Multiscale and Multiphysics Modeling of Additive Manufacturing of Advanced Materials

NASA Technical Reports Server (NTRS)

Liou, Frank; Newkirk, Joseph; Fan, Zhiqiang; Sparks, Todd; Chen, Xueyang; Fletcher, Kenneth; Zhang, Jingwei; Zhang, Yunlu; Kumar, Kannan Suresh; Karnati, Sreekar

2015-01-01

The objective of this proposed project is to research and develop a prediction tool for advanced additive manufacturing (AAM) processes for advanced materials and develop experimental methods to provide fundamental properties and establish validation data. Aircraft structures and engines demand materials that are stronger, useable at much higher temperatures, provide less acoustic transmission, and enable more aeroelastic tailoring than those currently used. Significant improvements in properties can only be achieved by processing the materials under nonequilibrium conditions, such as AAM processes. AAM processes encompass a class of processes that use a focused heat source to create a melt pool on a substrate. Examples include Electron Beam Freeform Fabrication and Direct Metal Deposition. These types of additive processes enable fabrication of parts directly from CAD drawings. To achieve the desired material properties and geometries of the final structure, assessing the impact of process parameters and predicting optimized conditions with numerical modeling as an effective prediction tool is necessary. The targets for the processing are multiple and at different spatial scales, and the physical phenomena associated occur in multiphysics and multiscale. In this project, the research work has been developed to model AAM processes in a multiscale and multiphysics approach. A macroscale model was developed to investigate the residual stresses and distortion in AAM processes. A sequentially coupled, thermomechanical, finite element model was developed and validated experimentally. The results showed the temperature distribution, residual stress, and deformation within the formed deposits and substrates. A mesoscale model was developed to include heat transfer, phase change with mushy zone, incompressible free surface flow, solute redistribution, and surface tension. Because of excessive computing time needed, a parallel computing approach was also tested. In addition, after investigating various methods, a Smoothed Particle Hydrodynamics Model (SPH Model) was developed to model wire feeding process. Its computational efficiency and simple architecture makes it more robust and flexible than other models. More research on material properties may be needed to realistically model the AAM processes. A microscale model was developed to investigate heterogeneous nucleation, dendritic grain growth, epitaxial growth of columnar grains, columnar-to-equiaxed transition, grain transport in melt, and other properties. The orientations of the columnar grains were almost perpendicular to the laser motion's direction. Compared to the similar studies in the literature, the multiple grain morphology modeling result is in the same order of magnitude as optical morphologies in the experiment. Experimental work was conducted to validate different models. An infrared camera was incorporated as a process monitoring and validating tool to identify the solidus and mushy zones during deposition. The images were successfully processed to identify these regions. This research project has investigated multiscale and multiphysics of the complex AAM processes thus leading to advanced understanding of these processes. The project has also developed several modeling tools and experimental validation tools that will be very critical in the future of AAM process qualification and certification.

A mathematical study of a random process proposed as an atmospheric turbulence model

NASA Technical Reports Server (NTRS)

Sidwell, K.

1977-01-01

A random process is formed by the product of a local Gaussian process and a random amplitude process, and the sum of that product with an independent mean value process. The mathematical properties of the resulting process are developed, including the first and second order properties and the characteristic function of general order. An approximate method for the analysis of the response of linear dynamic systems to the process is developed. The transition properties of the process are also examined.

Evolution of material properties during free radical photopolymerization

NASA Astrophysics Data System (ADS)

Wu, Jiangtao; Zhao, Zeang; Hamel, Craig M.; Mu, Xiaoming; Kuang, Xiao; Guo, Zaoyang; Qi, H. Jerry

2018-03-01

Photopolymerization is a widely used polymerization method in many engineering applications such as coating, dental restoration, and 3D printing. It is a complex chemical and physical process, through which a liquid monomer solution is rapidly converted to a solid polymer. In the most common free-radical photopolymerization process, the photoinitiator in the solution is exposed to light and decomposes into active radicals, which attach to monomers to start the polymerization reaction. The activated monomers then attack Cdbnd C double bonds of unsaturated monomers, which leads to the growth of polymer chains. With increases in the polymer chain length and the average molecular weight, polymer chains start to connect and form a network structure, and the liquid polymer solution becomes a dense solid. During this process, the material properties of the cured polymer change dramatically. In this paper, experiments and theoretical modeling are used to investigate the free-radical photopolymerization reaction kinetics, material property evolution and mechanics during the photopolymerization process. The model employs the first order chemical reaction rate equations to calculate the variation of the species concentrations. The degree of monomer conversion is used as an internal variable that dictates the mechanical properties of the cured polymer at different curing states, including volume shrinkage, glass transition temperature, and nonlinear viscoelastic properties. To capture the nonlinear behavior of the cured polymer under low temperature and finite deformation, a multibranch nonlinear viscoelastic model is developed. A phase evolution model is used to describe the mechanics of the coupling between the crosslink network evolution and mechanical loading during the curing process. The comparison of the model and the experimental results indicates that the model can capture property changes during curing. The model is further applied to investigate the internal stress of a thick sample caused by volume shrinkage during photopolymerization. Changes in the conversion degree gradient and the internal stress during photopolymerization are determined using FEM simulation. The model can be extended to many photocuring processes, such as photopolymerization 3D printing, surface coating and automotive part curing processes.

Effect of roll compaction on granule size distribution of microcrystalline cellulose–mannitol mixtures: computational intelligence modeling and parametric analysis

PubMed Central

Kazemi, Pezhman; Khalid, Mohammad Hassan; Pérez Gago, Ana; Kleinebudde, Peter; Jachowicz, Renata; Szlęk, Jakub; Mendyk, Aleksander

2017-01-01

Dry granulation using roll compaction is a typical unit operation for producing solid dosage forms in the pharmaceutical industry. Dry granulation is commonly used if the powder mixture is sensitive to heat and moisture and has poor flow properties. The output of roll compaction is compacted ribbons that exhibit different properties based on the adjusted process parameters. These ribbons are then milled into granules and finally compressed into tablets. The properties of the ribbons directly affect the granule size distribution (GSD) and the quality of final products; thus, it is imperative to study the effect of roll compaction process parameters on GSD. The understanding of how the roll compactor process parameters and material properties interact with each other will allow accurate control of the process, leading to the implementation of quality by design practices. Computational intelligence (CI) methods have a great potential for being used within the scope of quality by design approach. The main objective of this study was to show how the computational intelligence techniques can be useful to predict the GSD by using different process conditions of roll compaction and material properties. Different techniques such as multiple linear regression, artificial neural networks, random forest, Cubist and k-nearest neighbors algorithm assisted by sevenfold cross-validation were used to present generalized models for the prediction of GSD based on roll compaction process setting and material properties. The normalized root-mean-squared error and the coefficient of determination (R2) were used for model assessment. The best fit was obtained by Cubist model (normalized root-mean-squared error =3.22%, R2=0.95). Based on the results, it was confirmed that the material properties (true density) followed by compaction force have the most significant effect on GSD. PMID:28176905

Effect of roll compaction on granule size distribution of microcrystalline cellulose-mannitol mixtures: computational intelligence modeling and parametric analysis.

PubMed

Kazemi, Pezhman; Khalid, Mohammad Hassan; Pérez Gago, Ana; Kleinebudde, Peter; Jachowicz, Renata; Szlęk, Jakub; Mendyk, Aleksander

2017-01-01

Dry granulation using roll compaction is a typical unit operation for producing solid dosage forms in the pharmaceutical industry. Dry granulation is commonly used if the powder mixture is sensitive to heat and moisture and has poor flow properties. The output of roll compaction is compacted ribbons that exhibit different properties based on the adjusted process parameters. These ribbons are then milled into granules and finally compressed into tablets. The properties of the ribbons directly affect the granule size distribution (GSD) and the quality of final products; thus, it is imperative to study the effect of roll compaction process parameters on GSD. The understanding of how the roll compactor process parameters and material properties interact with each other will allow accurate control of the process, leading to the implementation of quality by design practices. Computational intelligence (CI) methods have a great potential for being used within the scope of quality by design approach. The main objective of this study was to show how the computational intelligence techniques can be useful to predict the GSD by using different process conditions of roll compaction and material properties. Different techniques such as multiple linear regression, artificial neural networks, random forest, Cubist and k-nearest neighbors algorithm assisted by sevenfold cross-validation were used to present generalized models for the prediction of GSD based on roll compaction process setting and material properties. The normalized root-mean-squared error and the coefficient of determination ( R 2 ) were used for model assessment. The best fit was obtained by Cubist model (normalized root-mean-squared error =3.22%, R 2 =0.95). Based on the results, it was confirmed that the material properties (true density) followed by compaction force have the most significant effect on GSD.

Design Optimization of Microalloyed Steels Using Thermodynamics Principles and Neural-Network-Based Modeling

NASA Astrophysics Data System (ADS)

Mohanty, Itishree; Chintha, Appa Rao; Kundu, Saurabh

2018-06-01

The optimization of process parameters and composition is essential to achieve the desired properties with minimal additions of alloying elements in microalloyed steels. In some cases, it may be possible to substitute such steels for those which are more richly alloyed. However, process control involves a larger number of parameters, making the relationship between structure and properties difficult to assess. In this work, neural network models have been developed to estimate the mechanical properties of steels containing Nb + V or Nb + Ti. The outcomes have been validated by thermodynamic calculations and plant data. It has been shown that subtle thermodynamic trends can be captured by the neural network model. Some experimental rolling data have also been used to support the model, which in addition has been applied to calculate the costs of optimizing microalloyed steel. The generated pareto fronts identify many combinations of strength and elongation, making it possible to select composition and process parameters for a range of applications. The ANN model and the optimization model are being used for prediction of properties in a running plant and for development of new alloys, respectively.

Determination of orthotropic material properties by modal analysis

NASA Astrophysics Data System (ADS)

Lai, Junpeng

The methodology for determination of orthotropic material properties in plane stress condition will be presented. It is applied to orthotropic laminated plates like printed wiring boards. The first part of the thesis will focus on theories and methodologies. The static beam model and vibratory plate model is presented. The methods are validated by operating a series of test on aluminum. In the static tests, deflection and two directions of strain are measured, thus four of the properties will be identified: Ex, Ey, nuxy, nuyx. Moving on to dynamic test, the first ten modes' resonance frequencies are obtained. The technique of modal analysis is adopted. The measured data is processed by FFT and analyzed by curve fitting to extract natural frequencies and mode shapes. With the last material property to be determined, a finite element method using ANSYS is applied. Along with the identified material properties in static tests, and proper initial guess of the unknown shear modulus, an iterative process creates finite element model and conducts modal analysis with the updating model. When the modal analysis result produced by ANSYS matches the natural frequencies acquired by dynamic test, the process will halt. Then we obtained the last material property in plane stress condition.

Hot Isostatic Press Manufacturing Process Development for Fabrication of RERTR Monolithic Fuel Plates

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

Crapps, Justin M.; Clarke, Kester D.; Katz, Joel D.

2012-06-06

We use experimentation and finite element modeling to study a Hot Isostatic Press (HIP) manufacturing process for U-10Mo Monolithic Fuel Plates. Finite element simulations are used to identify the material properties affecting the process and improve the process geometry. Accounting for the high temperature material properties and plasticity is important to obtain qualitative agreement between model and experimental results. The model allows us to improve the process geometry and provide guidance on selection of material and finish conditions for the process strongbacks. We conclude that the HIP can must be fully filled to provide uniform normal stress across the bondingmore » interface.« less

MODFLOW-2000, the U.S. Geological Survey Modular Ground-Water Model -Documentation of the Hydrogeologic-Unit Flow (HUF) Package

USGS Publications Warehouse

Anderman, E.R.; Hill, M.C.

2000-01-01

This report documents the Hydrogeologic-Unit Flow (HUF) Package for the groundwater modeling computer program MODFLOW-2000. The HUF Package is an alternative internal flow package that allows the vertical geometry of the system hydrogeology to be defined explicitly within the model using hydrogeologic units that can be different than the definition of the model layers. The HUF Package works with all the processes of MODFLOW-2000. For the Ground-Water Flow Process, the HUF Package calculates effective hydraulic properties for the model layers based on the hydraulic properties of the hydrogeologic units, which are defined by the user using parameters. The hydraulic properties are used to calculate the conductance coefficients and other terms needed to solve the ground-water flow equation. The sensitivity of the model to the parameters defined within the HUF Package input file can be calculated using the Sensitivity Process, using observations defined with the Observation Process. Optimal values of the parameters can be estimated by using the Parameter-Estimation Process. The HUF Package is nearly identical to the Layer-Property Flow (LPF) Package, the major difference being the definition of the vertical geometry of the system hydrogeology. Use of the HUF Package is illustrated in two test cases, which also serve to verify the performance of the package by showing that the Parameter-Estimation Process produces the true parameter values when exact observations are used.

The influence of API concentration on the roller compaction process: modeling and prediction of the post compacted ribbon, granule and tablet properties using multivariate data analysis.

PubMed

Boersen, Nathan; Carvajal, M Teresa; Morris, Kenneth R; Peck, Garnet E; Pinal, Rodolfo

2015-01-01

While previous research has demonstrated roller compaction operating parameters strongly influence the properties of the final product, a greater emphasis might be placed on the raw material attributes of the formulation. There were two main objectives to this study. First, to assess the effects of different process variables on the properties of the obtained ribbons and downstream granules produced from the rolled compacted ribbons. Second, was to establish if models obtained with formulations of one active pharmaceutical ingredient (API) could predict the properties of similar formulations in terms of the excipients used, but with a different API. Tolmetin and acetaminophen, chosen for their different compaction properties, were roller compacted on Fitzpatrick roller compactor using the same formulation. Models created using tolmetin and tested using acetaminophen. The physical properties of the blends, ribbon, granule and tablet were characterized. Multivariate analysis using partial least squares was used to analyze all data. Multivariate models showed that the operating parameters and raw material attributes were essential in the prediction of ribbon porosity and post-milled particle size. The post compacted ribbon and granule attributes also significantly contributed to the prediction of the tablet tensile strength. Models derived using tolmetin could reasonably predict the ribbon porosity of a second API. After further processing, the post-milled ribbon and granules properties, rather than the physical attributes of the formulation were needed to predict downstream tablet properties. An understanding of the percolation threshold of the formulation significantly improved the predictive ability of the models.

Estimation of Environment-Related Properties of Chemicals for Design of Sustainable Processes: Development of Group-Contribution+ (GC+) Property Models and Uncertainty Analysis

EPA Science Inventory

The aim of this work is to develop group-contribution+ (GC+) method (combined group-contribution (GC) method and atom connectivity index (CI) method) based property models to provide reliable estimations of environment-related properties of organic chemicals together with uncert...

Modeling of Unit-Cells With Z-Pins Using FLASH: Pre-Processing and Post Processing

NASA Technical Reports Server (NTRS)

Krueger, Ronald

2005-01-01

Although the toughening properties of stitches, z-pins and similar structures have been studied extensively, investigations on the effect of z-pins on the in-plane properties of laminates are limited. A brief summary on the effect of z-pins on the in-plane tensile and compressive properties of composite laminates is presented together with a concise introduction into the finite element code FLASH. The remainder of the report illustrates the modeling aspect of unit cells with z-pins in FLASH and focuses on input and output data as well as post-processing of results.

Rapid response tools and datasets for post-fire modeling: Linking Earth Observations and process-based hydrological models to support post-fire remediation

Treesearch

M. E. Miller; M. Billmire; W. J. Elliot; K. A. Endsley; P. R. Robichaud

2015-01-01

Preparation is key to utilizing Earth Observations and process-based models to support post-wildfire mitigation. Post-fire flooding and erosion can pose a serious threat to life, property and municipal water supplies. Increased runoff and sediment delivery due to the loss of surface cover and fire-induced changes in soil properties are of great concern. Remediation...

On the Coupling Between the Incus and the Stapes in the Cat

PubMed Central

Heng Siah, T.; McKee, Marc D.; Daniel, Sam J.; Decraemer, Willem F.

2005-01-01

The connection between the long process and the lenticular process of the incus is extremely fine, so much so that some authors have treated the lenticular process as a separate bone. We review descriptions of the lenticular process that have appeared in the literature, and present some new histological observations. We discuss the dimensions and composition of the lenticular process and of the incudostapedial joint, and present estimates of the material properties for the bone, cartilage, and ligament of which they are composed. We present a preliminary finite-element model which includes the lenticular plate, the bony pedicle connecting the lenticular plate to the long process, the head of the stapes, and the incudostapedial joint. The model has a much simplified geometry. We present simulation results for ranges of values for the material properties. We then present simulation results for this model when it is incorporated into an overall model of the middle ear of the cat. For the geometries and material properties used here, the bony pedicle is found to contribute significant flexibility to the coupling between the incus and the stapes. PMID:15735938

Effect of processing on Polymer/Composite structure and properties

NASA Technical Reports Server (NTRS)

1982-01-01

Advances in the vitality and economic health of the field of polymer forecasting are discussed. A consistent and rational point of view which considers processing as a participant in the underlying triad of relationships which comprise materials science and engineering is outlined. This triad includes processing as it influences material structure, and ultimately properties. Methods in processing structure properties, polymer science and engineering, polymer chemistry and synthesis, structure and modification and optimization through processing, and methods of melt flow modeling in processing structure property relations of polymer were developed. Mechanical properties of composites are considered, and biomedical materials research to include polymer processing effects are studied. An analysis of the design technology of advances graphite/epoxy composites is also reported.

Computer-Aided Process Model For Carbon/Phenolic Materials

NASA Technical Reports Server (NTRS)

Letson, Mischell A.; Bunker, Robert C.

1996-01-01

Computer program implements thermochemical model of processing of carbon-fiber/phenolic-matrix composite materials into molded parts of various sizes and shapes. Directed toward improving fabrication of rocket-engine-nozzle parts, also used to optimize fabrication of other structural components, and material-property parameters changed to apply to other materials. Reduces costs by reducing amount of laboratory trial and error needed to optimize curing processes and to predict properties of cured parts.

9th Annual Science and Engineering Technology Conference

DTIC Science & Technology

2008-04-17

Disks Composite Technology Titanium Aluminides Processing Microstructure Properties Curve Generator Go-Forward: Integrated Materials & Process Models...Initiatives Current DPA/T3s: Atomic Layer Deposition Hermetic Coatings: ...domestic ALD for electronic components; transition to fabrication process ...Production windows estim • Process capability fully established >Production specifications in place >Supply chain established •All necessary property

Determination of injection molding process windows for optical lenses using response surface methodology.

PubMed

Tsai, Kuo-Ming; Wang, He-Yi

2014-08-20

This study focuses on injection molding process window determination for obtaining optimal imaging optical properties, astigmatism, coma, and spherical aberration using plastic lenses. The Taguchi experimental method was first used to identify the optimized combination of parameters and significant factors affecting the imaging optical properties of the lens. Full factorial experiments were then implemented based on the significant factors to build the response surface models. The injection molding process windows for lenses with optimized optical properties were determined based on the surface models, and confirmation experiments were performed to verify their validity. The results indicated that the significant factors affecting the optical properties of lenses are mold temperature, melt temperature, and cooling time. According to experimental data for the significant factors, the oblique ovals for different optical properties on the injection molding process windows based on melt temperature and cooling time can be obtained using the curve fitting approach. The confirmation experiments revealed that the average errors for astigmatism, coma, and spherical aberration are 3.44%, 5.62%, and 5.69%, respectively. The results indicated that the process windows proposed are highly reliable.

Multiphysics Modeling and Simulations of Mil A46100 Armor-Grade Martensitic Steel Gas Metal Arc Welding Process

NASA Astrophysics Data System (ADS)

Grujicic, M.; Ramaswami, S.; Snipes, J. S.; Yen, C.-F.; Cheeseman, B. A.; Montgomery, J. S.

2013-10-01

A multiphysics computational model has been developed for the conventional Gas Metal Arc Welding (GMAW) joining process and used to analyze butt-welding of MIL A46100, a prototypical high-hardness armor martensitic steel. The model consists of five distinct modules, each covering a specific aspect of the GMAW process, i.e., (a) dynamics of welding-gun behavior; (b) heat transfer from the electric arc and mass transfer from the electrode to the weld; (c) development of thermal and mechanical fields during the GMAW process; (d) the associated evolution and spatial distribution of the material microstructure throughout the weld region; and (e) the final spatial distribution of the as-welded material properties. To make the newly developed GMAW process model applicable to MIL A46100, the basic physical-metallurgy concepts and principles for this material have to be investigated and properly accounted for/modeled. The newly developed GMAW process model enables establishment of the relationship between the GMAW process parameters (e.g., open circuit voltage, welding current, electrode diameter, electrode-tip/weld distance, filler-metal feed speed, and gun travel speed), workpiece material chemistry, and the spatial distribution of as-welded material microstructure and properties. The predictions of the present GMAW model pertaining to the spatial distribution of the material microstructure and properties within the MIL A46100 weld region are found to be consistent with general expectations and prior observations.

A thermodynamic approach to obtain materials properties for engineering applications

NASA Technical Reports Server (NTRS)

Chang, Y. Austin

1993-01-01

With the ever increases in the capabilities of computers for numerical computations, we are on the verge of using these tools to model manufacturing processes for improving the efficiency of these processes as well as the quality of the products. One such process is casting for the production of metals. However, in order to model metal casting processes in a meaningful way it is essential to have the basic properties of these materials in their molten state, solid state as well as in the mixed state of solid and liquid. Some of the properties needed may be considered as intrinsic such as the density, heat capacity or enthalpy of freezing of a pure metal, while others are not. For instance, the enthalpy of solidification of an alloy is not a defined thermodynamic quantity. Its value depends on the micro-segregation of the phases during the course of solidification. The objective of the present study is to present a thermodynamic approach to obtain some of the intrinsic properties and combining thermodynamics with kinetic models to estimate such quantities as the enthalpy of solidification of an alloy.

Predictive modeling of solidification during laser additive manufacturing of nickel superalloys: recent developments, future directions

NASA Astrophysics Data System (ADS)

Ghosh, Supriyo

2018-01-01

Additive manufacturing (AM) processes produce parts with improved physical, chemical, and mechanical properties compared to conventional manufacturing processes. In AM processes, intricate part geometries are produced from multicomponent alloy powder, in a layer-by-layer fashion with multipass laser melting, solidification, and solid-state phase transformations, in a shorter manufacturing time, with minimal surface finishing, and at a reasonable cost. However, there is an increasing need for post-processing of the manufactured parts via, for example, stress relieving heat treatment and hot isostatic pressing to achieve homogeneous microstructure and properties at all times. Solidification in an AM process controls the size, shape, and distribution of the grains, the growth morphology, the elemental segregation and precipitation, the subsequent solid-state phase changes, and ultimately the material properties. The critical issues in this process are linked with multiphysics (such as fluid flow and diffusion of heat and mass) and multiscale (lengths, times and temperature ranges) challenges that arise due to localized rapid heating and cooling during AM processing. The alloy chemistry-process-microstructure-property-performance correlation in this process will be increasingly better understood through multiscale modeling and simulation.

A model framework to represent plant-physiology and rhizosphere processes in soil profile simulation models

NASA Astrophysics Data System (ADS)

Vanderborght, J.; Javaux, M.; Couvreur, V.; Schröder, N.; Huber, K.; Abesha, B.; Schnepf, A.; Vereecken, H.

2013-12-01

Plant roots play a crucial role in several key processes in soils. Besides their impact on biogeochemical cycles and processes, they also have an important influence on physical processes such as water flow and transport of dissolved substances in soils. Interaction between plant roots and soil processes takes place at different scales and ranges from the scale of an individual root and its directly surrounding soil or rhizosphere over the scale of a root system of an individual plant in a soil profile to the scale of vegetation patterns in landscapes. Simulation models that are used to predict water flow and solute transport in soil-plant systems mainly focus on the individual plant root system scale, parameterize single-root scale phenomena, and aggregate the root system scale to the vegetation scale. In this presentation, we will focus on the transition from the single root to the root system scale. Using high resolution non-invasive imaging techniques and methods, gradients in soil properties and states around roots and their difference from the bulk soil properties could be demonstrated. Recent developments in plant sciences provide new insights in the mechanisms that control water fluxes in plants and in the adaptation of root properties or root plasticity to changing soil conditions. However, since currently used approaches to simulate root water uptake neither resolve these small scale processes nor represent processes and controls within the root system, transferring this information to the whole soil-plant system scale is a challenge. Using a simulation model that describes flow and transport processes in the soil, resolves flow and transport towards individual roots, and describes flow and transport within the root system, such a transfer could be achieved. We present a few examples that illustrate: (i) the impact of changed rhizosphere hydraulic properties, (ii) the effect of root hydraulic properties and root system architecture, (iii) the regulation of plant transpiration by root-zone produced plant hormones, and (iv) the impact of salt accumulation at the soil-root interface on root water uptake. We further propose a framework how this process knowledge could be implemented in root zone simulation models that do not resolve small scale processes.

A first attempt to reproduce basaltic soil chronosequences using a process-based soil profile model: implications for our understanding of soil evolution

NASA Astrophysics Data System (ADS)

Johnson, M.; Gloor, M.; Lloyd, J.

2012-04-01

Soils are complex systems which hold a wealth of information on both current and past conditions and many biogeochemical processes. The ability to model soil forming processes and predict soil properties will enable us to quantify such conditions and contribute to our understanding of long-term biogeochemical cycles, particularly the carbon cycle and plant nutrient cycles. However, attempts to confront such soil model predictions with data are rare, although increasingly more data from chronosquence studies is becoming available for such a purpose. Here we present initial results of an attempt to reproduce soil properties with a process-based soil evolution model similar to the model of Kirkby (1985, J. Soil Science). We specifically focus on the basaltic soils in both Hawaii and north Queensland, Australia. These soils are formed on a series of volcanic lava flows which provide sequences of different aged soils all with a relatively uniform parent material. These soil chronosequences provide a snapshot of a soil profile during different stages of development. Steep rainfall gradients in these regions also provide a system which allows us to test the model's ability to reproduce soil properties under differing climates. The mechanistic, soil evolution model presented here includes the major processes of soil formation such as i) mineral weathering, ii) percolation of rainfall through the soil, iii) leaching of solutes out of the soil profile iv) surface erosion and v) vegetation and biotic interactions. The model consists of a vertical profile and assumes simple geometry with a constantly sloping surface. The timescales of interest are on the order of tens to hundreds of thousand years. The specific properties the model predicts are, soil depth, the proportion of original elemental oxides remaining in each soil layer, pH of the soil solution, organic carbon distribution and CO2 production and concentration. The presentation will focus on a brief introduction of the model, followed by a description of novel methods using tracers such as optically stimulated luminescence (OSL) dates and meteoric 10Be to evaluate the modelled processes of bioturbation and surface erosion. We will also discuss comparisons of modelled properties with observations and conclude with implications on our understanding of soil evolution.

Cirrus Susceptibility to Changes in Ice Nuclei: Physical Processes, Model Uncertainties, and Measurement Needs

NASA Technical Reports Server (NTRS)

Jensen, Eric

2018-01-01

One of the proposed concepts for mitigating the warming effect of increasing greenhouse gases is seeding cirrus cloud with ice nuclei (IN) in order to reduce the lifetime and coverage of cold cirrus that have a net warming impact on the earth's surface. Global model simulations of the net impact of changing upper tropospheric IN have given widely disparate results, partly as a result of poor understanding of ice nucleation processes in the current atmosphere, and partly as a result of poor representation of these processes in global models. Here, we present detailed process-model simulations of tropical tropopause layer (TTL) transport and cirrus formation with ice nuclei properties based on recent laboratory nucleation experiments and field measurements of aerosol composition. The model is used to assess the sensitivity of TTL cirrus occurrence frequency and microphysical properties to the abundance and efficacy of ice nuclei. The simulated cloud properties compared with recent high-altitude aircraft measurements of TTL cirrus and ice supersaturation. We find that abundant effective IN (either from glassy organic aerosols or crystalline ammonium sulfate with concentrations greater than about 100/L) prevent the occurrences of large ice concentration and large ice supersaturations, both of which are clearly indicated by the in situ observations. We find that concentrations of effective ice nuclei larger than about 50/L can drive significant changes in cirrus microphysical properties and occurrence frequency. However, the cloud occurrence frequency can either increase or decrease, depending on the efficacy and abundance of IN added to the TTL. We suggest that our lack of information about ice nuclei properties in the current atmosphere, as well as uncertainties in ice nucleation processes and their representations in global models, preclude meaningful estimates of climate impacts associated with addition of ice nuclei in the upper troposphere. We will briefly discuss the key field measurements needed to constrain ice nucleation processes.

Heat Transfer Modeling of an Annular On-Line Spray Water Cooling Process for Electric-Resistance-Welded Steel Pipe

PubMed Central

Chen, Zejun; Han, Huiquan; Ren, Wei; Huang, Guangjie

2015-01-01

On-line spray water cooling (OSWC) of electric-resistance-welded (ERW) steel pipes can replace the conventional off-line heat treatment process and become an important and critical procedure. The OSWC process improves production efficiency, decreases costs, and enhances the mechanical properties of ERW steel pipe, especially the impact properties of the weld joint. In this paper, an annular OSWC process is investigated based on an experimental simulation platform that can obtain precise real-time measurements of the temperature of the pipe, the water pressure and flux, etc. The effects of the modes of annular spray water cooling and related cooling parameters on the mechanical properties of the pipe are investigated. The temperature evolutions of the inner and outer walls of the pipe are measured during the spray water cooling process, and the uniformity of mechanical properties along the circumferential and longitudinal directions is investigated. A heat transfer coefficient model of spray water cooling is developed based on measured temperature data in conjunction with simulation using the finite element method. Industrial tests prove the validity of the heat transfer model of a steel pipe undergoing spray water cooling. The research results can provide a basis for the industrial application of the OSWC process in the production of ERW steel pipes. PMID:26201073

Heat Transfer Modeling of an Annular On-Line Spray Water Cooling Process for Electric-Resistance-Welded Steel Pipe.

PubMed

Chen, Zejun; Han, Huiquan; Ren, Wei; Huang, Guangjie

2015-01-01

On-line spray water cooling (OSWC) of electric-resistance-welded (ERW) steel pipes can replace the conventional off-line heat treatment process and become an important and critical procedure. The OSWC process improves production efficiency, decreases costs, and enhances the mechanical properties of ERW steel pipe, especially the impact properties of the weld joint. In this paper, an annular OSWC process is investigated based on an experimental simulation platform that can obtain precise real-time measurements of the temperature of the pipe, the water pressure and flux, etc. The effects of the modes of annular spray water cooling and related cooling parameters on the mechanical properties of the pipe are investigated. The temperature evolutions of the inner and outer walls of the pipe are measured during the spray water cooling process, and the uniformity of mechanical properties along the circumferential and longitudinal directions is investigated. A heat transfer coefficient model of spray water cooling is developed based on measured temperature data in conjunction with simulation using the finite element method. Industrial tests prove the validity of the heat transfer model of a steel pipe undergoing spray water cooling. The research results can provide a basis for the industrial application of the OSWC process in the production of ERW steel pipes.

Statistical properties of superimposed stationary spike trains.

PubMed

Deger, Moritz; Helias, Moritz; Boucsein, Clemens; Rotter, Stefan

2012-06-01

The Poisson process is an often employed model for the activity of neuronal populations. It is known, though, that superpositions of realistic, non- Poisson spike trains are not in general Poisson processes, not even for large numbers of superimposed processes. Here we construct superimposed spike trains from intracellular in vivo recordings from rat neocortex neurons and compare their statistics to specific point process models. The constructed superimposed spike trains reveal strong deviations from the Poisson model. We find that superpositions of model spike trains that take the effective refractoriness of the neurons into account yield a much better description. A minimal model of this kind is the Poisson process with dead-time (PPD). For this process, and for superpositions thereof, we obtain analytical expressions for some second-order statistical quantities-like the count variability, inter-spike interval (ISI) variability and ISI correlations-and demonstrate the match with the in vivo data. We conclude that effective refractoriness is the key property that shapes the statistical properties of the superposition spike trains. We present new, efficient algorithms to generate superpositions of PPDs and of gamma processes that can be used to provide more realistic background input in simulations of networks of spiking neurons. Using these generators, we show in simulations that neurons which receive superimposed spike trains as input are highly sensitive for the statistical effects induced by neuronal refractoriness.

Microbial production of polyhydroxybutyrate with tailor-made properties: an integrated modelling approach and experimental validation.

PubMed

Penloglou, Giannis; Chatzidoukas, Christos; Kiparissides, Costas

2012-01-01

The microbial production of polyhydroxybutyrate (PHB) is a complex process in which the final quantity and quality of the PHB depend on a large number of process operating variables. Consequently, the design and optimal dynamic operation of a microbial process for the efficient production of PHB with tailor-made molecular properties is an extremely interesting problem. The present study investigates how key process operating variables (i.e., nutritional and aeration conditions) affect the biomass production rate and the PHB accumulation in the cells and its associated molecular weight distribution. A combined metabolic/polymerization/macroscopic modelling approach, relating the process performance and product quality with the process variables, was developed and validated using an extensive series of experiments and measurements. The model predicts the dynamic evolution of the biomass growth, the polymer accumulation, the consumption of carbon and nitrogen sources and the average molecular weights of the PHB in a bioreactor, under batch and fed-batch operating conditions. The proposed integrated model was used for the model-based optimization of the production of PHB with tailor-made molecular properties in Azohydromonas lata bacteria. The process optimization led to a high intracellular PHB accumulation (up to 95% g of PHB per g of DCW) and the production of different grades (i.e., different molecular weight distributions) of PHB. Copyright © 2011 Elsevier Inc. All rights reserved.

First-passage and escape problems in the Feller process

NASA Astrophysics Data System (ADS)

Masoliver, Jaume; Perelló, Josep

2012-10-01

The Feller process is an one-dimensional diffusion process with linear drift and state-dependent diffusion coefficient vanishing at the origin. The process is positive definite and it is this property along with its linear character that have made Feller process a convenient candidate for the modeling of a number of phenomena ranging from single-neuron firing to volatility of financial assets. While general properties of the process have long been well known, less known are properties related to level crossing such as the first-passage and the escape problems. In this work we thoroughly address these questions.

Comparative Analyses of Creep Models of a Solid Propellant

NASA Astrophysics Data System (ADS)

Zhang, J. B.; Lu, B. J.; Gong, S. F.; Zhao, S. P.

2018-05-01

The creep experiments of a solid propellant samples under five different stresses are carried out at 293.15 K and 323.15 K. In order to express the creep properties of this solid propellant, the viscoelastic model i.e. three Parameters solid, three Parameters fluid, four Parameters solid, four Parameters fluid and exponential model are involved. On the basis of the principle of least squares fitting, and different stress of all the parameters for the models, the nonlinear fitting procedure can be used to analyze the creep properties. The study shows that the four Parameters solid model can best express the behavior of creep properties of the propellant samples. However, the three Parameters solid and exponential model cannot very well reflect the initial value of the creep process, while the modified four Parameters models are found to agree well with the acceleration characteristics of the creep process.

Jet production and fragmentation properties in deep inelastic muon scattering

NASA Astrophysics Data System (ADS)

Arneodo, M.; Arvidson, A.; Aubert, J. J.; Badelek, B.; Beaufays, J.; Bee, C. P.; Benchouk, C.; Berghoff, G.; Bird, I.; Blum, D.; Böhm, E.; de Bouard, X.; Brasse, F. W.; Braun, H.; Broll, C.; Brown, S.; Brück, H.; Calen, H.; Chima, J. S.; Ciborowski, J.; Clifft, R.; Coignet, G.; Combley, F.; Conrad, J.; Coughlan, J.; D'Agostini, G.; Dahlgren, S.; Dengler, F.; Derado, I.; Dreyer, T.; Drees, J.; Drobnitzki, M.; Düren, M.; Eckardt, V.; Edwards, A.; Edwards, M.; Ernst, T.; Eszes, G.; Favier, J.; Ferrero, M. I.; Figiel, J.; Flauger, W.; Foster, J.; Ftàčnik, J.; Gabathuler, E.; Gajewski, J.; Gamet, R.; Gayler, J.; Geddes, N.; Grafström, P.; Grard, F.; Haas, J.; Hagberg, E.; Hasert, F. J.; Hayman, P.; Heusse, P.; Jaffre, M.; Jacholkowska, A.; Janata, F.; Jancso, G.; Johnson, A. S.; Kabuss, E. M.; Kellner, G.; Korbel, V.; Krüger, A.; Krüger, J.; Kullander, S.; Landgraf, U.; Lanske, D.; Loken, J.; Long, K.; Maire, M.; Malecki, P.; Manz, A.; Maselli, S.; Mohr, W.; Montanet, F.; Montgomery, H. E.; Nagy, E.; Nassalski, J.; Norton, P. R.; Oakham, F. G.; Osborne, A. M.; Pascaud, C.; Pawlik, B.; Payre, P.; Peroni, C.; Peschel, H.; Pessard, H.; Pettingale, J.; Pietrzyk, B.; Pietrzyk, U.; Pönsgen, B.; Pötsch, M.; Renton, P.; Ribarics, P.; Rith, K.; Rondio, E.; Sandacz, A.; Scheer, M.; Schlabböhmer, A.; Schiemann, H.; Schmitz, N.; Schneegans, M.; Scholz, M.; Schröder, T.; Schultze, K.; Sloan, T.; Stier, H. E.; Studt, M.; Taylor, G. N.; Thénard, J. M.; Thompson, J. C.; de La Torre, A.; Toth, J.; Urban, L.; Urban, L.; Wallucks, W.; Whalley, M.; Wheeler, S.; Williams, W. S. C.; Wimpenny, S. J.; Windmolders, R.; Wolf, G.; Ziemons, K.

1987-12-01

Results are presented from a study of deep inelastic 280 GeV muon-nucleon interactions on the transverse momenta and jet properties of the final state hadrons. The results are analysed in a way which attempts to separate the contributions of hard and soft QCD effects from those that arise from the fragmentation process. The fragmentation models with which the data are compared are the Lund string model, the independent jet model, the QCD parton shower model including soft gluon interference effects, and the firestring model. The discrimination between these models is discussed. Various methods of analysis of the data in terms of hard QCD processes are presented. From a study of the properties of the jet profiles a value of α s , to leading order, is determined using the Lund string model, namely α s =0.29±0.01 (stat.) ±0.02 (syst.), for Q 2˜20 GeV2.

Stochastic Processes as True-Score Models for Highly Speeded Mental Tests.

ERIC Educational Resources Information Center

Moore, William E.

The previous theoretical development of the Poisson process as a strong model for the true-score theory of mental tests is discussed, and additional theoretical properties of the model from the standpoint of individual examinees are developed. The paper introduces the Erlang process as a family of test theory models and shows in the context of…

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.

Effects of uniquely processed cowpea and plantain flours on wheat bread properties

USDA-ARS?s Scientific Manuscript database

The effect of incorporating uniquely processed whole-seed cowpeas or plantain flours at 10 or 20 g/100 g in all-purpose flour on paste viscosity and bread-baking properties in model bread was determined. Flours from plantains processed as follows: unblanched plantains dried at 60 degrees C (PLC), so...

Multiscale Modeling of Carbon Fiber Reinforced Polymer (CFRP) for Integrated Computational Materials Engineering Process

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

Gao, Jiaying; Liang, Biao; Zhang, Weizhao

In this work, a multiscale modeling framework for CFRP is introduced to study hierarchical structure of CFRP. Four distinct scales are defined: nanoscale, microscale, mesoscale, and macroscale. Information at lower scales can be passed to higher scale, which is beneficial for studying effect of constituents on macroscale part’s mechanical property. This bottom-up modeling approach enables better understanding of CFRP from finest details. Current study focuses on microscale and mesoscale. Representative volume element is used at microscale and mesoscale to model material’s properties. At microscale, unidirection CFRP (UD) RVE is used to study properties of UD. The UD RVE can bemore » modeled with different volumetric fraction to encounter non-uniform fiber distribution in CFRP part. Such consideration is important in modeling uncertainties at microscale level. Currently, we identified volumetric fraction as the only uncertainty parameters in UD RVE. To measure effective material properties of UD RVE, periodic boundary conditions (PBC) are applied to UD RVE to ensure convergence of obtained properties. Properties of UD is directly used at mesoscale woven RVE modeling, where each yarn is assumed to have same properties as UD. Within woven RVE, there can be many potential uncertainties parameters to consider for a physical modeling of CFRP. Currently, we will consider fiber misalignment within yarn and angle between wrap and weft yarns. PBC is applied to woven RVE to calculate its effective material properties. The effect of uncertainties are investigated quantitatively by Gaussian process. Preliminary results of UD and Woven study are analyzed for efficacy of the RVE modeling. This work is considered as the foundation for future multiscale modeling framework development for ICME project.« less

A process-based model for cattle manure compost windrows: Model performance and application

USDA-ARS?s Scientific Manuscript database

A model was developed and incorporated in the Integrated Farm System Model (IFSM, v.4.3) that simulates important processes occurring during windrow composting of manure. The model, documented in an accompanying paper, predicts changes in windrow properties and conditions and the resulting emissions...

Thermophysical Property Models for Lunar Regolith

NASA Technical Reports Server (NTRS)

Schreiner, Samuel S.; Dominguez, Jesus A.; Sibille, Laurent; Hoffman, Jeffrey A.

2015-01-01

We present a set of models for a wide range of lunar regolith material properties. Data from the literature are t with regression models for the following regolith properties: composition, density, specific heat, thermal conductivity, electrical conductivity, optical absorption length, and latent heat of melting/fusion. These models contain both temperature and composition dependencies so that they can be tailored for a range of applications. These models can enable more consistent, informed analysis and design of lunar regolith processing hardware. Furthermore, these models can be utilized to further inform lunar geological simulations. In addition to regression models for each material property, the raw data is also presented to allow for further interpretation and fitting as necessary.

Multiphysics numerical modeling of the continuous flow microwave-assisted transesterification process.

PubMed

Muley, Pranjali D; Boldor, Dorin

2012-01-01

Use of advanced microwave technology for biodiesel production from vegetable oil is a relatively new technology. Microwave dielectric heating increases the process efficiency and reduces reaction time. Microwave heating depends on various factors such as material properties (dielectric and thermo-physical), frequency of operation and system design. Although lab scale results are promising, it is important to study these parameters and optimize the process before scaling up. Numerical modeling approach can be applied for predicting heating and temperature profiles including at larger scale. The process can be studied for optimization without actually performing the experiments, reducing the amount of experimental work required. A basic numerical model of continuous electromagnetic heating of biodiesel precursors was developed. A finite element model was built using COMSOL Multiphysics 4.2 software by coupling the electromagnetic problem with the fluid flow and heat transfer problem. Chemical reaction was not taken into account. Material dielectric properties were obtained experimentally, while the thermal properties were obtained from the literature (all the properties were temperature dependent). The model was tested for the two different power levels 4000 W and 4700 W at a constant flow rate of 840ml/min. The electric field, electromagnetic power density flow and temperature profiles were studied. Resulting temperature profiles were validated by comparing to the temperatures obtained at specific locations from the experiment. The results obtained were in good agreement with the experimental data.

Glass Property Data and Models for Estimating High-Level Waste Glass Volume

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

Vienna, John D.; Fluegel, Alexander; Kim, Dong-Sang

2009-10-05

This report describes recent efforts to develop glass property models that can be used to help estimate the volume of high-level waste (HLW) glass that will result from vitrification of Hanford tank waste. The compositions of acceptable and processable HLW glasses need to be optimized to minimize the waste-form volume and, hence, to save cost. A database of properties and associated compositions for simulated waste glasses was collected for developing property-composition models. This database, although not comprehensive, represents a large fraction of data on waste-glass compositions and properties that were available at the time of this report. Glass property-composition modelsmore » were fit to subsets of the database for several key glass properties. These models apply to a significantly broader composition space than those previously publised. These models should be considered for interim use in calculating properties of Hanford waste glasses.« less

Simulation of the Press Hardening Process and Prediction of the Final Mechanical Material Properties

NASA Astrophysics Data System (ADS)

Hochholdinger, Bernd; Hora, Pavel; Grass, Hannes; Lipp, Arnulf

2011-08-01

Press hardening is a well-established production process in the automotive industry today. The actual trend of this process technology points towards the manufacturing of parts with tailored properties. Since the knowledge of the mechanical properties of a structural part after forming and quenching is essential for the evaluation of for example the crash performance, an accurate as possible virtual assessment of the production process is more than ever necessary. In order to achieve this, the definition of reliable input parameters and boundary conditions for the thermo-mechanically coupled simulation of the process steps is required. One of the most important input parameters, especially regarding the final properties of the quenched material, is the contact heat transfer coefficient (IHTC). The CHTC depends on the effective pressure or the gap distance between part and tool. The CHTC at different contact pressures and gap distances is determined through inverse parameter identification. Furthermore a simulation strategy for the subsequent steps of the press hardening process as well as adequate modeling approaches for part and tools are discussed. For the prediction of the yield curves of the material after press hardening a phenomenological model is presented. This model requires the knowledge of the microstructure within the part. By post processing the nodal temperature history with a CCT diagram the quantitative distribution of the phase fractions martensite, bainite, ferrite and pearlite after press hardening is determined. The model itself is based on a Hockett-Sherby approach with the Hockett-Sherby parameters being defined in function of the phase fractions and a characteristic cooling rate.

Modeling of Ti-W Solidification Microstructures Under Additive Manufacturing Conditions

NASA Astrophysics Data System (ADS)

Rolchigo, Matthew R.; Mendoza, Michael Y.; Samimi, Peyman; Brice, David A.; Martin, Brian; Collins, Peter C.; LeSar, Richard

2017-07-01

Additive manufacturing (AM) processes have many benefits for the fabrication of alloy parts, including the potential for greater microstructural control and targeted properties than traditional metallurgy processes. To accelerate utilization of this process to produce such parts, an effective computational modeling approach to identify the relationships between material and process parameters, microstructure, and part properties is essential. Development of such a model requires accounting for the many factors in play during this process, including laser absorption, material addition and melting, fluid flow, various modes of heat transport, and solidification. In this paper, we start with a more modest goal, to create a multiscale model for a specific AM process, Laser Engineered Net Shaping (LENS™), which couples a continuum-level description of a simplified beam melting problem (coupling heat absorption, heat transport, and fluid flow) with a Lattice Boltzmann-cellular automata (LB-CA) microscale model of combined fluid flow, solute transport, and solidification. We apply this model to a binary Ti-5.5 wt pct W alloy and compare calculated quantities, such as dendrite arm spacing, with experimental results reported in a companion paper.

Modeling soil processes - are we lost in diversity?

NASA Astrophysics Data System (ADS)

Vogel, Hans-Joerg; Schlüter, Steffen

2015-04-01

Soils are among the most complex environmental systems. Soil functions - e.g. production of biomass, habitat for organisms, reactor for and storage of organic matter, filter for ground water - emerge from a multitude of processes interacting at different scales. It still remains a challenge to model and predict these functions including their stability and resilience towards external perturbations. As an inherent property of complex systems it is prohibitive to unravel all the relevant process in all detail to derive soil functions and their dynamics from first principles. Hence, when modeling soil processes and their interactions one is close to be lost in the overwhelming diversity and spatial heterogeneity of soil properties. In this contribution we suggest to look for characteristic similarities within the hyperdimensional state space of soil properties. The underlying hypothesis is that this state space is not evenly and/or randomly populated but that processes of self organization produce attractors of physical, chemical and biological properties which can be identified. (The formation of characteristic soil horizons is an obvious example). To render such a concept operational a suitable and limited set of indicators is required. Ideally, such indicators are i) related to soil functions, ii) are measurable and iii) are integral measures of the relevant physical, chemical and biological soil properties. This would allow for identifying suitable attractors. We will discuss possible indicators and will focus on soil structure as an especially promising candidate. It governs the availability of water and gas, it effects the spatial distribution of organic matter and, moreover, it forms the habitat of soil organisms and it is formed by soil biota. Quantification of soil structural properties became possible only recently with the development of more powerful tools for non-invasive imaging. Future research need to demonstrate in how far these tools can be used to identify functional soil types (i.e. attractors) allowing for modeling soil processes at an integral level. We provide an example from the 100-years fertilization experiment in Bad-Lauchstädt.

Speech Perception as a Cognitive Process: The Interactive Activation Model.

ERIC Educational Resources Information Center

Elman, Jeffrey L.; McClelland, James L.

Research efforts to model speech perception in terms of a processing system in which knowledge and processing are distributed over large numbers of highly interactive--but computationally primative--elements are described in this report. After discussing the properties of speech that demand a parallel interactive processing system, the report…

Compositional Models of Glass/Melt Properties and their Use for Glass Formulation

DOE PAGES

Vienna, John D.; USA, Richland Washington

2014-12-18

Nuclear waste glasses must simultaneously meet a number of criteria related to their processability, product quality, and cost factors. The properties that must be controlled in glass formulation and waste vitrification plant operation tend to vary smoothly with composition allowing for glass property-composition models to be developed and used. Models have been fit to the key glass properties. The properties are transformed so that simple functions of composition (e.g., linear, polynomial, or component ratios) can be used as model forms. The model forms are fit to experimental data designed statistically to efficiently cover the composition space of interest. Examples ofmore » these models are found in literature. The glass property-composition models, their uncertainty definitions, property constraints, and optimality criteria are combined to formulate optimal glass compositions, control composition in vitrification plants, and to qualify waste glasses for disposal. An overview of current glass property-composition modeling techniques is summarized in this paper along with an example of how those models are applied to glass formulation and product qualification at the planned Hanford high-level waste vitrification plant.« less

Multiphase porous media modelling: A novel approach to predicting food processing performance.

PubMed

Khan, Md Imran H; Joardder, M U H; Kumar, Chandan; Karim, M A

2018-03-04

The development of a physics-based model of food processing is essential to improve the quality of processed food and optimize energy consumption. Food materials, particularly plant-based food materials, are complex in nature as they are porous and have hygroscopic properties. A multiphase porous media model for simultaneous heat and mass transfer can provide a realistic understanding of transport processes and thus can help to optimize energy consumption and improve food quality. Although the development of a multiphase porous media model for food processing is a challenging task because of its complexity, many researchers have attempted it. The primary aim of this paper is to present a comprehensive review of the multiphase models available in the literature for different methods of food processing, such as drying, frying, cooking, baking, heating, and roasting. A critical review of the parameters that should be considered for multiphase modelling is presented which includes input parameters, material properties, simulation techniques and the hypotheses. A discussion on the general trends in outcomes, such as moisture saturation, temperature profile, pressure variation, and evaporation patterns, is also presented. The paper concludes by considering key issues in the existing multiphase models and future directions for development of multiphase models.

Development and evaluation of spatial point process models for epidermal nerve fibers.

PubMed

Olsbo, Viktor; Myllymäki, Mari; Waller, Lance A; Särkkä, Aila

2013-06-01

We propose two spatial point process models for the spatial structure of epidermal nerve fibers (ENFs) across human skin. The models derive from two point processes, Φb and Φe, describing the locations of the base and end points of the fibers. Each point of Φe (the end point process) is connected to a unique point in Φb (the base point process). In the first model, both Φe and Φb are Poisson processes, yielding a null model of uniform coverage of the skin by end points and general baseline results and reference values for moments of key physiologic indicators. The second model provides a mechanistic model to generate end points for each base, and we model the branching structure more directly by defining Φe as a cluster process conditioned on the realization of Φb as its parent points. In both cases, we derive distributional properties for observable quantities of direct interest to neurologists such as the number of fibers per base, and the direction and range of fibers on the skin. We contrast both models by fitting them to data from skin blister biopsy images of ENFs and provide inference regarding physiological properties of ENFs. Copyright © 2013 Elsevier Inc. All rights reserved.

Comparative Analysis on Nonlinear Models for Ron Gasoline Blending Using Neural Networks

NASA Astrophysics Data System (ADS)

Aguilera, R. Carreño; Yu, Wen; Rodríguez, J. C. Tovar; Mosqueda, M. Elena Acevedo; Ortiz, M. Patiño; Juarez, J. J. Medel; Bautista, D. Pacheco

The blending process always being a nonlinear process is difficult to modeling, since it may change significantly depending on the components and the process variables of each refinery. Different components can be blended depending on the existing stock, and the chemical characteristics of each component are changing dynamically, they all are blended until getting the expected specification in different properties required by the customer. One of the most relevant properties is the Octane, which is difficult to control in line (without the component storage). Since each refinery process is quite different, a generic gasoline blending model is not useful when a blending in line wants to be done in a specific process. A mathematical gasoline blending model is presented in this paper for a given process described in state space as a basic gasoline blending process description. The objective is to adjust the parameters allowing the blending gasoline model to describe a signal in its trajectory, representing in neural networks extreme learning machine method and also for nonlinear autoregressive-moving average (NARMA) in neural networks method, such that a comparative work be developed.

Multiscale regression modeling in mouse supraspinatus tendons reveals that dynamic processes act as mediators in structure-function relationships.

PubMed

Connizzo, Brianne K; Adams, Sheila M; Adams, Thomas H; Jawad, Abbas F; Birk, David E; Soslowsky, Louis J

2016-06-14

Recent advances in technology have allowed for the measurement of dynamic processes (re-alignment, crimp, deformation, sliding), but only a limited number of studies have investigated their relationship with mechanical properties. The overall objective of this study was to investigate the role of composition, structure, and the dynamic response to load in predicting tendon mechanical properties in a multi-level fashion mimicking native hierarchical collagen structure. Multiple linear regression models were investigated to determine the relationships between composition/structure, dynamic processes, and mechanical properties. Mediation was then used to determine if dynamic processes mediated structure-function relationships. Dynamic processes were strong predictors of mechanical properties. These predictions were location-dependent, with the insertion site utilizing all four dynamic responses and the midsubstance responding primarily with fibril deformation and sliding. In addition, dynamic processes were moderately predicted by composition and structure in a regionally-dependent manner. Finally, dynamic processes were partial mediators of the relationship between composition/structure and mechanical function, and results suggested that mediation is likely shared between multiple dynamic processes. In conclusion, the mechanical properties at the midsubstance of the tendon are controlled primarily by fibril structure and this region responds to load via fibril deformation and sliding. Conversely, the mechanical function at the insertion site is controlled by many other important parameters and the region responds to load via all four dynamic mechanisms. Overall, this study presents a strong foundation on which to design future experimental and modeling efforts in order to fully understand the complex structure-function relationships present in tendon. Copyright © 2016 Elsevier Ltd. All rights reserved.

Networks for image acquisition, processing and display

NASA Technical Reports Server (NTRS)

Ahumada, Albert J., Jr.

1990-01-01

The human visual system comprises layers of networks which sample, process, and code images. Understanding these networks is a valuable means of understanding human vision and of designing autonomous vision systems based on network processing. Ames Research Center has an ongoing program to develop computational models of such networks. The models predict human performance in detection of targets and in discrimination of displayed information. In addition, the models are artificial vision systems sharing properties with biological vision that has been tuned by evolution for high performance. Properties include variable density sampling, noise immunity, multi-resolution coding, and fault-tolerance. The research stresses analysis of noise in visual networks, including sampling, photon, and processing unit noises. Specific accomplishments include: models of sampling array growth with variable density and irregularity comparable to that of the retinal cone mosaic; noise models of networks with signal-dependent and independent noise; models of network connection development for preserving spatial registration and interpolation; multi-resolution encoding models based on hexagonal arrays (HOP transform); and mathematical procedures for simplifying analysis of large networks.

In-situ measurement of processing properties during fabrication in a production tool

NASA Technical Reports Server (NTRS)

Kranbuehl, D. E.; Haverty, P.; Hoff, M.; Loos, A. C.

1988-01-01

Progress is reported on the use of frequency-dependent electromagnetic measurements (FDEMs) as a single, convenient technique for continuous in situ monitoring of polyester cure during fabrication in a laboratory and manufacturing environment. Preliminary FDEM sensor and modeling work using the Loss-Springer model in order to develop an intelligent closed-loop, sensor-controlled cure process is described. FDEMs using impedance bridges in the Hz to MHz region is found to be ideal for automatically monitoring polyester processing properties continuously throughout the cure cycle.

Processing and mechanical properties of metal-ceramic composites with controlled microstructure formed by reactive metal penetration

NASA Astrophysics Data System (ADS)

Ellerby, Donald Thomas

1999-12-01

Compared to monolithic ceramics, metal-reinforced ceramic composites offer the potential for improved toughness and reliability in ceramic materials. As such, there is significant scientific and commercial interest in the microstructure and properties of metal-ceramic composites. Considerable work has been conducted on modeling the toughening behavior of metal reinforcements in ceramics; however, there has been limited application and testing of these concepts on real systems. Composites formed by newly developed reactive processes now offer the flexibility to systematically control metal-ceramic composite microstructure, and to test some of the property models that have been proposed for these materials. In this work, the effects of metal-ceramic composite microstructure on resistance curve (R-curve) behavior, strength, and reliability were systematically investigated. Al/Al2O3 composites were formed by reactive metal penetration (RMP) of aluminum metal into aluminosilicate ceramic preforms. Processing techniques were developed to control the metal content, metal composition, and metal ligament size in the resultant composite microstructure. Quantitative stereology and microscopy were used to characterize the composite microstructures, and then the influence of microstructure on strength, toughness, R-curve behavior, and reliability, was investigated. To identify the strength limiting flaws in the composite microstructure, fractography was used to determine the failure origins. Additionally, the crack bridging tractions produced by the metal ligaments in metal-ceramic composites formed by the RMP process were modeled. Due to relatively large flaws and low bridging stresses in RMP composites, no dependence of reliability on R-curve behavior was observed. The inherent flaws formed during reactive processing appear to limit the strength and reliability of composites formed by the RMP process. This investigation has established a clear relationship between processing, microstructure, and properties in metal-ceramic composites formed by the RMP process. RMP composite properties are determined by the metal-ceramic composite microstructure (e.g., metal content and ligament size), which can be systematically varied by processing. Furthermore, relative to the ceramic preforms used to make the composites, metal-ceramic composites formed by RMP generally have improved properties and combinations of properties that make them more desirable for advanced engineering applications.

Spatio-Temporal Data Analysis at Scale Using Models Based on Gaussian Processes

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

Stein, Michael

Gaussian processes are the most commonly used statistical model for spatial and spatio-temporal processes that vary continuously. They are broadly applicable in the physical sciences and engineering and are also frequently used to approximate the output of complex computer models, deterministic or stochastic. We undertook research related to theory, computation, and applications of Gaussian processes as well as some work on estimating extremes of distributions for which a Gaussian process assumption might be inappropriate. Our theoretical contributions include the development of new classes of spatial-temporal covariance functions with desirable properties and new results showing that certain covariance models lead tomore » predictions with undesirable properties. To understand how Gaussian process models behave when applied to deterministic computer models, we derived what we believe to be the first significant results on the large sample properties of estimators of parameters of Gaussian processes when the actual process is a simple deterministic function. Finally, we investigated some theoretical issues related to maxima of observations with varying upper bounds and found that, depending on the circumstances, standard large sample results for maxima may or may not hold. Our computational innovations include methods for analyzing large spatial datasets when observations fall on a partially observed grid and methods for estimating parameters of a Gaussian process model from observations taken by a polar-orbiting satellite. In our application of Gaussian process models to deterministic computer experiments, we carried out some matrix computations that would have been infeasible using even extended precision arithmetic by focusing on special cases in which all elements of the matrices under study are rational and using exact arithmetic. The applications we studied include total column ozone as measured from a polar-orbiting satellite, sea surface temperatures over the Pacific Ocean, and annual temperature extremes at a site in New York City. In each of these applications, our theoretical and computational innovations were directly motivated by the challenges posed by analyzing these and similar types of data.« less

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 method to investigate the diffusion properties of nuclear calcium.

PubMed

Queisser, Gillian; Wittum, Gabriel

2011-10-01

Modeling biophysical processes in general requires knowledge about underlying biological parameters. The quality of simulation results is strongly influenced by the accuracy of these parameters, hence the identification of parameter values that the model includes is a major part of simulating biophysical processes. In many cases, secondary data can be gathered by experimental setups, which are exploitable by mathematical inverse modeling techniques. Here we describe a method for parameter identification of diffusion properties of calcium in the nuclei of rat hippocampal neurons. The method is based on a Gauss-Newton method for solving a least-squares minimization problem and was formulated in such a way that it is ideally implementable in the simulation platform uG. Making use of independently published space- and time-dependent calcium imaging data, generated from laser-assisted calcium uncaging experiments, here we could identify the diffusion properties of nuclear calcium and were able to validate a previously published model that describes nuclear calcium dynamics as a diffusion process.

Characterizing Organic Aerosol Processes and Climatically Relevant Properties via Advanced and Integrated Analyses of Aerosol Mass Spectrometry Datasets from DOE Campaigns and ACRF Measurements. Final report for DE-SC0007178

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

Zhang, Qi

Organic aerosols (OA) are an important but poorly characterized component of the earth’s climate system. Enormous complexities commonly associated with OA composition and life cycle processes have significantly complicated the simulation and quantification of aerosol effects. To unravel these complexities and improve understanding of the properties, sources, formation, evolution processes, and radiative properties of atmospheric OA, we propose to perform advanced and integrated analyses of multiple DOE aerosol mass spectrometry datasets, including two high-resolution time-of-flight aerosol mass spectrometer (HR-AMS) datasets from intensive field campaigns on the aerosol life cycle and the Aerosol Chemical Speciation Monitor (ACSM) datasets from long-term routinemore » measurement programs at ACRF sites. In this project, we will focus on 1) characterizing the chemical (i.e., composition, organic elemental ratios), physical (i.e., size distribution and volatility), and radiative (i.e., sub- and super-saturated growth) properties of organic aerosols, 2) examining the correlations of these properties with different source and process regimes (e.g., primary, secondary, urban, biogenic, biomass burning, marine, or mixtures), 3) quantifying the evolutions of these properties as a function of photochemical processing, 4) identifying and characterizing special cases for important processes such as SOA formation and new particle formation and growth, and 5) correlating size-resolved aerosol chemistry with measurements of radiative properties of aerosols to determine the climatically relevant properties of OA and characterize the relationship between these properties and processes of atmospheric aerosol organics. Our primary goal is to improve a process-level understanding of the life cycle of organic aerosols in the Earth’s atmosphere. We will also aim at bridging between observations and models via synthesizing and translating the results and insights generated from this research into data products and formulations that may be directly used to inform, improve, and evaluate regional and global models. In addition, we will continue our current very active collaborations with several modeling groups to enhance the use and interpretation of our data products. Overall, this research will contribute new data to improve quantification of the aerosol’s effects on climate and thus the achievement of ASR’s science goal of – “improving the fidelity and predictive capability of global climate models”.« less

Physics at a 100 TeV pp Collider: Standard Model Processes

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

Mangano, M. L.; Zanderighi, G.; Aguilar Saavedra, J. A.

This report summarises the properties of Standard Model processes at the 100 TeV pp collider. We document the production rates and typical distributions for a number of benchmark Standard Model processes, and discuss new dynamical phenomena arising at the highest energies available at this collider. We discuss the intrinsic physics interest in the measurement of these Standard Model processes, as well as their role as backgrounds for New Physics searches.

A Chemical Properties Simulator to Support Integrated Environmental Modeling

EPA Science Inventory

Users of Integrated Environmental Modeling (IEM) systems are responsible for defining individual chemicals and their properties, a process that is time-consuming at best and overwhelming at worst, especially for new chemicals with new structures. A software tool is needed to allo...

Evaluating a process-based model for use in streambank stabilization and stream restoration: insights on the bank stability and toe erosion model (BSTEM)

USDA-ARS?s Scientific Manuscript database

Streambank retreat is a complex cyclical process involving subaerial processes, fluvial erosion, seepage erosion, and geotechnical failures and is driven by several soil properties that themselves are temporally and spatially variable. Therefore, it can be extremely challenging to predict and model ...

Modeling of heat transfer in compacted machining chips during friction consolidation process

NASA Astrophysics Data System (ADS)

Abbas, Naseer; Deng, Xiaomin; Li, Xiao; Reynolds, Anthony

2018-04-01

The current study aims to provide an understanding of the heat transfer process in compacted aluminum alloy AA6061 machining chips during the friction consolidation process (FCP) through experimental investigations and mathematical modelling and numerical simulation. Compaction and friction consolidation of machining chips is the first stage of the Friction Extrusion Process (FEP), which is a novel method for recycling machining chips to produce useful products such as wires. In this study, compacted machining chips are modelled as a continuum whose material properties vary with density during friction consolidation. Based on density and temperature dependent thermal properties, the temperature field in the chip material and process chamber caused by frictional heating during the friction consolidation process is predicted. The predicted temperature field is found to compare well with temperature measurements at select points where such measurements can be made using thermocouples.

Perceptual asymmetry in texture perception.

