Near infrared spectroscopy for determination of various physical, chemical and biochemical properties in Mediterranean soils.

PubMed

Zornoza, R; Guerrero, C; Mataix-Solera, J; Scow, K M; Arcenegui, V; Mataix-Beneyto, J

2008-07-01

The potential of near infrared (NIR) reflectance spectroscopy to predict various physical, chemical and biochemical properties in Mediterranean soils from SE Spain was evaluated. Soil samples (n=393) were obtained by sampling thirteen locations during three years (2003-2005 period). These samples had a wide range of soil characteristics due to variations in land use, vegetation cover and specific climatic conditions. Biochemical properties also included microbial biomarkers based on phospholipid fatty acids (PLFA). Partial least squares (PLS) regression with cross validation was used to establish relationships between the NIR spectra and the reference data from physical, chemical and biochemical analyses. Based on the values of coefficient of determination (r(2)) and the ratio of standard deviation of validation set to root mean square error of cross validation (RPD), predicted results were evaluated as excellent (r(2)>0.90 and RPD>3) for soil organic carbon, Kjeldahl nitrogen, soil moisture, cation exchange capacity, microbial biomass carbon, basal soil respiration, acid phosphatase activity, β-glucosidase activity and PLFA biomarkers for total bacteria, Gram positive bacteria, actinomycetes, vesicular-arbuscular mycorrhizal fungi and total PLFA biomass. Good predictions (0.81

Physical Properties of Low-Molecular Weight Polydimethylsiloxane Fluids

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

Roberts, Christine Cardinal; Graham, Alan; Nemer, Martin

Physical property measurements including viscosity, density, thermal conductivity, and heat capacity of low-molecular weight polydimethylsiloxane (PDMS) fluids were measured over a wide temperature range (-50°C to 150°C when possible). Properties of blends of 1 cSt and 20 cSt PDMS fluids were also investigated. Uncertainties in the measurements are cited. These measurements will provide greater fidelity predictions of environmental sensing device behavior in hot and cold environments.

Predicting the Coupling Properties of Axially-Textured Materials

PubMed Central

Fuentes-Cobas, Luis E.; Muñoz-Romero, Alejandro; Montero-Cabrera, María E.; Fuentes-Montero, Luis; Fuentes-Montero, María E.

2013-01-01

A description of methods and computer programs for the prediction of “coupling properties” in axially-textured polycrystals is presented. Starting data are the single-crystal properties, texture and stereography. The validity and proper protocols for applying the Voigt, Reuss and Hill approximations to estimate coupling properties effective values is analyzed. Working algorithms for predicting mentioned averages are given. Bunge’s symmetrized spherical harmonics expansion of orientation distribution functions, inverse pole figures and (single and polycrystals) physical properties is applied in all stages of the proposed methodology. The established mathematical route has been systematized in a working computer program. The discussion of piezoelectricity in a representative textured ferro-piezoelectric ceramic illustrates the application of the proposed methodology. Polycrystal coupling properties, predicted by the suggested route, are fairly close to experimentally measured ones. PMID:28788370

Characterizing scale- and location-dependent correlation of water retention parameters with soil physical properties using wavelet techniques.

PubMed

Shu, Qiaosheng; Liu, Zuoxin; Si, Bingcheng

2008-01-01

Understanding the correlation between soil hydraulic parameters and soil physical properties is a prerequisite for the prediction of soil hydraulic properties from soil physical properties. The objective of this study was to examine the scale- and location-dependent correlation between two water retention parameters (alpha and n) in the van Genuchten (1980) function and soil physical properties (sand content, bulk density [Bd], and organic carbon content) using wavelet techniques. Soil samples were collected from a transect from Fuxin, China. Soil water retention curves were measured, and the van Genuchten parameters were obtained through curve fitting. Wavelet coherency analysis was used to elucidate the location- and scale-dependent relationships between these parameters and soil physical properties. Results showed that the wavelet coherence between alpha and sand content was significantly different from red noise at small scales (8-20 m) and from a distance of 30 to 470 m. Their wavelet phase spectrum was predominantly out of phase, indicating negative correlation between these two variables. The strong negative correlation between alpha and Bd existed mainly at medium scales (30-80 m). However, parameter n had a strong positive correlation only with Bd at scales between 20 and 80 m. Neither of the two retention parameters had significant wavelet coherency with organic carbon content. These results suggested that location-dependent scale analyses are necessary to improve the performance for soil water retention characteristic predictions.

Estimation of the viscosities of liquid binary alloys

NASA Astrophysics Data System (ADS)

Wu, Min; Su, Xiang-Yu

2018-01-01

As one of the most important physical and chemical properties, viscosity plays a critical role in physics and materials as a key parameter to quantitatively understanding the fluid transport process and reaction kinetics in metallurgical process design. Experimental and theoretical studies on liquid metals are problematic. Today, there are many empirical and semi-empirical models available with which to evaluate the viscosity of liquid metals and alloys. However, the parameter of mixed energy in these models is not easily determined, and most predictive models have been poorly applied. In the present study, a new thermodynamic parameter Δ G is proposed to predict liquid alloy viscosity. The prediction equation depends on basic physical and thermodynamic parameters, namely density, melting temperature, absolute atomic mass, electro-negativity, electron density, molar volume, Pauling radius, and mixing enthalpy. Our results show that the liquid alloy viscosity predicted using the proposed model is closely in line with the experimental values. In addition, if the component radius difference is greater than 0.03 nm at a certain temperature, the atomic size factor has a significant effect on the interaction of the binary liquid metal atoms. The proposed thermodynamic parameter Δ G also facilitates the study of other physical properties of liquid metals.

A Combined Experimental and Computational Study on Selected Physical Properties of Aminosilicones

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

Perry, RJ; Genovese, SE; Farnum, RL

2014-01-29

A number of physical properties of aminosilicones have been determined experimentally and predicted computationally. It was found that COSMO-RS predicted the densities of the materials under study to within about 4% of the experimentally determined values. Vapor pressure measurements were performed, and all of the aminosilicones of interest were found to be significantly less volatile than the benchmark MEA material. COSMO-RS was reasonably accurate for predicting the vapor pressures for aminosilicones that were thermally stable. The heat capacities of all aminosilicones tested were between 2.0 and 2.3 J/(g.degrees C); again substantially lower than a benchmark 30% aqueous MEA solution. Surfacemore » energies for the aminosilicones were found to be 23.3-28.3 dyne/cm and were accurately predicted using the parachor method.« less

Integrating sequence stratigraphy and rock-physics to interpret seismic amplitudes and predict reservoir quality

NASA Astrophysics Data System (ADS)

Dutta, Tanima

This dissertation focuses on the link between seismic amplitudes and reservoir properties. Prediction of reservoir properties, such as sorting, sand/shale ratio, and cement-volume from seismic amplitudes improves by integrating knowledge from multiple disciplines. The key contribution of this dissertation is to improve the prediction of reservoir properties by integrating sequence stratigraphy and rock physics. Sequence stratigraphy has been successfully used for qualitative interpretation of seismic amplitudes to predict reservoir properties. Rock physics modeling allows quantitative interpretation of seismic amplitudes. However, often there is uncertainty about selecting geologically appropriate rock physics model and its input parameters, away from the wells. In the present dissertation, we exploit the predictive power of sequence stratigraphy to extract the spatial trends of sedimentological parameters that control seismic amplitudes. These spatial trends of sedimentological parameters can serve as valuable constraints in rock physics modeling, especially away from the wells. Consequently, rock physics modeling, integrated with the trends from sequence stratigraphy, become useful for interpreting observed seismic amplitudes away from the wells in terms of underlying sedimentological parameters. We illustrate this methodology using a comprehensive dataset from channelized turbidite systems, deposited in minibasin settings in the offshore Equatorial Guinea, West Africa. First, we present a practical recipe for using closed-form expressions of effective medium models to predict seismic velocities in unconsolidated sandstones. We use an effective medium model that combines perfectly rough and smooth grains (the extended Walton model), and use that model to derive coordination number, porosity, and pressure relations for P and S wave velocities from experimental data. Our recipe provides reasonable fits to other experimental and borehole data, and specifically improves the predictions of shear wave velocities. In addition, we provide empirical relations on normal compaction depth trends of porosity, velocities, and VP/VS ratio for shale and clean sands in shallow, supra-salt sediments in the Gulf of Mexico. Next, we identify probable spatial trends of sand/shale ratio and sorting as predicted by the conventional sequence stratigraphic model in minibasin settings (spill-and-fill model). These spatial trends are evaluated using well data from offshore West Africa, and the same well data are used to calibrate rock physics models (modified soft-sand model) that provide links between P-impedance and quartz/clay ratio, and sorting. The spatial increase in sand/shale ratio and sorting corresponds to an overall increase in P-impedance, and AVO intercept and gradient. The results are used as a guide to interpret sedimentological parameters from seismic attributes, away from the well locations. We present a quantitative link between carbonate cement and seismic attributes by combining stratigraphie cycles and the rock physics model (modified differential effective medium model). The variation in carbonate cement volume in West Africa can be linked with two distinct stratigraphic cycles: the coarsening-upward cycles and the fining-upward cycles. Cemented sandstones associated with these cycles exhibit distinct signatures on P-impedance vs. porosity and AVO intercept vs. gradient crossplots. These observations are important for assessing reservoir properties in the West Africa as well as in other analogous depositional environments. Finally, we investigate the relationship between seismic velocities and time temperature index (TTI) using basin and petroleum system modeling at Rio Muni basin, West Africa. We find that both VP and VS increase exponentially with TTI. The results can be applied to predict TTI, and thereby thermal maturity, from observed velocities.

Prediction of the physical properties of barium titanates using an artificial neural network

NASA Astrophysics Data System (ADS)

Al-Jabar, Ahmed Jaafar Abed; Al-dujaili, Mohammed Assi Ahmed; Al-hydary, Imad Ali Disher

2017-04-01

Barium titanate is one of the most important ceramics amongst those that are widely used in the electronic industry because of their dielectric properties. These properties are related to the physical properties of the material, namely, the density and the porosity. Thus, the prediction of these properties is highly desirable. The aim of the current work is to develop models that can predict the density, porosity, firing shrinkage, and the green density of barium titanate BaTiO3. An artificial neural network was used to fulfill this aim. The modified pechini method was used to prepare barium titanate powders with five different particle size distributions. Eighty samples were prepared using different processing parameters including the pressing rate, pressing pressure, heating rate, sintering temperature, and soaking time. In the artificial neural network (ANN) model, the experimental data set consisted of these 80 samples, 70 samples were used for training the network and 10 samples were employed for testing. A comparison was made between the experimental and the predicted data. Good performance of the ANN model was achieved, in which the results showed that the mean error for the density, porosity, shrinkage, and green density are 0.02, 0.06, 0.04, and 0.002, respectively.

Prediction of hole expansion ratio for various steel sheets based on uniaxial tensile properties

NASA Astrophysics Data System (ADS)

Kim, Jae Hyung; Kwon, Young Jin; Lee, Taekyung; Lee, Kee-Ahn; Kim, Hyoung Seop; Lee, Chong Soo

2018-01-01

Stretch-flangeability is one of important formability parameters of thin steel sheets used in the automotive industry. There have been many attempts to predict hole expansion ratio (HER), a typical term to evaluate stretch-flangeability, using uniaxial tensile properties for convenience. This paper suggests a new approach that uses total elongation and average normal anisotropy to predict HER of thin steel sheets. The method provides a good linear relationship between HER of the machined hole and the predictive variables in a variety of materials with different microstructures obtained using different processing methods. The HER of the punched hole was also well predicted using the similar approach, which reflected only the portion of post uniform elongation. The physical meaning drawn by our approach successfully explained the poor HER of austenitic steels despite their considerable elongation. The proposed method to predict HER is simple and cost-effective, so it will be useful in industry. In addition, the model provides a physical explanation of HER, so it will be useful in academia.

Thermophysical properties of fluids: dynamic viscosity and thermal conductivity

NASA Astrophysics Data System (ADS)

Latini, G.

2017-11-01

Thermophysical properties of fluids strongly depend upon atomic and molecular structure, complex systems governed by physics laws providing the time evolution. Theoretically the knowledge of the initial position and velocity of each atom, of the interaction forces and of the boundary conditions, leads to the solution; actually this approach contains too many variables and it is generally impossible to obtain an acceptable solution. In many cases it is only possible to calculate or to measure some macroscopic properties of fluids (pressure, temperature, molar volume, heat capacities...). The ideal gas “law,” PV = nRT, was one of the first important correlations of properties and the deviations from this law for real gases were usefully proposed. Moreover the statistical mechanics leads for example to the “hard-sphere” model providing the link between the transport properties and the molecular size and speed of the molecules. Further approximations take into account the intermolecular interactions (the potential functions) which can be used to describe attractions and repulsions. In any case thermodynamics reduces experimental or theoretical efforts by relating one physical property to another: the Clausius-Clapeyron equation provides a classical example of this method and the PVT function must be known accurately. However, in spite of the useful developments in molecular theory and computers technology, often it is usual to search for physical properties when the existing theories are not reliable and experimental data are not available: the required value of the physical or thermophysical property must be estimated or predicted (very often estimation and prediction are improperly used as synonymous). In some cases empirical correlations are useful, if it is clearly defined the range of conditions on which they are based. This work is concerned with dynamic viscosity µ and thermal conductivity λ and is based on clear and important rules to be respected when a prediction or estimation method is proposed.

Model of cohesive properties and structural phase transitions in non-metallic solids

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

Majewski, J.A.; Vogl, P.

1986-01-01

We have developed a simple, yet microscopic and universal model for cohesive properties of solids. This model explains the physical mechanisms determining the chemical and predicts semiquantitatively static and dynamic cohesive properties. It predicts a substantial softening of the long-wavelength transverse optical phonons across the pressure induced phase transition from the zincblenda to rocksalt structure in II-VI compounds. The origin of this softening is shown to be closely related to ferroelectricity.

Solid harmonic wavelet scattering for predictions of molecule properties

NASA Astrophysics Data System (ADS)

Eickenberg, Michael; Exarchakis, Georgios; Hirn, Matthew; Mallat, Stéphane; Thiry, Louis

2018-06-01

We present a machine learning algorithm for the prediction of molecule properties inspired by ideas from density functional theory (DFT). Using Gaussian-type orbital functions, we create surrogate electronic densities of the molecule from which we compute invariant "solid harmonic scattering coefficients" that account for different types of interactions at different scales. Multilinear regressions of various physical properties of molecules are computed from these invariant coefficients. Numerical experiments show that these regressions have near state-of-the-art performance, even with relatively few training examples. Predictions over small sets of scattering coefficients can reach a DFT precision while being interpretable.

Thermal barrier coating life prediction model development, phase 2

NASA Technical Reports Server (NTRS)

Meier, Susan Manning; Sheffler, Keith D.; Nissley, David M.

1991-01-01

The objective of this program was to generate a life prediction model for electron-beam-physical vapor deposited (EB-PVD) zirconia thermal barrier coating (TBC) on gas turbine engine components. Specific activities involved in development of the EB-PVD life prediction model included measurement of EB-PVD ceramic physical and mechanical properties and adherence strength, measurement of the thermally grown oxide (TGO) growth kinetics, generation of quantitative cyclic thermal spallation life data, and development of a spallation life prediction model. Life data useful for model development was obtained by exposing instrumented, EB-PVD ceramic coated cylindrical specimens in a jet fueled burner rig. Monotonic compression and tensile mechanical tests and physical property tests were conducted to obtain the EB-PVD ceramic behavior required for burner rig specimen analysis. As part of that effort, a nonlinear constitutive model was developed for the EB-PVD ceramic. Spallation failure of the EB-PVD TBC system consistently occurred at the TGO-metal interface. Calculated out-of-plane stresses were a small fraction of that required to statically fail the TGO. Thus, EB-PVD spallation was attributed to the interfacial cracking caused by in-plane TGO strains. Since TGO mechanical properties were not measured in this program, calculation of the burner rig specimen TGO in-plane strains was performed by using alumina properties. A life model based on maximum in-plane TGO tensile mechanical strain and TGO thickness correlated the burner rig specimen EB-PVD ceramic spallation lives within a factor of about plus or minus 2X.

Peer-to-Peer Instruction with Interactive Demonstrations in Upper Level Astronomy Courses

NASA Astrophysics Data System (ADS)

Gelderman, Richard

2013-06-01

Spectral and polarization properties of light are topics that most intro physics courses barely touch. Students therefore rarely have any useful experience to draw on when those topics come up in an upper level astronomy class. This means that they approach problems dealing with spectra or polarization as plug-and-chug mathematics applications, devoid of physical context. We have been addressing such dilemmas by using interactive demonstrations in the lecture meeting to give students direct experience with polarization filters, diffraction gratings, spectral sources, and situations requiring them to analyze sources based on the observed polarization of spectral properties. Each student individually predicts the outcomes for a demonstration. Students then collaborate within in a group of three to discuss their prediction, reporting the group’s consensus prediction. After observing the demonstration, students in the group compare their predictions to the results, and attempt to explain the phenomena. Based on curricular reforms in physics education, these methods have provided our students with the ability to much more than just manipulate equations related to spectroscopic and polarization analysis.

Weight, Volume, and Physical Properties of Major Hardwood Species in the Gulf and Atlantic Coastal Plains

Treesearch

Alexander Clark; Douglas R. Phillips; Douglas J. Frederick

1985-01-01

The weight, volume, and physical properties of trees 1 to 20 inches d.b.h. were determined for green ash, blackgum, red maple, sweetgum, water tupelo, yellow-poplar, hickory, laurel oak, water oak, and white oak in the Gulf and Atlantic Coastal Plains. Hard hardwood, soft hardwood, and individual species equations are presented for predicting green and dry weight...

DATA ASSIMILATION APPROACH FOR FORECAST OF SOLAR ACTIVITY CYCLES

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

Kitiashvili, Irina N., E-mail: irina.n.kitiashvili@nasa.gov

Numerous attempts to predict future solar cycles are mostly based on empirical relations derived from observations of previous cycles, and they yield a wide range of predicted strengths and durations of the cycles. Results obtained with current dynamo models also deviate strongly from each other, thus raising questions about criteria to quantify the reliability of such predictions. The primary difficulties in modeling future solar activity are shortcomings of both the dynamo models and observations that do not allow us to determine the current and past states of the global solar magnetic structure and its dynamics. Data assimilation is a relativelymore » new approach to develop physics-based predictions and estimate their uncertainties in situations where the physical properties of a system are not well-known. This paper presents an application of the ensemble Kalman filter method for modeling and prediction of solar cycles through use of a low-order nonlinear dynamo model that includes the essential physics and can describe general properties of the sunspot cycles. Despite the simplicity of this model, the data assimilation approach provides reasonable estimates for the strengths of future solar cycles. In particular, the prediction of Cycle 24 calculated and published in 2008 is so far holding up quite well. In this paper, I will present my first attempt to predict Cycle 25 using the data assimilation approach, and discuss the uncertainties of that prediction.« less

Flow properties of suspensions rich in solids

NASA Technical Reports Server (NTRS)

Armstrong, W. P.; Gay, E. C.; Nelson, P. A.

1969-01-01

Mathematical evaluation of flow properties of fluids carrying high concentrations of solids in suspension relates suspension viscosity to physical properties of the solids and liquids, and provides a means for predicting flow behavior. A technique for calculating a suspensions flow rates is applicable to the design of pipelines.

The Influence of Fuelbed Physical Properties on Biomass Burning Emissions

NASA Astrophysics Data System (ADS)

Urbanski, S. P.; Lincoln, E.; Baker, S. P.; Richardson, M.

2014-12-01

Emissions from biomass fires can significantly degrade regional air quality and therefore are of major concern to air regulators and land managers in the U.S. and Canada. Accurately estimating emissions from different fire types in various ecosystems is crucial to predicting and mitigating the impact of fires on air quality. The physical properties of ecosystems' fuelbeds can heavily influence the combustion processes (e.g. flaming or smoldering) and the resultant emissions. However, despite recent progress in characterizing the composition of biomass smoke, significant knowledge gaps remain regarding the linkage between basic fuelbed physical properties and emissions. In laboratory experiments we examined the effects of fuelbed properties on combustion efficiency (CE) and emissions for an important fuel component of temperate and boreal forests - conifer needles. The bulk density (BD), depth (DZ), and moisture content (MC) of Ponderosa Pine needle fuelbeds were manipulated in 75 burns for which gas and particle emissions were measured. We found CE was negatively correlated with BD, DZ and MC and that the emission factors of species associated with smoldering combustion processes (CO, CH4, particles) were positively correlated with these fuelbed properties. The study indicates the physical properties of conifer needle fuelbeds have a significant effect on CE and hence emissions. However, many of the emission models used to predict and manage smoke impacts on air quality assume conifer litter burns by flaming combustion with a high CE and correspondingly low emissions of CO, CH4, particles, and organic compounds. Our results suggest emission models underestimate emissions from fires involving a large component of conifer needles. Additionally, our findings indicate that laboratory studies of emissions should carefully control fuelbed physical properties to avoid confounding effects that may obscure the effects being tested and lead to erroneous interpretations.

Universal structural parameter to quantitatively predict metallic glass properties

DOE PAGES

Ding, Jun; Cheng, Yong-Qiang; Sheng, Howard; ...

2016-12-12

Quantitatively correlating the amorphous structure in metallic glasses (MGs) with their physical properties has been a long-sought goal. Here we introduce flexibility volume' as a universal indicator, to bridge the structural state the MG is in with its properties, on both atomic and macroscopic levels. The flexibility volume combines static atomic volume with dynamics information via atomic vibrations that probe local configurational space and interaction between neighbouring atoms. We demonstrate that flexibility volume is a physically appropriate parameter that can quantitatively predict the shear modulus, which is at the heart of many key properties of MGs. Moreover, the new parametermore » correlates strongly with atomic packing topology, and also with the activation energy for thermally activated relaxation and the propensity for stress-driven shear transformations. These correlations are expected to be robust across a very wide range of MG compositions, processing conditions and length scales.« less

Blind test of physics-based prediction of protein structures.

PubMed

Shell, M Scott; Ozkan, S Banu; Voelz, Vincent; Wu, Guohong Albert; Dill, Ken A

2009-02-01

We report here a multiprotein blind test of a computer method to predict native protein structures based solely on an all-atom physics-based force field. We use the AMBER 96 potential function with an implicit (GB/SA) model of solvation, combined with replica-exchange molecular-dynamics simulations. Coarse conformational sampling is performed using the zipping and assembly method (ZAM), an approach that is designed to mimic the putative physical routes of protein folding. ZAM was applied to the folding of six proteins, from 76 to 112 monomers in length, in CASP7, a community-wide blind test of protein structure prediction. Because these predictions have about the same level of accuracy as typical bioinformatics methods, and do not utilize information from databases of known native structures, this work opens up the possibility of predicting the structures of membrane proteins, synthetic peptides, or other foldable polymers, for which there is little prior knowledge of native structures. This approach may also be useful for predicting physical protein folding routes, non-native conformations, and other physical properties from amino acid sequences.

Blind Test of Physics-Based Prediction of Protein Structures

PubMed Central

Shell, M. Scott; Ozkan, S. Banu; Voelz, Vincent; Wu, Guohong Albert; Dill, Ken A.

2009-01-01

We report here a multiprotein blind test of a computer method to predict native protein structures based solely on an all-atom physics-based force field. We use the AMBER 96 potential function with an implicit (GB/SA) model of solvation, combined with replica-exchange molecular-dynamics simulations. Coarse conformational sampling is performed using the zipping and assembly method (ZAM), an approach that is designed to mimic the putative physical routes of protein folding. ZAM was applied to the folding of six proteins, from 76 to 112 monomers in length, in CASP7, a community-wide blind test of protein structure prediction. Because these predictions have about the same level of accuracy as typical bioinformatics methods, and do not utilize information from databases of known native structures, this work opens up the possibility of predicting the structures of membrane proteins, synthetic peptides, or other foldable polymers, for which there is little prior knowledge of native structures. This approach may also be useful for predicting physical protein folding routes, non-native conformations, and other physical properties from amino acid sequences. PMID:19186130

Effects of physical aging on long-term behavior of composites

NASA Technical Reports Server (NTRS)

Brinson, L. Catherine

1993-01-01

The HSCT plane, envisioned to have a lifetime of over 60,000 flight hours and to travel at speeds in excess of Mach 2, is the source of intensive study at NASA. In particular, polymer matrix composites are being strongly considered for use in primary and secondary structures due to their high strength to weight ratio and the options of property tailoring. However, an added difficulty in the use of polymer based materials is that their properties change significantly over time, especially at the elevated temperatures that will be experienced during flight, and prediction of properties based on irregular thermal and mechanical loading is extremely difficult. This study focused on one aspect of long-term polymer composite behavior: physical aging. When a polymer is cooled to below its glass transition temperature, the material is not in thermodynamic equilibrium and the free volume and enthalpy evolve over time to approach their equilibrium values. During this time, the mechanical properties change significantly and this change is termed physical aging. This work begins with a review of the concepts of physical aging on a pure polymer system. The effective time theory, which can be used to predict long term behavior based on short term data, is mathematically formalized. The effects of aging to equilibrium are proven and discussed. The theory developed for polymers is then applied first to a unidirectional composite, then to a general laminate. Comparison to experimental data is excellent. It is shown that the effects of aging on the long-term properties of composites can be counter-intuitive, stressing the importance of the development and use of a predictive theory to analyze structures.

Temperature and pressure dependent structural and thermo-physical properties of quaternary CoVTiAl alloy

NASA Astrophysics Data System (ADS)

Yousuf, Saleem; Gupta, Dinesh C.

2017-09-01

Investigation of band structure and thermo-physical response of new quaternary CoVTiAl Heusler alloy within the frame work of density functional theory has been analyzed. 100% spin polarization with ferromagnetic stable ground state at the optimized lattice parameter of 6.01 Å is predicted for the compound. Slater-Pauling rule for the total magnetic moment of 3 μB and an indirect semiconducting behavior is also seen for the compound. In order to perfectly analyze the thermo-physical response, the lattice thermal conductivity and thermodynamic properties have been calculated. Thermal effects on some macroscopic properties of CoVTiAl are predicted using the quasi-harmonic Debye model, in which the lattice vibrations are taken into account. The variations of the lattice constant, volume expansion coefficient, heat capacities, and Debye temperature with pressure and temperature in the ranges of 0 GPa to 15 GPa and 0 K to 800 K have been obtained.

3D Printed Organ Models with Physical Properties of Tissue and Integrated Sensors.

PubMed

Qiu, Kaiyan; Zhao, Zichen; Haghiashtiani, Ghazaleh; Guo, Shuang-Zhuang; He, Mingyu; Su, Ruitao; Zhu, Zhijie; Bhuiyan, Didarul B; Murugan, Paari; Meng, Fanben; Park, Sung Hyun; Chu, Chih-Chang; Ogle, Brenda M; Saltzman, Daniel A; Konety, Badrinath R; Sweet, Robert M; McAlpine, Michael C

2018-03-01

The design and development of novel methodologies and customized materials to fabricate patient-specific 3D printed organ models with integrated sensing capabilities could yield advances in smart surgical aids for preoperative planning and rehearsal. Here, we demonstrate 3D printed prostate models with physical properties of tissue and integrated soft electronic sensors using custom-formulated polymeric inks. The models show high quantitative fidelity in static and dynamic mechanical properties, optical characteristics, and anatomical geometries to patient tissues and organs. The models offer tissue-mimicking tactile sensation and behavior and thus can be used for the prediction of organ physical behavior under deformation. The prediction results show good agreement with values obtained from simulations. The models also allow the application of surgical and diagnostic tools to their surface and inner channels. Finally, via the conformal integration of 3D printed soft electronic sensors, pressure applied to the models with surgical tools can be quantitatively measured.

Exploring parameter space effects on structure-property relationships of surfactants at liquid-liquid interfaces.

PubMed

Emborsky, Christopher P; Cox, Kenneth R; Chapman, Walter G

2011-08-28

The ubiquitous use of surfactants in commercial and industrial applications has led to many experimental, theoretical, and simulation based studies. These efforts seek to provide a molecular level understanding of the effects on structuring behavior and the corresponding impacts on observable properties (e.g., interfacial tension). With such physical detail, targeted system design can be improved over typical techniques of observational trends and phenomenological correlations by taking advantage of predictive system response. This research provides a systematic study of part of the broad parameter space effects on equilibrium microstructure and interfacial properties of amphiphiles at a liquid-liquid interface using the interfacial statistical associating fluid theory density functional theory as a molecular model for the system from the bulk to the interface. Insights into the molecular level physics and thermodynamics governing the system behavior are discussed as they relate to both predictions qualitatively consistent with experimental observations and extensions beyond currently available studies. © 2011 American Institute of Physics

3D Printed Organ Models with Physical Properties of Tissue and Integrated Sensors

PubMed Central

Qiu, Kaiyan; Zhao, Zichen; Haghiashtiani, Ghazaleh; Guo, Shuang-Zhuang; He, Mingyu; Su, Ruitao; Zhu, Zhijie; Bhuiyan, Didarul B.; Murugan, Paari; Meng, Fanben; Park, Sung Hyun; Chu, Chih-Chang; Ogle, Brenda M.; Saltzman, Daniel A.; Konety, Badrinath R.

2017-01-01

The design and development of novel methodologies and customized materials to fabricate patient-specific 3D printed organ models with integrated sensing capabilities could yield advances in smart surgical aids for preoperative planning and rehearsal. Here, we demonstrate 3D printed prostate models with physical properties of tissue and integrated soft electronic sensors using custom-formulated polymeric inks. The models show high quantitative fidelity in static and dynamic mechanical properties, optical characteristics, and anatomical geometries to patient tissues and organs. The models offer tissue-mimicking tactile sensation and behavior and thus can be used for the prediction of organ physical behavior under deformation. The prediction results show good agreement with values obtained from simulations. The models also allow the application of surgical and diagnostic tools to their surface and inner channels. Finally, via the conformal integration of 3D printed soft electronic sensors, pressure applied to the models with surgical tools can be quantitatively measured. PMID:29608202

Empirical relations of rock properties of outcrop and core samples from the Northwest German Basin for geothermal drilling

NASA Astrophysics Data System (ADS)

Reyer, D.; Philipp, S. L.

2014-09-01

Information about geomechanical and physical rock properties, particularly uniaxial compressive strength (UCS), are needed for geomechanical model development and updating with logging-while-drilling methods to minimise costs and risks of the drilling process. The following parameters with importance at different stages of geothermal exploitation and drilling are presented for typical sedimentary and volcanic rocks of the Northwest German Basin (NWGB): physical (P wave velocities, porosity, and bulk and grain density) and geomechanical parameters (UCS, static Young's modulus, destruction work and indirect tensile strength both perpendicular and parallel to bedding) for 35 rock samples from quarries and 14 core samples of sandstones and carbonate rocks. With regression analyses (linear- and non-linear) empirical relations are developed to predict UCS values from all other parameters. Analyses focus on sedimentary rocks and were repeated separately for clastic rock samples or carbonate rock samples as well as for outcrop samples or core samples. Empirical relations have high statistical significance for Young's modulus, tensile strength and destruction work; for physical properties, there is a wider scatter of data and prediction of UCS is less precise. For most relations, properties of core samples plot within the scatter of outcrop samples and lie within the 90% prediction bands of developed regression functions. The results indicate the applicability of empirical relations that are based on outcrop data on questions related to drilling operations when the database contains a sufficient number of samples with varying rock properties. The presented equations may help to predict UCS values for sedimentary rocks at depth, and thus develop suitable geomechanical models for the adaptation of the drilling strategy on rock mechanical conditions in the NWGB.

Review of incursive, hyperincursive and anticipatory systems-foundation of anticipation in electromagnetism

NASA Astrophysics Data System (ADS)

Dubois, Daniel M.

2000-05-01

The main purpose of this paper is to show that anticipation is not only a property of biosystems but is also a fundamental property of physical systems. In electromagnetism, the anticipation is related to the Lorentz transform. In this framework the anticipation is a strong anticipation because it is not based on a prediction from a model of the physical system but is embedded in the fundamental system. So, Robert Rosen's anticipatory systems deal with weak anticipation. Contrary to Robert Rosen's affirmation, anticipation is thus not a characteristic of living systems. Finality is implicitly embedded in any system and thus the final cause of Aristotle is implicitly embedded in any physical and biological systems, contrary to what Robert Rosen argued. This paper will review some incursive and hyperincursive systems giving rise to strong anticipation. Space-time incursive parabolic systems show non-local properties. Hyperincursive crisp systems are related to catastrophe theory. Finally it will be shown that incursive and hyperincursive anticipatory systems could model properties of biosystems like free will, game strategy, theorem creation, etc. Anticipation is not only related to predictions but to decisions: hyperincursive systems create multiple choices and a decision process selects one choice. So, anticipation is not a final goal, like in cybernetics and system science, but is a fundamental property of physical and biological systems.

Strength and acoustic properties of Ottawa sand containing laboratory-formed methane gas hydrate

USGS Publications Warehouse

Winters, William J.; Waite, William F.; Mason, David H.

2004-01-01

Although gas hydrate occurs in a wide variety of sediment types and is present and even pervasive at some locations on continental margins, little is known about how it forms naturally. Physical properties of the resultant gas hydrate-sediment mixtures, data needed for input into models that predict location and quantity of in situ hydrate are also lacking. Not only do properties of the host materials influence the type and quantity of hydrate formed and whether a particular deposit may be an economic resource or a geohazard, the properties of the natural sediment are also subsequently changed by the formation of gas hydrate in the pore space. The magnitude of the change is primarily related to the amount and the weighted inter-particle distribution of the hydrate deposits in relation to the actual sediment grains. Our goal is to understand the interaction between natural sediments and gas hydrate formation in order to quantify physical properties that are useful to predictive models.

Application of Artificial Neural Network to Predict Colour Change, Shrinkage and Texture of Osmotically Dehydrated Pumpkin

NASA Astrophysics Data System (ADS)

Tang, S. Y.; Lee, J. S.; Loh, S. P.; Tham, H. J.

2017-06-01

The objectives of this study were to use Artificial Neural Network (ANN) to predict colour change, shrinkage and texture of osmotically dehydrated pumpkin slices. The effects of process variables such as concentration of osmotic solution, immersion temperature and immersion time on the above mentioned physical properties were studied. The colour of the samples was measured using a colorimeter and the net colour difference changes, ΔE were determined. The texture was measured in terms of hardness by using a Texture Analyzer. As for the shrinkage, displacement of volume method was applied and percentage of shrinkage was obtained in terms of volume changes. A feed-forward backpropagation network with sigmoidal function was developed and best network configuration was chosen based on the highest correlation coefficients between the experimental values versus predicted values. As a comparison, Response Surface Methodology (RSM) statistical analysis was also employed. The performances of both RSM and ANN modelling were evaluated based on absolute average deviation (AAD), correlation of determination (R2) and root mean square error (RMSE). The results showed that ANN has higher prediction capability as compared to RSM. The relative importance of the variables on the physical properties were also determined by using connection weight approach in ANN. It was found that solution concentration showed the highest influence on all three physical properties.

Prediction of porosity of food materials during drying: Current challenges and directions.

PubMed

Joardder, Mohammad U H; Kumar, C; Karim, M A

2017-07-18

Pore formation in food samples is a common physical phenomenon observed during dehydration processes. The pore evolution during drying significantly affects the physical properties and quality of dried foods. Therefore, it should be taken into consideration when predicting transport processes in the drying sample. Characteristics of pore formation depend on the drying process parameters, product properties and processing time. Understanding the physics of pore formation and evolution during drying will assist in accurately predicting the drying kinetics and quality of food materials. Researchers have been trying to develop mathematical models to describe the pore formation and evolution during drying. In this study, existing porosity models are critically analysed and limitations are identified. Better insight into the factors affecting porosity is provided, and suggestions are proposed to overcome the limitations. These include considerations of process parameters such as glass transition temperature, sample temperature, and variable material properties in the porosity models. Several researchers have proposed models for porosity prediction of food materials during drying. However, these models are either very simplistic or empirical in nature and failed to consider relevant significant factors that influence porosity. In-depth understanding of characteristics of the pore is required for developing a generic model of porosity. A micro-level analysis of pore formation is presented for better understanding, which will help in developing an accurate and generic porosity model.

Research and Development of Energetic Ionic Liquids

DTIC Science & Technology

2012-03-01

Navy/ AF ) – USAF AF - M315E • Propellant uses ionic liquids to yield low vapor toxicity 22 – Sweden/ECAPS LMP-103S • Propellant uses ADN-based formulation...hydrazine replacement monopropellant objectives, relevant monopropellant properties, AF -M1028A monopropellant composition and physical properties...thruster tests of AF -M1028A, ionic liquids as explosives, predictive toxicology, predictive methods expected payoff. AFRL continues efforts in energetic

Development of a predictive model for lead, cadmium and fluorine soil-water partition coefficients using sparse multiple linear regression analysis.

PubMed

Nakamura, Kengo; Yasutaka, Tetsuo; Kuwatani, Tatsu; Komai, Takeshi

2017-11-01

In this study, we applied sparse multiple linear regression (SMLR) analysis to clarify the relationships between soil properties and adsorption characteristics for a range of soils across Japan and identify easily-obtained physical and chemical soil properties that could be used to predict K and n values of cadmium, lead and fluorine. A model was first constructed that can easily predict the K and n values from nine soil parameters (pH, cation exchange capacity, specific surface area, total carbon, soil organic matter from loss on ignition and water holding capacity, the ratio of sand, silt and clay). The K and n values of cadmium, lead and fluorine of 17 soil samples were used to verify the SMLR models by the root mean square error values obtained from 512 combinations of soil parameters. The SMLR analysis indicated that fluorine adsorption to soil may be associated with organic matter, whereas cadmium or lead adsorption to soil is more likely to be influenced by soil pH, IL. We found that an accurate K value can be predicted from more than three soil parameters for most soils. Approximately 65% of the predicted values were between 33 and 300% of their measured values for the K value; 76% of the predicted values were within ±30% of their measured values for the n value. Our findings suggest that adsorption properties of lead, cadmium and fluorine to soil can be predicted from the soil physical and chemical properties using the presented models. Copyright © 2017 Elsevier Ltd. All rights reserved.

Original predictive approach to the compressibility of pharmaceutical powder mixtures based on the Kawakita equation.

PubMed

Mazel, Vincent; Busignies, Virginie; Duca, Stéphane; Leclerc, Bernard; Tchoreloff, Pierre

2011-05-30

In the pharmaceutical industry, tablets are obtained by the compaction of two or more components which have different physical properties and compaction behaviours. Therefore, it could be interesting to predict the physical properties of the mixture using the single-component results. In this paper, we have focused on the prediction of the compressibility of binary mixtures using the Kawakita model. Microcrystalline cellulose (MCC) and L-alanine were compacted alone and mixed at different weight fractions. The volume reduction, as a function of the compaction pressure, was acquired during the compaction process ("in-die") and after elastic recovery ("out-of-die"). For the pure components, the Kawakita model is well suited to the description of the volume reduction. For binary mixtures, an original approach for the prediction of the volume reduction without using the effective Kawakita parameters was proposed and tested. The good agreement between experimental and predicted data proved that this model was efficient to predict the volume reduction of MCC and L-alanine mixtures during compaction experiments. Copyright © 2011 Elsevier B.V. All rights reserved.

Sakurai Prize: The Future of Higgs Physics

NASA Astrophysics Data System (ADS)

Dawson, Sally

2017-01-01

The discovery of the Higgs boson relied critically on precision calculations. The quantum contributions from the Higgs boson to the W and top quark masses suggested long before the Higgs discovery that a Standard Model Higgs boson should have a mass in the 100-200 GeV range. The experimental extraction of Higgs properties requires normalization to the predicted Higgs production and decay rates, for which higher order corrections are also essential. As Higgs physics becomes a mature subject, more and more precise calculations will be required. If there is new physics at high scales, it will contribute to the predictions and precision Higgs physics will be a window to beyond the Standard Model physics.

CALCULATING PHYSICAL PROPERTIES OF ORGANIC COMPOUNDS FOR ENVIRONMENTAL MODELING FROM MOLECULAR STRUCTURE

EPA Science Inventory

Mathematical models for predicting the transport and fate of pollutants in the environment require reactivity parameter values-- that is value of the physical and chemical constants that govern reactivity. Although empirical structure activity relationships have been developed t...

Environmental Capability of Liquid Lubricants

NASA Technical Reports Server (NTRS)

Beerbower, A.

1973-01-01

The methods available for predicting the properties of liquid lubricants from their structural formulas are discussed. The methods make it possible to design lubricants by forecasting the results of changing the structure and to determine the limits to which liquid lubricants can cope with environmental extremes. The methods are arranged in order of their thermodynamic properties through empirical physical properties to chemical properties.

Three-dimensional prediction of soil physical, chemical, and hydrological properties in a forested catchment of the Santa Catalina CZO

NASA Astrophysics Data System (ADS)

Shepard, C.; Holleran, M.; Lybrand, R. A.; Rasmussen, C.

2014-12-01

Understanding critical zone evolution and function requires an accurate assessment of local soil properties. Two-dimensional (2D) digital soil mapping provides a general assessment of soil characteristics across a sampled landscape, but lacks the ability to predict soil properties with depth. The utilization of mass-preserving spline functions enable the extrapolation of soil properties with depth, extending predictive functions to three-dimensions (3D). The present study was completed in the Marshall Gulch (MG) catchment, located in the Santa Catalina Mountains, 30 km northwest of Tucson, Arizona, as part of the Santa Catalina-Jemez Mountains Critical Zone Observatory. Twenty-four soil pits were excavated and described following standard procedures. Mass-preserving splines were used to extrapolate mass carbon (kg C m-2); percent clay, silt, and sand (%); sodium mass flux (kg Na m-2); and pH for 24 sampled soil pits in 1-cm depth increments. Saturated volumetric water content (θs) and volumetric water content at 10 kPa (θ10) were predicted using ROSETTA and established empirical relationships. The described profiles were all sampled to differing depths; to compensate for the unevenness of the profile descriptions, the soil depths were standardized from 0.0 to 1.0 and then split into five equal standard depth sections. A logit-transformation was used to normalize the target variables. Step-wise regressions were calculated using available environmental covariates to predict the properties of each variable across the catchment in each depth section, and interpolated model residuals added back to the predicted layers to generate the final soil maps. Logit-transformed R2 for the predictive functions varied widely, ranging from 0.20 to 0.79, with logit-transformed RMSE ranging from 0.15 to 2.77. The MG catchment was further classified into clusters with similar properties based on the environmental covariates, and representative depth functions for each target variable in each cluster calculated. Mass-preserving splines combined with stepwise regressions are an effective tool for predicting soil physical, chemical, and hydrological properties with depth, enhancing our understanding of the critical zone.

The Perception of Materials through Oral Sensation

PubMed Central

Howes, Philip D.; Wongsriruksa, Supinya; Laughlin, Zoe; Witchel, Harry J.; Miodownik, Mark

2014-01-01

This paper presents the results of a multimodal study of oral perception conducted with a set of material samples made from metals, polymers and woods, in which both the somatosensory and taste factors were examined. A multidimensional scaling analysis coupled with subjective attribute ratings was performed to assess these factors both qualitatively and quantitatively. The perceptual somatosensory factors of warmth, hardness and roughness dominated over the basic taste factors, and roughness was observed to be a less significant sensation compared to touch-only experiments. The perceptual somatosensory ratings were compared directly with physical property data in order to assess the correlation between the perceived properties and measured physical properties. In each case, a strong correlation was observed, suggesting that physical properties may be useful in industrial design for predicting oral perception. PMID:25136793

Method and apparatus for determination of mechanical properties of functionally-graded materials

DOEpatents

Giannakopoulos, Antonios E.; Suresh, Subra

1999-01-01

Techniques for the determination of mechanical properties of homogenous or functionally-graded materials from indentation testing are presented. The technique is applicable to indentation on the nano-scale through the macro-scale including the geological scale. The technique involves creating a predictive load/depth relationship for a sample, providing an experimental load/depth relationship, comparing the experimental data to the predictive data, and determining a physical characteristic from the comparison.

Prediction of brittleness based on anisotropic rock physics model for kerogen-rich shale

NASA Astrophysics Data System (ADS)

Qian, Ke-Ran; He, Zhi-Liang; Chen, Ye-Quan; Liu, Xi-Wu; Li, Xiang-Yang

2017-12-01

The construction of a shale rock physics model and the selection of an appropriate brittleness index ( BI) are two significant steps that can influence the accuracy of brittleness prediction. On one hand, the existing models of kerogen-rich shale are controversial, so a reasonable rock physics model needs to be built. On the other hand, several types of equations already exist for predicting the BI whose feasibility needs to be carefully considered. This study constructed a kerogen-rich rock physics model by performing the selfconsistent approximation and the differential effective medium theory to model intercoupled clay and kerogen mixtures. The feasibility of our model was confirmed by comparison with classical models, showing better accuracy. Templates were constructed based on our model to link physical properties and the BI. Different equations for the BI had different sensitivities, making them suitable for different types of formations. Equations based on Young's Modulus were sensitive to variations in lithology, while those using Lame's Coefficients were sensitive to porosity and pore fluids. Physical information must be considered to improve brittleness prediction.

pDHS-SVM: A prediction method for plant DNase I hypersensitive sites based on support vector machine.

PubMed

Zhang, Shanxin; Zhou, Zhiping; Chen, Xinmeng; Hu, Yong; Yang, Lindong

2017-08-07

DNase I hypersensitive sites (DHSs) are accessible chromatin regions hypersensitive to cleavages by DNase I endonucleases. DHSs are indicative of cis-regulatory DNA elements (CREs), all of which play important roles in global gene expression regulation. It is helpful for discovering CREs by recognition of DHSs in genome. To accelerate the investigation, it is an important complement to develop cost-effective computational methods to identify DHSs. However, there is a lack of tools used for identifying DHSs in plant genome. Here we presented pDHS-SVM, a computational predictor to identify plant DHSs. To integrate the global sequence-order information and local DNA properties, reverse complement kmer and dinucleotide-based auto covariance of DNA sequences were applied to construct the feature space. In this work, fifteen physical-chemical properties of dinucleotides were used and Support Vector Machine (SVM) was employed. To further improve the performance of the predictor and extract an optimized subset of nucleotide physical-chemical properties positive for the DHSs, a heuristic nucleotide physical-chemical property selection algorithm was introduced. With the optimized subset of properties, experimental results of Arabidopsis thaliana and rice (Oryza sativa) showed that pDHS-SVM could achieve accuracies up to 87.00%, and 85.79%, respectively. The results indicated the effectiveness of proposed method for predicting DHSs. Furthermore, pDHS-SVM could provide a helpful complement for predicting CREs in plant genome. Our implementation of the novel proposed method pDHS-SVM is freely available as source code, at https://github.com/shanxinzhang/pDHS-SVM. Copyright © 2017 Elsevier Ltd. All rights reserved.

SOURCES AND RADIATIVE PROPERTIES OF ORGANOSULFATES IN THE ATMOSPHERE

EPA Science Inventory

It is expected that these studies will provide mechanistic insight to how SOA forms under acidic conditions and how it impacts direct and indirect radiative forcing. Understanding the chemical and physical properties of SOA will lead to future advancements in the predictive...

Advanced Fuel Properties; A Computer Program for Estimating Property Values

DTIC Science & Technology

1993-05-01

security considerations, contractual obligations, or notice on a specific document. REPORT DOCUMENTATION PAGE Fogu Approwd I OMB No. 0704-01=5 Ps NP...found in fuels. 14. SUBJECT TERMS 15. NUMBEROF PAGES 175 Fuel properties, Physical Propertie, Thermodynamnics, Predictions 16. PRICE CODE 17. SECURITY ...CLASSIFICATION is. SECURrrY CLASSIFICATION 19. SECURITY CLASSIFICATION 20. LIMITFATION OF ABSTRACT OF REPORT OF THIS PAGE OF ABSTRACT Unclassified

Multi-scale Modeling, Design Strategies and Physical Properties of 2D Composite Sheets

DTIC Science & Technology

2014-09-22

talks and training of two postdoctoral candidates, one graduate student The theoretical work on thennal, elecu·onic and optical prope1iies of 2D ...materials led to several new experimentalists to validate our predictions. 1S. SUBJECT TERMS 2D materials, multi scale modeling 16. SECURITY...strategies and physical properties of 2D composite sheets: Final Report Report Title This report describes the progress made as part of the subject contract

Physical and Hydraulic Properties at Recently Burned and Long-Unburned Boreal Forest Areas in Interior Alaska, USA

NASA Astrophysics Data System (ADS)

Ebel, B. A.; Koch, J. C.; Walvoord, M. A.

2017-12-01

Boreal forest regions in interior Alaska, USA are subject to recurring wildfire disturbance and climate shifts. These "press" and "pulse" disturbances impact water, solute, carbon, and energy fluxes, with feedbacks and consequences that are not adequately characterized. The NASA Arctic Boreal Vulnerability Experiment (ABoVE) seeks to understand susceptibility to disturbance in boreal regions. Subsurface physical and hydraulic properties are among the largest uncertainties in cryohydrogeologic modeling aiming to predict impacts of disturbance in Arctic and boreal regions. We address this research gap by characterizing physical and hydraulic properties of soil across a gradient of sites covering disparate soil textures and wildfire disturbance in interior Alaska. Samples were collected in the field within the domain of the NASA ABoVE project and analyzed in the laboratory. Physical properties measured include soil organic matter fraction, soil-particle size distribution, dry bulk density, and saturated soil-water content. Hydraulic properties measured include soil-water retention and field-saturated hydraulic conductivity using tension infiltrometers (-1 cm applied pressure head). The physical and hydraulic properties provide the foundation for site conceptual model development, cryohydrogeologic model parameterization, and integration with geophysical data. This foundation contributes to the NASA ABoVE objectives of understanding the underlying physical processes that control vulnerability in Arctic and Boreal landscapes.

Estimation of Physical Properties and Chemical Reactivity Parameters of Organic Compounds for Environmental Modeling by SPARC

EPA Science Inventory

Mathematical models for predicting the transport and fate of pollutants in the environment require reactivity parameter values that is value of the physical and chemical constants that govern reactivity. Although empirical structure activity relationships have been developed th...

PREDICTION OF THE VAPOR PRESSURE, BOILING POINT, HEAT OF VAPORIZATION AND DIFFUSION COEFFICIENT OF ORGANIC COMPOUNDS

EPA Science Inventory

The prototype computer program SPARC has been under development for several years to estimate physical properties and chemical reactivity parameters of organic compounds strictly from molecular structure. SPARC solute-solute physical process models have been developed and tested...

Computational studies of physical properties of Nb-Si based alloys

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

Ouyang, Lizhi

2015-04-16

The overall goal is to provide physical properties data supplementing experiments for thermodynamic modeling and other simulations such as phase filed simulation for microstructure and continuum simulations for mechanical properties. These predictive computational modeling and simulations may yield insights that can be used to guide materials design, processing, and manufacture. Ultimately, they may lead to usable Nb-Si based alloy which could play an important role in current plight towards greener energy. The main objectives of the proposed projects are: (1) developing a first principles method based supercell approach for calculating thermodynamic and mechanic properties of ordered crystals and disordered latticesmore » including solid solution; (2) application of the supercell approach to Nb-Si base alloy to compute physical properties data that can be used for thermodynamic modeling and other simulations to guide the optimal design of Nb-Si based alloy.« less

Physical property changes in hydrate-bearing sediment due to depressurization and subsequent repressurization

USGS Publications Warehouse

Waite, W.F.; Kneafsey, T.J.; Winters, W.J.; Mason, D.H.

2008-01-01

Physical property measurements of sediment cores containing natural gas hydrate are typically performed on material exposed, at least briefly, to non-in situ conditions during recovery. To examine the effects of a brief excursion from the gas-hydrate stability field, as can occur when pressure cores are transferred to pressurized storage vessels, we measured physical properties on laboratory-formed sand packs containing methane hydrate and methane pore gas. After depressurizing samples to atmospheric pressure, we repressurized them into the methane-hydrate stability field and remeasured their physical properties. Thermal conductivity, shear strength, acoustic compressional and shear wave amplitudes, and speeds of the original and depressurized/repressurized samples are compared. X– ray computed tomography images track how the gas-hydrate distribution changes in the hydrate-cemented sands owing to the depressurizaton/repressurization process. Because depressurization-induced property changes can be substantial and are not easily predicted, particularly in water-saturated, hydrate-bearing sediment, maintaining pressure and temperature conditions throughout the core recovery and measurement process is critical for using laboratory measurements to estimate in situ properties.

Physical property changes in hydrate-bearing sediment due to depressurization and subsequent repressurization

USGS Publications Warehouse

Waite, W.F.; Kneafsey, T.J.; Winters, W.J.; Mason, D.H.

2008-01-01

Physical property measurements of sediment cores containing natural gas hydrate are typically performed on material exposed, at least briefly, to non-in situ conditions during recovery. To examine the effects of a brief excursion from the gas-hydrate stability field, as can occur when pressure cores are transferred to pressurized storage vessels, we measured physical properties on laboratory-formed sand packs containing methane hydrate and methane pore gas. After depressurizing samples to atmospheric pressure, we repressurized them into the methane-hydrate stability field and remeasured their physical properties. Thermal conductivity, shear strength, acoustic compressional and shear wave amplitudes, and speeds of the original and depressurized/repressurized samples are compared. X-ray computed tomography images track how the gas-hydrate distribution changes in the hydrate-cemented sands owing to the depressurizaton/repressurization process. Because depressurization-induced property changes can be substantial and are not easily predicted, particularly in water-saturated, hydrate-bearing sediment, maintaining pressure and temperature conditions throughout the core recovery and measurement process is critical for using laboratory measurements to estimate in situ properties.

Surface temperature distribution of GTA weld pools on thin-plate 304 stainless steel

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

Zacharia, T.; David, S.A.; Vitek, J.M.

1995-11-01

A transient multidimensional computational model was utilized to study gas tungsten arc (GTA) welding of thin-plate 304 stainless steel (SS). The model eliminates several of the earlier restrictive assumptions including temperature-independent thermal-physical properties. Consequently, all important thermal-physical properties were considered as temperature dependent throughout the range of temperatures experienced by the weld metal. The computational model was used to predict surface temperature distribution of the GTA weld pools in 1.5-mm-thick AISI 304 SS. The welding parameters were chosen so as to correspond with an earlier experimental study that produced high-resolution surface temperature maps. One of the motivations of the presentmore » study was to verify the predictive capability of the computational model. Comparison of the numerical predictions and experimental observations indicate excellent agreement, thereby verifying the model.« less

Composite structural materials

NASA Technical Reports Server (NTRS)

Ansell, G. S.; Loewy, R. G.; Wiberley, S. E.

1979-01-01

Technology utilization of fiber reinforced composite materials is discussed in the areas of physical properties, and life prediction. Programs related to the Composite Aircraft Program are described in detail.

Molecular simulation of the thermophysical properties and phase behaviour of impure CO2 relevant to CCS.

PubMed

Cresswell, Alexander J; Wheatley, Richard J; Wilkinson, Richard D; Graham, Richard S

2016-10-20

Impurities from the CCS chain can greatly influence the physical properties of CO 2 . This has important design, safety and cost implications for the compression, transport and storage of CO 2 . There is an urgent need to understand and predict the properties of impure CO 2 to assist with CCS implementation. However, CCS presents demanding modelling requirements. A suitable model must both accurately and robustly predict CO 2 phase behaviour over a wide range of temperatures and pressures, and maintain that predictive power for CO 2 mixtures with numerous, mutually interacting chemical species. A promising technique to address this task is molecular simulation. It offers a molecular approach, with foundations in firmly established physical principles, along with the potential to predict the wide range of physical properties required for CCS. The quality of predictions from molecular simulation depends on accurate force-fields to describe the interactions between CO 2 and other molecules. Unfortunately, there is currently no universally applicable method to obtain force-fields suitable for molecular simulation. In this paper we present two methods of obtaining force-fields: the first being semi-empirical and the second using ab initio quantum-chemical calculations. In the first approach we optimise the impurity force-field against measurements of the phase and pressure-volume behaviour of CO 2 binary mixtures with N 2 , O 2 , Ar and H 2 . A gradient-free optimiser allows us to use the simulation itself as the underlying model. This leads to accurate and robust predictions under conditions relevant to CCS. In the second approach we use quantum-chemical calculations to produce ab initio evaluations of the interactions between CO 2 and relevant impurities, taking N 2 as an exemplar. We use a modest number of these calculations to train a machine-learning algorithm, known as a Gaussian process, to describe these data. The resulting model is then able to accurately predict a much broader set of ab initio force-field calculations at comparatively low numerical cost. Although our method is not yet ready to be implemented in a molecular simulation, we outline the necessary steps here. Such simulations have the potential to deliver first-principles simulation of the thermodynamic properties of impure CO 2 , without fitting to experimental data.

Learning physical descriptors for materials science by compressed sensing

NASA Astrophysics Data System (ADS)

Ghiringhelli, Luca M.; Vybiral, Jan; Ahmetcik, Emre; Ouyang, Runhai; Levchenko, Sergey V.; Draxl, Claudia; Scheffler, Matthias

2017-02-01

The availability of big data in materials science offers new routes for analyzing materials properties and functions and achieving scientific understanding. Finding structure in these data that is not directly visible by standard tools and exploitation of the scientific information requires new and dedicated methodology based on approaches from statistical learning, compressed sensing, and other recent methods from applied mathematics, computer science, statistics, signal processing, and information science. In this paper, we explain and demonstrate a compressed-sensing based methodology for feature selection, specifically for discovering physical descriptors, i.e., physical parameters that describe the material and its properties of interest, and associated equations that explicitly and quantitatively describe those relevant properties. As showcase application and proof of concept, we describe how to build a physical model for the quantitative prediction of the crystal structure of binary compound semiconductors.

Quantitative structure-property relationships for chemical functional use and weight fractions in consumer articles

EPA Science Inventory

Chemical functional use -- the functional role a chemical plays in processes or products -- may be a useful heuristic for predicting human exposure potential in that it comprises information about the compound's likely physical properties and the product formulations or articles ...

The Chemical Bond and Solid-state Physics

ERIC Educational Resources Information Center

Phillips, James C.

1970-01-01

Proposes a new scale of ionicity, with which the ionic character of bonding in crystals can be predicted and measured. This new scale of ionicity has led to improved understanding of such crystalline properties as lattice structure, heats of formation, elastic constants, and nonlinear optical properties. Bibliography. (LC)

Nano-QSPR Modelling of Carbon-Based Nanomaterials Properties.

PubMed

Salahinejad, Maryam

2015-01-01

Evaluation of chemical and physical properties of nanomaterials is of critical importance in a broad variety of nanotechnology researches. There is an increasing interest in computational methods capable of predicting properties of new and modified nanomaterials in the absence of time-consuming and costly experimental studies. Quantitative Structure- Property Relationship (QSPR) approaches are progressive tools in modelling and prediction of many physicochemical properties of nanomaterials, which are also known as nano-QSPR. This review provides insight into the concepts, challenges and applications of QSPR modelling of carbon-based nanomaterials. First, we try to provide a general overview of QSPR implications, by focusing on the difficulties and limitations on each step of the QSPR modelling of nanomaterials. Then follows with the most significant achievements of QSPR methods in modelling of carbon-based nanomaterials properties and their recent applications to generate predictive models. This review specifically addresses the QSPR modelling of physicochemical properties of carbon-based nanomaterials including fullerenes, single-walled carbon nanotube (SWNT), multi-walled carbon nanotube (MWNT) and graphene.

Using remote sensing and soil physical properties for predicting the spatial distribution of cotton lint yield

USDA-ARS?s Scientific Manuscript database

Timely reflectance data from cotton (Gossypium hirsutum L.) production fields provide a useful tool for crop health assessment and site-specific crop management decisions. This field study investigated the relationships among site-specific normalized difference vegetation index (NDVI), soil physical...

User’s Guide for T.E.S.T. (version 4.2) (Toxicity Estimation Software Tool) A Program to Estimate Toxicity from Molecular Structure

EPA Science Inventory

The user's guide describes the methods used by TEST to predict toxicity and physical properties (including the new mode of action based method used to predict acute aquatic toxicity). It describes all of the experimental data sets included in the tool. It gives the prediction res...

Stereotype Formation: Biased by Association

ERIC Educational Resources Information Center

Le Pelley, Mike E.; Reimers, Stian J.; Calvini, Guglielmo; Spears, Russell; Beesley, Tom; Murphy, Robin A.

2010-01-01

We propose that biases in attitude and stereotype formation might arise as a result of learned differences in the extent to which social groups have previously been predictive of behavioral or physical properties. Experiments 1 and 2 demonstrate that differences in the experienced predictiveness of groups with respect to evaluatively neutral…

PREDICTION OF THE SOLUBILITY, ACTIVITY COEFFICIENT AND LIQUID/LIQUID PARTITION COEFFICIENT OF ORGANIC COMPOUNDS

EPA Science Inventory

Solvation models, based on fundamental chemical structure theory, were developed in the SPARC mechanistic tool box to predict a large array of physical properties of organic compounds in water and in non-aqueous solvents strictly from molecular structure. The SPARC self-interact...

Prediction of Transport Properties of Permeants through Polymer Films. A Simple Gravimetric Experiment.

ERIC Educational Resources Information Center

Britton, L. N.; And Others

1988-01-01

Considers the applicability of the simple emersion/weight-gain method for predicting diffusion coefficients, solubilities, and permeation rates of chemicals in polymers that do not undergo physical and chemical deterioration. Presents the theoretical background, procedures and typical results related to this activity. (CW)

The Effect of Stabilization Heat Treatments on the Tensile and Creep Behavior of an Advanced Nickel-Based Disk Alloy

NASA Technical Reports Server (NTRS)

Gayda, John

2003-01-01

As part of NASA s Advanced Subsonic Technology Program, a study of stabilization heat treatment options for an advanced nickel-base disk alloy, ME 209, was performed. Using a simple, physically based approach, the effect of stabilization heat treatments on tensile and creep properties was analyzed in this paper. Solutions temperature, solution cooling rate, and stabilization temperature/time were found to have a significant impact on tensile and creep properties. These effects were readily quantified using the following methodology. First, the effect of solution cooling rate was assessed to determine its impact on a given property. The as-cooled property was then modified by using two multiplicative factors which assess the impact of solution temperature and stabilization parameters. Comparison of experimental data with predicted values showed this physically based analysis produced good results that rivaled the statistical analysis employed, which required numerous changes in the form of the regression equation depending on the property and temperature in question. As this physically based analysis uses the data for input, it should be noted that predictions which attempt to extrapolate beyond the bounds of the data must be viewed with skepticism. Future work aimed at expanding the range of the stabilization/aging parameters explored in this study would be highly desirable, especially at the higher solution cooling rates.

Tunable Physical Properties of Ethylcellulose/Gelatin Composite Nanofibers by Electrospinning.

PubMed

Liu, Yuyu; Deng, Lingli; Zhang, Cen; Feng, Fengqin; Zhang, Hui

2018-02-28

In this work, the ethylcellulose/gelatin blends at various weight ratios in water/ethanol/acetic acid solution were electrospun to fabricate nanofibers with tunable physical properties. The solution compatibility was predicted based on Hansen solubility parameters and evaluated by rheological measurements. The physical properties were characterized by scanning electron microscopy, porosity, differential scanning calorimetry, thermogravimetry, Fourier transform infrared spectroscopy, and water contact angle. Results showed that the entangled structures among ethylcellulose and gelatin chains through hydrogen bonds gave rise to a fine morphology of the composite fibers with improved thermal stability. The fibers with higher gelatin ratio (75%), possessed hydrophilic surface (water contact angle of 53.5°), and adequate water uptake ability (1234.14%), while the fibers with higher ethylcellulose proportion (75%) tended to be highly water stable with a hydrophobic surface (water contact angle of 129.7°). This work suggested that the composite ethylcellulose/gelatin nanofibers with tunable physical properties have potentials as materials for bioactive encapsulation, food packaging, and filtration applications.

Accurate RNA 5-methylcytosine site prediction based on heuristic physical-chemical properties reduction and classifier ensemble.

PubMed

Zhang, Ming; Xu, Yan; Li, Lei; Liu, Zi; Yang, Xibei; Yu, Dong-Jun

2018-06-01

RNA 5-methylcytosine (m 5 C) is an important post-transcriptional modification that plays an indispensable role in biological processes. The accurate identification of m 5 C sites from primary RNA sequences is especially useful for deeply understanding the mechanisms and functions of m 5 C. Due to the difficulty and expensive costs of identifying m 5 C sites with wet-lab techniques, developing fast and accurate machine-learning-based prediction methods is urgently needed. In this study, we proposed a new m 5 C site predictor, called M5C-HPCR, by introducing a novel heuristic nucleotide physicochemical property reduction (HPCR) algorithm and classifier ensemble. HPCR extracts multiple reducts of physical-chemical properties for encoding discriminative features, while the classifier ensemble is applied to integrate multiple base predictors, each of which is trained based on a separate reduct of the physical-chemical properties obtained from HPCR. Rigorous jackknife tests on two benchmark datasets demonstrate that M5C-HPCR outperforms state-of-the-art m 5 C site predictors, with the highest values of MCC (0.859) and AUC (0.962). We also implemented the webserver of M5C-HPCR, which is freely available at http://cslab.just.edu.cn:8080/M5C-HPCR/. Copyright © 2018 Elsevier Inc. All rights reserved.

Quantifying physical characteristics of wildland fuels using the fuel characteristic classification system.

Treesearch

Cynthia L. Riccardi; Susan J. Prichard; David V. Sandberg; Roger D. Ottmar

2007-01-01

Wildland fuel characteristics are used in many applications of operational fire predictions and to understand fire effects and behaviour. Even so, there is a shortage of information on basic fuel properties and the physical characteristics of wildland fuels. The Fuel Characteristic Classification System (FCCS) builds and catalogues fuelbed descriptions based on...

The Early Universe and High-Energy Physics.

