition (EEMD), is applied to decompose the denoised series into a number of intrinsic mode function (IMF) components and one residual component. Next, the radial basis function neural network (RBFNN) is adopted to predict the trend of all of the components obtained in the decomposition stage. In the final ensemble prediction stage, the forecasting results of all of the IMF and residual components obtained in the third stage are combined to generate the final prediction results, using a linear neural network (LNN) model. For illustration and verification, six hydrological cases with different characteristics are used to test the effectiveness of the proposed model. The proposed hybrid model performs better than conventional single models, the hybrid models without denoising or decomposition and the hybrid models based on other methods, such as the wavelet analysis (WA)-based hybrid models. In addition, the denoising and decomposition strategies decrease the complexity of the series and reduce the difficulties of the forecasting. With its effective denoising and accurate decomposition ability, high prediction precision and wide applicability, the new model is very promising for complex time series forecasting. This new forecast model is an extension of nonlinear prediction models. PMID:25111782

A four-stage hybrid model for hydrological time series forecasting.

PubMed

Di, Chongli; Yang, Xiaohua; Wang, Xiaochao

2014-01-01

Hydrological time series forecasting remains a difficult task due to its complicated nonlinear, non-stationary and multi-scale characteristics. To solve this difficulty and improve the prediction accuracy, a novel four-stage hybrid model is proposed for hydrological time series forecasting based on the principle of 'denoising, decomposition and ensemble'. The proposed model has four stages, i.e., denoising, decomposition, components prediction and ensemble. In the denoising stage, the empirical mode decomposition (EMD) method is utilized to reduce the noises in the hydrological time series. Then, an improved method of EMD, the ensemble empirical mode decomposition (EEMD), is applied to decompose the denoised series into a number of intrinsic mode function (IMF) components and one residual component. Next, the radial basis function neural network (RBFNN) is adopted to predict the trend of all of the components obtained in the decomposition stage. In the final ensemble prediction stage, the forecasting results of all of the IMF and residual components obtained in the third stage are combined to generate the final prediction results, using a linear neural network (LNN) model. For illustration and verification, six hydrological cases with different characteristics are used to test the effectiveness of the proposed model. The proposed hybrid model performs better than conventional single models, the hybrid models without denoising or decomposition and the hybrid models based on other methods, such as the wavelet analysis (WA)-based hybrid models. In addition, the denoising and decomposition strategies decrease the complexity of the series and reduce the difficulties of the forecasting. With its effective denoising and accurate decomposition ability, high prediction precision and wide applicability, the new model is very promising for complex time series forecasting. This new forecast model is an extension of nonlinear prediction models.

Three-pattern decomposition of global atmospheric circulation: part I—decomposition model and theorems

NASA Astrophysics Data System (ADS)

Hu, Shujuan; Chou, Jifan; Cheng, Jianbo

2018-04-01

In order to study the interactions between the atmospheric circulations at the middle-high and low latitudes from the global perspective, the authors proposed the mathematical definition of three-pattern circulations, i.e., horizontal, meridional and zonal circulations with which the actual atmospheric circulation is expanded. This novel decomposition method is proved to accurately describe the actual atmospheric circulation dynamics. The authors used the NCEP/NCAR reanalysis data to calculate the climate characteristics of those three-pattern circulations, and found that the decomposition model agreed with the observed results. Further dynamical analysis indicates that the decomposition model is more accurate to capture the major features of global three dimensional atmospheric motions, compared to the traditional definitions of Rossby wave, Hadley circulation and Walker circulation. The decomposition model for the first time realized the decomposition of global atmospheric circulation using three orthogonal circulations within the horizontal, meridional and zonal planes, offering new opportunities to study the large-scale interactions between the middle-high latitudes and low latitudes circulations.

A New Approach of evaluating the damage in simply-supported reinforced concrete beam by Local mean decomposition (LMD)

NASA Astrophysics Data System (ADS)

Zhang, Xuebing; Liu, Ning; Xi, Jiaxin; Zhang, Yunqi; Zhang, Wenchun; Yang, Peipei

2017-08-01

How to analyze the nonstationary response signals and obtain vibration characters is extremely important in the vibration-based structural diagnosis methods. In this work, we introduce a more reasonable time-frequency decomposition method termed local mean decomposition (LMD) to instead the widely-used empirical mode decomposition (EMD). By employing the LMD method, one can derive a group of component signals, each of which is more stationary, and then analyze the vibration state and make the assessment of structural damage of a construction or building. We illustrated the effectiveness of LMD by a synthetic data and an experimental data recorded in a simply-supported reinforced concrete beam. Then based on the decomposition results, an elementary method of damage diagnosis was proposed.

The Variance of Intraclass Correlations in Three- and Four-Level Models

ERIC Educational Resources Information Center

Hedges, Larry V.; Hedberg, E. C.; Kuyper, Arend M.

2012-01-01

Intraclass correlations are used to summarize the variance decomposition in populations with multilevel hierarchical structure. There has recently been considerable interest in estimating intraclass correlations from surveys or designed experiments to provide design parameters for planning future large-scale randomized experiments. The large…

Massively Parallel Dantzig-Wolfe Decomposition Applied to Traffic Flow Scheduling

NASA Technical Reports Server (NTRS)

Rios, Joseph Lucio; Ross, Kevin

2009-01-01

Optimal scheduling of air traffic over the entire National Airspace System is a computationally difficult task. To speed computation, Dantzig-Wolfe decomposition is applied to a known linear integer programming approach for assigning delays to flights. The optimization model is proven to have the block-angular structure necessary for Dantzig-Wolfe decomposition. The subproblems for this decomposition are solved in parallel via independent computation threads. Experimental evidence suggests that as the number of subproblems/threads increases (and their respective sizes decrease), the solution quality, convergence, and runtime improve. A demonstration of this is provided by using one flight per subproblem, which is the finest possible decomposition. This results in thousands of subproblems and associated computation threads. This massively parallel approach is compared to one with few threads and to standard (non-decomposed) approaches in terms of solution quality and runtime. Since this method generally provides a non-integral (relaxed) solution to the original optimization problem, two heuristics are developed to generate an integral solution. Dantzig-Wolfe followed by these heuristics can provide a near-optimal (sometimes optimal) solution to the original problem hundreds of times faster than standard (non-decomposed) approaches. In addition, when massive decomposition is employed, the solution is shown to be more likely integral, which obviates the need for an integerization step. These results indicate that nationwide, real-time, high fidelity, optimal traffic flow scheduling is achievable for (at least) 3 hour planning horizons.

Small Angle Neutron Scattering Study in Multi-Component Polymer Systems: Spinodal Decomposition and Beyond

NASA Astrophysics Data System (ADS)

Han, Charles

Institute for Advanced Study, Shenzhen University, Shenzhen, China In memory of Professor John Kohn at this symposium, a time resolved SANS study for the early stage of spinodal decomposition kinetics of deuterated polycarbonate/poly(methylmethacrylate) blend will be reviewed which gives a clear proof of the Cahn-Hillard-Cook theory. This early stage of spinodal decomposition kinetics has been observed starting from the dimension (q-l) comparable to the single chain radius of gyration, Rg\\ , for a binary polymer mixture. The results provide an unequivocal quantitative measure of the virtual structure factor, S (q, ∞); the relationship of qm and qc through rate of growth, Cahn-plot analysis, and singularity in S (q, ∞); the growth of fluctuation of qRg <1 and intra-chain relaxation of qRg >1. More recent study of using mixed suspensions of polystyrene microspheres and poly(N-isopropylacrylamide) microgels as a molecular model system which has a long range repulsive interaction potential and a short range attractive potential, will also be discussed. In this model system, dynamic gelation, transition to soft glass state and cross-over to hard glass state will be demonstrated and compared with available theories for glass transition in structural materials. Acknowledgements go to: Polymers Division, and NCNR of NIST, and to ICCAS, Beijing, China. Also to my colleagues: M. Motowoka, H. Jinnai, T. Hashimoto, G.C. Yuan and H. Cheng.

Kinetics of Thermal Unimolecular Decomposition of Acetic Anhydride: An Integrated Deterministic and Stochastic Model.

PubMed

Mai, Tam V-T; Duong, Minh V; Nguyen, Hieu T; Lin, Kuang C; Huynh, Lam K

2017-04-27

An integrated deterministic and stochastic model within the master equation/Rice-Ramsperger-Kassel-Marcus (ME/RRKM) framework was first used to characterize temperature- and pressure-dependent behaviors of thermal decomposition of acetic anhydride in a wide range of conditions (i.e., 300-1500 K and 0.001-100 atm). Particularly, using potential energy surface and molecular properties obtained from high-level electronic structure calculations at CCSD(T)/CBS, macroscopic thermodynamic properties and rate coefficients of the title reaction were derived with corrections for hindered internal rotation and tunneling treatments. Being in excellent agreement with the scattered experimental data, the results from deterministic and stochastic frameworks confirmed and complemented each other to reveal that the main decomposition pathway proceeds via a 6-membered-ring transition state with the 0 K barrier of 35.2 kcal·mol -1 . This observation was further understood and confirmed by the sensitivity analysis on the time-resolved species profiles and the derived rate coefficients with respect to the ab initio barriers. Such an agreement suggests the integrated model can be confidently used for a wide range of conditions as a powerful postfacto and predictive tool in detailed chemical kinetic modeling and simulation for the title reaction and thus can be extended to complex chemical reactions.

Structural optimization by multilevel decomposition

NASA Technical Reports Server (NTRS)

Sobieszczanski-Sobieski, J.; James, B.; Dovi, A.

1983-01-01

A method is described for decomposing an optimization problem into a set of subproblems and a coordination problem which preserves coupling between the subproblems. The method is introduced as a special case of multilevel, multidisciplinary system optimization and its algorithm is fully described for two level optimization for structures assembled of finite elements of arbitrary type. Numerical results are given for an example of a framework to show that the decomposition method converges and yields results comparable to those obtained without decomposition. It is pointed out that optimization by decomposition should reduce the design time by allowing groups of engineers, using different computers to work concurrently on the same large problem.

Decomposition and model selection for large contingency tables.

PubMed

Dahinden, Corinne; Kalisch, Markus; Bühlmann, Peter

2010-04-01

Large contingency tables summarizing categorical variables arise in many areas. One example is in biology, where large numbers of biomarkers are cross-tabulated according to their discrete expression level. Interactions of the variables are of great interest and are generally studied with log-linear models. The structure of a log-linear model can be visually represented by a graph from which the conditional independence structure can then be easily read off. However, since the number of parameters in a saturated model grows exponentially in the number of variables, this generally comes with a heavy computational burden. Even if we restrict ourselves to models of lower-order interactions or other sparse structures, we are faced with the problem of a large number of cells which play the role of sample size. This is in sharp contrast to high-dimensional regression or classification procedures because, in addition to a high-dimensional parameter, we also have to deal with the analogue of a huge sample size. Furthermore, high-dimensional tables naturally feature a large number of sampling zeros which often leads to the nonexistence of the maximum likelihood estimate. We therefore present a decomposition approach, where we first divide the problem into several lower-dimensional problems and then combine these to form a global solution. Our methodology is computationally feasible for log-linear interaction models with many categorical variables each or some of them having many levels. We demonstrate the proposed method on simulated data and apply it to a bio-medical problem in cancer research.

Explicit parametric solutions of lattice structures with proper generalized decomposition (PGD) - Applications to the design of 3D-printed architectured materials

NASA Astrophysics Data System (ADS)

Sibileau, Alberto; Auricchio, Ferdinando; Morganti, Simone; Díez, Pedro

2018-01-01

Architectured materials (or metamaterials) are constituted by a unit-cell with a complex structural design repeated periodically forming a bulk material with emergent mechanical properties. One may obtain specific macro-scale (or bulk) properties in the resulting architectured material by properly designing the unit-cell. Typically, this is stated as an optimal design problem in which the parameters describing the shape and mechanical properties of the unit-cell are selected in order to produce the desired bulk characteristics. This is especially pertinent due to the ease manufacturing of these complex structures with 3D printers. The proper generalized decomposition provides explicit parametic solutions of parametric PDEs. Here, the same ideas are used to obtain parametric solutions of the algebraic equations arising from lattice structural models. Once the explicit parametric solution is available, the optimal design problem is a simple post-process. The same strategy is applied in the numerical illustrations, first to a unit-cell (and then homogenized with periodicity conditions), and in a second phase to the complete structure of a lattice material specimen.

Unraveling the physical meaning of the Jaffe-Manohar decomposition of the nucleon spin

NASA Astrophysics Data System (ADS)

Wakamatsu, M.

2016-09-01

A general consensus now is that there are two physically inequivalent complete decompositions of the nucleon spin, i.e. the decomposition of the canonical type and that of mechanical type. The well-known Jaffe-Manohar decomposition is of the former type. Unfortunately, there is a wide-spread misbelief that this decomposition matches the partonic picture, which states that motion of quarks in the nucleon is approximately free. In the present monograph, we reveal that this understanding is not necessarily correct and that the Jaffe-Manohar decomposition is not such a decomposition, which natively reflects the intrinsic (or static) orbital angular momentum structure of the nucleon.

Dynamic mode decomposition for plasma diagnostics and validation.

PubMed

Taylor, Roy; Kutz, J Nathan; Morgan, Kyle; Nelson, Brian A

2018-05-01

We demonstrate the application of the Dynamic Mode Decomposition (DMD) for the diagnostic analysis of the nonlinear dynamics of a magnetized plasma in resistive magnetohydrodynamics. The DMD method is an ideal spatio-temporal matrix decomposition that correlates spatial features of computational or experimental data while simultaneously associating the spatial activity with periodic temporal behavior. DMD can produce low-rank, reduced order surrogate models that can be used to reconstruct the state of the system with high fidelity. This allows for a reduction in the computational cost and, at the same time, accurate approximations of the problem, even if the data are sparsely sampled. We demonstrate the use of the method on both numerical and experimental data, showing that it is a successful mathematical architecture for characterizing the helicity injected torus with steady inductive (HIT-SI) magnetohydrodynamics. Importantly, the DMD produces interpretable, dominant mode structures, including a stationary mode consistent with our understanding of a HIT-SI spheromak accompanied by a pair of injector-driven modes. In combination, the 3-mode DMD model produces excellent dynamic reconstructions across the domain of analyzed data.

Dynamic mode decomposition for plasma diagnostics and validation

NASA Astrophysics Data System (ADS)

Taylor, Roy; Kutz, J. Nathan; Morgan, Kyle; Nelson, Brian A.

2018-05-01

We demonstrate the application of the Dynamic Mode Decomposition (DMD) for the diagnostic analysis of the nonlinear dynamics of a magnetized plasma in resistive magnetohydrodynamics. The DMD method is an ideal spatio-temporal matrix decomposition that correlates spatial features of computational or experimental data while simultaneously associating the spatial activity with periodic temporal behavior. DMD can produce low-rank, reduced order surrogate models that can be used to reconstruct the state of the system with high fidelity. This allows for a reduction in the computational cost and, at the same time, accurate approximations of the problem, even if the data are sparsely sampled. We demonstrate the use of the method on both numerical and experimental data, showing that it is a successful mathematical architecture for characterizing the helicity injected torus with steady inductive (HIT-SI) magnetohydrodynamics. Importantly, the DMD produces interpretable, dominant mode structures, including a stationary mode consistent with our understanding of a HIT-SI spheromak accompanied by a pair of injector-driven modes. In combination, the 3-mode DMD model produces excellent dynamic reconstructions across the domain of analyzed data.

Methane hydrate formation and decomposition: structural studies via neutron diffraction and empirical potential structure refinement.

PubMed

Thompson, Helen; Soper, Alan K; Buchanan, Piers; Aldiwan, Nawaf; Creek, Jefferson L; Koh, Carolyn A

2006-04-28

Neutron diffraction studies with hydrogen/deuterium isotope substitution measurements are performed to investigate the water structure at the early, medium, and late periods of methane clathrate hydrate formation and decomposition. These measurements are coupled with simultaneous gas consumption measurements to track the formation of methane hydrate from a gas/water mixture, and then the complete decomposition of hydrate. Empirical potential structure refinement computer simulations are used to analyze the neutron diffraction data and extract from the data the water structure in the bulk methane hydrate solution. The results highlight the significant changes in the water structure of the remaining liquid at various stages of hydrate formation and decomposition, and give further insight into the way in which hydrates form. The results also have important implications on the memory effect, suggesting that the water structure in the presence of hydrate crystallites is significantly different at equivalent stages of forming compared to decomposing. These results are in sharp contrast to the previously reported cases when all remaining hydrate crystallites are absent from the solution. For these systems there is no detectable change in the water structure or the methane hydration shell before hydrate formation and after decomposition. Based on the new results presented in this paper, it is clear that the local water structure is affected by the presence of hydrate crystallites, which may in turn be responsible for the "history" or "memory" effect where the production of hydrate from a solution of formed and then subsequently melted hydrate is reportedly much quicker than producing hydrate from a fresh water/gas mixture.

Synthesis, crystal structure and catalytic effect on thermal decomposition of RDX and AP: An energetic coordination polymer [Pb{sub 2}(C{sub 5}H{sub 3}N{sub 5}O{sub 5}){sub 2}(NMP)·NMP]{sub n}

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Jin-jian; Yancheng Teachers College, Yancheng 224002; Liu, Zu-Liang, E-mail: liuzl@mail.njust.edu.cn

2013-04-15

An energetic lead(II) coordination polymer based on the ligand ANPyO has been synthesized and its crystal structure has been got. The polymer was characterized by FT-IR spectroscopy, elemental analysis, DSC and TG-DTG technologies. Thermal analysis shows that there are one endothermic process and two exothermic decomposition stages in the temperature range of 50–600 °C with final residues 57.09%. The non-isothermal kinetic has also been studied on the main exothermic decomposition using the Kissinger's and Ozawa–Doyle's methods, the apparent activation energy is calculated as 195.2 KJ/mol. Furthermore, DSC measurements show that the polymer has significant catalytic effect on the thermal decompositionmore » of ammonium perchlorate. - Graphical abstract: An energetic lead(II) coordination polymer of ANPyO has been synthesized, structurally characterized and properties tested. Highlights: ► We have synthesized and characterized an energetic lead(II) coordination polymer. ► We have measured its molecular structure and thermal decomposition. ► It has significant catalytic effect on thermal decomposition of AP.« less

Aging-driven decomposition in zolpidem hemitartrate hemihydrate and the single-crystal structure of its decomposition products.

PubMed

Vega, Daniel R; Baggio, Ricardo; Roca, Mariana; Tombari, Dora

2011-04-01

The "aging-driven" decomposition of zolpidem hemitartrate hemihydrate (form A) has been followed by X-ray powder diffraction (XRPD), and the crystal and molecular structures of the decomposition products studied by single-crystal methods. The process is very similar to the "thermally driven" one, recently described in the literature for form E (Halasz and Dinnebier. 2010. J Pharm Sci 99(2): 871-874), resulting in a two-phase system: the neutral free base (common to both decomposition processes) and, in the present case, a novel zolpidem tartrate monohydrate, unique to the "aging-driven" decomposition. Our room-temperature single-crystal analysis gives for the free base comparable results as the high-temperature XRPD ones already reported by Halasz and Dinnebier: orthorhombic, Pcba, a = 9.6360(10) Å, b = 18.2690(5) Å, c = 18.4980(11) Å, and V = 3256.4(4) Å(3) . The unreported zolpidem tartrate monohydrate instead crystallizes in monoclinic P21 , which, for comparison purposes, we treated in the nonstandard setting P1121 with a = 20.7582(9) Å, b = 15.2331(5) Å, c = 7.2420(2) Å, γ = 90.826(2)°, and V = 2289.73(14) Å(3) . The structure presents two complete moieties in the asymmetric unit (z = 4, z' = 2). The different phases obtained in both decompositions are readily explained, considering the diverse genesis of both processes. Copyright © 2010 Wiley-Liss, Inc.

Stochastic blockmodeling of the modules and core of the Caenorhabditis elegans connectome.

PubMed

Pavlovic, Dragana M; Vértes, Petra E; Bullmore, Edward T; Schafer, William R; Nichols, Thomas E

2014-01-01

Recently, there has been much interest in the community structure or mesoscale organization of complex networks. This structure is characterised either as a set of sparsely inter-connected modules or as a highly connected core with a sparsely connected periphery. However, it is often difficult to disambiguate these two types of mesoscale structure or, indeed, to summarise the full network in terms of the relationships between its mesoscale constituents. Here, we estimate a community structure with a stochastic blockmodel approach, the Erdős-Rényi Mixture Model, and compare it to the much more widely used deterministic methods, such as the Louvain and Spectral algorithms. We used the Caenorhabditis elegans (C. elegans) nervous system (connectome) as a model system in which biological knowledge about each node or neuron can be used to validate the functional relevance of the communities obtained. The deterministic algorithms derived communities with 4-5 modules, defined by sparse inter-connectivity between all modules. In contrast, the stochastic Erdős-Rényi Mixture Model estimated a community with 9 blocks or groups which comprised a similar set of modules but also included a clearly defined core, made of 2 small groups. We show that the "core-in-modules" decomposition of the worm brain network, estimated by the Erdős-Rényi Mixture Model, is more compatible with prior biological knowledge about the C. elegans nervous system than the purely modular decomposition defined deterministically. We also show that the blockmodel can be used both to generate stochastic realisations (simulations) of the biological connectome, and to compress network into a small number of super-nodes and their connectivity. We expect that the Erdős-Rényi Mixture Model may be useful for investigating the complex community structures in other (nervous) systems.

Time-dependent density functional theory for open systems with a positivity-preserving decomposition scheme for environment spectral functions

NASA Astrophysics Data System (ADS)

Wang, RuLin; Zheng, Xiao; Kwok, YanHo; Xie, Hang; Chen, GuanHua; Yam, ChiYung

2015-04-01

Understanding electronic dynamics on material surfaces is fundamentally important for applications including nanoelectronics, inhomogeneous catalysis, and photovoltaics. Practical approaches based on time-dependent density functional theory for open systems have been developed to characterize the dissipative dynamics of electrons in bulk materials. The accuracy and reliability of such approaches depend critically on how the electronic structure and memory effects of surrounding material environment are accounted for. In this work, we develop a novel squared-Lorentzian decomposition scheme, which preserves the positive semi-definiteness of the environment spectral matrix. The resulting electronic dynamics is guaranteed to be both accurate and convergent even in the long-time limit. The long-time stability of electronic dynamics simulation is thus greatly improved within the current decomposition scheme. The validity and usefulness of our new approach are exemplified via two prototypical model systems: quasi-one-dimensional atomic chains and two-dimensional bilayer graphene.

Untangling climate signals from autogenic changes in long-term peatland development

NASA Astrophysics Data System (ADS)

Morris, Paul J.; Baird, Andy J.; Young, Dylan M.; Swindles, Graeme T.

2015-12-01

Peatlands represent important archives of Holocene paleoclimatic information. However, autogenic processes may disconnect peatland hydrological behavior from climate and overwrite climatic signals in peat records. We use a simulation model of peatland development driven by a range of Holocene climate reconstructions to investigate climate signal preservation in peat records. Simulated water-table depths and peat decomposition profiles exhibit homeostatic recovery from prescribed changes in rainfall, whereas changes in temperature cause lasting alterations to peatland structure and function. Autogenic ecohydrological feedbacks provide both high- and low-pass filters for climatic information, particularly rainfall. Large-magnitude climatic changes of an intermediate temporal scale (i.e., multidecadal to centennial) are most readily preserved in our simulated peat records. Simulated decomposition signals are offset from the climatic changes that generate them due to a phenomenon known as secondary decomposition. Our study provides the mechanistic foundations for a framework to separate climatic and autogenic signals in peat records.

Experimental and modeling study on decomposition kinetics of methane hydrates in different media.

PubMed

Liang, Minyan; Chen, Guangjin; Sun, Changyu; Yan, Lijun; Liu, Jiang; Ma, Qinglan

2005-10-13

The decomposition kinetic behaviors of methane hydrates formed in 5 cm3 porous wet activated carbon were studied experimentally in a closed system in the temperature range of 275.8-264.4 K. The decomposition rates of methane hydrates formed from 5 cm3 of pure free water and an aqueous solution of 650 g x m(-3) sodium dodecyl sulfate (SDS) were also measured for comparison. The decomposition rates of methane hydrates in seven different cases were compared. The results showed that the methane hydrates dissociate more rapidly in porous activated carbon than in free systems. A mathematical model was developed for describing the decomposition kinetic behavior of methane hydrates below ice point based on an ice-shielding mechanism in which a porous ice layer was assumed to be formed during the decomposition of hydrate, and the diffusion of methane molecules through it was assumed to be one of the control steps. The parameters of the model were determined by correlating the decomposition rate data, and the activation energies were further determined with respect to three different media. The model was found to well describe the decomposition kinetic behavior of methane hydrate in different media.

Adaptive Identification by Systolic Arrays.

DTIC Science & Technology

1987-12-01

BIBLIOGRIAPHY Anton , Howard, Elementary Linear Algebra , John Wiley & Sons, 19S4. Cristi, Roberto, A Parallel Structure Jor Adaptive Pole Placement...10 11. SYSTEM IDENTIFICATION M*YETHODS ....................... 12 A. LINEAR SYSTEM MODELING ......................... 12 B. SOLUTION OF SYSTEMS OF... LINEAR EQUATIONS ......... 13 C. QR DECOMPOSITION ................................ 14 D. RECURSIVE LEAST SQUARES ......................... 16 E. BLOCK

Spreadsheets and Bulgarian Goats

ERIC Educational Resources Information Center

Sugden, Steve

2012-01-01

We consider a problem appearing in an Australian Mathematics Challenge in 2003. This article considers whether a spreadsheet might be used to model this problem, thus allowing students to explore its structure within the spreadsheet environment. It then goes on to reflect on some general principles of problem decomposition when the final goal is a…

Thermal decomposition of ammonium hexachloroosmate.

PubMed

Asanova, T I; Kantor, I; Asanov, I P; Korenev, S V; Yusenko, K V

2016-12-07

Structural changes of (NH 4 ) 2 [OsCl 6 ] occurring during thermal decomposition in a reduction atmosphere have been studied in situ using combined energy-dispersive X-ray absorption spectroscopy (ED-XAFS) and powder X-ray diffraction (PXRD). According to PXRD, (NH 4 ) 2 [OsCl 6 ] transforms directly to metallic Os without the formation of any crystalline intermediates but through a plateau where no reactions occur. XANES and EXAFS data by means of Multivariate Curve Resolution (MCR) analysis show that thermal decomposition occurs with the formation of an amorphous intermediate {OsCl 4 } x with a possible polymeric structure. Being revealed for the first time the intermediate was subjected to determine the local atomic structure around osmium. The thermal decomposition of hexachloroosmate is much more complex and occurs within a minimum two-step process, which has never been observed before.

Probability of atrial fibrillation after ablation: Using a parametric nonlinear temporal decomposition mixed effects model.

PubMed

Rajeswaran, Jeevanantham; Blackstone, Eugene H; Ehrlinger, John; Li, Liang; Ishwaran, Hemant; Parides, Michael K

2018-01-01

Atrial fibrillation is an arrhythmic disorder where the electrical signals of the heart become irregular. The probability of atrial fibrillation (binary response) is often time varying in a structured fashion, as is the influence of associated risk factors. A generalized nonlinear mixed effects model is presented to estimate the time-related probability of atrial fibrillation using a temporal decomposition approach to reveal the pattern of the probability of atrial fibrillation and their determinants. This methodology generalizes to patient-specific analysis of longitudinal binary data with possibly time-varying effects of covariates and with different patient-specific random effects influencing different temporal phases. The motivation and application of this model is illustrated using longitudinally measured atrial fibrillation data obtained through weekly trans-telephonic monitoring from an NIH sponsored clinical trial being conducted by the Cardiothoracic Surgery Clinical Trials Network.

Modelling Behaviour of a Carbon Epoxy Composite Exposed to Fire: Part I—Characterisation of Thermophysical Properties

PubMed Central

Tranchard, Pauline; Samyn, Fabienne; Duquesne, Sophie; Estèbe, Bruno; Bourbigot, Serge

2017-01-01

Thermophysical properties of a carbon-reinforced epoxy composite laminate (T700/M21 composite for aircraft structures) were evaluated using different innovative characterisation methods. Thermogravimetric Analysis (TGA), Simultaneous Thermal analysis (STA), Laser Flash analysis (LFA), and Fourier Transform Infrared (FTIR) analysis were used for measuring the thermal decomposition, the specific heat capacity, the anisotropic thermal conductivity of the composite, the heats of decomposition and the specific heat capacity of released gases. It permits to get input data to feed a three-dimensional (3D) model given the temperature profile and the mass loss obtained during well-defined fire scenarios (model presented in Part II of this paper). The measurements were optimised to get accurate data. The data also permit to create a public database on an aeronautical carbon fibre/epoxy composite for fire safety engineering. PMID:28772854

Decomposing phenotype descriptions for the human skeletal phenome.

PubMed

Groza, Tudor; Hunter, Jane; Zankl, Andreas

2013-01-01

Over the course of the last few years there has been a significant amount of research performed on ontology-based formalization of phenotype descriptions. The intrinsic value and knowledge captured within such descriptions can only be expressed by taking advantage of their inner structure that implicitly combines qualities and anatomical entities. We present a meta-model (the Phenotype Fragment Ontology) and a processing pipeline that enable together the automatic decomposition and conceptualization of phenotype descriptions for the human skeletal phenome. We use this approach to showcase the usefulness of the generic concept of phenotype decomposition by performing an experimental study on all skeletal phenotype concepts defined in the Human Phenotype Ontology.

Photoacoustic imaging optimization with raw signal deconvolution and empirical mode decomposition

NASA Astrophysics Data System (ADS)

Guo, Chengwen; Wang, Jing; Qin, Yu; Zhan, Hongchen; Yuan, Jie; Cheng, Qian; Wang, Xueding

2018-02-01

Photoacoustic (PA) signal of an ideal optical absorb particle is a single N-shape wave. PA signals of a complicated biological tissue can be considered as the combination of individual N-shape waves. However, the N-shape wave basis not only complicates the subsequent work, but also results in aliasing between adjacent micro-structures, which deteriorates the quality of the final PA images. In this paper, we propose a method to improve PA image quality through signal processing method directly working on raw signals, which including deconvolution and empirical mode decomposition (EMD). During the deconvolution procedure, the raw PA signals are de-convolved with a system dependent point spread function (PSF) which is measured in advance. Then, EMD is adopted to adaptively re-shape the PA signals with two constraints, positive polarity and spectrum consistence. With our proposed method, the built PA images can yield more detail structural information. Micro-structures are clearly separated and revealed. To validate the effectiveness of this method, we present numerical simulations and phantom studies consist of a densely distributed point sources model and a blood vessel model. In the future, our study might hold the potential for clinical PA imaging as it can help to distinguish micro-structures from the optimized images and even measure the size of objects from deconvolved signals.

Hierarchical prediction of industrial water demand based on refined Laspeyres decomposition analysis.

PubMed

Shang, Yizi; Lu, Shibao; Gong, Jiaguo; Shang, Ling; Li, Xiaofei; Wei, Yongping; Shi, Hongwang

2017-12-01

A recent study decomposed the changes in industrial water use into three hierarchies (output, technology, and structure) using a refined Laspeyres decomposition model, and found monotonous and exclusive trends in the output and technology hierarchies. Based on that research, this study proposes a hierarchical prediction approach to forecast future industrial water demand. Three water demand scenarios (high, medium, and low) were then established based on potential future industrial structural adjustments, and used to predict water demand for the structural hierarchy. The predictive results of this approach were compared with results from a grey prediction model (GPM (1, 1)). The comparison shows that the results of the two approaches were basically identical, differing by less than 10%. Taking Tianjin, China, as a case, and using data from 2003-2012, this study predicts that industrial water demand will continuously increase, reaching 580 million m 3 , 776.4 million m 3 , and approximately 1.09 billion m 3 by the years 2015, 2020 and 2025 respectively. It is concluded that Tianjin will soon face another water crisis if no immediate measures are taken. This study recommends that Tianjin adjust its industrial structure with water savings as the main objective, and actively seek new sources of water to increase its supply.

The PHAT and SPLASH Surveys: Rigorous Structural Decomposition of the Andromeda Galaxy

NASA Astrophysics Data System (ADS)

Dorman, Claire; Guhathakurta, P.; Widrow, L.; Foreman-Mackey, D.; Seth, A.; Dalcanton, J.; Gilbert, K.; Lang, D.; Williams, B. F.; SPLASH Team; PHAT Team

2013-01-01

Traditional surface brightness profile (SBP) based structural decompositions of late-type galaxies into Sersic bulge, exponential disk, and power-law halo are often degenerate in the best-fit profiles. The Andromeda galaxy (M31) is the only large spiral close enough that the relative contributions of the subcomponents can be further constrained via their distinct signatures in resolved stellar population surveys. We make use of two such surveys. The SPLASH program has used the Keck/DEIMOS multiobject spectrograph to measure radial velocities of over 10,000 individual red giant branch stars in the inner 20kpc of M31. The PHAT survey, an ongoing Hubble Space Telescope Multicycle Treasury program, has so far obtained six-filter photometry of over 90 million stars in the same region. We use an MCMC algorithm to simultaneously fit a simple bulge/disk/halo structural model to the SBP, the disk fraction as measured from kinematics, and the PHAT luminosity function. We find that the additional constraints favor a larger bulge than expected from a pure SBP fit. Comparison to galaxy formation models will constrain the formation histories of large spiral galaxies such as the Milky Way and Andromeda.

Deorientation of PolSAR coherency matrix for volume scattering retrieval

NASA Astrophysics Data System (ADS)

Kumar, Shashi; Garg, R. D.; Kushwaha, S. P. S.

2016-05-01

Polarimetric SAR data has proven its potential to extract scattering information for different features appearing in single resolution cell. Several decomposition modelling approaches have been developed to retrieve scattering information from PolSAR data. During scattering power decomposition based on physical scattering models it becomes very difficult to distinguish volume scattering as a result from randomly oriented vegetation from scattering nature of oblique structures which are responsible for double-bounce and volume scattering , because both are decomposed in same scattering mechanism. The polarization orientation angle (POA) of an electromagnetic wave is one of the most important character which gets changed due to scattering from geometrical structure of topographic slopes, oriented urban area and randomly oriented features like vegetation cover. The shift in POA affects the polarimetric radar signatures. So, for accurate estimation of scattering nature of feature compensation in polarization orientation shift becomes an essential procedure. The prime objective of this work was to investigate the effect of shift in POA in scattering information retrieval and to explore the effect of deorientation on regression between field-estimated aboveground biomass (AGB) and volume scattering. For this study Dudhwa National Park, U.P., India was selected as study area and fully polarimetric ALOS PALSAR data was used to retrieve scattering information from the forest area of Dudhwa National Park. Field data for DBH and tree height was collect for AGB estimation using stratified random sampling. AGB was estimated for 170 plots for different locations of the forest area. Yamaguchi four component decomposition modelling approach was utilized to retrieve surface, double-bounce, helix and volume scattering information. Shift in polarization orientation angle was estimated and deorientation of coherency matrix for compensation of POA shift was performed. Effect of deorientation on RGB color composite for the forest area can be easily seen. Overestimation of volume scattering and under estimation of double bounce scattering was recorded for PolSAR decomposition without deorientation and increase in double bounce scattering and decrease in volume scattering was noticed after deorientation. This study was mainly focused on volume scattering retrieval and its relation with field estimated AGB. Change in volume scattering after POA compensation of PolSAR data was recorded and a comparison was performed on volume scattering values for all the 170 forest plots for which field data were collected. Decrease in volume scattering after deorientation was noted for all the plots. Regression between PolSAR decomposition based volume scattering and AGB was performed. Before deorientation, coefficient determination (R2) between volume scattering and AGB was 0.225. After deorientation an improvement in coefficient of determination was found and the obtained value was 0.613. This study recommends deorientation of PolSAR data for decomposition modelling to retrieve reliable volume scattering information from forest area.

Audio-frequency analysis of inductive voltage dividers based on structural models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Avramov, S.; Oldham, N.M.; Koffman, A.D.

1994-12-31

A Binary Inductive Voltage Divider (BIVD) is compared with a Decade Inductive Voltage Divider (DIVD) in an automatic IVD bridge. New detection and injection circuitry was designed and used to evaluate the IVDs with either the input or output tied to ground potential. In the audio frequency range the DIVD and BIVD error patterns are characterized for both in-phase and quadrature components. Differences between results obtained using a new error decomposition scheme based on structural modeling, and measurements using conventional IVD standards are reported.

Method of fuzzy inference for one class of MISO-structure systems with non-singleton inputs

NASA Astrophysics Data System (ADS)

Sinuk, V. G.; Panchenko, M. V.

2018-03-01

In fuzzy modeling, the inputs of the simulated systems can receive both crisp values and non-Singleton. Computational complexity of fuzzy inference with fuzzy non-Singleton inputs corresponds to an exponential. This paper describes a new method of inference, based on the theorem of decomposition of a multidimensional fuzzy implication and a fuzzy truth value. This method is considered for fuzzy inputs and has a polynomial complexity, which makes it possible to use it for modeling large-dimensional MISO-structure systems.

Modeling Oil Shale Pyrolysis: High-Temperature Unimolecular Decomposition Pathways for Thiophene.

PubMed

Vasiliou, AnGayle K; Hu, Hui; Cowell, Thomas W; Whitman, Jared C; Porterfield, Jessica; Parish, Carol A

2017-10-12

The thermal decomposition mechanism of thiophene has been investigated both experimentally and theoretically. Thermal decomposition experiments were done using a 1 mm × 3 cm pulsed silicon carbide microtubular reactor, C 4 H 4 S + Δ → Products. Unlike previous studies these experiments were able to identify the initial thiophene decomposition products. Thiophene was entrained in either Ar, Ne, or He carrier gas, passed through a heated (300-1700 K) SiC microtubular reactor (roughly ≤100 μs residence time), and exited into a vacuum chamber. The resultant molecular beam was probed by photoionization mass spectroscopy and IR spectroscopy. The pyrolysis mechanisms of thiophene were also investigated with the CBS-QB3 method using UB3LYP/6-311++G(2d,p) optimized geometries. In particular, these electronic structure methods were used to explore pathways for the formation of elemental sulfur as well as for the formation of H 2 S and 1,3-butadiyne. Thiophene was found to undergo unimolecular decomposition by five pathways: C 4 H 4 S → (1) S═C═CH 2 + HCCH, (2) CS + HCCCH 3 , (3) HCS + HCCCH 2 , (4) H 2 S + HCC-CCH, and (5) S + HCC-CH═CH 2 . The experimental and theoretical findings are in excellent agreement.

Function of bacterial community dynamics in the formation of cadaveric semiochemicals during in situ carcass decomposition.

PubMed

Pascual, Javier; von Hoermann, Christian; Rottler-Hoermann, Ann-Marie; Nevo, Omer; Geppert, Alicia; Sikorski, Johannes; Huber, Katharina J; Steiger, Sandra; Ayasse, Manfred; Overmann, Jörg

2017-08-01

The decomposition of dead mammalian tissue involves a complex temporal succession of epinecrotic bacteria. Microbial activity may release different cadaveric volatile organic compounds which in turn attract other key players of carcass decomposition such as scavenger insects. To elucidate the dynamics and potential functions of epinecrotic bacteria on carcasses, we monitored bacterial communities developing on still-born piglets incubated in different forest ecosystems by combining high-throughput Illumina 16S rRNA sequencing with gas chromatography-mass spectrometry of volatiles. Our results show that the community structure of epinecrotic bacteria and the types of cadaveric volatile compounds released over the time course of decomposition are driven by deterministic rather than stochastic processes. Individual cadaveric volatile organic compounds were correlated with specific taxa during the first stages of decomposition which are dominated by bacteria. Through best-fitting multiple linear regression models, the synthesis of acetic acid, indole and phenol could be linked to the activity of Enterobacteriaceae, Tissierellaceae and Xanthomonadaceae, respectively. These conclusions are also commensurate with the metabolism described for the dominant taxa identified for these families. The predictable nature of in situ synthesis of cadaveric volatile organic compounds by epinecrotic bacteria provides a new basis for future chemical ecology and forensic studies. © 2017 Society for Applied Microbiology and John Wiley & Sons Ltd.

Assessing protein conformational sampling methods based on bivariate lag-distributions of backbone angles

PubMed Central

Maadooliat, Mehdi; Huang, Jianhua Z.

2013-01-01

Despite considerable progress in the past decades, protein structure prediction remains one of the major unsolved problems in computational biology. Angular-sampling-based methods have been extensively studied recently due to their ability to capture the continuous conformational space of protein structures. The literature has focused on using a variety of parametric models of the sequential dependencies between angle pairs along the protein chains. In this article, we present a thorough review of angular-sampling-based methods by assessing three main questions: What is the best distribution type to model the protein angles? What is a reasonable number of components in a mixture model that should be considered to accurately parameterize the joint distribution of the angles? and What is the order of the local sequence–structure dependency that should be considered by a prediction method? We assess the model fits for different methods using bivariate lag-distributions of the dihedral/planar angles. Moreover, the main information across the lags can be extracted using a technique called Lag singular value decomposition (LagSVD), which considers the joint distribution of the dihedral/planar angles over different lags using a nonparametric approach and monitors the behavior of the lag-distribution of the angles using singular value decomposition. As a result, we developed graphical tools and numerical measurements to compare and evaluate the performance of different model fits. Furthermore, we developed a web-tool (http://www.stat.tamu.edu/∼madoliat/LagSVD) that can be used to produce informative animations. PMID:22926831

Data-driven process decomposition and robust online distributed modelling for large-scale processes

NASA Astrophysics Data System (ADS)

Shu, Zhang; Lijuan, Li; Lijuan, Yao; Shipin, Yang; Tao, Zou

2018-02-01

With the increasing attention of networked control, system decomposition and distributed models show significant importance in the implementation of model-based control strategy. In this paper, a data-driven system decomposition and online distributed subsystem modelling algorithm was proposed for large-scale chemical processes. The key controlled variables are first partitioned by affinity propagation clustering algorithm into several clusters. Each cluster can be regarded as a subsystem. Then the inputs of each subsystem are selected by offline canonical correlation analysis between all process variables and its controlled variables. Process decomposition is then realised after the screening of input and output variables. When the system decomposition is finished, the online subsystem modelling can be carried out by recursively block-wise renewing the samples. The proposed algorithm was applied in the Tennessee Eastman process and the validity was verified.

Deformation twinning induced decomposition of lamellar LPSO structure and its re-precipitation in an Mg-Zn-Y alloy

NASA Astrophysics Data System (ADS)

Shao, X. H.; Zheng, S. J.; Chen, D.; Jin, Q. Q.; Peng, Z. Z.; Ma, X. L.

2016-07-01

The high hardness or yield strength of an alloy is known to benefit from the presence of small-scale precipitation, whose hardening effect is extensively applied in various engineering materials. Stability of the precipitates is of critical importance in maintaining the high performance of a material under mechanical loading. The long period stacking ordered (LPSO) structures play an important role in tuning the mechanical properties of an Mg-alloy. Here, we report deformation twinning induces decomposition of lamellar LPSO structures and their re-precipitation in an Mg-Zn-Y alloy. Using atomic resolution scanning transmission electron microscopy (STEM), we directly illustrate that the misfit dislocations at the interface between the lamellar LPSO structure and the deformation twin is corresponding to the decomposition and re-precipitation of LPSO structure, owing to dislocation effects on redistribution of Zn/Y atoms. This finding demonstrates that deformation twinning could destabilize complex precipitates. An occurrence of decomposition and re-precipitation, leading to a variant spatial distribution of the precipitates under plastic loading, may significantly affect the precipitation strengthening.

Deformation twinning induced decomposition of lamellar LPSO structure and its re-precipitation in an Mg-Zn-Y alloy

PubMed Central

Shao, X. H.; Zheng, S. J.; Chen, D.; Jin, Q. Q.; Peng, Z. Z.; Ma, X. L.

2016-01-01

The high hardness or yield strength of an alloy is known to benefit from the presence of small-scale precipitation, whose hardening effect is extensively applied in various engineering materials. Stability of the precipitates is of critical importance in maintaining the high performance of a material under mechanical loading. The long period stacking ordered (LPSO) structures play an important role in tuning the mechanical properties of an Mg-alloy. Here, we report deformation twinning induces decomposition of lamellar LPSO structures and their re-precipitation in an Mg-Zn-Y alloy. Using atomic resolution scanning transmission electron microscopy (STEM), we directly illustrate that the misfit dislocations at the interface between the lamellar LPSO structure and the deformation twin is corresponding to the decomposition and re-precipitation of LPSO structure, owing to dislocation effects on redistribution of Zn/Y atoms. This finding demonstrates that deformation twinning could destabilize complex precipitates. An occurrence of decomposition and re-precipitation, leading to a variant spatial distribution of the precipitates under plastic loading, may significantly affect the precipitation strengthening. PMID:27435638

Chinese Orthographic Decomposition and Logographic Structure

ERIC Educational Resources Information Center

Cheng, Chao-Ming; Lin, Shan-Yuan

2013-01-01

"Chinese orthographic decomposition" refers to a sense of uncertainty about the writing of a well-learned Chinese character following a prolonged inspection of the character. This study investigated the decomposition phenomenon in a test situation in which Chinese characters were repeatedly presented in a word context and assessed…

A comparison of reduced-order modelling techniques for application in hyperthermia control and estimation.

PubMed

Bailey, E A; Dutton, A W; Mattingly, M; Devasia, S; Roemer, R B

1998-01-01

Reduced-order modelling techniques can make important contributions in the control and state estimation of large systems. In hyperthermia, reduced-order modelling can provide a useful tool by which a large thermal model can be reduced to the most significant subset of its full-order modes, making real-time control and estimation possible. Two such reduction methods, one based on modal decomposition and the other on balanced realization, are compared in the context of simulated hyperthermia heat transfer problems. The results show that the modal decomposition reduction method has three significant advantages over that of balanced realization. First, modal decomposition reduced models result in less error, when compared to the full-order model, than balanced realization reduced models of similar order in problems with low or moderate advective heat transfer. Second, because the balanced realization based methods require a priori knowledge of the sensor and actuator placements, the reduced-order model is not robust to changes in sensor or actuator locations, a limitation not present in modal decomposition. Third, the modal decomposition transformation is less demanding computationally. On the other hand, in thermal problems dominated by advective heat transfer, numerical instabilities make modal decomposition based reduction problematic. Modal decomposition methods are therefore recommended for reduction of models in which advection is not dominant and research continues into methods to render balanced realization based reduction more suitable for real-time clinical hyperthermia control and estimation.

Application of Dynamic Mode Decomposition: Temporal Evolution of Flow Structures in an Aneurysm

NASA Astrophysics Data System (ADS)

Conlin, William; Yu, Paulo; Durgesh, Vibhav

2017-11-01

An aneurysm is an enlargement of a weakened arterial wall that can be fatal or debilitating on rupture. Aneurysm hemodynamics is integral to developing an understanding of aneurysm formation, growth, and rupture. The flow in an aneurysm exhibits complex fluid dynamics behavior due to an inherent unsteady inflow condition and its interactions with large-scale flow structures present in the aneurysm. The objective of this study is to identify the large-scale structures in the aneurysm, study temporal behavior, and quantify their interaction with the inflow condition. For this purpose, detailed Particle Image Velocimetry (PIV) measurements were performed at the center plane of an idealized aneurysm model for a range of inflow conditions. Inflow conditions were precisely controlled using a ViVitro SuperPump system. Dynamic Modal Decomposition (DMD) of the velocity field was used to identify coherent structures and their temporal behavior. DMD was successful in capturing the large-scale flow structures and their temporal behavior. A low dimensional approximation to the flow field was obtained with the most relevant dynamic modes and was used to obtain temporal information about the coherent structures and their interaction with the inflow, formation, evolution, and growth.

SU-F-J-138: An Extension of PCA-Based Respiratory Deformation Modeling Via Multi-Linear Decomposition

DOE Office of Scientific and Technical Information (OSTI.GOV)

Iliopoulos, AS; Sun, X; Pitsianis, N

Purpose: To address and lift the limited degree of freedom (DoF) of globally bilinear motion components such as those based on principal components analysis (PCA), for encoding and modeling volumetric deformation motion. Methods: We provide a systematic approach to obtaining a multi-linear decomposition (MLD) and associated motion model from deformation vector field (DVF) data. We had previously introduced MLD for capturing multi-way relationships between DVF variables, without being restricted by the bilinear component format of PCA-based models. PCA-based modeling is commonly used for encoding patient-specific deformation as per planning 4D-CT images, and aiding on-board motion estimation during radiotherapy. However, themore » bilinear space-time decomposition inherently limits the DoF of such models by the small number of respiratory phases. While this limit is not reached in model studies using analytical or digital phantoms with low-rank motion, it compromises modeling power in the presence of relative motion, asymmetries and hysteresis, etc, which are often observed in patient data. Specifically, a low-DoF model will spuriously couple incoherent motion components, compromising its adaptability to on-board deformation changes. By the multi-linear format of extracted motion components, MLD-based models can encode higher-DoF deformation structure. Results: We conduct mathematical and experimental comparisons between PCA- and MLD-based models. A set of temporally-sampled analytical trajectories provides a synthetic, high-rank DVF; trajectories correspond to respiratory and cardiac motion factors, including different relative frequencies and spatial variations. Additionally, a digital XCAT phantom is used to simulate a lung lesion deforming incoherently with respect to the body, which adheres to a simple respiratory trend. In both cases, coupling of incoherent motion components due to a low model DoF is clearly demonstrated. Conclusion: Multi-linear decomposition can enable decoupling of distinct motion factors in high-rank DVF measurements. This may improve motion model expressiveness and adaptability to on-board deformation, aiding model-based image reconstruction for target verification. NIH Grant No. R01-184173.« less

Decomposition of silicon carbide at high pressures and temperatures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Daviau, Kierstin; Lee, Kanani K. M.

We measure the onset of decomposition of silicon carbide, SiC, to silicon and carbon (e.g., diamond) at high pressures and high temperatures in a laser-heated diamond-anvil cell. We identify decomposition through x-ray diffraction and multiwavelength imaging radiometry coupled with electron microscopy analyses on quenched samples. We find that B3 SiC (also known as 3C or zinc blende SiC) decomposes at high pressures and high temperatures, following a phase boundary with a negative slope. The high-pressure decomposition temperatures measured are considerably lower than those at ambient, with our measurements indicating that SiC begins to decompose at ~ 2000 K at 60more » GPa as compared to ~ 2800 K at ambient pressure. Once B3 SiC transitions to the high-pressure B1 (rocksalt) structure, we no longer observe decomposition, despite heating to temperatures in excess of ~ 3200 K. The temperature of decomposition and the nature of the decomposition phase boundary appear to be strongly influenced by the pressure-induced phase transitions to higher-density structures in SiC, silicon, and carbon. The decomposition of SiC at high pressure and temperature has implications for the stability of naturally forming moissanite on Earth and in carbon-rich exoplanets.« less

Structural Evolution of Silicon Oxynitride Fiber Reinforced Boron Nitride Matrix Composite at High Temperatures

NASA Astrophysics Data System (ADS)

Zou, Chunrong; Li, Bin; Zhang, Changrui; Wang, Siqing; Xie, Zhengfang; Shao, Changwei

2016-02-01

The structural evolution of a silicon oxynitride fiber reinforced boron nitride matrix (Si-N-Of/BN) wave-transparent composite at high temperatures was investigated. When heat treated at 1600 °C, the composite retained a favorable bending strength of 55.3 MPa while partially crystallizing to Si2N2O and h-BN from the as-received amorphous structure. The Si-N-O fibers still performed as effective reinforcements despite the presence of small pores due to fiber decomposition. Upon heat treatment at 1800 °C, the Si-N-O fibers already lost their reinforcing function and rough hollow microstructure formed within the fibers because of the accelerated decomposition. Further heating to 2000 °C led to the complete decomposition of the reinforcing fibers and only h-BN particles survived. The crystallization and decomposition behaviors of the composite at high temperatures are discussed.