PubMed

Williams, D; Julesz, B

1992-07-15

A fundamental property of human visual perception is our ability to distinguish between textures. A concerted effort has been made to account for texture segregation in terms of linear spatial filter models and their nonlinear extensions. However, for certain texture pairs the ease of discrimination changes when the role of figure and ground are reversed. This asymmetry poses a problem for both linear and nonlinear models. We have isolated a property of texture perception that can account for this asymmetry in discrimination: subjective closure. This property, which is also responsible for visual illusions, appears to be explainable by early visual processes alone. Our results force a reexamination of the process of human texture segregation and of some recent models that were introduced to explain it.

Systems view on spatial planning and perception based on invariants in agent-environment dynamics

PubMed Central

Mettler, Bérénice; Kong, Zhaodan; Li, Bin; Andersh, Jonathan

2015-01-01

Modeling agile and versatile spatial behavior remains a challenging task, due to the intricate coupling of planning, control, and perceptual processes. Previous results have shown that humans plan and organize their guidance behavior by exploiting patterns in the interactions between agent or organism and the environment. These patterns, described under the concept of Interaction Patterns (IPs), capture invariants arising from equivalences and symmetries in the interaction with the environment, as well as effects arising from intrinsic properties of human control and guidance processes, such as perceptual guidance mechanisms. The paper takes a systems' perspective, considering the IP as a unit of organization, and builds on its properties to present a hierarchical model that delineates the planning, control, and perceptual processes and their integration. The model's planning process is further elaborated by showing that the IP can be abstracted, using spatial time-to-go functions. The perceptual processes are elaborated from the hierarchical model. The paper provides experimental support for the model's ability to predict the spatial organization of behavior and the perceptual processes. PMID:25628524

Thermal and Mechanical Property Characterization of the Advanced Disk Alloy LSHR

NASA Technical Reports Server (NTRS)

Gabb, Timothy P.; Gayda, John; Telesman, Jack; Kantzos, Peter T.

2005-01-01

A low solvus, high refractory (LSHR) powder metallurgy disk alloy was recently designed using experimental screening and statistical modeling of composition and processing variables on sub-scale disks to have versatile processing-property capabilities for advanced disk applications. The objective of the present study was to produce a scaled-up disk and apply varied heat treat processes to enable full-scale demonstration of LSHR properties. Scaled-up disks were produced, heat treated, sectioned, and then machined into specimens for mechanical testing. Results indicate the LSHR alloy can be processed to produce fine and coarse grain microstructures with differing combinations of strength and time-dependent mechanical properties, for application at temperatures exceeding 1300 F.

A Chemical Properties Simulator to Support Integrated Environmental Modeling (proceeding)

EPA Science Inventory

Users of Integrated Environmental Modeling (IEM) systems are responsible for defining individual chemicals and their properties, a process that is time-consuming at best and overwhelming at worst, especially for new chemicals with new structures. A software tool is needed to allo...

Computer program for analysis of split-Stirling-cycle cryogenic coolers

NASA Technical Reports Server (NTRS)

Brown, M. T.; Russo, S. C.

1983-01-01

A computer program for predicting the detailed thermodynamic performance of split-Stirling-cycle refrigerators has been developed. The mathematical model includes the refrigerator cold head, free-displacer/regenerator, gas transfer line, and provision for modeling a mechanical or thermal compressor. To allow for dynamic processes (such as aerodynamic friction and heat transfer) temperature, pressure, and mass flow rate are varied by sub-dividing the refrigerator into an appropriate number of fluid and structural control volumes. Of special importance to modeling of cryogenic coolers is the inclusion of real gas properties, and allowance for variation of thermo-physical properties such as thermal conductivities, specific heats and viscosities, with temperature and/or pressure. The resulting model, therefore, comprehensively simulates the split-cycle cooler both spatially and temporally by reflecting the effects of dynamic processes and real material properties.

Modeling the spray casting process

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

El-Haggar, S.M.; Muoio, N.; Crowe, C.T.

1995-12-31

Spray forming is a process in which a liquid metal is atomized into very small droplets and deposited on a substrate. These small droplets cool very rapidly in a high velocity gas jet, giving rise to smaller grain structure and improved mechanical properties. This paper presents a numerical model, based on the trajectory approach, for the velocity and thermal properties of the droplets in the jet and predicts the deposition pattern and the state of the droplets upon contact with the substrate.

Computational Modeling as a Design Tool in Microelectronics Manufacturing

NASA Technical Reports Server (NTRS)

Meyyappan, Meyya; Arnold, James O. (Technical Monitor)

1997-01-01

Plans to introduce pilot lines or fabs for 300 mm processing are in progress. The IC technology is simultaneously moving towards 0.25/0.18 micron. The convergence of these two trends places unprecedented stringent demands on processes and equipments. More than ever, computational modeling is called upon to play a complementary role in equipment and process design. The pace in hardware/process development needs a matching pace in software development: an aggressive move towards developing "virtual reactors" is desirable and essential to reduce design cycle and costs. This goal has three elements: reactor scale model, feature level model, and database of physical/chemical properties. With these elements coupled, the complete model should function as a design aid in a CAD environment. This talk would aim at the description of various elements. At the reactor level, continuum, DSMC(or particle) and hybrid models will be discussed and compared using examples of plasma and thermal process simulations. In microtopography evolution, approaches such as level set methods compete with conventional geometric models. Regardless of the approach, the reliance on empricism is to be eliminated through coupling to reactor model and computational surface science. This coupling poses challenging issues of orders of magnitude variation in length and time scales. Finally, database development has fallen behind; current situation is rapidly aggravated by the ever newer chemistries emerging to meet process metrics. The virtual reactor would be a useless concept without an accompanying reliable database that consists of: thermal reaction pathways and rate constants, electron-molecule cross sections, thermochemical properties, transport properties, and finally, surface data on the interaction of radicals, atoms and ions with various surfaces. Large scale computational chemistry efforts are critical as experiments alone cannot meet database needs due to the difficulties associated with such controlled experiments and costs.

Continuous melt granulation: Influence of process and formulation parameters upon granule and tablet properties.

PubMed

Monteyne, Tinne; Vancoillie, Jochem; Remon, Jean-Paul; Vervaet, Chris; De Beer, Thomas

2016-10-01

The pharmaceutical industry has a growing interest in alternative manufacturing models allowing automation and continuous production in order to improve process efficiency and reduce costs. Implementing a switch from batch to continuous processing requires fundamental process understanding and the implementation of quality-by-design (QbD) principles. The aim of this study was to examine the relationship between formulation-parameters (type binder, binder concentration, drug-binder miscibility), process-parameters (screw speed, powder feed rate and granulation temperature), granule properties (size, size distribution, shape, friability, true density, flowability) and tablet properties (tensile strength, friability, dissolution rate) of four different drug-binder formulations using Design of experiments (DOE). Two binders (polyethylene glycol (PEG) and Soluplus®) with a different solid state, semi-crystalline vs amorphous respectively, were combined with two model-drugs, metoprolol tartrate (MPT) and caffeine anhydrous (CAF), both having a contrasting miscibility with the binders. This research revealed that the granule properties of miscible drug-binder systems depended on the powder feed rate and barrel filling degree of the granulator whereas the granule properties of immiscible systems were mainly influenced by binder concentration. Using an amorphous binder, the tablet tensile strength depended on the granule size. In contrast, granule friability was more important for tablet quality using a brittle binder. However, this was not the case for caffeine-containing blends, since these phenomena were dominated by the enhanced compression properties of caffeine Form I, which was formed during granulation. Hence, it is important to gain knowledge about formulation behavior during processing since this influences the effect of process parameters onto the granule and tablet properties. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

High Temperature Composites: Properties, Processing and Performance

DTIC Science & Technology

1998-05-21

of Titanium Matrix Composite: Models and Mechanisms Schroedter, Robert D. M.S. Mesoscale Damage Modeling of the Laminated Carbon Fiber- Polyimide...materials are between 800 and 1000 °C. Therefor, understanding the effects of high temperature aging on the mechanical properties is essential. Fig...will grow. Our approach was to isolate the effect of each sintering phenomena in order to understand how they related to mechanical properties

Improving the spatial representation of soil properties and hydrology using topographically derived initialization processes in the SWAT model

USDA-ARS?s Scientific Manuscript database

Topography exerts critical controls on many hydrologic, geomorphologic, and environmental biophysical processes. Unfortunately many watershed modeling systems use topography only to define basin boundaries and stream channels and do not explicitly account for the topographic controls on processes su...

Product/Process (P/P) Models For The Defense Waste Processing Facility (DWPF): Model Ranges And Validation Ranges For Future Processing

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

Jantzen, C.; Edwards, T.

Radioactive high level waste (HLW) at the Savannah River Site (SRS) has successfully been vitrified into borosilicate glass in the Defense Waste Processing Facility (DWPF) since 1996. Vitrification requires stringent product/process (P/P) constraints since the glass cannot be reworked once it is poured into ten foot tall by two foot diameter canisters. A unique “feed forward” statistical process control (SPC) was developed for this control rather than statistical quality control (SQC). In SPC, the feed composition to the DWPF melter is controlled prior to vitrification. In SQC, the glass product would be sampled after it is vitrified. Individual glass property-compositionmore » models form the basis for the “feed forward” SPC. The models transform constraints on the melt and glass properties into constraints on the feed composition going to the melter in order to guarantee, at the 95% confidence level, that the feed will be processable and that the durability of the resulting waste form will be acceptable to a geologic repository.« less

A unified inversion scheme to process multifrequency measurements of various dispersive electromagnetic properties

NASA Astrophysics Data System (ADS)

Han, Y.; Misra, S.

2018-04-01

Multi-frequency measurement of a dispersive electromagnetic (EM) property, such as electrical conductivity, dielectric permittivity, or magnetic permeability, is commonly analyzed for purposes of material characterization. Such an analysis requires inversion of the multi-frequency measurement based on a specific relaxation model, such as Cole-Cole model or Pelton's model. We develop a unified inversion scheme that can be coupled to various type of relaxation models to independently process multi-frequency measurement of varied EM properties for purposes of improved EM-based geomaterial characterization. The proposed inversion scheme is firstly tested in few synthetic cases in which different relaxation models are coupled into the inversion scheme and then applied to multi-frequency complex conductivity, complex resistivity, complex permittivity, and complex impedance measurements. The method estimates up to seven relaxation-model parameters exhibiting convergence and accuracy for random initializations of the relaxation-model parameters within up to 3-orders of magnitude variation around the true parameter values. The proposed inversion method implements a bounded Levenberg algorithm with tuning initial values of damping parameter and its iterative adjustment factor, which are fixed in all the cases shown in this paper and irrespective of the type of measured EM property and the type of relaxation model. Notably, jump-out step and jump-back-in step are implemented as automated methods in the inversion scheme to prevent the inversion from getting trapped around local minima and to honor physical bounds of model parameters. The proposed inversion scheme can be easily used to process various types of EM measurements without major changes to the inversion scheme.

A framework for the computer-aided planning and optimisation of manufacturing processes for components with functional graded properties

NASA Astrophysics Data System (ADS)

Biermann, D.; Gausemeier, J.; Heim, H.-P.; Hess, S.; Petersen, M.; Ries, A.; Wagner, T.

2014-05-01

In this contribution a framework for the computer-aided planning and optimisation of functional graded components is presented. The framework is divided into three modules - the "Component Description", the "Expert System" for the synthetisation of several process chains and the "Modelling and Process Chain Optimisation". The Component Description module enhances a standard computer-aided design (CAD) model by a voxel-based representation of the graded properties. The Expert System synthesises process steps stored in the knowledge base to generate several alternative process chains. Each process chain is capable of producing components according to the enhanced CAD model and usually consists of a sequence of heating-, cooling-, and forming processes. The dependencies between the component and the applied manufacturing processes as well as between the processes themselves need to be considered. The Expert System utilises an ontology for that purpose. The ontology represents all dependencies in a structured way and connects the information of the knowledge base via relations. The third module performs the evaluation of the generated process chains. To accomplish this, the parameters of each process are optimised with respect to the component specification, whereby the result of the best parameterisation is used as representative value. Finally, the process chain which is capable of manufacturing a functionally graded component in an optimal way regarding to the property distributions of the component description is presented by means of a dedicated specification technique.

Interference among the Processing of Facial Emotion, Face Race, and Face Gender.

PubMed

Li, Yongna; Tse, Chi-Shing

2016-01-01

People can process multiple dimensions of facial properties simultaneously. Facial processing models are based on the processing of facial properties. The current study examined the processing of facial emotion, face race, and face gender using categorization tasks. The same set of Chinese, White and Black faces, each posing a neutral, happy or angry expression, was used in three experiments. Facial emotion interacted with face race in all the tasks. The interaction of face race and face gender was found in the race and gender categorization tasks, whereas the interaction of facial emotion and face gender was significant in the emotion and gender categorization tasks. These results provided evidence for a symmetric interaction between variant facial properties (emotion) and invariant facial properties (race and gender).

Interference among the Processing of Facial Emotion, Face Race, and Face Gender

PubMed Central

Li, Yongna; Tse, Chi-Shing

2016-01-01

People can process multiple dimensions of facial properties simultaneously. Facial processing models are based on the processing of facial properties. The current study examined the processing of facial emotion, face race, and face gender using categorization tasks. The same set of Chinese, White and Black faces, each posing a neutral, happy or angry expression, was used in three experiments. Facial emotion interacted with face race in all the tasks. The interaction of face race and face gender was found in the race and gender categorization tasks, whereas the interaction of facial emotion and face gender was significant in the emotion and gender categorization tasks. These results provided evidence for a symmetric interaction between variant facial properties (emotion) and invariant facial properties (race and gender). PMID:27840621

Computational Fluid Dynamics (CFD) Modeling for High Rate Pulverized Coal Injection (PCI) into the Blast Furnace

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

Dr. Chenn Zhou

2008-10-15

Pulverized coal injection (PCI) into the blast furnace (BF) has been recognized as an effective way to decrease the coke and total energy consumption along with minimization of environmental impacts. However, increasing the amount of coal injected into the BF is currently limited by the lack of knowledge of some issues related to the process. It is therefore important to understand the complex physical and chemical phenomena in the PCI process. Due to the difficulty in attaining trus BF measurements, Computational fluid dynamics (CFD) modeling has been identified as a useful technology to provide such knowledge. CFD simulation is powerfulmore » for providing detailed information on flow properties and performing parametric studies for process design and optimization. In this project, comprehensive 3-D CFD models have been developed to simulate the PCI process under actual furnace conditions. These models provide raceway size and flow property distributions. The results have provided guidance for optimizing the PCI process.« less

[Establishment and practice of traditional Chinese medicine property cognitive model based on three elements].

PubMed

Zhang, Bing; Jin, Rui; Huang, Jianmei; Liu, Xiaoqing; Xue, Chunmiao; Lin, Zhijian

2012-08-01

Traditional Chinese medicine (TCM) property theory is believed to be a key and difficult point of basic theory studies of TCM. Complex concepts, components and characteristics of TCM property have long puzzled researchers and urged them to develop new angles and approaches. In the view of cognitive science, TCM property theory is a cognitive process of storing, extracting, rebuilding and summarizing the sensory information about TCMs and their effects during the medical practice struggling against diseases under the guidance of traditional Chinese philosophical thinking. The cognitive process of TCM property has particular cognitive elements and strategies. Taking into account clinical application characteristics of TCMs, this study defines the particular cognitive elements. In the combination of research methods of modern chemistry, biology and mathematics, and on the basis early-stage work for five years, we have built a TCM property cognition model based on three elements and practiced with drugs with pungent and hot properties as example, in the hope of interpreting TCM properties with modern science and providing thoughts for the nature of medical properties and instruction for rational clinical prescription.

SPATIAL FOREST SOIL PROPERTIES FOR ECOLOGICAL MODELING IN THE WESTERN OREGON CASCADES

EPA Science Inventory

The ultimate objective of this work is to provide a spatially distributed database of soil properties to serve as inputs to model ecological processes in western forests at the landscape scale. The Central Western Oregon Cascades are rich in biodiversity and they are a fascinati...

A review of combined experimental and computational procedures for assessing biopolymer structure-process-property relationships.

PubMed

Gronau, Greta; Krishnaji, Sreevidhya T; Kinahan, Michelle E; Giesa, Tristan; Wong, Joyce Y; Kaplan, David L; Buehler, Markus J

2012-11-01

Tailored biomaterials with tunable functional properties are desirable for many applications ranging from drug delivery to regenerative medicine. To improve the predictability of biopolymer materials functionality, multiple design parameters need to be considered, along with appropriate models. In this article we review the state of the art of synthesis and processing related to the design of biopolymers, with an emphasis on the integration of bottom-up computational modeling in the design process. We consider three prominent examples of well-studied biopolymer materials - elastin, silk, and collagen - and assess their hierarchical structure, intriguing functional properties and categorize existing approaches to study these materials. We find that an integrated design approach in which both experiments and computational modeling are used has rarely been applied for these materials due to difficulties in relating insights gained on different length- and time-scales. In this context, multiscale engineering offers a powerful means to accelerate the biomaterials design process for the development of tailored materials that suit the needs posed by the various applications. The combined use of experimental and computational tools has a very broad applicability not only in the field of biopolymers, but can be exploited to tailor the properties of other polymers and composite materials in general. Copyright © 2012 Elsevier Ltd. All rights reserved.

Planetary geology: Impact processes on asteroids

NASA Technical Reports Server (NTRS)

Chapman, C. R.; Davis, D. R.; Greenberg, R.; Weidenschilling, S. J.

1982-01-01

The fundamental geological and geophysical properties of asteroids were studied by theoretical and simulation studies of their collisional evolution. Numerical simulations incorporating realistic physical models were developed to study the collisional evolution of hypothetical asteroid populations over the age of the solar system. Ideas and models are constrained by the observed distributions of sizes, shapes, and spin rates in the asteroid belt, by properties of Hirayama families, and by experimental studies of cratering and collisional phenomena. It is suggested that many asteroids are gravitationally-bound "rubble piles.' Those that rotate rapidly may have nonspherical quasi-equilibrium shapes, such as ellipsoids or binaries. Through comparison of models with astronomical data, physical properties of these asteroids (including bulk density) are determined, and physical processes that have operated in the solar system in primordial and subsequent epochs are studied.

User Guide for HUFPrint, A Tabulation and Visualization Utility for the Hydrogeologic-Unit Flow (HUF) Package of MODFLOW

USGS Publications Warehouse

Banta, Edward R.; Provost, Alden M.

2008-01-01

This report documents HUFPrint, a computer program that extracts and displays information about model structure and hydraulic properties from the input data for a model built using the Hydrogeologic-Unit Flow (HUF) Package of the U.S. Geological Survey's MODFLOW program for modeling ground-water flow. HUFPrint reads the HUF Package and other MODFLOW input files, processes the data by hydrogeologic unit and by model layer, and generates text and graphics files useful for visualizing the data or for further processing. For hydrogeologic units, HUFPrint outputs such hydraulic properties as horizontal hydraulic conductivity along rows, horizontal hydraulic conductivity along columns, horizontal anisotropy, vertical hydraulic conductivity or anisotropy, specific storage, specific yield, and hydraulic-conductivity depth-dependence coefficient. For model layers, HUFPrint outputs such effective hydraulic properties as horizontal hydraulic conductivity along rows, horizontal hydraulic conductivity along columns, horizontal anisotropy, specific storage, primary direction of anisotropy, and vertical conductance. Text files tabulating hydraulic properties by hydrogeologic unit, by model layer, or in a specified vertical section may be generated. Graphics showing two-dimensional cross sections and one-dimensional vertical sections at specified locations also may be generated. HUFPrint reads input files designed for MODFLOW-2000 or MODFLOW-2005.

Stability of phase transformation models for Ti-6Al-4V under cyclic thermal loading imposed during laser metal deposition

NASA Astrophysics Data System (ADS)

Klusemann, Benjamin; Bambach, Markus

2018-05-01

Processing conditions play a crucial role for the resulting microstructure and properties of the material. In particular, processing materials under non-equilibrium conditions can lead to a remarkable improvement of the final properties [1]. Additive manufacturing represents a specific process example considered in this study. Models for the prediction of residual stresses and microstructure in additive manufacturing processes, such as laser metal deposition, are being developed with huge efforts to support the development of materials and processes as well as to support process design [2-4]. Since the microstructure predicted after each heating and cooling cycle induced by the moving laser source enters the phase transformation kinetics and microstucture evolution of the subsequent heating and cooling cycle, a feed-back loop for the microstructure calculation is created. This calculation loop may become unstable so that the computed microstructure and related properties become very sensitive to small variations in the input parameters, e.g. thermal conductivity. In this paper, a model for phase transformation in Ti-6Al-4V, originally proposed by Charles Murgau et al. [5], is adopted and minimal adjusted concerning the decomposition of the martensite phase are made. This model is subsequently used to study the changes in the predictions of the different phase volume fractions during heating and cooling under the conditions of laser metal deposition with respect to slight variations in the thermal process history.

Brain Networks Associated with Sublexical Properties of Chinese Characters

ERIC Educational Resources Information Center

Yang, Jianfeng; Wang, Xiaojuan; Shu, Hua; Zevin, Jason D.

2011-01-01

Cognitive models of reading all assume some division of labor among processing pathways in mapping among print, sound and meaning. Many studies of the neural basis of reading have used task manipulations such as rhyme or synonym judgment to tap these processes independently. Here we take advantage of specific properties of the Chinese writing…

Application of physicochemical properties and process parameters in the development of a neural network model for prediction of tablet characteristics.

PubMed

Sovány, Tamás; Papós, Kitti; Kása, Péter; Ilič, Ilija; Srčič, Stane; Pintye-Hódi, Klára

2013-06-01

The importance of in silico modeling in the pharmaceutical industry is continuously increasing. The aim of the present study was the development of a neural network model for prediction of the postcompressional properties of scored tablets based on the application of existing data sets from our previous studies. Some important process parameters and physicochemical characteristics of the powder mixtures were used as training factors to achieve the best applicability in a wide range of possible compositions. The results demonstrated that, after some pre-processing of the factors, an appropriate prediction performance could be achieved. However, because of the poor extrapolation capacity, broadening of the training data range appears necessary.

Thermodynamics and combustion modeling

NASA Technical Reports Server (NTRS)

Zeleznik, Frank J.

1986-01-01

Modeling fluid phase phenomena blends the conservation equations of continuum mechanics with the property equations of thermodynamics. The thermodynamic contribution becomes especially important when the phenomena involve chemical reactions as they do in combustion systems. The successful study of combustion processes requires (1) the availability of accurate thermodynamic properties for both the reactants and the products of reaction and (2) the computational capabilities to use the properties. A discussion is given of some aspects of the problem of estimating accurate thermodynamic properties both for reactants and products of reaction. Also, some examples of the use of thermodynamic properties for modeling chemically reacting systems are presented. These examples include one-dimensional flow systems and the internal combustion engine.

Can Process Understanding Help Elucidate The Structure Of The Critical Zone? Comparing Process-Based Soil Formation Models With Digital Soil Mapping.

NASA Astrophysics Data System (ADS)

Vanwalleghem, T.; Román, A.; Peña, A.; Laguna, A.; Giráldez, J. V.

2017-12-01

There is a need for better understanding the processes influencing soil formation and the resulting distribution of soil properties in the critical zone. Soil properties can exhibit strong spatial variation, even at the small catchment scale. Especially soil carbon pools in semi-arid, mountainous areas are highly uncertain because bulk density and stoniness are very heterogeneous and rarely measured explicitly. In this study, we explore the spatial variability in key soil properties (soil carbon stocks, stoniness, bulk density and soil depth) as a function of processes shaping the critical zone (weathering, erosion, soil water fluxes and vegetation patterns). We also compare the potential of traditional digital soil mapping versus a mechanistic soil formation model (MILESD) for predicting these key soil properties. Soil core samples were collected from 67 locations at 6 depths. Total soil organic carbon stocks were 4.38 kg m-2. Solar radiation proved to be the key variable controlling soil carbon distribution. Stone content was mostly controlled by slope, indicating the importance of erosion. Spatial distribution of bulk density was found to be highly random. Finally, total carbon stocks were predicted using a random forest model whose main covariates were solar radiation and NDVI. The model predicts carbon stocks that are double as high on north versus south-facing slopes. However, validation showed that these covariates only explained 25% of the variation in the dataset. Apparently, present-day landscape and vegetation properties are not sufficient to fully explain variability in the soil carbon stocks in this complex terrain under natural vegetation. This is attributed to a high spatial variability in bulk density and stoniness, key variables controlling carbon stocks. Similar results were obtained with the mechanistic soil formation model MILESD, suggesting that more complex models might be needed to further explore this high spatial variability.

Thermographic Assessment of the HAZ Properties and Structure of Thermomechanically Treated Steel

NASA Astrophysics Data System (ADS)

Górka, Jacek; Janicki, Damian; Fidali, Marek; Jamrozik, Wojciech

2017-12-01

Thermomechanically processed steels are materials of great mechanical properties connected with more than good weldability. This mixture makes them interesting for different types of industrial applications. When creating welded joints, a specified amount of heat is introduced into the welding area and a so called heat-affected zone (HAZ) is formed. The key issue is to reduce the width of the HAZ, because properties of the material in the HAZ are worse than in the base material. In the paper, thermographic measurements of HAZ temperatures were presented as a potential tool for quality assuring the welding process in terms of monitoring and control. The main issue solved was the precise temperature measurement in terms of varying emissivity during a welding thermal cycle. A model of emissivity changes was elaborated and successfully applied. Additionally, material in the HAZ was tested to reveal its properties and connect changes of those properties with heating parameters. The obtained results prove that correctly modeled emissivity allows measurement of temperature, which is a valuable tool for welding process monitoring.

Process property studies of melt blown thermoplastic polyurethane polymers

NASA Astrophysics Data System (ADS)

Lee, Youn Eung

The primary goal of this research was to determine optimum processing conditions to produce commercially acceptable melt blown (MB) thermoplastic polyurethane (TPU) webs. The 6-inch MB line and the 20-inch wide Accurate Products MB pilot line at the Textiles and Nonwovens Development Center (TANDEC), The University of Tennessee, Knoxville, were utilized for this study. The MB TPU trials were performed in four different phases: Phase 1 focused on the envelope of the MB operating conditions for different TPU polymers; Phase 2 focused on the production of commercially acceptable MB TPU webs; Phase 3 focused on the optimization of the processing conditions of MB TPU webs, and the determination of the significant relationships between processing parameters and web properties utilizing statistical analyses; Based on the first three phases, a more extensive study of fiber and web formation in the MB TPU process was made and a multi liner regression model for the MB TPU process versus properties was also developed in Phase 4. In conclusion, the basic MB process was fundamentally valid for the MB TPU process; however, the MB process was more complicated for TPU than PP, because web structures and properties of MB TPUs are very sensitive to MB process conditions: Furthermore, different TPU grades responded very differently to MB processing and exhibited different web structure and properties. In Phase 3 and Phase 4, small fiber diameters of less than 5mum were produced from TPU237, TPU245 and TPU280 pellets, and the mechanical strengths of MB TPU webs including the tensile strength, tear strength, abrasion resistance and tensile elongation were notably good. In addition, the statistical model showed useful interaction regarding trends for processing parameters versus properties of MB TPU webs. Die and air temperature showed multicollinearity problems and fiber diameter was notably affected by air flow rate, throughput and die/air temperature. It was also shown that most of the MB TPU web properties including mechanical strength, air permeability and fiber diameters were affected by air velocity and die temperature.

Charge transport model in nanodielectric composites based on quantum tunneling mechanism and dual-level traps

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

Li, Guochang; Chen, George, E-mail: gc@ecs.soton.ac.uk, E-mail: sli@mail.xjtu.edu.cn; School of Electronic and Computer Science, University of Southampton, Southampton SO17 1BJ

Charge transport properties in nanodielectrics present different tendencies for different loading concentrations. The exact mechanisms that are responsible for charge transport in nanodielectrics are not detailed, especially for high loading concentration. A charge transport model in nanodielectrics has been proposed based on quantum tunneling mechanism and dual-level traps. In the model, the thermally assisted hopping (TAH) process for the shallow traps and the tunnelling process for the deep traps are considered. For different loading concentrations, the dominant charge transport mechanisms are different. The quantum tunneling mechanism plays a major role in determining the charge conduction in nanodielectrics with high loadingmore » concentrations. While for low loading concentrations, the thermal hopping mechanism will dominate the charge conduction process. The model can explain the observed conductivity property in nanodielectrics with different loading concentrations.« less

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.

FE Simulation Models for Hot Stamping an Automobile Component with Tailor-Welded High-Strength Steels

NASA Astrophysics Data System (ADS)

Tang, Bingtao; Wang, Qiaoling; Wei, Zhaohui; Meng, Xianju; Yuan, Zhengjun

2016-05-01

Ultra-high-strength in sheet metal parts can be achieved with hot stamping process. To improve the crash performance and save vehicle weight, it is necessary to produce components with tailored properties. The use of tailor-welded high-strength steel is a relatively new hot stamping process for saving weight and obtaining desired local stiffness and crash performance. The simulation of hot stamping boron steel, especially tailor-welded blanks (TWBs) stamping, is more complex and challenging. Information about thermal/mechanical properties of tools and sheet materials, heat transfer, and friction between the deforming material and the tools is required in detail. In this study, the boron-manganese steel B1500HS and high-strength low-alloy steel B340LA are tailor welded and hot stamped. In order to precisely simulate the hot stamping process, modeling and simulation of hot stamping tailor-welded high-strength steels, including phase transformation modeling, thermal modeling, and thermal-mechanical modeling, is investigated. Meanwhile, the welding zone of tailor-welded blanks should be sufficiently accurate to describe thermal, mechanical, and metallurgical parameters. FE simulation model using TWBs with the thickness combination of 1.6 mm boron steel and 1.2 mm low-alloy steel is established. In order to evaluate the mechanical properties of the hot stamped automotive component (mini b-pillar), hardness and microstructure at each region are investigated. The comparisons between simulated results and experimental observations show the reliability of thermo-mechanical and metallurgical modeling strategies of TWBs hot stamping process.

Process compensated resonance testing modeling for damage evolution and uncertainty quantification

NASA Astrophysics Data System (ADS)

Biedermann, Eric; Heffernan, Julieanne; Mayes, Alexander; Gatewood, Garrett; Jauriqui, Leanne; Goodlet, Brent; Pollock, Tresa; Torbet, Chris; Aldrin, John C.; Mazdiyasni, Siamack

2017-02-01

Process Compensated Resonance Testing (PCRT) is a nondestructive evaluation (NDE) method based on the fundamentals of Resonant Ultrasound Spectroscopy (RUS). PCRT is used for material characterization, defect detection, process control and life monitoring of critical gas turbine engine and aircraft components. Forward modeling and model inversion for PCRT have the potential to greatly increase the method's material characterization capability while reducing its dependence on compiling a large population of physical resonance measurements. This paper presents progress on forward modeling studies for damage mechanisms and defects in common to structural materials for gas turbine engines. Finite element method (FEM) models of single crystal (SX) Ni-based superalloy Mar-M247 dog bones and Ti-6Al-4V cylindrical bars were created, and FEM modal analyses calculated the resonance frequencies for the samples in their baseline condition. Then the frequency effects of superalloy creep (high-temperature plastic deformation) and macroscopic texture (preferred crystallographic orientation of grains detrimental to fatigue properties) were evaluated. A PCRT sorting module for creep damage in Mar-M247 was trained with a virtual database made entirely of modeled design points. The sorting module demonstrated successful discrimination of design points with as little as 1% creep strain in the gauge section from a population of acceptable design points with a range of material and geometric variation. The resonance frequency effects of macro-scale texture in Ti-6Al-4V were quantified with forward models of cylinder samples. FEM-based model inversion was demonstrated for Mar-M247 bulk material properties and variations in crystallographic orientation. PCRT uncertainty quantification (UQ) was performed using Monte Carlo studies for Mar-M247 that quantified the overall uncertainty in resonance frequencies resulting from coupled variation in geometry, material properties, crystallographic orientation and creep damage. A model calibration process was also developed that evaluates inversion fitting to differences from a designated reference sample rather than absolute property values, yielding a reduction in fit error.

Modeling of Microstructure Evolution During the Thermomechanical Processing of Titanium Alloys (Preprint)

DTIC Science & Technology

2008-07-01

Tailoring the Properties of Aluminum and Titanium Alloys", Deformation, Processing, and Structure , G. Krauss, ed., ASM International, Materials Park, OH...1984, pp. 279-354. 51. G.W. Kuhlman, "A Critical Appraisal of Thermomechanical Processing of Structural Titanium Alloys", Microstructure/ Property ... titanium alloys is heavily dependent on the allotropic transformation from a hexagonal-close-packed crystal structure (denoted as alpha phase) found at

Optimization of critical quality attributes in continuous twin-screw wet granulation via design space validated with pilot scale experimental data.

PubMed

Liu, Huolong; Galbraith, S C; Ricart, Brendon; Stanton, Courtney; Smith-Goettler, Brandye; Verdi, Luke; O'Connor, Thomas; Lee, Sau; Yoon, Seongkyu

2017-06-15

In this study, the influence of key process variables (screw speed, throughput and liquid to solid (L/S) ratio) of a continuous twin screw wet granulation (TSWG) was investigated using a central composite face-centered (CCF) experimental design method. Regression models were developed to predict the process responses (motor torque, granule residence time), granule properties (size distribution, volume average diameter, yield, relative width, flowability) and tablet properties (tensile strength). The effects of the three key process variables were analyzed via contour and interaction plots. The experimental results have demonstrated that all the process responses, granule properties and tablet properties are influenced by changing the screw speed, throughput and L/S ratio. The TSWG process was optimized to produce granules with specific volume average diameter of 150μm and the yield of 95% based on the developed regression models. A design space (DS) was built based on volume average granule diameter between 90 and 200μm and the granule yield larger than 75% with a failure probability analysis using Monte Carlo simulations. Validation experiments successfully validated the robustness and accuracy of the DS generated using the CCF experimental design in optimizing a continuous TSWG process. Copyright © 2017 Elsevier B.V. All rights reserved.

Iron-Based Amorphous Coatings Produced by HVOF Thermal Spray Processing-Coating Structure and Properties

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

Beardsley, M B

2008-03-26

The feasibility to coat large SNF/HLW containers with a structurally amorphous material (SAM) was demonstrated on sub-scale models fabricated from Type 316L stainless steel. The sub-scale model were coated with SAM 1651 material using kerosene high velocity oxygen fuel (HVOF) torch to thicknesses ranging from 1 mm to 2 mm. The process parameters such as standoff distance, oxygen flow, and kerosene flow, were optimized in order to improve the corrosion properties of the coatings. Testing in an electrochemical cell and long-term exposure to a salt spray environment were used to guide the selection of process parameters.

The Structural Properties of Sexual Fantasies for Sexual Offenders: A Preliminary Model

ERIC Educational Resources Information Center

Gee, Dion; Ward, Tony; Belofastov, Aleksandra; Beech, Anthony

2006-01-01

While the phenomenon of sexual fantasy has been researched extensively, little contemporary inquiry has investigated the structural properties of sexual fantasy within the context of sexual offending. In this study, a qualitative analysis was used to develop a descriptive model of the phenomena of sexual fantasy during the offence process.…

Predictive analysis of the influence of the chemical composition and pre-processing regimen on structural properties of steel alloys using machine learning techniques

NASA Astrophysics Data System (ADS)

Krishnamurthy, Narayanan; Maddali, Siddharth; Romanov, Vyacheslav; Hawk, Jeffrey

We present some structural properties of multi-component steel alloys as predicted by a random forest machine-learning model. These non-parametric models are trained on high-dimensional data sets defined by features such as chemical composition, pre-processing temperatures and environmental influences, the latter of which are based upon standardized testing procedures for tensile, creep and rupture properties as defined by the American Society of Testing and Materials (ASTM). We quantify the goodness of fit of these models as well as the inferred relative importance of each of these features, all with a conveniently defined metric and scale. The models are tested with synthetic data points, generated subject to the appropriate mathematical constraints for the various features. By this we highlight possible trends in the increase or degradation of the structural properties with perturbations in the features of importance. This work is presented as part of the Data Science Initiative at the National Energy Technology Laboratory, directed specifically towards the computational design of steel alloys.

Macro-magnetic Modeling of the ARL Microelectromechanical System (MEMS) Flux Concentrator

DTIC Science & Technology

2011-09-01

are drawn as solid pieces and assigned the material properties of permalloy (nickel-iron [ NiFe ]) with a permeability of 5,000 as that is a value...energy densities, and saturation. The modeling process consists of drawing the objects of interest, assigning properties (coercivity, permeability...that is readily achieved in thin films of the material. The material properties assigned to this background are those of a vacuum, with a relative

Southern Ocean Bottom Water Characteristics in CMIP5 Models

NASA Astrophysics Data System (ADS)

Heuzé, Céline; Heywood, Karen; Stevens, David; Ridley, Jeff

2013-04-01

The depiction of Southern Ocean deep water properties and formation processes in climate models is an indicator of their capability to simulate future climate, heat and carbon uptake, and sea level rise. Southern Ocean potential temperature and density averaged over 1986-2005 from fifteen CMIP5 climate models are compared with an observed climatology, focusing on bottom water properties. The mean bottom properties are reasonably accurate for half of the models, but the other half may not yet have approached an equilibrium state. Eleven models create dense water on the Antarctic shelf, but it does not spill off and propagate northwards, alternatively mixing rapidly with less dense water. Instead most models create deep water by open ocean deep convection. Models with large deep convection areas are those with a strong seasonal cycle in sea ice. The most accurate bottom properties occur in models hosting deep convection in the Weddell and Ross gyres.

Many roads to synchrony: natural time scales and their algorithms.

PubMed

James, Ryan G; Mahoney, John R; Ellison, Christopher J; Crutchfield, James P

2014-04-01

We consider two important time scales-the Markov and cryptic orders-that monitor how an observer synchronizes to a finitary stochastic process. We show how to compute these orders exactly and that they are most efficiently calculated from the ε-machine, a process's minimal unifilar model. Surprisingly, though the Markov order is a basic concept from stochastic process theory, it is not a probabilistic property of a process. Rather, it is a topological property and, moreover, it is not computable from any finite-state model other than the ε-machine. Via an exhaustive survey, we close by demonstrating that infinite Markov and infinite cryptic orders are a dominant feature in the space of finite-memory processes. We draw out the roles played in statistical mechanical spin systems by these two complementary length scales.

Advanced Models and Algorithms for Self-Similar IP Network Traffic Simulation and Performance Analysis

NASA Astrophysics Data System (ADS)

Radev, Dimitar; Lokshina, Izabella

2010-11-01

The paper examines self-similar (or fractal) properties of real communication network traffic data over a wide range of time scales. These self-similar properties are very different from the properties of traditional models based on Poisson and Markov-modulated Poisson processes. Advanced fractal models of sequentional generators and fixed-length sequence generators, and efficient algorithms that are used to simulate self-similar behavior of IP network traffic data are developed and applied. Numerical examples are provided; and simulation results are obtained and analyzed.

Analytical Modelling and Optimization of the Temperature-Dependent Dynamic Mechanical Properties of Fused Deposition Fabricated Parts Made of PC-ABS.

PubMed

Mohamed, Omar Ahmed; Masood, Syed Hasan; Bhowmik, Jahar Lal

2016-11-04

Fused deposition modeling (FDM) additive manufacturing has been intensively used for many industrial applications due to its attractive advantages over traditional manufacturing processes. The process parameters used in FDM have significant influence on the part quality and its properties. This process produces the plastic part through complex mechanisms and it involves complex relationships between the manufacturing conditions and the quality of the processed part. In the present study, the influence of multi-level manufacturing parameters on the temperature-dependent dynamic mechanical properties of FDM processed parts was investigated using IV-optimality response surface methodology (RSM) and multilayer feed-forward neural networks (MFNNs). The process parameters considered for optimization and investigation are slice thickness, raster to raster air gap, deposition angle, part print direction, bead width, and number of perimeters. Storage compliance and loss compliance were considered as response variables. The effect of each process parameter was investigated using developed regression models and multiple regression analysis. The surface characteristics are studied using scanning electron microscope (SEM). Furthermore, performance of optimum conditions was determined and validated by conducting confirmation experiment. The comparison between the experimental values and the predicted values by IV-Optimal RSM and MFNN was conducted for each experimental run and results indicate that the MFNN provides better predictions than IV-Optimal RSM.

Analytical Modelling and Optimization of the Temperature-Dependent Dynamic Mechanical Properties of Fused Deposition Fabricated Parts Made of PC-ABS

PubMed Central

Mohamed, Omar Ahmed; Masood, Syed Hasan; Bhowmik, Jahar Lal

2016-01-01

Fused deposition modeling (FDM) additive manufacturing has been intensively used for many industrial applications due to its attractive advantages over traditional manufacturing processes. The process parameters used in FDM have significant influence on the part quality and its properties. This process produces the plastic part through complex mechanisms and it involves complex relationships between the manufacturing conditions and the quality of the processed part. In the present study, the influence of multi-level manufacturing parameters on the temperature-dependent dynamic mechanical properties of FDM processed parts was investigated using IV-optimality response surface methodology (RSM) and multilayer feed-forward neural networks (MFNNs). The process parameters considered for optimization and investigation are slice thickness, raster to raster air gap, deposition angle, part print direction, bead width, and number of perimeters. Storage compliance and loss compliance were considered as response variables. The effect of each process parameter was investigated using developed regression models and multiple regression analysis. The surface characteristics are studied using scanning electron microscope (SEM). Furthermore, performance of optimum conditions was determined and validated by conducting confirmation experiment. The comparison between the experimental values and the predicted values by IV-Optimal RSM and MFNN was conducted for each experimental run and results indicate that the MFNN provides better predictions than IV-Optimal RSM. PMID:28774019

Finding simplicity in complexity: modelling post-fire hydrogeomorphic processes and risks

NASA Astrophysics Data System (ADS)

Sheridan, Gary; Langhans, Christoph; Lane, Patrick; Nyman, Petter

2017-04-01

Post-fire runoff and erosion can shape landscapes, destroy infrastructure, and result in the loss of human life. However even within seemingly similar geographic regions post-fire hydro-geomorphic responses vary from almost no response through to catastrophic flash floods and debris flows. Why is there so much variability, and how can we predict areas at risk? This presentation describes the research journey taken by the post-fire research group at The University of Melbourne to answer this question for the se Australian uplands. Key steps along the way have included identifying the dominant erosion processes (and their forcings), and the key system properties controlling the rates of these dominant processes. The high degree of complexity in the interactions between the forcings, the system properties, and the erosion processes, necessitated the development of a simplified conceptual representation of post-fire hydrogeomorphic system that was conducive to modelling and simulation. Spatially mappable metrics (and proxies) for key system forcings and properties were then required to parameterize and drive the model. Each step in this journey has depended on new research, as well as ongoing feedback from land and water management agencies tasked with implementing these risk models and interpreting the results. These models are now imbedded within agencies and used for strategic risk assessments, for tactical response during fires, and for post-fire remediation and risk planning. Reflecting on the successes and failures along the way provides for some more general insights into the process of developing research-based models for operational use by land and water management agencies.

Know your fibers : process and properties, or, a material science approach to designing pulp molded products

Treesearch

John F. Hunt

1998-01-01

The following results are preliminary, but show some basic information that will be used in an attempt to model pulp molded structures so that by measuring several basic fundamental properties of a fiber furnish and specifying process conditions, a molded structure could be designed for a particular performance need.

Recent development in preparation of European soil hydraulic maps

NASA Astrophysics Data System (ADS)

Toth, B.; Weynants, M.; Pasztor, L.; Hengl, T.

2017-12-01

Reliable quantitative information on soil hydraulic properties is crucial for modelling hydrological, meteorological, ecological and biological processes of the Critical Zone. Most of the Earth system models need information on soil moisture retention capacity and hydraulic conductivity in the full matric potential range. These soil hydraulic properties can be quantified, but their measurement is expensive and time consuming, therefore measurement-based catchment scale mapping of these soil properties is not possible. The increasing availability of soil information and methods describing relationships between simple soil characteristics and soil hydraulic properties provide the possibility to derive soil hydraulic maps based on spatial soil datasets and pedotransfer functions (PTFs). Over the last decade there has been a significant development in preparation of soil hydraulic maps. Spatial datasets on model parameters describing the soil hydraulic processes have become available for countries, continents and even for the whole globe. Our aim is to present European soil hydraulic maps, show their performance, highlight their advantages and drawbacks, and propose possible ways to further improve the performance of those.

Modeling of inter-neuronal coupling medium and its impact on neuronal synchronization

PubMed Central

Iqbal, Muhammad; Hong, Keum-Shik

2017-01-01

In this paper, modeling of the coupling medium between two neurons, the effects of the model parameters on the synchronization of those neurons, and compensation of coupling strength deficiency in synchronization are studied. Our study exploits the inter-neuronal coupling medium and investigates its intrinsic properties in order to get insight into neuronal-information transmittance and, there from, brain-information processing. A novel electrical model of the coupling medium that represents a well-known RLC circuit attributable to the coupling medium’s intrinsic resistive, inductive, and capacitive properties is derived. Surprisingly, the integration of such properties reveals the existence of a natural three-term control strategy, referred to in the literature as the proportional integral derivative (PID) controller, which can be responsible for synchronization between two neurons. Consequently, brain-information processing can rely on a large number of PID controllers based on the coupling medium properties responsible for the coherent behavior of neurons in a neural network. Herein, the effects of the coupling model (or natural PID controller) parameters are studied and, further, a supervisory mechanism is proposed that follows a learning and adaptation policy based on the particle swarm optimization algorithm for compensation of the coupling strength deficiency. PMID:28486505

Group Contribution Methods for Phase Equilibrium Calculations.

PubMed

Gmehling, Jürgen; Constantinescu, Dana; Schmid, Bastian

2015-01-01

The development and design of chemical processes are carried out by solving the balance equations of a mathematical model for sections of or the whole chemical plant with the help of process simulators. For process simulation, besides kinetic data for the chemical reaction, various pure component and mixture properties are required. Because of the great importance of separation processes for a chemical plant in particular, a reliable knowledge of the phase equilibrium behavior is required. The phase equilibrium behavior can be calculated with the help of modern equations of state or g(E)-models using only binary parameters. But unfortunately, only a very small part of the experimental data for fitting the required binary model parameters is available, so very often these models cannot be applied directly. To solve this problem, powerful predictive thermodynamic models have been developed. Group contribution methods allow the prediction of the required phase equilibrium data using only a limited number of group interaction parameters. A prerequisite for fitting the required group interaction parameters is a comprehensive database. That is why for the development of powerful group contribution methods almost all published pure component properties, phase equilibrium data, excess properties, etc., were stored in computerized form in the Dortmund Data Bank. In this review, the present status, weaknesses, advantages and disadvantages, possible applications, and typical results of the different group contribution methods for the calculation of phase equilibria are presented.

Computational Models of Relational Processes in Cognitive Development

ERIC Educational Resources Information Center

Halford, Graeme S.; Andrews, Glenda; Wilson, William H.; Phillips, Steven

2012-01-01

Acquisition of relational knowledge is a core process in cognitive development. Relational knowledge is dynamic and flexible, entails structure-consistent mappings between representations, has properties of compositionality and systematicity, and depends on binding in working memory. We review three types of computational models relevant to…

EDDA: integrated simulation of debris flow erosion, deposition and property changes

NASA Astrophysics Data System (ADS)

Chen, H. X.; Zhang, L. M.

2014-11-01

Debris flow material properties change during the initiation, transportation and deposition processes, which influences the runout characteristics of the debris flow. A quasi-three-dimensional depth-integrated numerical model, EDDA, is presented in this paper to simulate debris flow erosion, deposition and induced material property changes. The model considers changes in debris flow density, yield stress and dynamic viscosity during the flow process. The yield stress of debris flow mixture is determined at limit equilibrium using the Mohr-Coulomb equation, which is applicable to clear water flow, hyper-concentrated flow and fully developed debris flow. To assure numerical stability and computational efficiency at the same time, a variable time stepping algorithm is developed to solve the governing differential equations. Four numerical tests are conducted to validate the model. The first two tests involve a one-dimensional dam-break water flow and a one-dimensional debris flow with constant properties. The last two tests involve erosion and deposition, and the movement of multi-directional debris flows. The changes in debris flow mass and properties due to either erosion or deposition are shown to affect the runout characteristics significantly. The model is also applied to simulate a large-scale debris flow in Xiaojiagou Ravine to test the performance of the model in catchment-scale simulations. The results suggest that the model estimates well the volume, inundated area, and runout distance of the debris flow. The model is intended for use as a module in a real-time debris flow warning system.

A qualitative assessment of a random process proposed as an atmospheric turbulence model

NASA Technical Reports Server (NTRS)

Sidwell, K.

1977-01-01

A random process is formed by the product of two Gaussian processes and the sum of that product with a third Gaussian process. The resulting total random process is interpreted as the sum of an amplitude modulated process and a slowly varying, random mean value. The properties of the process are examined, including an interpretation of the process in terms of the physical structure of atmospheric motions. The inclusion of the mean value variation gives an improved representation of the properties of atmospheric motions, since the resulting process can account for the differences in the statistical properties of atmospheric velocity components and their gradients. The application of the process to atmospheric turbulence problems, including the response of aircraft dynamic systems, is examined. The effects of the mean value variation upon aircraft loads are small in most cases, but can be important in the measurement and interpretation of atmospheric turbulence data.

On two diffusion neuronal models with multiplicative noise: The mean first-passage time properties

NASA Astrophysics Data System (ADS)

D'Onofrio, G.; Lansky, P.; Pirozzi, E.

2018-04-01

Two diffusion processes with multiplicative noise, able to model the changes in the neuronal membrane depolarization between two consecutive spikes of a single neuron, are considered and compared. The processes have the same deterministic part but different stochastic components. The differences in the state-dependent variabilities, their asymptotic distributions, and the properties of the first-passage time across a constant threshold are investigated. Closed form expressions for the mean of the first-passage time of both processes are derived and applied to determine the role played by the parameters involved in the model. It is shown that for some values of the input parameters, the higher variability, given by the second moment, does not imply shorter mean first-passage time. The reason for that can be found in the complete shape of the stationary distribution of the two processes. Applications outside neuroscience are also mentioned.

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

A Computer Code for Dynamic Stress Analysis of Media-Structure Problems with Nonlinearities (SAMSON). Volume III. User’s Manual.

DTIC Science & Technology

NONLINEAR SYSTEMS, LINEAR SYSTEMS, SUBROUTINES , SOIL MECHANICS, INTERFACES, DYNAMICS, LOADS(FORCES), FORCE(MECHANICS), DAMPING, ACCELERATION, ELASTIC...PROPERTIES, PLASTIC PROPERTIES, CRACKS , REINFORCING MATERIALS , COMPOSITE MATERIALS , FAILURE(MECHANICS), MECHANICAL PROPERTIES, INSTRUCTION MANUALS, DIGITAL COMPUTERS...STRESSES, *COMPUTER PROGRAMS), (*STRUCTURES, STRESSES), (*DATA PROCESSING, STRUCTURAL PROPERTIES), SOILS , STRAIN(MECHANICS), MATHEMATICAL MODELS

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.

“Using Statistical Comparisons between SPartICus Cirrus Microphysical Measurements, Detailed Cloud Models, and GCM Cloud Parameterizations to Understand Physical Processes Controlling Cirrus Properties and to Improve the Cloud Parameterizations”

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

Woods, Sarah

2015-12-01

The dual objectives of this project were improving our basic understanding of processes that control cirrus microphysical properties and improvement of the representation of these processes in the parameterizations. A major effort in the proposed research was to integrate, calibrate, and better understand the uncertainties in all of these measurements.

Authoring and verification of clinical guidelines: a model driven approach.

PubMed

Pérez, Beatriz; Porres, Ivan

2010-08-01

The goal of this research is to provide a framework to enable authoring and verification of clinical guidelines. The framework is part of a larger research project aimed at improving the representation, quality and application of clinical guidelines in daily clinical practice. The verification process of a guideline is based on (1) model checking techniques to verify guidelines against semantic errors and inconsistencies in their definition, (2) combined with Model Driven Development (MDD) techniques, which enable us to automatically process manually created guideline specifications and temporal-logic statements to be checked and verified regarding these specifications, making the verification process faster and cost-effective. Particularly, we use UML statecharts to represent the dynamics of guidelines and, based on this manually defined guideline specifications, we use a MDD-based tool chain to automatically process them to generate the input model of a model checker. The model checker takes the resulted model together with the specific guideline requirements, and verifies whether the guideline fulfils such properties. The overall framework has been implemented as an Eclipse plug-in named GBDSSGenerator which, particularly, starting from the UML statechart representing a guideline, allows the verification of the guideline against specific requirements. Additionally, we have established a pattern-based approach for defining commonly occurring types of requirements in guidelines. We have successfully validated our overall approach by verifying properties in different clinical guidelines resulting in the detection of some inconsistencies in their definition. The proposed framework allows (1) the authoring and (2) the verification of clinical guidelines against specific requirements defined based on a set of property specification patterns, enabling non-experts to easily write formal specifications and thus easing the verification process. Copyright 2010 Elsevier Inc. All rights reserved.

Manufacturing of tailored tubes with a process integrated heat treatment

NASA Astrophysics Data System (ADS)

Hordych, Illia; Boiarkin, Viacheslav; Rodman, Dmytro; Nürnberger, Florian

2017-10-01

The usage of work-pieces with tailored properties allows for reducing costs and materials. One example are tailored tubes that can be used as end parts e.g. in the automotive industry or in domestic applications as well as semi-finished products for subsequent controlled deformation processes. An innovative technology to manufacture tubes is roll forming with a subsequent inductive heating and adapted quenching to obtain tailored properties in the longitudinal direction. This processing offers a great potential for the production of tubes with a wide range of properties, although this novel approach still requires a suited process design. Based on experimental data, a process simulation is being developed. The simulation shall be suitable for a virtual design of the tubes and allows for gaining a deeper understanding of the required processing. The model proposed shall predict microstructural and mechanical tube properties by considering process parameters, different geometries, batch-related influences etc. A validation is carried out using experimental data of tubes manufactured from various steel grades.

A modeling-based assessment of acousto-optic sensing for monitoring high-intensity focused ultrasound lesion formation

NASA Astrophysics Data System (ADS)

Adams, Matthew Tyler

Real-time acousto-optic (AO) sensing---a dual-wave modality that combines ultrasound with diffuse light to probe the optical properties of turbid media---has been demonstrated to non-invasively detect changes in ex vivo tissue optical properties during high-intensity focused ultrasound (HIFU) exposure. The AO signal indicates the onset of lesion formation and predicts resulting lesion volumes. Although proof-of-concept experiments have been successful, many of the underlying parameters and mechanisms affecting thermally induced optical property changes and the AO detectability of HIFU lesion formation are not well understood. In thesis, a numerical simulation was developed to model the AO sensing process and capture the relevant acoustic, thermal, and optical transport processes. The simulation required data that described how optical properties changed with heating. Experiments were carried out where excised chicken breast was exposed to thermal bath heating and changes in the optical absorption and scattering spectra (500 nm--1100 nm) were measured using a scanning spectrophotometer and an integrating sphere assembly. Results showed that the standard thermal dose model currently used for guiding HIFU treatments needs to be adjusted to describe thermally induced optical property changes. To model the entire AO process, coupled models were used for ultrasound propagation, tissue heating, and diffusive light transport. The angular spectrum method was used to model the acoustic field from the HIFU source. Spatial-temporal temperature elevations induced by the absorption of ultrasound were modeled using a finite-difference time-domain solution to the Pennes bioheat equation. The thermal dose model was then used to determine optical properties based on the temperature history. The diffuse optical field in the tissue was then calculated using a GPU-accelerated Monte Carlo algorithm, which accounted for light-sound interactions and AO signal detection. The simulation was used to determine the optimal design for an AO guided HIFU system by evaluating the robustness of the systems signal to changes in tissue thickness, lesion optical contrast, and lesion location. It was determined that AO sensing is a clinically viable technique for guiding the ablation of large volumes and that real-time sensing may be feasible in the breast and prostate.

A unifying view of synchronization for data assimilation in complex nonlinear networks

NASA Astrophysics Data System (ADS)

Abarbanel, Henry D. I.; Shirman, Sasha; Breen, Daniel; Kadakia, Nirag; Rey, Daniel; Armstrong, Eve; Margoliash, Daniel

2017-12-01

Networks of nonlinear systems contain unknown parameters and dynamical degrees of freedom that may not be observable with existing instruments. From observable state variables, we want to estimate the connectivity of a model of such a network and determine the full state of the model at the termination of a temporal observation window during which measurements transfer information to a model of the network. The model state at the termination of a measurement window acts as an initial condition for predicting the future behavior of the network. This allows the validation (or invalidation) of the model as a representation of the dynamical processes producing the observations. Once the model has been tested against new data, it may be utilized as a predictor of responses to innovative stimuli or forcing. We describe a general framework for the tasks involved in the "inverse" problem of determining properties of a model built to represent measured output from physical, biological, or other processes when the measurements are noisy, the model has errors, and the state of the model is unknown when measurements begin. This framework is called statistical data assimilation and is the best one can do in estimating model properties through the use of the conditional probability distributions of the model state variables, conditioned on observations. There is a very broad arena of applications of the methods described. These include numerical weather prediction, properties of nonlinear electrical circuitry, and determining the biophysical properties of functional networks of neurons. Illustrative examples will be given of (1) estimating the connectivity among neurons with known dynamics in a network of unknown connectivity, and (2) estimating the biophysical properties of individual neurons in vitro taken from a functional network underlying vocalization in songbirds.

Monitoring autocorrelated process: A geometric Brownian motion process approach

NASA Astrophysics Data System (ADS)

Li, Lee Siaw; Djauhari, Maman A.

2013-09-01

Autocorrelated process control is common in today's modern industrial process control practice. The current practice of autocorrelated process control is to eliminate the autocorrelation by using an appropriate model such as Box-Jenkins models or other models and then to conduct process control operation based on the residuals. In this paper we show that many time series are governed by a geometric Brownian motion (GBM) process. Therefore, in this case, by using the properties of a GBM process, we only need an appropriate transformation and model the transformed data to come up with the condition needs in traditional process control. An industrial example of cocoa powder production process in a Malaysian company will be presented and discussed to illustrate the advantages of the GBM approach.

Modeling the curing process of thermosetting resin matrix composites

NASA Technical Reports Server (NTRS)

Loos, A. C.

1986-01-01

A model is presented for simulating the curing process of a thermosetting resin matrix composite. The model relates the cure temperature, the cure pressure, and the properties of the prepreg to the thermal, chemical, and rheological processes occurring in the composite during cure. The results calculated with the computer code developed on the basis of the model were compared with the experimental data obtained from autoclave-curved composite laminates. Good agreement between the two sets of results was obtained.

Process modeling and parameter optimization using radial basis function neural network and genetic algorithm for laser welding of dissimilar materials

NASA Astrophysics Data System (ADS)

Ai, Yuewei; Shao, Xinyu; Jiang, Ping; Li, Peigen; Liu, Yang; Yue, Chen

2015-11-01

The welded joints of dissimilar materials have been widely used in automotive, ship and space industries. The joint quality is often evaluated by weld seam geometry, microstructures and mechanical properties. To obtain the desired weld seam geometry and improve the quality of welded joints, this paper proposes a process modeling and parameter optimization method to obtain the weld seam with minimum width and desired depth of penetration for laser butt welding of dissimilar materials. During the process, Taguchi experiments are conducted on the laser welding of the low carbon steel (Q235) and stainless steel (SUS301L-HT). The experimental results are used to develop the radial basis function neural network model, and the process parameters are optimized by genetic algorithm. The proposed method is validated by a confirmation experiment. Simultaneously, the microstructures and mechanical properties of the weld seam generated from optimal process parameters are further studied by optical microscopy and tensile strength test. Compared with the unoptimized weld seam, the welding defects are eliminated in the optimized weld seam and the mechanical properties are improved. The results show that the proposed method is effective and reliable for improving the quality of welded joints in practical production.

Multiscale Modeling for Linking Growth, Microstructure, and Properties of Inorganic Microporous Films

NASA Technical Reports Server (NTRS)

Vlachos, Dion G.

2002-01-01

The focus of this presentation is on multiscale modeling in order to link processing, microstructure, and properties of materials. Overview of problems we study includes: Growth mechanisms in chemical and physical vapor epitaxy; thin films of zeolites for separation and sensing; thin Pd films for hydrogen separation and pattern formation by self-regulation routes.

Thermo-hydroforming of a fiber-reinforced thermoplastic composites considering fiber orientations

NASA Astrophysics Data System (ADS)

Ahn, Hyunchul; Kuuttila, Nicholas Eric; Pourboghrat, Farhang

2018-05-01

The Thermoplastic woven composites were formed using a composite thermal hydroforming process, utilizing heated and pressurized fluid, similar to sheet metal forming. This study focuses on the modification of 300-ton pressure formation and predicts its behavior. Spectra Shield SR-3136 is used in this study and material properties are measured by experiments. The behavior of fiber-reinforced thermoplastic polymer composites (FRTP) was modeled using the Preferred Fiber Orientation (PFO) model and validated by comparing numerical analysis with experimental results. The thermo-hydroforming process has shown good results in the ability to form deep drawn parts with reduced wrinkles. Numerical analysis was performed using the PFO model and implemented as commercial finite element software ABAQUS / Explicit. The user subroutine (VUMAT) was used for the material properties of the thermoplastic composite layer. This model is suitable for working with multiple layers of composite laminates. Model parameters have been updated to work with cohesive zone model to calculate the interfacial properties between each composite layer. The results of the numerical modeling showed a good correlation with the molding experiment on the forming shape. Numerical results were also compared with experimental results on punch force-displacement curves for deformed geometry and forming processes of the composite layer. Overall, the shape of the deformed FRTP, including the distribution of wrinkles, was accurately predicted as shown in this study.

Signatures of microevolutionary processes in phylogenetic patterns.

PubMed

Costa, Carolina L N; Lemos-Costa, Paula; Marquitti, Flavia M D; Fernandes, Lucas D; Ramos, Marlon F; Schneider, David M; Martins, Ayana B; Aguiar, Marcus A M

2018-06-23

Phylogenetic trees are representations of evolutionary relationships among species and contain signatures of the processes responsible for the speciation events they display. Inferring processes from tree properties, however, is challenging. To address this problem we analysed a spatially-explicit model of speciation where genome size and mating range can be controlled. We simulated parapatric and sympatric (narrow and wide mating range, respectively) radiations and constructed their phylogenetic trees, computing structural properties such as tree balance and speed of diversification. We showed that parapatric and sympatric speciation are well separated by these structural tree properties. Balanced trees with constant rates of diversification only originate in sympatry and genome size affected both the balance and the speed of diversification of the simulated trees. Comparison with empirical data showed that most of the evolutionary radiations considered to have developed in parapatry or sympatry are in good agreement with model predictions. Even though additional forces other than spatial restriction of gene flow, genome size, and genetic incompatibilities, do play a role in the evolution of species formation, the microevolutionary processes modeled here capture signatures of the diversification pattern of evolutionary radiations, regarding the symmetry and speed of diversification of lineages.

AN OVERVIEW OF THE INTEROPERABILITY ROADMAP FOR COM/.NET-BASED CAPE-OPEN

EPA Science Inventory

The CAPE-OPEN standard interfaces have been designed to permit flexibility and modularization of process simulation environments (PMEs) in order to use process modeling components such as unit operation or thermodynamic property models across a range of tolls employed in the life...

Discrete element method as an approach to model the wheat milling process

USDA-ARS?s Scientific Manuscript database

It is a well-known phenomenon that break-release, particle size, and size distribution of wheat milling are functions of machine operational parameters and grain properties. Due to the non-uniformity of characteristics and properties of wheat kernels, the kernel physical and mechanical properties af...