ERIC Educational Resources Information Center

Schramm, David N.

1983-01-01

Many properties of new particle field theories can only be tested by comparing their predictions about the physical conditions immediately after the big bang with what can be reconstructed about this event from astronomical data. Facts/questions about big bang, unified field theories, and universe epochs/mass are among the topics discussed. (JN)

Prediction of toxicity and comparison of alternatives using WebTEST (Web-services Toxicity Estimation Software Tool)

EPA Science Inventory

A Java-based web service is being developed within the US EPA’s Chemistry Dashboard to provide real time estimates of toxicity values and physical properties. WebTEST can generate toxicity predictions directly from a simple URL which includes the endpoint, QSAR method, and ...

Prediction of toxicity and comparison of alternatives using WebTEST (Web-services Toxicity Estimation Software Tool)(Bled Slovenia)

EPA Science Inventory

A Java-based web service is being developed within the US EPA’s Chemistry Dashboard to provide real time estimates of toxicity values and physical properties. WebTEST can generate toxicity predictions directly from a simple URL which includes the endpoint, QSAR method, and ...

Functional materials discovery using energy-structure-function maps

NASA Astrophysics Data System (ADS)

Pulido, Angeles; Chen, Linjiang; Kaczorowski, Tomasz; Holden, Daniel; Little, Marc A.; Chong, Samantha Y.; Slater, Benjamin J.; McMahon, David P.; Bonillo, Baltasar; Stackhouse, Chloe J.; Stephenson, Andrew; Kane, Christopher M.; Clowes, Rob; Hasell, Tom; Cooper, Andrew I.; Day, Graeme M.

2017-03-01

Molecular crystals cannot be designed in the same manner as macroscopic objects, because they do not assemble according to simple, intuitive rules. Their structures result from the balance of many weak interactions, rather than from the strong and predictable bonding patterns found in metal-organic frameworks and covalent organic frameworks. Hence, design strategies that assume a topology or other structural blueprint will often fail. Here we combine computational crystal structure prediction and property prediction to build energy-structure-function maps that describe the possible structures and properties that are available to a candidate molecule. Using these maps, we identify a highly porous solid, which has the lowest density reported for a molecular crystal so far. Both the structure of the crystal and its physical properties, such as methane storage capacity and guest-molecule selectivity, are predicted using the molecular structure as the only input. More generally, energy-structure-function maps could be used to guide the experimental discovery of materials with any target function that can be calculated from predicted crystal structures, such as electronic structure or mechanical properties.

Functional materials discovery using energy-structure-function maps.

PubMed

Pulido, Angeles; Chen, Linjiang; Kaczorowski, Tomasz; Holden, Daniel; Little, Marc A; Chong, Samantha Y; Slater, Benjamin J; McMahon, David P; Bonillo, Baltasar; Stackhouse, Chloe J; Stephenson, Andrew; Kane, Christopher M; Clowes, Rob; Hasell, Tom; Cooper, Andrew I; Day, Graeme M

2017-03-30

Molecular crystals cannot be designed in the same manner as macroscopic objects, because they do not assemble according to simple, intuitive rules. Their structures result from the balance of many weak interactions, rather than from the strong and predictable bonding patterns found in metal-organic frameworks and covalent organic frameworks. Hence, design strategies that assume a topology or other structural blueprint will often fail. Here we combine computational crystal structure prediction and property prediction to build energy-structure-function maps that describe the possible structures and properties that are available to a candidate molecule. Using these maps, we identify a highly porous solid, which has the lowest density reported for a molecular crystal so far. Both the structure of the crystal and its physical properties, such as methane storage capacity and guest-molecule selectivity, are predicted using the molecular structure as the only input. More generally, energy-structure-function maps could be used to guide the experimental discovery of materials with any target function that can be calculated from predicted crystal structures, such as electronic structure or mechanical properties.

Which forms of child/adolescent externalizing behaviors account for late adolescent risky sexual behavior and substance use?

PubMed

Timmermans, Maartje; van Lier, Pol A C; Koot, Hans M

2008-04-01

Health risk behaviors like substance use (alcohol, tobacco, soft/hard drugs) and risky sexual behavior become more prevalent in adolescence. Children with behavior problems are thought to be prone to engage in health risk behaviors later in life. It is, however, unclear which problems within the externalizing spectrum account for these outcomes. Three hundred and nine children were followed from age 4/5 years to 18 years (14-year follow-up). Level and course of parent-rated opposition, physical aggression, status violations and property violations were used to predict adolescent-reported substance use and risky sexual behavior at age 18 years. Both level and change in physical aggression were unique predictors of all forms of adolescent health risk behavior. Levels of status violations predicted smoking and soft drug use only, while change in property violations predicted each of the health risk behaviors. The links between opposition and health risk behaviors were accounted for by co-occurring problem behaviors. Of externalizing problems, physical aggression is the best predictor of adolescent substance use and risky sexual behavior from childhood onwards. Possible explanations and implications of these findings, and future research directions are discussed.

Formation enthalpies for transition metal alloys using machine learning

NASA Astrophysics Data System (ADS)

Ubaru, Shashanka; Miedlar, Agnieszka; Saad, Yousef; Chelikowsky, James R.

2017-06-01

The enthalpy of formation is an important thermodynamic property. Developing fast and accurate methods for its prediction is of practical interest in a variety of applications. Material informatics techniques based on machine learning have recently been introduced in the literature as an inexpensive means of exploiting materials data, and can be used to examine a variety of thermodynamics properties. We investigate the use of such machine learning tools for predicting the formation enthalpies of binary intermetallic compounds that contain at least one transition metal. We consider certain easily available properties of the constituting elements complemented by some basic properties of the compounds, to predict the formation enthalpies. We show how choosing these properties (input features) based on a literature study (using prior physics knowledge) seems to outperform machine learning based feature selection methods such as sensitivity analysis and LASSO (least absolute shrinkage and selection operator) based methods. A nonlinear kernel based support vector regression method is employed to perform the predictions. The predictive ability of our model is illustrated via several experiments on a dataset containing 648 binary alloys. We train and validate the model using the formation enthalpies calculated using a model by Miedema, which is a popular semiempirical model used for the prediction of formation enthalpies of metal alloys.

High Fidelity Ion Beam Simulation of High Dose Neutron Irradiation

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

Was, Gary; Wirth, Brian; Motta, Athur

The objective of this proposal is to demonstrate the capability to predict the evolution of microstructure and properties of structural materials in-reactor and at high doses, using ion irradiation as a surrogate for reactor irradiations. “Properties” includes both physical properties (irradiated microstructure) and the mechanical properties of the material. Demonstration of the capability to predict properties has two components. One is ion irradiation of a set of alloys to yield an irradiated microstructure and corresponding mechanical behavior that are substantially the same as results from neutron exposure in the appropriate reactor environment. Second is the capability to predict the irradiatedmore » microstructure and corresponding mechanical behavior on the basis of improved models, validated against both ion and reactor irradiations and verified against ion irradiations. Taken together, achievement of these objectives will yield an enhanced capability for simulating the behavior of materials in reactor irradiations.« less

Comptational Design Of Functional CA-S-H and Oxide Doped Alloy Systems

NASA Astrophysics Data System (ADS)

Yang, Shizhong; Chilla, Lokeshwar; Yang, Yan; Li, Kuo; Wicker, Scott; Zhao, Guang-Lin; Khosravi, Ebrahim; Bai, Shuju; Zhang, Boliang; Guo, Shengmin

Computer aided functional materials design accelerates the discovery of novel materials. This presentation will cover our recent research advance on the Ca-S-H system properties prediction and oxide doped high entropy alloy property simulation and experiment validation. Several recent developed computational materials design methods were utilized to the two systems physical and chemical properties prediction. A comparison of simulation results to the corresponding experiment data will be introduced. This research is partially supported by NSF CIMM project (OIA-15410795 and the Louisiana BoR), NSF HBCU Supplement climate change and ecosystem sustainability subproject 3, and LONI high performance computing time allocation loni mat bio7.

Atomic and molecular far-infrared lines from high redshift galaxies

NASA Astrophysics Data System (ADS)

Vallini, L.

2015-03-01

The advent of Atacama Large Millimeter-submillimeter Array (ALMA), with its unprecedented sensitivity, makes it possible the detection of far-infrared (FIR) metal cooling and molecular lines from the first galaxies that formed after the Big Bang. These lines represent a powerful tool to shed light on the physical properties of the interstellar medium (ISM) in high-redshift sources. In what follows we show the potential of a physically motivated theoretical approach that we developed to predict the ISM properties of high redshift galaxies. The model allows to infer, as a function of the metallicity, the luminosities of various FIR lines observable with ALMA. It is based on high resolution cosmological simulations of star-forming galaxies at the end of the Epoch of Reionization (z˜eq6) , further implemented with sub-grid physics describing the cooling and the heating processes that take place in the neutral diffuse ISM. Finally we show how a different approach based on semi-analytical calculations can allow to predict the CO flux function at z>6.

Spectral reflectance of surface soils - A statistical analysis

NASA Technical Reports Server (NTRS)

Crouse, K. R.; Henninger, D. L.; Thompson, D. R.

1983-01-01

The relationship of the physical and chemical properties of soils to their spectral reflectance as measured at six wavebands of Thematic Mapper (TM) aboard NASA's Landsat-4 satellite was examined. The results of performing regressions of over 20 soil properties on the six TM bands indicated that organic matter, water, clay, cation exchange capacity, and calcium were the properties most readily predicted from TM data. The middle infrared bands, bands 5 and 7, were the best bands for predicting soil properties, and the near infrared band, band 4, was nearly as good. Clustering 234 soil samples on the TM bands and characterizing the clusters on the basis of soil properties revealed several clear relationships between properties and reflectance. Discriminant analysis found organic matter, fine sand, base saturation, sand, extractable acidity, and water to be significant in discriminating among clusters.

Prediction of Building Limestone Physical and Mechanical Properties by Means of Ultrasonic P-Wave Velocity

PubMed Central

Concu, Giovanna; De Nicolo, Barbara; Valdes, Monica

2014-01-01

The aim of this study was to evaluate ultrasonic P-wave velocity as a feature for predicting some physical and mechanical properties that describe the behavior of local building limestone. To this end, both ultrasonic testing and compressive tests were carried out on several limestone specimens and statistical correlation between ultrasonic velocity and density, compressive strength, and modulus of elasticity was studied. The effectiveness of ultrasonic velocity was evaluated by regression, with the aim of observing the coefficient of determination r 2 between ultrasonic velocity and the aforementioned parameters, and the mathematical expressions of the correlations were found and discussed. The strong relations that were established between ultrasonic velocity and limestone properties indicate that these parameters can be reasonably estimated by means of this nondestructive parameter. This may be of great value in a preliminary phase of the diagnosis and inspection of stone masonry conditions, especially when the possibility of sampling material cores is reduced. PMID:24511286

Use of principal-component, correlation, and stepwise multiple-regression analyses to investigate selected physical and hydraulic properties of carbonate-rock aquifers

USGS Publications Warehouse

Brown, C. Erwin

1993-01-01

Correlation analysis in conjunction with principal-component and multiple-regression analyses were applied to laboratory chemical and petrographic data to assess the usefulness of these techniques in evaluating selected physical and hydraulic properties of carbonate-rock aquifers in central Pennsylvania. Correlation and principal-component analyses were used to establish relations and associations among variables, to determine dimensions of property variation of samples, and to filter the variables containing similar information. Principal-component and correlation analyses showed that porosity is related to other measured variables and that permeability is most related to porosity and grain size. Four principal components are found to be significant in explaining the variance of data. Stepwise multiple-regression analysis was used to see how well the measured variables could predict porosity and (or) permeability for this suite of rocks. The variation in permeability and porosity is not totally predicted by the other variables, but the regression is significant at the 5% significance level. ?? 1993.

Prediction of building limestone physical and mechanical properties by means of ultrasonic P-wave velocity.

PubMed

Concu, Giovanna; De Nicolo, Barbara; Valdes, Monica

2014-01-01

The aim of this study was to evaluate ultrasonic P-wave velocity as a feature for predicting some physical and mechanical properties that describe the behavior of local building limestone. To this end, both ultrasonic testing and compressive tests were carried out on several limestone specimens and statistical correlation between ultrasonic velocity and density, compressive strength, and modulus of elasticity was studied. The effectiveness of ultrasonic velocity was evaluated by regression, with the aim of observing the coefficient of determination r(2) between ultrasonic velocity and the aforementioned parameters, and the mathematical expressions of the correlations were found and discussed. The strong relations that were established between ultrasonic velocity and limestone properties indicate that these parameters can be reasonably estimated by means of this nondestructive parameter. This may be of great value in a preliminary phase of the diagnosis and inspection of stone masonry conditions, especially when the possibility of sampling material cores is reduced.

An interpretation of photometric parameters of bright desert regions of Mars and their dependence on wave length

NASA Technical Reports Server (NTRS)

Weaver, W. R.; Meador, W. E.

1977-01-01

Photometric data from the bright desert areas of Mars were used to determine the dependence of the three photometric parameters of the photometric function on wavelength and to provide qualitative predictions about the physical properties of the surface. Knowledge of the parameters allowed the brightness of these areas of Mars to be determined for any scattering geometry in the wavelength range of 0.45 to 0.70 micron. The changes that occur in the photometric parameters due to changes in wavelength were shown to be consistent with their physical interpretations, and the predictions of surface properties were shown to be consistent with conditions expected to exist in these regions of Mars. The photometric function was shown to have potential as a diagnostic tool for the qualitative determination of surface properties, and the consistency of the behavior of the photometric parameters was considered to be support for the validity of the photometric function.

Establishment of a Physical Model for Solute Diffusion in Hydrogel: Understanding the Diffusion of Proteins in Poly(sulfobetaine methacrylate) Hydrogel.

PubMed

Zhou, Yuhang; Li, Junjie; Zhang, Ying; Dong, Dianyu; Zhang, Ershuai; Ji, Feng; Qin, Zhihui; Yang, Jun; Yao, Fanglian

2017-02-02

Prediction of the diffusion coefficient of solute, especially bioactive molecules, in hydrogel is significant in the biomedical field. Considering the randomness of solute movement in a hydrogel network, a physical diffusion RMP-1 model based on obstruction theory was established in this study. The physical properties of the solute and the polymer chain and their interactions were introduced into this model. Furthermore, models RMP-2 and RMP-3 were established to understand and predict the diffusion behaviors of proteins in hydrogel. In addition, zwitterionic poly(sulfobetaine methacrylate) (PSBMA) hydrogels with wide range and fine adjustable mesh sizes were prepared and used as efficient experimental platforms for model validation. The Flory characteristic ratios, Flory-Huggins parameter, mesh size, and polymer chain radii of PSBMA hydrogels were determined. The diffusion coefficients of the proteins (bovine serum albumin, immunoglobulin G, and lysozyme) in PSBMA hydrogels were studied by the fluorescence recovery after photobleaching technique. The measured diffusion coefficients were compared with the predictions of obstruction models, and it was found that our model presented an excellent predictive ability. Furthermore, the assessment of our model revealed that protein diffusion in PSBMA hydrogel would be affected by the physical properties of the protein and the PSBMA network. It was also confirmed that the diffusion behaviors of protein in zwitterionic hydrogels can be adjusted by changing the cross-linking density of the hydrogel and the ionic strength of the swelling medium. Our model is expected to possess accurate predictive ability for the diffusion coefficient of solute in hydrogel, which will be widely used in the biomedical field.

EPI Suite™-Estimation Program Interface

EPA Pesticide Factsheets

EPISuite predicts various physical-chemical properties and environmental fate endpoints and also include models for environmental transport. Running the tool will give the user an indication of the transport and persistence of a chemical

Characterization of Thermo-Physical Properties of EVA/ATH: Application to Gasification Experiments and Pyrolysis Modeling.

PubMed

Girardin, Bertrand; Fontaine, Gaëlle; Duquesne, Sophie; Försth, Michael; Bourbigot, Serge

2015-11-20

The pyrolysis of solid polymeric materials is a complex process that involves both chemical and physical phenomena such as phase transitions, chemical reactions, heat transfer, and mass transport of gaseous components. For modeling purposes, it is important to characterize and to quantify the properties driving those phenomena, especially in the case of flame-retarded materials. In this study, protocols have been developed to characterize the thermal conductivity and the heat capacity of an ethylene-vinyl acetate copolymer (EVA) flame retarded with aluminum tri-hydroxide (ATH). These properties were measured for the various species identified across the decomposition of the material. Namely, the thermal conductivity was found to decrease as a function of temperature before decomposition whereas the ceramic residue obtained after the decomposition at the steady state exhibits a thermal conductivity as low as 0.2 W/m/K. The heat capacity of the material was also investigated using both isothermal modulated Differential Scanning Calorimetry (DSC) and the standard method (ASTM E1269). It was shown that the final residue exhibits a similar behavior to alumina, which is consistent with the decomposition pathway of EVA/ATH. Besides, the two experimental approaches give similar results over the whole range of temperatures. Moreover, the optical properties before decomposition and the heat capacity of the decomposition gases were also analyzed. Those properties were then used as input data for a pyrolysis model in order to predict gasification experiments. Mass losses of gasification experiments were well predicted, thus validating the characterization of the thermo-physical properties of the material.

Characterization of Thermo-Physical Properties of EVA/ATH: Application to Gasification Experiments and Pyrolysis Modeling

PubMed Central

Girardin, Bertrand; Fontaine, Gaëlle; Duquesne, Sophie; Försth, Michael; Bourbigot, Serge

2015-01-01

The pyrolysis of solid polymeric materials is a complex process that involves both chemical and physical phenomena such as phase transitions, chemical reactions, heat transfer, and mass transport of gaseous components. For modeling purposes, it is important to characterize and to quantify the properties driving those phenomena, especially in the case of flame-retarded materials. In this study, protocols have been developed to characterize the thermal conductivity and the heat capacity of an ethylene-vinyl acetate copolymer (EVA) flame retarded with aluminum tri-hydroxide (ATH). These properties were measured for the various species identified across the decomposition of the material. Namely, the thermal conductivity was found to decrease as a function of temperature before decomposition whereas the ceramic residue obtained after the decomposition at the steady state exhibits a thermal conductivity as low as 0.2 W/m/K. The heat capacity of the material was also investigated using both isothermal modulated Differential Scanning Calorimetry (DSC) and the standard method (ASTM E1269). It was shown that the final residue exhibits a similar behavior to alumina, which is consistent with the decomposition pathway of EVA/ATH. Besides, the two experimental approaches give similar results over the whole range of temperatures. Moreover, the optical properties before decomposition and the heat capacity of the decomposition gases were also analyzed. Those properties were then used as input data for a pyrolysis model in order to predict gasification experiments. Mass losses of gasification experiments were well predicted, thus validating the characterization of the thermo-physical properties of the material. PMID:28793682

Integrated Vehicle Ground Vibration Testing in Support of Launch Vehicle Loads and Controls Analysis

NASA Technical Reports Server (NTRS)

Askins, Bruce R.; Davis, Susan R.; Salyer, Blaine H.; Tuma, Margaret L.

2008-01-01

All structural systems possess a basic set of physical characteristics unique to that system. These unique physical characteristics include items such as mass distribution and damping. When specified, they allow engineers to understand and predict how a structural system behaves under given loading conditions and different methods of control. These physical properties of launch vehicles may be predicted by analysis or measured by certain types of tests. Generally, these properties are predicted by analysis during the design phase of a launch vehicle and then verified by testing before the vehicle becomes operational. A ground vibration test (GVT) is intended to measure by test the fundamental dynamic characteristics of launch vehicles during various phases of flight. During the series of tests, properties such as natural frequencies, mode shapes, and transfer functions are measured directly. These data will then be used to calibrate loads and control systems analysis models for verifying analyses of the launch vehicle. NASA manned launch vehicles have undergone ground vibration testing leading to the development of successful launch vehicles. A GVT was not performed on the inaugural launch of the unmanned Delta III which was lost during launch. Subsequent analyses indicated had a GVT been performed, it would have identified instability issues avoiding loss of the vehicle. This discussion will address GVT planning, set-up, execution and analyses, for the Saturn and Shuttle programs, and will also focus on the current and on-going planning for the Ares I and V Integrated Vehicle Ground Vibration Test (IVGVT).

Cell Model Of A Disordered Solid

NASA Technical Reports Server (NTRS)

Peng, Steven T. J.; Landel, Robert F.; Moacanin, Jovan; Simha, Robert; Papazoglou, Elizabeth

1990-01-01

Elastic properties predicted from first principles. Paper discusses generalization of cell theory of disordered (non-crystaline) solid to include anisotropic stresses. Study part of continuing effort to understand macroscopic stress-and-strain properties of solid materials in terms of microscopic physical phenomena. Emphasis on derivation, from first principles, of bulk, shear, and Young's moduli of glassy material at zero absolute temperature.

Observational evidence of dust evolution in galactic extinction curves

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

Cecchi-Pestellini, Cesare; Casu, Silvia; Mulas, Giacomo

Although structural and optical properties of hydrogenated amorphous carbons are known to respond to varying physical conditions, most conventional extinction models are basically curve fits with modest predictive power. We compare an evolutionary model of the physical properties of carbonaceous grain mantles with their determination by homogeneously fitting observationally derived Galactic extinction curves with the same physically well-defined dust model. We find that a large sample of observed Galactic extinction curves are compatible with the evolutionary scenario underlying such a model, requiring physical conditions fully consistent with standard density, temperature, radiation field intensity, and average age of diffuse interstellar clouds.more » Hence, through the study of interstellar extinction we may, in principle, understand the evolutionary history of the diffuse interstellar clouds.« less

From Artificial Atoms to Nanocrystal Molecules: Preparation and Properties of More Complex Nanostructures

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

Choi, Charina L; Alivisatos, A Paul

2009-10-20

Quantum dots, which have found widespread use in fields such as biomedicine, photovoltaics, and electronics, are often called artificial atoms due to their size-dependent physical properties. Here this analogy is extended to consider artificial nanocrystal molecules, formed from well-defined groupings of plasmonically or electronically coupled single nanocrystals. Just as a hydrogen molecule has properties distinct from two uncoupled hydrogen atoms, a key feature of nanocrystal molecules is that they exhibit properties altered from those of the component nanoparticles due to coupling. The nature of the coupling between nanocrystal atoms and its response to vibrations and deformations of the nanocrystal moleculemore » bonds are of particular interest. We discuss synthetic approaches, predicted and observed physical properties, and prospects and challenges toward this new class of materials.« less

Dielectric Spectroscopy in Biomaterials: Agrophysics

PubMed Central

El Khaled, Dalia; Castellano, Nuria N.; Gázquez, Jose A.; Perea-Moreno, Alberto-Jesus; Manzano-Agugliaro, Francisco

2016-01-01

Being dependent on temperature and frequency, dielectric properties are related to various types of food. Predicting multiple physical characteristics of agri-food products has been the main objective of non-destructive assessment possibilities executed in many studies on horticultural products and food materials. This review manipulates the basic fundamentals of dielectric properties with their concepts and principles. The different factors affecting the behavior of dielectric properties have been dissected, and applications executed on different products seeking the characterization of a diversity of chemical and physical properties are all pointed out and referenced with their conclusions. Throughout the review, a detailed description of the various adopted measurement techniques and the mostly popular equipment are presented. This compiled review serves in coming out with an updated reference for the dielectric properties of spectroscopy that are applied in the agrophysics field. PMID:28773438

Setting Ideal Lubricant Mixing Time for Manufacturing Tablets by Evaluating Powder Flowability.

PubMed

Nakamura, Shohei; Yamaguchi, Saori; Hiraide, Rikiha; Iga, Kumi; Sakamoto, Takatoshi; Yuasa, Hiroshi

2017-10-01

We investigated the effectiveness of using Carr's flowability index (FI) and practical angle of internal friction (Φ) as indexes for setting the target Mg-St mixing time needed for preparing tablets with the target physical properties. We used FI as a measure of flowability under non-loaded conditions, and Φ as a measure of flowability under loaded conditions for pharmaceutical powders undergoing direct compression with varying concentrations of Mg-St and mixing times. We evaluated the relationship between Mg-St mixing conditions and pharmaceutical powder flowability, analyzed the correlation between the physical properties of the tablets (i.e., tablet weight variation, drug content uniformity, hardness, friability, and disintegration time of tablets prepared using the pharmaceutical powder), and studied the effect of Mg-St mixing conditions and pharmaceutical powder flowability on tablet properties. Mg-St mixing time highly correlated with pharmaceutical powder FI (R 2  = 0.883) while Mg-St concentration has low correlation with FI, and FI highly correlated with the physical properties of the tablet (R 2 values: weight variation 0.509, drug content variation 0.314, hardness 0.525, friability 0.477, and disintegration time 0.346). Therefore, using pharmaceutical powder FI as an index could enable prediction of the physical properties of a tablet without the need for tableting, and setting the Mg-St mixing time by using pharmaceutical powder FI could enable preparation of tablets with the target physical properties. Thus, the FI of the intermediate product (i.e., pharmaceutical powder) is an effective index for controlling the physical properties of the finished tablet.

[Influence of autonomy support, social goals and relatedness on amotivation in physical education classes].

PubMed

Moreno Murcia, Juan A; Parra Rojas, Nicolás; González-Cutre Coll, David

2008-11-01

The purpose of this study was to analyze some factors that influence amotivation in physical education classes. A sample of 399 students, of ages 14 to 16 years, was used. They completed the Perceived Autonomy Support Scale in Exercise Settings (PASSES), the Social Goal Scale-Physical Education (SGS-PE), the factor of the Basic Psychological Needs in Exercise Scale (BPNES) adapted to physical education and the factor of the Perceived Locus of Causality Scale (PLOC). The psychometric properties of the PASSES were analyzed, as this scale had not been validated to the Spanish context. In this analysis, the scale showed appropriate validity and reliability. The results of the structural equation model indicated that social responsibility and social relationship goals positively predicted perception of relatedness, whereas the context of autonomy support did not significantly predict it. In turn, perception of relatedness negatively predicted amotivation. The findings are discussed with regard to enhancing students' positive motivation.

Quantifying the Effect of Polymer Blending through Molecular Modelling of Cyanurate Polymers

PubMed Central

Crawford, Alasdair O.; Hamerton, Ian; Cavalli, Gabriel; Howlin, Brendan J.

2012-01-01

Modification of polymer properties by blending is a common practice in the polymer industry. We report here a study of blends of cyanurate polymers by molecular modelling that shows that the final experimentally determined properties can be predicted from first principles modelling to a good degree of accuracy. There is always a compromise between simulation length, accuracy and speed of prediction. A comparison of simulation times shows that 125ps of molecular dynamics simulation at each temperature provides the optimum compromise for models of this size with current technology. This study opens up the possibility of computer aided design of polymer blends with desired physical and mechanical properties. PMID:22970230

Thrust chamber life prediction. Volume 1: Mechanical and physical properties of high performance rocket nozzle materials

NASA Technical Reports Server (NTRS)

Esposito, J. J.; Zabora, R. F.

1975-01-01

Pertinent mechanical and physical properties of six high conductivity metals were determined. The metals included Amzirc, NARloy Z, oxygen free pure copper, electroformed copper, fine silver, and electroformed nickel. Selection of these materials was based on their possible use in high performance reusable rocket nozzles. The typical room temperature properties determined for each material included tensile ultimate strength, tensile yield strength, elongation, reduction of area, modulus of elasticity, Poisson's ratio, density, specific heat, thermal conductivity, and coefficient of thermal expansion. Typical static tensile stress-strain curves, cyclic stress-strain curves, and low-cycle fatigue life curves are shown. Properties versus temperature are presented in graphical form for temperatures from 27.6K (-410 F) to 810.9K (1000 F).

Inferring mass in complex scenes by mental simulation.

PubMed

Hamrick, Jessica B; Battaglia, Peter W; Griffiths, Thomas L; Tenenbaum, Joshua B

2016-12-01

After observing a collision between two boxes, you can immediately tell which is empty and which is full of books based on how the boxes moved. People form rich perceptions about the physical properties of objects from their interactions, an ability that plays a crucial role in learning about the physical world through our experiences. Here, we present three experiments that demonstrate people's capacity to reason about the relative masses of objects in naturalistic 3D scenes. We find that people make accurate inferences, and that they continue to fine-tune their beliefs over time. To explain our results, we propose a cognitive model that combines Bayesian inference with approximate knowledge of Newtonian physics by estimating probabilities from noisy physical simulations. We find that this model accurately predicts judgments from our experiments, suggesting that the same simulation mechanism underlies both peoples' predictions and inferences about the physical world around them. Copyright © 2016 Elsevier B.V. All rights reserved.

Superheavy magnetic monopoles and the standard cosmology

NASA Astrophysics Data System (ADS)

Turner, M. S.

1984-10-01

The superheavy magnetic monopoles predicted to exist in grand unified theories (GUTs) are for particle physics, astrophysics and cosmology. Astrophysical and cosmological considerations are invaluable in the study of the properties of GUT monopoles. Because of the glut of monopoles predicted in the standard cosmology for the simplest GUTs. The simplest GUTs and the standard cosmology are not compatible. This is a very important piece of information about physics at unification energies and about the earliest movements of the Universe. The cosmological consequences of GUT monopoles within the context of the standard hot big bang model are reviewed.

Sensitivity of hot-cathode ionization vacuum gages in several gases

NASA Technical Reports Server (NTRS)

Holanda, R.

1972-01-01

Four hot-cathode ionization vacuum gages were calibrated in 12 gases. The relative sensitivities of these gages were compared to several gas properties. Ionization cross section was the physical property which correlated best with gage sensitivity. The effects of gage accelerating voltage and ionization-cross-section energy level were analyzed. Recommendations for predicting gage sensitivity according to gage type were made.

Machine learning properties of materials and molecules with entropy-regularized kernels

NASA Astrophysics Data System (ADS)

Ceriotti, Michele; Bartók, Albert; CsáNyi, GáBor; de, Sandip

Application of machine-learning methods to physics, chemistry and materials science is gaining traction as a strategy to obtain accurate predictions of the properties of matter at a fraction of the typical cost of quantum mechanical electronic structure calculations. In this endeavor, one can leverage general-purpose frameworks for supervised-learning. It is however very important that the input data - for instance the positions of atoms in a molecule or solid - is processed into a form that reflects all the underlying physical symmetries of the problem, and that possesses the regularity properties that are required by machine-learning algorithms. Here we introduce a general strategy to build a representation of this kind. We will start from existing approaches to compare local environments (basically, groups of atoms), and combine them using techniques borrowed from optimal transport theory, discussing the relation between this idea and additive energy decompositions. We will present a few examples demonstrating the potential of this approach as a tool to predict molecular and materials' properties with an accuracy on par with state-of-the-art electronic structure methods. MARVEL NCCR (Swiss National Science Foundation) and ERC StG HBMAP (European Research Council, G.A. 677013).

Elastic velocity models for gas-hydrate-bearing sediments-a comparison

NASA Astrophysics Data System (ADS)

Chand, Shyam; Minshull, Tim A.; Gei, Davide; Carcione, José M.

2004-11-01

The presence of gas hydrate in oceanic sediments is mostly identified by bottom-simulating reflectors (BSRs), reflection events with reversed polarity following the trend of the seafloor. Attempts to quantify the amount of gas hydrate present in oceanic sediments have been based mainly on the presence or absence of a BSR and its relative amplitude. Recent studies have shown that a BSR is not a necessary criterion for the presence of gas hydrates, but rather its presence depends on the type of sediments and the in situ conditions. The influence of hydrate on the physical properties of sediments overlying the BSR is determined by the elastic properties of their constituents and on sediment microstructure. In this context several approaches have been developed to predict the physical properties of sediments, and thereby quantify the amount of gas/gas hydrate present from observed deviations of these properties from those predicted for sediments without gas hydrate. We tested four models: the empirical weighted equation (WE); the three-phase effective-medium theory (TPEM); the three-phase Biot theory (TPB) and the differential effective-medium theory (DEM). We compared these models for a range of variables (porosity and clay content) using standard values for physical parameters. The comparison shows that all the models predict sediment properties comparable to field values except for the WE model at lower porosities and the TPB model at higher porosities. The models differ in the variation of velocity with porosity and clay content. The variation of velocity with hydrate saturation is also different, although the range is similar. We have used these models to predict velocities for field data sets from sediment sections with and without gas hydrates. The first is from the Mallik 2L-38 well, Mackenzie Delta, Canada, and the second is from Ocean Drilling Program (ODP) Leg 164 on Blake Ridge. Both data sets have Vp and Vs information along with the composition and porosity of the matrix. Models are considered successful if predictions from both Vp and Vs match hydrate saturations inferred from other data. Three of the models predict consistent hydrate saturations of 60-80 per cent from both Vp and Vs from log and vertical seismic profiling data for the Mallik 2L-38 well data set, but the TPEM model predicts 20 per cent higher saturations, as does the DEM model with a clay-water starting medium. For the clay-rich sediments of Blake Ridge, the DEM, TPEM and WE models predict 10-20 per cent hydrate saturation from Vp data, comparable to that inferred from resistivity data. The hydrate saturation predicted by the TPB model from Vp is higher. Using Vs data, the DEM and TPEM models predict very low or zero hydrate saturation while the TPB and WE models predict hydrate saturation very much higher than those predicted from Vp data. Low hydrate saturations are observed to have little effect on Vs. The hydrate phase appears to be connected within the sediment microstructure even at low saturations.

Strain-Dependence of the Structure and Ferroic Properties of Epitaxial NiTiO 3 Thin Films Grown on Different Substrates

DOE PAGES

Varga, Tamas; Droubay, Timothy C.; Bowden, Mark E.; ...

2015-01-01

Polarization-induced weak ferromagnetism has been predicted a few years back in perovskite MTiO 3 (M = Fe, Mn, and Ni). We set out to stabilize this metastable perovskite structure by growing NiTiO 3 epitaxially on different substrates and to investigate the dependence of polar and magnetic properties on strain. Epitaxial NiTiO 3 films were deposited on Al 2 O 3 , Fe 2 O 3 , and LiNbO 3 substrates by pulsed laser deposition and characterized using several techniques. The effect of substrate choice on lattice strain, film structure, and physical properties was investigated. Our structural data from X-ray diffractionmore » and electron microscopy shows that substrate-induced strain has a marked effect on the structure and crystalline quality of the films. Physical property measurements reveal a dependence of the weak ferromagnetism and lattice polarization on strain and highlight our ability to control the ferroic properties in NiTiO 3 thin films by the choice of substrate. Our results are also consistent with the theoretical prediction that the ferromagnetism in acentric NiTiO 3 is polarization induced. From the substrates studied here, the perovskite substrate LiNbO 3 proved to be the most promising one for strong multiferroism.« less

Physical properties of hydrated tissue determined by surface interferometry of laser-induced thermoelastic deformation

NASA Astrophysics Data System (ADS)

Dark, Marta L.; Perelman, Lev T.; Itzkan, Irving; Schaffer, Jonathan L.; Feld, Michael S.

2000-02-01

Knee meniscus is a hydrated tissue; it is a fibrocartilage of the knee joint composed primarily of water. We present results of interferometric surface monitoring by which we measure physical properties of human knee meniscal cartilage. The physical response of biological tissue to a short laser pulse is primarily thermomechanical. When the pulse is shorter than characteristic times (thermal diffusion time and acoustic relaxation time) stresses build and propagate as acoustic waves in the tissue. The tissue responds to the laser-induced stress by thermoelastic expansion. Solving the thermoelastic wave equation numerically predicts the correct laser-induced expansion. By comparing theory with experimental data, we can obtain the longitudinal speed of sound, the effective optical penetration depth and the Grüneisen coefficient. This study yields information about the laser-tissue interaction and determines properties of the meniscus samples that could be used as diagnostic parameters.

Hydrate-Bearing Clayey Sediments: Morphology, Physical Properties, Production and Engineering/Geological Implications

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

Dai, Sheng; Santamarina, J. Carlos

Fine-grained sediments host more than 90 percent of global gas hydrate accumulation. However, hydrate formation in clay-dominated sediments is less understood and characterized than other types of hydrate occurrence. There is an inadequate understanding of hydrate formation mechanisms, segregation structures, hydrate lens topology, system connectivity, and physical macro-scale properties of clay-dominated hydrate-bearing sediments. This situation hinders further analyses of the global carbon budget as well as engineering challenges/solutions related to hydrate instability and production. This project studies hydrate-bearing clay-dominated sediments with emphasis on the enhanced fundamental understanding of hydrate formation and resulting morphology, the development laboratory techniques to emulate naturalmore » hydrate formations, the assessment of analytical tools to predict physical properties, the evaluation of engineering and geological implications, and the advanced understanding of gas production potential from finegrained sediments.« less

Nitrogen Cycling from Increased Soil Organic Carbon Contributes Both Positively and Negatively to Ecosystem Services in Wheat Agro-Ecosystems

PubMed Central

Palmer, Jeda; Thorburn, Peter J.; Biggs, Jody S.; Dominati, Estelle J.; Probert, Merv E.; Meier, Elizabeth A.; Huth, Neil I.; Dodd, Mike; Snow, Val; Larsen, Joshua R.; Parton, William J.

2017-01-01

Soil organic carbon (SOC) is an important and manageable property of soils that impacts on multiple ecosystem services through its effect on soil processes such as nitrogen (N) cycling and soil physical properties. There is considerable interest in increasing SOC concentration in agro-ecosystems worldwide. In some agro-ecosystems, increased SOC has been found to enhance the provision of ecosystem services such as the provision of food. However, increased SOC may increase the environmental footprint of some agro-ecosystems, for example by increasing nitrous oxide emissions. Given this uncertainty, progress is needed in quantifying the impact of increased SOC concentration on agro-ecosystems. Increased SOC concentration affects both N cycling and soil physical properties (i.e., water holding capacity). Thus, the aim of this study was to quantify the contribution, both positive and negative, of increased SOC concentration on ecosystem services provided by wheat agro-ecosystems. We used the Agricultural Production Systems sIMulator (APSIM) to represent the effect of increased SOC concentration on N cycling and soil physical properties, and used model outputs as proxies for multiple ecosystem services from wheat production agro-ecosystems at seven locations around the world. Under increased SOC, we found that N cycling had a larger effect on a range of ecosystem services (food provision, filtering of N, and nitrous oxide regulation) than soil physical properties. We predicted that food provision in these agro-ecosystems could be significantly increased by increased SOC concentration when N supply is limiting. Conversely, we predicted no significant benefit to food production from increasing SOC when soil N supply (from fertiliser and soil N stocks) is not limiting. The effect of increasing SOC on N cycling also led to significantly higher nitrous oxide emissions, although the relative increase was small. We also found that N losses via deep drainage were minimally affected by increased SOC in the dryland agro-ecosystems studied, but increased in the irrigated agro-ecosystem. Therefore, we show that under increased SOC concentration, N cycling contributes both positively and negatively to ecosystem services depending on supply, while the effects on soil physical properties are negligible. PMID:28539929

Nitrogen Cycling from Increased Soil Organic Carbon Contributes Both Positively and Negatively to Ecosystem Services in Wheat Agro-Ecosystems.

PubMed

Palmer, Jeda; Thorburn, Peter J; Biggs, Jody S; Dominati, Estelle J; Probert, Merv E; Meier, Elizabeth A; Huth, Neil I; Dodd, Mike; Snow, Val; Larsen, Joshua R; Parton, William J

2017-01-01

Soil organic carbon (SOC) is an important and manageable property of soils that impacts on multiple ecosystem services through its effect on soil processes such as nitrogen (N) cycling and soil physical properties. There is considerable interest in increasing SOC concentration in agro-ecosystems worldwide. In some agro-ecosystems, increased SOC has been found to enhance the provision of ecosystem services such as the provision of food. However, increased SOC may increase the environmental footprint of some agro-ecosystems, for example by increasing nitrous oxide emissions. Given this uncertainty, progress is needed in quantifying the impact of increased SOC concentration on agro-ecosystems. Increased SOC concentration affects both N cycling and soil physical properties (i.e., water holding capacity). Thus, the aim of this study was to quantify the contribution, both positive and negative, of increased SOC concentration on ecosystem services provided by wheat agro-ecosystems. We used the Agricultural Production Systems sIMulator (APSIM) to represent the effect of increased SOC concentration on N cycling and soil physical properties, and used model outputs as proxies for multiple ecosystem services from wheat production agro-ecosystems at seven locations around the world. Under increased SOC, we found that N cycling had a larger effect on a range of ecosystem services (food provision, filtering of N, and nitrous oxide regulation) than soil physical properties. We predicted that food provision in these agro-ecosystems could be significantly increased by increased SOC concentration when N supply is limiting. Conversely, we predicted no significant benefit to food production from increasing SOC when soil N supply (from fertiliser and soil N stocks) is not limiting. The effect of increasing SOC on N cycling also led to significantly higher nitrous oxide emissions, although the relative increase was small. We also found that N losses via deep drainage were minimally affected by increased SOC in the dryland agro-ecosystems studied, but increased in the irrigated agro-ecosystem. Therefore, we show that under increased SOC concentration, N cycling contributes both positively and negatively to ecosystem services depending on supply, while the effects on soil physical properties are negligible.

Prediction of protein mutant stability using classification and regression tool.

PubMed

Huang, Liang-Tsung; Saraboji, K; Ho, Shinn-Ying; Hwang, Shiow-Fen; Ponnuswamy, M N; Gromiha, M Michael

2007-02-01

Prediction of protein stability upon amino acid substitutions is an important problem in molecular biology and the solving of which would help for designing stable mutants. In this work, we have analyzed the stability of protein mutants using two different datasets of 1396 and 2204 mutants obtained from ProTherm database, respectively for free energy change due to thermal (DeltaDeltaG) and denaturant denaturations (DeltaDeltaG(H(2)O)). We have used a set of 48 physical, chemical energetic and conformational properties of amino acid residues and computed the difference of amino acid properties for each mutant in both sets of data. These differences in amino acid properties have been related to protein stability (DeltaDeltaG and DeltaDeltaG(H(2)O)) and are used to train with classification and regression tool for predicting the stability of protein mutants. Further, we have tested the method with 4 fold, 5 fold and 10 fold cross validation procedures. We found that the physical properties, shape and flexibility are important determinants of protein stability. The classification of mutants based on secondary structure (helix, strand, turn and coil) and solvent accessibility (buried, partially buried, partially exposed and exposed) distinguished the stabilizing/destabilizing mutants at an average accuracy of 81% and 80%, respectively for DeltaDeltaG and DeltaDeltaG(H(2)O). The correlation between the experimental and predicted stability change is 0.61 for DeltaDeltaG and 0.44 for DeltaDeltaG(H(2)O). Further, the free energy change due to the replacement of amino acid residue has been predicted within an average error of 1.08 kcal/mol and 1.37 kcal/mol for thermal and chemical denaturation, respectively. The relative importance of secondary structure and solvent accessibility, and the influence of the dataset on prediction of protein mutant stability have been discussed.

Developing model asphalt systems using molecular simulation : final model.

DOT National Transportation Integrated Search

2009-09-01

Computer based molecular simulations have been used towards developing simple mixture compositions whose : physical properties resemble those of real asphalts. First, Monte Carlo simulations with the OPLS all-atom force : field were used to predict t...

Different parameters support generalization and discrimination learning in Drosophila at the flight simulator.

PubMed

Brembs, Björn; Hempel de Ibarra, Natalie

2006-01-01

We have used a genetically tractable model system, the fruit fly Drosophila melanogaster to study the interdependence between sensory processing and associative processing on learning performance. We investigated the influence of variations in the physical and predictive properties of color stimuli in several different operant-conditioning procedures on the subsequent learning performance. These procedures included context and stimulus generalization as well as color, compound, and conditional discrimination (colors and patterns). A surprisingly complex dependence of the learning performance on the colors' physical and predictive properties emerged, which was clarified by taking into account the fly-subjective perception of the color stimuli. Based on estimates of the stimuli's color and brightness values, we propose that the different tasks are supported by different parameters of the color stimuli; generalization occurs only if the chromaticity is sufficiently similar, whereas discrimination learning relies on brightness differences.

Adaptive method for electron bunch profile prediction

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

Scheinker, Alexander; Gessner, Spencer

2015-10-01

We report on an experiment performed at the Facility for Advanced Accelerator Experimental Tests (FACET) at SLAC National Accelerator Laboratory, in which a new adaptive control algorithm, one with known, bounded update rates, despite operating on analytically unknown cost functions, was utilized in order to provide quasi-real-time bunch property estimates of the electron beam. Multiple parameters, such as arbitrary rf phase settings and other time-varying accelerator properties, were simultaneously tuned in order to match a simulated bunch energy spectrum with a measured energy spectrum. The simple adaptive scheme was digitally implemented using matlab and the experimental physics and industrial controlmore » system. The main result is a nonintrusive, nondestructive, real-time diagnostic scheme for prediction of bunch profiles, as well as other beam parameters, the precise control of which are important for the plasma wakefield acceleration experiments being explored at FACET. © 2015 authors. Published by the American Physical Society.« less

An improved Cauchy number approach for predicting the drag and reconfiguration of flexible vegetation

NASA Astrophysics Data System (ADS)

Whittaker, Peter; Wilson, Catherine A. M. E.; Aberle, Jochen

2015-09-01

An improved model to describe the drag and reconfiguration of flexible riparian vegetation is proposed. The key improvement over previous models is the use of a refined 'vegetative' Cauchy number to explicitly determine the magnitude and rate of the vegetation's reconfiguration. After being derived from dimensional consideration, the model is applied to two experimental data sets. The first contains high-resolution drag force and physical property measurements for twenty-one foliated and defoliated full-scale trees, including specimens of Alnus glutinosa, Populus nigra and Salix alba. The second data set is independent and of a different scale, consisting of drag force and physical property measurements for natural and artificial branches of willow and poplar, under partially and fully submerged flow conditions. Good agreement between the measured and predicted drag forces is observed for both data sets, especially when compared to a more typical 'rigid' approximation, where the effects of reconfiguration are neglected.

A physicochemical investigation of ionic liquid mixtures† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c4sc02931c Click here for additional data file.

PubMed Central

Clough, Matthew T.; Crick, Colin R.; Gräsvik, John; Niedermeyer, Heiko; Whitaker, Oliver P.

2015-01-01

Ionic liquids have earned the reputation of being ‘designer solvents’ due to the wide range of accessible properties and the degree of fine-tuning afforded by varying the constituent ions. Mixtures of ionic liquids offer the opportunity for further fine-tuning of properties. A broad selection of common ionic liquid cations and anions are employed to create a sample of binary and reciprocal binary ionic liquid mixtures, which are analysed and described in this paper. Physical properties such as the conductivity, viscosity, density and phase behaviour (glass transition temperatures) are examined. In addition, thermal stabilities of the mixtures are evaluated. The physical properties examined for these formulations are found to generally adhere remarkably closely to ideal mixing laws, with a few consistent exceptions, allowing for the facile prediction and control of properties of ionic liquid mixtures. PMID:29560198

Effect of water phase transition on dynamic ruptures with thermal pressurization: Numerical simulations with changes in physical properties of water

NASA Astrophysics Data System (ADS)

Urata, Yumi; Kuge, Keiko; Kase, Yuko

2015-02-01

Phase transitions of pore water have never been considered in dynamic rupture simulations with thermal pressurization (TP), although they may control TP. From numerical simulations of dynamic rupture propagation including TP, in the absence of any water phase transition process, we predict that frictional heating and TP are likely to change liquid pore water into supercritical water for a strike-slip fault under depth-dependent stress. This phase transition causes changes of a few orders of magnitude in viscosity, compressibility, and thermal expansion among physical properties of water, thus affecting the diffusion of pore pressure. Accordingly, we perform numerical simulations of dynamic ruptures with TP, considering physical properties that vary with the pressure and temperature of pore water on a fault. To observe the effects of the phase transition, we assume uniform initial stress and no fault-normal variations in fluid density and viscosity. The results suggest that the varying physical properties decrease the total slip in cases with high stress at depth and small shear zone thickness. When fault-normal variations in fluid density and viscosity are included in the diffusion equation, they activate TP much earlier than the phase transition. As a consequence, the total slip becomes greater than that in the case with constant physical properties, eradicating the phase transition effect. Varying physical properties do not affect the rupture velocity, irrespective of the fault-normal variations. Thus, the phase transition of pore water has little effect on dynamic ruptures. Fault-normal variations in fluid density and viscosity may play a more significant role.

Physical Properties of the MER and Beagle II Landing Sites on Mars

NASA Astrophysics Data System (ADS)

Jakosky, B. M.; Pelkey, S. M.; Mellon, M. T.; Putzig, N.; Martinez-Alonso, S.; Murphy, N.; Hynek, B.

2003-12-01

The ESA Beagle II and the NASA Mars Exploration Rover spacecraft are scheduled to land on the martian surface in December 2003 and January 2004, respectively. Mission operations and success depends on the physical properties of the surfaces on which they land. Surface structural characteristics such as the abundances of loose, unconsolidated fine material, of fine material that has been cemented into a duricrust, and of rocks affect the ability to safely land and to successfully sample and traverse the surface. Also, physical properties affect surface and atmospheric temperatures, which affect lander and rover functionality. We are in the process of analyzing surface temperature information for these sites, derived from MGS TES and Odyssey THEMIS daytime and nighttime measurements. Our approach is to: (i) remap thermal inertia using TES data at ~3-km resolution, to obtain the most complete coverage possible; (ii) interpret physical properties from TES coverage in conjunction with other remote-sensing data sets; (iii) map infrared brightness using daytime and nighttime THEMIS data at 100-m resolution, and do qualitative analysis of physical properties and processes; and (iv) derive thermal inertia from THEMIS nighttime data in conjunction with daytime albedo measurements derived from TES, THEMIS, and MOC observations. In addition, we will use measured temperatures and derived thermal inertia to predict surface temperatures for the periods of the missions.

A review on ab initio studies of static, transport, and optical properties of polystyrene under extreme conditions for inertial confinement fusion applications

NASA Astrophysics Data System (ADS)

Hu, S. X.; Collins, L. A.; Boehly, T. R.; Ding, Y. H.; Radha, P. B.; Goncharov, V. N.; Karasiev, V. V.; Collins, G. W.; Regan, S. P.; Campbell, E. M.

2018-05-01

Polystyrene (CH), commonly known as "plastic," has been one of the widely used ablator materials for capsule designs in inertial confinement fusion (ICF). Knowing its precise properties under high-energy-density conditions is crucial to understanding and designing ICF implosions through radiation-hydrodynamic simulations. For this purpose, systematic ab initio studies on the static, transport, and optical properties of CH, in a wide range of density and temperature conditions (ρ = 0.1 to 100 g/cm3 and T = 103 to 4 × 106 K), have been conducted using quantum molecular dynamics (QMD) simulations based on the density functional theory. We have built several wide-ranging, self-consistent material-properties tables for CH, such as the first-principles equation of state, the QMD-based thermal conductivity (κQMD) and ionization, and the first-principles opacity table. This paper is devoted to providing a review on (1) what results were obtained from these systematic ab initio studies; (2) how these self-consistent results were compared with both traditional plasma-physics models and available experiments; and (3) how these first-principles-based properties of polystyrene affect the predictions of ICF target performance, through both 1-D and 2-D radiation-hydrodynamic simulations. In the warm dense regime, our ab initio results, which can significantly differ from predictions of traditional plasma-physics models, compared favorably with experiments. When incorporated into hydrocodes for ICF simulations, these first-principles material properties of CH have produced significant differences over traditional models in predicting 1-D/2-D target performance of ICF implosions on OMEGA and direct-drive-ignition designs for the National Ignition Facility. Finally, we will discuss the implications of these studies on the current small-margin ICF target designs using a CH ablator.

SiC/SiC Cladding Materials Properties Handbook

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

Snead, Mary A.; Katoh, Yutai; Koyanagi, Takaaki

When a new class of material is considered for a nuclear core structure, the in-pile performance is usually assessed based on multi-physics modeling in coordination with experiments. This report aims to provide data for the mechanical and physical properties and environmental resistance of silicon carbide (SiC) fiber–reinforced SiC matrix (SiC/SiC) composites for use in modeling for their application as accidenttolerant fuel cladding for light water reactors (LWRs). The properties are specific for tube geometry, although many properties can be predicted from planar specimen data. This report presents various properties, including mechanical properties, thermal properties, chemical stability under normal and offnormalmore » operation conditions, hermeticity, and irradiation resistance. Table S.1 summarizes those properties mainly for nuclear-grade SiC/SiC composites fabricated via chemical vapor infiltration (CVI). While most of the important properties are available, this work found that data for the in-pile hydrothermal corrosion resistance of SiC materials and for thermal properties of tube materials are lacking for evaluation of SiC-based cladding for LWR applications.« less

An Update on Design Tools for Optimization of CMC 3D Fiber Architectures

NASA Technical Reports Server (NTRS)

Lang, J.; DiCarlo, J.

2012-01-01

Objective: Describe and up-date progress for NASA's efforts to develop 3D architectural design tools for CMC in general and for SIC/SiC composites in particular. Describe past and current sequential work efforts aimed at: Understanding key fiber and tow physical characteristics in conventional 2D and 3D woven architectures as revealed by microstructures in the literature. Developing an Excel program for down-selecting and predicting key geometric properties and resulting key fiber-controlled properties for various conventional 3D architectures. Developing a software tool for accurately visualizing all the key geometric details of conventional 3D architectures. Validating tools by visualizing and predicting the Internal geometry and key mechanical properties of a NASA SIC/SIC panel with a 3D orthogonal architecture. Applying the predictive and visualization tools toward advanced 3D orthogonal SiC/SIC composites, and combining them into a user-friendly software program.

The wavelength dependence and an interpretation of the photometric parameters of Mars

NASA Technical Reports Server (NTRS)

Weaver, W. R.; Meador, W. E.

1976-01-01

The photometric function developed by Meador and Weaver has been used with photometric data from the bright desert areas of Mars to determine the wavelength dependence of the three photometric parameters of that function and to provide some predictions about the physical properties of the surface. Knowledge of the parameters permits the brightness of these areas of Mars to be determined for scattering geometry over the wavelength range of 0.45 to 0.70 micrometer. The changes in the photometric parameters with wavelength are shown to be consistent with qualitative theoretical predictions, and the predictions of surface properties are shown to be consistent with conditions that might exist in these regions of Mars. The photometric function is shown to have good potential as a diagnostic tool for the determination of surface properties, and the consistency of the behavior of the photometric parameters is shown to be good support for the validity of the photometric function.

Experimental studies on thermodynamic effects of developed cavitation

NASA Technical Reports Server (NTRS)

Ruggeri, R. S.

1974-01-01

A method for predicting thermodynamic effects of cavitation (changes in cavity pressure relative to stream vapor pressure) is presented. The prediction method accounts for changes in liquid, liquid temperature, flow velocity, and body scale. Both theoretical and experimental studies used in formulating the method are discussed. The prediction method provided good agreement between predicted and experimental results for geometrically scaled venturis handling four different liquids of widely diverse physical properties. Use of the method requires geometric similarity of the body and cavitated region and a known reference cavity-pressure depression at one operating condition.

Constraining the physical properties of compositionally distinctive surfaces on Mars from overlapping THEMIS observations

NASA Astrophysics Data System (ADS)

Ahern, A.; Rogers, D.

2017-12-01

Better constraints on the physical properties (e.g. grain size, rock abundance, cohesion, porosity and amount of induration) of Martian surface materials can lead to greater understanding of outcrop origin (e.g. via sedimentary, effusive volcanic, pyroclastic processes). Many outcrop surfaces on Mars likely contain near-surface (<3 cm) vertical heterogeneity in physical properties due to thin sediment cover, induration, and physical weathering, that can obscure measurement of the bulk thermal conductivity of the outcrop materials just below. Fortunately, vertical heterogeneity within near-surface materials can result in unique, and possibly predictable, diurnal and seasonal temperature patterns. The KRC thermal model has been utilized in a number of previous studies to predict thermal inertia of surface materials on Mars. Here we use KRC to model surface temperatures from overlapping Mars Odyssey THEMIS surface temperature observations that span multiple seasons and local times, in order to constrain both the nature of vertical heterogeneity and the underlying outcrop thermal inertia for various spectrally distinctive outcrops on Mars. We utilize spectral observations from TES and CRISM to constrain the particle size of the uppermost surface. For this presentation, we will focus specifically on chloride-bearing units in Terra Sirenum and Meridiani Planum, as well as mafic and feldspathic bedrock locations with distinct spectral properties, yet uncertain origins, in Noachis Terra and Nili Fossae. We find that many of these surfaces exhibit variations in apparent thermal inertia with season and local time that are consistent with low thermal inertia materials overlying higher thermal inertia substrates. Work is ongoing to compare surface temperature measurements with modeled two-layer scenarios in order to constrain the top layer thickness and bottom layer thermal inertia. The information will be used to better interpret the origins of these distinctive outcrops.

Prediction of friction coefficients for gases

NASA Technical Reports Server (NTRS)

Taylor, M. F.

1969-01-01

Empirical relations are used for correlating laminar and turbulent friction coefficients for gases, with large variations in the physical properties, flowing through smooth tubes. These relations have been used to correlate friction coefficients for hydrogen, helium, nitrogen, carbon dioxide and air.

Influence of wheat kernel physical properties on the pulverizing process.

PubMed

Dziki, Dariusz; Cacak-Pietrzak, Grażyna; Miś, Antoni; Jończyk, Krzysztof; Gawlik-Dziki, Urszula

2014-10-01

The physical properties of wheat kernel were determined and related to pulverizing performance by correlation analysis. Nineteen samples of wheat cultivars about similar level of protein content (11.2-12.8 % w.b.) and obtained from organic farming system were used for analysis. The kernel (moisture content 10 % w.b.) was pulverized by using the laboratory hammer mill equipped with round holes 1.0 mm screen. The specific grinding energy ranged from 120 kJkg(-1) to 159 kJkg(-1). On the basis of data obtained many of significant correlations (p < 0.05) were found between wheat kernel physical properties and pulverizing process of wheat kernel, especially wheat kernel hardness index (obtained on the basis of Single Kernel Characterization System) and vitreousness significantly and positively correlated with the grinding energy indices and the mass fraction of coarse particles (> 0.5 mm). Among the kernel mechanical properties determined on the basis of uniaxial compression test only the rapture force was correlated with the impact grinding results. The results showed also positive and significant relationships between kernel ash content and grinding energy requirements. On the basis of wheat physical properties the multiple linear regression was proposed for predicting the average particle size of pulverized kernel.

Tuning relaxation dynamics and mechanical properties of polymer films of identical thickness

NASA Astrophysics Data System (ADS)

Kchaou, Marwa; Alcouffe, Pierre; Chandran, Sivasurender; Cassagnau, Philippe; Reiter, Günter; Al Akhrass, Samer

2018-03-01

Using dewetting as a characterization tool, we demonstrate that physical properties of thin polymer films can be regulated and tuned by employing variable processing conditions. For different molecular weights, the variable behavior of polystyrene films of identical thickness, prepared along systematically altered pathways, became predictable through a single parameter P , defined as the ratio of time required over time available for the equilibration of polymers. In particular, preparation-induced residual stresses, the corresponding relaxation times as well as the rupture probability of such films (of identical thickness) varied by orders of magnitude following scaling relations with P . Our experimental findings suggest that we can predictably enhance properties and hence maximize the performance of thin polymer films via appropriately chosen processing conditions.

Quantifying the Interactions Between Soil Thermal Characteristics, Soil Physical Properties, Hydro-geomorphological Conditions and Vegetation Distribution in an Arctic Watershed

NASA Astrophysics Data System (ADS)

Dafflon, B.; Leger, E.; Robert, Y.; Ulrich, C.; Peterson, J. E.; Soom, F.; Biraud, S.; Tran, A. P.; Hubbard, S. S.

2017-12-01

Improving understanding of Arctic ecosystem functioning and parameterization of process-rich hydro-biogeochemical models require advances in quantifying ecosystem properties, from the bedrock to the top of the canopy. In Arctic regions having significant subsurface heterogeneity, understanding the link between soil physical properties (incl. fraction of soil constituents, bedrock depth, permafrost characteristics), thermal behavior, hydrological conditions and landscape properties is particularly challenging yet is critical for predicting the storage and flux of carbon in a changing climate. This study takes place in Seward Peninsula Watersheds near Nome AK and Council AK, which are characterized by an elevation gradient, shallow bedrock, and discontinuous permafrost. To characterize permafrost distribution where the top of permafrost cannot be easily identified with a tile probe (due to rocky soil and/or large thaw layer thickness), we developed a novel technique using vertically resolved thermistor probes to directly sense the temperature regime at multiple depths and locations. These measurements complement electrical imaging, seismic refraction and point-scale data for identification of the various thermal behavior and soil characteristics. Also, we evaluate linkages between the soil physical-thermal properties and the surface properties (hydrological conditions, geomorphic characteristics and vegetation distribution) using UAV-based aerial imaging. Data integration and analysis is supported by numerical approaches that simulate hydrological and thermal processes. Overall, this study enables the identification of watershed structure and the links between various subsurface and landscape properties in representative Arctic watersheds. Results show very distinct trends in vertically resolved soil temperature profiles and strong lateral variations over tens of meters that are linked to zones with various hydrological conditions, soil properties and vegetation types. The interaction between these zones is of strong interest to understand the evolution of the landscape and the permafrost distribution. The obtained information is expected to be useful for improving predictions of Arctic ecosystem feedbacks to climate.

Physical, Hydraulic, and Transport Properties of Sediments and Engineered Materials Associated with Hanford Immobilized Low-Activity Waste

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

Rockhold, Mark L.; Zhang, Z. F.; Meyer, Philip D.

2015-02-28

Current plans for treatment and disposal of immobilized low-activity waste (ILAW) from Hanford’s underground waste storage tanks include vitrification and storage of the glass waste form in a nearsurface disposal facility. This Integrated Disposal Facility (IDF) is located in the 200 East Area of the Hanford Central Plateau. Performance assessment (PA) of the IDF requires numerical modeling of subsurface flow and reactive transport processes over very long periods (thousands of years). The models used to predict facility performance require parameters describing various physical, hydraulic, and transport properties. This report provides updated estimates of physical, hydraulic, and transport properties and parametersmore » for both near- and far-field materials, intended for use in future IDF PA modeling efforts. Previous work on physical and hydraulic property characterization for earlier IDF PA analyses is reviewed and summarized. For near-field materials, portions of this document and parameter estimates are taken from an earlier data package. For far-field materials, a critical review is provided of methodologies used in previous data packages. Alternative methods are described and associated parameters are provided.« less

Composite structural materials

NASA Technical Reports Server (NTRS)

Loewy, Robert G.; Wiberley, Stephen E.

1988-01-01

A decade long program to develop critical advanced composite technology in the areas of physical properties, structural concept and analysis, manufacturing, reliability, and life predictions is reviewed. Specific goals are discussed. The status of the chemical vapor deposition effects on carbon fiber properties; inelastic deformation of metal matrix laminates; fatigue damage in fibrous MMC laminates; delamination fracture toughness in thermoplastic matrix composites; and numerical analysis of composite micromechanical behavior are presented.

Thermodynamics of reformulated automotive fuels

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

Zudkevitch, D.; Murthy, A.K.S.; Gmehling, J.

1995-06-01

Two methods for predicting Reid vapor pressure (Rvp) and initial vapor emissions of reformulated gasoline blends that contain one or more oxygenated compounds show excellent agreement with experimental data. In the first method, method A, D-86 distillation data for gasoline blends are used for predicting Rvp from a simulation of the mini dry vapor pressure equivalent (Dvpe) experiment. The other method, method B, relies on analytical information (PIANO analyses) of the base gasoline and uses classical thermodynamics for simulating the same Rvp equivalent (Rvpe) mini experiment. Method B also predicts composition and other properties for the fuel`s initial vapor emission.more » Method B, although complex, is more useful in that is can predict properties of blends without a D-86 distillation. An important aspect of method B is its capability to predict composition of initial vapor emissions from gasoline blends. Thus, it offers a powerful tool to planners of gasoline blending. Method B uses theoretically sound formulas, rigorous thermodynamic routines and uses data and correlations of physical properties that are in the public domain. Results indicate that predictions made with both methods agree very well with experimental values of Dvpe. Computer simulation methods were programmed and tested.« less

Higher Leptin and Adiponectin Concentrations Predict Poorer Performance-based Physical Functioning in Midlife Women: the Michigan Study of Women’s Health Across the Nation

PubMed Central

Zheng, Huiyong; Mancuso, Peter; Harlow, Siobán D.

2016-01-01

Background. Excess fat mass is a greater contributor to functional limitations than is reduced lean mass or the presence of obesity-related conditions. The impact of fat mass on physical functioning may be due to adipokines, adipose-derived proteins that have pro- or anti-inflammatory properties. Methods. Serum samples from 1996 to 2003 that were assayed for leptin, adiponectin, and resistin were provided by 511 participants from the Michigan site of the Study of Women’s Health Across the Nation. Physical functioning performance was assessed annually during study visits from 1996 to 2003. Results. Among this population of Black and White women (mean baseline age = 45.6 years, SD = 2.7 years), all of whom were premenopausal at baseline, higher baseline leptin concentrations predicted longer stair climb, sit-to-rise, and 2-pound lift times and shorter forward reach distance (all p < .01). This relationship persisted after adjustment for age, BMI, percent skeletal muscle mass, race/ethnicity, economic strain, bodily pain, diabetes, knee osteoarthritis, and C-reactive protein. Baseline total adiponectin concentrations did not predict any mobility measures but did predict quadriceps strength; a 1 µg/mL higher adiponectin concentration was associated with 0.64 Nm lower quadriceps strength (p = .02). Resistin was not associated with any of the physical functioning performance measures. Change in the adipokines was not associated with physical functioning. Conclusion. In this population of middle-aged women, higher baseline leptin concentrations predicted poorer mobility-based functioning, whereas higher adiponectin concentrations predicted reduced quadriceps strength. These findings suggest that the relationship between the adipokines and physical functioning performance is independent of other known correlates of poor functioning. PMID:26302979

Revealing the Physical Properties of GMC Complexes in the Spiral Arms of NGC 6946

NASA Astrophysics Data System (ADS)

Topal, Selçuk; Bayet, Estelle; Bureau, Martin; Walsh, Wilfred; Davis, Timothy A.