Comparing and improving proper orthogonal decomposition (POD) to reduce the complexity of groundwater models

NASA Astrophysics Data System (ADS)

Gosses, Moritz; Nowak, Wolfgang; Wöhling, Thomas

2017-04-01

Physically-based modeling is a wide-spread tool in understanding and management of natural systems. With the high complexity of many such models and the huge amount of model runs necessary for parameter estimation and uncertainty analysis, overall run times can be prohibitively long even on modern computer systems. An encouraging strategy to tackle this problem are model reduction methods. In this contribution, we compare different proper orthogonal decomposition (POD, Siade et al. (2010)) methods and their potential applications to groundwater models. The POD method performs a singular value decomposition on system states as simulated by the complex (e.g., PDE-based) groundwater model taken at several time-steps, so-called snapshots. The singular vectors with the highest information content resulting from this decomposition are then used as a basis for projection of the system of model equations onto a subspace of much lower dimensionality than the original complex model, thereby greatly reducing complexity and accelerating run times. In its original form, this method is only applicable to linear problems. Many real-world groundwater models are non-linear, tough. These non-linearities are introduced either through model structure (unconfined aquifers) or boundary conditions (certain Cauchy boundaries, like rivers with variable connection to the groundwater table). To date, applications of POD focused on groundwater models simulating pumping tests in confined aquifers with constant head boundaries. In contrast, POD model reduction either greatly looses accuracy or does not significantly reduce model run time if the above-mentioned non-linearities are introduced. We have also found that variable Dirichlet boundaries are problematic for POD model reduction. An extension to the POD method, called POD-DEIM, has been developed for non-linear groundwater models by Stanko et al. (2016). This method uses spatial interpolation points to build the equation system in the reduced model space, thereby allowing the recalculation of system matrices at every time-step necessary for non-linear models while retaining the speed of the reduced model. This makes POD-DEIM applicable for groundwater models simulating unconfined aquifers. However, in our analysis, the method struggled to reproduce variable river boundaries accurately and gave no advantage for variable Dirichlet boundaries compared to the original POD method. We have developed another extension for POD that targets to address these remaining problems by performing a second POD operation on the model matrix on the left-hand side of the equation. The method aims to at least reproduce the accuracy of the other methods where they are applicable while outperforming them for setups with changing river boundaries or variable Dirichlet boundaries. We compared the new extension with original POD and POD-DEIM for different combinations of model structures and boundary conditions. The new method shows the potential of POD extensions for applications to non-linear groundwater systems and complex boundary conditions that go beyond the current, relatively limited range of applications. References: Siade, A. J., Putti, M., and Yeh, W. W.-G. (2010). Snapshot selection for groundwater model reduction using proper orthogonal decomposition. Water Resour. Res., 46(8):W08539. Stanko, Z. P., Boyce, S. E., and Yeh, W. W.-G. (2016). Nonlinear model reduction of unconfined groundwater flow using pod and deim. Advances in Water Resources, 97:130 - 143.

Component-specific modeling. [jet engine hot section components

NASA Technical Reports Server (NTRS)

Mcknight, R. L.; Maffeo, R. J.; Tipton, M. T.; Weber, G.

1992-01-01

Accomplishments are described for a 3 year program to develop methodology for component-specific modeling of aircraft hot section components (turbine blades, turbine vanes, and burner liners). These accomplishments include: (1) engine thermodynamic and mission models, (2) geometry model generators, (3) remeshing, (4) specialty three-dimensional inelastic structural analysis, (5) computationally efficient solvers, (6) adaptive solution strategies, (7) engine performance parameters/component response variables decomposition and synthesis, (8) integrated software architecture and development, and (9) validation cases for software developed.

Testing the Use of Pigs as Human Proxies in Decomposition Studies.

PubMed

Connor, Melissa; Baigent, Christiane; Hansen, Eriek S

2017-12-28

Pigs are a common human analogue in taphonomic study, yet data comparing the trajectory of decomposition between the two groups are lacking. This study compared decomposition rate and gross tissue change in 17 pigs and 22 human remains placed in the Forensic Investigation Research Station in western Colorado between 2012 and 2015. Accumulated degree days (ADD) were used to assess the number of thermal units required to reach a given total body score (TBS) (1) which was used as the measure of decomposition. A comparison of slopes in linear mixed effects model indicated that decomposition rates significantly differed between human donors and pig remains χ 2 (1) = 5.662, p = 0.017. Neither the pig nor the human trajectory compared well to the TBS model. Thus, (i) pigs are not an adequate proxy for human decomposition studies, and (ii) in the semiarid environment of western Colorado, there is a need to develop a regional decomposition model. © 2017 American Academy of Forensic Sciences.

Numerical predictions and experiments for optimizing hidden corrosion detection in aircraft structures using Lamb modes.

PubMed

Terrien, N; Royer, D; Lepoutre, F; Déom, A

2007-06-01

To increase the sensitivity of Lamb waves to hidden corrosion in aircraft structures, a preliminary step is to understand the phenomena governing this interaction. A hybrid model combining a finite element approach and a modal decomposition method is used to investigate the interaction of Lamb modes with corrosion pits. The finite element mesh is used to describe the region surrounding the corrosion pits while the modal decomposition method permits to determine the waves reflected and transmitted by the damaged area. Simulations make easier the interpretation of some parts of the measured waveform corresponding to superposition of waves diffracted by the corroded area. Numerical results permit to extract significant information from the transmitted waveform and thus to optimize the signal processing for the detection of corrosion at an early stage. Now, we are able to detect corrosion pits down to 80-mum depth distributed randomly on a square centimeter of an aluminum plate. Moreover, thickness variations present on aircraft structures can be discriminated from a slightly corroded area. Finally, using this experimental setup, aircraft structures have been tested.

Effects of Soil Organic Matter Properties and Microbial Community Composition on Enzyme Activities in Cryoturbated Arctic Soils

PubMed Central

Schnecker, Jörg; Wild, Birgit; Hofhansl, Florian; Eloy Alves, Ricardo J.; Bárta, Jiří; Čapek, Petr; Fuchslueger, Lucia; Gentsch, Norman; Gittel, Antje; Guggenberger, Georg; Hofer, Angelika; Kienzl, Sandra; Knoltsch, Anna; Lashchinskiy, Nikolay; Mikutta, Robert; Šantrůčková, Hana; Shibistova, Olga; Takriti, Mounir; Urich, Tim; Weltin, Georg; Richter, Andreas

2014-01-01

Enzyme-mediated decomposition of soil organic matter (SOM) is controlled, amongst other factors, by organic matter properties and by the microbial decomposer community present. Since microbial community composition and SOM properties are often interrelated and both change with soil depth, the drivers of enzymatic decomposition are hard to dissect. We investigated soils from three regions in the Siberian Arctic, where carbon rich topsoil material has been incorporated into the subsoil (cryoturbation). We took advantage of this subduction to test if SOM properties shape microbial community composition, and to identify controls of both on enzyme activities. We found that microbial community composition (estimated by phospholipid fatty acid analysis), was similar in cryoturbated material and in surrounding subsoil, although carbon and nitrogen contents were similar in cryoturbated material and topsoils. This suggests that the microbial community in cryoturbated material was not well adapted to SOM properties. We also measured three potential enzyme activities (cellobiohydrolase, leucine-amino-peptidase and phenoloxidase) and used structural equation models (SEMs) to identify direct and indirect drivers of the three enzyme activities. The models included microbial community composition, carbon and nitrogen contents, clay content, water content, and pH. Models for regular horizons, excluding cryoturbated material, showed that all enzyme activities were mainly controlled by carbon or nitrogen. Microbial community composition had no effect. In contrast, models for cryoturbated material showed that enzyme activities were also related to microbial community composition. The additional control of microbial community composition could have restrained enzyme activities and furthermore decomposition in general. The functional decoupling of SOM properties and microbial community composition might thus be one of the reasons for low decomposition rates and the persistence of 400 Gt carbon stored in cryoturbated material. PMID:24705618

Forecasting hotspots in East Kutai, Kutai Kartanegara, and West Kutai as early warning information

NASA Astrophysics Data System (ADS)

Wahyuningsih, S.; Goejantoro, R.; Rizki, N. A.

2018-04-01

The aims of this research are to model hotspots and forecast hotspot 2017 in East Kutai, Kutai Kartanegara and West Kutai. The methods which used in this research were Holt exponential smoothing, Holt’s additive dump trend method, Holt-Winters’ additive method, additive decomposition method, multiplicative decomposition method, Loess decomposition method and Box-Jenkins method. For smoothing techniques, additive decomposition is better than Holt’s exponential smoothing. The hotspots model using Box-Jenkins method were Autoregressive Moving Average ARIMA(1,1,0), ARIMA(0,2,1), and ARIMA(0,1,0). Comparing the results from all methods which were used in this research, and based on Root of Mean Squared Error (RMSE), show that Loess decomposition method is the best times series model, because it has the least RMSE. Thus the Loess decomposition model used to forecast the number of hotspot. The forecasting result indicatethat hotspots pattern tend to increase at the end of 2017 in Kutai Kartanegara and West Kutai, but stationary in East Kutai.

Towards Interactive Construction of Topical Hierarchy: A Recursive Tensor Decomposition Approach

PubMed Central

Wang, Chi; Liu, Xueqing; Song, Yanglei; Han, Jiawei

2015-01-01

Automatic construction of user-desired topical hierarchies over large volumes of text data is a highly desirable but challenging task. This study proposes to give users freedom to construct topical hierarchies via interactive operations such as expanding a branch and merging several branches. Existing hierarchical topic modeling techniques are inadequate for this purpose because (1) they cannot consistently preserve the topics when the hierarchy structure is modified; and (2) the slow inference prevents swift response to user requests. In this study, we propose a novel method, called STROD, that allows efficient and consistent modification of topic hierarchies, based on a recursive generative model and a scalable tensor decomposition inference algorithm with theoretical performance guarantee. Empirical evaluation shows that STROD reduces the runtime of construction by several orders of magnitude, while generating consistent and quality hierarchies. PMID:26705505

Wavelet decomposition and radial basis function networks for system monitoring

NASA Astrophysics Data System (ADS)

Ikonomopoulos, A.; Endou, A.

1998-10-01

Two approaches are coupled to develop a novel collection of black box models for monitoring operational parameters in a complex system. The idea springs from the intention of obtaining multiple predictions for each system variable and fusing them before they are used to validate the actual measurement. The proposed architecture pairs the analytical abilities of the discrete wavelet decomposition with the computational power of radial basis function networks. Members of a wavelet family are constructed in a systematic way and chosen through a statistical selection criterion that optimizes the structure of the network. Network parameters are further optimized through a quasi-Newton algorithm. The methodology is demonstrated utilizing data obtained during two transients of the Monju fast breeder reactor. The models developed are benchmarked with respect to similar regressors based on Gaussian basis functions.

Towards Interactive Construction of Topical Hierarchy: A Recursive Tensor Decomposition Approach.

PubMed

Wang, Chi; Liu, Xueqing; Song, Yanglei; Han, Jiawei

2015-08-01

Automatic construction of user-desired topical hierarchies over large volumes of text data is a highly desirable but challenging task. This study proposes to give users freedom to construct topical hierarchies via interactive operations such as expanding a branch and merging several branches. Existing hierarchical topic modeling techniques are inadequate for this purpose because (1) they cannot consistently preserve the topics when the hierarchy structure is modified; and (2) the slow inference prevents swift response to user requests. In this study, we propose a novel method, called STROD, that allows efficient and consistent modification of topic hierarchies, based on a recursive generative model and a scalable tensor decomposition inference algorithm with theoretical performance guarantee. Empirical evaluation shows that STROD reduces the runtime of construction by several orders of magnitude, while generating consistent and quality hierarchies.

Uncertainty Analysis of Decomposing Polyurethane Foam

NASA Technical Reports Server (NTRS)

Hobbs, Michael L.; Romero, Vicente J.

2000-01-01

Sensitivity/uncertainty analyses are necessary to determine where to allocate resources for improved predictions in support of our nation's nuclear safety mission. Yet, sensitivity/uncertainty analyses are not commonly performed on complex combustion models because the calculations are time consuming, CPU intensive, nontrivial exercises that can lead to deceptive results. To illustrate these ideas, a variety of sensitivity/uncertainty analyses were used to determine the uncertainty associated with thermal decomposition of polyurethane foam exposed to high radiative flux boundary conditions. The polyurethane used in this study is a rigid closed-cell foam used as an encapsulant. Related polyurethane binders such as Estane are used in many energetic materials of interest to the JANNAF community. The complex, finite element foam decomposition model used in this study has 25 input parameters that include chemistry, polymer structure, and thermophysical properties. The response variable was selected as the steady-state decomposition front velocity calculated as the derivative of the decomposition front location versus time. An analytical mean value sensitivity/uncertainty (MV) analysis was used to determine the standard deviation by taking numerical derivatives of the response variable with respect to each of the 25 input parameters. Since the response variable is also a derivative, the standard deviation was essentially determined from a second derivative that was extremely sensitive to numerical noise. To minimize the numerical noise, 50-micrometer element dimensions and approximately 1-msec time steps were required to obtain stable uncertainty results. As an alternative method to determine the uncertainty and sensitivity in the decomposition front velocity, surrogate response surfaces were generated for use with a constrained Latin Hypercube Sampling (LHS) technique. Two surrogate response surfaces were investigated: 1) a linear surrogate response surface (LIN) and 2) a quadratic response surface (QUAD). The LHS techniques do not require derivatives of the response variable and are subsequently relatively insensitive to numerical noise. To compare the LIN and QUAD methods to the MV method, a direct LHS analysis (DLHS) was performed using the full grid and timestep resolved finite element model. The surrogate response models (LIN and QUAD) are shown to give acceptable values of the mean and standard deviation when compared to the fully converged DLHS model.

The relationship between two fast/slow analysis techniques for bursting oscillations

PubMed Central

Teka, Wondimu; Tabak, Joël; Bertram, Richard

2012-01-01

Bursting oscillations in excitable systems reflect multi-timescale dynamics. These oscillations have often been studied in mathematical models by splitting the equations into fast and slow subsystems. Typically, one treats the slow variables as parameters of the fast subsystem and studies the bifurcation structure of this subsystem. This has key features such as a z-curve (stationary branch) and a Hopf bifurcation that gives rise to a branch of periodic spiking solutions. In models of bursting in pituitary cells, we have recently used a different approach that focuses on the dynamics of the slow subsystem. Characteristic features of this approach are folded node singularities and a critical manifold. In this article, we investigate the relationships between the key structures of the two analysis techniques. We find that the z-curve and Hopf bifurcation of the two-fast/one-slow decomposition are closely related to the voltage nullcline and folded node singularity of the one-fast/two-slow decomposition, respectively. They become identical in the double singular limit in which voltage is infinitely fast and calcium is infinitely slow. PMID:23278052

Emergent causality and the N-photon scattering matrix in waveguide QED

NASA Astrophysics Data System (ADS)

Sánchez-Burillo, E.; Cadarso, A.; Martín-Moreno, L.; García-Ripoll, J. J.; Zueco, D.

2018-01-01

In this work we discuss the emergence of approximate causality in a general setup from waveguide QED—i.e. a one-dimensional propagating field interacting with a scatterer. We prove that this emergent causality translates into a structure for the N-photon scattering matrix. Our work builds on the derivation of a Lieb-Robinson-type bound for continuous models and for all coupling strengths, as well as on several intermediate results, of which we highlight: (i) the asymptotic independence of space-like separated wave packets, (ii) the proper definition of input and output scattering states, and (iii) the characterization of the ground state and correlations in the model. We illustrate our formal results by analyzing the two-photon scattering from a quantum impurity in the ultrastrong coupling regime, verifying the cluster decomposition and ground-state nature. Besides, we generalize the cluster decomposition if inelastic or Raman scattering occurs, finding the structure of the S-matrix in momentum space for linear dispersion relations. In this case, we compute the decay of the fluorescence (photon-photon correlations) caused by this S-matrix.

Density functional theory based screening of ternary alkali-transition metal borohydrides: A computational material design project

NASA Astrophysics Data System (ADS)

Hummelshøj, J. S.; Landis, D. D.; Voss, J.; Jiang, T.; Tekin, A.; Bork, N.; Dułak, M.; Mortensen, J. J.; Adamska, L.; Andersin, J.; Baran, J. D.; Barmparis, G. D.; Bell, F.; Bezanilla, A. L.; Bjork, J.; Björketun, M. E.; Bleken, F.; Buchter, F.; Bürkle, M.; Burton, P. D.; Buus, B. B.; Calborean, A.; Calle-Vallejo, F.; Casolo, S.; Chandler, B. D.; Chi, D. H.; Czekaj, I.; Datta, S.; Datye, A.; DeLaRiva, A.; Despoja, V.; Dobrin, S.; Engelund, M.; Ferrighi, L.; Frondelius, P.; Fu, Q.; Fuentes, A.; Fürst, J.; García-Fuente, A.; Gavnholt, J.; Goeke, R.; Gudmundsdottir, S.; Hammond, K. D.; Hansen, H. A.; Hibbitts, D.; Hobi, E.; Howalt, J. G.; Hruby, S. L.; Huth, A.; Isaeva, L.; Jelic, J.; Jensen, I. J. T.; Kacprzak, K. A.; Kelkkanen, A.; Kelsey, D.; Kesanakurthi, D. S.; Kleis, J.; Klüpfel, P. J.; Konstantinov, I.; Korytar, R.; Koskinen, P.; Krishna, C.; Kunkes, E.; Larsen, A. H.; Lastra, J. M. G.; Lin, H.; Lopez-Acevedo, O.; Mantega, M.; Martínez, J. I.; Mesa, I. N.; Mowbray, D. J.; Mýrdal, J. S. G.; Natanzon, Y.; Nistor, A.; Olsen, T.; Park, H.; Pedroza, L. S.; Petzold, V.; Plaisance, C.; Rasmussen, J. A.; Ren, H.; Rizzi, M.; Ronco, A. S.; Rostgaard, C.; Saadi, S.; Salguero, L. A.; Santos, E. J. G.; Schoenhalz, A. L.; Shen, J.; Smedemand, M.; Stausholm-Møller, O. J.; Stibius, M.; Strange, M.; Su, H. B.; Temel, B.; Toftelund, A.; Tripkovic, V.; Vanin, M.; Viswanathan, V.; Vojvodic, A.; Wang, S.; Wellendorff, J.; Thygesen, K. S.; Rossmeisl, J.; Bligaard, T.; Jacobsen, K. W.; Nørskov, J. K.; Vegge, T.

2009-07-01

We present a computational screening study of ternary metal borohydrides for reversible hydrogen storage based on density functional theory. We investigate the stability and decomposition of alloys containing 1 alkali metal atom, Li, Na, or K (M1); and 1 alkali, alkaline earth or 3d/4d transition metal atom (M2) plus two to five (BH4)- groups, i.e., M1M2(BH4)2-5, using a number of model structures with trigonal, tetrahedral, octahedral, and free coordination of the metal borohydride complexes. Of the over 700 investigated structures, about 20 were predicted to form potentially stable alloys with promising decomposition energies. The M1(Al/Mn/Fe)(BH4)4, (Li/Na)Zn(BH4)3, and (Na/K)(Ni/Co)(BH4)3 alloys are found to be the most promising, followed by selected M1(Nb/Rh)(BH4)4 alloys.

Design and Evaluation of a Boron Dipyrrin Electrophore for Redox Flow Batteries.

PubMed

Heiland, Niklas; Cidarér, Clemens; Rohr, Camilla; Piescheck, Mathias; Ahrens, Johannes; Bröring, Martin; Schröder, Uwe

2017-08-29

A boron dipyrrin (BODIPY) dye was designed as a molecular single-component electrophore for redox flow batteries. All positions of the BODIPY core were assessed on the basis of literature data, in particular cyclic voltammetry and density functional calculations, and a minimum required substitution pattern was designed to provide solubility, aggregation, radical cation and anion stabilities, a large potential window, and synthetic accessibility. In-depth electrochemical and physical studies of this electrophore revealed suitable cathodic behavior and stability of the radical anion but rapid anodic decomposition of the radical cation. The three products that formed under the conditions of controlled oxidative electrolysis were isolated, and their structures were determined by spectroscopy and comparison with a synthetic model compound. From these structures, a benzylic radical reactivity, initiated by one-electron oxidation, was concluded to play the major role in this unexpected decomposition. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

The Variability of Internal Tides in the Northern South China Sea

DTIC Science & Technology

2013-08-27

mean N(z) profile from the climatology dataset provided by the Generalized Digital Environmental Model ( GDEM ) (Teague et al. 1990) (Fig. 2). Eigenmode...decomposed eigenmodes have similar magnitude. The GDEM profiles for the eigenmode decomposition are used for this analysis because the profiles from...provided by the Generalized Digital Environmental Model ( GDEM ) and the shading represents one standard deviation. b Vertical structures of the first

Papua New Guinea MT: Looking where seismic is blind

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hoversten, G.M.

1996-11-01

Hydrocarbon exploration in the Papuan fold belt is made extremely difficult by mountainous terrain, equatorial jungle and thick karstified Miocene limestones at the surface. The high-velocity karstified limestones at or near the surface often render the seismic technique useless for imaging the subsurface. In such areas magnetotellurics (MT) provides a valuable capability for mapping subsurface structure. Numerical and field data examples are presented which demonstrate the severity of the 1D errors and the improvements in accuracy which can be achieved using a 2D inverse solution. Two MT lines over adjacent anticlines, both with well control and seismic data, are usedmore » to demonstrate the application of 1D and 2D inversions for structural models. The example over the Hides anticline illustrates a situation where 1D inversion of either TE or TM mode provides essentially the same depth to base of Darai as 2D inversion of both TE and TM. The example over the Angore anticline illustrates the inadequacy of 1D inversion in structurally complex geology complicated by electrical statics. Four MT lines along the Angore anticline have been interpreted using 2D inversion. Three-dimensional modelling has been used to simulate 3D statics in an otherwise 2D earth. These data were used to test the Groom-Bailey (GB) decomposition for possible benefits in reducing static effects and estimating geoelectric strike in the Papua New Guinea (PNG) field data. It has been found that the GB decomposition can provide improved regional 2D strike estimates in 3D contaminated data. However, in situations such as PNG, where the regional 2D strike is well established and hence can be fixed, the GB decomposition provides apparent resistivities identical to those simply rotated to strike.« less

Utilization of a balanced steady state free precession signal model for improved fat/water decomposition.

PubMed

Henze Bancroft, Leah C; Strigel, Roberta M; Hernando, Diego; Johnson, Kevin M; Kelcz, Frederick; Kijowski, Richard; Block, Walter F

2016-03-01

Chemical shift based fat/water decomposition methods such as IDEAL are frequently used in challenging imaging environments with large B0 inhomogeneity. However, they do not account for the signal modulations introduced by a balanced steady state free precession (bSSFP) acquisition. Here we demonstrate improved performance when the bSSFP frequency response is properly incorporated into the multipeak spectral fat model used in the decomposition process. Balanced SSFP allows for rapid imaging but also introduces a characteristic frequency response featuring periodic nulls and pass bands. Fat spectral components in adjacent pass bands will experience bulk phase offsets and magnitude modulations that change the expected constructive and destructive interference between the fat spectral components. A bSSFP signal model was incorporated into the fat/water decomposition process and used to generate images of a fat phantom, and bilateral breast and knee images in four normal volunteers at 1.5 Tesla. Incorporation of the bSSFP signal model into the decomposition process improved the performance of the fat/water decomposition. Incorporation of this model allows rapid bSSFP imaging sequences to use robust fat/water decomposition methods such as IDEAL. While only one set of imaging parameters were presented, the method is compatible with any field strength or repetition time. © 2015 Wiley Periodicals, Inc.

Structure and decomposition of the silver formate Ag(HCO{sub 2})

DOE Office of Scientific and Technical Information (OSTI.GOV)

Puzan, Anna N., E-mail: anna_puzan@mail.ru; Baumer, Vyacheslav N.; Mateychenko, Pavel V.

Crystal structure of the silver formate Ag(HCO{sub 2}) has been determined (orthorhombic, sp.gr. Pccn, a=7.1199(5), b=10.3737(4), c=6.4701(3)Å, V=477.88(4) Å{sup 3}, Z=8). The structure contains isolated formate ions and the pairs Ag{sub 2}{sup 2+} which form the layers in (001) planes (the shortest Ag–Ag distances is 2.919 in the pair and 3.421 and 3.716 Å between the nearest Ag atoms of adjacent pairs). Silver formate is unstable compound which decompose spontaneously vs time. Decomposition was studied using Rietveld analysis of the powder diffraction patterns. It was concluded that the diffusion of Ag atoms leads to the formation of plate-like metal particlesmore » as nuclei in the (100) planes which settle parallel to (001) planes of the silver formate matrix. - Highlights: • Silver formate Ag(HCO{sub 2}) was synthesized and characterized. • Layered packing of Ag-Ag pairs in the structure was found. • Decomposition of Ag(HCO{sub 2}) and formation of metal phase were studied. • Rietveld-refined micro-structural characteristics during decomposition reveal the space relationship between the matrix structure and forming Ag phase REPLACE with: Space relationship between the matrix structure and forming Ag phase.« less

Theoretical study of gas hydrate decomposition kinetics: model predictions.

PubMed

Windmeier, Christoph; Oellrich, Lothar R

2013-11-27

In order to provide an estimate of intrinsic gas hydrate dissolution and dissociation kinetics, the Consecutive Desorption and Melting Model (CDM) was developed in a previous publication (Windmeier, C.; Oellrich, L. R. J. Phys. Chem. A 2013, 117, 10151-10161). In this work, an extensive summary of required model data is given. Obtained model predictions are discussed with respect to their temperature dependence as well as their significance for technically relevant areas of gas hydrate decomposition. As a result, an expression for determination of the intrinsic gas hydrate decomposition kinetics for various hydrate formers is given together with an estimate for the maximum possible rates of gas hydrate decomposition.

A communication library for the parallelization of air quality models on structured grids

NASA Astrophysics Data System (ADS)

Miehe, Philipp; Sandu, Adrian; Carmichael, Gregory R.; Tang, Youhua; Dăescu, Dacian

PAQMSG is an MPI-based, Fortran 90 communication library for the parallelization of air quality models (AQMs) on structured grids. It consists of distribution, gathering and repartitioning routines for different domain decompositions implementing a master-worker strategy. The library is architecture and application independent and includes optimization strategies for different architectures. This paper presents the library from a user perspective. Results are shown from the parallelization of STEM-III on Beowulf clusters. The PAQMSG library is available on the web. The communication routines are easy to use, and should allow for an immediate parallelization of existing AQMs. PAQMSG can also be used for constructing new models.

Simulation of Structural Transformations in Heating of Alloy Steel

NASA Astrophysics Data System (ADS)

Kurkin, A. S.; Makarov, E. L.; Kurkin, A. B.; Rubtsov, D. E.; Rubtsov, M. E.

2017-07-01

Amathematical model for computer simulation of structural transformations in an alloy steel under the conditions of the thermal cycle of multipass welding is presented. The austenitic transformation under the heating and the processes of decomposition of bainite and martensite under repeated heating are considered. Amethod for determining the necessary temperature-time parameters of the model from the chemical composition of the steel is described. Published data are processed and the results used to derive regression models of the temperature ranges and parameters of transformation kinetics of alloy steels. The method developed is used in computer simulation of the process of multipass welding of pipes by the finite-element method.

On the combinatorics of sparsification.

PubMed

Huang, Fenix Wd; Reidys, Christian M

2012-10-22

We study the sparsification of dynamic programming based on folding algorithms of RNA structures. Sparsification is a method that improves significantly the computation of minimum free energy (mfe) RNA structures. We provide a quantitative analysis of the sparsification of a particular decomposition rule, Λ∗. This rule splits an interval of RNA secondary and pseudoknot structures of fixed topological genus. Key for quantifying sparsifications is the size of the so called candidate sets. Here we assume mfe-structures to be specifically distributed (see Assumption 1) within arbitrary and irreducible RNA secondary and pseudoknot structures of fixed topological genus. We then present a combinatorial framework which allows by means of probabilities of irreducible sub-structures to obtain the expectation of the Λ∗-candidate set w.r.t. a uniformly random input sequence. We compute these expectations for arc-based energy models via energy-filtered generating functions (GF) in case of RNA secondary structures as well as RNA pseudoknot structures. Furthermore, for RNA secondary structures we also analyze a simplified loop-based energy model. Our combinatorial analysis is then compared to the expected number of Λ∗-candidates obtained from the folding mfe-structures. In case of the mfe-folding of RNA secondary structures with a simplified loop-based energy model our results imply that sparsification provides a significant, constant improvement of 91% (theory) to be compared to an 96% (experimental, simplified arc-based model) reduction. However, we do not observe a linear factor improvement. Finally, in case of the "full" loop-energy model we can report a reduction of 98% (experiment). Sparsification was initially attributed a linear factor improvement. This conclusion was based on the so called polymer-zeta property, which stems from interpreting polymer chains as self-avoiding walks. Subsequent findings however reveal that the O(n) improvement is not correct. The combinatorial analysis presented here shows that, assuming a specific distribution (see Assumption 1), of mfe-structures within irreducible and arbitrary structures, the expected number of Λ∗-candidates is Θ(n2). However, the constant reduction is quite significant, being in the range of 96%. We furthermore show an analogous result for the sparsification of the Λ∗-decomposition rule for RNA pseudoknotted structures of genus one. Finally we observe that the effect of sparsification is sensitive to the employed energy model.

Structure formation and surface chemistry of ionic liquids on model electrode surfaces—Model studies for the electrode | electrolyte interface in Li-ion batteries

NASA Astrophysics Data System (ADS)

Buchner, Florian; Uhl, Benedikt; Forster-Tonigold, Katrin; Bansmann, Joachim; Groß, Axel; Behm, R. Jürgen

2018-05-01

Ionic liquids (ILs) are considered as attractive electrolyte solvents in modern battery concepts such as Li-ion batteries. Here we present a comprehensive review of the results of previous model studies on the interaction of the battery relevant IL 1-butyl-1-methylpyrrolidinium bis(trifluoromethylsulfonyl)imide ([BMP]+[TFSI]-) with a series of structurally and chemically well-defined model electrode surfaces, which are increasingly complex and relevant for battery applications [Ag(111), Au(111), Cu(111), pristine and lithiated highly oriented pyrolytic graphite (HOPG), and rutile TiO2(110)]. Combining surface science techniques such as high resolution scanning tunneling microscopy and X-ray photoelectron spectroscopy for characterizing surface structure and chemical composition in deposited (sub-)monolayer adlayers with dispersion corrected density functional theory based calculations, this work aims at a molecular scale understanding of the fundamental processes at the electrode | electrolyte interface, which are crucial for the development of the so-called solid electrolyte interphase (SEI) layer in batteries. Performed under idealized conditions, in an ultrahigh vacuum environment, these model studies provide detailed insights on the structure formation in the adlayer, the substrate-adsorbate and adsorbate-adsorbate interactions responsible for this, and the tendency for chemically induced decomposition of the IL. To mimic the situation in an electrolyte, we also investigated the interaction of adsorbed IL (sub-)monolayers with coadsorbed lithium. Even at 80 K, postdeposited Li is found to react with the IL, leading to decomposition products such as LiF, Li3N, Li2S, LixSOy, and Li2O. In the absence of a [BMP]+[TFSI]- adlayer, it tends to adsorb, dissolve, or intercalate into the substrate (metals, HOPG) or to react with the substrate (TiO2) above a critical temperature, forming LiOx and Ti3+ species in the latter case. Finally, the formation of stable decomposition products was found to sensitively change the equilibrium between surface Li and Li+ intercalated in the bulk, leading to a deintercalation from lithiated HOPG in the presence of an adsorbed IL adlayer at >230 K. Overall, these results provide detailed insights into the surface chemistry at the solid | electrolyte interface and the initial stages of SEI formation at electrode surfaces in the absence of an applied potential, which is essential for the further improvement of future Li-ion batteries.

A distributed finite-element modeling and control approach for large flexible structures

NASA Technical Reports Server (NTRS)

Young, K. D.

1989-01-01

An unconventional framework is described for the design of decentralized controllers for large flexible structures. In contrast to conventional control system design practice which begins with a model of the open loop plant, the controlled plant is assembled from controlled components in which the modeling phase and the control design phase are integrated at the component level. The developed framework is called controlled component synthesis (CCS) to reflect that it is motivated by the well developed Component Mode Synthesis (CMS) methods which were demonstrated to be effective for solving large complex structural analysis problems for almost three decades. The design philosophy behind CCS is also closely related to that of the subsystem decomposition approach in decentralized control.

Direct and inverse problems of studying the properties of multilayer nanostructures based on a two-dimensional model of X-ray reflection and scattering

NASA Astrophysics Data System (ADS)

Khachaturov, R. V.

2014-06-01

A mathematical model of X-ray reflection and scattering by multilayered nanostructures in the quasi-optical approximation is proposed. X-ray propagation and the electric field distribution inside the multilayered structure are considered with allowance for refraction, which is taken into account via the second derivative with respect to the depth of the structure. This model is used to demonstrate the possibility of solving inverse problems in order to determine the characteristics of irregularities not only over the depth (as in the one-dimensional problem) but also over the length of the structure. An approximate combinatorial method for system decomposition and composition is proposed for solving the inverse problems.

The Complexities of Teaching Prime Decomposition and Multiplicative Structure with Tools to Preservice Elementary Teachers

ERIC Educational Resources Information Center

Kurz, Terri L.; Garcia, Jorge

2012-01-01

Preservice elementary teachers often struggle with prime decomposition and other mathematical topics that correlate with number theory. This paper provides a framework for integrating prime factor tiles into their curriculum with a particular emphasis on prime decomposition. Using this framework, preservice teachers explored and evaluated numbers…

TEMPORAL SIGNATURES OF AIR QUALITY OBSERVATIONS AND MODEL OUTPUTS: DO TIME SERIES DECOMPOSITION METHODS CAPTURE RELEVANT TIME SCALES?

EPA Science Inventory

Time series decomposition methods were applied to meteorological and air quality data and their numerical model estimates. Decomposition techniques express a time series as the sum of a small number of independent modes which hypothetically represent identifiable forcings, thereb...

Structural applications of metal foams considering material and geometrical uncertainty

NASA Astrophysics Data System (ADS)

Moradi, Mohammadreza

Metal foam is a relatively new and potentially revolutionary material that allows for components to be replaced with elements capable of large energy dissipation, or components to be stiffened with elements which will generate significant supplementary energy dissipation when buckling occurs. Metal foams provide a means to explore reconfiguring steel structures to mitigate cross-section buckling in many cases and dramatically increase energy dissipation in all cases. The microstructure of metal foams consists of solid and void phases. These voids have random shape and size. Therefore, randomness ,which is introduced into metal foams during the manufacturing processes, creating more uncertainty in the behavior of metal foams compared to solid steel. Therefore, studying uncertainty in the performance metrics of structures which have metal foams is more crucial than for conventional structures. Therefore, in this study, structural application of metal foams considering material and geometrical uncertainty is presented. This study applies the Sobol' decomposition of a function of many random variables to different problem in structural mechanics. First, the Sobol' decomposition itself is reviewed and extended to cover the case in which the input random variables have Gaussian distribution. Then two examples are given for a polynomial function of 3 random variables and the collapse load of a two story frame. In the structural example, the Sobol' decomposition is used to decompose the variance of the response, the collapse load, into contributions from the individual input variables. This decomposition reveals the relative importance of the individual member yield stresses in determining the collapse load of the frame. In applying the Sobol' decomposition to this structural problem the following issues are addressed: calculation of the components of the Sobol' decomposition by Monte Carlo simulation; the effect of input distribution on the Sobol' decomposition; convergence of estimates of the Sobol' decomposition with sample size using various sampling schemes; the possibility of model reduction guided by the results of the Sobol' decomposition. For the rest of the study the different structural applications of metal foam is investigated. In the first application, it is shown that metal foams have the potential to serve as hysteric dampers in the braces of braced building frames. Using metal foams in the structural braces decreases different dynamic responses such as roof drift, base shear and maximum moment in the columns. Optimum metal foam strengths are different for different earthquakes. In order to use metal foam in the structural braces, metal foams need to have stable cyclic response which might be achievable for metal foams with high relative density. The second application is to improve strength and ductility of a steel tube by filling it with steel foam. Steel tube beams and columns are able to provide significant strength for structures. They have an efficient shape with large second moment of inertia which leads to light elements with high bending strength. Steel foams with high strength to weight ratio are used to fill the steel tube to improves its mechanical behavior. The linear eigenvalue and plastic collapse finite element (FE) analysis are performed on steel foam filled tube under pure compression and three point bending simulation. It is shown that foam improves the maximum strength and the ability of energy absorption of the steel tubes significantly. Different configurations with different volume of steel foam and composite behavior are investigated. It is demonstrated that there are some optimum configurations with more efficient behavior. If composite action between steel foam and steel increases, the strength of the element will improve due to the change of the failure mode from local buckling to yielding. Moreover, the Sobol' decomposition is used to investigate uncertainty in the strength and ductility of the composite tube, including the sensitivity of the strength to input parameters such as the foam density, tube wall thickness, steel properties etc. Monte Carlo simulation is performed on aluminum foam filled tubes under three point bending conditions. The simulation method is nonlinear finite element analysis. Results show that the steel foam properties have a greater effect on ductility of the steel foam filled tube than its strength. Moreover, flexural strength is more sensitive to steel properties than to aluminum foam properties. Finally, the properties of hypothetical structural steel foam C-channels foamed are investigated via simulations. In thin-walled structural members, stability of the walls is the primary driver of structural limit states. Moreover, having a light weight is one of the main advantages of the thin-walled structural members. Therefore, thin-walled structural members made of steel foam exhibit improved strength while maintaining their low weight. Linear eigenvalue, finite strip method (FSM) and plastic collapse FE analysis is used to evaluate the strength and ductility of steel foam C-channels under uniform compression and bending. It is found that replacing steel walls of the C-channel with steel foam walls increases the local buckling resistance and decreases the global buckling resistance of the C-channel. By using the Sobol' decomposition, an optimum configuration for the variable density steel foam C-channel can be found. For high relative density, replacing solid steel of the lips and flange elements with steel foam increases the buckling strength. On the other hand, for low relative density replacing solid steel of the lips and flange elements with steel foam deceases the buckling strength. Moreover, it is shown that buckling strength of the steel foam C-channel is sensitive to the second order Sobol' indices. In summary, it is shown in this research that the metal foams have a great potential to improve different types of structural responses, and there are many promising application for metal foam in civil structures.

Spectral decomposition of nonlinear systems with memory

NASA Astrophysics Data System (ADS)

Svenkeson, Adam; Glaz, Bryan; Stanton, Samuel; West, Bruce J.

2016-02-01

We present an alternative approach to the analysis of nonlinear systems with long-term memory that is based on the Koopman operator and a Lévy transformation in time. Memory effects are considered to be the result of interactions between a system and its surrounding environment. The analysis leads to the decomposition of a nonlinear system with memory into modes whose temporal behavior is anomalous and lacks a characteristic scale. On average, the time evolution of a mode follows a Mittag-Leffler function, and the system can be described using the fractional calculus. The general theory is demonstrated on the fractional linear harmonic oscillator and the fractional nonlinear logistic equation. When analyzing data from an ill-defined (black-box) system, the spectral decomposition in terms of Mittag-Leffler functions that we propose may uncover inherent memory effects through identification of a small set of dynamically relevant structures that would otherwise be obscured by conventional spectral methods. Consequently, the theoretical concepts we present may be useful for developing more general methods for numerical modeling that are able to determine whether observables of a dynamical system are better represented by memoryless operators, or operators with long-term memory in time, when model details are unknown.

First-principles-based kinetic Monte Carlo simulation of nitric oxide decomposition over Pt and Rh surfaces under lean-burn conditions

NASA Astrophysics Data System (ADS)

Mei, Donghai; Ge, Qingfeng; Neurock, Matthew; Kieken, Laurent; Lerou, Jan

First-principles-based kinetic Monte Carlo simulation was used to track the elementary surface transformations involved in the catalytic decomposition of NO over Pt(100) and Rh(100) surfaces under lean-burn operating conditions. Density functional theory (DFT) calculations were carried out to establish the structure and energetics for all reactants, intermediates and products over Pt(100) and Rh(100). Lateral interactions which arise from neighbouring adsorbates were calculated by examining changes in the binding energies as a function of coverage and different coadsorbed configurations. These data were fitted to a bond order conservation (BOC) model which is subsequently used to establish the effects of coverage within the simulation. The intrinsic activation barriers for all the elementary reaction steps in the proposed mechanism of NO reduction over Pt(100) were calculated by using DFT. These values are corrected for coverage effects by using the parametrized BOC model internally within the simulation. This enables a site-explicit kinetic Monte Carlo simulation that can follow the kinetics of NO decomposition over Pt(100) and Rh(100) in the presence of excess oxygen. The simulations are used here to model various experimental protocols including temperature programmed desorption as well as batch catalytic kinetics. The simulation results for the temperature programmed desorption and decomposition of NO over Pt(100) and Rh(100) under vacuum condition were found to be in very good agreement with experimental results. NO decomposition is strongly tied to the temporal number of sites that remain vacant. Experimental results show that Pt is active in the catalytic reaction of NO into N2 and NO2 under lean-burn conditions. The simulated reaction orders for NO and O2 were found to be +0.9 and -0.4 at 723 K, respectively. The simulation also indicates that there is no activity over Rh(100) since the surface becomes poisoned by oxygen.

Application of decomposition techniques to the preliminary design of a transport aircraft

NASA Technical Reports Server (NTRS)

Rogan, J. E.; Mcelveen, R. P.; Kolb, M. A.

1986-01-01

A multifaceted decomposition of a nonlinear constrained optimization problem describing the preliminary design process for a transport aircraft has been made. Flight dynamics, flexible aircraft loads and deformations, and preliminary structural design subproblems appear prominently in the decomposition. The use of design process decomposition for scheduling design projects, a new system integration approach to configuration control, and the application of object-centered programming to a new generation of design tools are discussed.

Thermal Decomposition Mechanism of CL-20 at Different Temperatures by ReaxFF Reactive Molecular Dynamics Simulations.

PubMed

Wang, Fuping; Chen, Lang; Geng, Deshen; Wu, Junying; Lu, Jianying; Wang, Chen

2018-04-26

Hexanitrohexaazaisowurtzitane (CL-20) has a high detonation velocity and pressure, but its sensitivity is also high, which somewhat limits its applications. Therefore, it is important to understand the mechanism and characteristics of thermal decomposition of CL-20. In this study, a ε-CL-20 supercell was constructed and ReaxFF-lg reactive molecular dynamics simulations were performed to investigate thermal decomposition of ε-CL-20 at various temperatures (2000, 2500, 2750, 3000, 3250, and 3500 K). The mechanism of thermal decomposition of CL-20 was analyzed from the aspects of potential energy evolution, the primary reactions, and the intermediate and final product species. The effect of temperature on thermal decomposition of CL-20 is also discussed. The initial reaction path of thermal decomposition of CL-20 is N-NO 2 cleavage to form NO 2 , followed by C-N cleavage, leading to the destruction of the cage structure. A small number of clusters appear in the early reactions and disappear at the end of the reactions. The initial reaction path of CL-20 decomposition is the same at different temperatures. However, as the temperature increases, the decomposition rate of CL-20 increases and the cage structure is destroyed earlier. The temperature greatly affects the rate constants of H 2 O and N 2 , but it has little effect on the rate constants of CO 2 and H 2 .

Residue decomposition of submodel of WEPS

USDA-ARS?s Scientific Manuscript database

The Residue Decomposition submodel of the Wind Erosion Prediction System (WEPS) simulates the decrease in crop residue biomass due to microbial activity. The decomposition process is modeled as a first-order reaction with temperature and moisture as driving variables. Decomposition is a function of ...

Input-decomposition balance of heterotrophic processes in a warm-temperate mixed forest in Japan

NASA Astrophysics Data System (ADS)

Jomura, M.; Kominami, Y.; Ataka, M.; Makita, N.; Dannoura, M.; Miyama, T.; Tamai, K.; Goto, Y.; Sakurai, S.

2010-12-01

Carbon accumulation in forest ecosystem has been evaluated using three approaches. One is net ecosystem exchange (NEE) estimated by tower flux measurement. The second is net ecosystem production (NEP) estimated by biometric measurements. NEP can be expressed as the difference between net primary production and heterotrophic respiration. NEP can also be expressed as the annual increment in the plant biomass (ΔW) plus soil (ΔS) carbon pools defined as follows; NEP = ΔW+ΔS The third approach needs to evaluate annual carbon increment in soil compartment. Soil carbon accumulation rate could not be measured directly in a short term because of the small amount of annual accumulation. Soil carbon accumulation rate can be estimated by a model calculation. Rothamsted carbon model is a soil organic carbon turnover model and a useful tool to estimate the rate of soil carbon accumulation. However, the model has not sufficiently included variations in decomposition processes of organic matters in forest ecosystems. Organic matter in forest ecosystems have a different turnover rate that creates temporal variations in input-decomposition balance and also have a large variation in spatial distribution. Thus, in order to estimate the rate of soil carbon accumulation, temporal and spatial variation in input-decomposition balance of heterotrophic processes should be incorporated in the model. In this study, we estimated input-decomposition balance and the rate of soil carbon accumulation using the modified Roth-C model. We measured respiration rate of many types of organic matters, such as leaf litter, fine root litter, twigs and coarse woody debris using a chamber method. We can illustrate the relation of respiration rate to diameter of organic matters. Leaf and fine root litters have no diameter, so assumed to be zero in diameter. Organic matters in small size, such as leaf and fine root litter, have high decomposition respiration. It could be caused by the difference in structure of organic matter. Because coarse woody debris has shape of cylinder, microbes decompose from the surface of it. Thus, respiration rate of coarse woody debris is lower than that of leaf and fine root litter. Based on this result, we modified Roth-C model and estimate soil carbon accumulation rate in recent years. Based on the results from a soil survey, the forest soil stored 30tC ha-1 in O and A horizon. We can evaluate the modified model using this result. NEP can be expressed as the annual increment in the plant biomass plus soil carbon pools. So if we can estimate NEP using this approach, then we can evaluate NEP estimated by micrometeorological and ecological approaches and reduce uncertainty of NEP estimation.

Structural system identification based on variational mode decomposition

NASA Astrophysics Data System (ADS)

Bagheri, Abdollah; Ozbulut, Osman E.; Harris, Devin K.

2018-03-01

In this paper, a new structural identification method is proposed to identify the modal properties of engineering structures based on dynamic response decomposition using the variational mode decomposition (VMD). The VMD approach is a decomposition algorithm that has been developed as a means to overcome some of the drawbacks and limitations of the empirical mode decomposition method. The VMD-based modal identification algorithm decomposes the acceleration signal into a series of distinct modal responses and their respective center frequencies, such that when combined their cumulative modal responses reproduce the original acceleration response. The decaying amplitude of the extracted modal responses is then used to identify the modal damping ratios using a linear fitting function on modal response data. Finally, after extracting modal responses from available sensors, the mode shape vector for each of the decomposed modes in the system is identified from all obtained modal response data. To demonstrate the efficiency of the algorithm, a series of numerical, laboratory, and field case studies were evaluated. The laboratory case study utilized the vibration response of a three-story shear frame, whereas the field study leveraged the ambient vibration response of a pedestrian bridge to characterize the modal properties of the structure. The modal properties of the shear frame were computed using analytical approach for a comparison with the experimental modal frequencies. Results from these case studies demonstrated that the proposed method is efficient and accurate in identifying modal data of the structures.

Queueing Network Models for Parallel Processing of Task Systems: an Operational Approach

NASA Technical Reports Server (NTRS)

Mak, Victor W. K.

1986-01-01

Computer performance modeling of possibly complex computations running on highly concurrent systems is considered. Earlier works in this area either dealt with a very simple program structure or resulted in methods with exponential complexity. An efficient procedure is developed to compute the performance measures for series-parallel-reducible task systems using queueing network models. The procedure is based on the concept of hierarchical decomposition and a new operational approach. Numerical results for three test cases are presented and compared to those of simulations.

Old and stable soil organic matter is not necessarily chemically recalcitrant: Implications for modeling concepts and temperature sensitivity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kleber, M.; Nico, P.S.; Plante, A.

2010-03-01

Soil carbon turnover models generally divide soil carbon into pools with varying intrinsic decomposition rates. Although these decomposition rates are modified by factors such as temperature, texture, and moisture, they are rationalized by assuming chemical structure is a primary controller of decomposition. In the current work, we use near edge X-ray absorption fine structure (NEXAFS) spectroscopy in combination with differential scanning calorimetry (DSC) and alkaline cupric oxide (CuO) oxidation to explore this assumption. Specifically, we examined material from the 2.3-2.6 kg L{sup -1} density fraction of three soils of different type (Oxisol, Alfisol, Inceptisol). The density fraction with the youngestmore » {sup 14}C age (Oxisol, 107 years) showed the highest relative abundance of aromatic groups and the lowest O-alkyl C/aromatic C ratio as determined by NEXAFS. Conversely, the fraction with the oldest C (Inceptisol, 680 years) had the lowest relative abundance of aromatic groups and highest O-alkyl C/aromatic C ratio. This sample also had the highest proportion of thermally labile materials as measured by DSC, and the highest ratio of substituted fatty acids to lignin phenols as indicated by CuO oxidation. Therefore, the organic matter of the Inceptisol sample, with a {sup 14}C age associated with 'passive' pools of carbon (680 years), had the largest proportion of easily metabolizable organic molecules with low thermodynamic stability, whereas the organic matter of the much younger Oxisol sample (107 years) had the highest proportion of supposedly stable organic structures considered more difficult to metabolize. Our results demonstrate that C age is not necessarily related to molecular structure or thermodynamic stability, and we suggest that soil carbon models would benefit from viewing turnover rate as codetermined by the interaction between substrates, microbial actors, and abiotic driving variables. Furthermore, assuming that old carbon is composed of complex or 'recalcitrant' compounds will erroneously attribute a greater temperature sensitivity to those materials than they may actually possess.« less

Investigations of formation of quasi-static vortex-structures in granular bodies using DEM

NASA Astrophysics Data System (ADS)

Kozicki, Jan; Tejchman, Jacek

2017-06-01

The paper presents some two-dimensional simulation results of vortex-structures in cohesionless initially dense sand during quasi-static passive wall translation. The sand behaviour was simulated using the discrete element method (DEM). Sand grains were modelled by spheres with contact moments to approximately capture the irregular grain shape. In order to detect vortex-structures, the Helmholtz-Hodge decomposition of a flow displacement field from DEM calculations was used. This approach enabled us to distinguish both incompressibility and vorticity in the granular displacement field.

Multilevel decomposition of complete vehicle configuration in a parallel computing environment

NASA Technical Reports Server (NTRS)

Bhatt, Vinay; Ragsdell, K. M.

1989-01-01

This research summarizes various approaches to multilevel decomposition to solve large structural problems. A linear decomposition scheme based on the Sobieski algorithm is selected as a vehicle for automated synthesis of a complete vehicle configuration in a parallel processing environment. The research is in a developmental state. Preliminary numerical results are presented for several example problems.

Coupling experimental data and a prototype model to probe the physical and chemical processes of 2,4-dinitroimidazole solid-phase thermal decomposition

DOE Office of Scientific and Technical Information (OSTI.GOV)

Behrens, R.; Minier, L.; Bulusu, S.

1998-12-31

The time-dependent, solid-phase thermal decomposition behavior of 2,4-dinitroimidazole (2,4-DNI) has been measured utilizing simultaneous thermogravimetric modulated beam mass spectrometry (STMBMS) methods. The decomposition products consist of gaseous and non-volatile polymeric products. The temporal behavior of the gas formation rates of the identified products indicate that the overall thermal decomposition process is complex. In isothermal experiments with 2,4-DNI in the solid phase, four distinguishing features are observed: (1) elevated rates of gas formation are observed during the early stages of the decomposition, which appear to be correlated to the presence of exogenous water in the sample; (2) this is followed bymore » a period of relatively constant rates of gas formation; (3) next, the rates of gas formation accelerate, characteristic of an autocatalytic reaction; (4) finally, the 2,4-DNI is depleted and gaseous decomposition products continue to evolve at a decreasing rate. A physicochemical and mathematical model of the decomposition of 2,4-DNI has been developed and applied to the experimental results. The first generation of this model is described in this paper. Differences between the first generation of the model and the experimental data collected under different conditions suggest refinements for the next generation of the model.« less

Morphological decomposition of 2-D binary shapes into convex polygons: a heuristic algorithm.