Empirical evidence for musical syntax processing? Computer simulations reveal the contribution of auditory short-term memory

PubMed Central

Bigand, Emmanuel; Delbé, Charles; Poulin-Charronnat, Bénédicte; Leman, Marc; Tillmann, Barbara

2014-01-01

During the last decade, it has been argued that (1) music processing involves syntactic representations similar to those observed in language, and (2) that music and language share similar syntactic-like processes and neural resources. This claim is important for understanding the origin of music and language abilities and, furthermore, it has clinical implications. The Western musical system, however, is rooted in psychoacoustic properties of sound, and this is not the case for linguistic syntax. Accordingly, musical syntax processing could be parsimoniously understood as an emergent property of auditory memory rather than a property of abstract processing similar to linguistic processing. To support this view, we simulated numerous empirical studies that investigated the processing of harmonic structures, using a model based on the accumulation of sensory information in auditory memory. The simulations revealed that most of the musical syntax manipulations used with behavioral and neurophysiological methods as well as with developmental and cross-cultural approaches can be accounted for by the auditory memory model. This led us to question whether current research on musical syntax can really be compared with linguistic processing. Our simulation also raises methodological and theoretical challenges to study musical syntax while disentangling the confounded low-level sensory influences. In order to investigate syntactic abilities in music comparable to language, research should preferentially use musical material with structures that circumvent the tonal effect exerted by psychoacoustic properties of sounds. PMID:24936174

Finite Element Modeling Used to Study Stress Distribution on the Foot

NASA Technical Reports Server (NTRS)

Morales, Nelson; Davis, Brian; Tajaddini, Azita

2004-01-01

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

Investigation of the laser engineered net shaping process for nanostructured cermets

NASA Astrophysics Data System (ADS)

Xiong, Yuhong

Laser Engineered Net Shaping (LENSRTM) is a solid freeform fabrication (SFF) technology that combines high power laser deposition and powder metallurgy technologies. The LENSRTM technology has been used to fabricate a number of metallic alloys with improved physical and mechanical material properties. The successful application provides a motivation to also apply this method to fabricate non-metallic alloys, such as tungsten carbide-cobalt (WC-Co) cermets in a timely and easy way. However, reports on this topic are very limited. In this work, the LENSRTM technology was used to investigate its application to nanostructured WC-Co cermets, including processing conditions, microstructural evolution, thermal behavior, mechanical properties, and environmental and economic benefits. Details of the approaches are described as follows. A comprehensive analysis of the relationships between process parameters, microstructural evolution and mechanical properties was conducted through various analytical techniques. Effects of process parameters on sample profiles and microstructures were analyzed. Dissolution, shape change and coarsening of WC particles were investigated to study the mechanisms of microstructural evolution. The thermal features were correlated with the microstructure and mechanical properties. The special thermal behavior during this process and its relevant effects on the microstructure have been experimentally studied and numerically simulated. A high-speed digital camera was applied to study the temperature profile, temperature gradient and cooling rate in and near the molten pool. Numerical modeling was employed for 3D samples using finite element method with ADINA software for the first time. The validated modeling results were used to interpret microstructural evolution and thermal history. In order to fully evaluate the capability of the LENSRTM technology for the fabrication of cermets, material properties of WC-Co cermets produced by different powder metallurgy technologies were compared. In addition, another cermet system, nanostructured titanium/tungsten carbide-nickel ((Ti,W)C-Ni) powder, prepared using high-energy ball milling process, was also deposited by the LENSRTM technology. Because of the near net shape feature of the LENSRTM process, special emphasis was also placed on its potential environmental and economic benefits by applying life cycle assessment (LCA) and technical cost modeling (TCM). Comparisons were conducted between the conventional powder metallurgy processes and the LENSRTM process.

ON NONSTATIONARY STOCHASTIC MODELS FOR EARTHQUAKES.

USGS Publications Warehouse

Safak, Erdal; Boore, David M.

1986-01-01

A seismological stochastic model for earthquake ground-motion description is presented. Seismological models are based on the physical properties of the source and the medium and have significant advantages over the widely used empirical models. The model discussed here provides a convenient form for estimating structural response by using random vibration theory. A commonly used random process for ground acceleration, filtered white-noise multiplied by an envelope function, introduces some errors in response calculations for structures whose periods are longer than the faulting duration. An alternate random process, filtered shot-noise process, eliminates these errors.

Modeling of digestive processes in the stomach as a Fluid-Structure Interaction (FSI) phenomenon

NASA Astrophysics Data System (ADS)

Acharya, Shashank; Kou, Wenjun; Kahrilas, Peter J.; Pandolfino, John E.; Patankar, Neelesh A.

2017-11-01

The process of digestion in the gastro-intestinal (GI) tract is a complex mechanical and chemical process. Digestion in the stomach involves substantial mixing and breakup of food into smaller particles by muscular activity. In this work, we have developed a fully resolved model of the stomach (along with the esophagus) and its various muscle groups that deform the wall to agitate the contents inside. We use the Immersed Boundary finite-element method to model this FSI problem. From the resulting simulations, the mixing intensity is analyzed as a function of muscle deformation. As muscle deformation is controlled by changing the intensity of the neural signal, the material properties of the stomach wall will have a significant effect on the resultant kinematics. Thus, the model is then used to identify the source of common GI tract motility pathologies by replicating irregular motions as a consequence of varying the mechanical properties of the wall and the related activation signal patterns. This approach gives us an in-silico framework that can be used to study the effect of tissue properties & muscle activity on the mechanical response of the stomach wall. This work is supported by NIH Grant 5R01DK079902-09.

Universal avalanche statistics and triggering close to failure in a mean-field model of rheological fracture

NASA Astrophysics Data System (ADS)

Baró, Jordi; Davidsen, Jörn

2018-03-01

The hypothesis of critical failure relates the presence of an ultimate stability point in the structural constitutive equation of materials to a divergence of characteristic scales in the microscopic dynamics responsible for deformation. Avalanche models involving critical failure have determined common universality classes for stick-slip processes and fracture. However, not all empirical failure processes exhibit the trademarks of criticality. The rheological properties of materials introduce dissipation, usually reproduced in conceptual models as a hardening of the coarse grained elements of the system. Here, we investigate the effects of transient hardening on (i) the activity rate and (ii) the statistical properties of avalanches. We find the explicit representation of transient hardening in the presence of generalized viscoelasticity and solve the corresponding mean-field model of fracture. In the quasistatic limit, the accelerated energy release is invariant with respect to rheology and the avalanche propagation can be reinterpreted in terms of a stochastic counting process. A single universality class can be defined from such analogy, and all statistical properties depend only on the distance to criticality. We also prove that interevent correlations emerge due to the hardening—even in the quasistatic limit—that can be interpreted as "aftershocks" and "foreshocks."

Neurobiological roots of language in primate audition: common computational properties.

PubMed

Bornkessel-Schlesewsky, Ina; Schlesewsky, Matthias; Small, Steven L; Rauschecker, Josef P

2015-03-01

Here, we present a new perspective on an old question: how does the neurobiology of human language relate to brain systems in nonhuman primates? We argue that higher-order language combinatorics, including sentence and discourse processing, can be situated in a unified, cross-species dorsal-ventral streams architecture for higher auditory processing, and that the functions of the dorsal and ventral streams in higher-order language processing can be grounded in their respective computational properties in primate audition. This view challenges an assumption, common in the cognitive sciences, that a nonhuman primate model forms an inherently inadequate basis for modeling higher-level language functions. Copyright © 2014 Elsevier Ltd. All rights reserved.

Biomedically relevant chemical and physical properties of coal combustion products.

PubMed Central

Fisher, G L

1983-01-01

The evaluation of the potential public and occupational health hazards of developing and existing combustion processes requires a detailed understanding of the physical and chemical properties of effluents available for human and environmental exposures. These processes produce complex mixtures of gases and aerosols which may interact synergistically or antagonistically with biological systems. Because of the physicochemical complexity of the effluents, the biomedically relevant properties of these materials must be carefully assessed. Subsequent to release from combustion sources, environmental interactions further complicate assessment of the toxicity of combustion products. This report provides an overview of the biomedically relevant physical and chemical properties of coal fly ash. Coal fly ash is presented as a model complex mixture for health and safety evaluation of combustion processes. PMID:6337824

Unsupervised Neural Network Quantifies the Cost of Visual Information Processing.

PubMed

Orbán, Levente L; Chartier, Sylvain

2015-01-01

Untrained, "flower-naïve" bumblebees display behavioural preferences when presented with visual properties such as colour, symmetry, spatial frequency and others. Two unsupervised neural networks were implemented to understand the extent to which these models capture elements of bumblebees' unlearned visual preferences towards flower-like visual properties. The computational models, which are variants of Independent Component Analysis and Feature-Extracting Bidirectional Associative Memory, use images of test-patterns that are identical to ones used in behavioural studies. Each model works by decomposing images of floral patterns into meaningful underlying factors. We reconstruct the original floral image using the components and compare the quality of the reconstructed image to the original image. Independent Component Analysis matches behavioural results substantially better across several visual properties. These results are interpreted to support a hypothesis that the temporal and energetic costs of information processing by pollinators served as a selective pressure on floral displays: flowers adapted to pollinators' cognitive constraints.

Some considerations concerning the challenge of incorporating social variables into epidemiological models of infectious disease transmission.

PubMed

Barnett, Tony; Fournié, Guillaume; Gupta, Sunetra; Seeley, Janet

2015-01-01

Incorporation of 'social' variables into epidemiological models remains a challenge. Too much detail and models cease to be useful; too little and the very notion of infection - a highly social process in human populations - may be considered with little reference to the social. The French sociologist Émile Durkheim proposed that the scientific study of society required identification and study of 'social currents'. Such 'currents' are what we might today describe as 'emergent properties', specifiable variables appertaining to individuals and groups, which represent the perspectives of social actors as they experience the environment in which they live their lives. Here we review the ways in which one particular emergent property, hope, relevant to a range of epidemiological situations, might be used in epidemiological modelling of infectious diseases in human populations. We also indicate how such an approach might be extended to include a range of other potential emergent properties to represent complex social and economic processes bearing on infectious disease transmission.

Characterization of mechanical properties of battery electrode films from acoustic resonance measurements

NASA Astrophysics Data System (ADS)

Dallon, Kathryn L.; Yao, Jing; Wheeler, Dean R.; Mazzeo, Brian A.

2018-04-01

Measurements of the mechanical properties of lithium-ion battery electrode films can be used to quantify and improve manufacturing processes and to predict the mechanical and electrochemical performance of the battery. This paper demonstrates the use of acoustic resonances to distinguish among commercial-grade battery films with different active electrode materials, thicknesses, and densities. Resonances are excited in a clamped circular area of the film using a pulsed infrared laser, and responses are measured using an electret condenser microphone. A numerical model is used to quantify the sensitivity of resonances to changes in mechanical properties. When the numerical model is compared to simple analytical models for thin plates and membranes, the battery films measured here trend more similarly to the membrane model. Resonance measurements are also used to monitor the drying process. Results from a scanning laser Doppler vibrometer verify the modes excited in the films, and a combination of experimental and simulated results is used to estimate the Young's modulus of the battery electrode coating layer.

A numerical model to simulate foams during devolatilization of polymers

NASA Astrophysics Data System (ADS)

Khan, Irfan; Dixit, Ravindra

2014-11-01

Customers often demand that the polymers sold in the market have low levels of volatile organic compounds (VOC). Some of the processes for making polymers involve the removal of volatiles to the levels of parts per million (devolatilization). During this step the volatiles are phase separated out of the polymer through a combination of heating and applying lower pressure, creating foam with the pure polymer in liquid phase and the volatiles in the gas phase. The efficiency of the devolatilization process depends on predicting the onset of solvent phase change in the polymer and volatiles mixture accurately based on the processing conditions. However due to the complex relationship between the polymer properties and the processing conditions this is not trivial. In this work, a bubble scale model is coupled with a bulk scale transport model to simulate the processing conditions of polymer devolatilization. The bubble scale model simulates the nucleation and bubble growth based on the classical nucleation theory and the popular ``influence volume approach.'' As such it provides the information of bubble size distribution and number density inside the polymer at any given time and position. This information is used to predict the bulk properties of the polymer and its behavior under the applied processing conditions. Initial results of this modeling approach will be presented.

Prediction of Tensile Strength of Friction Stir Weld Joints with Adaptive Neuro-Fuzzy Inference System (ANFIS) and Neural Network

NASA Technical Reports Server (NTRS)

Dewan, Mohammad W.; Huggett, Daniel J.; Liao, T. Warren; Wahab, Muhammad A.; Okeil, Ayman M.

2015-01-01

Friction-stir-welding (FSW) is a solid-state joining process where joint properties are dependent on welding process parameters. In the current study three critical process parameters including spindle speed (??), plunge force (????), and welding speed (??) are considered key factors in the determination of ultimate tensile strength (UTS) of welded aluminum alloy joints. A total of 73 weld schedules were welded and tensile properties were subsequently obtained experimentally. It is observed that all three process parameters have direct influence on UTS of the welded joints. Utilizing experimental data, an optimized adaptive neuro-fuzzy inference system (ANFIS) model has been developed to predict UTS of FSW joints. A total of 1200 models were developed by varying the number of membership functions (MFs), type of MFs, and combination of four input variables (??,??,????,??????) utilizing a MATLAB platform. Note EFI denotes an empirical force index derived from the three process parameters. For comparison, optimized artificial neural network (ANN) models were also developed to predict UTS from FSW process parameters. By comparing ANFIS and ANN predicted results, it was found that optimized ANFIS models provide better results than ANN. This newly developed best ANFIS model could be utilized for prediction of UTS of FSW joints.

Concentration-driven models revisited: towards a unified framework to model settling tanks in water resource recovery facilities.

PubMed

Torfs, Elena; Martí, M Carmen; Locatelli, Florent; Balemans, Sophie; Bürger, Raimund; Diehl, Stefan; Laurent, Julien; Vanrolleghem, Peter A; François, Pierre; Nopens, Ingmar

2017-02-01

A new perspective on the modelling of settling behaviour in water resource recovery facilities is introduced. The ultimate goal is to describe in a unified way the processes taking place both in primary settling tanks (PSTs) and secondary settling tanks (SSTs) for a more detailed operation and control. First, experimental evidence is provided, pointing out distributed particle properties (such as size, shape, density, porosity, and flocculation state) as an important common source of distributed settling behaviour in different settling unit processes and throughout different settling regimes (discrete, hindered and compression settling). Subsequently, a unified model framework that considers several particle classes is proposed in order to describe distributions in settling behaviour as well as the effect of variations in particle properties on the settling process. The result is a set of partial differential equations (PDEs) that are valid from dilute concentrations, where they correspond to discrete settling, to concentrated suspensions, where they correspond to compression settling. Consequently, these PDEs model both PSTs and SSTs.

A Study of Upgraded Phenolic Curing for RSRM Nozzle Rings

NASA Technical Reports Server (NTRS)

Smartt, Ziba

2000-01-01

A thermochemical cure model for predicting temperature and degree of cure profiles in curing phenolic parts was developed, validated and refined over several years. The model supports optimization of cure cycles and allows input of properties based upon the types of material and the process by which these materials are used to make nozzle components. The model has been refined to use sophisticated computer graphics to demonstrate the changes in temperature and degree of cure during the curing process. The effort discussed in the paper will be the conversion from an outdated solid modeling input program and SINDA analysis code to an integrated solid modeling and analysis package (I-DEAS solid model and TMG). Also discussed will be the incorporation of updated material properties obtained during full scale curing tests into the cure models and the results for all the Reusable Solid Rocket Motor (RSRM) nozzle rings.

High-Fidelity Microstructural Characterization and Performance Modeling of Aluminized Composite Propellant

DOE PAGES

Kosiba, Graham D.; Wixom, Ryan R.; Oehlschlaeger, Matthew A.

2017-10-27

Image processing and stereological techniques were used to characterize the heterogeneity of composite propellant and inform a predictive burn rate model. Composite propellant samples made up of ammonium perchlorate (AP), hydroxyl-terminated polybutadiene (HTPB), and aluminum (Al) were faced with an ion mill and imaged with a scanning electron microscope (SEM) and x-ray tomography (micro-CT). Properties of both the bulk and individual components of the composite propellant were determined from a variety of image processing tools. An algebraic model, based on the improved Beckstead-Derr-Price model developed by Cohen and Strand, was used to predict the steady-state burning of the aluminized compositemore » propellant. In the presented model the presence of aluminum particles within the propellant was introduced. The thermal effects of aluminum particles are accounted for at the solid-gas propellant surface interface and aluminum combustion is considered in the gas phase using a single global reaction. In conclusion, properties derived from image processing were used directly as model inputs, leading to a sample-specific predictive combustion model.« less

High-Fidelity Microstructural Characterization and Performance Modeling of Aluminized Composite Propellant

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

Kosiba, Graham D.; Wixom, Ryan R.; Oehlschlaeger, Matthew A.

Image processing and stereological techniques were used to characterize the heterogeneity of composite propellant and inform a predictive burn rate model. Composite propellant samples made up of ammonium perchlorate (AP), hydroxyl-terminated polybutadiene (HTPB), and aluminum (Al) were faced with an ion mill and imaged with a scanning electron microscope (SEM) and x-ray tomography (micro-CT). Properties of both the bulk and individual components of the composite propellant were determined from a variety of image processing tools. An algebraic model, based on the improved Beckstead-Derr-Price model developed by Cohen and Strand, was used to predict the steady-state burning of the aluminized compositemore » propellant. In the presented model the presence of aluminum particles within the propellant was introduced. The thermal effects of aluminum particles are accounted for at the solid-gas propellant surface interface and aluminum combustion is considered in the gas phase using a single global reaction. In conclusion, properties derived from image processing were used directly as model inputs, leading to a sample-specific predictive combustion model.« less

How visual illusions illuminate complementary brain processes: illusory depth from brightness and apparent motion of illusory contours

PubMed Central

Grossberg, Stephen

2014-01-01

Neural models of perception clarify how visual illusions arise from adaptive neural processes. Illusions also provide important insights into how adaptive neural processes work. This article focuses on two illusions that illustrate a fundamental property of global brain organization; namely, that advanced brains are organized into parallel cortical processing streams with computationally complementary properties. That is, in order to process certain combinations of properties, each cortical stream cannot process complementary properties. Interactions between these streams, across multiple processing stages, overcome their complementary deficiencies to compute effective representations of the world, and to thereby achieve the property of complementary consistency. The two illusions concern how illusory depth can vary with brightness, and how apparent motion of illusory contours can occur. Illusory depth from brightness arises from the complementary properties of boundary and surface processes, notably boundary completion and surface-filling in, within the parvocellular form processing cortical stream. This illusion depends upon how surface contour signals from the V2 thin stripes to the V2 interstripes ensure complementary consistency of a unified boundary/surface percept. Apparent motion of illusory contours arises from the complementary properties of form and motion processes across the parvocellular and magnocellular cortical processing streams. This illusion depends upon how illusory contours help to complete boundary representations for object recognition, how apparent motion signals can help to form continuous trajectories for target tracking and prediction, and how formotion interactions from V2-to-MT enable completed object representations to be continuously tracked even when they move behind intermittently occluding objects through time. PMID:25389399

A MULTISCALE FRAMEWORK FOR THE STOCHASTIC ASSIMILATION AND MODELING OF UNCERTAINTY ASSOCIATED NCF COMPOSITE MATERIALS

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

Mehrez, Loujaine; Ghanem, Roger; McAuliffe, Colin

multiscale framework to construct stochastic macroscopic constitutive material models is proposed. A spectral projection approach, specifically polynomial chaos expansion, has been used to construct explicit functional relationships between the homogenized properties and input parameters from finer scales. A homogenization engine embedded in Multiscale Designer, software for composite materials, has been used for the upscaling process. The framework is demonstrated using non-crimp fabric composite materials by constructing probabilistic models of the homogenized properties of a non-crimp fabric laminate in terms of the input parameters together with the homogenized properties from finer scales.

Fundamental analysis of the failure of polymer-based fiber reinforced composites

NASA Technical Reports Server (NTRS)

Kanninen, M. F.; Rybicki, E. F.; Griffith, W. I.; Broek, D.

1976-01-01

A mathematical model is described which will permit predictions of the strength of fiber reinforced composites containing known flaws to be made from the basic properties of their constituents. The approach was to embed a local heterogeneous region (LHR) surrounding the crack tip into an anisotropic elastic continuum. The model should (1) permit an explicit analysis of the micromechanical processes involved in the fracture process, and (2) remain simple enough to be useful in practical computations. Computations for arbitrary flaw size and orientation under arbitrary applied load combinations were performed from unidirectional composites with linear elastic-brittle constituent behavior. The mechanical properties were nominally those of graphite epoxy. With the rupture properties arbitrarily varied to test the capability of the model to reflect real fracture modes in fiber composites, it was shown that fiber breakage, matrix crazing, crack bridging, matrix-fiber debonding, and axial splitting can all occur during a period of (gradually) increasing load prior to catastrophic fracture. The computations reveal qualitatively the sequential nature of the stable crack process that precedes fracture.

Ballistic-Failure Mechanisms in Gas Metal Arc Welds of Mil A46100 Armor-Grade Steel: A Computational Investigation

NASA Astrophysics Data System (ADS)

Grujicic, M.; Snipes, J. S.; Galgalikar, R.; Ramaswami, S.; Yavari, R.; Yen, C.-F.; Cheeseman, B. A.

2014-09-01

In our recent work, a multi-physics computational model for the conventional gas metal arc welding (GMAW) joining process was introduced. The model is of a modular type and comprises five modules, each designed to handle a specific aspect of the GMAW process, i.e.: (i) electro-dynamics of the welding-gun; (ii) radiation-/convection-controlled heat transfer from the electric-arc to the workpiece and mass transfer from the filler-metal consumable electrode to the weld; (iii) prediction of the temporal evolution and the spatial distribution of thermal and mechanical fields within the weld region during the GMAW joining process; (iv) the resulting temporal evolution and spatial distribution of the material microstructure throughout the weld region; and (v) spatial distribution of the as-welded material mechanical properties. In the present work, the GMAW process model has been upgraded with respect to its predictive capabilities regarding the spatial distribution of the mechanical properties controlling the ballistic-limit (i.e., penetration-resistance) of the weld. The model is upgraded through the introduction of the sixth module in the present work in recognition of the fact that in thick steel GMAW weldments, the overall ballistic performance of the armor may become controlled by the (often inferior) ballistic limits of its weld (fusion and heat-affected) zones. To demonstrate the utility of the upgraded GMAW process model, it is next applied to the case of butt-welding of a prototypical high-hardness armor-grade martensitic steel, MIL A46100. The model predictions concerning the spatial distribution of the material microstructure and ballistic-limit-controlling mechanical properties within the MIL A46100 butt-weld are found to be consistent with prior observations and general expectations.

Mathematical modeling of high-pH chemical flooding

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

Bhuyan, D.; Lake, L.W.; Pope, G.A.

1990-05-01

This paper describes a generalized compositional reservoir simulator for high-pH chemical flooding processes. This simulator combines the reaction chemistry associated with these processes with the extensive physical- and flow-property modeling schemes of an existing micellar/polymer flood simulator, UTCHEM. Application of the model is illustrated for cases from a simple alkaline preflush to surfactant-enhanced alkaline-polymer flooding.

Investigation of Parametric Influence on the Properties of Al6061-SiCp Composite

NASA Astrophysics Data System (ADS)

Adebisi, A. A.; Maleque, M. A.; Bello, K. A.

2017-03-01

The influence of process parameter in stir casting play a major role on the development of aluminium reinforced silicon carbide particle (Al-SiCp) composite. This study aims to investigate the influence of process parameters on wear and density properties of Al-SiCp composite using stir casting technique. Experimental data are generated based on a four-factors-five-level central composite design of response surface methodology. Analysis of variance is utilized to confirm the adequacy and validity of developed models considering the significant model terms. Optimization of the process parameters adequately predicts the Al-SiCp composite properties with stirring speed as the most influencing factor. The aim of optimization process is to minimize wear and maximum density. The multiple objective optimization (MOO) achieved an optimal value of 14 wt% reinforcement fraction (RF), 460 rpm stirring speed (SS), 820 °C processing temperature (PTemp) and 150 secs processing time (PT). Considering the optimum parametric combination, wear mass loss achieved a minimum of 1 x 10-3 g and maximum density value of 2.780g/mm3 with a confidence and desirability level of 95.5%.

26 CFR 1.6038A-2 - Requirement of return.

Code of Federal Regulations, 2010 CFR

2010-04-01

..., formulas, inventions, models, patents, processes, trademarks, and other similar intangible property rights; (v) Consideration paid and received for technical, managerial, engineering, construction, scientific... of all property (including monetary consideration), rights, or obligations transferred from the...

Systematic observations of the slip pulse properties of large earthquake ruptures

USGS Publications Warehouse

Melgar, Diego; Hayes, Gavin

2017-01-01

In earthquake dynamics there are two end member models of rupture: propagating cracks and self-healing pulses. These arise due to different properties of faults and have implications for seismic hazard; rupture mode controls near-field strong ground motions. Past studies favor the pulse-like mode of rupture; however, due to a variety of limitations, it has proven difficult to systematically establish their kinematic properties. Here we synthesize observations from a database of >150 rupture models of earthquakes spanning M7–M9 processed in a uniform manner and show the magnitude scaling properties of these slip pulses indicates self-similarity. Further, we find that large and very large events are statistically distinguishable relatively early (at ~15 s) in the rupture process. This suggests that with dense regional geophysical networks strong ground motions from a large rupture can be identified before their onset across the source region.

Estimation Model for Magnetic Properties of Stamped Electrical Steel Sheet

NASA Astrophysics Data System (ADS)

Kashiwara, Yoshiyuki; Fujimura, Hiroshi; Okamura, Kazuo; Imanishi, Kenji; Yashiki, Hiroyoshi

Less deterioration in magnetic properties of electrical steel sheets in the process of stamping out iron-core are necessary in order to maintain its performance. First, the influence of plastic strain and stress on magnetic properties was studied by test pieces, in which plastic strain was added uniformly and residual stress was not induced. Because the influence of plastic strain was expressed by equivalent plastic strain, at each equivalent plastic strain state the influence of load stress was investigated. Secondly, elastic limit was determined about 60% of macroscopic yield point (MYP), and it was found to agree with stress limit inducing irreversible deterioration in magnetic properties. Therefore simulation models, where beyond elastic limit plastic deformation begins and magnetic properties are deteriorated steeply, are proposed. Besides considered points in the deformation analysis are strain-rate sensitivity of flow stress, anisotropy under deformation, and influence of stress triaxiality on fracture. Finally, proposed models have been shown to be valid, because magnetic properties of 5mm width rectangular sheets stamped out from non-oriented electrical steel sheet (35A250 JIS grade) can be estimated with good accuracy. It is concluded that the elastic limit must be taken into account in both stamping process simulation and magnetic field calculation.

On the Modeling of Vacuum Arc Remelting Process in Titanium Alloys

NASA Astrophysics Data System (ADS)

Patel, Ashish; Fiore, Daniel

2016-07-01

Mathematical modeling is routinely used in the process development and production of advanced aerospace alloys to gain greater insight into the effect of process parameters on final properties. This article describes the application of a 2-D mathematical VAR model presented at previous LMPC meetings. The impact of process parameters on melt pool geometry, solidification behavior, fluid-flow and chemistry in a Ti-6Al-4V ingot is discussed. Model predictions are validated against published data from a industrial size ingot, and results of a parametric study on particle dissolution are also discussed.

A review of combined experimental and computational procedures for assessing biopolymer structure–process–property relationships

PubMed Central

Gronau, Greta; Krishnaji, Sreevidhya T.; Kinahan, Michelle E.; Giesa, Tristan; Wong, Joyce Y.; Kaplan, David L.; Buehler, Markus J.

2013-01-01

Tailored biomaterials with tunable functional properties are desirable for many applications ranging from drug delivery to regenerative medicine. To improve the predictability of biopolymer materials functionality, multiple design parameters need to be considered, along with appropriate models. In this article we review the state of the art of synthesis and processing related to the design of biopolymers, with an emphasis on the integration of bottom-up computational modeling in the design process. We consider three prominent examples of well-studied biopolymer materials – elastin, silk, and collagen – and assess their hierarchical structure, intriguing functional properties and categorize existing approaches to study these materials. We find that an integrated design approach in which both experiments and computational modeling are used has rarely been applied for these materials due to difficulties in relating insights gained on different length- and time-scales. In this context, multiscale engineering offers a powerful means to accelerate the biomaterials design process for the development of tailored materials that suit the needs posed by the various applications. The combined use of experimental and computational tools has a very broad applicability not only in the field of biopolymers, but can be exploited to tailor the properties of other polymers and composite materials in general. PMID:22938765

Process modeling for carbon-phenolic nozzle materials

NASA Technical Reports Server (NTRS)

Letson, Mischell A.; Bunker, Robert C.; Remus, Walter M., III; Clinton, R. G.

1989-01-01

A thermochemical model based on the SINDA heat transfer program is developed for carbon-phenolic nozzle material processes. The model can be used to optimize cure cycles and to predict material properties based on the types of materials and the process by which these materials are used to make nozzle components. Chemical kinetic constants for Fiberite MX4926 were determined so that optimization of cure cycles for the current Space Shuttle Solid Rocket Motor nozzle rings can be determined.

Perceptual uncertainty is a property of the cognitive system.

PubMed

Perea, Manuel; Carreiras, Manuel

2012-10-01

We qualify Frost's proposals regarding letter-position coding in visual word recognition and the universal model of reading. First, we show that perceptual uncertainty regarding letter position is not tied to European languages-instead it is a general property of the cognitive system. Second, we argue that a universal model of reading should incorporate a developmental view of the reading process.

Associative learning is necessary but not sufficient for mirror neuron development.

PubMed

Bonaiuto, James

2014-04-01

Existing computational models of the mirror system demonstrate the additional circuitry needed for mirror neurons to display the range of properties that they exhibit. Such models emphasize the need for existing connectivity to form visuomotor associations, processing to reduce the space of possible inputs, and demonstrate the role neurons with mirror properties might play in monitoring one's own actions.

Analyzing Students' Learning Progressions throughout a Teaching Sequence on Acoustic Properties of Materials with a Model-Based Inquiry Approach

ERIC Educational Resources Information Center

Hernández, María Isabel; Couso, Digna; Pintó, Roser

2015-01-01

The study we have carried out aims to characterize 15-to 16-year-old students' learning progressions throughout the implementation of a teaching-learning sequence on the acoustic properties of materials. Our purpose is to better understand students' modeling processes about this topic and to identify how the instructional design and actual…

The role of scattering and absorption on the optical properties of birefringent polycrystalline ceramics: Modeling and experiments on ruby (Cr:Al2O3)

NASA Astrophysics Data System (ADS)

Penilla, E. H.; Hardin, C. L.; Kodera, Y.; Basun, S. A.; Evans, D. R.; Garay, J. E.

2016-01-01

Light scattering due to birefringence has prevented the use of polycrystalline ceramics with anisotropic optical properties in applications such as laser gain media. However, continued development of processing technology has allowed for very low porosity and fine grains, significantly improving transparency and is paving the way for polycrystalline ceramics to be used in demanding optical applications. We present a method for producing highly transparent Cr3+ doped Al2O3 (ruby) using current activated pressure assisted densification. The one-step doping/densification process produces fine grained ceramics with well integrated (doped) Cr, resulting in good absorption and emission. In order to explain the light transmission properties, we extend the analytical model based on the Rayleigh-Gans-Debye approximation that has been previously used for undoped alumina to include absorption. The model presented captures reflection, scattering, and absorption phenomena in the ceramics. Comparison with measured transmission confirms that the model adequately describes the properties of polycrystalline ruby. In addition the measured emission spectra and emission lifetime are found to be similar to single crystals, confirming the high optical quality of the ceramics.

Prediction of mechanical and wear properties of 6026 aluminum alloy waste to be used in prosthetics limbs

NASA Astrophysics Data System (ADS)

Arbilei, Marwan N.

2018-05-01

This paper aimed to recycle high power electrical wires west in prosthetics limbs manufacturing. The effect of grain size on mechanical properties (Hardness and Tensile Strength), and wear resistance of commercial 6026 T9 Aluminum alloys that used in electrical industry have been modeled to be predicted. Six sets of samples were prepared with different annealing heat treatment parameters, (300,350 and 400)°C with (1 and 2) hours. Each treatment gained different grain sizes (23-71) μm and evenly HV (61-169) values. The grain size that produced from heat treatments was ranged from. Tensile properties regarding HV have been reviewed and all data haven collected to create a mathematical model showing the relation between Tensile strength and Hardness. The Sliding wear tests applied with (3 and 8) N with five periods (20-100) minutes. Multiple regression model prepared for predicting the values of weight loss for wear process. The model was tested and validated for the properties. The main purpose of this research is to provide an effective and accurate way to predict weight loose rate in wear process.

Screening of the aerodynamic and biophysical properties of barley malt

NASA Astrophysics Data System (ADS)

Ghodsvali, Alireza; Farzaneh, Vahid; Bakhshabadi, Hamid; Zare, Zahra; Karami, Zahra; Mokhtarian, Mohsen; Carvalho, Isabel. S.

2016-10-01

An understanding of the aerodynamic and biophysical properties of barley malt is necessary for the appropriate design of equipment for the handling, shipping, dehydration, grading, sorting and warehousing of this strategic crop. Malting is a complex biotechnological process that includes steeping; germination and finally, the dehydration of cereal grains under controlled temperature and humidity conditions. In this investigation, the biophysical properties of barley malt were predicted using two models of artificial neural networks as well as response surface methodology. Stepping time and germination time were selected as the independent variables and 1 000 kernel weight, kernel density and terminal velocity were selected as the dependent variables (responses). The obtained outcomes showed that the artificial neural network model, with a logarithmic sigmoid activation function, presents more precise results than the response surface model in the prediction of the aerodynamic and biophysical properties of produced barley malt. This model presented the best result with 8 nodes in the hidden layer and significant correlation coefficient values of 0.783, 0.767 and 0.991 were obtained for responses one thousand kernel weight, kernel density, and terminal velocity, respectively. The outcomes indicated that this novel technique could be successfully applied in quantitative and qualitative monitoring within the malting process.

EDDA 1.0: integrated simulation of debris flow erosion, deposition and property changes

NASA Astrophysics Data System (ADS)

Chen, H. X.; Zhang, L. M.

2015-03-01

Debris flow material properties change during the initiation, transportation and deposition processes, which influences the runout characteristics of the debris flow. A quasi-three-dimensional depth-integrated numerical model, EDDA (Erosion-Deposition Debris flow Analysis), is presented in this paper to simulate debris flow erosion, deposition and induced material property changes. The model considers changes in debris flow density, yield stress and dynamic viscosity during the flow process. The yield stress of the debris flow mixture determined at limit equilibrium using the Mohr-Coulomb equation is applicable to clear water flow, hyper-concentrated flow and fully developed debris flow. To assure numerical stability and computational efficiency at the same time, an adaptive time stepping algorithm is developed to solve the governing differential equations. Four numerical tests are conducted to validate the model. The first two tests involve a one-dimensional debris flow with constant properties and a two-dimensional dam-break water flow. The last two tests involve erosion and deposition, and the movement of multi-directional debris flows. The changes in debris flow mass and properties due to either erosion or deposition are shown to affect the runout characteristics significantly. The model is also applied to simulate a large-scale debris flow in Xiaojiagou Ravine to test the performance of the model in catchment-scale simulations. The results suggest that the model estimates well the volume, inundated area, and runout distance of the debris flow. The model is intended for use as a module in a real-time debris flow warning system.

Development and evaluation of P/M processing techniques to improve and control the mechanical properties of metal injection molded parts

NASA Astrophysics Data System (ADS)

Sago, James Alan

Metal Injection Molding (MIM) is one of the most rapidly growing areas of powder metallurgy (P/M) but the growth of MIM into new markets and more demanding applications is limited by two fundamental barriers, the availability of low cost metal powders and a lack of knowledge and understanding of how mechanical properties, especially toughness, are affected by the many parameters in the MIM process. The goals of this study were to investigate solutions to these challenges for MIM. Mechanical alloying (MA) is a technique which can produce a wide variety of powder compositions in a size range suited to MIM and in smaller batches. However MA typically suffers from low production volumes and long milling times. This study will show that a saucer mill can produce sizable volumes of MA powders in times typically less than an hour. The MA process was also used to produce powders of 17-4PH stainless steel and the NiTi shape memory alloy for a MIM feedstock. This study shows that the MA powder characteristics led to successful MIM processing of parts. Previous studies have shown that the toughness of individual MIM parts can vary widely within a single production run and from one producer to another. In the last part of the study a Design of Experiments (DOE) approach was used to evaluate the effects of MIM processing parameters on the mechanical properties. Analysis of Variance produced mathematical models for Charpy impact toughness, hardness, density, and carbon content. Tensile properties did not produce a good model due to processing problems. The models and recommendations for improving both toughness and reproducibility of toughness are presented.

QUANTIFYING THE EFFECTS OF THE MIXING PROCESS IN FABRICATED DILUTION SYSTEMS ON PARTICULATE EMISSION MEASUREMENTS VIA AN INTEGRATED EXPERIMENTAL AND MODELING APPROACH

EPA Science Inventory

Uncertainties of simulated aerosol optical properties induced by assumptions on aerosol physical and chemical properties: an AQMEII-2 perspective

EPA Science Inventory

The calculation of aerosol optical properties from aerosol mass is a process subject to uncertainty related to necessary assumptions on the treatment of the chemical species mixing state, density, refractive index, and hygroscopic growth. In the framework of the AQMEII-2 model in...

Evaluating aerosol influence on cloud models using in-situ measurements during the INUPIAQ campaign

NASA Astrophysics Data System (ADS)

Farrington, R.; Connolly, P.; Choularton, T.; Bower, K.; Lloyd, G.; Flynn, M.; Crosier, J.; Field, P.

2014-12-01

At temperatures between -35°C and 0°C, the presence of insoluble aerosols acting as ice nuclei (IN) initiate the nucleation of ice under atmospheric conditions. Previous field and laboratory campaigns have suggested that mineral dust present in the atmosphere act as IN at temperatures around -20°C (e.g. Sassen et al. 2003), however the cause of ice nucleation at temperatures of around -5°C is less certain. Coupled with the limited representation of aerosol and cloud processes in large-scale weather and climate models, the need for improved in-situ measurements of aerosol properties and cloud micro-physical processes to drive the improvement of aerosol-clouds processes in models is evident. As part of the Ice NUcleation Process Investigation and Quantification (INUPIAQ) project, two field campaigns were conducted in early 2013 and early 2014. Both campaigns included measurements of cloud micro-physical properties at the summit of Jungfraujoch in Switzerland (3580m asl). Using data from the 2013 campaign and modelling simulations from the Weather Research and Forecasting model (WRF), an upwind site, located at Schilthorn (2970m asl), was determined for measuring aerosol properties out of cloud during the 2014 campaign. Further measurements of the cloud and aerosols properties were taken remotely using a doppler LiDAR located at Kleine Scheidegg (2061m asl). The aim of this project is to determine whether detailed aerosol information is important to determining cloud and precipitation properties downwind. To this end WRF was run using the aerosol number concentrations and size distributions measured at the Schilthorn site to compare modelled ice number concentrations with measurements taken at Jungfraujoch using state of the science cloud ice probes, including the Three-View Cloud Particle Imager (3V-CPI) and the Cloud Aerosol Spectrometer with Depolarization (CAS-DPOL), with the results of the comparison presented and discussed at this meeting. ReferencesSassen, K., et al, 2003: Saharan dust storms and indirect aerosol effects on clouds: Crystal-face results. Geophys. Res. Lett., 30(12), 1633-1636.

Aircraft Structural Mass Property Prediction Using Conceptual-Level Structural Analysis

NASA Technical Reports Server (NTRS)

Sexstone, Matthew G.

1998-01-01

This paper describes a methodology that extends the use of the Equivalent LAminated Plate Solution (ELAPS) structural analysis code from conceptual-level aircraft structural analysis to conceptual-level aircraft mass property analysis. Mass property analysis in aircraft structures has historically depended upon parametric weight equations at the conceptual design level and Finite Element Analysis (FEA) at the detailed design level. ELAPS allows for the modeling of detailed geometry, metallic and composite materials, and non-structural mass coupled with analytical structural sizing to produce high-fidelity mass property analyses representing fully configured vehicles early in the design process. This capability is especially valuable for unusual configuration and advanced concept development where existing parametric weight equations are inapplicable and FEA is too time consuming for conceptual design. This paper contrasts the use of ELAPS relative to empirical weight equations and FEA. ELAPS modeling techniques are described and the ELAPS-based mass property analysis process is detailed. Examples of mass property stochastic calculations produced during a recent systems study are provided. This study involved the analysis of three remotely piloted aircraft required to carry scientific payloads to very high altitudes at subsonic speeds. Due to the extreme nature of this high-altitude flight regime, few existing vehicle designs are available for use in performance and weight prediction. ELAPS was employed within a concurrent engineering analysis process that simultaneously produces aerodynamic, structural, and static aeroelastic results for input to aircraft performance analyses. The ELAPS models produced for each concept were also used to provide stochastic analyses of wing structural mass properties. The results of this effort indicate that ELAPS is an efficient means to conduct multidisciplinary trade studies at the conceptual design level.

Aircraft Structural Mass Property Prediction Using Conceptual-Level Structural Analysis

NASA Technical Reports Server (NTRS)

Sexstone, Matthew G.

1998-01-01

This paper describes a methodology that extends the use of the Equivalent LAminated Plate Solution (ELAPS) structural analysis code from conceptual-level aircraft structural analysis to conceptual-level aircraft mass property analysis. Mass property analysis in aircraft structures has historically depended upon parametric weight equations at the conceptual design level and Finite Element Analysis (FEA) at the detailed design level ELAPS allows for the modeling of detailed geometry, metallic and composite materials, and non-structural mass coupled with analytical structural sizing to produce high-fidelity mass property analyses representing fully configured vehicles early in the design process. This capability is especially valuable for unusual configuration and advanced concept development where existing parametric weight equations are inapplicable and FEA is too time consuming for conceptual design. This paper contrasts the use of ELAPS relative to empirical weight equations and FEA. ELAPS modeling techniques are described and the ELAPS-based mass property analysis process is detailed Examples of mass property stochastic calculations produced during a recent systems study are provided This study involved the analysis of three remotely piloted aircraft required to carry scientific payloads to very high altitudes at subsonic speeds. Due to the extreme nature of this high-altitude flight regime,few existing vehicle designs are available for use in performance and weight prediction. ELAPS was employed within a concurrent engineering analysis process that simultaneously produces aerodynamic, structural, and static aeroelastic results for input to aircraft performance analyses. The ELAPS models produced for each concept were also used to provide stochastic analyses of wing structural mass properties. The results of this effort indicate that ELAPS is an efficient means to conduct multidisciplinary trade studies at the conceptual design level.

A mixed boundary representation to simulate the displacement of a biofluid by a biomaterial in porous media.

PubMed

Widmer, René P; Ferguson, Stephen J

2011-05-01

Characterization of the biomaterial flow through porous bone is crucial for the success of the bone augmentation process in vertebroplasty. The biofluid, biomaterial, and local morphological bone characteristics determine the final shape of the filling, which is important both for the post-treatment mechanical loading and the risk of intraoperative extraosseous leakage. We have developed a computational model that describes the flow of biomaterials in porous bone structures by considering the material porosity, the region-dependent intrinsic permeability of the porous structure, the rheological properties of the biomaterial, and the boundary conditions of the filling process. To simulate the process of the substitution of a biofluid (bone marrow) by a biomaterial (bone cement), we developed a hybrid formulation to describe the evolution of the fluid boundary and properties and coupled it to a modified version of Darcy's law. The apparent rheological properties are derived from a fluid-fluid interface tracking algorithm and a mixed boundary representation. The region- specific intrinsic permeability of the bone is governed by an empirical relationship resulting from a fitting process of experimental data. In a first step, we verified the model by studying the displacement process in spherical domains, where the spreading pattern is known in advance. The mixed boundary model demonstrated, as expected, that the determinants of the spreading pattern are the local intrinsic permeability of the porous matrix and the ratio of the viscosity of the fluids that are contributing to the displacement process. The simulations also illustrate the sensitivity of the mixed boundary representation to anisotropic permeability, which is related to the directional dependent microstructural properties of the porous medium. Furthermore, we compared the nonlinear finite element model to different published experimental studies and found a moderate to good agreement (R(2)=0.9895 for a one-dimensional bone core infiltration test and a 10.94-16.92% relative error for a three-dimensional spreading pattern study, respectively) between computational and experimental results.

Fractional Brownian motion time-changed by gamma and inverse gamma process

NASA Astrophysics Data System (ADS)

Kumar, A.; Wyłomańska, A.; Połoczański, R.; Sundar, S.

2017-02-01

Many real time-series exhibit behavior adequate to long range dependent data. Additionally very often these time-series have constant time periods and also have characteristics similar to Gaussian processes although they are not Gaussian. Therefore there is need to consider new classes of systems to model these kinds of empirical behavior. Motivated by this fact in this paper we analyze two processes which exhibit long range dependence property and have additional interesting characteristics which may be observed in real phenomena. Both of them are constructed as the superposition of fractional Brownian motion (FBM) and other process. In the first case the internal process, which plays role of the time, is the gamma process while in the second case the internal process is its inverse. We present in detail their main properties paying main attention to the long range dependence property. Moreover, we show how to simulate these processes and estimate their parameters. We propose to use a novel method based on rescaled modified cumulative distribution function for estimation of parameters of the second considered process. This method is very useful in description of rounded data, like waiting times of subordinated processes delayed by inverse subordinators. By using the Monte Carlo method we show the effectiveness of proposed estimation procedures. Finally, we present the applications of proposed models to real time series.

Selecting the process variables for filament winding

NASA Technical Reports Server (NTRS)

Calius, E.; Springer, G. S.

1986-01-01

A model is described which can be used to determine the appropriate values of the process variables for filament winding cylinders. The process variables which can be selected by the model include the winding speed, fiber tension, initial resin degree of cure, and the temperatures applied during winding, curing, and post-curing. The effects of these process variables on the properties of the cylinder during and after manufacture are illustrated by a numerical example.

Assessing global vegetation activity using spatio-temporal Bayesian modelling

NASA Astrophysics Data System (ADS)

Mulder, Vera L.; van Eck, Christel M.; Friedlingstein, Pierre; Regnier, Pierre A. G.

2016-04-01

This work demonstrates the potential of modelling vegetation activity using a hierarchical Bayesian spatio-temporal model. This approach allows modelling changes in vegetation and climate simultaneous in space and time. Changes of vegetation activity such as phenology are modelled as a dynamic process depending on climate variability in both space and time. Additionally, differences in observed vegetation status can be contributed to other abiotic ecosystem properties, e.g. soil and terrain properties. Although these properties do not change in time, they do change in space and may provide valuable information in addition to the climate dynamics. The spatio-temporal Bayesian models were calibrated at a regional scale because the local trends in space and time can be better captured by the model. The regional subsets were defined according to the SREX segmentation, as defined by the IPCC. Each region is considered being relatively homogeneous in terms of large-scale climate and biomes, still capturing small-scale (grid-cell level) variability. Modelling within these regions is hence expected to be less uncertain due to the absence of these large-scale patterns, compared to a global approach. This overall modelling approach allows the comparison of model behavior for the different regions and may provide insights on the main dynamic processes driving the interaction between vegetation and climate within different regions. The data employed in this study encompasses the global datasets for soil properties (SoilGrids), terrain properties (Global Relief Model based on SRTM DEM and ETOPO), monthly time series of satellite-derived vegetation indices (GIMMS NDVI3g) and climate variables (Princeton Meteorological Forcing Dataset). The findings proved the potential of a spatio-temporal Bayesian modelling approach for assessing vegetation dynamics, at a regional scale. The observed interrelationships of the employed data and the different spatial and temporal trends support our hypothesis. That is, the change of vegetation in space and time may be better understood when modelling vegetation change as both a dynamic and multivariate process. Therefore, future research will focus on a multivariate dynamical spatio-temporal modelling approach. This ongoing research is performed within the context of the project "Global impacts of hydrological and climatic extremes on vegetation" (project acronym: SAT-EX) which is part of the Belgian research programme for Earth Observation Stereo III.

SME Acceptability Determination For DWPF Process Control (U)

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

Edwards, T.

2017-06-12

The statistical system described in this document is called the Product Composition Control System (PCCS). K. G. Brown and R. L. Postles were the originators and developers of this system as well as the authors of the first three versions of this technical basis document for PCCS. PCCS has guided acceptability decisions for the processing at the Defense Waste Processing Facility (DWPF) at the Savannah River Site (SRS) since the start of radioactive operations in 1996. The author of this revision to the document gratefully acknowledges the firm technical foundation that Brown and Postles established to support the ongoing successfulmore » operation at the DWPF. Their integration of the glass propertycomposition models, developed under the direction of C. M. Jantzen, into a coherent and robust control system, has served the DWPF well over the last 20+ years, even as new challenges, such as the introduction into the DWPF flowsheet of auxiliary streams from the Actinide Removal Process (ARP) and other processes, were met. The purpose of this revision is to provide a technical basis for modifications to PCCS required to support the introduction of waste streams from the Salt Waste Processing Facility (SWPF) into the DWPF flowsheet. An expanded glass composition region is anticipated by the introduction of waste streams from SWPF, and property-composition studies of that glass region have been conducted. Jantzen, once again, directed the development of glass property-composition models applicable for this expanded composition region. The author gratefully acknowledges the technical contributions of C.M. Jantzen leading to the development of these glass property-composition models. The integration of these models into the PCCS constraints necessary to administer future acceptability decisions for the processing at DWPF is provided by this sixth revision of this document.« less

Inductive Reasoning about Causally Transmitted Properties

ERIC Educational Resources Information Center

Shafto, Patrick; Kemp, Charles; Bonawitz, Elizabeth Baraff; Coley, John D.; Tenenbaum, Joshua B.

2008-01-01

Different intuitive theories constrain and guide inferences in different contexts. Formalizing simple intuitive theories as probabilistic processes operating over structured representations, we present a new computational model of category-based induction about causally transmitted properties. A first experiment demonstrates undergraduates'…

PREDICTION OF PHYSICOCHEMICAL PROCESSES FOR ENVIRONMENTAL MODELING BY COMPUTER

EPA Science Inventory

The major differences among behavioral profiles of molecules in the environment are attributable to their physicochemical properties. For most chemicals, only fragmentary knowledge exists about those properties that determine each compound's environmental fate. A chemical-by-ch...

A phenomenological model for orificed hollow cathodes. Ph.D. Thesis, 1 Dec. 1981 - 1 Dec. 1982; [electrostatic thruster

NASA Technical Reports Server (NTRS)

Siegfried, D. E.

1982-01-01

A quartz hollow tube cathode was used to determine the operating conditions within a mercury orificed hollow cathode. Insert temperature profiles, cathode current distributions, plasma properties profile, and internal pressure-mass flow rate results are summarized and used in a phenomenological model which qualitatively describes electron emission and plasma production processes taking place within the cathode. By defining an idealized ion production region within which most of the plasma processes are concentrated, this model is expressed analytically as a simple set of equations which relate cathode dimensions and specifiable operating conditions, such as mass flow rate and discharge current, to such important parameters as emission surface temperature and internal plasma properties. Key aspects of the model are examined.

Modelling coupled microbial processes in the subsurface: Model development, verification, evaluation and application

NASA Astrophysics Data System (ADS)

Masum, Shakil A.; Thomas, Hywel R.

2018-06-01

To study subsurface microbial processes, a coupled model which has been developed within a Thermal-Hydraulic-Chemical-Mechanical (THCM) framework is presented. The work presented here, focuses on microbial transport, growth and decay mechanisms under the influence of multiphase flow and bio-geochemical reactions. In this paper, theoretical formulations and numerical implementations of the microbial model are presented. The model has been verified and also evaluated against relevant experimental results. Simulated results show that the microbial processes have been accurately implemented and their impacts on porous media properties can be predicted either qualitatively or quantitatively or both. The model has been applied to investigate biofilm growth in a sandstone core that is subjected to a two-phase flow and variable pH conditions. The results indicate that biofilm growth (if not limited by substrates) in a multiphase system largely depends on the hydraulic properties of the medium. When the change in porewater pH which occurred due to dissolution of carbon dioxide gas is considered, growth processes are affected. For the given parameter regime, it has been shown that the net biofilm growth is favoured by higher pH; whilst the processes are considerably retarded at lower pH values. The capabilities of the model to predict microbial respiration in a fully coupled multiphase flow condition and microbial fermentation leading to production of a gas phase are also demonstrated.

Controls on the spatial variability of key soil properties: comparing field data with a mechanistic soilscape evolution model

NASA Astrophysics Data System (ADS)

Vanwalleghem, T.; Román, A.; Giraldez, J. V.

2016-12-01

There is a need for better understanding the processes influencing soil formation and the resulting distribution of soil properties. Soil properties can exhibit strong spatial variation, even at the small catchment scale. Especially soil carbon pools in semi-arid, mountainous areas are highly uncertain because bulk density and stoniness are very heterogeneous and rarely measured explicitly. In this study, we explore the spatial variability in key soil properties (soil carbon stocks, stoniness, bulk density and soil depth) as a function of processes shaping the critical zone (weathering, erosion, soil water fluxes and vegetation patterns). We also compare the potential of a geostatistical versus a mechanistic soil formation model (MILESD) for predicting these key soil properties. Soil core samples were collected from 67 locations at 6 depths. Total soil organic carbon stocks were 4.38 kg m-2. Solar radiation proved to be the key variable controlling soil carbon distribution. Stone content was mostly controlled by slope, indicating the importance of erosion. Spatial distribution of bulk density was found to be highly random. Finally, total carbon stocks were predicted using a random forest model whose main covariates were solar radiation and NDVI. The model predicts carbon stocks that are double as high on north versus south-facing slopes. However, validation showed that these covariates only explained 25% of the variation in the dataset. Apparently, present-day landscape and vegetation properties are not sufficient to fully explain variability in the soil carbon stocks in this complex terrain under natural vegetation. This is attributed to a high spatial variability in bulk density and stoniness, key variables controlling carbon stocks. Similar results were obtained with the mechanistic soil formation model MILESD, suggesting that more complex models might be needed to further explore this high spatial variability.

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.

Hybrid network modeling and the effect of image resolution on digitally-obtained petrophysical and two-phase flow properties

NASA Astrophysics Data System (ADS)

Aghaei, A.

2017-12-01

Digital imaging and modeling of rocks and subsequent simulation of physical phenomena in digitally-constructed rock models are becoming an integral part of core analysis workflows. One of the inherent limitations of image-based analysis, at any given scale, is image resolution. This limitation becomes more evident when the rock has multiple scales of porosity such as in carbonates and tight sandstones. Multi-scale imaging and constructions of hybrid models that encompass images acquired at multiple scales and resolutions are proposed as a solution to this problem. In this study, we investigate the effect of image resolution and unresolved porosity on petrophysical and two-phase flow properties calculated based on images. A helical X-ray micro-CT scanner with a high cone-angle is used to acquire digital rock images that are free of geometric distortion. To remove subjectivity from the analyses, a semi-automated image processing technique is used to process and segment the acquired data into multiple phases. Direct and pore network based models are used to simulate physical phenomena and obtain absolute permeability, formation factor and two-phase flow properties such as relative permeability and capillary pressure. The effect of image resolution on each property is investigated. Finally a hybrid network model incorporating images at multiple resolutions is built and used for simulations. The results from the hybrid model are compared against results from the model built at the highest resolution and those from laboratory tests.

Quantitative modeling of soil genesis processes

NASA Technical Reports Server (NTRS)

Levine, E. R.; Knox, R. G.; Kerber, A. G.

1992-01-01

For fine spatial scale simulation, a model is being developed to predict changes in properties over short-, meso-, and long-term time scales within horizons of a given soil profile. Processes that control these changes can be grouped into five major process clusters: (1) abiotic chemical reactions; (2) activities of organisms; (3) energy balance and water phase transitions; (4) hydrologic flows; and (5) particle redistribution. Landscape modeling of soil development is possible using digitized soil maps associated with quantitative soil attribute data in a geographic information system (GIS) framework to which simulation models are applied.

The Cognitive Processes Associated with Occupational/Career Indecision: A Model for Gifted Adolescents

ERIC Educational Resources Information Center

Jung, Jae Yup

2013-01-01

This study developed and tested a new model of the cognitive processes associated with occupational/career indecision for gifted adolescents. A survey instrument with rigorous psychometric properties, developed from a number of existing instruments, was administered to a sample of 687 adolescents attending three academically selective high schools…

Suffix Ordering and Morphological Processing

ERIC Educational Resources Information Center

Plag, Ingo; Baayen, Harald

2009-01-01

There is a long-standing debate about the principles constraining the combinatorial properties of suffixes. Hay 2002 and Hay & Plag 2004 proposed a model in which suffixes can be ordered along a hierarchy of processing complexity. We show that this model generalizes to a larger set of suffixes, and we provide independent evidence supporting the…

The Influence of Welding Parameters on the Nugget Formation of Resistance Spot Welding of Inconel 625 Sheets

NASA Astrophysics Data System (ADS)

Rezaei Ashtiani, Hamid Reza; Zarandooz, Roozbeh

2015-09-01

A 2D axisymmetric electro-thermo-mechanical finite element (FE) model is developed to investigate the effect of current intensity, welding time, and electrode tip diameter on temperature distributions and nugget size in resistance spot welding (RSW) process of Inconel 625 superalloy sheets using ABAQUS commercial software package. The coupled electro-thermal analysis and uncoupled thermal-mechanical analysis are used for modeling process. In order to improve accuracy of simulation, material properties including physical, thermal, and mechanical properties have been considered to be temperature dependent. The thickness and diameter of computed weld nuggets are compared with experimental results and good agreement is observed. So, FE model developed in this paper provides prediction of quality and shape of the weld nuggets and temperature distributions with variation of each process parameter, suitably. Utilizing this FE model assists in adjusting RSW parameters, so that expensive experimental process can be avoided. The results show that increasing welding time and current intensity lead to an increase in the nugget size and electrode indentation, whereas increasing electrode tip diameter decreases nugget size and electrode indentation.

SPY: A new scission point model based on microscopic ingredients to predict fission fragments properties

NASA Astrophysics Data System (ADS)

Lemaître, J.-F.; Dubray, N.; Hilaire, S.; Panebianco, S.; Sida, J.-L.

2013-12-01

Our purpose is to determine fission fragments characteristics in a framework of a scission point model named SPY for Scission Point Yields. This approach can be considered as a theoretical laboratory to study fission mechanism since it gives access to the correlation between the fragments properties and their nuclear structure, such as shell correction, pairing, collective degrees of freedom, odd-even effects. Which ones are dominant in final state? What is the impact of compound nucleus structure? The SPY model consists in a statistical description of the fission process at the scission point where fragments are completely formed and well separated with fixed properties. The most important property of the model relies on the nuclear structure of the fragments which is derived from full quantum microscopic calculations. This approach allows computing the fission final state of extremely exotic nuclei which are inaccessible by most of the fission model available on the market.

Incorporating seismic observations into 2D conduit flow modeling

NASA Astrophysics Data System (ADS)

Collier, L.; Neuberg, J.

2006-04-01

Conduit flow modeling aims to understand the conditions of magma at depth, and to provide insight into the physical processes that occur inside the volcano. Low-frequency events, characteristic to many volcanoes, are thought to contain information on the state of magma at depth. Therefore, by incorporating information from low-frequency seismic analysis into conduit flow modeling a greater understanding of magma ascent and its interdependence on magma conditions and physical processes is possible. The 2D conduit flow model developed in this study demonstrates the importance of lateral pressure and parameter variations on overall magma flow dynamics, and the substantial effect bubbles have on magma shear viscosity and on magma ascent. The 2D nature of the conduit flow model developed here allows in depth investigation into processes which occur at, or close to the wall, such as magma cooling and brittle failure of melt. These processes are shown to have a significant effect on magma properties and therefore, on flow dynamics. By incorporating low-frequency seismic information, an advanced conduit flow model is developed including the consequences of brittle failure of melt, namely friction-controlled slip and gas loss. This model focuses on the properties and behaviour of magma at depth within the volcano, and their interaction with the formation of seismic events by brittle failure of melt.

Optical properties of mineral dust aerosol including analysis of particle size, composition, and shape effects, and the impact of physical and chemical processing

NASA Astrophysics Data System (ADS)

Alexander, Jennifer Mary

Atmospheric mineral dust has a large impact on the earth's radiation balance and climate. The radiative effects of mineral dust depend on factors including, particle size, shape, and composition which can all be extremely complex. Mineral dust particles are typically irregular in shape and can include sharp edges, voids, and fine scale surface roughness. Particle shape can also depend on the type of mineral and can vary as a function of particle size. In addition, atmospheric mineral dust is a complex mixture of different minerals as well as other, possibly organic, components that have been mixed in while these particles are suspended in the atmosphere. Aerosol optical properties are investigated in this work, including studies of the effect of particle size, shape, and composition on the infrared (IR) extinction and visible scattering properties in order to achieve more accurate modeling methods. Studies of particle shape effects on dust optical properties for single component mineral samples of silicate clay and diatomaceous earth are carried out here first. Experimental measurements are modeled using T-matrix theory in a uniform spheroid approximation. Previous efforts to simulate the measured optical properties of silicate clay, using models that assumed particle shape was independent of particle size, have achieved only limited success. However, a model which accounts for a correlation between particle size and shape for the silicate clays offers a large improvement over earlier modeling approaches. Diatomaceous earth is also studied as an example of a single component mineral dust aerosol with extreme particle shapes. A particle shape distribution, determined by fitting the experimental IR extinction data, used as a basis for modeling the visible light scattering properties. While the visible simulations show only modestly good agreement with the scattering data, the fits are generally better than those obtained using more commonly invoked particle shape distributions. The next goal of this work is to investigate if modeling methods developed in the studies of single mineral components can be generalized to predict the optical properties of more authentic aerosol samples which are complex mixtures of different minerals. Samples of Saharan sand, Iowa loess, and Arizona road dust are used here as test cases. T-matrix based simulations of the authentic samples, using measured particle size distributions, empirical mineralogies, and a priori particle shape models for each mineral component are directly compared with the measured IR extinction spectra and visible scattering profiles. This modeling approach offers a significant improvement over more commonly applied models that ignore variations in particle shape with size or mineralogy and include only a moderate range of shape parameters. Mineral dust samples processed with organic acids and humic material are also studied in order to explore how the optical properties of dust can change after being aged in the atmosphere. Processed samples include quartz mixed with humic material, and calcite reacted with acetic and oxalic acid. Clear differences in the light scattering properties are observed for all three processed mineral dust samples when compared to the unprocessed mineral dust or organic salt products. These interactions result in both internal and external mixtures depending on the sample. In addition, the presence of these organic materials can alter the mineral dust particle shape. Overall, however, these results demonstrate the need to account for the effects of atmospheric aging of mineral dust on aerosol optical properties. Particle shape can also affect the aerodynamic properties of mineral dust aerosol. In order to account for these effects, the dynamic shape factor is used to give a measure of particle asphericity. Dynamic shape factors of quartz are measured by mass and mobility selecting particles and measuring their vacuum aerodynamic diameter. From this, dynamic shape factors in both the transition and vacuum regime can be derived. The measured dynamic shape factors of quartz agree quite well with the spheroidal shape distributions derived through studies of the optical properties.

Does the PFC model of analogy account for decision making, problem solving, reasoning, flexibility, adaptability, and even creativity?

PubMed

Barutta, Joaquin; Guex, Raphael; Ibáñez, Agustín

2010-06-01

Abstract From everyday cognition to scientific discovery, analogical processes play an important role: bringing connection, integration, and interrelation of information. Recently, a PFC model of analogy has been proposed to explain many cognitive processes and integrate general functional properties of PFC. We argue here that analogical processes do not suffice to explain the cognitive processes and functions of PFC. Moreover the model does not satisfactorily integrate specific explanatory mechanisms required for the different processes involved. Its relevance would be improved if fewer cognitive phenomena were considered and more specific predictions and explanations about those processes were stated.

Simulation of blood flow in deformable vessels using subject-specific geometry and spatially varying wall properties

PubMed Central

Xiong, Guanglei; Figueroa, C. Alberto; Xiao, Nan; Taylor, Charles A.

2011-01-01

SUMMARY Simulation of blood flow using image-based models and computational fluid dynamics has found widespread application to quantifying hemodynamic factors relevant to the initiation and progression of cardiovascular diseases and for planning interventions. Methods for creating subject-specific geometric models from medical imaging data have improved substantially in the last decade but for many problems, still require significant user interaction. In addition, while fluid–structure interaction methods are being employed to model blood flow and vessel wall dynamics, tissue properties are often assumed to be uniform. In this paper, we propose a novel workflow for simulating blood flow using subject-specific geometry and spatially varying wall properties. The geometric model construction is based on 3D segmentation and geometric processing. Variable wall properties are assigned to the model based on combining centerline-based and surface-based methods. We finally demonstrate these new methods using an idealized cylindrical model and two subject-specific vascular models with thoracic and cerebral aneurysms. PMID:21765984

Orientation distribution and process modeling of thermotropic liquid crystalline copolyester (TLCP) injection-moldings

NASA Astrophysics Data System (ADS)

Bubeck, Robert; Fang, Jun; Burghardt, Wesley; Burgard, Susan; Fischer, Daniel

2009-03-01

The influence of melt processing conditions upon mechanical properties and degrees of compound molecular orientation have been thoroughly studied for a series of well-defined injection molded samples fabricated from VECTRA (TM) A950 and 4,4'-dihydroxy-a-methylstilbene TLCPs. Fracture and tensile data were correlated with processing conditions, orientation, and molecular weight. Mechanical properties for both TLCPs were found to follow a ``universal'' Anisotropy Factor (AF) associated with the bimodal orientation states in the plaques determined from 2-D WAXS. Surface orientations were globally surveyed using Attenuated Total Reflectance -- Fourier Transform Infrared (ATR-FTIR) spectroscopy and C K edge Near-Edge X-ray Absorption Fine Structure (NEXAFS). The results derived from the two spectroscopy techniques confirmed each other well. These results along with those from 2-D WAXS in transmission were compared with the results of process modeling using a commercial program, MOLDFLOW(TM). The agreement between model predictions and the measured orientation states was gratifyingly good.