2013-03-01

In this study, we probe for the first time the molecular gas physical properties of several star forming regions located in the arms and inter-arms of the spiral galaxy NGC 6946. Combining our observations with additional data found in the literature, we provide in this study the most complete CO ladder ever obtained in these inter-arm and arm regions, i.e. the CO(1-0, 2-1, 3-2, 4-3, 6-5) and 13CO(1-0, 2-1) transitions. For each region studied, we use more precisely the large velocity gradient (LVG) assumption in order to derive the beam-averaged molecular gas physical properties. Namely, we obtained the gas kinetic temperature (i.e. 'best' T K), volume number gas density (i.e. 'best' n(H2)) and CO column density (i.e. 'best' N(CO)) which best reproduce the data for 8 regions investigated. Optical depths were also estimated for a large variety of CO lines in these regions. To identify the best values found, we used two complementary theoretical approaches when comparing the model predictions with the observations, i.e. the χ2 minimisation and the likelihood. Very different physical conditions for the molecular gas from a region to another have been obtained: T K ranges from 10 to 250 K, n(H2) ranges from 102.3 to 107.0 cm-3 and N(CO) ranges from 1015.0 to 1019.3 cm-2 among the arm and inter-arm regions. For each region probed, we also published for the first time the CO spectral line energy distribution (SLED) from CO(1-0) to CO(10-9) for this galaxy, mixing observations and model predictions which provide an essential insight for future follow-up observational programmes. Finally, in this work, we discuss the physical properties we obtained for each region in relation with the presence of young stellar population characteristics such as supernovae remnants (SNRs), Hi holes, Hii regions.

Can different quantum state vectors correspond to the same physical state? An experimental test

NASA Astrophysics Data System (ADS)

Nigg, Daniel; Monz, Thomas; Schindler, Philipp; Martinez, Esteban A.; Hennrich, Markus; Blatt, Rainer; Pusey, Matthew F.; Rudolph, Terry; Barrett, Jonathan

2016-01-01

A century after the development of quantum theory, the interpretation of a quantum state is still discussed. If a physicist claims to have produced a system with a particular quantum state vector, does this represent directly a physical property of the system, or is the state vector merely a summary of the physicist’s information about the system? Assume that a state vector corresponds to a probability distribution over possible values of an unknown physical or ‘ontic’ state. Then, a recent no-go theorem shows that distinct state vectors with overlapping distributions lead to predictions different from quantum theory. We report an experimental test of these predictions using trapped ions. Within experimental error, the results confirm quantum theory. We analyse which kinds of models are ruled out.

Characterization of structural connections using free and forced response test data

NASA Technical Reports Server (NTRS)

Lawrence, Charles; Huckelbridge, Arthur A.

1989-01-01

The accurate prediction of system dynamic response often has been limited by deficiencies in existing capabilities to characterize connections adequately. Connections between structural components often are complex mechanically, and difficult to accurately model analytically. Improved analytical models for connections are needed to improve system dynamic preditions. A procedure for identifying physical connection properties from free and forced response test data is developed, then verified utilizing a system having both a linear and nonlinear connection. Connection properties are computed in terms of physical parameters so that the physical characteristics of the connections can better be understood, in addition to providing improved input for the system model. The identification procedure is applicable to multi-degree of freedom systems, and does not require that the test data be measured directly at the connection locations.

Hierarchical multi-scale approach to validation and uncertainty quantification of hyper-spectral image modeling

NASA Astrophysics Data System (ADS)

Engel, Dave W.; Reichardt, Thomas A.; Kulp, Thomas J.; Graff, David L.; Thompson, Sandra E.

2016-05-01

Validating predictive models and quantifying uncertainties inherent in the modeling process is a critical component of the HARD Solids Venture program [1]. Our current research focuses on validating physics-based models predicting the optical properties of solid materials for arbitrary surface morphologies and characterizing the uncertainties in these models. We employ a systematic and hierarchical approach by designing physical experiments and comparing the experimental results with the outputs of computational predictive models. We illustrate this approach through an example comparing a micro-scale forward model to an idealized solid-material system and then propagating the results through a system model to the sensor level. Our efforts should enhance detection reliability of the hyper-spectral imaging technique and the confidence in model utilization and model outputs by users and stakeholders.

Some predictions of the attached eddy model for a high Reynolds number boundary layer.

PubMed

Nickels, T B; Marusic, I; Hafez, S; Hutchins, N; Chong, M S

2007-03-15

Many flows of practical interest occur at high Reynolds number, at which the flow in most of the boundary layer is turbulent, showing apparently random fluctuations in velocity across a wide range of scales. The range of scales over which these fluctuations occur increases with the Reynolds number and hence high Reynolds number flows are difficult to compute or predict. In this paper, we discuss the structure of these flows and describe a physical model, based on the attached eddy hypothesis, which makes predictions for the statistical properties of these flows and their variation with Reynolds number. The predictions are shown to compare well with the results from recent experiments in a new purpose-built high Reynolds number facility. The model is also shown to provide a clear physical explanation for the trends in the data. The limits of applicability of the model are also discussed.

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

Antropov, Vladimir P; Antonov, Victor N

We present a first-principles investigation of the electronic structure and physical properties of doped lithium nitridometalates Li 2(Li 1-xM x)N (LiMN) with M = Cr, Mn, Fe, Co, and Ni. The diverse properties include the equilibrium magnetic moments, magneto-crystalline anisotropy, magneto-optical Kerr spectra, and x-ray magnetic circular dichroism. We explain the colossal magnetic anisotropy in LiFeN by its unique electronic structure which ultimately leads to a series of unusual physical properties. The most unique property is a complete suppression of relativistic effects and freezing of orbital moments for in-plane orientation of the magnetization. This leads to the colossal spatial anisotropymore » of many magnetic properties including energy, Kerr, and dichroism effects. LiFeN is identified as an ultimate single-ion anisotropy system where a nearly insulating state can be produced by a spin orbital coupling alone. A very nontrivial strongly fluctuating and sign changing character of the magnetic anisotropy with electronic 3d-atomic doping is predicted theoretically. A large and highly anisotropic Kerr effect due to the interband transitions between atomic-like Fe 3d bands is found for LiFeN. A giant anisotropy of the x-ray magnetic circular dichroism for the Fe K spectrum and a very weak one for the Fe L 2,3 spectra in LiFeN are also predicted.« less

Concentration Dependent Speciation and Mass Transport Properties of Switchable Polarity Solvents

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

Aaron D. Wilson; Christopher J. Orme

2014-12-01

Tertiary amine switchable polarity solvents (SPS) consisting of predominantly water, tertiary amine, and tertiary ammonium and bicarbonate ions were produced at various concentrations for three different amines: N,N-dimethylcyclohexylamine, N,N-dimethyloctylamine, and 1 cyclohexylpiperidine. For all concentrations, physical properties were measured including viscosity, molecular diffusion coefficients, freezing point depression, and density. Based on these measurements a variation on the Mark Houwink equation was developed to predict the viscosity of any tertiary amine SPS as a function of concentration using the amine’s molecular mass. The observed physical properties allowed the identification of solution state speciation of non-osmotic SPS, where the amine to carbonicmore » acid ratio is significantly greater than one. These results indicate that at most concentrations the stoichiometric excess amine is involved in solvating a proton with two amines. The physical properties of osmotic SPS have consistent concentration dependence behavior over a wide range of concentrations; this consistence suggests osmotic pressures based on low concentrations freezing point studies can be reliably extrapolated to higher concentrations.« less

Acoustical and Other Physical Properties of Marine Sediments

DTIC Science & Technology

1991-01-01

Granular Structure of Rocks 4. Anisotropic Poroelasticity and Biot’s Parameters PART 1 A simple analytical model has been developed to describe the...mentioned properties. PART 4 Prediction of wave propagation in a submarine environment re- quires modeling the acoustic response of ocean bottom...Biot’s theory is a promising approach for modelling acoustic wave propa- gation in ocean sediments which generally consist of elastic or viscoelastic

Environmental factors limiting fertilisation and larval success in corals

NASA Astrophysics Data System (ADS)

Woods, Rachael M.; Baird, Andrew H.; Mizerek, Toni L.; Madin, Joshua S.

2016-12-01

Events in the early life history of reef-building corals, including fertilisation and larval survival, are susceptible to changes in the chemical and physical properties of sea water. Quantifying how changes in water quality affect these events is therefore important for understanding and predicting population establishment in novel and changing environments. A review of the literature identified that levels of salinity, temperature, pH, suspended sediment, nutrients and heavy metals affect coral early life-history stages to various degrees. In this study, we combined published experimental data to determine the relative importance of sea water properties for coral fertilisation success and larval survivorship. Of the water properties manipulated in experiments, fertilisation success was most sensitive to suspended sediment, copper, salinity, phosphate and ammonium. Larval survivorship was sensitive to copper, lead and salinity. A combined model was developed that estimated the joint probability of both fertilisation and larval survivorship in sea water with different chemical and physical properties. We demonstrated the combined model using water samples from Sydney and Lizard Island in Australia to estimate the likelihood of larvae surviving through both stages of development to settlement competency. Our combined model could be used to recommend targets for water quality in coastal waterways as well as to predict the potential for species to expand their geographical ranges in response to climate change.

Gravitational waves from warm inflation

NASA Astrophysics Data System (ADS)

Li, Xi-Bin; Wang, He; Zhu, Jian-Yang

2018-03-01

A fundamental prediction of inflation is a nearly scale-invariant spectrum of gravitational wave. The features of such a signal provide extremely important information about the physics of the early universe. In this paper, we focus on several topics about warm inflation. First, we discuss the stability property about warm inflation based on nonequilibrium statistical mechanics, which gives more fundamental physical illustrations to thermal property of such model. Then, we calculate the power spectrum of gravitational waves generated during warm inflation, in which there are three components contributing to such spectrum: thermal term, quantum term, and cross term combining the both. We also discuss some interesting properties about these terms and illustrate them in different panels. As a model different from cold inflation, warm inflation model has its individual properties in observational practice, so we finally give a discussion about the observational effect to distinguish it from cold inflation.

Correlation between structure and physical properties of chalcogenide glasses in the AsxSe1-x system

NASA Astrophysics Data System (ADS)

Yang, Guang; Bureau, Bruno; Rouxel, Tanguy; Gueguen, Yann; Gulbiten, Ozgur; Roiland, Claire; Soignard, Emmanuel; Yarger, Jeffery L.; Troles, Johann; Sangleboeuf, Jean-Christophe; Lucas, Pierre

2010-11-01

Physical properties of chalcogenide glasses in the AsxSe1-x system have been measured as a function of composition including the Young’s modulus E , shear modulus G , bulk modulus K , Poisson’s ratio ν , the density ρ , and the glass transition Tg . All these properties exhibit a relatively sharp extremum at the average coordination number ⟨r⟩=2.4 . The structural origin of this trend is investigated by Raman spectroscopy and nuclear magnetic resonance. It is shown that the reticulation of the glass structure increases continuously until x=0.4 following the “chain crossing model” and then undergoes a transition toward a lower dimension pyramidal network containing an increasing number of molecular inclusions at x>0.4 . Simple theoretical estimates of the network bonding energy confirm a mismatch between the values of mechanical properties measured experimentally and the values predicted from a continuously reticulated structure, therefore corroborating the formation of a lower dimension network at high As content. The evolution of a wide range of physical properties is consistent with this sharp structural transition and suggests that there is no intermediate phase in these glasses at room temperature.

Overview of T.E.S.T. (Toxicity Estimation Software Tool)

EPA Science Inventory

This talk provides an overview of T.E.S.T. (Toxicity Estimation Software Tool). T.E.S.T. predicts toxicity values and physical properties using a variety of different QSAR (quantitative structure activity relationship) approaches including hierarchical clustering, group contribut...

Clinical performance of amalgam as predicted by physical property tests.

PubMed

Gale, E N; Osborne, J W

1980-01-01

For a number of years, dentistry has relied upon laboratory data to select and to certify the materials to be used in restorations. The data obtained from laboratory studies are used as criteria for clinical performance and also for sales promotion.

Cardiovascular Outcomes and the Physical and Chemical Properties of Metal Ions Found in Particulate Matter Air Pollution: A QICAR Study

PubMed Central

Meng, Qingyu; Lu, Shou-En; Buckley, Barbara; Welsh, William J.; Whitsel, Eric A.; Hanna, Adel; Yeatts, Karin B.; Warren, Joshua; Herring, Amy H.; Xiu, Aijun

2013-01-01

Background: This paper presents an application of quantitative ion character–activity relationships (QICAR) to estimate associations of human cardiovascular (CV) diseases (CVDs) with a set of metal ion properties commonly observed in ambient air pollutants. QICAR has previously been used to predict ecotoxicity of inorganic metal ions based on ion properties. Objectives: The objective of this work was to examine potential associations of biological end points with a set of physical and chemical properties describing inorganic metal ions present in exposures using QICAR. Methods: Chemical and physical properties of 17 metal ions were obtained from peer-reviewed publications. Associations of cardiac arrhythmia, myocardial ischemia, myocardial infarction, stroke, and thrombosis with exposures to metal ions (measured as inference scores) were obtained from the Comparative Toxicogenomics Database (CTD). Robust regressions were applied to estimate the associations of CVDs with ion properties. Results: CVD was statistically significantly associated (Bonferroni-adjusted significance level of 0.003) with many ion properties reflecting ion size, solubility, oxidation potential, and abilities to form covalent and ionic bonds. The properties are relevant for reactive oxygen species (ROS) generation, which has been identified as a possible mechanism leading to CVDs. Conclusion: QICAR has the potential to complement existing epidemiologic methods for estimating associations between CVDs and air pollutant exposures by providing clues about the underlying mechanisms that may explain these associations. PMID:23462649

Growth, structure, and properties of epitaxial thin films of first-principles predicted multiferroic Bi2FeCrO6

NASA Astrophysics Data System (ADS)

Nechache, Riad; Harnagea, Catalin; Pignolet, Alain; Normandin, François; Veres, Teodor; Carignan, Louis-Philippe; Ménard, David

2006-09-01

The authors report the structural and physical properties of epitaxial Bi2FeCrO6 thin films on epitaxial SrRuO3 grown on (100)-oriented SrTiO3 substrates by pulsed laser ablation. The 300nm thick films exhibit both ferroelectricity and magnetism at room temperature with a maximum dielectric polarization of 2.8μC /cm2 at Emax=82kV/cm and a saturated magnetization of 20emu/cm3 (corresponding to ˜0.26μB per rhombohedral unit cell), with coercive fields below 100Oe. The results confirm the predictions made using ab initio calculations about the existence of multiferroic properties in Bi2FeCrO6.

Thermal Decomposition Synthesis of Iron Oxide Nanoparticles with Diminished Magnetic Dead Layer by Controlled Addition of Oxygen.

PubMed

Unni, Mythreyi; Uhl, Amanda M; Savliwala, Shehaab; Savitzky, Benjamin H; Dhavalikar, Rohan; Garraud, Nicolas; Arnold, David P; Kourkoutis, Lena F; Andrew, Jennifer S; Rinaldi, Carlos

2017-02-28

Decades of research focused on size and shape control of iron oxide nanoparticles have led to methods of synthesis that afford excellent control over physical size and shape but comparatively poor control over magnetic properties. Popular synthesis methods based on thermal decomposition of organometallic precursors in the absence of oxygen have yielded particles with mixed iron oxide phases, crystal defects, and poorer than expected magnetic properties, including the existence of a thick "magnetically dead layer" experimentally evidenced by a magnetic diameter significantly smaller than the physical diameter. Here, we show how single-crystalline iron oxide nanoparticles with few defects and similar physical and magetic diameter distributions can be obtained by introducing molecular oxygen as one of the reactive species in the thermal decomposition synthesis. This is achieved without the need for any postsynthesis oxidation or thermal annealing. These results address a significant challenge in the synthesis of nanoparticles with predictable magnetic properties and could lead to advances in applications of magnetic nanoparticles.

Retrieving the properties of ice-phase precipitation with multi-frequency radar measurements

NASA Astrophysics Data System (ADS)

Mace, G. G.; Gergely, M.; Mascio, J.

2017-12-01

The objective of most retrieval algorithms applied to remote sensing measurements is the microphysical properties that a model might predict such as condensed water content, particle number, or effective size. However, because ice crystals grow and aggregate into complex non spherical shapes, the microphysical properties of interest are very much dependent on the physical characteristics of the precipitation such as how mass and crystal area are distributed as a function of particle size. Such physical properties also have a strong influence on how microwave electromagnetic energy scatters from ice crystals causing significant ambiguity in retrieval algorithms. In fact, passive and active microwave remote sensing measurements are typically nearly as sensitive to the ice crystal physical properties as they are to the microphysical characteristics that are typically the aim of the retrieval algorithm. There has, however, been active development of multi frequency algorithms recently that attempt to ameliorate and even exploit this sensitivity. In this paper, we will review these approaches and present practical applications of retrieving ice crystal properties such as mass- and area dimensional relationships from single and dual frequency radar measurements of precipitating ice using data collected aboard ship in the Southern Ocean and from remote sensors in the Rocky Mountains of the Western U.S.

Organic Chemistry in Two Dimensions: Surface-Functionalized Polymers and Self-Assembled Monolayer Films

DTIC Science & Technology

1988-09-01

surfaces as components of materials . In particular, we hope to develop the ability to rationalize and predict the macroscooic properties of surfaces...of much of the current research in areas such as materials science, condensed matter and device physics, and polymer physical chemistry. Surface...6 Underlying our program in surface chemistry is a broad interest in the prop- erties of organic surfaces as components of materials . In particular

Updating Physical and Chemical Characteristics of Fly Ash for Use in Concrete

DOT National Transportation Integrated Search

2017-12-22

When incorporated in concrete mixtures, fly ashes are known to influence both its fresh and hardened properties. An accurate and quick technique to predict the extent of this influence based on the characteristics of fly ash would be highly beneficia...

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

Michaelides, Angelos, E-mail: angelos.michaelides@ucl.ac.uk; Martinez, Todd J.; Alavi, Ali

This Special Topic section on Advanced Electronic Structure Methods for Solids and Surfaces contains a collection of research papers that showcase recent advances in the high accuracy prediction of materials and surface properties. It provides a timely snapshot of a growing field that is of broad importance to chemistry, physics, and materials science.

REVIEWS OF TOPICAL PROBLEMS: Physics of pulsar magnetospheres

NASA Astrophysics Data System (ADS)

Beskin, Vasilii S.; Gurevich, Aleksandr V.; Istomin, Yakov N.

1986-10-01

A self-consistent model of the magnetosphere of a pulsar is constructed. This model is based on a successive solution of the equations describing global properties of the magnetosphere and on a comparison of the basic predictions of the developed theory and observational data.

Field-Scale Evaluation of Infiltration Parameters From Soil Texture for Hydrologic Analysis

NASA Astrophysics Data System (ADS)

Springer, Everett P.; Cundy, Terrance W.

1987-02-01

Recent interest in predicting soil hydraulic properties from simple physical properties such as texture has major implications in the parameterization of physically based models of surface runoff. This study was undertaken to (1) compare, on a field scale, soil hydraulic parameters predicted from texture to those derived from field measurements and (2) compare simulated overland flow response using these two parameter sets. The parameters for the Green-Ampt infiltration equation were obtained from field measurements and using texture-based predictors for two agricultural fields, which were mapped as single soil units. Results of the analyses were that (1) the mean and variance of the field-based parameters were not preserved by the texture-based estimates, (2) spatial and cross correlations between parameters were induced by the texture-based estimation procedures, (3) the overland flow simulations using texture-based parameters were significantly different than those from field-based parameters, and (4) simulations using field-measured hydraulic conductivities and texture-based storage parameters were very close to simulations using only field-based parameters.

Computationally-Guided Synthetic Control over Pore Size in Isostructural Porous Organic Cages

DOE PAGES

Slater, Anna G.; Reiss, Paul S.; Pulido, Angeles; ...

2017-06-20

The physical properties of 3-D porous solids are defined by their molecular geometry. Hence, precise control of pore size, pore shape, and pore connectivity are needed to tailor them for specific applications. However, for porous molecular crystals, the modification of pore size by adding pore-blocking groups can also affect crystal packing in an unpredictable way. This precludes strategies adopted for isoreticular metal-organic frameworks, where addition of a small group, such as a methyl group, does not affect the basic framework topology. Here, we narrow the pore size of a cage molecule, CC3, in a systematic way by introducing methyl groupsmore » into the cage windows. Computational crystal structure prediction was used to anticipate the packing preferences of two homochiral methylated cages, CC14-R and CC15-R, and to assess the structure-energy landscape of a CC15-R/CC3-S cocrystal, designed such that both component cages could be directed to pack with a 3-D, interconnected pore structure. The experimental gas sorption properties of these three cage systems agree well with physical properties predicted by computational energy-structure-function maps.« less

Geometrical basis for the Standard Model

NASA Astrophysics Data System (ADS)

Potter, Franklin

1994-02-01

The robust character of the Standard Model is confirmed. Examination of its geometrical basis in three equivalent internal symmetry spaces-the unitary plane C 2, the quaternion space Q, and the real space R 4—as well as the real space R 3 uncovers mathematical properties that predict the physical properties of leptons and quarks. The finite rotational subgroups of the gauge group SU(2) L × U(1) Y generate exactly three lepton families and four quark families and reveal how quarks and leptons are related. Among the physical properties explained are the mass ratios of the six leptons and eight quarks, the origin of the left-handed preference by the weak interaction, the geometrical source of color symmetry, and the zero neutrino masses. The ( u, d) and ( c, s) quark families team together to satisfy the triangle anomaly cancellation with the electron family, while the other families pair one-to-one for cancellation. The spontaneously broken symmetry is discrete and needs no Higgs mechanism. Predictions include all massless neutrinos, the top quark at 160 GeV/ c 2, the b' quark at 80 GeV/ c 2, and the t' quark at 2600 GeV/ c 2.

Computationally-Guided Synthetic Control over Pore Size in Isostructural Porous Organic Cages

PubMed Central

2017-01-01

The physical properties of 3-D porous solids are defined by their molecular geometry. Hence, precise control of pore size, pore shape, and pore connectivity are needed to tailor them for specific applications. However, for porous molecular crystals, the modification of pore size by adding pore-blocking groups can also affect crystal packing in an unpredictable way. This precludes strategies adopted for isoreticular metal–organic frameworks, where addition of a small group, such as a methyl group, does not affect the basic framework topology. Here, we narrow the pore size of a cage molecule, CC3, in a systematic way by introducing methyl groups into the cage windows. Computational crystal structure prediction was used to anticipate the packing preferences of two homochiral methylated cages, CC14-R and CC15-R, and to assess the structure–energy landscape of a CC15-R/CC3-S cocrystal, designed such that both component cages could be directed to pack with a 3-D, interconnected pore structure. The experimental gas sorption properties of these three cage systems agree well with physical properties predicted by computational energy–structure–function maps. PMID:28776015

Computationally-Guided Synthetic Control over Pore Size in Isostructural Porous Organic Cages

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

Slater, Anna G.; Reiss, Paul S.; Pulido, Angeles

The physical properties of 3-D porous solids are defined by their molecular geometry. Hence, precise control of pore size, pore shape, and pore connectivity are needed to tailor them for specific applications. However, for porous molecular crystals, the modification of pore size by adding pore-blocking groups can also affect crystal packing in an unpredictable way. This precludes strategies adopted for isoreticular metal-organic frameworks, where addition of a small group, such as a methyl group, does not affect the basic framework topology. Here, we narrow the pore size of a cage molecule, CC3, in a systematic way by introducing methyl groupsmore » into the cage windows. Computational crystal structure prediction was used to anticipate the packing preferences of two homochiral methylated cages, CC14-R and CC15-R, and to assess the structure-energy landscape of a CC15-R/CC3-S cocrystal, designed such that both component cages could be directed to pack with a 3-D, interconnected pore structure. The experimental gas sorption properties of these three cage systems agree well with physical properties predicted by computational energy-structure-function maps.« less

QSAR Methods.

PubMed

Gini, Giuseppina

2016-01-01

In this chapter, we introduce the basis of computational chemistry and discuss how computational methods have been extended to some biological properties and toxicology, in particular. Since about 20 years, chemical experimentation is more and more replaced by modeling and virtual experimentation, using a large core of mathematics, chemistry, physics, and algorithms. Then we see how animal experiments, aimed at providing a standardized result about a biological property, can be mimicked by new in silico methods. Our emphasis here is on toxicology and on predicting properties through chemical structures. Two main streams of such models are available: models that consider the whole molecular structure to predict a value, namely QSAR (Quantitative Structure Activity Relationships), and models that find relevant substructures to predict a class, namely SAR. The term in silico discovery is applied to chemical design, to computational toxicology, and to drug discovery. We discuss how the experimental practice in biological science is moving more and more toward modeling and simulation. Such virtual experiments confirm hypotheses, provide data for regulation, and help in designing new chemicals.

Electric Conduction in Solids: a Pedagogical Approach Supported by Laboratory Measurements and Computer Modelling Environments

NASA Astrophysics Data System (ADS)

Bonura, A.; Capizzo, M. C.; Fazio, C.; Guastella, I.

2008-05-01

In this paper we present a pedagogic approach aimed at modeling electric conduction in semiconductors, built by using NetLogo, a programmable modeling environment for building and exploring multi-agent systems. `Virtual experiments' are implemented to confront predictions of different microscopic models with real measurements of electric properties of matter, such as resistivity. The relations between these electric properties and other physical variables, like temperature, are, then, analyzed.

Hierarchical Multi-Scale Approach To Validation and Uncertainty Quantification of Hyper-Spectral Image Modeling

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

Engel, David W.; Reichardt, Thomas A.; Kulp, Thomas J.

Validating predictive models and quantifying uncertainties inherent in the modeling process is a critical component of the HARD Solids Venture program [1]. Our current research focuses on validating physics-based models predicting the optical properties of solid materials for arbitrary surface morphologies and characterizing the uncertainties in these models. We employ a systematic and hierarchical approach by designing physical experiments and comparing the experimental results with the outputs of computational predictive models. We illustrate this approach through an example comparing a micro-scale forward model to an idealized solid-material system and then propagating the results through a system model to the sensormore » level. Our efforts should enhance detection reliability of the hyper-spectral imaging technique and the confidence in model utilization and model outputs by users and stakeholders.« less

Engineering the Mechanical Properties of Polymer Networks with Precise Doping of Primary Defects.

PubMed

Chan, Doreen; Ding, Yichuan; Dauskardt, Reinhold H; Appel, Eric A

2017-12-06

Polymer networks are extensively utilized across numerous applications ranging from commodity superabsorbent polymers and coatings to high-performance microelectronics and biomaterials. For many applications, desirable properties are known; however, achieving them has been challenging. Additionally, the accurate prediction of elastic modulus has been a long-standing difficulty owing to the presence of loops. By tuning the prepolymer formulation through precise doping of monomers, specific primary network defects can be programmed into an elastomeric scaffold, without alteration of their resulting chemistry. The addition of these monomers that respond mechanically as primary defects is used both to understand their impact on the resulting mechanical properties of the materials and as a method to engineer the mechanical properties. Indeed, these materials exhibit identical bulk and surface chemistry, yet vastly different mechanical properties. Further, we have adapted the real elastic network theory (RENT) to the case of primary defects in the absence of loops, thus providing new insights into the mechanism for material strength and failure in polymer networks arising from primary network defects, and to accurately predict the elastic modulus of the polymer system. The versatility of the approach we describe and the fundamental knowledge gained from this study can lead to new advancements in the development of novel materials with precisely defined and predictable chemical, physical, and mechanical properties.

Experimental test of quantum nonlocality in three-photon Greenberger-Horne-Zeilinger entanglement

PubMed

Pan; Bouwmeester; Daniell; Weinfurter; Zeilinger

2000-02-03

Bell's theorem states that certain statistical correlations predicted by quantum physics for measurements on two-particle systems cannot be understood within a realistic picture based on local properties of each individual particle-even if the two particles are separated by large distances. Einstein, Podolsky and Rosen first recognized the fundamental significance of these quantum correlations (termed 'entanglement' by Schrodinger) and the two-particle quantum predictions have found ever-increasing experimental support. A more striking conflict between quantum mechanical and local realistic predictions (for perfect correlations) has been discovered; but experimental verification has been difficult, as it requires entanglement between at least three particles. Here we report experimental confirmation of this conflict, using our recently developed method to observe three-photon entanglement, or 'Greenberger-Horne-Zeilinger' (GHZ) states. The results of three specific experiments, involving measurements of polarization correlations between three photons, lead to predictions for a fourth experiment; quantum physical predictions are mutually contradictory with expectations based on local realism. We find the results of the fourth experiment to be in agreement with the quantum prediction and in striking conflict with local realism.

Prediction of Physical Properties of Nanofiltration Membranes for Neutral and Charged Solutes

EPA Science Inventory

Two commercial nanofiltration (NF) membranes viz., NF 300 MWCO and NF 250 MWCO were used for neutral and charged solute species viz., glucose, sodium chloride and magnesium chloride to investigate their rejection rates using Donnan steric pore model (DSPM) and DSPM-dielectric exc...

Composite structural materials. [aircraft applications

NASA Technical Reports Server (NTRS)

Ansell, G. S.; Loewy, R. G.; Wiberley, S. E.

1981-01-01

The development of composite materials for aircraft applications is addressed with specific consideration of physical properties, structural concepts and analysis, manufacturing, reliability, and life prediction. The design and flight testing of composite ultralight gliders is documented. Advances in computer aided design and methods for nondestructive testing are also discussed.

Application of spatial pedotransfer functions to understand soil modulation of vegetation response to climate

USDA-ARS?s Scientific Manuscript database

A fundamental knowledge gap in understanding land-atmosphere interactions is accurate, high resolution spatial representation of soil physical and hydraulic properties. We present a novel approach to predict hydraulic soil parameters by combining digital soil mapping techniques with pedotransfer fun...

Molecular modeling of polycarbonate materials: Glass transition and mechanical properties

NASA Astrophysics Data System (ADS)

Palczynski, Karol; Wilke, Andreas; Paeschke, Manfred; Dzubiella, Joachim

2017-09-01

Linking the experimentally accessible macroscopic properties of thermoplastic polymers to their microscopic static and dynamic properties is a key requirement for targeted material design. Classical molecular dynamics simulations enable us to study the structural and dynamic behavior of molecules on microscopic scales, and statistical physics provides a framework for relating these properties to the macroscopic properties. We take a first step toward creating an automated workflow for the theoretical prediction of thermoplastic material properties by developing an expeditious method for parameterizing a simple yet surprisingly powerful coarse-grained bisphenol-A polycarbonate model which goes beyond previous coarse-grained models and successfully reproduces the thermal expansion behavior, the glass transition temperature as a function of the molecular weight, and several elastic properties.

Critical assessment of density functional theory for computing vibrational (hyper)polarizabilities

NASA Astrophysics Data System (ADS)

Zaleśny, R.; Bulik, I. W.; Mikołajczyk, M.; Bartkowiak, W.; Luis, J. M.; Kirtman, B.; Avramopoulos, A.; Papadopoulos, M. G.

2012-12-01

Despite undisputed success of the density functional theory (DFT) in various branches of chemistry and physics, an application of the DFT for reliable predictions of nonlinear optical properties of molecules has been questioned a decade ago. As it was shown by Champagne, et al. [1, 2, 3] most conventional DFT schemes were unable to qualitatively predict the response of conjugated oligomers to a static electric field. Long-range corrected (LRC) functionals, like LC-BLYP or CAM-B3LYP, have been proposed to alleviate this deficiency. The reliability of LRC functionals for evaluating molecular (hyper)polarizabilities is studied for various groups of organic systems, with a special focus on vibrational corrections to the electric properties.

Ultrasonic evaluation of the physical and mechanical properties of granites.

PubMed

Vasconcelos, G; Lourenço, P B; Alves, C A S; Pamplona, J

2008-09-01

Masonry is the oldest building material that survived until today, being used all over the world and being present in the most impressive historical structures as an evidence of spirit of enterprise of ancient cultures. Conservation, rehabilitation and strengthening of the built heritage and protection of human lives are clear demands of modern societies. In this process, the use of nondestructive methods has become much common in the diagnosis of structural integrity of masonry elements. With respect to the evaluation of the stone condition, the ultrasonic pulse velocity is a simple and economical tool. Thus, the central issue of the present paper concerns the evaluation of the suitability of the ultrasonic pulse velocity method for describing the mechanical and physical properties of granites (range size between 0.1-4.0 mm and 0.3-16.5 mm) and for the assessment of its weathering state. The mechanical properties encompass the compressive and tensile strength and modulus of elasticity, and the physical properties include the density and porosity. For this purpose, measurements of the longitudinal ultrasonic pulse velocity with distinct natural frequency of the transducers were carried out on specimens with different size and shape. A discussion of the factors that induce variations on the ultrasonic velocity is also provided. Additionally, statistical correlations between ultrasonic pulse velocity and mechanical and physical properties of granites are presented and discussed. The major output of the work is the confirmation that ultrasonic pulse velocity can be effectively used as a simple and economical nondestructive method for a preliminary prediction of mechanical and physical properties, as well as a tool for the assessment of the weathering changes of granites that occur during the serviceable life. This is of much interest due to the usual difficulties in removing specimens for mechanical characterization.

A Focused Fundamental Study of Predicting Materials Degradation & Fatigue. Volume 1

DTIC Science & Technology

1997-05-31

physical properties are: bulk modulus, shear strength, coefficient of friction, modulus of elasticity/ rigidity and Poisson’s ratio. Each of these physical...acting on a subsurface crack when abrasive motion occurs on the surface using linear elastic fracture mechanics theory. Both mechanisms involve a...The body of the scattering 5 cell was a 4-way Swagelok*(Crawford Fitting Co., Solon, OH) connector with a 1.5 mm hole drilled in the top for

Adolescents’ Aggression to Parents: Longitudinal Links with Parents’ Physical Aggression

PubMed Central

Margolin, Gayla; Baucom, Brian R.

2014-01-01

Purpose To investigate whether parents’ previous physical aggression (PPA) exhibited during early adolescence is associated with adolescents’ subsequent parent-directed aggression even beyond parents’ concurrent physical aggression (CPA); to investigate whether adolescents’ emotion dysregulation and attitudes condoning child-to-parent aggression moderate associations. Methods Adolescents (N = 93) and their parents participated in a prospective, longitudinal study. Adolescents and parents reported at waves 1–3 on four types of parents’ PPA (mother-to-adolescent, father-to-adolescent, mother-to-father, father-to-mother). Wave 3 assessments also included adolescents’ emotion dysregulation, attitudes condoning aggression, and externalizing behaviors. At waves 4 and 5, adolescents and parents reported on adolescents’ parent-directed physical aggression, property damage, and verbal aggression, and on parents’ CPA Results Parents’ PPA emerged as a significant indicator of adolescents’ parent-directed physical aggression (odds ratio [OR]: 1.25, 95% confidence interval [CI]: 1.0–1.55; p = .047), property damage (OR: 1.29, 95% CI: 1.1–1.5, p = .002), and verbal aggression (OR: 1.35, 95% CI: 1.15–1.6, p < .001) even controlling for adolescents’ sex, externalizing behaviors, and family income. When controlling for parents’ CPA, previous mother-to-adolescent aggression still predicted adolescents’ parent-directed physical aggression (OR: 5.56, 95% CI: 1.82–17.0, p = .003), and father-to-mother aggression predicted adolescents’ parent-directed verbal aggression (OR: 1.86, 95% CI: 1.0–3.3, p = .036). Emotion dysregulation and attitudes condoning aggression did not produce direct or moderated effects. Conclusions Adolescents’ parent-directed aggression deserves greater attention in discourse about lasting, adverse effects of even minor forms of parents’ physical aggression. Future research should investigate parent-directed aggression as an early signal of aggression into adulthood. PMID:25037891

Quantitative structure--property relationships for enhancing predictions of synthetic organic chemical removal from drinking water by granular activated carbon.

PubMed

Magnuson, Matthew L; Speth, Thomas F

2005-10-01

Granular activated carbon is a frequently explored technology for removing synthetic organic contaminants from drinking water sources. The success of this technology relies on a number of factors based not only on the adsorptive properties of the contaminant but also on properties of the water itself, notably the presence of substances in the water which compete for adsorption sites. Because it is impractical to perform field-scale evaluations for all possible contaminants, the pore surface diffusion model (PSDM) has been developed and used to predict activated carbon column performance using single-solute isotherm data as inputs. Many assumptions are built into this model to account for kinetics of adsorption and competition for adsorption sites. This work further evaluates and expands this model, through the use of quantitative structure-property relationships (QSPRs) to predict the effect of natural organic matter fouling on activated carbon adsorption of specific contaminants. The QSPRs developed are based on a combination of calculated topographical indices and quantum chemical parameters. The QSPRs were evaluated in terms of their statistical predictive ability,the physical significance of the descriptors, and by comparison with field data. The QSPR-enhanced PSDM was judged to give results better than what could previously be obtained.

Integration of experimental and computational methods for identifying geometric, thermal and diffusive properties of biomaterials

NASA Astrophysics Data System (ADS)

Weres, Jerzy; Kujawa, Sebastian; Olek, Wiesław; Czajkowski, Łukasz

2016-04-01

Knowledge of physical properties of biomaterials is important in understanding and designing agri-food and wood processing industries. In the study presented in this paper computational methods were developed and combined with experiments to enhance identification of agri-food and forest product properties, and to predict heat and water transport in such products. They were based on the finite element model of heat and water transport and supplemented with experimental data. Algorithms were proposed for image processing, geometry meshing, and inverse/direct finite element modelling. The resulting software system was composed of integrated subsystems for 3D geometry data acquisition and mesh generation, for 3D geometry modelling and visualization, and for inverse/direct problem computations for the heat and water transport processes. Auxiliary packages were developed to assess performance, accuracy and unification of data access. The software was validated by identifying selected properties and using the estimated values to predict the examined processes, and then comparing predictions to experimental data. The geometry, thermal conductivity, specific heat, coefficient of water diffusion, equilibrium water content and convective heat and water transfer coefficients in the boundary layer were analysed. The estimated values, used as an input for simulation of the examined processes, enabled reduction in the uncertainty associated with predictions.

A review on ab initio studies of static, transport, and optical properties of polystyrene under extreme conditions for inertial confinement fusion applications

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

Collins, L. A.; Boehly, T. R.; Ding, Y. H.

Polystyrene (CH), commonly known as “plastic,” has been one of the widely used ablator materials for capsule designs in inertial confinement fusion (ICF). Knowing its precise properties under high-energy-density conditions is crucial to understanding and designing ICF implosions through radiation–hydrodynamic simulations. For this purpose, systematic ab initio studies on the static, transport, and optical properties of CH, in a wide range of density and temperature conditions (ρ= 0.1 to 100 g/cm 3 and T = 10 3 to 4 × 10 6K), have been conducted using quantum molecular dynamics (QMD) simulations based on the density functional theory. We have builtmore » several wide-ranging, self-consistent material-properties tables for CH, such as the first-principles equation of state (FPEOS), the QMD-based thermal conductivity (Κ QMD) and ionization, and the first-principles opacity table (FPOT). This paper is devoted to providing a review on (1) what results were obtained from these systematic ab initio studies; (2) how these self-consistent results were compared with both traditional plasma-physics models and available experiments; and (3) how these first-principles–based properties of polystyrene affect the predictions of ICF target performance, through both 1-D and 2-D radiation–hydrodynamic simulations. In the warm dense regime, our ab initio results, which can significantly differ from predictions of traditional plasma-physics models, compared favorably with experiments. When incorporated into hydrocodes for ICF simulations, these first-principles material properties of CH have produced significant differences over traditional models in predicting 1-D/2-D target performance of ICF implosions on OMEGA and direct-drive–ignition designs for the National Ignition Facility. Lastly, we will discuss the implications of these studies on the current small-margin ICF target designs using a CH ablator.« less

A review on ab initio studies of static, transport, and optical properties of polystyrene under extreme conditions for inertial confinement fusion applications

DOE PAGES

Collins, L. A.; Boehly, T. R.; Ding, Y. H.; ...

2018-03-23

Polystyrene (CH), commonly known as “plastic,” has been one of the widely used ablator materials for capsule designs in inertial confinement fusion (ICF). Knowing its precise properties under high-energy-density conditions is crucial to understanding and designing ICF implosions through radiation–hydrodynamic simulations. For this purpose, systematic ab initio studies on the static, transport, and optical properties of CH, in a wide range of density and temperature conditions (ρ= 0.1 to 100 g/cm 3 and T = 10 3 to 4 × 10 6K), have been conducted using quantum molecular dynamics (QMD) simulations based on the density functional theory. We have builtmore » several wide-ranging, self-consistent material-properties tables for CH, such as the first-principles equation of state (FPEOS), the QMD-based thermal conductivity (Κ QMD) and ionization, and the first-principles opacity table (FPOT). This paper is devoted to providing a review on (1) what results were obtained from these systematic ab initio studies; (2) how these self-consistent results were compared with both traditional plasma-physics models and available experiments; and (3) how these first-principles–based properties of polystyrene affect the predictions of ICF target performance, through both 1-D and 2-D radiation–hydrodynamic simulations. In the warm dense regime, our ab initio results, which can significantly differ from predictions of traditional plasma-physics models, compared favorably with experiments. When incorporated into hydrocodes for ICF simulations, these first-principles material properties of CH have produced significant differences over traditional models in predicting 1-D/2-D target performance of ICF implosions on OMEGA and direct-drive–ignition designs for the National Ignition Facility. Lastly, we will discuss the implications of these studies on the current small-margin ICF target designs using a CH ablator.« less

Density functional theory in the solid state

PubMed Central

Hasnip, Philip J.; Refson, Keith; Probert, Matt I. J.; Yates, Jonathan R.; Clark, Stewart J.; Pickard, Chris J.

2014-01-01

Density functional theory (DFT) has been used in many fields of the physical sciences, but none so successfully as in the solid state. From its origins in condensed matter physics, it has expanded into materials science, high-pressure physics and mineralogy, solid-state chemistry and more, powering entire computational subdisciplines. Modern DFT simulation codes can calculate a vast range of structural, chemical, optical, spectroscopic, elastic, vibrational and thermodynamic phenomena. The ability to predict structure–property relationships has revolutionized experimental fields, such as vibrational and solid-state NMR spectroscopy, where it is the primary method to analyse and interpret experimental spectra. In semiconductor physics, great progress has been made in the electronic structure of bulk and defect states despite the severe challenges presented by the description of excited states. Studies are no longer restricted to known crystallographic structures. DFT is increasingly used as an exploratory tool for materials discovery and computational experiments, culminating in ex nihilo crystal structure prediction, which addresses the long-standing difficult problem of how to predict crystal structure polymorphs from nothing but a specified chemical composition. We present an overview of the capabilities of solid-state DFT simulations in all of these topics, illustrated with recent examples using the CASTEP computer program. PMID:24516184

Predicting Odor Pleasantness from Odorant Structure: Pleasantness as a Reflection of the Physical World

DTIC Science & Technology

2009-11-01

34 ( Engen , 1982). We next reduced the dimensionality of physico- chemical properties, and identified a primary axis of physico- chemical space. This axis...words, there is no scientist or perfumer who can predict the smell of a novel molecule by its physico- chemical structure, or the physico- chemical ...structure of a novel smell. Understanding this link between physico- chemical structure and percept has been elusive because the percept is in large

Towards A Predictive First Principles Understanding Of Molecular Adsorption On Graphene

DTIC Science & Technology

2016-10-05

used and developed state-of-the-art quantum mechanical methods to make accurate predictions about the interaction strength and adsorption structure...density functional theory, ab initio methods 16.  SECURITY CLASSIFICATION OF: 17.  LIMITATION OF ABSTRACT SAR 18.  NUMBER OF PAGES   11   19a.  NAME OF...important physical properties for a whole class of systems with weak non-covalent interactions, for example those involving the binding between water

Predicting the Performance of Chain Saw Machines Based on Shore Scleroscope Hardness

NASA Astrophysics Data System (ADS)

Tumac, Deniz

2014-03-01

Shore hardness has been used to estimate several physical and mechanical properties of rocks over the last few decades. However, the number of researches correlating Shore hardness with rock cutting performance is quite limited. Also, rather limited researches have been carried out on predicting the performance of chain saw machines. This study differs from the previous investigations in the way that Shore hardness values (SH1, SH2, and deformation coefficient) are used to determine the field performance of chain saw machines. The measured Shore hardness values are correlated with the physical and mechanical properties of natural stone samples, cutting parameters (normal force, cutting force, and specific energy) obtained from linear cutting tests in unrelieved cutting mode, and areal net cutting rate of chain saw machines. Two empirical models developed previously are improved for the prediction of the areal net cutting rate of chain saw machines. The first model is based on a revised chain saw penetration index, which uses SH1, machine weight, and useful arm cutting depth as predictors. The second model is based on the power consumed for only cutting the stone, arm thickness, and specific energy as a function of the deformation coefficient. While cutting force has a strong relationship with Shore hardness values, the normal force has a weak or moderate correlation. Uniaxial compressive strength, Cerchar abrasivity index, and density can also be predicted by Shore hardness values.

Covariate selection with iterative principal component analysis for predicting physical

USDA-ARS?s Scientific Manuscript database

Local and regional soil data can be improved by coupling new digital soil mapping techniques with high resolution remote sensing products to quantify both spatial and absolute variation of soil properties. The objective of this research was to advance data-driven digital soil mapping techniques for ...

Composite structural materials

NASA Technical Reports Server (NTRS)

Ansell, G. S.; Wiberley, S. E.

1978-01-01

The purpose of the RPI composites program is to develop advanced technology in the areas of physical properties, structural concepts and analysis, manufacturing, reliability and life prediction. Concommitant goals are to educate engineers to design and use composite materials as normal or conventional materials. A multifaceted program was instituted to achieve these objectives.

Microcomputer Calculation of Theoretical Pre-Exponential Factors for Bimolecular Reactions.

ERIC Educational Resources Information Center

Venugopalan, Mundiyath

1991-01-01

Described is the application of microcomputers to predict reaction rates based on theoretical atomic and molecular properties taught in undergraduate physical chemistry. Listed is the BASIC program which computes the partition functions for any specific bimolecular reactants. These functions are then used to calculate the pre-exponential factor of…

Group to Use Chemistry to Solve Developing Countries' Ills.

ERIC Educational Resources Information Center

O'Sullivan, Dermot A.

1983-01-01

Chemical engineers have begun savoring the first fruits of a massive effort to gather, determine, and evaluate data of physical properties and predictive methods for large numbers of compounds and mixtures processed in the chemical industry. The use of this centralized data source is highlighted. (Author/JN)

Different Parameters Support Generalization and Discrimination Learning in "Drosophila" at the Flight Simulator

ERIC Educational Resources Information Center

Brembs, Bjorn; de Ibarra, Natalie Hempel

2006-01-01

We have used a genetically tractable model system, the fruit fly "Drosophila melanogaster" to study the interdependence between sensory processing and associative processing on learning performance. We investigated the influence of variations in the physical and predictive properties of color stimuli in several different operant-conditioning…

Measures of Hindu Pathways: Development and Preliminary Evidence of Reliability and Validity.

ERIC Educational Resources Information Center

Tarakeshwar, Nalini; Pargament, Kenneth I.; Mahoney, Annette

2003-01-01

Examines religious practices of Hindus in the United States and develops measures of their religious pathways. Four religious pathways were identified: devotion, ethical action, knowledge, and physical restraint/yoga. Results indicate that the measures of the religious pathways possessed adequate psychometric properties and were predictive of…

Predicting the concentration and specific gravity of biodiesel-diesel blends using near-infrared spectroscopy

USDA-ARS?s Scientific Manuscript database

Biodiesel made from different source materials usually have different physical and chemical properties and the concentration of biodiesel in biodiesel-diesel blends varies from pump to pump and from user to user; all these factors have significant effects on performance and efficiency of engines fue...

Versatile composite resins simplifying the practice of restorative dentistry.

PubMed

Margeas, Robert

2014-01-01

After decades of technical development and refinement, composite resins continue to simplify the practice of restorative dentistry, offering clinicians versatility, predictability, and enhanced physical properties. With a wide range of products available today, composite resins are a reliable, conservative, multi-functional restorative material option. As manufacturers strive to improve such properties as compression strength, flexural strength, elastic modulus, coefficient of thermal expansion, water sorption, and wear resistance, several classification systems of composite resins have been developed.

Simulating the Exoplanet Yield from the Transiting Exoplanet Survey Satellite

NASA Astrophysics Data System (ADS)

Barclay, Thomas; Pepper, Joshua; Schlieder, Joshua; Quintana, Elisa

2018-01-01

In 2018 NASA will launch the MIT-led Transiting Exoplanet Survey Satellite (TESS) which has a goal of detecting terrestrial-mass planets orbiting stars bright enough for mass determination via ground-based radial velocity observations. We inferred how many exoplanets the TESS mission will detect, the physical properties of these detected planets, and the properties of the stars that those planets orbit, subject to certain assumptions about the mission performance. To make these predictions we use samples of stars that are drawn from the TESS Input Catalog Candidate Target List. We place zero or more planets in orbit around these stars with physical properties following known exoplanet occurrence rates, and use the TESS noise model to predict the derived properties of the detected exoplanets. We find that it is feasible to detect around 1000 exoplanets, including 250 smaller than 2 earth-radii using the TESS 2-min cadence data. We examined alternative noise models and detection models and find in our pessimistic model that TESS will detect just 500 exoplanets. When potential detections in the full-frame image data are included, the number of detected planets could increase by a factor of 4. Perhaps most excitingly, TESS will find over 2 dozen planets orbiting in the habitable zone of bright, nearby cool stars. These planets will make ideal candidates for atmospheric characerization by JWST.

Optimizing the physical-chemical properties of carbon nanotubes (CNT) and graphene nanoplatelets (GNP) on Cu(II) adsorption.

PubMed

Rosenzweig, Shirley; Sorial, George A; Sahle-Demessie, Endalkachew; McAvoy, Drew C

2014-08-30

Systematic experiments of copper adsorption on 10 different commercially available nanomaterials were studied for the influence of physical-chemical properties and their interactions. Design of experiment and response surface methodology was used to develop a polynomial model to predict maximum copper adsorption (initial concentration, Co=10mg/L) per mass of nanomaterial, qe, using multivariable regression and maximum R-square criterion. The best subsets of properties to predict qe in order of significant contribution to the model were: bulk density, ID, mesopore volume, tube length, pore size, zeta-charge, specific surface area and OD. The highest experimental qe observed was for an alcohol-functionalized MWCNT (16.7mg/g) with relative high bulk density (0.48g/cm(3)), ID (2-5nm), 10-30μm long and OD<8nm. Graphene nanoplatelets (GNP) showed poor adsorptive capacity associated to stacked-nanoplatelets, but good colloidal stability due to high functionalized surface. Good adsorption results for pristine SWCNT indicated that tubes with small diameter were more associated with good adsorption than functionalized surface. XPS and ICP analysis explored surface chemistry and purity, but pHpzc and zeta-charge were ultimately applied to indicate the degree of functionalization. Optimum CNT were identified in the scatter plot, but actual manufacturing processes introduced size and shape variations which interfered with final property results. Copyright © 2014 Elsevier B.V. All rights reserved.

Variation in the anthropomorphization of supernatural beings and its implications for cognitive theories of religion.

PubMed

Shtulman, Andrew

2008-09-01

The cognitive study of religion has been highly influenced by P. Boyer's (2001, 2003) claim that supernatural beings are conceptualized as persons with counterintuitive properties. The present study tests the generality of this claim by exploring how different supernatural beings are conceptualized by the same individual and how different individuals conceptualize the same supernatural beings. In Experiment 1, college undergraduates decided whether three types of human properties (psychological, biological, physical) could or could not be attributed to two types of supernatural beings (religious, fictional). On average, participants attributed more human properties to fictional beings, like fairies and vampires, than to religious beings, like God and Satan, and they attributed more psychological properties than nonpsychological properties to both. In Experiment 2, 5-year-old children and their parents made both open-ended and closed-ended property attributions. Although both groups of participants attributed a majority of human properties to the fictional beings, children attributed a majority of human properties to the religious beings as well. Taken together, these findings suggest that anthropomorphic theories of supernatural-being concepts, though fully predictive of children's concepts, are only partially predictive of adults' concepts. (c) 2008 APA, all rights reserved.

The Mechanical Properties of Nanowires

PubMed Central

Wang, Shiliang; Shan, Zhiwei

2017-01-01

Applications of nanowires into future generation nanodevices require a complete understanding of the mechanical properties of the nanowires. A great research effort has been made in the past two decades to understand the deformation physics and mechanical behaviors of nanowires, and to interpret the discrepancies between experimental measurements and theoretical predictions. This review focused on the characterization and understanding of the mechanical properties of nanowires, including elasticity, plasticity, anelasticity and strength. As the results from the previous literature in this area appear inconsistent, a critical evaluation of the characterization techniques and methodologies were presented. In particular, the size effects of nanowires on the mechanical properties and their deformation mechanisms were discussed. PMID:28435775

Exploring warm dense matter using quantum molecular dynamics

NASA Astrophysics Data System (ADS)

Clérouin, J.; Mazevet, S.

2006-06-01

For dense plasmas produced in shock experiments, the influence of the media on the isolated atomic properties can no longer be treated as a perturbation and conventional atomic physics approaches usually fail. Recently, quantum molecular dynamics (QMD) has been used to successfully predict static, dynamical and optical properties in this regime within the framework of a first principle method. In this short report, we illustrate the usefulness of the method for dense plasmas with a few selected examples: the equation of state of liquid deuterium, the electrical properties of expanded metals, the optical properties of shocked insulators, and the interaction of femto-second lasers with gold thin films.

Hyperspectral target detection analysis of a cluttered scene from a virtual airborne sensor platform using MuSES

NASA Astrophysics Data System (ADS)

Packard, Corey D.; Viola, Timothy S.; Klein, Mark D.

2017-10-01

The ability to predict spectral electro-optical (EO) signatures for various targets against realistic, cluttered backgrounds is paramount for rigorous signature evaluation. Knowledge of background and target signatures, including plumes, is essential for a variety of scientific and defense-related applications including contrast analysis, camouflage development, automatic target recognition (ATR) algorithm development and scene material classification. The capability to simulate any desired mission scenario with forecast or historical weather is a tremendous asset for defense agencies, serving as a complement to (or substitute for) target and background signature measurement campaigns. In this paper, a systematic process for the physical temperature and visible-through-infrared radiance prediction of several diverse targets in a cluttered natural environment scene is presented. The ability of a virtual airborne sensor platform to detect and differentiate targets from a cluttered background, from a variety of sensor perspectives and across numerous wavelengths in differing atmospheric conditions, is considered. The process described utilizes the thermal and radiance simulation software MuSES and provides a repeatable, accurate approach for analyzing wavelength-dependent background and target (including plume) signatures in multiple band-integrated wavebands (multispectral) or hyperspectrally. The engineering workflow required to combine 3D geometric descriptions, thermal material properties, natural weather boundary conditions, all modes of heat transfer and spectral surface properties is summarized. This procedure includes geometric scene creation, material and optical property attribution, and transient physical temperature prediction. Radiance renderings, based on ray-tracing and the Sandford-Robertson BRDF model, are coupled with MODTRAN for the inclusion of atmospheric effects. This virtual hyperspectral/multispectral radiance prediction methodology has been extensively validated and provides a flexible process for signature evaluation and algorithm development.

Close encounters with DNA

PubMed Central

Maffeo, C.; Yoo, J.; Comer, J.; Wells, D. B.; Luan, B.; Aksimentiev, A.

2014-01-01

Over the past ten years, the all-atom molecular dynamics method has grown in the scale of both systems and processes amenable to it and in its ability to make quantitative predictions about the behavior of experimental systems. The field of computational DNA research is no exception, witnessing a dramatic increase in the size of systems simulated with atomic resolution, the duration of individual simulations and the realism of the simulation outcomes. In this topical review, we describe the hallmark physical properties of DNA from the perspective of all-atom simulations. We demonstrate the amazing ability of such simulations to reveal the microscopic physical origins of experimentally observed phenomena and we review the frustrating limitations associated with imperfections of present atomic force fields and inadequate sampling. The review is focused on the following four physical properties of DNA: effective electric charge, response to an external mechanical force, interaction with other DNA molecules and behavior in an external electric field. PMID:25238560

Close encounters with DNA.

PubMed

Maffeo, C; Yoo, J; Comer, J; Wells, D B; Luan, B; Aksimentiev, A

2014-10-15

Over the past ten years, the all-atom molecular dynamics method has grown in the scale of both systems and processes amenable to it and in its ability to make quantitative predictions about the behavior of experimental systems. The field of computational DNA research is no exception, witnessing a dramatic increase in the size of systems simulated with atomic resolution, the duration of individual simulations and the realism of the simulation outcomes. In this topical review, we describe the hallmark physical properties of DNA from the perspective of all-atom simulations. We demonstrate the amazing ability of such simulations to reveal the microscopic physical origins of experimentally observed phenomena. We also discuss the frustrating limitations associated with imperfections of present atomic force fields and inadequate sampling. The review is focused on the following four physical properties of DNA: effective electric charge, response to an external mechanical force, interaction with other DNA molecules and behavior in an external electric field.

Intuitive reasoning about abstract and familiar physics problems

NASA Technical Reports Server (NTRS)

Kaiser, Mary Kister; Jonides, John; Alexander, Joanne

1986-01-01

Previous research has demonstrated that many people have misconceptions about basic properties of motion. Two experiments examined whether people are more likely to produce dynamically correct predictions about basic motion problems involving situations with which they are familiar, and whether solving such problems enhances performance on a subsequent abstract problem. In experiment 1, college students were asked to predict the trajectories of objects exiting a curved tube. Subjects were more accurate on the familiar version of the problem, and there was no evidence of transfer to the abstract problem. In experiment 2, two familiar problems were provided in an attempt to enhance subjects' tendency to extract the general structure of the problems. Once again, they gave more correct responses to the familiar problems but failed to generalize to the abstract problem. Formal physics training was associated with correct predictions for the abstract problem but was unrelated to performance on the familiar problems.

Liquid part of the phase diagram and percolation line for two-dimensional Mercedes-Benz water.

PubMed

Urbic, T

2017-09-01

Monte Carlo simulations and Wertheim's thermodynamic perturbation theory (TPT) are used to predict the phase diagram and percolation curve for the simple two-dimensional Mercedes-Benz (MB) model of water. The MB model of water is quite popular for explaining water properties, but the phase diagram has not been reported till now. In the MB model, water molecules are modeled as two-dimensional Lennard-Jones disks, with three orientation-dependent hydrogen-bonding arms, arranged as in the MB logo. The liquid part of the phase space is explored using grand canonical Monte Carlo simulations and two versions of Wertheim's TPT for associative fluids, which have been used before to predict the properties of the simple MB model. We find that the theory reproduces well the physical properties of hot water but is less successful at capturing the more structured hydrogen bonding that occurs in cold water. In addition to reporting the phase diagram and percolation curve of the model, it is shown that the improved TPT predicts the phase diagram rather well, while the standard one predicts a phase transition at lower temperatures. For the percolation line, both versions have problems predicting the correct position of the line at high temperatures.

Liquid part of the phase diagram and percolation line for two-dimensional Mercedes-Benz water

NASA Astrophysics Data System (ADS)

Urbic, T.

2017-09-01

Monte Carlo simulations and Wertheim's thermodynamic perturbation theory (TPT) are used to predict the phase diagram and percolation curve for the simple two-dimensional Mercedes-Benz (MB) model of water. The MB model of water is quite popular for explaining water properties, but the phase diagram has not been reported till now. In the MB model, water molecules are modeled as two-dimensional Lennard-Jones disks, with three orientation-dependent hydrogen-bonding arms, arranged as in the MB logo. The liquid part of the phase space is explored using grand canonical Monte Carlo simulations and two versions of Wertheim's TPT for associative fluids, which have been used before to predict the properties of the simple MB model. We find that the theory reproduces well the physical properties of hot water but is less successful at capturing the more structured hydrogen bonding that occurs in cold water. In addition to reporting the phase diagram and percolation curve of the model, it is shown that the improved TPT predicts the phase diagram rather well, while the standard one predicts a phase transition at lower temperatures. For the percolation line, both versions have problems predicting the correct position of the line at high temperatures.

Understanding earthquake from the granular physics point of view — Causes of earthquake, earthquake precursors and predictions

NASA Astrophysics Data System (ADS)

Lu, Kunquan; Hou, Meiying; Jiang, Zehui; Wang, Qiang; Sun, Gang; Liu, Jixing

2018-03-01

We treat the earth crust and mantle as large scale discrete matters based on the principles of granular physics and existing experimental observations. Main outcomes are: A granular model of the structure and movement of the earth crust and mantle is established. The formation mechanism of the tectonic forces, which causes the earthquake, and a model of propagation for precursory information are proposed. Properties of the seismic precursory information and its relevance with the earthquake occurrence are illustrated, and principle of ways to detect the effective seismic precursor is elaborated. The mechanism of deep-focus earthquake is also explained by the jamming-unjamming transition of the granular flow. Some earthquake phenomena which were previously difficult to understand are explained, and the predictability of the earthquake is discussed. Due to the discrete nature of the earth crust and mantle, the continuum theory no longer applies during the quasi-static seismological process. In this paper, based on the principles of granular physics, we study the causes of earthquakes, earthquake precursors and predictions, and a new understanding, different from the traditional seismological viewpoint, is obtained.

Julius Edgar Lilienfeld Prize Lecture: The Higgs Boson, String Theory, and the Real World

NASA Astrophysics Data System (ADS)

Kane, Gordon

2012-03-01

In this talk I'll describe how string theory is exciting because it can address most, perhaps all, of the questions we hope to understand about our world: why quarks and leptons make up our world, what forces form our world, cosmology, parity violation, and much more. I'll explain why string theory is testable in basically the same ways as the rest of physics, and why much of what is written about that is misleading. String theory is already or soon being tested in several ways, including correctly predicting the recently observed Higgs boson properties and mass, and predictions for dark matter, LHC physics, cosmological history, and more, from work in the increasingly active subfield ``string phenomenology.''

Toward autonomous spacecraft

NASA Technical Reports Server (NTRS)

Fogel, L. J.; Calabrese, P. G.; Walsh, M. J.; Owens, A. J.

1982-01-01

Ways in which autonomous behavior of spacecraft can be extended to treat situations wherein a closed loop control by a human may not be appropriate or even possible are explored. Predictive models that minimize mean least squared error and arbitrary cost functions are discussed. A methodology for extracting cyclic components for an arbitrary environment with respect to usual and arbitrary criteria is developed. An approach to prediction and control based on evolutionary programming is outlined. A computer program capable of predicting time series is presented. A design of a control system for a robotic dense with partially unknown physical properties is presented.

Predicting Physical Time Series Using Dynamic Ridge Polynomial Neural Networks

PubMed Central

Al-Jumeily, Dhiya; Ghazali, Rozaida; Hussain, Abir

2014-01-01

Forecasting naturally occurring phenomena is a common problem in many domains of science, and this has been addressed and investigated by many scientists. The importance of time series prediction stems from the fact that it has wide range of applications, including control systems, engineering processes, environmental systems and economics. From the knowledge of some aspects of the previous behaviour of the system, the aim of the prediction process is to determine or predict its future behaviour. In this paper, we consider a novel application of a higher order polynomial neural network architecture called Dynamic Ridge Polynomial Neural Network that combines the properties of higher order and recurrent neural networks for the prediction of physical time series. In this study, four types of signals have been used, which are; The Lorenz attractor, mean value of the AE index, sunspot number, and heat wave temperature. The simulation results showed good improvements in terms of the signal to noise ratio in comparison to a number of higher order and feedforward neural networks in comparison to the benchmarked techniques. PMID:25157950

Predicting physical time series using dynamic ridge polynomial neural networks.

PubMed

Al-Jumeily, Dhiya; Ghazali, Rozaida; Hussain, Abir

2014-01-01

Forecasting naturally occurring phenomena is a common problem in many domains of science, and this has been addressed and investigated by many scientists. The importance of time series prediction stems from the fact that it has wide range of applications, including control systems, engineering processes, environmental systems and economics. From the knowledge of some aspects of the previous behaviour of the system, the aim of the prediction process is to determine or predict its future behaviour. In this paper, we consider a novel application of a higher order polynomial neural network architecture called Dynamic Ridge Polynomial Neural Network that combines the properties of higher order and recurrent neural networks for the prediction of physical time series. In this study, four types of signals have been used, which are; The Lorenz attractor, mean value of the AE index, sunspot number, and heat wave temperature. The simulation results showed good improvements in terms of the signal to noise ratio in comparison to a number of higher order and feedforward neural networks in comparison to the benchmarked techniques.

Analytical relationships for prediction of the mechanical properties of additively manufactured porous biomaterials

PubMed Central

Hedayati, Reza

2016-01-01

Abstract Recent developments in additive manufacturing techniques have motivated an increasing number of researchers to study regular porous biomaterials that are based on repeating unit cells. The physical and mechanical properties of such porous biomaterials have therefore received increasing attention during recent years. One of the areas that have revived is analytical study of the mechanical behavior of regular porous biomaterials with the aim of deriving analytical relationships that could predict the relative density and mechanical properties of porous biomaterials, given the design and dimensions of their repeating unit cells. In this article, we review the analytical relationships that have been presented in the literature for predicting the relative density, elastic modulus, Poisson's ratio, yield stress, and buckling limit of regular porous structures based on various types of unit cells. The reviewed analytical relationships are used to compare the mechanical properties of porous biomaterials based on different types of unit cells. The major areas where the analytical relationships have improved during the recent years are discussed and suggestions are made for future research directions. © 2016 Wiley Periodicals, Inc. J Biomed Mater Res Part A: 104A: 3164–3174, 2016. PMID:27502358

Soot and Spectral Radiation Modeling in ECN Spray A and in Engines

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

Haworth, Daniel C; Ferreyro-Fernandez, Sebastian; Paul, Chandan

The amount of soot formed in a turbulent combustion system is determined by a complex system of coupled nonlinear chemical and physical processes. Different physical subprocesses can dominate, depending on the hydrodynamic and thermochemical environments. Similarly, the relative importance of reabsorption, spectral radiation properties, and molecular gas radiation versus soot radiation varies with thermochemical conditions, and in ways that are difficult to predict for the highly nonhomogeneous in-cylinder mixtures in engines. Here it is shown that transport and mixing play relatively more important roles as rate-determining processes in soot formation at engine-relevant conditions. It is also shown that molecular gasmore » radiation and spectral radiation properties are important for engine-relevant conditions.« less

Physical optics for oven-plate scattering prediction

NASA Technical Reports Server (NTRS)

Baldauf, J.; Lambert, K.

