15 CFR 700.12 - Elements of a rated order.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 15 Commerce and Foreign Trade 2 2014-01-01 2014-01-01 false Elements of a rated order. 700.12 Section 700.12 Commerce and Foreign Trade Regulations Relating to Commerce and Foreign Trade (Continued... DEFENSE PRIORITIES AND ALLOCATIONS SYSTEM Industrial Priorities § 700.12 Elements of a rated order. Each...

15 CFR 700.12 - Elements of a rated order.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 15 Commerce and Foreign Trade 2 2012-01-01 2012-01-01 false Elements of a rated order. 700.12 Section 700.12 Commerce and Foreign Trade Regulations Relating to Commerce and Foreign Trade (Continued... DEFENSE PRIORITIES AND ALLOCATIONS SYSTEM Industrial Priorities § 700.12 Elements of a rated order. Each...

15 CFR 700.12 - Elements of a rated order.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 15 Commerce and Foreign Trade 2 2011-01-01 2011-01-01 false Elements of a rated order. 700.12 Section 700.12 Commerce and Foreign Trade Regulations Relating to Commerce and Foreign Trade (Continued... DEFENSE PRIORITIES AND ALLOCATIONS SYSTEM Industrial Priorities § 700.12 Elements of a rated order. Each...

15 CFR 700.12 - Elements of a rated order.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 15 Commerce and Foreign Trade 2 2013-01-01 2013-01-01 false Elements of a rated order. 700.12 Section 700.12 Commerce and Foreign Trade Regulations Relating to Commerce and Foreign Trade (Continued... DEFENSE PRIORITIES AND ALLOCATIONS SYSTEM Industrial Priorities § 700.12 Elements of a rated order. Each...

Test order in teacher-rated behavior assessments: Is counterbalancing necessary?

PubMed

Kooken, Janice; Welsh, Megan E; McCoach, D Betsy; Miller, Faith G; Chafouleas, Sandra M; Riley-Tillman, T Chris; Fabiano, Gregory

2017-01-01

Counterbalancing treatment order in experimental research design is well established as an option to reduce threats to internal validity, but in educational and psychological research, the effect of varying the order of multiple tests to a single rater has not been examined and is rarely adhered to in practice. The current study examines the effect of test order on measures of student behavior by teachers as raters utilizing data from a behavior measure validation study. Using multilevel modeling to control for students nested within teachers, the effect of rating an earlier measure on the intercept or slope of a later behavior assessment was statistically significant in 22% of predictor main effects for the spring test period. Test order effects had potential for high stakes consequences with differences large enough to change risk classification. Results suggest that researchers and practitioners in classroom settings using multiple measures evaluate the potential impact of test order. Where possible, they should counterbalance when the risk of an order effect exists and report justification for the decision to not counterbalance. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

The determination of third order linear models from a seventh order nonlinear jet engine model

NASA Technical Reports Server (NTRS)

Lalonde, Rick J.; Hartley, Tom T.; De Abreu-Garcia, J. Alex

1989-01-01

Results are presented that demonstrate how good reduced-order models can be obtained directly by recursive parameter identification using input/output (I/O) data of high-order nonlinear systems. Three different methods of obtaining a third-order linear model from a seventh-order nonlinear turbojet engine model are compared. The first method is to obtain a linear model from the original model and then reduce the linear model by standard reduction techniques such as residualization and balancing. The second method is to identify directly a third-order linear model by recursive least-squares parameter estimation using I/O data of the original model. The third method is to obtain a reduced-order model from the original model and then linearize the reduced model. Frequency responses are used as the performance measure to evaluate the reduced models. The reduced-order models along with their Bode plots are presented for comparison purposes.

Application of the Zero-Order Reaction Rate Model and Transition State Theory to predict porous Ti6Al4V bending strength.

PubMed

Reig, L; Amigó, V; Busquets, D; Calero, J A; Ortiz, J L

2012-08-01

Porous Ti6Al4V samples were produced by microsphere sintering. The Zero-Order Reaction Rate Model and Transition State Theory were used to model the sintering process and to estimate the bending strength of the porous samples developed. The evolution of the surface area during the sintering process was used to obtain sintering parameters (sintering constant, activation energy, frequency factor, constant of activation and Gibbs energy of activation). These were then correlated with the bending strength in order to obtain a simple model with which to estimate the evolution of the bending strength of the samples when the sintering temperature and time are modified: σY=P+B·[lnT·t-ΔGa/R·T]. Although the sintering parameters were obtained only for the microsphere sizes analysed here, the strength of intermediate sizes could easily be estimated following this model. Copyright © 2012 Elsevier B.V. All rights reserved.

Terminal hospitalizations of nursing home residents: does facility increasing the rate of do not resuscitate orders reduce them?