A novel approach to support formulation design on twin screw wet granulation technology: Understanding the impact of overarching excipient properties on drug product quality attributes.

PubMed

Willecke, N; Szepes, A; Wunderlich, M; Remon, J P; Vervaet, C; De Beer, T

2018-04-21

The overall objective of this work is to understand how excipient characteristics influence the drug product quality attributes and process performance of a continuous twin screw wet granulation process. The knowledge gained in this study is intended to be used for Quality by Design (QbD)-based formulation design and formulation optimization. Three principal components which represent the overarching properties of 8 selected pharmaceutical fillers were used as factors, whereas factors 4 and 5 represented binder type and binder concentration in a design of experiments (DoE). The majority of process parameters were kept constant to minimize their influence on the granule and drug product quality. 27 DoE batches consisting of binary filler/binder mixtures were processed via continuous twin screw wet granulation followed by tablet compression. Multiple linear regression models were built providing understanding of the impact of filler and binder properties on granule and tablet quality attributes (i.e. 16 DoE responses). The impact of fillers on the granule and tablet responses was more dominant compared to the impact of binder type and concentration. The filler properties had a relevant effect on granule characteristics, such as particle size, friability and specific surface area. Binder type and concentration revealed a relevant influence on granule flowability and friability as well as on the compactability (required compression force during tableting to obtain target hardness). In order to evaluate the DoE models' validity, a verification of the DoE models was performed with new formulations (i.e. a new combination of filler, binder type and binder concentration) which were initially not included in the dataset used to build the DoE models. The combined PCA (principle component analysis)/DoE approach allowed to link the excipient properties with the drug product quality attributes. Copyright © 2018 Elsevier B.V. All rights reserved.

A Study on the Influence of Process Parameters on the Viscoelastic Properties of ABS Components Manufactured by FDM Process

NASA Astrophysics Data System (ADS)

Dakshinamurthy, Devika; Gupta, Srinivasa

2018-04-01

Fused Deposition Modelling (FDM) is a fast growing Rapid Prototyping (RP) technology due to its ability to build parts having complex geometrical shape in reasonable time period. The quality of built parts depends on many process variables. In this study, the influence of three FDM process parameters namely, slice height, raster angle and raster width on viscoelastic properties of Acrylonitrile Butadiene Styrene (ABS) RP-specimen is studied. Statistically designed experiments have been conducted for finding the optimum process parameter setting for enhancing the storage modulus. Dynamic Mechanical Analysis has been used to understand the viscoelastic properties at various parameter settings. At the optimal parameter setting the storage modulus and loss modulus of the ABS-RP specimen was 1008 and 259.9 MPa respectively. The relative percentage contribution of slice height and raster width on the viscoelastic properties of the FDM-RP components was found to be 55 and 31 % respectively.

Observations of Co-variation in Cloud Properties and their Relationships with Atmospheric State

NASA Astrophysics Data System (ADS)

Sinclair, K.; van Diedenhoven, B.; Fridlind, A. M.; Arnold, T. G.; Yorks, J. E.; Heymsfield, G. M.; McFarquhar, G. M.; Um, J.

2017-12-01

Radiative properties of upper tropospheric ice clouds are generally not well represented in global and cloud models. Cloud top height, cloud thermodynamic phase, cloud optical thickness, cloud water path, particle size and ice crystal shape all serve as observational targets for models to constrain cloud properties. Trends or biases in these cloud properties could have profound effects on the climate since they affect cloud radiative properties. Better understanding of co-variation between these cloud properties and linkages with atmospheric state variables can lead to better representation of clouds in models by reducing biases in their micro- and macro-physical properties as well as their radiative properties. This will also enhance our general understanding of cloud processes. In this analysis we look at remote sensing, in situ and reanalysis data from the MODIS Airborne Simulator (MAS), Cloud Physics Lidar (CPL), Cloud Radar System (CRS), GEOS-5 reanalysis data and GOES imagery obtained during the Tropical Composition, Cloud and Climate Coupling (TC4) airborne campaign. The MAS, CPL and CRS were mounted on the ER-2 high-altitude aircraft during this campaign. In situ observations of ice size and shape were made aboard the DC8 and WB57 aircrafts. We explore how thermodynamic phase, ice effective radius, particle shape and radar reflectivity vary with altitude and also investigate how these observed cloud properties vary with cloud type, cloud top temperature, relative humidity and wind profiles. Observed systematic relationships are supported by physical interpretations of cloud processes and any unexpected differences are examined.

Experimental Validation of Strategy for the Inverse Estimation of Mechanical Properties and Coefficient of Friction in Flat Rolling

NASA Astrophysics Data System (ADS)

Yadav, Vinod; Singh, Arbind Kumar; Dixit, Uday Shanker

2017-08-01

Flat rolling is one of the most widely used metal forming processes. For proper control and optimization of the process, modelling of the process is essential. Modelling of the process requires input data about material properties and friction. In batch production mode of rolling with newer materials, it may be difficult to determine the input parameters offline. In view of it, in the present work, a methodology to determine these parameters online by the measurement of exit temperature and slip is verified experimentally. It is observed that the inverse prediction of input parameters could be done with a reasonable accuracy. It was also assessed experimentally that there is a correlation between micro-hardness and flow stress of the material; however the correlation between surface roughness and reduction is not that obvious.

Sojourning with the Homogeneous Poisson Process.

PubMed

Liu, Piaomu; Peña, Edsel A

2016-01-01

In this pedagogical article, distributional properties, some surprising, pertaining to the homogeneous Poisson process (HPP), when observed over a possibly random window, are presented. Properties of the gap-time that covered the termination time and the correlations among gap-times of the observed events are obtained. Inference procedures, such as estimation and model validation, based on event occurrence data over the observation window, are also presented. We envision that through the results in this paper, a better appreciation of the subtleties involved in the modeling and analysis of recurrent events data will ensue, since the HPP is arguably one of the simplest among recurrent event models. In addition, the use of the theorem of total probability, Bayes theorem, the iterated rules of expectation, variance and covariance, and the renewal equation could be illustrative when teaching distribution theory, mathematical statistics, and stochastic processes at both the undergraduate and graduate levels. This article is targeted towards both instructors and students.

Prediction of normalized biodiesel properties by simulation of multiple feedstock blends.

PubMed

García, Manuel; Gonzalo, Alberto; Sánchez, José Luis; Arauzo, Jesús; Peña, José Angel

2010-06-01

A continuous process for biodiesel production has been simulated using Aspen HYSYS V7.0 software. As fresh feed, feedstocks with a mild acid content have been used. The process flowsheet follows a traditional alkaline transesterification scheme constituted by esterification, transesterification and purification stages. Kinetic models taking into account the concentration of the different species have been employed in order to simulate the behavior of the CSTR reactors and the product distribution within the process. The comparison between experimental data found in literature and the predicted normalized properties, has been discussed. Additionally, a comparison between different thermodynamic packages has been performed. NRTL activity model has been selected as the most reliable of them. The combination of these models allows the prediction of 13 out of 25 parameters included in standard EN-14214:2003, and confers simulators a great value as predictive as well as optimization tool. (c) 2010 Elsevier Ltd. All rights reserved.

Computational Process Modeling for Additive Manufacturing

NASA Technical Reports Server (NTRS)

Bagg, Stacey; Zhang, Wei

2014-01-01

Computational Process and Material Modeling of Powder Bed additive manufacturing of IN 718. Optimize material build parameters with reduced time and cost through modeling. Increase understanding of build properties. Increase reliability of builds. Decrease time to adoption of process for critical hardware. Potential to decrease post-build heat treatments. Conduct single-track and coupon builds at various build parameters. Record build parameter information and QM Meltpool data. Refine Applied Optimization powder bed AM process model using data. Report thermal modeling results. Conduct metallography of build samples. Calibrate STK models using metallography findings. Run STK models using AO thermal profiles and report STK modeling results. Validate modeling with additional build. Photodiode Intensity measurements highly linear with power input. Melt Pool Intensity highly correlated to Melt Pool Size. Melt Pool size and intensity increase with power. Applied Optimization will use data to develop powder bed additive manufacturing process model.

A 3-Component Mixture of Rayleigh Distributions: Properties and Estimation in Bayesian Framework

PubMed Central

Aslam, Muhammad; Tahir, Muhammad; Hussain, Zawar; Al-Zahrani, Bander

2015-01-01

To study lifetimes of certain engineering processes, a lifetime model which can accommodate the nature of such processes is desired. The mixture models of underlying lifetime distributions are intuitively more appropriate and appealing to model the heterogeneous nature of process as compared to simple models. This paper is about studying a 3-component mixture of the Rayleigh distributionsin Bayesian perspective. The censored sampling environment is considered due to its popularity in reliability theory and survival analysis. The expressions for the Bayes estimators and their posterior risks are derived under different scenarios. In case the case that no or little prior information is available, elicitation of hyperparameters is given. To examine, numerically, the performance of the Bayes estimators using non-informative and informative priors under different loss functions, we have simulated their statistical properties for different sample sizes and test termination times. In addition, to highlight the practical significance, an illustrative example based on a real-life engineering data is also given. PMID:25993475

Braze alloy process and strength characterization studies for 18 nickel grade 200 maraging steel with application to wind tunnel models

NASA Technical Reports Server (NTRS)

Bradshaw, James F.; Sandefur, Paul G., Jr.; Young, Clarence P., Jr.

1991-01-01

A comprehensive study of braze alloy selection process and strength characterization with application to wind tunnel models is presented. The applications for this study include the installation of stainless steel pressure tubing in model airfoil sections make of 18 Ni 200 grade maraging steel and the joining of wing structural components by brazing. Acceptable braze alloys for these applications are identified along with process, thermal braze cycle data, and thermal management procedures. Shear specimens are used to evaluate comparative shear strength properties for the various alloys at both room and cryogenic (-300 F) temperatures and include the effects of electroless nickel plating. Nickel plating was found to significantly enhance both the wetability and strength properties for the various braze alloys studied. The data are provided for use in selecting braze alloys for use with 18 Ni grade 200 steel in the design of wind tunnel models to be tested in an ambient or cryogenic environment.

Investigating Effects of Fused-Deposition Modeling (FDM) Processing Parameters on Flexural Properties of ULTEM 9085 using Designed Experiment.

PubMed

Gebisa, Aboma Wagari; Lemu, Hirpa G

2018-03-27

Fused-deposition modeling (FDM), one of the additive manufacturing (AM) technologies, is an advanced digital manufacturing technique that produces parts by heating, extruding and depositing filaments of thermoplastic polymers. The properties of FDM-produced parts apparently depend on the processing parameters. These processing parameters have conflicting advantages that need to be investigated. This article focuses on an investigation into the effect of these parameters on the flexural properties of FDM-produced parts. The investigation is carried out on high-performance ULTEM 9085 material, as this material is relatively new and has potential application in the aerospace, military and automotive industries. Five parameters: air gap, raster width, raster angle, contour number, and contour width, with a full factorial design of the experiment, are considered for the investigation. From the investigation, it is revealed that raster angle and raster width have the greatest effect on the flexural properties of the material. The optimal levels of the process parameters achieved are: air gap of 0.000 mm, raster width of 0.7814 mm, raster angle of 0°, contour number of 5, and contour width of 0.7814 mm, leading to a flexural strength of 127 MPa, a flexural modulus of 2400 MPa, and 0.081 flexural strain.

Investigating Effects of Fused-Deposition Modeling (FDM) Processing Parameters on Flexural Properties of ULTEM 9085 using Designed Experiment

PubMed Central

Gebisa, Aboma Wagari

2018-01-01

Fused-deposition modeling (FDM), one of the additive manufacturing (AM) technologies, is an advanced digital manufacturing technique that produces parts by heating, extruding and depositing filaments of thermoplastic polymers. The properties of FDM-produced parts apparently depend on the processing parameters. These processing parameters have conflicting advantages that need to be investigated. This article focuses on an investigation into the effect of these parameters on the flexural properties of FDM-produced parts. The investigation is carried out on high-performance ULTEM 9085 material, as this material is relatively new and has potential application in the aerospace, military and automotive industries. Five parameters: air gap, raster width, raster angle, contour number, and contour width, with a full factorial design of the experiment, are considered for the investigation. From the investigation, it is revealed that raster angle and raster width have the greatest effect on the flexural properties of the material. The optimal levels of the process parameters achieved are: air gap of 0.000 mm, raster width of 0.7814 mm, raster angle of 0°, contour number of 5, and contour width of 0.7814 mm, leading to a flexural strength of 127 MPa, a flexural modulus of 2400 MPa, and 0.081 flexural strain. PMID:29584674

Application of a Model for Simulating the Vacuum Arc Remelting Process in Titanium Alloys

NASA Astrophysics Data System (ADS)

Patel, Ashish; Tripp, David W.; Fiore, Daniel

Mathematical modeling is routinely used in the process development and production of advanced aerospace alloys to gain greater insight into system dynamics and to predict the effect of process modifications or upsets on final properties. This article describes the application of a 2-D mathematical VAR model presented in previous LMPC meetings. The impact of process parameters on melt pool geometry, solidification behavior, fluid-flow and chemistry in Ti-6Al-4V ingots will be discussed. Model predictions were first validated against the measured characteristics of industrially produced ingots, and process inputs and model formulation were adjusted to match macro-etched pool shapes. The results are compared to published data in the literature. Finally, the model is used to examine ingot chemistry during successive VAR melts.

Effects of build parameters on linear wear loss in plastic part produced by fused deposition modeling

NASA Astrophysics Data System (ADS)

Mohamed, Omar Ahmed; Masood, Syed Hasan; Bhowmik, Jahar Lal

2017-07-01

Fused Deposition Modeling (FDM) is one of the prominent additive manufacturing technologies for producing polymer products. FDM is a complex additive manufacturing process that can be influenced by many process conditions. The industrial demands required from the FDM process are increasing with higher level product functionality and properties. The functionality and performance of FDM manufactured parts are greatly influenced by the combination of many various FDM process parameters. Designers and researchers always pay attention to study the effects of FDM process parameters on different product functionalities and properties such as mechanical strength, surface quality, dimensional accuracy, build time and material consumption. However, very limited studies have been carried out to investigate and optimize the effect of FDM build parameters on wear performance. This study focuses on the effect of different build parameters on micro-structural and wear performance of FDM specimens using definitive screening design based quadratic model. This would reduce the cost and effort of additive manufacturing engineer to have a systematic approachto make decision among the manufacturing parameters to achieve the desired product quality.

Defense waste processing facility (DWPF) liquids model: revisions for processing higher TIO 2 containing glasses

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

Jantzen, C. M.; Edwards, T. B.; Trivelpiece, C. L.

Radioactive high level waste (HLW) at the Savannah River Site (SRS) has successfully been vitrified into borosilicate glass in the Defense Waste Processing Facility (DWPF) since 1996. Vitrification requires stringent product/process (P/P) constraints since the glass cannot be reworked once it is poured into ten foot tall by two foot diameter canisters. A unique “feed forward” statistical process control (SPC) was developed for this control rather than statistical quality control (SQC). In SPC, the feed composition to the DWPF melter is controlled prior to vitrification. In SQC, the glass product would be sampled after it is vitrified. Individual glass property-compositionmore » models form the basis for the “feed forward” SPC. The models transform constraints on the melt and glass properties into constraints on the feed composition going to the melter in order to guarantee, at the 95% confidence level, that the feed will be processable and that the durability of the resulting waste form will be acceptable to a geologic repository. This report documents the development of revised TiO 2, Na 2O, Li 2O and Fe 2O 3 coefficients in the SWPF liquidus model and revised coefficients (a, b, c, and d).« less

The effects of polymers' visco-elastoplastic properties on the micro cavities filling step of hot embossing process

NASA Astrophysics Data System (ADS)

Cheng, Gang; Barrière, Thierry

2018-05-01

The hot embossing process has been widely used in the manufacturing of polymer components, especially for the fabrication of micro or nano components. The significant advantage of the hot embossing process compared to the traditional injection moulding process is the excellent effective filling ratio for the high aspect ratio components and large surface structural components. The lack of material behavior modeling and numerical simulation limits the further development the hot embossing process, especially at the micro and nano scales. In this paper, a visco-elastoplastic behavior law has been proposed to describe the amorphous thermoplastic polymer mechanical properties in the hot embossing processing temperature range, which is lightly above their glass transition temperature. Uniaxial compression tests have been carried out in order to investigate the amorphous thermoplastic polymers properties. The material parameters in the visco-elastoplastic model have been identified according to the experimental results. A 3D numerical model has been created in the simulation software, which is based on the finite element method. The numerical simulation of the filling step of the hot embossing process has been effectuated by taking into account the viscous, elastic and plastic behaviors of thermoplastic polymers. The micro hot embossing process has been carried out using horizontal injection compression moulding equipment. A complete compression mould tool, equipped with the heating system, the cooling system, the ejection system and the vacuum system, has been designed and elaborated for this research work. The microfluidic devices based on the amorphous thermoplastic polymers have been successfully elaborated by hot embossing process. Proper agreement between the numerical simulation and the experimental elaboration has been obtained.

Blueprint for a coupled model of sedimentology, hydrology, and hydrogeology in streambeds

NASA Astrophysics Data System (ADS)

Partington, Daniel; Therrien, Rene; Simmons, Craig T.; Brunner, Philip

2017-06-01

The streambed constitutes the physical interface between the surface and the subsurface of a stream. Across all spatial scales, the physical properties of the streambed control surface water-groundwater interactions. Continuous alteration of streambed properties such as topography or hydraulic conductivity occurs through erosion and sedimentation processes. Recent studies from the fields of ecology, hydrogeology, and sedimentology provide field evidence that sedimentological processes themselves can be heavily influenced by surface water-groundwater interactions, giving rise to complex feedback mechanisms between sedimentology, hydrology, and hydrogeology. More explicitly, surface water-groundwater exchanges play a significant role in the deposition of fine sediments, which in turn modify the hydraulic properties of the streambed. We explore these feedback mechanisms and critically review the extent of current interaction between the different disciplines. We identify opportunities to improve current modeling practices. For example, hydrogeological models treat the streambed as a static rather than a dynamic entity, while sedimentological models do not account for critical catchment processes such as surface water-groundwater exchange. We propose a blueprint for a new modeling framework that bridges the conceptual gaps between sedimentology, hydrogeology, and hydrology. Specifically, this blueprint (1) fully integrates surface-subsurface flows with erosion, transport, and deposition of sediments and (2) accounts for the dynamic changes in surface elevation and hydraulic conductivity of the streambed. Finally, we discuss the opportunities for new research within the coupled framework.

Sensitivity studies of pediatric material properties on juvenile lumbar spine responses using finite element analysis.

PubMed

Jebaseelan, D Davidson; Jebaraj, C; Yoganandan, Narayan; Rajasekaran, S; Kanna, Rishi M

2012-05-01

The objective of the study was to determine the sensitivity of material properties of the juvenile spine to its external and internal responses using a finite element model under compression, and flexion-extension bending moments. The methodology included exercising the 8-year-old juvenile lumbar spine using parametric procedures. The model included the vertebral centrum, growth plates, laminae, pedicles, transverse processes and spinous processes; disc annulus and nucleus; and various ligaments. The sensitivity analysis was conducted by varying the modulus of elasticity for various components. The first simulation was done using mean material properties. Additional simulations were done for each component corresponding to low and high material property variations. External displacement/rotation and internal stress-strain responses were determined under compression and flexion-extension bending. Results indicated that, under compression, disc properties were more sensitive than bone properties, implying an elevated role of the disc under this mode. Under flexion-extension moments, ligament properties were more dominant than the other components, suggesting that various ligaments of the juvenile spine play a key role in modulating bending behaviors. Changes in the growth plate stress associated with ligament properties explained the importance of the growth plate in the pediatric spine with potential implications in progressive deformities.

Statistical Analysis of CMC Constituent and Processing Data

NASA Technical Reports Server (NTRS)

Fornuff, Jonathan

2004-01-01

Ceramic Matrix Composites (CMCs) are the next "big thing" in high-temperature structural materials. In the case of jet engines, it is widely believed that the metallic superalloys currently being utilized for hot structures (combustors, shrouds, turbine vanes and blades) are nearing their potential limits of improvement. In order to allow for increased turbine temperatures to increase engine efficiency, material scientists have begun looking toward advanced CMCs and SiC/SiC composites in particular. Ceramic composites provide greater strength-to-weight ratios at higher temperatures than metallic alloys, but at the same time require greater challenges in micro-structural optimization that in turn increases the cost of the material as well as increases the risk of variability in the material s thermo-structural behavior. to model various potential CMC engine materials and examines the current variability in these properties due to variability in component processing conditions and constituent materials; then, to see how processing and constituent variations effect key strength, stiffness, and thermal properties of the finished components. Basically, this means trying to model variations in the component s behavior by knowing what went into creating it. inter-phase and manufactured by chemical vapor infiltration (CVI) and melt infiltration (MI) were considered. Examinations of: (1) the percent constituents by volume, (2) the inter-phase thickness, (3) variations in the total porosity, and (4) variations in the chemical composition of the Sic fiber are carried out and modeled using various codes used here at NASA-Glenn (PCGina, NASALife, CEMCAN, etc...). The effects of these variations and the ranking of their respective influences on the various thermo-mechanical material properties are studied and compared to available test data. The properties of the materials as well as minor changes to geometry are then made to the computer model and the detrimental effects observed using statistical analysis software. The ultimate purpose of this study is to determine what variations in material processing can lead to the most critical changes in the materials property. The work I have taken part in this summer explores, in general, the key properties needed In this study SiC/SiC composites of varying architectures, utilizing a boron-nitride (BN)

Acoustic response of cemented granular sedimentary rocks: molecular dynamics modeling.

PubMed

García, Xavier; Medina, Ernesto

2007-06-01

The effect of cementation processes on the acoustical properties of sands is studied via molecular dynamics simulation methods. We propose numerical methods where the initial uncemented sand is built by simulating the settling process of sediments. Uncemented samples of different porosity are considered by emulating natural mechanical compaction of sediments due to overburden. Cementation is considered through a particle-based model that captures the underlying physics behind the process. In our simulations, we consider samples with different degrees of compaction and cementing materials with distinct elastic properties. The microstructure of cemented sands is taken into account while adding cement at specific locations within the pores, such as grain-to-grain contacts. Results show that the acoustical properties of cemented sands are strongly dependent on the amount of cement, its stiffness relative to the hosting medium, and its location within the pores. Simulation results are in good correspondence with available experimental data and compare favorably with some theoretical predictions for the sound velocity within a range of cement saturation, porosity, and confining pressure.

Viscoelastic processing and characterization of high-performance polymeric composite systems

NASA Astrophysics Data System (ADS)

Buehler, Frederic Ulysse

2000-10-01

Fiber reinforced composites, a combination of reinforcing fiber and resin matrix, offer many advantages over traditional materials, and have therefore found wide application in the aerospace and sporting goods industry. Among the advantages that composite materials offer, the most often cited are weight saving, high modulus, high strength-to-weight ratio, corrosion resistance, and fatigue resistance. As much as their attributes are desirable, composites are difficult to process due to their heterogeneous, anisotropic, and viscoelastic nature. It is therefore not surprising that the interrelationship between structure, property, and process is not fully understood. Consequently, the major purpose of this research work was to investigate this interrelationship, and ways to scale it to utilization. First, four prepreg materials, which performed differently in the manufacturing of composite parts, but were supposedly identical, were characterized. The property variations that were found among these prepregs in terms of tack and frictional resistance assessed the need for improved understanding of the prepregging process. Therefore, the influence of the processing parameters on final prepreg quality were investigated, and led to the definition of more adequate process descriptors. Additionally, one of the characterization techniques used in this work, temperature modulated differential scanning calorimetry, was examined in depth with the development of a mathematical model. This model, which enabled the exploration of the relationship between user parameters, sample thermophysical properties, and final results, was then compared to literature data. Collectively, this work explored and identified the key connectors between process, structure, and property as they relate to the manufacturing, design, and performance of composite materials.

Further developments of the Neyman-Scott clustered point process for modeling rainfall

NASA Astrophysics Data System (ADS)

Cowpertwait, Paul S. P.

1991-07-01

This paper provides some useful results for modeling rainfall. It extends work on the Neyman-Scott cluster model for simulating rainfall time series. Several important properties have previously been found for the model, for example, the expectation and variance of the amount of rain captured in an arbitrary time interval (Rodriguez-Iturbe et al., 1987a), In this paper additional properties are derived, such as the probability of an arbitrary interval of any chosen length being dry. In applications this is a desirable property to have, and is often used for fitting stochastic rainfall models to field data. The model is currently being used in rainfall time series research directed toward improving sewage systems in the United Kingdom. To illustrate the model's performance an example is given, where the model is fitted to 10 years of hourly data taken from Blackpool, England.

An Application Domain Extension to CityGML for immovable property taxation: A Turkish case study

NASA Astrophysics Data System (ADS)

Çağdaş, Volkan

2013-04-01

It is generally acknowledged that immovable property taxes are one of the main revenue sources for local government. The literature emphasizes that the administration of property taxes needs well-developed inventories or registers that provide complete and accurate records of the taxed properties and their legal-economic attributes. This requirement is generally fulfilled by Spatial Data Infrastructures (SDIs) in which the coordinate exchange and sharing of geo-spatial data is provided by separate registers/information systems such as: cadastral systems, building and address registers. Recently, the Open Geospatial Consortium presented a core component of a 3D SDI in the form of an international domain standard for representing, storing and exchanging 3D city models. The CityGML allows the semantic and 3D geometrical representation of physical objects but does not deal with the legal and administrative aspects of the city objects which are required for the process of property taxation. This paper outlines the development of an Application Domain Extension (ADE) for the immovable property taxation domain that expands the CityGML data model with the legal and administrative concepts defined in Turkish Law. The study shows that this ADE could be a 3D national data model for municipal information systems and facilitate a more efficient taxation process, as well as providing data for urban planning, facility management and other municipal services.

Equivalent Sensor Radiance Generation and Remote Sensing from Model Parameters. Part 1; Equivalent Sensor Radiance Formulation

NASA Technical Reports Server (NTRS)

Wind, Galina; DaSilva, Arlindo M.; Norris, Peter M.; Platnick, Steven E.

2013-01-01

In this paper we describe a general procedure for calculating equivalent sensor radiances from variables output from a global atmospheric forecast model. In order to take proper account of the discrepancies between model resolution and sensor footprint the algorithm takes explicit account of the model subgrid variability, in particular its description of the probably density function of total water (vapor and cloud condensate.) The equivalent sensor radiances are then substituted into an operational remote sensing algorithm processing chain to produce a variety of remote sensing products that would normally be produced from actual sensor output. This output can then be used for a wide variety of purposes such as model parameter verification, remote sensing algorithm validation, testing of new retrieval methods and future sensor studies. We show a specific implementation using the GEOS-5 model, the MODIS instrument and the MODIS Adaptive Processing System (MODAPS) Data Collection 5.1 operational remote sensing cloud algorithm processing chain (including the cloud mask, cloud top properties and cloud optical and microphysical properties products.) We focus on clouds and cloud/aerosol interactions, because they are very important to model development and improvement.

Multi-sensor Cloud Retrieval Simulator and Remote Sensing from Model Parameters . Pt. 1; Synthetic Sensor Radiance Formulation; [Synthetic Sensor Radiance Formulation

NASA Technical Reports Server (NTRS)

Wind, G.; DaSilva, A. M.; Norris, P. M.; Platnick, S.

2013-01-01

In this paper we describe a general procedure for calculating synthetic sensor radiances from variable output from a global atmospheric forecast model. In order to take proper account of the discrepancies between model resolution and sensor footprint, the algorithm takes explicit account of the model subgrid variability, in particular its description of the probability density function of total water (vapor and cloud condensate.) The simulated sensor radiances are then substituted into an operational remote sensing algorithm processing chain to produce a variety of remote sensing products that would normally be produced from actual sensor output. This output can then be used for a wide variety of purposes such as model parameter verification, remote sensing algorithm validation, testing of new retrieval methods and future sensor studies.We show a specific implementation using the GEOS-5 model, the MODIS instrument and the MODIS Adaptive Processing System (MODAPS) Data Collection 5.1 operational remote sensing cloud algorithm processing chain (including the cloud mask, cloud top properties and cloud optical and microphysical properties products). We focus on clouds because they are very important to model development and improvement.

An analytical model of SAGD process considering the effect of threshold pressure gradient

NASA Astrophysics Data System (ADS)

Morozov, P.; Abdullin, A.; Khairullin, M.

2018-05-01

An analytical model is proposed for the development of super-viscous oil deposits by the method of steam-assisted gravity drainage, taking into account the nonlinear filtration law with the limiting gradient. The influence of non-Newtonian properties of oil on the productivity of a horizontal well and the cumulative steam-oil ratio are studied. Verification of the proposed model based on the results of physical modeling of the SAGD process was carried out.

Fundamental properties of cooperative contagion processes

NASA Astrophysics Data System (ADS)

Chen, Li; Ghanbarnejad, Fakhteh; Brockmann, Dirk

2017-10-01

We investigate the effects of cooperativity between contagion processes that spread and persist in a host population. We propose and analyze a dynamical model in which individuals that are affected by one transmissible agent A exhibit a higher than baseline propensity of being affected by a second agent B and vice versa. The model is a natural extension of the traditional susceptible-infected-susceptible model used for modeling single contagion processes. We show that cooperativity changes the dynamics of the system considerably when cooperativity is strong. The system exhibits discontinuous phase transitions not observed in single agent contagion, multi-stability, a separation of the traditional epidemic threshold into different thresholds for inception and extinction as well as hysteresis. These properties are robust and are corroborated by stochastic simulations on lattices and generic network topologies. Finally, we investigate wave propagation and transients in a spatially extended version of the model and show that especially for intermediate values of baseline reproduction ratios the system is characterized by various types of wave-front speeds. The system can exhibit spatially heterogeneous stationary states for some parameters and negative front speeds (receding wave fronts). The two agent model can be employed as a starting point for more complex contagion processes, involving several interacting agents, a model framework particularly suitable for modeling the spread and dynamics of microbiological ecosystems in host populations.

Nice Guys Finish Fast and Bad Guys Finish Last: Facilitatory vs. Inhibitory Interaction in Parallel Systems

PubMed Central

Eidels, Ami; Houpt, Joseph W.; Altieri, Nicholas; Pei, Lei; Townsend, James T.

2011-01-01

Systems Factorial Technology is a powerful framework for investigating the fundamental properties of human information processing such as architecture (i.e., serial or parallel processing) and capacity (how processing efficiency is affected by increased workload). The Survivor Interaction Contrast (SIC) and the Capacity Coefficient are effective measures in determining these underlying properties, based on response-time data. Each of the different architectures, under the assumption of independent processing, predicts a specific form of the SIC along with some range of capacity. In this study, we explored SIC predictions of discrete-state (Markov process) and continuous-state (Linear Dynamic) models that allow for certain types of cross-channel interaction. The interaction can be facilitatory or inhibitory: one channel can either facilitate, or slow down processing in its counterpart. Despite the relative generality of these models, the combination of the architecture-oriented plus the capacity oriented analyses provide for precise identification of the underlying system. PMID:21516183

Nice Guys Finish Fast and Bad Guys Finish Last: Facilitatory vs. Inhibitory Interaction in Parallel Systems.

PubMed

Eidels, Ami; Houpt, Joseph W; Altieri, Nicholas; Pei, Lei; Townsend, James T

2011-04-01

Systems Factorial Technology is a powerful framework for investigating the fundamental properties of human information processing such as architecture (i.e., serial or parallel processing) and capacity (how processing efficiency is affected by increased workload). The Survivor Interaction Contrast (SIC) and the Capacity Coefficient are effective measures in determining these underlying properties, based on response-time data. Each of the different architectures, under the assumption of independent processing, predicts a specific form of the SIC along with some range of capacity. In this study, we explored SIC predictions of discrete-state (Markov process) and continuous-state (Linear Dynamic) models that allow for certain types of cross-channel interaction. The interaction can be facilitatory or inhibitory: one channel can either facilitate, or slow down processing in its counterpart. Despite the relative generality of these models, the combination of the architecture-oriented plus the capacity oriented analyses provide for precise identification of the underlying system.

Chemically Aware Model Builder (camb): an R package for property and bioactivity modelling of small molecules.

PubMed

Murrell, Daniel S; Cortes-Ciriano, Isidro; van Westen, Gerard J P; Stott, Ian P; Bender, Andreas; Malliavin, Thérèse E; Glen, Robert C

2015-01-01

In silico predictive models have proved to be valuable for the optimisation of compound potency, selectivity and safety profiles in the drug discovery process. camb is an R package that provides an environment for the rapid generation of quantitative Structure-Property and Structure-Activity models for small molecules (including QSAR, QSPR, QSAM, PCM) and is aimed at both advanced and beginner R users. camb's capabilities include the standardisation of chemical structure representation, computation of 905 one-dimensional and 14 fingerprint type descriptors for small molecules, 8 types of amino acid descriptors, 13 whole protein sequence descriptors, filtering methods for feature selection, generation of predictive models (using an interface to the R package caret), as well as techniques to create model ensembles using techniques from the R package caretEnsemble). Results can be visualised through high-quality, customisable plots (R package ggplot2). Overall, camb constitutes an open-source framework to perform the following steps: (1) compound standardisation, (2) molecular and protein descriptor calculation, (3) descriptor pre-processing and model training, visualisation and validation, and (4) bioactivity/property prediction for new molecules. camb aims to speed model generation, in order to provide reproducibility and tests of robustness. QSPR and proteochemometric case studies are included which demonstrate camb's application.Graphical abstractFrom compounds and data to models: a complete model building workflow in one package.

Partial discharges and breakdown in C3F8

NASA Astrophysics Data System (ADS)

Koch, M.; Franck, C. M.

2014-10-01

Traditional search processes of gases or gas mixtures for replacing SF6 involve time consuming measurements of partial discharges and breakdown behaviour for several voltage waveforms and different field configurations. Recently a model for prediction of this behaviour for SF6 was described in literature. The model only requires basic properties of the gas such as the critical field strength and the effective ionization coefficient, which can be obtained by swarm parameter measurements, and thermodynamic properties, which can be calculated. In this paper, we show for the well-known and electronegative gas octafluoropropane (C3F8) that it is possible to transfer the model developed for SF6 to this gas to describe the breakdown behaviour of C3F8. Thus the model can be beneficial in the screening process of new insulation gases.

A remote sensing data assimilation system for cold land processes hydrologic estimation

NASA Astrophysics Data System (ADS)

Andreadis, Konstantinos M.

2009-12-01

Accurate forecasting of snow properties is important for effective water resources management, especially in mountainous areas. Model-based approaches are limited by biases and uncertainties. Remote sensing offers an opportunity for observation of snow properties over larger areas. Traditional approaches to direct estimation of snow properties from passive microwave remote sensing have been plagued by limitations such as the tendency of estimates to saturate for moderately deep snowpacks and the effects of mixed land cover. To address these complications, a data assimilation system is developed and evaluated in a three-part research. The data assimilation system requires the embedding of a microwave emissions model which uses modeled snowpack properties. In the first part of this study, such a model is evaluated using multi-scale TB measurements from the Cold Land Processes Experiment. The model's ability to reproduce snowpack microphysical properties is evaluated through comparison with snowpit measurements, while TB predictions are evaluated through comparison with in-situ, aircraft and satellite measurements. Point comparisons showed limitations in the model, while the spatial averaging and the effects of forest cover suppressed errors in comparisons with aircraft measurements. The layered character of snowpacks increases the complexity of algorithms intended to retrieve snow properties from the snowpack microwave return signal. Implementation of a retrieval strategy requires knowledge of stratigraphy, which practically can only be produced by models. In the second part of this study, we describe a multi-layer model designed for such applications. The model coupled with a radiative transfer scheme improved the estimation of TB, while potential impacts when assimilating radiances are explored. A system that merges SWE model predictions and observations of SCE and TB, is evaluated in the third part of this study over one winter season in the Upper Snake River basin. Two data assimilation techniques, the Ensemble Kalman filter and the Ensemble Multiscale Kalman filter are tested with the multilayer snow model forced by downscaled re-analysis meteorological observations. Both the EnKF and EnMKF showed modest improvements when compared with the open-loop simulation, relative to a baseline simulation which used in-situ meteorological data, while comparisons with in-situ SWE measurements showed an overall improvement.

Towards a unified theory of neocortex: laminar cortical circuits for vision and cognition.

PubMed

Grossberg, Stephen

2007-01-01

A key goal of computational neuroscience is to link brain mechanisms to behavioral functions. The present article describes recent progress towards explaining how laminar neocortical circuits give rise to biological intelligence. These circuits embody two new and revolutionary computational paradigms: Complementary Computing and Laminar Computing. Circuit properties include a novel synthesis of feedforward and feedback processing, of digital and analog processing, and of preattentive and attentive processing. This synthesis clarifies the appeal of Bayesian approaches but has a far greater predictive range that naturally extends to self-organizing processes. Examples from vision and cognition are summarized. A LAMINART architecture unifies properties of visual development, learning, perceptual grouping, attention, and 3D vision. A key modeling theme is that the mechanisms which enable development and learning to occur in a stable way imply properties of adult behavior. It is noted how higher-order attentional constraints can influence multiple cortical regions, and how spatial and object attention work together to learn view-invariant object categories. In particular, a form-fitting spatial attentional shroud can allow an emerging view-invariant object category to remain active while multiple view categories are associated with it during sequences of saccadic eye movements. Finally, the chapter summarizes recent work on the LIST PARSE model of cognitive information processing by the laminar circuits of prefrontal cortex. LIST PARSE models the short-term storage of event sequences in working memory, their unitization through learning into sequence, or list, chunks, and their read-out in planned sequential performance that is under volitional control. LIST PARSE provides a laminar embodiment of Item and Order working memories, also called Competitive Queuing models, that have been supported by both psychophysical and neurobiological data. These examples show how variations of a common laminar cortical design can embody properties of visual and cognitive intelligence that seem, at least on the surface, to be mechanistically unrelated.

The influence of buoyant forces and volume fraction of particles on the particle pushing/entrapment transition during directional solidification of Al/SiC and Al/graphite composites

NASA Technical Reports Server (NTRS)

Stefanescu, Doru M.; Moitra, Avijit; Kacar, A. Sedat; Dhindaw, Brij K.

1990-01-01

Directional solidification experiments in a Bridgman-type furnace were used to study particle behavior at the liquid/solid interface in aluminum metal matrix composites. Graphite or silicon-carbide particles were first dispersed in aluminum-base alloys via a mechanically stirred vortex. Then, 100-mm-diameter and 120-mm-long samples were cast in steel dies and used for directional solidification. The processing variables controlled were the direction and velocity of solidification and the temperature gradient at the interface. The material variables monitored were the interface energy, the liquid/particle density difference, the particle/liquid thermal conductivity ratio, and the volume fraction of particles. These properties were changed by selecting combinations of particles (graphite or silicon carbide) and alloys (Al-Cu, Al-Mg, Al-Ni). A model which consideres process thermodynamics, process kinetics (including the role of buoyant forces), and thermophysical properties was developed. Based on solidification direction and velocity, and on materials properties, four types of behavior were predicted. Sessile drop experiments were also used to determine some of the interface energies required in calculation with the proposed model. Experimental results compared favorably with model predictions.

The influence of buoyant forces and volume fraction of particles on the particle pushing/entrapment transition during directional solidification of Al/SiC and Al/graphite composites

NASA Astrophysics Data System (ADS)

Stefanescu, Doru M.; Moitra, Avijit; Kacar, A. Sedat; Dhindaw, Brij K.

1990-01-01

Directional solidification experiments in a Bridgman-type furnace were used to study particle behavior at the liquid/solid interface in aluminum metal matrix composites. Graphite or siliconcarbide particles were first dispersed in aluminum-base alloys via a mechanically stirred vortex. Then, 100-mm-diameter and 120-mm-long samples were cast in steel dies and used for directional solidification. The processing variables controlled were the direction and velocity of solidification and the temperature gradient at the interface. The material variables monitored were the interface energy, the liquid/particle density difference, the particle/liquid thermal conductivity ratio, and the volume fraction of particles. These properties were changed by selecting combinations of particles (graphite or silicon carbide) and alloys (Al-Cu, Al-Mg, Al-Ni). A model which considers process thermodynamics, process kinetics (including the role of buoyant forces), and thermophysical properties was developed. Based on solidification direction and velocity, and on materials properties, four types of behavior were predicted. Sessile drop experiments were also used to determine some of the interface energies required in calculation with the proposed model. Experimental results compared favorably with model predictions.

Evaluating the hydraulic and transport properties of peat soil using pore network modeling and X-ray micro computed tomography

NASA Astrophysics Data System (ADS)

Gharedaghloo, Behrad; Price, Jonathan S.; Rezanezhad, Fereidoun; Quinton, William L.

2018-06-01

Micro-scale properties of peat pore space and their influence on hydraulic and transport properties of peat soils have been given little attention so far. Characterizing the variation of these properties in a peat profile can increase our knowledge on the processes controlling contaminant transport through peatlands. As opposed to the common macro-scale (or bulk) representation of groundwater flow and transport processes, a pore network model (PNM) simulates flow and transport processes within individual pores. Here, a pore network modeling code capable of simulating advective and diffusive transport processes through a 3D unstructured pore network was developed; its predictive performance was evaluated by comparing its results to empirical values and to the results of computational fluid dynamics (CFD) simulations. This is the first time that peat pore networks have been extracted from X-ray micro-computed tomography (μCT) images of peat deposits and peat pore characteristics evaluated in a 3D approach. Water flow and solute transport were modeled in the unstructured pore networks mapped directly from μCT images. The modeling results were processed to determine the bulk properties of peat deposits. Results portray the commonly observed decrease in hydraulic conductivity with depth, which was attributed to the reduction of pore radius and increase in pore tortuosity. The increase in pore tortuosity with depth was associated with more decomposed peat soil and decreasing pore coordination number with depth, which extended the flow path of fluid particles. Results also revealed that hydraulic conductivity is isotropic locally, but becomes anisotropic after upscaling to core-scale; this suggests the anisotropy of peat hydraulic conductivity observed in core-scale and field-scale is due to the strong heterogeneity in the vertical dimension that is imposed by the layered structure of peat soils. Transport simulations revealed that for a given solute, the effective diffusion coefficient decreases with depth due to the corresponding increase of diffusional tortuosity. Longitudinal dispersivity of peat also was computed by analyzing advective-dominant transport simulations that showed peat dispersivity is similar to the empirical values reported in the same peat soil; it is not sensitive to soil depth and does not vary much along the soil profile.

Consolidation modelling for thermoplastic composites forming simulation

NASA Astrophysics Data System (ADS)

Xiong, H.; Rusanov, A.; Hamila, N.; Boisse, P.

2016-10-01

Pre-impregnated thermoplastic composites are widely used in the aerospace industry for their excellent mechanical properties, Thermoforming thermoplastic prepregs is a fast manufacturing process, the automotive industry has shown increasing interest in this manufacturing processes, in which the reconsolidation is an essential stage. The model of intimate contact is investigated as the consolidation model, compression experiments have been launched to identify the material parameters, several numerical tests show the influents of the temperature and pressure applied during processing. Finally, a new solid-shell prismatic element has been presented for the simulation of consolidation step in the thermoplastic composites forming process.

IVUS-Based Computational Modeling and Planar Biaxial Artery Material Properties for Human Coronary Plaque Vulnerability Assessment

PubMed Central

Liu, Haofei; Cai, Mingchao; Yang, Chun; Zheng, Jie; Bach, Richard; Kural, Mehmet H.; Billiar, Kristen L.; Muccigrosso, David; Lu, Dongsi; Tang, Dalin

2012-01-01

Image-based computational modeling has been introduced for vulnerable atherosclerotic plaques to identify critical mechanical conditions which may be used for better plaque assessment and rupture predictions. In vivo patient-specific coronary plaque models are lagging due to limitations on non-invasive image resolution, flow data, and vessel material properties. A framework is proposed to combine intravascular ultrasound (IVUS) imaging, biaxial mechanical testing and computational modeling with fluid-structure interactions and anisotropic material properties to acquire better and more complete plaque data and make more accurate plaque vulnerability assessment and predictions. Impact of pre-shrink-stretch process, vessel curvature and high blood pressure on stress, strain, flow velocity and flow maximum principal shear stress was investigated. PMID:22428362

Does a pear growl? Interference from semantic properties of orthographic neighbors.

PubMed

Pecher, Diane; de Rooij, Jimmy; Zeelenberg, René

2009-07-01

In this study, we investigated whether semantic properties of a word's orthographic neighbors are activated during visual word recognition. In two experiments, words were presented with a property that was not true for the word itself. We manipulated whether the property was true for an orthographic neighbor of the word. Our results showed that rejection of the property was slower and less accurate when the property was true for a neighbor than when the property was not true for a neighbor. These findings indicate that semantic information is activated before orthographic processing is finished. The present results are problematic for the links model (Forster, 2006; Forster & Hector, 2002) that was recently proposed in order to bring form-first models of visual word recognition into line with previously reported findings (Forster & Hector, 2002; Pecher, Zeelenberg, & Wagenmakers, 2005; Rodd, 2004).

Carbon nanotube thin film strain sensor models assembled using nano- and micro-scale imaging

NASA Astrophysics Data System (ADS)

Lee, Bo Mi; Loh, Kenneth J.; Yang, Yuan-Sen

2017-07-01

Nanomaterial-based thin films, particularly those based on carbon nanotubes (CNT), have brought forth tremendous opportunities for designing next-generation strain sensors. However, their strain sensing properties can vary depending on fabrication method, post-processing treatment, and types of CNTs and polymers employed. The objective of this study was to derive a CNT-based thin film strain sensor model using inputs from nano-/micro-scale experimental measurements of nanotube physical properties. This study began with fabricating ultra-low-concentration CNT-polymer thin films, followed by imaging them using atomic force microscopy. Image processing was employed for characterizing CNT dispersed shapes, lengths, and other physical attributes, and results were used for building five different types of thin film percolation-based models. Numerical simulations were conducted to assess how the morphology of dispersed CNTs in its 2D matrix affected bulk film electrical and electromechanical (strain sensing) properties. The simulation results showed that CNT morphology had a significant impact on strain sensing performance.

Genealogical Properties of Subsamples in Highly Fecund Populations

NASA Astrophysics Data System (ADS)

Eldon, Bjarki; Freund, Fabian

2018-03-01

We consider some genealogical properties of nested samples. The complete sample is assumed to have been drawn from a natural population characterised by high fecundity and sweepstakes reproduction (abbreviated HFSR). The random gene genealogies of the samples are—due to our assumption of HFSR—modelled by coalescent processes which admit multiple mergers of ancestral lineages looking back in time. Among the genealogical properties we consider are the probability that the most recent common ancestor is shared between the complete sample and the subsample nested within the complete sample; we also compare the lengths of `internal' branches of nested genealogies between different coalescent processes. The results indicate how `informative' a subsample is about the properties of the larger complete sample, how much information is gained by increasing the sample size, and how the `informativeness' of the subsample varies between different coalescent processes.

Anti-icing property of bio-inspired micro-structure superhydrophobic surfaces and heat transfer model

NASA Astrophysics Data System (ADS)

Liu, Yan; Li, Xinlin; Jin, Jingfu; Liu, Jiaan; Yan, Yuying; Han, Zhiwu; Ren, Luquan

2017-04-01

Ice accumulation is a thorny problem which may inflict serious damage even disasters in many areas, such as aircraft, power line maintenance, offshore oil platform and locators of ships. Recent researches have shed light on some promising bio-inspired anti-icing strategies to solve this problem. Inspired by typical plant surfaces with super-hydrophobic character such as lotus leaves and rose petals, structured superhydrophobic surface are prepared to discuss the anti-icing property. 7075 Al alloy, an extensively used materials in aircrafts and marine vessels, is employed as the substrates. As-prepared surfaces are acquired by laser processing after being modified by stearic acid for 1 h at room temperature. The surface morphology, chemical composition and wettability are characterized by means of SEM, XPS, Fourier transform infrared (FTIR) spectroscopy and contact angle measurements. The morphologies of structured as-prepared samples include round hump, square protuberance and mountain-range-like structure, and that the as-prepared structured surfaces shows an excellent superhydrophobic property with a WCA as high as 166 ± 2°. Furthermore, the anti-icing property of as-prepared surfaces was tested by a self-established apparatus, and the crystallization process of a cooling water on the sample was recorded. More importantly, we introduced a model to analyze heat transfer process between the droplet and the structured surfaces. This study offers an insight into understanding the heat transfer process of the superhydrophobic surface, so as to further research about its unique property against ice accumulation.

Modelling and simulation of cure in pultrusion processes

NASA Astrophysics Data System (ADS)

Tucci, F.; Rubino, F.; Paradiso, V.; Carlone, P.; Valente, R.

2017-10-01

Trial and error approach is not a suitable method to optimize the pultrusion process because of the high times required for the start up and the wide range of possible combinations of matrix and reinforcement. On the other hand, numerical approaches can be a suitable solution to test different parameter configuration. One of the main tasks in pultrusion processes is to obtain a complete and homogeneous resin polymerization. The formation of cross-links between polymeric chains is thermally induced but it leads to a strong exothermic heat generation, hence the thermal and the chemical phenomena are mutually affected. It requires that the two problems have to be modelled in coupled way. The mathematical model used in this work considers the composite as a lumped material, whose thermal and mechanical properties are evaluated as function of resin and fibers properties. The numerical pattern is based on a quasi-static approach in a three-dimensional Eulerian domain, which describes both thermal and chemical phenomena. The data obtained are used in a simplified C.H.I.L.E. (Cure Hardening Instantaneous Linear Elastic) model to compute the mechanical properties of the resin fraction in the pultruded. The two combined approaches allow to formulate a numerical model which takes into account the normal (no-penetration) and tangential (viscosity/friction) interactions between die and profile, the pulling force and the hydrostatic pressure of the liquid resin to evaluate the stress and strain fields induced by the process within the pultruded. The implementation of the numerical models has been carried out using the ABAQUS finite element suite, by means of several user subroutines (in Fortran language) which improve the basic software potentialities.

Modelling the complete operation of a free-piston shock tunnel for a low enthalpy condition

NASA Astrophysics Data System (ADS)

McGilvray, M.; Dann, A. G.; Jacobs, P. A.

2013-07-01

Only a limited number of free-stream flow properties can be measured in hypersonic impulse facilities at the nozzle exit. This poses challenges for experimenters when subsequently analysing experimental data obtained from these facilities. Typically in a reflected shock tunnel, a simple analysis that requires small amounts of computational resources is used to calculate quasi-steady gas properties. This simple analysis requires initial fill conditions and experimental measurements in analytical calculations of each major flow process, using forward coupling with minor corrections to include processes that are not directly modeled. However, this simplistic approach leads to an unknown level of discrepancy to the true flow properties. To explore the simple modelling techniques accuracy, this paper details the use of transient one and two-dimensional numerical simulations of a complete facility to obtain more refined free-stream flow properties from a free-piston reflected shock tunnel operating at low-enthalpy conditions. These calculations were verified by comparison to experimental data obtained from the facility. For the condition and facility investigated, the test conditions at nozzle exit produced with the simple modelling technique agree with the time and space averaged results from the complete facility calculations to within the accuracy of the experimental measurements.

Tensile Properties Characterization of AlSi10Mg Parts Produced by Direct Metal Laser Sintering via Nested Effects Modeling.

PubMed

Palumbo, Biagio; Del Re, Francesco; Martorelli, Massimo; Lanzotti, Antonio; Corrado, Pasquale

2017-02-08

A statistical approach for the characterization of Additive Manufacturing (AM) processes is presented in this paper. Design of Experiments (DOE) and ANalysis of VAriance (ANOVA), both based on Nested Effects Modeling (NEM) technique, are adopted to assess the effect of different laser exposure strategies on physical and mechanical properties of AlSi10Mg parts produced by Direct Metal Laser Sintering (DMLS). Due to the wide industrial interest in AM technologies in many different fields, it is extremely important to ensure high parts performances and productivity. For this aim, the present paper focuses on the evaluation of tensile properties of specimens built with different laser exposure strategies. Two optimal laser parameters settings, in terms of both process quality (part performances) and productivity (part build rate), are identified.

Tensile Properties Characterization of AlSi10Mg Parts Produced by Direct Metal Laser Sintering via Nested Effects Modeling

PubMed Central

Palumbo, Biagio; Del Re, Francesco; Martorelli, Massimo; Lanzotti, Antonio; Corrado, Pasquale

2017-01-01

A statistical approach for the characterization of Additive Manufacturing (AM) processes is presented in this paper. Design of Experiments (DOE) and ANalysis of VAriance (ANOVA), both based on Nested Effects Modeling (NEM) technique, are adopted to assess the effect of different laser exposure strategies on physical and mechanical properties of AlSi10Mg parts produced by Direct Metal Laser Sintering (DMLS). Due to the wide industrial interest in AM technologies in many different fields, it is extremely important to ensure high parts performances and productivity. For this aim, the present paper focuses on the evaluation of tensile properties of specimens built with different laser exposure strategies. Two optimal laser parameters settings, in terms of both process quality (part performances) and productivity (part build rate), are identified. PMID:28772505

Universal Fragment Descriptors for Predicting Electronic and Mechanical Properties of Inorganic Crystals

NASA Astrophysics Data System (ADS)

Oses, Corey; Isayev, Olexandr; Toher, Cormac; Curtarolo, Stefano; Tropsha, Alexander

Historically, materials discovery is driven by a laborious trial-and-error process. The growth of materials databases and emerging informatics approaches finally offer the opportunity to transform this practice into data- and knowledge-driven rational design-accelerating discovery of novel materials exhibiting desired properties. By using data from the AFLOW repository for high-throughput, ab-initio calculations, we have generated Quantitative Materials Structure-Property Relationship (QMSPR) models to predict critical materials properties, including the metal/insulator classification, band gap energy, and bulk modulus. The prediction accuracy obtained with these QMSPR models approaches training data for virtually any stoichiometric inorganic crystalline material. We attribute the success and universality of these models to the construction of new materials descriptors-referred to as the universal Property-Labeled Material Fragments (PLMF). This representation affords straightforward model interpretation in terms of simple heuristic design rules that could guide rational materials design. This proof-of-concept study demonstrates the power of materials informatics to dramatically accelerate the search for new materials.

Systematic Observations of the Slip-pulse Properties of Large Earthquake Ruptures

NASA Astrophysics Data System (ADS)

Melgar, D.; Hayes, G. P.

2017-12-01

In earthquake dynamics there are two end member models of rupture: propagating cracks and self-healing pulses. These arise due to different properties of ruptures and have implications for seismic hazard; rupture mode controls near-field strong ground motions. Past studies favor the pulse-like mode of rupture, however, due to a variety of limitations, it has proven difficult to systematically establish their kinematic properties. Here we synthesize observations from a database of >150 rupture models of earthquakes spanning M7-M9 processed in a uniform manner and show the magnitude scaling properties (rise time, pulse width, and peak slip rate) of these slip pulses indicates self-similarity. Self similarity suggests a weak form of rupture determinism, where early on in the source process broader, higher amplitude slip pulses will distinguish between events of icnreasing magnitude. Indeed, we find by analyzing the moment rate functions that large and very large events are statistically distinguishable relatively early (at 15 seconds) in the rupture process. This suggests that with dense regional geophysical networks strong ground motions from a large rupture can be identified before their onset across the source region.

Simulating the Effects of Semivolatile Compounds on Cloud Processing of Aerosol

NASA Astrophysics Data System (ADS)

Kokkola, H.; Kudzotsa, I.; Tonttila, J.; Raatikainen, T.; Romakkaniemi, S.

2017-12-01

Aerosol removal processes largely dictate how well aerosol is transported in the atmosphere and thus the aerosol load over remote regions depends on how effectively aerosol is removed during its transport from the source regions. This means that in order to model the global distribution aerosol, both in vertical and horizontal, wet deposition processes have to be properly modelled. However, in large scale models, the description of wet removal and the vertical redistribution of aerosol by cloud processes is often extremely simplified.Here we present a novel aerosol-cloud model SALSA, where the aerosol properties are tracked through different cloud processes. These processes include: cloud droplet activation, precipitation formation, ice nucleation, melting, and evaporation. It is a sectional model that includes separate size sections for non-activated aerosol, cloud droplets, precipitation droplets, and ice crystals. The aerosol-cloud model was coupled to a large eddy model UCLALES which simulates the boundary-layer dynamics. In this study, the model has been applied in studying the wet removal as well as interactions between aerosol, clouds, and semi-volatile compounds, ammonia and nitric acid. These semi-volative compounds are special in the sense that they co-condense together with water during cloud activation and have been suggested to form droplets that can be considered cloud-droplet-like already in subsaturated conditions. In our model, we calculate the kinetic partitioning of ammonia and sulfate thus explicitly taking into account the effect of ammonia and nitric acid in the cloud formation. Our simulations indicate that especially in polluted conditions, these compounds significantly affect the properties of cloud droplets thus significantly affecting the lifecycle of different aerosol compounds.

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

Numerical Modeling of Nanocellular Foams Using Classical Nucleation Theory and Influence Volume Approach

NASA Astrophysics Data System (ADS)

Khan, Irfan; Costeux, Stephane; Bunker, Shana; Moore, Jonathan; Kar, Kishore

2012-11-01

Nanocellular porous materials present unusual optical, dielectric, thermal and mechanical properties and are thus envisioned to find use in a variety of applications. Thermoplastic polymeric foams show considerable promise in achieving these properties. However, there are still considerable challenges in achieving nanocellular foams with densities as low as conventional foams. Lack of in-depth understanding of the effect of process parameters and physical properties on the foaming process is a major obstacle. A numerical model has been developed to simulate the simultaneous nucleation and bubble growth during depressurization of thermoplastic polymers saturated with supercritical blowing agents. The model is based on the popular ``Influence Volume Approach,'' which assumes a growing boundary layer with depleted blowing agent surrounds each bubble. Classical nucleation theory is used to predict the rate of nucleation of bubbles. By solving the mass balance, momentum balance and species conservation equations for each bubble, the model is capable of predicting average bubble size, bubble size distribution and bulk porosity. The model is modified to include mechanisms for Joule-Thompson cooling during depressurization and secondary foaming. Simulation results for polymer with and without nucleating agents will be discussed and compared with experimental data.

Analysis of thermohydraulic explosion energetics

NASA Astrophysics Data System (ADS)

Büttner, Ralf; Zimanowski, Bernd; Mohrholz, Chris-Oliver; Kümmel, Reiner

2005-08-01

Thermohydraulic explosion, caused by direct contact of hot liquids with cold water, represent a major danger of volcanism and in technical processes. Based on experimental observations and nonequilibrium thermodynamics we propose a model of heat transfer from the hot liquid to the water during the thermohydraulic fragmentation process. The model was validated using the experimentally observed thermal energy release. From a database of more than 1000 experimental runs, conducted during the last 20 years, a standardized entrapment experiment was defined, where a conversion of 1 MJ/kg of thermal energy to kinetic energy within 700μs is observed. The results of the model calculations are in good agreement with this value. Furthermore, the model was found to be robust with respect to the material properties of the hot melt, which also is observed in experiments using different melt compositions. As the model parameters can be easily obtained from size and shape properties of the products of thermohydraulic explosions and from material properties of the hot melt, we believe that this method will not only allow a better analysis of volcanic eruptions or technical accidents, but also significantly improve the quality of hazard assessment and mitigation.

Breaking the limits of structural and mechanical imaging of the heterogeneous structure of coal macerals

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

Collins, L.; Tselev, A.; Jesse, S.

The correlation between local mechanical (elasto-plastic) and structural (composition) properties of coal presents significant fundamental and practical interest for coal processing and the development of rheological models of coal to coke transformations and for advancing novel approaches. Here, we explore the relationship between the local structural, chemical composition and mechanical properties of coal using a combination of confocal micro-Raman imaging and band excitation atomic force acoustic microscopy (BE-AFAM) for a bituminous coal. This allows high resolution imaging (10s of nm) of mechanical properties of the heterogeneous (banded) architecture of coal and correlating them to the optical gap, average crystallite size,more » the bond-bending disorder of sp2 aromatic double bonds and the defect density. This methodology hence allows the structural and mechanical properties of coal components (lithotypes, microlithotypes, and macerals) to be understood, and related to local chemical structure, potentially allowing for knowledge-based modelling and optimization of coal utilization processes.« less

Characterizations and Electrical Modelling of Sensory Samples Formed from Synthesized Vanadium (V) Oxide and Copper Oxide Graphene Quantum Tunneling Composites (GQTC) Applied in Electrotribology

PubMed Central

Habdank-Wojewódzki, Tadeusz; Habdank, Josef; Cwik, Przemyslaw; Zimowski, Slawomir

2016-01-01

CuO and V2O5 graphene quantum tunneling composites (GQTC) presented in this article were produced and their sensory properties were analyzed. The composites were synthesised using two stage high-power milling process, which resulted in materials that have good temeprature and pressure sensory properties. Described production process defines internal structure of materials such that when used as sensor in the desired range, it exhibits a strong percolation effect. The experiment, with controlled changing physical conditions during electrotribological measurement, enabled analyzing of the composites’ conductivity as a function of the sensory properties: applied temperature, pressure, tangential force and wear. The sensory characteristic was successfully modelled by invertible generalized equations, and used to create sensor capable of estimating temperature or pressure in the real time. The developed materials have the potential to be applied in the areas where miniaturization is essential, due to the materials exhibiting good sensory properties in mini and micro scale. PMID:26742044

Characterizations and Electrical Modelling of Sensory Samples Formed from Synthesized Vanadium (V) Oxide and Copper Oxide Graphene Quantum Tunneling Composites (GQTC) Applied in Electrotribology.

PubMed

Habdank-Wojewódzki, Tadeusz; Habdank, Josef; Cwik, Przemyslaw; Zimowski, Slawomir

2016-01-05

CuO and V₂O₅ graphene quantum tunneling composites (GQTC) presented in this article were produced and their sensory properties were analyzed. The composites were synthesised using two stage high-power milling process, which resulted in materials that have good temeprature and pressure sensory properties. Described production process defines internal structure of materials such that when used as sensor in the desired range, it exhibits a strong percolation effect. The experiment, with controlled changing physical conditions during electrotribological measurement, enabled analyzing of the composites' conductivity as a function of the sensory properties: applied temperature, pressure, tangential force and wear. The sensory characteristic was successfully modelled by invertible generalized equations, and used to create sensor capable of estimating temperature or pressure in the real time. The developed materials have the potential to be applied in the areas where miniaturization is essential, due to the materials exhibiting good sensory properties in mini and micro scale.

Approximate Model Checking of PCTL Involving Unbounded Path Properties

NASA Astrophysics Data System (ADS)

Basu, Samik; Ghosh, Arka P.; He, Ru

We study the problem of applying statistical methods for approximate model checking of probabilistic systems against properties encoded as PCTL formulas. Such approximate methods have been proposed primarily to deal with state-space explosion that makes the exact model checking by numerical methods practically infeasible for large systems. However, the existing statistical methods either consider a restricted subset of PCTL, specifically, the subset that can only express bounded until properties; or rely on user-specified finite bound on the sample path length. We propose a new method that does not have such restrictions and can be effectively used to reason about unbounded until properties. We approximate probabilistic characteristics of an unbounded until property by that of a bounded until property for a suitably chosen value of the bound. In essence, our method is a two-phase process: (a) the first phase is concerned with identifying the bound k 0; (b) the second phase computes the probability of satisfying the k 0-bounded until property as an estimate for the probability of satisfying the corresponding unbounded until property. In both phases, it is sufficient to verify bounded until properties which can be effectively done using existing statistical techniques. We prove the correctness of our technique and present its prototype implementations. We empirically show the practical applicability of our method by considering different case studies including a simple infinite-state model, and large finite-state models such as IPv4 zeroconf protocol and dining philosopher protocol modeled as Discrete Time Markov chains.

Improving the spatial representation of soil properties and hydrology using topographically derived watershed model initialization processes

NASA Astrophysics Data System (ADS)

Easton, Z. M.; Fuka, D.; Collick, A.; Kleinman, P. J. A.; Auerbach, D.; Sommerlot, A.; Wagena, M. B.