1991-01-01

An oven assembly design is described, which will be used to determine the effects of temperature on the electrical properties of materials which are used as coatings for metal plates. Experimentally, these plates will be heated to a very high temperature in the oven assembly, and measured using a microwave reflectance measurement system developed for the NASA Lewis Research Center, Near-Field Facility. One unknown in this measurement is the effect that the oven assembly will have on the reflectance properties of the plate. Since the oven will be much larger than the plate, the effect could potentially be significant as the size of the plate becomes smaller. Therefore, it is necessary to predict the effect of the oven on the measurement of the plate. A method for predicting the oven effect is described, and the theoretical oven effect is compared to experimental results of the oven material. The computer code which is used to predict the oven effect is also described.

Model-assisted analysis of spatial and temporal variations in fruit temperature and transpiration highlighting the role of fruit development.

PubMed

Nordey, Thibault; Léchaudel, Mathieu; Saudreau, Marc; Joas, Jacques; Génard, Michel

2014-01-01

Fruit physiology is strongly affected by both fruit temperature and water losses through transpiration. Fruit temperature and its transpiration vary with environmental factors and fruit characteristics. In line with previous studies, measurements of physical and thermal fruit properties were found to significantly vary between fruit tissues and maturity stages. To study the impact of these variations on fruit temperature and transpiration, a modelling approach was used. A physical model was developed to predict the spatial and temporal variations of fruit temperature and transpiration according to the spatial and temporal variations of environmental factors and thermal and physical fruit properties. Model predictions compared well to temperature measurements on mango fruits, making it possible to accurately simulate the daily temperature variations of the sunny and shaded sides of fruits. Model simulations indicated that fruit development induced an increase in both the temperature gradient within the fruit and fruit water losses, mainly due to fruit expansion. However, the evolution of fruit characteristics has only a very slight impact on the average temperature and the transpiration per surface unit. The importance of temperature and transpiration gradients highlighted in this study made it necessary to take spatial and temporal variations of environmental factors and fruit characteristics into account to model fruit physiology.

Computational split-field finite-difference time-domain evaluation of simplified tilt-angle models for parallel-aligned liquid-crystal devices

NASA Astrophysics Data System (ADS)

Márquez, Andrés; Francés, Jorge; Martínez, Francisco J.; Gallego, Sergi; Álvarez, Mariela L.; Calzado, Eva M.; Pascual, Inmaculada; Beléndez, Augusto

2018-03-01

Simplified analytical models with predictive capability enable simpler and faster optimization of the performance in applications of complex photonic devices. We recently demonstrated the most simplified analytical model still showing predictive capability for parallel-aligned liquid crystal on silicon (PA-LCoS) devices, which provides the voltage-dependent retardance for a very wide range of incidence angles and any wavelength in the visible. We further show that the proposed model is not only phenomenological but also physically meaningful, since two of its parameters provide the correct values for important internal properties of these devices related to the birefringence, cell gap, and director profile. Therefore, the proposed model can be used as a means to inspect internal physical properties of the cell. As an innovation, we also show the applicability of the split-field finite-difference time-domain (SF-FDTD) technique for phase-shift and retardance evaluation of PA-LCoS devices under oblique incidence. As a simplified model for PA-LCoS devices, we also consider the exact description of homogeneous birefringent slabs. However, we show that, despite its higher degree of simplification, the proposed model is more robust, providing unambiguous and physically meaningful solutions when fitting its parameters.

Molecular design, synthesis and physical properties of novel Cytisine-derivatives - Experimental and theoretical study

NASA Astrophysics Data System (ADS)

Ivanova, Bojidarka; Spiteller, Michael

2013-02-01

The paper presented a comprehensive theoretical and experimental study on the molecular drugs-design, synthesis, isolation, physical spectroscopic and mass spectrometric elucidation of novel functionalization derivatives of Cytisine (Cyt), using nucleosidic residues. Since these alkaloids have established biochemical profile, related the binding affinity of the nicotinic acetylcholine receptors (nAChRs), particularly α7 sub-type, the presented correlation between the molecular structure and properties allowed to evaluated the highlights of the biochemical hypothesises related the Schizophrenia. The anticancer activity of α7 subtype agonists and the crucial role of the nucleoside-based medications in the cancer therapy provided opportunity for further study on the biochemical relationship between Schizophrenia and few kinds of cancers, which has been hypothesized recently. The physical electronic absorptions (EAs), circular dichroic (CD) and Raman spectroscopic (RS) properties as well as mass spectrometric (MS) data, obtained using electrospray ionization (ESI) and atmospheric-pressure chemical ionization (APCI) methods under the positive single (MS) and tandem (MS/MS) modes of operation are discussed. Taking into account reports on a fatal intoxication of Cyt, the presented data would be of interest in the field of forensic chemistry, through development of highly selective and sensitive analytical protocols. Quantum chemical method is used to predict the physical properties of the isolated alkaloids, their affinity to the receptor loop and gas-phase stabilized species, observed mass spectrometrically.

Integration of active pharmaceutical ingredient solid form selection and particle engineering into drug product design.

PubMed

Ticehurst, Martyn David; Marziano, Ivan

2015-06-01

This review seeks to offer a broad perspective that encompasses an understanding of the drug product attributes affected by active pharmaceutical ingredient (API) physical properties, their link to solid form selection and the role of particle engineering. While the crucial role of active pharmaceutical ingredient (API) solid form selection is universally acknowledged in the pharmaceutical industry, the value of increasing effort to understanding the link between solid form, API physical properties and drug product formulation and manufacture is now also being recognised. A truly holistic strategy for drug product development should focus on connecting solid form selection, particle engineering and formulation design to both exploit opportunities to access simpler manufacturing operations and prevent failures. Modelling and predictive tools that assist in establishing these links early in product development are discussed. In addition, the potential for differences between the ingoing API physical properties and those in the final product caused by drug product processing is considered. The focus of this review is on oral solid dosage forms and dry powder inhaler products for lung delivery. © 2015 Royal Pharmaceutical Society.

Axial point groups: rank 1, 2, 3 and 4 property tensor tables.

PubMed

Litvin, Daniel B

2015-05-01

The form of a physical property tensor of a quasi-one-dimensional material such as a nanotube or a polymer is determined from the material's axial point group. Tables of the form of rank 1, 2, 3 and 4 property tensors are presented for a wide variety of magnetic and non-magnetic tensor types invariant under each point group in all 31 infinite series of axial point groups. An application of these tables is given in the prediction of the net polarization and magnetic-field-induced polarization in a one-dimensional longitudinal conical magnetic structure in multiferroic hexaferrites.

Thermal properties of soils: effect of biochar application

NASA Astrophysics Data System (ADS)

Usowicz, Boguslaw; Lukowski, Mateusz; Lipiec, Jerzy

2014-05-01

Thermal properties (thermal conductivity, heat capacity and thermal diffusivity) have a significant effect on the soil surface energy partitioning and resulting in the temperature distribution. Thermal properties of soil depend on water content, bulk density and organic matter content. An important source of organic matter is biochar. Biochar as a material is defined as: "charcoal for application as a soil conditioner". Biochar is generally associated with co-produced end products of pyrolysis. Many different materials are used as biomass feedstock for biochar, including wood, crop residues and manures. Additional predictions were done for terra preta soil (also known as "Amazonian dark earth"), high in charcoal content, due to adding a mixture of charcoal, bone, and manure for thousands of years i.e. approximately 10-1,000 times longer than residence times of most soil organic matter. The effect of biochar obtained from the wood biomass and other organic amendments (peat, compost) on soil thermal properties is presented in this paper. The results were compared with wetland soils of different organic matter content. The measurements of the thermal properties at various water contents were performed after incubation, under laboratory conditions using KD2Pro, Decagon Devices. The measured data were compared with predictions made using Usowicz statistical-physical model (Usowicz et al., 2006) for biochar, mineral soil and soil with addition of biochar at various water contents and bulk densities. The model operates statistically by probability of occurrence of contacts between particular fractional compounds. It combines physical properties, specific to particular compounds, into one apparent conductance specific to the mixture. The results revealed that addition of the biochar and other organic amendments into the soil caused considerable reduction of the thermal conductivity and diffusivity. The mineral soil showed the highest thermal conductivity and diffusivity that decreased in soil with addition of biochar and pure biochar. The reduction of both properties was mostly due to decrease in both particle density and bulk density. Both biochar and the organic amendments addition resulted in a decrease of the heat capacity of the mixtures in dry state and considerable increase in wet state. The lowest and highest reduction in the thermal conductivity with decreasing water content was obtained for pure biochar and mineral soil, respectively. The thermal diffusivity had a characteristic maximum at higher bulk densities and lower water contents. The wetland soil higher in organic matter content exhibit smaller temporal variation of the thermal properties compared to soils lower in organic matter content in response to changes of water content. The statistical-physical model was found to be useful for satisfactory predicting thermal properties of the soil with addition of biochar and organic amendments. Usowicz B. et al., 2006. Thermal conductivity modelling of terrestrial soil media - A comparative study. Planetary and Space Science 54, 1086-1095.

Determination of the mechanical and physical properties of cartilage by coupling poroelastic-based finite element models of indentation with artificial neural networks.

PubMed

Arbabi, Vahid; Pouran, Behdad; Campoli, Gianni; Weinans, Harrie; Zadpoor, Amir A

2016-03-21

One of the most widely used techniques to determine the mechanical properties of cartilage is based on indentation tests and interpretation of the obtained force-time or displacement-time data. In the current computational approaches, one needs to simulate the indentation test with finite element models and use an optimization algorithm to estimate the mechanical properties of cartilage. The modeling procedure is cumbersome, and the simulations need to be repeated for every new experiment. For the first time, we propose a method for fast and accurate estimation of the mechanical and physical properties of cartilage as a poroelastic material with the aid of artificial neural networks. In our study, we used finite element models to simulate the indentation for poroelastic materials with wide combinations of mechanical and physical properties. The obtained force-time curves are then divided into three parts: the first two parts of the data is used for training and validation of an artificial neural network, while the third part is used for testing the trained network. The trained neural network receives the force-time curves as the input and provides the properties of cartilage as the output. We observed that the trained network could accurately predict the properties of cartilage within the range of properties for which it was trained. The mechanical and physical properties of cartilage could therefore be estimated very fast, since no additional finite element modeling is required once the neural network is trained. The robustness of the trained artificial neural network in determining the properties of cartilage based on noisy force-time data was assessed by introducing noise to the simulated force-time data. We found that the training procedure could be optimized so as to maximize the robustness of the neural network against noisy force-time data. Copyright © 2016 Elsevier Ltd. All rights reserved.

Measurement techniques and instruments suitable for life-prediction testing of photovoltaic arrays

NASA Technical Reports Server (NTRS)

Noel, G. T.; Sliemers, F. A.; Deringer, G. C.; Wood, V. E.; Wilkes, K. E.; Gaines, G. B.; Carmichael, D. C.

1978-01-01

Array failure modes, relevant materials property changes, and primary degradation mechanisms are discussed as a prerequisite to identifying suitable measurement techniques and instruments. Candidate techniques and instruments are identified on the basis of extensive reviews of published and unpublished information. These methods are organized in six measurement categories - chemical, electrical, optical, thermal, mechanical, and other physicals. Using specified evaluation criteria, the most promising techniques and instruments for use in life prediction tests of arrays were selected.

Use of porosity to estimate hydraulic properties of volcanic tuffs

USGS Publications Warehouse

Flint, L.E.; Selker, J.S.

2003-01-01

Correlations of hydraulic properties with easily measured physical properties are useful for purposes of site characterization in heterogeneous sites. Approximately 600 samples of volcanic rocks from Yucca Mountain, Nevada, representing lithologies with a large range of hydraulic properties, were analyzed to develop correlations of effective porosity with saturated hydraulic conductivity and moisture-retention curve-fit parameters that relate to lithologies of varying depositional history and alteration processes. Effective porosity, ??e, defined as the porosity calculated using drying at a relative humidity of -70 MPa, is used in a generalized Kozeny-Carman equation to predict saturated hydraulic conductivity, Ks = b??en, where b and n are constants. The entire dataset has an R2 of 0.36. When samples are grouped according to general lithology, correlations result in an R2 of 0.71 for the crystallized/vitric samples, 0.24 for samples with mineral alteration, and 0.34 for samples with microfractures, thus increasing the predictive capability over that of the total dataset. Published by Elsevier Science Ltd.

Molecular Dynamics Simulation Of Novel Elastomer Nanocomposites: Structure Design And Property Prediction

NASA Astrophysics Data System (ADS)

Liu, Jun; Zhang, Liqun

In this talk, by employing molecular dynamics simulation, we aim to provide the structure design and property prediction of novel elastomer nanocomposites(ENCs), by considering three typical systems such as physical compounding, self-assembly and end-linked systems. We examine the dispersion, interfacial interaction and the resulting static and dynamic mechanical properties of each system. Emphasis is placed on how to tune the visco-elasticity and decrease the dynamic hysteresis loss of ENCs, by considering to introduce the flexible nanoparticles(NPs) with reversible mechanical deformation such as carbon nanosprings and graphene nanoribbon, or by achieving a homogeneous distribution of NPs in the elastomeric polymer matrix together with decreasing the mobility of the end-groups of polymer chains. In particular, the end-linked system exhibits both excellent static and dynamic mechanical properties, independent of the temperature. This novel ENCs could provide some useful guidances for the fabrication of high performance ENCs tailored for tire tread of green tires by cutting the fuel consumption.

Insight into interfacial effect on effective physical properties of fibrous materials. I. The volume fraction of soft interfaces around anisotropic fibers.

PubMed

Xu, Wenxiang; Wang, Han; Niu, Yanze; Bai, Jingtao

2016-01-07

With advances in interfacial properties characterization technologies, the interfacial volume fraction is a feasible parameter for evaluating effective physical properties of materials. However, there is a need to determine the interfacial volume fraction around anisotropic fibers and a need to assess the influence of such the interfacial property on effective properties of fibrous materials. Either ways, the accurate prediction of interfacial volume fraction is required. Towards this end, we put forward both theoretical and numerical schemes to determine the interfacial volume fraction in fibrous materials, which are considered as a three-phase composite structure consisting of matrix, anisotropic hard spherocylinder fibers, and soft interfacial layers with a constant dimension coated on the surface of each fiber. The interfacial volume fraction actually represents the fraction of space not occupied by all hard fibers and matrix. The theoretical scheme that adopts statistical geometry and stereological theories is essentially an analytic continuation from spherical inclusions. By simulating such three-phase chopped fibrous materials, we numerically derive the interfacial volume fraction. The theoretical and numerical schemes provide a quantitative insight that the interfacial volume fraction depends strongly on the fiber geometries like fiber shape, geometric size factor, and fiber size distribution. As a critical interfacial property, the present contribution can be further drawn into assessing effective physical properties of fibrous materials, which will be demonstrated in another paper (Part II) of this series.

Preformulation considerations for controlled release dosage forms. Part I. Selecting candidates.

PubMed

Chrzanowski, Frank

2008-01-01

The physical-chemical properties of interest for controlled release (CR) dosage form development presented are based on the author's experience. Part I addresses selection of the final form based on a logical progression of physical-chemical properties evaluation of candidate forms and elimination of forms with undesirable properties from further evaluation in order to simplify final form selection. Several candidate forms which could include salt, free base or acid, polymorphic and amorphic forms of a new chemical entity (NCE) or existing drug substance (DS) are prepared and evaluated for critical properties in a scheme relevant to manufacturing processes, predictive of problems, requiring small amounts of test materials and simple analytical tools. A stability indicating assay is not needed to initiate the evaluation. This process is applicable to CR and immediate release (IR) dosage form development. The critical properties evaluated are melting, crystallinity, solubilities in water, 0.1 N HCl, and SIF, hygrodymamics, i.e., moisture sorption and loss at extremes of RH, and LOD at typical wet granulation drying conditions, and processability, i.e., corrosivity, and filming and/or sticking upon compression.

Interfacial effect on physical properties of composite media: Interfacial volume fraction with non-spherical hard-core-soft-shell-structured particles.

PubMed

Xu, Wenxiang; Duan, Qinglin; Ma, Huaifa; Chen, Wen; Chen, Huisu

2015-11-02

Interfaces are known to be crucial in a variety of fields and the interfacial volume fraction dramatically affects physical properties of composite media. However, it is an open problem with great significance how to determine the interfacial property in composite media with inclusions of complex geometry. By the stereological theory and the nearest-surface distribution functions, we first propose a theoretical framework to symmetrically present the interfacial volume fraction. In order to verify the interesting generalization, we simulate three-phase composite media by employing hard-core-soft-shell structures composed of hard mono-/polydisperse non-spherical particles, soft interfaces, and matrix. We numerically derive the interfacial volume fraction by a Monte Carlo integration scheme. With the theoretical and numerical results, we find that the interfacial volume fraction is strongly dependent on the so-called geometric size factor and sphericity characterizing the geometric shape in spite of anisotropic particle types. As a significant interfacial property, the present theoretical contribution can be further drawn into predicting the effective transport properties of composite materials.

Interfacial effect on physical properties of composite media: Interfacial volume fraction with non-spherical hard-core-soft-shell-structured particles

PubMed Central

Xu, Wenxiang; Duan, Qinglin; Ma, Huaifa; Chen, Wen; Chen, Huisu

2015-01-01

Interfaces are known to be crucial in a variety of fields and the interfacial volume fraction dramatically affects physical properties of composite media. However, it is an open problem with great significance how to determine the interfacial property in composite media with inclusions of complex geometry. By the stereological theory and the nearest-surface distribution functions, we first propose a theoretical framework to symmetrically present the interfacial volume fraction. In order to verify the interesting generalization, we simulate three-phase composite media by employing hard-core-soft-shell structures composed of hard mono-/polydisperse non-spherical particles, soft interfaces, and matrix. We numerically derive the interfacial volume fraction by a Monte Carlo integration scheme. With the theoretical and numerical results, we find that the interfacial volume fraction is strongly dependent on the so-called geometric size factor and sphericity characterizing the geometric shape in spite of anisotropic particle types. As a significant interfacial property, the present theoretical contribution can be further drawn into predicting the effective transport properties of composite materials. PMID:26522701

Application of Molecular Interaction Volume Model for Phase Equilibrium of Sn-Based Binary System in Vacuum Distillation

NASA Astrophysics Data System (ADS)

Kong, Lingxin; Yang, Bin; Xu, Baoqiang; Li, Yifu

2014-09-01

Based on the molecular interaction volume model (MIVM), the activities of components of Sn-Sb, Sb-Bi, Sn-Zn, Sn-Cu, and Sn-Ag alloys were predicted. The predicted values are in good agreement with the experimental data, which indicate that the MIVM is of better stability and reliability due to its good physical basis. A significant advantage of the MIVM lies in its ability to predict the thermodynamic properties of liquid alloys using only two parameters. The phase equilibria of Sn-Sb and Sn-Bi alloys were calculated based on the properties of pure components and the activity coefficients, which indicates that Sn-Sb and Sn-Bi alloys can be separated thoroughly by vacuum distillation. This study extends previous investigations and provides an effective and convenient model on which to base refining simulations for Sn-based alloys.

Efficient first-principles prediction of solid stability: Towards chemical accuracy

NASA Astrophysics Data System (ADS)

Zhang, Yubo; Kitchaev, Daniil A.; Yang, Julia; Chen, Tina; Dacek, Stephen T.; Sarmiento-Pérez, Rafael A.; Marques, Maguel A. L.; Peng, Haowei; Ceder, Gerbrand; Perdew, John P.; Sun, Jianwei

2018-03-01

The question of material stability is of fundamental importance to any analysis of system properties in condensed matter physics and materials science. The ability to evaluate chemical stability, i.e., whether a stoichiometry will persist in some chemical environment, and structure selection, i.e. what crystal structure a stoichiometry will adopt, is critical to the prediction of materials synthesis, reactivity and properties. Here, we demonstrate that density functional theory, with the recently developed strongly constrained and appropriately normed (SCAN) functional, has advanced to a point where both facets of the stability problem can be reliably and efficiently predicted for main group compounds, while transition metal compounds are improved but remain a challenge. SCAN therefore offers a robust model for a significant portion of the periodic table, presenting an opportunity for the development of novel materials and the study of fine phase transformations even in largely unexplored systems with little to no experimental data.

Bridging a gap between continuum-QCD and ab initio predictions of hadron observables

DOE PAGES

Binosi, Daniele; Chang, Lei; Papavassiliou, Joannis; ...

2015-03-01

Within contemporary hadron physics there are two common methods for determining the momentum- dependence of the interaction between quarks: the top-down approach, which works toward an ab initiocomputation of the interaction via direct analysis of the gauge-sector gap equations; and the bottom-up scheme, which aims to infer the interaction by fitting data within a well-defined truncation of those equations in the matter sector that are relevant to bound-state properties. We unite these two approaches by demonstrating that the renormalisation-group-invariant running-interaction predicted by contemporary analyses of QCD’s gauge sector coincides with that required in order to describe ground-state hadron observables usingmore » a nonperturbative truncation of QCD’s Dyson–Schwinger equations in the matter sector. This bridges a gap that had lain between nonperturbative continuum-QCD and the ab initio prediction of bound-state properties.« less

Thermodynamic model effects on the design and optimization of natural gas plants

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

Diaz, S.; Zabaloy, M.; Brignole, E.A.

1999-07-01

The design and optimization of natural gas plants is carried out on the basis of process simulators. The physical property package is generally based on cubic equations of state. By rigorous thermodynamics phase equilibrium conditions, thermodynamic functions, equilibrium phase separations, work and heat are computed. The aim of this work is to analyze the NGL turboexpansion process and identify possible process computations that are more sensitive to model predictions accuracy. Three equations of state, PR, SRK and Peneloux modification, are used to study the effect of property predictions on process calculations and plant optimization. It is shown that turboexpander plantsmore » have moderate sensitivity with respect to phase equilibrium computations, but higher accuracy is required for the prediction of enthalpy and turboexpansion work. The effect of modeling CO{sub 2} solubility is also critical in mixtures with high CO{sub 2} content in the feed.« less

Coupling among Microbial Communities, Biogeochemistry, and Mineralogy across Biogeochemical Facies

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

Stegen, James C.; Konopka, Allan; McKinely, Jim

Physical properties of sediments are commonly used to define subsurface lithofacies and these same physical properties influence subsurface microbial communities. This suggests an (unexploited) opportunity to use the spatial distribution of facies to predict spatial variation in biogeochemically relevant microbial attributes. Here, we characterize three biogeochemical facies—oxidized, reduced, and transition—within one lithofacies and elucidate relationships among facies features and microbial community biomass, diversity, and community composition. Consistent with previous observations of biogeochemical hotspots at environmental transition zones, we find elevated biomass within a biogeochemical facies that occurred at the transition between oxidized and reduced biogeochemical facies. Microbial diversity—the number ofmore » microbial taxa—was lower within the reduced facies and was well-explained by a combination of pH and mineralogy. Null modeling revealed that microbial community composition was influenced by ecological selection imposed by redox state and mineralogy, possibly due to effects on nutrient availability or transport. As an illustrative case, we predict microbial biomass concentration across a three-dimensional spatial domain by coupling the spatial distribution of subsurface biogeochemical facies with biomass-facies relationships revealed here. We expect that merging such an approach with hydro-biogeochemical models will provide important constraints on simulated dynamics, thereby reducing uncertainty in model predictions.« less

Computational integration of nanoscale physical biomarkers and cognitive assessments for Alzheimer’s disease diagnosis and prognosis

PubMed Central

Yue, Tao; Jia, Xinghua; Petrosino, Jennifer; Sun, Leming; Fan, Zhen; Fine, Jesse; Davis, Rebecca; Galster, Scott; Kuret, Jeff; Scharre, Douglas W.; Zhang, Mingjun

2017-01-01

With the increasing prevalence of Alzheimer’s disease (AD), significant efforts have been directed toward developing novel diagnostics and biomarkers that can enhance AD detection and management. AD affects the cognition, behavior, function, and physiology of patients through mechanisms that are still being elucidated. Current AD diagnosis is contingent on evaluating which symptoms and signs a patient does or does not display. Concerns have been raised that AD diagnosis may be affected by how those measurements are analyzed. Unbiased means of diagnosing AD using computational algorithms that integrate multidisciplinary inputs, ranging from nanoscale biomarkers to cognitive assessments, and integrating both biochemical and physical changes may provide solutions to these limitations due to lack of understanding for the dynamic progress of the disease coupled with multiple symptoms in multiscale. We show that nanoscale physical properties of protein aggregates from the cerebral spinal fluid and blood of patients are altered during AD pathogenesis and that these properties can be used as a new class of “physical biomarkers.” Using a computational algorithm, developed to integrate these biomarkers and cognitive assessments, we demonstrate an approach to impartially diagnose AD and predict its progression. Real-time diagnostic updates of progression could be made on the basis of the changes in the physical biomarkers and the cognitive assessment scores of patients over time. Additionally, the Nyquist-Shannon sampling theorem was used to determine the minimum number of necessary patient checkups to effectively predict disease progression. This integrated computational approach can generate patient-specific, personalized signatures for AD diagnosis and prognosis. PMID:28782028

Shreddability of pizza Mozzarella cheese predicted using physicochemical properties.

PubMed

Banville, V; Morin, P; Pouliot, Y; Britten, M

2014-07-01

This study used rheological techniques such as uniaxial compression, wire cutting, and dynamic oscillatory shear to probe the physical properties of pizza Mozzarella cheeses. Predictive models were built using compositional and textural descriptors to predict cheese shreddability. Experimental cheeses were made using milk with (0.25% wt/wt) or without denatured whey protein and renneted at pH 6.5 or 6.4. The cheeses were aged for 8, 22, or 36 d and then tested at 4, 13, or 22°C for textural attributes using 11 descriptors. Adding denatured whey protein and reducing the milk renneting pH strongly affected cheese mechanical properties, but these effects were usually dependent on testing temperature. Cheeses were generally weaker as they aged. None of the compositional or rheological descriptors taken alone could predict the shredding behavior of the cheeses. Using the stepwise method, an objective selection of a few (<4) relevant descriptors made it possible to predict the production of fines (R(2)=0.82), the percentage of long shreds (R(2)=0.67), and to a lesser degree, the adhesion of cheese to the shredding blade (R(2)=0.45). The principal component analysis markedly contrasted the adhesion of cheese to the shredding blade with other shredding properties such as the production of fines or long shreds. The predictive models and principal component analysis can help manufacturers select relevant descriptors for the development of cheese with optimal mechanical behavior under shredding conditions. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Conceptualization and calibration of anisotropic, dynamic alluvial systems: Pitfalls and biases in current modelling practices

NASA Astrophysics Data System (ADS)

Gianni, Guillaume; Doherty, John; Perrochet, Pierre; Brunner, Philip

2017-04-01

Physical properties of alluvial environments are typically featuring a high degree of anisotropy and are characterized by dynamic interactions between the surface and the subsurface. A literature review on current modelling practice shows that hydrogeological models are often calibrated using isotropic hydraulic conductivity fields and steady state conditions. We aim at understanding how these simplifications affect the predictions of hydraulic heads and exchange fluxes using fully coupled, physically based synthetic models and advanced calibration approaches. Specifically, we present an analysis of the information content provided by averaged, steady state hydraulic data compared to transient data with respect to the determination of aquifer hydraulic properties. We show that the information content in average hydraulic heads is insufficient to inform anisotropic properties of alluvial aquifers and can lead to important biases on the calibrated parameters. We further explore the consequences of these biases on predictions of fluxes and water table dynamics. The results of this synthetic analysis are considered in the calibration of a highly dynamic and anisotropic alluvial aquifer system in Switzerland (the Rhône River). The results of the synthetic and real-world modelling and calibration exercises provide insight on future data acquisition, modelling and calibration strategies for these environments.

Estimation of soil hydraulic properties with microwave techniques

NASA Technical Reports Server (NTRS)

Oneill, P. E.; Gurney, R. J.; Camillo, P. J.

1985-01-01

Useful quantitative information about soil properties may be obtained by calibrating energy and moisture balance models with remotely sensed data. A soil physics model solves heat and moisture flux equations in the soil profile and is driven by the surface energy balance. Model generated surface temperature and soil moisture and temperature profiles are then used in a microwave emission model to predict the soil brightness temperature. The model hydraulic parameters are varied until the predicted temperatures agree with the remotely sensed values. This method is used to estimate values for saturated hydraulic conductivity, saturated matrix potential, and a soil texture parameter. The conductivity agreed well with a value measured with an infiltration ring and the other parameters agreed with values in the literature.

Consciousness: here, there and everywhere?

PubMed

Tononi, Giulio; Koch, Christof

2015-05-19

The science of consciousness has made great strides by focusing on the behavioural and neuronal correlates of experience. However, while such correlates are important for progress to occur, they are not enough if we are to understand even basic facts, for example, why the cerebral cortex gives rise to consciousness but the cerebellum does not, though it has even more neurons and appears to be just as complicated. Moreover, correlates are of little help in many instances where we would like to know if consciousness is present: patients with a few remaining islands of functioning cortex, preterm infants, non-mammalian species and machines that are rapidly outperforming people at driving, recognizing faces and objects, and answering difficult questions. To address these issues, we need not only more data but also a theory of consciousness-one that says what experience is and what type of physical systems can have it. Integrated information theory (IIT) does so by starting from experience itself via five phenomenological axioms: intrinsic existence, composition, information, integration and exclusion. From these it derives five postulates about the properties required of physical mechanisms to support consciousness. The theory provides a principled account of both the quantity and the quality of an individual experience (a quale), and a calculus to evaluate whether or not a particular physical system is conscious and of what. Moreover, IIT can explain a range of clinical and laboratory findings, makes a number of testable predictions and extrapolates to a number of problematic conditions. The theory holds that consciousness is a fundamental property possessed by physical systems having specific causal properties. It predicts that consciousness is graded, is common among biological organisms and can occur in some very simple systems. Conversely, it predicts that feed-forward networks, even complex ones, are not conscious, nor are aggregates such as groups of individuals or heaps of sand. Also, in sharp contrast to widespread functionalist beliefs, IIT implies that digital computers, even if their behaviour were to be functionally equivalent to ours, and even if they were to run faithful simulations of the human brain, would experience next to nothing.

Consciousness: here, there and everywhere?

PubMed Central

Tononi, Giulio; Koch, Christof

2015-01-01

The science of consciousness has made great strides by focusing on the behavioural and neuronal correlates of experience. However, while such correlates are important for progress to occur, they are not enough if we are to understand even basic facts, for example, why the cerebral cortex gives rise to consciousness but the cerebellum does not, though it has even more neurons and appears to be just as complicated. Moreover, correlates are of little help in many instances where we would like to know if consciousness is present: patients with a few remaining islands of functioning cortex, preterm infants, non-mammalian species and machines that are rapidly outperforming people at driving, recognizing faces and objects, and answering difficult questions. To address these issues, we need not only more data but also a theory of consciousness—one that says what experience is and what type of physical systems can have it. Integrated information theory (IIT) does so by starting from experience itself via five phenomenological axioms: intrinsic existence, composition, information, integration and exclusion. From these it derives five postulates about the properties required of physical mechanisms to support consciousness. The theory provides a principled account of both the quantity and the quality of an individual experience (a quale), and a calculus to evaluate whether or not a particular physical system is conscious and of what. Moreover, IIT can explain a range of clinical and laboratory findings, makes a number of testable predictions and extrapolates to a number of problematic conditions. The theory holds that consciousness is a fundamental property possessed by physical systems having specific causal properties. It predicts that consciousness is graded, is common among biological organisms and can occur in some very simple systems. Conversely, it predicts that feed-forward networks, even complex ones, are not conscious, nor are aggregates such as groups of individuals or heaps of sand. Also, in sharp contrast to widespread functionalist beliefs, IIT implies that digital computers, even if their behaviour were to be functionally equivalent to ours, and even if they were to run faithful simulations of the human brain, would experience next to nothing. PMID:25823865

Quantifying economic fluctuations by adapting methods of statistical physics

NASA Astrophysics Data System (ADS)

Plerou, Vasiliki

2001-09-01

The first focus of this thesis is the investigation of cross-correlations between the price fluctuations of different stocks using the conceptual framework of random matrix theory (RMT), developed in physics to describe the statistical properties of energy-level spectra of complex nuclei. RMT makes predictions for the statistical properties of matrices that are universal, i.e., do not depend on the interactions between the elements comprising the system. In physical systems, deviations from the predictions of RMT provide clues regarding the mechanisms controlling the dynamics of a given system so this framework is of potential value if applied to economic systems. This thesis compares the statistics of cross-correlation matrix C-whose elements Cij are the correlation coefficients of price fluctuations of stock i and j-against the ``null hypothesis'' of a random matrix having the same symmetry properties. It is shown that comparison of the eigenvalue statistics of C with RMT results can be used to distinguish random and non-random parts of C. The non-random part of C which deviates from RMT results, provides information regarding genuine cross-correlations between stocks. The interpretations and potential practical utility of these deviations are also investigated. The second focus is the characterization of the dynamics of stock price fluctuations. The statistical properties of the changes G Δt in price over a time interval Δ t are quantified and the statistical relation between G Δt and the trading activity-measured by the number of transactions NΔ t in the interval Δt is investigated. The statistical properties of the volatility, i.e., the time dependent standard deviation of price fluctuations, is related to two microscopic quantities: NΔt and the variance W2Dt of the price changes for all transactions in the interval Δ t. In addition, the statistical relationship between G Δt and the number of shares QΔt traded in Δ t is investigated.

[Fabric static effect after the use of synthetic detergents].

PubMed

Golenkova, L G; Voloshchenko, O I; Antomonov, M Iu

2003-01-01

The residues of surfactants that are present on textile materials were found to affect the surface charge of tissues. If physical properties of clothes materials, such as electrifiability, the positive or negative charge, resistivity, hygroscopicity are known, you may predict the values of residues of surfactants to be adsorbed onto the surface of tissues.

Disruption of Attention by Irrelevant Stimuli in Serial Recall

ERIC Educational Resources Information Center

Lange, Elke B.

2005-01-01

In four experiments the behavioral consequences of an involuntary attentional distraction concerning memory performance was investigated. The working memory model of Cowan (1995) predicts a performance deficit for memory representations that are held in an active state when the focus of attention is distracted by a change in physical properties.…

Mystery Powders. [Modified Primary]. Revised. Anchorage School District Elementary Science Program.

ERIC Educational Resources Information Center

Anchorage School District, AK.

This publication provides information and activities for identifying objects using the five senses and process skills including observing, classifying, collecting and interpreting data, inferring, and predicting. Lessons 1 through 3 deal with the identification of an unknown substance and the physical properties of powders. Lessons 4 through 6 are…

Electronic Structure Control of Sub-nanometer 1D SnTe via Nanostructuring within Single-Walled Carbon Nanotubes.

PubMed

Vasylenko, Andrij; Marks, Samuel; Wynn, Jamie M; Medeiros, Paulo V C; Ramasse, Quentin M; Morris, Andrew J; Sloan, Jeremy; Quigley, David

2018-05-25

Nanostructuring, e. g., reduction of dimensionality in materials, offers a viable route toward regulation of materials electronic and hence functional properties. Here, we present the extreme case of nanostructuring, exploiting the capillarity of single-walled carbon nanotubes (SWCNTs) for the synthesis of the smallest possible SnTe nanowires with cross sections as thin as a single atom column. We demonstrate that by choosing the appropriate diameter of a template SWCNT, we can manipulate the structure of the quasi-one-dimensional (1D) SnTe to design electronic behavior. From first principles, we predict the structural re-formations that SnTe undergoes in varying encapsulations and confront the prediction with TEM imagery. To further illustrate the control of physical properties by nanostructuring, we study the evolution of transport properties in a homologous series of models of synthesized and isolated SnTe nanowires varying only in morphology and atomic layer thickness. This extreme scaling is predicted to significantly enhance thermoelectric performance of SnTe, offering a prospect for further experimental studies and future applications.

Phosphorene oxide: stability and electronic properties of a novel two-dimensional material.

PubMed

Wang, Gaoxue; Pandey, Ravindra; Karna, Shashi P

2015-01-14

Phosphorene, the monolayer form of (black) phosphorus, was recently exfoliated from its bulk counterpart. Phosphorene oxide, by analogy to graphene oxide, is expected to have novel chemical and electronic properties, and may provide an alternative route to the synthesis of phosphorene. In this research, the physical and chemical properties of phosphorene oxide including its formation by oxygen adsorption on the bare phosphorene was investigated. Analysis of the phonon dispersion curves finds stoichiometric and non-stoichiometric oxide configurations to be stable at ambient conditions, thus suggesting that the oxygen adsorption may not degrade the phosphorene. The nature of the band gap of the oxides depends on the degree of functionalization of phosphorene; an indirect gap is predicted for the non-stoichiometric configurations, whereas a direct gap is predicted for the stoichiometric oxide. Application of mechanical strain or an external electric field leads to tunability of the band gap of the phosphorene oxide. In contrast to the case of the bare phosphorene, dependence of the diode-like asymmetric current-voltage response on the degree of stoichiometry is predicted for the phosphorene oxide.

Building Synthetic Sterols Computationally – Unlocking the Secrets of Evolution?

PubMed Central

Róg, Tomasz; Pöyry, Sanja; Vattulainen, Ilpo

2015-01-01

Cholesterol is vital in regulating the physical properties of animal cell membranes. While it remains unclear what renders cholesterol so unique, it is known that other sterols are less capable in modulating membrane properties, and there are membrane proteins whose function is dependent on cholesterol. Practical applications of cholesterol include its use in liposomes in drug delivery and cosmetics, cholesterol-based detergents in membrane protein crystallography, its fluorescent analogs in studies of cholesterol transport in cells and tissues, etc. Clearly, in spite of their difficult synthesis, producing the synthetic analogs of cholesterol is of great commercial and scientific interest. In this article, we discuss how synthetic sterols non-existent in nature can be used to elucidate the roles of cholesterol’s structural elements. To this end, we discuss recent atomistic molecular dynamics simulation studies that have predicted new synthetic sterols with properties comparable to those of cholesterol. We also discuss more recent experimental studies that have vindicated these predictions. The paper highlights the strength of computational simulations in making predictions for synthetic biology, thereby guiding experiments. PMID:26347865

Prediction of some physical and drying properties of terebinth fruit (Pistacia atlantica L.) using Artificial Neural Networks.

PubMed

Kaveh, Mohammad; Chayjan, Reza Amiri

2014-01-01

Drying of terebinth fruit was conducted to provide microbiological stability, reduce product deterioration due to chemical reactions, facilitate storage and lower transportation costs. Because terebinth fruit is susceptible to heat, the selection of a suitable drying technology is a challenging task. Artificial neural networks (ANNs) are used as a nonlinear mapping structures for modelling and prediction of some physical and drying properties of terebinth fruit. Drying characteristics of terebinth fruit with an initial moisture content of 1.16 (d.b.) was studied in an infrared fluidized bed dryer. Different levels of air temperatures (40, 55 and 70°C), air velocities (0.93, 1.76 and 2.6 m/s) and infrared (IR) radiation powers (500, 1000 and 1500 W) were applied. In the present study, the application of Artificial Neural Network (ANN) for predicting the drying moisture diffusivity, energy consumption, shrinkage, drying rate and moisture ratio (output parameter for ANN modelling) was investigated. Air temperature, air velocity, IR radiation and drying time were considered as input parameters. The results revealed that to predict drying rate and moisture ratio a network with the TANSIG-LOGSIG-TANSIG transfer function and Levenberg-Marquardt (LM) training algorithm made the most accurate predictions for the terebinth fruit drying. The best results for ANN at predications were R2 = 0.9678 for drying rate, R2 = 0.9945 for moisture ratio, R2 = 0.9857 for moisture diffusivity and R2 = 0.9893 for energy consumption. Results indicated that artificial neural network can be used as an alternative approach for modelling and predicting of terebinth fruit drying parameters with high correlation. Also ANN can be used in optimization of the process.

A review: applications of the phase field method in predicting microstructure and property evolution of irradiated nuclear materials

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

Li, Yulan; Hu, Shenyang; Sun, Xin

Here, complex microstructure changes occur in nuclear fuel and structural materials due to the extreme environments of intense irradiation and high temperature. This paper evaluates the role of the phase field method in predicting the microstructure evolution of irradiated nuclear materials and the impact on their mechanical, thermal, and magnetic properties. The paper starts with an overview of the important physical mechanisms of defect evolution and the significant gaps in simulating microstructure evolution in irradiated nuclear materials. Then, the phase field method is introduced as a powerful and predictive tool and its applications to microstructure and property evolution in irradiatedmore » nuclear materials are reviewed. The review shows that (1) Phase field models can correctly describe important phenomena such as spatial-dependent generation, migration, and recombination of defects, radiation-induced dissolution, the Soret effect, strong interfacial energy anisotropy, and elastic interaction; (2) The phase field method can qualitatively and quantitatively simulate two-dimensional and three-dimensional microstructure evolution, including radiation-induced segregation, second phase nucleation, void migration, void and gas bubble superlattice formation, interstitial loop evolution, hydrate formation, and grain growth, and (3) The Phase field method correctly predicts the relationships between microstructures and properties. The final section is dedicated to a discussion of the strengths and limitations of the phase field method, as applied to irradiation effects in nuclear materials.« less

A review: applications of the phase field method in predicting microstructure and property evolution of irradiated nuclear materials

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

Li, Yulan; Hu, Shenyang; Sun, Xin

Complex microstructure changes occur in nuclear fuel and structural materials due to the extreme environments of intense irradiation and high temperature. This paper evaluates the role of the phase field (PF) method in predicting the microstructure evolution of irradiated nuclear materials and the impact on their mechanical, thermal, and magnetic properties. The paper starts with an overview of the important physical mechanisms of defect evolution and the significant gaps in simulating microstructure evolution in irradiated nuclear materials. Then, the PF method is introduced as a powerful and predictive tool and its applications to microstructure and property evolution in irradiated nuclearmore » materials are reviewed. The review shows that 1) FP models can correctly describe important phenomena such as spatial dependent generation, migration, and recombination of defects, radiation-induced dissolution, the Soret effect, strong interfacial energy anisotropy, and elastic interaction; 2) The PF method can qualitatively and quantitatively simulate 2-D and 3-D microstructure evolution, including radiation-induced segregation, second phase nucleation, void migration, void and gas bubble superlattice formation, interstitial loop evolution, hydrate formation, and grain growth, and 3) The FP method correctly predicts the relationships between microstructures and properties. The final section is dedicated to a discussion of the strengths and limitations of the PF method, as applied to irradiation effects in nuclear materials.« less

A review: applications of the phase field method in predicting microstructure and property evolution of irradiated nuclear materials

DOE PAGES

Li, Yulan; Hu, Shenyang; Sun, Xin; ...

2017-04-14

Here, complex microstructure changes occur in nuclear fuel and structural materials due to the extreme environments of intense irradiation and high temperature. This paper evaluates the role of the phase field method in predicting the microstructure evolution of irradiated nuclear materials and the impact on their mechanical, thermal, and magnetic properties. The paper starts with an overview of the important physical mechanisms of defect evolution and the significant gaps in simulating microstructure evolution in irradiated nuclear materials. Then, the phase field method is introduced as a powerful and predictive tool and its applications to microstructure and property evolution in irradiatedmore » nuclear materials are reviewed. The review shows that (1) Phase field models can correctly describe important phenomena such as spatial-dependent generation, migration, and recombination of defects, radiation-induced dissolution, the Soret effect, strong interfacial energy anisotropy, and elastic interaction; (2) The phase field method can qualitatively and quantitatively simulate two-dimensional and three-dimensional microstructure evolution, including radiation-induced segregation, second phase nucleation, void migration, void and gas bubble superlattice formation, interstitial loop evolution, hydrate formation, and grain growth, and (3) The Phase field method correctly predicts the relationships between microstructures and properties. The final section is dedicated to a discussion of the strengths and limitations of the phase field method, as applied to irradiation effects in nuclear materials.« less

Machine learning for the structure-energy-property landscapes of molecular crystals.

PubMed

Musil, Félix; De, Sandip; Yang, Jack; Campbell, Joshua E; Day, Graeme M; Ceriotti, Michele

2018-02-07

Molecular crystals play an important role in several fields of science and technology. They frequently crystallize in different polymorphs with substantially different physical properties. To help guide the synthesis of candidate materials, atomic-scale modelling can be used to enumerate the stable polymorphs and to predict their properties, as well as to propose heuristic rules to rationalize the correlations between crystal structure and materials properties. Here we show how a recently-developed machine-learning (ML) framework can be used to achieve inexpensive and accurate predictions of the stability and properties of polymorphs, and a data-driven classification that is less biased and more flexible than typical heuristic rules. We discuss, as examples, the lattice energy and property landscapes of pentacene and two azapentacene isomers that are of interest as organic semiconductor materials. We show that we can estimate force field or DFT lattice energies with sub-kJ mol -1 accuracy, using only a few hundred reference configurations, and reduce by a factor of ten the computational effort needed to predict charge mobility in the crystal structures. The automatic structural classification of the polymorphs reveals a more detailed picture of molecular packing than that provided by conventional heuristics, and helps disentangle the role of hydrogen bonded and π-stacking interactions in determining molecular self-assembly. This observation demonstrates that ML is not just a black-box scheme to interpolate between reference calculations, but can also be used as a tool to gain intuitive insights into structure-property relations in molecular crystal engineering.

Observed ground-motion variabilities and implication for source properties

NASA Astrophysics Data System (ADS)

Cotton, F.; Bora, S. S.; Bindi, D.; Specht, S.; Drouet, S.; Derras, B.; Pina-Valdes, J.

2016-12-01

One of the key challenges of seismology is to be able to calibrate and analyse the physical factors that control earthquake and ground-motion variabilities. Within the framework of empirical ground-motion prediction equation (GMPE) developments, ground-motions residuals (differences between recorded ground motions and the values predicted by a GMPE) are computed. The exponential growth of seismological near-field records and modern regression algorithms allow to decompose these residuals into between-event and a within-event residual components. The between-event term quantify all the residual effects of the source (e.g. stress-drops) which are not accounted by magnitude term as the only source parameter of the model. Between-event residuals provide a new and rather robust way to analyse the physical factors that control earthquake source properties and associated variabilities. We first will show the correlation between classical stress-drops and between-event residuals. We will also explain why between-event residuals may be a more robust way (compared to classical stress-drop analysis) to analyse earthquake source-properties. We will finally calibrate between-events variabilities using recent high-quality global accelerometric datasets (NGA-West 2, RESORCE) and datasets from recent earthquakes sequences (Aquila, Iquique, Kunamoto). The obtained between-events variabilities will be used to evaluate the variability of earthquake stress-drops but also the variability of source properties which cannot be explained by a classical Brune stress-drop variations. We will finally use the between-event residual analysis to discuss regional variations of source properties, differences between aftershocks and mainshocks and potential magnitude dependencies of source characteristics.

A comprehensive combustion model for biodiesel-fueled engine simulations

NASA Astrophysics Data System (ADS)

Brakora, Jessica L.

Engine models for alternative fuels are available, but few are comprehensive, well-validated models that include accurate physical property data as well as a detailed description of the fuel chemistry. In this work, a comprehensive biodiesel combustion model was created for use in multi-dimensional engine simulations, specifically the KIVA3v R2 code. The model incorporates realistic physical properties in a vaporization model developed for multi-component fuel sprays and applies an improved mechanism for biodiesel combustion chemistry. A reduced mechanism was generated from the methyl decanoate (MD) and methyl-9-decenoate (MD9D) mechanism developed at Lawrence Livermore National Laboratory. It was combined with a multi-component mechanism to include n-heptane in the fuel chemistry. The biodiesel chemistry was represented using a combination of MD, MD9D and n-heptane, which varied for a given fuel source. The reduced mechanism, which contained 63 species, accurately predicted ignition delay times of the detailed mechanism over a range of engine-specific operating conditions. Physical property data for the five methyl ester components of biodiesel were added to the KIVA library. Spray simulations were performed to ensure that the models adequately reproduce liquid penetration observed in biodiesel spray experiments. Fuel composition impacted liquid length as expected, with saturated species vaporizing more and penetrating less. Distillation curves were created to ensure the fuel vaporization process was comparable to available data. Engine validation was performed against a low-speed, high-load, conventional combustion experiments and the model was able to predict the performance and NOx formation seen in the experiment. High-speed, low-load, low-temperature combustion conditions were also modeled, and the emissions (HC, CO, NOx) and fuel consumption were well-predicted for a sweep of injection timings. Finally, comparisons were made between the results of biodiesel composition (palm vs. soy) and fuel blends (neat vs. B20). The model effectively reproduced the trends observed in the experiments.

Designing with figer-reinforced plastics (planar random composites)

NASA Technical Reports Server (NTRS)

Chamis, C. C.

1982-01-01

The use of composite mechanics to predict the hygrothermomechanical behavior of planar random composites (PRC) is reviewed and described. These composites are usually made from chopped fiber reinforced resins (thermoplastics or thermosets). The hygrothermomechanical behavior includes mechanical properties, physical properties, thermal properties, fracture toughness, creep and creep rupture. Properties are presented in graphical form with sample calculations to illustrate their use. Concepts such as directional reinforcement and strip hybrids are described. Typical data that can be used for preliminary design for various PRCs are included. Several resins and molding compounds used to make PRCs are described briefly. Pertinent references are cited that cover analysis and design methods, materials, data, fabrication procedures and applications.

Upper and lower bounds of ground-motion variabilities: implication for source properties

NASA Astrophysics Data System (ADS)

Cotton, Fabrice; Reddy-Kotha, Sreeram; Bora, Sanjay; Bindi, Dino

2017-04-01

One of the key challenges of seismology is to be able to analyse the physical factors that control earthquakes and ground-motion variabilities. Such analysis is particularly important to calibrate physics-based simulations and seismic hazard estimations at high frequencies. Within the framework of the development of ground-motion prediction equation (GMPE) developments, ground-motions residuals (differences between recorded ground motions and the values predicted by a GMPE) are computed. The exponential growth of seismological near-source records and modern GMPE analysis technics allow to partition these residuals into between- and a within-event components. In particular, the between-event term quantifies all those repeatable source effects (e.g. related to stress-drop or kappa-source variability) which have not been accounted by the magnitude-dependent term of the model. In this presentation, we first discuss the between-event variabilities computed both in the Fourier and Response Spectra domains, using recent high-quality global accelerometric datasets (e.g. NGA-west2, Resorce, Kiknet). These analysis lead to the assessment of upper bounds for the ground-motion variability. Then, we compare these upper bounds with lower bounds estimated by analysing seismic sequences which occurred on specific fault systems (e.g., located in Central Italy or in Japan). We show that the lower bounds of between-event variabilities are surprisingly large which indicates a large variability of earthquake dynamic properties even within the same fault system. Finally, these upper and lower bounds of ground-shaking variability are discussed in term of variability of earthquake physical properties (e.g., stress-drop and kappa_source).

MHC2NNZ: A novel peptide binding prediction approach for HLA DQ molecules

NASA Astrophysics Data System (ADS)

Xie, Jiang; Zeng, Xu; Lu, Dongfang; Liu, Zhixiang; Wang, Jiao

2017-07-01

The major histocompatibility complex class II (MHC-II) molecule plays a crucial role in immunology. Computational prediction of MHC-II binding peptides can help researchers understand the mechanism of immune systems and design vaccines. Most of the prediction algorithms for MHC-II to date have made large efforts in human leukocyte antigen (HLA, the name of MHC in Human) molecules encoded in the DR locus. However, HLA DQ molecules are equally important and have only been made less progress because it is more difficult to handle them experimentally. In this study, we propose an artificial neural network-based approach called MHC2NNZ to predict peptides binding to HLA DQ molecules. Unlike previous artificial neural network-based methods, MHC2NNZ not only considers sequence similarity features but also captures the chemical and physical properties, and a novel method incorporating these properties is proposed to represent peptide flanking regions (PFR). Furthermore, MHC2NNZ improves the prediction accuracy by combining with amino acid preference at more specific positions of the peptides binding core. By evaluating on 3549 peptides binding to six most frequent HLA DQ molecules, MHC2NNZ is demonstrated to outperform other state-of-the-art MHC-II prediction methods.

Atomic Oxygen Erosion Yield Predictive Tool for Spacecraft Polymers in Low Earth Orbit

NASA Technical Reports Server (NTRS)

Bank, Bruce A.; de Groh, Kim K.; Backus, Jane A.

2008-01-01

A predictive tool was developed to estimate the low Earth orbit (LEO) atomic oxygen erosion yield of polymers based on the results of the Polymer Erosion and Contamination Experiment (PEACE) Polymers experiment flown as part of the Materials International Space Station Experiment 2 (MISSE 2). The MISSE 2 PEACE experiment accurately measured the erosion yield of a wide variety of polymers and pyrolytic graphite. The 40 different materials tested were selected specifically to represent a variety of polymers used in space as well as a wide variety of polymer chemical structures. The resulting erosion yield data was used to develop a predictive tool which utilizes chemical structure and physical properties of polymers that can be measured in ground laboratory testing to predict the in-space atomic oxygen erosion yield of a polymer. The properties include chemical structure, bonding information, density and ash content. The resulting predictive tool has a correlation coefficient of 0.914 when compared with actual MISSE 2 space data for 38 polymers and pyrolytic graphite. The intent of the predictive tool is to be able to make estimates of atomic oxygen erosion yields for new polymers without requiring expensive and time consumptive in-space testing.

Statistical models for sediment/detritus and dissolved absorption coefficients in coastal waters of the northern Gulf of Mexico

NASA Astrophysics Data System (ADS)

Green, Rebecca E.; Gould, Richard W., Jr.; Ko, Dong S.

2008-06-01

We developed statistically-based, optical models to estimate tripton (sediment/detrital) and colored dissolved organic matter (CDOM) absorption coefficients ( a sd, a g) from physical hydrographic and atmospheric properties. The models were developed for northern Gulf of Mexico shelf waters using multi-year satellite and physical data. First, empirical algorithms for satellite-derived a sd and a g were developed, based on comparison with a large data set of cruise measurements from northern Gulf shelf waters; these algorithms were then applied to a time series of ocean color (SeaWiFS) satellite imagery for 2002-2005. Unique seasonal timing was observed in satellite-derived optical properties, with a sd peaking most often in fall/winter on the shelf, in contrast to summertime peaks observed in a g. Next, the satellite-derived values were coupled with the physical data to form multiple regression models. A suite of physical forcing variables were tested for inclusion in the models: discharge from the Mississippi River and Mobile Bay, Alabama; gridded fields for winds, precipitation, solar radiation, sea surface temperature and height (SST, SSH); and modeled surface salinity and currents (Navy Coastal Ocean Model, NCOM). For satellite-derived a sd and a g time series (2002-2004), correlation and stepwise regression analyses revealed the most important physical forcing variables. Over our region of interest, the best predictors of tripton absorption were wind speed, river discharge, and SST, whereas dissolved absorption was best predicted by east-west wind speed, river discharge, and river discharge lagged by 1 month. These results suggest the importance of vertical mixing (as a function of winds and thermal stratification) in controlling a sd distribution patterns over large regions of the shelf, in comparison to advection as the most important control on a g. The multiple linear regression models for estimating a sd and a g were applied on a pixel-by-pixel basis and results were compared to monthly SeaWiFS composite imagery. The models performed well in resolving seasonal and interannual optical variability in model development years (2002-2004) (mean error of 32% for a sd and 29% for a g) and in predicting shelfwide optical patterns in a year independent of model development (2005; mean error of 41% for a sd and 46% for a g). The models provide insight into the dominant processes controlling optical distributions in this region, and they can be used to predict the optical fields from the physical properties at monthly timescales.

Modeling the Impact of Baryons on Subhalo Populations with Machine Learning

NASA Astrophysics Data System (ADS)

Nadler, Ethan O.; Mao, Yao-Yuan; Wechsler, Risa H.; Garrison-Kimmel, Shea; Wetzel, Andrew

2018-06-01

We identify subhalos in dark matter–only (DMO) zoom-in simulations that are likely to be disrupted due to baryonic effects by using a random forest classifier trained on two hydrodynamic simulations of Milky Way (MW)–mass host halos from the Latte suite of the Feedback in Realistic Environments (FIRE) project. We train our classifier using five properties of each disrupted and surviving subhalo: pericentric distance and scale factor at first pericentric passage after accretion and scale factor, virial mass, and maximum circular velocity at accretion. Our five-property classifier identifies disrupted subhalos in the FIRE simulations with an 85% out-of-bag classification score. We predict surviving subhalo populations in DMO simulations of the FIRE host halos, finding excellent agreement with the hydrodynamic results; in particular, our classifier outperforms DMO zoom-in simulations that include the gravitational potential of the central galactic disk in each hydrodynamic simulation, indicating that it captures both the dynamical effects of a central disk and additional baryonic physics. We also predict surviving subhalo populations for a suite of DMO zoom-in simulations of MW-mass host halos, finding that baryons impact each system consistently and that the predicted amount of subhalo disruption is larger than the host-to-host scatter among the subhalo populations. Although the small size and specific baryonic physics prescription of our training set limits the generality of our results, our work suggests that machine-learning classification algorithms trained on hydrodynamic zoom-in simulations can efficiently predict realistic subhalo populations.

An improved probabilistic approach for linking progenitor and descendant galaxy populations using comoving number density

NASA Astrophysics Data System (ADS)

Wellons, Sarah; Torrey, Paul

2017-06-01

Galaxy populations at different cosmic epochs are often linked by cumulative comoving number density in observational studies. Many theoretical works, however, have shown that the cumulative number densities of tracked galaxy populations not only evolve in bulk, but also spread out over time. We present a method for linking progenitor and descendant galaxy populations which takes both of these effects into account. We define probability distribution functions that capture the evolution and dispersion of galaxy populations in number density space, and use these functions to assign galaxies at redshift zf probabilities of being progenitors/descendants of a galaxy population at another redshift z0. These probabilities are used as weights for calculating distributions of physical progenitor/descendant properties such as stellar mass, star formation rate or velocity dispersion. We demonstrate that this probabilistic method provides more accurate predictions for the evolution of physical properties than the assumption of either a constant number density or an evolving number density in a bin of fixed width by comparing predictions against galaxy populations directly tracked through a cosmological simulation. We find that the constant number density method performs least well at recovering galaxy properties, the evolving method density slightly better and the probabilistic method best of all. The improvement is present for predictions of stellar mass as well as inferred quantities such as star formation rate and velocity dispersion. We demonstrate that this method can also be applied robustly and easily to observational data, and provide a code package for doing so.

Parameterizing the binding properties of dissolved organic matter with default values skews the prediction of copper solution speciation and ecotoxicity in soil.

PubMed

Djae, Tanalou; Bravin, Matthieu N; Garnier, Cédric; Doelsch, Emmanuel

2017-04-01

Parameterizing speciation models by setting the percentage of dissolved organic matter (DOM) that is reactive (% r-DOM) toward metal cations at a single 65% default value is very common in predictive ecotoxicology. The authors tested this practice by comparing the free copper activity (pCu 2+  = -log 10 [Cu 2+ ]) measured in 55 soil sample solutions with pCu 2+ predicted with the Windermere humic aqueous model (WHAM) parameterized by default. Predictions of Cu toxicity to soil organisms based on measured or predicted pCu 2+ were also compared. Default WHAM parameterization substantially skewed the prediction of measured pCu 2+ by up to 2.7 pCu 2+ units (root mean square residual = 0.75-1.3) and subsequently the prediction of Cu toxicity for microbial functions, invertebrates, and plants by up to 36%, 45%, and 59% (root mean square residuals ≤9 %, 11%, and 17%), respectively. Reparametrizing WHAM by optimizing the 2 DOM binding properties (i.e., % r-DOM and the Cu complexation constant) within a physically realistic value range much improved the prediction of measured pCu 2+ (root mean square residual = 0.14-0.25). Accordingly, this WHAM parameterization successfully predicted Cu toxicity for microbial functions, invertebrates, and plants (root mean square residual ≤3.4%, 4.4%, and 5.8%, respectively). Thus, it is essential to account for the real heterogeneity in DOM binding properties for relatively accurate prediction of Cu speciation in soil solution and Cu toxic effects on soil organisms. Environ Toxicol Chem 2017;36:898-905. © 2016 SETAC. © 2016 SETAC.

Physical properties of the WR stars in Westerlund 1

NASA Astrophysics Data System (ADS)

Rosslowe, C. K.; Crowther, P. A.; Clark, J. S.; Negueruela, I.

The Westerlund 1 (Wd1) cluster hosts a rich and varied collection of massive stars. Its dynamical youth and the absence of ongoing star formation indicate a coeval population. As such, the simultaneous presence of both late-type supergiants and Wolf-Rayet stars has defied explanation in the context of single-star evolution. Observational evidence points to a high binary fraction, hence this stellar population offers a robust test for stellar models accounting for both single-star and binary evolution. We present an optical to near-IR (VLT & NTT) spectroscopic analysis of 22 WR stars in Wd 1, delivering physical properties for the WR stars. We discuss how these differ from the Galactic field population, and how they may be reconciled with the predictions of single and binary evolutionary models.

Bayesian coronal seismology

NASA Astrophysics Data System (ADS)

Arregui, Iñigo

2018-01-01

In contrast to the situation in a laboratory, the study of the solar atmosphere has to be pursued without direct access to the physical conditions of interest. Information is therefore incomplete and uncertain and inference methods need to be employed to diagnose the physical conditions and processes. One of such methods, solar atmospheric seismology, makes use of observed and theoretically predicted properties of waves to infer plasma and magnetic field properties. A recent development in solar atmospheric seismology consists in the use of inversion and model comparison methods based on Bayesian analysis. In this paper, the philosophy and methodology of Bayesian analysis are first explained. Then, we provide an account of what has been achieved so far from the application of these techniques to solar atmospheric seismology and a prospect of possible future extensions.

Overview of physical models of liquid entrainment in annular gas-liquid flow

NASA Astrophysics Data System (ADS)

Cherdantsev, Andrey V.

2018-03-01

A number of recent papers devoted to development of physically-based models for prediction of liquid entrainment in annular regime of two-phase flow are analyzed. In these models shearing-off the crests of disturbance waves by the gas drag force is supposed to be the physical mechanism of entrainment phenomenon. The models are based on a number of assumptions on wavy structure, including inception of disturbance waves due to Kelvin-Helmholtz instability, linear velocity profile inside liquid film and high degree of three-dimensionality of disturbance waves. Validity of the assumptions is analyzed by comparison to modern experimental observations. It was shown that nearly every assumption is in strong qualitative and quantitative disagreement with experiments, which leads to massive discrepancies between the modeled and real properties of the disturbance waves. As a result, such models over-predict the entrained fraction by several orders of magnitude. The discrepancy is usually reduced using various kinds of empirical corrections. This, combined with empiricism already included in the models, turns the models into another kind of empirical correlations rather than physically-based models.

Novel nano bearings constructed by physical adsorption

PubMed Central

Zhang, Yongbin

2015-01-01

The paper proposes a novel nano bearing formed by the physical adsorption of the confined fluid to the solid wall. The bearing is formed between two parallel smooth solid plane walls sliding against one another, where conventional hydrodynamic lubrication theory predicted no lubricating effect. In this bearing, the stationary solid wall is divided into two subzones which respectively have different interaction strengths with the lubricating fluid. It leads to different physical adsorption and slip properties of the lubricating fluid at the stationary solid wall respectively in these two subzones. It was found that a significant load-carrying capacity of the bearing can be generated for low lubricating film thicknesses, because of the strong physical adsorption and non-continuum effects of the lubricating film. PMID:26412488

Preface: Special Topic Section on Advanced Electronic Structure Methods for Solids and Surfaces.

PubMed

Michaelides, Angelos; Martinez, Todd J; Alavi, Ali; Kresse, Georg; Manby, Frederick R

2015-09-14

This Special Topic section on Advanced Electronic Structure Methods for Solids and Surfaces contains a collection of research papers that showcase recent advances in the high accuracy prediction of materials and surface properties. It provides a timely snapshot of a growing field that is of broad importance to chemistry, physics, and materials science.

Feasibility Analysis of Incorporating In-Vitro Toxicokinetic Data as a Surrogate for In-Vivo Data for Read-across Predictions (ASCCT meeting)

EPA Science Inventory

The underlying principle of read-across is that biological activity is a function of physical and structural properties of chemicals. Analogs are typically identified on the basis of structural similarity and subsequently evaluated for their use in read-across on the basis of the...

Novel fuelbed characteristics associated with mechanical mastication treatments in northern California and south-western Oregon, USA

Treesearch

Jeffrey M. Kane; J. Morgan Varner; Eric E. Knapp

2009-01-01

Mechanically masticated fuelbeds are distinct from natural or logging slash fuelbeds, with different particle size distributions, bulk density, and particle shapes, leading to challenges in predicting fire behavior and effects. Our study quantified some physical properties of fuel particles (e.g. squared quadratic mean diameter, proportion of non-cylindrical particles...

Complex transition metal hydrides: linear correlation of countercation electronegativity versus T-D bond lengths.