PubMed

Xu, J

2001-01-01

In many morphological shape decomposition algorithms, either a shape can only be decomposed into shape components of extremely simple forms or a time consuming search process is employed to determine a decomposition. In this paper, we present a morphological shape decomposition algorithm that decomposes a two-dimensional (2-D) binary shape into a collection of convex polygonal components. A single convex polygonal approximation for a given image is first identified. This first component is determined incrementally by selecting a sequence of basic shape primitives. These shape primitives are chosen based on shape information extracted from the given shape at different scale levels. Additional shape components are identified recursively from the difference image between the given image and the first component. Simple operations are used to repair certain concavities caused by the set difference operation. The resulting hierarchical structure provides descriptions for the given shape at different detail levels. The experiments show that the decomposition results produced by the algorithm seem to be in good agreement with the natural structures of the given shapes. The computational cost of the algorithm is significantly lower than that of an earlier search-based convex decomposition algorithm. Compared to nonconvex decomposition algorithms, our algorithm allows accurate approximations for the given shapes at low coding costs.

Investigation on an ammonia supply system for flue gas denitrification of low-speed marine diesel

PubMed Central

Yuan, Han; Zhao, Jian; Mei, Ning

2017-01-01

Low-speed marine diesel flue gas denitrification is in great demand in the ship transport industry. This research proposes an ammonia supply system which can be used for flue gas denitrification of low-speed marine diesel. In this proposed ammonia supply system, ammonium bicarbonate is selected as the ammonia carrier to produce ammonia and carbon dioxide by thermal decomposition. The diesel engine exhaust heat is used as the heating source for ammonium bicarbonate decomposition and ammonia gas desorption. As the ammonium bicarbonate decomposition is critical to the proper operation of this system, effects have been observed to reveal the performance of the thermal decomposition chamber in this paper. A visualization experiment for determination of the single-tube heat transfer coefficient and simulation of flow and heat transfer in two structures is conducted; the decomposition of ammonium bicarbonate is simulated by ASPEN PLUS. The results show that the single-tube heat transfer coefficient is 1052 W m2 °C−1; the thermal decomposition chamber fork-type structure gets a higher heat transfer compared with the row-type. With regard to the simulation of ammonium bicarbonate thermal decomposition, the ammonia production is significantly affected by the reaction temperature and the mass flow rate of the ammonium bicarbonate input. PMID:29308269

Investigation on an ammonia supply system for flue gas denitrification of low-speed marine diesel

NASA Astrophysics Data System (ADS)

Huang, Xiankun; Yuan, Han; Zhao, Jian; Mei, Ning

2017-12-01

Low-speed marine diesel flue gas denitrification is in great demand in the ship transport industry. This research proposes an ammonia supply system which can be used for flue gas denitrification of low-speed marine diesel. In this proposed ammonia supply system, ammonium bicarbonate is selected as the ammonia carrier to produce ammonia and carbon dioxide by thermal decomposition. The diesel engine exhaust heat is used as the heating source for ammonium bicarbonate decomposition and ammonia gas desorption. As the ammonium bicarbonate decomposition is critical to the proper operation of this system, effects have been observed to reveal the performance of the thermal decomposition chamber in this paper. A visualization experiment for determination of the single-tube heat transfer coefficient and simulation of flow and heat transfer in two structures is conducted; the decomposition of ammonium bicarbonate is simulated by ASPEN PLUS. The results show that the single-tube heat transfer coefficient is 1052 W m2 °C-1; the thermal decomposition chamber fork-type structure gets a higher heat transfer compared with the row-type. With regard to the simulation of ammonium bicarbonate thermal decomposition, the ammonia production is significantly affected by the reaction temperature and the mass flow rate of the ammonium bicarbonate input.

Towards accurate modeling of noncovalent interactions for protein rigidity analysis.

PubMed

Fox, Naomi; Streinu, Ileana

2013-01-01

Protein rigidity analysis is an efficient computational method for extracting flexibility information from static, X-ray crystallography protein data. Atoms and bonds are modeled as a mechanical structure and analyzed with a fast graph-based algorithm, producing a decomposition of the flexible molecule into interconnected rigid clusters. The result depends critically on noncovalent atomic interactions, primarily on how hydrogen bonds and hydrophobic interactions are computed and modeled. Ongoing research points to the stringent need for benchmarking rigidity analysis software systems, towards the goal of increasing their accuracy and validating their results, either against each other and against biologically relevant (functional) parameters. We propose two new methods for modeling hydrogen bonds and hydrophobic interactions that more accurately reflect a mechanical model, without being computationally more intensive. We evaluate them using a novel scoring method, based on the B-cubed score from the information retrieval literature, which measures how well two cluster decompositions match. To evaluate the modeling accuracy of KINARI, our pebble-game rigidity analysis system, we use a benchmark data set of 20 proteins, each with multiple distinct conformations deposited in the Protein Data Bank. Cluster decompositions for them were previously determined with the RigidFinder method from Gerstein's lab and validated against experimental data. When KINARI's default tuning parameters are used, an improvement of the B-cubed score over a crude baseline is observed in 30% of this data. With our new modeling options, improvements were observed in over 70% of the proteins in this data set. We investigate the sensitivity of the cluster decomposition score with case studies on pyruvate phosphate dikinase and calmodulin. To substantially improve the accuracy of protein rigidity analysis systems, thorough benchmarking must be performed on all current systems and future extensions. We have measured the gain in performance by comparing different modeling methods for noncovalent interactions. We showed that new criteria for modeling hydrogen bonds and hydrophobic interactions can significantly improve the results. The two new methods proposed here have been implemented and made publicly available in the current version of KINARI (v1.3), together with the benchmarking tools, which can be downloaded from our software's website, http://kinari.cs.umass.edu.

Towards accurate modeling of noncovalent interactions for protein rigidity analysis

PubMed Central

2013-01-01

Background Protein rigidity analysis is an efficient computational method for extracting flexibility information from static, X-ray crystallography protein data. Atoms and bonds are modeled as a mechanical structure and analyzed with a fast graph-based algorithm, producing a decomposition of the flexible molecule into interconnected rigid clusters. The result depends critically on noncovalent atomic interactions, primarily on how hydrogen bonds and hydrophobic interactions are computed and modeled. Ongoing research points to the stringent need for benchmarking rigidity analysis software systems, towards the goal of increasing their accuracy and validating their results, either against each other and against biologically relevant (functional) parameters. We propose two new methods for modeling hydrogen bonds and hydrophobic interactions that more accurately reflect a mechanical model, without being computationally more intensive. We evaluate them using a novel scoring method, based on the B-cubed score from the information retrieval literature, which measures how well two cluster decompositions match. Results To evaluate the modeling accuracy of KINARI, our pebble-game rigidity analysis system, we use a benchmark data set of 20 proteins, each with multiple distinct conformations deposited in the Protein Data Bank. Cluster decompositions for them were previously determined with the RigidFinder method from Gerstein's lab and validated against experimental data. When KINARI's default tuning parameters are used, an improvement of the B-cubed score over a crude baseline is observed in 30% of this data. With our new modeling options, improvements were observed in over 70% of the proteins in this data set. We investigate the sensitivity of the cluster decomposition score with case studies on pyruvate phosphate dikinase and calmodulin. Conclusion To substantially improve the accuracy of protein rigidity analysis systems, thorough benchmarking must be performed on all current systems and future extensions. We have measured the gain in performance by comparing different modeling methods for noncovalent interactions. We showed that new criteria for modeling hydrogen bonds and hydrophobic interactions can significantly improve the results. The two new methods proposed here have been implemented and made publicly available in the current version of KINARI (v1.3), together with the benchmarking tools, which can be downloaded from our software's website, http://kinari.cs.umass.edu. PMID:24564209

Spreadsheets and Bulgarian goats

NASA Astrophysics Data System (ADS)

Sugden, Steve

2012-10-01

We consider a problem appearing in an Australian Mathematics Challenge in 2003. This article considers whether a spreadsheet might be used to model this problem, thus allowing students to explore its structure within the spreadsheet environment. It then goes on to reflect on some general principles of problem decomposition when the final goal is a successful and lucid spreadsheet implementation.

Application of decomposition techniques to the preliminary design of a transport aircraft

NASA Technical Reports Server (NTRS)

Rogan, J. E.; Kolb, M. A.

1987-01-01

A nonlinear constrained optimization problem describing the preliminary design process for a transport aircraft has been formulated. A multifaceted decomposition of the optimization problem has been made. Flight dynamics, flexible aircraft loads and deformations, and preliminary structural design subproblems appear prominently in the decomposition. The use of design process decomposition for scheduling design projects, a new system integration approach to configuration control, and the application of object-centered programming to a new generation of design tools are discussed.

A study of the parallel algorithm for large-scale DC simulation of nonlinear systems

NASA Astrophysics Data System (ADS)

Cortés Udave, Diego Ernesto; Ogrodzki, Jan; Gutiérrez de Anda, Miguel Angel

Newton-Raphson DC analysis of large-scale nonlinear circuits may be an extremely time consuming process even if sparse matrix techniques and bypassing of nonlinear models calculation are used. A slight decrease in the time required for this task may be enabled on multi-core, multithread computers if the calculation of the mathematical models for the nonlinear elements as well as the stamp management of the sparse matrix entries are managed through concurrent processes. This numerical complexity can be further reduced via the circuit decomposition and parallel solution of blocks taking as a departure point the BBD matrix structure. This block-parallel approach may give a considerable profit though it is strongly dependent on the system topology and, of course, on the processor type. This contribution presents the easy-parallelizable decomposition-based algorithm for DC simulation and provides a detailed study of its effectiveness.

Modal analysis of 2-D sedimentary basin from frequency domain decomposition of ambient vibration array recordings

NASA Astrophysics Data System (ADS)

Poggi, Valerio; Ermert, Laura; Burjanek, Jan; Michel, Clotaire; Fäh, Donat

2015-01-01

Frequency domain decomposition (FDD) is a well-established spectral technique used in civil engineering to analyse and monitor the modal response of buildings and structures. The method is based on singular value decomposition of the cross-power spectral density matrix from simultaneous array recordings of ambient vibrations. This method is advantageous to retrieve not only the resonance frequencies of the investigated structure, but also the corresponding modal shapes without the need for an absolute reference. This is an important piece of information, which can be used to validate the consistency of numerical models and analytical solutions. We apply this approach using advanced signal processing to evaluate the resonance characteristics of 2-D Alpine sedimentary valleys. In this study, we present the results obtained at Martigny, in the Rhône valley (Switzerland). For the analysis, we use 2 hr of ambient vibration recordings from a linear seismic array deployed perpendicularly to the valley axis. Only the horizontal-axial direction (SH) of the ground motion is considered. Using the FDD method, six separate resonant frequencies are retrieved together with their corresponding modal shapes. We compare the mode shapes with results from classical standard spectral ratios and numerical simulations of ambient vibration recordings.

The patch mosaic and ecological decomposition across spatial scales in a managed landscape of northern Wisconsin, USA

Treesearch

Sari C. ​Saunders; Jiquan Chen; Thomas D. Drummer; Thomas R. Crow; Kimberley D. Brosofske; Eric J. Gustafson

2002-01-01

Understanding landscape organization across scales is vital for determining the impacts of management and retaining structurally and functionally diverse ecosystems. We studied the relationships of a functional variable, decomposition, to microclimatic, vegetative and structural features at multiple scales in two distinct landscapes of northern Wisconsin, USA. We hoped...

A Generalized Framework for Reduced-Order Modeling of a Wind Turbine Wake

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hamilton, Nicholas; Viggiano, Bianca; Calaf, Marc

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 seriesmore » 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. 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.« less

Organic Carbon Sorption and Decomposition in Selected Global Soils

DOE Data Explorer

Jagadamma, S.; Mayes, M. A.; Steinweg, J. M.; Wang, G.; Post, W. M.

2014-01-01

This data set reports the results of lab-scale experiments conducted to investigate the dynamics of organic carbon (C) decomposition from several soils from temperate, tropical, arctic, and sub-arctic environments. Results were used to test the newly developed soil microbe decomposition C model--Microbial-ENzyme-medicated Decomposition (MEND).

Simple three-pool model accurately describes patterns of long-term litter decomposition in diverse climates

Treesearch

E. Carol Adair; William J. Parton; Steven J. Del Grosso; Shendee L. Silver; Mark E. Harmon; Sonia A. Hall; Ingrid C. Burke; Stephen C. Hart

2008-01-01

As atmospheric CO2 increases, ecosystem carbon sequestration will largely depend on how global changes in climate will alter the balance between net primary production and decomposition. The response of primary production to climatic change has been examined using well-validated mechanistic models, but the same is not true for decomposition, a...

Boreal soil carbon dynamics under a changing climate: a model inversion approach

Treesearch

Zhaosheng Fan; Jason C. Neff; Jennifer W. Harden; Kimberly P. Wickland

2008-01-01

Several fundamental but important factors controlling the feedback of boreal organic carbon (OC) to climate change were examined using a mechanistic model of soil OC dynamics, including the combined effects of temperature and moisture on the decomposition of OC and the factors controlling carbon quality and decomposition with depth. To estimate decomposition rates and...

Introducing Network Analysis into Science Education: Methodological Research Examining Secondary School Students' Understanding of "Decomposition"

ERIC Educational Resources Information Center

Schizas, Dimitrios; Katrana, Evagelia; Stamou, George

2013-01-01

In the present study we used the technique of word association tests to assess students' cognitive structures during the learning period. In particular, we tried to investigate what students living near a protected area in Greece (Dadia forest) knew about the phenomenon of decomposition. Decomposition was chosen as a stimulus word because it…

The trait contribution to wood decomposition rates of 15 Neotropical tree species.

PubMed

van Geffen, Koert G; Poorter, Lourens; Sass-Klaassen, Ute; van Logtestijn, Richard S P; Cornelissen, Johannes H C

2010-12-01

The decomposition of dead wood is a critical uncertainty in models of the global carbon cycle. Despite this, relatively few studies have focused on dead wood decomposition, with a strong bias to higher latitudes. Especially the effect of interspecific variation in species traits on differences in wood decomposition rates remains unknown. In order to fill these gaps, we applied a novel method to study long-term wood decomposition of 15 tree species in a Bolivian semi-evergreen tropical moist forest. We hypothesized that interspecific differences in species traits are important drivers of variation in wood decomposition rates. Wood decomposition rates (fractional mass loss) varied between 0.01 and 0.31 yr(-1). We measured 10 different chemical, anatomical, and morphological traits for all species. The species' average traits were useful predictors of wood decomposition rates, particularly the average diameter (dbh) of the tree species (R2 = 0.41). Lignin concentration further increased the proportion of explained inter-specific variation in wood decomposition (both negative relations, cumulative R2 = 0.55), although it did not significantly explain variation in wood decomposition rates if considered alone. When dbh values of the actual dead trees sampled for decomposition rate determination were used as a predictor variable, the final model (including dead tree dbh and lignin concentration) explained even more variation in wood decomposition rates (R2 = 0.71), underlining the importance of dbh in wood decomposition. Other traits, including wood density, wood anatomical traits, macronutrient concentrations, and the amount of phenolic extractives could not significantly explain the variation in wood decomposition rates. The surprising results of this multi-species study, in which for the first time a large set of traits is explicitly linked to wood decomposition rates, merits further testing in other forest ecosystems.

International Trade Drives Global Resource Use: A Structural Decomposition Analysis of Raw Material Consumption from 1990-2010.

PubMed

Plank, Barbara; Eisenmenger, Nina; Schaffartzik, Anke; Wiedenhofer, Dominik

2018-04-03

Globalization led to an immense increase of international trade and the emergence of complex global value chains. At the same time, global resource use and pressures on the environment are increasing steadily. With these two processes in parallel, the question arises whether trade contributes positively to resource efficiency, or to the contrary is further driving resource use? In this article, the socioeconomic driving forces of increasing global raw material consumption (RMC) are investigated to assess the role of changing trade relations, extended supply chains and increasing consumption. We apply a structural decomposition analysis of changes in RMC from 1990 to 2010, utilizing the Eora multi-regional input-output (MRIO) model. We find that changes in international trade patterns significantly contributed to an increase of global RMC. Wealthy developed countries play a major role in driving global RMC growth through changes in their trade structures, as they shifted production processes increasingly to less material-efficient input suppliers. Even the dramatic increase in material consumption in the emerging economies has not diminished the role of industrialized countries as drivers of global RMC growth.

X-ray Thomson Scattering in Warm Dense Matter without the Chihara Decomposition.

PubMed

Baczewski, A D; Shulenburger, L; Desjarlais, M P; Hansen, S B; Magyar, R J

2016-03-18

X-ray Thomson scattering is an important experimental technique used to measure the temperature, ionization state, structure, and density of warm dense matter (WDM). The fundamental property probed in these experiments is the electronic dynamic structure factor. In most models, this is decomposed into three terms [J. Chihara, J. Phys. F 17, 295 (1987)] representing the response of tightly bound, loosely bound, and free electrons. Accompanying this decomposition is the classification of electrons as either bound or free, which is useful for gapped and cold systems but becomes increasingly questionable as temperatures and pressures increase into the WDM regime. In this work we provide unambiguous first principles calculations of the dynamic structure factor of warm dense beryllium, independent of the Chihara form, by treating bound and free states under a single formalism. The computational approach is real-time finite-temperature time-dependent density functional theory (TDDFT) being applied here for the first time to WDM. We compare results from TDDFT to Chihara-based calculations for experimentally relevant conditions in shock-compressed beryllium.

Vibration fatigue using modal decomposition

NASA Astrophysics Data System (ADS)

Mršnik, Matjaž; Slavič, Janko; Boltežar, Miha

2018-01-01

Vibration-fatigue analysis deals with the material fatigue of flexible structures operating close to natural frequencies. Based on the uniaxial stress response, calculated in the frequency domain, the high-cycle fatigue model using the S-N curve material data and the Palmgren-Miner hypothesis of damage accumulation is applied. The multiaxial criterion is used to obtain the equivalent uniaxial stress response followed by the spectral moment approach to the cycle-amplitude probability density estimation. The vibration-fatigue analysis relates the fatigue analysis in the frequency domain to the structural dynamics. However, once the stress response within a node is obtained, the physical model of the structure dictating that response is discarded and does not propagate through the fatigue-analysis procedure. The structural model can be used to evaluate how specific dynamic properties (e.g., damping, modal shapes) affect the damage intensity. A new approach based on modal decomposition is presented in this research that directly links the fatigue-damage intensity with the dynamic properties of the system. It thus offers a valuable insight into how different modes of vibration contribute to the total damage to the material. A numerical study was performed showing good agreement between results obtained using the newly presented approach with those obtained using the classical method, especially with regards to the distribution of damage intensity and critical point location. The presented approach also offers orders of magnitude faster calculation in comparison with the conventional procedure. Furthermore, it can be applied in a straightforward way to strain experimental modal analysis results, taking advantage of experimentally measured strains.

Microbial decomposition is highly sensitive to leaf litter emersion in a permanent temperate stream.

PubMed

Mora-Gómez, Juanita; Duarte, Sofia; Cássio, Fernanda; Pascoal, Cláudia; Romaní, Anna M

2018-04-15

Drought frequency and intensity in some temperate regions are forecasted to increase under the ongoing global change, which might expose permanent streams to intermittence and have severe repercussions on stream communities and ecosystem processes. In this study, we investigated the effect of drought duration on microbial decomposition of Populus nigra leaf litter in a temperate permanent stream (Oliveira, NW Portugal). Specifically, we measured the response of the structural (assemblage composition, bacterial and fungal biomass) and functional (leaf litter decomposition, extracellular enzyme activities (EEA), and fungal sporulation) parameters of fungal and bacterial communities on leaf litter exposed to emersion during different time periods (7, 14 and 21d). Emersion time affected microbial assemblages and litter decomposition, but the response differed among variables. Leaf decomposition rates and the activity of β-glucosidase, cellobiohydrolase and phosphatase were gradually reduced with increasing emersion time, while β-xylosidase reduction was similar when emersion last for 7 or more days, and the phenol oxidase reduction was similar at 14 and 21days of leaf emersion. Microbial biomass and fungal sporulation were reduced after 21days of emersion. The structure of microbial assemblages was affected by the duration of the emersion period. The shifts in fungal assemblages were correlated with a decreased microbial capacity to degrade lignin and hemicellulose in leaf litter exposed to emersion. Additionally, some resilience was observed in leaf litter mass loss, bacterial biomass, some enzyme activities and structure of fungal assemblages. Our study shows that drought can strongly alter structural and functional aspects of microbial decomposers. Therefore, the exposure of leaf litter to increasing emersion periods in temperate streams is expected to affect decomposer communities and overall decomposition of plant material by decelerating carbon cycling in streams. Copyright © 2017 Elsevier B.V. All rights reserved.

Problem decomposition by mutual information and force-based clustering

NASA Astrophysics Data System (ADS)

Otero, Richard Edward

The scale of engineering problems has sharply increased over the last twenty years. Larger coupled systems, increasing complexity, and limited resources create a need for methods that automatically decompose problems into manageable sub-problems by discovering and leveraging problem structure. The ability to learn the coupling (inter-dependence) structure and reorganize the original problem could lead to large reductions in the time to analyze complex problems. Such decomposition methods could also provide engineering insight on the fundamental physics driving problem solution. This work forwards the current state of the art in engineering decomposition through the application of techniques originally developed within computer science and information theory. The work describes the current state of automatic problem decomposition in engineering and utilizes several promising ideas to advance the state of the practice. Mutual information is a novel metric for data dependence and works on both continuous and discrete data. Mutual information can measure both the linear and non-linear dependence between variables without the limitations of linear dependence measured through covariance. Mutual information is also able to handle data that does not have derivative information, unlike other metrics that require it. The value of mutual information to engineering design work is demonstrated on a planetary entry problem. This study utilizes a novel tool developed in this work for planetary entry system synthesis. A graphical method, force-based clustering, is used to discover related sub-graph structure as a function of problem structure and links ranked by their mutual information. This method does not require the stochastic use of neural networks and could be used with any link ranking method currently utilized in the field. Application of this method is demonstrated on a large, coupled low-thrust trajectory problem. Mutual information also serves as the basis for an alternative global optimizer, called MIMIC, which is unrelated to Genetic Algorithms. Advancement to the current practice demonstrates the use of MIMIC as a global method that explicitly models problem structure with mutual information, providing an alternate method for globally searching multi-modal domains. By leveraging discovered problem inter- dependencies, MIMIC may be appropriate for highly coupled problems or those with large function evaluation cost. This work introduces a useful addition to the MIMIC algorithm that enables its use on continuous input variables. By leveraging automatic decision tree generation methods from Machine Learning and a set of randomly generated test problems, decision trees for which method to apply are also created, quantifying decomposition performance over a large region of the design space.

Evaluation of global horizontal irradiance to plane-of-array irradiance models at locations across the United States

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lave, Matthew; Hayes, William; Pohl, Andrew

2015-02-02

We report an evaluation of the accuracy of combinations of models that estimate plane-of-array (POA) irradiance from measured global horizontal irradiance (GHI). This estimation involves two steps: 1) decomposition of GHI into direct and diffuse horizontal components and 2) transposition of direct and diffuse horizontal irradiance (DHI) to POA irradiance. Measured GHI and coincident measured POA irradiance from a variety of climates within the United States were used to evaluate combinations of decomposition and transposition models. A few locations also had DHI measurements, allowing for decoupled analysis of either the decomposition or the transposition models alone. Results suggest that decompositionmore » models had mean bias differences (modeled versus measured) that vary with climate. Transposition model mean bias differences depended more on the model than the location. Lastly, when only GHI measurements were available and combinations of decomposition and transposition models were considered, the smallest mean bias differences were typically found for combinations which included the Hay/Davies transposition model.« less

Estimation of beam material random field properties via sensitivity-based model updating using experimental frequency response functions

NASA Astrophysics Data System (ADS)

Machado, M. R.; Adhikari, S.; Dos Santos, J. M. C.; Arruda, J. R. F.

2018-03-01

Structural parameter estimation is affected not only by measurement noise but also by unknown uncertainties which are present in the system. Deterministic structural model updating methods minimise the difference between experimentally measured data and computational prediction. Sensitivity-based methods are very efficient in solving structural model updating problems. Material and geometrical parameters of the structure such as Poisson's ratio, Young's modulus, mass density, modal damping, etc. are usually considered deterministic and homogeneous. In this paper, the distributed and non-homogeneous characteristics of these parameters are considered in the model updating. The parameters are taken as spatially correlated random fields and are expanded in a spectral Karhunen-Loève (KL) decomposition. Using the KL expansion, the spectral dynamic stiffness matrix of the beam is expanded as a series in terms of discretized parameters, which can be estimated using sensitivity-based model updating techniques. Numerical and experimental tests involving a beam with distributed bending rigidity and mass density are used to verify the proposed method. This extension of standard model updating procedures can enhance the dynamic description of structural dynamic models.

Stochastic Blockmodeling of the Modules and Core of the Caenorhabditis elegans Connectome

PubMed Central

Pavlovic, Dragana M.; Vértes, Petra E.; Bullmore, Edward T.; Schafer, William R.; Nichols, Thomas E.

2014-01-01

Recently, there has been much interest in the community structure or mesoscale organization of complex networks. This structure is characterised either as a set of sparsely inter-connected modules or as a highly connected core with a sparsely connected periphery. However, it is often difficult to disambiguate these two types of mesoscale structure or, indeed, to summarise the full network in terms of the relationships between its mesoscale constituents. Here, we estimate a community structure with a stochastic blockmodel approach, the Erdős-Rényi Mixture Model, and compare it to the much more widely used deterministic methods, such as the Louvain and Spectral algorithms. We used the Caenorhabditis elegans (C. elegans) nervous system (connectome) as a model system in which biological knowledge about each node or neuron can be used to validate the functional relevance of the communities obtained. The deterministic algorithms derived communities with 4–5 modules, defined by sparse inter-connectivity between all modules. In contrast, the stochastic Erdős-Rényi Mixture Model estimated a community with 9 blocks or groups which comprised a similar set of modules but also included a clearly defined core, made of 2 small groups. We show that the “core-in-modules” decomposition of the worm brain network, estimated by the Erdős-Rényi Mixture Model, is more compatible with prior biological knowledge about the C. elegans nervous system than the purely modular decomposition defined deterministically. We also show that the blockmodel can be used both to generate stochastic realisations (simulations) of the biological connectome, and to compress network into a small number of super-nodes and their connectivity. We expect that the Erdős-Rényi Mixture Model may be useful for investigating the complex community structures in other (nervous) systems. PMID:24988196

Towards a representation of priming on soil carbon decomposition in the global land biosphere model ORCHIDEE (version 1.9.5.2)

NASA Astrophysics Data System (ADS)

Guenet, Bertrand; Esteban Moyano, Fernando; Peylin, Philippe; Ciais, Philippe; Janssens, Ivan A.

2016-03-01

Priming of soil carbon decomposition encompasses different processes through which the decomposition of native (already present) soil organic matter is amplified through the addition of new organic matter, with new inputs typically being more labile than the native soil organic matter. Evidence for priming comes from laboratory and field experiments, but to date there is no estimate of its impact at global scale and under the current anthropogenic perturbation of the carbon cycle. Current soil carbon decomposition models do not include priming mechanisms, thereby introducing uncertainty when extrapolating short-term local observations to ecosystem and regional to global scale. In this study we present a simple conceptual model of decomposition priming, called PRIM, able to reproduce laboratory (incubation) and field (litter manipulation) priming experiments. Parameters for this model were first optimized against data from 20 soil incubation experiments using a Bayesian framework. The optimized parameter values were evaluated against another set of soil incubation data independent from the ones used for calibration and the PRIM model reproduced the soil incubations data better than the original, CENTURY-type soil decomposition model, whose decomposition equations are based only on first-order kinetics. We then compared the PRIM model and the standard first-order decay model incorporated into the global land biosphere model ORCHIDEE (Organising Carbon and Hydrology In Dynamic Ecosystems). A test of both models was performed at ecosystem scale using litter manipulation experiments from five sites. Although both versions were equally able to reproduce observed decay rates of litter, only ORCHIDEE-PRIM could simulate the observed priming (R2 = 0.54) in cases where litter was added or removed. This result suggests that a conceptually simple and numerically tractable representation of priming adapted to global models is able to capture the sign and magnitude of the priming of litter and soil organic matter.

Towards a representation of priming on soil carbon decomposition in the global land biosphere model ORCHIDEE (version 1.9.5.2)

NASA Astrophysics Data System (ADS)

Guenet, B.; Moyano, F. E.; Peylin, P.; Ciais, P.; Janssens, I. A.

2015-10-01

Priming of soil carbon decomposition encompasses different processes through which the decomposition of native (already present) soil organic matter is amplified through the addition of new organic matter, with new inputs typically being more labile than the native soil organic matter. Evidence for priming comes from laboratory and field experiments, but to date there is no estimate of its impact at global scale and under the current anthropogenic perturbation of the carbon cycle. Current soil carbon decomposition models do not include priming mechanisms, thereby introducing uncertainty when extrapolating short-term local observations to ecosystem and regional to global scale. In this study we present a simple conceptual model of decomposition priming, called PRIM, able to reproduce laboratory (incubation) and field (litter manipulation) priming experiments. Parameters for this model were first optimized against data from 20 soil incubation experiments using a Bayesian framework. The optimized parameter values were evaluated against another set of soil incubation data independent from the ones used for calibration and the PRIM model reproduced the soil incubations data better than the original, CENTURY-type soil decomposition model, whose decomposition equations are based only on first order kinetics. We then compared the PRIM model and the standard first order decay model incorporated into the global land biosphere model ORCHIDEE. A test of both models was performed at ecosystem scale using litter manipulation experiments from 5 sites. Although both versions were equally able to reproduce observed decay rates of litter, only ORCHIDEE-PRIM could simulate the observed priming (R2 = 0.54) in cases where litter was added or removed. This result suggests that a conceptually simple and numerically tractable representation of priming adapted to global models is able to capture the sign and magnitude of the priming of litter and soil organic matter.

Analytical electron microscope study of eight ataxites

NASA Technical Reports Server (NTRS)

Novotny, P. M.; Goldstein, J. I.; Williams, D. B.

1982-01-01

Optical and electron optical (SEM, TEM, AEM) techniques were employed to investigate the fine structure of eight ataxite-iron meteorites. Structural studies indicated that the ataxites can be divided into two groups: a Widmanstaetten decomposition group and a martensite decomposition group. The Widmanstaetten decomposition group has a Type I plessite microstructure and the central taenite regions contain highly dislocated lath martensite. The steep M shaped Ni gradients in the taenite are consistent with the fast cooling rates, of not less than 500 C/my, observed for this group. The martensite decomposition group has a Type III plessite microstructure and contains all the chemical group IVB ataxites. The maximum taenite Ni contents vary from 47.5 to 52.7 wt % and are consistent with slow cooling to low temperatures of not greater than 350 C at cooling rates of not greater than 25 C/my.

Climate fails to predict wood decomposition at regional scales

NASA Astrophysics Data System (ADS)

Bradford, Mark A.; Warren, Robert J., II; Baldrian, Petr; Crowther, Thomas W.; Maynard, Daniel S.; Oldfield, Emily E.; Wieder, William R.; Wood, Stephen A.; King, Joshua R.

2014-07-01

Decomposition of organic matter strongly influences ecosystem carbon storage. In Earth-system models, climate is a predominant control on the decomposition rates of organic matter. This assumption is based on the mean response of decomposition to climate, yet there is a growing appreciation in other areas of global change science that projections based on mean responses can be irrelevant and misleading. We test whether climate controls on the decomposition rate of dead wood--a carbon stock estimated to represent 73 +/- 6 Pg carbon globally--are sensitive to the spatial scale from which they are inferred. We show that the common assumption that climate is a predominant control on decomposition is supported only when local-scale variation is aggregated into mean values. Disaggregated data instead reveal that local-scale factors explain 73% of the variation in wood decomposition, and climate only 28%. Further, the temperature sensitivity of decomposition estimated from local versus mean analyses is 1.3-times greater. Fundamental issues with mean correlations were highlighted decades ago, yet mean climate-decomposition relationships are used to generate simulations that inform management and adaptation under environmental change. Our results suggest that to predict accurately how decomposition will respond to climate change, models must account for local-scale factors that control regional dynamics.

Predicting the decomposition of Scots pine, Norway spruce, and birch stems in Finland.

PubMed

Mäkinen, Harri; Hynynen, Jari; Siitonen, Juha; Sievänen, Risto

2006-10-01

Models were developed for predicting the decomposition of dead wood for the main tree species in Finland, based on data collected from long-term thinning experiments in southern and central Finland. The decomposition rates were strongly related to the number of years after tree death. In contrast to previous studies, which have used the first-order exponential model, we found that the decomposition rate was not constant. Therefore, the Gompertz and Chapman-Richard's functions were fitted to the data. The slow initial decomposition period was mainly due to the fact that most dead trees remained standing as snags after their death. The initial period was followed by a period of rapid decomposition and, finally, by a period of moderately slow decomposition. Birch stems decomposed more rapidly than Scots pine and Norway spruce stems. Decomposition rates of Norway spruce stems were somewhat lower than those of Scots pine. Because the carbon concentration of decaying boles was relatively stable (about 50%) the rate of carbon loss follows that of mass loss. Models were also developed for the probability that a dead tree remains standing as a snag. During the first years after death, the probability was high. Thereafter, it decreased rapidly, the decrease being faster for birch stems than for Scots pine and Norway spruce stems. Almost all stems had fallen down within 40 years after their death. In Scots pine and Norway spruce, most snags remained hard and belonged to decay class 1. In birch, a higher proportion of snags belonged to the more advanced decay classes. The models provide a framework for predicting dead wood dynamics in managed as well as dense unthinned stands. The models can be incorporated into forest management planning systems, thereby facilitating estimates of carbon dynamics.

Computational and Experimental Study of the Structure of Diffusion Flames of Jet Fuel and Its Surrogates at Pressures up to 40 ATM

DTIC Science & Technology

2012-11-21

examination of some of the aromatics show that the model captures well benzene from toluene decomposition in BF, but underpredicts styrene and ethylbenzene ...critical toluene pyrolysis products and stable soot precursors were compared with computational models using two semi-detailed chemical mechanisms... ethylbenzene , which at least one of the mechanisms reproduces quite well. The largest measured species in the incipiently sooting flame is indene, whose

Research and application of a novel hybrid decomposition-ensemble learning paradigm with error correction for daily PM10 forecasting

NASA Astrophysics Data System (ADS)

Luo, Hongyuan; Wang, Deyun; Yue, Chenqiang; Liu, Yanling; Guo, Haixiang

2018-03-01

In this paper, a hybrid decomposition-ensemble learning paradigm combining error correction is proposed for improving the forecast accuracy of daily PM10 concentration. The proposed learning paradigm is consisted of the following two sub-models: (1) PM10 concentration forecasting model; (2) error correction model. In the proposed model, fast ensemble empirical mode decomposition (FEEMD) and variational mode decomposition (VMD) are applied to disassemble original PM10 concentration series and error sequence, respectively. The extreme learning machine (ELM) model optimized by cuckoo search (CS) algorithm is utilized to forecast the components generated by FEEMD and VMD. In order to prove the effectiveness and accuracy of the proposed model, two real-world PM10 concentration series respectively collected from Beijing and Harbin located in China are adopted to conduct the empirical study. The results show that the proposed model performs remarkably better than all other considered models without error correction, which indicates the superior performance of the proposed model.

Automatic network coupling analysis for dynamical systems based on detailed kinetic models.

PubMed

Lebiedz, Dirk; Kammerer, Julia; Brandt-Pollmann, Ulrich

2005-10-01

We introduce a numerical complexity reduction method for the automatic identification and analysis of dynamic network decompositions in (bio)chemical kinetics based on error-controlled computation of a minimal model dimension represented by the number of (locally) active dynamical modes. Our algorithm exploits a generalized sensitivity analysis along state trajectories and subsequent singular value decomposition of sensitivity matrices for the identification of these dominant dynamical modes. It allows for a dynamic coupling analysis of (bio)chemical species in kinetic models that can be exploited for the piecewise computation of a minimal model on small time intervals and offers valuable functional insight into highly nonlinear reaction mechanisms and network dynamics. We present results for the identification of network decompositions in a simple oscillatory chemical reaction, time scale separation based model reduction in a Michaelis-Menten enzyme system and network decomposition of a detailed model for the oscillatory peroxidase-oxidase enzyme system.

The response of soil carbon storage and microbially mediated carbon turnover to simulated climatic disturbance in a northern peatland forest. Revisiting the concept of soil organic matter recalcitrance

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kostka, Joel

The goal of this project was to investigate changes in the structure of dissolved and solid phase organic matter, the production of CO 2 and CH 4, and the composition of decomposer microbial communities in response to the climatic forcing of environmental processes that determine the balance between carbon gas production versus storage and sequestration in peatlands. Cutting-edge analytical chemistry and next generation sequencing of microbial genes were been applied to habitats at the Marcell Experimental Forest (MEF), where the US DOE’s Oak Ridge National Laboratory and the USDA Forest Service are constructing a large-scale ecosystem study entitled, “Spruce andmore » Peatland Responses Under Climatic and Environmental Change”(SPRUCE). Our study represented a comprehensive characterization of the sources, transformation, and decomposition of organic matter in the S1 bog at MEF. Multiple lines of evidence point to distinct, vertical zones of organic matter transformation: 1) the acrotelm consisting of living mosses, root material, and newly formed litter (0-30 cm), 2) the mesotelm, a mid-depth transition zone (30-75 cm) characterized by labile organic C compounds and intense decomposition, and 3) the underlying catotelm (below 75cm) characterized by refractory organic compounds as well as relatively low decomposition rates. These zones are in part defined by physical changes in hydraulic conductivity and water table depth. O-alkyl-C, which represents the carbohydrate fraction in the peat, was shown to be an excellent proxy for soil decomposition rates. The carbon cycle in deep peat was shown to be fueled by modern carbon sources further indicating that hydrology and surface vegetation play a role in belowground carbon cycling. We provide the first metagenomic study of an ombrotrophic peat bog, with novel insights into microbial specialization and functions in this unique terrestrial ecosystem. Vertical structuring of microbial communities closely paralleled the chemical evolution of peat, with large shifts in microbial populations occurring in the biogeochemical hotspot, the mesotelm, where the highest rates of decomposition were detected. Stable isotope geochemistry and potential rates of methane production paralleled vertical changes in methanogen community composition to indicate a predominance of acetoclastic methanogenesis mediated by the Methanosarcinales in the mesotelm, while hydrogen-utilizing methanogens dominated in the deeper catotelm. Evidence pointed to the availability of phosphorus as well as nitrogen limiting the microbially-mediated turnover of organic carbon at MEF. Prior to initiation of the experimental treatments, our study provided key baseline data for the SPRUCE site on the vertical stratification of peat decomposition, key enzymatic pathways, and microbial taxa containing these pathways. The sensitivity of soil carbon turnover to climate change is strongly linked to recalcitrant carbon stocks and the temperature sensitivity of decomposition is thought to increase with increasing molecular complexity of carbon substrates. This project delivered results on how climate change perturbations impact the microbially-mediated turnover of recalcitrant organic matter in peatland forest soils, both under controlled conditions in the laboratory and at the ecosystem-scale in the field. This project revisited the concept of “recalcitrance” in the regulation of soil carbon turnover using a combination of natural abundance radiocarbon and optical spectroscopic measurements on bulk DOM, and high resolution molecular characterization of DOM. The project elucidated how organic matter reactivity and decomposition will respond to climate change in a both a qualitative (organic matter lability) and quantitiative (increased rates) manner. An Aromaticity Index was developed to represent a more direct and accurate parameter for modeling of DOM reactivity in peatlands. The abundance and community composition of soil microorganisms that mediate C cycling were interrogated with depth in the peat, with season, and in manipulated climate enclosures at unprecedented resolution. Therefore this project delivered strategic new insights on the functioning of peatland ecosystems that collectively store approximately one-third of the world's soil carbon. Furthermore, results from the detailed characterization of DOM lability and microbial community structure/ function will be employed to further develop biogeochemical models to include microbial respiration pathways as well as to track carbon flow with a term that incorporates relative reactivity based on aromaticity index. As it stands now, detailed soil organic matter structure and microbial parameters are not included in Earth system models.« less

A compositional approach to building applications in a computational environment

NASA Astrophysics Data System (ADS)

Roslovtsev, V. V.; Shumsky, L. D.; Wolfengagen, V. E.

2014-04-01

The paper presents an approach to creating an applicative computational environment to feature computational processes and data decomposition, and a compositional approach to application building. The approach in question is based on the notion of combinator - both in systems with variable binding (such as λ-calculi) and those allowing programming without variables (combinatory logic style). We present a computation decomposition technique based on objects' structural decomposition, with the focus on computation decomposition. The computational environment's architecture is based on a network with nodes playing several roles simultaneously.

A one-step thermal decomposition method to prepare anatase TiO2 nanosheets with improved adsorption capacities and enhanced photocatalytic activities

NASA Astrophysics Data System (ADS)

Li, Wenting; Shang, Chunli; Li, Xue

2015-12-01

Anatase TiO2 nanosheets (NSs) with high surface area have been prepared via a one-step thermal decomposition of titanium tetraisopropoxide (TTIP) in oleylamine (OM), and their adsorption capacities and photocatalytic activities are investigated by using methylene blue (MB) and methyl orange (MO) as model pollutants. During the synthesis procedure, only one type of surfactant, oleylamine (OM), is used as capping agents and no other solvents are added. Structure and properties of the TiO2 NSs were characterized by X-ray diffraction (XRD), transmission electron microscopy (TEM), N2 adsorption analysis, UV-vis spectrum, X-ray photoelectron spectroscopy (XPS) and Photoluminescence (PL) methods. The results indicate that the TiO2 NSs possess high surface area up to 378 m2 g-1. The concentration of capping agents is found to be a key factor controlling the morphology and crystalline structure of the product. Adsorption and photodegradation experiments reveal that the prepared TiO2 NSs possess high adsorption capacities of model pollutants MB and high photocatalytic activity, showing that TiO2 NSs can be used as efficient pollutant adsorbents and photocatalytic degradation catalysts of MB in wastewater treatment.

Towards a paradigm shift in the modeling of soil organic carbon decomposition for earth system models

NASA Astrophysics Data System (ADS)

He, Yujie

Soils are the largest terrestrial carbon pools and contain approximately 2200 Pg of carbon. Thus, the dynamics of soil carbon plays an important role in the global carbon cycle and climate system. Earth System Models are used to project future interactions between terrestrial ecosystem carbon dynamics and climate. However, these models often predict a wide range of soil carbon responses and their formulations have lagged behind recent soil science advances, omitting key biogeochemical mechanisms. In contrast, recent mechanistically-based biogeochemical models that explicitly account for microbial biomass pools and enzyme kinetics that catalyze soil carbon decomposition produce notably different results and provide a closer match to recent observations. However, a systematic evaluation of the advantages and disadvantages of the microbial models and how they differ from empirical, first-order formulations in soil decomposition models for soil organic carbon is still needed. This dissertation consists of a series of model sensitivity and uncertainty analyses and identifies dominant decomposition processes in determining soil organic carbon dynamics. Poorly constrained processes or parameters that require more experimental data integration are also identified. This dissertation also demonstrates the critical role of microbial life-history traits (e.g. microbial dormancy) in the modeling of microbial activity in soil organic matter decomposition models. Finally, this study surveys and synthesizes a number of recently published microbial models and provides suggestions for future microbial model developments.

Electricity market pricing, risk hedging and modeling

NASA Astrophysics Data System (ADS)

Cheng, Xu

In this dissertation, we investigate the pricing, price risk hedging/arbitrage, and simplified system modeling for a centralized LMP-based electricity market. In an LMP-based market model, the full AC power flow model and the DC power flow model are most widely used to represent the transmission system. We investigate the differences of dispatching results, congestion pattern, and LMPs for the two power flow models. An appropriate LMP decomposition scheme to quantify the marginal costs of the congestion and real power losses is critical for the implementation of financial risk hedging markets. However, the traditional LMP decomposition heavily depends on the slack bus selection. In this dissertation we propose a slack-independent scheme to break LMP down into energy, congestion, and marginal loss components by analyzing the actual marginal cost of each bus at the optimal solution point. The physical and economic meanings of the marginal effect at each bus provide accurate price information for both congestion and losses, and thus the slack-dependency of the traditional scheme is eliminated. With electricity priced at the margin instead of the average value, the market operator typically collects more revenue from power sellers than that paid to power buyers. According to the LMP decomposition results, the revenue surplus is then divided into two parts: congestion charge surplus and marginal loss revenue surplus. We apply the LMP decomposition results to the financial tools, such as financial transmission right (FTR) and loss hedging right (LHR), which have been introduced to hedge against price risks associated to congestion and losses, to construct a full price risk hedging portfolio. The two-settlement market structure and the introduction of financial tools inevitably create market manipulation opportunities. We investigate several possible market manipulation behaviors by virtual bidding and propose a market monitor approach to identify and quantify such behavior. Finally, the complexity of the power market and size of the transmission grid make it difficult for market participants to efficiently analyze the long-term market behavior. We propose a simplified power system commercial model by simulating the PTDFs of critical transmission bottlenecks of the original system.

Development of a ReaxFF reactive force field for ammonium nitrate and application to shock compression and thermal decomposition.

PubMed

Shan, Tzu-Ray; van Duin, Adri C T; Thompson, Aidan P

2014-02-27

We have developed a new ReaxFF reactive force field parametrization for ammonium nitrate. Starting with an existing nitramine/TATB ReaxFF parametrization, we optimized it to reproduce electronic structure calculations for dissociation barriers, heats of formation, and crystal structure properties of ammonium nitrate phases. We have used it to predict the isothermal pressure-volume curve and the unreacted principal Hugoniot states. The predicted isothermal pressure-volume curve for phase IV solid ammonium nitrate agreed with electronic structure calculations and experimental data within 10% error for the considered range of compression. The predicted unreacted principal Hugoniot states were approximately 17% stiffer than experimental measurements. We then simulated thermal decomposition during heating to 2500 K. Thermal decomposition pathways agreed with experimental findings.

Knot soliton in DNA and geometric structure of its free-energy density.

PubMed

Wang, Ying; Shi, Xuguang

2018-03-01

In general, the geometric structure of DNA is characterized using an elastic rod model. The Landau model provides us a new theory to study the geometric structure of DNA. By using the decomposition of the arc unit in the helical axis of DNA, we find that the free-energy density of DNA is similar to the free-energy density of a two-condensate superconductor. By using the φ-mapping topological current theory, the torus knot soliton hidden in DNA is demonstrated. We show the relation between the geometric structure and free-energy density of DNA and the Frenet equations in differential geometry theory are considered. Therefore, the free-energy density of DNA can be expressed by the curvature and torsion of the helical axis.

Challenges of including nitrogen effects on decomposition in earth system models

NASA Astrophysics Data System (ADS)

Hobbie, S. E.

2011-12-01

Despite the importance of litter decomposition for ecosystem fertility and carbon balance, key uncertainties remain about how this fundamental process is affected by nitrogen (N) availability. Nevertheless, resolving such uncertainties is critical for mechanistic inclusion of such processes in earth system models, towards predicting the ecosystem consequences of increased anthropogenic reactive N. Towards that end, we have conducted a series of experiments examining nitrogen effects on litter decomposition. We found that both substrate N and externally supplied N (regardless of form) accelerated the initial decomposition rate. Faster initial decomposition rates were linked to the higher activity of carbohydrate-degrading enzymes associated with externally supplied N and the greater relative abundances of Gram negative and Gram positive bacteria associated with green leaves and externally supplied organic N (assessed using phospholipid fatty acid analysis, PLFA). By contrast, later in decomposition, externally supplied N slowed decomposition, increasing the fraction of slowly decomposing litter and reducing lignin-degrading enzyme activity and relative abundances of Gram negative and Gram positive bacteria. Our results suggest that elevated atmospheric N deposition may have contrasting effects on the dynamics of different soil carbon pools, decreasing mean residence times of active fractions comprising very fresh litter, while increasing those of more slowly decomposing fractions including more processed litter. Incorporating these contrasting effects of N on decomposition processes into models is complicated by lingering uncertainties about how these effects generalize across ecosystems and substrates.

Low-rank network decomposition reveals structural characteristics of small-world networks

NASA Astrophysics Data System (ADS)

Barranca, Victor J.; Zhou, Douglas; Cai, David

2015-12-01

Small-world networks occur naturally throughout biological, technological, and social systems. With their prevalence, it is particularly important to prudently identify small-world networks and further characterize their unique connection structure with respect to network function. In this work we develop a formalism for classifying networks and identifying small-world structure using a decomposition of network connectivity matrices into low-rank and sparse components, corresponding to connections within clusters of highly connected nodes and sparse interconnections between clusters, respectively. We show that the network decomposition is independent of node indexing and define associated bounded measures of connectivity structure, which provide insight into the clustering and regularity of network connections. While many existing network characterizations rely on constructing benchmark networks for comparison or fail to describe the structural properties of relatively densely connected networks, our classification relies only on the intrinsic network structure and is quite robust with respect to changes in connection density, producing stable results across network realizations. Using this framework, we analyze several real-world networks and reveal new structural properties, which are often indiscernible by previously established characterizations of network connectivity.

China’s marriage squeeze: A decomposition into age and sex structure

PubMed Central

LI, Xiaomin; LI, Shuzhuo; FELDMAN, Marcus W.

2016-01-01

Most recent studies of marriage patterns in China have emphasized the male-biased sex ratio but have largely neglected age structure as a factor in China’s male marriage squeeze. In this paper we develop an index we call “spousal sex ratio” (SSR) to measure the marriage squeeze, and a method of decomposing the proportion of male surplus into age and sex structure effects within a small spousal age difference interval. We project that China’s marriage market will be confronted with a relatively severe male squeeze. For the decomposition of the cohort aged 30, from 2010 to 2020 age structure will be dominant, while from 2020 through 2034 the contribution of age structure will gradually decrease and that of sex structure will increase. From then on, sex structure will be dominant. The index and decomposition, concentrated on a specific female birth cohort, can distinguish spousal competition for single cohorts which may be covered by a summary index for the whole marriage market; these can also be used for consecutive cohorts to reflect the situation of the whole marriage market. PMID:27242390

China's marriage squeeze: A decomposition into age and sex structure.

PubMed

Jiang, Quanbao; Li, Xiaomin; Li, Shuzhuo; Feldman, Marcus W

2016-06-01

Most recent studies of marriage patterns in China have emphasized the male-biased sex ratio but have largely neglected age structure as a factor in China's male marriage squeeze. In this paper we develop an index we call "spousal sex ratio" (SSR) to measure the marriage squeeze, and a method of decomposing the proportion of male surplus into age and sex structure effects within a small spousal age difference interval. We project that China's marriage market will be confronted with a relatively severe male squeeze. For the decomposition of the cohort aged 30, from 2010 to 2020 age structure will be dominant, while from 2020 through 2034 the contribution of age structure will gradually decrease and that of sex structure will increase. From then on, sex structure will be dominant. The index and decomposition, concentrated on a specific female birth cohort, can distinguish spousal competition for single cohorts which may be covered by a summary index for the whole marriage market; these can also be used for consecutive cohorts to reflect the situation of the whole marriage market.

Dictionary-Based Tensor Canonical Polyadic Decomposition

NASA Astrophysics Data System (ADS)

Cohen, Jeremy Emile; Gillis, Nicolas

2018-04-01

To ensure interpretability of extracted sources in tensor decomposition, we introduce in this paper a dictionary-based tensor canonical polyadic decomposition which enforces one factor to belong exactly to a known dictionary. A new formulation of sparse coding is proposed which enables high dimensional tensors dictionary-based canonical polyadic decomposition. The benefits of using a dictionary in tensor decomposition models are explored both in terms of parameter identifiability and estimation accuracy. Performances of the proposed algorithms are evaluated on the decomposition of simulated data and the unmixing of hyperspectral images.

Bubble Divergences: Sorting out Topology from Cell Structure

NASA Astrophysics Data System (ADS)

Bonzom, Valentin; Smerlak, Matteo

2012-02-01

We conclude our analysis of bubble divergences in the flat spinfoam model. In [arXiv:1008.1476] we showed that the divergence degree of an arbitrary two-complex Gamma can be evaluated exactly by means of twisted cohomology. Here, we specialize this result to the case where Gamma is the two-skeleton of the cell decomposition of a pseudomanifold, and sharpen it with a careful analysis of the cellular and topological structures involved. Moreover, we explain in detail how this approach reproduces all the previous powercounting results for the Boulatov-Ooguri (colored) tensor models, and sheds light on algebraic-topological aspects of Gurau's 1/N expansion.