2015-12-01

Topography exerts critical controls on many hydrologic, geomorphologic, and environmental biophysical processes. Unfortunately many watershed modeling systems use topography only to define basin boundaries and stream channels and do not explicitly account for the topographic controls on processes such as soil genesis, soil moisture distributions and hydrological response. We develop and demonstrate a method that uses topography to spatially adjust soil morphological and soil hydrological attributes [soil texture, depth to the C-horizon, saturated conductivity, bulk density, porosity, and the field capacities at 33kpa (~ field capacity) and 1500kpa (~ wilting point) tensions]. In order to test the performance of the method the topographical adjusted soils and standard SSURGO soil (available at 1:20,000 scale) were overlaid on soil pedon pit data in the Grasslands Soil and Water Research Lab in Resiel, TX. The topographically adjusted soils exhibited significant correlations with measurements from the soil pits, while the SSURGO soil data showed almost no correlation to measured data. We also applied the method to the Grasslands Soil and Water Research watershed using the Soil and Water Assessment Tool (SWAT) model to 15 separate fields as a proxy to propagate changes in soil properties into field scale hydrological responses. Results of this test showed that the topographically adjusted soils resulted better model predictions of field runoff in 50% of the field, with the SSURGO soils preforming better in the remainder of the fields. However, the topographically adjusted soils generally predicted baseflow response more accurately, reflecting the influence of these soil properties on non-storm responses. These results indicate that adjusting soil properties based on topography can result in more accurate soil characterization and, in some cases improve model performance.

Prediction of the properties of PVD/CVD coatings with the use of FEM analysis

NASA Astrophysics Data System (ADS)

Śliwa, Agata; Mikuła, Jarosław; Gołombek, Klaudiusz; Tański, Tomasz; Kwaśny, Waldemar; Bonek, Mirosław; Brytan, Zbigniew

2016-12-01

The aim of this paper is to present the results of the prediction of the properties of PVD/CVD coatings with the use of finite element method (FEM) analysis. The possibility of employing the FEM in the evaluation of stress distribution in multilayer Ti/Ti(C,N)/CrN, Ti/Ti(C,N)/(Ti,Al)N, Ti/(Ti,Si)N/(Ti,Si)N, and Ti/DLC/DLC coatings by taking into account their deposition conditions on magnesium alloys has been discussed in the paper. The difference in internal stresses in the zone between the coating and the substrate is caused by, first of all, the difference between the mechanical and thermal properties of the substrate and the coating, and also by the structural changes that occur in these materials during the fabrication process, especially during the cooling process following PVD and CVD treatment. The experimental values of stresses were determined based on X-ray diffraction patterns that correspond to the modelled values, which in turn can be used to confirm the correctness of the accepted mathematical model for testing the problem. An FEM model was established for the purpose of building a computer simulation of the internal stresses in the coatings. The accuracy of the FEM model was verified by comparing the results of the computer simulation of the stresses with experimental results. A computer simulation of the stresses was carried out in the ANSYS environment using the FEM method. Structure observations, chemical composition measurements, and mechanical property characterisations of the investigated materials has been carried out to give a background for the discussion of the results that were recorded during the modelling process.

A PROCESS FOR SELECTING INDICATORS FOR MONITORING CONDITIONS OF RANGELAND HEALTH (COPY)

EPA Science Inventory

This paper reports on a process for selecting a suite of indicators that, in combination, can be useful in assessing the ecological conditions of rangelands. Conceptual models that depict the structural and functional properties of ecological processes were used to show the linka...

The Impact of Rhizosphere Processes on Water Flow and Root Water Uptake

NASA Astrophysics Data System (ADS)

Schwartz, Nimrod; Kroener, Eva; Carminati, Andrea; Javaux, Mathieu

2015-04-01

For many years, the rhizosphere, which is the zone of soil in the vicinity of the roots and which is influenced by the roots, is known as a unique soil environment with different physical, biological and chemical properties than those of the bulk soil. Indeed, in recent studies it has been shown that root exudate and especially mucilage alter the hydraulic properties of the soil, and that drying and wetting cycles of mucilage result in non-equilibrium water dynamics in the rhizosphere. While there are experimental evidences and simplified 1D model for those concepts, an integrated model that considers rhizosphere processes with a detailed model for water and roots flow is absent. Therefore, the objective of this work is to develop a 3D physical model of water flow in the soil-plant continuum that take in consideration root architecture and rhizosphere specific properties. Ultimately, this model will enhance our understanding on the impact of processes occurring in the rhizosphere on water flow and root water uptake. To achieve this objective, we coupled R-SWMS, a detailed 3D model for water flow in soil and root system (Javaux et al 2008), with the rhizosphere model developed by Kroener et al (2014). In the new Rhizo-RSWMS model the rhizosphere hydraulic properties differ from those of the bulk soil, and non-equilibrium dynamics between the rhizosphere water content and pressure head is also considered. We simulated a wetting scenario. The soil was initially dry and it was wetted from the top at a constant flow rate. The model predicts that, after infiltration the water content in the rhizosphere remained lower than in the bulk soil (non-equilibrium), but over time water infiltrated into the rhizosphere and eventually the water content in the rhizosphere became higher than in the bulk soil. These results are in qualitative agreement with the available experimental data on water dynamics in the rhizosphere. Additionally, the results show that rhizosphere processes affect the spatial distribution of root water uptake. This suggests that rhizosphere processes effect root water uptake at the plant scale. Overall, these preliminary results demonstrate the impact of rhizosphere on water flow and root water uptake, and the ability of the Rhizo-RSWMS to simulate these processes. References Javaux, M., Schröder, T., Vanderborght, J., & Vereecken, H. (2008). Use of a three-dimensional detailed modeling approach for predicting root water uptake. Vadose Zone Journal, 7(3), 1079-1088.‏ Kroener, E., Zarebanadkouki, M., Kaestner, A., & Carminati, A. (2014). Nonequilibrium water dynamics in the rhizosphere: How mucilage affects water flow in soils. Water Resources Research, 50(8), 6479-6495.‏

Prediction of the properties anhydrite construction mixtures based on neural network approach

NASA Astrophysics Data System (ADS)

Fedorchuk, Y. M.; Zamyatin, N. V.; Smirnov, G. V.; Rusina, O. N.; Sadenova, M. A.

2017-08-01

The article considered the question of applying the backstop modeling mechanism from the components of anhydride mixtures in the process of managing the technological processes of receiving construction products which based on fluoranhydrite.

Drift-Scale Coupled Processes (DST and THC Seepage) Models

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

E. Gonnenthal; N. Spyoher

The purpose of this Analysis/Model Report (AMR) is to document the Near-Field Environment (NFE) and Unsaturated Zone (UZ) models used to evaluate the potential effects of coupled thermal-hydrologic-chemical (THC) processes on unsaturated zone flow and transport. This is in accordance with the ''Technical Work Plan (TWP) for Unsaturated Zone Flow and Transport Process Model Report'', Addendum D, Attachment D-4 (Civilian Radioactive Waste Management System (CRWMS) Management and Operating Contractor (M and O) 2000 [153447]) and ''Technical Work Plan for Nearfield Environment Thermal Analyses and Testing'' (CRWMS M and O 2000 [153309]). These models include the Drift Scale Test (DST) THCmore » Model and several THC seepage models. These models provide the framework to evaluate THC coupled processes at the drift scale, predict flow and transport behavior for specified thermal loading conditions, and predict the chemistry of waters and gases entering potential waste-emplacement drifts. The intended use of this AMR is to provide input for the following: (1) Performance Assessment (PA); (2) Abstraction of Drift-Scale Coupled Processes AMR (ANL-NBS-HS-000029); (3) UZ Flow and Transport Process Model Report (PMR); and (4) Near-Field Environment (NFE) PMR. The work scope for this activity is presented in the TWPs cited above, and summarized as follows: continue development of the repository drift-scale THC seepage model used in support of the TSPA in-drift geochemical model; incorporate heterogeneous fracture property realizations; study sensitivity of results to changes in input data and mineral assemblage; validate the DST model by comparison with field data; perform simulations to predict mineral dissolution and precipitation and their effects on fracture properties and chemistry of water (but not flow rates) that may seep into drifts; submit modeling results to the TDMS and document the models. The model development, input data, sensitivity and validation studies described in this AMR are required to fully document and address the requirements of the TWPs.« less

Drift-Scale Coupled Processes (DST and THC Seepage) Models

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

E. Sonnenthale

The purpose of this Analysis/Model Report (AMR) is to document the Near-Field Environment (NFE) and Unsaturated Zone (UZ) models used to evaluate the potential effects of coupled thermal-hydrologic-chemical (THC) processes on unsaturated zone flow and transport. This is in accordance with the ''Technical Work Plan (TWP) for Unsaturated Zone Flow and Transport Process Model Report'', Addendum D, Attachment D-4 (Civilian Radioactive Waste Management System (CRWMS) Management and Operating Contractor (M&O) 2000 [1534471]) and ''Technical Work Plan for Nearfield Environment Thermal Analyses and Testing'' (CRWMS M&O 2000 [153309]). These models include the Drift Scale Test (DST) THC Model and several THCmore » seepage models. These models provide the framework to evaluate THC coupled processes at the drift scale, predict flow and transport behavior for specified thermal loading conditions, and predict the chemistry of waters and gases entering potential waste-emplacement drifts. The intended use of this AMR is to provide input for the following: Performance Assessment (PA); Near-Field Environment (NFE) PMR; Abstraction of Drift-Scale Coupled Processes AMR (ANL-NBS-HS-000029); and UZ Flow and Transport Process Model Report (PMR). The work scope for this activity is presented in the TWPs cited above, and summarized as follows: Continue development of the repository drift-scale THC seepage model used in support of the TSPA in-drift geochemical model; incorporate heterogeneous fracture property realizations; study sensitivity of results to changes in input data and mineral assemblage; validate the DST model by comparison with field data; perform simulations to predict mineral dissolution and precipitation and their effects on fracture properties and chemistry of water (but not flow rates) that may seep into drifts; submit modeling results to the TDMS and document the models. The model development, input data, sensitivity and validation studies described in this AMR are required to fully document and address the requirements of the TWPs.« less

Laser welding of polymers: phenomenological model for a quick and reliable process quality estimation considering beam shape influences

NASA Astrophysics Data System (ADS)

Timpe, Nathalie F.; Stuch, Julia; Scholl, Marcus; Russek, Ulrich A.

2016-03-01

This contribution presents a phenomenological, analytical model for laser welding of polymers which is suited for a quick process quality estimation for the practitioner. Besides material properties of the polymer and processing parameters like welding pressure, feed rate and laser power the model is based on a simple few parameter description of the size and shape of the laser power density distribution (PDD) in the processing zone. The model allows an estimation of the weld seam tensile strength. It is based on energy balance considerations within a thin sheet with the thickness of the optical penetration depth on the surface of the absorbing welding partner. The joining process itself is modelled by a phenomenological approach. The model reproduces the experimentally known process windows for the main process parameters correctly. Using the parameters describing the shape of the laser PDD the critical dependence of the process windows on the PDD shape will be predicted and compared with experiments. The adaption of the model to other laser manufacturing processes where the PDD influence can be modelled comparably will be discussed.

Vacuum drying of apples (cv. Golden Delicious): drying characteristics, thermodynamic properties, and mass transfer parameters

NASA Astrophysics Data System (ADS)

Nadi, Fatemeh; Tzempelikos, Dimitrios

2018-01-01

In this work, apples of cv. Golden Delicious were cut into slices that were 5 and 7 mm thick and then vacuum dried at 50, 60 and 70 °C and pressure of 0.02 bar. The thin layer model drying kinetics was studied, and mass transfer properties, specifically effective moisture diffusivity and convective mass transfer coefficient, were evaluated using the Fick's equation of diffusion. Also, thermodynamic parameters of the process, i.e. enthalpy (ΔH), entropy (ΔS) and Gibbs free energy (ΔG), were determined. Colour properties were evaluated as one of the important indicators of food quality and marketability. Determination of mass transfer parameters and thermodynamic properties of vacuum dried apple slices has not been discussed much in the literature. In conclusion, the Nadi's model fitted best the observed data that represent the drying process. Thermodynamic properties were determined based on the dependence of the drying constant of the Henderson and Pabis model on temperature, and it was concluded that the variation in drying kinetics depends on the energy contribution of the surrounding environment. The enthalpy and entropy diminished, while the Gibbs free energy increased with the increase of the temperature of drying; therefore, it was possible to verify that variation in the diffusion process in the apple during drying depends on energetic contributions of the environment. The obtained results showed that diffusivity increased for 69%, while the mass transfer coefficient increase was even higher, 75%, at the variation of temperature of 20 °C. The increase in the dimensionless Biot number was 20%.

Vacuum drying of apples (cv. Golden Delicious): drying characteristics, thermodynamic properties, and mass transfer parameters

NASA Astrophysics Data System (ADS)

Nadi, Fatemeh; Tzempelikos, Dimitrios

2018-07-01

In this work, apples of cv. Golden Delicious were cut into slices that were 5 and 7 mm thick and then vacuum dried at 50, 60 and 70 °C and pressure of 0.02 bar. The thin layer model drying kinetics was studied, and mass transfer properties, specifically effective moisture diffusivity and convective mass transfer coefficient, were evaluated using the Fick's equation of diffusion. Also, thermodynamic parameters of the process, i.e. enthalpy ( ΔH), entropy ( ΔS) and Gibbs free energy ( ΔG), were determined. Colour properties were evaluated as one of the important indicators of food quality and marketability. Determination of mass transfer parameters and thermodynamic properties of vacuum dried apple slices has not been discussed much in the literature. In conclusion, the Nadi's model fitted best the observed data that represent the drying process. Thermodynamic properties were determined based on the dependence of the drying constant of the Henderson and Pabis model on temperature, and it was concluded that the variation in drying kinetics depends on the energy contribution of the surrounding environment. The enthalpy and entropy diminished, while the Gibbs free energy increased with the increase of the temperature of drying; therefore, it was possible to verify that variation in the diffusion process in the apple during drying depends on energetic contributions of the environment. The obtained results showed that diffusivity increased for 69%, while the mass transfer coefficient increase was even higher, 75%, at the variation of temperature of 20 °C. The increase in the dimensionless Biot number was 20%.

Part-to-itself model inversion in process compensated resonance testing

NASA Astrophysics Data System (ADS)

Mayes, Alexander; Jauriqui, Leanne; Biedermann, Eric; Heffernan, Julieanne; Livings, Richard; Aldrin, John C.; Goodlet, Brent; Mazdiyasni, Siamack

2018-04-01

Process Compensated Resonance Testing (PCRT) is a non-destructive evaluation (NDE) method involving the collection and analysis of a part's resonance spectrum to characterize its material or damage state. Prior work used the finite element method (FEM) to develop forward modeling and model inversion techniques. In many cases, the inversion problem can become confounded by multiple parameters having similar effects on a part's resonance frequencies. To reduce the influence of confounding parameters and isolate the change in a part (e.g., creep), a part-to-itself (PTI) approach can be taken. A PTI approach involves inverting only the change in resonance frequencies from the before and after states of a part. This approach reduces the possible inversion parameters to only those that change in response to in-service loads and damage mechanisms. To evaluate the effectiveness of using a PTI inversion approach, creep strain and material properties were estimated in virtual and real samples using FEM inversion. Virtual and real dog bone samples composed of nickel-based superalloy Mar-M-247 were examined. Virtual samples were modeled with typically observed variations in material properties and dimensions. Creep modeling was verified with the collected resonance spectra from an incrementally crept physical sample. All samples were inverted against a model space that allowed for change in the creep damage state and the material properties but was blind to initial part dimensions. Results quantified the capabilities of PTI inversion in evaluating creep strain and material properties, as well as its sensitivity to confounding initial dimensions.

A comparison of calculated and measured rheological properties of crystallising lavas in the field and in the laboratory

NASA Technical Reports Server (NTRS)

Pinkerton, Harry; Norton, Gill

1993-01-01

Models of most magmatic processes, including realistic models of planetary lava flows require accurate data on the rheological properties of magma. Previous studies suggest that field and laboratory rheological properties of Hawaiian lavas can be calculated from their physico-chemical properties using a non-Newtonian rheology model. The present study uses new measurements of the rheological properties of crystallizing lavas to show that this is also true for lavas from Mount Etna. Rheological measurements on quenched Etna basalts were made in a specially designed furnace using a Haake Rotovisco viscometer attached to a spindle which has been designed to eliminate slippage at the melt-spindle interface. Using this spindle, we have made measurements at lower temperatures than other workers in this field. From these measurements, Mount Etna lavas are Newtonian at temperatures above 1120 C and they are thixotropic pseudoplastic fluids with a yield strength at lower temperatures. The close agreement between calculated and measured rheology over the temperature range 1084 - 1125 C support the use of the non-Newtonian rheology model in future modeling of planetary lava flows.

β-decay studies of r-process nuclei at NSCL

NASA Astrophysics Data System (ADS)

Pereira, J.; Aprahamian, A.; Arndt, O.; Becerril, A.; Elliot, T.; Estrade, A.; Galaviz, D.; Hennrich, S.; Hosmer, P.; Schnorrenberger, L.; Kessler, R.; Kratz, K.-L.; Lorusso, G.; Mantica, P. F.; Matos, M.; Montes, F.; Pfeiffer, B.; Quinn, M.; Santi, P.; Schatz, H.; Schertz, F.; Smith, E.; Tomlin, B. E.; Walters, W. B.; Wöhr, A.

2008-06-01

Observed neutron-capture elemental abundances in metal-poor stars, along with ongoing analysis of the extremely metal-poor Eu-enriched sub-class provide new guidance for astrophysical models aimed at finding the r-process sites. The present paper emphasizes the importance of nuclear physics parameters entering in these models, particularly β-decay properties of neutron-rich nuclei. In this context, several r-process motivated β-decay experiments performed at the National Superconducting Cyclotron Laboratory (NSCL) are presented, including a summary of results and impact on model calculations.

A computational modeling approach for the characterization of mechanical properties of 3D alginate tissue scaffolds.

PubMed

Nair, K; Yan, K C; Sun, W

2008-01-01

Scaffold guided tissue engineering is an innovative approach wherein cells are seeded onto biocompatible and biodegradable materials to form 3-dimensional (3D) constructs that, when implanted in the body facilitate the regeneration of tissue. Tissue scaffolds act as artificial extracellular matrix providing the environment conducive for tissue growth. Characterization of scaffold properties is necessary to understand better the underlying processes involved in controlling cell behavior and formation of functional tissue. We report a computational modeling approach to characterize mechanical properties of 3D gellike biomaterial, specifically, 3D alginate scaffold encapsulated with cells. Alginate inherent nonlinearity and variations arising from minute changes in its concentration and viscosity make experimental evaluation of its mechanical properties a challenging and time consuming task. We developed an in silico model to determine the stress-strain relationship of alginate based scaffolds from experimental data. In particular, we compared the Ogden hyperelastic model to other hyperelastic material models and determined that this model was the most suitable to characterize the nonlinear behavior of alginate. We further propose a mathematical model that represents the alginate material constants in Ogden model as a function of concentrations and viscosity. This study demonstrates the model capability to predict mechanical properties of 3D alginate scaffolds.

Recent advances in understanding secondary organic aerosols: implications for global climate forcing

NASA Astrophysics Data System (ADS)

Shrivastava, Manish

2017-04-01

Anthropogenic emissions and land-use changes have modified atmospheric aerosol concentrations and size distributions over time. Understanding pre-industrial conditions and changes in organic aerosol due to anthropogenic activities is important because these features 1) influence estimates of aerosol radiative forcing and 2) can confound estimates of the historical response of climate to increases in greenhouse gases (e.g. the 'climate sensitivity'). Secondary organic aerosol (SOA), formed in the atmosphere by oxidation of organic gases, often represents a major fraction of global submicron-sized atmospheric organic aerosol. Over the past decade, significant advances in understanding SOA properties and formation mechanisms have occurred through measurements, yet current climate models typically do not comprehensively include all important processes. This presentation is based on a US Department of Energy Atmospheric Systems Research sponsored workshop, which highlighted key SOA processes overlooked in climate models that could greatly affect climate forcing estimates. We will highlight the importance of processes that influence the growth of SOA particles to sizes relevant for clouds and radiative forcing, including: formation of extremely low-volatility organics in the gas-phase; isoprene epoxydiols (IEPOX) multi-phase chemistry; particle-phase oligomerization; and physical properties such as viscosity. We also highlight some of the recently discovered important processes that involve interactions between natural biogenic emissions and anthropogenic emissions such as effects of sulfur and NOx emissions on SOA. We will present examples of integrated model-measurement studies that relate the observed evolution of organic aerosol mass and number with knowledge of particle properties such as volatility and viscosity. We will also highlight the importance of continuing efforts to rank the most influential SOA processes that affect climate forcing, but are often missing in climate models. Ultimately, gas- and particle-phase chemistry processes that capture the dynamic evolution of number and mass concentrations of SOA particles need to be accurately and efficiently represented in regional and global atmospheric chemistry-climate models.

Discrete bivariate population balance modelling of heteroaggregation processes.

PubMed

Rollié, Sascha; Briesen, Heiko; Sundmacher, Kai

2009-08-15

Heteroaggregation in binary particle mixtures was simulated with a discrete population balance model in terms of two internal coordinates describing the particle properties. The considered particle species are of different size and zeta-potential. Property space is reduced with a semi-heuristic approach to enable an efficient solution. Aggregation rates are based on deterministic models for Brownian motion and stability, under consideration of DLVO interaction potentials. A charge-balance kernel is presented, relating the electrostatic surface potential to the property space by a simple charge balance. Parameter sensitivity with respect to the fractal dimension, aggregate size, hydrodynamic correction, ionic strength and absolute particle concentration was assessed. Results were compared to simulations with the literature kernel based on geometric coverage effects for clusters with heterogeneous surface properties. In both cases electrostatic phenomena, which dominate the aggregation process, show identical trends: impeded cluster-cluster aggregation at low particle mixing ratio (1:1), restabilisation at high mixing ratios (100:1) and formation of complex clusters for intermediate ratios (10:1). The particle mixing ratio controls the surface coverage extent of the larger particle species. Simulation results are compared to experimental flow cytometric data and show very satisfactory agreement.

Species richness and soil properties in Pinus ponderosa forests: A structural equation modeling analysis

USGS Publications Warehouse

Laughlin, D.C.; Abella, S.R.; Covington, W.W.; Grace, J.B.

2007-01-01

Question: How are the effects of mineral soil properties on understory plant species richness propagated through a network of processes involving the forest overstory, soil organic matter, soil nitrogen, and understory plant abundance? Location: North-central Arizona, USA. Methods: We sampled 75 0.05-ha plots across a broad soil gradient in a Pinus ponderosa (ponderosa pine) forest ecosystem. We evaluated multivariate models of plant species richness using structural equation modeling. Results: Richness was highest at intermediate levels of understory plant cover, suggesting that both colonization success and competitive exclusion can limit richness in this system. We did not detect a reciprocal positive effect of richness on plant cover. Richness was strongly related to soil nitrogen in the model, with evidence for both a direct negative effect and an indirect non-linear relationship mediated through understory plant cover. Soil organic matter appeared to have a positive influence on understory richness that was independent of soil nitrogen. Richness was lowest where the forest overstory was densest, which can be explained through indirect effects on soil organic matter, soil nitrogen and understory cover. Finally, model results suggest a variety of direct and indirect processes whereby mineral soil properties can influence richness. Conclusions: Understory plant species richness and plant cover in P. ponderosa forests appear to be significantly influenced by soil organic matter and nitrogen, which are, in turn, related to overstory density and composition and mineral soil properties. Thus, soil properties can impose direct and indirect constraints on local species diversity in ponderosa pine forests. ?? IAVS; Opulus Press.

Sensor-model prediction, monitoring and in-situ control of liquid RTM advanced fiber architecture composite processing

NASA Technical Reports Server (NTRS)

Kranbuehl, D.; Kingsley, P.; Hart, S.; Loos, A.; Hasko, G.; Dexter, B.

1992-01-01

In-situ frequency dependent electromagnetic sensors (FDEMS) and the Loos resin transfer model have been used to select and control the processing properties of an epoxy resin during liquid pressure RTM impregnation and cure. Once correlated with viscosity and degree of cure the FDEMS sensor monitors and the RTM processing model predicts the reaction advancement of the resin, viscosity and the impregnation of the fabric. This provides a direct means for predicting, monitoring, and controlling the liquid RTM process in-situ in the mold throughout the fabrication process and the effects of time, temperature, vacuum and pressure. Most importantly, the FDEMS-sensor model system has been developed to make intelligent decisions, thereby automating the liquid RTM process and removing the need for operator direction.

Transient Properties of Probability Distribution for a Markov Process with Size-dependent Additive Noise

NASA Astrophysics Data System (ADS)

Yamada, Yuhei; Yamazaki, Yoshihiro

2018-04-01

This study considered a stochastic model for cluster growth in a Markov process with a cluster size dependent additive noise. According to this model, the probability distribution of the cluster size transiently becomes an exponential or a log-normal distribution depending on the initial condition of the growth. In this letter, a master equation is obtained for this model, and derivation of the distributions is discussed.

Evaluating dedicated and intrinsic models of temporal encoding by varying context

PubMed Central

Spencer, Rebecca M.C.; Karmarkar, Uma; Ivry, Richard B.

2009-01-01

Two general classes of models have been proposed to account for how people process temporal information in the milliseconds range. Dedicated models entail a mechanism in which time is explicitly encoded; examples include clock–counter models and functional delay lines. Intrinsic models, such as state-dependent networks (SDN), represent time as an emergent property of the dynamics of neural processing. An important property of SDN is that the encoding of duration is context dependent since the representation of an interval will vary as a function of the initial state of the network. Consistent with this assumption, duration discrimination thresholds for auditory intervals spanning 100 ms are elevated when an irrelevant tone is presented at varying times prior to the onset of the test interval. We revisit this effect in two experiments, considering attentional issues that may also produce such context effects. The disruptive effect of a variable context was eliminated or attenuated when the intervals between the irrelevant tone and test interval were made dissimilar or the duration of the test interval was increased to 300 ms. These results indicate how attentional processes can influence the perception of brief intervals, as well as point to important constraints for SDN models. PMID:19487188

Modeling and FE Simulation of Quenchable High Strength Steels Sheet Metal Hot Forming Process

NASA Astrophysics Data System (ADS)

Liu, Hongsheng; Bao, Jun; Xing, Zhongwen; Zhang, Dejin; Song, Baoyu; Lei, Chengxi

2011-08-01

High strength steel (HSS) sheet metal hot forming process is investigated by means of numerical simulations. With regard to a reliable numerical process design, the knowledge of the thermal and thermo-mechanical properties is essential. In this article, tensile tests are performed to examine the flow stress of the material HSS 22MnB5 at different strains, strain rates, and temperatures. Constitutive model based on phenomenological approach is developed to describe the thermo-mechanical properties of the material 22MnB5 by fitting the experimental data. A 2D coupled thermo-mechanical finite element (FE) model is developed to simulate the HSS sheet metal hot forming process for U-channel part. The ABAQUS/explicit model is used conduct the hot forming stage simulations, and ABAQUS/implicit model is used for accurately predicting the springback which happens at the end of hot forming stage. Material modeling and FE numerical simulations are carried out to investigate the effect of the processing parameters on the hot forming process. The processing parameters have significant influence on the microstructure of U-channel part. The springback after hot forming stage is the main factor impairing the shape precision of hot-formed part. The mechanism of springback is advanced and verified through numerical simulations and tensile loading-unloading tests. Creep strain is found in the tensile loading-unloading test under isothermal condition and has a distinct effect on springback. According to the numerical and experimental results, it can be concluded that springback is mainly caused by different cooling rats and the nonhomogengeous shrink of material during hot forming process, the creep strain is the main factor influencing the amount of the springback.

Digamma, what next?

NASA Astrophysics Data System (ADS)

Franceschini, Roberto; Giudice, Gian F.; Kamenik, Jernej F.; McCullough, Matthew; Riva, Francesco; Strumia, Alessandro; Torre, Riccardo

2016-07-01

If the 750 GeV resonance in the diphoton channel is confirmed, what are the measurements necessary to infer the properties of the new particle and understand its nature? We address this question in the framework of a single new scalar particle, called digamma ( Ϝ). We describe it by an effective field theory, which allows us to obtain general and model-independent results, and to identify the most useful observables, whose relevance will remain also in model-by-model analyses. We derive full expressions for the leading-order processes and compute rates for higher-order decays, digamma production in association with jets, gauge or Higgs bosons, and digamma pair production. We illustrate how measurements of these higher-order processes can be used to extract couplings, quantum numbers, and properties of the new particle.

Distinct Reward Properties are Encoded via Corticostriatal Interactions

PubMed Central

Smith, David V.; Rigney, Anastasia E.; Delgado, Mauricio R.

2016-01-01

The striatum serves as a critical brain region for reward processing. Yet, understanding the link between striatum and reward presents a challenge because rewards are composed of multiple properties. Notably, affective properties modulate emotion while informative properties help obtain future rewards. We approached this problem by emphasizing affective and informative reward properties within two independent guessing games. We found that both reward properties evoked activation within the nucleus accumbens, a subregion of the striatum. Striatal responses to informative, but not affective, reward properties predicted subsequent utilization of information for obtaining monetary reward. We hypothesized that activation of the striatum may be necessary but not sufficient to encode distinct reward properties. To investigate this possibility, we examined whether affective and informative reward properties were differentially encoded in corticostriatal interactions. Strikingly, we found that the striatum exhibited dissociable connectivity patterns with the ventrolateral prefrontal cortex, with increasing connectivity for affective reward properties and decreasing connectivity for informative reward properties. Our results demonstrate that affective and informative reward properties are encoded via corticostriatal interactions. These findings highlight how corticostriatal systems contribute to reward processing, potentially advancing models linking striatal activation to behavior. PMID:26831208

Distinct Reward Properties are Encoded via Corticostriatal Interactions.

PubMed

Smith, David V; Rigney, Anastasia E; Delgado, Mauricio R

2016-02-02

The striatum serves as a critical brain region for reward processing. Yet, understanding the link between striatum and reward presents a challenge because rewards are composed of multiple properties. Notably, affective properties modulate emotion while informative properties help obtain future rewards. We approached this problem by emphasizing affective and informative reward properties within two independent guessing games. We found that both reward properties evoked activation within the nucleus accumbens, a subregion of the striatum. Striatal responses to informative, but not affective, reward properties predicted subsequent utilization of information for obtaining monetary reward. We hypothesized that activation of the striatum may be necessary but not sufficient to encode distinct reward properties. To investigate this possibility, we examined whether affective and informative reward properties were differentially encoded in corticostriatal interactions. Strikingly, we found that the striatum exhibited dissociable connectivity patterns with the ventrolateral prefrontal cortex, with increasing connectivity for affective reward properties and decreasing connectivity for informative reward properties. Our results demonstrate that affective and informative reward properties are encoded via corticostriatal interactions. These findings highlight how corticostriatal systems contribute to reward processing, potentially advancing models linking striatal activation to behavior.

Thermo-Mechanical Characterization of Friction Stir Spot Welded AA7050 Sheets by Means of Experimental and FEM Analyses

PubMed Central

D’Urso, Gianluca; Giardini, Claudio

2016-01-01

The present study was carried out to evaluate how the friction stir spot welding (FSSW) process parameters affect the temperature distribution in the welding region, the welding forces and the mechanical properties of the joints. The experimental study was performed by means of a CNC machine tool obtaining FSSW lap joints on AA7050 aluminum alloy plates. Three thermocouples were inserted into the samples to measure the temperatures at different distance from the joint axis during the whole FSSW process. Experiments was repeated varying the process parameters, namely rotational speed, axial feed rate and plunging depth. Axial welding forces were measured during the tests using a piezoelectric load cell, while the mechanical properties of the joints were evaluated by executing shear tests on the specimens. The correlation found between process parameters and joints properties, allowed to identify the best technological window. The data collected during the experiments were used to validate a simulation model of the FSSW process, too. The model was set up using a 2D approach for the simulation of a 3D problem, in order to guarantee a very simple and practical solution for achieving results in a very short time. A specific external routine for the calculation of the thermal energy due to friction acting between pin and sheet was developed. An index for the prediction of the joint mechanical properties using the FEM simulations was finally presented and validated. PMID:28773810

Thermo-Mechanical Characterization of Friction Stir Spot Welded AA7050 Sheets by Means of Experimental and FEM Analyses.

PubMed

D'Urso, Gianluca; Giardini, Claudio

2016-08-11

The present study was carried out to evaluate how the friction stir spot welding (FSSW) process parameters affect the temperature distribution in the welding region, the welding forces and the mechanical properties of the joints. The experimental study was performed by means of a CNC machine tool obtaining FSSW lap joints on AA7050 aluminum alloy plates. Three thermocouples were inserted into the samples to measure the temperatures at different distance from the joint axis during the whole FSSW process. Experiments was repeated varying the process parameters, namely rotational speed, axial feed rate and plunging depth. Axial welding forces were measured during the tests using a piezoelectric load cell, while the mechanical properties of the joints were evaluated by executing shear tests on the specimens. The correlation found between process parameters and joints properties, allowed to identify the best technological window. The data collected during the experiments were used to validate a simulation model of the FSSW process, too. The model was set up using a 2D approach for the simulation of a 3D problem, in order to guarantee a very simple and practical solution for achieving results in a very short time. A specific external routine for the calculation of the thermal energy due to friction acting between pin and sheet was developed. An index for the prediction of the joint mechanical properties using the FEM simulations was finally presented and validated.

The cost of uniqueness in groundwater model calibration

NASA Astrophysics Data System (ADS)

Moore, Catherine; Doherty, John

2006-04-01

Calibration of a groundwater model requires that hydraulic properties be estimated throughout a model domain. This generally constitutes an underdetermined inverse problem, for which a solution can only be found when some kind of regularization device is included in the inversion process. Inclusion of regularization in the calibration process can be implicit, for example through the use of zones of constant parameter value, or explicit, for example through solution of a constrained minimization problem in which parameters are made to respect preferred values, or preferred relationships, to the degree necessary for a unique solution to be obtained. The "cost of uniqueness" is this: no matter which regularization methodology is employed, the inevitable consequence of its use is a loss of detail in the calibrated field. This, in turn, can lead to erroneous predictions made by a model that is ostensibly "well calibrated". Information made available as a by-product of the regularized inversion process allows the reasons for this loss of detail to be better understood. In particular, it is easily demonstrated that the estimated value for an hydraulic property at any point within a model domain is, in fact, a weighted average of the true hydraulic property over a much larger area. This averaging process causes loss of resolution in the estimated field. Where hydraulic conductivity is the hydraulic property being estimated, high averaging weights exist in areas that are strategically disposed with respect to measurement wells, while other areas may contribute very little to the estimated hydraulic conductivity at any point within the model domain, this possibly making the detection of hydraulic conductivity anomalies in these latter areas almost impossible. A study of the post-calibration parameter field covariance matrix allows further insights into the loss of system detail incurred through the calibration process to be gained. A comparison of pre- and post-calibration parameter covariance matrices shows that the latter often possess a much smaller spectral bandwidth than the former. It is also demonstrated that, as an inevitable consequence of the fact that a calibrated model cannot replicate every detail of the true system, model-to-measurement residuals can show a high degree of spatial correlation, a fact which must be taken into account when assessing these residuals either qualitatively, or quantitatively in the exploration of model predictive uncertainty. These principles are demonstrated using a synthetic case in which spatial parameter definition is based on pilot points, and calibration is implemented using both zones of piecewise constancy and constrained minimization regularization.

Recent advances in understanding secondary organic aerosol: Implications for global climate forcing

NASA Astrophysics Data System (ADS)

Shrivastava, Manish; Cappa, Christopher D.; Fan, Jiwen; Goldstein, Allen H.; Guenther, Alex B.; Jimenez, Jose L.; Kuang, Chongai; Laskin, Alexander; Martin, Scot T.; Ng, Nga Lee; Petaja, Tuukka; Pierce, Jeffrey R.; Rasch, Philip J.; Roldin, Pontus; Seinfeld, John H.; Shilling, John; Smith, James N.; Thornton, Joel A.; Volkamer, Rainer; Wang, Jian; Worsnop, Douglas R.; Zaveri, Rahul A.; Zelenyuk, Alla; Zhang, Qi

2017-06-01

Anthropogenic emissions and land use changes have modified atmospheric aerosol concentrations and size distributions over time. Understanding preindustrial conditions and changes in organic aerosol due to anthropogenic activities is important because these features (1) influence estimates of aerosol radiative forcing and (2) can confound estimates of the historical response of climate to increases in greenhouse gases. Secondary organic aerosol (SOA), formed in the atmosphere by oxidation of organic gases, represents a major fraction of global submicron-sized atmospheric organic aerosol. Over the past decade, significant advances in understanding SOA properties and formation mechanisms have occurred through measurements, yet current climate models typically do not comprehensively include all important processes. This review summarizes some of the important developments during the past decade in understanding SOA formation. We highlight the importance of some processes that influence the growth of SOA particles to sizes relevant for clouds and radiative forcing, including formation of extremely low volatility organics in the gas phase, acid-catalyzed multiphase chemistry of isoprene epoxydiols, particle-phase oligomerization, and physical properties such as volatility and viscosity. Several SOA processes highlighted in this review are complex and interdependent and have nonlinear effects on the properties, formation, and evolution of SOA. Current global models neglect this complexity and nonlinearity and thus are less likely to accurately predict the climate forcing of SOA and project future climate sensitivity to greenhouse gases. Efforts are also needed to rank the most influential processes and nonlinear process-related interactions, so that these processes can be accurately represented in atmospheric chemistry-climate models.

On the physical properties of volcanic rock masses

NASA Astrophysics Data System (ADS)

Heap, M. J.; Villeneuve, M.; Ball, J. L.; Got, J. L.

2017-12-01

The physical properties (e.g., elastic properties, porosity, permeability, cohesion, strength, amongst others) of volcanic rocks are crucial input parameters for modelling volcanic processes. These parameters, however, are often poorly constrained and there is an apparent disconnect between modellers and those who measure/determine rock and rock mass properties. Although it is well known that laboratory measurements are scale dependent, experimentalists, field volcanologists, and modellers should work together to provide the most appropriate model input parameters. Our pluridisciplinary approach consists of (1) discussing with modellers to better understand their needs, (2) using experimental know-how to build an extensive database of volcanic rock properties, and (3) using geotechnical and field-based volcanological know-how to address scaling issues. For instance, increasing the lengthscale of interest from the laboratory-scale to the volcano-scale will reduce the elastic modulus and strength and increase permeability, but to what extent? How variable are the physical properties of volcanic rocks, and is it appropriate to assume constant, isotropic, and/or homogeneous values for volcanoes? How do alteration, depth, and temperature influence rock physical and mechanical properties? Is rock type important, or do rock properties such as porosity exert a greater control on such parameters? How do we upscale these laboratory-measured properties to rock mass properties using the "fracturedness" of a volcano or volcanic outcrop, and how do we quantify fracturedness? We hope to discuss and, where possible, address some of these issues through active discussion between two (or more) scientific communities.

Ecosystem Restoration: Fact or Fancy?

Treesearch

John A. Stanturf; Callie J. Schweitzer; Stephen H. Schoenholtz; James P. Barnett; Charles K. McMahon; Donald J. Tomszak

1998-01-01

Ecological restoration is generally accepted as the reestablishment of natural ecological processes that produce certain dynamic ecosystem properties of structure, function, and processes. But restore to what? The most frequently used conceptual model for the restoration process is the shift of conditions from some current (degraded) dynamic state to some past dynamic...

Recommended direct simulation Monte Carlo collision model parameters for modeling ionized air transport processes

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

Swaminathan-Gopalan, Krishnan; Stephani, Kelly A., E-mail: ksteph@illinois.edu

2016-02-15

A systematic approach for calibrating the direct simulation Monte Carlo (DSMC) collision model parameters to achieve consistency in the transport processes is presented. The DSMC collision cross section model parameters are calibrated for high temperature atmospheric conditions by matching the collision integrals from DSMC against ab initio based collision integrals that are currently employed in the Langley Aerothermodynamic Upwind Relaxation Algorithm (LAURA) and Data Parallel Line Relaxation (DPLR) high temperature computational fluid dynamics solvers. The DSMC parameter values are computed for the widely used Variable Hard Sphere (VHS) and the Variable Soft Sphere (VSS) models using the collision-specific pairing approach.more » The recommended best-fit VHS/VSS parameter values are provided over a temperature range of 1000-20 000 K for a thirteen-species ionized air mixture. Use of the VSS model is necessary to achieve consistency in transport processes of ionized gases. The agreement of the VSS model transport properties with the transport properties as determined by the ab initio collision integral fits was found to be within 6% in the entire temperature range, regardless of the composition of the mixture. The recommended model parameter values can be readily applied to any gas mixture involving binary collisional interactions between the chemical species presented for the specified temperature range.« less

Indigenous lunar construction materials

NASA Technical Reports Server (NTRS)

Rogers, Wayne; Sture, Stein

1991-01-01

The objectives are the following: to investigate the feasibility of the use of local lunar resources for construction of a lunar base structure; to develop a material processing method and integrate the method with design and construction of a pressurized habitation structure; to estimate specifications of the support equipment necessary for material processing and construction; and to provide parameters for systems models of lunar base constructions, supply, and operations. The topics are presented in viewgraph form and include the following: comparison of various lunar structures; guidelines for material processing methods; cast lunar regolith; examples of cast basalt components; cast regolith process; processing equipment; mechanical properties of cast basalt; material properties and structural design; and future work.

Fractional properties of geophysical field variability on the example of hydrochemical parameters

NASA Astrophysics Data System (ADS)

Shevtsov, Boris; Shevtsova, Olga

2017-10-01

Using the properties of compound Poisson process and its fractional generalizations, statistical models of geophysical fields variability are considered on an example of hydrochemical parameters system. These models are universal to describe objects of different nature and allow us to explain various pulsing regime. Manifestations of non-conservatism in hydrochemical parameters system and the advantages of the system approach in the description of geophysical fields variability are discussed.

Synthesis, Microstructure and Properties of Metallic Materials with Nanoscale Growth Twins

DTIC Science & Technology

2006-11-01

2004: Wu et al, 2005) and austenitic stainless steels (Zhang et al, 2004a; Zhang et al, 2005). However, processing routes to produce nanoscale...mechanical properties (hardness, yield strength, tensile strength) of bulk austenitic stainless steel (304, 310, 316 and 330) are quite similar and...model developed for the formation of growth twins in sputter- deposited austenitic stainless steel thin films (Zhang et al, 2004b). The model predicts

Nonparametric Transfer Function Models

PubMed Central

Liu, Jun M.; Chen, Rong; Yao, Qiwei

2009-01-01

In this paper a class of nonparametric transfer function models is proposed to model nonlinear relationships between ‘input’ and ‘output’ time series. The transfer function is smooth with unknown functional forms, and the noise is assumed to be a stationary autoregressive-moving average (ARMA) process. The nonparametric transfer function is estimated jointly with the ARMA parameters. By modeling the correlation in the noise, the transfer function can be estimated more efficiently. The parsimonious ARMA structure improves the estimation efficiency in finite samples. The asymptotic properties of the estimators are investigated. The finite-sample properties are illustrated through simulations and one empirical example. PMID:20628584

Tension-compression viscoelastic behaviors of the periodontal ligament.

PubMed

Wang, Chen-Ying; Su, Ming-Zen; Chang, Hao-Hueng; Chiang, Yu-Chih; Tao, Shao-Huan; Cheng, Jung-Ho; Fuh, Lih-Jyh; Lin, Chun-Pin

2012-09-01

Although exhaustively studied, the mechanism responsible for tooth support and the mechanical properties of the periodontal ligament (PDL) remain a subject of considerable controversy. In the past, various experimental techniques and theoretical analyses have been employed to tackle this intricate problem. The aim of this study was to investigate the viscoelastic behaviors of the PDL using three-dimensional finite element analysis. Three dentoalveolar complex models were established to simulate the tissue behaviors of the PDL: (1) deviatoric viscoelastic model; (2) volumetric viscoelastic model; and (3) tension-compression volumetric viscoelastic model. These modified models took into consideration the presence of tension and compression along the PDL during both loading and unloading. The inverse parameter identification process was developed to determine the mechanical properties of the PDL from the results of previously reported in vitro and in vivo experiments. The results suggest that the tension-compression volumetric viscoelastic model is a good approximation of normal PDL behavior during the loading-unloading process, and the deviatoric viscoelastic model is a good representation of how a damaged PDL behaves under loading conditions. Moreover, fluid appears to be the main creep source in the PDL. We believe that the biomechanical properties of the PDL established via retrograde calculation in this study can lead to the construction of more accurate extra-oral models and a comprehensive understanding of the biomechanical behavior of the PDL. Copyright © 2012. Published by Elsevier B.V.

A Unified Multi-scale Model for Cross-Scale Evaluation and Integration of Hydrological and Biogeochemical Processes

NASA Astrophysics Data System (ADS)

Liu, C.; Yang, X.; Bailey, V. L.; Bond-Lamberty, B. P.; Hinkle, C.

2013-12-01

Mathematical representations of hydrological and biogeochemical processes in soil, plant, aquatic, and atmospheric systems vary with scale. Process-rich models are typically used to describe hydrological and biogeochemical processes at the pore and small scales, while empirical, correlation approaches are often used at the watershed and regional scales. A major challenge for multi-scale modeling is that water flow, biogeochemical processes, and reactive transport are described using different physical laws and/or expressions at the different scales. For example, the flow is governed by the Navier-Stokes equations at the pore-scale in soils, by the Darcy law in soil columns and aquifer, and by the Navier-Stokes equations again in open water bodies (ponds, lake, river) and atmosphere surface layer. This research explores whether the physical laws at the different scales and in different physical domains can be unified to form a unified multi-scale model (UMSM) to systematically investigate the cross-scale, cross-domain behavior of fundamental processes at different scales. This presentation will discuss our research on the concept, mathematical equations, and numerical execution of the UMSM. Three-dimensional, multi-scale hydrological processes at the Disney Wilderness Preservation (DWP) site, Florida will be used as an example for demonstrating the application of the UMSM. In this research, the UMSM was used to simulate hydrological processes in rooting zones at the pore and small scales including water migration in soils under saturated and unsaturated conditions, root-induced hydrological redistribution, and role of rooting zone biogeochemical properties (e.g., root exudates and microbial mucilage) on water storage and wetting/draining. The small scale simulation results were used to estimate effective water retention properties in soil columns that were superimposed on the bulk soil water retention properties at the DWP site. The UMSM parameterized from smaller scale simulations were then used to simulate coupled flow and moisture migration in soils in saturated and unsaturated zones, surface and groundwater exchange, and surface water flow in streams and lakes at the DWP site under dynamic precipitation conditions. Laboratory measurements of soil hydrological and biogeochemical properties are used to parameterize the UMSM at the small scales, and field measurements are used to evaluate the UMSM.

The coalescent process in models with selection and recombination.

PubMed

Hudson, R R; Kaplan, N L

1988-11-01

The statistical properties of the process describing the genealogical history of a random sample of genes at a selectively neutral locus which is linked to a locus at which natural selection operates are investigated. It is found that the equations describing this process are simple modifications of the equations describing the process assuming that the two loci are completely linked. Thus, the statistical properties of the genealogical process for a random sample at a neutral locus linked to a locus with selection follow from the results obtained for the selected locus. Sequence data from the alcohol dehydrogenase (Adh) region of Drosophila melanogaster are examined and compared to predictions based on the theory. It is found that the spatial distribution of nucleotide differences between Fast and Slow alleles of Adh is very similar to the spatial distribution predicted if balancing selection operates to maintain the allozyme variation at the Adh locus. The spatial distribution of nucleotide differences between different Slow alleles of Adh do not match the predictions of this simple model very well.

Soft sensor development for Mooney viscosity prediction in rubber mixing process based on GMMDJITGPR algorithm

NASA Astrophysics Data System (ADS)

Yang, Kai; Chen, Xiangguang; Wang, Li; Jin, Huaiping

2017-01-01

In rubber mixing process, the key parameter (Mooney viscosity), which is used to evaluate the property of the product, can only be obtained with 4-6h delay offline. It is quite helpful for the industry, if the parameter can be estimate on line. Various data driven soft sensors have been used to prediction in the rubber mixing. However, it always not functions well due to the phase and nonlinear property in the process. The purpose of this paper is to develop an efficient soft sensing algorithm to solve the problem. Based on the proposed GMMD local sample selecting criterion, the phase information is extracted in the local modeling. Using the Gaussian local modeling method within Just-in-time (JIT) learning framework, nonlinearity of the process is well handled. Efficiency of the new method is verified by comparing the performance with various mainstream soft sensors, using the samples from real industrial rubber mixing process.

Markov Decision Process Measurement Model.

PubMed

LaMar, Michelle M

2018-03-01

Within-task actions can provide additional information on student competencies but are challenging to model. This paper explores the potential of using a cognitive model for decision making, the Markov decision process, to provide a mapping between within-task actions and latent traits of interest. Psychometric properties of the model are explored, and simulation studies report on parameter recovery within the context of a simple strategy game. The model is then applied to empirical data from an educational game. Estimates from the model are found to correlate more strongly with posttest results than a partial-credit IRT model based on outcome data alone.

Tree-Structured Infinite Sparse Factor Model

PubMed Central

Zhang, XianXing; Dunson, David B.; Carin, Lawrence

2013-01-01

A tree-structured multiplicative gamma process (TMGP) is developed, for inferring the depth of a tree-based factor-analysis model. This new model is coupled with the nested Chinese restaurant process, to nonparametrically infer the depth and width (structure) of the tree. In addition to developing the model, theoretical properties of the TMGP are addressed, and a novel MCMC sampler is developed. The structure of the inferred tree is used to learn relationships between high-dimensional data, and the model is also applied to compressive sensing and interpolation of incomplete images. PMID:25279389

Effect of Chemical and Physical Properties on the In Vitro Degradation of 3D Printed High Resolution Poly(propylene fumarate) Scaffolds.

PubMed

Walker, Jason M; Bodamer, Emily; Krebs, Olivia; Luo, Yuanyuan; Kleinfehn, Alex; Becker, Matthew L; Dean, David

2017-04-10

Two distinct molecular masses of poly(propylene fumarate) (PPF) are combined with an additive manufacturing process to fabricate highly complex scaffolds possessing controlled chemical properties and porous architecture. Scaffolds were manufactured with two polymer molecular masses and two architecture styles. Degradation was assessed in an accelerated in vitro environment. The purpose of the degradation study is not to model or mimic in vivo degradation, but to efficiently compare the effect of modulating scaffold properties. This is the first study addressing degradation of chain-growth synthesized PPF, a process that allows for considerably more control over molecular mass distribution. It demonstrates that, with greater process control, not only is scaffold fabrication reproducible, but the mechanical properties and degradation kinetics can be tailored by altering the physical properties of the scaffold. This is a clear step forward in using PPF to address unmet medical needs while meeting regulatory demands and ultimately obtaining clinical relevancy.

A prediction model for cognitive performance in health ageing using diffusion tensor imaging with graph theory.

PubMed

Yun, Ruijuan; Lin, Chung-Chih; Wu, Shuicai; Huang, Chu-Chung; Lin, Ching-Po; Chao, Yi-Ping

2013-01-01

In this study, we employed diffusion tensor imaging (DTI) to construct brain structural network and then derive the connection matrices from 96 healthy elderly subjects. The correlation analysis between these topological properties of network based on graph theory and the Cognitive Abilities Screening Instrument (CASI) index were processed to extract the significant network characteristics. These characteristics were then integrated to estimate the models by various machine-learning algorithms to predict user's cognitive performance. From the results, linear regression model and Gaussian processes model showed presented better abilities with lower mean absolute errors of 5.8120 and 6.25 to predict the cognitive performance respectively. Moreover, these extracted topological properties of brain structural network derived from DTI also could be regarded as the bio-signatures for further evaluation of brain degeneration in healthy aged and early diagnosis of mild cognitive impairment (MCI).

Processing and Modeling of Porous Copper Using Sintering Dissolution Process

NASA Astrophysics Data System (ADS)

Salih, Mustafa Abualgasim Abdalhakam

The growth of porous metal has produced materials with improved properties as compared to non-metals and solid metals. Porous metal can be classified as either open cell or closed cell. Open cell allows a fluid media to pass through it. Closed cell is made up of adjacent sealed pores with shared cell walls. Metal foams offer higher strength to weight ratios, increased impact energy absorption, and a greater tolerance to high temperatures and adverse environmental conditions when compared to bulk materials. Copper and its alloys are examples of these, well known for high strength and good mechanical, thermal and electrical properties. In the present study, the porous Cu was made by a powder metallurgy process, using three different space holders, sodium chloride, sodium carbonate and potassium carbonate. Several different samples have been produced, using different ratios of volume fraction. The densities of the porous metals have been measured and compared to the theoretical density calculated using an equation developed for these foams. The porous structure was determined with the removal of spacer materials through sintering process. The sintering process of each spacer material depends on the melting point of the spacer material. Processing, characterization, and mechanical properties were completed. These tests include density measurements, compression tests, computed tomography (CT) and scanning electron microscopy (SEM). The captured morphological images are utilized to generate the object-oriented finite element (OOF) analysis for the porous copper. Porous copper was formed with porosities in the range of 40-66% with density ranges from 3 to 5.2 g/cm3. A study of two different methods to measure porosity was completed. OOF (Object Oriented Finite Elements) is a desktop software application for studying the relationship between the microstructure of a material and its overall mechanical, dielectric, or thermal properties using finite element models based on real or simulated micrographs. OOF provides methods for segmenting images, creating meshes and solving of complex geometries using finite element models, and visualizing 2D results.

Seabed-Structure Interaction: Workshop Report and Recommendations for Future Research Held in Metairie, Louisiana on 5-6 November 1991.

DTIC Science & Technology

1992-02-01

14 Measurements of Sediment Properties and Data Analysis ............................................. 15 object...Object Sensing Methods (Detect/Classification) and (B) Sediment Properties Measurements and Data Analysis . Although important to the understanding of S...characterized by a variety of geological materials, seabed properties, and hydrodynamic processes, the problems of I modeling, analysis , and prediction of S-SI

Space-time-modulated stochastic processes

NASA Astrophysics Data System (ADS)

Giona, Massimiliano

2017-10-01

Starting from the physical problem associated with the Lorentzian transformation of a Poisson-Kac process in inertial frames, the concept of space-time-modulated stochastic processes is introduced for processes possessing finite propagation velocity. This class of stochastic processes provides a two-way coupling between the stochastic perturbation acting on a physical observable and the evolution of the physical observable itself, which in turn influences the statistical properties of the stochastic perturbation during its evolution. The definition of space-time-modulated processes requires the introduction of two functions: a nonlinear amplitude modulation, controlling the intensity of the stochastic perturbation, and a time-horizon function, which modulates its statistical properties, providing irreducible feedback between the stochastic perturbation and the physical observable influenced by it. The latter property is the peculiar fingerprint of this class of models that makes them suitable for extension to generic curved-space times. Considering Poisson-Kac processes as prototypical examples of stochastic processes possessing finite propagation velocity, the balance equations for the probability density functions associated with their space-time modulations are derived. Several examples highlighting the peculiarities of space-time-modulated processes are thoroughly analyzed.

An electronic system for measuring thermophysical properties of wind tunnel models

NASA Technical Reports Server (NTRS)

Corwin, R. R.; Kramer, J. S.

1975-01-01

An electronic system is described which measures the surface temperature of a small portion of the surface of the model or sample at high speeds using an infrared radiometer. This data is processed along with heating rate data from the reference heat gauge in a small computer and prints out the desired thermophysical properties, time, surface temperature, and reference heat rate. This system allows fast and accurate property measurements over thirty temperature increments. The technique, the details of the apparatus, the procedure for making these measurements, and the results of some preliminary tests are presented.

Advances in SiC/SiC Composites for Aerospace Applications

NASA Technical Reports Server (NTRS)

DiCarlo, James A.

2006-01-01

In recent years, supported by a variety of materials development programs, NASA Glenn Research Center has significantly increased the thermostructural capability of SiC/SiC composite materials for high-temperature aerospace applications. These state-of-the-art advances have occurred in every key constituent of the composite: fiber, fiber coating, matrix, and environmental barrier coating, as well as processes for forming the fiber architectures needed for complex-shaped components such as turbine vanes for gas turbine engines. This presentation will briefly elaborate on the nature of these advances in terms of performance data and underlying mechanisms. Based on a list of first-order property goals for typical high-temperature applications, key data from a variety of laboratory tests are presented which demonstrate that the NASA-developed constituent materials and processes do indeed result in SiC/SiC systems with the desired thermal and structural capabilities. Remaining process and microstructural issues for further property enhancement are discussed, as well as on-going approaches at NASA to solve these issues. NASA efforts to develop physics-based property models that can be used not only for component design and life modeling, but also for constituent material and process improvement will also be discussed.

Integration of Basic Knowledge Models for the Simulation of Cereal Foods Processing and Properties.

PubMed

Kristiawan, Magdalena; Kansou, Kamal; Valle, Guy Della

Cereal processing (breadmaking, extrusion, pasting, etc.) covers a range of mechanisms that, despite their diversity, can be often reduced to a succession of two core phenomena: (1) the transition from a divided solid medium (the flour) to a continuous one through hydration, mechanical, biochemical, and thermal actions and (2) the expansion of a continuous matrix toward a porous structure as a result of the growth of bubble nuclei either by yeast fermentation or by water vaporization after a sudden pressure drop. Modeling them is critical for the domain, but can be quite challenging to address with mechanistic approaches relying on partial differential equations. In this chapter we present alternative approaches through basic knowledge models (BKM) that integrate scientific and expert knowledge, and possess operational interest for domain specialists. Using these BKMs, simulations of two cereal foods processes, extrusion and breadmaking, are provided by focusing on the two core phenomena. To support the use by non-specialists, these BKMs are implemented as computer tools, a Knowledge-Based System developed for the modeling of the flour mixing operation or Ludovic ® , a simulation software for twin screw extrusion. They can be applied to a wide domain of compositions, provided that the data on product rheological properties are available. Finally, it is stated that the use of such systems can help food engineers to design cereal food products and predict their texture properties.

Bidirectional Reflectance Modeling of Non-homogeneous Plant Canopies

NASA Technical Reports Server (NTRS)

Norman, J. M.

1984-01-01

Efforts to develop a three dimensional model to predict canopy, bidirectional reflectance for heterogenous plant stands using incident radiation and canopy structural descriptions as inputs are described. Utility programs were developed to cope with the complex output from the 3 dimensional model. In addition an attempt was made to define leaf and soil properties, which are appropriate to the mode, by measuring leaf and soil bidirectional reflectance distribution functions; since almost no data exist on these distributions. In the process it was realized that most models probably are using the wrong leaf spectral properties, and that off-nadir reflectance measurements are difficult to make because of non-Lambertian properties of reference surfaces. Also, in the visible wavebands, rough soil may not be distinguishable from canopies when viewed from above.

Automatic Review of Abstract State Machines by Meta Property Verification

NASA Technical Reports Server (NTRS)

Arcaini, Paolo; Gargantini, Angelo; Riccobene, Elvinia

2010-01-01

A model review is a validation technique aimed at determining if a model is of sufficient quality and allows defects to be identified early in the system development, reducing the cost of fixing them. In this paper we propose a technique to perform automatic review of Abstract State Machine (ASM) formal specifications. We first detect a family of typical vulnerabilities and defects a developer can introduce during the modeling activity using the ASMs and we express such faults as the violation of meta-properties that guarantee certain quality attributes of the specification. These meta-properties are then mapped to temporal logic formulas and model checked for their violation. As a proof of concept, we also report the result of applying this ASM review process to several specifications.

A Complex Network Approach to Distributional Semantic Models

PubMed Central

Utsumi, Akira

2015-01-01

A number of studies on network analysis have focused on language networks based on free word association, which reflects human lexical knowledge, and have demonstrated the small-world and scale-free properties in the word association network. Nevertheless, there have been very few attempts at applying network analysis to distributional semantic models, despite the fact that these models have been studied extensively as computational or cognitive models of human lexical knowledge. In this paper, we analyze three network properties, namely, small-world, scale-free, and hierarchical properties, of semantic networks created by distributional semantic models. We demonstrate that the created networks generally exhibit the same properties as word association networks. In particular, we show that the distribution of the number of connections in these networks follows the truncated power law, which is also observed in an association network. This indicates that distributional semantic models can provide a plausible model of lexical knowledge. Additionally, the observed differences in the network properties of various implementations of distributional semantic models are consistently explained or predicted by considering the intrinsic semantic features of a word-context matrix and the functions of matrix weighting and smoothing. Furthermore, to simulate a semantic network with the observed network properties, we propose a new growing network model based on the model of Steyvers and Tenenbaum. The idea underlying the proposed model is that both preferential and random attachments are required to reflect different types of semantic relations in network growth process. We demonstrate that this model provides a better explanation of network behaviors generated by distributional semantic models. PMID:26295940

Investigating the 3-D Subduction Initiation Processes at Transform Faults and Passive Margins

NASA Astrophysics Data System (ADS)

Peng, H.; Leng, W.

2017-12-01

Studying the processes of subduction initiation is a key for understanding the Wilson cycle and improving the theory of plate tectonics. Previous studies investigated subduction initiation with geological synthesis and geodynamic modeling methods, discovering that subduction intends to initiate at the transform faults close to oceanic arcs, and that its evolutionary processes and surface volcanic expressions are controlled by plate strength. However, these studies are mainly conducted with 2-D models, which cannot deal with lateral heterogeneities of crustal thickness and strength along the plate interfaces. Here we extend the 2-D model to a 3-D parallel subduction model with high computational efficiency. With the new model, we study the dynamic controlling factors, morphology evolutionary processes and surface expressions for subduction initiation with lateral heterogeneities of material properties along transform faults and passive margins. We find that lateral lithospheric heterogeneities control the starting point of the subduction initiation along the newly formed trenches and the propagation speed for the trench formation. New subduction tends to firstly initiate at the property changing point along the transform faults or passive margins. Such finds may be applied to explain the formation process of the Izu-Bonin-Mariana (IBM) subduction zone in the western Pacific and the Scotia subduction zone at the south end of the South America. Our results enhance our understanding for the formation of new trenches and help to provide geodynamic modeling explanations for the observed remnant slabs in the upper mantle and the surface volcanic expressions.

3D Sedimentological and geophysical studies of clastic reservoir analogs: Facies architecture, reservoir properties, and flow behavior within delta front facies elements of the Cretaceous Wall Creek Member, Frontier Formation, Wyoming

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

Christopher D. White

2009-12-21

Significant volumes of oil and gas occur in reservoirs formed by ancient river deltas. This has implications for the spatial distribution of rock types and the variation of transport properties. A between mudstones and sandstones may form baffles that influence productivity and recovery efficiency. Diagenetic processes such as compaction, dissolution, and cementation can also alter flow properties. A better understanding of these properties and improved methods will allow improved reservoir development planning and increased recovery of oil and gas from deltaic reservoirs. Surface exposures of ancient deltaic rocks provide a high-resolution view of variability. Insights gleaned from these exposures canmore » be used to model analogous reservoirs, for which data is sparser. The Frontier Formation in central Wyoming provides an opportunity for high-resolution models. The same rocks exposed in the Tisdale anticline are productive in nearby oil fields. Kilometers of exposure are accessible, and bedding-plane exposures allow use of high-resolution ground-penetrating radar. This study combined geologic interpretations, maps, vertical sections, core data, and ground-penetrating radar to construct geostatistical and flow models. Strata-conforming grids were use to reproduce the observed geometries. A new Bayesian method integrates outcrop, core, and radar amplitude and phase data. The proposed method propagates measurement uncertainty and yields an ensemble of plausible models for calcite concretions. These concretions affect flow significantly. Models which integrate more have different flow responses from simpler models, as demonstrated an exhaustive two-dimensional reference image and in three dimensions. This method is simple to implement within widely available geostatistics packages. Significant volumes of oil and gas occur in reservoirs that are inferred to have been formed by ancient river deltas. This geologic setting has implications for the spatial distribution of rock types (\\Eg sandstones and mudstones) and the variation of transport properties (\\Eg permeability and porosity) within bodies of a particular rock type. Both basin-wide processes such as sea-level change and the autocyclicity of deltaic processes commonly cause deltaic reservoirs to have large variability in rock properties; in particular, alternations between mudstones and sandstones may form baffles and trends in rock body permeability can influence productivity and recovery efficiency. In addition, diagenetic processes such as compaction, dissolution, and cementation can alter the spatial pattern of flow properties. A better understanding of these properties, and improved methods to model the properties and their effects, will allow improved reservoir development planning and increased recovery of oil and gas from deltaic reservoirs. Surface exposures of ancient deltaic rocks provide a high resolution, low uncertainty view of subsurface variability. Patterns and insights gleaned from these exposures can be used to model analogous reservoirs, for which data is much sparser. This approach is particularly attractive when reservoir formations are exposed at the surface. The Frontier Formation in central Wyoming provides an opportunity for high resolution characterization. The same rocks exposed in the vicinity of the Tisdale anticline are productive in nearby oil fields, including Salt Creek. Many kilometers of good-quality exposure are accessible, and the common bedding-plane exposures allow use of shallow-penetration, high-resolution electromagnetic methods known as ground-penetrating radar. This study combined geologic interpretations, maps, vertical sections, core data, and ground-penetrating radar to construct high-resolution geostatistical and flow models for the Wall Creek Member of the Frontier Formation. Stratal-conforming grids were use to reproduce the progradational and aggradational geometries observed in outcrop and radar data. A new, Bayesian method integrates outcrop--derived statistics, core observations of concretions, and radar amplitude and phase data. The proposed method consistently propagates measurement uncertainty through the model-building process, and yields an ensemble of plausible models for diagenetic calcite concretions. These concretions have a statistically significant on flow. Furthermore, neither geostatistical data from the outcrops nor geophysical data from radar is sufficient: models which integrate these data have significantly different flow responses. This was demonstrated both for an exhaustive two-dimensional reference image and in three dimensions, using flow simulations. This project wholly supported one PhD student and part of the education of an additional MS and PhD student. It helped to sponsor 6 refereed articles and 8 conference or similar presentations.« less

The Surface Layer Mechanical Condition and Residual Stress Forming Model in Surface Plastic Deformation Process with the Hardened Body Effect Consideration

NASA Astrophysics Data System (ADS)

Mahalov, M. S.; Blumenstein, V. Yu

2017-10-01

The mechanical condition and residual stresses (RS) research and computational algorithms creation in complex types of loading on the product lifecycle stages relevance is shown. The mechanical state and RS forming finite element model at surface plastic deformation strengthening machining, including technological inheritance effect, is presented. A model feature is the production previous stages obtained transformation properties consideration, as well as these properties evolution during metal particles displacement through the deformation space in the present loading step.