PubMed

Teno, Joan M; Gozalo, Pedro; Mitchell, Susan L; Bynum, Julie P W; Dosa, David; Mor, Vincent

2011-06-01

Terminal hospitalizations are costly and often avoidable with appropriate advance care planning. This study examined the association between advance care planning, as measured by facility rate of do not resuscitate (DNR) orders in U.S. nursing homes (NHs) and changes in terminal hospitalization rates. Retrospective cohort study of the changing prevalence of DNR orders in U.S. NHs. Using a fixed effect multivariate model, we examined whether increasing facility rate of DNR orders correlates with reductions in terminal hospitalizations in the last week of life, controlling for changes in facility characteristics (staffing, use of NP/PA, case mix of nursing residents, admission volume, racial composition, payer mix). The average facility rate of terminal hospitalizations was 15.5%, fluctuating between 1999 (15.0%) and 2007 (14.8%). NHs starting with low rates of DNR orders that increased their rates had fewer terminal hospital admissions in 2007 (11.2%) than facilities with continuously low DNR usage. Even after applying a multivariate fixed effect model, the effect of changes in facility DNR order rate on terminal hospitalization was -0.056 (95% confidence interval: -0.061, -0.050), indicating that for every 10% increase in DNR orders there was 0.56% decrease in terminal hospitalizations. This rate can be compared with the increase of 0.70% in the terminal hospitalization rate when an NH became disproportionately dependent on Medicaid funding or the 0.40% decrease in terminal hospitalization rate associated with adding a nurse practitioner to the clinical staff complement. NHs that changed their culture of decision making by increasing their facility rate of DNR orders decreased their rate of terminal hospitalizations. Copyright © 2011 U.S. Cancer Pain Relief Committee. Published by Elsevier Inc. All rights reserved.

Higher Order, Hybrid BEM/FEM Methods Applied to Antenna Modeling

NASA Technical Reports Server (NTRS)

Fink, P. W.; Wilton, D. R.; Dobbins, J. A.

2002-01-01

In this presentation, the authors address topics relevant to higher order modeling using hybrid BEM/FEM formulations. The first of these is the limitation on convergence rates imposed by geometric modeling errors in the analysis of scattering by a dielectric sphere. The second topic is the application of an Incomplete LU Threshold (ILUT) preconditioner to solve the linear system resulting from the BEM/FEM formulation. The final tOpic is the application of the higher order BEM/FEM formulation to antenna modeling problems. The authors have previously presented work on the benefits of higher order modeling. To achieve these benefits, special attention is required in the integration of singular and near-singular terms arising in the surface integral equation. Several methods for handling these terms have been presented. It is also well known that achieving he high rates of convergence afforded by higher order bases may als'o require the employment of higher order geometry models. A number of publications have described the use of quadratic elements to model curved surfaces. The authors have shown in an EFIE formulation, applied to scattering by a PEC .sphere, that quadratic order elements may be insufficient to prevent the domination of modeling errors. In fact, on a PEC sphere with radius r = 0.58 Lambda(sub 0), a quartic order geometry representation was required to obtain a convergence benefi.t from quadratic bases when compared to the convergence rate achieved with linear bases. Initial trials indicate that, for a dielectric sphere of the same radius, - requirements on the geometry model are not as severe as for the PEC sphere. The authors will present convergence results for higher order bases as a function of the geometry model order in the hybrid BEM/FEM formulation applied to dielectric spheres. It is well known that the system matrix resulting from the hybrid BEM/FEM formulation is ill -conditioned. For many real applications, a good preconditioner is required

Effects of Cooling Rate on 6.5% Silicon Steel Ordering

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

Cui, Jun; Macziewski, Chad; Jensen, Brandt

Increasing Si content improves magnetic and electrical properties of electrical steel, with 6.5% Si as the optimum. Unfortunately, when Si content approaches 5.7%, the Fe-Si alloy becomes brittle. At 6.5%, the steel conventional cold rolling process is no longer applicable. The heterogeneous formation of B2 and D03 ordered phases is responsible for the embrittlement. The formation of these ordered phases can be impeded by rapid cooling. However, only the cooling rates of water and brine water were investigated. A comprehensive study of the effect of rapid cooling rate on the formation of the ordered phases was carried out by varyingmore » wheel speed and melt-injection rate. Thermal imaging employed to measure cooling rates while microstructures of the obtained ribbons are characterized using X-ray diffraction and TEM. The electrical, magnetic and mechanical properties are characterized using 4-pt probe, VSM, and macro-indentation methods. The relations between physical properties and ordered phases are established.« less

Mechanical model for filament buckling and growth by phase ordering.