Daily water level forecasting using wavelet decomposition and artificial intelligence techniques

NASA Astrophysics Data System (ADS)

Seo, Youngmin; Kim, Sungwon; Kisi, Ozgur; Singh, Vijay P.

2015-01-01

Reliable water level forecasting for reservoir inflow is essential for reservoir operation. The objective of this paper is to develop and apply two hybrid models for daily water level forecasting and investigate their accuracy. These two hybrid models are wavelet-based artificial neural network (WANN) and wavelet-based adaptive neuro-fuzzy inference system (WANFIS). Wavelet decomposition is employed to decompose an input time series into approximation and detail components. The decomposed time series are used as inputs to artificial neural networks (ANN) and adaptive neuro-fuzzy inference system (ANFIS) for WANN and WANFIS models, respectively. Based on statistical performance indexes, the WANN and WANFIS models are found to produce better efficiency than the ANN and ANFIS models. WANFIS7-sym10 yields the best performance among all other models. It is found that wavelet decomposition improves the accuracy of ANN and ANFIS. This study evaluates the accuracy of the WANN and WANFIS models for different mother wavelets, including Daubechies, Symmlet and Coiflet wavelets. It is found that the model performance is dependent on input sets and mother wavelets, and the wavelet decomposition using mother wavelet, db10, can further improve the efficiency of ANN and ANFIS models. Results obtained from this study indicate that the conjunction of wavelet decomposition and artificial intelligence models can be a useful tool for accurate forecasting daily water level and can yield better efficiency than the conventional forecasting models.

Dominant modal decomposition method

NASA Astrophysics Data System (ADS)

Dombovari, Zoltan

2017-03-01

The paper deals with the automatic decomposition of experimental frequency response functions (FRF's) of mechanical structures. The decomposition of FRF's is based on the Green function representation of free vibratory systems. After the determination of the impulse dynamic subspace, the system matrix is formulated and the poles are calculated directly. By means of the corresponding eigenvectors, the contribution of each element of the impulse dynamic subspace is determined and the sufficient decomposition of the corresponding FRF is carried out. With the presented dominant modal decomposition (DMD) method, the mode shapes, the modal participation vectors and the modal scaling factors are identified using the decomposed FRF's. Analytical example is presented along with experimental case studies taken from machine tool industry.

Decomposition rates of American chestnut (Castanea dentata) wood and implications for coarse woody debris pools

Treesearch

Arjan de Bruijn; Eric J. Gustafson; Daniel M. Kashian; Harmony J. Dalgleish; Brian R. Sturtevant; Douglass F. Jacobs

2014-01-01

Observations of the rapid growth and slow decomposition of American chestnut (Castanea dentata (Marsh.) Borkh.) suggest that its reintroduction could enhance terrestrial carbon (C) sequestration. A suite of decomposition models was fit with decomposition data from coarse woody debris (CWD) sampled in Wisconsin and Virginia, U.S. The optimal (two-...

Perovskite oxides: Oxygen electrocatalysis and bulk structure

NASA Technical Reports Server (NTRS)

Carbonio, R. E.; Fierro, C.; Tryk, D.; Scherson, D.; Yeager, Ernest

1987-01-01

Perovskite type oxides were considered for use as oxygen reduction and generation electrocatalysts in alkaline electrolytes. Perovskite stability and electrocatalytic activity are studied along with possible relationships of the latter with the bulk solid state properties. A series of compounds of the type LaFe(x)Ni1(-x)O3 was used as a model system to gain information on the possible relationships between surface catalytic activity and bulk structure. Hydrogen peroxide decomposition rate constants were measured for these compounds. Ex situ Mossbauer effect spectroscopy (MES), and magnetic susceptibility measurements were used to study the solid state properties. X ray photoelectron spectroscopy (XPS) was used to examine the surface. MES has indicated the presence of a paramagnetic to magnetically ordered phase transition for values of x between 0.4 and 0.5. A correlation was found between the values of the MES isomer shift and the catalytic activity for peroxide decomposition. Thus, the catalytic activity can be correlated to the d-electron density for the transition metal cations.

A modeling study of methane hydrate decomposition in contact with the external surface of zeolites.

PubMed

Smirnov, Konstantin S

2017-08-30

The behavior of methane hydrate (MH) enclosed between the (010) surfaces of the silicalite-1 zeolite was studied by means of molecular dynamics simulations at temperatures of 150 and 250 K. Calculations reveal that the interaction with the hydrophilic surface OH groups destabilizes the clathrate structure of hydrate. While MH mostly conserves the structure in the simulation at the low temperature, thermal motion at the high temperature breaks the fragilized cages of H-bonded water molecules, thus leading to the release of methane. The dissociation proceeds in a layer-by-layer manner starting from the outer parts of the MH slab until complete hydrate decomposition. The released CH 4 molecules are absorbed by the microporous solid, whereas water is retained at the surfaces of hydrophobic silicalite and forms a meniscus in the interlayer space. Methane uptake reaches 70% of the silicalite sorption capacity. The energy necessary for the endothermic MH dissociation is supplied by the exothermic methane absorption by the zeolite.

Perovskite-type oxides - Oxygen electrocatalysis and bulk structure

NASA Technical Reports Server (NTRS)

Carbonio, R. E.; Fierro, C.; Tryk, D.; Scherson, D.; Yeager, E.

1988-01-01

Perovskite type oxides were considered for use as oxygen reduction and generation electrocatalysts in alkaline electrolytes. Perovskite stability and electrocatalytic activity are studied along with possible relationships of the latter with the bulk solid state properties. A series of compounds of the type LaFe(x)Ni1(-x)O3 was used as a model system to gain information on the possible relationships between surface catalytic activity and bulk structure. Hydrogen peroxide decomposition rate constants were measured for these compounds. Ex situ Mossbauer effect spectroscopy (MES), and magnetic susceptibility measurements were used to study the solid state properties. X ray photoelectron spectroscopy (XPS) was used to examine the surface. MES has indicated the presence of a paramagnetic to magnetically ordered phase transition for values of x between 0.4 and 0.5. A correlation was found between the values of the MES isomer shift and the catalytic activity for peroxide decomposition. Thus, the catalytic activity can be correlated to the d-electron density for the transition metal cations.

Corrected confidence bands for functional data using principal components.

PubMed

Goldsmith, J; Greven, S; Crainiceanu, C

2013-03-01

Functional principal components (FPC) analysis is widely used to decompose and express functional observations. Curve estimates implicitly condition on basis functions and other quantities derived from FPC decompositions; however these objects are unknown in practice. In this article, we propose a method for obtaining correct curve estimates by accounting for uncertainty in FPC decompositions. Additionally, pointwise and simultaneous confidence intervals that account for both model- and decomposition-based variability are constructed. Standard mixed model representations of functional expansions are used to construct curve estimates and variances conditional on a specific decomposition. Iterated expectation and variance formulas combine model-based conditional estimates across the distribution of decompositions. A bootstrap procedure is implemented to understand the uncertainty in principal component decomposition quantities. Our method compares favorably to competing approaches in simulation studies that include both densely and sparsely observed functions. We apply our method to sparse observations of CD4 cell counts and to dense white-matter tract profiles. Code for the analyses and simulations is publicly available, and our method is implemented in the R package refund on CRAN. Copyright © 2013, The International Biometric Society.

Corrected Confidence Bands for Functional Data Using Principal Components

PubMed Central

Goldsmith, J.; Greven, S.; Crainiceanu, C.

2014-01-01

Functional principal components (FPC) analysis is widely used to decompose and express functional observations. Curve estimates implicitly condition on basis functions and other quantities derived from FPC decompositions; however these objects are unknown in practice. In this article, we propose a method for obtaining correct curve estimates by accounting for uncertainty in FPC decompositions. Additionally, pointwise and simultaneous confidence intervals that account for both model- and decomposition-based variability are constructed. Standard mixed model representations of functional expansions are used to construct curve estimates and variances conditional on a specific decomposition. Iterated expectation and variance formulas combine model-based conditional estimates across the distribution of decompositions. A bootstrap procedure is implemented to understand the uncertainty in principal component decomposition quantities. Our method compares favorably to competing approaches in simulation studies that include both densely and sparsely observed functions. We apply our method to sparse observations of CD4 cell counts and to dense white-matter tract profiles. Code for the analyses and simulations is publicly available, and our method is implemented in the R package refund on CRAN. PMID:23003003

Three-Component Decomposition of Polarimetric SAR Data Integrating Eigen-Decomposition Results

NASA Astrophysics Data System (ADS)

Lu, Da; He, Zhihua; Zhang, Huan

2018-01-01

This paper presents a novel three-component scattering power decomposition of polarimetric SAR data. There are two problems in three-component decomposition method: volume scattering component overestimation in urban areas and artificially set parameter to be a fixed value. Though volume scattering component overestimation can be partly solved by deorientation process, volume scattering still dominants some oriented urban areas. The speckle-like decomposition results introduced by artificially setting value are not conducive to further image interpretation. This paper integrates the results of eigen-decomposition to solve the aforementioned problems. Two principal eigenvectors are used to substitute the surface scattering model and the double bounce scattering model. The decomposed scattering powers are obtained using a constrained linear least-squares method. The proposed method has been verified using an ESAR PolSAR image, and the results show that the proposed method has better performance in urban area.

Initial insights into bacterial succession during human decomposition.

PubMed

Hyde, Embriette R; Haarmann, Daniel P; Petrosino, Joseph F; Lynne, Aaron M; Bucheli, Sibyl R

2015-05-01

Decomposition is a dynamic ecological process dependent upon many factors such as environment, climate, and bacterial, insect, and vertebrate activity in addition to intrinsic properties inherent to individual cadavers. Although largely attributed to microbial metabolism, very little is known about the bacterial basis of human decomposition. To assess the change in bacterial community structure through time, bacterial samples were collected from several sites across two cadavers placed outdoors to decompose and analyzed through 454 pyrosequencing and analysis of variable regions 3-5 of the bacterial 16S ribosomal RNA (16S rRNA) gene. Each cadaver was characterized by a change in bacterial community structure for all sites sampled as time, and decomposition, progressed. Bacteria community structure is variable at placement and before purge for all body sites. At bloat and purge and until tissues began to dehydrate or were removed, bacteria associated with flies, such as Ignatzschineria and Wohlfahrtimonas, were common. After dehydration and skeletonization, bacteria associated with soil, such as Acinetobacter, were common at most body sites sampled. However, more cadavers sampled through multiple seasons are necessary to assess major trends in bacterial succession.

Review on modeling of the anode solid electrolyte interphase (SEI) for lithium-ion batteries

NASA Astrophysics Data System (ADS)

Wang, Aiping; Kadam, Sanket; Li, Hong; Shi, Siqi; Qi, Yue

2018-03-01

A passivation layer called the solid electrolyte interphase (SEI) is formed on electrode surfaces from decomposition products of electrolytes. The SEI allows Li+ transport and blocks electrons in order to prevent further electrolyte decomposition and ensure continued electrochemical reactions. The formation and growth mechanism of the nanometer thick SEI films are yet to be completely understood owing to their complex structure and lack of reliable in situ experimental techniques. Significant advances in computational methods have made it possible to predictively model the fundamentals of SEI. This review aims to give an overview of state-of-the-art modeling progress in the investigation of SEI films on the anodes, ranging from electronic structure calculations to mesoscale modeling, covering the thermodynamics and kinetics of electrolyte reduction reactions, SEI formation, modification through electrolyte design, correlation of SEI properties with battery performance, and the artificial SEI design. Multi-scale simulations have been summarized and compared with each other as well as with experiments. Computational details of the fundamental properties of SEI, such as electron tunneling, Li-ion transport, chemical/mechanical stability of the bulk SEI and electrode/(SEI/) electrolyte interfaces have been discussed. This review shows the potential of computational approaches in the deconvolution of SEI properties and design of artificial SEI. We believe that computational modeling can be integrated with experiments to complement each other and lead to a better understanding of the complex SEI for the development of a highly efficient battery in the future.

Interacting Microbe and Litter Quality Controls on Litter Decomposition: A Modeling Analysis

PubMed Central

Moorhead, Daryl; Lashermes, Gwenaëlle; Recous, Sylvie; Bertrand, Isabelle

2014-01-01

The decomposition of plant litter in soil is a dynamic process during which substrate chemistry and microbial controls interact. We more clearly quantify these controls with a revised version of the Guild-based Decomposition Model (GDM) in which we used a reverse Michaelis-Menten approach to simulate short-term (112 days) decomposition of roots from four genotypes of Zea mays that differed primarily in lignin chemistry. A co-metabolic relationship between the degradation of lignin and holocellulose (cellulose+hemicellulose) fractions of litter showed that the reduction in decay rate with increasing lignin concentration (LCI) was related to the level of arabinan substitutions in arabinoxylan chains (i.e., arabinan to xylan or A∶X ratio) and the extent to which hemicellulose chains are cross-linked with lignin in plant cell walls. This pattern was consistent between genotypes and during progressive decomposition within each genotype. Moreover, decay rates were controlled by these cross-linkages from the start of decomposition. We also discovered it necessary to divide the Van Soest soluble (labile) fraction of litter C into two pools: one that rapidly decomposed and a second that was more persistent. Simulated microbial production was consistent with recent studies suggesting that more rapidly decomposing materials can generate greater amounts of potentially recalcitrant microbial products despite the rapid loss of litter mass. Sensitivity analyses failed to identify any model parameter that consistently explained a large proportion of model variation, suggesting that feedback controls between litter quality and microbial activity in the reverse Michaelis-Menten approach resulted in stable model behavior. Model extrapolations to an independent set of data, derived from the decomposition of 12 different genotypes of maize roots, averaged within <3% of observed respiration rates and total CO2 efflux over 112 days. PMID:25264895

Subgrid-scale physical parameterization in atmospheric modeling: How can we make it consistent?

NASA Astrophysics Data System (ADS)

Yano, Jun-Ichi

2016-07-01

Approaches to subgrid-scale physical parameterization in atmospheric modeling are reviewed by taking turbulent combustion flow research as a point of reference. Three major general approaches are considered for its consistent development: moment, distribution density function (DDF), and mode decomposition. The moment expansion is a standard method for describing the subgrid-scale turbulent flows both in geophysics and engineering. The DDF (commonly called PDF) approach is intuitively appealing as it deals with a distribution of variables in subgrid scale in a more direct manner. Mode decomposition was originally applied by Aubry et al (1988 J. Fluid Mech. 192 115-73) in the context of wall boundary-layer turbulence. It is specifically designed to represent coherencies in compact manner by a low-dimensional dynamical system. Their original proposal adopts the proper orthogonal decomposition (empirical orthogonal functions) as their mode-decomposition basis. However, the methodology can easily be generalized into any decomposition basis. Among those, wavelet is a particularly attractive alternative. The mass-flux formulation that is currently adopted in the majority of atmospheric models for parameterizing convection can also be considered a special case of mode decomposition, adopting segmentally constant modes for the expansion basis. This perspective further identifies a very basic but also general geometrical constraint imposed on the massflux formulation: the segmentally-constant approximation. Mode decomposition can, furthermore, be understood by analogy with a Galerkin method in numerically modeling. This analogy suggests that the subgrid parameterization may be re-interpreted as a type of mesh-refinement in numerical modeling. A link between the subgrid parameterization and downscaling problems is also pointed out.

Continuous-variable gate decomposition for the Bose-Hubbard model

NASA Astrophysics Data System (ADS)

Kalajdzievski, Timjan; Weedbrook, Christian; Rebentrost, Patrick

2018-06-01

In this work, we decompose the time evolution of the Bose-Hubbard model into a sequence of logic gates that can be implemented on a continuous-variable photonic quantum computer. We examine the structure of the circuit that represents this time evolution for one-dimensional and two-dimensional lattices. The elementary gates needed for the implementation are counted as a function of lattice size. We also include the contribution of the leading dipole interaction term which may be added to the Hamiltonian and its corresponding circuit.

Importance of vegetation distribution for future carbon balance

NASA Astrophysics Data System (ADS)

Ahlström, A.; Xia, J.; Arneth, A.; Luo, Y.; Smith, B.

2015-12-01

Projections of future terrestrial carbon uptake vary greatly between simulations. Net primary production (NPP), wild fires, vegetation dynamics (including biome shifts) and soil decomposition constitute the main processes governing the response of the terrestrial carbon cycle in a changing climate. While primary production and soil respiration are relatively well studied and implemented in all global ecosystem models used to project the future land sink of CO2, vegetation dynamics are less studied and not always represented in global models. Here we used a detailed second generation dynamic global vegetation model with advanced representation of vegetation growth and mortality and the associated turnover and proven skill in predicting vegetation distribution and succession. We apply an emulator that describes the carbon flows and pools exactly as in simulations with the full model. The emulator simulates ecosystem dynamics in response to 13 different climate or Earth system model simulations from the CMIP5 ensemble under RCP8.5 radiative forcing at year 2085. We exchanged carbon cycle processes between these 13 simulations and investigate the changes predicted by the emulator. This method allowed us to partition the entire ensemble carbon uptake uncertainty into individual processes. We found that NPP, vegetation dynamics (including biome shifts, wild fires and mortality) and soil decomposition rates explained 49%, 17% and 33% respectively of uncertainties in modeled global C-uptake. Uncertainty due to vegetation dynamics was further partitioned into stand-clearing disturbances (16%), wild fires (0%), stand dynamics (7%), reproduction (10%) and biome shifts (67%) globally. We conclude that while NPP and soil decomposition rates jointly account for 83% of future climate induced C-uptake uncertainties, vegetation turnover and structure, dominated by shifts in vegetation distribution, represent a significant fraction globally and regionally (tropical forests: 40%), strongly motivating their representation and analysis in future C-cycle studies.

Climate fails to predict wood decomposition at regional scales

Treesearch

Mark A. Bradford; Robert J. Warren; Petr Baldrian; Thomas W. Crowther; Daniel S. Maynard; Emily E. Oldfield; William R. Wieder; Stephen A. Wood; Joshua R. King

2014-01-01

Decomposition of organic matter strongly influences ecosystem carbon storage1. In Earth-system models, climate is a predominant control on the decomposition rates of organic matter2, 3, 4, 5. This assumption is based on the mean response of decomposition to climate, yet there is a growing appreciation in other areas of global change science that projections based on...

Solvent decompositions and physical properties of decomposition compounds in Li-ion battery electrolytes studied by DFT calculations and molecular dynamics simulations.

PubMed

Tasaki, Ken

2005-02-24

The density functional theory (DFT) calculations have been performed for the reduction decompositions of solvents widely used in Li-ion secondary battery electrolytes, ethylene carbonate (EC), propylene carbonate (PC), dimethyl carbonates (DMC), ethyl methyl carbonate (EMC), and diethyl carbonate (DEC), including a typical electrolyte additive, vinylene carbonate (VC), at the level of B3LYP/6-311+G(2d,p), both in the gas phase and solution using the polarizable conductor calculation model. In the gas phase, the first electron reduction for the cyclic carbonates and for the linear carbonates is found to be exothermic and endothermic, respectively, while the second electron reduction is endothermic for all the compounds examined. On the contrary, in solution both first and second electron reductions are exothermic for all the compounds. Among the solvents and the additive examined, the likelihood of undergoing the first electron reduction in solution was found in the order of EC > PC > VC > DMC > EMC > DEC with EC being the most likely reduced. VC, on the other hand, is most likely to undergo the second electron reduction among the compounds, in the order of VC > EC > PC. Based on the results, the experimentally demonstrated effectiveness of VC as an excellent electrolyte additive was discussed. The bulk thermodynamic properties of two dilithium alkylene glycol dicarbonates, dilithium ethylene glycol dicarbonate (Li-EDC) and dilithium 1,2-propylene glycol dicarbonate (Li-PDC), as the major component of solid-electrolyte interface (SEI) films were also examined through molecular dynamics (MD) simulations in order to understand the stability of the SEI film. It was found that film produced from a decomposition of EC, modeled by Li-EDC, has a higher density, more cohesive energy, and less solubility to the solvent than the film produced from decomposition of PC, Li-PDC. Further, MD simulations of the interface between the decomposition compound and graphite suggested that Li-EDC has more favorable interactions with the graphite surface than Li-PDC. The difference in the SEI film stability and the behavior of Li-ion battery cycling among the solvents were discussed in terms of the molecular structures.

Role of Reactive Mn Complexes in a Litter Decomposition Model System

NASA Astrophysics Data System (ADS)

Nico, P. S.; Keiluweit, M.; Bougoure, J.; Kleber, M.; Summering, J. A.; Maynard, J. J.; Johnson, M.; Pett-Ridge, J.

2012-12-01

The search for controls on litter decomposition rates and pathways has yet to return definitive characteristics that are both statistically robust and can be understood as part of a mechanistic or numerical model. Herein we focus on Mn, an element present in all litter that is likely an active chemical agent of decomposition. Berg and co-workers (2010) found a strong correlation between Mn concentration in litter and the magnitude of litter degradation in boreal forests, suggesting that litter decomposition proceeds more efficiently in the presence of Mn. Although there is much circumstantial evidence for the potential role of Mn in lignin decomposition, few reports exist on mechanistic details of this process. For the current work, we are guided by the hypothesis that the dependence of decomposition on Mn is due to Mn (III)-oxalate complexes act as a 'pretreatment' for structurally intact ligno-carbohydrate complexes (LCC) in fresh plant cell walls (e.g. in litter, root and wood). Manganese (III)-ligand complexes such as Mn (III)-oxalate are known to be potent oxidizers of many different organic and inorganic compounds. In the litter system, the unique property of these complexes may be that they are much smaller than exo-enzymes and therefore more easily able to penetrate LCC complexes in plant cell walls. By acting as 'diffusible oxidizers' and reacting with the organic matrix of the cell wall, these compounds can increase the porosity of fresh litter thereby facilitating access of more specific lignin- and cellulose decomposing enzymes. This possibility was investigated by reacting cell walls of single Zinnia elegans tracheary elements with Mn (III)-oxalate complexes in a continuous flow reactor. The uniformity of these individual plant cells allowed us to examine Mn (III)-induced changes in cell wall chemistry and ultrastructure on the micro-scale using fluorescence and electron microscopy as well as IR and X-ray spectromicroscopy. This presentation will discuss the chemical changes induced by reaction of Mn (III)-complexes with the Zinnia cells, the impact of such reactions on cell integrity, and potential implications for soil C cycling.

Stochiometry, Microbial community composition and decomposition, a modelling analysis

NASA Astrophysics Data System (ADS)

Berninger, Frank; Zhou, Xuan; Aaltonen, Heidi; Köster, Kajar; Heinonsalo, Jussi; Pumpanen, Jukka

2017-04-01

Enzyme activity based litter decomposition models describe the decomposition of soil organic matter as a function of microbial biomass and its activity. In these models, decomposition depends largely on microbial and litter stoïchiometry. We, used the model of Schimel and Weintraub (Soil Biology & Biochemistry 35 (2003) 549-563 largely relying on the modification of Waring B et al. Ecology Letters, (2013) 16: 887-894) and we modified the model to include bacteria, fungi and mycorrizal fungi as decomposer groups assuming different stochiometries. The model was tested against previously published data from a fire chronosequence from northern Finland. The model reconstructed well the development of soil organic matter, microbial biomasses, enzyme actitivies with time after fire. In a theoretical model analysis we tried to understand how the exchange of carbon and nitrogen between mycorrhiza and the plant as different litter stoïchiometries interact. The results indicate that if a high percentage of fungal N uptake is transferred to the plant mycorrhizal biomass will decrease drastically and does decrease, due to low mycorrhizal biomasses, the N uptake of plants. If a lower proportion of the fungal N uptake is transferred to the plant the N uptake of the plants is reasonable stable while the proportion of mycorrhiza of the total fungal biomass varies. The model is also able to simulate priming of soil organic matter decomposition.

Sensitivity of decomposition rates of soil organic matter with respect to simultaneous changes in temperature and moisture

NASA Astrophysics Data System (ADS)

Sierra, Carlos A.; Trumbore, Susan E.; Davidson, Eric A.; Vicca, Sara; Janssens, I.

2015-03-01

The sensitivity of soil organic matter decomposition to global environmental change is a topic of prominent relevance for the global carbon cycle. Decomposition depends on multiple factors that are being altered simultaneously as a result of global environmental change; therefore, it is important to study the sensitivity of the rates of soil organic matter decomposition with respect to multiple and interacting drivers. In this manuscript, we present an analysis of the potential response of decomposition rates to simultaneous changes in temperature and moisture. To address this problem, we first present a theoretical framework to study the sensitivity of soil organic matter decomposition when multiple driving factors change simultaneously. We then apply this framework to models and data at different levels of abstraction: (1) to a mechanistic model that addresses the limitation of enzyme activity by simultaneous effects of temperature and soil water content, the latter controlling substrate supply and oxygen concentration for microbial activity; (2) to different mathematical functions used to represent temperature and moisture effects on decomposition in biogeochemical models. To contrast model predictions at these two levels of organization, we compiled different data sets of observed responses in field and laboratory studies. Then we applied our conceptual framework to: (3) observations of heterotrophic respiration at the ecosystem level; (4) laboratory experiments looking at the response of heterotrophic respiration to independent changes in moisture and temperature; and (5) ecosystem-level experiments manipulating soil temperature and water content simultaneously.

A theoretical investigation of symmetry-origin unidirectional energy gradient in light-harvesting dendrimers.

PubMed

Koda, Shin-ichi

2016-03-21

We theoretically investigate a possibility that the symmetry of the repetitively branched structure of light-harvesting dendrimers creates the energy gradient descending toward inner generations (layers of pigment molecules) of the dendrimers. In the first half of this paper, we define a model system using the Frenkel exciton Hamiltonian that focuses only on the topology of dendrimers and numerically show that excitation energy tends to gather at inner generations of the model system at a thermal equilibrium state. This indicates that an energy gradient is formed in the model system. In the last half, we attribute this result to the symmetry of the model system and propose two symmetry-origin mechanisms creating the energy gradient. The present analysis and proposition are based on the theory of the linear chain (LC) decomposition [S. Koda, J. Chem. Phys. 142, 204112 (2015)], which equivalently transforms the model system into a set of one-dimensional systems on the basis of the symmetry of dendrimers. In the picture of the LC decomposition, we find that energy gradient is formed both in each linear chain and among linear chains, and these two mechanisms explain the numerical results well.

A theoretical investigation of symmetry-origin unidirectional energy gradient in light-harvesting dendrimers

NASA Astrophysics Data System (ADS)

Koda, Shin-ichi

2016-03-01

We theoretically investigate a possibility that the symmetry of the repetitively branched structure of light-harvesting dendrimers creates the energy gradient descending toward inner generations (layers of pigment molecules) of the dendrimers. In the first half of this paper, we define a model system using the Frenkel exciton Hamiltonian that focuses only on the topology of dendrimers and numerically show that excitation energy tends to gather at inner generations of the model system at a thermal equilibrium state. This indicates that an energy gradient is formed in the model system. In the last half, we attribute this result to the symmetry of the model system and propose two symmetry-origin mechanisms creating the energy gradient. The present analysis and proposition are based on the theory of the linear chain (LC) decomposition [S. Koda, J. Chem. Phys. 142, 204112 (2015)], which equivalently transforms the model system into a set of one-dimensional systems on the basis of the symmetry of dendrimers. In the picture of the LC decomposition, we find that energy gradient is formed both in each linear chain and among linear chains, and these two mechanisms explain the numerical results well.

Closed-form solution of decomposable stochastic models

NASA Technical Reports Server (NTRS)

Sjogren, Jon A.

1990-01-01

Markov and semi-Markov processes are increasingly being used in the modeling of complex reconfigurable systems (fault tolerant computers). The estimation of the reliability (or some measure of performance) of the system reduces to solving the process for its state probabilities. Such a model may exhibit numerous states and complicated transition distributions, contributing to an expensive and numerically delicate solution procedure. Thus, when a system exhibits a decomposition property, either structurally (autonomous subsystems), or behaviorally (component failure versus reconfiguration), it is desirable to exploit this decomposition in the reliability calculation. In interesting cases there can be failure states which arise from non-failure states of the subsystems. Equations are presented which allow the computation of failure probabilities of the total (combined) model without requiring a complete solution of the combined model. This material is presented within the context of closed-form functional representation of probabilities as utilized in the Symbolic Hierarchical Automated Reliability and Performance Evaluator (SHARPE) tool. The techniques adopted enable one to compute such probability functions for a much wider class of systems at a reduced computational cost. Several examples show how the method is used, especially in enhancing the versatility of the SHARPE tool.

Attribute And-Or Grammar for Joint Parsing of Human Pose, Parts and Attributes.

PubMed

Park, Seyoung; Nie, Xiaohan; Zhu, Song-Chun

2017-07-25

This paper presents an attribute and-or grammar (A-AOG) model for jointly inferring human body pose and human attributes in a parse graph with attributes augmented to nodes in the hierarchical representation. In contrast to other popular methods in the current literature that train separate classifiers for poses and individual attributes, our method explicitly represents the decomposition and articulation of body parts, and account for the correlations between poses and attributes. The A-AOG model is an amalgamation of three traditional grammar formulations: (i)Phrase structure grammar representing the hierarchical decomposition of the human body from whole to parts; (ii)Dependency grammar modeling the geometric articulation by a kinematic graph of the body pose; and (iii)Attribute grammar accounting for the compatibility relations between different parts in the hierarchy so that their appearances follow a consistent style. The parse graph outputs human detection, pose estimation, and attribute prediction simultaneously, which are intuitive and interpretable. We conduct experiments on two tasks on two datasets, and experimental results demonstrate the advantage of joint modeling in comparison with computing poses and attributes independently. Furthermore, our model obtains better performance over existing methods for both pose estimation and attribute prediction tasks.

Decomposition of Proteins into Dynamic Units from Atomic Cross-Correlation Functions.

PubMed

Calligari, Paolo; Gerolin, Marco; Abergel, Daniel; Polimeno, Antonino

2017-01-10

In this article, we present a clustering method of atoms in proteins based on the analysis of the correlation times of interatomic distance correlation functions computed from MD simulations. The goal is to provide a coarse-grained description of the protein in terms of fewer elements that can be treated as dynamically independent subunits. Importantly, this domain decomposition method does not take into account structural properties of the protein. Instead, the clustering of protein residues in terms of networks of dynamically correlated domains is defined on the basis of the effective correlation times of the pair distance correlation functions. For these properties, our method stands as a complementary analysis to the customary protein decomposition in terms of quasi-rigid, structure-based domains. Results obtained for a prototypal protein structure illustrate the approach proposed.

Dynamics in the Decompositions Approach to Quantum Mechanics

NASA Astrophysics Data System (ADS)

Harding, John

2017-12-01

In Harding (Trans. Amer. Math. Soc. 348(5), 1839-1862 1996) it was shown that the direct product decompositions of any non-empty set, group, vector space, and topological space X form an orthomodular poset Fact X. This is the basis for a line of study in foundational quantum mechanics replacing Hilbert spaces with other types of structures. Here we develop dynamics and an abstract version of a time independent Schrödinger's equation in the setting of decompositions by considering representations of the group of real numbers in the automorphism group of the orthomodular poset Fact X of decompositions.

A parsimonious modular approach to building a mechanistic belowground carbon and nitrogen model

NASA Astrophysics Data System (ADS)

Abramoff, Rose Z.; Davidson, Eric A.; Finzi, Adrien C.

2017-09-01

Soil decomposition models range from simple empirical functions to those that represent physical, chemical, and biological processes. Here we develop a parsimonious, modular C and N cycle model, the Dual Arrhenius Michaelis-Menten-Microbial Carbon and Nitrogen Phyisology (DAMM-MCNiP), that generates testable hypotheses regarding the effect of temperature, moisture, and substrate supply on C and N cycling. We compared this model to DAMM alone and an empirical model of heterotrophic respiration based on Harvard Forest data. We show that while different model structures explain similar amounts of variation in respiration, they differ in their ability to infer processes that affect C flux. We applied DAMM-MCNiP to explain an observed seasonal hysteresis in the relationship between respiration and temperature and show using an exudation simulation that the strength of the priming effect depended on the stoichiometry of the inputs. Low C:N inputs stimulated priming of soil organic matter decomposition, but high C:N inputs were preferentially utilized by microbes as a C source with limited priming. The simplicity of DAMM-MCNiP's simultaneous representations of temperature, moisture, substrate supply, enzyme activity, and microbial growth processes is unique among microbial physiology models and is sufficiently parsimonious that it could be incorporated into larger-scale models of C and N cycling.

Text Extraction from Scene Images by Character Appearance and Structure Modeling

PubMed Central

Yi, Chucai; Tian, Yingli

2012-01-01

In this paper, we propose a novel algorithm to detect text information from natural scene images. Scene text classification and detection are still open research topics. Our proposed algorithm is able to model both character appearance and structure to generate representative and discriminative text descriptors. The contributions of this paper include three aspects: 1) a new character appearance model by a structure correlation algorithm which extracts discriminative appearance features from detected interest points of character samples; 2) a new text descriptor based on structons and correlatons, which model character structure by structure differences among character samples and structure component co-occurrence; and 3) a new text region localization method by combining color decomposition, character contour refinement, and string line alignment to localize character candidates and refine detected text regions. We perform three groups of experiments to evaluate the effectiveness of our proposed algorithm, including text classification, text detection, and character identification. The evaluation results on benchmark datasets demonstrate that our algorithm achieves the state-of-the-art performance on scene text classification and detection, and significantly outperforms the existing algorithms for character identification. PMID:23316111

Formability and thermal stability of phase in (Fe1-y Coy)-(B, C, N) films

NASA Astrophysics Data System (ADS)

Sunaga, K.; Kadowaki, S.; Tsunoda, M.; Takahashi, M.

2004-06-01

In order to find a way to obtain stable -Fe16X2 phase, the formability and thermal stability of (bct) phase were discussed. According to a rigid sphere model, we concluded that the less formability of B for the phase is due to its large atomic radius. We elucidated the difference of thermal stability of -Fe-X, taking into account their decomposition process. While, the decomposition of -Fe-N progresses only by the migration of N, without changing the bone structure of Fe lattice, the additional energy is needed to break the original α-Fe lattice in the cases of α-Fe-B and α-Fe-C. Therefore thermal stability of α-Fe-B and α-Fe-C is higher than that of α-Fe-N.

A non-orthogonal decomposition of flows into discrete events

NASA Astrophysics Data System (ADS)

Boxx, Isaac; Lewalle, Jacques

1998-11-01

This work is based on the formula for the inverse Hermitian wavelet transform. A signal can be interpreted as a (non-unique) superposition of near-singular, partially overlapping events arising from Dirac functions and/or its derivatives combined with diffusion.( No dynamics implied: dimensionless diffusion is related to the definition of the analyzing wavelets.) These events correspond to local maxima of spectral energy density. We successfully fitted model events of various orders on a succession of fields, ranging from elementary signals to one-dimensional hot-wire traces. We document edge effects, event overlap and its implications on the algorithm. The interpretation of the discrete singularities as flow events (such as coherent structures) and the fundamental non-uniqueness of the decomposition are discussed. The dynamics of these events will be examined in the companion paper.

A domain decomposition approach to implementing fault slip in finite-element models of quasi-static and dynamic crustal deformation

USGS Publications Warehouse

Aagaard, Brad T.; Knepley, M.G.; Williams, C.A.

2013-01-01

We employ a domain decomposition approach with Lagrange multipliers to implement fault slip in a finite-element code, PyLith, for use in both quasi-static and dynamic crustal deformation applications. This integrated approach to solving both quasi-static and dynamic simulations leverages common finite-element data structures and implementations of various boundary conditions, discretization schemes, and bulk and fault rheologies. We have developed a custom preconditioner for the Lagrange multiplier portion of the system of equations that provides excellent scalability with problem size compared to conventional additive Schwarz methods. We demonstrate application of this approach using benchmarks for both quasi-static viscoelastic deformation and dynamic spontaneous rupture propagation that verify the numerical implementation in PyLith.

Numerical modeling of the exterior-to-interior transmission of impulsive sound through three-dimensional, thin-walled elastic structures

NASA Astrophysics Data System (ADS)

Remillieux, Marcel C.; Pasareanu, Stephanie M.; Svensson, U. Peter

2013-12-01

Exterior propagation of impulsive sound and its transmission through three-dimensional, thin-walled elastic structures, into enclosed cavities, are investigated numerically in the framework of linear dynamics. A model was developed in the time domain by combining two numerical tools: (i) exterior sound propagation and induced structural loading are computed using the image-source method for the reflected field (specular reflections) combined with an extension of the Biot-Tolstoy-Medwin method for the diffracted field, (ii) the fully coupled vibro-acoustic response of the interior fluid-structure system is computed using a truncated modal-decomposition approach. In the model for exterior sound propagation, it is assumed that all surfaces are acoustically rigid. Since coupling between the structure and the exterior fluid is not enforced, the model is applicable to the case of a light exterior fluid and arbitrary interior fluid(s). The structural modes are computed with the finite-element method using shell elements. Acoustic modes are computed analytically assuming acoustically rigid boundaries and rectangular geometries of the enclosed cavities. This model is verified against finite-element solutions for the cases of rectangular structures containing one and two cavities, respectively.

Primary decomposition of zero-dimensional ideals over finite fields

NASA Astrophysics Data System (ADS)

Gao, Shuhong; Wan, Daqing; Wang, Mingsheng

2009-03-01

A new algorithm is presented for computing primary decomposition of zero-dimensional ideals over finite fields. Like Berlekamp's algorithm for univariate polynomials, the new method is based on the invariant subspace of the Frobenius map acting on the quotient algebra. The dimension of the invariant subspace equals the number of primary components, and a basis of the invariant subspace yields a complete decomposition. Unlike previous approaches for decomposing multivariate polynomial systems, the new method does not need primality testing nor any generic projection, instead it reduces the general decomposition problem directly to root finding of univariate polynomials over the ground field. Also, it is shown how Groebner basis structure can be used to get partial primary decomposition without any root finding.

Thermogravimetric analysis and kinetic modeling of low-transition-temperature mixtures pretreated oil palm empty fruit bunch for possible maximum yield of pyrolysis oil.

PubMed

Yiin, Chung Loong; Yusup, Suzana; Quitain, Armando T; Uemura, Yoshimitsu; Sasaki, Mitsuru; Kida, Tetsuya

2018-05-01

The impacts of low-transition-temperature mixtures (LTTMs) pretreatment on thermal decomposition and kinetics of empty fruit bunch (EFB) were investigated by thermogravimetric analysis. EFB was pretreated with the LTTMs under different duration of pretreatment which enabled various degrees of alteration to their structure. The TG-DTG curves showed that LTTMs pretreatment on EFB shifted the temperature and rate of decomposition to higher values. The EFB pretreated with sucrose and choline chloride-based LTTMs had attained the highest mass loss of volatile matter (78.69% and 75.71%) after 18 h of pretreatment. For monosodium glutamate-based LTTMs, the 24 h pretreated EFB had achieved the maximum mass loss (76.1%). Based on the Coats-Redfern integral method, the LTTMs pretreatment led to an increase in activation energy of the thermal decomposition of EFB from 80.00 to 82.82-94.80 kJ/mol. The activation energy was mainly affected by the demineralization and alteration in cellulose crystallinity after LTTMs pretreatment. Copyright © 2018 Elsevier Ltd. All rights reserved.

Radiation noise of the bearing applied to the ceramic motorized spindle based on the sub-source decomposition method

NASA Astrophysics Data System (ADS)

Bai, X. T.; Wu, Y. H.; Zhang, K.; Chen, C. Z.; Yan, H. P.

2017-12-01

This paper mainly focuses on the calculation and analysis on the radiation noise of the angular contact ball bearing applied to the ceramic motorized spindle. The dynamic model containing the main working conditions and structural parameters is established based on dynamic theory of rolling bearing. The sub-source decomposition method is introduced in for the calculation of the radiation noise of the bearing, and a comparative experiment is adopted to check the precision of the method. Then the comparison between the contribution of different components is carried out in frequency domain based on the sub-source decomposition method. The spectrum of radiation noise of different components under various rotation speeds are used as the basis of assessing the contribution of different eigenfrequencies on the radiation noise of the components, and the proportion of friction noise and impact noise is evaluated as well. The results of the research provide the theoretical basis for the calculation of bearing noise, and offers reference to the impact of different components on the radiation noise of the bearing under different rotation speed.

MEG masked priming evidence for form-based decomposition of irregular verbs

PubMed Central

Fruchter, Joseph; Stockall, Linnaea; Marantz, Alec

2013-01-01

To what extent does morphological structure play a role in early processing of visually presented English past tense verbs? Previous masked priming studies have demonstrated effects of obligatory form-based decomposition for genuinely affixed words (teacher-TEACH) and pseudo-affixed words (corner-CORN), but not for orthographic controls (brothel-BROTH). Additionally, MEG single word reading studies have demonstrated that the transition probability from stem to affix (in genuinely affixed words) modulates an early evoked response known as the M170; parallel findings have been shown for the transition probability from stem to pseudo-affix (in pseudo-affixed words). Here, utilizing the M170 as a neural index of visual form-based morphological decomposition, we ask whether the M170 demonstrates masked morphological priming effects for irregular past tense verbs (following a previous study which obtained behavioral masked priming effects for irregulars). Dual mechanism theories of the English past tense predict a rule-based decomposition for regulars but not for irregulars, while certain single mechanism theories predict rule-based decomposition even for irregulars. MEG data was recorded for 16 subjects performing a visual masked priming lexical decision task. Using a functional region of interest (fROI) defined on the basis of repetition priming and regular morphological priming effects within the left fusiform and inferior temporal regions, we found that activity in this fROI was modulated by the masked priming manipulation for irregular verbs, during the time window of the M170. We also found effects of the scores generated by the learning model of Albright and Hayes (2003) on the degree of priming for irregular verbs. The results favor a single mechanism account of the English past tense, in which even irregulars are decomposed into stems and affixes prior to lexical access, as opposed to a dual mechanism model, in which irregulars are recognized as whole forms. PMID:24319420

Application of singular value decomposition to structural dynamics systems with constraints

NASA Technical Reports Server (NTRS)

Juang, J.-N.; Pinson, L. D.

1985-01-01

Singular value decomposition is used to construct a coordinate transformation for a linear dynamic system subject to linear, homogeneous constraint equations. The method is compared with two commonly used methods, namely classical Gaussian elimination and Walton-Steeves approach. Although the classical method requires fewer numerical operations, the singular value decomposition method is more accurate and convenient in eliminating the dependent coordinates. Numerical examples are presented to demonstrate the application of the method.

Application of Koopmans' theorem for density functional theory to full valence-band photoemission spectroscopy modeling.

PubMed

Li, Tsung-Lung; Lu, Wen-Cai

2015-10-05

In this work, Koopmans' theorem for Kohn-Sham density functional theory (KS-DFT) is applied to the photoemission spectra (PES) modeling over the entire valence-band. To examine the validity of this application, a PES modeling scheme is developed to facilitate a full valence-band comparison of theoretical PES spectra with experiments. The PES model incorporates the variations of electron ionization cross-sections over atomic orbitals and a linear dispersion of spectral broadening widths. KS-DFT simulations of pristine rubrene (5,6,11,12-tetraphenyltetracene) and potassium-rubrene complex are performed, and the simulation results are used as the input to the PES models. Two conclusions are reached. First, decompositions of the theoretical total spectra show that the dissociated electron of the potassium mainly remains on the backbone and has little effect on the electronic structures of phenyl side groups. This and other electronic-structure results deduced from the spectral decompositions have been qualitatively obtained with the anionic approximation to potassium-rubrene complexes. The qualitative validity of the anionic approximation is thus verified. Second, comparison of the theoretical PES with the experiments shows that the full-scale simulations combined with the PES modeling methods greatly enhance the agreement on spectral shapes over the anionic approximation. This agreement of the theoretical PES spectra with the experiments over the full valence-band can be regarded, to some extent, as a collective validation of the application of Koopmans' theorem for KS-DFT to valence-band PES, at least, for this hydrocarbon and its alkali-adsorbed complex. Copyright © 2015 Elsevier B.V. All rights reserved.

Cross-biome transplants of plant litter show decomposition models extend to a broader climatic range but lose predictability at the decadal time scale

Treesearch

William S. Currie; Mark E. Harmon; Ingrid C. Burke; Stephen C. Hart; William J. Parton; Whendee L. Silver

2009-01-01

We analyzed results from 10-year long field incubations of foliar and fine root litter from the Long-term lntersite Decomposition Experiment Team (LIDET) study. We tested whether a variety of climate and litter quality variables could be used to develop regression models of decomposition parameters across wide ranges in litter quality and climate and whether these...

Development of a structured approach for decomposition of complex systems on a functional basis

NASA Astrophysics Data System (ADS)

Yildirim, Unal; Felician Campean, I.

2014-07-01

The purpose of this paper is to present the System State Flow Diagram (SSFD) as a structured and coherent methodology to decompose a complex system on a solution- independent functional basis. The paper starts by reviewing common function modelling frameworks in literature and discusses practical requirements of the SSFD in the context of the current literature and current approaches in industry. The proposed methodology is illustrated through the analysis of a case study: design analysis of a generic Bread Toasting System (BTS).

Confinement in F4 Exceptional Gauge Group Using Domain Structures

NASA Astrophysics Data System (ADS)

Rafibakhsh, Shahnoosh; Shahlaei, Amir

2017-03-01

We calculate the potential between static quarks in the fundamental representation of the F4 exceptional gauge group using domain structures of the thick center vortex model. As non-trivial center elements are absent, the asymptotic string tension is lost while an intermediate linear potential is observed. SU(2) is a subgroup of F4. Investigating the decomposition of the 26 dimensional representation of F4 to the SU(2) representations, might explain what accounts for the intermediate linear potential, in the exceptional groups with no center element.

Data driven discrete-time parsimonious identification of a nonlinear state-space model for a weakly nonlinear system with short data record

NASA Astrophysics Data System (ADS)

Relan, Rishi; Tiels, Koen; Marconato, Anna; Dreesen, Philippe; Schoukens, Johan

2018-05-01

Many real world systems exhibit a quasi linear or weakly nonlinear behavior during normal operation, and a hard saturation effect for high peaks of the input signal. In this paper, a methodology to identify a parsimonious discrete-time nonlinear state space model (NLSS) for the nonlinear dynamical system with relatively short data record is proposed. The capability of the NLSS model structure is demonstrated by introducing two different initialisation schemes, one of them using multivariate polynomials. In addition, a method using first-order information of the multivariate polynomials and tensor decomposition is employed to obtain the parsimonious decoupled representation of the set of multivariate real polynomials estimated during the identification of NLSS model. Finally, the experimental verification of the model structure is done on the cascaded water-benchmark identification problem.

Theoretical study of the partial molar volume change associated with the pressure-induced structural transition of ubiquitin

PubMed Central

Imai, Takashi; Ohyama, Shusaku; Kovalenko, Andriy; Hirata, Fumio

2007-01-01

The partial molar volume (PMV) change associated with the pressure-induced structural transition of ubiquitin is analyzed by the three-dimensional reference interaction site model (3D-RISM) theory of molecular solvation. The theory predicts that the PMV decreases upon the structural transition, which is consistent with the experimental observation. The volume decomposition analysis demonstrates that the PMV reduction is primarily caused by the decrease in the volume of structural voids in the protein, which is partially canceled by the volume expansion due to the hydration effects. It is found from further analysis that the PMV reduction is ascribed substantially to the penetration of water molecules into a specific part of the protein. Based on the thermodynamic relation, this result implies that the water penetration causes the pressure-induced structural transition. It supports the water penetration model of pressure denaturation of proteins proposed earlier. PMID:17660257

Theoretical study of the partial molar volume change associated with the pressure-induced structural transition of ubiquitin.

PubMed

Imai, Takashi; Ohyama, Shusaku; Kovalenko, Andriy; Hirata, Fumio

2007-09-01

The partial molar volume (PMV) change associated with the pressure-induced structural transition of ubiquitin is analyzed by the three-dimensional reference interaction site model (3D-RISM) theory of molecular solvation. The theory predicts that the PMV decreases upon the structural transition, which is consistent with the experimental observation. The volume decomposition analysis demonstrates that the PMV reduction is primarily caused by the decrease in the volume of structural voids in the protein, which is partially canceled by the volume expansion due to the hydration effects. It is found from further analysis that the PMV reduction is ascribed substantially to the penetration of water molecules into a specific part of the protein. Based on the thermodynamic relation, this result implies that the water penetration causes the pressure-induced structural transition. It supports the water penetration model of pressure denaturation of proteins proposed earlier.

Beyond Principal Component Analysis: A Trilinear Decomposition Model and Least Squares Estimation.

ERIC Educational Resources Information Center

Pham, Tuan Dinh; Mocks, Joachim

1992-01-01

Sufficient conditions are derived for the consistency and asymptotic normality of the least squares estimator of a trilinear decomposition model for multiway data analysis. The limiting covariance matrix is computed. (Author/SLD)

Global Existence Results for Viscoplasticity at Finite Strain

NASA Astrophysics Data System (ADS)

Mielke, Alexander; Rossi, Riccarda; Savaré, Giuseppe

2018-01-01

We study a model for rate-dependent gradient plasticity at finite strain based on the multiplicative decomposition of the strain tensor, and investigate the existence of global-in-time solutions to the related PDE system. We reveal its underlying structure as a generalized gradient system, where the driving energy functional is highly nonconvex and features the geometric nonlinearities related to finite-strain elasticity as well as the multiplicative decomposition of finite-strain plasticity. Moreover, the dissipation potential depends on the left-invariant plastic rate, and thus depends on the plastic state variable. The existence theory is developed for a class of abstract, nonsmooth, and nonconvex gradient systems, for which we introduce suitable notions of solutions, namely energy-dissipation-balance and energy-dissipation-inequality solutions. Hence, we resort to the toolbox of the direct method of the calculus of variations to check that the specific energy and dissipation functionals for our viscoplastic models comply with the conditions of the general theory.

Interdependence between Greece and other European stock markets: A comparison of wavelet and VMD copula, and the portfolio implications

NASA Astrophysics Data System (ADS)

Shahzad, Syed Jawad Hussain; Kumar, Ronald Ravinesh; Ali, Sajid; Ameer, Saba

2016-09-01

The interdependence of Greece and other European stock markets and the subsequent portfolio implications are examined in wavelet and variational mode decomposition domain. In applying the decomposition techniques, we analyze the structural properties of data and distinguish between short and long term dynamics of stock market returns. First, the GARCH-type models are fitted to obtain the standardized residuals. Next, different copula functions are evaluated, and based on the conventional information criteria and time varying parameter, Joe-Clayton copula is chosen to model the tail dependence between the stock markets. The short-run lower tail dependence time paths show a sudden increase in comovement during the global financial crises. The results of the long-run dependence suggest that European stock markets have higher interdependence with Greece stock market. Individual country's Value at Risk (VaR) separates the countries into two distinct groups. Finally, the two-asset portfolio VaR measures provide potential markets for Greece stock market investment diversification.

Fundamental Phenomena on Fuel Decomposition and Boundary-Layer Combustion Precesses with Applications to Hybrid Rocket Motors. Part 1; Experimental Investigation

NASA Technical Reports Server (NTRS)

Kuo, Kenneth K.; Lu, Yeu-Cherng; Chiaverini, Martin J.; Johnson, David K.; Serin, Nadir; Risha, Grant A.; Merkle, Charles L.; Venkateswaran, Sankaran

1996-01-01

This final report summarizes the major findings on the subject of 'Fundamental Phenomena on Fuel Decomposition and Boundary-Layer Combustion Processes with Applications to Hybrid Rocket Motors', performed from 1 April 1994 to 30 June 1996. Both experimental results from Task 1 and theoretical/numerical results from Task 2 are reported here in two parts. Part 1 covers the experimental work performed and describes the test facility setup, data reduction techniques employed, and results of the test firings, including effects of operating conditions and fuel additives on solid fuel regression rate and thermal profiles of the condensed phase. Part 2 concerns the theoretical/numerical work. It covers physical modeling of the combustion processes including gas/surface coupling, and radiation effect on regression rate. The numerical solution of the flowfield structure and condensed phase regression behavior are presented. Experimental data from the test firings were used for numerical model validation.