Modeling of Processing-Induced Pore Morphology in an Additively-Manufactured Ti-6Al-4V Alloy

PubMed Central

Kabir, Mohammad Rizviul; Richter, Henning

2017-01-01

A selective laser melting (SLM)-based, additively-manufactured Ti-6Al-4V alloy is prone to the accumulation of undesirable defects during layer-by-layer material build-up. Defects in the form of complex-shaped pores are one of the critical issues that need to be considered during the processing of this alloy. Depending on the process parameters, pores with concave or convex boundaries may occur. To exploit the full potential of additively-manufactured Ti-6Al-4V, the interdependency between the process parameters, pore morphology, and resultant mechanical properties, needs to be understood. By incorporating morphological details into numerical models for micromechanical analyses, an in-depth understanding of how these pores interact with the Ti-6Al-4V microstructure can be gained. However, available models for pore analysis lack a realistic description of both the Ti-6Al-4V grain microstructure, and the pore geometry. To overcome this, we propose a comprehensive approach for modeling and discretizing pores with complex geometry, situated in a polycrystalline microstructure. In this approach, the polycrystalline microstructure is modeled by means of Voronoi tessellations, and the complex pore geometry is approximated by strategically combining overlapping spheres of varied sizes. The proposed approach provides an elegant way to model the microstructure of SLM-processed Ti-6Al-4V containing pores or crack-like voids, and makes it possible to investigate the relationship between process parameters, pore morphology, and resultant mechanical properties in a finite-element-based simulation framework. PMID:28772504

Modeling of Processing-Induced Pore Morphology in an Additively-Manufactured Ti-6Al-4V Alloy.

PubMed

Kabir, Mohammad Rizviul; Richter, Henning

2017-02-08

A selective laser melting (SLM)-based, additively-manufactured Ti-6Al-4V alloy is prone to the accumulation of undesirable defects during layer-by-layer material build-up. Defects in the form of complex-shaped pores are one of the critical issues that need to be considered during the processing of this alloy. Depending on the process parameters, pores with concave or convex boundaries may occur. To exploit the full potential of additively-manufactured Ti-6Al-4V, the interdependency between the process parameters, pore morphology, and resultant mechanical properties, needs to be understood. By incorporating morphological details into numerical models for micromechanical analyses, an in-depth understanding of how these pores interact with the Ti-6Al-4V microstructure can be gained. However, available models for pore analysis lack a realistic description of both the Ti-6Al-4V grain microstructure, and the pore geometry. To overcome this, we propose a comprehensive approach for modeling and discretizing pores with complex geometry, situated in a polycrystalline microstructure. In this approach, the polycrystalline microstructure is modeled by means of Voronoi tessellations, and the complex pore geometry is approximated by strategically combining overlapping spheres of varied sizes. The proposed approach provides an elegant way to model the microstructure of SLM-processed Ti-6Al-4V containing pores or crack-like voids, and makes it possible to investigate the relationship between process parameters, pore morphology, and resultant mechanical properties in a finite-element-based simulation framework.

Identification of Upper and Lower Level Yield Strength in Materials.

PubMed

Valíček, Jan; Harničárová, Marta; Kopal, Ivan; Palková, Zuzana; Kušnerová, Milena; Panda, Anton; Šepelák, Vladimír

2017-08-23

This work evaluates the possibility of identifying mechanical parameters, especially upper and lower yield points, by the analytical processing of specific elements of the topography of surfaces generated with abrasive waterjet technology. We developed a new system of equations, which are connected with each other in such a way that the result of a calculation is a comprehensive mathematical-physical model, which describes numerically as well as graphically the deformation process of material cutting using an abrasive waterjet. The results of our model have been successfully checked against those obtained by means of a tensile test. The main prospect for future applications of the method presented in this article concerns the identification of mechanical parameters associated with the prediction of material behavior. The findings of this study can contribute to a more detailed understanding of the relationships: material properties-tool properties-deformation properties.

Investigation into the influence of build parameters on failure of 3D printed parts

NASA Astrophysics Data System (ADS)

Fornasini, Giacomo

Additive manufacturing, including fused deposition modeling (FDM), is transforming the built world and engineering education. Deep understanding of parts created through FDM technology has lagged behind its adoption in home, work, and academic environments. Properties of parts created from bulk materials through traditional manufacturing are understood well enough to accurately predict their behavior through analytical models. Unfortunately, Additive Manufacturing (AM) process parameters create anisotropy on a scale that fundamentally affects the part properties. Understanding AM process parameters (implemented by program algorithms called slicers) is necessary to predict part behavior. Investigating algorithms controlling print parameters (slicers) revealed stark differences between the generation of part layers. In this work, tensile testing experiments, including a full factorial design, determined that three key factors, width, thickness, infill density, and their interactions, significantly affect the tensile properties of 3D printed test samples.

Dynamical Evolution of Properties for Atom and Field in the Process of Two-Photon Absorption and Emission Between Atomic Levels

NASA Astrophysics Data System (ADS)

Wang, Jian-ming; Xu, Xue-xiang

2018-04-01

Using dressed state method, we cleverly solve the dynamics of atom-field interaction in the process of two-photon absorption and emission between atomic levels. Here we suppose that the atom is initially in the ground state and the optical field is initially in Fock state, coherent state or thermal state, respectively. The properties of the atom, including the population in excited state and ground state, the atom inversion, and the properties for optical field, including the photon number distribution, the mean photon number, the second-order correlation function and the Wigner function, are discussed in detail. We derive their analytical expressions and then make numerical analysis for them. In contrast with Jaynes-Cummings model, some similar results, such as quantum Rabi oscillation, revival and collapse, are also exhibit in our considered model. Besides, some novel nonclassical states are generated.

Negative Binomial Process Count and Mixture Modeling.

PubMed

Zhou, Mingyuan; Carin, Lawrence

2015-02-01

The seemingly disjoint problems of count and mixture modeling are united under the negative binomial (NB) process. A gamma process is employed to model the rate measure of a Poisson process, whose normalization provides a random probability measure for mixture modeling and whose marginalization leads to an NB process for count modeling. A draw from the NB process consists of a Poisson distributed finite number of distinct atoms, each of which is associated with a logarithmic distributed number of data samples. We reveal relationships between various count- and mixture-modeling distributions and construct a Poisson-logarithmic bivariate distribution that connects the NB and Chinese restaurant table distributions. Fundamental properties of the models are developed, and we derive efficient Bayesian inference. It is shown that with augmentation and normalization, the NB process and gamma-NB process can be reduced to the Dirichlet process and hierarchical Dirichlet process, respectively. These relationships highlight theoretical, structural, and computational advantages of the NB process. A variety of NB processes, including the beta-geometric, beta-NB, marked-beta-NB, marked-gamma-NB and zero-inflated-NB processes, with distinct sharing mechanisms, are also constructed. These models are applied to topic modeling, with connections made to existing algorithms under Poisson factor analysis. Example results show the importance of inferring both the NB dispersion and probability parameters.

Modeling Coupled Thermal-Hydrological-Chemical Processes in the Unsaturated Fractured Rock of Yucca Mountain, Nevada: Heterogeneity and Seepage

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

S. Mukhopadhyay; E.L. Donnenthal; N. Spycher

An understanding of processes affecting seepage into emplacement tunnels is needed for correctly predicting the performance of underground radioactive waste repositories. It has been previously estimated that the capillary and vaporization barriers in the unsaturated fractured rock of Yucca Mountain are enough to prevent seepage under present day infiltration conditions. It has also been thought that a substantially elevated infiltration flux will be required to cause seepage after the thermal period is over. While coupled thermal-hydrological-chemical (THC) changes in Yucca Mountain host rock due to repository heating has been previously investigated, those THC models did not incorporate elements of themore » seepage model. In this paper, we combine the THC processes in unsaturated fractured rock with the processes affecting seepage. We observe that the THC processes alter the hydrological properties of the fractured rock through mineral precipitation and dissolution. We show that such alteration in the hydrological properties of the rock often leads to local flow channeling. We conclude that such local flow channeling may result in seepage under certain conditions, even with nonelevated infiltration fluxes.« less

Evaluation of ceramics for stator application: Gas turbine engine report

NASA Technical Reports Server (NTRS)

Trela, W.; Havstad, P. H.

1978-01-01

Current ceramic materials, component fabrication processes, and reliability prediction capability for ceramic stators in an automotive gas turbine engine environment are assessed. Simulated engine duty cycle testing of stators conducted at temperatures up to 1093 C is discussed. Materials evaluated are SiC and Si3N4 fabricated from two near-net-shape processes: slip casting and injection molding. Stators for durability cycle evaluation and test specimens for material property characterization, and reliability prediction model prepared to predict stator performance in the simulated engine environment are considered. The status and description of the work performed for the reliability prediction modeling, stator fabrication, material property characterization, and ceramic stator evaluation efforts are reported.

Characterizing and Assessing a Large-Scale Software Maintenance Organization

NASA Technical Reports Server (NTRS)

Briand, Lionel; Melo, Walcelio; Seaman, Carolyn; Basili, Victor

1995-01-01

One important component of a software process is the organizational context in which the process is enacted. This component is often missing or incomplete in current process modeling approaches. One technique for modeling this perspective is the Actor-Dependency (AD) Model. This paper reports on a case study which used this approach to analyze and assess a large software maintenance organization. Our goal was to identify the approach's strengths and weaknesses while providing practical recommendations for improvement and research directions. The AD model was found to be very useful in capturing the important properties of the organizational context of the maintenance process, and aided in the understanding of the flaws found in this process. However, a number of opportunities for extending and improving the AD model were identified. Among others, there is a need to incorporate quantitative information to complement the qualitative model.

Recovery of lactic acid from the pretreated fermentation broth based on a novel hyper-cross-linked meso-micropore resin: Modeling.

PubMed

Song, Mingkai; Jiao, Pengfei; Qin, Taotao; Jiang, Kangkang; Zhou, Jingwei; Zhuang, Wei; Chen, Yong; Liu, Dong; Zhu, Chenjie; Chen, Xiaochun; Ying, Hanjie; Wu, Jinglan

2017-10-01

An innovative benign process for recovery lactic acid from its fermentation broth is proposed using a novel hyper-cross-linked meso-micropore resin and water as eluent. This work focuses on modeling the competitive adsorption behaviors of glucose, lactic acid and acetic acid ternary mixture and explosion of the adsorption mechanism. The characterization results showed the resin had a large BET surface area and specific pore structure with hydrophobic properties. By analysis of the physicochemical properties of the solutes and the resin, the mechanism of the separation is proposed as hydrophobic effect and size-exclusion. Subsequently three chromatographic models were applied to predict the competitive breakthrough curves of the ternary mixture under different operating conditions. The pore diffusion was the major limiting factor for the adsorption process, which was consistent with the BET results. The novel HD-06 resin can be a good potential adsorbent for the future SMB continuous separation process. Copyright © 2017 Elsevier Ltd. All rights reserved.

Modeling and optimization of red currants vacuum drying process by response surface methodology (RSM).

PubMed

Šumić, Zdravko; Vakula, Anita; Tepić, Aleksandra; Čakarević, Jelena; Vitas, Jasmina; Pavlić, Branimir

2016-07-15

Fresh red currants were dried by vacuum drying process under different drying conditions. Box-Behnken experimental design with response surface methodology was used for optimization of drying process in terms of physical (moisture content, water activity, total color change, firmness and rehydratation power) and chemical (total phenols, total flavonoids, monomeric anthocyanins and ascorbic acid content and antioxidant activity) properties of dried samples. Temperature (48-78 °C), pressure (30-330 mbar) and drying time (8-16 h) were investigated as independent variables. Experimental results were fitted to a second-order polynomial model where regression analysis and analysis of variance were used to determine model fitness and optimal drying conditions. The optimal conditions of simultaneously optimized responses were temperature of 70.2 °C, pressure of 39 mbar and drying time of 8 h. It could be concluded that vacuum drying provides samples with good physico-chemical properties, similar to lyophilized sample and better than conventionally dried sample. Copyright © 2016 Elsevier Ltd. All rights reserved.

Induction heating process of ferromagnetic filled carbon nanotubes based on 3-D model

NASA Astrophysics Data System (ADS)

Wiak, Sławomir; Firych-Nowacka, Anna; Smółka, Krzysztof; Pietrzak, Łukasz; Kołaciński, Zbigniew; Szymański, Łukasz

2017-12-01

Since their discovery by Iijima in 1991 [1], carbon nanotubes have sparked unwavering interest among researchers all over the world. This is due to the unique properties of carbon nanotubes (CNTs). Carbon nanotubes have excellent mechanical and electrical properties with high chemical and thermal stability. In addition, carbon nanotubes have a very large surface area and are hollow inside. This gives a very broad spectrum of nanotube applications, such as in combination with polymers as polymer composites in the automotive, aerospace or textile industries. At present, many methods of nanotube synthesis are known [2, 3, 4, 5, 6]. It is also possible to use carbon nanotubes in biomedical applications [7, 8, 9, 10, 11, 12, 13, 14], including the destruction of cancer cells using iron-filled carbon nanotubes in the hyperthermia process. Computer modelling results of Fe-CNTs induction heating process are presented in the paper. As an object used for computer model creation, Fe-CNTs were synthesized by the authors using CCVD technique.

Incorporating Midbrain Adaptation to Mean Sound Level Improves Models of Auditory Cortical Processing

PubMed Central

Schoppe, Oliver; King, Andrew J.; Schnupp, Jan W.H.; Harper, Nicol S.

2016-01-01

Adaptation to stimulus statistics, such as the mean level and contrast of recently heard sounds, has been demonstrated at various levels of the auditory pathway. It allows the nervous system to operate over the wide range of intensities and contrasts found in the natural world. Yet current standard models of the response properties of auditory neurons do not incorporate such adaptation. Here we present a model of neural responses in the ferret auditory cortex (the IC Adaptation model), which takes into account adaptation to mean sound level at a lower level of processing: the inferior colliculus (IC). The model performs high-pass filtering with frequency-dependent time constants on the sound spectrogram, followed by half-wave rectification, and passes the output to a standard linear–nonlinear (LN) model. We find that the IC Adaptation model consistently predicts cortical responses better than the standard LN model for a range of synthetic and natural stimuli. The IC Adaptation model introduces no extra free parameters, so it improves predictions without sacrificing parsimony. Furthermore, the time constants of adaptation in the IC appear to be matched to the statistics of natural sounds, suggesting that neurons in the auditory midbrain predict the mean level of future sounds and adapt their responses appropriately. SIGNIFICANCE STATEMENT An ability to accurately predict how sensory neurons respond to novel stimuli is critical if we are to fully characterize their response properties. Attempts to model these responses have had a distinguished history, but it has proven difficult to improve their predictive power significantly beyond that of simple, mostly linear receptive field models. Here we show that auditory cortex receptive field models benefit from a nonlinear preprocessing stage that replicates known adaptation properties of the auditory midbrain. This improves their predictive power across a wide range of stimuli but keeps model complexity low as it introduces no new free parameters. Incorporating the adaptive coding properties of neurons will likely improve receptive field models in other sensory modalities too. PMID:26758822

Overpressure generation by load transfer following shale framework weakening due to smectite diagenesis

USGS Publications Warehouse

Lahann, R.W.; Swarbrick, R.E.

2011-01-01

Basin model studies which have addressed the importance of smectite conversion to illite as a source of overpressure in the Gulf of Mexico have principally relied on a single-shale compaction model and treated the smectite reaction as only a fluid-source term. Recent fluid pressure interpretation and shale petrology studies indicate that conversion of bound water to mobile water, dissolution of load-bearing grains, and increased preferred orientation change the compaction properties of the shale. This results in substantial changes in effective stress and fluid pressure. The resulting fluid pressure can be 1500-3000psi higher than pressures interpreted from models based on shallow compaction trends. Shale diagenesis changes the mineralogy, volume, and orientation of the load-bearing grains in the shale as well as the volume of bound water. This process creates a weaker (more compactable) grain framework. When these changes occur without fluid export from the shale, some of the stress is transferred from the grains onto the fluid. Observed relationships between shale density and calculated effective stress in Gulf of Mexico shelf wells confirm these changes in shale properties with depth. Further, the density-effective stress changes cannot be explained by fluid-expansion or fluid-source processes or by prediagenesis compaction, but are consistent with a dynamic diagenetic modification of the shale mineralogy, texture, and compaction properties during burial. These findings support the incorporation of diagenetic modification of compaction properties as part of the fluid pressure interpretation process. ?? 2011 Blackwell Publishing Ltd.

The basis function approach for modeling autocorrelation in ecological data

USGS Publications Warehouse

Hefley, Trevor J.; Broms, Kristin M.; Brost, Brian M.; Buderman, Frances E.; Kay, Shannon L.; Scharf, Henry; Tipton, John; Williams, Perry J.; Hooten, Mevin B.

2017-01-01

Analyzing ecological data often requires modeling the autocorrelation created by spatial and temporal processes. Many seemingly disparate statistical methods used to account for autocorrelation can be expressed as regression models that include basis functions. Basis functions also enable ecologists to modify a wide range of existing ecological models in order to account for autocorrelation, which can improve inference and predictive accuracy. Furthermore, understanding the properties of basis functions is essential for evaluating the fit of spatial or time-series models, detecting a hidden form of collinearity, and analyzing large data sets. We present important concepts and properties related to basis functions and illustrate several tools and techniques ecologists can use when modeling autocorrelation in ecological data.

Formal Analysis of BPMN Models Using Event-B

NASA Astrophysics Data System (ADS)

Bryans, Jeremy W.; Wei, Wei

The use of business process models has gone far beyond documentation purposes. In the development of business applications, they can play the role of an artifact on which high level properties can be verified and design errors can be revealed in an effort to reduce overhead at later software development and diagnosis stages. This paper demonstrates how formal verification may add value to the specification, design and development of business process models in an industrial setting. The analysis of these models is achieved via an algorithmic translation from the de-facto standard business process modeling language BPMN to Event-B, a widely used formal language supported by the Rodin platform which offers a range of simulation and verification technologies.

Representation of Arctic mixed-phase clouds and the Wegener-Bergeron-Findeisen process in climate models: Perspectives from a cloud-resolving study

NASA Astrophysics Data System (ADS)

Fan, Jiwen; Ghan, Steven; Ovchinnikov, Mikhail; Liu, Xiaohong; Rasch, Philip J.; Korolev, Alexei

2011-01-01

Two types of Arctic mixed-phase clouds observed during the ISDAC and M-PACE field campaigns are simulated using a 3-dimensional cloud-resolving model (CRM) with size-resolved cloud microphysics. The modeled cloud properties agree reasonably well with aircraft measurements and surface-based retrievals. Cloud properties such as the probability density function (PDF) of vertical velocity (w), cloud liquid and ice, regimes of cloud particle growth, including the Wegener-Bergeron-Findeisen (WBF) process, and the relationships among properties/processes in mixed-phase clouds are examined to gain insights for improving their representation in General Circulation Models (GCMs). The PDF of the simulated w is well represented by a Gaussian function, validating, at least for arctic clouds, the subgrid treatment used in GCMs. The PDFs of liquid and ice water contents can be approximated by Gamma functions, and a Gaussian function can describe the total water distribution, but a fixed variance assumption should be avoided in both cases. The CRM results support the assumption frequently used in GCMs that mixed phase clouds maintain water vapor near liquid saturation. Thus, ice continues to grow throughout the stratiform cloud but the WBF process occurs in about 50% of cloud volume where liquid and ice co-exist, predominantly in downdrafts. In updrafts, liquid and ice particles grow simultaneously. The relationship between the ice depositional growth rate and cloud ice strongly depends on the capacitance of ice particles. The simplified size-independent capacitance of ice particles used in GCMs could lead to large deviations in ice depositional growth.

Internally electrodynamic particle model: Its experimental basis and its predictions

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

Zheng-Johansson, J. X., E-mail: jxzj@iofpr.or

2010-03-15

The internally electrodynamic (IED) particle model was derived based on overall experimental observations, with the IED process itself being built directly on three experimental facts: (a) electric charges present with all material particles, (b) an accelerated charge generates electromagnetic waves according to Maxwell's equations and Planck energy equation, and (c) source motion produces Doppler effect. A set of well-known basic particle equations and properties become predictable based on first principles solutions for the IED process; several key solutions achieved are outlined, including the de Broglie phase wave, de Broglie relations, Schroedinger equation, mass, Einstein mass-energy relation, Newton's law of gravity,more » single particle self interference, and electromagnetic radiation and absorption; these equations and properties have long been broadly experimentally validated or demonstrated. A conditioned solution also predicts the Doebner-Goldin equation which emerges to represent a form of long-sought quantum wave equation including gravity. A critical review of the key experiments is given which suggests that the IED process underlies the basic particle equations and properties not just sufficiently but also necessarily.« less

Internally electrodynamic particle model: Its experimental basis and its predictions

NASA Astrophysics Data System (ADS)

Zheng-Johansson, J. X.

2010-03-01

The internally electrodynamic (IED) particle model was derived based on overall experimental observations, with the IED process itself being built directly on three experimental facts: (a) electric charges present with all material particles, (b) an accelerated charge generates electromagnetic waves according to Maxwell’s equations and Planck energy equation, and (c) source motion produces Doppler effect. A set of well-known basic particle equations and properties become predictable based on first principles solutions for the IED process; several key solutions achieved are outlined, including the de Broglie phase wave, de Broglie relations, Schrödinger equation, mass, Einstein mass-energy relation, Newton’s law of gravity, single particle self interference, and electromagnetic radiation and absorption; these equations and properties have long been broadly experimentally validated or demonstrated. A conditioned solution also predicts the Doebner-Goldin equation which emerges to represent a form of long-sought quantum wave equation including gravity. A critical review of the key experiments is given which suggests that the IED process underlies the basic particle equations and properties not just sufficiently but also necessarily.

Textured silicon nitride: processing and anisotropic properties

PubMed Central

Zhu, Xinwen; Sakka, Yoshio

2008-01-01

Textured silicon nitride (Si3N4) has been intensively studied over the past 15 years because of its use for achieving its superthermal and mechanical properties. In this review we present the fundamental aspects of the processing and anisotropic properties of textured Si3N4, with emphasis on the anisotropic and abnormal grain growth of β-Si3N4, texture structure and texture analysis, processing methods and anisotropic properties. On the basis of the texturing mechanisms, the processing methods described in this article have been classified into two types: hot-working (HW) and templated grain growth (TGG). The HW method includes the hot-pressing, hot-forging and sinter-forging techniques, and the TGG method includes the cold-pressing, extrusion, tape-casting and strong magnetic field alignment techniques for β-Si3N4 seed crystals. Each processing technique is thoroughly discussed in terms of theoretical models and experimental data, including the texturing mechanisms and the factors affecting texture development. Also, methods of synthesizing the rodlike β-Si3N4 single crystals are presented. Various anisotropic properties of textured Si3N4 and their origins are thoroughly described and discussed, such as hardness, elastic modulus, bending strength, fracture toughness, fracture energy, creep behavior, tribological and wear behavior, erosion behavior, contact damage behavior and thermal conductivity. Models are analyzed to determine the thermal anisotropy by considering the intrinsic thermal anisotropy, degree of orientation and various microstructure factors. Textured porous Si3N4 with a unique microstructure composed of oriented elongated β-Si3N4 and anisotropic pores is also described for the first time, with emphasis on its unique mechanical and thermal-mechanical properties. Moreover, as an important related material, textured α-Sialon is also reviewed, because the presence of elongated α-Sialon grains allows the production of textured α-Sialon using the same methods as those used for textured β-Si3N4 and β-Sialon. PMID:27877995

Transverse Tensile Properties of 3 Dimension-4 Directional Braided Cf/SiC Composite Based on Double-Scale Model

NASA Astrophysics Data System (ADS)

Niu, Xuming; Sun, Zhigang; Song, Yingdong

2017-11-01

In this thesis, a double-scale model for 3 Dimension-4 directional(3D-4d) braided C/SiC composites(CMCs) has been proposed to investigate mechanical properties of it. The double-scale model involves micro-scale which takes fiber/matrix/porosity in fibers tows into consideration and the unit cell scale which considers the 3D-4d braiding structure. Basing on the Micro-optical photographs of composite, we can build a parameterized finite element model that reflects structure of 3D-4d braided composites. The mechanical properties of fiber tows in transverse direction are studied by combining the crack band theory for matrix cracking and cohesive zone model for interface debonding. Transverse tensile process of 3D-4d CMCs can be simulated by introducing mechanical properties of fiber tows into finite element of 3D-4d braided CMCs. Quasi-static tensile tests of 3D-4d braided CMCs have been performed with PWS-100 test system. The predicted tensile stress-strain curve by the double scale model finds good agreement with the experimental results.

Self-Assembly Behavior of Pullulan Abietate

NASA Astrophysics Data System (ADS)

Gradwell, Sheila; Esker, Alan; Glasser, Wolgang; Heinze, Thomas

2003-03-01

Wood is one of nature's most fascinating biological composites due to its toughness and resistance to fracture properties. These properties stem from the self-assembly of cellulose microfibrils in an amorphous matrix of hemicellulose and lignin. In recent years, science has looked to nature for guidance in preparing synthetic materials with desirable physical properties. In order to study the self-assembly process in wood, a model system composed of a polysaccharide, pullulan abietate, and a biomimetic cellulose substrate prepared by the Langmuir-Blodgett technique has been developed. Interfacial tension and surface plasmon resonance measurements used to study the self-assembly process will be discussed for different pullulan derivatives.

Systems cell biology

PubMed Central

Mast, Fred D.; Ratushny, Alexander V.

2014-01-01

Systems cell biology melds high-throughput experimentation with quantitative analysis and modeling to understand many critical processes that contribute to cellular organization and dynamics. Recently, there have been several advances in technology and in the application of modeling approaches that enable the exploration of the dynamic properties of cells. Merging technology and computation offers an opportunity to objectively address unsolved cellular mechanisms, and has revealed emergent properties and helped to gain a more comprehensive and fundamental understanding of cell biology. PMID:25225336

Broadband electromagnetic analysis of compacted kaolin

NASA Astrophysics Data System (ADS)

Bore, Thierry; Wagner, Norman; Cai, Caifang; Scheuermann, Alexander

2017-01-01

The mechanical compaction of soil influences not only the mechanical strength and compressibility but also the hydraulic behavior in terms of hydraulic conductivity and soil suction. At the same time, electric and dielectric parameters are increasingly used to characterize soil and to relate them with mechanic and hydraulic parameters. In the presented study electromagnetic soil properties and suction were measured under defined conditions of standardized compaction tests. The impact of external mechanical stress conditions of nearly pure kaolinite was analyzed on soil suction and broadband electromagnetic soil properties. An experimental procedure was developed and validated to simultaneously determine mechanical, hydraulic and broadband (1 MHz-3 GHz) electromagnetic properties of the porous material. The frequency dependent electromagnetic properties were modeled with a classical mixture equation (advanced Lichtenecker and Rother model, ALRM) and a hydraulic-mechanical-electromagnetic coupling approach was introduced considering water saturation, soil structure (bulk density, porosity), soil suction (pore size distribution, water sorption) as well as electrical conductivity of the aqueous pore solution. Moreover, the relaxation behavior was analyzed with a generalized fractional relaxation model concerning a high-frequency water process and two interface processes extended with an apparent direct current conductivity contribution. The different modeling approaches provide a satisfactory agreement with experimental data for the real part. These results show the potential of broadband electromagnetic approaches for quantitative estimation of the hydraulic state of the soil during densification.

The Contributions Regarding the Use of Microwave to Obtain Modeling Gypsum for Phonic-Absorbent Construction and Orthopedic Materials

NASA Astrophysics Data System (ADS)

Pop, P. A.; Ungur, P. A.; Caraban, A.; Marcu, F.

2009-11-01

The paper has presented some experiments realized at "Congips" Co. Oradea and University of Oradea, regarding of increase machining efficiency and quality for modeling gypsum plaster by using of microwave energy to gypsum ore roast. The elaboration process of microwave energy for modeling gypsum plaster has done on electromagnetic waves properties and specific properties for dielectric materials. Microwaves are radiations of electromagnetic waveform nature, determine by pulsations of electrical-E) and magnetically-H components of electromagnetic wave in interdependence with Maxwell equations. The gypsum ore is calcium sulphate dehydrate (CaSO4ṡ2H2O) using at modeling gypsum plaster fabrication, which is calcium sulphate hemihydrate (CaSO4ṡ1/2H2O), that has behavior of dielectric with losses. The gypsum ore getting in microwave field, in conditions of predictable pressure and temperature has transformed in modeling gypsum plaster, by quick lost of a part from crystallization water. The processing time is very short, which due to a great productivity and machining efficiency, finally of low process cost. All of these recommend continuing the research at pilot station level.

Soft sensor modeling based on variable partition ensemble method for nonlinear batch processes

NASA Astrophysics Data System (ADS)

Wang, Li; Chen, Xiangguang; Yang, Kai; Jin, Huaiping

2017-01-01

Batch processes are always characterized by nonlinear and system uncertain properties, therefore, the conventional single model may be ill-suited. A local learning strategy soft sensor based on variable partition ensemble method is developed for the quality prediction of nonlinear and non-Gaussian batch processes. A set of input variable sets are obtained by bootstrapping and PMI criterion. Then, multiple local GPR models are developed based on each local input variable set. When a new test data is coming, the posterior probability of each best performance local model is estimated based on Bayesian inference and used to combine these local GPR models to get the final prediction result. The proposed soft sensor is demonstrated by applying to an industrial fed-batch chlortetracycline fermentation process.

Boundary Condition Effects on Hillslope Form and Soil Development Along a Climatic Gradient From Semiarid to Hyperarid in Northern Chile

NASA Astrophysics Data System (ADS)

Owen, J. J.; Dietrich, W. E.; Nishiizumi, K.; Bellugi, D.; Amundson, R.

2008-12-01

Modeling the development of hillslopes using mass balance equations has generated many testable hypotheses related to morphology, process rates, and soil properties, however it is only relatively recently that techniques for constraining these models (such as cosmogenic radionuclides) have become commonplace. As such, many hypotheses related to the effects of boundary conditions or climate on process rates and soil properties have been left untested. We selected pairs of hillslopes along a precipitation gradient in northern Chile (24°-30° S) which were either bounded by actively eroding (bedrock-bedded) channels or by stable or aggradational landforms (pediments, colluvial aprons, valley bottoms). For each hillslope we measured soil properties, atmospheric deposition rates, and bedrock denudation rates. We observe significant changes in soil properties with climate: there is a shift from thick, weathered soils in the semiarid south, to the near absence of soil in the arid middle, to salt-rich soils in the hyperarid north. Coincident with these are dramatic changes in the types and rates of processes acting on the soils. We found relatively quick, biotically-driven soil formation and transport in the south, and very slow, salt-driven processes in the north. Additionally, we observe systematic differences between hillslopes of different boundary condition within the same climate zone, such as thicker soils, gentler slopes, and slower erosion rates on hillslopes with a non-eroding boundary versus an eroding boundary. These support general predictions based on hillslope soil mass balance equations and geomorphic transport laws. Using parameters derived from our field data, we attempt to use a mass balance model of hillslope development to explore the effect of changing boundary conditions and/or shifting climate.

Monte-Carlo based Uncertainty Analysis For CO2 Laser Microchanneling Model

NASA Astrophysics Data System (ADS)

Prakash, Shashi; Kumar, Nitish; Kumar, Subrata

2016-09-01

CO2 laser microchanneling has emerged as a potential technique for the fabrication of microfluidic devices on PMMA (Poly-methyl-meth-acrylate). PMMA directly vaporizes when subjected to high intensity focused CO2 laser beam. This process results in clean cut and acceptable surface finish on microchannel walls. Overall, CO2 laser microchanneling process is cost effective and easy to implement. While fabricating microchannels on PMMA using a CO2 laser, the maximum depth of the fabricated microchannel is the key feature. There are few analytical models available to predict the maximum depth of the microchannels and cut channel profile on PMMA substrate using a CO2 laser. These models depend upon the values of thermophysical properties of PMMA and laser beam parameters. There are a number of variants of transparent PMMA available in the market with different values of thermophysical properties. Therefore, for applying such analytical models, the values of these thermophysical properties are required to be known exactly. Although, the values of laser beam parameters are readily available, extensive experiments are required to be conducted to determine the value of thermophysical properties of PMMA. The unavailability of exact values of these property parameters restrict the proper control over the microchannel dimension for given power and scanning speed of the laser beam. In order to have dimensional control over the maximum depth of fabricated microchannels, it is necessary to have an idea of uncertainty associated with the predicted microchannel depth. In this research work, the uncertainty associated with the maximum depth dimension has been determined using Monte Carlo method (MCM). The propagation of uncertainty with different power and scanning speed has been predicted. The relative impact of each thermophysical property has been determined using sensitivity analysis.

Humor Facilitates Text Comprehension: Evidence from Eye Movements

ERIC Educational Resources Information Center

Ferstl, Evelyn C.; Israel, Laura; Putzar, Lisa

2017-01-01

One crucial property of verbal jokes is that the punchline usually contains an incongruency that has to be resolved by updating the situation model representation. In the standard pragmatic model, these processes are considered to require cognitive effort. However, only few studies compared jokes to texts requiring a situation model revision…

Wheat mill stream properties for discrete element method modeling

USDA-ARS?s Scientific Manuscript database

A discrete phase approach based on individual wheat kernel characteristics is needed to overcome the limitations of previous statistical models and accurately predict the milling behavior of wheat. As a first step to develop a discrete element method (DEM) model for the wheat milling process, this s...

Processable high temperature resistant addition type polyimide laminating resins

NASA Technical Reports Server (NTRS)

Serafini, T. T.; Delvigs, P.

1973-01-01

Basic studies that were performed using model compounds to elucidate the polymerization mechanism of the so-called addition-type (A-type) polyimides are reviewed. The fabrication and properties of polyimide/graphite fiber composites using A-type polyimide prepolymers as the matrix are also reviewed. An alternate method for preparing processable A-type polyimides by means of in situ polymerization of monomer reactants (PMR) on the fiber reinforcement is described. The elevated temperature properties of A-type PMR/graphite fiber composites are also presented.

Regional TEC dynamic modeling based on Slepian functions

NASA Astrophysics Data System (ADS)

Sharifi, Mohammad Ali; Farzaneh, Saeed

2015-09-01

In this work, the three-dimensional state of the ionosphere has been estimated by integrating the spherical Slepian harmonic function and Kalman filter. The spherical Slepian harmonic functions have been used to establish the observation equations because of their properties in local modeling. Spherical harmonics are poor choices to represent or analyze geophysical processes without perfect global coverage but the Slepian functions afford spatial and spectral selectivity. The Kalman filter has been utilized to perform the parameter estimation due to its suitable properties in processing the GPS measurements in the real-time mode. The proposed model has been applied to the real data obtained from the ground-based GPS observations across some portion of the IGS network in Europe. Results have been compared with the estimated TECs by the CODE, ESA, IGS centers and IRI-2012 model. The results indicated that the proposed model which takes advantage of the Slepian basis and Kalman filter is efficient and allows for the generation of the near-real-time regional TEC map.

A neural model of motion processing and visual navigation by cortical area MST.

PubMed

Grossberg, S; Mingolla, E; Pack, C

1999-12-01

Cells in the dorsal medial superior temporal cortex (MSTd) process optic flow generated by self-motion during visually guided navigation. A neural model shows how interactions between well-known neural mechanisms (log polar cortical magnification, Gaussian motion-sensitive receptive fields, spatial pooling of motion-sensitive signals and subtractive extraretinal eye movement signals) lead to emergent properties that quantitatively simulate neurophysiological data about MSTd cell properties and psychophysical data about human navigation. Model cells match MSTd neuron responses to optic flow stimuli placed in different parts of the visual field, including position invariance, tuning curves, preferred spiral directions, direction reversals, average response curves and preferred locations for stimulus motion centers. The model shows how the preferred motion direction of the most active MSTd cells can explain human judgments of self-motion direction (heading), without using complex heading templates. The model explains when extraretinal eye movement signals are needed for accurate heading perception, and when retinal input is sufficient, and how heading judgments depend on scene layouts and rotation rates.

Reactive Radial Diffusion Model for the Aging/Sequestration Process

NASA Astrophysics Data System (ADS)

Ginn, T. R.; Basagaoglu, H.; McCoy, B. J.; Scow, K. M.

2001-12-01

A radial diffusion model has been formulated to simulate age-dependent bioavailability of chemical compounds to micro-organisms residing outside (and/or inside) the porous soil particles. Experimental findings in the literature indicate that the sequestration and reduction in bioavailability of contaminants are controlled presumably by the diffusion-limited sorption kinetics and the time-variant desorption process. Here we combine radial-diffusion mass transfer modeling with the exposure-time concept to generate mass-balance equations for the intra- and extra-particle concentrations. The model accomodates reversible sorption kinetics involving sorption time-dependence of the rate coefficients, distinct intra- and extra-particle biodegradation rates; and a dynamic mass interaction between the intra- and extra-particle concentrations arising from the radial diffusion concept. The model explicitly treats multiple particle classes distributed in size and chemical properties in a bulk aquifer or soil volume, which allows the simulation of the sequestration and bioavailability of contaminants in different particle size classes that have distinct diffusion, reaction, and aging properties.

Manufacturing at the Nanoscale. Report of the National Nanotechnology Initiative Workshops, 2002-2004

DTIC Science & Technology

2007-01-01

positioning and assembling? • Do nanoscale properties remain once the nanostructures are integrated up to the microscale? • How do we measure...viii Manufacturing at the Nanoscale 1 1. VISION Employing the novel properties and processes that are associated with the nanoscale—in the...Theory, modeling, and simulation software are being developed to investigate nanoscale material properties and synthesis of macromolecular systems with

Electron Transport Modeling of Molecular Nanoscale Bridges Used in Energy Conversion Schemes

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

Dunietz, Barry D

2016-08-09

The goal of the research program is to reliably describe electron transport and transfer processes at the molecular level. Such insight is essential for improving molecular applications of solar and thermal energy conversion. We develop electronic structure models to study (1) photoinduced electron transfer and transport processes in organic semiconducting materials, and (2) charge and heat transport through molecular bridges. We seek fundamental understanding of key processes, which lead to design new experiments and ultimately to achieve systems with improved properties.

Electrostatic Levitation for Studies of Additive Manufactured Materials

NASA Technical Reports Server (NTRS)

SanSoucie, Michael P.; Rogers, Jan R.; Tramel, Terri

2014-01-01

The electrostatic levitation (ESL) laboratory at NASA's Marshall Space Flight Center is a unique facility for investigators studying high temperature materials. The laboratory boasts two levitators in which samples can be levitated, heated, melted, undercooled, and resolidified. Electrostatic levitation minimizes gravitational effects and allows materials to be studied without contact with a container or instrumentation. The lab also has a high temperature emissivity measurement system, which provides normal spectral and normal total emissivity measurements at use temperature. The ESL lab has been instrumental in many pioneering materials investigations of thermophysical properties, e.g., creep measurements, solidification, triggered nucleation, and emissivity at high temperatures. Research in the ESL lab has already led to the development of advanced high temperature materials for aerospace applications, coatings for rocket nozzles, improved medical and industrial optics, metallic glasses, ablatives for reentry vehicles, and materials with memory. Modeling of additive manufacturing materials processing is necessary for the study of their resulting materials properties. In addition, the modeling of the selective laser melting processes and its materials property predictions are also underway. Unfortunately, there is very little data for the properties of these materials, especially of the materials in the liquid state. Some method to measure thermophysical properties of additive manufacturing materials is necessary. The ESL lab is ideal for these studies. The lab can provide surface tension and viscosity of molten materials, density measurements, emissivity measurements, and even creep strength measurements. The ESL lab can also determine melting temperature, surface temperatures, and phase transition temperatures of additive manufactured materials. This presentation will provide background on the ESL lab and its capabilities, provide an approach to using the ESL in supporting the development and modeling of the selective laser melting process for metals, and provide an overview of the results to date.

Pore network properties of sandstones in a fault damage zone

NASA Astrophysics Data System (ADS)

Bossennec, Claire; Géraud, Yves; Moretti, Isabelle; Mattioni, Luca; Stemmelen, Didier

2018-05-01

The understanding of fluid flow in faulted sandstones is based on a wide range of techniques. These depend on the multi-method determination of petrological and structural features, porous network properties and both spatial and temporal variations and interactions of these features. The question of the multi-parameter analysis on fluid flow controlling properties is addressed for an outcrop damage zone in the hanging wall of a normal fault zone on the western border of the Upper Rhine Graben, affecting the Buntsandstein Group (Early Triassic). Diagenetic processes may alter the original pore type and geometry in fractured and faulted sandstones. Therefore, these may control the ultimate porosity and permeability of the damage zone. The classical model of evolution of hydraulic properties with distance from the major fault core is nuanced here. The hydraulic behavior of the rock media is better described by a pluri-scale model including: 1) The grain scale, where the hydraulic properties are controlled by sedimentary features, the distance from the fracture, and the impact of diagenetic processes. These result in the ultimate porous network characteristics observed. 2) A larger scale, where the structural position and characteristics (density, connectivity) of the fracture corridors are strongly correlated with both geo-mechanical and hydraulic properties within the damage zone.

Optimization of Gas Metal Arc Welding (GMAW) Process for Maximum Ballistic Limit in MIL A46100 Steel Welded All-Metal Armor

NASA Astrophysics Data System (ADS)

Grujicic, M.; Ramaswami, S.; Snipes, J. S.; Yavari, R.; Yen, C.-F.; Cheeseman, B. A.

2015-01-01

Our recently developed multi-physics computational model for the conventional gas metal arc welding (GMAW) joining process has been upgraded with respect to its predictive capabilities regarding the process optimization for the attainment of maximum ballistic limit within the weld. The original model consists of six modules, each dedicated to handling a specific aspect of the GMAW process, i.e., (a) electro-dynamics of the welding gun; (b) radiation-/convection-controlled heat transfer from the electric arc to the workpiece and mass transfer from the filler metal consumable electrode to the weld; (c) prediction of the temporal evolution and the spatial distribution of thermal and mechanical fields within the weld region during the GMAW joining process; (d) the resulting temporal evolution and spatial distribution of the material microstructure throughout the weld region; (e) spatial distribution of the as-welded material mechanical properties; and (f) spatial distribution of the material ballistic limit. In the present work, the model is upgraded through the introduction of the seventh module in recognition of the fact that identification of the optimum GMAW process parameters relative to the attainment of the maximum ballistic limit within the weld region entails the use of advanced optimization and statistical sensitivity analysis methods and tools. The upgraded GMAW process model is next applied to the case of butt welding of MIL A46100 (a prototypical high-hardness armor-grade martensitic steel) workpieces using filler metal electrodes made of the same material. The predictions of the upgraded GMAW process model pertaining to the spatial distribution of the material microstructure and ballistic limit-controlling mechanical properties within the MIL A46100 butt weld are found to be consistent with general expectations and prior observations.

View-tolerant face recognition and Hebbian learning imply mirror-symmetric neural tuning to head orientation

PubMed Central

Leibo, Joel Z.; Liao, Qianli; Freiwald, Winrich A.; Anselmi, Fabio; Poggio, Tomaso

2017-01-01

SUMMARY The primate brain contains a hierarchy of visual areas, dubbed the ventral stream, which rapidly computes object representations that are both specific for object identity and robust against identity-preserving transformations like depth-rotations [1, 2]. Current computational models of object recognition, including recent deep learning networks, generate these properties through a hierarchy of alternating selectivity-increasing filtering and tolerance-increasing pooling operations, similar to simple-complex cells operations [3, 4, 5, 6]. Here we prove that a class of hierarchical architectures and a broad set of biologically plausible learning rules generate approximate invariance to identity-preserving transformations at the top level of the processing hierarchy. However, all past models tested failed to reproduce the most salient property of an intermediate representation of a three-level face-processing hierarchy in the brain: mirror-symmetric tuning to head orientation [7]. Here we demonstrate that one specific biologically-plausible Hebb-type learning rule generates mirror-symmetric tuning to bilaterally symmetric stimuli like faces at intermediate levels of the architecture and show why it does so. Thus the tuning properties of individual cells inside the visual stream appear to result from group properties of the stimuli they encode and to reflect the learning rules that sculpted the information-processing system within which they reside. PMID:27916522

Examining Mechanical Strength Characteristics of Selective Inhibition Sintered HDPE Specimens Using RSM and Desirability Approach

NASA Astrophysics Data System (ADS)

Rajamani, D.; Esakki, Balasubramanian

2017-09-01

Selective inhibition sintering (SIS) is a powder based additive manufacturing (AM) technique to produce functional parts with an inexpensive system compared with other AM processes. Mechanical properties of SIS fabricated parts are of high dependence on various process parameters importantly layer thickness, heat energy, heater feedrate, and printer feedrate. In this paper, examining the influence of these process parameters on evaluating mechanical properties such as tensile and flexural strength using Response Surface Methodology (RSM) is carried out. The test specimens are fabricated using high density polyethylene (HDPE) and mathematical models are developed to correlate the control factors to the respective experimental design response. Further, optimal SIS process parameters are determined using desirability approach to enhance the mechanical properties of HDPE specimens. Optimization studies reveal that, combination of high heat energy, low layer thickness, medium heater feedrate and printer feedrate yielded superior mechanical strength characteristics.

Experimental investigation and constitutive model for lime mudstone.

PubMed

Wang, Junbao; Liu, Xinrong; Zhao, Baoyun; Song, Zhanping; Lai, Jinxing

2016-01-01

In order to investigate the mechanical properties of lime mudstone, conventional triaxial compression tests under different confining pressures (0, 5, 15 and 20 MPa) are performed on lime mudstone samples. The test results show that, from the overall perspective of variation law, the axial peak stress, axial peak strain and elastic modulus of lime mudstone tend to gradually increase with increasing confining pressure. In the range of tested confining pressure, the variations in axial peak stress and elastic modulus with confining pressure can be described with linear functions; while the variation in axial peak strain with confining pressure can be reflected with a power function. To describe the axial stress-strain behavior in failure process of lime mudstone, a new constitutive model is proposed, with the model characteristics analyzed and the parameter determination method put forward. Compared with Wang' model, only one parameter n is added to the new model. The comparison of predicted curves from the model and test data indicates that the new model can preferably simulate the strain softening property of lime mudstone and the axial stress-strain response in rock failure process.

Fracture of Carbon Nanotube - Amorphous Carbon Composites: Molecular Modeling

NASA Technical Reports Server (NTRS)

Jensen, Benjamin D.; Wise, Kristopher E.; Odegard, Gregory M.

2015-01-01

Carbon nanotubes (CNTs) are promising candidates for use as reinforcements in next generation structural composite materials because of their extremely high specific stiffness and strength. They cannot, however, be viewed as simple replacements for carbon fibers because there are key differences between these materials in areas such as handling, processing, and matrix design. It is impossible to know for certain that CNT composites will represent a significant advance over carbon fiber composites before these various factors have been optimized, which is an extremely costly and time intensive process. This work attempts to place an upper bound on CNT composite mechanical properties by performing molecular dynamics simulations on idealized model systems with a reactive forcefield that permits modeling of both elastic deformations and fracture. Amorphous carbon (AC) was chosen for the matrix material in this work because of its structural simplicity and physical compatibility with the CNT fillers. It is also much stiffer and stronger than typical engineering polymer matrices. Three different arrangements of CNTs in the simulation cell have been investigated: a single-wall nanotube (SWNT) array, a multi-wall nanotube (MWNT) array, and a SWNT bundle system. The SWNT and MWNT array systems are clearly idealizations, but the SWNT bundle system is a step closer to real systems in which individual tubes aggregate into large assemblies. The effect of chemical crosslinking on composite properties is modeled by adding bonds between the CNTs and AC. The balance between weakening the CNTs and improving fiber-matrix load transfer is explored by systematically varying the extent of crosslinking. It is, of course, impossible to capture the full range of deformation and fracture processes that occur in real materials with even the largest atomistic molecular dynamics simulations. With this limitation in mind, the simulation results reported here provide a plausible upper limit on achievable CNT composite properties and yield some insight on the influence of processing conditions on the mechanical properties of CNT composites.

Numerical prediction of mechanical properties of Pb-Sn solder alloys containing antimony, bismuth and or silver ternary trace elements

NASA Astrophysics Data System (ADS)

Gadag, Shiva P.; Patra, Susant

2000-12-01

Solder joint interconnects are mechanical means of structural support for bridging the various electronic components and providing electrical contacts and a thermal path for heat dissipation. The functionality of the electronic device often relies on the structural integrity of the solder. The dimensional stability of solder joints is numerically predicted based on their mechanical properties. Algorithms to model the kinetics of dissolution and subsequent growth of intermetallic from the complete knowledge of a single history of time-temperature-reflow profile, by considering equivalent isothermal time intervals, have been developed. The information for dissolution is derived during the heating cycle of reflow and for the growth process from cooling curve of reflow profile. A simple and quick analysis tool to derive tensile stress-strain maps as a function of the reflow temperature of solder and strain rate has been developed by numerical program. The tensile properties are used in modeling thermal strain, thermal fatigue and to predict the overall fatigue life of solder joints. The numerical analysis of the tensile properties as affected by their composition and rate of testing, has been compiled in this paper. A numerical model using constitutive equation has been developed to evaluate the interfacial fatigue crack growth rate. The model can assess the effect of cooling rate, which depends on the level of strain energy release rate. Increasing cooling rate from normalizing to water-quenching, enhanced the fatigue resistance to interfacial crack growth by up to 50% at low strain energy release rate. The increased cooling rates enhanced the fatigue crack growth resistance by surface roughening at the interface of solder joint. This paper highlights salient features of process modeling. Interfacial intermetallic microstructure is affected by cooling rate and thereby affects the mechanical properties.

The Case Against Charge Transfer Interactions in Dissolved Organic Matter Optical Properties

NASA Astrophysics Data System (ADS)

McKay, G.; Korak, J.; Erickson, P. R.; Latch, D. E.; McNeill, K.; Rosario-Ortiz, F.

2017-12-01

The optical properties of dissolved organic matter influence chemical and biological processes in all aquatic ecosystems. Organic matter optical properties have been used by scientists and engineers for decades for remote sensing, in situ monitoring, and characterizing laboratory samples to track dissolved organic carbon concentration and character. However, there is still a lack of understanding of the origin of organic matter optical properties, which could conflict with other empirical fluorescence interpretation methods (e.g. PARAFAC). Organic matter optical properties have been attributed to a charge-transfer model in which donor-acceptor complexes play a primary role. This model was evaluated by measuring the absorbance and fluorescence response of organic matter isolates to perturbations in solvent temperature, viscosity, and polarity, which affect the position and intensity of spectra for known donor-acceptor complexes of organic molecules. Absorbance and fluorescence spectral shape were unaffected by these perturbations, indicating that the distribution of absorbing and emitting species was unchanged. These results call into question the wide applicability of the charge-transfer model for explaining organic matter optical properties and suggest that future research should explore other models for organic matter photophysics.

Identification of sequence motifs significantly associated with antisense activity.

PubMed

McQuisten, Kyle A; Peek, Andrew S

2007-06-07

Predicting the suppression activity of antisense oligonucleotide sequences is the main goal of the rational design of nucleic acids. To create an effective predictive model, it is important to know what properties of an oligonucleotide sequence associate significantly with antisense activity. Also, for the model to be efficient we must know what properties do not associate significantly and can be omitted from the model. This paper will discuss the results of a randomization procedure to find motifs that associate significantly with either high or low antisense suppression activity, analysis of their properties, as well as the results of support vector machine modelling using these significant motifs as features. We discovered 155 motifs that associate significantly with high antisense suppression activity and 202 motifs that associate significantly with low suppression activity. The motifs range in length from 2 to 5 bases, contain several motifs that have been previously discovered as associating highly with antisense activity, and have thermodynamic properties consistent with previous work associating thermodynamic properties of sequences with their antisense activity. Statistical analysis revealed no correlation between a motif's position within an antisense sequence and that sequences antisense activity. Also, many significant motifs existed as subwords of other significant motifs. Support vector regression experiments indicated that the feature set of significant motifs increased correlation compared to all possible motifs as well as several subsets of the significant motifs. The thermodynamic properties of the significantly associated motifs support existing data correlating the thermodynamic properties of the antisense oligonucleotide with antisense efficiency, reinforcing our hypothesis that antisense suppression is strongly associated with probe/target thermodynamics, as there are no enzymatic mediators to speed the process along like the RNA Induced Silencing Complex (RISC) in RNAi. The independence of motif position and antisense activity also allows us to bypass consideration of this feature in the modelling process, promoting model efficiency and reducing the chance of overfitting when predicting antisense activity. The increase in SVR correlation with significant features compared to nearest-neighbour features indicates that thermodynamics alone is likely not the only factor in determining antisense efficiency.

Numerical investigations on the lateral angular co-extrusion of aluminium and steel

NASA Astrophysics Data System (ADS)

Behrens, B.-A.; Klose, C.; Chugreev, A.; Thürer, S. E.; Uhe, J.

2018-05-01

In order to save weight and costs, different materials can be combined within one component. In the novel process chain being developed within the Collaborative Research Centre (CRC) 1153, joined semi-finished workpieces are used to produce hybrid solid components with locally adapted properties. Different materials are joined in an initial step before the forming process takes place. Hereby, the quality of the joining zone is improved by means of the thermo-mechanical treatment during the forming and machining processes. The lateral angular co-extrusion (LACE) approach is used to produce semi-finished workpieces because it allows for the production of coaxial semi-finished products consisting of aluminium and steel. In the further process chain, these semi-finished products are processed into hybrid bearing bushings with locally adapted properties by die forging. In the scope of this work, numerical investigations of the co-extrusion of aluminium-steel compounds were carried out using finite element (FE) simulation in order to examine the influence of the process parameters on the co-extrusion process. For this purpose, the relevant material properties of the aluminium alloy EN AW-6082 were determined experimentally and subsequently implemented in the numerical model. The obtained numerical model was used to study the impact of different ram speeds, press ratios and billet temperatures on the resulting extrusion forces and the material flow. The numerical results have been validated using force-time curves obtained from experimental extrusion tests carried out on a 2.5 MN laboratory extrusion press.

Properties predictive modeling through the concept of a hybrid interphase existing between phases in contact

NASA Astrophysics Data System (ADS)

Portan, D. V.; Papanicolaou, G. C.

2018-02-01

From practical point of view, predictive modeling based on the physics of composite material behavior is wealth generating; by guiding material system selection and process choices, by cutting down on experimentation and associated costs; and by speeding up the time frame from the research stage to the market place. The presence of areas with different properties and the existence of an interphase between them have a pronounced influence on the behavior of a composite system. The Viscoelastic Hybrid Interphase Model (VHIM), considers the existence of a non-homogeneous viscoelastic and anisotropic interphase having properties depended on the degree of adhesion between the two phases in contact. The model applies for any physical/mechanical property (e.g. mechanical, thermal, electrical and/or biomechanical). Knowing the interphasial variation of a specific property one can predict the corresponding macroscopic behavior of the composite. Moreover, the model acts as an algorithm and a two-way approach can be used: (i) phases in contact may be chosen to get the desired properties of the final composite system or (ii) the initial phases in contact determine the final behavior of the composite system, that can be approximately predicted. The VHIM has been proven, amongst others, to be extremely useful in biomaterial designing for improved contact with human tissues.

Heat Transfer during Blanching and Hydrocooling of Broccoli Florets.

PubMed

Iribe-Salazar, Rosalina; Caro-Corrales, José; Hernández-Calderón, Óscar; Zazueta-Niebla, Jorge; Gutiérrez-Dorado, Roberto; Carrazco-Escalante, Marco; Vázquez-López, Yessica

2015-12-01

The objective of this work was to simulate heat transfer during blanching (90 °C) and hydrocooling (5 °C) of broccoli florets (Brassica oleracea L. Italica) and to evaluate the impact of these processes on the physicochemical and nutrimental quality properties. Thermophysical properties (thermal conductivity [line heat source], specific heat capacity [differential scanning calorimetry], and bulk density [volume displacement]) of stem and inflorescence were measured as a function of temperature (5, 10, 20, 40, 60, and 80 °C). The activation energy and the frequency factor (Arrhenius model) of these thermophysical properties were calculated. A 3-dimensional finite element model was developed to predict the temperature history at different points inside the product. Comparison of the theoretical and experimental temperature histories was carried out. Quality parameters (firmness, total color difference, and vitamin C content) and peroxidase activity were measured. The satisfactory validation of the finite element model allows the prediction of temperature histories and profiles under different process conditions, which could lead to an eventual optimization aimed to minimize the nutritional and sensorial losses in broccoli florets. © 2015 Institute of Food Technologists®

Determining heat loss from the surface of polymer films via modeling of experimental fluorescence thermometry

NASA Astrophysics Data System (ADS)

Firestone, Gabriel; Bochinski, Jason; Meth, Jeffrey; Clarke, Laura

Understanding of the heat transfer characteristics of a polymer during processing is critical to predicting and controlling the resulting properties and has been studied extensively in injection molding. As new methodologies for polymer processing are developed, such as photothermal heating, it is important to build an understanding of how heat transfer properties change under these novel conditions. By combining theoretical and experimental approaches, the thermal properties of photothermally heated polymer films were measured. The key idea is that by measuring the steady state temperature profile of a spot heated polymer film via a fluorescence probe (the temperature versus distance from the heated region) and fitting to a theoretical model, heat transfer coefficients can be extracted. We apply this approach to three different polymer systems, crosslinked epoxy, poly(methyl methacrylate) and poly(ethylene oxide) thin films with a range of thicknesses, under different heating laser intensities and with different resultant temperatures. We will discuss the resultant trends and extension of the model beyond a simple spot heating configuration. Support from National Science Foundation CMMI-1069108 and CMMI-1462966.

Effect of feed moisture, extrusion temperature and screw speed on properties of soy white flakes based aquafeed: a response surface analysis.

PubMed

Singh, Sushil K; Muthukumarappan, Kasiviswanathan

2016-04-01

Soy white flakes (SWF) is an intermediate product during soy bean processing. It is an untoasted inexpensive product and contains around 51% of crude protein. It can be a potential source of protein to replace fish meal for developing aquafeed. The extrusion process is versatile and is used for the development of aquafeed. Our objective was to study the effects of inclusion of SWF (up to 50%) and other extrusion processing parameters such as barrel temperature and screw speed on the properties of aquafeed extrudates using a single-screw extruder. Extrudate properties, including pellet durability index, bulk density, water absorption and solubility indices and mass flow rate, were significantly (P < 0.05) affected by the process variables. SWF was the most significant variable with quadratic effects on most of the properties. Increasing temperature and screw speed resulted in increase in durability and mass flow rate of extrudates. Response surface regression models were established to correlate the properties of extrudates to the process variables. SWF was used as an alternative protein source of fish meal. Our study shows that aquafeed with high durability, lower bulk density and lower water absorption and higher solubility indices can be obtained by adding SWF up to 40%. © 2015 Society of Chemical Industry.

Understanding Surface Adhesion in Nature: A Peeling Model.

PubMed

Gu, Zhen; Li, Siheng; Zhang, Feilong; Wang, Shutao

2016-07-01

Nature often exhibits various interesting and unique adhesive surfaces. The attempt to understand the natural adhesion phenomena can continuously guide the design of artificial adhesive surfaces by proposing simplified models of surface adhesion. Among those models, a peeling model can often effectively reflect the adhesive property between two surfaces during their attachment and detachment processes. In the context, this review summarizes the recent advances about the peeling model in understanding unique adhesive properties on natural and artificial surfaces. It mainly includes four parts: a brief introduction to natural surface adhesion, the theoretical basis and progress of the peeling model, application of the peeling model, and finally, conclusions. It is believed that this review is helpful to various fields, such as surface engineering, biomedicine, microelectronics, and so on.

Validation of mathematical model for CZ process using small-scale laboratory crystal growth furnace

NASA Astrophysics Data System (ADS)

Bergfelds, Kristaps; Sabanskis, Andrejs; Virbulis, Janis

2018-05-01

The present material is focused on the modelling of small-scale laboratory NaCl-RbCl crystal growth furnace. First steps towards fully transient simulations are taken in the form of stationary simulations that deal with the optimization of material properties to match the model to experimental conditions. For this purpose, simulation software primarily used for the modelling of industrial-scale silicon crystal growth process was successfully applied. Finally, transient simulations of the crystal growth are presented, giving a sufficient agreement to experimental results.

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.

Rapid Automated Aircraft Simulation Model Updating from Flight Data

NASA Technical Reports Server (NTRS)

Brian, Geoff; Morelli, Eugene A.

2011-01-01

Techniques to identify aircraft aerodynamic characteristics from flight measurements and compute corrections to an existing simulation model of a research aircraft were investigated. The purpose of the research was to develop a process enabling rapid automated updating of aircraft simulation models using flight data and apply this capability to all flight regimes, including flight envelope extremes. The process presented has the potential to improve the efficiency of envelope expansion flight testing, revision of control system properties, and the development of high-fidelity simulators for pilot training.

Exponential order statistic models of software reliability growth

NASA Technical Reports Server (NTRS)

Miller, D. R.

1985-01-01

Failure times of a software reliabilty growth process are modeled as order statistics of independent, nonidentically distributed exponential random variables. The Jelinsky-Moranda, Goel-Okumoto, Littlewood, Musa-Okumoto Logarithmic, and Power Law models are all special cases of Exponential Order Statistic Models, but there are many additional examples also. Various characterizations, properties and examples of this class of models are developed and presented.

Modeling the reduction in soil loss due to soil armouring caused by rainfall erosion

USDA-ARS?s Scientific Manuscript database

Surface soil properties can change as a result of soil disturbances, erosion, or deposition. One process that can significantly change surface soil properties is soil armouring, which is the selective removal of finer particles by rill or interrill erosion, leaving an armoured layer of coarser parti...

Shale Gas Well, Hydraulic Fracturing, and Formation Data to Support Modeling of Gas and Water Flow in Shale Formations

NASA Astrophysics Data System (ADS)

Edwards, Ryan W. J.; Celia, Michael A.

2018-04-01

The potential for shale gas development and hydraulic fracturing to cause subsurface water contamination has prompted a number of modeling studies to assess the risk. A significant impediment for conducting robust modeling is the lack of comprehensive publicly available information and data about the properties of shale formations, shale wells, the process of hydraulic fracturing, and properties of the hydraulic fractures. We have collated a substantial amount of these data that are relevant for modeling multiphase flow of water and gas in shale gas formations. We summarize these data and their sources in tabulated form.

The Case Against Charge Transfer Interactions in Dissolved Organic Matter Photophysics.

PubMed

McKay, Garrett; Korak, Julie A; Erickson, Paul R; Latch, Douglas E; McNeill, Kristopher; Rosario-Ortiz, Fernando L

2018-01-16

The optical properties of dissolved organic matter influence chemical and biological processes in all aquatic ecosystems. Dissolved organic matter optical properties have been attributed to a charge-transfer model in which donor-acceptor complexes play a primary role. This model was evaluated by measuring the absorbance and fluorescence response of organic matter isolates to changes in solvent temperature, viscosity, and polarity, which affect the position and intensity of spectra for known donor-acceptor complexes of organic molecules. Absorbance and fluorescence spectral shape were largely unaffected by these changes, indicating that the distribution of absorbing and emitting species was unchanged. Overall, these results call into question the wide applicability of the charge-transfer model for explaining organic matter optical properties and suggest that future research should explore other models for dissolved organic matter photophysics.