PubMed

Rey, Alejandro D; Abukhdeir, Nasser M

2008-02-05

A mechanical model of open filament shape and growth driven by phase ordering is formulated. For a given phase-ordering driving force, the model output is the filament shape evolution and the filament end-point kinematics. The linearized model for the slope of the filament is the Cahn-Hilliard model of spinodal decomposition, where the buckling corresponds to concentration fluctuations. Two modes are predicted: (i) sequential growth and buckling and (ii) simultaneous buckling and growth. The relation among the maximum buckling rate, filament tension, and matrix viscosity is given. These results contribute to ongoing work in smectic A filament buckling.

Computer Calculation of First-Order Rate Constants

ERIC Educational Resources Information Center

Williams, Robert C.; Taylor, James W.

1970-01-01

Discusses the computer program used to calculate first-order rate constants. Discussion includes data preparation, weighting options, comparison techniques, infinity point adjustment, least-square fit, Guggenheim calculation, and printed outputs. Exemplifies the utility of the computer program by two experiments: (1) the thermal decomposition of…

Adaptive h -refinement for reduced-order models: ADAPTIVE h -refinement for reduced-order models

DOE PAGES

Carlberg, Kevin T.

2014-11-05

Our work presents a method to adaptively refine reduced-order models a posteriori without requiring additional full-order-model solves. The technique is analogous to mesh-adaptive h-refinement: it enriches the reduced-basis space online by ‘splitting’ a given basis vector into several vectors with disjoint support. The splitting scheme is defined by a tree structure constructed offline via recursive k-means clustering of the state variables using snapshot data. This method identifies the vectors to split online using a dual-weighted-residual approach that aims to reduce error in an output quantity of interest. The resulting method generates a hierarchy of subspaces online without requiring large-scale operationsmore » or full-order-model solves. Furthermore, it enables the reduced-order model to satisfy any prescribed error tolerance regardless of its original fidelity, as a completely refined reduced-order model is mathematically equivalent to the original full-order model. Experiments on a parameterized inviscid Burgers equation highlight the ability of the method to capture phenomena (e.g., moving shocks) not contained in the span of the original reduced basis.« less

15 CFR 700.17 - Use of rated orders.

Code of Federal Regulations, 2010 CFR

2010-01-01

...) BUREAU OF INDUSTRY AND SECURITY, DEPARTMENT OF COMMERCE NATIONAL SECURITY INDUSTRIAL BASE REGULATIONS DEFENSE PRIORITIES AND ALLOCATIONS SYSTEM Industrial Priorities § 700.17 Use of rated orders. (a) A person...

Regularized learning of linear ordered-statistic constant false alarm rate filters (Conference Presentation)

NASA Astrophysics Data System (ADS)

Havens, Timothy C.; Cummings, Ian; Botts, Jonathan; Summers, Jason E.

2017-05-01

The linear ordered statistic (LOS) is a parameterized ordered statistic (OS) that is a weighted average of a rank-ordered sample. LOS operators are useful generalizations of aggregation as they can represent any linear aggregation, from minimum to maximum, including conventional aggregations, such as mean and median. In the fuzzy logic field, these aggregations are called ordered weighted averages (OWAs). Here, we present a method for learning LOS operators from training data, viz., data for which you know the output of the desired LOS. We then extend the learning process with regularization, such that a lower complexity or sparse LOS can be learned. Hence, we discuss what 'lower complexity' means in this context and how to represent that in the optimization procedure. Finally, we apply our learning methods to the well-known constant-false-alarm-rate (CFAR) detection problem, specifically for the case of background levels modeled by long-tailed distributions, such as the K-distribution. These backgrounds arise in several pertinent imaging problems, including the modeling of clutter in synthetic aperture radar and sonar (SAR and SAS) and in wireless communications.

78 FR 25264 - Washoe Project-Rate Order No. WAPA-160

Federal Register 2010, 2011, 2012, 2013, 2014

2013-04-30

... DEPARTMENT OF ENERGY Western Area Power Administration Washoe Project-Rate Order No. WAPA-160... existing Washoe Project formula rate through September 30, 2017. The existing Non-Firm Power Formula Rate... the existing formula rate for the Washoe Project, Stampede Division (Project), Non-Firm Power [[Page...

Reduced-order modeling for hyperthermia control.

PubMed

Potocki, J K; Tharp, H S

1992-12-01

This paper analyzes the feasibility of using reduced-order modeling techniques in the design of multiple-input, multiple-output (MIMO) hyperthermia temperature controllers. State space thermal models are created based upon a finite difference expansion of the bioheat transfer equation model of a scanned focused ultrasound system (SFUS). These thermal state space models are reduced using the balanced realization technique, and an order reduction criterion is tabulated. Results show that a drastic reduction in model dimension can be achieved using the balanced realization. The reduced-order model is then used to design a reduced-order optimal servomechanism controller for a two-scan input, two thermocouple output tissue model. In addition, a full-order optimal servomechanism controller is designed for comparison and validation purposes. These two controllers are applied to a variety of perturbed tissue thermal models to test the robust nature of the reduced-order controller. A comparison of the two controllers validates the use of open-loop balanced reduced-order models in the design of MIMO hyperthermia controllers.