Temporal and Spatial Impact of Human Cadaver Decomposition on Soil Bacterial and Arthropod Community Structure and Function

PubMed Central

Singh, Baneshwar; Minick, Kevan J.; Strickland, Michael S.; Wickings, Kyle G.; Crippen, Tawni L.; Tarone, Aaron M.; Benbow, M. Eric; Sufrin, Ness; Tomberlin, Jeffery K.; Pechal, Jennifer L.

2018-01-01

As vertebrate carrion decomposes, there is a release of nutrient-rich fluids into the underlying soil, which can impact associated biological community structure and function. How these changes alter soil biogeochemical cycles is relatively unknown and may prove useful in the identification of carrion decomposition islands that have long lasting, focal ecological effects. This study investigated the spatial (0, 1, and 5 m) and temporal (3–732 days) dynamics of human cadaver decomposition on soil bacterial and arthropod community structure and microbial function. We observed strong evidence of a predictable response to cadaver decomposition that varies over space for soil bacterial and arthropod community structure, carbon (C) mineralization and microbial substrate utilization patterns. In the presence of a cadaver (i.e., 0 m samples), the relative abundance of Bacteroidetes and Firmicutes was greater, while the relative abundance of Acidobacteria, Chloroflexi, Gemmatimonadetes, and Verrucomicrobia was lower when compared to samples at 1 and 5 m. Micro-arthropods were more abundant (15 to 17-fold) in soils collected at 0 m compared to either 1 or 5 m, but overall, micro-arthropod community composition was unrelated to either bacterial community composition or function. Bacterial community structure and microbial function also exhibited temporal relationships, whereas arthropod community structure did not. Cumulative precipitation was more effective in predicting temporal variations in bacterial abundance and microbial activity than accumulated degree days. In the presence of the cadaver (i.e., 0 m samples), the relative abundance of Actinobacteria increased significantly with cumulative precipitation. Furthermore, soil bacterial communities and C mineralization were sensitive to the introduction of human cadavers as they diverged from baseline levels and did not recover completely in approximately 2 years. These data are valuable for understanding ecosystem function surrounding carrion decomposition islands and can be applicable to environmental bio-monitoring and forensic sciences. PMID:29354106

Temporal and Spatial Impact of Human Cadaver Decomposition on Soil Bacterial and Arthropod Community Structure and Function.

PubMed

Singh, Baneshwar; Minick, Kevan J; Strickland, Michael S; Wickings, Kyle G; Crippen, Tawni L; Tarone, Aaron M; Benbow, M Eric; Sufrin, Ness; Tomberlin, Jeffery K; Pechal, Jennifer L

2017-01-01

As vertebrate carrion decomposes, there is a release of nutrient-rich fluids into the underlying soil, which can impact associated biological community structure and function. How these changes alter soil biogeochemical cycles is relatively unknown and may prove useful in the identification of carrion decomposition islands that have long lasting, focal ecological effects. This study investigated the spatial (0, 1, and 5 m) and temporal (3-732 days) dynamics of human cadaver decomposition on soil bacterial and arthropod community structure and microbial function. We observed strong evidence of a predictable response to cadaver decomposition that varies over space for soil bacterial and arthropod community structure, carbon (C) mineralization and microbial substrate utilization patterns. In the presence of a cadaver (i.e., 0 m samples), the relative abundance of Bacteroidetes and Firmicutes was greater, while the relative abundance of Acidobacteria, Chloroflexi, Gemmatimonadetes, and Verrucomicrobia was lower when compared to samples at 1 and 5 m. Micro-arthropods were more abundant (15 to 17-fold) in soils collected at 0 m compared to either 1 or 5 m, but overall, micro-arthropod community composition was unrelated to either bacterial community composition or function. Bacterial community structure and microbial function also exhibited temporal relationships, whereas arthropod community structure did not. Cumulative precipitation was more effective in predicting temporal variations in bacterial abundance and microbial activity than accumulated degree days. In the presence of the cadaver (i.e., 0 m samples), the relative abundance of Actinobacteria increased significantly with cumulative precipitation. Furthermore, soil bacterial communities and C mineralization were sensitive to the introduction of human cadavers as they diverged from baseline levels and did not recover completely in approximately 2 years. These data are valuable for understanding ecosystem function surrounding carrion decomposition islands and can be applicable to environmental bio-monitoring and forensic sciences.

Preserving Lagrangian Structure in Nonlinear Model Reduction with Application to Structural Dynamics

DOE PAGES

Carlberg, Kevin; Tuminaro, Ray; Boggs, Paul

2015-03-11

Our work proposes a model-reduction methodology that preserves Lagrangian structure and achieves computational efficiency in the presence of high-order nonlinearities and arbitrary parameter dependence. As such, the resulting reduced-order model retains key properties such as energy conservation and symplectic time-evolution maps. We focus on parameterized simple mechanical systems subjected to Rayleigh damping and external forces, and consider an application to nonlinear structural dynamics. To preserve structure, the method first approximates the system's “Lagrangian ingredients''---the Riemannian metric, the potential-energy function, the dissipation function, and the external force---and subsequently derives reduced-order equations of motion by applying the (forced) Euler--Lagrange equation with thesemore » quantities. Moreover, from the algebraic perspective, key contributions include two efficient techniques for approximating parameterized reduced matrices while preserving symmetry and positive definiteness: matrix gappy proper orthogonal decomposition and reduced-basis sparsification. Our results for a parameterized truss-structure problem demonstrate the practical importance of preserving Lagrangian structure and illustrate the proposed method's merits: it reduces computation time while maintaining high accuracy and stability, in contrast to existing nonlinear model-reduction techniques that do not preserve structure.« less

Preserving Lagrangian Structure in Nonlinear Model Reduction with Application to Structural Dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carlberg, Kevin; Tuminaro, Ray; Boggs, Paul

Our work proposes a model-reduction methodology that preserves Lagrangian structure and achieves computational efficiency in the presence of high-order nonlinearities and arbitrary parameter dependence. As such, the resulting reduced-order model retains key properties such as energy conservation and symplectic time-evolution maps. We focus on parameterized simple mechanical systems subjected to Rayleigh damping and external forces, and consider an application to nonlinear structural dynamics. To preserve structure, the method first approximates the system's “Lagrangian ingredients''---the Riemannian metric, the potential-energy function, the dissipation function, and the external force---and subsequently derives reduced-order equations of motion by applying the (forced) Euler--Lagrange equation with thesemore » quantities. Moreover, from the algebraic perspective, key contributions include two efficient techniques for approximating parameterized reduced matrices while preserving symmetry and positive definiteness: matrix gappy proper orthogonal decomposition and reduced-basis sparsification. Our results for a parameterized truss-structure problem demonstrate the practical importance of preserving Lagrangian structure and illustrate the proposed method's merits: it reduces computation time while maintaining high accuracy and stability, in contrast to existing nonlinear model-reduction techniques that do not preserve structure.« less

Decomposition of the complex system into nonlinear spatio-temporal modes: algorithm and application to climate data mining

NASA Astrophysics Data System (ADS)

Feigin, Alexander; Gavrilov, Andrey; Loskutov, Evgeny; Mukhin, Dmitry

2015-04-01

Proper decomposition of the complex system into well separated "modes" is a way to reveal and understand the mechanisms governing the system behaviour as well as discover essential feedbacks and nonlinearities. The decomposition is also natural procedure that provides to construct adequate and concurrently simplest models of both corresponding sub-systems, and of the system in whole. In recent works two new methods of decomposition of the Earth's climate system into well separated modes were discussed. The first method [1-3] is based on the MSSA (Multichannel Singular Spectral Analysis) [4] for linear expanding vector (space-distributed) time series and makes allowance delayed correlations of the processes recorded in spatially separated points. The second one [5-7] allows to construct nonlinear dynamic modes, but neglects delay of correlations. It was demonstrated [1-3] that first method provides effective separation of different time scales, but prevent from correct reduction of data dimension: slope of variance spectrum of spatio-temporal empirical orthogonal functions that are "structural material" for linear spatio-temporal modes, is too flat. The second method overcomes this problem: variance spectrum of nonlinear modes falls essentially sharply [5-7]. However neglecting time-lag correlations brings error of mode selection that is uncontrolled and increases with growth of mode time scale. In the report we combine these two methods in such a way that the developed algorithm allows constructing nonlinear spatio-temporal modes. The algorithm is applied for decomposition of (i) multi hundreds years globally distributed data generated by the INM RAS Coupled Climate Model [8], and (ii) 156 years time series of SST anomalies distributed over the globe [9]. We compare efficiency of different methods of decomposition and discuss the abilities of nonlinear spatio-temporal modes for construction of adequate and concurrently simplest ("optimal") models of climate systems. 1. Feigin A.M., Mukhin D., Gavrilov A., Volodin E.M., and Loskutov E.M. (2013) "Separation of spatial-temporal patterns ("climatic modes") by combined analysis of really measured and generated numerically vector time series", AGU 2013 Fall Meeting, Abstract NG33A-1574. 2. Alexander Feigin, Dmitry Mukhin, Andrey Gavrilov, Evgeny Volodin, and Evgeny Loskutov (2014) "Approach to analysis of multiscale space-distributed time series: separation of spatio-temporal modes with essentially different time scales", Geophysical Research Abstracts, Vol. 16, EGU2014-6877. 3. Dmitry Mukhin, Dmitri Kondrashov, Evgeny Loskutov, Andrey Gavrilov, Alexander Feigin, and Michael Ghil (2014) "Predicting critical transitions in ENSO models, Part II: Spatially dependent models", Journal of Climate (accepted, doi: 10.1175/JCLI-D-14-00240.1). 4. Ghil, M., R. M. Allen, M. D. Dettinger, K. Ide, D. Kondrashov, et al. (2002) "Advanced spectral methods for climatic time series", Rev. Geophys. 40(1), 3.1-3.41. 5. Dmitry Mukhin, Andrey Gavrilov, Evgeny M Loskutov and Alexander M Feigin (2014) "Nonlinear Decomposition of Climate Data: a New Method for Reconstruction of Dynamical Modes", AGU 2014 Fall Meeting, Abstract NG43A-3752. 6. Andrey Gavrilov, Dmitry Mukhin, Evgeny Loskutov, and Alexander Feigin (2015) "Empirical decomposition of climate data into nonlinear dynamic modes", Geophysical Research Abstracts, Vol. 17, EGU2015-627. 7. Dmitry Mukhin, Andrey Gavrilov, Evgeny Loskutov, Alexander Feigin, and Juergen Kurths (2015) "Reconstruction of principal dynamical modes from climatic variability: nonlinear approach", Geophysical Research Abstracts, Vol. 17, EGU2015-5729. 8. http://83.149.207.89/GCM_DATA_PLOTTING/GCM_INM_DATA_XY_en.htm. 9. http://iridl.ldeo.columbia.edu/SOURCES/.KAPLAN/.EXTENDED/.v2/.ssta/.

Understanding changes in the UK's CO2 emissions: a global perspective.

PubMed

Baiocchi, Giovanni; Minx, Jan C

2010-02-15

The UK appears to be a leading country in curbing greenhouse gas (GHG) emissions. Unlike many other developed countries, it has already met its Kyoto obligations and defined ambitious, legally binding targets for the future. Recently this achievement has been called into question as it ignores rapidly changing patterns of production and international trade. We use structural decomposition analysis (SDA) to investigate the drivers behind annual changes in CO(2) emission from consumption in the UK between 1992 and 2004. In contrast with previous SDA-based studies, we apply the decomposition to a global, multiregional input-output model (MRIO), which accounts for UK imports from all regions and uses region-specific production structures and CO(2) intensities. We find that improvements from "domestic" changes in efficiency and production structure led to a 148 Mt reduction in CO(2) emissions, which only partially offsets emission increases of 217 Mt from changes in the global supply chain and from growing consumer demand. Recent emission reductions achieved in the UK are not merely a reflection of a greening of the domestic supply chain, but also of a change in the international division of labor in the global production of goods and services.

Time Domain Strain/Stress Reconstruction Based on Empirical Mode Decomposition: Numerical Study and Experimental Validation.

PubMed

He, Jingjing; Zhou, Yibin; Guan, Xuefei; Zhang, Wei; Zhang, Weifang; Liu, Yongming

2016-08-16

Structural health monitoring has been studied by a number of researchers as well as various industries to keep up with the increasing demand for preventive maintenance routines. This work presents a novel method for reconstruct prompt, informed strain/stress responses at the hot spots of the structures based on strain measurements at remote locations. The structural responses measured from usage monitoring system at available locations are decomposed into modal responses using empirical mode decomposition. Transformation equations based on finite element modeling are derived to extrapolate the modal responses from the measured locations to critical locations where direct sensor measurements are not available. Then, two numerical examples (a two-span beam and a 19956-degree of freedom simplified airfoil) are used to demonstrate the overall reconstruction method. Finally, the present work investigates the effectiveness and accuracy of the method through a set of experiments conducted on an aluminium alloy cantilever beam commonly used in air vehicle and spacecraft. The experiments collect the vibration strain signals of the beam via optical fiber sensors. Reconstruction results are compared with theoretical solutions and a detailed error analysis is also provided.

Three-pattern decomposition of global atmospheric circulation: part II—dynamical equations of horizontal, meridional and zonal circulations

NASA Astrophysics Data System (ADS)

Hu, Shujuan; Cheng, Jianbo; Xu, Ming; Chou, Jifan

2018-04-01

The three-pattern decomposition of global atmospheric circulation (TPDGAC) partitions three-dimensional (3D) atmospheric circulation into horizontal, meridional and zonal components to study the 3D structures of global atmospheric circulation. This paper incorporates the three-pattern decomposition model (TPDM) into primitive equations of atmospheric dynamics and establishes a new set of dynamical equations of the horizontal, meridional and zonal circulations in which the operator properties are studied and energy conservation laws are preserved, as in the primitive equations. The physical significance of the newly established equations is demonstrated. Our findings reveal that the new equations are essentially the 3D vorticity equations of atmosphere and that the time evolution rules of the horizontal, meridional and zonal circulations can be described from the perspective of 3D vorticity evolution. The new set of dynamical equations includes decomposed expressions that can be used to explore the source terms of large-scale atmospheric circulation variations. A simplified model is presented to demonstrate the potential applications of the new equations for studying the dynamics of the Rossby, Hadley and Walker circulations. The model shows that the horizontal air temperature anomaly gradient (ATAG) induces changes in meridional and zonal circulations and promotes the baroclinic evolution of the horizontal circulation. The simplified model also indicates that the absolute vorticity of the horizontal circulation is not conserved, and its changes can be described by changes in the vertical vorticities of the meridional and zonal circulations. Moreover, the thermodynamic equation shows that the induced meridional and zonal circulations and advection transport by the horizontal circulation in turn cause a redistribution of the air temperature. The simplified model reveals the fundamental rules between the evolution of the air temperature and the horizontal, meridional and zonal components of global atmospheric circulation.

A simple numerical model for predicting organic matter decomposition in a fed-batch composting operation.

PubMed

Nakasaki, Kiyohiko; Ohtaki, Akihito

2002-01-01

Using dog food as a model of the organic waste that comprises composting raw material, the degradation pattern of organic materials was examined by continuously measuring the quantity of CO2 evolved during the composting process in both batch and fed-batch operations. A simple numerical model was made on the basis of three suppositions for describing the organic matter decomposition in the batch operation. First, a certain quantity of carbon in the dog food was assumed to be recalcitrant to degradation in the composting reactor within the retention time allowed. Second, it was assumed that the decomposition rate of carbon is proportional to the quantity of easily degradable carbon, that is, the carbon recalcitrant to degradation was subtracted from the total carbon remaining in the dog food. Third, a certain lag time is assumed to occur before the start of active decomposition of organic matter in the dog food; this lag corresponds to the time required for microorganisms to proliferate and become active. It was then ascertained that the decomposition pattern for the organic matter in the dog food during the fed-batch operation could be predicted by the numerical model with the parameters obtained from the batch operation. This numerical model was modified so that the change in dry weight of composting materials could be obtained. The modified model was found suitable for describing the organic matter decomposition pattern in an actual fed-batch composting operation of the garbage obtained from a restaurant, approximately 10 kg d(-1) loading for 60 d.

Syntheses, structural, computational, and thermal analysis of acid-base complexes of picric acid with N-heterocyclic bases.

PubMed

Goel, Nidhi; Singh, Udai P

2013-10-10

Four new acid-base complexes using picric acid [(OH)(NO2)3C6H2] (PA) and N-heterocyclic bases (1,10-phenanthroline (phen)/2,2';6',2"-terpyridine (terpy)/hexamethylenetetramine (hmta)/2,4,6-tri(2-pyridyl)-1,3,5-triazine (tptz)) were prepared and characterized by elemental analysis, IR, NMR and X-ray crystallography. Crystal structures provide detailed information of the noncovalent interactions present in different complexes. The optimized structures of the complexes were calculated in terms of the density functional theory. The thermolysis of these complexes was investigated by TG-DSC and ignition delay measurements. The model-free isoconversional and model-fitting kinetic approaches have been applied to isothermal TG data for kinetics investigation of thermal decomposition of these complexes.

Patched bimetallic surfaces are active catalysts for ammonia decomposition.

PubMed

Guo, Wei; Vlachos, Dionisios G

2015-10-07

Ammonia decomposition is often used as an archetypical reaction for predicting new catalytic materials and understanding the very reason of why some reactions are sensitive on material's structure. Core-shell or surface-segregated bimetallic nanoparticles expose outstanding activity for many heterogeneously catalysed reactions but the reasons remain elusive owing to the difficulties in experimentally characterizing active sites. Here by performing multiscale simulations in ammonia decomposition on various nickel loadings on platinum (111), we show that the very high activity of core-shell structures requires patches of the guest metal to create and sustain dual active sites: nickel terraces catalyse N-H bond breaking and nickel edge sites drive atomic nitrogen association. The structure sensitivity on these active catalysts depends profoundly on reaction conditions due to kinetically competing relevant elementary reaction steps. We expose a remarkable difference in active sites between transient and steady-state studies and provide insights into optimal material design.

Synthesis and structure characterization of chromium oxide prepared by solid thermal decomposition reaction.

PubMed

Li, Li; Yan, Zi F; Lu, Gao Q; Zhu, Zhong H

2006-01-12

Mesoporous chromium oxide (Cr2O3) nanocrystals were first synthesized by the thermal decomposition reaction of Cr(NO3)3.9H2O using citric acid monohydrate (CA) as the mesoporous template agent. The texture and chemistry of chromium oxide nanocrystals were characterized by N2 adsorption-desorption isotherms, FTIR, X-ray diffraction (XRD), UV-vis, and thermoanalytical methods. It was shown that the hydrate water and CA are the crucial factors in influencing the formation of mesoporous Cr2O3 nanocrystals in the mixture system. The decomposition of CA results in the formation of a mesoporous structure with wormlike pores. The hydrate water of the mixture provides surface hydroxyls that act as binders, making the nanocrystals aggregate. The pore structures and phases of chromium oxide are affected by the ratio of precursor-to-CA, thermal temperature, and time.

A Graph Based Backtracking Algorithm for Solving General CSPs

NASA Technical Reports Server (NTRS)

Pang, Wanlin; Goodwin, Scott D.

2003-01-01

Many AI tasks can be formalized as constraint satisfaction problems (CSPs), which involve finding values for variables subject to constraints. While solving a CSP is an NP-complete task in general, tractable classes of CSPs have been identified based on the structure of the underlying constraint graphs. Much effort has been spent on exploiting structural properties of the constraint graph to improve the efficiency of finding a solution. These efforts contributed to development of a class of CSP solving algorithms called decomposition algorithms. The strength of CSP decomposition is that its worst-case complexity depends on the structural properties of the constraint graph and is usually better than the worst-case complexity of search methods. Its practical application is limited, however, since it cannot be applied if the CSP is not decomposable. In this paper, we propose a graph based backtracking algorithm called omega-CDBT, which shares merits and overcomes the weaknesses of both decomposition and search approaches.

Patched bimetallic surfaces are active catalysts for ammonia decomposition

NASA Astrophysics Data System (ADS)

Guo, Wei; Vlachos, Dionisios G.

2015-10-01

Ammonia decomposition is often used as an archetypical reaction for predicting new catalytic materials and understanding the very reason of why some reactions are sensitive on material's structure. Core-shell or surface-segregated bimetallic nanoparticles expose outstanding activity for many heterogeneously catalysed reactions but the reasons remain elusive owing to the difficulties in experimentally characterizing active sites. Here by performing multiscale simulations in ammonia decomposition on various nickel loadings on platinum (111), we show that the very high activity of core-shell structures requires patches of the guest metal to create and sustain dual active sites: nickel terraces catalyse N-H bond breaking and nickel edge sites drive atomic nitrogen association. The structure sensitivity on these active catalysts depends profoundly on reaction conditions due to kinetically competing relevant elementary reaction steps. We expose a remarkable difference in active sites between transient and steady-state studies and provide insights into optimal material design.

A statistical forecast model using the time-scale decomposition technique to predict rainfall during flood period over the middle and lower reaches of the Yangtze River Valley

NASA Astrophysics Data System (ADS)

Hu, Yijia; Zhong, Zhong; Zhu, Yimin; Ha, Yao

2018-04-01

In this paper, a statistical forecast model using the time-scale decomposition method is established to do the seasonal prediction of the rainfall during flood period (FPR) over the middle and lower reaches of the Yangtze River Valley (MLYRV). This method decomposites the rainfall over the MLYRV into three time-scale components, namely, the interannual component with the period less than 8 years, the interdecadal component with the period from 8 to 30 years, and the interdecadal component with the period larger than 30 years. Then, the predictors are selected for the three time-scale components of FPR through the correlation analysis. At last, a statistical forecast model is established using the multiple linear regression technique to predict the three time-scale components of the FPR, respectively. The results show that this forecast model can capture the interannual and interdecadal variation of FPR. The hindcast of FPR during 14 years from 2001 to 2014 shows that the FPR can be predicted successfully in 11 out of the 14 years. This forecast model performs better than the model using traditional scheme without time-scale decomposition. Therefore, the statistical forecast model using the time-scale decomposition technique has good skills and application value in the operational prediction of FPR over the MLYRV.

A Dual Super-Element Domain Decomposition Approach for Parallel Nonlinear Finite Element Analysis

NASA Astrophysics Data System (ADS)

Jokhio, G. A.; Izzuddin, B. A.

2015-05-01

This article presents a new domain decomposition method for nonlinear finite element analysis introducing the concept of dual partition super-elements. The method extends ideas from the displacement frame method and is ideally suited for parallel nonlinear static/dynamic analysis of structural systems. In the new method, domain decomposition is realized by replacing one or more subdomains in a "parent system," each with a placeholder super-element, where the subdomains are processed separately as "child partitions," each wrapped by a dual super-element along the partition boundary. The analysis of the overall system, including the satisfaction of equilibrium and compatibility at all partition boundaries, is realized through direct communication between all pairs of placeholder and dual super-elements. The proposed method has particular advantages for matrix solution methods based on the frontal scheme, and can be readily implemented for existing finite element analysis programs to achieve parallelization on distributed memory systems with minimal intervention, thus overcoming memory bottlenecks typically faced in the analysis of large-scale problems. Several examples are presented in this article which demonstrate the computational benefits of the proposed parallel domain decomposition approach and its applicability to the nonlinear structural analysis of realistic structural systems.

Waveform LiDAR processing: comparison of classic approaches and optimized Gold deconvolution to characterize vegetation structure and terrain elevation

NASA Astrophysics Data System (ADS)

Zhou, T.; Popescu, S. C.; Krause, K.

2016-12-01

Waveform Light Detection and Ranging (LiDAR) data have advantages over discrete-return LiDAR data in accurately characterizing vegetation structure. However, we lack a comprehensive understanding of waveform data processing approaches under different topography and vegetation conditions. The objective of this paper is to highlight a novel deconvolution algorithm, the Gold algorithm, for processing waveform LiDAR data with optimal deconvolution parameters. Further, we present a comparative study of waveform processing methods to provide insight into selecting an approach for a given combination of vegetation and terrain characteristics. We employed two waveform processing methods: 1) direct decomposition, 2) deconvolution and decomposition. In method two, we utilized two deconvolution algorithms - the Richardson Lucy (RL) algorithm and the Gold algorithm. The comprehensive and quantitative comparisons were conducted in terms of the number of detected echoes, position accuracy, the bias of the end products (such as digital terrain model (DTM) and canopy height model (CHM)) from discrete LiDAR data, along with parameter uncertainty for these end products obtained from different methods. This study was conducted at three study sites that include diverse ecological regions, vegetation and elevation gradients. Results demonstrate that two deconvolution algorithms are sensitive to the pre-processing steps of input data. The deconvolution and decomposition method is more capable of detecting hidden echoes with a lower false echo detection rate, especially for the Gold algorithm. Compared to the reference data, all approaches generate satisfactory accuracy assessment results with small mean spatial difference (<1.22 m for DTMs, < 0.77 m for CHMs) and root mean square error (RMSE) (<1.26 m for DTMs, < 1.93 m for CHMs). More specifically, the Gold algorithm is superior to others with smaller root mean square error (RMSE) (< 1.01m), while the direct decomposition approach works better in terms of the percentage of spatial difference within 0.5 and 1 m. The parameter uncertainty analysis demonstrates that the Gold algorithm outperforms other approaches in dense vegetation areas, with the smallest RMSE, and the RL algorithm performs better in sparse vegetation areas in terms of RMSE.

The Living Dead: Bacterial Community Structure of a Cadaver at the Onset and End of the Bloat Stage of Decomposition

PubMed Central

Hyde, Embriette R.; Haarmann, Daniel P.; Lynne, Aaron M.; Bucheli, Sibyl R.; Petrosino, Joseph F.

2013-01-01

Human decomposition is a mosaic system with an intimate association between biotic and abiotic factors. Despite the integral role of bacteria in the decomposition process, few studies have catalogued bacterial biodiversity for terrestrial scenarios. To explore the microbiome of decomposition, two cadavers were placed at the Southeast Texas Applied Forensic Science facility and allowed to decompose under natural conditions. The bloat stage of decomposition, a stage easily identified in taphonomy and readily attributed to microbial physiology, was targeted. Each cadaver was sampled at two time points, at the onset and end of the bloat stage, from various body sites including internal locations. Bacterial samples were analyzed by pyrosequencing of the 16S rRNA gene. Our data show a shift from aerobic bacteria to anaerobic bacteria in all body sites sampled and demonstrate variation in community structure between bodies, between sample sites within a body, and between initial and end points of the bloat stage within a sample site. These data are best not viewed as points of comparison but rather additive data sets. While some species recovered are the same as those observed in culture-based studies, many are novel. Our results are preliminary and add to a larger emerging data set; a more comprehensive study is needed to further dissect the role of bacteria in human decomposition. PMID:24204941

The living dead: bacterial community structure of a cadaver at the onset and end of the bloat stage of decomposition.

PubMed

Hyde, Embriette R; Haarmann, Daniel P; Lynne, Aaron M; Bucheli, Sibyl R; Petrosino, Joseph F

2013-01-01

Human decomposition is a mosaic system with an intimate association between biotic and abiotic factors. Despite the integral role of bacteria in the decomposition process, few studies have catalogued bacterial biodiversity for terrestrial scenarios. To explore the microbiome of decomposition, two cadavers were placed at the Southeast Texas Applied Forensic Science facility and allowed to decompose under natural conditions. The bloat stage of decomposition, a stage easily identified in taphonomy and readily attributed to microbial physiology, was targeted. Each cadaver was sampled at two time points, at the onset and end of the bloat stage, from various body sites including internal locations. Bacterial samples were analyzed by pyrosequencing of the 16S rRNA gene. Our data show a shift from aerobic bacteria to anaerobic bacteria in all body sites sampled and demonstrate variation in community structure between bodies, between sample sites within a body, and between initial and end points of the bloat stage within a sample site. These data are best not viewed as points of comparison but rather additive data sets. While some species recovered are the same as those observed in culture-based studies, many are novel. Our results are preliminary and add to a larger emerging data set; a more comprehensive study is needed to further dissect the role of bacteria in human decomposition.

Nanoscale Structure of Organic Matter Could Explain Litter Decomposition

NASA Astrophysics Data System (ADS)

Papa, G.; Adani, F.

2014-12-01

According to the literature biochemical catalyses are limited in their actions because of the complex macroscopic and, above all, microscopic structures of cell wall that limit mass transportation (i.e. 3D structure). Our study on energy crop showed that plant digestibility increased by modifying the 3D cell wall microstructure. Results obtained were ascribed to the enlargement, such as effectively measured, of the pore spaces between cellulose fibrils. Therefore we postulated that 3 D structure of plant residues drives degradability in soil determining its recalcitrance in short time. Here we focused on the drivers of short-term decomposition of organic matter (plant residues) in soils evaluating the architecture of plant tissues, captured via measurements of the microporosiy of the cell walls. Decomposition rates of a wide variety of biomass types were studied conducting experiments in both aerobic and anaerobic environments. Different analytical approaches were applied in order to characterize biomass at both chemical and physical level. Combined statistical approaches were used to examine the relationships between carbon mineralization and chemical/physical characteristics. The results revealed that degradation was significantly and negatively correlated with the micro-porosity surface (MiS) (surface of pores of 0.3-1.5 nm of diameter). The multiple regressions performed by using partial least square model enabled describing biomass biodegradability under either aerobic and anaerobic condition by using micro-porosity and aromatic-C content (assumed to be representative of lignin) as independent variables (R2 =0.97, R2cv =0.95 for aerobic condition; R2 =0.99, R2cv =0.98 for anaerobic condition, respectively). These results corroborate the hypothesis that plant tissues are physically protected from enzymatic attack by a microporous "sheath" that limit penetration into cell wall, and demonstrate the key role played by aromatic carbon, because of its chemical protection of the other cell wall polymers and its contribution to the three-dimensional (3D) cell wall structure.

Isoconversional approach for non-isothermal decomposition of un-irradiated and photon-irradiated 5-fluorouracil.

PubMed

Mohamed, Hala Sh; Dahy, AbdelRahman A; Mahfouz, Refaat M

2017-10-25

Kinetic analysis for the non-isothermal decomposition of un-irradiated and photon-beam-irradiated 5-fluorouracil (5-FU) as anti-cancer drug, was carried out in static air. Thermal decomposition of 5-FU proceeds in two steps. One minor step in the temperature range of (270-283°C) followed by the major step in the temperature range of (285-360°C). The non-isothermal data for un-irradiated and photon-irradiated 5-FU were analyzed using linear (Tang) and non-linear (Vyazovkin) isoconversional methods. The results of the application of these free models on the present kinetic data showed quite a dependence of the activation energy on the extent of conversion. For un-irradiated 5-FU, the non-isothermal data analysis indicates that the decomposition is generally described by A3 and A4 modeles for the minor and major decomposition steps, respectively. For a photon-irradiated sample of 5-FU with total absorbed dose of 10Gy, the decomposition is controlled by A2 model throughout the coversion range. The activation energies calculated in case of photon-irradiated 5-FU were found to be lower compared to the values obtained from the thermal decomposition of the un-irradiated sample probably due to the formation of additional nucleation sites created by a photon-irradiation. The decomposition path was investigated by intrinsic reaction coordinate (IRC) at the B3LYP/6-311++G(d,p) level of DFT. Two transition states were involved in the process by homolytic rupture of NH bond and ring secession, respectively. Published by Elsevier B.V.

Functional and Structural Succession of Soil Microbial Communities below Decomposing Human Cadavers

PubMed Central

Cobaugh, Kelly L.; Schaeffer, Sean M.; DeBruyn, Jennifer M.

2015-01-01

The ecological succession of microbes during cadaver decomposition has garnered interest in both basic and applied research contexts (e.g. community assembly and dynamics; forensic indicator of time since death). Yet current understanding of microbial ecology during decomposition is almost entirely based on plant litter. We know very little about microbes recycling carcass-derived organic matter despite the unique decomposition processes. Our objective was to quantify the taxonomic and functional succession of microbial populations in soils below decomposing cadavers, testing the hypotheses that a) periods of increased activity during decomposition are associated with particular taxa; and b) human-associated taxa are introduced to soils, but do not persist outside their host. We collected soils from beneath four cadavers throughout decomposition, and analyzed soil chemistry, microbial activity and bacterial community structure. As expected, decomposition resulted in pulses of soil C and nutrients (particularly ammonia) and stimulated microbial activity. There was no change in total bacterial abundances, however we observed distinct changes in both function and community composition. During active decay (7 - 12 days postmortem), respiration and biomass production rates were high: the community was dominated by Proteobacteria (increased from 15.0 to 26.1% relative abundance) and Firmicutes (increased from 1.0 to 29.0%), with reduced Acidobacteria abundances (decreased from 30.4 to 9.8%). Once decay rates slowed (10 - 23 d postmortem), respiration was elevated, but biomass production rates dropped dramatically; this community with low growth efficiency was dominated by Firmicutes (increased to 50.9%) and other anaerobic taxa. Human-associated bacteria, including the obligately anaerobic Bacteroides, were detected at high concentrations in soil throughout decomposition, up to 198 d postmortem. Our results revealed the pattern of functional and compositional succession in soil microbial communities during decomposition of human-derived organic matter, provided insight into decomposition processes, and identified putative predictor populations for time since death estimation. PMID:26067226

Robust permanence for ecological equations with internal and external feedbacks.

PubMed

Patel, Swati; Schreiber, Sebastian J

2018-07-01

Species experience both internal feedbacks with endogenous factors such as trait evolution and external feedbacks with exogenous factors such as weather. These feedbacks can play an important role in determining whether populations persist or communities of species coexist. To provide a general mathematical framework for studying these effects, we develop a theorem for coexistence for ecological models accounting for internal and external feedbacks. Specifically, we use average Lyapunov functions and Morse decompositions to develop sufficient and necessary conditions for robust permanence, a form of coexistence robust to large perturbations of the population densities and small structural perturbations of the models. We illustrate how our results can be applied to verify permanence in non-autonomous models, structured population models, including those with frequency-dependent feedbacks, and models of eco-evolutionary dynamics. In these applications, we discuss how our results relate to previous results for models with particular types of feedbacks.

A hierarchical model of metabolic machinery based on the kcore decomposition of plant metabolic networks.

PubMed

Filho, Humberto A; Machicao, Jeaneth; Bruno, Odemir M

2018-01-01

Modeling the basic structure of metabolic machinery is a challenge for modern biology. Some models based on complex networks have provided important information regarding this machinery. In this paper, we constructed metabolic networks of 17 plants covering unicellular organisms to more complex dicotyledonous plants. The metabolic networks were built based on the substrate-product model and a topological percolation was performed using the kcore decomposition. The distribution of metabolites across the percolation layers showed correlations between the metabolic integration hierarchy and the network topology. We show that metabolites concentrated in the internal network (maximum kcore) only comprise molecules of the primary basal metabolism. Moreover, we found a high proportion of a set of common metabolites, among the 17 plants, centered at the inner kcore layers. Meanwhile, the metabolites recognized as participants in the secondary metabolism of plants are concentrated in the outermost layers of the network. This data suggests that the metabolites in the central layer form a basic molecular module in which the whole plant metabolism is anchored. The elements from this central core participate in almost all plant metabolic reactions, which suggests that plant metabolic networks follows a centralized topology.

A hierarchical model of metabolic machinery based on the kcore decomposition of plant metabolic networks

PubMed Central

Filho, Humberto A.; Machicao, Jeaneth

2018-01-01

Modeling the basic structure of metabolic machinery is a challenge for modern biology. Some models based on complex networks have provided important information regarding this machinery. In this paper, we constructed metabolic networks of 17 plants covering unicellular organisms to more complex dicotyledonous plants. The metabolic networks were built based on the substrate-product model and a topological percolation was performed using the kcore decomposition. The distribution of metabolites across the percolation layers showed correlations between the metabolic integration hierarchy and the network topology. We show that metabolites concentrated in the internal network (maximum kcore) only comprise molecules of the primary basal metabolism. Moreover, we found a high proportion of a set of common metabolites, among the 17 plants, centered at the inner kcore layers. Meanwhile, the metabolites recognized as participants in the secondary metabolism of plants are concentrated in the outermost layers of the network. This data suggests that the metabolites in the central layer form a basic molecular module in which the whole plant metabolism is anchored. The elements from this central core participate in almost all plant metabolic reactions, which suggests that plant metabolic networks follows a centralized topology. PMID:29734359

Multidisciplinary Optimization Methods for Aircraft Preliminary Design

NASA Technical Reports Server (NTRS)

Kroo, Ilan; Altus, Steve; Braun, Robert; Gage, Peter; Sobieski, Ian

1994-01-01

This paper describes a research program aimed at improved methods for multidisciplinary design and optimization of large-scale aeronautical systems. The research involves new approaches to system decomposition, interdisciplinary communication, and methods of exploiting coarse-grained parallelism for analysis and optimization. A new architecture, that involves a tight coupling between optimization and analysis, is intended to improve efficiency while simplifying the structure of multidisciplinary, computation-intensive design problems involving many analysis disciplines and perhaps hundreds of design variables. Work in two areas is described here: system decomposition using compatibility constraints to simplify the analysis structure and take advantage of coarse-grained parallelism; and collaborative optimization, a decomposition of the optimization process to permit parallel design and to simplify interdisciplinary communication requirements.

Alkaloids May Not be Responsible for Endophyte Associated Reductions in Tall Fescue Decomposition Rates

USDA-ARS?s Scientific Manuscript database

1. Fungal endophyte - grass symbioses can have dramatic ecological effects, altering individual plant physiology, plant and animal community structure and function, and ecosystem processes such as litter decomposition and nutrient cycling. 2. Within the tall fescue (Schedonorus arundinaceus) - funga...

Characterization of alkyl carbon in forest soils by CPMAS 13C NMR spectroscopy and dipolar dephasing

USGS Publications Warehouse

Kogel-Knabner, I.; Hatcher, P.G.

1989-01-01

Samples obtained from forest soils at different stages of decomposition were treated sequentially with chloroform/methanol (extraction of lipids), sulfuric acid (hydrolysis), and sodium chlorite (delignification) to enrich them in refractory alkyl carbon. As revealed by NMR spectroscopy, this treatment yielded residues with high contents of alkyl carbon. In the NMR spectra of residues obtained from litter samples, resonances for carbohydrates are also present, indicating that these carbohydrates are tightly bound to the alkyl carbon structures. During decomposition in the soils this resistant carbohydrate fraction is lost almost completely. In the litter samples the alkyl carbon shows a dipolar dephasing behavior indicative of two structural components, a rigid and a more mobile component. As depth and decomposition increase, only the rigid component is observed. This fact could be due to selective degradation of the mobile component or to changes in molecular mobility during decomposition, e.g., because of an increase in cross linking or contact with the mineral matter of the soil.

Rapid characterization of lithium ion battery electrolytes and thermal aging products by low-temperature plasma ambient ionization high-resolution mass spectrometry.

PubMed

Vortmann, Britta; Nowak, Sascha; Engelhard, Carsten

2013-03-19

Lithium ion batteries (LIBs) are key components for portable electronic devices that are used around the world. However, thermal decomposition products in the battery reduce its lifetime, and decomposition processes are still not understood. In this study, a rapid method for in situ analysis and reaction monitoring in LIB electrolytes is presented based on high-resolution mass spectrometry (HR-MS) with low-temperature plasma probe (LTP) ambient desorption/ionization for the first time. This proof-of-principle study demonstrates the capabilities of ambient mass spectrometry in battery research. LTP-HR-MS is ideally suited for qualitative analysis in the ambient environment because it allows direct sample analysis independent of the sample size, geometry, and structure. Further, it is environmental friendly because it eliminates the need of organic solvents that are typically used in separation techniques coupled to mass spectrometry. Accurate mass measurements were used to identify the time-/condition-dependent formation of electrolyte decomposition compounds. A LIB model electrolyte containing ethylene carbonate and dimethyl carbonate was analyzed before and after controlled thermal stress and over the course of several weeks. Major decomposition products identified include difluorophosphoric acid, monofluorophosphoric acid methyl ester, monofluorophosphoric acid dimethyl ester, and hexafluorophosphate. Solvents (i.e., dimethyl carbonate) were partly consumed via an esterification pathway. LTP-HR-MS is considered to be an attractive method for fundamental LIB studies.

Decomposition of algal lipids in clay-enriched marine sediment under oxic and anoxic conditions

NASA Astrophysics Data System (ADS)

Lü, Dongwei; Song, Qian; Wang, Xuchen

2010-01-01

A series of laboratory incubation experiments were conducted to examine the decomposition of algal organic matter in clay-enriched marine sediment under oxic and anoxic conditions. During the 245-day incubation period, changes in the concentrations of TOC, major algal fatty acid components (14:0, 16:0, 16:1, 18:1 and 20:5), and n-alkanes (C16-C23) were quantified in the samples. Our results indicate that the organic matters were degraded more rapidly in oxic than anoxic conditions. Adsorption of fatty acids onto clay minerals was a rapid and reversible process. Using a simple G model, we calculated the decomposition rate constants for TOC, n-alkanes and fatty acids which ranged from 0.017-0.024 d-1, 0.049-0.103 d-1 and 0.011 to 0.069 d-1, respectively. Algal organic matter degraded in two stages characterized by a fast and a slow degradation processes. The addition of clay minerals montmorillonite and kaolinite to the sediments showed significant influence affecting the decomposition processes of algal TOC and fatty acids by adsorption and incorporation of the compounds with clay particles. Adsorption/association of fatty acids by clay minerals was rapid but appeared to be a slow reversible process. In addition to the sediment redox and clay influence, the structure of the compounds also played important roles in affecting their degradation dynamic in sediments.

Molecular modeling of the dissociation of methane hydrate in contact with a silica surface.

PubMed

Bagherzadeh, S Alireza; Englezos, Peter; Alavi, Saman; Ripmeester, John A

2012-03-15

We use constant energy, constant volume (NVE) molecular dynamics simulations to study the dissociation of the fully occupied structure I methane hydrate in a confined geometry between two hydroxylated silica surfaces between 36 and 41 Å apart, at initial temperatures of 283, 293, and 303 K. Simulations of the two-phase hydrate/water system are performed in the presence of silica, with and without a 3 Å thick buffering water layer between the hydrate phase and silica surfaces. Faster decomposition is observed in the presence of silica, where the hydrate phase is prone to decomposition from four surfaces, as compared to only two sides in the case of the hydrate/water simulations. The existence of the water layer between the hydrate phase and the silica surface stabilizes the hydrate phase relative to the case where the hydrate is in direct contact with silica. Hydrates bound between the silica surfaces dissociate layer-by-layer in a shrinking core manner with a curved decomposition front which extends over a 5-8 Å thickness. Labeling water molecules shows that there is exchange of water molecules between the surrounding liquid and intact cages in the methane hydrate phase. In all cases, decomposition of the methane hydrate phase led to the formation of methane nanobubbles in the liquid water phase. © 2012 American Chemical Society

When are Overcomplete Topic Models Identifiable? Uniqueness of Tensor Tucker Decompositions with Structured Sparsity

DTIC Science & Technology

2013-08-14

Communications and Computing, Electrical Engineering and Computer Science Dept., University of California, Irvine, USA 92697. Email : a.anandkumar...uci.edu,mjanzami@uci.edu. Daniel Hsu and Sham Kakade are with Microsoft Research New England, 1 Memorial Drive, Cambridge, MA 02142. Email : dahsu...Andreas Maurer, Massimiliano Pontil, and Bernardino Romera-Paredes. Sparse coding for multitask and transfer learning. ArxXiv preprint, abs/1209.0738, 2012

Inundation, vegetation, and sediment effects on litter decomposition in Pacific Coast tidal marshes

USGS Publications Warehouse

Janousek, Christopher; Buffington, Kevin J.; Guntenspergen, Glenn R.; Thorne, Karen M.; Dugger, Bruce D.; Takekawa, John Y.

2017-01-01

The cycling and sequestration of carbon are important ecosystem functions of estuarine wetlands that may be affected by climate change. We conducted experiments across a latitudinal and climate gradient of tidal marshes in the northeast Pacific to evaluate the effects of climate- and vegetation-related factors on litter decomposition. We manipulated tidal exposure and litter type in experimental mesocosms at two sites and used variation across marsh landscapes at seven sites to test for relationships between decomposition and marsh elevation, soil temperature, vegetation composition, litter quality, and sediment organic content. A greater than tenfold increase in manipulated tidal inundation resulted in small increases in decomposition of roots and rhizomes of two species, but no significant change in decay rates of shoots of three other species. In contrast, across the latitudinal gradient, decomposition rates of Salicornia pacifica litter were greater in high marsh than in low marsh. Rates were not correlated with sediment temperature or organic content, but were associated with plant assemblage structure including above-ground cover, species composition, and species richness. Decomposition rates also varied by litter type; at two sites in the Pacific Northwest, the grasses Deschampsia cespitosa and Distichlis spicata decomposed more slowly than the forb S. pacifica. Our data suggest that elevation gradients and vegetation structure in tidal marshes both affect rates of litter decay, potentially leading to complex spatial patterns in sediment carbon dynamics. Climate change may thus have direct effects on rates of decomposition through increased inundation from sea-level rise and indirect effects through changing plant community composition.

Nascent energy distribution of the Criegee intermediate CH2OO from direct dynamics calculations of primary ozonide dissociation.

PubMed

Pfeifle, Mark; Ma, Yong-Tao; Jasper, Ahren W; Harding, Lawrence B; Hase, William L; Klippenstein, Stephen J

2018-05-07

Ozonolysis produces chemically activated carbonyl oxides (Criegee intermediates, CIs) that are either stabilized or decompose directly. This branching has an important impact on atmospheric chemistry. Prior theoretical studies have employed statistical models for energy partitioning to the CI arising from dissociation of the initially formed primary ozonide (POZ). Here, we used direct dynamics simulations to explore this partitioning for decomposition of c-C 2 H 4 O 3 , the POZ in ethylene ozonolysis. A priori estimates for the overall stabilization probability were then obtained by coupling the direct dynamics results with master equation simulations. Trajectories were initiated at the concerted cycloreversion transition state, as well as the second transition state of a stepwise dissociation pathway, both leading to a CI (H 2 COO) and formaldehyde (H 2 CO). The resulting CI energy distributions were incorporated in master equation simulations of CI decomposition to obtain channel-specific stabilized CI (sCI) yields. Master equation simulations of POZ formation and decomposition, based on new high-level electronic structure calculations, were used to predict yields for the different POZ decomposition channels. A non-negligible contribution of stepwise POZ dissociation was found, and new mechanistic aspects of this pathway were elucidated. By combining the trajectory-based channel-specific sCI yields with the channel branching fractions, an overall sCI yield of (48 ± 5)% was obtained. Non-statistical energy release was shown to measurably affect sCI formation, with statistical models predicting significantly lower overall sCI yields (∼30%). Within the range of experimental literature values (35%-54%), our trajectory-based calculations favor those clustered at the upper end of the spectrum.

Nascent energy distribution of the Criegee intermediate CH2OO from direct dynamics calculations of primary ozonide dissociation

NASA Astrophysics Data System (ADS)

Pfeifle, Mark; Ma, Yong-Tao; Jasper, Ahren W.; Harding, Lawrence B.; Hase, William L.; Klippenstein, Stephen J.

2018-05-01

Ozonolysis produces chemically activated carbonyl oxides (Criegee intermediates, CIs) that are either stabilized or decompose directly. This branching has an important impact on atmospheric chemistry. Prior theoretical studies have employed statistical models for energy partitioning to the CI arising from dissociation of the initially formed primary ozonide (POZ). Here, we used direct dynamics simulations to explore this partitioning for decomposition of c-C2H4O3, the POZ in ethylene ozonolysis. A priori estimates for the overall stabilization probability were then obtained by coupling the direct dynamics results with master equation simulations. Trajectories were initiated at the concerted cycloreversion transition state, as well as the second transition state of a stepwise dissociation pathway, both leading to a CI (H2COO) and formaldehyde (H2CO). The resulting CI energy distributions were incorporated in master equation simulations of CI decomposition to obtain channel-specific stabilized CI (sCI) yields. Master equation simulations of POZ formation and decomposition, based on new high-level electronic structure calculations, were used to predict yields for the different POZ decomposition channels. A non-negligible contribution of stepwise POZ dissociation was found, and new mechanistic aspects of this pathway were elucidated. By combining the trajectory-based channel-specific sCI yields with the channel branching fractions, an overall sCI yield of (48 ± 5)% was obtained. Non-statistical energy release was shown to measurably affect sCI formation, with statistical models predicting significantly lower overall sCI yields (˜30%). Within the range of experimental literature values (35%-54%), our trajectory-based calculations favor those clustered at the upper end of the spectrum.

Interfacial instability of amorphous LiPON against lithium: A combined Density Functional Theory and spectroscopic study

NASA Astrophysics Data System (ADS)

Sicolo, Sabrina; Fingerle, Mathias; Hausbrand, René; Albe, Karsten

2017-06-01

The chemical instability of the glassy solid electrolyte LiPON against metallic lithium and the occurrence of side reactions at their interface is investigated by combining a surface science approach and quantum-mechanical calculations. Using an evolutionary structure search followed by a melt-quenching protocol, a model for the disordered structure of LiPON is generated and put into contact with lithium. Even the static optimization of a simple model interface suggests that the diffusion of lithium into LiPON is driven by a considerable driving force that could easily take place under experimental conditions. Calculated reaction energies indicate that the reduction and decomposition of LiPON is thermodynamically favorable. By monitoring the evolution of the LiPON core levels as a function of lithium exposure, the disruption of the LiPON network alongside the occurrence of new phases is observed. The direct comparison between UV photoelectron spectroscopy measurements and calculated electronic densities of states for increasing stages of lithiation univocally identifies the new phases as Li2O, Li3P and Li3N. These products are stable against Li metal and form a passivation layer which shields the electrolyte from further decomposition while allowing for the diffusion of Li ions.

The 'overflow tap' theory: linking GPP to forest soil carbon dynamics and the mycorrhizal component

NASA Astrophysics Data System (ADS)

Heinemeyer, Andreas; Willkinson, Matthew; Subke, Jens-Arne; Casella, Eric; Vargas, Rodrigo; Morison, James; Ineson, Phil

2010-05-01

Quantifying soil organic carbon (SOC) dynamics accurately is crucial to underpin better predictions of future climate change feedbacks within the atmosphere-vegetation-soil system. Measuring the components of ecosystem carbon fluxes has become a central point of the research focus during the last decade, not least because of the large SOC stocks, potentially vulnerable to climate change. However, our basic understanding of the composition and environmental responses of the soil CO2 efflux is still under debate and limited by the available field methodologies. For example, only recently did we separate successfully root (R), mycorrhizal fungal (F) and soil animal/microbial (H) respiration based on a mesh-bag/collar methodology and described their unique environmental responses. Yet it might be these differences which are crucial for understanding C-cycle feedbacks and observed limitations in plant biomass increase under elevated carbon dioxide (e.g. FACE) studies. It is becoming clear that these flux components and their environmental responses must be incorporated in models that link but also treat the heterotrophic and autotrophic fluxes separately. However, owing to a scarcity of experimental data, separation of fluxes and environmental drivers has been ignored in current models. We are now in a position to parameterize realistic soil C turnover models that include both, decomposition and plant-derived fluxes. Such models will allow (1) a direct comparison of model output to field data for all flux components, (2) include the potential to link plant C allocation to the rhizosphere with increased decomposition activity through soil C priming, and (3) to explore the potential of plant biomass C sequestration limitations under increased C assimilation. These mechanisms are fundamental in describing the stability of future SOC stocks due to elevated temperatures and carbon dioxide, altering SOC decomposition directly and indirectly through changes in plant productivity. The work presented here focuses on three critical areas: (1) We present annual fluxes at hourly intervals for the three soil CO2 efflux components (R, F and H) from a 75 year-old deciduous oak forest in SE England. We investigate the individual environmental responses of the three flux components, and compare them to soil decomposition modelled by CENTURY and its latest version (i.e. DAYCENT), which separately models root-derived respiration in addition to the soil decomposition output. (2) Using estimates of gross primary productivity (GPP) based on eddy covariance measurements from the same site, we explore linkages between GPP and soil respiration component fluxes using basic regression and wavelet analyses. We show a distinctly different time lag signal between GPP and root vs. mycorrhizal fungal respiration. We then discuss how models might need to be improved to accurately predict total soil CO2 efflux, including root-derived respiration. (3) We finally discuss the ‘overflow tap' theory, that during periods of high assimilation (e.g. optimum environmental conditions or elevated CO2) surplus non-structural C is allocated belowground to the mycorrhizal network; this additional C could then be used and released by the associated fungal partners, causing soil priming through stimulating decomposition.