Digital Materials - Evaluation of the Possibilities of using Selected Hyperelastic Models to Describe Constitutive Relations

NASA Astrophysics Data System (ADS)

Mańkowski, J.; Lipnicki, J.

2017-08-01

The authors tried to identify the parameters of numerical models of digital materials, which are a kind of composite resulting from the manufacture of the product in 3D printers. With the arrangement of several heads of the printer, the new material can result from mixing of materials with radically different properties, during the process of producing single layer of the product. The new material has properties dependent on the base materials properties and their proportions. Digital materials tensile characteristics are often non-linear and qualify to be described by hyperelastic materials models. The identification was conducted based on the results of tensile tests models, its various degrees coefficients of the polynomials to various degrees coefficients of the polynomials. The Drucker's stability criterion was also examined. Fourteen different materials were analyzed.

A process-based inventory model for landfill CH4 emissions inclusive of seasonal soil microclimate and CH4 oxidation

USDA-ARS?s Scientific Manuscript database

We have developed and field-validated an annual inventory model for California landfill CH4 emissions that incorporates both site-specific soil properties and soil microclimate modeling coupled to 0.5o scale global climatic models. Based on 1-D diffusion, CALMIM (California Landfill Methane Inventor...

Multiscale Micromechanical Modeling of Polymer/Clay Nanocomposites and the Effective Clay Particle

NASA Astrophysics Data System (ADS)

Sheng, Nuo; Boyce, Mary C.; Parks, David M.; Manovitch, Oleg; Rutledge, Gregory C.; Lee, Hojun; McKinley, Gareth H.

2003-03-01

Polymer/clay nanocomposites have been observed to exhibit enhanced mechanical properties at low weight fractions (Wp) of clay. Continuum-based composite modeling reveals that the enhanced properties are strongly dependent on particular features of the second-phase ¡°particles¡+/-; in particular, the particle volume fraction (fp), the particle aspect ratio (L/t), and the ratio of particle mechanical properties to those of the matrix. However, these important aspects of as-processed nanoclay composites have yet to be consistently and accurately defined. A multiscale modeling strategy was developed to account for the hierarchical morphology of the nanocomposite: at a lengthscale of thousands of microns, the structure is one of high aspect ratio particles within a matrix; at the lengthscale of microns, the clay particle structure is either (a) exfoliated clay sheets of nanometer level thickness or (b) stacks of parallel clay sheets separated from one another by interlayer galleries of nanometer level height. Here, quantitative structural parameters extracted from XRD patterns and TEM micrographs are used to determine geometric features of the as-processed clay ¡°particles¡+/-, including L/t and the ratio of fp to Wp. These geometric features, together with estimates of silicate lamina stiffness obtained from molecular dynamics simulations, provide a basis for modeling effective mechanical properties of the clay particle. The structure-based predictions of the macroscopic elastic modulus of the nanocomposite as a function of clay weight fraction are in excellent agreement with experimental data. The adopted methodology offers promise for study of related properties in polymer/clay nanocomposites.

Computational study of textured ferroelectric polycrystals: Dielectric and piezoelectric properties of template-matrix composites

NASA Astrophysics Data System (ADS)

Zhou, Jie E.; Yan, Yongke; Priya, Shashank; Wang, Yu U.

2017-01-01

Quantitative relationships between processing, microstructure, and properties in textured ferroelectric polycrystals and the underlying responsible mechanisms are investigated by phase field modeling and computer simulation. This study focuses on three important aspects of textured ferroelectric ceramics: (i) grain microstructure evolution during templated grain growth processing, (ii) crystallographic texture development as a function of volume fraction and seed size of the templates, and (iii) dielectric and piezoelectric properties of the obtained template-matrix composites of textured polycrystals. Findings on the third aspect are presented here, while an accompanying paper of this work reports findings on the first two aspects. In this paper, the competing effects of crystallographic texture and template seed volume fraction on the dielectric and piezoelectric properties of ferroelectric polycrystals are investigated. The phase field model of ferroelectric composites consisting of template seeds embedded in matrix grains is developed to simulate domain evolution, polarization-electric field (P-E), and strain-electric field (ɛ-E) hysteresis loops. The coercive field, remnant polarization, dielectric permittivity, piezoelectric coefficient, and dissipation factor are studied as a function of grain texture and template seed volume fraction. It is found that, while crystallographic texture significantly improves the polycrystal properties towards those of single crystals, a higher volume fraction of template seeds tends to decrease the electromechanical properties, thus canceling the advantage of ferroelectric polycrystals textured by templated grain growth processing. This competing detrimental effect is shown to arise from the composite effect, where the template phase possesses material properties inferior to the matrix phase, causing mechanical clamping and charge accumulation at inter-phase interfaces between matrix and template inclusions. The computational results are compared with complementary experiments, where good agreement is obtained.

A Comparative study of two RVE modelling methods for chopped carbon fiber SMC

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

Chen, Zhangxing; Li, Yi; Shao, Yimin

To achieve vehicle light-weighting, the chopped carbon fiber sheet molding compound (SMC) is identified as a promising material to replace metals. However, there are no effective tools and methods to predict the mechanical property of the chopped carbon fiber SMC due to the high complexity in microstructure features and the anisotropic properties. In this paper, the Representative Volume Element (RVE) approach is used to model the SMC microstructure. Two modeling methods, the Voronoi diagram-based method and the chip packing method, are developed for material RVE property prediction. The two methods are compared in terms of the predicted elastic modulus andmore » the predicted results are validated using the Digital Image Correlation (DIC) tensile test results. Furthermore, the advantages and shortcomings of these two methods are discussed in terms of the required input information and the convenience of use in the integrated processing-microstructure-property analysis.« less

Fractional Generalizations of Maxwell and Kelvin-Voigt Models for Biopolymer Characterization

PubMed Central

Jóźwiak, Bertrand; Orczykowska, Magdalena; Dziubiński, Marek

2015-01-01

The paper proposes a fractional generalization of the Maxwell and Kelvin-Voigt rheological models for a description of dynamic behavior of biopolymer materials. It was found that the rheological models of Maxwell-type do not work in the case of modeling of viscoelastic solids, and the model which significantly better describes the nature of changes in rheological properties of such media is the modified fractional Kelvin-Voigt model with two built-in springpots (MFKVM2). The proposed model was used to describe the experimental data from the oscillatory and creep tests of 3% (w/v) kuzu starch pastes, and to determine the values of their rheological parameters as a function of pasting time. These parameters provide a lot of additional information about structure and viscoelastic properties of the medium in comparison to the classical analysis of dynamic curves G’ and G” and shear creep compliance J(t). It allowed for a comprehensive description of a wide range of properties of kuzu starch pastes, depending on the conditions of pasting process. PMID:26599756

A Harris-Todaro Agent-Based Model to Rural-Urban Migration

NASA Astrophysics Data System (ADS)

Espíndola, Aquino L.; Silveira, Jaylson J.; Penna, T. J. P.

2006-09-01

The Harris-Todaro model of the rural-urban migration process is revisited under an agent-based approach. The migration of the workers is interpreted as a process of social learning by imitation, formalized by a computational model. By simulating this model, we observe a transitional dynamics with continuous growth of the urban fraction of overall population toward an equilibrium. Such an equilibrium is characterized by stabilization of rural-urban expected wages differential (generalized Harris-Todaro equilibrium condition), urban concentration and urban unemployment. These classic results obtained originally by Harris and Todaro are emergent properties of our model.

Effect of thermal and mechanical parameter’s damage numerical simulation cycling effects on defects in hot metal forming processes

NASA Astrophysics Data System (ADS)

El Amri, Abdelouahid; el yakhloufi Haddou, Mounir; Khamlichi, Abdellatif

2017-10-01

Damage mechanisms in hot metal forming processes are accelerated by mechanical stresses arising during Thermal and mechanical properties variations, because it consists of the materials with different thermal and mechanical loadings and swelling coefficients. In this work, 3D finite element models (FEM) are developed to simulate the effect of Temperature and the stresses on the model development, using a general purpose FE software ABAQUS. Explicit dynamic analysis with coupled Temperature displacement procedure is used for a model. The purpose of this research was to study the thermomechanical damage mechanics in hot forming processes. The important process variables and the main characteristics of various hot forming processes will also be discussed.

From conceptual modeling to a map

NASA Astrophysics Data System (ADS)

Gotlib, Dariusz; Olszewski, Robert

2018-05-01

Nowadays almost every map is a component of the information system. Design and production of maps requires the use of specific rules for modeling information systems: conceptual, application and data modelling. While analyzing various stages of cartographic modeling the authors ask the question: at what stage of this process a map occurs. Can we say that the "life of the map" begins even before someone define its form of presentation? This question is particularly important at the time of exponentially increasing number of new geoinformation products. During the analysis of the theory of cartography and relations of the discipline to other fields of knowledge it has been attempted to define a few properties of cartographic modeling which distinguish the process from other methods of spatial modeling. Assuming that the map is a model of reality (created in the process of cartographic modeling supported by domain-modeling) the article proposes an analogy of the process of cartographic modeling to the scheme of conceptual modeling presented in ISO 19101 standard.

Spectral imaging toolbox: segmentation, hyperstack reconstruction, and batch processing of spectral images for the determination of cell and model membrane lipid order.

PubMed

Aron, Miles; Browning, Richard; Carugo, Dario; Sezgin, Erdinc; Bernardino de la Serna, Jorge; Eggeling, Christian; Stride, Eleanor

2017-05-12

Spectral imaging with polarity-sensitive fluorescent probes enables the quantification of cell and model membrane physical properties, including local hydration, fluidity, and lateral lipid packing, usually characterized by the generalized polarization (GP) parameter. With the development of commercial microscopes equipped with spectral detectors, spectral imaging has become a convenient and powerful technique for measuring GP and other membrane properties. The existing tools for spectral image processing, however, are insufficient for processing the large data sets afforded by this technological advancement, and are unsuitable for processing images acquired with rapidly internalized fluorescent probes. Here we present a MATLAB spectral imaging toolbox with the aim of overcoming these limitations. In addition to common operations, such as the calculation of distributions of GP values, generation of pseudo-colored GP maps, and spectral analysis, a key highlight of this tool is reliable membrane segmentation for probes that are rapidly internalized. Furthermore, handling for hyperstacks, 3D reconstruction and batch processing facilitates analysis of data sets generated by time series, z-stack, and area scan microscope operations. Finally, the object size distribution is determined, which can provide insight into the mechanisms underlying changes in membrane properties and is desirable for e.g. studies involving model membranes and surfactant coated particles. Analysis is demonstrated for cell membranes, cell-derived vesicles, model membranes, and microbubbles with environmentally-sensitive probes Laurdan, carboxyl-modified Laurdan (C-Laurdan), Di-4-ANEPPDHQ, and Di-4-AN(F)EPPTEA (FE), for quantification of the local lateral density of lipids or lipid packing. The Spectral Imaging Toolbox is a powerful tool for the segmentation and processing of large spectral imaging datasets with a reliable method for membrane segmentation and no ability in programming required. The Spectral Imaging Toolbox can be downloaded from https://uk.mathworks.com/matlabcentral/fileexchange/62617-spectral-imaging-toolbox .

Dissolution of covalent adaptable network polymers in organic solvent

NASA Astrophysics Data System (ADS)

Yu, Kai; Yang, Hua; Dao, Binh H.; Shi, Qian; Yakacki, Christopher M.

2017-12-01

It was recently reported that thermosetting polymers can be fully dissolved in a proper organic solvent utilizing a bond-exchange reaction (BER), where small molecules diffuse into the polymer, break the long polymer chains into short segments, and eventually dissolve the network when sufficient solvent is provided. The solvent-assisted dissolution approach was applied to fully recycle thermosets and their fiber composites. This paper presents the first multi-scale modeling framework to predict the dissolution kinetics and mechanics of thermosets in organic solvent. The model connects the micro-scale network dynamics with macro-scale material properties: in the micro-scale, a model is developed based on the kinetics of BERs to describe the cleavage rate of polymer chains and evolution of chain segment length during the dissolution. The micro-scale model is then fed into a continuum-level model with considerations of the transportation of solvent molecules and chain segments in the system. The model shows good prediction on conversion rate of functional groups, degradation of network mechanical properties, and dissolution rate of thermosets during the dissolution. It identifies the underlying kinetic factors governing the dissolution process, and reveals the influence of different material and processing variables on the dissolution process, such as time, temperature, catalyst concentration, and chain length between cross-links.

Synchronous versus asynchronous modeling of gene regulatory networks.

PubMed

Garg, Abhishek; Di Cara, Alessandro; Xenarios, Ioannis; Mendoza, Luis; De Micheli, Giovanni

2008-09-01

In silico modeling of gene regulatory networks has gained some momentum recently due to increased interest in analyzing the dynamics of biological systems. This has been further facilitated by the increasing availability of experimental data on gene-gene, protein-protein and gene-protein interactions. The two dynamical properties that are often experimentally testable are perturbations and stable steady states. Although a lot of work has been done on the identification of steady states, not much work has been reported on in silico modeling of cellular differentiation processes. In this manuscript, we provide algorithms based on reduced ordered binary decision diagrams (ROBDDs) for Boolean modeling of gene regulatory networks. Algorithms for synchronous and asynchronous transition models have been proposed and their corresponding computational properties have been analyzed. These algorithms allow users to compute cyclic attractors of large networks that are currently not feasible using existing software. Hereby we provide a framework to analyze the effect of multiple gene perturbation protocols, and their effect on cell differentiation processes. These algorithms were validated on the T-helper model showing the correct steady state identification and Th1-Th2 cellular differentiation process. The software binaries for Windows and Linux platforms can be downloaded from http://si2.epfl.ch/~garg/genysis.html.

Mathematical modeling of the integrated process of mercury bioremediation in the industrial bioreactor.

PubMed

Głuszcz, Paweł; Petera, Jerzy; Ledakowicz, Stanisław

2011-03-01

The mathematical model of the integrated process of mercury contaminated wastewater bioremediation in a fixed-bed industrial bioreactor is presented. An activated carbon packing in the bioreactor plays the role of an adsorbent for ionic mercury and at the same time of a carrier material for immobilization of mercury-reducing bacteria. The model includes three basic stages of the bioremediation process: mass transfer in the liquid phase, adsorption of mercury onto activated carbon and ionic mercury bioreduction to Hg(0) by immobilized microorganisms. Model calculations were verified using experimental data obtained during the process of industrial wastewater bioremediation in the bioreactor of 1 m³ volume. It was found that the presented model reflects the properties of the real system quite well. Numerical simulation of the bioremediation process confirmed the experimentally observed positive effect of the integration of ionic mercury adsorption and bioreduction in one apparatus.

The Coalescent Process in Models with Selection

PubMed Central

Kaplan, N. L.; Darden, T.; Hudson, R. R.

1988-01-01

Statistical properties of the process describing the genealogical history of a random sample of genes are obtained for a class of population genetics models with selection. For models with selection, in contrast to models without selection, the distribution of this process, the coalescent process, depends on the distribution of the frequencies of alleles in the ancestral generations. If the ancestral frequency process can be approximated by a diffusion, then the mean and the variance of the number of segregating sites due to selectively neutral mutations in random samples can be numerically calculated. The calculations are greatly simplified if the frequencies of the alleles are tightly regulated. If the mutation rates between alleles maintained by balancing selection are low, then the number of selectively neutral segregating sites in a random sample of genes is expected to substantially exceed the number predicted under a neutral model. PMID:3066685

Physical and mathematical modeling of antimicrobial photodynamic therapy

NASA Astrophysics Data System (ADS)

Bürgermeister, Lisa; López, Fernando Romero; Schulz, Wolfgang

2014-07-01

Antimicrobial photodynamic therapy (aPDT) is a promising method to treat local bacterial infections. The therapy is painless and does not cause bacterial resistances. However, there are gaps in understanding the dynamics of the processes, especially in periodontal treatment. This work describes the advances in fundamental physical and mathematical modeling of aPDT used for interpretation of experimental evidence. The result is a two-dimensional model of aPDT in a dental pocket phantom model. In this model, the propagation of laser light and the kinetics of the chemical reactions are described as coupled processes. The laser light induces the chemical processes depending on its intensity. As a consequence of the chemical processes, the local optical properties and distribution of laser light change as well as the reaction rates. The mathematical description of these coupled processes will help to develop treatment protocols and is the first step toward an inline feedback system for aPDT users.

Artificial neural networks to model formulation-property correlations in the process of inline-compounding on an injection moulding machine

NASA Astrophysics Data System (ADS)

Moritzer, Elmar; Müller, Ellen; Martin, Yannick; Kleeschulte, Rainer

2015-05-01

Today the global market poses great challenges for industrial product development. Complexity, diversity of variants, flexibility and individuality are just some of the features that products have to offer today. In addition, the product series have shorter lifetimes. Because of their high capacity for adaption, polymers are increasingly able to displace traditional materials such as wood, glass and metals from various fields of application. Polymers can only be used to substitute other materials, however, if they are optimally suited to the applications in question. Hence, product-specific material development is becoming increasingly important. Integrating the compounding step in the injection moulding process permits a more efficient and faster development process for a new polymer formulation, making it possible to create new product-specific materials. This process is called inline-compounding on an injection moulding machine. The entire process sequence is supported by software from Bayer Technology called Product Design Workbench (PDWB), which provides assistance in all the individual steps from data management, via analysis and model compilation, right through to the optimization of the formulation and the design of experiments. The software is based on artificial neural networks and can model the formulation-property correlations and thus enable different formulations to be optimized. In the study presented, the workflow and the modelling with the software are presented.

Quasi- and pseudo-maximum likelihood estimators for discretely observed continuous-time Markov branching processes

PubMed Central

Chen, Rui; Hyrien, Ollivier

2011-01-01

This article deals with quasi- and pseudo-likelihood estimation in a class of continuous-time multi-type Markov branching processes observed at discrete points in time. “Conventional” and conditional estimation are discussed for both approaches. We compare their properties and identify situations where they lead to asymptotically equivalent estimators. Both approaches possess robustness properties, and coincide with maximum likelihood estimation in some cases. Quasi-likelihood functions involving only linear combinations of the data may be unable to estimate all model parameters. Remedial measures exist, including the resort either to non-linear functions of the data or to conditioning the moments on appropriate sigma-algebras. The method of pseudo-likelihood may also resolve this issue. We investigate the properties of these approaches in three examples: the pure birth process, the linear birth-and-death process, and a two-type process that generalizes the previous two examples. Simulations studies are conducted to evaluate performance in finite samples. PMID:21552356

Introducing local property tax for fiscal decentralization and local authority autonomy

NASA Astrophysics Data System (ADS)

Dimopoulos, Thomas; Labropoulos, Tassos; Hadjimitsis, Diafantos G.

2015-06-01

Charles Tiebout (1956), in his work "A Pure Theory of Local Expenditures", provides a vision of the workings of the local public sector, acknowledging many similarities to the features of a competitive market, however omitting any references to local taxation. Contrary to other researchers' claim that the Tiebout model and the theory of fiscal decentralization are by no means synonymous, this paper aims to expand Tiebout's theory, by adding the local property tax in the context, introducing a fair, ad valorem property taxation system based on the automated assessment of the value of real estate properties within the boundaries of local authorities. Computer Assisted Mass Appraisal methodology integrated with Remote Sensing technology and GIS analysis is applied to local authorities' property registries and cadastral data, building a spatial relational database and providing data to be statistically processed through Multiple Regression Analysis modeling. The proposed scheme accomplishes economy of scale using CAMA procedures on one hand, but also succeeds in making local authorities self-sufficient through a decentralized, fair, locally calibrated property taxation model, providing rational income administration.

Graph-Theoretic Properties of Networks Based on Word Association Norms: Implications for Models of Lexical Semantic Memory.

PubMed

Gruenenfelder, Thomas M; Recchia, Gabriel; Rubin, Tim; Jones, Michael N

2016-08-01

We compared the ability of three different contextual models of lexical semantic memory (BEAGLE, Latent Semantic Analysis, and the Topic model) and of a simple associative model (POC) to predict the properties of semantic networks derived from word association norms. None of the semantic models were able to accurately predict all of the network properties. All three contextual models over-predicted clustering in the norms, whereas the associative model under-predicted clustering. Only a hybrid model that assumed that some of the responses were based on a contextual model and others on an associative network (POC) successfully predicted all of the network properties and predicted a word's top five associates as well as or better than the better of the two constituent models. The results suggest that participants switch between a contextual representation and an associative network when generating free associations. We discuss the role that each of these representations may play in lexical semantic memory. Concordant with recent multicomponent theories of semantic memory, the associative network may encode coordinate relations between concepts (e.g., the relation between pea and bean, or between sparrow and robin), and contextual representations may be used to process information about more abstract concepts. Copyright © 2015 Cognitive Science Society, Inc.

Clean Metal Casting

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

Makhlouf M. Makhlouf; Diran Apelian

The objective of this project is to develop a technology for clean metal processing that is capable of consistently providing a metal cleanliness level that is fit for a given application. The program has five tasks: Development of melt cleanliness assessment technology, development of melt contamination avoidance technology, development of high temperature phase separation technology, establishment of a correlation between the level of melt cleanliness and as cast mechanical properties, and transfer of technology to the industrial sector. Within the context of the first task, WPI has developed a standardized Reduced Pressure Test that has been endorsed by AFS asmore » a recommended practice. In addition, within the context of task1, WPI has developed a melt cleanliness sensor based on the principles of electromagnetic separation. An industrial partner is commercializing the sensor. Within the context of the second task, WPI has developed environmentally friendly fluxes that do not contain fluorine. Within the context of the third task, WPI modeled the process of rotary degassing and verified the model predictions with experimental data. This model may be used to optimize the performance of industrial rotary degassers. Within the context of the fourth task, WPI has correlated the level of melt cleanliness at various foundries, including a sand casting foundry, a permanent mold casting foundry, and a die casting foundry, to the casting process and the resultant mechanical properties. This is useful in tailoring the melt cleansing operations at foundries to the particular casting process and the desired properties of cast components.« less

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.

Modeling of First-Passage Processes in Financial Markets

NASA Astrophysics Data System (ADS)

Inoue, Jun-Ichi; Hino, Hikaru; Sazuka, Naoya; Scalas, Enrico

2010-03-01

In this talk, we attempt to make a microscopic modeling the first-passage process (or the first-exit process) of the BUND future by minority game with market history. We find that the first-passage process of the minority game with appropriate history length generates the same properties as the BTP future (the middle and long term Italian Government bonds with fixed interest rates), namely, both first-passage time distributions have a crossover at some specific time scale as is the case for the Mittag-Leffler function. We also provide a macroscopic (or a phenomenological) modeling of the first-passage process of the BTP future and show analytically that the first-passage time distribution of a simplest mixture of the normal compound Poisson processes does not have such a crossover.

Systems cell biology.

PubMed

Mast, Fred D; Ratushny, Alexander V; Aitchison, John D

2014-09-15

Systems cell biology melds high-throughput experimentation with quantitative analysis and modeling to understand many critical processes that contribute to cellular organization and dynamics. Recently, there have been several advances in technology and in the application of modeling approaches that enable the exploration of the dynamic properties of cells. Merging technology and computation offers an opportunity to objectively address unsolved cellular mechanisms, and has revealed emergent properties and helped to gain a more comprehensive and fundamental understanding of cell biology. © 2014 Mast et al.

The Processing and Mechanical Properties of High Temperature/High Performance Composites. Book 3. Constituent Properties and Macroscopic Performance: MMCs

DTIC Science & Technology

1993-04-01

re - expressed as, v .= hCSw (C3) Combining Eqns. (C2) and C3) yields, Se = - ’. S (C4...of vi( s ) or v ’( s ). Substituting eq. (B10) into eq. (25), one finds the finite element method expression for functional Ud [ v ] which is U, d [] = v , K...Measurements 1- D 2- D S ,_DL 4 Constitutive W Constitutive Laws Laws Matrix Cracking Labor Models Models Stress Redistribution Numerical Calculations

Properties of animal-manure based hydrochars and predictions using published models

USDA-ARS?s Scientific Manuscript database

In order to fully utilize hydrothermal carbonization (HTC) to produce value-added hydrochars from animal manures, it is important to understand how process conditions (e.g., temperature, reaction time, solids concentration) influence product characteristics. The effect of process conditions on the e...

Lifelong modelling of properties for materials with technological memory

NASA Astrophysics Data System (ADS)

Falaleev, AP; Meshkov, VV; Vetrogon, AA; Ogrizkov, SV; Shymchenko, AV

2016-10-01

An investigation of real automobile parts produced from dual phase steel during standard periods of life cycle is presented, which considers such processes as stamping, exploitation, automobile accident, and further repair. The development of the phenomenological model of the mechanical properties of such parts was based on the two surface plastic theory of Chaboche. As a consequence of the composite structure of dual phase steel, it was shown that local mechanical properties of parts produced from this material change significantly their during their life cycle, depending on accumulated plastic deformations and thermal treatments. Such mechanical property changes have a considerable impact on the accuracy of the computer modelling of automobile behaviour. The most significant errors of modelling were obtained at the critical operating conditions, such as crashes and accidents. The model developed takes into account the kinematics (Bauschinger effect), isotropic hardening, non-linear elastic steel behaviour and changes caused by the thermal treatment. Using finite element analysis, the model allows the evaluation of the passive safety of a repaired car body, and enables increased restoration accuracy following an accident. The model was confirmed experimentally for parts produced from dual phase steel DP780.

Compound activity prediction using models of binding pockets or ligand properties in 3D

PubMed Central

Kufareva, Irina; Chen, Yu-Chen; Ilatovskiy, Andrey V.; Abagyan, Ruben

2014-01-01

Transient interactions of endogenous and exogenous small molecules with flexible binding sites in proteins or macromolecular assemblies play a critical role in all biological processes. Current advances in high-resolution protein structure determination, database development, and docking methodology make it possible to design three-dimensional models for prediction of such interactions with increasing accuracy and specificity. Using the data collected in the Pocketome encyclopedia, we here provide an overview of two types of the three-dimensional ligand activity models, pocket-based and ligand property-based, for two important classes of proteins, nuclear and G-protein coupled receptors. For half the targets, the pocket models discriminate actives from property matched decoys with acceptable accuracy (the area under ROC curve, AUC, exceeding 84%) and for about one fifth of the targets with high accuracy (AUC > 95%). The 3D ligand property field models performed better than 95% in half of the cases. The high performance models can already become a basis of activity predictions for new chemicals. Family-wide benchmarking of the models highlights strengths of both approaches and helps identify their inherent bottlenecks and challenges. PMID:23116466

Modeling coupled thermal-hydrological-chemical processes in theunsaturated fractured rock of Yucca Mountain, Nevada: Heterogeneity andseepage

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

Mukhopadhyay, Sumit; Sonnenthal, Eric L.; Spycher, Nicolas

An understanding of processes affecting seepage intoemplacement tunnels is needed for correctly predicting the performance ofunderground radioactive waste repositories. It has been previouslyestimated that the capillary and vaporization barriers in the unsaturatedfractured rock of Yucca Mountain are enough to prevent seepage underpresent day infiltration conditions. It has also been thought that asubstantially elevated infiltration flux will be required to causeseepage after the thermal period is over. While coupledthermal-hydrological-chemical (THC) changes in Yucca Mountain host rockdue to repository heating has been previously investigated, those THCmodels did not incorporate elements of the seepage model. In this paper,we combine the THC processes inmore » unsaturated fractured rock with theprocesses affecting seepage. We observe that the THC processes alter thehydrological properties of the fractured rock through mineralprecipitation and dissolution. We show that such alteration in thehydrological properties of the rock often leads to local flow channeling.We conclude that such local flow channeling may result in seepage undercertain conditions, even with nonelevated infiltrationfluxes.« less

Towards a Stochastic Predictive Understanding of Ecosystem Functioning and Resilience to Environmental Changes

NASA Astrophysics Data System (ADS)

Pappas, C.

2017-12-01

Terrestrial ecosystem processes respond differently to hydrometeorological variability across timescales, and so does our scientific understanding of the underlying mechanisms. Process-based modeling of ecosystem functioning is therefore challenging, especially when long-term predictions are envisioned. Here we analyze the statistical properties of hydrometeorological and ecosystem variability, i.e., the variability of ecosystem process related to vegetation carbon dynamics, from hourly to decadal timescales. 23 extra-tropical forest sites, covering different climatic zones and vegetation characteristics, are examined. Micrometeorological and reanalysis data of precipitation, air temperature, shortwave radiation and vapor pressure deficit are used to describe hydrometeorological variability. Ecosystem variability is quantified using long-term eddy covariance flux data of hourly net ecosystem exchange of CO2 between land surface and atmosphere, monthly remote sensing vegetation indices, annual tree-ring widths and above-ground biomass increment estimates. We find that across sites and timescales ecosystem variability is confined within a hydrometeorological envelope that describes the range of variability of the available resources, i.e., water and energy. Furthermore, ecosystem variability demonstrates long-term persistence, highlighting ecological memory and slow ecosystem recovery rates after disturbances. We derive an analytical model, combining deterministic harmonics and stochastic processes, that represents major mechanisms and uncertainties and mimics the observed pattern of hydrometeorological and ecosystem variability. This stochastic framework offers a parsimonious and mathematically tractable approach for modelling ecosystem functioning and for understanding its response and resilience to environmental changes. Furthermore, this framework reflects well the observed ecological memory, an inherent property of ecosystem functioning that is currently not captured by simulation results with process-based models. Our analysis offers a perspective for terrestrial ecosystem modelling, combining current process understanding with stochastic methods, and paves the way for new model-data integration opportunities in Earth system sciences.

A spatial scaling relationship for soil moisture in a semiarid landscape, using spatial scaling relationships for pedology

NASA Astrophysics Data System (ADS)

Willgoose, G. R.; Chen, M.; Cohen, S.; Saco, P. M.; Hancock, G. R.

2013-12-01

In humid areas it is generally considered that soil moisture scales spatially according to the wetness index of the landscape. This scaling arises from lateral flow downslope of ground water within the soil zone. However, in semi-arid and drier regions, this lateral flow is small and fluxes are dominated by vertical flows driven by infiltration and evapotranspiration. Thus, in the absence of runon processes, soil moisture at a location is more driven by local factors such as soil and vegetation properties at that location rather than upstream processes draining to that point. The 'apparent' spatial randomness of soil and vegetation properties generally suggests that soil moisture for semi-arid regions is spatially random. In this presentation a new analysis of neutron probe data during summer from the Tarrawarra site near Melbourne, Australia shows persistent spatial organisation of soil moisture over several years. This suggests a link between permanent features of the catchment (e.g. soil properties) and soil moisture distribution, even though the spatial pattern of soil moisture during the 4 summers monitored appears spatially random. This and other data establishes a prima facie case that soil variations drive spatial variation in soil moisture. Accordingly, we used a previously published spatial scaling relationship for soil properties derived using the mARM pedogenesis model to simulate the spatial variation of soil grading. This soil grading distribution was used in the Rosetta pedotransfer model to derive a spatial distribution of soil functional properties (e.g. saturated hydraulic conductivity, porosity). These functional properties were then input into the HYDRUS-1D soil moisture model and soil moisture simulated for 3 years at daily resolution. The HYDRUS model used had previously been calibrated to field observed soil moisture data at our SASMAS field site. The scaling behaviour of soil moisture derived from this modelling will be discussed and compared with observed data from our SASMAS field sites.

Basic difference between brain and computer: integration of asynchronous processes implemented as hardware model of the retina.

PubMed

Przybyszewski, Andrzej W; Linsay, Paul S; Gaudiano, Paolo; Wilson, Christopher M

2007-01-01

There exists a common view that the brain acts like a Turing machine: The machine reads information from an infinite tape (sensory data) and, on the basis of the machine's state and information from the tape, an action (decision) is made. The main problem with this model lies in how to synchronize a large number of tapes in an adaptive way so that the machine is able to accomplish tasks such as object classification. We propose that such mechanisms exist already in the eye. A popular view is that the retina, typically associated with high gain and adaptation for light processing, is actually performing local preprocessing by means of its center-surround receptive field. We would like to show another property of the retina: The ability to integrate many independent processes. We believe that this integration is implemented by synchronization of neuronal oscillations. In this paper, we present a model of the retina consisting of a series of coupled oscillators which can synchronize on several scales. Synchronization is an analog process which is converted into a digital spike train in the output of the retina. We have developed a hardware implementation of this model, which enables us to carry out rapid simulation of multineuron oscillatory dynamics. We show that the properties of the spike trains in our model are similar to those found in vivo in the cat retina.

Ecological communities with Lotka-Volterra dynamics

NASA Astrophysics Data System (ADS)

Bunin, Guy

2017-04-01

Ecological communities in heterogeneous environments assemble through the combined effect of species interaction and migration. Understanding the effect of these processes on the community properties is central to ecology. Here we study these processes for a single community subject to migration from a pool of species, with population dynamics described by the generalized Lotka-Volterra equations. We derive exact results for the phase diagram describing the dynamical behaviors, and for the diversity and species abundance distributions. A phase transition is found from a phase where a unique globally attractive fixed point exists to a phase where multiple dynamical attractors exist, leading to history-dependent community properties. The model is shown to possess a symmetry that also establishes a connection with other well-known models.

Ecological communities with Lotka-Volterra dynamics.

PubMed

Bunin, Guy

2017-04-01

Ecological communities in heterogeneous environments assemble through the combined effect of species interaction and migration. Understanding the effect of these processes on the community properties is central to ecology. Here we study these processes for a single community subject to migration from a pool of species, with population dynamics described by the generalized Lotka-Volterra equations. We derive exact results for the phase diagram describing the dynamical behaviors, and for the diversity and species abundance distributions. A phase transition is found from a phase where a unique globally attractive fixed point exists to a phase where multiple dynamical attractors exist, leading to history-dependent community properties. The model is shown to possess a symmetry that also establishes a connection with other well-known models.

The VATES-Diamond as a Verifier's Best Friend

NASA Astrophysics Data System (ADS)

Glesner, Sabine; Bartels, Björn; Göthel, Thomas; Kleine, Moritz

Within a model-based software engineering process it needs to be ensured that properties of abstract specifications are preserved by transformations down to executable code. This is even more important in the area of safety-critical real-time systems where additionally non-functional properties are crucial. In the VATES project, we develop formal methods for the construction and verification of embedded systems. We follow a novel approach that allows us to formally relate abstract process algebraic specifications to their implementation in a compiler intermediate representation. The idea is to extract a low-level process algebraic description from the intermediate code and to formally relate it to previously developed abstract specifications. We apply this approach to a case study from the area of real-time operating systems and show that this approach has the potential to seamlessly integrate modeling, implementation, transformation and verification stages of embedded system development.

Potential for Remotely Sensed Soil Moisture Data in Hydrologic Modeling

NASA Technical Reports Server (NTRS)

Engman, Edwin T.

1997-01-01

Many hydrologic processes display a unique signature that is detectable with microwave remote sensing. These signatures are in the form of the spatial and temporal distributions of surface soil moisture and portray the spatial heterogeneity of hydrologic processes and properties that one encounters in drainage basins. The hydrologic processes that may be detected include ground water recharge and discharge zones, storm runoff contributing areas, regions of potential and less than potential ET, and information about the hydrologic properties of soils and heterogeneity of hydrologic parameters. Microwave remote sensing has the potential to detect these signatures within a basin in the form of volumetric soil moisture measurements in the top few cm. These signatures should provide information on how and where to apply soil physical parameters in distributed and lumped parameter models and how to subdivide drainage basins into hydrologically similar sub-basins.

Effect analysis of material properties of picosecond laser ablation for ABS/PVC

NASA Astrophysics Data System (ADS)

Tsai, Y. H.; Ho, C. Y.; Chiou, Y. J.

2017-06-01

This paper analytically investigates the picosecond laser ablation of ABS/PVC. Laser-pulsed ablation is a wellestablished tool for polymer. However the ablation mechanism of laser processing for polymer has not been thoroughly understood yet. This study utilized a thermal transport model to analyze the relationship between the ablation rate and laser fluences. This model considered the energy balance at the decomposition interface and Arrhenius law as the ablation mechanisms. The calculated variation of the ablation rate with the logarithm of the laser fluence agrees with the measured data. It is also validated in this work that the variation of the ablation rate with the logarithm of the laser fluence obeys Beer's law for low laser fluences. The effects of material properties and processing parameters on the ablation depth per pulse are also discussed for picosecond laser processing of ABS/PVC.

Invariant measures in brain dynamics

NASA Astrophysics Data System (ADS)

Boyarsky, Abraham; Góra, Paweł

2006-10-01

This note concerns brain activity at the level of neural ensembles and uses ideas from ergodic dynamical systems to model and characterize chaotic patterns among these ensembles during conscious mental activity. Central to our model is the definition of a space of neural ensembles and the assumption of discrete time ensemble dynamics. We argue that continuous invariant measures draw the attention of deeper brain processes, engendering emergent properties such as consciousness. Invariant measures supported on a finite set of ensembles reflect periodic behavior, whereas the existence of continuous invariant measures reflect the dynamics of nonrepeating ensemble patterns that elicit the interest of deeper mental processes. We shall consider two different ways to achieve continuous invariant measures on the space of neural ensembles: (1) via quantum jitters, and (2) via sensory input accompanied by inner thought processes which engender a “folding” property on the space of ensembles.

Experiments and Modeling in Support of Generic Salt Repository Science

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

Bourret, Suzanne Michelle; Stauffer, Philip H.; Weaver, Douglas James

Salt is an attractive material for the disposition of heat generating nuclear waste (HGNW) because of its self-sealing, viscoplastic, and reconsolidation properties (Hansen and Leigh, 2012). The rate at which salt consolidates and the properties of the consolidated salt depend on the composition of the salt, including its content in accessory minerals and moisture, and the temperature under which consolidation occurs. Physicochemical processes, such as mineral hydration/dehydration salt dissolution and precipitation play a significant role in defining the rate of salt structure changes. Understanding the behavior of these complex processes is paramount when considering safe design for disposal of heat-generatingmore » nuclear waste (HGNW) in salt formations, so experimentation and modeling is underway to characterize these processes. This report presents experiments and simulations in support of the DOE-NE Used Fuel Disposition Campaign (UFDC) for development of drift-scale, in-situ field testing of HGNW in salt formations.« less

Constraints on active region coronal heating properties from observations and modeling of chromospheric, transition region, and coronal emission

NASA Astrophysics Data System (ADS)

Testa, P.; Polito, V.; De Pontieu, B.; Carlsson, M.; Reale, F.; Allred, J. C.; Hansteen, V. H.

2017-12-01

We investigate coronal heating properties in active region cores in non-flaring conditions, using high spatial, spectral, and temporal resolution chromospheric/transition region/coronal observations coupled with detailed modeling. We will focus, in particular, on observations with the Interface Region Imaging Spectrograph (IRIS), joint with observations with Hinode (XRT and EIS) and SDO/AIA. We will discuss how these observations and models (1D HD and 3D MHD, with the RADYN and Bifrost codes) provide useful diagnostics of the coronal heating processes and mechanisms of energy transport.

Updating the Finite Element Model of the Aerostructures Test Wing Using Ground Vibration Test Data

NASA Technical Reports Server (NTRS)

Lung, Shun-Fat; Pak, Chan-Gi

2009-01-01

Improved and/or accelerated decision making is a crucial step during flutter certification processes. Unfortunately, most finite element structural dynamics models have uncertainties associated with model validity. Tuning the finite element model using measured data to minimize the model uncertainties is a challenging task in the area of structural dynamics. The model tuning process requires not only satisfactory correlations between analytical and experimental results, but also the retention of the mass and stiffness properties of the structures. Minimizing the difference between analytical and experimental results is a type of optimization problem. By utilizing the multidisciplinary design, analysis, and optimization (MDAO) tool in order to optimize the objective function and constraints; the mass properties, the natural frequencies, and the mode shapes can be matched to the target data to retain the mass matrix orthogonality. This approach has been applied to minimize the model uncertainties for the structural dynamics model of the aerostructures test wing (ATW), which was designed and tested at the National Aeronautics and Space Administration Dryden Flight Research Center (Edwards, California). This study has shown that natural frequencies and corresponding mode shapes from the updated finite element model have excellent agreement with corresponding measured data.

Updating the Finite Element Model of the Aerostructures Test Wing using Ground Vibration Test Data

NASA Technical Reports Server (NTRS)

Lung, Shun-fat; Pak, Chan-gi

2009-01-01

Improved and/or accelerated decision making is a crucial step during flutter certification processes. Unfortunately, most finite element structural dynamics models have uncertainties associated with model validity. Tuning the finite element model using measured data to minimize the model uncertainties is a challenging task in the area of structural dynamics. The model tuning process requires not only satisfactory correlations between analytical and experimental results, but also the retention of the mass and stiffness properties of the structures. Minimizing the difference between analytical and experimental results is a type of optimization problem. By utilizing the multidisciplinary design, analysis, and optimization (MDAO) tool in order to optimize the objective function and constraints; the mass properties, the natural frequencies, and the mode shapes can be matched to the target data to retain the mass matrix orthogonality. This approach has been applied to minimize the model uncertainties for the structural dynamics model of the Aerostructures Test Wing (ATW), which was designed and tested at the National Aeronautics and Space Administration (NASA) Dryden Flight Research Center (DFRC) (Edwards, California). This study has shown that natural frequencies and corresponding mode shapes from the updated finite element model have excellent agreement with corresponding measured data.

Feature-Selective Attentional Modulations in Human Frontoparietal Cortex.

PubMed

Ester, Edward F; Sutterer, David W; Serences, John T; Awh, Edward

2016-08-03

Control over visual selection has long been framed in terms of a dichotomy between "source" and "site," where top-down feedback signals originating in frontoparietal cortical areas modulate or bias sensory processing in posterior visual areas. This distinction is motivated in part by observations that frontoparietal cortical areas encode task-level variables (e.g., what stimulus is currently relevant or what motor outputs are appropriate), while posterior sensory areas encode continuous or analog feature representations. Here, we present evidence that challenges this distinction. We used fMRI, a roving searchlight analysis, and an inverted encoding model to examine representations of an elementary feature property (orientation) across the entire human cortical sheet while participants attended either the orientation or luminance of a peripheral grating. Orientation-selective representations were present in a multitude of visual, parietal, and prefrontal cortical areas, including portions of the medial occipital cortex, the lateral parietal cortex, and the superior precentral sulcus (thought to contain the human homolog of the macaque frontal eye fields). Additionally, representations in many-but not all-of these regions were stronger when participants were instructed to attend orientation relative to luminance. Collectively, these findings challenge models that posit a strict segregation between sources and sites of attentional control on the basis of representational properties by demonstrating that simple feature values are encoded by cortical regions throughout the visual processing hierarchy, and that representations in many of these areas are modulated by attention. Influential models of visual attention posit a distinction between top-down control and bottom-up sensory processing networks. These models are motivated in part by demonstrations showing that frontoparietal cortical areas associated with top-down control represent abstract or categorical stimulus information, while visual areas encode parametric feature information. Here, we show that multivariate activity in human visual, parietal, and frontal cortical areas encode representations of a simple feature property (orientation). Moreover, representations in several (though not all) of these areas were modulated by feature-based attention in a similar fashion. These results provide an important challenge to models that posit dissociable top-down control and sensory processing networks on the basis of representational properties. Copyright © 2016 the authors 0270-6474/16/368188-12$15.00/0.

Microstructure and Magnetic Properties of Magnetic Material Fabricated by Selective Laser Melting

NASA Astrophysics Data System (ADS)

Jhong, Kai Jyun; Huang, Wei-Chin; Lee, Wen Hsi

Selective Laser Melting (SLM) is a powder-based additive manufacturing which is capable of producing parts layer-by-layer from a 3D CAD model. The aim of this study is to adopt the selective laser melting technique to magnetic material fabrication. [1]For the SLM process to be practical in industrial use, highly specific mechanical properties of the final product must be achieved. The integrity of the manufactured components depend strongly on each single laser-melted track and every single layer, as well as the strength of the connections between them. In this study, effects of the processing parameters, such as the space distance of surface morphology is analyzed. Our hypothesis is that when a magnetic product is made by the selective laser melting techniques instead of traditional techniques, the finished component will have more precise and effective properties. This study analyzed the magnitudes of magnetic properties in comparison with different parameters in the SLM process and compiled a completed product to investigate the efficiency in contrast with products made with existing manufacturing processes.

From behavioural analyses to models of collective motion in fish schools

PubMed Central

Lopez, Ugo; Gautrais, Jacques; Couzin, Iain D.; Theraulaz, Guy

2012-01-01

Fish schooling is a phenomenon of long-lasting interest in ethology and ecology, widely spread across taxa and ecological contexts, and has attracted much interest from statistical physics and theoretical biology as a case of self-organized behaviour. One topic of intense interest is the search of specific behavioural mechanisms at stake at the individual level and from which the school properties emerges. This is fundamental for understanding how selective pressure acting at the individual level promotes adaptive properties of schools and in trying to disambiguate functional properties from non-adaptive epiphenomena. Decades of studies on collective motion by means of individual-based modelling have allowed a qualitative understanding of the self-organization processes leading to collective properties at school level, and provided an insight into the behavioural mechanisms that result in coordinated motion. Here, we emphasize a set of paradigmatic modelling assumptions whose validity remains unclear, both from a behavioural point of view and in terms of quantitative agreement between model outcome and empirical data. We advocate for a specific and biologically oriented re-examination of these assumptions through experimental-based behavioural analysis and modelling. PMID:24312723

Soil Erosion as a stochastic process

NASA Astrophysics Data System (ADS)

Casper, Markus C.

2015-04-01

The main tools to provide estimations concerning risk and amount of erosion are different types of soil erosion models: on the one hand, there are empirically based model concepts on the other hand there are more physically based or process based models. However, both types of models have substantial weak points. All empirical model concepts are only capable of providing rough estimates over larger temporal and spatial scales, they do not account for many driving factors that are in the scope of scenario related analysis. In addition, the physically based models contain important empirical parts and hence, the demand for universality and transferability is not given. As a common feature, we find, that all models rely on parameters and input variables, which are to certain, extend spatially and temporally averaged. A central question is whether the apparent heterogeneity of soil properties or the random nature of driving forces needs to be better considered in our modelling concepts. Traditionally, researchers have attempted to remove spatial and temporal variability through homogenization. However, homogenization has been achieved through physical manipulation of the system, or by statistical averaging procedures. The price for obtaining this homogenized (average) model concepts of soils and soil related processes has often been a failure to recognize the profound importance of heterogeneity in many of the properties and processes that we study. Especially soil infiltrability and the resistance (also called "critical shear stress" or "critical stream power") are the most important empirical factors of physically based erosion models. The erosion resistance is theoretically a substrate specific parameter, but in reality, the threshold where soil erosion begins is determined experimentally. The soil infiltrability is often calculated with empirical relationships (e.g. based on grain size distribution). Consequently, to better fit reality, this value needs to be corrected experimentally. To overcome this disadvantage of our actual models, soil erosion models are needed that are able to use stochastic directly variables and parameter distributions. There are only some minor approaches in this direction. The most advanced is the model "STOSEM" proposed by Sidorchuk in 2005. In this model, only a small part of the soil erosion processes is described, the aggregate detachment and the aggregate transport by flowing water. The concept is highly simplified, for example, many parameters are temporally invariant. Nevertheless, the main problem is that our existing measurements and experiments are not geared to provide stochastic parameters (e.g. as probability density functions); in the best case they deliver a statistical validation of the mean values. Again, we get effective parameters, spatially and temporally averaged. There is an urgent need for laboratory and field experiments on overland flow structure, raindrop effects and erosion rate, which deliver information on spatial and temporal structure of soil and surface properties and processes.

The basis function approach for modeling autocorrelation in ecological data.

PubMed

Hefley, Trevor J; Broms, Kristin M; Brost, Brian M; Buderman, Frances E; Kay, Shannon L; Scharf, Henry R; Tipton, John R; Williams, Perry J; Hooten, Mevin B

2017-03-01

Analyzing ecological data often requires modeling the autocorrelation created by spatial and temporal processes. Many seemingly disparate statistical methods used to account for autocorrelation can be expressed as regression models that include basis functions. Basis functions also enable ecologists to modify a wide range of existing ecological models in order to account for autocorrelation, which can improve inference and predictive accuracy. Furthermore, understanding the properties of basis functions is essential for evaluating the fit of spatial or time-series models, detecting a hidden form of collinearity, and analyzing large data sets. We present important concepts and properties related to basis functions and illustrate several tools and techniques ecologists can use when modeling autocorrelation in ecological data. © 2016 by the Ecological Society of America.

Impact of Thermal Pretreatment Temperatures on Woody Biomass Chemical Composition, Physical Properties and Microstructure

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

Wang, Ping; Howard, Bret H.

Thermal pretreatment of biomass by torrefaction and low temperature pyrolysis has the potential for generating high quality and more suitable fuels. To utilize a model to describe the complex and dynamic changes taking place during these two treatments for process design, optimization and scale-up, detailed data is needed on the property evolution during treatment of well-defined individual biomass particles. The objectives of this study are to investigate the influence of thermal pretreatment temperatures on wood biomass biochemical compositions, physical properties and microstructure. Wild cherry wood was selected as a model biomass and prepared for this study. The well-defined wood particlemore » samples were consecutively heated at 220, 260, 300, 350, 450 and 550 °C for 0.5 h under nitrogen. Untreated and treated samples were characterized for biochemical composition changes (cellulose, hemicellulose, and lignin) by thermogravimetric analyzer (TGA), physical properties (color, dimensions, weight, density and grindablity), chemical property (proximate analysis and heating value) and microstructural changes by scanning electron microscopy (SEM). Hemicellulose was mostly decomposed in the samples treated at 260 and 300 °C and resulted in the cell walls weakening resulting in improved grindability. The dimensions of the wood were reduced in all directions and shrinkage increased with increased treatment temperature and weight loss. With increased treatment temperature, losses of weight and volume increased and bulk density decreased. The low temperature pyrolyzed wood samples improved solid fuel property with high fuel ratio, which are close to lignite/bituminous coal. Morphology of the wood remained intact through the treatment range but the cell walls were thinner. Lastly, these results will improve the understanding of the property changes of the biomass during pretreatment and will help to develop models for process simulation and potential application of the treated biomass.« less

Impact of Thermal Pretreatment Temperatures on Woody Biomass Chemical Composition, Physical Properties and Microstructure

DOE PAGES

Wang, Ping; Howard, Bret H.

2017-12-23

Thermal pretreatment of biomass by torrefaction and low temperature pyrolysis has the potential for generating high quality and more suitable fuels. To utilize a model to describe the complex and dynamic changes taking place during these two treatments for process design, optimization and scale-up, detailed data is needed on the property evolution during treatment of well-defined individual biomass particles. The objectives of this study are to investigate the influence of thermal pretreatment temperatures on wood biomass biochemical compositions, physical properties and microstructure. Wild cherry wood was selected as a model biomass and prepared for this study. The well-defined wood particlemore » samples were consecutively heated at 220, 260, 300, 350, 450 and 550 °C for 0.5 h under nitrogen. Untreated and treated samples were characterized for biochemical composition changes (cellulose, hemicellulose, and lignin) by thermogravimetric analyzer (TGA), physical properties (color, dimensions, weight, density and grindablity), chemical property (proximate analysis and heating value) and microstructural changes by scanning electron microscopy (SEM). Hemicellulose was mostly decomposed in the samples treated at 260 and 300 °C and resulted in the cell walls weakening resulting in improved grindability. The dimensions of the wood were reduced in all directions and shrinkage increased with increased treatment temperature and weight loss. With increased treatment temperature, losses of weight and volume increased and bulk density decreased. The low temperature pyrolyzed wood samples improved solid fuel property with high fuel ratio, which are close to lignite/bituminous coal. Morphology of the wood remained intact through the treatment range but the cell walls were thinner. Lastly, these results will improve the understanding of the property changes of the biomass during pretreatment and will help to develop models for process simulation and potential application of the treated biomass.« less

Modelling and simulation of the consolidation behavior during thermoplastic prepreg composites forming process

NASA Astrophysics Data System (ADS)

Xiong, H.; Hamila, N.; Boisse, P.

2017-10-01

Pre-impregnated thermoplastic composites have recently attached increasing interest in the automotive industry for their excellent mechanical properties and their rapid cycle manufacturing process, modelling and numerical simulations of forming processes for composites parts with complex geometry is necessary to predict and optimize manufacturing practices, especially for the consolidation effects. A viscoelastic relaxation model is proposed to characterize the consolidation behavior of thermoplastic prepregs based on compaction tests with a range of temperatures. The intimate contact model is employed to predict the evolution of the consolidation which permits the microstructure prediction of void presented through the prepreg. Within a hyperelastic framework, several simulation tests are launched by combining a new developed solid shell finite element and the consolidation models.

Systematic Error Modeling and Bias Estimation

PubMed Central

Zhang, Feihu; Knoll, Alois

2016-01-01

This paper analyzes the statistic properties of the systematic error in terms of range and bearing during the transformation process. Furthermore, we rely on a weighted nonlinear least square method to calculate the biases based on the proposed models. The results show the high performance of the proposed approach for error modeling and bias estimation. PMID:27213386

Discrete-State and Continuous Models of Recognition Memory: Testing Core Properties under Minimal Assumptions

ERIC Educational Resources Information Center

Kellen, David; Klauer, Karl Christoph

2014-01-01

A classic discussion in the recognition-memory literature concerns the question of whether recognition judgments are better described by continuous or discrete processes. These two hypotheses are instantiated by the signal detection theory model (SDT) and the 2-high-threshold model, respectively. Their comparison has almost invariably relied on…

Issues of Spatial and Temporal Scale in Modeling the Effects of Field Operatiions on Soil Properties

USDA-ARS?s Scientific Manuscript database

Tillage is an important procedure for modifying the soil environment in order to enhance crop growth and conserve soil and water resources. Process-based models of crop production are widely used in decision support, but few explicitly simulate tillage. The Cropping Systems Model (CSM) was modified ...

IRT-ZIP Modeling for Multivariate Zero-Inflated Count Data

ERIC Educational Resources Information Center

Wang, Lijuan

2010-01-01

This study introduces an item response theory-zero-inflated Poisson (IRT-ZIP) model to investigate psychometric properties of multiple items and predict individuals' latent trait scores for multivariate zero-inflated count data. In the model, two link functions are used to capture two processes of the zero-inflated count data. Item parameters are…

Experimental and Numerical Modeling of Fluid Flow Processes in Continuous Casting: Results from the LIMMCAST-Project

NASA Astrophysics Data System (ADS)

Timmel, K.; Kratzsch, C.; Asad, A.; Schurmann, D.; Schwarze, R.; Eckert, S.

2017-07-01

The present paper reports about numerical simulations and model experiments concerned with the fluid flow in the continuous casting process of steel. This work was carried out in the LIMMCAST project in the framework of the Helmholtz alliance LIMTECH. A brief description of the LIMMCAST facilities used for the experimental modeling at HZDR is given here. Ultrasonic and inductive techniques and the X-ray radioscopy were employed for flow measurements or visualizations of two-phase flow regimes occurring in the submerged entry nozzle and the mold. Corresponding numerical simulations were performed at TUBAF taking into account the dimensions and properties of the model experiments. Numerical models were successfully validated using the experimental data base. The reasonable and in many cases excellent agreement of numerical with experimental data allows to extrapolate the models to real casting configurations. Exemplary results will be presented here showing the effect of electromagnetic brakes or electromagnetic stirrers on the flow in the mold or illustrating the properties of two-phase flows resulting from an Ar injection through the stopper rod.

Influence of raw material properties upon critical quality attributes of continuously produced granules and tablets.

PubMed

Fonteyne, Margot; Wickström, Henrika; Peeters, Elisabeth; Vercruysse, Jurgen; Ehlers, Henrik; Peters, Björn-Hendrik; Remon, Jean Paul; Vervaet, Chris; Ketolainen, Jarkko; Sandler, Niklas; Rantanen, Jukka; Naelapää, Kaisa; De Beer, Thomas

2014-07-01

Continuous manufacturing gains more and more interest within the pharmaceutical industry. The International Conference of Harmonisation (ICH) states in its Q8 'Pharmaceutical Development' guideline that the manufacturer of pharmaceuticals should have an enhanced knowledge of the product performance over a range of raw material attributes, manufacturing process options and process parameters. This fits further into the Process Analytical Technology (PAT) and Quality by Design (QbD) framework. The present study evaluates the effect of variation in critical raw material properties on the critical quality attributes of granules and tablets, produced by a continuous from-powder-to-tablet wet granulation line. The granulation process parameters were kept constant to examine the differences in the end product quality caused by the variability of the raw materials properties only. Theophylline-Lactose-PVP (30-67.5-2.5%) was used as model formulation. Seven different grades of theophylline were granulated. Afterward, the obtained granules were tableted. Both the characteristics of granules and tablets were determined. The results show that differences in raw material properties both affect their processability and several critical quality attributes of the resulting granules and tablets. Copyright © 2014 Elsevier B.V. All rights reserved.

Phase-I monitoring of standard deviations in multistage linear profiles

NASA Astrophysics Data System (ADS)

Kalaei, Mahdiyeh; Soleimani, Paria; Niaki, Seyed Taghi Akhavan; Atashgar, Karim

2018-03-01

In most modern manufacturing systems, products are often the output of some multistage processes. In these processes, the stages are dependent on each other, where the output quality of each stage depends also on the output quality of the previous stages. This property is called the cascade property. Although there are many studies in multistage process monitoring, there are fewer works on profile monitoring in multistage processes, especially on the variability monitoring of a multistage profile in Phase-I for which no research is found in the literature. In this paper, a new methodology is proposed to monitor the standard deviation involved in a simple linear profile designed in Phase I to monitor multistage processes with the cascade property. To this aim, an autoregressive correlation model between the stages is considered first. Then, the effect of the cascade property on the performances of three types of T 2 control charts in Phase I with shifts in standard deviation is investigated. As we show that this effect is significant, a U statistic is next used to remove the cascade effect, based on which the investigated control charts are modified. Simulation studies reveal good performances of the modified control charts.

Using satellites and global models to investigate aerosol-cloud interactions

NASA Astrophysics Data System (ADS)

Gryspeerdt, E.; Quaas, J.; Goren, T.; Sourdeval, O.; Mülmenstädt, J.

2017-12-01

Aerosols are known to impact liquid cloud properties, through both microphysical and radiative processes. Increasing the number concentration of aerosol particles can increase the cloud droplet number concentration (CDNC). Through impacts on precipitation processes, this increase in CDNC may also be able to impact the cloud fraction (CF) and the cloud liquid water path (LWP). Several studies have looked into the effect of aerosols on the CDNC, but as the albedo of a cloudy scene depends much more strongly on LWP and CF, an aerosol influence on these properties could generate a significant radiative forcing. While the impact of aerosols on cloud properties can be seen in case studies involving shiptracks and volcanoes, producing a global estimate of these effects remains challenging due to the confounding effect of local meteorology. For example, relative humidity significantly impacts the aerosol optical depth (AOD), a common satellite proxy for CCN, as well as being a strong control on cloud properties. This can generate relationships between AOD and cloud properties, even when there is no impact of aerosol-cloud interactions. In this work, we look at how aerosol-cloud interactions can be distinguished from the effect of local meteorology in satellite studies. With a combination global climate models and multiple sources of satellite data, we show that the choice of appropriate mediating variables and case studies can be used to develop constraints on the aerosol impact on CF and LWP. This will lead to improved representations of clouds in global climate models and help to reduce the uncertainty in the global impact of anthropogenic aerosols on cloud properties.

Study on inverse estimation of radiative properties from directional radiances by using statistical RPSO algorithm

NASA Astrophysics Data System (ADS)

Han, Kuk-Il; Kim, Do-Hwi; Choi, Jun-Hyuk; Kim, Tae-Kuk; Shin, Jong-Jin

2016-09-01

Infrared signals are widely used to discriminate objects against the background. Prediction of infrared signal from an object surface is essential in evaluating the detectability of the object. Appropriate and easy method of procurement of the radiative properties such as the surface emissivity, bidirectional reflectivity is important in estimating infrared signals. Direct measurement can be a good choice but a costly and time consuming way of obtaining the radiative properties for surfaces coated with many different newly developed paints. Especially measurement of the bidirectional reflectivity usually expressed by the bidirectional reflectance distribution function (BRDF) is the most costly job. In this paper we are presenting an inverse estimation method of the radiative properties by using the directional radiances from the surface of concern. The inverse estimation method used in this study is the statistical repulsive particle swarm optimization (RPSO) algorithm which uses the randomly picked directional radiance data emitted and reflected from the surface. In this paper, we test the proposed inverse method by considering the radiation from a steel plate surface coated with different paints at a clear sunny day condition. For convenience, the directional radiance data from the steel plate within a spectral band of concern are obtained from the simulation using the commercial software, RadthermIR, instead of the field measurement. A widely used BRDF model called as the Sandford-Robertson(S-R) model is considered and the RPSO process is then used to find the best fitted model parameters for the S-R model. The results obtained from this study show an excellent agreement with the reference property data used for the simulation for directional radiances. The proposed process can be a useful way of obtaining the radiative properties from field measured directional radiance data for surfaces coated with or without various kinds of paints of unknown radiative properties.

Modelling Of Flotation Processes By Classical Mathematical Methods - A Review

NASA Astrophysics Data System (ADS)

Jovanović, Ivana; Miljanović, Igor

2015-12-01

Flotation process modelling is not a simple task, mostly because of the process complexity, i.e. the presence of a large number of variables that (to a lesser or a greater extent) affect the final outcome of the mineral particles separation based on the differences in their surface properties. The attempts toward the development of the quantitative predictive model that would fully describe the operation of an industrial flotation plant started in the middle of past century and it lasts to this day. This paper gives a review of published research activities directed toward the development of flotation models based on the classical mathematical rules. The description and systematization of classical flotation models were performed according to the available references, with emphasize exclusively given to the flotation process modelling, regardless of the model application in a certain control system. In accordance with the contemporary considerations, models were classified as the empirical, probabilistic, kinetic and population balance types. Each model type is presented through the aspects of flotation modelling at the macro and micro process levels.

Markov modulated Poisson process models incorporating covariates for rainfall intensity.

PubMed

Thayakaran, R; Ramesh, N I

2013-01-01

Time series of rainfall bucket tip times at the Beaufort Park station, Bracknell, in the UK are modelled by a class of Markov modulated Poisson processes (MMPP) which may be thought of as a generalization of the Poisson process. Our main focus in this paper is to investigate the effects of including covariate information into the MMPP model framework on statistical properties. In particular, we look at three types of time-varying covariates namely temperature, sea level pressure, and relative humidity that are thought to be affecting the rainfall arrival process. Maximum likelihood estimation is used to obtain the parameter estimates, and likelihood ratio tests are employed in model comparison. Simulated data from the fitted model are used to make statistical inferences about the accumulated rainfall in the discrete time interval. Variability of the daily Poisson arrival rates is studied.

Behavior of Aging, Micro-Void, and Self-Healing of Glass/Ceramic Materials and Its Effect on Mechanical Properties

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

Liu, Wenning N.; Sun, Xin; Khaleel, Mohammad A.

This chapter first describes tests to investigate the temporal evolution of the volume fraction of ceramic phases, the evolution of micro-damage, and the self-healing behavior of the glass ceramic sealant used in SOFCs, then a phenomenological model based on mechanical analogs is developed to describe the temperature dependent Young’s modulus of glass ceramic seal materials. It was found that after the initial sintering process, further crystallization of the glass ceramic sealant does not stop, but slows down and reduces the residual glass content while boosting the ceramic crystalline content. Under the long-term operating environment, distinct fibrous and needle-like crystals inmore » the amorphous phase disappeared, and smeared/diffused phase boundaries between the glass phase and ceramic phase were observed. Meanwhile, the micro-damage was induced by the cooling-down process from the operating temperature to the room temperature, which can potentially degrade the mechanical properties of the glass/ceramic sealant. The glass/ceramic sealant self-healed upon reheating to the SOFC operating temperature, which can restore the mechanical performance of the glass/ceramic sealant. The phenomenological model developed here includes the effects of continuing aging and devitrification on the ceramic phase volume fraction and the resulted mechanical properties of glass ceramic seal material are considered. The effects of micro-voids and self-healing are also considered using a continuum damage mechanics (CDM) model. The formulation is for glass/ceramic seal in general, and it can be further developed to account for effects of various processing parameters. This model was applied to G18, and the temperature-dependent experimental measurements were used to calibrate the modeling parameters and to validate the model prediction.« less

A verification strategy for web services composition using enhanced stacked automata model.