PubMed

Humphries, T D; Sheppard, D A; Buckley, C E

2015-06-30

For homoleptic 18-electron complex hydrides, an inverse linear correlation has been established between the T-deuterium bond length (T = Fe, Co, Ni) and the average electronegativity of the metal countercations. This relationship can be further employed towards aiding structural solutions and predicting physical properties of novel complex transition metal hydrides.

Geometry as an Object of Experience: The Missed Debate between Poincare and Einstein

ERIC Educational Resources Information Center

Hacyan, Shahen

2009-01-01

According to Poincare, a geometry cannot be an object of experience since any geometrical experiment must be realized with physical objects, such as rulers and light rays, and it is only their properties that can be tested. This position was apparently refuted by general relativity and the successful confirmation of its predictions by astronomical…

Induction of molecular endpoints by reactive oxygen species in human lung cells predicted by physical chemical properties of engineered nanoparticles

EPA Science Inventory

A series of six titanium dioxide and two cerium oxide engineered nanomaterials were assessed for their ability to induce cytotoxicity, reactive oxygen species (ROS), and various types of DNA and protein damage in human respiratory BEAS-2B cells exposed in vitro for 72 hours at se...

A combined molecular dynamics/micromechanics/finite element approach for multiscale constitutive modeling of nanocomposites with interface effects

NASA Astrophysics Data System (ADS)

Yang, B. J.; Shin, H.; Lee, H. K.; Kim, H.

2013-12-01

We introduce a multiscale framework based on molecular dynamic (MD) simulation, micromechanics, and finite element method (FEM). A micromechanical model, which considers influences of the interface properties, nanoparticle (NP) size, and microcracks, is developed. Then, we perform MD simulations to characterize the mechanical properties of the nanocomposite system (silica/nylon 6) with varying volume fraction and size of NPs. By comparing the MD with micromechanics results, intrinsic physical properties at interfacial region are derived. Finally, we implement the developed model in the FEM code with the derived interfacial parameters, and predict the mechanical behavior of the nanocomposite at the macroscopic scale.

Variability in soil-water retention properties and implications for physics-based simulation of landslide early warning criteria

USGS Publications Warehouse

Thomas, Matthew A.; Mirus, Benjamin B.; Collins, Brian D.; Lu, Ning; Godt, Jonathan W.

2018-01-01

Rainfall-induced shallow landsliding is a persistent hazard to human life and property. Despite the observed connection between infiltration through the unsaturated zone and shallow landslide initiation, there is considerable uncertainty in how estimates of unsaturated soil-water retention properties affect slope stability assessment. This source of uncertainty is critical to evaluating the utility of physics-based hydrologic modeling as a tool for landslide early warning. We employ a numerical model of variably saturated groundwater flow parameterized with an ensemble of texture-, laboratory-, and field-based estimates of soil-water retention properties for an extensively monitored landslide-prone site in the San Francisco Bay Area, CA, USA. Simulations of soil-water content, pore-water pressure, and the resultant factor of safety show considerable variability across and within these different parameter estimation techniques. In particular, we demonstrate that with the same permeability structure imposed across all simulations, the variability in soil-water retention properties strongly influences predictions of positive pore-water pressure coincident with widespread shallow landsliding. We also find that the ensemble of soil-water retention properties imposes an order-of-magnitude and nearly two-fold variability in seasonal and event-scale landslide susceptibility, respectively. Despite the reduced factor of safety uncertainty during wet conditions, parameters that control the dry end of the soil-water retention function markedly impact the ability of a hydrologic model to capture soil-water content dynamics observed in the field. These results suggest that variability in soil-water retention properties should be considered for objective physics-based simulation of landslide early warning criteria.

On The Importance of Connecting Laboratory Measurements of Ice Crystal Growth with Model Parameterizations: Predicting Ice Particle Properties

NASA Astrophysics Data System (ADS)

Harrington, J. Y.

2017-12-01

Parameterizing the growth of ice particles in numerical models is at an interesting cross-roads. Most parameterizations developed in the past, including some that I have developed, parse model ice into numerous categories based primarily on the growth mode of the particle. Models routinely possess smaller ice, snow crystals, aggregates, graupel, and hail. The snow and ice categories in some models are further split into subcategories to account for the various shapes of ice. There has been a relatively recent shift towards a new class of microphysical models that predict the properties of ice particles instead of using multiple categories and subcategories. Particle property models predict the physical characteristics of ice, such as aspect ratio, maximum dimension, effective density, rime density, effective area, and so forth. These models are attractive in the sense that particle characteristics evolve naturally in time and space without the need for numerous (and somewhat artificial) transitions among pre-defined classes. However, particle property models often require fundamental parameters that are typically derived from laboratory measurements. For instance, the evolution of particle shape during vapor depositional growth requires knowledge of the growth efficiencies for the various axis of the crystals, which in turn depends on surface parameters that can only be determined in the laboratory. The evolution of particle shapes and density during riming, aggregation, and melting require data on the redistribution of mass across a crystals axis as that crystal collects water drops, ice crystals, or melts. Predicting the evolution of particle properties based on laboratory-determined parameters has a substantial influence on the evolution of some cloud systems. Radiatively-driven cirrus clouds show a broader range of competition between heterogeneous nucleation and homogeneous freezing when ice crystal properties are predicted. Even strongly convective squall lines show a substantial influence to predicted particle properties: The more natural evolution of ice crystals during riming produces graupel-like particles with size and fall-speeds required for the formation of a classic transition zone and extended stratiform precipitation region.

Setting semantics: conceptual set can determine the physical properties that capture attention.

PubMed

Goodhew, Stephanie C; Kendall, William; Ferber, Susanne; Pratt, Jay

2014-08-01

The ability of a stimulus to capture visuospatial attention depends on the interplay between its bottom-up saliency and its relationship to an observer's top-down control set, such that stimuli capture attention if they match the predefined properties that distinguish a searched-for target from distractors (Folk, Remington, & Johnston, Journal of Experimental Psychology: Human Perception & Performance, 18, 1030-1044 1992). Despite decades of research on this phenomenon, however, the vast majority has focused exclusively on matches based on low-level physical properties. Yet if contingent capture is indeed a "top-down" influence on attention, then semantic content should be accessible and able to determine which physical features capture attention. Here we tested this prediction by examining whether a semantically defined target could create a control set for particular features. To do this, we had participants search to identify a target that was differentiated from distractors by its meaning (e.g., the word "red" among color words all written in black). Before the target array, a cue was presented, and it was varied whether the cue appeared in the physical color implied by the target word. Across three experiments, we found that cues that embodied the meaning of the word produced greater cuing than cues that did not. This suggests that top-down control sets activate content that is semantically associated with the target-defining property, and this content in turn has the ability to exogenously orient attention.

Prediction of solvation enthalpy of gaseous organic compounds in propanol

NASA Astrophysics Data System (ADS)

Golmohammadi, Hassan; Dashtbozorgi, Zahra

2016-09-01

The purpose of this paper is to present a novel way for developing quantitative structure-property relationship (QSPR) models to predict the gas-to-propanol solvation enthalpy (Δ H solv) of 95 organic compounds. Different kinds of descriptors were calculated for each compound using the Dragon software package. The variable selection technique of replacement method (RM) was employed to select the optimal subset of solute descriptors. Our investigation reveals that the dependence of physical chemistry properties of solution on solvation enthalpy is nonlinear and that the RM method is unable to model the solvation enthalpy accurately. The results established that the calculated Δ H solv values by SVM were in good agreement with the experimental ones, and the performances of the SVM models were superior to those obtained by RM model.

Space shuttle nonmetallic materials age life prediction

NASA Technical Reports Server (NTRS)

Mendenhall, G. D.; Hassell, J. A.; Nathan, R. A.

1975-01-01

The chemiluminescence from samples of polybutadiene, Viton, Teflon, Silicone, PL 731 Adhesive, and SP 296 Boron-Epoxy composite was measured at temperatures from 25 to 150 C. Excellent correlations were obtained between chemiluminescence and temperature. These correlations serve to validate accelerated aging tests (at elevated temperatures) designed to predict service life at lower temperatures. In most cases, smooth or linear correlations were obtained between chemiluminescence and physical properties of purified polymer gums, including the tensile strength, viscosity, and loss tangent. The latter is a complex function of certain polymer properties. Data were obtained with far greater ease by the chemiluminescence technique than by the conventional methods of study. The chemiluminescence from the Teflon (Halon) samples was discovered to arise from trace amounts of impurities, which were undetectable by conventional, destructive analysis of the sample.

Water permeation and electrical properties of pottants, backings, and pottant/backing composites

NASA Technical Reports Server (NTRS)

Orehotsky, J.

1986-01-01

It is reported that the interface between plastic film back covers and ethylene vinyl acetates (EVA) or polyvinyl butyral (PVB) in photovoltaic modules can influence water permeation, and electrial properties of the composites such as leakage current and dielectric constant. The interface can either be one of two dissimilar materials in physical contact with no intermixing, or the interface can constitute a thin zone which is an interphase of the two materials having a gradient composition from one material to the other. The former condition is described as a discrete interface. A discrete interface model was developed to predict water permeation, dielectric strength, and leakage current for EVA, ethylene methyl acrylate (EMA), and PVB coupled to Tedlar and mylar films. Experimental data was compared with predicted data.

Superhigh moduli and tension-induced phase transition of monolayer gamma-boron at finite temperatures.

PubMed

Zhao, Junhua; Yang, Zhaoyao; Wei, Ning; Kou, Liangzhi

2016-03-16

Two dimensional (2D) gamma-boron (γ-B28) thin films have been firstly reported by the experiments of the chemical vapor deposition in the latest study. However, their mechanical properties are still not clear. Here we predict the superhigh moduli (785 ± 42 GPa at 300 K) and the tension-induced phase transition of monolayer γ-B28 along a zigzag direction for large deformations at finite temperatures using molecular dynamics (MD) simulations. The new phase can be kept stable after unloading process at these temperatures. The predicted mechanical properties are reasonable when compared with our results from density functional theory. This study provides physical insights into the origins of the new phase transition of monolayer γ-B28 at finite temperatures.

Prediction of soil properties using imaging spectroscopy: Considering fractional vegetation cover to improve accuracy

NASA Astrophysics Data System (ADS)

Franceschini, M. H. D.; Demattê, J. A. M.; da Silva Terra, F.; Vicente, L. E.; Bartholomeus, H.; de Souza Filho, C. R.

2015-06-01

Spectroscopic techniques have become attractive to assess soil properties because they are fast, require little labor and may reduce the amount of laboratory waste produced when compared to conventional methods. Imaging spectroscopy (IS) can have further advantages compared to laboratory or field proximal spectroscopic approaches such as providing spatially continuous information with a high density. However, the accuracy of IS derived predictions decreases when the spectral mixture of soil with other targets occurs. This paper evaluates the use of spectral data obtained by an airborne hyperspectral sensor (ProSpecTIR-VS - Aisa dual sensor) for prediction of physical and chemical properties of Brazilian highly weathered soils (i.e., Oxisols). A methodology to assess the soil spectral mixture is adapted and a progressive spectral dataset selection procedure, based on bare soil fractional cover, is proposed and tested. Satisfactory performances are obtained specially for the quantification of clay, sand and CEC using airborne sensor data (R2 of 0.77, 0.79 and 0.54; RPD of 2.14, 2.22 and 1.50, respectively), after spectral data selection is performed; although results obtained for laboratory data are more accurate (R2 of 0.92, 0.85 and 0.75; RPD of 3.52, 2.62 and 2.04, for clay, sand and CEC, respectively). Most importantly, predictions based on airborne-derived spectra for which the bare soil fractional cover is not taken into account show considerable lower accuracy, for example for clay, sand and CEC (RPD of 1.52, 1.64 and 1.16, respectively). Therefore, hyperspectral remotely sensed data can be used to predict topsoil properties of highly weathered soils, although spectral mixture of bare soil with vegetation must be considered in order to achieve an improved prediction accuracy.

Mapping The Temporal and Spatial Variability of Soil Moisture Content Using Proximal Soil Sensing

NASA Astrophysics Data System (ADS)

Virgawati, S.; Mawardi, M.; Sutiarso, L.; Shibusawa, S.; Segah, H.; Kodaira, M.

2018-05-01

In studies related to soil optical properties, it has been proven that visual and NIR soil spectral response can predict soil moisture content (SMC) using proper data analysis techniques. SMC is one of the most important soil properties influencing most physical, chemical, and biological soil processes. The problem is how to provide reliable, fast and inexpensive information of SMC in the subsurface from numerous soil samples and repeated measurement. The use of spectroscopy technology has emerged as a rapid and low-cost tool for extensive investigation of soil properties. The objective of this research was to develop calibration models based on laboratory Vis-NIR spectroscopy to estimate the SMC at four different growth stages of the soybean crop in Yogyakarta Province. An ASD Field-spectrophotoradiometer was used to measure the reflectance of soil samples. The partial least square regression (PLSR) was performed to establish the relationship between the SMC with Vis-NIR soil reflectance spectra. The selected calibration model was used to predict the new samples of SMC. The temporal and spatial variability of SMC was performed in digital maps. The results revealed that the calibration model was excellent for SMC prediction. Vis-NIR spectroscopy was a reliable tool for the prediction of SMC.

Biot-Gassmann theory for velocities of gas hydrate-bearing sediments

USGS Publications Warehouse

Lee, M.W.

2002-01-01

Elevated elastic velocities are a distinct physical property of gas hydrate-bearing sediments. A number of velocity models and equations (e.g., pore-filling model, cementation model, effective medium theories, weighted equations, and time-average equations) have been used to describe this effect. In particular, the weighted equation and effective medium theory predict reasonably well the elastic properties of unconsolidated gas hydrate-bearing sediments. A weakness of the weighted equation is its use of the empirical relationship of the time-average equation as one element of the equation. One drawback of the effective medium theory is its prediction of unreasonably higher shear-wave velocity at high porosities, so that the predicted velocity ratio does not agree well with the observed velocity ratio. To overcome these weaknesses, a method is proposed, based on Biot-Gassmann theories and assuming the formation velocity ratio (shear to compressional velocity) of an unconsolidated sediment is related to the velocity ratio of the matrix material of the formation and its porosity. Using the Biot coefficient calculated from either the weighted equation or from the effective medium theory, the proposed method accurately predicts the elastic properties of unconsolidated sediments with or without gas hydrate concentration. This method was applied to the observed velocities at the Mallik 2L-39 well, Mackenzie Delta, Canada.

Predicting the Magnetic Properties of ICMEs: A Pragmatic View

NASA Astrophysics Data System (ADS)

Riley, P.; Linker, J.; Ben-Nun, M.; Torok, T.; Ulrich, R. K.; Russell, C. T.; Lai, H.; de Koning, C. A.; Pizzo, V. J.; Liu, Y.; Hoeksema, J. T.

2017-12-01

The southward component of the interplanetary magnetic field plays a crucial role in being able to successfully predict space weather phenomena. Yet, thus far, it has proven extremely difficult to forecast with any degree of accuracy. In this presentation, we describe an empirically-based modeling framework for estimating Bz values during the passage of interplanetary coronal mass ejections (ICMEs). The model includes: (1) an empirically-based estimate of the magnetic properties of the flux rope in the low corona (including helicity and field strength); (2) an empirically-based estimate of the dynamic properties of the flux rope in the high corona (including direction, speed, and mass); and (3) a physics-based estimate of the evolution of the flux rope during its passage to 1 AU driven by the output from (1) and (2). We compare model output with observations for a selection of events to estimate the accuracy of this approach. Importantly, we pay specific attention to the uncertainties introduced by the components within the framework, separating intrinsic limitations from those that can be improved upon, either by better observations or more sophisticated modeling. Our analysis suggests that current observations/modeling are insufficient for this empirically-based framework to provide reliable and actionable prediction of the magnetic properties of ICMEs. We suggest several paths that may lead to better forecasts.

Analytical relationships for prediction of the mechanical properties of additively manufactured porous biomaterials.

PubMed

Zadpoor, Amir Abbas; Hedayati, Reza

2016-12-01

Recent developments in additive manufacturing techniques have motivated an increasing number of researchers to study regular porous biomaterials that are based on repeating unit cells. The physical and mechanical properties of such porous biomaterials have therefore received increasing attention during recent years. One of the areas that have revived is analytical study of the mechanical behavior of regular porous biomaterials with the aim of deriving analytical relationships that could predict the relative density and mechanical properties of porous biomaterials, given the design and dimensions of their repeating unit cells. In this article, we review the analytical relationships that have been presented in the literature for predicting the relative density, elastic modulus, Poisson's ratio, yield stress, and buckling limit of regular porous structures based on various types of unit cells. The reviewed analytical relationships are used to compare the mechanical properties of porous biomaterials based on different types of unit cells. The major areas where the analytical relationships have improved during the recent years are discussed and suggestions are made for future research directions. © 2016 Wiley Periodicals, Inc. J Biomed Mater Res Part A: 104A: 3164-3174, 2016. © 2016 The Authors Journal of Biomedical Materials Research Part A Published by Wiley Periodicals, Inc.

A Database Approach for Predicting and Monitoring Baked Anode Properties

NASA Astrophysics Data System (ADS)

Lauzon-Gauthier, Julien; Duchesne, Carl; Tessier, Jayson

2012-11-01

The baked anode quality control strategy currently used by most carbon plants based on testing anode core samples in the laboratory is inadequate for facing increased raw material variability. The low core sampling rate limited by lab capacity and the common practice of reporting averaged properties based on some anode population mask a significant amount of individual anode variability. In addition, lab results are typically available a few weeks after production and the anodes are often already set in the reduction cells preventing early remedial actions when necessary. A database approach is proposed in this work to develop a soft-sensor for predicting individual baked anode properties at the end of baking cycle. A large historical database including raw material properties, process operating parameters and anode core data was collected from a modern Alcoa plant. A multivariate latent variable PLS regression method was used for analyzing the large database and building the soft-sensor model. It is shown that the general low frequency trends in most anode physical and mechanical properties driven by raw material changes are very well captured by the model. Improvements in the data infrastructure (instrumentation, sampling frequency and location) will be necessary for predicting higher frequency variations in individual baked anode properties. This paper also demonstrates how multivariate latent variable models can be interpreted against process knowledge and used for real-time process monitoring of carbon plants, and detection of faults and abnormal operation.

Development of property-transfer models for estimating the hydraulic properties of deep sediments at the Idaho National Engineering and Environmental Laboratory, Idaho

USGS Publications Warehouse

Winfield, Kari A.

2005-01-01

Because characterizing the unsaturated hydraulic properties of sediments over large areas or depths is costly and time consuming, development of models that predict these properties from more easily measured bulk-physical properties is desirable. At the Idaho National Engineering and Environmental Laboratory, the unsaturated zone is composed of thick basalt flow sequences interbedded with thinner sedimentary layers. Determining the unsaturated hydraulic properties of sedimentary layers is one step in understanding water flow and solute transport processes through this complex unsaturated system. Multiple linear regression was used to construct simple property-transfer models for estimating the water-retention curve and saturated hydraulic conductivity of deep sediments at the Idaho National Engineering and Environmental Laboratory. The regression models were developed from 109 core sample subsets with laboratory measurements of hydraulic and bulk-physical properties. The core samples were collected at depths of 9 to 175 meters at two facilities within the southwestern portion of the Idaho National Engineering and Environmental Laboratory-the Radioactive Waste Management Complex, and the Vadose Zone Research Park southwest of the Idaho Nuclear Technology and Engineering Center. Four regression models were developed using bulk-physical property measurements (bulk density, particle density, and particle size) as the potential explanatory variables. Three representations of the particle-size distribution were compared: (1) textural-class percentages (gravel, sand, silt, and clay), (2) geometric statistics (mean and standard deviation), and (3) graphical statistics (median and uniformity coefficient). The four response variables, estimated from linear combinations of the bulk-physical properties, included saturated hydraulic conductivity and three parameters that define the water-retention curve. For each core sample,values of each water-retention parameter were estimated from the appropriate regression equation and used to calculate an estimated water-retention curve. The degree to which the estimated curve approximated the measured curve was quantified using a goodness-of-fit indicator, the root-mean-square error. Comparison of the root-mean-square-error distributions for each alternative particle-size model showed that the estimated water-retention curves were insensitive to the way the particle-size distribution was represented. Bulk density, the median particle diameter, and the uniformity coefficient were chosen as input parameters for the final models. The property-transfer models developed in this study allow easy determination of hydraulic properties without need for their direct measurement. Additionally, the models provide the basis for development of theoretical models that rely on physical relationships between the pore-size distribution and the bulk-physical properties of the media. With this adaptation, the property-transfer models should have greater application throughout the Idaho National Engineering and Environmental Laboratory and other geographic locations.

FTire and puzzling tyre physics: teacher, not student

NASA Astrophysics Data System (ADS)

Gipser, Michael

2016-04-01

By means of some instructive examples, the contribution shows how even complex phenomena and relations in tyre physics are better understood by using a physics-based tyre simulation model like FTire. In contrast to approximation-based phenomenological models, such an approach will give insight into, rather than requiring description of, the tyre's behaviour. Examples studied here comprise * predicted influence of wheel load, inflation pressure, camber angle, and slow rolling speed on parking torque, * predicted influence of inflation pressure on cornering stiffness and pneumatic trail, * relaxation length: ramping up and down slip angle and wheel load, * handling characteristic on very rough roads, * a strange phenomenon: cleats that 'attract' a tyre. Related to these studies, user-friendly simulation tools on the basis of FTire are introduced, which help in understanding the above-mentioned complex tyre properties. One of these tools, being valuable both in teaching and for vehicle/tyre dynamics experts in industry and research, allows the user to interactively modify, during a running simulation, tyre geometry, material data, and operating conditions. The impact of these variations both on tyre forces and moments as well as on internal tyre states can be directly seen in a running animation, and later analysed with a large variety of post-processing tools. Animations for all case studies are available for download on http://www.cosin.eu/animations. All registered trademarks used here are properties of their respective owners.

Relationships between physical properties and sequence in silkworm silks

PubMed Central

Malay, Ali D.; Sato, Ryota; Yazawa, Kenjiro; Watanabe, Hiroe; Ifuku, Nao; Masunaga, Hiroyasu; Hikima, Takaaki; Guan, Juan; Mandal, Biman B.; Damrongsakkul, Siriporn; Numata, Keiji

2016-01-01

Silk has attracted widespread attention due to its superlative material properties and promising applications. However, the determinants behind the variations in material properties among different types of silk are not well understood. We analysed the physical properties of silk samples from a variety of silkmoth cocoons, including domesticated Bombyx mori varieties and several species from Saturniidae. Tensile deformation tests, thermal analyses, and investigations on crystalline structure and orientation of the fibres were performed. The results showed that saturniid silks produce more highly-defined structural transitions compared to B. mori, as seen in the yielding and strain hardening events during tensile deformation and in the changes observed during thermal analyses. These observations were analysed in terms of the constituent fibroin sequences, which in B. mori are predicted to produce heterogeneous structures, whereas the strictly modular repeats of the saturniid sequences are hypothesized to produce structures that respond in a concerted manner. Within saturniid fibroins, thermal stability was found to correlate with the abundance of poly-alanine residues, whereas differences in fibre extensibility can be related to varying ratios of GGX motifs versus bulky hydrophobic residues in the amorphous phase. PMID:27279149

Kinetics and equilibrium of solute diffusion into human hair.

PubMed

Wang, Liming; Chen, Longjian; Han, Lujia; Lian, Guoping

2012-12-01

The uptake kinetics of five molecules by hair has been measured and the effects of pH and physical chemical properties of molecules were investigated. A theoretical model is proposed to analyze the experimental data. The results indicate that the binding affinity of solute to hair, as characterized by hair-water partition coefficient, scales to the hydrophobicity of the solute and decreases dramatically as the pH increases to the dissociation constant. The effective diffusion coefficient of solute depended not only on the molecular size as most previous studies suggested, but also on the binding affinity as well as solute dissociation. It appears that the uptake of molecules by hair is due to both hydrophobic interaction and ionic charge interaction. Based on theoretical considerations of the cellular structure, composition and physical chemical properties of hair, quantitative-structure-property-relationships (QSPR) have been proposed to predict the hair-water partition coefficient (PC) and the effective diffusion coefficient (D (e)) of solute. The proposed QSPR models fit well with the experimental data. This paper could be taken as a reference for investigating the adsorption properties for polymeric materials, fibres, and biomaterials.

Relationships between physical properties and sequence in silkworm silks

NASA Astrophysics Data System (ADS)

Malay, Ali D.; Sato, Ryota; Yazawa, Kenjiro; Watanabe, Hiroe; Ifuku, Nao; Masunaga, Hiroyasu; Hikima, Takaaki; Guan, Juan; Mandal, Biman B.; Damrongsakkul, Siriporn; Numata, Keiji

2016-06-01

Silk has attracted widespread attention due to its superlative material properties and promising applications. However, the determinants behind the variations in material properties among different types of silk are not well understood. We analysed the physical properties of silk samples from a variety of silkmoth cocoons, including domesticated Bombyx mori varieties and several species from Saturniidae. Tensile deformation tests, thermal analyses, and investigations on crystalline structure and orientation of the fibres were performed. The results showed that saturniid silks produce more highly-defined structural transitions compared to B. mori, as seen in the yielding and strain hardening events during tensile deformation and in the changes observed during thermal analyses. These observations were analysed in terms of the constituent fibroin sequences, which in B. mori are predicted to produce heterogeneous structures, whereas the strictly modular repeats of the saturniid sequences are hypothesized to produce structures that respond in a concerted manner. Within saturniid fibroins, thermal stability was found to correlate with the abundance of poly-alanine residues, whereas differences in fibre extensibility can be related to varying ratios of GGX motifs versus bulky hydrophobic residues in the amorphous phase.

Improved method for predicting protein fold patterns with ensemble classifiers.

PubMed

Chen, W; Liu, X; Huang, Y; Jiang, Y; Zou, Q; Lin, C

2012-01-27

Protein folding is recognized as a critical problem in the field of biophysics in the 21st century. Predicting protein-folding patterns is challenging due to the complex structure of proteins. In an attempt to solve this problem, we employed ensemble classifiers to improve prediction accuracy. In our experiments, 188-dimensional features were extracted based on the composition and physical-chemical property of proteins and 20-dimensional features were selected using a coupled position-specific scoring matrix. Compared with traditional prediction methods, these methods were superior in terms of prediction accuracy. The 188-dimensional feature-based method achieved 71.2% accuracy in five cross-validations. The accuracy rose to 77% when we used a 20-dimensional feature vector. These methods were used on recent data, with 54.2% accuracy. Source codes and dataset, together with web server and software tools for prediction, are available at: http://datamining.xmu.edu.cn/main/~cwc/ProteinPredict.html.

Optical and Excitonic Properties of Atomically Thin Transition-Metal Dichalcogenides

NASA Astrophysics Data System (ADS)

Berkelbach, Timothy C.; Reichman, David R.

2018-03-01

Starting with the isolation of a single sheet of graphene, the study of layered materials has been one of the most active areas of condensed matter physics, chemistry, and materials science. Single-layer transition-metal dichalcogenides are direct-gap semiconducting analogs of graphene that exhibit novel electronic and optical properties. These features provide exciting opportunities for the discovery of both new fundamental physical phenomena as well as innovative device platforms. Here, we review the progress associated with the creation and use of a simple microscopic framework for describing the optical and excitonic behavior of few-layer transition-metal dichalcogenides, which is based on symmetry, band structure, and the effective interactions between charge carriers in these materials. This approach provides an often quantitative account of experiments that probe the physics associated with strong electron–hole interactions in these quasi two-dimensional systems and has been successfully employed by many groups to both describe and predict emergent excitonic behavior in these layered semiconducting systems.

Recovering Galaxy Properties Using Gaussian Process SED Fitting

NASA Astrophysics Data System (ADS)

Iyer, Kartheik; Awan, Humna

2018-01-01

Information about physical quantities like the stellar mass, star formation rates, and ages for distant galaxies is contained in their spectral energy distributions (SEDs), obtained through photometric surveys like SDSS, CANDELS, LSST etc. However, noise in the photometric observations often is a problem, and using naive machine learning methods to estimate physical quantities can result in overfitting the noise, or converging on solutions that lie outside the physical regime of parameter space.We use Gaussian Process regression trained on a sample of SEDs corresponding to galaxies from a Semi-Analytic model (Somerville+15a) to estimate their stellar masses, and compare its performance to a variety of different methods, including simple linear regression, Random Forests, and k-Nearest Neighbours. We find that the Gaussian Process method is robust to noise and predicts not only stellar masses but also their uncertainties. The method is also robust in the cases where the distribution of the training data is not identical to the target data, which can be extremely useful when generalized to more subtle galaxy properties.

The Physics of Extrasolar Gaseous Planets : from Theory to Observable Signatures

NASA Astrophysics Data System (ADS)

Chabrier, G.; Allard, F.; Baraffe, I.; Barman, T.; Hauschildt, P. H.

2004-12-01

We review our present understanding of the physical properties of substellar objects, brown dwarfs and irradiated or non-irradiated gaseous exoplanets. This includes a description of their internal properties, mechanical structure and heat content, their atmospheric properties, thermal profile and emergent spectrum, and their evolution, in particular as irradiated companions of a close parent star. The general theory can be used to make predictions in term of detectability for the future observational projects. Special attention is devoted to the evolution of the two presently detected transit planets, HD 209458b and OGLE-TR-56B. For this latter, we present a consistent evolution for its recently revised mass and show that we reproduce the observed radius within its error bars. We briefly discuss differences between brown dwarfs and gaseous planets, both in terms of mass function and formation process. We outline several arguments to show that the minimum mass for deuterium burning, recently adopted officially as the limit to distinguish the two types of objects, is unlikely to play any specific role in star formation, so that such a limit is of purely semantic nature and is not supported by a physical justification.

Evaluating measurement uncertainty in fluid phase equilibrium calculations

NASA Astrophysics Data System (ADS)

van der Veen, Adriaan M. H.

2018-04-01

The evaluation of measurement uncertainty in accordance with the ‘Guide to the expression of uncertainty in measurement’ (GUM) has not yet become widespread in physical chemistry. With only the law of the propagation of uncertainty from the GUM, many of these uncertainty evaluations would be cumbersome, as models are often non-linear and require iterative calculations. The methods from GUM supplements 1 and 2 enable the propagation of uncertainties under most circumstances. Experimental data in physical chemistry are used, for example, to derive reference property data and support trade—all applications where measurement uncertainty plays an important role. This paper aims to outline how the methods for evaluating and propagating uncertainty can be applied to some specific cases with a wide impact: deriving reference data from vapour pressure data, a flash calculation, and the use of an equation-of-state to predict the properties of both phases in a vapour-liquid equilibrium. The three uncertainty evaluations demonstrate that the methods of GUM and its supplements are a versatile toolbox that enable us to evaluate the measurement uncertainty of physical chemical measurements, including the derivation of reference data, such as the equilibrium thermodynamical properties of fluids.

Handbook of LHC Higgs Cross Sections: 4. Deciphering the Nature of the Higgs Sector

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

de Florian, D.

This Report summarizes the results of the activities of the LHC Higgs Cross Section Working Group in the period 2014-2016. The main goal of the working group was to present the state-of-the-art of Higgs physics at the LHC, integrating all new results that have appeared in the last few years. The first part compiles the most up-to-date predictions of Higgs boson production cross sections and decay branching ratios, parton distribution functions, and off-shell Higgs boson production and interference effects. The second part discusses the recent progress in Higgs effective field theory predictions, followed by the third part on pseudo-observables, simplifiedmore » template cross section and fiducial cross section measurements, which give the baseline framework for Higgs boson property measurements. The fourth part deals with the beyond the Standard Model predictions of various benchmark scenarios of Minimal Supersymmetric Standard Model, extended scalar sector, Next-to-Minimal Supersymmetric Standard Model and exotic Higgs boson decays. This report follows three previous working-group reports: Handbook of LHC Higgs Cross Sections: 1. Inclusive Observables (CERN-2011-002), Handbook of LHC Higgs Cross Sections: 2. Differential Distributions (CERN-2012-002), and Handbook of LHC Higgs Cross Sections: 3. Higgs properties (CERN-2013-004). The current report serves as the baseline reference for Higgs physics in LHC Run 2 and beyond.« less

On the role of fluctuations in the modeling of complex systems.

NASA Astrophysics Data System (ADS)

Droz, Michel; Pekalski, Andrzej

2016-09-01

The study of models is ubiquitous in sciences like physics, chemistry, ecology, biology or sociology. Models are used to explain experimental facts or to make new predictions. For any system, one can distinguish several levels of description. In the simplest mean-field like description the dynamics is described in terms of spatially averaged quantities while in a microscopic approach local properties are taken into account and local fluctuations for the relevant variables are present. The properties predicted by these two different approaches may be drastically different. In a large body of research literature concerning complex systems this problem is often overlooked and simple mean-field like approximation are used without asking the question of the robustness of the corresponding predictions. The goal of this paper is twofold, first to illustrate the importance of the fluctuations in a self-contained and pedagogical way, by revisiting two different classes of problems where thorough investigations have been conducted (equilibrium and non-equilibrium statistical physics). Second, we present our original research on the dynamics of population of annual plants which are competing among themselves for just one resource (water) through a stochastic dynamics. Depending on the observable considered, the mean-field like and microscopic approaches agree or totally disagree. There is not a general criterion allowing to decide a priori when the two approaches will agree.

Pore network extraction from pore space images of various porous media systems

NASA Astrophysics Data System (ADS)

Yi, Zhixing; Lin, Mian; Jiang, Wenbin; Zhang, Zhaobin; Li, Haishan; Gao, Jian

2017-04-01

Pore network extraction, which is defined as the transformation from irregular pore space to a simplified network in the form of pores connected by throats, is significant to microstructure analysis and network modeling. A physically realistic pore network is not only a representation of the pore space in the sense of topology and morphology, but also a good tool for predicting transport properties accurately. We present a method to extract pore network by employing the centrally located medial axis to guide the construction of maximal-balls-like skeleton where the pores and throats are defined and parameterized. To validate our method, various rock samples including sand pack, sandstones, and carbonates were used to extract pore networks. The pore structures were compared quantitatively with the structures extracted by medial axis method or maximal ball method. The predicted absolute permeability and formation factor were verified against the theoretical solutions obtained by lattice Boltzmann method and finite volume method, respectively. The two-phase flow was simulated through the networks extracted from homogeneous sandstones, and the generated relative permeability curves were compared with the data obtained from experimental method and other numerical models. The results show that the accuracy of our network is higher than that of other networks for predicting transport properties, so the presented method is more reliable for extracting physically realistic pore network.

Prediction and characterization of heat-affected zone formation in tin-bismuth alloys due to nickel-aluminum multilayer foil reaction

DOE PAGES

Hooper, R. J.; Davis, C. G.; Johns, P. M.; ...

2015-06-26

Reactive multilayer foils have the potential to be used as local high intensity heat sources for a variety of applications. In this study, most of the past research effort concerning these materials have focused on understanding the structure-property relationships of the foils that govern the energy released during a reaction. To improve the ability of researchers to more rapidly develop technologies based on reactive multilayer foils, a deeper and more predictive understanding of the relationship between the heat released from the foil and microstructural evolution in the neighboring materials is needed. This work describes the development of a numerical modelmore » for the purpose of predicting heat affected zone size in substrate materials. The model is experimentally validated using a commercially available Ni-Al multilayer foils and alloys from the Sn-Bi binary system. To accomplish this, phenomenological models for predicting the variation of physical properties (i.e., thermal conductivity, density, and heat capacity) with temperature and composition in the Sn-Bi system were utilized using literature data.« less

The Effect of Petrographic Characteristics on Engineering Properties of Conglomerates from Famenin Region, Northeast of Hamedan, Iran

NASA Astrophysics Data System (ADS)

Khanlari, G. R.; Heidari, M.; Noori, M.; Momeni, A.

2016-07-01

To assess relationship between engineering characteristics and petrographic features, conglomerates samples related to Qom formation from Famenin region in northeast of Hamedan province were studied. Samples were tested in laboratory to determine the uniaxial compressive strength, point load strength index, modulus of elasticity, porosity, dry and saturation densities. For determining petrographic features, textural and mineralogical parameters, thin sections of the samples were prepared and studied. The results show that the effect of textural characteristics on the engineering properties of conglomerates supposed to be more important than mineralogical composition. It also was concluded that the packing proximity, packing density, grain shape and mean grain size, cement and matrix frequency are as textural features that have a significant effect on the physical and mechanical properties of the studied conglomerates. In this study, predictive statistical relationships were developed to estimate the physical and mechanical properties of the rocks based on the results of petrographic features. Furthermore, multivariate linear regression was used in four different steps comprising various combinations of petrographical characteristics for each engineering parameters. Finally, the best equations with specific arrangement were suggested to estimate engineering properties of the Qom formation conglomerates.

Local functional descriptors for surface comparison based binding prediction

PubMed Central

2012-01-01

Background Molecular recognition in proteins occurs due to appropriate arrangements of physical, chemical, and geometric properties of an atomic surface. Similar surface regions should create similar binding interfaces. Effective methods for comparing surface regions can be used in identifying similar regions, and to predict interactions without regard to the underlying structural scaffold that creates the surface. Results We present a new descriptor for protein functional surfaces and algorithms for using these descriptors to compare protein surface regions to identify ligand binding interfaces. Our approach uses descriptors of local regions of the surface, and assembles collections of matches to compare larger regions. Our approach uses a variety of physical, chemical, and geometric properties, adaptively weighting these properties as appropriate for different regions of the interface. Our approach builds a classifier based on a training corpus of examples of binding sites of the target ligand. The constructed classifiers can be applied to a query protein providing a probability for each position on the protein that the position is part of a binding interface. We demonstrate the effectiveness of the approach on a number of benchmarks, demonstrating performance that is comparable to the state-of-the-art, with an approach with more generality than these prior methods. Conclusions Local functional descriptors offer a new method for protein surface comparison that is sufficiently flexible to serve in a variety of applications. PMID:23176080

Variability of computational fluid dynamics solutions for pressure and flow in a giant aneurysm: the ASME 2012 Summer Bioengineering Conference CFD Challenge.

PubMed

Steinman, David A; Hoi, Yiemeng; Fahy, Paul; Morris, Liam; Walsh, Michael T; Aristokleous, Nicolas; Anayiotos, Andreas S; Papaharilaou, Yannis; Arzani, Amirhossein; Shadden, Shawn C; Berg, Philipp; Janiga, Gábor; Bols, Joris; Segers, Patrick; Bressloff, Neil W; Cibis, Merih; Gijsen, Frank H; Cito, Salvatore; Pallarés, Jordi; Browne, Leonard D; Costelloe, Jennifer A; Lynch, Adrian G; Degroote, Joris; Vierendeels, Jan; Fu, Wenyu; Qiao, Aike; Hodis, Simona; Kallmes, David F; Kalsi, Hardeep; Long, Quan; Kheyfets, Vitaly O; Finol, Ender A; Kono, Kenichi; Malek, Adel M; Lauric, Alexandra; Menon, Prahlad G; Pekkan, Kerem; Esmaily Moghadam, Mahdi; Marsden, Alison L; Oshima, Marie; Katagiri, Kengo; Peiffer, Véronique; Mohamied, Yumnah; Sherwin, Spencer J; Schaller, Jens; Goubergrits, Leonid; Usera, Gabriel; Mendina, Mariana; Valen-Sendstad, Kristian; Habets, Damiaan F; Xiang, Jianping; Meng, Hui; Yu, Yue; Karniadakis, George E; Shaffer, Nicholas; Loth, Francis

2013-02-01

Stimulated by a recent controversy regarding pressure drops predicted in a giant aneurysm with a proximal stenosis, the present study sought to assess variability in the prediction of pressures and flow by a wide variety of research groups. In phase I, lumen geometry, flow rates, and fluid properties were specified, leaving each research group to choose their solver, discretization, and solution strategies. Variability was assessed by having each group interpolate their results onto a standardized mesh and centerline. For phase II, a physical model of the geometry was constructed, from which pressure and flow rates were measured. Groups repeated their simulations using a geometry reconstructed from a micro-computed tomography (CT) scan of the physical model with the measured flow rates and fluid properties. Phase I results from 25 groups demonstrated remarkable consistency in the pressure patterns, with the majority predicting peak systolic pressure drops within 8% of each other. Aneurysm sac flow patterns were more variable with only a few groups reporting peak systolic flow instabilities owing to their use of high temporal resolutions. Variability for phase II was comparable, and the median predicted pressure drops were within a few millimeters of mercury of the measured values but only after accounting for submillimeter errors in the reconstruction of the life-sized flow model from micro-CT. In summary, pressure can be predicted with consistency by CFD across a wide range of solvers and solution strategies, but this may not hold true for specific flow patterns or derived quantities. Future challenges are needed and should focus on hemodynamic quantities thought to be of clinical interest.

Juvenile body mass estimation: A methodological evaluation.

PubMed

Cowgill, Libby

2018-02-01

Two attempts have been made to develop body mass prediction formulae specifically for immature remains: Ruff (Ruff, C.C., 2007, Body size prediction from juvenile skeletal remains. American Journal Physical Anthropology 133, 698-716) and Robbins et al. (Robbins, G., Sciulli, P.W., Blatt, S.H., 2010. Estimating body mass in subadult human skeletons. American Journal Physical Anthropology 143, 146-150). While both were developed from the same reference population, they differ in their independent variable selection: Ruff (2008) used measures of metaphyseal and articular surface size to predict body mass in immature remains, whereas Robbins et al. (2010) relied on cross-sectional properties. Both methods perform well on independent testing samples; however, differences between the two methods exist in the predicted values. This research evaluates the differences in the body mass estimates from these two methods in seven geographically diverse skeletal samples under the age of 18 (n = 461). The purpose of this analysis is not to assess which method performs with greater accuracy or precision; instead, differences between the two methods are used as a heuristic device to focus attention on the unique challenges affecting the prediction of immature body mass estimates in particular. The two methods differ by population only in some cases, which may be a reflection of activity variation or nutritional status. In addition, cross-sectional properties almost always produce higher estimates than metaphyseal surface size across all age categories. This highlights the difficulty in teasing apart information related to body mass from that relevant to loading, particularly when the original reference population is urban/industrial. Copyright © 2017 Elsevier Ltd. All rights reserved.

Mechanical properties of transription

NASA Astrophysics Data System (ADS)

Sevier, Stuart; Levine, Herbert

Over the last several decades it has been increasingly recognized that both stochastic and mechanical processes play a central role in transcription. Though many aspects have been explained a number of fundamental properties are undeveloped. Recent results have pointed to mechanical feedback as the source of transcriptional bursting and DNA supercoiling but a reconciliation of this perspective with preexisting views of transcriptional is lacking. In this work we present a simple model of transcription where RNA elongation, RNA polymerase rotation and DNA supercoiling are coupled. The mechanical properties of each object form a foundational framework for understanding the physical nature of transcription. The resulting model can explain several important aspects of chromatin structure and generates a number of predictions for the mechanical properties of transcription.

Linear elastic properties derivation from microstructures representative of transport parameters.

PubMed

Hoang, Minh Tan; Bonnet, Guy; Tuan Luu, Hoang; Perrot, Camille

2014-06-01

It is shown that three-dimensional periodic unit cells (3D PUC) representative of transport parameters involved in the description of long wavelength acoustic wave propagation and dissipation through real foam samples may also be used as a standpoint to estimate their macroscopic linear elastic properties. Application of the model yields quantitative agreement between numerical homogenization results, available literature data, and experiments. Key contributions of this work include recognizing the importance of membranes and properties of the base material for the physics of elasticity. The results of this paper demonstrate that a 3D PUC may be used to understand and predict not only the sound absorbing properties of porous materials but also their transmission loss, which is critical for sound insulation problems.

Quantitative property-structural relation modeling on polymeric dielectric materials

NASA Astrophysics Data System (ADS)

Wu, Ke

Nowadays, polymeric materials have attracted more and more attention in dielectric applications. But searching for a material with desired properties is still largely based on trial and error. To facilitate the development of new polymeric materials, heuristic models built using the Quantitative Structure Property Relationships (QSPR) techniques can provide reliable "working solutions". In this thesis, the application of QSPR on polymeric materials is studied from two angles: descriptors and algorithms. A novel set of descriptors, called infinite chain descriptors (ICD), are developed to encode the chemical features of pure polymers. ICD is designed to eliminate the uncertainty of polymer conformations and inconsistency of molecular representation of polymers. Models for the dielectric constant, band gap, dielectric loss tangent and glass transition temperatures of organic polymers are built with high prediction accuracy. Two new algorithms, the physics-enlightened learning method (PELM) and multi-mechanism detection, are designed to deal with two typical challenges in material QSPR. PELM is a meta-algorithm that utilizes the classic physical theory as guidance to construct the candidate learning function. It shows better out-of-domain prediction accuracy compared to the classic machine learning algorithm (support vector machine). Multi-mechanism detection is built based on a cluster-weighted mixing model similar to a Gaussian mixture model. The idea is to separate the data into subsets where each subset can be modeled by a much simpler model. The case study on glass transition temperature shows that this method can provide better overall prediction accuracy even though less data is available for each subset model. In addition, the techniques developed in this work are also applied to polymer nanocomposites (PNC). PNC are new materials with outstanding dielectric properties. As a key factor in determining the dispersion state of nanoparticles in the polymer matrix, the surface tension components of polymers are modeled using ICD. Compared to the 3D surface descriptors used in a previous study, the model with ICD has a much improved prediction accuracy and stability particularly for the polar component. In predicting the enhancement effect of grafting functional groups on the breakdown strength of PNC, a simple local charge transfer model is proposed where the electron affinity (EA) and ionization energy (IE) determines the main charge trap depth in the system. This physical model is supported by first principle computation. QSPR models for EA and IE are also built, decreasing the computation time of EA and IE for a single molecule from several hours to less than one second. Furthermore, the designs of two web-based tools are introduced. The tools represent two commonly used applications for QSPR studies: data inquiry and prediction. Making models and data public available and easy to use is particularly crucial for QSPR research. The web tools described in this work should provide a good guidance and starting point for the further development of information tools enabling more efficient cooperation between computational and experimental communities.

On the influence of frequency-dependent elastic properties in vibro-acoustic modelling of porous materials under structural excitation

NASA Astrophysics Data System (ADS)

Van der Kelen, C.; Göransson, P.; Pluymers, B.; Desmet, W.

2014-12-01

The aspects related to modelling the frequency dependence of the elastic properties of air-saturated porous materials have been largely neglected in the past for several reasons. For acoustic excitation of porous materials, the material behaviour can be quite well represented by models where the properties of the solid frame have little influence. Only recently has the importance of the dynamic moduli of the frame come into focus. This is related to a growing interest in the material behaviour due to structural excitation. Two aspects stand out in connection with the elastic-dynamic behaviour. The first is related to methods for the characterisation of the dynamic moduli of porous materials. The second is a perceived lack of numerical methods able to model the complex material behaviour under structural excitation, in particular at higher frequencies. In the current paper, experimental data from a panel under structural excitation, coated with a porous material, are presented. In an attempt to correlate the experimental data to numerical predictions, it is found that the measured quasi-static material parameters do not suffice for an accurate prediction of the measured results. The elastic material parameters are then estimated by correlating the numerical prediction to the experimental data, following the physical behaviour predicted by the augmented Hooke's law. The change in material behaviour due to the frequency-dependent properties is illustrated in terms of the propagation of the slow wave and the shear wave in the porous material.

Use of similarity scoring in the development of oral solid dosage forms.

PubMed

Ferreira, Ana P; Olusanmi, Dolapo; Sprockel, Omar; Abebe, Admassu; Nikfar, Faranak; Tobyn, Mike

2016-12-05

In the oral solid dosage form space, material physical properties have a strong impact on the behaviour of the formulation during processing. The ability to identify materials with similar characteristics (and thus expected to exhibit similar behaviour) within the company's portfolio can help accelerate drug development by enabling early assessment and prediction of potential challenges associated with the powder properties of a new active pharmaceutical ingredient. Such developments will aid the production of robust dosage forms, in an efficient manner. Similarity scoring metrics are widely used in a number of scientific fields. This study proposes a practical implementation of this methodology within pharmaceutical development. The developed similarity metrics is based on the Mahalanobis distance. Scanning electron microscopy was used to confirm morphological similarity between the reference material and the closest matches identified by the metrics proposed. The results show that the metrics proposed are able to successfully identify material with similar physical properties. Copyright © 2015 Elsevier B.V. All rights reserved.

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

Martinez Ortega, Jorge

The Standard Model of Partice Physics (SM) is probably the most successful theory, regarding to his predictions. The SM prediction formore » $CP$ violation is not enough to explain the overwhelming asymmetry among the matter and anti-matter abundance. Measuring some process where $CP$ violation is different to the one predicted by the SM would be a clear signal for Physics Beyond the Standard Model. The SM prediction for the $CP$ violation phase, $$\\phi_{s}$$, in the $$B^{0}_{s}$$ meson is practically equal to zero for the current experiments. This means that measuring a deviation from zero in $$\\phi_{s}$$ could be an indication for Physics Beyond the SM. On the other hand, the approximation based on the ``heavy quark symmetry'' let approximated calculations of the fundamental quantities of those hadrons containing a heavy quark, $c,b,t$. These calculations are expressed as expansions on inverse powers of the heavy quark mass in such hadron. This formalism is called `` Heavy Quark Effective Theory'' (HQET), and has been successful predicting some properties of the heavy hadrons. The HQET prediction for the lifetime ratio the $$B^{0}_{d}$$ and $$B^{0}_{s}$$ is practically equal to one. So, measuring with good precision the $$B^{0}_{s}$$ lifetime is also a way to test an approximation based on the SM. In this thesis it is detailed presented the method to measure the $$\\phi_{s}$$ and the lifetime ratio of the $$B^{0}_{d}$$ and $$B^{0}_{s}$$, among other quantities, with the DØ located in the Fermi National Accelerator Laboratory, in the United States.« less

An operational mesoscale ensemble data assimilation and prediction system: E-RTFDDA

NASA Astrophysics Data System (ADS)

Liu, Y.; Hopson, T.; Roux, G.; Hacker, J.; Xu, M.; Warner, T.; Swerdlin, S.

2009-04-01

Mesoscale (2-2000 km) meteorological processes differ from synoptic circulations in that mesoscale weather changes rapidly in space and time, and physics processes that are parameterized in NWP models play a great role. Complex interactions of synoptic circulations, regional and local terrain, land-surface heterogeneity, and associated physical properties, and the physical processes of radiative transfer, cloud and precipitation and boundary layer mixing, are crucial in shaping regional weather and climate. Mesoscale ensemble analysis and prediction should sample the uncertainties of mesoscale modeling systems in representing these factors. An innovative mesoscale Ensemble Real-Time Four Dimensional Data Assimilation (E-RTFDDA) and forecasting system has been developed at NCAR. E-RTFDDA contains diverse ensemble perturbation approaches that consider uncertainties in all major system components to produce multi-scale continuously-cycling probabilistic data assimilation and forecasting. A 30-member E-RTFDDA system with three nested domains with grid sizes of 30, 10 and 3.33 km has been running on a Department of Defense high-performance computing platform since September 2007. It has been applied at two very different US geographical locations; one in the western inter-mountain area and the other in the northeastern states, producing 6 hour analyses and 48 hour forecasts, with 4 forecast cycles a day. The operational model outputs are analyzed to a) assess overall ensemble performance and properties, b) study terrain effect on mesoscale predictability, c) quantify the contribution of different ensemble perturbation approaches to the overall forecast skill, and d) assess the additional contributed skill from an ensemble calibration process based on a quantile-regression algorithm. The system and the results will be reported at the meeting.

Statistical analysis and modeling of intermittent transport events in the tokamak scrape-off layer

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

Anderson, Johan, E-mail: anderson.johan@gmail.com; Halpern, Federico D.; Ricci, Paolo

The turbulence observed in the scrape-off-layer of a tokamak is often characterized by intermittent events of bursty nature, a feature which raises concerns about the prediction of heat loads on the physical boundaries of the device. It appears thus necessary to delve into the statistical properties of turbulent physical fields such as density, electrostatic potential, and temperature, focusing on the mathematical expression of tails of the probability distribution functions. The method followed here is to generate statistical information from time-traces of the plasma density stemming from Braginskii-type fluid simulations and check this against a first-principles theoretical model. The analysis ofmore » the numerical simulations indicates that the probability distribution function of the intermittent process contains strong exponential tails, as predicted by the analytical theory.« less

Significant-Loophole-Free Test of Bell's Theorem with Entangled Photons.

PubMed

Giustina, Marissa; Versteegh, Marijn A M; Wengerowsky, Sören; Handsteiner, Johannes; Hochrainer, Armin; Phelan, Kevin; Steinlechner, Fabian; Kofler, Johannes; Larsson, Jan-Åke; Abellán, Carlos; Amaya, Waldimar; Pruneri, Valerio; Mitchell, Morgan W; Beyer, Jörn; Gerrits, Thomas; Lita, Adriana E; Shalm, Lynden K; Nam, Sae Woo; Scheidl, Thomas; Ursin, Rupert; Wittmann, Bernhard; Zeilinger, Anton

2015-12-18

Local realism is the worldview in which physical properties of objects exist independently of measurement and where physical influences cannot travel faster than the speed of light. Bell's theorem states that this worldview is incompatible with the predictions of quantum mechanics, as is expressed in Bell's inequalities. Previous experiments convincingly supported the quantum predictions. Yet, every experiment requires assumptions that provide loopholes for a local realist explanation. Here, we report a Bell test that closes the most significant of these loopholes simultaneously. Using a well-optimized source of entangled photons, rapid setting generation, and highly efficient superconducting detectors, we observe a violation of a Bell inequality with high statistical significance. The purely statistical probability of our results to occur under local realism does not exceed 3.74×10^{-31}, corresponding to an 11.5 standard deviation effect.

Information thermodynamics of near-equilibrium computation

NASA Astrophysics Data System (ADS)

Prokopenko, Mikhail; Einav, Itai

2015-06-01

In studying fundamental physical limits and properties of computational processes, one is faced with the challenges of interpreting primitive information-processing functions through well-defined information-theoretic as well as thermodynamic quantities. In particular, transfer entropy, characterizing the function of computational transmission and its predictability, is known to peak near critical regimes. We focus on a thermodynamic interpretation of transfer entropy aiming to explain the underlying critical behavior by associating information flows intrinsic to computational transmission with particular physical fluxes. Specifically, in isothermal systems near thermodynamic equilibrium, the gradient of the average transfer entropy is shown to be dynamically related to Fisher information and the curvature of system's entropy. This relationship explicitly connects the predictability, sensitivity, and uncertainty of computational processes intrinsic to complex systems and allows us to consider thermodynamic interpretations of several important extreme cases and trade-offs.

Parametric bicubic spline and CAD tools for complex targets shape modelling in physical optics radar cross section prediction

NASA Astrophysics Data System (ADS)

Delogu, A.; Furini, F.

1991-09-01

Increasing interest in radar cross section (RCS) reduction is placing new demands on theoretical, computation, and graphic techniques for calculating scattering properties of complex targets. In particular, computer codes capable of predicting the RCS of an entire aircraft at high frequency and of achieving RCS control with modest structural changes, are becoming of paramount importance in stealth design. A computer code, evaluating the RCS of arbitrary shaped metallic objects that are computer aided design (CAD) generated, and its validation with measurements carried out using ALENIA RCS test facilities are presented. The code, based on the physical optics method, is characterized by an efficient integration algorithm with error control, in order to contain the computer time within acceptable limits, and by an accurate parametric representation of the target surface in terms of bicubic splines.

Predicting the Macroscopic Fracture Energy of Epoxy Resins from Atomistic Molecular Simulations

DOE PAGES

Meng, Zhaoxu; Bessa, Miguel A.; Xia, Wenjie; ...

2016-12-06

Predicting the macroscopic fracture energy of highly crosslinked glassy polymers from atomistic simulations is challenging due to the size of the process zone being large in these systems. Here, we present a scale-bridging approach that links atomistic molecular dynamics simulations to macroscopic fracture properties on the basis of a continuum fracture mechanics model for two different epoxy materials. Our approach reveals that the fracture energy of epoxy resins strongly depends on the functionality of epoxy resin and the component ratio between the curing agent (amine) and epoxide. The most intriguing part of our study is that we demonstrate that themore » fracture energy exhibits a maximum value within the range of conversion degrees considered (from 65% to 95%), which can be attributed to the combined effects of structural rigidity and post-yield deformability. Our study provides physical insight into the molecular mechanisms that govern the fracture characteristics of epoxy resins and demonstrates the success of utilizing atomistic molecular simulations towards predicting macroscopic material properties.« less

Modelling Behaviour of a Carbon Epoxy Composite Exposed to Fire: Part II—Comparison with Experimental Results

PubMed Central

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

2017-01-01

Based on a phenomenological methodology, a three dimensional (3D) thermochemical model was developed to predict the temperature profile, the mass loss and the decomposition front of a carbon-reinforced epoxy composite laminate (T700/M21 composite) exposed to fire conditions. This 3D model takes into account the energy accumulation by the solid material, the anisotropic heat conduction, the thermal decomposition of the material, the gas mass flow into the composite, and the internal pressure. Thermophysical properties defined as temperature dependant properties were characterised using existing as well as innovative methodologies in order to use them as inputs into our physical model. The 3D thermochemical model accurately predicts the measured mass loss and observed decomposition front when the carbon fibre/epoxy composite is directly impacted by a propane flame. In short, the model shows its capability to predict the fire behaviour of a carbon fibre reinforced composite for fire safety engineering. PMID:28772836

Efficient first-principles prediction of solid stability: Towards chemical accuracy

DOE PAGES

Zhang, Yubo; Kitchaev, Daniil A.; Yang, Julia; ...

2018-03-09

The question of material stability is of fundamental importance to any analysis of system properties in condensed matter physics and materials science. The ability to evaluate chemical stability, i.e., whether a stoichiometry will persist in some chemical environment, and structure selection, i.e. what crystal structure a stoichiometry will adopt, is critical to the prediction of materials synthesis, reactivity and properties. In this paper, we demonstrate that density functional theory, with the recently developed strongly constrained and appropriately normed (SCAN) functional, has advanced to a point where both facets of the stability problem can be reliably and efficiently predicted for mainmore » group compounds, while transition metal compounds are improved but remain a challenge. SCAN therefore offers a robust model for a significant portion of the periodic table, presenting an opportunity for the development of novel materials and the study of fine phase transformations even in largely unexplored systems with little to no experimental data.« less

Efficient first-principles prediction of solid stability: Towards chemical accuracy

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

Zhang, Yubo; Kitchaev, Daniil A.; Yang, Julia

The question of material stability is of fundamental importance to any analysis of system properties in condensed matter physics and materials science. The ability to evaluate chemical stability, i.e., whether a stoichiometry will persist in some chemical environment, and structure selection, i.e. what crystal structure a stoichiometry will adopt, is critical to the prediction of materials synthesis, reactivity and properties. In this paper, we demonstrate that density functional theory, with the recently developed strongly constrained and appropriately normed (SCAN) functional, has advanced to a point where both facets of the stability problem can be reliably and efficiently predicted for mainmore » group compounds, while transition metal compounds are improved but remain a challenge. SCAN therefore offers a robust model for a significant portion of the periodic table, presenting an opportunity for the development of novel materials and the study of fine phase transformations even in largely unexplored systems with little to no experimental data.« less

Predicting the Macroscopic Fracture Energy of Epoxy Resins from Atomistic Molecular Simulations

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

Meng, Zhaoxu; Bessa, Miguel A.; Xia, Wenjie

Predicting the macroscopic fracture energy of highly crosslinked glassy polymers from atomistic simulations is challenging due to the size of the process zone being large in these systems. Here, we present a scale-bridging approach that links atomistic molecular dynamics simulations to macroscopic fracture properties on the basis of a continuum fracture mechanics model for two different epoxy materials. Our approach reveals that the fracture energy of epoxy resins strongly depends on the functionality of epoxy resin and the component ratio between the curing agent (amine) and epoxide. The most intriguing part of our study is that we demonstrate that themore » fracture energy exhibits a maximum value within the range of conversion degrees considered (from 65% to 95%), which can be attributed to the combined effects of structural rigidity and post-yield deformability. Our study provides physical insight into the molecular mechanisms that govern the fracture characteristics of epoxy resins and demonstrates the success of utilizing atomistic molecular simulations towards predicting macroscopic material properties.« less

Modelling Behaviour of a Carbon Epoxy Composite Exposed to Fire: Part II-Comparison with Experimental Results.

PubMed

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

2017-04-28

Based on a phenomenological methodology, a three dimensional (3D) thermochemical model was developed to predict the temperature profile, the mass loss and the decomposition front of a carbon-reinforced epoxy composite laminate (T700/M21 composite) exposed to fire conditions. This 3D model takes into account the energy accumulation by the solid material, the anisotropic heat conduction, the thermal decomposition of the material, the gas mass flow into the composite, and the internal pressure. Thermophysical properties defined as temperature dependant properties were characterised using existing as well as innovative methodologies in order to use them as inputs into our physical model. The 3D thermochemical model accurately predicts the measured mass loss and observed decomposition front when the carbon fibre/epoxy composite is directly impacted by a propane flame. In short, the model shows its capability to predict the fire behaviour of a carbon fibre reinforced composite for fire safety engineering.

A method of site quality evaluation for red alder.

Treesearch

Constance A. Harrington

1986-01-01

A field guide to predict site index for red alder (Alnus rubra Bong.) was developed for use in western Washington and Oregon. The guide requires the user to evaluate 14 soil-site properties that are grouped into three general factors: (1) geographic and topographic position, (2) soil moisture and aeration during the growing season, and (3) soil fertility and physical...

Chain hexagonal cacti with the extremal eccentric distance sum.

PubMed

Qu, Hui; Yu, Guihai

2014-01-01

Eccentric distance sum (EDS), which can predict biological and physical properties, is a topological index based on the eccentricity of a graph. In this paper we characterize the chain hexagonal cactus with the minimal and the maximal eccentric distance sum among all chain hexagonal cacti of length n, respectively. Moreover, we present exact formulas for EDS of two types of hexagonal cacti.

Periodic Table of the Elements in the Perspective of Artificial Neural Networks

ERIC Educational Resources Information Center

Lemes, Mauricio R.; Dal Pino, Arnaldo

2011-01-01

Although several chemical elements were not known by end of the 19th century, Mendeleev came up with an astonishing achievement, the periodic table of elements. He was not only able to predict the existence of (then) new elements, but also to provide accurate estimates of their chemical and physical properties. This is a profound example of the…

Predictive model to describe water migration in cellular solid foods during storage.

PubMed

Voogt, Juliën A; Hirte, Anita; Meinders, Marcel B J

2011-11-01

Water migration in cellular solid foods during storage causes loss of crispness. To improve crispness retention, physical understanding of this process is needed. Mathematical models are suitable tools to gain this physical knowledge. Water migration in cellular solid foods involves migration through both the air cells and the solid matrix. For systems in which the water migration distance is large compared with the cell wall thickness of the solid matrix, the overall water flux through the system is dominated by the flux through the air. For these systems, water migration can be approximated well by a Fickian diffusion model. The effective diffusion coefficient can be expressed in terms of the material properties of the solid matrix (i.e. the density, sorption isotherm and diffusion coefficient of water in the solid matrix) and the morphological properties of the cellular structure (i.e. water vapour permeability and volume fraction of the solid matrix). The water vapour permeability is estimated from finite element method modelling using a simplified model for the cellular structure. It is shown that experimentally observed dynamical water profiles of bread rolls that differ in crust permeability are predicted well by the Fickian diffusion model. Copyright © 2011 Society of Chemical Industry.

JDFTx: Software for joint density-functional theory

DOE PAGES

Sundararaman, Ravishankar; Letchworth-Weaver, Kendra; Schwarz, Kathleen A.; ...

2017-11-14

Density-functional theory (DFT) has revolutionized computational prediction of atomic-scale properties from first principles in physics, chemistry and materials science. Continuing development of new methods is necessary for accurate predictions of new classes of materials and properties, and for connecting to nano- and mesoscale properties using coarse-grained theories. JDFTx is a fully-featured open-source electronic DFT software designed specifically to facilitate rapid development of new theories, models and algorithms. Using an algebraic formulation as an abstraction layer, compact C++11 code automatically performs well on diverse hardware including GPUs (Graphics Processing Units). This code hosts the development of joint density-functional theory (JDFT) thatmore » combines electronic DFT with classical DFT and continuum models of liquids for first-principles calculations of solvated and electrochemical systems. In addition, the modular nature of the code makes it easy to extend and interface with, facilitating the development of multi-scale toolkits that connect to ab initio calculations, e.g. photo-excited carrier dynamics combining electron and phonon calculations with electromagnetic simulations.« less

JDFTx: Software for joint density-functional theory

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

Sundararaman, Ravishankar; Letchworth-Weaver, Kendra; Schwarz, Kathleen A.

Density-functional theory (DFT) has revolutionized computational prediction of atomic-scale properties from first principles in physics, chemistry and materials science. Continuing development of new methods is necessary for accurate predictions of new classes of materials and properties, and for connecting to nano- and mesoscale properties using coarse-grained theories. JDFTx is a fully-featured open-source electronic DFT software designed specifically to facilitate rapid development of new theories, models and algorithms. Using an algebraic formulation as an abstraction layer, compact C++11 code automatically performs well on diverse hardware including GPUs (Graphics Processing Units). This code hosts the development of joint density-functional theory (JDFT) thatmore » combines electronic DFT with classical DFT and continuum models of liquids for first-principles calculations of solvated and electrochemical systems. In addition, the modular nature of the code makes it easy to extend and interface with, facilitating the development of multi-scale toolkits that connect to ab initio calculations, e.g. photo-excited carrier dynamics combining electron and phonon calculations with electromagnetic simulations.« less

Ablation and Thermal Response Property Model Validation for Phenolic Impregnated Carbon Ablator

NASA Technical Reports Server (NTRS)

Milos, F. S.; Chen, Y.-K.