Applications of molecular modeling in coal research

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carlson, G.A.; Faulon, J.L.

Over the past several years, molecular modeling has been applied to study various characteristics of coal molecular structures. Powerful workstations coupled with molecular force-field-based software packages have been used to study coal and coal-related molecules. Early work involved determination of the minimum-energy three-dimensional conformations of various published coal structures (Given, Wiser, Solomon and Shinn), and the dominant role of van der Waals and hydrogen bonding forces in defining the energy-minimized structures. These studies have been extended to explore various physical properties of coal structures, including density, microporosity, surface area, and fractal dimension. Other studies have related structural characteristics to cross-linkmore » density and have explored small molecule interactions with coal. Finally, recent studies using a structural elucidation (molecular builder) technique have constructed statistically diverse coal structures based on quantitative and qualitative data on coal and its decomposition products. This technique is also being applied to study coalification processes based on postulated coalification chemistry.« less

Limited-memory adaptive snapshot selection for proper orthogonal decomposition

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oxberry, Geoffrey M.; Kostova-Vassilevska, Tanya; Arrighi, Bill

2015-04-02

Reduced order models are useful for accelerating simulations in many-query contexts, such as optimization, uncertainty quantification, and sensitivity analysis. However, offline training of reduced order models can have prohibitively expensive memory and floating-point operation costs in high-performance computing applications, where memory per core is limited. To overcome this limitation for proper orthogonal decomposition, we propose a novel adaptive selection method for snapshots in time that limits offline training costs by selecting snapshots according an error control mechanism similar to that found in adaptive time-stepping ordinary differential equation solvers. The error estimator used in this work is related to theory boundingmore » the approximation error in time of proper orthogonal decomposition-based reduced order models, and memory usage is minimized by computing the singular value decomposition using a single-pass incremental algorithm. Results for a viscous Burgers’ test problem demonstrate convergence in the limit as the algorithm error tolerances go to zero; in this limit, the full order model is recovered to within discretization error. The resulting method can be used on supercomputers to generate proper orthogonal decomposition-based reduced order models, or as a subroutine within hyperreduction algorithms that require taking snapshots in time, or within greedy algorithms for sampling parameter space.« less

Vulnerability of Permafrost Soil Carbon to Climate Warming: Evaluating Controls on Microbial Community Composition

USDA-ARS?s Scientific Manuscript database

Abstract: Despite the fact that permafrost soils contain up to half of the carbon (C) in terrestrial pools, we have a poor understanding of the controls on decomposition in thawed permafrost. Global climate models assume that decomposition increases linearly with temperature, yet decomposition in th...

Integrated aerodynamic/dynamic/structural optimization of helicopter rotor blades using multilevel decomposition

NASA Technical Reports Server (NTRS)

Walsh, Joanne L.; Young, Katherine C.; Pritchard, Jocelyn I.; Adelman, Howard M.; Mantay, Wayne R.

1995-01-01

This paper describes an integrated aerodynamic/dynamic/structural (IADS) optimization procedure for helicopter rotor blades. The procedure combines performance, dynamics, and structural analyses with a general-purpose optimizer using multilevel decomposition techniques. At the upper level, the structure is defined in terms of global quantities (stiffness, mass, and average strains). At the lower level, the structure is defined in terms of local quantities (detailed dimensions of the blade structure and stresses). The IADS procedure provides an optimization technique that is compatible with industrial design practices in which the aerodynamic and dynamic designs are performed at a global level and the structural design is carried out at a detailed level with considerable dialog and compromise among the aerodynamic, dynamic, and structural groups. The IADS procedure is demonstrated for several examples.

Multilevel decomposition approach to integrated aerodynamic/dynamic/structural optimization of helicopter rotor blades

NASA Technical Reports Server (NTRS)

Walsh, Joanne L.; Young, Katherine C.; Pritchard, Jocelyn I.; Adelman, Howard M.; Mantay, Wayne R.

1994-01-01

This paper describes an integrated aerodynamic, dynamic, and structural (IADS) optimization procedure for helicopter rotor blades. The procedure combines performance, dynamics, and structural analyses with a general purpose optimizer using multilevel decomposition techniques. At the upper level, the structure is defined in terms of local quantities (stiffnesses, mass, and average strains). At the lower level, the structure is defined in terms of local quantities (detailed dimensions of the blade structure and stresses). The IADS procedure provides an optimization technique that is compatible with industrial design practices in which the aerodynamic and dynamic design is performed at a global level and the structural design is carried out at a detailed level with considerable dialogue and compromise among the aerodynamic, dynamic, and structural groups. The IADS procedure is demonstrated for several cases.

Quantum theory for the dynamic structure factor in correlated two-component systems in nonequilibrium: Application to x-ray scattering.

PubMed

Vorberger, J; Chapman, D A

2018-01-01

We present a quantum theory for the dynamic structure factors in nonequilibrium, correlated, two-component systems such as plasmas or warm dense matter. The polarization function, which is needed as the input for the calculation of the structure factors, is calculated in nonequilibrium based on a perturbation expansion in the interaction strength. To make our theory applicable for x-ray scattering, a generalized Chihara decomposition for the total electron structure factor in nonequilibrium is derived. Examples are given and the influence of correlations and exchange on the structure and the x-ray-scattering spectrum are discussed for a model nonequilibrium distribution, as often encountered during laser heating of materials, as well as for two-temperature systems.

Quantum theory for the dynamic structure factor in correlated two-component systems in nonequilibrium: Application to x-ray scattering

NASA Astrophysics Data System (ADS)

Vorberger, J.; Chapman, D. A.

2018-01-01

We present a quantum theory for the dynamic structure factors in nonequilibrium, correlated, two-component systems such as plasmas or warm dense matter. The polarization function, which is needed as the input for the calculation of the structure factors, is calculated in nonequilibrium based on a perturbation expansion in the interaction strength. To make our theory applicable for x-ray scattering, a generalized Chihara decomposition for the total electron structure factor in nonequilibrium is derived. Examples are given and the influence of correlations and exchange on the structure and the x-ray-scattering spectrum are discussed for a model nonequilibrium distribution, as often encountered during laser heating of materials, as well as for two-temperature systems.

Supermassive black holes and their host galaxies. I. Bulge luminosities from dedicated near-infrared data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Läsker, Ronald; Van de Ven, Glenn; Ferrarese, Laura, E-mail: laesker@mpia.de

2014-01-01

In an effort to secure, refine, and supplement the relation between central supermassive black hole masses, M {sub •}, and the bulge luminosities of their host galaxies, L {sub bul}, we obtained deep, high spatial resolution K-band images of 35 nearby galaxies with securely measured M {sub •}, using the wide-field WIRCam imager at the Canada-France-Hawaii-Telescope. A dedicated data reduction and sky subtraction strategy was adopted to estimate the brightness and structure of the sky, a critical step when tracing the light distribution of extended objects in the near-infrared. From the final image product, bulge and total magnitudes were extractedmore » via two-dimensional profile fitting. As a first order approximation, all galaxies were modeled using a simple Sérsic-bulge+exponential-disk decomposition. However, we found that such models did not adequately describe the structure that we observed in a large fraction of our sample galaxies which often include cores, bars, nuclei, inner disks, spiral arms, rings, and envelopes. In such cases, we adopted profile modifications and/or more complex models with additional components. The derived bulge magnitudes are very sensitive to the details and number of components used in the models, although total magnitudes remain almost unaffected. Usually, but not always, the luminosities and sizes of the bulges are overestimated when a simple bulge+disk decomposition is adopted in lieu of a more complex model. Furthermore, we found that some spheroids are not well fit when the ellipticity of the Sérsic model is held fixed. This paper presents the details of the image processing and analysis, while we discuss how model-induced biases and systematics in bulge magnitudes impact the M {sub •}-L {sub bul} relation in a companion paper.« less

Supermassive Black Holes and Their Host Galaxies. I. Bulge Luminosities from Dedicated Near-infrared Data

NASA Astrophysics Data System (ADS)

Läsker, Ronald; Ferrarese, Laura; van de Ven, Glenn

2014-01-01

In an effort to secure, refine, and supplement the relation between central supermassive black hole masses, M •, and the bulge luminosities of their host galaxies, L bul, we obtained deep, high spatial resolution K-band images of 35 nearby galaxies with securely measured M •, using the wide-field WIRCam imager at the Canada-France-Hawaii-Telescope. A dedicated data reduction and sky subtraction strategy was adopted to estimate the brightness and structure of the sky, a critical step when tracing the light distribution of extended objects in the near-infrared. From the final image product, bulge and total magnitudes were extracted via two-dimensional profile fitting. As a first order approximation, all galaxies were modeled using a simple Sérsic-bulge+exponential-disk decomposition. However, we found that such models did not adequately describe the structure that we observed in a large fraction of our sample galaxies which often include cores, bars, nuclei, inner disks, spiral arms, rings, and envelopes. In such cases, we adopted profile modifications and/or more complex models with additional components. The derived bulge magnitudes are very sensitive to the details and number of components used in the models, although total magnitudes remain almost unaffected. Usually, but not always, the luminosities and sizes of the bulges are overestimated when a simple bulge+disk decomposition is adopted in lieu of a more complex model. Furthermore, we found that some spheroids are not well fit when the ellipticity of the Sérsic model is held fixed. This paper presents the details of the image processing and analysis, while we discuss how model-induced biases and systematics in bulge magnitudes impact the M •-L bul relation in a companion paper.

Rate of warming affects temperature sensitivity of anaerobic peat decomposition and greenhouse gas production.

PubMed

Sihi, Debjani; Inglett, Patrick W; Gerber, Stefan; Inglett, Kanika S

2018-01-01

Temperature sensitivity of anaerobic carbon mineralization in wetlands remains poorly represented in most climate models and is especially unconstrained for warmer subtropical and tropical systems which account for a large proportion of global methane emissions. Several studies of experimental warming have documented thermal acclimation of soil respiration involving adjustments in microbial physiology or carbon use efficiency (CUE), with an initial decline in CUE with warming followed by a partial recovery in CUE at a later stage. The variable CUE implies that the rate of warming may impact microbial acclimation and the rate of carbon-dioxide (CO 2 ) and methane (CH 4 ) production. Here, we assessed the effects of warming rate on the decomposition of subtropical peats, by applying either a large single-step (10°C within a day) or a slow ramping (0.1°C/day for 100 days) temperature increase. The extent of thermal acclimation was tested by monitoring CO 2 and CH 4 production, CUE, and microbial biomass. Total gaseous C loss, CUE, and MBC were greater in the slow (ramp) warming treatment. However, greater values of CH 4 -C:CO 2 -C ratios lead to a greater global warming potential in the fast (step) warming treatment. The effect of gradual warming on decomposition was more pronounced in recalcitrant and nutrient-limited soils. Stable carbon isotopes of CH 4 and CO 2 further indicated the possibility of different carbon processing pathways under the contrasting warming rates. Different responses in fast vs. slow warming treatment combined with different endpoints may indicate alternate pathways with long-term consequences. Incorporations of experimental results into organic matter decomposition models suggest that parameter uncertainties in CUE and CH 4 -C:CO 2 -C ratios have a larger impact on long-term soil organic carbon and global warming potential than uncertainty in model structure, and shows that particular rates of warming are central to understand the response of wetland soils to global climate change. © 2017 John Wiley & Sons Ltd.

The decomposition of mixed oxide Ag2Cu2O3: Structural features and the catalytic properties in CO and C2H4 oxidation

NASA Astrophysics Data System (ADS)

Svintsitskiy, Dmitry A.; Kardash, Tatyana Yu.; Slavinskaya, Elena M.; Stonkus, Olga A.; Koscheev, Sergei V.; Boronin, Andrei I.

2018-01-01

The mixed silver-copper oxide Ag2Cu2O3 with a paramelaconite crystal structure is a promising material for catalytic applications. The as-prepared sample of Ag2Cu2O3 consisted of brick-like particles extended along the [001] direction. A combination of physicochemical techniques such as TEM, XPS and XRD was applied to investigate the structural features of this mixed silver-copper oxide. The thermal stability of Ag2Cu2O3 was investigated using in situ XRD under different reaction conditions, including a catalytic CO + O2 mixture. The first step of Ag2Cu2O3 decomposition was accompanied by the appearance of ensembles consisting of silver nanoparticles with sizes of 5-15 nm. Silver nanoparticles were strongly oriented to each other and to the surface of the initial Ag2Cu2O3 bricks. Based on the XRD data, it was shown that the release of silver occurred along the a and b axes of the paramelaconite structure. Partial decomposition of Ag2Cu2O3 accompanied by the formation of silver nanoparticles was observed during prolonged air storage under ambient conditions. The high reactivity is discussed as a reason for spontaneous decomposition during Ag2Cu2O3 storage. The full decomposition of the mixed oxide into metallic silver and copper (II) oxide took place at temperatures higher than 300 °C regardless of the nature of the reaction medium (helium, air, CO + O2). Catalytic properties of partially and fully decomposed samples of mixed silver-copper oxide were measured in low-temperature CO oxidation and C2H4 epoxidation reactions.

A lattice approach to the conformal OSp(2S+2|2S) supercoset sigma model. Part I: Algebraic structures in the spin chain. The Brauer algebra

NASA Astrophysics Data System (ADS)

Candu, Constantin; Saleur, Hubert

2009-02-01

We define and study a lattice model which we argue is in the universality class of the OSp(2S+2|2S) supercoset sigma model for a large range of values of the coupling constant gσ2. In this first paper, we analyze in details the symmetries of this lattice model, in particular the decomposition of the space of the quantum spin chain V as a bimodule over OSp(2S+2|2S) and its commutant, the Brauer algebra B(2). It turns out that V is a nonsemisimple module for both OSp(2S+2|2S) and B(2). The results are used in the companion paper to elucidate the structure of the (boundary) conformal field theory.

More of the same? In situ leaf and root decomposition rates do not vary between 80 native and nonnative deciduous forest species.

PubMed

Jo, Insu; Fridley, Jason D; Frank, Douglas A

2016-01-01

Invaders often have greater rates of production and produce more labile litter than natives. The increased litter quantity and quality of invaders should increase nutrient cycling through faster litter decomposition. However, the limited number of invasive species that have been included in decomposition studies has hindered the ability to generalize their impacts on decomposition rates. Further, previous decomposition studies have neglected roots. We measured litter traits and decomposition rates of leaves for 42 native and 36 nonnative woody species, and those of fine roots for 23 native and 25 nonnative species that occur in temperate deciduous forests throughout the Eastern USA. Among the leaf and root traits that differed between native and invasive species, only leaf nitrogen was significantly associated with decomposition rate. However, native and nonnative species did not differ systematically in leaf and root decomposition rates. We found that among the parameters measured, litter decomposer activity was driven by litter chemical quality rather than tissue density and structure. Our results indicate that litter decomposition rate per se is not a pathway by which forest woody invasive species affect North American temperate forest soil carbon and nutrient processes. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

The relative importance of decomposition and transport mechanisms in accounting for C profiles

NASA Astrophysics Data System (ADS)

Guenet, B.; Eglin, T.; Vasilyeva, N.; Peylin, P.; Ciais, P.; Chenu, C.

2012-10-01

Soil is the major terrestrial reservoirs of carbon, and a substantial part of this carbon is stored in deep layers, typically deeper than 50 cm below the surface. Several studies underlined the quantitative importance of this deep Soil Organic Carbon (SOC) pool and models are needed to better understand this stock and its evolution under climate and land-uses changes. In this study, we test and compare 3 simple theoretical models of vertical transport for SOC against SOC profiles measurements from a long-term bare fallow experiment carried out by the Central-Chernozem State Natural Biosphere Reserve named after V.V. Alekhin, in the Kursk Region of Russia. The transport schemes tested are diffusion, advection or both diffusion and advection. They are coupled to two different formulations of soil carbon decomposition kinetics. The first formulation is a first order kinetics widely used in global SOC decomposition models; the second one links SOC decomposition rate to the amount of fresh organic matter, representing a "priming effect". Field data are from a set of three bare fallow plots where soil received no input during the past 20, 26 and 58 yr respectively. Parameters of the models were optimized using a Bayesian method. The best results are obtained when SOC decomposition is assumed to be controlled by fresh organic matter. In comparison to the first-order kinetic model, the "priming" model reduces the underestimation of SOC decomposition in the top layers and the over estimation in the deep layers. We also observe that the transport scheme that improved the fit with the data depends on the soil carbon mineralization formulation chosen. When soil carbon decomposition is modelled to depend on the fresh organic matter amount, the transport mechanisms which improves best the fit to the SOC profile data is the model representing both advection and diffusion. Interestingly, the older the bare fallow is, the lesser the need for diffusion is. This suggests that stabilized carbon may not be transported within the profile by the same mechanisms than more labile carbon.

Are litter decomposition and fire linked through plant species traits?

PubMed

Cornelissen, Johannes H C; Grootemaat, Saskia; Verheijen, Lieneke M; Cornwell, William K; van Bodegom, Peter M; van der Wal, René; Aerts, Rien

2017-11-01

Contents 653 I. 654 II. 657 III. 659 IV. 661 V. 662 VI. 663 VII. 665 665 References 665 SUMMARY: Biological decomposition and wildfire are connected carbon release pathways for dead plant material: slower litter decomposition leads to fuel accumulation. Are decomposition and surface fires also connected through plant community composition, via the species' traits? Our central concept involves two axes of trait variation related to decomposition and fire. The 'plant economics spectrum' (PES) links biochemistry traits to the litter decomposability of different fine organs. The 'size and shape spectrum' (SSS) includes litter particle size and shape and their consequent effect on fuel bed structure, ventilation and flammability. Our literature synthesis revealed that PES-driven decomposability is largely decoupled from predominantly SSS-driven surface litter flammability across species; this finding needs empirical testing in various environmental settings. Under certain conditions, carbon release will be dominated by decomposition, while under other conditions litter fuel will accumulate and fire may dominate carbon release. Ecosystem-level feedbacks between decomposition and fire, for example via litter amounts, litter decomposition stage, community-level biotic interactions and altered environment, will influence the trait-driven effects on decomposition and fire. Yet, our conceptual framework, explicitly comparing the effects of two plant trait spectra on litter decomposition vs fire, provides a promising new research direction for better understanding and predicting Earth surface carbon dynamics. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.

Teaching Quality Management Model for the Training of Innovation Ability and the Multilevel Decomposition Indicators

ERIC Educational Resources Information Center

Lu, Xingjiang; Yao, Chen; Zheng, Jianmin

2013-01-01

This paper focuses on the training of undergraduate students' innovation ability. On top of the theoretical framework of the Quality Function Deployment (QFD), we propose a teaching quality management model. Based on this model, we establish a multilevel decomposition indicator system, which integrates innovation ability characterized by four…

Differential Decomposition Among Pig, Rabbit, and Human Remains.

PubMed

Dautartas, Angela; Kenyhercz, Michael W; Vidoli, Giovanna M; Meadows Jantz, Lee; Mundorff, Amy; Steadman, Dawnie Wolfe

2018-03-30

While nonhuman animal remains are often utilized in forensic research to develop methods to estimate the postmortem interval, systematic studies that directly validate animals as proxies for human decomposition are lacking. The current project compared decomposition rates among pigs, rabbits, and humans at the University of Tennessee's Anthropology Research Facility across three seasonal trials that spanned nearly 2 years. The Total Body Score (TBS) method was applied to quantify decomposition changes and calculate the postmortem interval (PMI) in accumulated degree days (ADD). Decomposition trajectories were analyzed by comparing the estimated and actual ADD for each seasonal trial and by fuzzy cluster analysis. The cluster analysis demonstrated that the rabbits formed one group while pigs and humans, although more similar to each other than either to rabbits, still showed important differences in decomposition patterns. The decomposition trends show that neither nonhuman model captured the pattern, rate, and variability of human decomposition. © 2018 American Academy of Forensic Sciences.

Assessing first-order emulator inference for physical parameters in nonlinear mechanistic models

USGS Publications Warehouse

Hooten, Mevin B.; Leeds, William B.; Fiechter, Jerome; Wikle, Christopher K.

2011-01-01

We present an approach for estimating physical parameters in nonlinear models that relies on an approximation to the mechanistic model itself for computational efficiency. The proposed methodology is validated and applied in two different modeling scenarios: (a) Simulation and (b) lower trophic level ocean ecosystem model. The approach we develop relies on the ability to predict right singular vectors (resulting from a decomposition of computer model experimental output) based on the computer model input and an experimental set of parameters. Critically, we model the right singular vectors in terms of the model parameters via a nonlinear statistical model. Specifically, we focus our attention on first-order models of these right singular vectors rather than the second-order (covariance) structure.

Morphological Decomposition in Reading Hebrew Homographs

ERIC Educational Resources Information Center

Miller, Paul; Liran-Hazan, Batel; Vaknin, Vered

2016-01-01

The present work investigates whether and how morphological decomposition processes bias the reading of Hebrew heterophonic homographs, i.e., unique orthographic patterns that are associated with two separate phonological, semantic entities depicted by means of two morphological structures (linear and nonlinear). In order to reveal the nature of…

Catalytic effects of inorganic acids on the decomposition of ammonium nitrate.

PubMed

Sun, Jinhua; Sun, Zhanhui; Wang, Qingsong; Ding, Hui; Wang, Tong; Jiang, Chuansheng

2005-12-09

In order to evaluate the catalytic effects of inorganic acids on the decomposition of ammonium nitrate (AN), the heat releases of decomposition or reaction of pure AN and its mixtures with inorganic acids were analyzed by a heat flux calorimeter C80. Through the experiments, the different reaction mechanisms of AN and its mixtures were analyzed. The chemical reaction kinetic parameters such as reaction order, activation energy and frequency factor were calculated with the C80 experimental results for different samples. Based on these parameters and the thermal runaway models (Semenov and Frank-Kamenestkii model), the self-accelerating decomposition temperatures (SADTs) of AN and its mixtures were calculated and compared. The results show that the mixtures of AN with acid are more unsteady than pure AN. The AN decomposition reaction is catalyzed by acid. The calculated SADTs of AN mixtures with acid are much lower than that of pure AN.

Trading strategy based on dynamic mode decomposition: Tested in Chinese stock market

NASA Astrophysics Data System (ADS)

Cui, Ling-xiao; Long, Wen

2016-11-01

Dynamic mode decomposition (DMD) is an effective method to capture the intrinsic dynamical modes of complex system. In this work, we adopt DMD method to discover the evolutionary patterns in stock market and apply it to Chinese A-share stock market. We design two strategies based on DMD algorithm. The strategy which considers only timing problem can make reliable profits in a choppy market with no prominent trend while fails to beat the benchmark moving-average strategy in bull market. After considering the spatial information from spatial-temporal coherent structure of DMD modes, we improved the trading strategy remarkably. Then the DMD strategies profitability is quantitatively evaluated by performing SPA test to correct the data-snooping effect. The results further prove that DMD algorithm can model the market patterns well in sideways market.

Modelling the influence of ectomycorrhizal decomposition on plant nutrition and soil carbon sequestration in boreal forest ecosystems.

PubMed

Baskaran, Preetisri; Hyvönen, Riitta; Berglund, S Linnea; Clemmensen, Karina E; Ågren, Göran I; Lindahl, Björn D; Manzoni, Stefano

2017-02-01

Tree growth in boreal forests is limited by nitrogen (N) availability. Most boreal forest trees form symbiotic associations with ectomycorrhizal (ECM) fungi, which improve the uptake of inorganic N and also have the capacity to decompose soil organic matter (SOM) and to mobilize organic N ('ECM decomposition'). To study the effects of 'ECM decomposition' on ecosystem carbon (C) and N balances, we performed a sensitivity analysis on a model of C and N flows between plants, SOM, saprotrophs, ECM fungi, and inorganic N stores. The analysis indicates that C and N balances were sensitive to model parameters regulating ECM biomass and decomposition. Under low N availability, the optimal C allocation to ECM fungi, above which the symbiosis switches from mutualism to parasitism, increases with increasing relative involvement of ECM fungi in SOM decomposition. Under low N conditions, increased ECM organic N mining promotes tree growth but decreases soil C storage, leading to a negative correlation between C stores above- and below-ground. The interplay between plant production and soil C storage is sensitive to the partitioning of decomposition between ECM fungi and saprotrophs. Better understanding of interactions between functional guilds of soil fungi may significantly improve predictions of ecosystem responses to environmental change. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

The ABC (in any D) of logarithmic CFT

NASA Astrophysics Data System (ADS)

Hogervorst, Matthijs; Paulos, Miguel; Vichi, Alessandro

2017-10-01

Logarithmic conformal field theories have a vast range of applications, from critical percolation to systems with quenched disorder. In this paper we thoroughly examine the structure of these theories based on their symmetry properties. Our analysis is model-independent and holds for any spacetime dimension. Our results include a determination of the general form of correlation functions and conformal block decompositions, clearing the path for future bootstrap applications. Several examples are discussed in detail, including logarithmic generalized free fields, holographic models, self-avoiding random walks and critical percolation.

Methods for simulation-based analysis of fluid-structure interaction.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barone, Matthew Franklin; Payne, Jeffrey L.

2005-10-01

Methods for analysis of fluid-structure interaction using high fidelity simulations are critically reviewed. First, a literature review of modern numerical techniques for simulation of aeroelastic phenomena is presented. The review focuses on methods contained within the arbitrary Lagrangian-Eulerian (ALE) framework for coupling computational fluid dynamics codes to computational structural mechanics codes. The review treats mesh movement algorithms, the role of the geometric conservation law, time advancement schemes, wetted surface interface strategies, and some representative applications. The complexity and computational expense of coupled Navier-Stokes/structural dynamics simulations points to the need for reduced order modeling to facilitate parametric analysis. The proper orthogonalmore » decomposition (POD)/Galerkin projection approach for building a reduced order model (ROM) is presented, along with ideas for extension of the methodology to allow construction of ROMs based on data generated from ALE simulations.« less

Many-level multilevel structural equation modeling: An efficient evaluation strategy.

PubMed

Pritikin, Joshua N; Hunter, Michael D; von Oertzen, Timo; Brick, Timothy R; Boker, Steven M

2017-01-01

Structural equation models are increasingly used for clustered or multilevel data in cases where mixed regression is too inflexible. However, when there are many levels of nesting, these models can become difficult to estimate. We introduce a novel evaluation strategy, Rampart, that applies an orthogonal rotation to the parts of a model that conform to commonly met requirements. This rotation dramatically simplifies fit evaluation in a way that becomes more potent as the size of the data set increases. We validate and evaluate the implementation using a 3-level latent regression simulation study. Then we analyze data from a state-wide child behavioral health measure administered by the Oklahoma Department of Human Services. We demonstrate the efficiency of Rampart compared to other similar software using a latent factor model with a 5-level decomposition of latent variance. Rampart is implemented in OpenMx, a free and open source software.

SVD-aided pseudo principal-component analysis: A new method to speed up and improve determination of the optimum kinetic model from time-resolved data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oang, Key Young; Yang, Cheolhee; Muniyappan, Srinivasan

Determination of the optimum kinetic model is an essential prerequisite for characterizing dynamics and mechanism of a reaction. Here, we propose a simple method, termed as singular value decomposition-aided pseudo principal-component analysis (SAPPA), to facilitate determination of the optimum kinetic model from time-resolved data by bypassing any need to examine candidate kinetic models. We demonstrate the wide applicability of SAPPA by examining three different sets of experimental time-resolved data and show that SAPPA can efficiently determine the optimum kinetic model. In addition, the results of SAPPA for both time-resolved X-ray solution scattering (TRXSS) and transient absorption (TA) data of themore » same protein reveal that global structural changes of protein, which is probed by TRXSS, may occur more slowly than local structural changes around the chromophore, which is probed by TA spectroscopy.« less

On the fine structure of meteoritical taenite/tetrataenite and its interpretation

NASA Astrophysics Data System (ADS)

Albertsen, J. F.; Nielsen, H. P.; Buchwald, V. F.

1983-04-01

TEM, electron microprobe, and Moessbauer spectroscopy are used in investigating taenite fields from several meteorites. A delicate pattern of antiphase domains is revealed in the tetrataenite, as is the presence of low-Ni taenite at the antiphase boundaries in what was hitherto believed to be pure tetrataenite. The observations suggest that the 'cloudy taenite' (cloudy zone II) was formed by a magnetically induced spinodal decomposition of the metastable taenite during slow cooling below 400 C. It is thought likely that decompositin occurs when the Curie temperature of the alloy changes rapidly with composition, as it does in f.c.c. iron-nickel alloys containing approximately 28-43 percent Ni (wt pct). The large contribution to Gibbs free energy from magnetic ordering leads to inflections in the Gibbs free energy curve, making the alloy unstable with regard to decomposition, in this case into a magnetically and atomically ordered Ni-rich alloy plus a magnetically and atomically disordered Ni-poor alloy. The model accounts well for the structure and composition of the two phases in the cloudy taenite.

Free energy decomposition of protein-protein interactions.

PubMed

Noskov, S Y; Lim, C

2001-08-01

A free energy decomposition scheme has been developed and tested on antibody-antigen and protease-inhibitor binding for which accurate experimental structures were available for both free and bound proteins. Using the x-ray coordinates of the free and bound proteins, the absolute binding free energy was computed assuming additivity of three well-defined, physical processes: desolvation of the x-ray structures, isomerization of the x-ray conformation to a nearby local minimum in the gas-phase, and subsequent noncovalent complex formation in the gas phase. This free energy scheme, together with the Generalized Born model for computing the electrostatic solvation free energy, yielded binding free energies in remarkable agreement with experimental data. Two assumptions commonly used in theoretical treatments; viz., the rigid-binding approximation (which assumes no conformational change upon complexation) and the neglect of vdW interactions, were found to yield large errors in the binding free energy. Protein-protein vdW and electrostatic interactions between complementary surfaces over a relatively large area (1400--1700 A(2)) were found to drive antibody-antigen and protease-inhibitor binding.

Examining drivers of the emissions embodied in trade

PubMed Central

Wu, Leying; Wang, Zheng

2017-01-01

Emissions embodied in provincial trade (EEPT) have important effects on provinces’ responsibilities for carbon emission reductions. Based on a multi-regional input-output model, we calculated EEPT for China’s 30 provinces in 2002, 2007 and 2010, and we attempted to determine the drivers of EEPT. The results showed that, during this period, the ratio of EEPT to production-based emissions increased over time, reaching 40.24% in 2010. In consideration of its important role in carbon emissions, we analyzed the factors attributable to EEPT through structure decomposition analysis. The decomposition results showed that final demand and carbon emission intensity were two major factors in EEPT, while the final demand in other provinces and the carbon emission intensity in the local province were major factors for Emissions embodied in provincial exports and the final demand in the local province and the carbon emission intensity in other provinces were major factors for Emissions embodied in provincial imports. Regarding the differences among the EEPT of different provinces, changes in the structure of trade were the primary reason. PMID:28426769

Effects of endogenous factors on regional land-use carbon emissions based on the Grossman decomposition model: a case study of Zhejiang Province, China.

PubMed

Wu, Cifang; Li, Guan; Yue, Wenze; Lu, Rucheng; Lu, Zhangwei; You, Heyuan

2015-02-01

The impact of land-use change on greenhouse gas emissions has become a core issue in current studies on global change and carbon cycle. However, a comprehensive evaluation of the effects of land-use changes on carbon emissions is very necessary. This paper attempted to apply the Grossman decomposition model to estimate the scale, structural, and management effects of land-use carbon emissions based on final energy consumption by establishing the relationship between the types of land use and carbon emissions in energy consumption. It was shown that land-use carbon emissions increase from 169.5624 million tons in 2000 to 637.0984 million tons in 2010, with an annual average growth rate of 14.15%. Meanwhile, land-use carbon intensity increased from 17.59 t/ha in 2000 to 64.42 t/ha in 2010, with an average annual growth rate of 13.86%. The results indicated that rapid industrialization and urbanization in Zhejiang Province promptly increased urban land and industrial land, which consequently affected land-use extensive emissions. The structural and management effects did not mitigate land-use carbon emissions. By contrast, both factors evidently affected the growth of carbon emissions because of the rigid demands of energy-intensive land-use types and the absence of land management. Results called for the policy implications of optimizing land-use structures and strengthening land-use management.

Effects of Endogenous Factors on Regional Land-Use Carbon Emissions Based on the Grossman Decomposition Model: A Case Study of Zhejiang Province, China

NASA Astrophysics Data System (ADS)

Wu, Cifang; Li, Guan; Yue, Wenze; Lu, Rucheng; Lu, Zhangwei; You, Heyuan

2015-02-01

The impact of land-use change on greenhouse gas emissions has become a core issue in current studies on global change and carbon cycle. However, a comprehensive evaluation of the effects of land-use changes on carbon emissions is very necessary. This paper attempted to apply the Grossman decomposition model to estimate the scale, structural, and management effects of land-use carbon emissions based on final energy consumption by establishing the relationship between the types of land use and carbon emissions in energy consumption. It was shown that land-use carbon emissions increase from 169.5624 million tons in 2000 to 637.0984 million tons in 2010, with an annual average growth rate of 14.15 %. Meanwhile, land-use carbon intensity increased from 17.59 t/ha in 2000 to 64.42 t/ha in 2010, with an average annual growth rate of 13.86 %. The results indicated that rapid industrialization and urbanization in Zhejiang Province promptly increased urban land and industrial land, which consequently affected land-use extensive emissions. The structural and management effects did not mitigate land-use carbon emissions. By contrast, both factors evidently affected the growth of carbon emissions because of the rigid demands of energy-intensive land-use types and the absence of land management. Results called for the policy implications of optimizing land-use structures and strengthening land-use management.

Kinetic analysis of overlapping multistep thermal decomposition comprising exothermic and endothermic processes: thermolysis of ammonium dinitramide.

PubMed

Muravyev, Nikita V; Koga, Nobuyoshi; Meerov, Dmitry B; Pivkina, Alla N

2017-01-25

This study focused on kinetic modeling of a specific type of multistep heterogeneous reaction comprising exothermic and endothermic reaction steps, as exemplified by the practical kinetic analysis of the experimental kinetic curves for the thermal decomposition of molten ammonium dinitramide (ADN). It is known that the thermal decomposition of ADN occurs as a consecutive two step mass-loss process comprising the decomposition of ADN and subsequent evaporation/decomposition of in situ generated ammonium nitrate. These reaction steps provide exothermic and endothermic contributions, respectively, to the overall thermal effect. The overall reaction process was deconvoluted into two reaction steps using simultaneously recorded thermogravimetry and differential scanning calorimetry (TG-DSC) curves by considering the different physical meanings of the kinetic data derived from TG and DSC by P value analysis. The kinetic data thus separated into exothermic and endothermic reaction steps were kinetically characterized using kinetic computation methods including isoconversional method, combined kinetic analysis, and master plot method. The overall kinetic behavior was reproduced as the sum of the kinetic equations for each reaction step considering the contributions to the rate data derived from TG and DSC. During reproduction of the kinetic behavior, the kinetic parameters and contributions of each reaction step were optimized using kinetic deconvolution analysis. As a result, the thermal decomposition of ADN was successfully modeled as partially overlapping exothermic and endothermic reaction steps. The logic of the kinetic modeling was critically examined, and the practical usefulness of phenomenological modeling for the thermal decomposition of ADN was illustrated to demonstrate the validity of the methodology and its applicability to similar complex reaction processes.

Thermal decomposition of gaseous ammonium nitrate at low pressure: kinetic modeling of product formation and heterogeneous decomposition of nitric acid.

PubMed

Park, J; Lin, M C

2009-12-03

The thermal decomposition of ammonium nitrate, NH(4)NO(3) (AN), in the gas phase has been studied at 423-56 K by pyrolysis/mass spectrometry under low-pressure conditions using a Saalfeld reactor coated with boric acid. The sublimation of NH(4)NO(3) at 423 K was proposed to produce equal amounts of NH(3) and HNO(3), followed by the decomposition reaction of HNO(3), HNO(3) + M --> OH + NO(2) + M (where M = third-body and reactor surface). The absolute yields of N(2), N(2)O, H(2)O, and NH(3), which can be unambiguously measured and quantitatively calibrated under a constant pressure at 5-6.2 torr He are kinetically modeled using the detailed [H,N,O]-mechanism established earlier for the simulation of NH(3)-NO(2) (Park, J.; Lin, M. C. Technologies and Combustion for a Clean Environment. Proc. 4th Int. Conf. 1997, 34-1, 1-5) and ADN decomposition reactions (Park, J.; Chakraborty, D.; Lin, M. C. Proc. Combust. Inst. 1998, 27, 2351-2357). Since the homogeneous decomposition reaction of HNO(3) itself was found to be too slow to account for the consumption of reactants and the formation of products, we also introduced the heterogeneous decomposition of HNO(3) in our kinetic modeling. The heterogeneous decomposition rate of HNO(3), HNO(3) + (B(2)O(3)/SiO(2)) --> OH + NO(2) + (B(2)O(3)/SiO(2)), was determined by varying its rate to match the modeled result to the measured concentrations of NH(3) and H(2)O; the rate could be represented by k(2b) = 7.91 x 10(7) exp(-12 600/T) s(-1), which appears to be consistent with those reported by Johnston and co-workers (Johnston, H. S.; Foering, L.; Tao, Y.-S.; Messerly, G. H. J. Am. Chem. Soc. 1951, 73, 2319-2321) for HNO(3) decomposition on glass reactors at higher temperatures. Notably, the concentration profiles of all species measured could be satisfactorily predicted by the existing [H,N,O]-mechanism with the heterogeneous initiation process.

Thermal Decomposition of Gaseous Ammonium Nitrate at Low Pressure: Kinetic Modeling of Product Formation and Heterogeneous Decomposition of Nitric Acid

NASA Astrophysics Data System (ADS)

Park, J.; Lin, M. C.

2009-10-01

The thermal decomposition of ammonium nitrate, NH4NO3 (AN), in the gas phase has been studied at 423-56 K by pyrolysis/mass spectrometry under low-pressure conditions using a Saalfeld reactor coated with boric acid. The sublimation of NH4NO3 at 423 K was proposed to produce equal amounts of NH3 and HNO3, followed by the decomposition reaction of HNO3, HNO3 + M → OH + NO2 + M (where M = third-body and reactor surface). The absolute yields of N2, N2O, H2O, and NH3, which can be unambiguously measured and quantitatively calibrated under a constant pressure at 5-6.2 torr He are kinetically modeled using the detailed [H,N,O]-mechanism established earlier for the simulation of NH3-NO2 (Park, J.; Lin, M. C. Technologies and Combustion for a Clean Environment. Proc. 4th Int. Conf. 1997, 34-1, 1-5) and ADN decomposition reactions (Park, J.; Chakraborty, D.; Lin, M. C. Proc. Combust. Inst. 1998, 27, 2351-2357). Since the homogeneous decomposition reaction of HNO3 itself was found to be too slow to account for the consumption of reactants and the formation of products, we also introduced the heterogeneous decomposition of HNO3 in our kinetic modeling. The heterogeneous decomposition rate of HNO3, HNO3 + (B2O3/SiO2) → OH + NO2 + (B2O3/SiO2), was determined by varying its rate to match the modeled result to the measured concentrations of NH3 and H2O; the rate could be represented by k2b = 7.91 × 107 exp(-12 600/T) s-1, which appears to be consistent with those reported by Johnston and co-workers (Johnston, H. S.; Foering, L.; Tao, Y.-S.; Messerly, G. H. J. Am. Chem. Soc. 1951, 73, 2319-2321) for HNO3 decomposition on glass reactors at higher temperatures. Notably, the concentration profiles of all species measured could be satisfactorily predicted by the existing [H,N,O]-mechanism with the heterogeneous initiation process.

Effects of reactive Mn(III)-oxalate complexes on structurally intact plant cell walls

NASA Astrophysics Data System (ADS)

Summering, J. A.; Keiluweit, M.; Goni, M. A.; Nico, P. S.; Kleber, M.

2011-12-01

Lignin components in the in plant litter are commonly assumed to have longer residence times in soil than many other compounds, which are supposedly, more easily degradable. The supposed resistance of lignin compounds to decomposition is generally attributed to the complex chain of biochemical steps required to create footholds in the non-porous structure of ligno-cellulose in cell walls. Interestingly, Mn(III) complexes have shown the ability to degrade ligno-cellulose. Mn(III) chelated by ligands such as oxalate are soluble oxidizers with a high affinity for lignin structures. Here we determined (i) the formation and decay kinetics of the Mn(III)-oxalate complexes in aqueous solution and (ii) the effects that these complexes have on intact ligno-cellulose. UV/vis spectroscopy and iodometric titrations confirmed the transient nature of Mn(III)-oxalate complexes with decay rates being in the order of hours. Zinnia elegans tracheary elements - a model ligno-cellulose substrate - were treated with Mn(III)-oxalate complexes in a newly developed flow-through reactor. Soluble decomposition products released during the treatment were analyzed by GC/MS and the degree of cell integrity was measured by cell counts, pre- and post-treatment counts indicate a decrease in intact Zinnia elegans as a result of Mn(III)-treatment. GC/MS results showed the release of a multitude of solubilized lignin breakdown products from plant cell walls. We conclude that Mn(III)-oxalate complexes have the ability to lyse intact plant cells and solubilize lignin. Lignin decomposition may thus be seen as resource dependent, with Mn(III) a powerful resource that should be abundant in terrestrial characterized by frequent redox fluctuations.

Structural optimization: Status and promise

NASA Astrophysics Data System (ADS)

Kamat, Manohar P.

Chapters contained in this book include fundamental concepts of optimum design, mathematical programming methods for constrained optimization, function approximations, approximate reanalysis methods, dual mathematical programming methods for constrained optimization, a generalized optimality criteria method, and a tutorial and survey of multicriteria optimization in engineering. Also included are chapters on the compromise decision support problem and the adaptive linear programming algorithm, sensitivity analyses of discrete and distributed systems, the design sensitivity analysis of nonlinear structures, optimization by decomposition, mixed elements in shape sensitivity analysis of structures based on local criteria, and optimization of stiffened cylindrical shells subjected to destabilizing loads. Other chapters are on applications to fixed-wing aircraft and spacecraft, integrated optimum structural and control design, modeling concurrency in the design of composite structures, and tools for structural optimization. (No individual items are abstracted in this volume)

Technical Note: Linking climate change and downed woody debris decomposition across forests of the eastern United States

USGS Publications Warehouse

Russell, Matthew B.; Woodall, Christopher W.; D'Amato, Anthony W.; Fraver, Shawn; Bradford, John B.

2014-01-01

Forest ecosystems play a critical role in mitigating greenhouse gas emissions. Forest carbon (C) is stored through photosynthesis and released via decomposition and combustion. Relative to C fixation in biomass, much less is known about C depletion through decomposition of woody debris, particularly under a changing climate. It is assumed that the increased temperatures and longer growing seasons associated with projected climate change will increase the decomposition rates (i.e., more rapid C cycling) of downed woody debris (DWD); however, the magnitude of this increase has not been previously addressed. Using DWD measurements collected from a national forest inventory of the eastern United States, we show that the residence time of DWD may decrease (i.e., more rapid decomposition) by as much as 13% over the next 200 years, depending on various future climate change scenarios and forest types. Although existing dynamic global vegetation models account for the decomposition process, they typically do not include the effect of a changing climate on DWD decomposition rates. We expect that an increased understanding of decomposition rates, as presented in this current work, will be needed to adequately quantify the fate of woody detritus in future forests. Furthermore, we hope these results will lead to improved models that incorporate climate change scenarios for depicting future dead wood dynamics in addition to a traditional emphasis on live-tree demographics.

Adjusting the catalytic properties of cobalt ferrite nanoparticles by pulsed laser fragmentation in water with defined energy dose.

PubMed

Waag, Friedrich; Gökce, Bilal; Kalapu, Chakrapani; Bendt, Georg; Salamon, Soma; Landers, Joachim; Hagemann, Ulrich; Heidelmann, Markus; Schulz, Stephan; Wende, Heiko; Hartmann, Nils; Behrens, Malte; Barcikowski, Stephan

2017-10-13

Highly active, structurally disordered CoFe 2 O 4 /CoO electrocatalysts are synthesized by pulsed laser fragmentation in liquid (PLFL) of a commercial CoFe 2 O 4 powder dispersed in water. A partial transformation of the CoFe 2 O 4 educt to CoO is observed and proposed to be a thermal decomposition process induced by the picosecond pulsed laser irradiation. The overpotential in the OER in aqueous alkaline media at 10 mA cm -2 is reduced by 23% compared to the educt down to 0.32 V with a Tafel slope of 71 mV dec -1 . Importantly, the catalytic activity is systematically adjustable by the number of PLFL treatment cycles. The occurrence of thermal melting and decomposition during one PLFL cycle is verified by modelling the laser beam energy distribution within the irradiated colloid volume and comparing the by single particles absorbed part to threshold energies. Thermal decomposition leads to a massive reduction in particle size and crystal transformations towards crystalline CoO and amorphous CoFe 2 O 4 . Subsequently, thermal melting forms multi-phase spherical and network-like particles. Additionally, Fe-based layered double hydroxides at higher process cycle repetitions emerge as a byproduct. The results show that PLFL is a promising method that allows modification of the structural order in oxides and thus access to catalytically interesting materials.

Decomposition of terrestrial resource subsidies in headwater streams: Does consumer diversity matter?

Treesearch

David Stoker; Amber J. Falkner; Kelly M. Murray; Ashley K. Lang; Thomas R. Barnum; Jeffrey Hepinstall-Cymerman; Michael J. Conroy; Robert J. Cooper; Catherine M. Pringle

2017-01-01

Resource subsidies and biodiversity are essential for maintaining community structure and ecosystem functioning, but the relative importance of consumer diversity and resource characteristics to decomposition remains unclear. Forested headwater streams are detritus-based systems, dependent on leaf litter inputs from adjacent riparian ecosystems, and...

Lasting effect of soil warming on organic matter decomposition depends on tillage practices

USDA-ARS?s Scientific Manuscript database

Global warming affects various parts of carbon (C) cycle including acceleration of soil organic matter (SOM) decomposition with strong feedback to atmospheric CO2 concentration. Despite many soil warming studies showed changes of microbial community structure, very few were focused on the effect of ...

Analyzing Number Composition and Decomposition Activities in Kindergarten from a Numeracy Perspective

ERIC Educational Resources Information Center

Tsamir, Pessia; Tirosh, Dina; Levenson, Esther; Tabach, Michal; Barkai, Ruthi

2015-01-01

This study explores two number composition and decomposition activities from a numeracy perspective. Both activities have the same mathematical structure but each employs different tools and contexts. Twenty kindergarten children engaged individually with these activities. Verbal utterances as well as actions of the child and interviewer were…

Different Mechanisms of Soil Microbial Response to Global Change Result in Different Outcomes in the MIMICS-CN Model

NASA Astrophysics Data System (ADS)

Kyker-Snowman, E.; Wieder, W. R.; Grandy, S.

2017-12-01

Microbial-explicit models of soil carbon (C) and nitrogen (N) cycling have improved upon simulations of C and N stocks and flows at site-to-global scales relative to traditional first-order linear models. However, the response of microbial-explicit soil models to global change factors depends upon which parameters and processes in a model are altered by those factors. We used the MIcrobial-MIneral Carbon Stabilization Model with coupled N cycling (MIMICS-CN) to compare modeled responses to changes in temperature and plant inputs at two previously-modeled sites (Harvard Forest and Kellogg Biological Station). We spun the model up to equilibrium, applied each perturbation, and evaluated 15 years of post-perturbation C and N pools and fluxes. To model the effect of increasing temperatures, we independently examined the impact of decreasing microbial C use efficiency (CUE), increasing the rate of microbial turnover, and increasing Michaelis-Menten kinetic rates of litter decomposition, plus several combinations of the three. For plant inputs, we ran simulations with stepwise increases in metabolic litter, structural litter, whole litter (structural and metabolic), or labile soil C. The cumulative change in soil C or N varied in both sign and magnitude across simulations. For example, increasing kinetic rates of litter decomposition resulted in net releases of both C and N from soil pools, while decreasing CUE produced short-term increases in respiration but long-term accumulation of C in litter pools and shifts in soil C:N as microbial demand for C increased and biomass declined. Given that soil N cycling constrains the response of plant productivity to global change and that soils generate a large amount of uncertainty in current earth system models, microbial-explicit models are a critical opportunity to advance the modeled representation of soils. However, microbial-explicit models must be improved by experiments to isolate the physiological and stoichiometric parameters of soil microbes that shift under global change.

Quantum secret sharing for a general quantum access structure

NASA Astrophysics Data System (ADS)

Bai, Chen-Ming; Li, Zhi-Hui; Si, Meng-Meng; Li, Yong-Ming

2017-10-01

Quantum secret sharing is a procedure for sharing a secret among a number of participants such that only certain subsets of participants can collaboratively reconstruct it, which are called authorized sets. The quantum access structure of a secret sharing is a family of all authorized sets. Firstly, in this paper, we propose the concept of decomposition of quantum access structure to design a quantum secret sharing scheme. Secondly, based on a maximal quantum access structure (MQAS) [D. Gottesman, Phys. Rev. A 61, 042311 (2000)], we propose an algorithm to improve a MQAS and obtain an improved maximal quantum access structure (IMQAS). Then, we present a sufficient and necessary condition about IMQAS, which shows the relationship between the minimal authorized sets and the players. In accordance with properties, we construct an efficient quantum secret sharing scheme with a decomposition and IMQAS. A major advantage of these techniques is that it allows us to construct a method to realize a general quantum access structure. Finally, we present two kinds of quantum secret sharing schemes via the thought of concatenation or a decomposition of quantum access structure. As a consequence, we find that the application of these techniques allows us to save more quantum shares and reduces more cost than the existing scheme.

Soil organic carbon dynamics across a nitrogen deposition gradient: application of the PnET-SOM model to northeastern forest ecosystems

NASA Astrophysics Data System (ADS)

Tonitto, C.; Goodale, C. L.; Ollinger, S. V.; Jenkins, J.

2009-12-01

Anthropogenic forcing of the C and N cycles has caused rapid change in atmospheric CO2 and N deposition, with complex and uncertain effects on forest C and N balance. We developed the PnET-SOM model to enhance the model description of carbon and nitrogen coupling. Here we applied PnET-SOM to study changes to ecosystem carbon storage across a nitrogen deposition gradient. We designed the PnET-SOM model to: 1) represent SOM structured around measurable SOM pools, 2) expand simulated soil horizon complexity beyond the 1-box approach to hydrology and SOM structure used in PnET-CN, 3) model humified and mineral associated SOM using parameters derived from C14 field studies, and 4) couple C and N cycles to allow N-limitation of decomposition and plant growth. We explicitly modeled labile, biochemically recalcitrant (humified SOM), and physically-chemically protected (mineral associated SOM) C pools. These SOM pools are modeled in distinct soil horizons including: a forest floor, a mixed organic horizon, an A horizon, and a B horizon. Slow turnover pools of the A and B horizon constitute a significant proportion of SOC; explicitly modeling a deeper soil profile is important for estimating ecosystem SOC storage. In the latest version of PnET-SOM, we described N mineralization-immobilization in the forest floor based on equations derived in the LIDET synthesis study. Validation of the PnET-SOM model was conducted using 1) long-term water flux and nitrate leaching data from the Hubbard Brook LTER, 2) CO2 respiration observations from the Harvard Forest LTER, and 3) C and N stock and flux observations from the Harvard Forest LTER. In this work, we applied the PnET-SOM model to study the effects of an N deposition gradient on SOC dynamics over a 300 year simulation. We represented the effects of N deposition on litter decomposition by varying the exponential decay parameters of the litter layer based on observations from the Harvard Forest N addition experiment. We derived the change in limit value across the N deposition gradient simulated by applying a polynomial fit to limit values observed in the Harvard Forest N addition experimental plots. In PnET-SOM, changes in SOC dynamics under varying N deposition rates are derived from 1) change in litter decomposition rate, which directly affects OM inputs into soil pools, and 2) altered N availability which limits decomposition of OM throughout the soil profile. In our model application, the coarse woody debris pool decreased with increasing N deposition, while the forest floor pools increased. Relative to SOC pools under current N deposition rates at the Harvard Forest (8 gN/m2), deposition at a rate of 20 gN/m2 over a 300 year simulation resulted in a 3.4% increase in the O horizon humified SOC pool, a 2.3% increase in the A horizon humified SOC pool, a 1.3% increase in the A horizon mineral associated SOC pool, and a 0.14% increase in the B horizon mineral associated SOC pool.