PubMed

Nagamouttou, Danapaquiame; Egambaram, Ilavarasan; Krishnan, Muthumanickam; Narasingam, Poonkuzhali

2015-01-01

Currently, Service-Oriented Architecture (SOA) is becoming the most popular software architecture of contemporary enterprise applications, and one crucial technique of its implementation is web services. Individual service offered by some service providers may symbolize limited business functionality; however, by composing individual services from different service providers, a composite service describing the intact business process of an enterprise can be made. Many new standards have been defined to decipher web service composition problem namely Business Process Execution Language (BPEL). BPEL provides an initial work for forming an Extended Markup Language (XML) specification language for defining and implementing business practice workflows for web services. The problems with most realistic approaches to service composition are the verification of composed web services. It has to depend on formal verification method to ensure the correctness of composed services. A few research works has been carried out in the literature survey for verification of web services for deterministic system. Moreover the existing models did not address the verification properties like dead transition, deadlock, reachability and safetyness. In this paper, a new model to verify the composed web services using Enhanced Stacked Automata Model (ESAM) has been proposed. The correctness properties of the non-deterministic system have been evaluated based on the properties like dead transition, deadlock, safetyness, liveness and reachability. Initially web services are composed using Business Process Execution Language for Web Service (BPEL4WS) and it is converted into ESAM (combination of Muller Automata (MA) and Push Down Automata (PDA)) and it is transformed into Promela language, an input language for Simple ProMeLa Interpreter (SPIN) tool. The model is verified using SPIN tool and the results revealed better recital in terms of finding dead transition and deadlock in contrast to the existing models.

Geochemical modeling of trivalent chromium migration in saline-sodic soil during Lasagna process: impact on soil physicochemical properties.

PubMed

Lukman, Salihu; Bukhari, Alaadin; Al-Malack, Muhammad H; Mu'azu, Nuhu D; Essa, Mohammed H

2014-01-01

Trivalent Cr is one of the heavy metals that are difficult to be removed from soil using electrokinetic study because of its geochemical properties. High buffering capacity soil is expected to reduce the mobility of the trivalent Cr and subsequently reduce the remedial efficiency thereby complicating the remediation process. In this study, geochemical modeling and migration of trivalent Cr in saline-sodic soil (high buffering capacity and alkaline) during integrated electrokinetics-adsorption remediation, called the Lasagna process, were investigated. The remedial efficiency of trivalent Cr in addition to the impacts of the Lasagna process on the physicochemical properties of the soil was studied. Box-Behnken design was used to study the interaction effects of voltage gradient, initial contaminant concentration, and polarity reversal rate on the soil pH, electroosmotic volume, soil electrical conductivity, current, and remedial efficiency of trivalent Cr in saline-sodic soil that was artificially spiked with Cr, Cu, Cd, Pb, Hg, phenol, and kerosene. Overall desirability of 0.715 was attained at the following optimal conditions: voltage gradient 0.36 V/cm; polarity reversal rate 17.63 hr; soil pH 10.0. Under these conditions, the expected trivalent Cr remedial efficiency is 64.75%.

Geochemical Modeling of Trivalent Chromium Migration in Saline-Sodic Soil during Lasagna Process: Impact on Soil Physicochemical Properties

PubMed Central

Bukhari, Alaadin; Al-Malack, Muhammad H.; Mu'azu, Nuhu D.; Essa, Mohammed H.

2014-01-01

Trivalent Cr is one of the heavy metals that are difficult to be removed from soil using electrokinetic study because of its geochemical properties. High buffering capacity soil is expected to reduce the mobility of the trivalent Cr and subsequently reduce the remedial efficiency thereby complicating the remediation process. In this study, geochemical modeling and migration of trivalent Cr in saline-sodic soil (high buffering capacity and alkaline) during integrated electrokinetics-adsorption remediation, called the Lasagna process, were investigated. The remedial efficiency of trivalent Cr in addition to the impacts of the Lasagna process on the physicochemical properties of the soil was studied. Box-Behnken design was used to study the interaction effects of voltage gradient, initial contaminant concentration, and polarity reversal rate on the soil pH, electroosmotic volume, soil electrical conductivity, current, and remedial efficiency of trivalent Cr in saline-sodic soil that was artificially spiked with Cr, Cu, Cd, Pb, Hg, phenol, and kerosene. Overall desirability of 0.715 was attained at the following optimal conditions: voltage gradient 0.36 V/cm; polarity reversal rate 17.63 hr; soil pH 10.0. Under these conditions, the expected trivalent Cr remedial efficiency is 64.75 %. PMID:25152905

Interdiffusion of Polycarbonate in Fused Deposition Modeling Welds

NASA Astrophysics Data System (ADS)

Seppala, Jonathan; Forster, Aaron; Satija, Sushil; Jones, Ronald; Migler, Kalman

2015-03-01

Fused deposition modeling (FDM), a now common and inexpensive additive manufacturing method, produces 3D objects by extruding molten polymer layer-by-layer. Compared to traditional polymer processing methods (injection, vacuum, and blow molding), FDM parts have inferior mechanical properties, surface finish, and dimensional stability. From a polymer processing point of view the polymer-polymer weld between each layer limits the mechanical strength of the final part. Unlike traditional processing methods, where the polymer is uniformly melted and entangled, FDM welds are typically weaker due to the short time available for polymer interdiffusion and entanglement. To emulate the FDM process thin film bilayers of polycarbonate/d-polycarbonate were annealed using scaled times and temperatures accessible in FDM. Shift factors from Time-Temperature Superposition, measured by small amplitude oscillatory shear, were used to calculate reasonable annealing times (min) at temperatures below the actual extrusion temperature. The extent of interdiffusion was then measured using neutron reflectivity. Analogous specimens were prepared to characterize the mechanical properties. FDM build parameters were then related to interdiffusion between welded layers and mechanical properties. Understating the relationship between build parameters, interdiffusion, and mechanical strength will allow FDM users to print stronger parts in an intelligent manner rather than using trial-and-error and build parameter lock-in.

Development of Multi-slice Analytical Tool to Support BIM-based Design Process

NASA Astrophysics Data System (ADS)

Atmodiwirjo, P.; Johanes, M.; Yatmo, Y. A.

2017-03-01

This paper describes the on-going development of computational tool to analyse architecture and interior space based on multi-slice representation approach that is integrated with Building Information Modelling (BIM). Architecture and interior space is experienced as a dynamic entity, which have the spatial properties that might be variable from one part of space to another, therefore the representation of space through standard architectural drawings is sometimes not sufficient. The representation of space as a series of slices with certain properties in each slice becomes important, so that the different characteristics in each part of space could inform the design process. The analytical tool is developed for use as a stand-alone application that utilises the data exported from generic BIM modelling tool. The tool would be useful to assist design development process that applies BIM, particularly for the design of architecture and interior spaces that are experienced as continuous spaces. The tool allows the identification of how the spatial properties change dynamically throughout the space and allows the prediction of the potential design problems. Integrating the multi-slice analytical tool in BIM-based design process thereby could assist the architects to generate better design and to avoid unnecessary costs that are often caused by failure to identify problems during design development stages.

A NASTRAN model of a large flexible swing-wing bomber. Volume 5: NASTRAN model development-fairing structure

NASA Technical Reports Server (NTRS)

Mock, W. D.; Latham, R. A.

1982-01-01

The NASTRAN model plan for the fairing structure was expanded in detail to generate the NASTRAN model of this substructure. The grid point coordinates, element definitions, material properties, and sizing data for each element were specified. The fairing model was thoroughly checked out for continuity, connectivity, and constraints. The substructure was processed for structural influence coefficients (SIC) point loadings to determine the deflection characteristics of the fairing model. Finally, a demonstration and validation processing of this substructure was accomplished using the NASTRAN finite element program. The bulk data deck, stiffness matrices, and SIC output data were delivered.

Numerical evaluation of implantable hearing devices using a finite element model of human ear considering viscoelastic properties.

PubMed

Zhang, Jing; Tian, Jiabin; Ta, Na; Huang, Xinsheng; Rao, Zhushi

2016-08-01

Finite element method was employed in this study to analyze the change in performance of implantable hearing devices due to the consideration of soft tissues' viscoelasticity. An integrated finite element model of human ear including the external ear, middle ear and inner ear was first developed via reverse engineering and analyzed by acoustic-structure-fluid coupling. Viscoelastic properties of soft tissues in the middle ear were taken into consideration in this model. The model-derived dynamic responses including middle ear and cochlea functions showed a better agreement with experimental data at high frequencies above 3000 Hz than the Rayleigh-type damping. On this basis, a coupled finite element model consisting of the human ear and a piezoelectric actuator attached to the long process of incus was further constructed. Based on the electromechanical coupling analysis, equivalent sound pressure and power consumption of the actuator corresponding to viscoelasticity and Rayleigh damping were calculated using this model. The analytical results showed that the implant performance of the actuator evaluated using a finite element model considering viscoelastic properties gives a lower output above about 3 kHz than does Rayleigh damping model. Finite element model considering viscoelastic properties was more accurate to numerically evaluate implantable hearing devices. © IMechE 2016.

Hierarchical species distribution models

USGS Publications Warehouse

Hefley, Trevor J.; Hooten, Mevin B.

2016-01-01

Determining the distribution pattern of a species is important to increase scientific knowledge, inform management decisions, and conserve biodiversity. To infer spatial and temporal patterns, species distribution models have been developed for use with many sampling designs and types of data. Recently, it has been shown that count, presence-absence, and presence-only data can be conceptualized as arising from a point process distribution. Therefore, it is important to understand properties of the point process distribution. We examine how the hierarchical species distribution modeling framework has been used to incorporate a wide array of regression and theory-based components while accounting for the data collection process and making use of auxiliary information. The hierarchical modeling framework allows us to demonstrate how several commonly used species distribution models can be derived from the point process distribution, highlight areas of potential overlap between different models, and suggest areas where further research is needed.

Southeast Atlantic Cloud Properties in a Multivariate Statistical Model - How Relevant is Air Mass History for Local Cloud Properties?

NASA Astrophysics Data System (ADS)

Fuchs, Julia; Cermak, Jan; Andersen, Hendrik

2017-04-01

This study aims at untangling the impacts of external dynamics and local conditions on cloud properties in the Southeast Atlantic (SEA) by combining satellite and reanalysis data using multivariate statistics. The understanding of clouds and their determinants at different scales is important for constraining the Earth's radiative budget, and thus prominent in climate-system research. In this study, SEA stratocumulus cloud properties are observed not only as the result of local environmental conditions but also as affected by external dynamics and spatial origins of air masses entering the study area. In order to assess to what extent cloud properties are impacted by aerosol concentration, air mass history, and meteorology, a multivariate approach is conducted using satellite observations of aerosol and cloud properties (MODIS, SEVIRI), information on aerosol species composition (MACC) and meteorological context (ERA-Interim reanalysis). To account for the often-neglected but important role of air mass origin, information on air mass history based on HYSPLIT modeling is included in the statistical model. This multivariate approach is intended to lead to a better understanding of the physical processes behind observed stratocumulus cloud properties in the SEA.

Studying the mechanisms of language learning by varying the learning environment and the learner

PubMed Central

Goldin-Meadow, Susan

2015-01-01

Language learning is a resilient process, and many linguistic properties can be developed under a wide range of learning environments and learners. The first goal of this review is to describe properties of language that can be developed without exposure to a language model – the resilient properties of language – and to explore conditions under which more fragile properties emerge. But even if a linguistic property is resilient, the developmental course that the property follows is likely to vary as a function of learning environment and learner, that is, there are likely to be individual differences in the learning trajectories children follow. The second goal is to consider how the resilient properties are brought to bear on language learning when a child is exposed to a language model. The review ends by considering the implications of both sets of findings for mechanisms, focusing on the role that the body and linguistic input play in language learning. PMID:26668813

Studying the mechanisms of language learning by varying the learning environment and the learner.

PubMed

Goldin-Meadow, Susan

Language learning is a resilient process, and many linguistic properties can be developed under a wide range of learning environments and learners. The first goal of this review is to describe properties of language that can be developed without exposure to a language model - the resilient properties of language - and to explore conditions under which more fragile properties emerge. But even if a linguistic property is resilient, the developmental course that the property follows is likely to vary as a function of learning environment and learner, that is, there are likely to be individual differences in the learning trajectories children follow. The second goal is to consider how the resilient properties are brought to bear on language learning when a child is exposed to a language model. The review ends by considering the implications of both sets of findings for mechanisms, focusing on the role that the body and linguistic input play in language learning.

Application of a Model for Quenching and Partitioning in Hot Stamping of High-Strength Steel

NASA Astrophysics Data System (ADS)

Zhu, Bin; Liu, Zhuang; Wang, Yanan; Rolfe, Bernard; Wang, Liang; Zhang, Yisheng

2018-04-01

Application of quenching and partitioning process in hot stamping has proven to be an effective method to improve the plasticity of advanced high-strength steels (AHSSs). In this study, the hot stamping and partitioning process of advanced high-strength steel 30CrMnSi2Nb is investigated with a hot stamping mold. Given the specific partitioning time and temperature, the influence of quenching temperature on the volume fraction of microstructure evolution and mechanical properties of the above steel are studied in detail. In addition, a model for quenching and partitioning process is applied to predict the carbon diffusion and interface migration during partitioning, which determines the retained austenite volume fraction and final properties of the part. The predicted trends of the retained austenite volume fraction agree with the experimental results. In both cases, the volume fraction of retained austenite increases first and then decreases with the increasing quenching temperature. The optimal quenching temperature is approximately 290 °C for 30CrMnSi2Nb with the partition conditions of 425 °C and 20 seconds. It is suggested that the model can be used to help determine the process parameters to obtain retained austenite as much as possible.

Monoclonal antibody disulfide reduction during manufacturing

PubMed Central

Hutterer, Katariina M.; Hong, Robert W.; Lull, Jonathon; Zhao, Xiaoyang; Wang, Tian; Pei, Rex; Le, M. Eleanor; Borisov, Oleg; Piper, Rob; Liu, Yaoqing Diana; Petty, Krista; Apostol, Izydor; Flynn, Gregory C.

2013-01-01

Manufacturing-induced disulfide reduction has recently been reported for monoclonal human immunoglobulin gamma (IgG) antibodies, a widely used modality in the biopharmaceutical industry. This effect has been tied to components of the intracellular thioredoxin reduction system that are released upon cell breakage. Here, we describe the effect of process parameters and intrinsic molecule properties on the extent of reduction. Material taken from cell cultures at the end of production displayed large variations in the extent of antibody reduction between different products, including no reduction, when subjected to the same reduction-promoting harvest conditions. Additionally, in a reconstituted model in which process variables could be isolated from product properties, we found that antibody reduction was dependent on the cell line (clone) and cell culture process. A bench-scale model using a thioredoxin/thioredoxin reductase regeneration system revealed that reduction susceptibility depended on not only antibody class but also light chain type; the model further demonstrates that the trend in reducibility was identical to DTT reduction sensitivity following the order IgG1λ > IgG1κ > IgG2λ > IgG2κ. Thus, both product attributes and process parameters contribute to the extent of antibody reduction during production. PMID:23751615

A Computational Study of Plastic Deformation in AISI 304 Induced by Surface Mechanical Attrition Treatment

NASA Astrophysics Data System (ADS)

Zhang, X. C.; Lu, J.; Shi, S. Q.

2010-05-01

As a technique of grain refinement process by plastic deformation, surface mechanical attrition treatment (SMAT) has been developed to be one of the most effective ways to optimize the mechanical properties of various materials including pure metals and alloys. SMAT can significantly reduce grain size into nanometer regime in the surface layer of bulk materials, providing tremendous opportunities for improving physical, chemical and mechanical properties of the materials. In this work, a computational modeling of the surface mechanical attrition treatment (SMAT) process is presented, in which Johnson-Cook plasticity model and the finite element method were employed to study the high strain rate, elastic-plastic dynamic process of ball impact on a metallic target. AISI 304 steel with low stacking fault energy was chosen as the target material. First, a random impact model was used to analyze the statistic characteristics of ball impact, and then the plastic deformation behavior and residual stress distribution in AISI 304 stainless steel during SMAT were studied. The simulation results show that the compressive residual stress and vertical deformation of the surface structures were directly affected by ball impact frequency, incident impact angle and ball diameter used in SMAT process.

Application of characteristic time concepts for hydraulic fracture configuration design, control, and optimization

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

Advani, S.H.; Lee, T.S.; Moon, H.

1992-10-01

The analysis of pertinent energy components or affiliated characteristic times for hydraulic stimulation processes serves as an effective tool for fracture configuration designs optimization, and control. This evaluation, in conjunction with parametric sensitivity studies, provides a rational base for quantifying dominant process mechanisms and the roles of specified reservoir properties relative to controllable hydraulic fracture variables for a wide spectrum of treatment scenarios. Results are detailed for the following multi-task effort: (a) Application of characteristic time concept and parametric sensitivity studies for specialized fracture geometries (rectangular, penny-shaped, elliptical) and three-layered elliptic crack models (in situ stress, elastic moduli, and fracturemore » toughness contrasts). (b) Incorporation of leak-off effects for models investigated in (a). (c) Simulation of generalized hydraulic fracture models and investigation of the role of controllable vaxiables and uncontrollable system properties. (d) Development of guidelines for hydraulic fracture design and optimization.« less

Application of characteristic time concepts for hydraulic fracture configuration design, control, and optimization. Final report

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

Advani, S.H.; Lee, T.S.; Moon, H.

1992-10-01

The analysis of pertinent energy components or affiliated characteristic times for hydraulic stimulation processes serves as an effective tool for fracture configuration designs optimization, and control. This evaluation, in conjunction with parametric sensitivity studies, provides a rational base for quantifying dominant process mechanisms and the roles of specified reservoir properties relative to controllable hydraulic fracture variables for a wide spectrum of treatment scenarios. Results are detailed for the following multi-task effort: (a) Application of characteristic time concept and parametric sensitivity studies for specialized fracture geometries (rectangular, penny-shaped, elliptical) and three-layered elliptic crack models (in situ stress, elastic moduli, and fracturemore » toughness contrasts). (b) Incorporation of leak-off effects for models investigated in (a). (c) Simulation of generalized hydraulic fracture models and investigation of the role of controllable vaxiables and uncontrollable system properties. (d) Development of guidelines for hydraulic fracture design and optimization.« less

Decoding the non-stationary neuron spike trains by dual Monte Carlo point process estimation in motor Brain Machine Interfaces.

PubMed

Liao, Yuxi; Li, Hongbao; Zhang, Qiaosheng; Fan, Gong; Wang, Yiwen; Zheng, Xiaoxiang

2014-01-01

Decoding algorithm in motor Brain Machine Interfaces translates the neural signals to movement parameters. They usually assume the connection between the neural firings and movements to be stationary, which is not true according to the recent studies that observe the time-varying neuron tuning property. This property results from the neural plasticity and motor learning etc., which leads to the degeneration of the decoding performance when the model is fixed. To track the non-stationary neuron tuning during decoding, we propose a dual model approach based on Monte Carlo point process filtering method that enables the estimation also on the dynamic tuning parameters. When applied on both simulated neural signal and in vivo BMI data, the proposed adaptive method performs better than the one with static tuning parameters, which raises a promising way to design a long-term-performing model for Brain Machine Interfaces decoder.

The Inverse Bagging Algorithm: Anomaly Detection by Inverse Bootstrap Aggregating

NASA Astrophysics Data System (ADS)

Vischia, Pietro; Dorigo, Tommaso

2017-03-01

For data sets populated by a very well modeled process and by another process of unknown probability density function (PDF), a desired feature when manipulating the fraction of the unknown process (either for enhancing it or suppressing it) consists in avoiding to modify the kinematic distributions of the well modeled one. A bootstrap technique is used to identify sub-samples rich in the well modeled process, and classify each event according to the frequency of it being part of such sub-samples. Comparisons with general MVA algorithms will be shown, as well as a study of the asymptotic properties of the method, making use of a public domain data set that models a typical search for new physics as performed at hadronic colliders such as the Large Hadron Collider (LHC).

Determining the compactive effort required to model pavement voids using the Corps of Engineers gyratory testing machine.

DOT National Transportation Integrated Search

1997-11-01

Various agencies have used the Corps of Engineers gyratory testing machine (GTM) to design and test asphalt mixes. Materials properties such as shear strength and strain are measured during the compaction process. However, a compaction process duplic...

A multiscale Markov random field model in wavelet domain for image segmentation

NASA Astrophysics Data System (ADS)

Dai, Peng; Cheng, Yu; Wang, Shengchun; Du, Xinyu; Wu, Dan

2017-07-01

The human vision system has abilities for feature detection, learning and selective attention with some properties of hierarchy and bidirectional connection in the form of neural population. In this paper, a multiscale Markov random field model in the wavelet domain is proposed by mimicking some image processing functions of vision system. For an input scene, our model provides its sparse representations using wavelet transforms and extracts its topological organization using MRF. In addition, the hierarchy property of vision system is simulated using a pyramid framework in our model. There are two information flows in our model, i.e., a bottom-up procedure to extract input features and a top-down procedure to provide feedback controls. The two procedures are controlled simply by two pyramidal parameters, and some Gestalt laws are also integrated implicitly. Equipped with such biological inspired properties, our model can be used to accomplish different image segmentation tasks, such as edge detection and region segmentation.

Intelligent Weld Manufacturing: Role of Integrated Computational Welding Engineering

DOE PAGES

David, Stan A.; Chen, Jian; Feng, Zhili; ...

2017-12-02

A master welder uses his sensory perceptions to evaluate the process and connect them with his/her knowledge base to take the necessary corrective measures with his/her acquired skills to make a good weld. All these actions must take place in real time. Success depends on intuition and skills, and the procedure is labor-intensive and frequently unreliable. The solution is intelligent weld manufacturing. The ultimate goal of intelligent weld manufacturing would involve sensing and control of heat source position, weld temperature, weld penetration, defect formation and ultimately control of microstructure and properties. This involves a solution to a problem (welding) withmore » many highly coupled and nonlinear variables. The trend is to use an emerging tool known as intelligent control. This approach enables the user to choose a desirable end factor such as properties, defect control, or productivity to derive the selection of process parameters such as current, voltage, or speed to provide for appropriate control of the process. Important elements of intelligent manufacturing are sensing and control theory and design, process modeling, and artificial intelligence. Significant progress has been made in all these areas. Integrated computational welding engineering (ICWE) is an emerging field that will aid in the realization of intelligent weld manufacturing. The paper will discuss the progress in process modeling, microstructure, properties, and process control and automation and the importance of ICWE. Also, control and automation strategies for friction stir welding will be discussed.« less

Intelligent Weld Manufacturing: Role of Integrated Computational Welding Engineering

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

David, Stan A.; Chen, Jian; Feng, Zhili

A master welder uses his sensory perceptions to evaluate the process and connect them with his/her knowledge base to take the necessary corrective measures with his/her acquired skills to make a good weld. All these actions must take place in real time. Success depends on intuition and skills, and the procedure is labor-intensive and frequently unreliable. The solution is intelligent weld manufacturing. The ultimate goal of intelligent weld manufacturing would involve sensing and control of heat source position, weld temperature, weld penetration, defect formation and ultimately control of microstructure and properties. This involves a solution to a problem (welding) withmore » many highly coupled and nonlinear variables. The trend is to use an emerging tool known as intelligent control. This approach enables the user to choose a desirable end factor such as properties, defect control, or productivity to derive the selection of process parameters such as current, voltage, or speed to provide for appropriate control of the process. Important elements of intelligent manufacturing are sensing and control theory and design, process modeling, and artificial intelligence. Significant progress has been made in all these areas. Integrated computational welding engineering (ICWE) is an emerging field that will aid in the realization of intelligent weld manufacturing. The paper will discuss the progress in process modeling, microstructure, properties, and process control and automation and the importance of ICWE. Also, control and automation strategies for friction stir welding will be discussed.« less

Experimental study of tensile strength of pharmaceutical tablets: effect of the diluent nature and compression pressure

NASA Astrophysics Data System (ADS)

Juban, Audrey; Briançon, Stéphanie; Puel, François; Hoc, Thierry; Nouguier-Lehon, Cécile

2017-06-01

In the pharmaceutical field, tablets are the most common dosage form for oral administration in the world. Among different manufacturing processes, direct compression is widely used because of its economics interest and it is a process which avoids the steps of wet granulation and drying processes. Tablets are composed of at least two ingredients: an active pharmaceutical ingredient (API) which is mixed with a diluent. The nature of the powders and the processing conditions are crucial for the properties of the blend and, consequently, strongly influence the mechanical characteristics of tablets. Moreover, tablets have to present a suitable mechanical strength to avoid crumbling or breaking when handling, while ensuring an appropriate disintegration after administration. Accordingly, this mechanical property is an essential parameter to consider. Experimental results showed that proportion of the diluent, fragmentary (DCPA) or plastic (MCC), had a large influence on the tensile strength evolution with API content as well as the compression load applied during tableting process. From these results a model was developed in order to predict the tensile strength of binary tablets by knowing the compression pressure. The validity of this model was demonstrated for the two studied systems and a comparison was made with two existing models.

Multi-Scale Low-Entropy Method for Optimizing the Processing Parameters during Automated Fiber Placement

PubMed Central

Han, Zhenyu; Sun, Shouzheng; Fu, Hongya; Fu, Yunzhong

2017-01-01

Automated fiber placement (AFP) process includes a variety of energy forms and multi-scale effects. This contribution proposes a novel multi-scale low-entropy method aiming at optimizing processing parameters in an AFP process, where multi-scale effect, energy consumption, energy utilization efficiency and mechanical properties of micro-system could be taken into account synthetically. Taking a carbon fiber/epoxy prepreg as an example, mechanical properties of macro–meso–scale are obtained by Finite Element Method (FEM). A multi-scale energy transfer model is then established to input the macroscopic results into the microscopic system as its boundary condition, which can communicate with different scales. Furthermore, microscopic characteristics, mainly micro-scale adsorption energy, diffusion coefficient entropy–enthalpy values, are calculated under different processing parameters based on molecular dynamics method. Low-entropy region is then obtained in terms of the interrelation among entropy–enthalpy values, microscopic mechanical properties (interface adsorbability and matrix fluidity) and processing parameters to guarantee better fluidity, stronger adsorption, lower energy consumption and higher energy quality collaboratively. Finally, nine groups of experiments are carried out to verify the validity of the simulation results. The results show that the low-entropy optimization method can reduce void content effectively, and further improve the mechanical properties of laminates. PMID:28869520

Multi-Scale Low-Entropy Method for Optimizing the Processing Parameters during Automated Fiber Placement.

PubMed

Han, Zhenyu; Sun, Shouzheng; Fu, Hongya; Fu, Yunzhong

2017-09-03

Automated fiber placement (AFP) process includes a variety of energy forms and multi-scale effects. This contribution proposes a novel multi-scale low-entropy method aiming at optimizing processing parameters in an AFP process, where multi-scale effect, energy consumption, energy utilization efficiency and mechanical properties of micro-system could be taken into account synthetically. Taking a carbon fiber/epoxy prepreg as an example, mechanical properties of macro-meso-scale are obtained by Finite Element Method (FEM). A multi-scale energy transfer model is then established to input the macroscopic results into the microscopic system as its boundary condition, which can communicate with different scales. Furthermore, microscopic characteristics, mainly micro-scale adsorption energy, diffusion coefficient entropy-enthalpy values, are calculated under different processing parameters based on molecular dynamics method. Low-entropy region is then obtained in terms of the interrelation among entropy-enthalpy values, microscopic mechanical properties (interface adsorbability and matrix fluidity) and processing parameters to guarantee better fluidity, stronger adsorption, lower energy consumption and higher energy quality collaboratively. Finally, nine groups of experiments are carried out to verify the validity of the simulation results. The results show that the low-entropy optimization method can reduce void content effectively, and further improve the mechanical properties of laminates.

Computational modeling of single-cell mechanics and cytoskeletal mechanobiology.

PubMed

Rajagopal, Vijay; Holmes, William R; Lee, Peter Vee Sin

2018-03-01

Cellular cytoskeletal mechanics plays a major role in many aspects of human health from organ development to wound healing, tissue homeostasis and cancer metastasis. We summarize the state-of-the-art techniques for mathematically modeling cellular stiffness and mechanics and the cytoskeletal components and factors that regulate them. We highlight key experiments that have assisted model parameterization and compare the advantages of different models that have been used to recapitulate these experiments. An overview of feed-forward mechanisms from signaling to cytoskeleton remodeling is provided, followed by a discussion of the rapidly growing niche of encapsulating feedback mechanisms from cytoskeletal and cell mechanics to signaling. We discuss broad areas of advancement that could accelerate research and understanding of cellular mechanobiology. A precise understanding of the molecular mechanisms that affect cell and tissue mechanics and function will underpin innovations in medical device technologies of the future. WIREs Syst Biol Med 2018, 10:e1407. doi: 10.1002/wsbm.1407 This article is categorized under: Models of Systems Properties and Processes > Mechanistic Models Physiology > Mammalian Physiology in Health and Disease Models of Systems Properties and Processes > Cellular Models. © 2017 The Authors. WIREs Systems Biology and Medicine published by Wiley Periodicals, Inc.

Computational modeling of single‐cell mechanics and cytoskeletal mechanobiology

PubMed Central

Holmes, William R.; Lee, Peter Vee Sin

2017-01-01

Cellular cytoskeletal mechanics plays a major role in many aspects of human health from organ development to wound healing, tissue homeostasis and cancer metastasis. We summarize the state‐of‐the‐art techniques for mathematically modeling cellular stiffness and mechanics and the cytoskeletal components and factors that regulate them. We highlight key experiments that have assisted model parameterization and compare the advantages of different models that have been used to recapitulate these experiments. An overview of feed‐forward mechanisms from signaling to cytoskeleton remodeling is provided, followed by a discussion of the rapidly growing niche of encapsulating feedback mechanisms from cytoskeletal and cell mechanics to signaling. We discuss broad areas of advancement that could accelerate research and understanding of cellular mechanobiology. A precise understanding of the molecular mechanisms that affect cell and tissue mechanics and function will underpin innovations in medical device technologies of the future. WIREs Syst Biol Med 2018, 10:e1407. doi: 10.1002/wsbm.1407 This article is categorized under: 1Models of Systems Properties and Processes > Mechanistic Models2Physiology > Mammalian Physiology in Health and Disease3Models of Systems Properties and Processes > Cellular Models PMID:29195023

Enabling model checking for collaborative process analysis: from BPMN to `Network of Timed Automata'

NASA Astrophysics Data System (ADS)

Mallek, Sihem; Daclin, Nicolas; Chapurlat, Vincent; Vallespir, Bruno

2015-04-01

Interoperability is a prerequisite for partners involved in performing collaboration. As a consequence, the lack of interoperability is now considered a major obstacle. The research work presented in this paper aims to develop an approach that allows specifying and verifying a set of interoperability requirements to be satisfied by each partner in the collaborative process prior to process implementation. To enable the verification of these interoperability requirements, it is necessary first and foremost to generate a model of the targeted collaborative process; for this research effort, the standardised language BPMN 2.0 is used. Afterwards, a verification technique must be introduced, and model checking is the preferred option herein. This paper focuses on application of the model checker UPPAAL in order to verify interoperability requirements for the given collaborative process model. At first, this step entails translating the collaborative process model from BPMN into a UPPAAL modelling language called 'Network of Timed Automata'. Second, it becomes necessary to formalise interoperability requirements into properties with the dedicated UPPAAL language, i.e. the temporal logic TCTL.

Effect of sub-pore scale morphology of biological deposits on porous media flow properties

NASA Astrophysics Data System (ADS)

Ghezzehei, T. A.

2012-12-01

Biological deposits often influence fluid flow by altering the pore space morphology and related hydrologic properties such as porosity, water retention characteristics, and permeability. In most coupled-processes models changes in porosity are inferred from biological process models using mass-balance. The corresponding evolution of permeability is estimated using (semi-) empirical porosity-permeability functions such as the Kozeny-Carman equation or power-law functions. These equations typically do not account for the heterogeneous spatial distribution and morphological irregularities of the deposits. As a result, predictions of permeability evolution are generally unsatisfactory. In this presentation, we demonstrate the significance of pore-scale deposit distribution on porosity-permeability relations using high resolution simulations of fluid flow through a single pore interspersed with deposits of varying morphologies. Based on these simulations, we present a modification to the Kozeny-Carman model that accounts for the shape of the deposits. Limited comparison with published experimental data suggests the plausibility of the proposed conceptual model.

Experimentally Determining β-Decay Intensities for 103,104Nb to Improve R-process Calculations

NASA Astrophysics Data System (ADS)

Gombas, J.; Deyoung, P. D.; Spyrou, A.; Dombos, A. C.; Lyons, S.; SuN Collaboration

2017-09-01

The rapid neutron capture process (r-process) is responsible for the formation of nuclei heavier than iron. This process is theorized to occur in supernovas and/or neutron star mergers. R-process calculations require the accurate knowledge of a significant amount of nuclear properties, the majority of which are not known experimentally. Nuclear masses, β-decay properties and neutron-capture reactions are all input ingredients into r-process models. This present study focuses on the β decay of 103Nb and 104Nb. The β decay of 103Nb and 104Nb, two nuclei found in the r-process, were observed at the NSCL using the Summing NaI (SuN) detector. An unstable beam implanted inside SuN. The γ rays were measured in coincidence with the emitted electrons. The β-decay intensity function was then extracted. The experimentally determined functions for 103Nb and 104Nb will be compared to predictions made by the Quasi Random Phase Approximation (QRPA) model. These theoretical calculations are used in astrophysical models of the r-process. This comparison will lead to a better understanding of the nuclear structure for 103Nb and 104Nb. A more dependable prediction of the formation of heavier nuclei birthed from supernovas or neutron star mergers can then be made. This material is based upon work supported by the National Science Foundation under Grant No. PHY-1613188 and PHY-1306074, and by the Hope College Department of Physics Guess Research Fund.

Recrystallization and Grain Growth Kinetics in Binary Alpha Titanium-Aluminum Alloys

NASA Astrophysics Data System (ADS)

Trump, Anna Marie

Titanium alloys are used in a variety of important naval and aerospace applications and often undergo thermomechanical processing which leads to recrystallization and grain growth. Both of these processes have a significant impact on the mechanical properties of the material. Therefore, understanding the kinetics of these processes is crucial to being able to predict the final properties. Three alloys are studied with varying concentrations of aluminum which allows for the direct quantification of the effect of aluminum content on the kinetics of recrystallization and grain growth. Aluminum is the most common alpha stabilizing alloying element used in titanium alloys, however the effect of aluminum on these processes has not been previously studied. This work is also part of a larger Integrated Computational Materials Engineering (ICME) effort whose goal is to combine both computational and experimental efforts to develop computationally efficient models that predict materials microstructure and properties based on processing history. The static recrystallization kinetics are measured using an electron backscatter diffraction (EBSD) technique and a significant retardation in the kinetics is observed with increasing aluminum concentration. An analytical model is then used to capture these results and is able to successfully predict the effect of solute concentration on the time to 50% recrystallization. The model reveals that this solute effect is due to a combination of a decrease in grain boundary mobility and a decrease in driving force with increasing aluminum concentration. The effect of microstructural inhomogeneities is also experimentally quantified and the results are validated with a phase field model for recrystallization. These microstructural inhomogeneities explain the experimentally measured Avrami exponent, which is lower than the theoretical value calculated by the JMAK model. Similar to the effect seen in recrystallization, the addition of aluminum also significantly slows downs the grain growth kinetics. This is generally attributed to the solute drag effect due to segregation of solute atoms at the grain boundaries, however aluminum segregation is not observed in these alloys. The mechanism for this result is explained and is used to validate the prediction of an existing model for solute drag.

Study on creep properties of Japonica cooked rice and its relationship with rice chemical compositions and sensory evaluation

USDA-ARS?s Scientific Manuscript database

Creep properties of four varieties japonica cooked rice were tested using a Dynamic Mechanical Analyser (DMA Q800). The creep curve was described by Burgers model. The creep process of japonica cooked rice mainly consisted of retarded elastic deformation, epsilonR and viscous flow deformation, epsil...

Cirrus clouds. I - A cirrus cloud model. II - Numerical experiments on the formation and maintenance of cirrus

NASA Technical Reports Server (NTRS)

Starr, D. OC.; Cox, S. K.

1985-01-01

A simplified cirrus cloud model is presented which may be used to investigate the role of various physical processes in the life cycle of a cirrus cloud. The model is a two-dimensional, time-dependent, Eulerian numerical model where the focus is on cloud-scale processes. Parametrizations are developed to account for phase changes of water, radiative processes, and the effects of microphysical structure on the vertical flux of ice water. The results of a simulation of a thin cirrostratus cloud are given. The results of numerical experiments performed with the model are described in order to demonstrate the important role of cloud-scale processes in determining the cloud properties maintained in response to larger scale forcing. The effects of microphysical composition and radiative processes are considered, as well as their interaction with thermodynamic and dynamic processes within the cloud. It is shown that cirrus clouds operate in an entirely different manner than liquid phase stratiform clouds.

Understanding Surface Adhesion in Nature: A Peeling Model

PubMed Central

Gu, Zhen; Li, Siheng; Zhang, Feilong

2016-01-01

Nature often exhibits various interesting and unique adhesive surfaces. The attempt to understand the natural adhesion phenomena can continuously guide the design of artificial adhesive surfaces by proposing simplified models of surface adhesion. Among those models, a peeling model can often effectively reflect the adhesive property between two surfaces during their attachment and detachment processes. In the context, this review summarizes the recent advances about the peeling model in understanding unique adhesive properties on natural and artificial surfaces. It mainly includes four parts: a brief introduction to natural surface adhesion, the theoretical basis and progress of the peeling model, application of the peeling model, and finally, conclusions. It is believed that this review is helpful to various fields, such as surface engineering, biomedicine, microelectronics, and so on. PMID:27812476

Applications of the solvation parameter model in reversed-phase liquid chromatography.

PubMed

Poole, Colin F; Lenca, Nicole

2017-02-24

The solvation parameter model is widely used to provide insight into the retention mechanism in reversed-phase liquid chromatography, for column characterization, and in the development of surrogate chromatographic models for biopartitioning processes. The properties of the separation system are described by five system constants representing all possible intermolecular interactions for neutral molecules. The general model can be extended to include ions and enantiomers by adding new descriptors to encode the specific properties of these compounds. System maps provide a comprehensive overview of the separation system as a function of mobile phase composition and/or temperature for method development. The solvation parameter model has been applied to gradient elution separations but here theory and practice suggest a cautious approach since the interpretation of system and compound properties derived from its use are approximate. A growing application of the solvation parameter model in reversed-phase liquid chromatography is the screening of surrogate chromatographic systems for estimating biopartitioning properties. Throughout the discussion of the above topics success as well as known and likely deficiencies of the solvation parameter model are described with an emphasis on the role of the heterogeneous properties of the interphase region on the interpretation and understanding of the general retention mechanism in reversed-phase liquid chromatography for porous chemically bonded sorbents. Copyright © 2016 Elsevier B.V. All rights reserved.

Southern Regional Center for Lightweight Innovative Design

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

Wang, Paul T.

The Southern Regional Center for Lightweight Innovative Design (SRCLID) has developed an experimentally validated cradle-to-grave modeling and simulation effort to optimize automotive components in order to decrease weight and cost, yet increase performance and safety in crash scenarios. In summary, the three major objectives of this project are accomplished: To develop experimentally validated cradle-to-grave modeling and simulation tools to optimize automotive and truck components for lightweighting materials (aluminum, steel, and Mg alloys and polymer-based composites) with consideration of uncertainty to decrease weight and cost, yet increase the performance and safety in impact scenarios; To develop multiscale computational models that quantifymore » microstructure-property relations by evaluating various length scales, from the atomic through component levels, for each step of the manufacturing process for vehicles; and To develop an integrated K-12 educational program to educate students on lightweighting designs and impact scenarios. In this final report, we divided the content into two parts: the first part contains the development of building blocks for the project, including materials and process models, process-structure-property (PSP) relationship, and experimental validation capabilities; the second part presents the demonstration task for Mg front-end work associated with USAMP projects.« less

Study on processing immiscible materials in zero gravity

NASA Technical Reports Server (NTRS)

Reger, J. L.; Mendelson, R. A.

1975-01-01

An experimental investigation was conducted to evaluate mixing immiscible metal combinations under several process conditions. Under one-gravity, these included thermal processing, thermal plus electromagnetic mixing, and thermal plus acoustic mixing. The same process methods were applied during free fall on the MSFC drop tower facility. The design is included of drop tower apparatus to provide the electromagnetic and acoustic mixing equipment, and a thermal model was prepared to design the specimen and cooling procedure. Materials systems studied were Ca-La, Cd-Ga and Al-Bi; evaluation of the processed samples included the morphology and electronic property measurements. The morphology was developed using optical and scanning electron microscopy and microprobe analyses. Electronic property characterization of the superconducting transition temperatures were made using an impedance change-tuned coil method.

High Volume Fraction Carbon Nanotube Composites for Aerospace Applications

NASA Technical Reports Server (NTRS)

Siochi, Emilie J.; Kim, Jae-Woo; Sauti, Godfrey; Cano, Roberto J.; Wincheski, Russell A.; Ratcliffe, James G.; Czabaj, Michael; Jensen, Benjamin D.; Wise, Kristopher E.

2015-01-01

Reported nanoscale mechanical properties of carbon nanotubes (CNTs) suggest that their use may enable the fabrication of significantly lighter structures for use in space applications. To be useful in the fabrication of large structures, however, their attractive nanoscale properties must be retained as they are scaled up to bulk materials and converted into practically useful forms. Advances in CNT production have significantly increased the quantities available for use in manufacturing processes, but challenges remain with the retention of nanoscale properties in larger assemblies of CNTs. This work summarizes recent progress in producing carbon nanotube composites with tensile properties approaching those of carbon fiber reinforced polymer composites. These advances were achieved in nanocomposites with CNT content of 70% by weight. The processing methods explored to yield these CNT composite properties will be discussed, as will the characterization and test methods that were developed to provide insight into the factors that contribute to the enhanced tensile properties. Technology maturation was guided by parallel advancements in computational modeling tools that aided in the interpretation of experimental data.

Variations on a theme - the evolution of hydrocarbon solids. I. Compositional and spectral modelling - the eRCN and DG models

NASA Astrophysics Data System (ADS)

Jones, A. P.

2012-04-01

Context. The compositional properties of hydrogenated amorphous carbons are known to evolve in response to the local conditions. Aims: We present a model for low-temperature, amorphous hydrocarbon solids, based on the microphysical properties of random and defected networks of carbon and hydrogen atoms, that can be used to study and predict the evolution of their properties in the interstellar medium. Methods: We adopt an adaptable and prescriptive approach to model these materials, which is based on a random covalent network (RCN) model, extended here to a full compositional derivation (the eRCN model), and a defective graphite (DG) model for the hydrogen poorer materials where the eRCN model is no longer valid. Results: We provide simple expressions that enable the determination of the structural, infrared and spectral properties of amorphous hydrocarbon grains as a function of the hydrogen atomic fraction, XH. Structural annealing, resulting from hydrogen atom loss, results in a transition from H-rich, aliphatic-rich to H-poor, aromatic-rich materials. Conclusions: The model predicts changes in the optical properties of hydrogenated amorphous carbon dust in response to the likely UV photon-driven and/or thermal annealing processes resulting, principally, from the radiation field in the environment. We show how this dust component will evolve, compositionally and structurally in the interstellar medium in response to the local conditions. Appendices A and B are available in electronic form at http://www.aanda.org

Modelling of peak temperature during friction stir processing of magnesium alloy AZ91

NASA Astrophysics Data System (ADS)

Vaira Vignesh, R.; Padmanaban, R.

2018-02-01

Friction stir processing (FSP) is a solid state processing technique with potential to modify the properties of the material through microstructural modification. The study of heat transfer in FSP aids in the identification of defects like flash, inadequate heat input, poor material flow and mixing etc. In this paper, transient temperature distribution during FSP of magnesium alloy AZ91 was simulated using finite element modelling. The numerical model results were validated using the experimental results from the published literature. The model was used to predict the peak temperature obtained during FSP for various process parameter combinations. The simulated peak temperature results were used to develop a statistical model. The effect of process parameters namely tool rotation speed, tool traverse speed and shoulder diameter of the tool on the peak temperature was investigated using the developed statistical model. It was found that peak temperature was directly proportional to tool rotation speed and shoulder diameter and inversely proportional to tool traverse speed.

A model for the Space Shuttle Main Engine High Pressure Oxidizer Turbopump shaft seal system

NASA Technical Reports Server (NTRS)

Paxson, Daniel E.

1990-01-01

A model of the High Pressure Oxidizer Turbopump (HPOTP) shaft seal system on the Space Shuttle Main Engine (SSME) is described. The model predicts the fluid properties and flow rates throughout this system for a number of conditions simulating failed seals. The results agree well with qualitative expectations and redline values but cannot be verified with actual data due to the lack thereof. The results indicate that each failure mode results in a unique distribution of properties throughout the seal system and can therefore be individually identified given the proper instrumentation. Furthermore, the detection process can be built on the principle of qualitative reasoning without the use of exact fluid property values. A simplified implementation of the model which does not include the slinger/labyrinth seal combination has been developed and will be useful for inclusion in a real-time diagnostic system.

Issues related to aircraft take-off plumes in a mesoscale photochemical model.

PubMed

Bossioli, Elissavet; Tombrou, Maria; Helmis, Costas; Kurtenbach, Ralf; Wiesen, Peter; Schäfer, Klaus; Dandou, Aggeliki; Varotsos, Kostas V

2013-07-01

The physical and chemical characteristics of aircraft plumes at the take-off phase are simulated with the mesoscale CAMx model using the individual plume segment approach, in a highly resolved domain, covering the Athens International Airport. Emission indices during take-off measured at the Athens International Airport are incorporated. Model predictions are compared with in situ point and path-averaged observations (NO, NO₂) downwind of the runway at the ground. The influence of modeling process, dispersion properties and background air composition on the chemical evolution of the aircraft plumes is examined. It is proven that the mixing properties mainly determine the plume dispersion. The initial plume properties become significant for the selection of the appropriate vertical resolution. Besides these factors, the background NOx and O₃ concentration levels control NOx distribution and their conversion to nitrogen reservoir species. Copyright © 2013 Elsevier B.V. All rights reserved.

Modeling for Ultrasonic Health Monitoring of Foams with Embedded Sensors

NASA Technical Reports Server (NTRS)

Wang, L.; Rokhlin, S. I.; Rokhlin, Stanislav, I.

2005-01-01

In this report analytical and numerical methods are proposed to estimate the effective elastic properties of regular and random open-cell foams. The methods are based on the principle of minimum energy and on structural beam models. The analytical solutions are obtained using symbolic processing software. The microstructure of the random foam is simulated using Voronoi tessellation together with a rate-dependent random close-packing algorithm. The statistics of the geometrical properties of random foams corresponding to different packing fractions have been studied. The effects of the packing fraction on elastic properties of the foams have been investigated by decomposing the compliance into bending and axial compliance components. It is shown that the bending compliance increases and the axial compliance decreases when the packing fraction increases. Keywords: Foam; Elastic properties; Finite element; Randomness

Workshop on the Thermophysical Properties of Molten Materials

NASA Technical Reports Server (NTRS)

1993-01-01

The role of accurate thermophysical property data in the process design and modeling of solidification processes was the subject of a workshop held on 22-23 Oct. 1992 in Cleveland, Ohio. The workshop was divided into three sequential sessions dealing with (1) industrial needs and priorities for thermophysical data, (2) experimental capabilities for measuring the necessary data, and (3) theoretical capabilities for predicting the necessary data. In addition, a 2-hour panel discussion of the salient issues was featured as well as a 2-hour caucus that assessed priorities and identified action plans.

Scratching as a Fracture Process: From Butter to Steel

NASA Astrophysics Data System (ADS)

Akono, A.-T.; Reis, P. M.; Ulm, F.-J.

2011-05-01

We present results of a hybrid experimental and theoretical investigation of the fracture scaling in scratch tests and show that scratching is a fracture dominated process. Validated for paraffin wax, cement paste, Jurassic limestone and steel, we derive a model that provides a quantitative means to relate quantities measured in scratch tests to fracture properties of materials at multiple scales. The scalability of scratching for different probes and depths opens new venues towards miniaturization of our technique, to extract fracture properties of materials at even smaller length scales.

RANdom SAmple Consensus (RANSAC) algorithm for material-informatics: application to photovoltaic solar cells.

PubMed

Kaspi, Omer; Yosipof, Abraham; Senderowitz, Hanoch

2017-06-06

An important aspect of chemoinformatics and material-informatics is the usage of machine learning algorithms to build Quantitative Structure Activity Relationship (QSAR) models. The RANdom SAmple Consensus (RANSAC) algorithm is a predictive modeling tool widely used in the image processing field for cleaning datasets from noise. RANSAC could be used as a "one stop shop" algorithm for developing and validating QSAR models, performing outlier removal, descriptors selection, model development and predictions for test set samples using applicability domain. For "future" predictions (i.e., for samples not included in the original test set) RANSAC provides a statistical estimate for the probability of obtaining reliable predictions, i.e., predictions within a pre-defined number of standard deviations from the true values. In this work we describe the first application of RNASAC in material informatics, focusing on the analysis of solar cells. We demonstrate that for three datasets representing different metal oxide (MO) based solar cell libraries RANSAC-derived models select descriptors previously shown to correlate with key photovoltaic properties and lead to good predictive statistics for these properties. These models were subsequently used to predict the properties of virtual solar cells libraries highlighting interesting dependencies of PV properties on MO compositions.

Experimental Methods for Investigation of Shape Memory Based Elastocaloric Cooling Processes and Model Validation

PubMed Central

Schmidt, Marvin; Ullrich, Johannes; Wieczorek, André; Frenzel, Jan; Eggeler, Gunther; Schütze, Andreas; Seelecke, Stefan

2016-01-01

Shape Memory Alloys (SMA) using elastocaloric cooling processes have the potential to be an environmentally friendly alternative to the conventional vapor compression based cooling process. Nickel-Titanium (Ni-Ti) based alloy systems, especially, show large elastocaloric effects. Furthermore, exhibit large latent heats which is a necessary material property for the development of an efficient solid-state based cooling process. A scientific test rig has been designed to investigate these processes and the elastocaloric effects in SMAs. The realized test rig enables independent control of an SMA's mechanical loading and unloading cycles, as well as conductive heat transfer between SMA cooling elements and a heat source/sink. The test rig is equipped with a comprehensive monitoring system capable of synchronized measurements of mechanical and thermal parameters. In addition to determining the process-dependent mechanical work, the system also enables measurement of thermal caloric aspects of the elastocaloric cooling effect through use of a high-performance infrared camera. This combination is of particular interest, because it allows illustrations of localization and rate effects — both important for efficient heat transfer from the medium to be cooled. The work presented describes an experimental method to identify elastocaloric material properties in different materials and sample geometries. Furthermore, the test rig is used to investigate different cooling process variations. The introduced analysis methods enable a differentiated consideration of material, process and related boundary condition influences on the process efficiency. The comparison of the experimental data with the simulation results (of a thermomechanically coupled finite element model) allows for better understanding of the underlying physics of the elastocaloric effect. In addition, the experimental results, as well as the findings based on the simulation results, are used to improve the material properties. PMID:27168093

Experimental Methods for Investigation of Shape Memory Based Elastocaloric Cooling Processes and Model Validation.

PubMed

Schmidt, Marvin; Ullrich, Johannes; Wieczorek, André; Frenzel, Jan; Eggeler, Gunther; Schütze, Andreas; Seelecke, Stefan

2016-05-02

Shape Memory Alloys (SMA) using elastocaloric cooling processes have the potential to be an environmentally friendly alternative to the conventional vapor compression based cooling process. Nickel-Titanium (Ni-Ti) based alloy systems, especially, show large elastocaloric effects. Furthermore, exhibit large latent heats which is a necessary material property for the development of an efficient solid-state based cooling process. A scientific test rig has been designed to investigate these processes and the elastocaloric effects in SMAs. The realized test rig enables independent control of an SMA's mechanical loading and unloading cycles, as well as conductive heat transfer between SMA cooling elements and a heat source/sink. The test rig is equipped with a comprehensive monitoring system capable of synchronized measurements of mechanical and thermal parameters. In addition to determining the process-dependent mechanical work, the system also enables measurement of thermal caloric aspects of the elastocaloric cooling effect through use of a high-performance infrared camera. This combination is of particular interest, because it allows illustrations of localization and rate effects - both important for efficient heat transfer from the medium to be cooled. The work presented describes an experimental method to identify elastocaloric material properties in different materials and sample geometries. Furthermore, the test rig is used to investigate different cooling process variations. The introduced analysis methods enable a differentiated consideration of material, process and related boundary condition influences on the process efficiency. The comparison of the experimental data with the simulation results (of a thermomechanically coupled finite element model) allows for better understanding of the underlying physics of the elastocaloric effect. In addition, the experimental results, as well as the findings based on the simulation results, are used to improve the material properties.

Space - A unique environment for process modeling R&D

NASA Technical Reports Server (NTRS)

Overfelt, Tony

1991-01-01

Process modeling, the application of advanced computational techniques to simulate real processes as they occur in regular use, e.g., welding, casting and semiconductor crystal growth, is discussed. Using the low-gravity environment of space will accelerate the technical validation of the procedures and enable extremely accurate determinations of the many necessary thermophysical properties. Attention is given to NASA's centers for the commercial development of space; joint ventures of universities, industries, and goverment agencies to study the unique attributes of space that offer potential for applied R&D and eventual commercial exploitation.

Carotene Degradation and Isomerization during Thermal Processing: A Review on the Kinetic Aspects.

PubMed

Colle, Ines J P; Lemmens, Lien; Knockaert, Griet; Van Loey, Ann; Hendrickx, Marc

2016-08-17

Kinetic models are important tools for process design and optimization to balance desired and undesired reactions taking place in complex food systems during food processing and preservation. This review covers the state of the art on kinetic models available to describe heat-induced conversion of carotenoids, in particular lycopene and β-carotene. First, relevant properties of these carotenoids are discussed. Second, some general aspects of kinetic modeling are introduced, including both empirical single-response modeling and mechanism-based multi-response modeling. The merits of multi-response modeling to simultaneously describe carotene degradation and isomerization are demonstrated. The future challenge in this research field lies in the extension of the current multi-response models to better approach the real reaction pathway and in the integration of kinetic models with mass transfer models in case of reaction in multi-phase food systems.

Mapping Viscoelastic and Plastic Properties of Polymers and Polymer-Nanotube Composites using Instrumented Indentation

PubMed Central

Gayle, Andrew J.; Cook, Robert F.

2016-01-01

An instrumented indentation method is developed for generating maps of time-dependent viscoelastic and time-independent plastic properties of polymeric materials. The method is based on a pyramidal indentation model consisting of two quadratic viscoelastic Kelvin-like elements and a quadratic plastic element in series. Closed-form solutions for indentation displacement under constant load and constant loading-rate are developed and used to determine and validate material properties. Model parameters are determined by point measurements on common monolithic polymers. Mapping is demonstrated on an epoxy-ceramic interface and on two composite materials consisting of epoxy matrices containing multi-wall carbon nanotubes. A fast viscoelastic deformation process in the epoxy was unaffected by the inclusion of the nanotubes, whereas a slow viscoelastic process was significantly impeded, as was the plastic deformation. Mapping revealed considerable spatial heterogeneity in the slow viscoelastic and plastic responses in the composites, particularly in the material with a greater fraction of nanotubes. PMID:27563168

Modeling heart rate variability including the effect of sleep stages

NASA Astrophysics Data System (ADS)

Soliński, Mateusz; Gierałtowski, Jan; Żebrowski, Jan

2016-02-01

We propose a model for heart rate variability (HRV) of a healthy individual during sleep with the assumption that the heart rate variability is predominantly a random process. Autonomic nervous system activity has different properties during different sleep stages, and this affects many physiological systems including the cardiovascular system. Different properties of HRV can be observed during each particular sleep stage. We believe that taking into account the sleep architecture is crucial for modeling the human nighttime HRV. The stochastic model of HRV introduced by Kantelhardt et al. was used as the initial starting point. We studied the statistical properties of sleep in healthy adults, analyzing 30 polysomnographic recordings, which provided realistic information about sleep architecture. Next, we generated synthetic hypnograms and included them in the modeling of nighttime RR interval series. The results of standard HRV linear analysis and of nonlinear analysis (Shannon entropy, Poincaré plots, and multiscale multifractal analysis) show that—in comparison with real data—the HRV signals obtained from our model have very similar properties, in particular including the multifractal characteristics at different time scales. The model described in this paper is discussed in the context of normal sleep. However, its construction is such that it should allow to model heart rate variability in sleep disorders. This possibility is briefly discussed.

Exposure limits: the underestimation of absorbed cell phone radiation, especially in children.

PubMed

Gandhi, Om P; Morgan, L Lloyd; de Salles, Alvaro Augusto; Han, Yueh-Ying; Herberman, Ronald B; Davis, Devra Lee

2012-03-01

The existing cell phone certification process uses a plastic model of the head called the Specific Anthropomorphic Mannequin (SAM), representing the top 10% of U.S. military recruits in 1989 and greatly underestimating the Specific Absorption Rate (SAR) for typical mobile phone users, especially children. A superior computer simulation certification process has been approved by the Federal Communications Commission (FCC) but is not employed to certify cell phones. In the United States, the FCC determines maximum allowed exposures. Many countries, especially European Union members, use the "guidelines" of International Commission on Non-Ionizing Radiation Protection (ICNIRP), a non governmental agency. Radiofrequency (RF) exposure to a head smaller than SAM will absorb a relatively higher SAR. Also, SAM uses a fluid having the average electrical properties of the head that cannot indicate differential absorption of specific brain tissue, nor absorption in children or smaller adults. The SAR for a 10-year old is up to 153% higher than the SAR for the SAM model. When electrical properties are considered, a child's head's absorption can be over two times greater, and absorption of the skull's bone marrow can be ten times greater than adults. Therefore, a new certification process is needed that incorporates different modes of use, head sizes, and tissue properties. Anatomically based models should be employed in revising safety standards for these ubiquitous modern devices and standards should be set by accountable, independent groups.

Accelerated rescaling of single Monte Carlo simulation runs with the Graphics Processing Unit (GPU).

PubMed

Yang, Owen; Choi, Bernard

2013-01-01

To interpret fiber-based and camera-based measurements of remitted light from biological tissues, researchers typically use analytical models, such as the diffusion approximation to light transport theory, or stochastic models, such as Monte Carlo modeling. To achieve rapid (ideally real-time) measurement of tissue optical properties, especially in clinical situations, there is a critical need to accelerate Monte Carlo simulation runs. In this manuscript, we report on our approach using the Graphics Processing Unit (GPU) to accelerate rescaling of single Monte Carlo runs to calculate rapidly diffuse reflectance values for different sets of tissue optical properties. We selected MATLAB to enable non-specialists in C and CUDA-based programming to use the generated open-source code. We developed a software package with four abstraction layers. To calculate a set of diffuse reflectance values from a simulated tissue with homogeneous optical properties, our rescaling GPU-based approach achieves a reduction in computation time of several orders of magnitude as compared to other GPU-based approaches. Specifically, our GPU-based approach generated a diffuse reflectance value in 0.08ms. The transfer time from CPU to GPU memory currently is a limiting factor with GPU-based calculations. However, for calculation of multiple diffuse reflectance values, our GPU-based approach still can lead to processing that is ~3400 times faster than other GPU-based approaches.

Engineering of layered, lipid-encapsulated drug nanoparticles through spray-drying.

PubMed

Sapra, Mahak; Mayya, Y S; Venkataraman, Chandra

2017-06-01

Drug-containing nanoparticles have been synthesized through the spray-drying of submicron droplet aerosols by using matrix materials such as lipids and biopolymers. Understanding layer formation in composite nanoparticles is essential for the appropriate engineering of particle substructures. The present study developed a droplet-shrinkage model for predicting the solid-phase formation of two non-volatile solutes-stearic acid lipid and a set of drugs, by considering molecular volume and solubility. Nanoparticle formation was simulated to define the parameter space of material properties and process conditions for the formation of a layered structure with the preferential accumulation of the lipid in the outer layer. Moreover, lipid-drug demarcation diagrams representing a set of critical values of ratios of solute properties at which the two solutes precipitate simultaneously were developed. The model was validated through the preparation of stearic acid-isoniazid nanoparticles under controlled processing conditions. The developed model can guide the selection of solvents, lipids, and processing conditions such that drug loading and lipid encapsulation in composite nanoparticles are optimized. Copyright © 2017 Elsevier B.V. All rights reserved.

Predicting Error Bars for QSAR Models

NASA Astrophysics Data System (ADS)

Schroeter, Timon; Schwaighofer, Anton; Mika, Sebastian; Ter Laak, Antonius; Suelzle, Detlev; Ganzer, Ursula; Heinrich, Nikolaus; Müller, Klaus-Robert

2007-09-01

Unfavorable physicochemical properties often cause drug failures. It is therefore important to take lipophilicity and water solubility into account early on in lead discovery. This study presents log D7 models built using Gaussian Process regression, Support Vector Machines, decision trees and ridge regression algorithms based on 14556 drug discovery compounds of Bayer Schering Pharma. A blind test was conducted using 7013 new measurements from the last months. We also present independent evaluations using public data. Apart from accuracy, we discuss the quality of error bars that can be computed by Gaussian Process models, and ensemble and distance based techniques for the other modelling approaches.

Explicit simulation of ice particle habits in a Numerical Weather Prediction Model

NASA Astrophysics Data System (ADS)

Hashino, Tempei

2007-05-01

This study developed a scheme for explicit simulation of ice particle habits in Numerical Weather Prediction (NWP) Models. The scheme is called Spectral Ice Habit Prediction System (SHIPS), and the goal is to retain growth history of ice particles in the Eulerian dynamics framework. It diagnoses characteristics of ice particles based on a series of particle property variables (PPVs) that reflect history of microphysieal processes and the transport between mass bins and air parcels in space. Therefore, categorization of ice particles typically used in bulk microphysical parameterization and traditional bin models is not necessary, so that errors that stem from the categorization can be avoided. SHIPS predicts polycrystals as well as hexagonal monocrystals based on empirically derived habit frequency and growth rate, and simulates the habit-dependent aggregation and riming processes by use of the stochastic collection equation with predicted PPVs. Idealized two dimensional simulations were performed with SHIPS in a NWP model. The predicted spatial distribution of ice particle habits and types, and evolution of particle size distributions showed good quantitative agreement with observation This comprehensive model of ice particle properties, distributions, and evolution in clouds can be used to better understand problems facing wide range of research disciplines, including microphysics processes, radiative transfer in a cloudy atmosphere, data assimilation, and weather modification.

Observing Ice in Clouds from Space

NASA Technical Reports Server (NTRS)

Ackerman, S.; Star, D. O'C.; Skofronick-Jackson, G.; Evans, F.; Wang, J. R.; Norris, P.; daSilva, A.; Soden, B.

2006-01-01

There are many satellite observations of cloud top properties and the liquid and rain content of clouds, however, we do not yet quantitatively understand the processes that control the water budget of the upper troposphere where ice is the predominant phase, and how these processes are linked to precipitation processes and the radiative energy budget. The ice in clouds in the upper troposphere either melts into rain or is detrained, and persists, as cirrus clouds affecting the hydrological and energy cycle, respectively. Fully modeling the Earth's climate and improving weather and climate forecasts requires accurate satellite measurements of various cloud properties at the temporal and spatial scales of cloud processes. These properties include cloud horizontal and vertical structure, cloud water content and some measure of particle sizes and shapes. The uncertainty in knowledge of these ice characteristics is reflected in the large discrepancies in model simulations of the upper tropospheric water budget. Model simulations are sensitive to the partition of ice between precipitation and outflow processes, i.e., to the parameterization of ice clouds and ice processes. One barrier to achieving accurate global ice cloud properties is the lack of adequate observations at millimeter and submillimeter wavelengths (183-874 GHz). Recent advances in instrumentation have allowed for the development and implementation of an airborne submillimeter-wave radiometer. The brightness temperatures at these frequencies are especially sensitive to cirrus ice particle sizes (because they are comparable to the wavelength). This allows for more accurate ice water path estimates when multiple channels are used to probe into the cloud layers. Further, submillimeter wavelengths offer simplicity in the retrieval algorithms because they do not probe into the liquid and near surface portions of clouds, thus requiring only one term of the radiative transfer equation (ice scattering) to relate brightness temperatures to ice. The next step is a satellite mission designed to acquire global Earth radiance measurements in the submillimeter-wave region, thus bridging the measurement gap between microwave sounders and shorter-wavelength infrared and visible sensors. This presentation provides scientific justification and an approach to measuring ice water path and particle size from a satellite platform that spans a range encompassing both the hydrologically active and radiatively active components of cloud systems.