2009-01-01

Phenolic Impregnated Carbon Ablator was the heatshield material for the Stardust probe and is also a candidate heatshield material for the Orion Crew Module. As part of the heatshield qualification for Orion, physical and thermal properties were measured for newly manufactured material, included emissivity, heat capacity, thermal conductivity, elemental composition, and thermal decomposition rates. Based on these properties, an ablation and thermal-response model was developed for temperatures up to 3500 K and pressures up to 100 kPa. The model includes orthotropic and pressure-dependent thermal conductivity. In this work, model validation is accomplished by comparison of predictions with data from many arcjet tests conducted over a range of stagnation heat flux and pressure from 107 Watts per square centimeter at 2.3 kPa to 1100 Watts per square centimeter at 84 kPa. Over the entire range of test conditions, model predictions compare well with measured recession, maximum surface temperatures, and in depth temperatures.

Inferring physical properties of galaxies from their emission-line spectra

NASA Astrophysics Data System (ADS)

Ucci, G.; Ferrara, A.; Gallerani, S.; Pallottini, A.

2017-02-01

We present a new approach based on Supervised Machine Learning algorithms to infer key physical properties of galaxies (density, metallicity, column density and ionization parameter) from their emission-line spectra. We introduce a numerical code (called GAME, GAlaxy Machine learning for Emission lines) implementing this method and test it extensively. GAME delivers excellent predictive performances, especially for estimates of metallicity and column densities. We compare GAME with the most widely used diagnostics (e.g. R23, [N II] λ6584/Hα indicators) showing that it provides much better accuracy and wider applicability range. GAME is particularly suitable for use in combination with Integral Field Unit spectroscopy, both for rest-frame optical/UV nebular lines and far-infrared/sub-millimeter lines arising from photodissociation regions. Finally, GAME can also be applied to the analysis of synthetic galaxy maps built from numerical simulations.

Modeling the Impact of Baryons on Subhalo Populations with Machine Learning

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

Nadler, Ethan O.; Mao, Yao -Yuan; Wechsler, Risa H.

Here, we identify subhalos in dark matter–only (DMO) zoom-in simulations that are likely to be disrupted due to baryonic effects by using a random forest classifier trained on two hydrodynamic simulations of Milky Way (MW)–mass host halos from the Latte suite of the Feedback in Realistic Environments (FIRE) project. We train our classifier using five properties of each disrupted and surviving subhalo: pericentric distance and scale factor at first pericentric passage after accretion and scale factor, virial mass, and maximum circular velocity at accretion. Our five-property classifier identifies disrupted subhalos in the FIRE simulations with an 85% out-of-bag classification score.more » We predict surviving subhalo populations in DMO simulations of the FIRE host halos, finding excellent agreement with the hydrodynamic results; in particular, our classifier outperforms DMO zoom-in simulations that include the gravitational potential of the central galactic disk in each hydrodynamic simulation, indicating that it captures both the dynamical effects of a central disk and additional baryonic physics. We also predict surviving subhalo populations for a suite of DMO zoom-in simulations of MW-mass host halos, finding that baryons impact each system consistently and that the predicted amount of subhalo disruption is larger than the host-to-host scatter among the subhalo populations. Although the small size and specific baryonic physics prescription of our training set limits the generality of our results, our work suggests that machine-learning classification algorithms trained on hydrodynamic zoom-in simulations can efficiently predict realistic subhalo populations.« less

Modeling the Impact of Baryons on Subhalo Populations with Machine Learning

DOE PAGES

Nadler, Ethan O.; Mao, Yao -Yuan; Wechsler, Risa H.; ...

2018-06-01

Here, we identify subhalos in dark matter–only (DMO) zoom-in simulations that are likely to be disrupted due to baryonic effects by using a random forest classifier trained on two hydrodynamic simulations of Milky Way (MW)–mass host halos from the Latte suite of the Feedback in Realistic Environments (FIRE) project. We train our classifier using five properties of each disrupted and surviving subhalo: pericentric distance and scale factor at first pericentric passage after accretion and scale factor, virial mass, and maximum circular velocity at accretion. Our five-property classifier identifies disrupted subhalos in the FIRE simulations with an 85% out-of-bag classification score.more » We predict surviving subhalo populations in DMO simulations of the FIRE host halos, finding excellent agreement with the hydrodynamic results; in particular, our classifier outperforms DMO zoom-in simulations that include the gravitational potential of the central galactic disk in each hydrodynamic simulation, indicating that it captures both the dynamical effects of a central disk and additional baryonic physics. We also predict surviving subhalo populations for a suite of DMO zoom-in simulations of MW-mass host halos, finding that baryons impact each system consistently and that the predicted amount of subhalo disruption is larger than the host-to-host scatter among the subhalo populations. Although the small size and specific baryonic physics prescription of our training set limits the generality of our results, our work suggests that machine-learning classification algorithms trained on hydrodynamic zoom-in simulations can efficiently predict realistic subhalo populations.« less

Influence of physical and chemical properties of HTSXT-FTIR samples on the quality of prediction models developed to determine absolute concentrations of total proteins, carbohydrates and triglycerides: a preliminary study on the determination of their absolute concentrations in fresh microalgal biomass.

PubMed

Serrano León, Esteban; Coat, Rémy; Moutel, Benjamin; Pruvost, Jérémy; Legrand, Jack; Gonçalves, Olivier

2014-11-01

Absolute concentrations of total macromolecules (triglycerides, proteins and carbohydrates) in microorganisms can be rapidly measured by FTIR spectroscopy, but caution is needed to avoid non-specific experimental bias. Here, we assess the limits within which this approach can be used on model solutions of macromolecules of interest. We used the Bruker HTSXT-FTIR system. Our results show that the solid deposits obtained after the sampling procedure present physical and chemical properties that influence the quality of the absolute concentration prediction models (univariate and multivariate). The accuracy of the models was degraded by a factor of 2 or 3 outside the recommended concentration interval of 0.5-35 µg spot(-1). Change occurred notably in the sample hydrogen bond network, which could, however, be controlled using an internal probe (pseudohalide anion). We also demonstrate that for aqueous solutions, accurate prediction of total carbohydrate quantities (in glucose equivalent) could not be made unless a constant amount of protein was added to the model solution (BSA). The results of the prediction model for more complex solutions, here with two components: glucose and BSA, were very encouraging, suggesting that this FTIR approach could be used as a rapid quantification method for mixtures of molecules of interest, provided the limits of use of the HTSXT-FTIR method are precisely known and respected. This last finding opens the way to direct quantification of total molecules of interest in more complex matrices.

On the reliability of computed chaotic solutions of non-linear differential equations

NASA Astrophysics Data System (ADS)

Liao, Shijun

2009-08-01

A new concept, namely the critical predictable time Tc, is introduced to give a more precise description of computed chaotic solutions of non-linear differential equations: it is suggested that computed chaotic solutions are unreliable and doubtable when t > Tc. This provides us a strategy to detect reliable solution from a given computed result. In this way, the computational phenomena, such as computational chaos (CC), computational periodicity (CP) and computational prediction uncertainty, which are mainly based on long-term properties of computed time-series, can be completely avoided. Using this concept, the famous conclusion `accurate long-term prediction of chaos is impossible' should be replaced by a more precise conclusion that `accurate prediction of chaos beyond the critical predictable time Tc is impossible'. So, this concept also provides us a timescale to determine whether or not a particular time is long enough for a given non-linear dynamic system. Besides, the influence of data inaccuracy and various numerical schemes on the critical predictable time is investigated in details by using symbolic computation software as a tool. A reliable chaotic solution of Lorenz equation in a rather large interval 0 <= t < 1200 non-dimensional Lorenz time units is obtained for the first time. It is found that the precision of the initial condition and the computed data at each time step, which is mathematically necessary to get such a reliable chaotic solution in such a long time, is so high that it is physically impossible due to the Heisenberg uncertainty principle in quantum physics. This, however, provides us a so-called `precision paradox of chaos', which suggests that the prediction uncertainty of chaos is physically unavoidable, and that even the macroscopical phenomena might be essentially stochastic and thus could be described by probability more economically.

Role of differential physical properties in the collective mechanics and dynamics of tissues

NASA Astrophysics Data System (ADS)

Das, Moumita

Living cells and tissues are highly mechanically sensitive and active. Mechanical stimuli influence the shape, motility, and functions of cells, modulate the behavior of tissues, and play a key role in several diseases. In this talk I will discuss how collective biophysical properties of tissues emerge from the interplay between differential mechanical properties and statistical physics of underlying components, focusing on two complementary tissue types whose properties are primarily determined by (1) the extracellular matrix (ECM), and (2) individual and collective cell properties. I will start with the structure-mechanics-function relationships in articular cartilage (AC), a soft tissue that has very few cells, and its mechanical response is primarily due to its ECM. AC is a remarkable tissue: it can support loads exceeding ten times our body weight and bear 60+ years of daily mechanical loading despite having minimal regenerative capacity. I will discuss the biophysical principles underlying this exceptional mechanical response using the framework of rigidity percolation theory, and compare our predictions with experiments done by our collaborators. Next I will discuss ongoing theoretical work on how the differences in cell mechanics, motility, adhesion, and proliferation in a co-culture of breast cancer cells and healthy breast epithelial cells may modulate experimentally observed differential migration and segregation. Our results may provide insights into the mechanobiology of tissues with cell populations with different physical properties present together such as during the formation of embryos or the initiation of tumors. This work was partially supported by a Cottrell College Science Award.

Characterizing ceramics and the interfacial adhesion to resin: I - The relationship of microstructure, composition, properties and fractography.

PubMed

Della Bona, Alvaro

2005-03-01

The appeal of ceramics as structural dental materials is based on their light weight, high hardness values, chemical inertness, and anticipated unique tribological characteristics. A major goal of current ceramic research and development is to produce tough, strong ceramics that can provide reliable performance in dental applications. Quantifying microstructural parameters is important to develop structure/property relationships. Quantitative microstructural analysis provides an association among the constitution, physical properties, and structural characteristics of materials. Structural reliability of dental ceramics is a major factor in the clinical success of ceramic restorations. Complex stress distributions are present in most practical conditions and strength data alone cannot be directly extrapolated to predict structural performance.

Status Report - Cane Fiberboard Properties And Degradation Rates For Storage Of The 9975 Shipping Package In KAC

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

Daugherty, W.

Thermal, mechanical and physical properties have been measured on cane fiberboard samples following accelerated aging for up to approximately 10 years. The aging environments have included elevated temperature < 250 ºF (the maximum allowed service temperature for fiberboard in 9975 packages) and elevated humidity. The results from this testing have been analyzed, and aging models fit to the data. Correlations relating several properties (thermal conductivity, energy absorption, weight, dimensions and density) to their rate of change in potential storage environments have been developed. Combined with an estimate of the actual conditions the fiberboard experiences in KAC, these models allow developmentmore » of service life predictions.« less

Hunting Solomonoff's Swans: Exploring the Boundary Between Physics and Statistics in Hydrological Modeling

NASA Astrophysics Data System (ADS)

Nearing, G. S.

2014-12-01

Statistical models consistently out-perform conceptual models in the short term, however to account for a nonstationary future (or an unobserved past) scientists prefer to base predictions on unchanging and commutable properties of the universe - i.e., physics. The problem with physically-based hydrology models is, of course, that they aren't really based on physics - they are based on statistical approximations of physical interactions, and we almost uniformly lack an understanding of the entropy associated with these approximations. Thermodynamics is successful precisely because entropy statistics are computable for homogeneous (well-mixed) systems, and ergodic arguments explain the success of Newton's laws to describe systems that are fundamentally quantum in nature. Unfortunately, similar arguments do not hold for systems like watersheds that are heterogeneous at a wide range of scales. Ray Solomonoff formalized the situation in 1968 by showing that given infinite evidence, simultaneously minimizing model complexity and entropy in predictions always leads to the best possible model. The open question in hydrology is about what happens when we don't have infinite evidence - for example, when the future will not look like the past, or when one watershed does not behave like another. How do we isolate stationary and commutable components of watershed behavior? I propose that one possible answer to this dilemma lies in a formal combination of physics and statistics. In this talk I outline my recent analogue (Solomonoff's theorem was digital) of Solomonoff's idea that allows us to quantify the complexity/entropy tradeoff in a way that is intuitive to physical scientists. I show how to formally combine "physical" and statistical methods for model development in a way that allows us to derive the theoretically best possible model given any given physics approximation(s) and available observations. Finally, I apply an analogue of Solomonoff's theorem to evaluate the tradeoff between model complexity and prediction power.

The diverse density profiles of galaxy clusters with self-interacting dark matter plus baryons

NASA Astrophysics Data System (ADS)

Robertson, Andrew; Massey, Richard; Eke, Vincent; Tulin, Sean; Yu, Hai-Bo; Bahé, Yannick; Barnes, David J.; Bower, Richard G.; Crain, Robert A.; Dalla Vecchia, Claudio; Kay, Scott T.; Schaller, Matthieu; Schaye, Joop

2018-05-01

We present the first simulated galaxy clusters (M200 > 1014 M⊙) with both self-interacting dark matter (SIDM) and baryonic physics. They exhibit a greater diversity in both dark matter and stellar density profiles than their counterparts in simulations with collisionless dark matter (CDM), which is generated by the complex interplay between dark matter self-interactions and baryonic physics. Despite variations in formation history, we demonstrate that analytical Jeans modelling predicts the SIDM density profiles remarkably well, and the diverse properties of the haloes can be understood in terms of their different final baryon distributions.

Faraday wave lattice as an elastic metamaterial.

PubMed

Domino, L; Tarpin, M; Patinet, S; Eddi, A

2016-05-01

Metamaterials enable the emergence of novel physical properties due to the existence of an underlying subwavelength structure. Here, we use the Faraday instability to shape the fluid-air interface with a regular pattern. This pattern undergoes an oscillating secondary instability and exhibits spontaneous vibrations that are analogous to transverse elastic waves. By locally forcing these waves, we fully characterize their dispersion relation and show that a Faraday pattern presents an effective shear elasticity. We propose a physical mechanism combining surface tension with the Faraday structured interface that quantitatively predicts the elastic wave phase speed, revealing that the liquid interface behaves as an elastic metamaterial.

Bringing life to soil physical processes

NASA Astrophysics Data System (ADS)

Hallett, P. D.

2013-12-01

When Oklahoma's native prairie grass roots were replaced by corn, the greatest environmental (and social) disaster ever to hit America ensued. The soils lost structure, physical binding by roots was annihilated and when drought came the Great Dust Bowl commenced. This form of environmental disaster has repeated over history and although not always apparent, similar processes drive the degradation of seemingly productive farmland and forests. But just as negative impacts on biology are deleterious to soil physical properties, positive impacts could reverse these trends. In finding solutions to soil sustainability and food security, we should be able to exploit biological processes to improve soil physical properties. This talk will focus on a quantitative understanding of how biology changes soil physical behaviour. Like the Great Dust Bowl, it starts with reinforcement mechanisms by plant roots. We found that binding of soil by cereal (barley) roots within 5 weeks of planting can more than double soil shear strength, with greater plant density causing greater reinforcement. With time, however, the relative impact of root reinforcement diminishes due to root turnover and aging of the seedbed. From mechanical tests of individual roots, reasonable predictions of reinforcement by tree roots are possible with fibre bundle models. With herbaceous plants like cereals, however, the same parameters (root strength, stiffness, size and distribution) result in a poor prediction. We found that root type, root age and abiotic factors such as compaction and waterlogging affect mechanical behaviour, further complicating the understanding and prediction of root reinforcement. For soil physical stability, the interface between root and soil is an extremely important zone in terms of resistance of roots to pull-out and rhizosphere formation. Compounds analogous to root exudates have been found with rheological tests to initially decrease the shear stress where wet soils flow, but after decomposition of these exudates by microbes the shear stress increases. This suggests an initial dispersion, followed by aggregation of the soil, which explains the structural arrangement of soil particles in the rhizosphere observed by microscopy. Dispersion of soil minerals in the root zone is important to release bound nutrients from mineral surfaces. Using fracture mechanics we measured large impacts of biological exudates on the toughness and interparticle bond energy of soils. Now novel tests are being developed to quantify interparticle bonding by biological exudates on single and multiple particle contacts, including mechanical test specimens that can be inoculated with specific bacteria or fungi. This will allow for clay mineralogy, water potential and solution chemistry impacts on interparticle bonding to be quantified directly. Wettability experiments with the same samples measure hydrological properties such as contact angle. Basic information from these tests will help explain biological processes that drive soil structure formation and stabilisation, providing data for models of soil structure dynamics.

Physical properties and rock physics models of sediment containing natural and laboratory-formed methane gas hydrate

USGS Publications Warehouse

Winters, W.J.; Pecher, I.A.; Waite, W.F.; Mason, D.H.

2004-01-01

This paper presents results of shear strength and acoustic velocity (p-wave) measurements performed on: (1) samples containing natural gas hydrate from the Mallik 2L-38 well, Mackenzie Delta, Northwest Territories; (2) reconstituted Ottawa sand samples containing methane gas hydrate formed in the laboratory; and (3) ice-bearing sands. These measurements show that hydrate increases shear strength and p-wave velocity in natural and reconstituted samples. The proportion of this increase depends on (1) the amount and distribution of hydrate present, (2) differences, in sediment properties, and (3) differences in test conditions. Stress-strain curves from the Mallik samples suggest that natural gas hydrate does not cement sediment grains. However, stress-strain curves from the Ottawa sand (containing laboratory-formed gas hydrate) do imply cementation is present. Acoustically, rock physics modeling shows that gas hydrate does not cement grains of natural Mackenzie Delta sediment. Natural gas hydrates are best modeled as part of the sediment frame. This finding is in contrast with direct observations and results of Ottawa sand containing laboratory-formed hydrate, which was found to cement grains (Waite et al. 2004). It therefore appears that the microscopic distribution of gas hydrates in sediment, and hence the effect of gas hydrate on sediment physical properties, differs between natural deposits and laboratory-formed samples. This difference may possibly be caused by the location of water molecules that are available to form hydrate. Models that use laboratory-derived properties to predict behavior of natural gas hydrate must account for these differences.

Machine-learning-assisted materials discovery using failed experiments

NASA Astrophysics Data System (ADS)

Raccuglia, Paul; Elbert, Katherine C.; Adler, Philip D. F.; Falk, Casey; Wenny, Malia B.; Mollo, Aurelio; Zeller, Matthias; Friedler, Sorelle A.; Schrier, Joshua; Norquist, Alexander J.

2016-05-01

Inorganic-organic hybrid materials such as organically templated metal oxides, metal-organic frameworks (MOFs) and organohalide perovskites have been studied for decades, and hydrothermal and (non-aqueous) solvothermal syntheses have produced thousands of new materials that collectively contain nearly all the metals in the periodic table. Nevertheless, the formation of these compounds is not fully understood, and development of new compounds relies primarily on exploratory syntheses. Simulation- and data-driven approaches (promoted by efforts such as the Materials Genome Initiative) provide an alternative to experimental trial-and-error. Three major strategies are: simulation-based predictions of physical properties (for example, charge mobility, photovoltaic properties, gas adsorption capacity or lithium-ion intercalation) to identify promising target candidates for synthetic efforts; determination of the structure-property relationship from large bodies of experimental data, enabled by integration with high-throughput synthesis and measurement tools; and clustering on the basis of similar crystallographic structure (for example, zeolite structure classification or gas adsorption properties). Here we demonstrate an alternative approach that uses machine-learning algorithms trained on reaction data to predict reaction outcomes for the crystallization of templated vanadium selenites. We used information on ‘dark’ reactions—failed or unsuccessful hydrothermal syntheses—collected from archived laboratory notebooks from our laboratory, and added physicochemical property descriptions to the raw notebook information using cheminformatics techniques. We used the resulting data to train a machine-learning model to predict reaction success. When carrying out hydrothermal synthesis experiments using previously untested, commercially available organic building blocks, our machine-learning model outperformed traditional human strategies, and successfully predicted conditions for new organically templated inorganic product formation with a success rate of 89 per cent. Inverting the machine-learning model reveals new hypotheses regarding the conditions for successful product formation.

Resolving structural influences on water-retention properties of alluvial deposits

USGS Publications Warehouse

Winfield, K.A.; Nimmo, J.R.; Izbicki, J.A.; Martin, P.M.

2006-01-01

With the goal of improving property-transfer model (PTM) predictions of unsaturated hydraulic properties, we investigated the influence of sedimentary structure, defined as particle arrangement during deposition, on laboratory-measured water retention (water content vs. potential [??(??)]) of 10 undisturbed core samples from alluvial deposits in the western Mojave Desert, California. The samples were classified as having fluvial or debris-flow structure based on observed stratification and measured spread of particle-size distribution. The ??(??) data were fit with the Rossi-Nimmo junction model, representing water retention with three parameters: the maximum water content (??max), the ??-scaling parameter (??o), and the shape parameter (??). We examined trends between these hydraulic parameters and bulk physical properties, both textural - geometric mean, Mg, and geometric standard deviation, ??g, of particle diameter - and structural - bulk density, ??b, the fraction of unfilled pore space at natural saturation, Ae, and porosity-based randomness index, ??s, defined as the excess of total porosity over 0.3. Structural parameters ??s and Ae were greater for fluvial samples, indicating greater structural pore space and a possibly broader pore-size distribution associated with a more systematic arrangement of particles. Multiple linear regression analysis and Mallow's Cp statistic identified combinations of textural and structural parameters for the most useful predictive models: for ??max, including Ae, ??s, and ??g, and for both ??o and ??, including only textural parameters, although use of Ae can somewhat improve ??o predictions. Textural properties can explain most of the sample-to-sample variation in ??(??) independent of deposit type, but inclusion of the simple structural indicators Ae and ??s can improve PTM predictions, especially for the wettest part of the ??(??) curve. ?? Soil Science Society of America.

Feasibility Analysis of Incorporating In-Vitro Toxicokinetic Data ...

EPA Pesticide Factsheets

The underlying principle of read-across is that biological activity is a function of physical and structural properties of chemicals. Analogs are typically identified on the basis of structural similarity and subsequently evaluated for their use in read-across on the basis of their bioavailability, reactivity and metabolic similarity. While the concept of similarity is the major tenet in grouping chemicals for read-across, a critical consideration is to evaluate if structural differences significantly impact toxicological activity. This is a key source of uncertainty in read-across predictions. We hypothesize that inclusion of toxicokinetic (TK) information will reduce the uncertainty in read-across predictions. TK information can help substantiate whether chemicals within a category have similar ADME properties and, hence, increase the likelihood of exhibiting similar toxicological properties. This current case study is part of a larger study aimed at performing a systematic assessment of the extent to which in-vitro TK data can obviate in-vivo TK data, while maintaining or increasing scientific confidence in read-across predictions. The analysis relied on a dataset of ~7k chemicals with predicted exposure data (chemical inventory), of which 819 chemicals had rat and/or human in-vitro TK data (analog inventory), and 33 chemicals had rat in-vivo TK data (target inventory). The set of chemicals with human in vitro TK data was investigated to determine whether str

MnNiO3 revisited with modern theoretical and experimental methods

NASA Astrophysics Data System (ADS)

Dzubak, Allison L.; Mitra, Chandrima; Chance, Michael; Kuhn, Stephen; Jellison, Gerald E.; Sefat, Athena S.; Krogel, Jaron T.; Reboredo, Fernando A.

2017-11-01

MnNiO3 is a strongly correlated transition metal oxide that has recently been investigated theoretically for its potential application as an oxygen-evolution photocatalyst. However, there is no experimental report on critical quantities such as the band gap or bulk modulus. Recent theoretical predictions with standard functionals such as LDA+U and HSE show large discrepancies in the band gaps (about 1.23 eV), depending on the nature of the functional used. Hence there is clearly a need for an accurate quantitative prediction of the band gap to gauge its utility as a photocatalyst. In this work, we present a diffusion quantum Monte Carlo study of the bulk properties of MnNiO3 and revisit the synthesis and experimental properties of the compound. We predict quasiparticle band gaps of 2.0(5) eV and 3.8(6) eV for the majority and minority spin channels, respectively, and an equilibrium volume of 92.8 Å3, which compares well to the experimental value of 94.4 Å3. A bulk modulus of 217 GPa is predicted for MnNiO3. We rationalize the difficulty for the formation of ordered ilmenite-type structure with specific sites for Ni and Mn to be potentially due to the formation of antisite defects that form during synthesis, which ultimately affects the physical properties of MnNiO3.

The Coastal Ocean Prediction Systems program: Understanding and managing our coastal ocean

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

Eden, H.F.; Mooers, C.N.K.

1990-06-01

The goal of COPS is to couple a program of regular observations to numerical models, through techniques of data assimilation, in order to provide a predictive capability for the US coastal ocean including the Great Lakes, estuaries, and the entire Exclusive Economic Zone (EEZ). The objectives of the program include: determining the predictability of the coastal ocean and the processes that govern the predictability; developing efficient prediction systems for the coastal ocean based on the assimilation of real-time observations into numerical models; and coupling the predictive systems for the physical behavior of the coastal ocean to predictive systems for biological,more » chemical, and geological processes to achieve an interdisciplinary capability. COPS will provide the basis for effective monitoring and prediction of coastal ocean conditions by optimizing the use of increased scientific understanding, improved observations, advanced computer models, and computer graphics to make the best possible estimates of sea level, currents, temperatures, salinities, and other properties of entire coastal regions.« less

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

Livescu, Veronica; Bronkhorst, Curt Allan; Vander Wiel, Scott Alan

Many challenges exist with regard to understanding and representing complex physical processes involved with ductile damage and failure in polycrystalline metallic materials. Currently, the ability to accurately predict the macroscale ductile damage and failure response of metallic materials is lacking. Research at Los Alamos National Laboratory (LANL) is aimed at building a coupled experimental and computational methodology that supports the development of predictive damage capabilities by: capturing real distributions of microstructural features from real material and implementing them as digitally generated microstructures in damage model development; and, distilling structure-property information to link microstructural details to damage evolution under a multitudemore » of loading states.« less

Intrinsic Raman spectroscopy for quantitative biological spectroscopy Part II

PubMed Central

Bechtel, Kate L.; Shih, Wei-Chuan; Feld, Michael S.

2009-01-01

We demonstrate the effectiveness of intrinsic Raman spectroscopy (IRS) at reducing errors caused by absorption and scattering. Physical tissue models, solutions of varying absorption and scattering coefficients with known concentrations of Raman scatterers, are studied. We show significant improvement in prediction error by implementing IRS to predict concentrations of Raman scatterers using both ordinary least squares regression (OLS) and partial least squares regression (PLS). In particular, we show that IRS provides a robust calibration model that does not increase in error when applied to samples with optical properties outside the range of calibration. PMID:18711512

Modeling of robotic fish propelled by an ionic polymer-metal composite caudal fin

NASA Astrophysics Data System (ADS)

Chen, Zheng; Shatara, Stephan; Tan, Xiaobo

2009-03-01

In this paper, a model is proposed for a biomimetic robotic fish propelled by an ionic polymer metal composite (IPMC) actuator with a rigid passive fin at the end. The model incorporates both IPMC actuation dynamics and the hydrodynamics, and predicts the steady-state speed of the robot under a periodic actuation voltage. Experimental results have shown that the proposed model can predict the fish motion for different tail dimensions. Since its parameters are expressed in terms of physical properties and geometric dimensions, the model is expected to be instrumental in optimal design of the robotic fish.

Measurement requirements and techniques for degradation studies and lifetime prediction testing of photovoltaic modules

NASA Technical Reports Server (NTRS)

Noel, G. T.; Sliemers, F. A.; Derringer, G. C.; Wood, V. E.; Wilkes, K. E.; Gaines, G. B.; Carmichael, D. C.

1978-01-01

Tests of weathering and aging behavior are being developed to characterize the degradation and predict the lifetimes of low-cost photovoltaic arrays. Environmental factors which affect array performance include UV radiation, thermal energy, water, oxygen (generally involved in synergistic effects with UV radiation or high temperatures), physical stress, pollutants (oxides of nitrogen, sulfur dioxide and ozone), abrasives and dirt. A survey of photovoltaic array testing has shown the need to establish quantitative correlations between certain measurable properties (carbonyl formation, glass transition temperature, and molecular weight change) and modes of degradation and failure.

Regional Assessment of Storm-triggered Shall Landslide Risks using the SLIDE (SLope-Infiltration-Distributed Equilibrium) Model

NASA Astrophysics Data System (ADS)

Hong, Y.; Kirschbaum, D. B.; Fukuoka, H.

2011-12-01

The key to advancing the predictability of rainfall-triggered landslides is to use physically based slope-stability models that simulate the dynamical response of the subsurface moisture to spatiotemporal variability of rainfall in complex terrains. An early warning system applying such physical models has been developed to predict rainfall-induced shallow landslides over Java Island in Indonesia and Honduras. The prototyped early warning system integrates three major components: (1) a susceptibility mapping or hotspot identification component based on a land surface geospatial database (topographical information, maps of soil properties, and local landslide inventory etc.); (2) a satellite-based precipitation monitoring system (http://trmm.gsfc.nasa.gov) and a precipitation forecasting model (i.e. Weather Research Forecast); and (3) a physically-based, rainfall-induced landslide prediction model SLIDE (SLope-Infiltration-Distributed Equilibrium). The system utilizes the modified physical model to calculate a Factor of Safety (FS) that accounts for the contribution of rainfall infiltration and partial saturation to the shear strength of the soil in topographically complex terrains. The system's prediction performance has been evaluated using a local landslide inventory. In Java Island, Indonesia, evaluation of SLIDE modeling results by local news reports shows that the system successfully predicted landslides in correspondence to the time of occurrence of the real landslide events. Further study of SLIDE is implemented in Honduras where Hurricane Mitch triggered widespread landslides in 1998. Results shows within the approximately 1,200 square kilometers study areas, the values of hit rates reached as high as 78% and 75%, while the error indices were 35% and 49%. Despite positive model performance, the SLIDE model is limited in the early warning system by several assumptions including, using general parameter calibration rather than in situ tests and neglecting geologic information. Advantages and limitations of this model will be discussed with respect to future applications of landslide assessment and prediction over large scales. In conclusion, integration of spatially distributed remote sensing precipitation products and in-situ datasets and physical models in this prototype system enable us to further develop a regional early warning tool in the future for forecasting storm-induced landslides.

Atomic Oxygen Erosion Yield Prediction for Spacecraft Polymers in Low Earth Orbit

NASA Technical Reports Server (NTRS)

Banks, Bruce A.; Backus, Jane A.; Manno, Michael V.; Waters, Deborah L.; Cameron, Kevin C.; deGroh, Kim K.

2009-01-01

The ability to predict the atomic oxygen erosion yield of polymers based on their chemistry and physical properties has been only partially successful because of a lack of reliable low Earth orbit (LEO) erosion yield data. Unfortunately, many of the early experiments did not utilize dehydrated mass loss measurements for erosion yield determination, and the resulting mass loss due to atomic oxygen exposure may have been compromised because samples were often not in consistent states of dehydration during the pre-flight and post-flight mass measurements. This is a particular problem for short duration mission exposures or low erosion yield materials. However, as a result of the retrieval of the Polymer Erosion and Contamination Experiment (PEACE) flown as part of the Materials International Space Station Experiment 2 (MISSE 2), the erosion yields of 38 polymers and pyrolytic graphite were accurately measured. The experiment was exposed to the LEO environment for 3.95 years from August 16, 2001 to July 30, 2005 and was successfully retrieved during a space walk on July 30, 2005 during Discovery s STS-114 Return to Flight mission. The 40 different materials tested (including Kapton H fluence witness samples) were selected specifically to represent a variety of polymers used in space as well as a wide variety of polymer chemical structures. The MISSE 2 PEACE Polymers experiment used carefully dehydrated mass measurements, as well as accurate density measurements to obtain accurate erosion yield data for high-fluence (8.43 1021 atoms/sq cm). The resulting data was used to develop an erosion yield predictive tool with a correlation coefficient of 0.895 and uncertainty of +/-6.3 10(exp -25)cu cm/atom. The predictive tool utilizes the chemical structures and physical properties of polymers to predict in-space atomic oxygen erosion yields. A predictive tool concept (September 2009 version) is presented which represents an improvement over an earlier (December 2008) version.

Fingerprinting: Modelling and mapping physical top soil properties with the Mole

NASA Astrophysics Data System (ADS)

Loonstra, Eddie; van Egmond, Fenny

2010-05-01

The Mole is a passive gamma ray soil sensor system. It is designed for the mobile collection of radioactive energy stemming from soil. As the system is passive, it only measures energy that reaches the surface of soil. In general, this energy comes from upto 30 to 40 cm deep, which can be considered topsoil. The gathered energy spectra are logged every second, are processed with the method of Full Spectrum Analysis. This method uses all available spectral data and processes it with a Chi square optimalisation using a set of standard spectra into individual nuclide point data. A standard spectrum is the measured full spectrum of a specific detector derived when exposed to 1 Bq/kg of a nuclide. With this method the outcome of the surveys become quantitative.The outcome of a field survey with the Mole results in a data file containing point information of position, Total Counts and the decay products of 232Th, 238U, 40K and 137Cs. Five elements are therefor available for the modelling of soil properties. There are several ways for the modelling of soil properties with sensor derived gamma ray data. The Mole generates ratio scale output. For modelling a quantitative deterministic approach is used based on sample locations. This process is called fingerprinting. Fingerprinting is a comparison of the concentration of the radioactive trace elements and the lab results (pH, clay content, etc.) by regression analysis. This results in a mathematical formula describing the relationship between a dependent and independent property. The results of the sensor readings are interpolated into a nuclide map with GIS software. With the derived formula a soil property map is composed. The principle of fingerprinting can be applied on large geographical areas for physical soil properties such as clay, loam or sand (50 micron), grain size and organic matter. Collected sample data of previous field surveys within the same region can be used for the prediction of soil properties elsewhere when adding a relatively small number of new calibration samples. For this purpose stratification of data is necessary. All radioactive trace elements play a part in the fingerprinting process for the mapping of physical soil properties. Clay content is best predicted with 232Th. It has a general R2 of 0.75 up to 0,9. The correlation is positive and basically linear. The variation of loam (or sand) content is very well described by 232Th or the combination of 232Th and 238U. It has a comparable R2 to clay. Grain size can be well modelled with 40K, probably due to the fact that this nuclide is positively correlated with matter. 40K is therefor negatively correlated to grain size. The R2 is good: 0,7 to 0,8 on average. The combination of 40K and 137Cs is generally applied for modelling organic matter content with a quality comparable with that of grain size models. Finally, Total Counts turns out to be a very useful parameter for the identification of different types of parent material and of unnatural or non-parent material. Passive gamma ray soil sensors as the Mole are very suitable for high resolution mapping of physical soil properties. The FSA method has the advantage that data from previous surveys becomes applicable in the fingerprinting procedure of new fields. Being able to model the physical soil properties with gamma ray sensors opens the possibility to run pedotransfer function models for a particular survey.

Machine learning for the structure–energy–property landscapes of molecular crystals† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c7sc04665k

PubMed Central

Yang, Jack; Campbell, Joshua E.; Day, Graeme M.; Ceriotti, Michele

2017-01-01

Molecular crystals play an important role in several fields of science and technology. They frequently crystallize in different polymorphs with substantially different physical properties. To help guide the synthesis of candidate materials, atomic-scale modelling can be used to enumerate the stable polymorphs and to predict their properties, as well as to propose heuristic rules to rationalize the correlations between crystal structure and materials properties. Here we show how a recently-developed machine-learning (ML) framework can be used to achieve inexpensive and accurate predictions of the stability and properties of polymorphs, and a data-driven classification that is less biased and more flexible than typical heuristic rules. We discuss, as examples, the lattice energy and property landscapes of pentacene and two azapentacene isomers that are of interest as organic semiconductor materials. We show that we can estimate force field or DFT lattice energies with sub-kJ mol–1 accuracy, using only a few hundred reference configurations, and reduce by a factor of ten the computational effort needed to predict charge mobility in the crystal structures. The automatic structural classification of the polymorphs reveals a more detailed picture of molecular packing than that provided by conventional heuristics, and helps disentangle the role of hydrogen bonded and π-stacking interactions in determining molecular self-assembly. This observation demonstrates that ML is not just a black-box scheme to interpolate between reference calculations, but can also be used as a tool to gain intuitive insights into structure–property relations in molecular crystal engineering. PMID:29675175

Workshop summary: Physical properties of gas hydrate-bearing sediment

USGS Publications Warehouse

Waite, William F.; Santamarina, J.C.

2008-01-01

A wide range of particle and pore scale phenomena, often coupled, determines the macro-scale response of gas-hydrate bearing sediment to changes in mechanical, thermal, or chemical conditions. Predicting this macro-scale response is critical for applications such as optimizing the production of methane from gas-hydrate deposits, or determining the role of gas hydrates in global carbon cycling and climate change.

a Study of Ultrasonic Wave Propagation Through Parallel Arrays of Immersed Tubes

NASA Astrophysics Data System (ADS)

Cocker, R. P.; Challis, R. E.

1996-06-01

Tubular array structures are a very common component in industrial heat exchanging plant and the non-destructive testing of these arrays is essential. Acoustic methods using microphones or ultrasound are attractive but require a thorough understanding of the acoustic properties of tube arrays. This paper details the development and testing of a small-scale physical model of a tube array to verify the predictions of a theoretical model for acoustic propagation through tube arrays developed by Heckl, Mulholland, and Huang [1-5] as a basis for the consideration of small-scale physical models in the development of non-destructive testing procedures for tube arrays. Their model predicts transmission spectra for plane waves incident on an array of tubes arranged in straight rows. Relative transmission is frequency dependent with bands of high and low attenuation caused by resonances within individual tubes and between tubes in the array. As the number of rows in the array increases the relative transmission spectrum becomes more complex, with increasingly well-defined bands of high and low attenuation. Diffraction of acoustic waves with wavelengths less than the tube spacing is predicted and appears as step reductions in the transmission spectrum at frequencies corresponding to integer multiples of the tube spacing. Experiments with the physical model confirm the principle features of the theoretical treatment.

Thermo-mechanical assessment of full SiC/SiC composite cladding for LWR applications with sensitivity analysis

NASA Astrophysics Data System (ADS)

Singh, Gyanender; Terrani, Kurt; Katoh, Yutai

2018-02-01

SiC/SiC composites are considered among leading candidates for accident tolerant fuel cladding in light water reactors. However, when SiC-based materials are exposed to neutron irradiation, they experience significant changes in dimensions and physical properties. Under a large heat flux application (i.e. fuel cladding), the non-uniform changes in the dimensions and physical properties will lead to build-up of stresses in the structure over the course of time. To ensure reliable and safe operation of such a structure it is important to assess its thermo-mechanical performance under in-reactor conditions of irradiation and elevated temperature. In this work, the foundation for 3D thermo-mechanical analysis of SiC/SiC cladding is put in place and a set of analyses with simplified boundary conditions has been performed. The analyses were carried out with two different codes that were benchmarked against one another and prior results in the literature. A constitutive model is constructed and solved numerically to predict the stress distribution and variation in the cladding under normal operating conditions. The dependence of dimensions and physical properties variation with irradiation and temperature has been incorporated. These robust models may now be modified to take into account the axial and circumferential variation in neutron and heat flux to fully account for 3D effects. The results from the simple analyses show the development of high tensile stresses especially in the circumferential and axial directions at the inner region of the cladding. Based on the results obtained, design guidelines are recommended. For lack of certainty in or tailor-ability for the physical and mechanical properties of SiC/SiC composite material a sensitivity analysis is conducted. The analysis results establish a precedence order of the properties based on the extent to which these properties influence the temperature and the stresses.

High-fidelity plasma codes for burn physics

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

Cooley, James; Graziani, Frank; Marinak, Marty

Accurate predictions of equation of state (EOS), ionic and electronic transport properties are of critical importance for high-energy-density plasma science. Transport coefficients inform radiation-hydrodynamic codes and impact diagnostic interpretation, which in turn impacts our understanding of the development of instabilities, the overall energy balance of burning plasmas, and the efficacy of self-heating from charged-particle stopping. Important processes include thermal and electrical conduction, electron-ion coupling, inter-diffusion, ion viscosity, and charged particle stopping. However, uncertainties in these coefficients are not well established. Fundamental plasma science codes, also called high-fidelity plasma codes, are a relatively recent computational tool that augments both experimental datamore » and theoretical foundations of transport coefficients. This paper addresses the current status of HFPC codes and their future development, and the potential impact they play in improving the predictive capability of the multi-physics hydrodynamic codes used in HED design.« less

Many-Body Descriptors for Predicting Molecular Properties with Machine Learning: Analysis of Pairwise and Three-Body Interactions in Molecules.

PubMed

Pronobis, Wiktor; Tkatchenko, Alexandre; Müller, Klaus-Robert

2018-06-12

Machine learning (ML) based prediction of molecular properties across chemical compound space is an important and alternative approach to efficiently estimate the solutions of highly complex many-electron problems in chemistry and physics. Statistical methods represent molecules as descriptors that should encode molecular symmetries and interactions between atoms. Many such descriptors have been proposed; all of them have advantages and limitations. Here, we propose a set of general two-body and three-body interaction descriptors which are invariant to translation, rotation, and atomic indexing. By adapting the successfully used kernel ridge regression methods of machine learning, we evaluate our descriptors on predicting several properties of small organic molecules calculated using density-functional theory. We use two data sets. The GDB-7 set contains 6868 molecules with up to 7 heavy atoms of type CNO. The GDB-9 set is composed of 131722 molecules with up to 9 heavy atoms containing CNO. When trained on 5000 random molecules, our best model achieves an accuracy of 0.8 kcal/mol (on the remaining 1868 molecules of GDB-7) and 1.5 kcal/mol (on the remaining 126722 molecules of GDB-9) respectively. Applying a linear regression model on our novel many-body descriptors performs almost equal to a nonlinear kernelized model. Linear models are readily interpretable: a feature importance ranking measure helps to obtain qualitative and quantitative insights on the importance of two- and three-body molecular interactions for predicting molecular properties computed with quantum-mechanical methods.

Assimilating Merged Remote Sensing and Ground based Snowpack Information for Runoff Simulation and Forecasting using Hydrological Models

NASA Astrophysics Data System (ADS)

Infante Corona, J. A.; Lakhankar, T.; Khanbilvardi, R.; Pradhanang, S. M.

2013-12-01

Stream flow estimation and flood prediction influenced by snow melting processes have been studied for the past couple of decades because of their destruction potential, money losses and demises. It has been observed that snow, that was very stationary during its seasons, now is variable in shorter time-scales (daily and hourly) and rapid snowmelt can contribute or been the cause of floods. Therefore, good estimates of snowpack properties on ground are necessary in order to have an accurate prediction of these destructive events. The snow thermal model (SNTHERM) is a 1-dimensional model that analyzes the snowpack properties given the climatological conditions of a particular area. Gridded data from both, in-situ meteorological observations and remote sensing data will be produced using interpolation methods; thus, snow water equivalent (SWE) and snowmelt estimations can be obtained. The soil and water assessment tool (SWAT) is a hydrological model capable of predicting runoff quantity and quality of a watershed given its main physical and hydrological properties. The results from SNTHERM will be used as an input for SWAT in order to have simulated runoff under snowmelt conditions. This project attempts to improve the river discharge estimation considering both, excess rainfall runoff and the snow melting process. Obtaining a better estimation of the snowpack properties and evolution is expected. A coupled use of SNTHERM and SWAT based on meteorological in situ and remote sensed data will improve the temporal and spatial resolution of the snowpack characterization and river discharge estimations, and thus flood prediction.

Dissolution assessment of allopurinol immediate release tablets by near infrared spectroscopy.

PubMed

Smetiško, Jelena; Miljanić, Snežana

2017-10-25

The purpose of this study was to develop a NIR spectroscopic method for assessment of drug dissolution from allopurinol immediate release tablets. Thirty three different batches of allopurinol immediate release tablets containing constant amount of the active ingredient, but varying in excipients content and physical properties were introduced in a PLS calibration model. Correlating allopurinol dissolution reference values measured by the routinely used UV/Vis method, with the data extracted from the NIR spectra, values of correlation coefficient, bias, slope, residual prediction determination and root mean square error of prediction (0.9632, 0.328%, 1.001, 3.58, 3.75%) were evaluated. The obtained values implied that the NIR diffuse reflectance spectroscopy could serve as a faster and simpler alternative to the conventional dissolution procedure, even for the tablets with a very fast dissolution rate (>85% in 15minutes). Apart from the possibility of prediction of the allopurinol dissolution rate, the other multivariate technique, PCA, provided additional data on the non-chemical characteristics of the product, which could not be obtained from the reference dissolution values. Analysis on an independent set of samples confirmed that a difference between the UV/Vis reference method and the proposed NIR method was not significant. According to the presented results, the proposed NIR method may be suitable for practical application in routine analysis and for continuously monitoring the product's chemical and physical properties responsible for expected quality. Copyright © 2017 Elsevier B.V. All rights reserved.

Intuitive, but not simple: including explicit water molecules in protein-protein docking simulations improves model quality.

PubMed

Parikh, Hardik I; Kellogg, Glen E

2014-06-01

Characterizing the nature of interaction between proteins that have not been experimentally cocrystallized requires a computational docking approach that can successfully predict the spatial conformation adopted in the complex. In this work, the Hydropathic INTeractions (HINT) force field model was used for scoring docked models in a data set of 30 high-resolution crystallographically characterized "dry" protein-protein complexes and was shown to reliably identify native-like models. However, most current protein-protein docking algorithms fail to explicitly account for water molecules involved in bridging interactions that mediate and stabilize the association of the protein partners, so we used HINT to illuminate the physical and chemical properties of bridging waters and account for their energetic stabilizing contributions. The HINT water Relevance metric identified the "truly" bridging waters at the 30 protein-protein interfaces and we utilized them in "solvated" docking by manually inserting them into the input files for the rigid body ZDOCK program. By accounting for these interfacial waters, a statistically significant improvement of ∼24% in the average hit-count within the top-10 predictions the protein-protein dataset was seen, compared to standard "dry" docking. The results also show scoring improvement, with medium and high accuracy models ranking much better than incorrect ones. These improvements can be attributed to the physical presence of water molecules that alter surface properties and better represent native shape and hydropathic complementarity between interacting partners, with concomitantly more accurate native-like structure predictions. © 2013 Wiley Periodicals, Inc.

Assessment of brittleness and empirical correlations between physical and mechanical parameters of the Asmari limestone in Khersan 2 dam site, in southwest of Iran

NASA Astrophysics Data System (ADS)

Lashkaripour, Gholam Reza; Rastegarnia, Ahmad; Ghafoori, Mohammad

2018-02-01

The determination of brittleness and geomechanical parameters, especially uniaxial compressive strength (UCS) and Young's modulus (ES) of rocks are needed for the design of different rock engineering applications. Evaluation of these parameters are time-consuming processes, tedious, expensive and require well-prepared rock cores. Therefore, compressional wave velocity (Vp) and index parameters such as point load index and porosity are often used to predict the properties of rocks. In this paper, brittleness and other properties, physical and mechanical in type, of 56 Asmari limestones in dry and saturated conditions were analyzed. The rock samples were collected from Khersan 2 dam site. This dam with the height of 240 m is being constructed and located in the Zagros Mountain, in the southwest of Iran. The bedrock and abutments of the dam site consist of Asemari and Gachsaran Formations. In this paper, a practical relation for predicting brittleness and some relations between mechanical and index parameters of the Asmari limestone were established. The presented equation for predicting brittleness based on UCS, Brazilian tensile strength and Vp had high accuracy. Moreover, results showed that the brittleness estimation based on B3 concept (the ratio of multiply compressive strength in tensile strength divided 2) had more accuracy as compared to the B2 (the ratio of compressive strength minus tensile strength to compressive strength plus tensile strength) and B1 (the ratio of compressive strength to tensile strength) concepts.

Gaussian process model for extrapolation of scattering observables for complex molecules: From benzene to benzonitrile

NASA Astrophysics Data System (ADS)

Cui, Jie; Li, Zhiying; Krems, Roman V.

2015-10-01

We consider a problem of extrapolating the collision properties of a large polyatomic molecule A-H to make predictions of the dynamical properties for another molecule related to A-H by the substitution of the H atom with a small molecular group X, without explicitly computing the potential energy surface for A-X. We assume that the effect of the -H →-X substitution is embodied in a multidimensional function with unknown parameters characterizing the change of the potential energy surface. We propose to apply the Gaussian Process model to determine the dependence of the dynamical observables on the unknown parameters. This can be used to produce an interval of the observable values which corresponds to physical variations of the potential parameters. We show that the Gaussian Process model combined with classical trajectory calculations can be used to obtain the dependence of the cross sections for collisions of C6H5CN with He on the unknown parameters describing the interaction of the He atom with the CN fragment of the molecule. The unknown parameters are then varied within physically reasonable ranges to produce a prediction uncertainty of the cross sections. The results are normalized to the cross sections for He — C6H6 collisions obtained from quantum scattering calculations in order to provide a prediction interval of the thermally averaged cross sections for collisions of C6H5CN with He.

An Investigation into the Use of Manufactured Sand as a 100% Replacement for Fine Aggregate in Concrete.

PubMed

Pilegis, Martins; Gardner, Diane; Lark, Robert

2016-06-02

Manufactured sand differs from natural sea and river dredged sand in its physical and mineralogical properties. These can be both beneficial and detrimental to the fresh and hardened properties of concrete. This paper presents the results of a laboratory study in which manufactured sand produced in an industry sized crushing plant was characterised with respect to its physical and mineralogical properties. The influence of these characteristics on concrete workability and strength, when manufactured sand completely replaced natural sand in concrete, was investigated and modelled using artificial neural networks (ANN). The results show that the manufactured sand concrete made in this study generally requires a higher water/cement (w/c) ratio for workability equal to that of natural sand concrete due to the higher angularity of the manufactured sand particles. Water reducing admixtures can be used to compensate for this if the manufactured sand does not contain clay particles. At the same w/c ratio, the compressive and flexural strength of manufactured sand concrete exceeds that of natural sand concrete. ANN proved a valuable and reliable method of predicting concrete strength and workability based on the properties of the fine aggregate (FA) and the concrete mix composition.

An Investigation into the Use of Manufactured Sand as a 100% Replacement for Fine Aggregate in Concrete

PubMed Central

Pilegis, Martins; Gardner, Diane; Lark, Robert

2016-01-01

Manufactured sand differs from natural sea and river dredged sand in its physical and mineralogical properties. These can be both beneficial and detrimental to the fresh and hardened properties of concrete. This paper presents the results of a laboratory study in which manufactured sand produced in an industry sized crushing plant was characterised with respect to its physical and mineralogical properties. The influence of these characteristics on concrete workability and strength, when manufactured sand completely replaced natural sand in concrete, was investigated and modelled using artificial neural networks (ANN). The results show that the manufactured sand concrete made in this study generally requires a higher water/cement (w/c) ratio for workability equal to that of natural sand concrete due to the higher angularity of the manufactured sand particles. Water reducing admixtures can be used to compensate for this if the manufactured sand does not contain clay particles. At the same w/c ratio, the compressive and flexural strength of manufactured sand concrete exceeds that of natural sand concrete. ANN proved a valuable and reliable method of predicting concrete strength and workability based on the properties of the fine aggregate (FA) and the concrete mix composition. PMID:28773560

Modeling of feed-forward control using the partial least squares regression method in the tablet compression process.

PubMed

Hattori, Yusuke; Otsuka, Makoto

2017-05-30

In the pharmaceutical industry, the implementation of continuous manufacturing has been widely promoted in lieu of the traditional batch manufacturing approach. More specially, in recent years, the innovative concept of feed-forward control has been introduced in relation to process analytical technology. In the present study, we successfully developed a feed-forward control model for the tablet compression process by integrating data obtained from near-infrared (NIR) spectra and the physical properties of granules. In the pharmaceutical industry, batch manufacturing routinely allows for the preparation of granules with the desired properties through the manual control of process parameters. On the other hand, continuous manufacturing demands the automatic determination of these process parameters. Here, we proposed the development of a control model using the partial least squares regression (PLSR) method. The most significant feature of this method is the use of dataset integrating both the NIR spectra and the physical properties of the granules. Using our model, we determined that the properties of products, such as tablet weight and thickness, need to be included as independent variables in the PLSR analysis in order to predict unknown process parameters. Copyright © 2017 Elsevier B.V. All rights reserved.

Physical biology of human brain development.

PubMed

Budday, Silvia; Steinmann, Paul; Kuhl, Ellen

2015-01-01

Neurodevelopment is a complex, dynamic process that involves a precisely orchestrated sequence of genetic, environmental, biochemical, and physical events. Developmental biology and genetics have shaped our understanding of the molecular and cellular mechanisms during neurodevelopment. Recent studies suggest that physical forces play a central role in translating these cellular mechanisms into the complex surface morphology of the human brain. However, the precise impact of neuronal differentiation, migration, and connection on the physical forces during cortical folding remains unknown. Here we review the cellular mechanisms of neurodevelopment with a view toward surface morphogenesis, pattern selection, and evolution of shape. We revisit cortical folding as the instability problem of constrained differential growth in a multi-layered system. To identify the contributing factors of differential growth, we map out the timeline of neurodevelopment in humans and highlight the cellular events associated with extreme radial and tangential expansion. We demonstrate how computational modeling of differential growth can bridge the scales-from phenomena on the cellular level toward form and function on the organ level-to make quantitative, personalized predictions. Physics-based models can quantify cortical stresses, identify critical folding conditions, rationalize pattern selection, and predict gyral wavelengths and gyrification indices. We illustrate that physical forces can explain cortical malformations as emergent properties of developmental disorders. Combining biology and physics holds promise to advance our understanding of human brain development and enable early diagnostics of cortical malformations with the ultimate goal to improve treatment of neurodevelopmental disorders including epilepsy, autism spectrum disorders, and schizophrenia.

Highly Improved Predictability in the Forecasting of the East Asian Summer Monsoon

NASA Astrophysics Data System (ADS)

Lee, E.; Chase, T. N.; Rajagopalan, B.

2007-12-01

The East Asian summer monsoon greatly influences the lives and property of about a quarter of all the people in the world. However, the predictability of the monsoon is very low in comparison with that of Indian summer monsoon because of the complexity of the system which involves both tropical and sub-tropical climates. Previous monsoon prediction models emphasized ocean factors as the primary monsoon forcing. Here we show that pre-season land surface cover is at least as important as ocean indices. A new statistical forecast model of the East Asian summer monsoon using land cover conditions in addition to ocean heat sources doubles the predictability relative to a model using ocean factors alone. This work highlights the, as yet, undocumented importance of seasonal land cover in monsoon prediction and the role of the biosphere in the climate system as a whole. We also detail the physical mechanisms involved in these land surface forcings.

A hierarchical spatial model for well yield in complex aquifers

NASA Astrophysics Data System (ADS)

Montgomery, J.; O'sullivan, F.

2017-12-01

Efficiently siting and managing groundwater wells requires reliable estimates of the amount of water that can be produced, or the well yield. This can be challenging to predict in highly complex, heterogeneous fractured aquifers due to the uncertainty around local hydraulic properties. Promising statistical approaches have been advanced in recent years. For instance, kriging and multivariate regression analysis have been applied to well test data with limited but encouraging levels of prediction accuracy. Additionally, some analytical solutions to diffusion in homogeneous porous media have been used to infer "effective" properties consistent with observed flow rates or drawdown. However, this is an under-specified inverse problem with substantial and irreducible uncertainty. We describe a flexible machine learning approach capable of combining diverse datasets with constraining physical and geostatistical models for improved well yield prediction accuracy and uncertainty quantification. Our approach can be implemented within a hierarchical Bayesian framework using Markov Chain Monte Carlo, which allows for additional sources of information to be incorporated in priors to further constrain and improve predictions and reduce the model order. We demonstrate the usefulness of this approach using data from over 7,000 wells in a fractured bedrock aquifer.

Molecular modeling of the microstructure evolution during carbon fiber processing

NASA Astrophysics Data System (ADS)

Desai, Saaketh; Li, Chunyu; Shen, Tongtong; Strachan, Alejandro

2017-12-01

The rational design of carbon fibers with desired properties requires quantitative relationships between the processing conditions, microstructure, and resulting properties. We developed a molecular model that combines kinetic Monte Carlo and molecular dynamics techniques to predict the microstructure evolution during the processes of carbonization and graphitization of polyacrylonitrile (PAN)-based carbon fibers. The model accurately predicts the cross-sectional microstructure of the fibers with the molecular structure of the stabilized PAN fibers and physics-based chemical reaction rates as the only inputs. The resulting structures exhibit key features observed in electron microcopy studies such as curved graphitic sheets and hairpin structures. In addition, computed X-ray diffraction patterns are in good agreement with experiments. We predict the transverse moduli of the resulting fibers between 1 GPa and 5 GPa, in good agreement with experimental results for high modulus fibers and slightly lower than those of high-strength fibers. The transverse modulus is governed by sliding between graphitic sheets, and the relatively low value for the predicted microstructures can be attributed to their perfect longitudinal texture. Finally, the simulations provide insight into the relationships between chemical kinetics and the final microstructure; we observe that high reaction rates result in porous structures with lower moduli.

A discrete element method-based approach to predict the breakage of coal

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

Gupta, Varun; Sun, Xin; Xu, Wei

Pulverization is an essential pre-combustion technique employed for solid fuels, such as coal, to reduce particle sizes. Smaller particles ensure rapid and complete combustion, leading to low carbon emissions. Traditionally, the resulting particle size distributions from pulverizers have been informed by empirical or semi-empirical approaches that rely on extensive data gathered over several decades during operations or experiments. However, the predictive capabilities for new coals and processes are limited. This work presents a Discrete Element Method based computational framework to predict particle size distribution resulting from the breakage of coal particles characterized by the coal’s physical properties. The effect ofmore » certain operating parameters on the breakage behavior of coal particles also is examined.« less

Preschool physics: Using the invisible property of weight in causal reasoning tasks

PubMed Central

Williamson, Rebecca A.; Meltzoff, Andrew N.

2018-01-01

Causal reasoning is an important aspect of scientific thinking. Even young human children can use causal reasoning to explain observations, make predictions, and design actions to bring about specific outcomes in the physical world. Weight is an interesting type of cause because it is an invisible property. Here, we tested preschool children with causal problem-solving tasks that assessed their understanding of weight. In an experimental setting, 2- to 5-year-old children completed three different tasks in which they had to use weight to produce physical effects—an object displacement task, a balance-scale task, and a tower-building task. The results showed that the children’s understanding of how to use object weight to produce specific object-to-object causal outcomes improved as a function of age, with 4- and 5-year-olds showing above-chance performance on all three tasks. The younger children’s performance was more variable. The pattern of results provides theoretical insights into which aspects of weight processing are particularly difficult for preschool children and why they find it difficult. PMID:29561840

Temperature and composition profile during double-track laser cladding of H13 tool steel

NASA Astrophysics Data System (ADS)

He, X.; Yu, G.; Mazumder, J.

2010-01-01

Multi-track laser cladding is now applied commercially in a range of industries such as automotive, mining and aerospace due to its diversified potential for material processing. The knowledge of temperature, velocity and composition distribution history is essential for a better understanding of the process and subsequent microstructure evolution and properties. Numerical simulation not only helps to understand the complex physical phenomena and underlying principles involved in this process, but it can also be used in the process prediction and system control. The double-track coaxial laser cladding with H13 tool steel powder injection is simulated using a comprehensive three-dimensional model, based on the mass, momentum, energy conservation and solute transport equation. Some important physical phenomena, such as heat transfer, phase changes, mass addition and fluid flow, are taken into account in the calculation. The physical properties for a mixture of solid and liquid phase are defined by treating it as a continuum media. The velocity of the laser beam during the transition between two tracks is considered. The evolution of temperature and composition of different monitoring locations is simulated.

Preschool physics: Using the invisible property of weight in causal reasoning tasks.

PubMed

Wang, Zhidan; Williamson, Rebecca A; Meltzoff, Andrew N

2018-01-01

Causal reasoning is an important aspect of scientific thinking. Even young human children can use causal reasoning to explain observations, make predictions, and design actions to bring about specific outcomes in the physical world. Weight is an interesting type of cause because it is an invisible property. Here, we tested preschool children with causal problem-solving tasks that assessed their understanding of weight. In an experimental setting, 2- to 5-year-old children completed three different tasks in which they had to use weight to produce physical effects-an object displacement task, a balance-scale task, and a tower-building task. The results showed that the children's understanding of how to use object weight to produce specific object-to-object causal outcomes improved as a function of age, with 4- and 5-year-olds showing above-chance performance on all three tasks. The younger children's performance was more variable. The pattern of results provides theoretical insights into which aspects of weight processing are particularly difficult for preschool children and why they find it difficult.

Adaptive method for electron bunch profile prediction

DOE PAGES

Scheinker, Alexander; Gessner, Spencer

2015-10-15

We report on an experiment performed at the Facility for Advanced Accelerator Experimental Tests (FACET) at SLAC National Accelerator Laboratory, in which a new adaptive control algorithm, one with known, bounded update rates, despite operating on analytically unknown cost functions, was utilized in order to provide quasi-real-time bunch property estimates of the electron beam. Multiple parameters, such as arbitrary rf phase settings and other time-varying accelerator properties, were simultaneously tuned in order to match a simulated bunch energy spectrum with a measured energy spectrum. Thus, the simple adaptive scheme was digitally implemented using matlab and the experimental physics and industrialmore » control system. Finally, the main result is a nonintrusive, nondestructive, real-time diagnostic scheme for prediction of bunch profiles, as well as other beam parameters, the precise control of which are important for the plasma wakefield acceleration experiments being explored at FACET.« less

Assessing Anxiety in Youth with the Multidimensional Anxiety Scale for Children (MASC)

PubMed Central

Wei, Chiaying; Hoff, Alexandra; Villabø, Marianne A.; Peterman, Jeremy; Kendall, Philip C.; Piacentini, John; McCracken, James; Walkup, John T.; Albano, Anne Marie; Rynn, Moira; Sherrill, Joel; Sakolsky, Dara; Birmaher, Boris; Ginsburg, Golda; Keaton, Courtney; Gosch, Elizabeth; Compton, Scott N.; March, John

2013-01-01

The present study examined the psychometric properties, including discriminant validity and clinical utility, of the youth self-report and parent-report forms of the Multidimensional Anxiety Scale for Children (MASC) among youth with anxiety disorders. The sample included parents and youth (N= 488, 49.6% male) ages 7 – 17 who participated in the Child/Adolescent Anxiety Multimodal Study (CAMS). Although the typical low agreement between parent and youth self-reports was found, the MASC evidenced good internal reliability across MASC subscales and informants. The main MASC subscales (i.e., Physical Symptoms, Harm Avoidance, Social Anxiety, and Separation/Panic) were examined. The Social Anxiety and Separation/Panic subscales were found to be significantly predictive of the presence and severity of social phobia and separation anxiety disorder, respectively. Using multiple informants improved the accuracy of prediction. The MASC subscales demonstrated good psychometric properties and clinical utilities in identifying youth with anxiety disorders. PMID:23845036

Topological properties of a self-assembled electrical network via ab initio calculation

NASA Astrophysics Data System (ADS)

Stephenson, C.; Lyon, D.; Hübler, A.

2017-02-01

Interacting electrical conductors self-assemble to form tree like networks in the presence of applied voltages or currents. Experiments have shown that the degree distribution of the steady state networks are identical over a wide range of network sizes. In this work we develop a new model of the self-assembly process starting from the underlying physical interaction between conductors. In agreement with experimental results we find that for steady state networks, our model predicts that the fraction of endpoints is a constant of 0.252, and the fraction of branch points is 0.237. We find that our model predicts that these scaling properties also hold for the network during the approach to the steady state as well. In addition, we also reproduce the experimental distribution of nodes with a given Strahler number for all steady state networks studied.

Non-Porod scattering and non-integer scaling of resistance in rough films

NASA Astrophysics Data System (ADS)

Bupathy, Arunkumar; Verma, Rupesh; Banerjee, Varsha; Puri, Sanjay

2017-04-01

In many physical systems, films are rough due to the stochastic behavior of depositing particles. They are characterized by non-Porod power law decays in the structure factor S (k) . Theoretical studies predict anomalous diffusion in such morphologies, with important implications for diffusivity, conductivity, etc. We use the non-Porod decay to accurately determine the fractal properties of two prototypical nanoparticle films: (i) Palladium (Pd) and (ii) Cu2O. Using scaling arguments, we find that the resistance of rough films of lateral size L obeys a non-integer power law R ∼L-ζ , in contrast to integer power laws for compact structures. The exponent ζ is anisotropic. We confirm our predictions by re-analyzing experimental data from Cu2O nano-particle films. Our results are valuable for understanding recent experiments that report anisotropic electrical properties in (rough) thin films.

Coronal Magnetism and Forward Solarsoft Idl Package

NASA Astrophysics Data System (ADS)

Gibson, S. E.

2014-12-01

The FORWARD suite of Solar Soft IDL codes is a community resource for model-data comparison, with a particular emphasis on analyzing coronal magnetic fields. FORWARD may be used both to synthesize a broad range of coronal observables, and to access and compare to existing data. FORWARD works with numerical model datacubes, interfaces with the web-served Predictive Science Inc MAS simulation datacubes and the Solar Soft IDL Potential Field Source Surface (PFSS) package, and also includes several analytic models (more can be added). It connects to the Virtual Solar Observatory and other web-served observations to download data in a format directly comparable to model predictions. It utilizes the CHIANTI database in modeling UV/EUV lines, and links to the CLE polarimetry synthesis code for forbidden coronal lines. FORWARD enables "forward-fitting" of specific observations, and helps to build intuition into how the physical properties of coronal magnetic structures translate to observable properties.