Nature of catalytic activities of CoO nanocrystals in thermal decomposition of ammonium perchlorate.

PubMed

Li, Liping; Sun, Xuefei; Qiu, Xiaoqing; Xu, Jiaoxing; Li, Guangshe

2008-10-06

This work addresses the chemical nature of the catalytic activity of X-ray "pure" CoO nanocrystals. All samples were prepared by a solvothermal reaction route. X-ray diffraction indicates the formation of CoO in a cubic rock-salt structure, while infrared spectra and magnetic measurements demonstrate the coexistence of CoO and Co 3O 4. Therefore, X-ray "pure" CoO nanocrystals are a unique composite structure with a CoO core surrounded by an extremely thin Co 3O 4 surface layer, which is likely a consequence of the surface passivation of CoO nanocrystals from the air oxidation at room temperature. The CoO core shows a particle size of 22 or 280 nm, depending on the types of the precursors used. This composite nanostructure was initiated as a catalytic additive to promote the thermal decomposition of ammonium perchlorate (AP). Our preliminary investigations indicate that the maximum decomposition temperature of AP is significantly reduced in the presence of CoO/Co 3O 4 composite nanocrystals and that the maximum decomposition peak shifts toward lower temperatures as the loading amount of the composite nanocrystals increases. These findings are different from the literature reports when using many nanoscale oxide additives. Finally, the decomposition heat for the low-temperature decomposition stages of AP was calculated and correlated to the chemical nature of the CoO/Co 3O 4 composite nanostructures.

Parametrization consequences of constraining soil organic matter models by total carbon and radiocarbon using long-term field data

NASA Astrophysics Data System (ADS)

Menichetti, Lorenzo; Kätterer, Thomas; Leifeld, Jens

2016-05-01

Soil organic carbon (SOC) dynamics result from different interacting processes and controls on spatial scales from sub-aggregate to pedon to the whole ecosystem. These complex dynamics are translated into models as abundant degrees of freedom. This high number of not directly measurable variables and, on the other hand, very limited data at disposal result in equifinality and parameter uncertainty. Carbon radioisotope measurements are a proxy for SOC age both at annual to decadal (bomb peak based) and centennial to millennial timescales (radio decay based), and thus can be used in addition to total organic C for constraining SOC models. By considering this additional information, uncertainties in model structure and parameters may be reduced. To test this hypothesis we studied SOC dynamics and their defining kinetic parameters in the Zürich Organic Fertilization Experiment (ZOFE) experiment, a > 60-year-old controlled cropland experiment in Switzerland, by utilizing SOC and SO14C time series. To represent different processes we applied five model structures, all stemming from a simple mother model (Introductory Carbon Balance Model - ICBM): (I) two decomposing pools, (II) an inert pool added, (III) three decomposing pools, (IV) two decomposing pools with a substrate control feedback on decomposition, (V) as IV but with also an inert pool. These structures were extended to explicitly represent total SOC and 14C pools. The use of different model structures allowed us to explore model structural uncertainty and the impact of 14C on kinetic parameters. We considered parameter uncertainty by calibrating in a formal Bayesian framework. By varying the relative importance of total SOC and SO14C data in the calibration, we could quantify the effect of the information from these two data streams on estimated model parameters. The weighing of the two data streams was crucial for determining model outcomes, and we suggest including it in future modeling efforts whenever SO14C data are available. The measurements and all model structures indicated a dramatic decline in SOC in the ZOFE experiment after an initial land use change in 1949 from grass- to cropland, followed by a constant but smaller decline. According to all structures, the three treatments (control, mineral fertilizer, farmyard manure) we considered were still far from equilibrium. The estimates of mean residence time (MRT) of the C pools defined by our models were sensitive to the consideration of the SO14C data stream. Model structure had a smaller effect on estimated MRT, which ranged between 5.9 ± 0.1 and 4.2 ± 0.1 years and 78.9 ± 0.1 and 98.9 ± 0.1 years for young and old pools, respectively, for structures without substrate interactions. The simplest model structure performed the best according to information criteria, validating the idea that we still lack data for mechanistic SOC models. Although we could not exclude any of the considered processes possibly involved in SOC decomposition, it was not possible to discriminate their relative importance.

Estimation of Hydrogen-Exchange Protection Factors from MD Simulation Based on Amide Hydrogen Bonding Analysis.

PubMed

Park, In-Hee; Venable, John D; Steckler, Caitlin; Cellitti, Susan E; Lesley, Scott A; Spraggon, Glen; Brock, Ansgar

2015-09-28

Hydrogen exchange (HX) studies have provided critical insight into our understanding of protein folding, structure, and dynamics. More recently, hydrogen exchange mass spectrometry (HX-MS) has become a widely applicable tool for HX studies. The interpretation of the wealth of data generated by HX-MS experiments as well as other HX methods would greatly benefit from the availability of exchange predictions derived from structures or models for comparison with experiment. Most reported computational HX modeling studies have employed solvent-accessible-surface-area based metrics in attempts to interpret HX data on the basis of structures or models. In this study, a computational HX-MS prediction method based on classification of the amide hydrogen bonding modes mimicking the local unfolding model is demonstrated. Analysis of the NH bonding configurations from molecular dynamics (MD) simulation snapshots is used to determine partitioning over bonded and nonbonded NH states and is directly mapped into a protection factor (PF) using a logistics growth function. Predicted PFs are then used for calculating deuteration values of peptides and compared with experimental data. Hydrogen exchange MS data for fatty acid synthase thioesterase (FAS-TE) collected for a range of pHs and temperatures was used for detailed evaluation of the approach. High correlation between prediction and experiment for observable fragment peptides is observed in the FAS-TE and additional benchmarking systems that included various apo/holo proteins for which literature data were available. In addition, it is shown that HX modeling can improve experimental resolution through decomposition of in-exchange curves into rate classes, which correlate with prediction from MD. Successful rate class decompositions provide further evidence that the presented approach captures the underlying physical processes correctly at the single residue level. This assessment is further strengthened in a comparison of residue resolved protection factor predictions for staphylococcal nuclease with NMR data, which was also used to compare prediction performance with other algorithms described in the literature. The demonstrated transferable and scalable MD based HX prediction approach adds significantly to the available tools for HX-MS data interpretation based on available structures and models.

Estimation of Hydrogen-Exchange Protection Factors from MD Simulation Based on Amide Hydrogen Bonding Analysis

PubMed Central

Park, In-Hee; Venable, John D.; Steckler, Caitlin; Cellitti, Susan E.; Lesley, Scott A.; Spraggon, Glen; Brock, Ansgar

2015-01-01

Hydrogen exchange (HX) studies have provided critical insight into our understanding of protein folding, structure and dynamics. More recently, Hydrogen Exchange Mass Spectrometry (HX-MS) has become a widely applicable tool for HX studies. The interpretation of the wealth of data generated by HX-MS experiments as well as other HX methods would greatly benefit from the availability of exchange predictions derived from structures or models for comparison with experiment. Most reported computational HX modeling studies have employed solvent-accessible-surface-area based metrics in attempts to interpret HX data on the basis of structures or models. In this study, a computational HX-MS prediction method based on classification of the amide hydrogen bonding modes mimicking the local unfolding model is demonstrated. Analysis of the NH bonding configurations from Molecular Dynamics (MD) simulation snapshots is used to determine partitioning over bonded and non-bonded NH states and is directly mapped into a protection factor (PF) using a logistics growth function. Predicted PFs are then used for calculating deuteration values of peptides and compared with experimental data. Hydrogen exchange MS data for Fatty acid synthase thioesterase (FAS-TE) collected for a range of pHs and temperatures was used for detailed evaluation of the approach. High correlation between prediction and experiment for observable fragment peptides is observed in the FAS-TE and additional benchmarking systems that included various apo/holo proteins for which literature data were available. In addition, it is shown that HX modeling can improve experimental resolution through decomposition of in-exchange curves into rate classes, which correlate with prediction from MD. Successful rate class decompositions provide further evidence that the presented approach captures the underlying physical processes correctly at the single residue level. This assessment is further strengthened in a comparison of residue resolved protection factor predictions for staphylococcal nuclease with NMR data, which was also used to compare prediction performance with other algorithms described in the literature. The demonstrated transferable and scalable MD based HX prediction approach adds significantly to the available tools for HX-MS data interpretation based on available structures and models. PMID:26241692

Key Process Uncertainties in Soil Carbon Dynamics: Comparing Multiple Model Structures and Observational Meta-analysis

NASA Astrophysics Data System (ADS)

Sulman, B. N.; Moore, J.; Averill, C.; Abramoff, R. Z.; Bradford, M.; Classen, A. T.; Hartman, M. D.; Kivlin, S. N.; Luo, Y.; Mayes, M. A.; Morrison, E. W.; Riley, W. J.; Salazar, A.; Schimel, J.; Sridhar, B.; Tang, J.; Wang, G.; Wieder, W. R.

2016-12-01

Soil carbon (C) dynamics are crucial to understanding and predicting C cycle responses to global change and soil C modeling is a key tool for understanding these dynamics. While first order model structures have historically dominated this area, a recent proliferation of alternative model structures representing different assumptions about microbial activity and mineral protection is providing new opportunities to explore process uncertainties related to soil C dynamics. We conducted idealized simulations of soil C responses to warming and litter addition using models from five research groups that incorporated different sets of assumptions about processes governing soil C decomposition and stabilization. We conducted a meta-analysis of published warming and C addition experiments for comparison with simulations. Assumptions related to mineral protection and microbial dynamics drove strong differences among models. In response to C additions, some models predicted long-term C accumulation while others predicted transient increases that were counteracted by accelerating decomposition. In experimental manipulations, doubling litter addition did not change soil C stocks in studies spanning as long as two decades. This result agreed with simulations from models with strong microbial growth responses and limited mineral sorption capacity. In observations, warming initially drove soil C loss via increased CO2 production, but in some studies soil C rebounded and increased over decadal time scales. In contrast, all models predicted sustained C losses under warming. The disagreement with experimental results could be explained by physiological or community-level acclimation, or by warming-related changes in plant growth. In addition to the role of microbial activity, assumptions related to mineral sorption and protected C played a key role in driving long-term model responses. In general, simulations were similar in their initial responses to perturbations but diverged over decadal time scales. This suggests that more long-term soil experiments may be necessary to resolve important process uncertainties related to soil C storage. We also suggest future experiments examine how microbial activity responds to warming under a range of soil clay contents and in concert with changes in litter inputs.

A comparative study of serial and parallel aeroelastic computations of wings

NASA Technical Reports Server (NTRS)

Byun, Chansup; Guruswamy, Guru P.

1994-01-01

A procedure for computing the aeroelasticity of wings on parallel multiple-instruction, multiple-data (MIMD) computers is presented. In this procedure, fluids are modeled using Euler equations, and structures are modeled using modal or finite element equations. The procedure is designed in such a way that each discipline can be developed and maintained independently by using a domain decomposition approach. In the present parallel procedure, each computational domain is scalable. A parallel integration scheme is used to compute aeroelastic responses by solving fluid and structural equations concurrently. The computational efficiency issues of parallel integration of both fluid and structural equations are investigated in detail. This approach, which reduces the total computational time by a factor of almost 2, is demonstrated for a typical aeroelastic wing by using various numbers of processors on the Intel iPSC/860.

Using Hybrid Simulation/Analytical Queueing Networks to Capacitate USAF Air Mobility Command Passenger Terminals

DTIC Science & Technology

2012-03-01

Simulation Simulation is a flexible tool for modeling airport operations , which has made the method a staple for airport systems analysts. Animation...be derived to define the character- istics of the airport terminal and describe the nature of the systems [sic] operation ”, which makes discrete...This system decomposition method, however, disregards the effects of network structure on performance measures. Real-life processes do not operate

Mass loss and chemical structures of wheat and maize straws in response to ultraviolet-B radiation and soil contact.

PubMed

Zhou, Guixiang; Zhang, Jiabao; Mao, Jingdong; Zhang, Congzhi; Chen, Lin; Xin, Xiuli; Zhao, Bingzi

2015-10-01

The role of photodegradation, an abiotic process, has been largely overlooked during straw decomposition in mesic ecosystems. We investigated the mass loss and chemical structures of straw decomposition in response to elevated UV-B radiation with or without soil contact over a 12-month litterbag experiment. Wheat and maize straw samples with and without soil contact were exposed to three radiation levels: a no-sunlight control, ambient solar UV-B, and artificially elevated UV-B radiation. A block control with soil contact was not included. Compared with the no-sunlight control, UV-B radiation increased the mass loss by 14-19% and the ambient radiation by 9-16% for wheat and maize straws without soil contact after 12 months. Elevated UV-B exposure decreased the decomposition rates of both wheat and maize straws when in contact with soil. Light exposure resulted in decreased O-alkyl carbons and increased alkyl carbons for both the wheat and maize straws compared with no-sunlight control. The difference in soil contact may influence the contribution of photodegradation to the overall straw decomposition process. These results indicate that we must take into account the effects of photodegradation when explaining the mechanisms of straw decomposition in mesic ecosystems.

Mass loss and chemical structures of wheat and maize straws in response to ultraviolet-B radiation and soil contact

PubMed Central

Zhou, Guixiang; Zhang, Jiabao; Mao, Jingdong; Zhang, Congzhi; Chen, Lin; Xin, Xiuli; Zhao, Bingzi

2015-01-01

The role of photodegradation, an abiotic process, has been largely overlooked during straw decomposition in mesic ecosystems. We investigated the mass loss and chemical structures of straw decomposition in response to elevated UV-B radiation with or without soil contact over a 12-month litterbag experiment. Wheat and maize straw samples with and without soil contact were exposed to three radiation levels: a no-sunlight control, ambient solar UV-B, and artificially elevated UV-B radiation. A block control with soil contact was not included. Compared with the no-sunlight control, UV-B radiation increased the mass loss by 14–19% and the ambient radiation by 9–16% for wheat and maize straws without soil contact after 12 months. Elevated UV-B exposure decreased the decomposition rates of both wheat and maize straws when in contact with soil. Light exposure resulted in decreased O-alkyl carbons and increased alkyl carbons for both the wheat and maize straws compared with no-sunlight control. The difference in soil contact may influence the contribution of photodegradation to the overall straw decomposition process. These results indicate that we must take into account the effects of photodegradation when explaining the mechanisms of straw decomposition in mesic ecosystems. PMID:26423726

The Standard Model Algebra - a summary

NASA Astrophysics Data System (ADS)

Cristinel Stoica, Ovidiu

2017-08-01

A generation of leptons and quarks and the gauge symmetries of the Standard Model can be obtained from the Clifford algebra ℂℓ 6. An instance of ℂℓ 6 is implicitly generated by the Dirac algebra combined with the electroweak symmetry, while the color symmetry gives another instance of ℂℓ 6 with a Witt decomposition. The minimal mathematical model proposed here results by identifying the two instances of ℂℓ 6. The left ideal decomposition generated by the Witt decomposition represents the leptons and quarks, and their antiparticles. The SU(3)c and U(1)em symmetries of the SM are the symmetries of this ideal decomposition. The patterns of electric charges, colors, chirality, weak isospins, and hypercharges, follow from this, without predicting additional particles or forces, or proton decay. The electroweak symmetry is present in its broken form, due to the geometry. The predicted Weinberg angle is given by sin2 W = 0.25. The model shares common features with previously known models, particularly with Chisholm and Farwell, 1996, Trayling and Baylis, 2004, and Furey, 2016.

Carbon cluster formation during thermal decomposition of octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine and 1,3,5-triamino-2,4,6-trinitrobenzene high explosives from ReaxFF reactive molecular dynamics simulations.

PubMed

Zhang, Luzheng; Zybin, Sergey V; van Duin, Adri C T; Dasgupta, Siddharth; Goddard, William A; Kober, Edward M

2009-10-08

We report molecular dynamics (MD) simulations using the first-principles-based ReaxFF reactive force field to study the thermal decomposition of 1,3,5-triamino-2,4,6-trinitrobenzene (TATB) and octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine (HMX) at various densities and temperatures. TATB is known to produce a large amount (15-30%) of high-molecular-weight carbon clusters, whereas detonation of nitramines such as HMX and RDX (1,3,5-trinitroperhydro-1,3,5-triazine) generate predominantly low-molecular-weight products. In agreement with experimental observation, these simulations predict that TATB decomposition quickly (by 30 ps) initiates the formation of large carbonaceous clusters (more than 4000 amu, or approximately 15-30% of the total system mass), and HMX decomposition leads almost exclusively to small-molecule products. We find that HMX decomposes readily on this time scale at lower temperatures, for which the decomposition rate of TATB is about an order of magnitude slower. Analyzing the ReaxFF MD results leads to the detailed atomistic structure of this carbon-rich phase of TATB and allows characterization of the kinetics and chemistry related to this phase and their dependence on system density and temperature. The carbon-rich phase formed from TATB contains mainly polyaromatic rings with large oxygen content, leading to graphitic regions. We use these results to describe the initial reaction steps of thermal decomposition of HMX and TATB in terms of the rates for forming primary and secondary products, allowing comparison to experimentally derived models. These studies show that MD using the ReaxFF reactive force field provides detailed atomistic information that explains such macroscopic observations as the dramatic difference in carbon cluster formation between TATB and HMX. This shows that ReaxFF MD captures the fundamental differences in the mechanisms of such systems and illustrates how the ReaxFF may be applied to model complex chemical phenomena in energetic materials. The studies here illustrate this for modestly sized systems and modest periods; however, ReaxFF calculations of reactive processes have already been reported on systems with approximately 10(6) atoms. Thus, with suitable computational facilities, one can study the atomistic level chemical processes in complex systems under extreme conditions.

Biomass is the main driver of changes in ecosystem process rates during tropical forest succession.

PubMed

Lohbeck, Madelon; Poorter, Lourens; Martínez-Ramos, Miguel; Bongers, Frans

2015-05-01

Over half of the world's forests are disturbed, and the rate at which ecosystem processes recover after disturbance is important for the services these forests can provide. We analyze the drivers' underlying changes in rates of key ecosystem processes (biomass productivity, litter productivity, actual litter decomposition, and potential litter decomposition) during secondary succession after shifting cultivation in wet tropical forest of Mexico. We test the importance of three alternative drivers of ecosystem processes: vegetation biomass (vegetation quantity hypothesis), community-weighted trait mean (mass ratio hypothesis), and functional diversity (niche complementarity hypothesis) using structural equation modeling. This allows us to infer the relative importance of different mechanisms underlying ecosystem process recovery. Ecosystem process rates changed during succession, and the strongest driver was aboveground biomass for each of the processes. Productivity of aboveground stem biomass and leaf litter as well as actual litter decomposition increased with initial standing vegetation biomass, whereas potential litter decomposition decreased with standing biomass. Additionally, biomass productivity was positively affected by community-weighted mean of specific leaf area, and potential decomposition was positively affected by functional divergence, and negatively by community-weighted mean of leaf dry matter content. Our empirical results show that functional diversity and community-weighted means are of secondary importance for explaining changes in ecosystem process rates during tropical forest succession. Instead, simply, the amount of vegetation in a site is the major driver of changes, perhaps because there is a steep biomass buildup during succession that overrides more subtle effects of community functional properties on ecosystem processes. We recommend future studies in the field of biodiversity and ecosystem functioning to separate the effects of vegetation quality (community-weighted mean trait values and functional diversity) from those of vegetation quantity (biomass) on ecosystem processes and services.

A two-agent model applied to the biological control of the sugarcane borer (Diatraea saccharalis) by the egg parasitoid Trichogramma galloi and the larvae parasitoid Cotesia flavipes.

PubMed

Molnár, Sándor; López, Inmaculada; Gámez, Manuel; Garay, József

2016-03-01

The paper is aimed at a methodological development in biological pest control. The considered one pest two-agent system is modelled as a verticum-type system. Originally, linear verticum-type systems were introduced by one of the authors for modelling certain industrial systems. These systems are hierarchically composed of linear subsystems such that a part of the state variables of each subsystem affect the dynamics of the next subsystem. Recently, verticum-type system models have been applied to population ecology as well, which required the extension of the concept a verticum-type system to the nonlinear case. In the present paper the general concepts and technics of nonlinear verticum-type control systems are used to obtain biological control strategies in a two-agent system. For the illustration of this verticum-type control, these tools of mathematical systems theory are applied to a dynamic model of interactions between the egg and larvae populations of the sugarcane borer (Diatraea saccharalis) and its parasitoids: the egg parasitoid Trichogramma galloi and the larvae parasitoid Cotesia flavipes. In this application a key role is played by the concept of controllability, which means that it is possible to steer the system to an equilibrium in given time. In addition to a usual linearization, the basic idea is a decomposition of the control of the whole system into the control of the subsystems, making use of the verticum structure of the population system. The main aim of this study is to show several advantages of the verticum (or decomposition) approach over the classical control theoretical model (without decomposition). For example, in the case of verticum control the pest larval density decreases below the critical threshold value much quicker than without decomposition. Furthermore, it is also shown that the verticum approach may be better even in terms of cost effectiveness. The presented optimal control methodology also turned out to be an efficient tool for the "in silico" analysis of the cost-effectiveness of different biocontrol strategies, e.g. by answering the question how far it is cost-effective to speed up the reduction of the pest larvae density, or along which trajectory this reduction should be carried out. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

On the use of the singular value decomposition for text retrieval

DOE Office of Scientific and Technical Information (OSTI.GOV)

Husbands, P.; Simon, H.D.; Ding, C.

2000-12-04

The use of the Singular Value Decomposition (SVD) has been proposed for text retrieval in several recent works. This technique uses the SVD to project very high dimensional document and query vectors into a low dimensional space. In this new space it is hoped that the underlying structure of the collection is revealed thus enhancing retrieval performance. Theoretical results have provided some evidence for this claim and to some extent experiments have confirmed this. However, these studies have mostly used small test collections and simplified document models. In this work we investigate the use of the SVD on large documentmore » collections. We show that, if interpreted as a mechanism for representing the terms of the collection, this technique alone is insufficient for dealing with the variability in term occurrence. Section 2 introduces the text retrieval concepts necessary for our work. A short description of our experimental architecture is presented in Section 3. Section 4 describes how term occurrence variability affects the SVD and then shows how the decomposition influences retrieval performance. A possible way of improving SVD-based techniques is presented in Section 5 and concluded in Section 6.« less

Reconstruction of Complex Network based on the Noise via QR Decomposition and Compressed Sensing.

PubMed

Li, Lixiang; Xu, Dafei; Peng, Haipeng; Kurths, Jürgen; Yang, Yixian

2017-11-08

It is generally known that the states of network nodes are stable and have strong correlations in a linear network system. We find that without the control input, the method of compressed sensing can not succeed in reconstructing complex networks in which the states of nodes are generated through the linear network system. However, noise can drive the dynamics between nodes to break the stability of the system state. Therefore, a new method integrating QR decomposition and compressed sensing is proposed to solve the reconstruction problem of complex networks under the assistance of the input noise. The state matrix of the system is decomposed by QR decomposition. We construct the measurement matrix with the aid of Gaussian noise so that the sparse input matrix can be reconstructed by compressed sensing. We also discover that noise can build a bridge between the dynamics and the topological structure. Experiments are presented to show that the proposed method is more accurate and more efficient to reconstruct four model networks and six real networks by the comparisons between the proposed method and only compressed sensing. In addition, the proposed method can reconstruct not only the sparse complex networks, but also the dense complex networks.

Application of vacuum stability test to determine thermal decomposition kinetics of nitramines bonded by polyurethane matrix

NASA Astrophysics Data System (ADS)

Elbeih, Ahmed; Abd-Elghany, Mohamed; Elshenawy, Tamer

2017-03-01

Vacuum stability test (VST) is mainly used to study compatibility and stability of energetic materials. In this work, VST has been investigated to study thermal decomposition kinetics of four cyclic nitramines, 1,3,5-trinitro-1,3,5-triazinane (RDX) and 1,3,5,7-tetranitro-1,3,5,7-tetrazocane (HMX), cis-1,3,4,6-tetranitrooctahydroimidazo-[4,5-d]imidazole (BCHMX), 2,4,6,8,10,12-hexanitro-2,4,6,8,10,12-hexaazaisowurtzitane (ε-HNIW, CL-20), bonded by polyurethane matrix based on hydroxyl terminated polybutadiene (HTPB). Model fitting and model free (isoconversional) methods have been applied to determine the decomposition kinetics from VST results. For comparison, the decomposition kinetics were determined isothermally by ignition delay technique and non-isothermally by Advanced Kinetics and Technology Solution (AKTS) software. The activation energies for thermolysis obtained by isoconversional method based on VST technique of RDX/HTPB, HMX/HTPB, BCHMX/HTPB and CL20/HTPB were 157.1, 203.1, 190.0 and 176.8 kJ mol-1 respectively. Model fitting method proved that the mechanism of thermal decomposition of BCHMX/HTPB is controlled by the nucleation model while all the other studied PBXs are controlled by the diffusion models. A linear relationship between the ignition temperatures and the activation energies was observed. BCHMX/HTPB is interesting new PBX in the research stage.

Modeling the hysteretic moisture and temperature responses of soil carbon decomposition resulting from organo-mineral interactions

NASA Astrophysics Data System (ADS)

Tang, J.; Riley, W. J.

2017-12-01

Most existing soil carbon cycle models have modeled the moisture and temperature dependence of soil respiration using deterministic response functions. However, empirical data suggest abundant variability in both of these dependencies. We here use the recently developed SUPECA (Synthesizing Unit and Equilibrium Chemistry Approximation) theory and a published dynamic energy budget based microbial model to investigate how soil carbon decomposition responds to changes in soil moisture and temperature under the influence of organo-mineral interactions. We found that both the temperature and moisture responses are hysteretic and cannot be represented by deterministic functions. We then evaluate how the multi-scale variability in temperature and moisture forcing affect soil carbon decomposition. Our results indicate that when the model is run in scenarios mimicking laboratory incubation experiments, the often-observed temperature and moisture response functions can be well reproduced. However, when such response functions are used for model extrapolation involving more transient variability in temperature and moisture forcing (as found in real ecosystems), the dynamic model that explicitly accounts for hysteresis in temperature and moisture dependency produces significantly different estimations of soil carbon decomposition, suggesting there are large biases in models that do not resolve such hysteresis. We call for more studies on organo-mineral interactions to improve modeling of such hysteresis.

Approximate analytical solutions in the analysis of elastic structures of complex geometry

NASA Astrophysics Data System (ADS)

Goloskokov, Dmitriy P.; Matrosov, Alexander V.

2018-05-01

A method of analytical decomposition for analysis plane structures of a complex configuration is presented. For each part of the structure in the form of a rectangle all the components of the stress-strain state are constructed by the superposition method. The method is based on two solutions derived in the form of trigonometric series with unknown coefficients using the method of initial functions. The coefficients are determined from the system of linear algebraic equations obtained while satisfying the boundary conditions and the conditions for joining the structure parts. The components of the stress-strain state of a bent plate with holes are calculated using the analytical decomposition method.

Resolving Some Paradoxes in the Thermal Decomposition Mechanism of Acetaldehyde

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sivaramakrishnan, Raghu; Michael, Joe V.; Harding, Lawrence B.

2015-07-16

The mechanism for the thermal decomposition of acetaldehyde has been revisited with an analysis of literature kinetics experiments using theoretical kinetics. The present modeling study was motivated by recent observations, with very sensitive diagnostics, of some unexpected products in high temperature micro-tubular reactor experiments on the thermal decomposition of CH3CHO and its deuterated analogs, CH3CDO, CD3CHO, and CD3CDO. The observations of these products prompted the authors of these studies to suggest that the enol tautomer, CH2CHOH (vinyl alcohol), is a primary intermediate in the thermal decomposition of acetaldehyde. The present modeling efforts on acetaldehyde decomposition incorporate a master equation re-analysismore » of the CH3CHO potential energy surface (PES). The lowest energy process on this PES is an isomerization of CH3CHO to CH2CHOH. However, the subsequent product channels for CH2CHOH are substantially higher in energy, and the only unimolecular process that can be thermally accessed is a re-isomerization to CH3CHO. The incorporation of these new theoretical kinetics predictions into models for selected literature experiments on CH3CHO thermal decomposition confirms our earlier experiment and theory based conclusions that the dominant decomposition process in CH3CHO at high temperatures is C-C bond fission with a minor contribution (~10-20%) from the roaming mechanism to form CH4 and CO. The present modeling efforts also incorporate a master-equation analysis of the H + CH2CHOH potential energy surface. This bimolecular reaction is the primary mechanism for removal of CH2CHOH, which can accumulate to minor amounts at high temperatures, T > 1000 K, in most lab-scale experiments that use large initial concentrations of CH3CHO. Our modeling efforts indicate that the observation of ketene, water and acetylene in the recent micro-tubular experiments are primarily due to bimolecular reactions of CH3CHO and CH2CHOH with H-atoms, and have no bearing on the unimolecular decomposition mechanism of CH3CHO. The present simulations also indicate that experiments using these micro-tubular reactors when interpreted with the aid of high-level theoretical calculations and kinetics modeling can offer insights into the chemistry of elusive intermediates in high temperature pyrolysis of organic molecules.« less

Generalized first-order kinetic model for biosolids decomposition and oxidation during hydrothermal treatment.

PubMed

Shanableh, A

2005-01-01

The main objective of this study was to develop generalized first-order kinetic models to represent hydrothermal decomposition and oxidation of biosolids within a wide range of temperatures (200-450 degrees C). A lumping approach was used in which oxidation of the various organic ingredients was characterized by the chemical oxygen demand (COD), and decomposition was characterized by the particulate (i.e., nonfilterable) chemical oxygen demand (PCOD). Using the Arrhenius equation (k = k(o)e(-Ea/RT)), activation energy (Ea) levels were derived from 42 continuous-flow hydrothermal treatment experiments conducted at temperatures in the range of 200-450 degrees C. Using predetermined values for k(o) in the Arrhenius equation, the activation energies of the various organic ingredients were separated into 42 values for oxidation and a similar number for decomposition. The activation energy values were then classified into levels representing the relative ease at which the organic ingredients of the biosolids were oxidized or decomposed. The resulting simple first-order kinetic models adequately represented, within the experimental data range, hydrothermal decomposition of the organic particles as measured by PCOD and oxidation of the organic content as measured by COD. The modeling approach presented in the paper provide a simple and general framework suitable for assessing the relative reaction rates of the various organic ingredients of biosolids.

Structured grid technology to enable flow simulation in an integrated system environment

NASA Astrophysics Data System (ADS)

Remotigue, Michael Gerard

An application-driven Computational Fluid Dynamics (CFD) environment needs flexible and general tools to effectively solve complex problems in a timely manner. In addition, reusable, portable, and maintainable specialized libraries will aid in rapidly developing integrated systems or procedures. The presented structured grid technology enables the flow simulation for complex geometries by addressing grid generation, grid decomposition/solver setup, solution, and interpretation. Grid generation is accomplished with the graphical, arbitrarily-connected, multi-block structured grid generation software system (GUM-B) developed and presented here. GUM-B is an integrated system comprised of specialized libraries for the graphical user interface and graphical display coupled with a solid-modeling data structure that utilizes a structured grid generation library and a geometric library based on Non-Uniform Rational B-Splines (NURBS). A presented modification of the solid-modeling data structure provides the capability for arbitrarily-connected regions between the grid blocks. The presented grid generation library provides algorithms that are reliable and accurate. GUM-B has been utilized to generate numerous structured grids for complex geometries in hydrodynamics, propulsors, and aerodynamics. The versatility of the libraries that compose GUM-B is also displayed in a prototype to automatically regenerate a grid for a free-surface solution. Grid decomposition and solver setup is accomplished with the graphical grid manipulation and repartition software system (GUMBO) developed and presented here. GUMBO is an integrated system comprised of specialized libraries for the graphical user interface and graphical display coupled with a structured grid-tools library. The described functions within the grid-tools library reduce the possibility of human error during decomposition and setup for the numerical solver by accounting for boundary conditions and connectivity. GUMBO is linked with a flow solver interface, to the parallel UNCLE code, to provide load balancing tools and solver setup. Weeks of boundary condition and connectivity specification and validation has been reduced to hours. The UNCLE flow solver is utilized for the solution of the flow field. To accelerate convergence toward a quick engineering answer, a full multigrid (FMG) approach coupled with UNCLE, which is a full approximation scheme (FAS), is presented. The prolongation operators used in the FMG-FAS method are compared. The procedure is demonstrated on a marine propeller in incompressible flow. Interpretation of the solution is accomplished by vortex feature detection. Regions of "Intrinsic Swirl" are located by interrogating the velocity gradient tensor for complex eigenvalues. The "Intrinsic Swirl" parameter is visualized on a solution of a marine propeller to determine if any vortical features are captured. The libraries and the structured grid technology presented herein are flexible and general enough to tackle a variety of complex applications. This technology has significantly enabled the capability of the ERC personnel to effectively calculate solutions for complex geometries.

Comparison of hybrid spectral-decomposition artificial neural network models for understanding climatic forcing of groundwater levels

NASA Astrophysics Data System (ADS)

Abrokwah, K.; O'Reilly, A. M.

2017-12-01

Groundwater is an important resource that is extracted every day because of its invaluable use for domestic, industrial and agricultural purposes. The need for sustaining groundwater resources is clearly indicated by declining water levels and has led to modeling and forecasting accurate groundwater levels. In this study, spectral decomposition of climatic forcing time series was used to develop hybrid wavelet analysis (WA) and moving window average (MWA) artificial neural network (ANN) models. These techniques are explored by modeling historical groundwater levels in order to provide understanding of potential causes of the observed groundwater-level fluctuations. Selection of the appropriate decomposition level for WA and window size for MWA helps in understanding the important time scales of climatic forcing, such as rainfall, that influence water levels. Discrete wavelet transform (DWT) is used to decompose the input time-series data into various levels of approximate and details wavelet coefficients, whilst MWA acts as a low-pass signal-filtering technique for removing high-frequency signals from the input data. The variables used to develop and validate the models were daily average rainfall measurements from five National Atmospheric and Oceanic Administration (NOAA) weather stations and daily water-level measurements from two wells recorded from 1978 to 2008 in central Florida, USA. Using different decomposition levels and different window sizes, several WA-ANN and MWA-ANN models for simulating the water levels were created and their relative performances compared against each other. The WA-ANN models performed better than the corresponding MWA-ANN models; also higher decomposition levels of the input signal by the DWT gave the best results. The results obtained show the applicability and feasibility of hybrid WA-ANN and MWA-ANN models for simulating daily water levels using only climatic forcing time series as model inputs.

A quantum chemical study of the decomposition of Keggin-structured heteropolyacids.

PubMed

Janik, Michael J; Bardin, Billy B; Davis, Robert J; Neurock, Matthew

2006-03-09

Heterpolyacids (HPAs) demonstrate catalytic activity for oxidative and acid-catalyzed hydrocarbon conversion processes. Deactivation and thermal instability, however, have prevented their widespread use. Herein, ab initio density functional theory is used to study the thermal decomposition of the Keggin molecular HPA structure through the desorption of constitutional water molecules. The overall reaction energy and activation barrier are computed for the overall reaction HnXM12O40-->Hn-2XM12O39+H2O. and subsequently used to predict the effect of HPA composition on thermal stability. For example, the desorption of a constitutional water molecule is found to be increasingly endothermic in the order silicomolybdic acid (H4SiMo12O40)

Ambient Vibration Testing for Story Stiffness Estimation of a Heritage Timber Building

PubMed Central

Min, Kyung-Won; Kim, Junhee; Park, Sung-Ah; Park, Chan-Soo

2013-01-01

This paper investigates dynamic characteristics of a historic wooden structure by ambient vibration testing, presenting a novel estimation methodology of story stiffness for the purpose of vibration-based structural health monitoring. As for the ambient vibration testing, measured structural responses are analyzed by two output-only system identification methods (i.e., frequency domain decomposition and stochastic subspace identification) to estimate modal parameters. The proposed methodology of story stiffness is estimation based on an eigenvalue problem derived from a vibratory rigid body model. Using the identified natural frequencies, the eigenvalue problem is efficiently solved and uniquely yields story stiffness. It is noteworthy that application of the proposed methodology is not necessarily confined to the wooden structure exampled in the paper. PMID:24227999

NASREN: Standard reference model for telerobot control

NASA Technical Reports Server (NTRS)

Albus, J. S.; Lumia, R.; Mccain, H.

1987-01-01

A hierarchical architecture is described which supports space station telerobots in a variety of modes. The system is divided into three hierarchies: task decomposition, world model, and sensory processing. Goals at each level of the task dedomposition heirarchy are divided both spatially and temporally into simpler commands for the next lower level. This decomposition is repreated until, at the lowest level, the drive signals to the robot actuators are generated. To accomplish its goals, task decomposition modules must often use information stored it the world model. The purpose of the sensory system is to update the world model as rapidly as possible to keep the model in registration with the physical world. The architecture of the entire control system hierarch is described and how it can be applied to space telerobot applications.

Modeling in-situ pine root decomposition using data from a 60-year chronosequence

Treesearch

Kim H. Ludovici; Stanley J. Zarnoch; Daniel D. Richter

2002-01-01

Because the root system of a mature pine tree typically accounts for 20-30% of the total tree biomass, decomposition of large lateral roots and taproots following forest harvest and re-establishment potentially impact nutrient supply and carbon sequestration in pine systems over several decades. If the relationship between stump diameter and decomposition of...

Biophysical controls on surface fuel litterfall and decomposition in the northern Rocky Mountains, USA

Treesearch

Robert E. Keane

2008-01-01

Litterfall and decomposition rates of the organic matter that comprise forest fuels are important to fire management, because they define fuel treatment longevity and provide parameters to design, test, and validate ecosystem models. This study explores the environmental factors that control litterfall and decomposition in the context of fuel management for several...

Reduced substrate supply limits the temperature response of soil organic carbon decomposition

Treesearch

Cinzia Fissore; Christian P. Giardina; Randall K. Kolka

2013-01-01

Controls on the decomposition rate of soil organic carbon (SOC), especially the more stable fraction of SOC, remain poorly understood, with implications for confidence in efforts to model terrestrial C balance under future climate. We investigated the role of substrate supply in the temperature sensitivity of SOC decomposition in laboratory incubations of coarse-...

The effects of substrate supply on the temperature sensitivity of soil carbon decomposition

Treesearch

Cinzia Fissore; Christian P. Giardina; Randall K. Kolka

2013-01-01

Controls on the decomposition rate of soil organic carbon (SOC), especially the more stable fraction of SOC, remain poorly understood, with implications for confidence in efforts to model terrestrial C balance under future climate. We investigated the role of substrate supply in the temperature sensitivity of SOC decomposition in laboratory incubations of coarse-...

Species associations overwhelm abiotic conditions to dictate the structure and function of wood-decay fungal communities.

PubMed

Maynard, Daniel S; Covey, Kristofer R; Crowther, Thomas W; Sokol, Noah W; Morrison, Eric W; Frey, Serita D; van Diepen, Linda T A; Bradford, Mark A

2018-04-01

Environmental conditions exert strong controls on the activity of saprotrophic microbes, yet abiotic factors often fail to adequately predict wood decomposition rates across broad spatial scales. Given that species interactions can have significant positive and negative effects on wood-decay fungal activity, one possibility is that biotic processes serve as the primary controls on community function, with abiotic controls emerging only after species associations are accounted for. Here we explore this hypothesis in a factorial field warming- and nitrogen-addition experiment by examining relationships among wood decomposition rates, fungal activity, and fungal community structure. We show that functional outcomes and community structure are largely unrelated to abiotic conditions, with microsite and plot-level abiotic variables explaining at most 19% of the total variability in decomposition and fungal activity, and 2% of the variability in richness and evenness. In contrast, taxonomic richness, evenness, and species associations (i.e., co-occurrence patterns) exhibited strong relationships with community function, accounting for 52% of the variation in decomposition rates and 73% in fungal activity. A greater proportion of positive vs. negative species associations in a community was linked to strong declines in decomposition rates and richness. Evenness emerged as a key mediator between richness and function, with highly even communities exhibiting a positive richness-function relationship and uneven communities exhibiting a negative or null response. These results suggest that community-assembly processes and species interactions are important controls on the function of wood-decay fungal communities, ultimately overwhelming substantial differences in abiotic conditions. © 2018 by the Ecological Society of America.

Influence of high-pressure torsion on formation/destruction of nano-sized spinodal structures

NASA Astrophysics Data System (ADS)

Alhamidi, Ali; Edalati, Kaveh; Horita, Zenji

2018-04-01

The microstructures and hardness of Al - 30 mol.% Zn are investigated after processing by high-pressure torsion (HPT) for different numbers of revolutions, N = 1, 3, 10 or 25, as well as after post-HPT annealing at different temperatures, T = 373 K, 473 K, 573 K and 673 K. It was found that a work softening occurs by decreasing the grain size to the submicrometer level and increasing the fraction of high-angle boundaries. As a result of HPT processing, a complete decomposition of supersaturated solid solution of Zn in Al occurs and the spinodal structure is destroyed. This suggests that softening of the Al-Zn alloys after HPT is due to the decomposition of the supersaturated solid solution and destruction of spinodal decomposition. After post-HPT annealing, ultrafine-grained Al-Zn alloys show an unusual mechanical properties and its hardness increased to 187 HV. Microstructural analysis showed that the high hardness after post-HPT annealing is due to the formation of spinodal structures.

Patched bimetallic surfaces are active catalysts for ammonia decomposition

DOE Office of Scientific and Technical Information (OSTI.GOV)

Guo, Wei; Vlachos, Dionisios G.

In this study, ammonia decomposition is often used as an archetypical reaction for predicting new catalytic materials and understanding the very reason of why some reactions are sensitive on material’s structure. Core–shell or surface-segregated bimetallic nanoparticles expose outstanding activity for many heterogeneously catalysed reactions but the reasons remain elusive owing to the difficulties in experimentally characterizing active sites. Here by performing multiscale simulations in ammonia decomposition on various nickel loadings on platinum (111), we show that the very high activity of core–shell structures requires patches of the guest metal to create and sustain dual active sites: nickel terraces catalyse N-Hmore » bond breaking and nickel edge sites drive atomic nitrogen association. The structure sensitivity on these active catalysts depends profoundly on reaction conditions due to kinetically competing relevant elementary reaction steps. We expose a remarkable difference in active sites between transient and steady-state studies and provide insights into optimal material design.« less

Patched bimetallic surfaces are active catalysts for ammonia decomposition

DOE PAGES

Guo, Wei; Vlachos, Dionisios G.

2015-10-07

In this study, ammonia decomposition is often used as an archetypical reaction for predicting new catalytic materials and understanding the very reason of why some reactions are sensitive on material’s structure. Core–shell or surface-segregated bimetallic nanoparticles expose outstanding activity for many heterogeneously catalysed reactions but the reasons remain elusive owing to the difficulties in experimentally characterizing active sites. Here by performing multiscale simulations in ammonia decomposition on various nickel loadings on platinum (111), we show that the very high activity of core–shell structures requires patches of the guest metal to create and sustain dual active sites: nickel terraces catalyse N-Hmore » bond breaking and nickel edge sites drive atomic nitrogen association. The structure sensitivity on these active catalysts depends profoundly on reaction conditions due to kinetically competing relevant elementary reaction steps. We expose a remarkable difference in active sites between transient and steady-state studies and provide insights into optimal material design.« less

Synthesis and characterization of an energetic compound Cu(Mtta)2(NO3)2 and effect on thermal decomposition of ammonium perchlorate.

PubMed

Yang, Qi; Chen, Sanping; Xie, Gang; Gao, Shengli

2011-12-15

An energetic coordination compound Cu(Mtta)(2)(NO(3))(2) has been synthesized by using 1-methyltetrazole (Mtta) as ligand and its structure has been characterized by X-ray single crystal diffraction. The central copper (II) cation was coordinated by four O atoms from two Mtta ligands and two N atoms from two NO(3)(-) anions to form a six-coordinated and distorted octahedral structure. 2D superamolecular layer structure was formed by the extensive intermolecular hydrogen bonds between Mtta ligands and NO(3)(-) anions. Thermal decomposition process of the compound was predicted based on DSC and TG-DTG analyses results. The kinetic parameters of the first exothermic process of the compound were studied by the Kissinger's and Ozawa-Doyle's methods. Sensitivity tests revealed that the compound was insensitive to mechanical stimuli. In addition, compound was explored as additive to promote the thermal decomposition of ammonium perchlorate (AP) by differential scanning calorimetry. Copyright © 2011 Elsevier B.V. All rights reserved.

Modeling Coherent Structures in Canopy Flows

NASA Astrophysics Data System (ADS)

Luhar, Mitul

2017-11-01

It is well known that flows over vegetation canopies are characterized by the presence of energetic coherent structures. Since the mean profile over dense canopies exhibits an inflection point, the emergence of such structures is often attributed to a Kelvin-Helmholtz instability. However, though stability analyses provide useful mechanistic insights into canopy flows, they are limited in their ability to generate predictions for spectra and coherent structure. The present effort seeks to address this limitation by extending the resolvent formulation (McKeon and Sharma, 2010, J. Fluid Mech.) to canopy flows. Under the resolvent formulation, the turbulent velocity field is expressed as a superposition of propagating modes, identified via a gain-based (singular value) decomposition of the Navier-Stokes equations. A key advantage of this approach is that it reconciles multiple mechanisms that lead to high amplification in turbulent flows, including modal instability, transient growth, and critical-layer phenomena. Further, individual high-gain modes can be combined to generate more complete models for coherent structure and velocity spectra. Preliminary resolvent-based model predictions for canopy flows agree well with existing experiments and simulations.

The Utility of Decomposition and Associated Microbial Parameters to Assess Changes in Stream Ecosystems due to Eutrophication

NASA Astrophysics Data System (ADS)

Gulis, V.; Ferreira, V. J.; Graca, M. A.

2005-05-01

Traditional approaches to assess stream ecosystem health rely on structural parameters, e.g. a variety of biotic indices. The goal of the Europe-wide RivFunction project is to develop methodology that uses functional parameters (e.g. plant litter decomposition) to this end. Here we report on decomposition experiments carried out in Portugal in five pairs of streams that differed in dissolved inorganic nutrients. On average, decomposition rates of alder and oak leaves were 2.8 and 1.4 times higher in high nutrient streams in coarse and fine mesh bags, respectively, than in corresponding reference streams. Breakdown rate correlated better with stream water SRP concentration rather than TIN. Fungal biomass and sporulation rates of aquatic hyphomycetes associated with decomposing leaves were stimulated by higher nutrient levels. Both fungal parameters measured at very early stages of decomposition (e.g. days 7-13) correlated well with overall decomposition rates. Eutrophication had no significant effect on shredder abundances in leaf bags but species richness was higher in disturbed streams. Decomposition is a key functional parameter in streams integrating many other variables and can be useful in assessing stream ecosystem health. We also argue that because decomposition is often controlled by fungal activity, microbial parameters can also be useful in bioassessment.

First-principles studies of phase stability and crystal structures in Li-Zn mixed-metal borohydrides

NASA Astrophysics Data System (ADS)

Wang, Yongli; Zhang, Yongsheng; Wolverton, C.

2013-07-01

We address the problem of finding mixed-metal borohydrides with favorable thermodynamics and illustrate the approach using the example of LiZn2(BH4)5. Using density functional theory (DFT), along with the grand-canonical linear programming method (GCLP), we examine the experimentally and computationally proposed crystal structures and the finite-temperature thermodynamics of dehydrogenation for the quaternary hydride LiZn2(BH4)5. We find the following: (i) For LiZn2(BH4)5, DFT calculations of the experimental crystal structures reveal that the structure from the neutron diffraction experiments of Ravnsbæk is more stable [by 24 kJ/(mol f.u.)] than that based on a previous x-ray study. (ii) Our DFT calculations show that when using the neutron-diffraction structure of LiZn2(BH4)5, the recently theoretically predicted LiZn(BH4)3 compound is unstable with respect to the decomposition into LiZn2(BH4)5+LiBH4. (iii) GCLP calculations show that even though LiZn2(BH4)5 is a combination of weakly [Zn(BH4)2] and strongly (LiBH4) bound borohydrides, its decomposition is not intermediate between the two individual borohydrides. Rather, we find that the decomposition of LiZn2(BH4)5 is divided into a weakly exothermic step [LiZn2(BH4)5→2Zn+(1)/(5)LiBH4+(2)/(5)Li2B12H12+(36)/(5)H2] and three strong endothermic steps (12LiBH4→10LiH+Li2B12H12+13H2; Zn+LiH→LiZn+(1)/(2)H2; 2Zn+Li2B12H12→2LiZn+12B+6H2). DFT-calculated ΔHZPET=0K values for the first three LiZn2(BH4)5 decomposition steps are -19, +37, +74 kJ/(mol H2), respectively. The behavior of LiZn2(BH4)5 shows that mixed-metal borohydrides formed by mixing borohydrides of high and low thermodynamics stabilities do not necessarily have an intermediate decomposition tendency. Our results suggest the correct strategy to find intermediate decomposition in mixed-metal borohydrides is to search for stable mixed-metal products such as ternary metal borides.

Evaluation of DeNitrification DeComposition model for estimating ammonia fluxes from chemical fertilizer application

USDA-ARS?s Scientific Manuscript database

DeNitrification DeComposition (DNDC) model predictions of NH3 fluxes following chemical fertilizer application were evaluated by comparison to relaxed eddy accumulation (REA) measurements, in Central Illinois, United States, over the 2014 growing season of corn. Practical issues for evaluating closu...

Development of rate expressions for the thermal decomposition of RDX

DOE Office of Scientific and Technical Information (OSTI.GOV)

Erickson, K.L.; Behrens, R. Jr.; Bulusu, S.

Decomposition and combustion of energetic materials involve processes in both condensed and gas phases. Development of reliable models for design, performance, stability, and hazard analyses requires detailed understanding of the mechanisms for both the initial condensed phase decomposition of the energetic material and the subsequent reaction of the decomposition species to form the ultimate reaction products. Those mechanisms must be described in terms of constitutive rate expressions that can be incorporated into mathematical models. The thermal decomposition of RDX has been studied by Behrens and Bulusu using Simultaneous Thermogravimetric Modulated Beam Mass Spectrometry (STMBMS). Their work provides a basis formore » developing some of the constitutive rate expressions that are needed in models for design, performance, stability and hazard analyses involving RDX. Behrens and Bulusu have identified four primary reaction pathways that control the liquid-phase decomposition of RDX at temperatures between 200 and 215{degrees}C, and one that controls solid-phase decomposition at temperatures below 200{degrees}C. Two of the liquid-phase pathways appear to be first order in RDX. Arrhenius parameters for the first-order rate constants were evaluated from data reported by Behrens and Bulusu. Reaction rates extrapolated to temperatures between 370 and 450{degrees}C are in good agreement with global reaction rates observed by Trott et al. using high-speed photography and laser-heated thin-film samples. Furthermore, the STMBMS results of Behrens and Bulusu appear to be consistent with condensed-phase infrared results reported by Trott et al. and Erickson et al.« less

Development of rate expressions for the thermal decomposition of RDX

DOE Office of Scientific and Technical Information (OSTI.GOV)

Erickson, K.L.; Behrens, R. Jr.; Bulusu, S.

Decomposition and combustion of energetic materials involve processes in both condensed and gas phases. Development of reliable models for design, performance, stability, and hazard analyses requires detailed understanding of the mechanisms for both the initial condensed phase decomposition of the energetic material and the subsequent reaction of the decomposition species to form the ultimate reaction products. Those mechanisms must be described in terms of constitutive rate expressions that can be incorporated into mathematical models. The thermal decomposition of RDX has been studied by Behrens and Bulusu using Simultaneous Thermogravimetric Modulated Beam Mass Spectrometry (STMBMS). Their work provides a basis formore » developing some of the constitutive rate expressions that are needed in models for design, performance, stability and hazard analyses involving RDX. Behrens and Bulusu have identified four primary reaction pathways that control the liquid-phase decomposition of RDX at temperatures between 200 and 215[degrees]C, and one that controls solid-phase decomposition at temperatures below 200[degrees]C. Two of the liquid-phase pathways appear to be first order in RDX. Arrhenius parameters for the first-order rate constants were evaluated from data reported by Behrens and Bulusu. Reaction rates extrapolated to temperatures between 370 and 450[degrees]C are in good agreement with global reaction rates observed by Trott et al. using high-speed photography and laser-heated thin-film samples. Furthermore, the STMBMS results of Behrens and Bulusu appear to be consistent with condensed-phase infrared results reported by Trott et al. and Erickson et al.« less

Nitrated graphene oxide and its catalytic activity in thermal decomposition of ammonium perchlorate

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Wenwen; Luo, Qingping; Duan, Xiaohui

2014-02-01

Highlights: • The NGO was synthesized by nitrifying homemade GO. • The N content of resulted NGO is up to 1.45 wt.%. • The NGO can facilitate the decomposition of AP and release much heat. - Abstract: Nitrated graphene oxide (NGO) was synthesized by nitrifying homemade GO with nitro-sulfuric acid. Fourier transform infrared spectroscopy (FTIR), laser Raman spectroscopy, CP/MAS {sup 13}C NMR spectra and X-ray photoelectron spectroscopy (XPS) were used to characterize the structure of NGO. The thickness and the compositions of GO and NGO were analyzed by atomic force microscopy (AFM) and elemental analysis (EA), respectively. The catalytic effectmore » of the NGO for the thermal decomposition of ammonium perchlorate (AP) was investigated by differential scanning calorimetry (DSC). Adding 10% of NGO to AP decreases the decomposition temperature by 106 °C and increases the apparent decomposition heat from 875 to 3236 J/g.« less

Proof of a new colour decomposition for QCD amplitudes

DOE PAGES

Melia, Tom

2015-12-16

Recently, Johansson and Ochirov conjectured the form of a new colour decom-position for QCD tree-level amplitudes. This note provides a proof of that conjecture. The proof is based on ‘Mario World’ Feynman diagrams, which exhibit the hierarchical Dyck structure previously found to be very useful when dealing with multi-quark amplitudes.

Ethanol-Glycerin Fixation with Thymol Conservation: A Potential Alternative to Formaldehyde and Phenol Embalming

ERIC Educational Resources Information Center

Hammer, Niels; Loffler, Sabine; Feja, Christine; Sandrock, Mara; Schmidt, Wolfgang; Bechmann, Ingo; Steinke, Hanno

2012-01-01

Anatomical fixation and conservation are required to prevent specimens from undergoing autolysis and decomposition. While fixation is the primary arrest of the structures responsible for autolysis and decomposition, conservation preserves the state of fixation. Although commonly used, formaldehyde has been classified as carcinogenic to humans. For…

Litter chemistry, community shift, and non-additive effects drive litter decomposition changes following invasion by a generalist pathogen

Treesearch

Richard C. Cobb; David M. Rizzo

2016-01-01

Forest pathogens have strong potential to shape ecosystem function by altering litterfall, microclimate, and changing community structure. We quantified changes in litter decomposition from a set of distinct diseases caused by Phytophthora ramorum, an exotic generalist pathogen. Phytophthora ramorum causes leaf blight and...

Proof of a new colour decomposition for QCD amplitudes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Melia, Tom

Recently, Johansson and Ochirov conjectured the form of a new colour decom-position for QCD tree-level amplitudes. This note provides a proof of that conjecture. The proof is based on ‘Mario World’ Feynman diagrams, which exhibit the hierarchical Dyck structure previously found to be very useful when dealing with multi-quark amplitudes.

Suppressing NOM access to controlled porous TiO2 particles enhances the decomposition of target water contaminants

EPA Science Inventory

Suppressing access of natural organic matter (NOM) to TiO2 is a key to the successful photocatalytic decomposition of a target contaminant in water. This study first demonstrates simply controlling the porous structure of TiO2 can significantly improve the selective oxidation.

Does cattle grazing of dual-purpose wheat accelerate the rate of stubble decomposition and nutrients released

USDA-ARS?s Scientific Manuscript database

Decomposition and nutrient release of winter annual forages in integrated crop-livestock systems could be affected by the resultant alterations in structure and quality of residues caused by grazing, but little information is available to test this hypothesis. Information on residue dynamics is need...

Regression-based adaptive sparse polynomial dimensional decomposition for sensitivity analysis

NASA Astrophysics Data System (ADS)

Tang, Kunkun; Congedo, Pietro; Abgrall, Remi

2014-11-01

Polynomial dimensional decomposition (PDD) is employed in this work for global sensitivity analysis and uncertainty quantification of stochastic systems subject to a large number of random input variables. Due to the intimate structure between PDD and Analysis-of-Variance, PDD is able to provide simpler and more direct evaluation of the Sobol' sensitivity indices, when compared to polynomial chaos (PC). Unfortunately, the number of PDD terms grows exponentially with respect to the size of the input random vector, which makes the computational cost of the standard method unaffordable for real engineering applications. In order to address this problem of curse of dimensionality, this work proposes a variance-based adaptive strategy aiming to build a cheap meta-model by sparse-PDD with PDD coefficients computed by regression. During this adaptive procedure, the model representation by PDD only contains few terms, so that the cost to resolve repeatedly the linear system of the least-square regression problem is negligible. The size of the final sparse-PDD representation is much smaller than the full PDD, since only significant terms are eventually retained. Consequently, a much less number of calls to the deterministic model is required to compute the final PDD coefficients.

Influence of macrophyte decomposition on growth rate and community structure of okefenokee swamp bacterioplankton.

PubMed

Murray, R E; Hodson, R E

1986-02-01

Dissolved substances released during decomposition of the white water lily (Nymphaea odorata) can alter the growth rate of Okefenokee Swamp bacterioplankton. In microcosm experiments dissolved compounds released from senescent Nymphaea leaves caused a transient reduction in the abundance and activity of water column bacterioplankton, followed by a period of intense bacterial growth. Rates of [H]thymidine incorporation and turnover of dissolved d-glucose were depressed by over 85%, 3 h after the addition of Nymphaea leachates to microcosms containing Okefenokee Swamp water. Bacterial activity subsequently recovered; after 20 h [H]thymidine incorporation in leachate-treated microcosms was 10-fold greater than that in control microcosms. The recovery of activity was due to a shift in the composition of the bacterial population toward resistance to the inhibitory compounds present in Nymphaea leachates. Inhibitory compounds released during the decomposition of aquatic macrophytes thus act as selective agents which alter the community structure of the bacterial population with respect to leachate resistance. Soluble compounds derived from macrophyte decomposition influence the rate of bacterial secondary production and the availability of microbial biomass to microconsumers.

Influence of macrophyte decomposition on growth rate and community structure of Okefenokee Swamp bacterioplankton

DOE Office of Scientific and Technical Information (OSTI.GOV)

Murray, R.E.; Hodson, R.E.

1986-02-01

Dissolved substances released during decomposition of the white water lily (Nymphaea odorata) can alter the growth rate of Okefenokee Swamp bacterioplankton. In microcosm experiments dissolved compounds released bacterioplankton, followed by a period of intense bacterial growth. Rates of (/sup 3/H)thymidine incorporation and turnover of dissolved D-glucose were depressed by over 85%, 3 h after the addition of Nymphaea leachates to microcosms containing Okefenokee Swamp water. Bacterial activity subsequently recovered; after 20 h (/sup 3/H)thymidine incorporation in leachate-treated microcosms was 10-fold greater than that in control microcosms. The recovery of activity was due to a shift in the composition of themore » bacterial population toward resistance to the inhibitory compounds present in Nymphaea leachates. Inhibitory compounds released during the decomposition of aquatic macrophytes thus act as selective agents which alter the community structure of the bacterial population with respect to leachate resistance. Soluble compounds derived from macrophyte decomposition influence the rate of bacterial secondary production and the availability of microbial biomass to microconsumers.« less

Total variation regularization of the 3-D gravity inverse problem using a randomized generalized singular value decomposition

NASA Astrophysics Data System (ADS)

Vatankhah, Saeed; Renaut, Rosemary A.; Ardestani, Vahid E.

2018-04-01

We present a fast algorithm for the total variation regularization of the 3-D gravity inverse problem. Through imposition of the total variation regularization, subsurface structures presenting with sharp discontinuities are preserved better than when using a conventional minimum-structure inversion. The associated problem formulation for the regularization is nonlinear but can be solved using an iteratively reweighted least-squares algorithm. For small-scale problems the regularized least-squares problem at each iteration can be solved using the generalized singular value decomposition. This is not feasible for large-scale, or even moderate-scale, problems. Instead we introduce the use of a randomized generalized singular value decomposition in order to reduce the dimensions of the problem and provide an effective and efficient solution technique. For further efficiency an alternating direction algorithm is used to implement the total variation weighting operator within the iteratively reweighted least-squares algorithm. Presented results for synthetic examples demonstrate that the novel randomized decomposition provides good accuracy for reduced computational and memory demands as compared to use of classical approaches.

Climate and litter quality differently modulate the effects of soil fauna on litter decomposition across biomes

PubMed Central

García-Palacios, Pablo; Maestre, Fernando T.; Kattge, Jens; Wall, Diana H.

2015-01-01

Climate and litter quality have been identified as major drivers of litter decomposition at large spatial scales. However, the role played by soil fauna remains largely unknown, despite its importance for litter fragmentation and microbial activity. We synthesized litterbag studies to quantify the effect sizes of soil fauna on litter decomposition rates at the global and biome scales, and to assess how climate, litter quality and soil fauna interact to determine such rates. Soil fauna consistently enhanced litter decomposition at both global and biome scales (average increment ~27%). However, climate and litter quality differently modulated the effects of soil fauna on decomposition rates between biomes, from climate-driven biomes to those where climate effects were mediated by changes in litter quality. Our results advocate for the inclusion of biome-specific soil fauna effects on litter decomposition as a mean to reduce the unexplained variation in large-scale decomposition models. PMID:23763716

A statistical approach based on accumulated degree-days to predict decomposition-related processes in forensic studies.

PubMed

Michaud, Jean-Philippe; Moreau, Gaétan

2011-01-01

Using pig carcasses exposed over 3 years in rural fields during spring, summer, and fall, we studied the relationship between decomposition stages and degree-day accumulation (i) to verify the predictability of the decomposition stages used in forensic entomology to document carcass decomposition and (ii) to build a degree-day accumulation model applicable to various decomposition-related processes. Results indicate that the decomposition stages can be predicted with accuracy from temperature records and that a reliable degree-day index can be developed to study decomposition-related processes. The development of degree-day indices opens new doors for researchers and allows for the application of inferential tools unaffected by climatic variability, as well as for the inclusion of statistics in a science that is primarily descriptive and in need of validation methods in courtroom proceedings. © 2010 American Academy of Forensic Sciences.

Warming alters community size structure and ecosystem functioning

PubMed Central

Dossena, Matteo; Yvon-Durocher, Gabriel; Grey, Jonathan; Montoya, José M.; Perkins, Daniel M.; Trimmer, Mark; Woodward, Guy

2012-01-01

Global warming can affect all levels of biological complexity, though we currently understand least about its potential impact on communities and ecosystems. At the ecosystem level, warming has the capacity to alter the structure of communities and the rates of key ecosystem processes they mediate. Here we assessed the effects of a 4°C rise in temperature on the size structure and taxonomic composition of benthic communities in aquatic mesocosms, and the rates of detrital decomposition they mediated. Warming had no effect on biodiversity, but altered community size structure in two ways. In spring, warmer systems exhibited steeper size spectra driven by declines in total community biomass and the proportion of large organisms. By contrast, in autumn, warmer systems had shallower size spectra driven by elevated total community biomass and a greater proportion of large organisms. Community-level shifts were mirrored by changes in decomposition rates. Temperature-corrected microbial and macrofaunal decomposition rates reflected the shifts in community structure and were strongly correlated with biomass across mesocosms. Our study demonstrates that the 4°C rise in temperature expected by the end of the century has the potential to alter the structure and functioning of aquatic ecosystems profoundly, as well as the intimate linkages between these levels of ecological organization. PMID:22496185

Structure disordering and thermal decomposition of manganese oxalate dihydrate, MnC2O4·2H2O

NASA Astrophysics Data System (ADS)

Puzan, Anna N.; Baumer, Vyacheslav N.; Lisovytskiy, Dmytro V.; Mateychenko, Pavel V.

2018-04-01

It is found that the known regular structures of MnC2O4·2H2O (I) do not allow to refine the powder X-ray pattern of (I) properly using the Rietveld method. Implementation of order-disorder scheme [28] via the including of appropriate displacement vector improves the refinement results. Also it is found that in the case of (I) the similar improvement may be achieved using the data on two phases of (I) obtained as result of decomposition MnC2O4·3H2O single crystal in the mother solution after growth. Thermal decomposition of (I) produce the anhydrous γ-MnC2O4 (II) the structure of which is differ from the known α- and β-modifications of VIIIb transition metal oxalates. The solved ab initio from the powder pattern structure (II) (space group Pmna, a = 7.1333 (1), b = 5.8787 (1), c = 9.0186 (2) Å, V = 378.19 (1) Å3, Z = 4 and Dx = 2.511 Mg m-3) contains seven-coordinated Mn atoms with Mn-O distances of 2.110-2.358 Å, and is not close-packed. Thermal decomposition of (II) in air flows via forming of amorphous MnO, the heating of which up to 723 K is accompanied by oxidation of MnO to Mn2O3 and further recrystallization of the latter.

Technical Note: Linking climate change and downed woody debris decomposition across forests of the eastern United States

NASA Astrophysics Data System (ADS)

Russell, M. B.; Woodall, C. W.; D'Amato, A. W.; Fraver, S.; Bradford, J. B.

2014-06-01

Forest ecosystems play a critical role in mitigating greenhouse gas emissions. Long-term forest carbon (C) storage is determined by the balance between C fixation into biomass through photosynthesis and C release via decomposition and combustion. Relative to C fixation in biomass, much less is known about C depletion through decomposition of woody debris, particularly under a changing climate. It is assumed that the increased temperatures and longer growing seasons associated with projected climate change will increase the decomposition rates (i.e., more rapid C cycling) of downed woody debris (DWD); however, the magnitude of this increase has not been previously addressed. Using DWD measurements collected from a national forest inventory of the eastern United States, we show that the residence time of DWD may decrease (i.e., more rapid decomposition) by as much as 13% over the next 200 years depending on various future climate change scenarios and forest types. Although existing dynamic global vegetation models account for the decomposition process, they typically do not include the effect of a changing climate on DWD decomposition rates. We expect that an increased understanding of decomposition rates, as presented in this current work, will be needed to adequately quantify the fate of woody detritus in future forests. Furthermore, we hope these results will lead to improved models that incorporate climate change scenarios for depicting future dead wood dynamics, in addition to a traditional emphasis on live tree demographics.

A structural design decomposition method utilizing substructuring

NASA Technical Reports Server (NTRS)

Scotti, Stephen J.

1994-01-01

A new method of design decomposition for structural analysis and optimization is described. For this method, the structure is divided into substructures where each substructure has its structural response described by a structural-response subproblem, and its structural sizing determined from a structural-sizing subproblem. The structural responses of substructures that have rigid body modes when separated from the remainder of the structure are further decomposed into displacements that have no rigid body components, and a set of rigid body modes. The structural-response subproblems are linked together through forces determined within a structural-sizing coordination subproblem which also determines the magnitude of any rigid body displacements. Structural-sizing subproblems having constraints local to the substructures are linked together through penalty terms that are determined by a structural-sizing coordination subproblem. All the substructure structural-response subproblems are totally decoupled from each other, as are all the substructure structural-sizing subproblems, thus there is significant potential for use of parallel solution methods for these subproblems.

The relative importance of decomposition and transport mechanisms in accounting for soil organic carbon profiles

NASA Astrophysics Data System (ADS)

Guenet, B.; Eglin, T.; Vasilyeva, N.; Peylin, P.; Ciais, P.; Chenu, C.

2013-04-01

Soil is the major terrestrial reservoir of carbon and a substantial part of this carbon is stored in deep layers, typically deeper than 50 cm below the surface. Several studies underlined the quantitative importance of this deep soil organic carbon (SOC) pool and models are needed to better understand this stock and its evolution under climate and land-uses changes. In this study, we tested and compared three simple theoretical models of vertical transport for SOC against SOC profiles measurements from a long-term bare fallow experiment carried out by the Central-Chernozem State Natural Biosphere Reserve in the Kursk Region of Russia. The transport schemes tested are diffusion, advection and both diffusion and advection. They are coupled to three different formulations of soil carbon decomposition kinetics. The first formulation is a first order kinetics widely used in global SOC decomposition models; the second one, so-called "priming" model, links SOC decomposition rate to the amount of fresh organic matter, representing the substrate interactions. The last one is also a first order kinetics, but SOC is split into two pools. Field data are from a set of three bare fallow plots where soil received no input during the past 20, 26 and 58 yr, respectively. Parameters of the models were optimised using a Bayesian method. The best results are obtained when SOC decomposition is assumed to be controlled by fresh organic matter (i.e., the priming model). In comparison to the first-order kinetic model, the priming model reduces the overestimation in the deep layers. We also observed that the transport scheme that improved the fit with the data depended on the soil carbon mineralisation formulation chosen. When soil carbon decomposition was modelled to depend on the fresh organic matter amount, the transport mechanism which improved best the fit to the SOC profile data was the model representing both advection and diffusion. Interestingly, the older the bare fallow is, the lesser the need for diffusion is, suggesting that stabilised carbon may not be transported within the profile by the same mechanisms than more labile carbon.

Structural Identifiability of Dynamic Systems Biology Models

PubMed Central

Villaverde, Alejandro F.

2016-01-01

A powerful way of gaining insight into biological systems is by creating a nonlinear differential equation model, which usually contains many unknown parameters. Such a model is called structurally identifiable if it is possible to determine the values of its parameters from measurements of the model outputs. Structural identifiability is a prerequisite for parameter estimation, and should be assessed before exploiting a model. However, this analysis is seldom performed due to the high computational cost involved in the necessary symbolic calculations, which quickly becomes prohibitive as the problem size increases. In this paper we show how to analyse the structural identifiability of a very general class of nonlinear models by extending methods originally developed for studying observability. We present results about models whose identifiability had not been previously determined, report unidentifiabilities that had not been found before, and show how to modify those unidentifiable models to make them identifiable. This method helps prevent problems caused by lack of identifiability analysis, which can compromise the success of tasks such as experiment design, parameter estimation, and model-based optimization. The procedure is called STRIKE-GOLDD (STRuctural Identifiability taKen as Extended-Generalized Observability with Lie Derivatives and Decomposition), and it is implemented in a MATLAB toolbox which is available as open source software. The broad applicability of this approach facilitates the analysis of the increasingly complex models used in systems biology and other areas. PMID:27792726

Full-envelope aerodynamic modeling of the Harrier aircraft

NASA Technical Reports Server (NTRS)

Mcnally, B. David

1986-01-01

A project to identify a full-envelope model of the YAV-8B Harrier using flight-test and parameter identification techniques is described. As part of the research in advanced control and display concepts for V/STOL aircraft, a full-envelope aerodynamic model of the Harrier is identified, using mathematical model structures and parameter identification methods. A global-polynomial model structure is also used as a basis for the identification of the YAV-8B aerodynamic model. State estimation methods are used to ensure flight data consistency prior to parameter identification.Equation-error methods are used to identify model parameters. A fixed-base simulator is used extensively to develop flight test procedures and to validate parameter identification software. Using simple flight maneuvers, a simulated data set was created covering the YAV-8B flight envelope from about 0.3 to 0.7 Mach and about -5 to 15 deg angle of attack. A singular value decomposition implementation of the equation-error approach produced good parameter estimates based on this simulated data set.

Response of SOM Decomposition to Anthropogenic N Deposition: Simulations From the PnET-SOM Model.

NASA Astrophysics Data System (ADS)

Tonitto, C.; Goodale, C. L.; Ollinger, S. V.; Jenkins, J. P.

2008-12-01

Anthropogenic forcing of the C and N cycles has caused rapid change in atmospheric CO2 and N deposition, with complex and uncertain effects on forest C and N balance. With some exceptions, models of forest ecosystem response to anthropogenic perturbation have historically focused more on aboveground than belowground processes; the complexity of soil organic matter (SOM) is often represented with abstract or incomplete SOM pools, and remains difficult to quantify. We developed a model of SOM dynamics in northern hardwood forests with explicit feedbacks between C and N cycles. The soil model is linked to the aboveground dynamics of the PnET model to form PnET-SOM. The SOM model includes: 1) physically measurable SOM pools, including humic and mineral-associated SOM in O, A, and B soil horizons, 2) empirical soil turnover times based on 14C data, 3) alternative SOM decomposition algorithms with and without explicit microbial processing, and 4) soluble element transport explicitly linked to the hydrologic cycle. We tested model sensitivity to changes in litter decomposition rate (k) and completeness of decomposition (limit value) by altering these parameters based on experimental observations from long-term litter decomposition experiments with N fertilization treatments. After a 100 year simulation, the Oe+Oa horizon SOC pool was reduced by 15 % and the A-horizon humified SOC was reduced by 7 % for N deposition scenarios relative to forests without N fertilization. In contrast, predictions for slower time-scale pools showed negligible variation in response to variation in the limit values tested, with A-horizon mineral SOC pools reduced by < 3 % and B-horizon mineral SOC reduced by 0.1 % for N deposition scenarios relative to forests without N fertilization. The model was also used to test the effect of varying initial litter decomposition rate to simulate response to N deposition. In contrast to the effect of varying limit values, simulations in which only k-values were varied did not drastically alter the predicted SOC pool distribution throughout the soil profile, but did significantly alter the Oi SOC pool. These results suggest that describing soil response to N deposition via alteration of the limit value alone, or as a combined alteration of limit value and the initial decomposition rate, can lead to significant variation in predicted long-term C storage.

Thermochemical and kinetic analysis of the thermal decomposition of monomethylhydrazine: an elementary reaction mechanism.

PubMed

Sun, Hongyan; Law, Chung K

2007-05-17

The reaction kinetics for the thermal decomposition of monomethylhydrazine (MMH) was studied with quantum Rice-Ramsperger-Kassel (QRRK) theory and a master equation analysis for pressure falloff. Thermochemical properties were determined by ab initio and density functional calculations. The entropies, S degrees (298.15 K), and heat capacities, Cp degrees (T) (0 < or = T/K < or = 1500), from vibrational, translational, and external rotational contributions were calculated using statistical mechanics based on the vibrational frequencies and structures obtained from the density functional study. Potential barriers for internal rotations were calculated at the B3LYP/6-311G(d,p) level, and hindered rotational contributions to S degrees (298.15 K) and Cp degrees (T) were calculated by solving the Schrödinger equation with free rotor wave functions, and the partition coefficients were treated by direct integration over energy levels of the internal rotation potentials. Enthalpies of formation, DeltafH degrees (298.15 K), for the parent MMH (CH3NHNH2) and its corresponding radicals CH3N*NH2, CH3NHN*H, and C*H2NHNH2 were determined to be 21.6, 48.5, 51.1, and 62.8 kcal mol(-1) by use of isodesmic reaction analysis and various ab initio methods. The kinetic analysis of the thermal decomposition, abstraction, and substitution reactions of MMH was performed at the CBS-QB3 level, with those of N-N and C-N bond scissions determined by high level CCSD(T)/6-311++G(3df,2p)//MPWB1K/6-31+G(d,p) calculations. Rate constants of thermally activated MMH to dissociation products were calculated as functions of pressure and temperature. An elementary reaction mechanism based on the calculated rate constants, thermochemical properties, and literature data was developed to model the experimental data on the overall MMH thermal decomposition rate. The reactions of N-N and C-N bond scission were found to be the major reaction paths for the modeling of MMH homogeneous decomposition at atmospheric conditions.

Decomposition and transformation of cutin and cutan biopolymers in soils: effect on their sorptive capabilities

NASA Astrophysics Data System (ADS)

Shechter, M.; Chefetz, B.

2009-04-01

Plant cuticle materials, especially the highly aliphatic biopolymers cutin and cutan, have been reported as highly efficient natural sorbents. The objective of this study was to examine the effects of decomposition on their sorption behavior with naphthol and phenanthrene. The level of cutin and cutan was reduced by 15 and 27% respectively during the first 3 mo of incubation. From that point, the level of the cutan did not change, while the level of the cutin continued to decrease up to 32% after 20 mo. 13C NMR analysis suggested transformation of cutan mainly within its alkyl-C structure which are assigned as crystalline moieties. Cutin, however, did not exhibit significant structure changes with time. The level of humic-like substances increased due to cutin decomposition but was not influenced in the cutan system after 20 mo of incubation. This indicates that the cutin biopolymer has been decomposed and transformed into humic-like substances, whereas the cutan was less subject to transformation. Decomposition affected sorption properties in similar trends for both cutin and cutan. The Freundlich capacity coefficients (KFOC) of naphthol were much lower than phenanthrene and were less influenced by the decomposition, whereas with phenanthrene KFOC values increased significantly with time. Naphthol exhibited non-linear isotherms; and nonlinearity was decreased with incubation time. In contrast, phenanthrene isotherms were more linear and showed only moderate change with time. The decrease in the linearity of naphthol isotherms might relate to the transformation of the sorption sites due to structural changes in the biopolymers. However, with phenanthrene, these changes did not affect sorption linearity but increased sorption affinities mainly for cutan. This is probably due to decomposition of the rigid alkyl-C moieties in the cutan biopolymer. Our data suggest that both biopolymers were relatively stable in the soil for 20 mo. Cutan is less degradable than cutin and therefore is more likely to accumulate in soils and contribute to the refractory aliphatic components of soil organic matter.

Entropic-elasticity-controlled dissociation and energetic-elasticity-controlled rupture induce catch-to-slip bonds in cell-adhesion molecules.

PubMed

Wei, YuJie

2008-03-01

We develop a physical model to describe the kinetic behavior in cell-adhesion molecules. Unbinding of noncovalent biological bonds is assumed to occur by both bond dissociation and bond rupture. Such a decomposition of debonding processes is a space decomposition of the debonding events. Dissociation under thermal fluctuation is nondirectional in a three-dimensional space, and its energy barrier to escape is not influenced by a tensile force, but the microstates that could lead to dissociation are changed by the tensile force; rupture happens along the tensile force direction. An applied force effectively lowers the energy barrier to escape along the loading direction. The lifetime of the biological bond, due to the two concurrent off rates, may grow with increasing tensile force to a moderate amount and then decrease with further increasing load. We hypothesize that a catch-to-slip bond transition is a generic feature in biological bonds. The model also predicts that catch bonds in a more flexible molecular structure have longer lifetimes and need less force to be fully activated.

Surface fuel litterfall and decomposition in the northern Rocky Mountains, U.S.A.

Treesearch

Robert E. Keane

2008-01-01

Surface fuel deposition and decomposition rates are important to fire management and research because they can define the longevity of fuel treatments in time and space and they can be used to design, build, test, and validate complex fire and ecosystem models useful in evaluating management alternatives. We determined rates of surface fuel litterfall and decomposition...

[Litter decomposition and nutrient release in Acacia mangium plantations established on degraded soils of Colombia].

PubMed

Castellanos-Barliza, Jeiner; León Peláez, Juan Diego

2011-03-01

Several factors control the decomposition in terrestrial ecosystems such as humidity, temperature, quality of litter and microbial activity. We investigated the effects of rainfall and soil plowing prior to the establishment of Acacia mangium plantations, using the litterbag technique, during a six month period, in forests plantations in Bajo Cauca region, Colombia. The annual decomposition constants (k) of simple exponential model, oscillated between 1.24 and 1.80, meanwhile k1 y k2 decomposition constants of double exponential model were 0.88-1.81 and 0.58-7.01. At the end of the study, the mean residual dry matter (RDM) was 47% of the initial value for the three sites. We found a slow N, Ca and Mg release pattern from the A. mangium leaf litter, meanwhile, phosphorus (P) showed a dominant immobilization phase, suggesting its low availability in soils. Chemical leaf litter quality parameters (e.g. N and P concentrations, C/N, N/P ratios and phenols content) showed an important influence on decomposition rates. The results of this study indicated that rainfall plays an important role on the decomposition process, but not soil plowing.

Beyond Low Rank + Sparse: Multi-scale Low Rank Matrix Decomposition

PubMed Central

Ong, Frank; Lustig, Michael

2016-01-01

We present a natural generalization of the recent low rank + sparse matrix decomposition and consider the decomposition of matrices into components of multiple scales. Such decomposition is well motivated in practice as data matrices often exhibit local correlations in multiple scales. Concretely, we propose a multi-scale low rank modeling that represents a data matrix as a sum of block-wise low rank matrices with increasing scales of block sizes. We then consider the inverse problem of decomposing the data matrix into its multi-scale low rank components and approach the problem via a convex formulation. Theoretically, we show that under various incoherence conditions, the convex program recovers the multi-scale low rank components either exactly or approximately. Practically, we provide guidance on selecting the regularization parameters and incorporate cycle spinning to reduce blocking artifacts. Experimentally, we show that the multi-scale low rank decomposition provides a more intuitive decomposition than conventional low rank methods and demonstrate its effectiveness in four applications, including illumination normalization for face images, motion separation for surveillance videos, multi-scale modeling of the dynamic contrast enhanced magnetic resonance imaging and collaborative filtering exploiting age information. PMID:28450978

Mathematical Methods of System Analysis in Construction Materials

NASA Astrophysics Data System (ADS)

Garkina, Irina; Danilov, Alexander

2017-10-01

System attributes of construction materials are defined: complexity of an object, integrity of set of elements, existence of essential, stable relations between elements defining integrative properties of system, existence of structure, etc. On the basis of cognitive modelling (intensive and extensive properties; the operating parameters) materials (as difficult systems) and creation of the cognitive map the hierarchical modular structure of criteria of quality is under construction. It actually is a basis for preparation of the specification on development of material (the required organization and properties). Proceeding from a modern paradigm (model of statement of problems and their decisions) of development of materials, levels and modules are specified in structure of material. It when using the principles of the system analysis allows to considered technological process as the difficult system consisting of elements of the distinguished specification level: from atomic before separate process. Each element of system depending on an effective objective is considered as separate system with more detailed levels of decomposition. Among them, semantic and qualitative analyses of an object (are considered a research objective, decomposition levels, separate elements and communications between them come to light). Further formalization of the available knowledge in the form of mathematical models (structural identification) is carried out; communications between input and output parameters (parametrical identification) are defined. Hierarchical structures of criteria of quality are under construction for each allocated level. On her the relevant hierarchical structures of system (material) are under construction. Regularities of structurization and formation of properties, generally are considered at the levels from micro to a macrostructure. The mathematical model of material is represented as set of the models corresponding to private criteria by which separate modules and their levels (the mathematical description, a decision algorithm) are defined. Adequacy is established (compliance of results of modelling to experimental data; is defined by the level of knowledge of process and validity of the accepted assumptions). The global criterion of quality of material is considered as a set of private criteria (properties). Synthesis of material is carried out on the basis of one-criteria optimization on each of the chosen private criteria. Results of one-criteria optimization are used at multicriteria optimization. The methods of developing materials as single-purpose, multi-purpose, including contradictory, systems are indicated. The scheme of synthesis of composite materials as difficult systems is developed. The specified system approach effectively was used in case of synthesis of composite materials with special properties.

Model diagnostics in reduced-rank estimation

PubMed Central

Chen, Kun

2016-01-01

Reduced-rank methods are very popular in high-dimensional multivariate analysis for conducting simultaneous dimension reduction and model estimation. However, the commonly-used reduced-rank methods are not robust, as the underlying reduced-rank structure can be easily distorted by only a few data outliers. Anomalies are bound to exist in big data problems, and in some applications they themselves could be of the primary interest. While naive residual analysis is often inadequate for outlier detection due to potential masking and swamping, robust reduced-rank estimation approaches could be computationally demanding. Under Stein's unbiased risk estimation framework, we propose a set of tools, including leverage score and generalized information score, to perform model diagnostics and outlier detection in large-scale reduced-rank estimation. The leverage scores give an exact decomposition of the so-called model degrees of freedom to the observation level, which lead to exact decomposition of many commonly-used information criteria; the resulting quantities are thus named information scores of the observations. The proposed information score approach provides a principled way of combining the residuals and leverage scores for anomaly detection. Simulation studies confirm that the proposed diagnostic tools work well. A pattern recognition example with hand-writing digital images and a time series analysis example with monthly U.S. macroeconomic data further demonstrate the efficacy of the proposed approaches. PMID:28003860

Model diagnostics in reduced-rank estimation.

PubMed

Chen, Kun

2016-01-01

Reduced-rank methods are very popular in high-dimensional multivariate analysis for conducting simultaneous dimension reduction and model estimation. However, the commonly-used reduced-rank methods are not robust, as the underlying reduced-rank structure can be easily distorted by only a few data outliers. Anomalies are bound to exist in big data problems, and in some applications they themselves could be of the primary interest. While naive residual analysis is often inadequate for outlier detection due to potential masking and swamping, robust reduced-rank estimation approaches could be computationally demanding. Under Stein's unbiased risk estimation framework, we propose a set of tools, including leverage score and generalized information score, to perform model diagnostics and outlier detection in large-scale reduced-rank estimation. The leverage scores give an exact decomposition of the so-called model degrees of freedom to the observation level, which lead to exact decomposition of many commonly-used information criteria; the resulting quantities are thus named information scores of the observations. The proposed information score approach provides a principled way of combining the residuals and leverage scores for anomaly detection. Simulation studies confirm that the proposed diagnostic tools work well. A pattern recognition example with hand-writing digital images and a time series analysis example with monthly U.S. macroeconomic data further demonstrate the efficacy of the proposed approaches.

Silicon Nitride Equation of State

NASA Astrophysics Data System (ADS)

Swaminathan, Pazhayannur; Brown, Robert

2015-06-01

This report presents the development a global, multi-phase equation of state (EOS) for the ceramic silicon nitride (Si3N4) . Structural forms include amorphous silicon nitride normally used as a thin film and three crystalline polymorphs. Crystalline phases include hexagonal α-Si3N4, hexagonalβ-Si3N4, and the cubic spinel c-Si3N4. Decomposition at about 1900 °C results in a liquid silicon phase and gas phase products such as molecular nitrogen, atomic nitrogen, and atomic silicon. The silicon nitride EOS was developed using EOSPro which is a new and extended version of the PANDA II code. Both codes are valuable tools and have been used successfully for a variety of material classes. Both PANDA II and EOSPro can generate a tabular EOS that can be used in conjunction with hydrocodes. The paper describes the development efforts for the component solid phases and presents results obtained using the EOSPro phase transition model to investigate the solid-solid phase transitions in relation to the available shock data. Furthermore, the EOSPro mixture model is used to develop a model for the decomposition products and then combined with the single component solid models to study the global phase diagram. Sponsored by the NASA Goddard Space Flight Center Living With a Star program office.

Nonlinear structural joint model updating based on instantaneous characteristics of dynamic responses

NASA Astrophysics Data System (ADS)

Wang, Zuo-Cai; Xin, Yu; Ren, Wei-Xin

2016-08-01

This paper proposes a new nonlinear joint model updating method for shear type structures based on the instantaneous characteristics of the decomposed structural dynamic responses. To obtain an accurate representation of a nonlinear system's dynamics, the nonlinear joint model is described as the nonlinear spring element with bilinear stiffness. The instantaneous frequencies and amplitudes of the decomposed mono-component are first extracted by the analytical mode decomposition (AMD) method. Then, an objective function based on the residuals of the instantaneous frequencies and amplitudes between the experimental structure and the nonlinear model is created for the nonlinear joint model updating. The optimal values of the nonlinear joint model parameters are obtained by minimizing the objective function using the simulated annealing global optimization method. To validate the effectiveness of the proposed method, a single-story shear type structure subjected to earthquake and harmonic excitations is simulated as a numerical example. Then, a beam structure with multiple local nonlinear elements subjected to earthquake excitation is also simulated. The nonlinear beam structure is updated based on the global and local model using the proposed method. The results show that the proposed local nonlinear model updating method is more effective for structures with multiple local nonlinear elements. Finally, the proposed method is verified by the shake table test of a real high voltage switch structure. The accuracy of the proposed method is quantified both in numerical and experimental applications using the defined error indices. Both the numerical and experimental results have shown that the proposed method can effectively update the nonlinear joint model.

Eastern Mediterranean Sea Spatial and Temporal Variability of Thermohaline Structure and Circulation Identified from Observational (T, S) Profiles

DTIC Science & Technology

2015-12-01

effect of Etesian winds between the late May and early October. Although they are generally dry, cool and moderate; they may turn into a windstorm...very significant to provide the realization of ocean modeling and prediction. The Optimal Spectral Decomposition (OSD) method is an effective ...represents the potential density, by differentiating this equation with respect to z and multiplying with the coriolis parameter f, conservation of

Excited electronic state decomposition mechanisms and dynamics of nitramine energetic materials and model systems

NASA Astrophysics Data System (ADS)

Greenfield, Margo

Energetic materials play an important role in aeronautics, the weapon industry, and the propellant industry due to their broad applications as explosives and fuels. RDX (1,3,5-trinitrohexahydro-s-triazine), HMX (octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine), and CL-20 (2,4,6,8,10,12-hexanitro-2,4,6,8,10,12-hexaazaisowurtzitane) are compounds which contain high energy density. Although RDX and HMX have been studied extensively over the past several decades a complete understanding of their decomposition mechanisms and dynamics is unknown. Time of flight mass spectroscopy (TOFMS) UV photodissociation (ns) experiments of gas phase RDX, HMX, and CL-20 generate the NO molecule as the initial decomposition product. Four different vibronic transitions of the initial decomposition product, the NO molecule, are observed: A2Sigma(upsilon'=0)←X 2pi(upsilon"=0,1,2,3). Simulations of the rovibronic intensities for the A←X transitions demonstrate that NO dissociated from RDX, HMX, and CL-20 is rotationally cold (˜20 K) and vibrationally hot (˜1800 K). Conversely, experiments on the five model systems (nitromethane, dimethylnitramine (DMNA), nitropyrrolidine, nitropiperidine and dinitropiperazine) produce rotationally hot and vibrationally cold spectra. Laser induced fluorescence (LIF) experiments are performed to rule out the possible decomposition product OH, generated along with NO, perhaps from the suggested HONO elimination mechanism. The OH radical is not observed in the fluorescence experiments, indicating the HONO decomposition intermediate is not an important pathway for the excited electronic state decomposition of cyclic nitramines. The NO molecule is also employed to measure the dynamics of the excited state decomposition. A 226 nm, 180 fs light pulse is utilized to photodissociate the gas phase systems. Stable ion states of DMNA and nitropyrrolidine are observed while the energetic materials and remaining model systems present the NO molecule as the only observed product. Pump-probe transients of the resonant A←X (0-0) transition of the NO molecule show a constant signal indicating these materials decompose faster than the time duration of the 226 nm laser light. Calculational results together with the experimental results indicate the energetic materials decompose through an internal conversion to very highly excited (˜5 eV of vibrational energy) vibrational states of their ground electronic state, while the model systems follow an excited electronic state decomposition pathway.

Quantitative analysis of microbial biomass yield in aerobic bioreactor.

PubMed

Watanabe, Osamu; Isoda, Satoru

2013-12-01

We have studied the integrated model of reaction rate equations with thermal energy balance in aerobic bioreactor for food waste decomposition and showed that the integrated model has the capability both of monitoring microbial activity in real time and of analyzing biodegradation kinetics and thermal-hydrodynamic properties. On the other hand, concerning microbial metabolism, it was known that balancing catabolic reactions with anabolic reactions in terms of energy and electron flow provides stoichiometric metabolic reactions and enables the estimation of microbial biomass yield (stoichiometric reaction model). We have studied a method for estimating real-time microbial biomass yield in the bioreactor during food waste decomposition by combining the integrated model with the stoichiometric reaction model. As a result, it was found that the time course of microbial biomass yield in the bioreactor during decomposition can be evaluated using the operational data of the bioreactor (weight of input food waste and bed temperature) by the combined model. The combined model can be applied to manage a food waste decomposition not only for controlling system operation to keep microbial activity stable, but also for producing value-added products such as compost on optimum condition. Copyright © 2013 The Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V. All rights reserved.

Thermal Decomposition Model Development of EN-7 and EN-8 Polyurethane Elastomers.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Keedy, Ryan Michael; Harrison, Kale Warren; Cordaro, Joseph Gabriel

Thermogravimetric analysis - gas chromatography/mass spectrometry (TGA- GC/MS) experiments were performed on EN-7 and EN-8, analyzed, and reported in [1] . This SAND report derives and describes pyrolytic thermal decomposition models for use in predicting the responses of EN-7 and EN-8 in an abnormal thermal environment.

Modelling the management of forest ecosystems: Importance of wood decomposition

Treesearch

Juan A. Blanco; Deborah S. Page-Dumroese; Martin F. Jurgensen; Michael P. Curran; Joanne M. Tirocke; Joanna Walitalo

2018-01-01

Scarce and uncertain data on woody debris decomposition rates are available for calibrating forest ecosystem models, owing to the difficulty of their empirical estimations. Using field data from three experimental sites which are part of the North American Long-Term Soil Productivity (LTSP) Study in south-eastern British Columbia (Canada), we developed probability...

A Novel Multilevel-SVD Method to Improve Multistep Ahead Forecasting in Traffic Accidents Domain.

PubMed

Barba, Lida; Rodríguez, Nibaldo

2017-01-01

Here is proposed a novel method for decomposing a nonstationary time series in components of low and high frequency. The method is based on Multilevel Singular Value Decomposition (MSVD) of a Hankel matrix. The decomposition is used to improve the forecasting accuracy of Multiple Input Multiple Output (MIMO) linear and nonlinear models. Three time series coming from traffic accidents domain are used. They represent the number of persons with injuries in traffic accidents of Santiago, Chile. The data were continuously collected by the Chilean Police and were weekly sampled from 2000:1 to 2014:12. The performance of MSVD is compared with the decomposition in components of low and high frequency of a commonly accepted method based on Stationary Wavelet Transform (SWT). SWT in conjunction with the Autoregressive model (SWT + MIMO-AR) and SWT in conjunction with an Autoregressive Neural Network (SWT + MIMO-ANN) were evaluated. The empirical results have shown that the best accuracy was achieved by the forecasting model based on the proposed decomposition method MSVD, in comparison with the forecasting models based on SWT.

A Novel Multilevel-SVD Method to Improve Multistep Ahead Forecasting in Traffic Accidents Domain

PubMed Central

Rodríguez, Nibaldo

2017-01-01

Here is proposed a novel method for decomposing a nonstationary time series in components of low and high frequency. The method is based on Multilevel Singular Value Decomposition (MSVD) of a Hankel matrix. The decomposition is used to improve the forecasting accuracy of Multiple Input Multiple Output (MIMO) linear and nonlinear models. Three time series coming from traffic accidents domain are used. They represent the number of persons with injuries in traffic accidents of Santiago, Chile. The data were continuously collected by the Chilean Police and were weekly sampled from 2000:1 to 2014:12. The performance of MSVD is compared with the decomposition in components of low and high frequency of a commonly accepted method based on Stationary Wavelet Transform (SWT). SWT in conjunction with the Autoregressive model (SWT + MIMO-AR) and SWT in conjunction with an Autoregressive Neural Network (SWT + MIMO-ANN) were evaluated. The empirical results have shown that the best accuracy was achieved by the forecasting model based on the proposed decomposition method MSVD, in comparison with the forecasting models based on SWT. PMID:28261267

Application of Mortar Coupling in Multiscale Modelling of Coupled Flow, Transport, and Biofilm Growth in Porous Media

NASA Astrophysics Data System (ADS)

Laleian, A.; Valocchi, A. J.; Werth, C. J.

2017-12-01

Multiscale models of reactive transport in porous media are capable of capturing complex pore-scale processes while leveraging the efficiency of continuum-scale models. In particular, porosity changes caused by biofilm development yield complex feedbacks between transport and reaction that are difficult to quantify at the continuum scale. Pore-scale models, needed to accurately resolve these dynamics, are often impractical for applications due to their computational cost. To address this challenge, we are developing a multiscale model of biofilm growth in which non-overlapping regions at pore and continuum spatial scales are coupled with a mortar method providing continuity at interfaces. We explore two decompositions of coupled pore-scale and continuum-scale regions to study biofilm growth in a transverse mixing zone. In the first decomposition, all reaction is confined to a pore-scale region extending the transverse mixing zone length. Only solute transport occurs in the surrounding continuum-scale regions. Relative to a fully pore-scale result, we find the multiscale model with this decomposition has a reduced run time and consistent result in terms of biofilm growth and solute utilization. In the second decomposition, reaction occurs in both an up-gradient pore-scale region and a down-gradient continuum-scale region. To quantify clogging, the continuum-scale model implements empirical relations between porosity and continuum-scale parameters, such as permeability and the transverse dispersion coefficient. Solutes are sufficiently mixed at the end of the pore-scale region, such that the initial reaction rate is accurately computed using averaged concentrations in the continuum-scale region. Relative to a fully pore-scale result, we find accuracy of biomass growth in the multiscale model with this decomposition improves as the interface between pore-scale and continuum-scale regions moves downgradient where transverse mixing is more fully developed. Also, this decomposition poses additional challenges with respect to mortar coupling. We explore these challenges and potential solutions. While recent work has demonstrated growing interest in multiscale models, further development is needed for their application to field-scale subsurface contaminant transport and remediation.

Examining responses of ecosystem carbon exchange to environmental changes using particle filtering mathod

NASA Astrophysics Data System (ADS)

Yokozawa, M.

2017-12-01

Attention has been paid to the agricultural field that could regulate ecosystem carbon exchange by water management and residual treatments. However, there have been less known about the dynamic responses of the ecosystem to environmental changes. In this study, focussing on paddy field, where CO2 emissions due to microbial decomposition of organic matter are suppressed and alternatively CH4 emitted under flooding condition during rice growth season and subsequently CO2 emission following the fallow season after harvest, the responses of ecosystem carbon exchange were examined. We conducted model data fusion analysis for examining the response of cropland-atmosphere carbon exchange to environmental variation. The used model consists of two sub models, paddy rice growth sub-model and soil decomposition sub-model. The crop growth sub-model mimics the rice plant growth processes including formation of reproductive organs as well as leaf expansion. The soil decomposition sub-model simulates the decomposition process of soil organic carbon. Assimilating the data on the time changes in CO2 flux measured by eddy covariance method, rice plant biomass, LAI and the final yield with the model, the parameters were calibrated using a stochastic optimization algorithm with a particle filter method. The particle filter method, which is one of the Monte Carlo filters, enable us to evaluating time changes in parameters based on the observed data until the time and to make prediction of the system. Iterative filtering and prediction with changing parameters and/or boundary condition enable us to obtain time changes in parameters governing the crop production as well as carbon exchange. In this study, we focused on the parameters related to crop production as well as soil carbon storage. As the results, the calibrated model with estimated parameters could accurately predict the NEE flux in the subsequent years. The temperature sensitivity, denoted by Q10s in the decomposition rate of soil organic carbon (SOC) were obtained as 1.4 for no cultivation period and 2.9 for cultivation period (submerged soil condition in flooding season). It suggests that the response of ecosystem carbon exchange differs due to SOC decomposition process which is sensitive to environmental variation during paddy rice cultivation period.

Toward a reaction rate model of condensed-phase RDX decomposition under high temperatures

NASA Astrophysics Data System (ADS)

Schweigert, Igor

2014-03-01

Shock ignition of energetic molecular solids is driven by microstructural heterogeneities, at which even moderate stresses can result in sufficiently high temperatures to initiate material decomposition and the release of the chemical energy. Mesoscale modeling of these ``hot spots'' requires a chemical reaction rate model that describes the energy release with a sub-microsecond resolution and under a wide range of temperatures. No such model is available even for well-studied energetic materials such as RDX. In this presentation, I will describe an ongoing effort to develop a reaction rate model of condensed-phase RDX decomposition under high temperatures using first-principles molecular dynamics, transition-state theory, and reaction network analysis. This work was supported by the Naval Research Laboratory, by the Office of Naval Research, and by the DOD High Performance Computing Modernization Program Software Application Institute for Multiscale Reactive Modeling of Insensitive Munitions.

Toward a reaction rate model of condensed-phase RDX decomposition under high temperatures

NASA Astrophysics Data System (ADS)

Schweigert, Igor

2015-06-01

Shock ignition of energetic molecular solids is driven by microstructural heterogeneities, at which even moderate stresses can result in sufficiently high temperatures to initiate material decomposition and chemical energy release. Mesoscale modeling of these ``hot spots'' requires a reaction rate model that describes the energy release with a sub-microsecond resolution and under a wide range of temperatures. No such model is available even for well-studied energetic materials such as RDX. In this presentation, I will describe an ongoing effort to develop a reaction rate model of condensed-phase RDX decomposition under high temperatures using first-principles molecular dynamics, transition-state theory, and reaction network analysis. This work was supported by the Naval Research Laboratory, by the Office of Naval Research, and by the DoD High Performance Computing Modernization Program Software Application Institute for Multiscale Reactive Modeling of Insensitive Munitions.

Automating CPM-GOMS

NASA Technical Reports Server (NTRS)

John, Bonnie; Vera, Alonso; Matessa, Michael; Freed, Michael; Remington, Roger

2002-01-01

CPM-GOMS is a modeling method that combines the task decomposition of a GOMS analysis with a model of human resource usage at the level of cognitive, perceptual, and motor operations. CPM-GOMS models have made accurate predictions about skilled user behavior in routine tasks, but developing such models is tedious and error-prone. We describe a process for automatically generating CPM-GOMS models from a hierarchical task decomposition expressed in a cognitive modeling tool called Apex. Resource scheduling in Apex automates the difficult task of interleaving the cognitive, perceptual, and motor resources underlying common task operators (e.g. mouse move-and-click). Apex's UI automatically generates PERT charts, which allow modelers to visualize a model's complex parallel behavior. Because interleaving and visualization is now automated, it is feasible to construct arbitrarily long sequences of behavior. To demonstrate the process, we present a model of automated teller interactions in Apex and discuss implications for user modeling. available to model human users, the Goals, Operators, Methods, and Selection (GOMS) method [6, 21] has been the most widely used, providing accurate, often zero-parameter, predictions of the routine performance of skilled users in a wide range of procedural tasks [6, 13, 15, 27, 28]. GOMS is meant to model routine behavior. The user is assumed to have methods that apply sequences of operators and to achieve a goal. Selection rules are applied when there is more than one method to achieve a goal. Many routine tasks lend themselves well to such decomposition. Decomposition produces a representation of the task as a set of nested goal states that include an initial state and a final state. The iterative decomposition into goals and nested subgoals can terminate in primitives of any desired granularity, the choice of level of detail dependent on the predictions required. Although GOMS has proven useful in HCI, tools to support the construction of GOMS models have not yet come into general use.

Recovering hidden diagonal structures via non-negative matrix factorization with multiple constraints.

PubMed

Yang, Xi; Han, Guoqiang; Cai, Hongmin; Song, Yan

2017-03-31

Revealing data with intrinsically diagonal block structures is particularly useful for analyzing groups of highly correlated variables. Earlier researches based on non-negative matrix factorization (NMF) have been shown to be effective in representing such data by decomposing the observed data into two factors, where one factor is considered to be the feature and the other the expansion loading from a linear algebra perspective. If the data are sampled from multiple independent subspaces, the loading factor would possess a diagonal structure under an ideal matrix decomposition. However, the standard NMF method and its variants have not been reported to exploit this type of data via direct estimation. To address this issue, a non-negative matrix factorization with multiple constraints model is proposed in this paper. The constraints include an sparsity norm on the feature matrix and a total variational norm on each column of the loading matrix. The proposed model is shown to be capable of efficiently recovering diagonal block structures hidden in observed samples. An efficient numerical algorithm using the alternating direction method of multipliers model is proposed for optimizing the new model. Compared with several benchmark models, the proposed method performs robustly and effectively for simulated and real biological data.

DECOMP: a PDB decomposition tool on the web.

PubMed

Ordog, Rafael; Szabadka, Zoltán; Grolmusz, Vince

2009-07-27

The protein databank (PDB) contains high quality structural data for computational structural biology investigations. We have earlier described a fast tool (the decomp_pdb tool) for identifying and marking missing atoms and residues in PDB files. The tool also automatically decomposes PDB entries into separate files describing ligands and polypeptide chains. Here, we describe a web interface named DECOMP for the tool. Our program correctly identifies multi-monomer ligands, and the server also offers the preprocessed ligand-protein decomposition of the complete PDB for downloading (up to size: 5GB) AVAILABILITY: http://decomp.pitgroup.org.