A model for large amplitude oscillations of coated bubbles accounting for buckling and rupture

NASA Astrophysics Data System (ADS)

Marmottant, Philippe; van der Meer, Sander; Emmer, Marcia; Versluis, Michel; de Jong, Nico; Hilgenfeldt, Sascha; Lohse, Detlef

2005-12-01

We present a model applicable to ultrasound contrast agent bubbles that takes into account the physical properties of a lipid monolayer coating on a gas microbubble. Three parameters describe the properties of the shell: a buckling radius, the compressibility of the shell, and a break-up shell tension. The model presents an original non-linear behavior at large amplitude oscillations, termed compression-only, induced by the buckling of the lipid monolayer. This prediction is validated by experimental recordings with the high-speed camera Brandaris 128, operated at several millions of frames per second. The effect of aging, or the resultant of repeated acoustic pressure pulses on bubbles, is predicted by the model. It corrects a flaw in the shell elasticity term previously used in the dynamical equation for coated bubbles. The break-up is modeled by a critical shell tension above which gas is directly exposed to water.

Low temperature physical properties of Co-35Ni-20Cr-10Mo alloy MP35N®

NASA Astrophysics Data System (ADS)

Lu, J.; Toplosky, V. J.; Goddard, R. E.; Han, K.

2017-09-01

Multiphase Co-35Ni-20Cr-10Mo alloy MP35N® is a high strength alloy with excellent corrosion resistance. Its applications span chemical, medical, and food processing industries. Thanks to its high modulus and high strength, it found applications in reinforcement of ultra-high field pulsed magnets. Recently, it has also been considered for reinforcement in superconducting wires used in ultra-high field superconducting magnets. For these applications, accurate measurement of its physical properties at cryogenic temperatures is very important. In this paper, physical properties including electrical resistivity, specific heat, thermal conductivity, and magnetization of as-received and aged samples are measured from 2 to 300 K. The electrical resistivity of the aged sample is slightly higher than the as-received sample, both showing a weak linear temperature dependence in the entire range of 2-300 K. The measured specific heat Cp of 430 J/kg-K at 295 K agrees with a theoretical prediction, but is significantly smaller than the values in the literature. The thermal conductivity between 2 and 300 K is in good agreement with the literature which is only available above 77 K. Magnetic property of MP35N® changes significantly with aging. The as-received sample exhibits Curie paramagnetism with a Curie constant C = 0.175 K. While the aged sample contains small amounts of a ferromagnetic phase even at room temperature. The measured MP35N® properties will be useful for the engineering design of pulsed magnets and superconducting magnets using MP35N® as reinforcement.

Challenges for the Modern Science in its Descend Towards Nano Scale

PubMed Central

Uskoković, Vuk

2013-01-01

The current rise in the interest in physical phenomena at nano spatial scale is described hereby as a natural consequence of the scientific progress in manipulation with matter with an ever higher sensitivity. The reason behind arising of the entirely new field of nanoscience is that the properties of nanostructured materials may significantly differ from their bulk counterparts and cannot be predicted by extrapolations of the size-dependent properties displayed by materials composed of microsized particles. It is also argued that although a material can comprise critical boundaries at the nano scale, this does not mean that it will inevitably exhibit properties that endow a nanomaterial. This implies that the attribute of “nanomaterial” can be used only in relation with a given property of interest. The major challenges faced with the expansion of resolution of the materials design, in terms of hardly reproducible experiments, are further discussed. It is claimed that owing to an unavoidable interference between the experimental system and its environment to which the controlling system belongs, an increased fineness of the experimental settings will lead to ever more difficulties in rendering them reproducible and controllable. Self-assembly methods in which a part of the preprogrammed scientific design is substituted with letting physical systems spontaneously evolve into attractive and functional structures is mentioned as one of the ways to overcome the problems inherent in synthetic approaches at the ultrafine scale. The fact that physical systems partly owe their properties to the interaction with their environment implies that each self-assembly process can be considered a co-assembly event. PMID:26491428

Developing a predictive model for the chemical composition of soot nanoparticles

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

Violi, Angela; Michelsen, Hope; Hansen, Nils

In order to provide the scientific foundation to enable technology breakthroughs in transportation fuel, it is important to develop a combustion modeling capability to optimize the operation and design of evolving fuels in advanced engines for transportation applications. The goal of this proposal is to develop a validated predictive model to describe the chemical composition of soot nanoparticles in premixed and diffusion flames. Atomistic studies in conjunction with state-of-the-art experiments are the distinguishing characteristics of this unique interdisciplinary effort. The modeling effort has been conducted at the University of Michigan by Prof. A. Violi. The experimental work has entailed amore » series of studies using different techniques to analyze gas-phase soot precursor chemistry and soot particle production in premixed and diffusion flames. Measurements have provided spatial distributions of polycyclic aromatic hydrocarbons and other gas-phase species and size and composition of incipient soot nanoparticles for comparison with model results. The experimental team includes Dr. N. Hansen and H. Michelsen at Sandia National Labs' Combustion Research Facility, and Dr. K. Wilson as collaborator at Lawrence Berkeley National Lab's Advanced Light Source. Our results show that the chemical and physical properties of nanoparticles affect the coagulation behavior in soot formation, and our results on an experimentally validated, predictive model for the chemical composition of soot nanoparticles will not only enhance our understanding of soot formation since but will also allow the prediction of particle size distributions under combustion conditions. These results provide a novel description of soot formation based on physical and chemical properties of the particles for use in the next generation of soot models and an enhanced capability for facilitating the design of alternative fuels and the engines they will power.« less

Final Report, DOE Early Career Award: Predictive modeling of complex physical systems: new tools for statistical inference, uncertainty quantification, and experimental design

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

Marzouk, Youssef

Predictive simulation of complex physical systems increasingly rests on the interplay of experimental observations with computational models. Key inputs, parameters, or structural aspects of models may be incomplete or unknown, and must be developed from indirect and limited observations. At the same time, quantified uncertainties are needed to qualify computational predictions in the support of design and decision-making. In this context, Bayesian statistics provides a foundation for inference from noisy and limited data, but at prohibitive computional expense. This project intends to make rigorous predictive modeling *feasible* in complex physical systems, via accelerated and scalable tools for uncertainty quantification, Bayesianmore » inference, and experimental design. Specific objectives are as follows: 1. Develop adaptive posterior approximations and dimensionality reduction approaches for Bayesian inference in high-dimensional nonlinear systems. 2. Extend accelerated Bayesian methodologies to large-scale {\\em sequential} data assimilation, fully treating nonlinear models and non-Gaussian state and parameter distributions. 3. Devise efficient surrogate-based methods for Bayesian model selection and the learning of model structure. 4. Develop scalable simulation/optimization approaches to nonlinear Bayesian experimental design, for both parameter inference and model selection. 5. Demonstrate these inferential tools on chemical kinetic models in reacting flow, constructing and refining thermochemical and electrochemical models from limited data. Demonstrate Bayesian filtering on canonical stochastic PDEs and in the dynamic estimation of inhomogeneous subsurface properties and flow fields.« less

Assessing participation in community-based physical activity programs in Brazil.

PubMed

Reis, Rodrigo S; Yan, Yan; Parra, Diana C; Brownson, Ross C

2014-01-01

This study aimed to develop and validate a risk prediction model to examine the characteristics that are associated with participation in community-based physical activity programs in Brazil. We used pooled data from three surveys conducted from 2007 to 2009 in state capitals of Brazil with 6166 adults. A risk prediction model was built considering program participation as an outcome. The predictive accuracy of the model was quantified through discrimination (C statistic) and calibration (Brier score) properties. Bootstrapping methods were used to validate the predictive accuracy of the final model. The final model showed sex (women: odds ratio [OR] = 3.18, 95% confidence interval [CI] = 2.14-4.71), having less than high school degree (OR = 1.71, 95% CI = 1.16-2.53), reporting a good health (OR = 1.58, 95% CI = 1.02-2.24) or very good/excellent health (OR = 1.62, 95% CI = 1.05-2.51), having any comorbidity (OR = 1.74, 95% CI = 1.26-2.39), and perceiving the environment as safe to walk at night (OR = 1.59, 95% CI = 1.18-2.15) as predictors of participation in physical activity programs. Accuracy indices were adequate (C index = 0.778, Brier score = 0.031) and similar to those obtained from bootstrapping (C index = 0.792, Brier score = 0.030). Sociodemographic and health characteristics as well as perceptions of the environment are strong predictors of participation in community-based programs in selected cities of Brazil.

Modeling the mechanics of cancer: effect of changes in cellular and extra-cellular mechanical properties.

PubMed

Katira, Parag; Bonnecaze, Roger T; Zaman, Muhammad H

2013-01-01

Malignant transformation, though primarily driven by genetic mutations in cells, is also accompanied by specific changes in cellular and extra-cellular mechanical properties such as stiffness and adhesivity. As the transformed cells grow into tumors, they interact with their surroundings via physical contacts and the application of forces. These forces can lead to changes in the mechanical regulation of cell fate based on the mechanical properties of the cells and their surrounding environment. A comprehensive understanding of cancer progression requires the study of how specific changes in mechanical properties influences collective cell behavior during tumor growth and metastasis. Here we review some key results from computational models describing the effect of changes in cellular and extra-cellular mechanical properties and identify mechanistic pathways for cancer progression that can be targeted for the prediction, treatment, and prevention of cancer.

Fouling resistance prediction using artificial neural network nonlinear auto-regressive with exogenous input model based on operating conditions and fluid properties correlations

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

Biyanto, Totok R.

Fouling in a heat exchanger in Crude Preheat Train (CPT) refinery is an unsolved problem that reduces the plant efficiency, increases fuel consumption and CO{sub 2} emission. The fouling resistance behavior is very complex. It is difficult to develop a model using first principle equation to predict the fouling resistance due to different operating conditions and different crude blends. In this paper, Artificial Neural Networks (ANN) MultiLayer Perceptron (MLP) with input structure using Nonlinear Auto-Regressive with eXogenous (NARX) is utilized to build the fouling resistance model in shell and tube heat exchanger (STHX). The input data of the model aremore » flow rates and temperatures of the streams of the heat exchanger, physical properties of product and crude blend data. This model serves as a predicting tool to optimize operating conditions and preventive maintenance of STHX. The results show that the model can capture the complexity of fouling characteristics in heat exchanger due to thermodynamic conditions and variations in crude oil properties (blends). It was found that the Root Mean Square Error (RMSE) are suitable to capture the nonlinearity and complexity of the STHX fouling resistance during phases of training and validation.« less

Toward a Time-Domain Fractal Lightning Simulation

NASA Astrophysics Data System (ADS)

Liang, C.; Carlson, B. E.; Lehtinen, N. G.; Cohen, M.; Lauben, D.; Inan, U. S.

2010-12-01

Electromagnetic simulations of lightning are useful for prediction of lightning properties and exploration of the underlying physical behavior. Fractal lightning models predict the spatial structure of the discharge, but thus far do not provide much information about discharge behavior in time and therefore cannot predict electromagnetic wave emissions or current characteristics. Here we develop a time-domain fractal lightning simulation from Maxwell's equations, the method of moments with the thin wire approximation, an adaptive time-stepping scheme, and a simplified electrical model of the lightning channel. The model predicts current pulse structure and electromagnetic wave emissions and can be used to simulate the entire duration of a lightning discharge. The model can be used to explore the electrical characteristics of the lightning channel, the temporal development of the discharge, and the effects of these characteristics on observable electromagnetic wave emissions.

Experiment and simulation of the fabrication process of lithium-ion battery cathodes for determining microstructure and mechanical properties

NASA Astrophysics Data System (ADS)

Forouzan, Mehdi M.; Chao, Chien-Wei; Bustamante, Danilo; Mazzeo, Brian A.; Wheeler, Dean R.

2016-04-01

The fabrication process of Li-ion battery electrodes plays a prominent role in the microstructure and corresponding cell performance. Here, a mesoscale particle dynamics simulation is developed to relate the manufacturing process of a cathode containing Toda NCM-523 active material to physical and structural properties of the dried film. Particle interactions are simulated with shifted-force Lennard-Jones and granular Hertzian functions. LAMMPS, a freely available particle simulator, is used to generate particle trajectories and resulting predicted properties. To make simulations of the full film thickness feasible, the carbon binder domain (CBD) is approximated with μm-scale particles, each representing about 1000 carbon black particles and associated binder. Metrics for model parameterization and validation are measured experimentally and include the following: slurry viscosity, elasticity of the dried film, shrinkage ratio during drying, volume fraction of phases, slurry and dried film densities, and microstructure cross sections. Simulation results are in substantial agreement with experiment, showing that the simulations reasonably reproduce the relevant physics of particle arrangement during fabrication.

Finite Element Modeling of the NASA Langley Aluminum Testbed Cylinder

NASA Technical Reports Server (NTRS)

Grosveld, Ferdinand W.; Pritchard, Joselyn I.; Buehrle, Ralph D.; Pappa, Richard S.

2002-01-01

The NASA Langley Aluminum Testbed Cylinder (ATC) was designed to serve as a universal structure for evaluating structural acoustic codes, modeling techniques and optimization methods used in the prediction of aircraft interior noise. Finite element models were developed for the components of the ATC based on the geometric, structural and material properties of the physical test structure. Numerically predicted modal frequencies for the longitudinal stringer, ring frame and dome component models, and six assembled ATC configurations were compared with experimental modal survey data. The finite element models were updated and refined, using physical parameters, to increase correlation with the measured modal data. Excellent agreement, within an average 1.5% to 2.9%, was obtained between the predicted and measured modal frequencies of the stringer, frame and dome components. The predictions for the modal frequencies of the assembled component Configurations I through V were within an average 2.9% and 9.1%. Finite element modal analyses were performed for comparison with 3 psi and 6 psi internal pressurization conditions in Configuration VI. The modal frequencies were predicted by applying differential stiffness to the elements with pressure loading and creating reduced matrices for beam elements with offsets inside external superelements. The average disagreement between the measured and predicted differences for the 0 psi and 6 psi internal pressure conditions was less than 0.5%. Comparably good agreement was obtained for the differences between the 0 psi and 3 psi measured and predicted internal pressure conditions.

Predicting the Highly Nonlinear Mechanical Properties of Polymeric Materials

NASA Astrophysics Data System (ADS)

Porter, David

2009-06-01

Over the past few years, we have developed models that calculate the highly nonlinear mechanical properties of polymers as a function of temperature, strain and strain rate from their molecular and morphological structure. A review of these models is presented here, with emphasis on combining the fundamental aspects of molecular physics that dictate these properties and the pragmatic need to make realistic predictions for our customers; the designer of new materials and the engineers who use these materials. The models calculate the highly nonlinear mechanical properties of polymers as a function of temperature, strain and strain rate from their molecular structure. The model is based upon the premise that mechanical properties are a direct consequence of energy stored and energy dissipated during deformation of a material. This premise is transformed into a consistent set of structure-property relations for the equation of state, EoS, and the engineering constitutive relations in a polymer by quantifying energy storage and loss at the molecular level of interactions between characteristic groups of atoms in a polymer. These relations are derived from a simple volumetric mean field Lennard-Jones potential function for the potential energy of intermolecular interactions in a polymer. First, properties such as temperature-volume relations and glass transition temperature are calculated directly from the potential function. Then, the `shock' EoS is derived simply by differentiating the potential function with respect to volume, assuming that the molecules cannot relax in the time scales of the deformation. The energy components are then used to predict the dynamic mechanical spectrum of a polymer in terms of temperature and rate. This can be transformed directly into the highly nonlinear stress-strain relations through yield. The constitutive relations are formulated as a set of analytical equations that predict properties directly in terms of a small set of structural parameters that can be calculated directly and independently from the chemical composition and morphology of a polymer. A number of examples are given to illustrate the model and also to show that the method can be applied, with appropriate modifications, to other materials.

Structural similarity based kriging for quantitative structure activity and property relationship modeling.

PubMed

Teixeira, Ana L; Falcao, Andre O

2014-07-28

Structurally similar molecules tend to have similar properties, i.e. closer molecules in the molecular space are more likely to yield similar property values while distant molecules are more likely to yield different values. Based on this principle, we propose the use of a new method that takes into account the high dimensionality of the molecular space, predicting chemical, physical, or biological properties based on the most similar compounds with measured properties. This methodology uses ordinary kriging coupled with three different molecular similarity approaches (based on molecular descriptors, fingerprints, and atom matching) which creates an interpolation map over the molecular space that is capable of predicting properties/activities for diverse chemical data sets. The proposed method was tested in two data sets of diverse chemical compounds collected from the literature and preprocessed. One of the data sets contained dihydrofolate reductase inhibition activity data, and the second molecules for which aqueous solubility was known. The overall predictive results using kriging for both data sets comply with the results obtained in the literature using typical QSPR/QSAR approaches. However, the procedure did not involve any type of descriptor selection or even minimal information about each problem, suggesting that this approach is directly applicable to a large spectrum of problems in QSAR/QSPR. Furthermore, the predictive results improve significantly with the similarity threshold between the training and testing compounds, allowing the definition of a confidence threshold of similarity and error estimation for each case inferred. The use of kriging for interpolation over the molecular metric space is independent of the training data set size, and no reparametrizations are necessary when more compounds are added or removed from the set, and increasing the size of the database will consequentially improve the quality of the estimations. Finally it is shown that this model can be used for checking the consistency of measured data and for guiding an extension of the training set by determining the regions of the molecular space for which new experimental measurements could be used to maximize the model's predictive performance.

An advanced technique for the prediction of decelerator system dynamics.

NASA Technical Reports Server (NTRS)

Talay, T. A.; Morris, W. D.; Whitlock, C. H.

1973-01-01

An advanced two-body six-degree-of-freedom computer model employing an indeterminate structures approach has been developed for the parachute deployment process. The program determines both vehicular and decelerator responses to aerodynamic and physical property inputs. A better insight into the dynamic processes that occur during parachute deployment has been developed. The model is of value in sensitivity studies to isolate important parameters that affect the vehicular response.

Using Ice Predictions to Guide Submarines

DTIC Science & Technology

2016-01-01

the Arctic Cap Nowcast/ Forecast System (ACNFS) in September 2013. The ACNFS consists of a coupled ice -ocean model that assimilates available real...of the ice cover. The age of the sea ice serves as an indicator of its physical properties including surface roughness, melt pond coverage, and...the Arctic Cap Nowcast/Forecast System (ACNFS). Ice thickness is in meters for 11 September 2015. Thickness ranges from zero to five meters as shown

BH3-Amine and B(CH3)3-Amine Adducts as Additives for Liquid/Gel Hypergols and Solid Hybrid Rocket Motor Fuels: Property and Performance Predictions

DTIC Science & Technology

2013-12-01

and Thermolysis of Lithium, Magnesium Calcium and Strontium Tetraborate Complex Compounds With Triethylenediamine-Crystal Structure of 2BH3•C6H12N2...of Closed-Shell Atoms and Hydrides of the 1st-Row Elements. Journal of Chemical Physics 1988, 89 , 2193-2218. Petersson, G. A.; Tensfeldt, T

The top quark (20 years after the discovery)

DOE PAGES

Boos, Eduard; Brandt, Oleg; Denisov, Dmitri; ...

2015-09-10

On the twentieth anniversary of the observation of the top quark, we trace our understanding of this heaviest of all known particles from the prediction of its existence, through the searches and discovery, to the current knowledge of its production mechanisms and properties. We also discuss the central role of the top quark in the Standard Model and the windows that it opens for seeking new physics beyond the Standard Model.

Li-ion synaptic transistor for low power analog computing

DOE PAGES

Fuller, Elliot J.; Gabaly, Farid El; Leonard, Francois; ...

2016-11-22

Nonvolatile redox transistors (NVRTs) based upon Li-ion battery materials are demonstrated as memory elements for neuromorphic computer architectures with multi-level analog states, “write” linearity, low-voltage switching, and low power dissipation. Simulations of back propagation using the device properties reach ideal classification accuracy. Finally, physics-based simulations predict energy costs per “write” operation of <10 aJ when scaled to 200 nm × 200 nm.

A technique for predicting steel corrosion resistance

NASA Astrophysics Data System (ADS)

Novikov, V. F.; Sokolov, R. A.; Neradovskiy, D. F.; Muratov, K. R.

2018-01-01

Research works were carried out to develop a technique with the aim to increase the lifetime of steel items used in corrosive media. The possibility to monitor corrosion parameters of steel samples is analyzed on the basis of magnetic properties obtained by means of a magnetic structuroscope DIUS-1.15M designed by the Institute of Metal Physics of the Ural Branch of the Russian Academy of Sciences (IMP UB RAS).

Using Theoretical Descriptions in Structure Activity Relations. 3. Electronic Descriptors

DTIC Science & Technology

1988-08-01

Activity Relationships (QSAR) have been used successfully in the past to develop predictive equations for several biological and physical properties...Linear Free Energy Relationships (,FF.3) and is based on work by Hammet in which he derived electronic descriptors for the dissociation of substituted...structure of a compound and its activity in a system. Several different structural descriptors have been used in QSAR equations . These range from

Aerodynamic distortion propagation calculation in application of high-speed target detection by laser

NASA Astrophysics Data System (ADS)

Zheng, Yonghui; Sun, Huayan; Zhao, Yanzhong; Chen, Jianbiao

2015-10-01

Active laser detection technique has a broad application prospect in antimissile and air defense, however the aerodynamic flow field around the planes and missiles cause serious distortion effect on the detecting laser beams. There are many computational fluid dynamics(CFD) codes that can predict the air density distribution and also the density fluctuations of the flow field, it's necessary for physical optics to be used to predict the distortion properties after propagation through the complex process. Aiming at the physical process of laser propagation in "Cat-eye" lenses and aerodynamic flow field for twice, distortion propagation calculation method is researched in this paper. In the minds of dividing the whole process into two parts, and tread the aero-optical optical path difference as a phase distortion, the incidence and reflection process are calculated using Collins formula and angular spectrum diffraction theory respectively. In addition, turbulent performance of the aerodynamic flow field is estimated according to the electromagnetic propagation theory through a random medium, the rms optical path difference and Strehl ratio of the turbulent optical distortion are obtained. Finally, Computational fluid mechanics and aero-optical distortion properties of the detecting laser beams are calculated with the hemisphere-on-cylinder turret as an example, calculation results are showed and analysed.

Virtual milk for modelling and simulation of dairy processes.

PubMed

Munir, M T; Zhang, Y; Yu, W; Wilson, D I; Young, B R

2016-05-01

The modeling of dairy processing using a generic process simulator suffers from shortcomings, given that many simulators do not contain milk components in their component libraries. Recently, pseudo-milk components for a commercial process simulator were proposed for simulation and the current work extends this pseudo-milk concept by studying the effect of both total milk solids and temperature on key physical properties such as thermal conductivity, density, viscosity, and heat capacity. This paper also uses expanded fluid and power law models to predict milk viscosity over the temperature range from 4 to 75°C and develops a succinct regressed model for heat capacity as a function of temperature and fat composition. The pseudo-milk was validated by comparing the simulated and actual values of the physical properties of milk. The milk thermal conductivity, density, viscosity, and heat capacity showed differences of less than 2, 4, 3, and 1.5%, respectively, between the simulated results and actual values. This work extends the capabilities of the previously proposed pseudo-milk and of a process simulator to model dairy processes, processing different types of milk (e.g., whole milk, skim milk, and concentrated milk) with different intrinsic compositions, and to predict correct material and energy balances for dairy processes. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Mathematical model of the stack region of a commercial lead blast furnace

NASA Astrophysics Data System (ADS)

Hussain, Mansoor M.; Morris, David R.

1989-02-01

A mathematical model of the stack region of a commercial lead blast furnace is presented. The mass and heat balance equations were solved in conjunction with the kinetic expression for the rate of re-duction of the solids based upon the grain model, utilizing the measured structural parameters of the sinter feed and the measured kinetic parameters. Satisfactory agreement has been achieved between the computed and experimental axial profiles of gas and solids temperature, pressure, gas composi-tion, and condensed phases composition. The model is used to predict the effects of changes of bed voidage, physical properties, and chemical constitution of the sinter and the effects of gas and solids flow maldistribution on the operation of the furnace. In particular, it is noted that for a sinter with the typical physical properties of a commercial sinter, improved conversion in the upper reaches of the furnace is predicted when lead is in the form of lead oxide rather than as the relatively unreac-tive lead calcium silicates. The improved conversion is accompanied by better utilization of carbon monoxide. Further, the model suggests that the formation of scaffolds in the furnace may be due to flow maldistribution causing high temperatures in the vicinity of the furnace wall.

Violence Related Behaviors and Weapon Carrying Among Hispanic Adolescents: Results from the National Youth Risk Behavior Survey, 2001-2015.

PubMed

Khubchandani, Jagdish; Price, James H

2018-04-01

Hispanic youths are disproportionately represented in gangs in the United States, are more likely to drink alcohol at younger ages, and to live in poverty; all are risks for violence and weapon carrying. No studies to date have assessed violence related behaviors and weapon carrying in Hispanic youth over an extended period. This study utilized the national Youth Risk Behavior Surveys from 2001 to 2015 to assess trends in violence related behaviors and weapon carrying of Hispanic adolescents. Our analyses found both physical fighting and fighting on school property had statistically significant reductions from 2001 to 2015 for Hispanic females and their suicide attempts increased from 2009 to 2015. Hispanic males had statistically significant decreasing trends for: being in a physical fight in the past year, being bullied on school property, being in a physical fight on school property within the past year; threatened or injured with a weapon on school property in the past year; and having attempted suicide in the past year. Hispanic females and males had two groups of items highly predictive of weapon carrying behaviors: alcohol, tobacco, and other drug use and violent risk behaviors. Both female and male students who made mostly A's or B's in school were significantly less likely (about half as likely) to carry weapons. This data could be used to identify Hispanic adolescents at higher risk for weapon carrying and used as a basis for enriching programs to improve academic success of Hispanic adolescents.

Epitaxial strain effect on the physical properties of layered ruthenate and iridate thin films

NASA Astrophysics Data System (ADS)

Miao, Ludi

Transition metal oxides have attracted widespread attention due to their broad range of fascinating exotic phenomena such as multiferroicity, superconductivity, colossal magnetoresistance and metal-to-insulator transition. Due to the interplay between spin, charge, lattice and orbital degrees of freedom of strongly correlated d electrons, these physical properties are extremely sensitive to the external perturbations such as magnetic field, charge carrier doping and pressure, which provide a unique chance in search for novel exotic quantum states. Ruthenate systems are a typical strongly correlated system, with rich ordered states and their properties are extremely sensitive to external stimuli. Recently, the experimental observation of spin-orbit coupling induced Mott insulator in Sr2IrO4 as well as the theoretical prediction of topological insulating state in other iridates, have attracted tremendous interest in the physics of strong correlation and spin-orbit coupling in 4d/5d compounds. We observe an itinerant ferromagnetic ground state of Ca2 RuO4 film in stark contrast to the Mott-insulating state in bulk Ca2RuO4. We have also established the epitaxial strain effect on the transport and magnetic properties for the (Ca,Sr) 2RuO4 thin films. For Sr2IrO4 thin films, we will show that the Jeff = 1/2 moment orientation can be modulated by epitaxial strain. In addition, we discovered novel Ba 7Ir3O13+x thin films which exhibit colossal permittivity.

Neogeomorphology, prediction, and the anthropic landscape

NASA Astrophysics Data System (ADS)

Haff, P. K.

The surface of the earth is undergoing profound change due to human impact. By some measures the level of human impact is comparable to the effects of major classical geomorphic processes such as fluvial sediment transport. This change is occurring rapidly, has no geologic precedent, and may represent an irreversible transition to a new and novel landscape with which we have no experience. For these reasons prediction of future landscape evolution will be of increasing importance. The combination of physical and social forces that drive modern landscape change represents the Anthropic Force. Neogeomorphology is the study of the Anthropic Force and its present and likely future effects on the landscape. Unique properties associated with the Anthropic Force include consciousness, intention and design. These properties support the occurrence of nonclassical geomorphic phenomena, such as landscape planning, engineering, and management. The occurrence of short time-scale phenomena induced by anthropic landscape change, the direct effects of this change on society, and the ability to anticipate and intentionally influence the future trajectory of the global landscape underscore the importance of prediction in a neogeomorphic world.

Electronic structure, mechanical and thermodynamic properties of BaPaO3 under pressure.

PubMed

Khandy, Shakeel Ahmad; Islam, Ishtihadah; Gupta, Dinesh C; Laref, Amel

2018-05-07

Density functional theory (DFT)-based investigations have been put forward on the elastic, mechanical, and thermo-dynamical properties of BaPaO 3 . The pressure dependence of electronic band structure and other physical properties has been carefully analyzed. The increase in Bulk modulus and decrease in lattice constant is seen on going from 0 to 30 GPa. The predicted lattice constants describe this material as anisotropic and ductile in nature at ambient conditions. Post-DFT calculations using quasi-harmonic Debye model are employed to envisage the pressure-dependent thermodynamic properties like Debye temperature, specific heat capacity, Grüneisen parameter, thermal expansion, etc. Also, the computed Debye temperature and melting temperature of BaPaO 3 at 0 K are 523 K and 1764.75 K, respectively.

Component analysis and initial validity of the exercise fear avoidance scale.

PubMed

Wingo, Brooks C; Baskin, Monica; Ard, Jamy D; Evans, Retta; Roy, Jane; Vogtle, Laura; Grimley, Diane; Snyder, Scott

2013-01-01

To develop the Exercise Fear Avoidance Scale (EFAS) to measure fear of exercise-induced discomfort. We conducted principal component analysis to determine component structure and Cronbach's alpha to assess internal consistency of the EFAS. Relationships between EFAS scores, BMI, physical activity, and pain were analyzed using multivariate regression. The best fit was a 3-component structure: weight-specific fears, cardiorespiratory fears, and musculoskeletal fears. Cronbach's alpha for the EFAS was α=.86. EFAS scores significantly predicted BMI, physical activity, and PDI scores. Psychometric properties of this scale suggest it may be useful for tailoring exercise prescriptions to address fear of exercise-related discomfort.

Experimentally validated quantitative linear model for the device physics of elastomeric microfluidic valves

NASA Astrophysics Data System (ADS)

Kartalov, Emil P.; Scherer, Axel; Quake, Stephen R.; Taylor, Clive R.; Anderson, W. French

2007-03-01

A systematic experimental study and theoretical modeling of the device physics of polydimethylsiloxane "pushdown" microfluidic valves are presented. The phase space is charted by 1587 dimension combinations and encompasses 45-295μm lateral dimensions, 16-39μm membrane thickness, and 1-28psi closing pressure. Three linear models are developed and tested against the empirical data, and then combined into a fourth-power-polynomial superposition. The experimentally validated final model offers a useful quantitative prediction for a valve's properties as a function of its dimensions. Typical valves (80-150μm width) are shown to behave like thin springs.

Relationship between body mass, lean mass, fat mass, and limb bone cross-sectional geometry: Implications for estimating body mass and physique from the skeleton.

PubMed

Pomeroy, Emma; Macintosh, Alison; Wells, Jonathan C K; Cole, Tim J; Stock, Jay T

2018-05-01

Estimating body mass from skeletal dimensions is widely practiced, but methods for estimating its components (lean and fat mass) are poorly developed. The ability to estimate these characteristics would offer new insights into the evolution of body composition and its variation relative to past and present health. This study investigates the potential of long bone cross-sectional properties as predictors of body, lean, and fat mass. Humerus, femur and tibia midshaft cross-sectional properties were measured by peripheral quantitative computed tomography in sample of young adult women (n = 105) characterized by a range of activity levels. Body composition was estimated from bioimpedance analysis. Lean mass correlated most strongly with both upper and lower limb bone properties (r values up to 0.74), while fat mass showed weak correlations (r ≤ 0.29). Estimation equations generated from tibial midshaft properties indicated that lean mass could be estimated relatively reliably, with some improvement using logged data and including bone length in the models (minimum standard error of estimate = 8.9%). Body mass prediction was less reliable and fat mass only poorly predicted (standard errors of estimate ≥11.9% and >33%, respectively). Lean mass can be predicted more reliably than body mass from limb bone cross-sectional properties. The results highlight the potential for studying evolutionary trends in lean mass from skeletal remains, and have implications for understanding the relationship between bone morphology and body mass or composition. © 2018 The Authors. American Journal of Physical Anthropology Published by Wiley Periodicals, Inc.

Impact of aluminum doping on the thermo-physical properties of refractory medium-entropy alloys

NASA Astrophysics Data System (ADS)

Tian, Fuyang; Wang, Yang; Vitos, Levente

2017-01-01

We investigate the elastic moduli, ideal tensile strength, and thermodynamic properties of TiVNb and AlTiVNb refractory medium-entropy alloys (HEAs) by using ab initio alloy theories: the coherent potential approximation (CPA), the special quasi-random supercell (SQS), and a 432-atom supercell (SC). We find that with increasing number of alloy components, the SQS elastic constants become sensitive to the supercell size. The predicted elastic moduli are consistent with the available experiments. Aluminum doping decreases the stability of the body centered cubic phase. The ideal tensile strength calculation indicates that adding equiatomic Al to TiVNb random solid solution increases the intrinsic strength (ideal strain increase from 9.6% to 11.8%) and decreases the intrinsic strength (from 9.6 to 5.7 GPa). Based on the equation of states calculated by the CPA and SC methods, the thermodynamic properties obtained by the two ab initio methods are assessed. The L21 AlTiVNb (Ti-Al-V-Nb) alloy is predicted to be thermodynamically and dynamically stable with respect to the solid solution.

Combining experimental design and orthogonal projections to latent structures to study the influence of microcrystalline cellulose properties on roll compaction.

PubMed

Dumarey, Melanie; Wikström, Håkan; Fransson, Magnus; Sparén, Anders; Tajarobi, Pirjo; Josefson, Mats; Trygg, Johan

2011-09-15

Roll compaction is gaining importance in pharmaceutical industry for the dry granulation of heat or moisture sensitive powder blends with poor flowing properties prior to tabletting. We studied the influence of microcrystalline cellulose (MCC) properties on the roll compaction process and the consecutive steps in tablet manufacturing. Four dissimilar MCC grades, selected by subjecting their physical characteristics to principal components analysis, and three speed ratios, i.e. the ratio of the feed screw speed and the roll speed of the roll compactor, were included in a full factorial design. Orthogonal projection to latent structures was then used to model the properties of the resulting roll compacted products (ribbons, granules and tablets) as a function of the physical MCC properties and the speed ratio. This modified version of partial least squares regression separates variation in the design correlated to the considered response from the variation orthogonal to that response. The contributions of the MCC properties and the speed ratio to the predictive and orthogonal components of the models were used to evaluate the effect of the design variation. The models indicated that several MCC properties, e.g. bulk density and compressibility, affected all granule and tablet properties, but only one studied ribbon property: porosity. After roll compaction, Ceolus KG 1000 resulted in tablets with obvious higher tensile strength and lower disintegration time compared to the other MCC grades. This study confirmed that the particle size increase caused by roll compaction is highly responsible for the tensile strength decrease of the tablets. Copyright © 2011 Elsevier B.V. All rights reserved.

A physical function test for use in the intensive care unit: validity, responsiveness, and predictive utility of the physical function ICU test (scored).

PubMed

Denehy, Linda; de Morton, Natalie A; Skinner, Elizabeth H; Edbrooke, Lara; Haines, Kimberley; Warrillow, Stephen; Berney, Sue

2013-12-01

Several tests have recently been developed to measure changes in patient strength and functional outcomes in the intensive care unit (ICU). The original Physical Function ICU Test (PFIT) demonstrates reliability and sensitivity. The aims of this study were to further develop the original PFIT, to derive an interval score (the PFIT-s), and to test the clinimetric properties of the PFIT-s. A nested cohort study was conducted. One hundred forty-four and 116 participants performed the PFIT at ICU admission and discharge, respectively. Original test components were modified using principal component analysis. Rasch analysis examined the unidimensionality of the PFIT, and an interval score was derived. Correlations tested validity, and multiple regression analyses investigated predictive ability. Responsiveness was assessed using the effect size index (ESI), and the minimal clinically important difference (MCID) was calculated. The shoulder lift component was removed. Unidimensionality of combined admission and discharge PFIT-s scores was confirmed. The PFIT-s displayed moderate convergent validity with the Timed "Up & Go" Test (r=-.60), the Six-Minute Walk Test (r=.41), and the Medical Research Council (MRC) sum score (rho=.49). The ESI of the PFIT-s was 0.82, and the MCID was 1.5 points (interval scale range=0-10). A higher admission PFIT-s score was predictive of: an MRC score of ≥48, increased likelihood of discharge home, reduced likelihood of discharge to inpatient rehabilitation, and reduced acute care hospital length of stay. Scoring of sit-to-stand assistance required is subjective, and cadence cutpoints used may not be generalizable. The PFIT-s is a safe and inexpensive test of physical function with high clinical utility. It is valid, responsive to change, and predictive of key outcomes. It is recommended that the PFIT-s be adopted to test physical function in the ICU.

Molecular mobility in amorphous state: Implications on physical stability

NASA Astrophysics Data System (ADS)

Bhardwaj, Sunny Piyush

Amorphous pharmaceuticals are desirable in drug development due to their advantageous biopharmaceutical properties of higher apparent aqueous solubility and dissolution rate. The main obstacle in their widespread use, however, is their higher physicochemical instability than their crystalline counterparts. The goal of the present research project was to investigate correlations between the molecular mobility and physical stability in model amorphous compounds. The objective was to identify the specific mobility which is responsible for the physical instability in each case. This will potentially enable the development of effective strategies for the stabilization of amorphous pharmaceuticals. Moreover, these correlations can be used to develop predictive models for the stability at the pharmaceutically relevant storage conditions. Subtraction of dc conductivity enabled the comprehensive characterization of molecular mobility in amorphous trehalose. This was followed by investigation of correlation between crystallization behavior and different relaxations. Global mobility was found to be strongly coupled to both crystallization onset time and rate. Different preparation methods imparted different mobility states to amorphous trehalose which was postulated to be the reason for the significant physical stability differences. Predictive models were developed and a good agreement was found between the predicted and the experimental crystallization onset times at temperatures around and below the glass transition temperature (Tg). Effect of annealing was investigated on water sorption, enthalpic recovery and dielectric relaxation times in amorphous trehalose. Global mobility was found to be linearly correlated to the water sorption potential which enabled the development of predictive models. Global mobility was also found to be strongly correlated to physical instability in amorphous itraconazole. Effect of polymer (PVP and HPMCAS) on itraconazole mobility and stability was also evaluated. Global mobility was found to be correlated to stability in both the solid dispersions. HPMCAS was found to be a better stabilizer than PVP due to its pronounced effect on global mobility.

Dynamic thermal signature prediction for real-time scene generation

NASA Astrophysics Data System (ADS)

Christie, Chad L.; Gouthas, Efthimios (Themie); Williams, Owen M.; Swierkowski, Leszek

2013-05-01

At DSTO, a real-time scene generation framework, VIRSuite, has been developed in recent years, within which trials data are predominantly used for modelling the radiometric properties of the simulated objects. Since in many cases the data are insufficient, a physics-based simulator capable of predicting the infrared signatures of objects and their backgrounds has been developed as a new VIRSuite module. It includes transient heat conduction within the materials, and boundary conditions that take into account the heat fluxes due to solar radiation, wind convection and radiative transfer. In this paper, an overview is presented, covering both the steady-state and transient performance.

Phasic dopamine signals: from subjective reward value to formal economic utility

PubMed Central

Schultz, Wolfram; Carelli, Regina M; Wightman, R Mark

2015-01-01

Although rewards are physical stimuli and objects, their value for survival and reproduction is subjective. The phasic, neurophysiological and voltammetric dopamine reward prediction error response signals subjective reward value. The signal incorporates crucial reward aspects such as amount, probability, type, risk, delay and effort. Differences of dopamine release dynamics with temporal delay and effort in rodents may derive from methodological issues and require further study. Recent designs using concepts and behavioral tools from experimental economics allow to formally characterize the subjective value signal as economic utility and thus to establish a neuronal value function. With these properties, the dopamine response constitutes a utility prediction error signal. PMID:26719853

3D Microstructures for Materials and Damage Models

DOE PAGES

Livescu, Veronica; Bronkhorst, Curt Allan; Vander Wiel, Scott Alan

2017-02-01

Many challenges exist with regard to understanding and representing complex physical processes involved with ductile damage and failure in polycrystalline metallic materials. Currently, the ability to accurately predict the macroscale ductile damage and failure response of metallic materials is lacking. Research at Los Alamos National Laboratory (LANL) is aimed at building a coupled experimental and computational methodology that supports the development of predictive damage capabilities by: capturing real distributions of microstructural features from real material and implementing them as digitally generated microstructures in damage model development; and, distilling structure-property information to link microstructural details to damage evolution under a multitudemore » of loading states.« less

Image Analysis of a Negatively Curved Graphitic Sheet Model for Amorphous Carbon

NASA Astrophysics Data System (ADS)

Bursill, L. A.; Bourgeois, Laure N.

High-resolution electron micrographs are presented which show essentially curved single sheets of graphitic carbon. Image calculations are then presented for the random surface schwarzite-related model of Townsend et al. (Phys. Rev. Lett. 69, 921-924, 1992). Comparison with experimental images does not rule out the contention that such models, containing surfaces of negative curvature, may be useful for predicting some physical properties of specific forms of nanoporous carbon. Some difficulties of the model predictions, when compared with the experimental images, are pointed out. The range of application of this model, as well as competing models, is discussed briefly.

Prediction of physical-chemical properties of crude oils by 1H NMR analysis of neat samples and chemometrics.

PubMed

Masili, Alice; Puligheddu, Sonia; Sassu, Lorenzo; Scano, Paola; Lai, Adolfo

2012-11-01

In this work, we report the feasibility study to predict the properties of neat crude oil samples from 300-MHz NMR spectral data and partial least squares (PLS) regression models. The study was carried out on 64 crude oil samples obtained from 28 different extraction fields and aims at developing a rapid and reliable method for characterizing the crude oil in a fast and cost-effective way. The main properties generally employed for evaluating crudes' quality and behavior during refining were measured and used for calibration and testing of the PLS models. Among these, the UOP characterization factor K (K(UOP)) used to classify crude oils in terms of composition, density (D), total acidity number (TAN), sulfur content (S), and true boiling point (TBP) distillation yields were investigated. Test set validation with an independent set of data was used to evaluate model performance on the basis of standard error of prediction (SEP) statistics. Model performances are particularly good for K(UOP) factor, TAN, and TPB distillation yields, whose standard error of calibration and SEP values match the analytical method precision, while the results obtained for D and S are less accurate but still useful for predictions. Furthermore, a strategy that reduces spectral data preprocessing and sample preparation procedures has been adopted. The models developed with such an ample crude oil set demonstrate that this methodology can be applied with success to modern refining process requirements. Copyright © 2012 John Wiley & Sons, Ltd.

MnNiO 3 revisited with modern theoretical and experimental methods

DOE PAGES

Dzubak, Allison L.; Mitra, Chandrima; Chance, Michael; ...

2017-11-03

MnNiO 3 is a strongly correlated transition metal oxide that has recently been investigated theoretically for its potential application as an oxygen-evolution photocatalyst. However, there is no experimental report on critical quantities such as the band gap or bulk modulus. Recent theoretical predictions with standard functionals such as LDA+U and HSE show large discrepancies in the band gaps (about 1.23 eV), depending on the nature of the functional used. Hence there is clearly a need for an accurate quantitative prediction of the band gap to gauge its utility as a photocatalyst. In this work, we present a diffusion quantum Montemore » Carlo study of the bulk properties of MnNiO 3 and revisit the synthesis and experimental properties of the compound. We predict quasiparticle band gaps of 2.0(5) eV and 3.8(6) eV for the majority and minority spin channels, respectively, and an equilibrium volume of 92.8 Å 3, which compares well to the experimental value of 94.4 Å 3. A bulk modulus of 217 GPa is predicted for MnNiO 3. As a result, we rationalize the difficulty for the formation of ordered ilmenite-type structure with specific sites for Ni and Mn to be potentially due to the formation of antisite defects that form during synthesis, which ultimately affects the physical properties of MnNiO 3.« less

Using reweighting and free energy surface interpolation to predict solid-solid phase diagrams

NASA Astrophysics Data System (ADS)

Schieber, Natalie P.; Dybeck, Eric C.; Shirts, Michael R.

2018-04-01

Many physical properties of small organic molecules are dependent on the current crystal packing, or polymorph, of the material, including bioavailability of pharmaceuticals, optical properties of dyes, and charge transport properties of semiconductors. Predicting the most stable crystalline form at a given temperature and pressure requires determining the crystalline form with the lowest relative Gibbs free energy. Effective computational prediction of the most stable polymorph could save significant time and effort in the design of novel molecular crystalline solids or predict their behavior under new conditions. In this study, we introduce a new approach using multistate reweighting to address the problem of determining solid-solid phase diagrams and apply this approach to the phase diagram of solid benzene. For this approach, we perform sampling at a selection of temperature and pressure states in the region of interest. We use multistate reweighting methods to determine the reduced free energy differences between T and P states within a given polymorph and validate this phase diagram using several measures. The relative stability of the polymorphs at the sampled states can be successively interpolated from these points to create the phase diagram by combining these reduced free energy differences with a reference Gibbs free energy difference between polymorphs. The method also allows for straightforward estimation of uncertainties in the phase boundary. We also find that when properly implemented, multistate reweighting for phase diagram determination scales better with the size of the system than previously estimated.

MnNiO 3 revisited with modern theoretical and experimental methods

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

Dzubak, Allison L.; Mitra, Chandrima; Chance, Michael

MnNiO 3 is a strongly correlated transition metal oxide that has recently been investigated theoretically for its potential application as an oxygen-evolution photocatalyst. However, there is no experimental report on critical quantities such as the band gap or bulk modulus. Recent theoretical predictions with standard functionals such as LDA+U and HSE show large discrepancies in the band gaps (about 1.23 eV), depending on the nature of the functional used. Hence there is clearly a need for an accurate quantitative prediction of the band gap to gauge its utility as a photocatalyst. In this work, we present a diffusion quantum Montemore » Carlo study of the bulk properties of MnNiO 3 and revisit the synthesis and experimental properties of the compound. We predict quasiparticle band gaps of 2.0(5) eV and 3.8(6) eV for the majority and minority spin channels, respectively, and an equilibrium volume of 92.8 Å 3, which compares well to the experimental value of 94.4 Å 3. A bulk modulus of 217 GPa is predicted for MnNiO 3. As a result, we rationalize the difficulty for the formation of ordered ilmenite-type structure with specific sites for Ni and Mn to be potentially due to the formation of antisite defects that form during synthesis, which ultimately affects the physical properties of MnNiO 3.« less

Dimensionality and predictive validity of the HAM-Nat, a test of natural sciences for medical school admission

PubMed Central

2011-01-01

Background Knowledge in natural sciences generally predicts study performance in the first two years of the medical curriculum. In order to reduce delay and dropout in the preclinical years, Hamburg Medical School decided to develop a natural science test (HAM-Nat) for student selection. In the present study, two different approaches to scale construction are presented: a unidimensional scale and a scale composed of three subject specific dimensions. Their psychometric properties and relations to academic success are compared. Methods 334 first year medical students of the 2006 cohort responded to 52 multiple choice items from biology, physics, and chemistry. For the construction of scales we generated two random subsamples, one for development and one for validation. In the development sample, unidimensional item sets were extracted from the item pool by means of weighted least squares (WLS) factor analysis, and subsequently fitted to the Rasch model. In the validation sample, the scales were subjected to confirmatory factor analysis and, again, Rasch modelling. The outcome measure was academic success after two years. Results Although the correlational structure within the item set is weak, a unidimensional scale could be fitted to the Rasch model. However, psychometric properties of this scale deteriorated in the validation sample. A model with three highly correlated subject specific factors performed better. All summary scales predicted academic success with an odds ratio of about 2.0. Prediction was independent of high school grades and there was a slight tendency for prediction to be better in females than in males. Conclusions A model separating biology, physics, and chemistry into different Rasch scales seems to be more suitable for item bank development than a unidimensional model, even when these scales are highly correlated and enter into a global score. When such a combination scale is used to select the upper quartile of applicants, the proportion of successful completion of the curriculum after two years is expected to rise substantially. PMID:21999767

[Development of an analyzing system for soil parameters based on NIR spectroscopy].

PubMed

Zheng, Li-Hua; Li, Min-Zan; Sun, Hong

2009-10-01

A rapid estimation system for soil parameters based on spectral analysis was developed by using object-oriented (OO) technology. A class of SOIL was designed. The instance of the SOIL class is the object of the soil samples with the particular type, specific physical properties and spectral characteristics. Through extracting the effective information from the modeling spectral data of soil object, a map model was established between the soil parameters and its spectral data, while it was possible to save the mapping model parameters in the database of the model. When forecasting the content of any soil parameter, the corresponding prediction model of this parameter can be selected with the same soil type and the similar soil physical properties of objects. And after the object of target soil samples was carried into the prediction model and processed by the system, the accurate forecasting content of the target soil samples could be obtained. The system includes modules such as file operations, spectra pretreatment, sample analysis, calibrating and validating, and samples content forecasting. The system was designed to run out of equipment. The parameters and spectral data files (*.xls) of the known soil samples can be input into the system. Due to various data pretreatment being selected according to the concrete conditions, the results of predicting content will appear in the terminal and the forecasting model can be stored in the model database. The system reads the predicting models and their parameters are saved in the model database from the module interface, and then the data of the tested samples are transferred into the selected model. Finally the content of soil parameters can be predicted by the developed system. The system was programmed with Visual C++6.0 and Matlab 7.0. And the Access XP was used to create and manage the model database.

Dimensionality and predictive validity of the HAM-Nat, a test of natural sciences for medical school admission.

PubMed

Hissbach, Johanna C; Klusmann, Dietrich; Hampe, Wolfgang

2011-10-14

Knowledge in natural sciences generally predicts study performance in the first two years of the medical curriculum. In order to reduce delay and dropout in the preclinical years, Hamburg Medical School decided to develop a natural science test (HAM-Nat) for student selection. In the present study, two different approaches to scale construction are presented: a unidimensional scale and a scale composed of three subject specific dimensions. Their psychometric properties and relations to academic success are compared. 334 first year medical students of the 2006 cohort responded to 52 multiple choice items from biology, physics, and chemistry. For the construction of scales we generated two random subsamples, one for development and one for validation. In the development sample, unidimensional item sets were extracted from the item pool by means of weighted least squares (WLS) factor analysis, and subsequently fitted to the Rasch model. In the validation sample, the scales were subjected to confirmatory factor analysis and, again, Rasch modelling. The outcome measure was academic success after two years. Although the correlational structure within the item set is weak, a unidimensional scale could be fitted to the Rasch model. However, psychometric properties of this scale deteriorated in the validation sample. A model with three highly correlated subject specific factors performed better. All summary scales predicted academic success with an odds ratio of about 2.0. Prediction was independent of high school grades and there was a slight tendency for prediction to be better in females than in males. A model separating biology, physics, and chemistry into different Rasch scales seems to be more suitable for item bank development than a unidimensional model, even when these scales are highly correlated and enter into a global score. When such a combination scale is used to select the upper quartile of applicants, the proportion of successful completion of the curriculum after two years is expected to rise substantially.

Factors which predict violence victimization in Nigeria

PubMed Central

Fry, Lincoln J.

2014-01-01

Background: Violence is a major public health issue, globally as well as in the African continent. This paper looks at Nigeria and begins the process of identifying the factors that predict interpersonal violence in that country. The purpose is to interpret the implications of the results presented here for violence prevention programmes in Nigeria. Materials and Methods: The study is based on the responses of 2324 Nigerians included in Round Four of the Afrobarometer surveys. The study concentrates on 579 respondents who reported either they or someone else in their family had been the victim of violence, defined as being physically attacked, in the past year. Results: A logistical regression analysis revealed five significant factors that predicted interpersonal violence: being the victim of a property crime, the fear of crime, the respondents faith, whethera police station was in the local area and poverty. The findings revealed that 43.7% of the sample had been victimised within the past year and 18.8% had been the victim of both violent and property crimes. One surprising findingwas the number of respondents who were re-victimised; 75% of violence victims also had been property crime victims. Conclusions: These findings suggest that target hardening should be the basis to plan, implement and evaluate violence prevention programmes in Nigeria. Prevention personnel and/or law enforcement need to respond to reported incidents of property and/or violence victimisation and attempt to prepare victims to protect both their premises and their persons in the future. PMID:24970968

Prediction of Reservoir Properties for Geomechanical Analysis Using 3-D Seismic Data and Rock Physics Modeling in the Vaca Muerta Formation, Neuquen Basin, Argentina

NASA Astrophysics Data System (ADS)

Convers-Gomez, Carlos E.

The Vaca Muerta Formation in the Neuquen Basin has recently received a lot of attention from oil companies interested in developing its shale resources. Early identification of potential zones with possible good production is extremely important to optimize the return on capital investment. Developing a work flow in shale plays that associates an effective hydraulic fracture response with the presence of hydrocarbons is crucial for economic success. The vertical and lateral heterogeneity of rock properties are critical factors that impact production. The integration of 3D seismic and well data is necessary for prediction of rock properties and identifies their distribution in the rock, which can also be integrated with geomechanical properties to model the rock response favorable to hydraulic stimulation. This study includes a 3D seismic survey and six vertical wells with full log suites in each well. The well logs allowed for the computation of a pre-stack model-based inversion which uses seismic data to estimate rock property volumes. An inverse relationship between P-impedance and Total Organic Content (TOC) was observed and quantified. Likewise, a direct relationship between P-impedance and volume of carbonate was observed. The volume of kerogen, type of clay, type of carbonate and fluid pressure all control the geomechanical properties of the formation when subject to hydraulic fracturing. Probabilistic Neural Networks were then used to predict the lateral and vertical heterogeneity of rock properties. TOC and volume of kerogen behaved as adequate indicators of possible zones with high presence of hydrocarbons. Meanwhile, the volume of carbonate was a valid indicator of brittle-ductile rock. The predicted density volume was used to estimate geomechanical properties (Young's Modulus and Poisson's Ratio) and to identify the zones that have a better response to hydraulic stimulation. During the analysis of geomechanical properties, Young's Modulus was observed to have a direct relationship with volume of carbonate and an inverse relationship with TOC, enabling the identification of brittle and ductile rocks zones. The analysis detected zones that had a good presence of hydrocarbons and brittle rock. The information was integrated with the analysis of geomechanical properties generating a model with the most possible zones of good production. This model will aid in the future exploration and development of the Vaca Muerta Formation.

A multilevel approach to modeling of porous bioceramics

NASA Astrophysics Data System (ADS)

Mikushina, Valentina A.; Sidorenko, Yury N.

2015-10-01

The paper is devoted to discussion of multiscale models of heterogeneous materials using principles. The specificity of approach considered is the using of geometrical model of composites representative volume, which must be generated with taking the materials reinforcement structure into account. In framework of such model may be considered different physical processes which have influence on the effective mechanical properties of composite, in particular, the process of damage accumulation. It is shown that such approach can be used to prediction the value of composite macroscopic ultimate strength. As an example discussed the particular problem of the study the mechanical properties of biocomposite representing porous ceramics matrix filled with cortical bones tissue.

Ab-initio study of superconducting state in intercalated MoSe2 and WSe2 bilayers

NASA Astrophysics Data System (ADS)

Szcześniak, R.; Durajski, A. P.; Jarosik, M. W.

2018-05-01

A two-dimensional systems have attracted significant interest due to their outstanding physical, chemical and optoelectronic properties. This paper focuses on the detailed investigations of the electronic, phononic and superconducting properties of transition-metal dichalcogenide bilayers MSe 2 (M = Mo, W) intercalated by calcium atoms. The first-principles calculations show that (MoSe2)2Ca and (WSe2)2Ca systems exhibit metallic behavior and weak phonon-mediated superconductivity with low critical temperature of 0.51 and 0.30 K, respectively. These results confirm other theoretical predictions and suggest that the investigated materials cannot be a good candidates for a nanoscale superconductors.

Interlayer interactions in graphites.

PubMed

Chen, Xiaobin; Tian, Fuyang; Persson, Clas; Duan, Wenhui; Chen, Nan-xian

2013-11-06

Based on ab initio calculations of both the ABC- and AB-stacked graphites, interlayer potentials (i.e., graphene-graphene interaction) are obtained as a function of the interlayer spacing using a modified Möbius inversion method, and are used to calculate basic physical properties of graphite. Excellent consistency is observed between the calculated and experimental phonon dispersions of AB-stacked graphite, showing the validity of the interlayer potentials. More importantly, layer-related properties for nonideal structures (e.g., the exfoliation energy, cleave energy, stacking fault energy, surface energy, etc.) can be easily predicted from the interlayer potentials, which promise to be extremely efficient and helpful in studying van der Waals structures.

Ellipsometric study of peptide layers - island-like character, depolarization and quasi-absorption

NASA Astrophysics Data System (ADS)

Pápa, Z.; Ramakrishnan, S.; Martin, M.; Cloitre, T.; Zimányi, L.; Tóth, Z.; Gergely, C.; Budai, J.

2017-11-01

In this work, the ellipsometric measurements of small molecular size polypeptides deposited onto silicon are analyzed. Results of ellipsometric evaluation procedures based on transparent layer, absorbing layer and discontinuous layer approaches are compared. Although these models result in similar fitting quality and can predict the amount of the deposited material, the gained optical properties can be rather different due to the different assumptions of the models. To choose the physically correct results, independent measurements as atomic force microscopy or transmission measurement of peptide solutions are necessary. It is shown that the measured ellipsometric depolarization can provide also useful information about the sample properties.

Thermal protection for hypervelocity flight in earth's atmosphere by use of radiation backscattering ablating materials

NASA Technical Reports Server (NTRS)

Howe, John T.; Yang, Lily

1991-01-01

A heat-shield-material response code predicting the transient performance of a material subject to the combined convective and radiative heating associated with the hypervelocity flight is developed. The code is dynamically interactive to the heating from a transient flow field, including the effects of material ablation on flow field behavior. It accomodates finite time variable material thickness, internal material phase change, wavelength-dependent radiative properties, and temperature-dependent thermal, physical, and radiative properties. The equations of radiative transfer are solved with the material and are coupled to the transfer energy equation containing the radiative flux divergence in addition to the usual energy terms.

``Heavy-water Lattice and Heavy-Quark''

NASA Astrophysics Data System (ADS)

Maksoed, Ssi, Wh-

Refer to Birgitt Roettger-Roessler: ``Feelings at the Margins'', 2014 retrieved the Vienna, 2006 UNIDO Research Programme: Combating Marginalization and Poverty through Industrial Development/COMPID. Also from Vienna, on Feb 18-22, 1963 reported Technical Report Series 20 about ``Heavy Water Lattice''. Failed to relates scale-invariant properties of public-Debt growth to convergence in perturbation theory, sought JH Field: ``Convergence & Gauge Dependence Properties:..''. Furthers, in GP Lepage: ``On the Viabilities of Lattice Perturbation Theory'', 1992 stated: ``in terms of physical quantities, like the heavy-quark potential, greatly enhanced the predictive power of lattice perturbation theory''. Acknowledgements to HE. Mr. H. TUK SETYOHADI, Jl. Sriwijaya Raya 3, South-Jakarta, INDONESIA.

Holocene alluvium around Lefkosia (Nicosia), Cyprus: An archive of land-use, tectonic processes, and climate change

USGS Publications Warehouse

Newell, Wayne L.; Stone, B.; Harrison, R.; ,

2004-01-01

Holocene alluvium of the Pedhicos River around Lefkosia (Nicosia), Cyprus, was studied. Alluvial stratigraphy was found to present serial flood deposits underlying river terraces and an extensive alluvial fan. It was found that the stratigraphy and geomorphology of the alluvium can be interpreted to distinguish not only the effects of climate change, but also land-use change, and the impact of particular engineering works. It was suggested that details of the physical properties of the flood deposit sequences and paleosols can contribute to modeling various geophysical and engineering properties and in predicting response to vertical acceleration during earthquakes.

Identification of extra neutral gauge bosons at the LHC using b and t quarks.

PubMed

Godfrey, Stephen; Martin, Travis A W

2008-10-10

New neutral gauge bosons (Z' 's) are predicted by many models of physics beyond the standard electroweak theory. It is possible that a Z' will be discovered by the Large Hadron Collider program. The next step would be to measure its properties to identify the underlying theory that gave rise to the Z'. Heavy quarks have the unique property that they can be identified in the final states. In this Letter we demonstrate that measuring Z' decays to b- and t-quark final states can act as an effective means of discriminating between models with extra gauge bosons.

Regionalization of subsurface stormflow parameters of hydrologic models: Up-scaling from physically based numerical simulations at hillslope scale

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

Ali, Melkamu; Ye, Sheng; Li, Hongyi

2014-07-19

Subsurface stormflow is an important component of the rainfall-runoff response, especially in steep forested regions. However; its contribution is poorly represented in current generation of land surface hydrological models (LSMs) and catchment-scale rainfall-runoff models. The lack of physical basis of common parameterizations precludes a priori estimation (i.e. without calibration), which is a major drawback for prediction in ungauged basins, or for use in global models. This paper is aimed at deriving physically based parameterizations of the storage-discharge relationship relating to subsurface flow. These parameterizations are derived through a two-step up-scaling procedure: firstly, through simulations with a physically based (Darcian) subsurfacemore » flow model for idealized three dimensional rectangular hillslopes, accounting for within-hillslope random heterogeneity of soil hydraulic properties, and secondly, through subsequent up-scaling to the catchment scale by accounting for between-hillslope and within-catchment heterogeneity of topographic features (e.g., slope). These theoretical simulation results produced parameterizations of the storage-discharge relationship in terms of soil hydraulic properties, topographic slope and their heterogeneities, which were consistent with results of previous studies. Yet, regionalization of the resulting storage-discharge relations across 50 actual catchments in eastern United States, and a comparison of the regionalized results with equivalent empirical results obtained on the basis of analysis of observed streamflow recession curves, revealed a systematic inconsistency. It was found that the difference between the theoretical and empirically derived results could be explained, to first order, by climate in the form of climatic aridity index. This suggests a possible codependence of climate, soils, vegetation and topographic properties, and suggests that subsurface flow parameterization needed for ungauged locations must account for both the physics of flow in heterogeneous landscapes, and the co-dependence of soil and topographic properties with climate, including possibly the mediating role of vegetation.« less

An LES-PBE-PDF approach for modeling particle formation in turbulent reacting flows

NASA Astrophysics Data System (ADS)

Sewerin, Fabian; Rigopoulos, Stelios

2017-10-01

Many chemical and environmental processes involve the formation of a polydispersed particulate phase in a turbulent carrier flow. Frequently, the immersed particles are characterized by an intrinsic property such as the particle size, and the distribution of this property across a sample population is taken as an indicator for the quality of the particulate product or its environmental impact. In the present article, we propose a comprehensive model and an efficient numerical solution scheme for predicting the evolution of the property distribution associated with a polydispersed particulate phase forming in a turbulent reacting flow. Here, the particulate phase is described in terms of the particle number density whose evolution in both physical and particle property space is governed by the population balance equation (PBE). Based on the concept of large eddy simulation (LES), we augment the existing LES-transported probability density function (PDF) approach for fluid phase scalars by the particle number density and obtain a modeled evolution equation for the filtered PDF associated with the instantaneous fluid composition and particle property distribution. This LES-PBE-PDF approach allows us to predict the LES-filtered fluid composition and particle property distribution at each spatial location and point in time without any restriction on the chemical or particle formation kinetics. In view of a numerical solution, we apply the method of Eulerian stochastic fields, invoking an explicit adaptive grid technique in order to discretize the stochastic field equation for the number density in particle property space. In this way, sharp moving features of the particle property distribution can be accurately resolved at a significantly reduced computational cost. As a test case, we consider the condensation of an aerosol in a developed turbulent mixing layer. Our investigation not only demonstrates the predictive capabilities of the LES-PBE-PDF model but also indicates the computational efficiency of the numerical solution scheme.

Novel models on fluid's variable thermo-physical properties for extensive study on convection heat and mass transfer

NASA Astrophysics Data System (ADS)

Shang, De-Yi; Zhong, Liang-Cai

2017-01-01

Our novel models for fluid's variable physical properties are improved and reported systematically in this work for enhancement of theoretical and practical value on study of convection heat and mass transfer. It consists of three models, namely (1) temperature parameter model, (2) polynomial model, and (3) weighted-sum model, respectively for treatment of temperature-dependent physical properties of gases, temperature-dependent physical properties of liquids, and concentration- and temperature-dependent physical properties of vapour-gas mixture. Two related components are proposed, and involved in each model for fluid's variable physical properties. They are basic physic property equations and theoretical similarity equations on physical property factors. The former, as the foundation of the latter, is based on the typical experimental data and physical analysis. The latter is built up by similarity analysis and mathematical derivation based on the former basic physical properties equations. These models are available for smooth simulation and treatment of fluid's variable physical properties for assurance of theoretical and practical value of study on convection of heat and mass transfer. Especially, so far, there has been lack of available study on heat and mass transfer of film condensation convection of vapour-gas mixture, and the wrong heat transfer results existed in widespread studies on the related research topics, due to ignorance of proper consideration of the concentration- and temperature-dependent physical properties of vapour-gas mixture. For resolving such difficult issues, the present novel physical property models have their special advantages.

Towards Characterization, Modeling, and Uncertainty Quantification in Multi-scale Mechanics of Oragnic-rich Shales

NASA Astrophysics Data System (ADS)

Abedi, S.; Mashhadian, M.; Noshadravan, A.

2015-12-01

Increasing the efficiency and sustainability in operation of hydrocarbon recovery from organic-rich shales requires a fundamental understanding of chemomechanical properties of organic-rich shales. This understanding is manifested in form of physics-bases predictive models capable of capturing highly heterogeneous and multi-scale structure of organic-rich shale materials. In this work we present a framework of experimental characterization, micromechanical modeling, and uncertainty quantification that spans from nanoscale to macroscale. Application of experiments such as coupled grid nano-indentation and energy dispersive x-ray spectroscopy and micromechanical modeling attributing the role of organic maturity to the texture of the material, allow us to identify unique clay mechanical properties among different samples that are independent of maturity of shale formations and total organic content. The results can then be used to inform the physically-based multiscale model for organic rich shales consisting of three levels that spans from the scale of elementary building blocks (e.g. clay minerals in clay-dominated formations) of organic rich shales to the scale of the macroscopic inorganic/organic hard/soft inclusion composite. Although this approach is powerful in capturing the effective properties of organic-rich shale in an average sense, it does not account for the uncertainty in compositional and mechanical model parameters. Thus, we take this model one step forward by systematically incorporating the main sources of uncertainty in modeling multiscale behavior of organic-rich shales. In particular we account for the uncertainty in main model parameters at different scales such as porosity, elastic properties and mineralogy mass percent. To that end, we use Maximum Entropy Principle and random matrix theory to construct probabilistic descriptions of model inputs based on available information. The Monte Carlo simulation is then carried out to propagate the uncertainty and consequently construct probabilistic descriptions of properties at multiple length-scales. The combination of experimental characterization and stochastic multi-scale modeling presented in this work improves the robustness in the prediction of essential subsurface parameters in engineering scale.

Indicative capacity of NDVI in predictive mapping of the properties of plow horizons of soils on slopes in the south of Western Siberia

NASA Astrophysics Data System (ADS)

Gopp, N. V.; Nechaeva, T. V.; Savenkov, O. A.; Smirnova, N. V.; Smirnov, V. V.

2017-11-01

The informativeness of NDVI for predictive mapping of the physical and chemical properties of plow horizons of soils on different slope positions within the first (280-310 m a.s.l.) and second (240-280 m a.s.l.) altitudinal steps has been examined. This index is uninformative for mapping soil properties in small hollows, whose factual width is less than the Landsat image resolution (30 m). In regression models, NDVI index explains 52% of variance in the content of humus; 35 and 24% of variance in the contents of total and nitrate nitrogen; 19 and 29% of variance in the contents of total and available phosphorus; 25 and 50% of variance in the contents of exchangeable calcium and manganese; and 30 and 29% of variance in the contents of fine silt and soil water, respectively. On the basis of the models obtained, prognostic maps of the soil properties have been developed. Spatial distribution patterns of NDVI calculated from Landsat 8 images (30-m resolution) serve as the cartographic base and the main indicator of the soil properties. The NDVI values and the contents of humus, physical clay (<0.01 mm) and fine silt particles, total and nitrate nitrogen, total phosphorus, and exchangeable calcium and manganese in the soils of the first altitudinal step are higher than those in the soils of the second altitudinal step. An opposite tendency has been found for the available phosphorus content: in the soils of the second altitudinal step and the hollow, its content is higher than that in the soils of the first altitudinal step by 1.8 and 2.4 times, respectively. Differences in the pH of soil water suspensions, easily available phosphorus, and clay in the soils of the compared topographic positions (first and second altitudinal steps and the hollow) are statistically unreliable.

Unsupervised classification of petroleum Certified Reference Materials and other fuels by chemometric analysis of gas chromatography-mass spectrometry data

PubMed Central

de Carvalho Rocha, Werickson Fortunato; Schantz, Michele M.; Sheen, David A.; Chu, Pamela M.; Lippa, Katrice A.

2017-01-01

As feedstocks transition from conventional oil to unconventional petroleum sources and biomass, it will be necessary to determine whether a particular fuel or fuel blend is suitable for use in engines. Certifying a fuel as safe for use is time-consuming and expensive and must be performed for each new fuel. In principle, suitability of a fuel should be completely determined by its chemical composition. This composition can be probed through use of detailed analytical techniques such as gas chromatography-mass spectroscopy (GC-MS). In traditional analysis, chromatograms would be used to determine the details of the composition. In the approach taken in this paper, the chromatogram is assumed to be entirely representative of the composition of a fuel, and is used directly as the input to an algorithm in order to develop a model that is predictive of a fuel's suitability. When a new fuel is proposed for service, its suitability for any application could then be ascertained by using this model to compare its chromatogram with those of the fuels already known to be suitable for that application. In this paper, we lay the mathematical and informatics groundwork for a predictive model of hydrocarbon properties. The objective of this work was to develop a reliable model for unsupervised classification of the hydrocarbons as a prelude to developing a predictive model of their engine-relevant physical and chemical properties. A set of hydrocarbons including biodiesel fuels, gasoline, highway and marine diesel fuels, and crude oils was collected and GC-MS profiles obtained. These profiles were then analyzed using multi-way principal components analysis (MPCA), principal factors analysis (PARAFAC), and a self-organizing map (SOM), which is a kind of artificial neural network. It was found that, while MPCA and PARAFAC were able to recover descriptive models of the fuels, their linear nature obscured some of the finer physical details due to the widely varying composition of the fuels. The SOM was able to find a descriptive classification model which has the potential for practical recognition and perhaps prediction of fuel properties. PMID:28603295

Seismic Velocity Gradients Across the Transition Zone

NASA Astrophysics Data System (ADS)

Escalante, C.; Cammarano, F.; de Koker, N.; Piazzoni, A.; Wang, Y.; Marone, F.; Dalton, C.; Romanowicz, B.

2006-12-01

One-D elastic velocity models derived from mineral physics do a notoriously poor job at predicting the velocity gradients in the upper mantle transition zone, as well as some other features of models derived from seismological data. During the 2006 CIDER summer program, we computed Vs and Vp velocity profiles in the upper mantle based on three different mineral physics approaches: two approaches based on the minimization of Gibbs Free Energy (Stixrude and Lithgow-Bertelloni, 2005; Piazzoni et al., 2006) and one obtained by using experimentally determined phase diagrams (Weidner and Wang, 1998). The profiles were compared by assuming a vertical temperature profile and two end-member compositional models, the pyrolite model of Ringwood (1979) and the piclogite model of Anderson and Bass (1984). The predicted seismic profiles, which are significantly different from each other, primarily due to different choices of properties of single minerals and their extrapolation with temperature, are tested against a global dataset of P and S travel times and spheroidal and toroidal normal mode eigenfrequencies. All the models derived using a potential temperature of 1600K predict seismic velocities that are too slow in the upper mantle, suggesting the need to use a colder geotherm. The velocity gradient in the transition zone is somewhat better for piclogite than for pyrolite, possibly indicating the need to increase Ca content. The presence of stagnant slabs in the transition zone is a possible explanation for the need for 1) colder temperature and 2) increased Ca content. Future improvements in seismic profiles obtained from mineral physics will arise from better knowledge of elastic properties of upper mantle constituents and aggregates at high temperature and pressure, a better understanding of differences between thermodynamic models, and possibly the effect of water through and on Q. High resolution seismic constraints on velocity jumps at 400 and 660 km also need to be included. earth.org/2006/workshop.html

Characterization of maximally random jammed sphere packings. III. Transport and electromagnetic properties via correlation functions

NASA Astrophysics Data System (ADS)

Klatt, Michael A.; Torquato, Salvatore

2018-01-01

In the first two papers of this series, we characterized the structure of maximally random jammed (MRJ) sphere packings across length scales by computing a variety of different correlation functions, spectral functions, hole probabilities, and local density fluctuations. From the remarkable structural features of the MRJ packings, especially its disordered hyperuniformity, exceptional physical properties can be expected. Here we employ these structural descriptors to estimate effective transport and electromagnetic properties via rigorous bounds, exact expansions, and accurate analytical approximation formulas. These property formulas include interfacial bounds as well as universal scaling laws for the mean survival time and the fluid permeability. We also estimate the principal relaxation time associated with Brownian motion among perfectly absorbing traps. For the propagation of electromagnetic waves in the long-wavelength limit, we show that a dispersion of dielectric MRJ spheres within a matrix of another dielectric material forms, to a very good approximation, a dissipationless disordered and isotropic two-phase medium for any phase dielectric contrast ratio. We compare the effective properties of the MRJ sphere packings to those of overlapping spheres, equilibrium hard-sphere packings, and lattices of hard spheres. Moreover, we generalize results to micro- and macroscopically anisotropic packings of spheroids with tensorial effective properties. The analytic bounds predict the qualitative trend in the physical properties associated with these structures, which provides guidance to more time-consuming simulations and experiments. They especially provide impetus for experiments to design materials with unique bulk properties resulting from hyperuniformity, including structural-color and color-sensing applications.

Predictive modeling of infrared detectors and material systems

NASA Astrophysics Data System (ADS)

Pinkie, Benjamin

Detectors sensitive to thermal and reflected infrared radiation are widely used for night-vision, communications, thermography, and object tracking among other military, industrial, and commercial applications. System requirements for the next generation of ultra-high-performance infrared detectors call for increased functionality such as large formats (> 4K HD) with wide field-of-view, multispectral sensitivity, and on-chip processing. Due to the low yield of infrared material processing, the development of these next-generation technologies has become prohibitively costly and time consuming. In this work, it will be shown that physics-based numerical models can be applied to predictively simulate infrared detector arrays of current technological interest. The models can be used to a priori estimate detector characteristics, intelligently design detector architectures, and assist in the analysis and interpretation of existing systems. This dissertation develops a multi-scale simulation model which evaluates the physics of infrared systems from the atomic (material properties and electronic structure) to systems level (modulation transfer function, dense array effects). The framework is used to determine the electronic structure of several infrared materials, optimize the design of a two-color back-to-back HgCdTe photodiode, investigate a predicted failure mechanism for next-generation arrays, and predict the systems-level measurables of a number of detector architectures.

Search for New Physics in Top Quark Production and Upgrade of the CMS Hadron Calorimeter

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

Yumiceva, Francisco

2016-10-07

Our goal is to measure precisely the properties of the heaviest subatomic particle ever discovered, the top quark. In the proton-proton collisions at the LHC, top quarks are produced copiously. The largest set of top quarks recorded by the CMS detector make it an ideal laboratory to measure properties such as its mass and the rate at which pair of top quarks are produced in association with energetic photons. Quantum electrodynamics, or QED, describes the emission of light by charged particles and is the most precise physics theory ever devised. Typically this means light emitted by electrons, but any chargedmore » particles will do, such as the top quark. Studies of the light-emitting properties of top quarks help us to refine our current theoretical predictions at the finest level, and provide additional tools to study in more detail the recently discovered Higgs boson particle. However, during this process, the studies may reveal interesting features not yet observed. Deviations from the standard predictions would be a strong sign of something entirely new. These new physics theories are motivated to answer the current big mysteries in the universe such as what is the nature of mass or what is dark matter. As the LHC increases the collision energy and its luminosity, the detectors need to be improved to cope with these high-luminosity scenarios. New sensors will be installed in the hadron calorimeter detectors along with new front and end electronics at the end of 2016. We are testing and calibrating the new front-end readout electronics that will allow us to have more options to reduce the noise on these detectors. In order to do this calibration, we have developed a system that can inject electric charge in the full range of the charge integrator chip, the QIE ASICs.« less

ACTRIS Aerosol, Clouds and Trace Gases Research Infrastructure

NASA Astrophysics Data System (ADS)

Pappalardo, Gelsomina

2018-04-01

The Aerosols, Clouds and Trace gases Research Infrastructure (ACTRIS) is a distributed infrastructure dedicated to high-quality observation of aerosols, clouds, trace gases and exploration of their interactions. It will deliver precision data, services and procedures regarding the 4D variability of clouds, short-lived atmospheric species and the physical, optical and chemical properties of aerosols to improve the current capacity to analyse, understand and predict past, current and future evolution of the atmospheric environment.

Integrated Earth System Model (iESM)

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

Thornton, Peter Edmond; Mao, Jiafu; Shi, Xiaoying

2016-12-02

The iESM is a simulation code that represents the physical and biological aspects of Earth's climate system, and also includes the macro-economic and demographic properties of human societies. The human aspect of the simulation code is focused in particular on the effects of human activities on land use and land cover change, but also includes aspects such as energy economies. The time frame for predictions with iESM is approximately 1970 through 2100.

Computer Simulations: A Tool to Predict Experimental Parameters with Cold Atoms

DTIC Science & Technology

2013-04-01

Department of the Army position unless so designated by other authorized documents. Citation of manufacturer’s or trade names does not constitute an...specifically designed to work with cold atom systems and atom chips, and is already able to compute their key properties. We simulate our experimental...also allows one to choose different physics and define the interdependencies between them. It is not specifically designed for cold atom systems or

Gaussian process model for extrapolation of scattering observables for complex molecules: From benzene to benzonitrile

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

Cui, Jie; Krems, Roman V.; Li, Zhiying

2015-10-21

We consider a problem of extrapolating the collision properties of a large polyatomic molecule A–H to make predictions of the dynamical properties for another molecule related to A–H by the substitution of the H atom with a small molecular group X, without explicitly computing the potential energy surface for A–X. We assume that the effect of the −H →−X substitution is embodied in a multidimensional function with unknown parameters characterizing the change of the potential energy surface. We propose to apply the Gaussian Process model to determine the dependence of the dynamical observables on the unknown parameters. This can bemore » used to produce an interval of the observable values which corresponds to physical variations of the potential parameters. We show that the Gaussian Process model combined with classical trajectory calculations can be used to obtain the dependence of the cross sections for collisions of C{sub 6}H{sub 5}CN with He on the unknown parameters describing the interaction of the He atom with the CN fragment of the molecule. The unknown parameters are then varied within physically reasonable ranges to produce a prediction uncertainty of the cross sections. The results are normalized to the cross sections for He — C{sub 6}H{sub 6} collisions obtained from quantum scattering calculations in order to provide a prediction interval of the thermally averaged cross sections for collisions of C{sub 6}H{sub 5}CN with He.« less

Micro-computed tomography pore-scale study of flow in porous media: Effect of voxel resolution

NASA Astrophysics Data System (ADS)

Shah, S. M.; Gray, F.; Crawshaw, J. P.; Boek, E. S.

2016-09-01

A fundamental understanding of flow in porous media at the pore-scale is necessary to be able to upscale average displacement processes from core to reservoir scale. The study of fluid flow in porous media at the pore-scale consists of two key procedures: Imaging - reconstruction of three-dimensional (3D) pore space images; and modelling such as with single and two-phase flow simulations with Lattice-Boltzmann (LB) or Pore-Network (PN) Modelling. Here we analyse pore-scale results to predict petrophysical properties such as porosity, single-phase permeability and multi-phase properties at different length scales. The fundamental issue is to understand the image resolution dependency of transport properties, in order to up-scale the flow physics from pore to core scale. In this work, we use a high resolution micro-computed tomography (micro-CT) scanner to image and reconstruct three dimensional pore-scale images of five sandstones (Bentheimer, Berea, Clashach, Doddington and Stainton) and five complex carbonates (Ketton, Estaillades, Middle Eastern sample 3, Middle Eastern sample 5 and Indiana Limestone 1) at four different voxel resolutions (4.4 μm, 6.2 μm, 8.3 μm and 10.2 μm), scanning the same physical field of view. Implementing three phase segmentation (macro-pore phase, intermediate phase and grain phase) on pore-scale images helps to understand the importance of connected macro-porosity in the fluid flow for the samples studied. We then compute the petrophysical properties for all the samples using PN and LB simulations in order to study the influence of voxel resolution on petrophysical properties. We then introduce a numerical coarsening scheme which is used to coarsen a high voxel resolution image (4.4 μm) to lower resolutions (6.2 μm, 8.3 μm and 10.2 μm) and study the impact of coarsening data on macroscopic and multi-phase properties. Numerical coarsening of high resolution data is found to be superior to using a lower resolution scan because it avoids the problem of partial volume effects and reduces the scaling effect by preserving the pore-space properties influencing the transport properties. This is evidently compared in this study by predicting several pore network properties such as number of pores and throats, average pore and throat radius and coordination number for both scan based analysis and numerical coarsened data.

Ocean-Science Mission Needs: Real-Time AUV Data for Command, Control, and Model Inputs

NASA Technical Reports Server (NTRS)

Carder, Kendall L.; Costello, D. K.; Warrior, H.; Langebrake, L. C.; Hou, W.; Patten, J. T.; Kaltenbacher, E.

2001-01-01

Predictive models for tides, hydrodynamics, and bio-optical properties affecting the visibility and buoyancy of coastal waters are needed to evaluate the safety of personnel and equipment engaged in maritime operations under potentially hazardous conditions. Predicted currents can be markedly different for two-layer systems affected by terrestrial runoff than for well-mixed conditions because the layering decouples the surface and bottom Ekman layers and rectifies the current response to oscillatory upwelling-and downwelling-favorable winds. Standard ocean models (e.g. Princeton Ocean Model) require initial-and boundary data on the physical and optical properties of the multilayered water column to provide accurate simulations of heat budgets and circulation. Two observational systems are designed to measure vertically structured conditions on the West Florida Shelf (WFS): a tethered buoy network and an autonomous underwater vehicle (AUV) observational system. The AUV system is described with a focus on the observational systems that challenge or limit the communications command and control network for various types of measurement programs. These include vertical oscillatory missions on shelf transects to observe the optical and hydrographic properties of the water column, and bottom-following missions for measuring the bottom albedo. Models of light propagation, absorption, and conversion to heat as well as determination of the buoyancy terms for physical models require these measurements. High data rates associated with video bottom imagery are the most challenging for the real-time, command and control communications system, but they are met through a combination of loss-less and lossy data-compression methods, depending upon the data-rate of the radio links.

Emergent chirality in the electric polarization texture of titanate superlattices.

PubMed

Shafer, Padraic; García-Fernández, Pablo; Aguado-Puente, Pablo; Damodaran, Anoop R; Yadav, Ajay K; Nelson, Christopher T; Hsu, Shang-Lin; Wojdeł, Jacek C; Íñiguez, Jorge; Martin, Lane W; Arenholz, Elke; Junquera, Javier; Ramesh, Ramamoorthy

2018-01-30

Chirality is a geometrical property by which an object is not superimposable onto its mirror image, thereby imparting a handedness. Chirality determines many important properties in nature-from the strength of the weak interactions according to the electroweak theory in particle physics to the binding of enzymes with naturally occurring amino acids or sugars, reactions that are fundamental for life. In condensed matter physics, the prediction of topologically protected magnetic skyrmions and related spin textures in chiral magnets has stimulated significant research. If the magnetic dipoles were replaced by their electrical counterparts, then electrically controllable chiral devices could be designed. Complex oxide BaTiO 3 /SrTiO 3 nanocomposites and PbTiO 3 /SrTiO 3 superlattices are perfect candidates, since "polar vortices," in which a continuous rotation of ferroelectric polarization spontaneously forms, have been recently discovered. Using resonant soft X-ray diffraction, we report the observation of a strong circular dichroism from the interaction between circularly polarized light and the chiral electric polarization texture that emerges in PbTiO 3 /SrTiO 3 superlattices. This hallmark of chirality is explained by a helical rotation of electric polarization that second-principles simulations predict to reside within complex 3D polarization textures comprising ordered topological line defects. The handedness of the texture can be topologically characterized by the sign of the helicity number of the chiral line defects. This coupling between the optical and novel polar properties could be exploited to encode chiral signatures into photon or electron beams for information processing.

Recent advances in chemical functionalization of nanoparticles with biomolecules for analytical applications.

PubMed

Oh, Ju-Hwan; Park, Do Hyun; Joo, Jang Ho; Lee, Jae-Seung

2015-11-01

The recent synthetic development of a variety of nanoparticles has led to their widespread application in diagnostics and therapeutics. In particular, the controlled size and shape of nanoparticles precisely determine their unique chemical and physical properties, which is highly attractive for accurate analysis of given systems. In addition to efforts toward controlling the synthesis and properties of nanoparticles, the surface functionalization of nanoparticles with biomolecules has been intensively investigated since the mid-1990s. The complicated yet programmable properties of biomolecules have proved to substantially enhance and enrich the novel functions of nanoparticles to achieve "smart" nanoparticle materials. In this review, the advances in chemical functionalization of four types of representative nanoparticle with DNA and protein molecules in the past five years are critically reviewed, and their future trends are predicted.

Enhanced superconductivity in aluminum-based hyperbolic metamaterials

NASA Astrophysics Data System (ADS)

Smolyaninova, Vera; Jensen, Christopher; Zimmerman, William; Prestigiacomo, Joseph; Osofsky, Michael; Kim, Heungsoo; Bassim, Nabil; Xing, Zhen; Qazilbash, Mumtaz; Smolyaninov, Igor

One of the most important goals of condensed matter physics is materials by design, i.e. the ability to reliably predict and design materials with a set of desired properties. A striking example is the deterministic enhancement of the superconducting properties of materials. Recent experiments have demonstrated that the metamaterial approach is capable of achieving this goal, such as tripling the critical temperature Tc in Al-Al2O3 epsilon near zero (ENZ) core-shell metamaterial superconductors. Here, we demonstrate that an Al/Al2O3 hyperbolic metamaterial geometry is capable of a similar Tc enhancement, while having superior transport and magnetic properties compared to the core-shell metamaterial superconductors. This work was supported in part by NSF Grant DMR-1104676 and the School of Emerging Technologies at Towson University.

Interlayer Coupling and Gate-Tunable Excitons in Transition Metal Dichalcogenide Heterostructures

DOE PAGES

Gao, Shiyuan; Yang, Li; Spataru, Catalin Dan

2017-11-22

Bilayer van der Waals (vdW) heterostructures such as MoS 2/WS 2 and MoSe 2/WSe 2 have attracted much attention recently, particularly because of their type II band alignments and the formation of interlayer exciton as the lowest-energy excitonic state. In this work, we calculate the electronic and optical properties of such heterostructures with the first-principles GW+Bethe–Salpeter Equation (BSE) method and reveal the important role of interlayer coupling in deciding the excited-state properties, including the band alignment and excitonic properties. Our calculation shows that due to the interlayer coupling, the low energy excitons can be widely tuned by a vertical gatemore » field. In particular, the dipole oscillator strength and radiative lifetime of the lowest energy exciton in these bilayer heterostructures is varied by over an order of magnitude within a practical external gate field. We also build a simple model that captures the essential physics behind this tunability and allows the extension of the ab initio results to a large range of electric fields. In conclusion, our work clarifies the physical picture of interlayer excitons in bilayer vdW heterostructures and predicts a wide range of gate-tunable excited-state properties of 2D optoelectronic devices.« less

Interrogating selectivity in catalysis using molecular vibrations

NASA Astrophysics Data System (ADS)

Milo, Anat; Bess, Elizabeth N.; Sigman, Matthew S.

2014-03-01

The delineation of molecular properties that underlie reactivity and selectivity is at the core of physical organic chemistry, and this knowledge can be used to inform the design of improved synthetic methods or identify new chemical transformations. For this reason, the mathematical representation of properties affecting reactivity and selectivity trends, that is, molecular parameters, is paramount. Correlations produced by equating these molecular parameters with experimental outcomes are often defined as free-energy relationships and can be used to evaluate the origin of selectivity and to generate new, experimentally testable hypotheses. The premise behind successful correlations of this type is that a systematically perturbed molecular property affects a transition-state interaction between the catalyst, substrate and any reaction components involved in the determination of selectivity. Classic physical organic molecular descriptors, such as Hammett, Taft or Charton parameters, seek to independently probe isolated electronic or steric effects. However, these parameters cannot address simultaneous, non-additive variations to more than one molecular property, which limits their utility. Here we report a parameter system based on the vibrational response of a molecule to infrared radiation that can be used to mathematically model and predict selectivity trends for reactions with interlinked steric and electronic effects at positions of interest. The disclosed parameter system is mechanistically derived and should find broad use in the study of chemical and biological systems.

Physical stability and recrystallization kinetics of amorphous ibipinabant drug product by fourier transform raman spectroscopy.

PubMed

Sinclair, Wayne; Leane, Michael; Clarke, Graham; Dennis, Andrew; Tobyn, Mike; Timmins, Peter

2011-11-01

The solid-state physical stability and recrystallization kinetics during storage stability are described for an amorphous solid dispersed drug substance, ibipinabant, at a low concentration (1.0%, w/w) in a solid oral dosage form (tablet). The recrystallization behavior of the amorphous ibipinabant-polyvinylpyrrolidone solid dispersion in the tablet product was characterized by Fourier transform (FT) Raman spectroscopy. A partial least-square analysis used for multivariate calibration based on Raman spectra was developed and validated to detect less than 5% (w/w) of the crystalline form (equivalent to less than 0.05% of the total mass of the tablet). The method provided reliable and highly accurate predictive crystallinity assessments after exposure to a variety of stability storage conditions. It was determined that exposure to moisture had a significant impact on the crystallinity of amorphous ibipinabant. The information provided by the method has potential utility for predictive physical stability assessments. Dissolution testing demonstrated that the predicted crystallinity had a direct correlation with this physical property of the drug product. Recrystallization kinetics was measured using FT Raman spectroscopy for the solid dispersion from the tablet product stored at controlled temperature and relative humidity. The measurements were evaluated by application of the Johnson-Mehl-Avrami (JMA) kinetic model to determine recrystallization rate constants and Avrami exponent (n = 2). The analysis showed that the JMA equation could describe the process very well, and indicated that the recrystallization kinetics observed was a two-step process with an induction period (nucleation) followed by rod-like crystal growth. Copyright © 2011 Wiley-Liss, Inc.

Satellite Observations and Chemistry Climate Models - A Meandering Path Towards Better Predictions

NASA Technical Reports Server (NTRS)

Douglass, Anne R.

2011-01-01

Knowledge of the chemical and dynamical processes that control the stratospheric ozone layer has grown rapidly since the 1970s, when ideas that depletion of the ozone layer due to human activity were put forth. The concept of ozone depletion due to anthropogenic chlorine increase is simple; quantification of the effect is much more difficult. The future of stratospheric ozone is complicated because ozone is expected to increase for two reasons: the slow decrease in anthropogenic chlorine due to the Montreal Protocol and its amendments and stratospheric cooling caused by increases in carbon dioxide and other greenhouse gases. Prediction of future ozone levels requires three-dimensional models that represent physical, photochemical and radiative processes, i.e., chemistry climate models (CCMs). While laboratory kinetic and photochemical data are necessary inputs for a CCM, atmospheric measurements are needed both to reveal physical and chemical processes and for comparison with simulations to test the conceptual model that CCMs represent. Global measurements are available from various satellites including but not limited to the LIMS and TOMS instruments on Nimbus 7 (1979 - 1993), and various instruments on the Upper Atmosphere Research Satellite (1991 - 2005), Envisat (2002 - ongoing), Sci-Sat (2003 - ongoing) and Aura (2004 - ongoing). Every successful satellite instrument requires a physical concept for the measurement, knowledge of physical chemical properties of the molecules to be measured, and stellar engineering to design an instrument that will survive launch and operate for years with no opportunity for repair but providing enough information that trend information can be separated from any instrument change. The on-going challenge is to use observations to decrease uncertainty in prediction. This talk will focus on two applications. The first considers transport diagnostics and implications for prediction of the eventual demise of the Antarctic ozone hole. The second focuses on the upper stratosphere, where ozone is predicted to increase both due to chlorine decrease and due to temperature decrease expected as a result of increased concentrations Of CO2 and other greenhouse gases. Both applications show how diagnostics developed from global observations are being used to explain why the ozone response varies among CCM predictions for stratospheric ozone in the 21st century.

Models for selecting GMA Welding Parameters for Improving Mechanical Properties of Weld Joints

NASA Astrophysics Data System (ADS)

Srinivasa Rao, P.; Ramachandran, Pragash; Jebaraj, S.

2016-02-01

During the process of Gas Metal Arc (GMAW) welding, the weld joints mechanical properties are influenced by the welding parameters such as welding current and arc voltage. These parameters directly will influence the quality of the weld in terms of mechanical properties. Even small variation in any of the cited parameters may have an important effect on depth of penetration and on joint strength. In this study, S45C Constructional Steel is taken as the base metal to be tested using the parameters wire feed rate, voltage and type of shielding gas. Physical properties considered in the present study are tensile strength and hardness. The testing of weld specimen is carried out as per ASTM Standards. Mathematical models to predict the tensile strength and depth of penetration of weld joint have been developed by regression analysis using the experimental results.

Assessing Participation in Community-Based Physical Activity Programs in Brazil

PubMed Central

REIS, RODRIGO S.; YAN, YAN; PARRA, DIANA C.; BROWNSON, ROSS C.

2015-01-01

Purpose This study aimed to develop and validate a risk prediction model to examine the characteristics that are associated with participation in community-based physical activity programs in Brazil. Methods We used pooled data from three surveys conducted from 2007 to 2009 in state capitals of Brazil with 6166 adults. A risk prediction model was built considering program participation as an outcome. The predictive accuracy of the model was quantified through discrimination (C statistic) and calibration (Brier score) properties. Bootstrapping methods were used to validate the predictive accuracy of the final model. Results The final model showed sex (women: odds ratio [OR] = 3.18, 95% confidence interval [CI] = 2.14–4.71), having less than high school degree (OR = 1.71, 95% CI = 1.16–2.53), reporting a good health (OR = 1.58, 95% CI = 1.02–2.24) or very good/excellent health (OR = 1.62, 95% CI = 1.05–2.51), having any comorbidity (OR = 1.74, 95% CI = 1.26–2.39), and perceiving the environment as safe to walk at night (OR = 1.59, 95% CI = 1.18–2.15) as predictors of participation in physical activity programs. Accuracy indices were adequate (C index = 0.778, Brier score = 0.031) and similar to those obtained from bootstrapping (C index = 0.792, Brier score = 0.030). Conclusions Sociodemographic and health characteristics as well as perceptions of the environment are strong predictors of participation in community-based programs in selected cities of Brazil. PMID:23846162

Bio-AIMS Collection of Chemoinformatics Web Tools based on Molecular Graph Information and Artificial Intelligence Models.

PubMed

Munteanu, Cristian R; Gonzalez-Diaz, Humberto; Garcia, Rafael; Loza, Mabel; Pazos, Alejandro

2015-01-01

The molecular information encoding into molecular descriptors is the first step into in silico Chemoinformatics methods in Drug Design. The Machine Learning methods are a complex solution to find prediction models for specific biological properties of molecules. These models connect the molecular structure information such as atom connectivity (molecular graphs) or physical-chemical properties of an atom/group of atoms to the molecular activity (Quantitative Structure - Activity Relationship, QSAR). Due to the complexity of the proteins, the prediction of their activity is a complicated task and the interpretation of the models is more difficult. The current review presents a series of 11 prediction models for proteins, implemented as free Web tools on an Artificial Intelligence Model Server in Biosciences, Bio-AIMS (http://bio-aims.udc.es/TargetPred.php). Six tools predict protein activity, two models evaluate drug - protein target interactions and the other three calculate protein - protein interactions. The input information is based on the protein 3D structure for nine models, 1D peptide amino acid sequence for three tools and drug SMILES formulas for two servers. The molecular graph descriptor-based Machine Learning models could be useful tools for in silico screening of new peptides/proteins as future drug targets for specific treatments.

Predicting crystal structures and properties of matter under extreme conditions via quantum mechanics: The pressure is on

DOE PAGES

Zurek, Eva; Grochala, Wojciech

2014-11-27

Experimental studies of compressed matter are now routinely conducted at pressures exceeding 1 mln atm (100 GPa) and occasionally they even surpass 10 mln atm (1 TPa). The structure and properties of solids that have been so significantly squeezed differ considerably from those know at ambient pressures (1 atm), often times leading to new and unexpected physics. Chemical reactivity is also substantially altered in the extreme pressure regime. In this feature paper we describe how synergy between theory and experiment can pave the road towards new experimental discoveries. Because chemical rules-of-thumb established at 1 atm often fail to predict themore » structures of solids under high pressure, automated crystal structure prediction (CSP) methods have been increasingly employed. After outlining the most important CSP techniques, we showcase a few examples from the recent literature that exemplify just how useful theory can be as an aid in the interpretation of experimental data, describe exciting theoretical predictions that are guiding experiment, and discuss when the computational methods that are currently routinely employed fail. Lastly, we forecast important problems that will be targeted by theory as theoretical methods undergo rapid development, along with the simultaneous increase of computational power.« less

41 CFR 109-1.5110 - Physical inventories of personal property.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 41 Public Contracts and Property Management 3 2010-07-01 2010-07-01 false Physical inventories of...-INTRODUCTION 1.51-Personal Property Management Standards and Practices § 109-1.5110 Physical inventories of personal property. (a) Physical inventories of those categories of personal property as specified in...

41 CFR 109-1.5110 - Physical inventories of personal property.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 41 Public Contracts and Property Management 3 2014-01-01 2014-01-01 false Physical inventories of...-INTRODUCTION 1.51-Personal Property Management Standards and Practices § 109-1.5110 Physical inventories of personal property. (a) Physical inventories of those categories of personal property as specified in...

41 CFR 109-1.5110 - Physical inventories of personal property.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 41 Public Contracts and Property Management 3 2012-01-01 2012-01-01 false Physical inventories of...-INTRODUCTION 1.51-Personal Property Management Standards and Practices § 109-1.5110 Physical inventories of personal property. (a) Physical inventories of those categories of personal property as specified in...

41 CFR 109-1.5110 - Physical inventories of personal property.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 41 Public Contracts and Property Management 3 2011-01-01 2011-01-01 false Physical inventories of...-INTRODUCTION 1.51-Personal Property Management Standards and Practices § 109-1.5110 Physical inventories of personal property. (a) Physical inventories of those categories of personal property as specified in...

41 CFR 109-1.5110 - Physical inventories of personal property.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 41 Public Contracts and Property Management 3 2013-07-01 2013-07-01 false Physical inventories of...-INTRODUCTION 1.51-Personal Property Management Standards and Practices § 109-1.5110 Physical inventories of personal property. (a) Physical inventories of those categories of personal property as specified in...

Understanding the physical metallurgy of the CoCrFeMnNi high-entropy alloy: an atomistic simulation study

NASA Astrophysics Data System (ADS)

Choi, Won-Mi; Jo, Yong Hee; Sohn, Seok Su; Lee, Sunghak; Lee, Byeong-Joo

2018-01-01

Although high-entropy alloys (HEAs) are attracting interest, the physical metallurgical mechanisms related to their properties have mostly not been clarified, and this limits wider industrial applications, in addition to the high alloy costs. We clarify the physical metallurgical reasons for the materials phenomena (sluggish diffusion and micro-twining at cryogenic temperatures) and investigate the effect of individual elements on solid solution hardening for the equiatomic CoCrFeMnNi HEA based on atomistic simulations (Monte Carlo, molecular dynamics and molecular statics). A significant number of stable vacant lattice sites with high migration energy barriers exists and is thought to cause the sluggish diffusion. We predict that the hexagonal close-packed (hcp) structure is more stable than the face-centered cubic (fcc) structure at 0 K, which we propose as the fundamental reason for the micro-twinning at cryogenic temperatures. The alloying effect on the critical resolved shear stress (CRSS) is well predicted by the atomistic simulation, used for a design of non-equiatomic fcc HEAs with improved strength, and is experimentally verified. This study demonstrates the applicability of the proposed atomistic approach combined with a thermodynamic calculation technique to a computational design of advanced HEAs.

Nicholas Metropolis Award Talk for Outstanding Doctoral Thesis Work in Computational Physics: Computational biophysics and multiscale modeling of blood cells and blood flow in health and disease

NASA Astrophysics Data System (ADS)

Fedosov, Dmitry

2011-03-01

Computational biophysics is a large and rapidly growing area of computational physics. In this talk, we will focus on a number of biophysical problems related to blood cells and blood flow in health and disease. Blood flow plays a fundamental role in a wide range of physiological processes and pathologies in the organism. To understand and, if necessary, manipulate the course of these processes it is essential to investigate blood flow under realistic conditions including deformability of blood cells, their interactions, and behavior in the complex microvascular network. Using a multiscale cell model we are able to accurately capture red blood cell mechanics, rheology, and dynamics in agreement with a number of single cell experiments. Further, this validated model yields accurate predictions of the blood rheological properties, cell migration, cell-free layer, and hemodynamic resistance in microvessels. In addition, we investigate blood related changes in malaria, which include a considerable stiffening of red blood cells and their cytoadherence to endothelium. For these biophysical problems computational modeling is able to provide new physical insights and capabilities for quantitative predictions of blood flow in health and disease.

Optimized Materials From First Principles Simulations: Are We There Yet?

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

Galli, G; Gygi, F

2005-07-26

In the past thirty years, the use of scientific computing has become pervasive in all disciplines: collection and interpretation of most experimental data is carried out using computers, and physical models in computable form, with various degrees of complexity and sophistication, are utilized in all fields of science. However, full prediction of physical and chemical phenomena based on the basic laws of Nature, using computer simulations, is a revolution still in the making, and it involves some formidable theoretical and computational challenges. We illustrate the progress and successes obtained in recent years in predicting fundamental properties of materials in condensedmore » phases and at the nanoscale, using ab-initio, quantum simulations. We also discuss open issues related to the validation of the approximate, first principles theories used in large scale simulations, and the resulting complex interplay between computation and experiment. Finally, we describe some applications, with focus on nanostructures and liquids, both at ambient and under extreme conditions.« less

A quality by design approach to investigate the effect of mannitol and dicalcium phosphate qualities on roll compaction.

PubMed

Souihi, Nabil; Dumarey, Melanie; Wikström, Håkan; Tajarobi, Pirjo; Fransson, Magnus; Svensson, Olof; Josefson, Mats; Trygg, Johan

2013-04-15

Roll compaction is a continuous process for solid dosage form manufacturing increasingly popular within pharmaceutical industry. Although roll compaction has become an established technique for dry granulation, the influence of material properties is still not fully understood. In this study, a quality by design (QbD) approach was utilized, not only to understand the influence of different qualities of mannitol and dicalcium phosphate (DCP), but also to predict critical quality attributes of the drug product based solely on the material properties of that filler. By describing each filler quality in terms of several representative physical properties, orthogonal projections to latent structures (OPLS) was used to understand and predict how those properties affected drug product intermediates as well as critical quality attributes of the final drug product. These models were then validated by predicting product attributes for filler qualities not used in the model construction. The results of this study confirmed that the tensile strength reduction, known to affect plastic materials when roll compacted, is not prominent when using brittle materials. Some qualities of these fillers actually demonstrated improved compactability following roll compaction. While direct compression qualities are frequently used for roll compacted drug products because of their excellent flowability and good compaction properties, this study revealed that granules from these qualities were more poor flowing than the corresponding powder blends, which was not seen for granules from traditional qualities. The QbD approach used in this study could be extended beyond fillers. Thus any new compound/ingredient would first be characterized and then suitable formulation characteristics could be determined in silico, without running any additional experiments. Copyright © 2013 Elsevier B.V. All rights reserved.

New 21 cm Power Spectrum Upper Limits From PAPER II: Constraints on IGM Properties at z = 7.7

NASA Astrophysics Data System (ADS)

Pober, Jonathan; Ali, Zaki; Parsons, Aaron; Paper Team

2015-01-01

Using a simulation-based framework, we interpret the power spectrum measurements from PAPER of Ali et al. in the context of IGM physics at z = 7.7. A cold IGM will result in strong 21 cm absorption relative to the CMB and leads to a 21 cm fluctuation power spectrum that can exceed 3000 mK^2. The new PAPER measurements allow us to rule out extreme cold IGM models, placing a lower limit on the physical temperature of the IGM. We also compare this limit with a calculation for the predicted heating from the currently observed galaxy population at z = 8.

Turbulence

NASA Astrophysics Data System (ADS)

Frisch, Uriel

1996-01-01

Written five centuries after the first studies of Leonardo da Vinci and half a century after A.N. Kolmogorov's first attempt to predict the properties of flow, this textbook presents a modern account of turbulence, one of the greatest challenges in physics. "Fully developed turbulence" is ubiquitous in both cosmic and natural environments, in engineering applications and in everyday life. Elementary presentations of dynamical systems ideas, probabilistic methods (including the theory of large deviations) and fractal geometry make this a self-contained textbook. This is the first book on turbulence to use modern ideas from chaos and symmetry breaking. The book will appeal to first-year graduate students in mathematics, physics, astrophysics, geosciences and engineering, as well as professional scientists and engineers.

Aggregate stability as an indicator of soil erodibility and soil physical quality: review and perspectives

NASA Astrophysics Data System (ADS)

Le Bissonnais, Yves; Chenu, Claire; Darboux, Frédéric; Duval, Odile; Legout, Cédric; Leguédois, Sophie; Gumiere, Silvio

2010-05-01

Aggregate breakdown due to water and rain action may cause surface crusting, slumping, a reduction of infiltration and interrill erosion. Aggregate stability determines the capacity of aggregates to resist the effects of water and rainfall. In this paper, we evaluated and reviewed the relevance of an aggregate stability measurement to characterize soil physical properties as well as to analyse the processes involved in these properties. Stability measurement assesses the sensitivity of soil aggregates to various basic disaggregation mechanisms such as slaking, differential swelling, dispersion and mechanical breakdown. It has been showed that aggregate size distributions of structural stability tests matched the size distributions of eroded aggregates under rainfall simulations and that erosion amount was well predicted using aggregate stability indexes. It means stability tests could be used to estimate both the erodibility and the size fractions that are available for crust formation and erosion processes. Several studies showed that organic matter was one of the main soil properties affecting soil stability. However, it has also been showed that aggregate stability of a given soil could vary within a year or between years. The factors controlling such changes have still to be specified. Aggregate stability appears therefore as a complex property, depending both on permanent soil characteristics and on dynamic factors such as the crusting stage, the climate and the biological activity. Despite, and may be, because of this complexity, aggregate stability seems an integrative and powerful indicator of soil physical quality. Future research efforts should look at the causes of short-term changes of structural stability, in order to fully understand all its aspects.

Miscellaneous Topics in Computer-Aided Drug Design: Synthetic Accessibility and GPU Computing, and Other Topics.

PubMed

Fukunishi, Yoshifumi; Mashimo, Tadaaki; Misoo, Kiyotaka; Wakabayashi, Yoshinori; Miyaki, Toshiaki; Ohta, Seiji; Nakamura, Mayu; Ikeda, Kazuyoshi

2016-01-01

Computer-aided drug design is still a state-of-the-art process in medicinal chemistry, and the main topics in this field have been extensively studied and well reviewed. These topics include compound databases, ligand-binding pocket prediction, protein-compound docking, virtual screening, target/off-target prediction, physical property prediction, molecular simulation and pharmacokinetics/pharmacodynamics (PK/PD) prediction. Message and Conclusion: However, there are also a number of secondary or miscellaneous topics that have been less well covered. For example, methods for synthesizing and predicting the synthetic accessibility (SA) of designed compounds are important in practical drug development, and hardware/software resources for performing the computations in computer-aided drug design are crucial. Cloud computing and general purpose graphics processing unit (GPGPU) computing have been used in virtual screening and molecular dynamics simulations. Not surprisingly, there is a growing demand for computer systems which combine these resources. In the present review, we summarize and discuss these various topics of drug design.

Miscellaneous Topics in Computer-Aided Drug Design: Synthetic Accessibility and GPU Computing, and Other Topics

PubMed Central

Fukunishi, Yoshifumi; Mashimo, Tadaaki; Misoo, Kiyotaka; Wakabayashi, Yoshinori; Miyaki, Toshiaki; Ohta, Seiji; Nakamura, Mayu; Ikeda, Kazuyoshi

2016-01-01

Abstract: Background Computer-aided drug design is still a state-of-the-art process in medicinal chemistry, and the main topics in this field have been extensively studied and well reviewed. These topics include compound databases, ligand-binding pocket prediction, protein-compound docking, virtual screening, target/off-target prediction, physical property prediction, molecular simulation and pharmacokinetics/pharmacodynamics (PK/PD) prediction. Message and Conclusion: However, there are also a number of secondary or miscellaneous topics that have been less well covered. For example, methods for synthesizing and predicting the synthetic accessibility (SA) of designed compounds are important in practical drug development, and hardware/software resources for performing the computations in computer-aided drug design are crucial. Cloud computing and general purpose graphics processing unit (GPGPU) computing have been used in virtual screening and molecular dynamics simulations. Not surprisingly, there is a growing demand for computer systems which combine these resources. In the present review, we summarize and discuss these various topics of drug design. PMID:27075578

Phonon Surface Scattering and Thermal Energy Distribution in Superlattices.

PubMed

Kothari, Kartik; Maldovan, Martin

2017-07-17

Thermal transport at small length scales has attracted significant attention in recent years and various experimental and theoretical methods have been developed to establish the reduced thermal conductivity. The fundamental understanding of how phonons move and the physical mechanisms behind nanoscale thermal transport, however, remains poorly understood. Here we move beyond thermal conductivity calculations and provide a rigorous and comprehensive physical description of thermal phonon transport in superlattices by solving the Boltzmann transport equation and using the Beckman-Kirchhoff surface scattering theory with shadowing to precisely describe phonon-surface interactions. We show that thermal transport in superlattices can be divided in two different heat transport modes having different physical properties at small length scales: layer-restricted and extended heat modes. We study how interface conditions, periodicity, and composition can be used to manipulate the distribution of thermal energy flow among such layer-restricted and extended heat modes. From predicted frequency and mean free path spectra of superlattices, we also investigate the existence of wave effects. The results and insights in this paper advance the fundamental understanding of heat transport in superlattices and the prospects of rationally designing thermal systems with tailored phonon transport properties.

Composite materials for space applications

NASA Technical Reports Server (NTRS)

Rawal, Suraj P.; Misra, Mohan S.; Wendt, Robert G.

1990-01-01

The objectives of the program were to: generate mechanical, thermal, and physical property test data for as-fabricated advanced materials; design and fabricate an accelerated thermal cycling chamber; and determine the effect of thermal cycling on thermomechanical properties and dimensional stability of composites. In the current program, extensive mechanical and thermophysical property tests of various organic matrix, metal matrix, glass matrix, and carbon-carbon composites were conducted, and a reliable database was constructed for spacecraft material selection. Material property results for the majority of the as-fabricated composites were consistent with the predicted values, providing a measure of consolidation integrity attained during fabrication. To determine the effect of thermal cycling on mechanical properties, microcracking, and thermal expansion behavior, approximately 500 composite specimens were exposed to 10,000 cycles between -150 and +150 F. These specimens were placed in a large (18 cu ft work space) thermal cycling chamber that was specially designed and fabricated to simulate one year low earth orbital (LEO) thermal cycling in 20 days. With this rate of thermal cycling, this is the largest thermal cycling unit in the country. Material property measurements of the thermal cycled organic matrix composite laminate specimens exhibited less than 24 percent decrease in strength, whereas, the remaining materials exhibited less than 8 percent decrease in strength. The thermal expansion response of each of the thermal cycled specimens revealed significant reduction in hysteresis and residual strain, and the average CTE values were close to the predicted values.

A sampling study on rock properties affecting drilling rate index (DRI)

NASA Astrophysics Data System (ADS)

Yenice, Hayati; Özdoğan, Mehmet V.; Özfırat, M. Kemal

2018-05-01

Drilling rate index (DRI) developed in Norway is a very useful index in determining the drillability of rocks and even in performance prediction of hard rock TBMs and it requires special laboratory test equipment. Drillability is one of the most important subjects in rock excavation. However, determining drillability index from physical and mechanical properties of rocks is very important for practicing engineers such as underground excavation, drilling operations in open pit mining, underground mining and natural stone production. That is why many researchers have studied concerned with drillability to find the correlations between drilling rate index (DRI) and penetration rate, influence of geological properties on drillability prediction in tunneling, correlations between rock properties and drillability. In this study, the relationships between drilling rate index (DRI) and some physico-mechanical properties (Density, Shore hardness, uniaxial compressive strength (UCS, σc), Indirect tensile strength (ITS, σt)) of three different rock groups including magmatic, sedimentary and metamorphic were evaluated using both simple and multiple regression analysis. This study reveals the effects of rock properties on DRI according to different types of rocks. In simple regression, quite high correlations were found between DRI and uniaxial compressive strength (UCS) and also between DRI and indirect tensile strength (ITS) values. Multiple regression analyses revealed even higher correlations when compared to simple regression. Especially, UCS, ITS, Shore hardness (SH) and the interactions between them were found to be very effective on DRI values.

Mass and energy budgets of animals: Behavioral and ecological implications

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

Porter, W.P.

1991-11-01

The two major aims of our lab are as follows: First, to develop and field-test general mechanistic models that predict animal life history characteristics as influenced by climate and the physical, physiological behavioral characteristics of species. This involves: understanding how animal time and energy budgets are affected by climate and animal properties; predicting growth and reproductive potential from time and energy budgets; predicting mortality based on climate and time and energy budgets; and linking these individual based models to population dynamics. Second to conduct empirical studies of animal physiological ecology, particularly the effects of temperature on time and energy budgets.more » The physiological ecology of individual animals is the key link between the physical environment and population-level phenomena. We address the macroclimate to microclimate linkage on a broad spatial scale; address the links between individuals and population dynamics for lizard species; test the endotherm energetics and behavior model using beaver; address the spatial variation in climate and its effects on individual energetics, growth and reproduction; and address patchiness in the environment and constraints they may impose on individual energetics, growth and reproduction. These projects are described individually in the following section. 24 refs., 9 figs.« less

Actuator and aerodynamic modeling for high-angle-of-attack aeroservoelasticity

NASA Technical Reports Server (NTRS)

Brenner, Martin J.

1993-01-01

Accurate prediction of airframe/actuation coupling is required by the imposing demands of modern flight control systems. In particular, for agility enhancement at high angle of attack and low dynamic pressure, structural integration characteristics such as hinge moments, effective actuator stiffness, and airframe/control surface damping can have a significant effect on stability predictions. Actuator responses are customarily represented with low-order transfer functions matched to actuator test data, and control surface stiffness is often modeled as a linear spring. The inclusion of the physical properties of actuation and its installation on the airframe is therefore addressed in this paper using detailed actuator models which consider the physical, electrical, and mechanical elements of actuation. The aeroservoelastic analysis procedure is described in which the actuators are modeled as detailed high-order transfer functions and as approximate low-order transfer functions. The impacts of unsteady aerodynamic modeling on aeroservoelastic stability are also investigated in this paper by varying the order of approximation, or number of aerodynamic lag states, in the analysis. Test data from a thrust-vectoring configuration of an F/A-18 aircraft are compared to predictions to determine the effects on accuracy as a function of modeling complexity.

Actuator and aerodynamic modeling for high-angle-of-attack aeroservoelasticity

NASA Technical Reports Server (NTRS)

Brenner, Martin J.

1993-01-01

Accurate prediction of airframe/actuation coupling is required by the imposing demands of modern flight control systems. In particular, for agility enhancement at high angle of attack and low dynamic pressure, structural integration characteristics such as hinge moments, effective actuator stiffness, and airframe/control surface damping can have a significant effect on stability predictions. Actuator responses are customarily represented with low-order transfer functions matched to actuator test data, and control surface stiffness is often modeled as a linear spring. The inclusion of the physical properties of actuation and its installation on the airframe is therefore addressed using detailed actuator models which consider the physical, electrical, and mechanical elements of actuation. The aeroservoelastic analysis procedure is described in which the actuators are modeled as detailed high-order transfer functions and as approximate low-order transfer functions. The impacts of unsteady aerodynamic modeling on aeroservoelastic stability are also investigated by varying the order of approximation, or number of aerodynamic lag states, in the analysis. Test data from a thrust-vectoring configuration of an F/A-l8 aircraft are compared to predictions to determine the effects on accuracy as a function of modeling complexity.

Atomic scale imaging of magnetic circular dichroism by achromatic electron microscopy.

PubMed

Wang, Zechao; Tavabi, Amir H; Jin, Lei; Rusz, Ján; Tyutyunnikov, Dmitry; Jiang, Hanbo; Moritomo, Yutaka; Mayer, Joachim; Dunin-Borkowski, Rafal E; Yu, Rong; Zhu, Jing; Zhong, Xiaoyan

2018-03-01

In order to obtain a fundamental understanding of the interplay between charge, spin, orbital and lattice degrees of freedom in magnetic materials and to predict and control their physical properties 1-3 , experimental techniques are required that are capable of accessing local magnetic information with atomic-scale spatial resolution. Here, we show that a combination of electron energy-loss magnetic chiral dichroism 4 and chromatic-aberration-corrected transmission electron microscopy, which reduces the focal spread of inelastically scattered electrons by orders of magnitude when compared with the use of spherical aberration correction alone, can achieve atomic-scale imaging of magnetic circular dichroism and provide element-selective orbital and spin magnetic moments atomic plane by atomic plane. This unique capability, which we demonstrate for Sr 2 FeMoO 6 , opens the door to local atomic-level studies of spin configurations in a multitude of materials that exhibit different types of magnetic coupling, thereby contributing to a detailed understanding of the physical origins of magnetic properties of materials at the highest spatial resolution.

Ionization potential depression in an atomic-solid-plasma picture

NASA Astrophysics Data System (ADS)

Rosmej, F. B.

2018-05-01

Exotic solid density matter such as heated hollow crystals allow extended material studies while their physical properties and models such as the famous ionization potential depression are presently under renewed controversial discussion. Here we develop an atomic-solid-plasma (ASP) model that permits ionization potential depression studies also for single and multiple core hole states. Numerical calculations show very good agreement with recently available data not only in absolute values but also for Z-scaled properties while currently employed methods fail. For much above solid density compression, the ASP model predicts increased K-edge energies that are related to a Fermi surface rising. This is in good agreement with recent quantum molecular dynamics simulations. For hot dense matter a quantum number dependent optical electron finite temperature ion sphere model is developed that fits well with line shift and line disappearance data from dense laser produced plasma experiments. Finally, the physical transparency of the ASP picture allows a critical discussion of current methods.

Chapter 24: Two- and Three-Dimensional Electronic Modeling of Thin-Film Solar Cells

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

Kanevce, Ana; Metzger, Wyatt K

2016-07-22

Modeling can provide physical insight to device operation, help distinguish important material properties from unimportant properties, predict trends, and help interpret experimental data. Numerical modeling is also useful to simulate different electro-optical experiments, in the presence of grain boundaries (GBs) and nonplanar junctions and geometries, and to help interpret data obtained in such experiments. This chapter presents methods for effective multidimensional modeling. The first step in creating a computational model is defining and providing discretization of a 2D area or a 3D volume. Two main approaches to the discretization have been used for studying solar cells: equivalent-circuit modeling and solvingmore » semiconductor equations. The chapter gives some examples of problems that were addressed with 2D or 3D modeling and the knowledge that was gained through them. Multidimensional modeling including GBs and other material variations is necessary to explain the device physics and experimental results present in diverse thin-film technologies.« less

Integrated Predictive Tools for Customizing Microstructure and Material Properties of Additively Manufactured Aerospace Components

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

Radhakrishnan, Balasubramaniam; Fattebert, Jean-Luc; Gorti, Sarma B.

Additive Manufacturing (AM) refers to a process by which digital three-dimensional (3-D) design data is converted to build up a component by depositing material layer-by-layer. United Technologies Corporation (UTC) is currently involved in fabrication and certification of several AM aerospace structural components made from aerospace materials. This is accomplished by using optimized process parameters determined through numerous design-of-experiments (DOE)-based studies. Certification of these components is broadly recognized as a significant challenge, with long lead times, very expensive new product development cycles and very high energy consumption. Because of these challenges, United Technologies Research Center (UTRC), together with UTC business unitsmore » have been developing and validating an advanced physics-based process model. The specific goal is to develop a physics-based framework of an AM process and reliably predict fatigue properties of built-up structures as based on detailed solidification microstructures. Microstructures are predicted using process control parameters including energy source power, scan velocity, deposition pattern, and powder properties. The multi-scale multi-physics model requires solution and coupling of governing physics that will allow prediction of the thermal field and enable solution at the microstructural scale. The state-of-the-art approach to solve these problems requires a huge computational framework and this kind of resource is only available within academia and national laboratories. The project utilized the parallel phase-fields codes at Oak Ridge National Laboratory (ORNL) and Lawrence Livermore National Laboratory (LLNL), along with the high-performance computing (HPC) capabilities existing at the two labs to demonstrate the simulation of multiple dendrite growth in threedimensions (3-D). The LLNL code AMPE was used to implement the UTRC phase field model that was previously developed for a model binary alloy, and the simulation results were compared against the UTRC simulation results, followed by extension of the UTRC model to simulate multiple dendrite growth in 3-D. The ORNL MEUMAPPS code was used to simulate dendritic growth in a model ternary alloy with the same equilibrium solidification range as the Ni-base alloy 718 using realistic model parameters, including thermodynamic integration with a Calphad based model for the ternary alloy. Implementation of the UTRC model in AMPE met with several numerical and parametric issues that were resolved and good comparison between the simulation results obtained by the two codes was demonstrated for two dimensional (2-D) dendrites. 3-D dendrite growth was then demonstrated with the AMPE code using nondimensional parameters obtained in 2-D simulations. Multiple dendrite growth in 2-D and 3-D were demonstrated using ORNL’s MEUMAPPS code using simple thermal boundary conditions. MEUMAPPS was then modified to incorporate the complex, time-dependent thermal boundary conditions obtained by UTRC’s thermal modeling of single track AM experiments to drive the phase field simulations. The results were in good agreement with UTRC’s experimental measurements.« less

Nutrient Deprivation Induces Property Variations in Spider Gluey Silk

PubMed Central

Blamires, Sean J.; Sahni, Vasav; Dhinojwala, Ali; Blackledge, Todd A.; Tso, I-Min

2014-01-01

Understanding the mechanisms facilitating property variability in biological adhesives may promote biomimetic innovations. Spider gluey silks such as the spiral threads in orb webs and the gumfoot threads in cobwebs, both of which comprise of an axial thread coated by glue, are biological adhesives that have variable physical and chemical properties. Studies show that the physical and chemical properties of orb web gluey threads change when spiders are deprived of food. It is, however, unknown whether gumfoot threads undergo similar property variations when under nutritional stress. Here we tested whether protein deprivation induces similar variations in spiral and gumfoot thread morphology and stickiness. We manipulated protein intake for the orb web spider Nephila clavipes and the cobweb spider Latrodectus hesperus and measured the diameter, glue droplet volume, number of droplets per mm, axial thread width, thread stickiness and adhesive energy of their gluey silks. We found that the gluey silks of both species were stickier when the spiders were deprived of protein than when the spiders were fed protein. In N. clavipes a concomitant increase in glue droplet volume was found. Load-extension curves showed that protein deprivation induced glue property variations independent of the axial thread extensions in both species. We predicted that changes in salt composition of the glues were primarily responsible for the changes in stickiness of the silks, although changes in axial thread properties might also contribute. We, additionally, showed that N. clavipes' glue changes color under protein deprivation, probably as a consequence of changes to its biochemical composition. PMID:24523902

Electronic Interfacial Effects in Epitaxial Heterostructures based on LaMnO3.

NASA Astrophysics Data System (ADS)

Christen, Hans M.; Varela, M.; Lee, H. N.; Kim, D. H.; Chisholm, M. F.; Cantoni, C.; Petit, L.; Schulthess, T. C.; Lowndes, D. H.

2006-03-01

Studies of chemically abrupt interfaces provide an ideal platform to study the effects of discontinuities and asymmetries of the electronic configuration on the transport and magnetic properties of complex oxides. In addition, the behavior of complex materials near interfaces plays the most crucial role not only in devices and nanostructures but also in complex structures in the form of composites and superlattices, including artificial multiferroics. Interfaces in the ABO3 perovskite system are particularly attractive because structurally similar oxides with fundamentally different physical properties can be integrated epitaxially. To explore the electronic effects at interfaces and to probe the physical properties that result from local electronic changes, we have synthesized structures containing LaMnO3 and insulating perovskites using pulsed laser deposition. The local electron energy loss spectroscopy (EELS) capability of a scanning transmission electron microscope (STEM) is used to probe the electronic configuration in the LaMnO3 films as a function of the distance from the interfaces. The results are compared to macroscopic measurements and theoretical predictions. Research sponsored by the U.S. Department of Energy under contract DE-AC05-00OR22725 with the Oak Ridge National Laboratory, managed by UT-Battelle, LLC.

Cubs in the Litter: Spectroscopy of New Andromodean Dwarfs from PAndAS

NASA Astrophysics Data System (ADS)

Lewis, Geraint; McConnachie, Alan; Irwin, Michael; Rich, R. Michael; Ibata, Rodrigo

2010-08-01

We will use Gemini/GMOS to obtain spectroscopy of Red Giant Branch (RGB) stars in four new dwarf galaxies identified within the Pan-Andromeda Archaeological Survey (PAndAS). With these data, we will measure the key physical properties of the dwarfs, namely their radial velocities, internal kinematics and spectroscopic metallicities. Such measurements are essential in determining the dwarfs' fundamental characteristics; namely their internal dynamics, dark matter content, and clues to star formation and evolutionary histories. PAndAS is revolutionizing our view of our nearest cosmic neighbour, the Andromeda Galaxy, revealing a wealth of previously undetected substructure and dwarf galaxies, and these new observations are indispensable in unraveling global properties of M31's population of satellites and their relation to the M31 galaxy and its extended stellar halo. Andromeda is one of the few targets available which can provide direct tests of predictions of the distribution of mass and light in galaxy haloes and satellite galaxies, but a detailed knowledge of the physical properties of such substructure is essential; the excellent capabilities of Gemini/GMOS makes it one of the few facilities which can obtain the required spectroscopic data.

Manipulating topological-insulator properties using quantum confinement

NASA Astrophysics Data System (ADS)

Kotulla, M.; Zülicke, U.

2017-07-01

Recent discoveries have spurred the theoretical prediction and experimental realization of novel materials that have topological properties arising from band inversion. Such topological insulators are insulating in the bulk but have conductive surface or edge states. Topological materials show various unusual physical properties and are surmised to enable the creation of exotic Majorana-fermion quasiparticles. How the signatures of topological behavior evolve when the system size is reduced is interesting from both a fundamental and an application-oriented point of view, as such understanding may form the basis for tailoring systems to be in specific topological phases. This work considers the specific case of quantum-well confinement defining two-dimensional layers. Based on the effective-Hamiltonian description of bulk topological insulators, and using a harmonic-oscillator potential as an example for a softer-than-hard-wall confinement, we have studied the interplay of band inversion and size quantization. Our model system provides a useful platform for systematic study of the transition between the normal and topological phases, including the development of band inversion and the formation of massless-Dirac-fermion surface states. The effects of bare size quantization, two-dimensional-subband mixing, and electron-hole asymmetry are disentangled and their respective physical consequences elucidated.

Universal features underlying the magnetism in diluted magnetic semiconductors

NASA Astrophysics Data System (ADS)

Andriotis, Antonis N.; Menon, Madhu

2018-04-01

Investigation of a diverse variety of wide band gap semiconductors and metal oxides that exhibit magnetism on substitutional doping has revealed the existence of universal features that relate the magnetic moment of the dopant to a number of physical properties inherent to the dopants and the hosts. The investigated materials consist of ZnO, GaN, GaP, TiO2, SnO2, Sn3N4, MoS2, ZnS and CdS doped with 3d-transition metal atoms. The primary physical properties contributing to magnetism include the orbital hybridization and charge distribution, the d-band filling, d-band center, crystal field splitting, electron pairing energy and electronegativity. These features specify the strength of the spin-polarization induced by the dopants on their first nearest neighboring anions which in turn specify the long range magnetic coupling among the dopants through successively induced spin polarizations (SSP) on neighboring dopants. The proposed local SSP process for the establishment of the magnetic coupling among the TM-dopants appears as a competitor to other classical processes (superexchange, double exchange, etc). Furthermore, these properties can be used as a set of descriptors suitable for developing statistical predictive theories for a much larger class of magnetic materials.

Observation of a superfluid Hall effect

PubMed Central

Jiménez-García, Karina; Williams, Ross A.; Beeler, Matthew C.; Perry, Abigail R.; Phillips, William D.; Spielman, Ian B.

2012-01-01

Measurement techniques based upon the Hall effect are invaluable tools in condensed-matter physics. When an electric current flows perpendicular to a magnetic field, a Hall voltage develops in the direction transverse to both the current and the field. In semiconductors, this behavior is routinely used to measure the density and charge of the current carriers (electrons in conduction bands or holes in valence bands)—internal properties of the system that are not accessible from measurements of the conventional resistance. For strongly interacting electron systems, whose behavior can be very different from the free electron gas, the Hall effect’s sensitivity to internal properties makes it a powerful tool; indeed, the quantum Hall effects are named after the tool by which they are most distinctly measured instead of the physics from which the phenomena originate. Here we report the first observation of a Hall effect in an ultracold gas of neutral atoms, revealed by measuring a Bose–Einstein condensate’s transport properties perpendicular to a synthetic magnetic field. Our observations in this vortex-free superfluid are in good agreement with hydrodynamic predictions, demonstrating that the system’s global irrotationality influences this superfluid Hall signal. PMID:22699494

A discrete element method-based approach to predict the breakage of coal

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

Gupta, Varun; Sun, Xin; Xu, Wei

Pulverization is an essential pre-combustion technique employed for solid fuels, such as coal, to reduce particle sizes. Smaller particles ensure rapid and complete combustion, leading to low carbon emissions. Traditionally, the resulting particle size distributions from pulverizers have been determined by empirical or semi-empirical approaches that rely on extensive data gathered over several decades during operations or experiments, with limited predictive capabilities for new coals and processes. Our work presents a Discrete Element Method (DEM)-based computational approach to model coal particle breakage with experimentally characterized coal physical properties. We also examined the effect of select operating parameters on the breakagemore » behavior of coal particles.« less

A discrete element method-based approach to predict the breakage of coal

DOE PAGES

Gupta, Varun; Sun, Xin; Xu, Wei; ...

2017-08-05

Pulverization is an essential pre-combustion technique employed for solid fuels, such as coal, to reduce particle sizes. Smaller particles ensure rapid and complete combustion, leading to low carbon emissions. Traditionally, the resulting particle size distributions from pulverizers have been determined by empirical or semi-empirical approaches that rely on extensive data gathered over several decades during operations or experiments, with limited predictive capabilities for new coals and processes. Our work presents a Discrete Element Method (DEM)-based computational approach to model coal particle breakage with experimentally characterized coal physical properties. We also examined the effect of select operating parameters on the breakagemore » behavior of coal particles.« less