Improvements to Fidelity, Generation and Implementation of Physics-Based Lithium-Ion Reduced-Order Models

NASA Astrophysics Data System (ADS)

Rodriguez Marco, Albert

Battery management systems (BMS) require computationally simple but highly accurate models of the battery cells they are monitoring and controlling. Historically, empirical equivalent-circuit models have been used, but increasingly researchers are focusing their attention on physics-based models due to their greater predictive capabilities. These models are of high intrinsic computational complexity and so must undergo some kind of order-reduction process to make their use by a BMS feasible: we favor methods based on a transfer-function approach of battery cell dynamics. In prior works, transfer functions have been found from full-order PDE models via two simplifying assumptions: (1) a linearization assumption--which is a fundamental necessity in order to make transfer functions--and (2) an assumption made out of expedience that decouples the electrolyte-potential and electrolyte-concentration PDEs in order to render an approach to solve for the transfer functions from the PDEs. This dissertation improves the fidelity of physics-based models by eliminating the need for the second assumption and, by linearizing nonlinear dynamics around different constant currents. Electrochemical transfer functions are infinite-order and cannot be expressed as a ratio of polynomials in the Laplace variable s. Thus, for practical use, these systems need to be approximated using reduced-order models that capture the most significant dynamics. This dissertation improves the generation of physics-based reduced-order models by introducing different realization algorithms, which produce a low-order model from the infinite-order electrochemical transfer functions. Physics-based reduced-order models are linear and describe cell dynamics if operated near the setpoint at which they have been generated. Hence, multiple physics-based reduced-order models need to be generated at different setpoints (i.e., state-of-charge, temperature and C-rate) in order to extend the cell operating range. This

Second order modeling of boundary-free turbulent shear flows

NASA Technical Reports Server (NTRS)

Shih, T.-H.; Chen, Y.-Y.; Lumley, J. L.

1991-01-01

A set of realizable second order models for boundary-free turbulent flows is presented. The constraints on second order models based on the realizability principle are re-examined. The rapid terms in the pressure correlations for both the Reynolds stress and the passive scalar flux equations are constructed to exactly satisfy the joint realizability. All other model terms (return-to-isotropy, third moments, and terms in the dissipation equations) already satisfy realizability. To correct the spreading rate of the axisymmetric jet, an extra term is added to the dissipation equation which accounts for the effect of mean vortex stretching on dissipation. The test flows used in this study are the mixing shear layer, plane jet, axisymmetric jet, and plane wake. The numerical solutions show that the unified model equations predict all these flows reasonably. It is expected that these models would be suitable for more complex and critical flows.

Reduced Order Modeling of Combustion Instability in a Gas Turbine Model Combustor

NASA Astrophysics Data System (ADS)

Arnold-Medabalimi, Nicholas; Huang, Cheng; Duraisamy, Karthik

2017-11-01

Hydrocarbon fuel based propulsion systems are expected to remain relevant in aerospace vehicles for the foreseeable future. Design of these devices is complicated by combustion instabilities. The capability to model and predict these effects at reduced computational cost is a requirement for both design and control of these devices. This work focuses on computational studies on a dual swirl model gas turbine combustor in the context of reduced order model development. Full fidelity simulations are performed utilizing URANS and Hybrid RANS-LES with finite rate chemistry. Following this, data decomposition techniques are used to extract a reduced basis representation of the unsteady flow field. These bases are first used to identify sensor locations to guide experimental interrogations and controller feedback. Following this, initial results on developing a control-oriented reduced order model (ROM) will be presented. The capability of the ROM will be further assessed based on different operating conditions and geometric configurations.

American option pricing in Gauss-Markov interest rate models

NASA Astrophysics Data System (ADS)

Galluccio, Stefano

1999-07-01

In the context of Gaussian non-homogeneous interest-rate models, we study the problem of American bond option pricing. In particular, we show how to efficiently compute the exercise boundary in these models in order to decompose the price as a sum of a European option and an American premium. Generalizations to coupon-bearing bonds and jump-diffusion processes for the interest rates are also discussed.

Pangenome Analysis of Burkholderia pseudomallei: Genome Evolution Preserves Gene Order despite High Recombination Rates.

PubMed

Spring-Pearson, Senanu M; Stone, Joshua K; Doyle, Adina; Allender, Christopher J; Okinaka, Richard T; Mayo, Mark; Broomall, Stacey M; Hill, Jessica M; Karavis, Mark A; Hubbard, Kyle S; Insalaco, Joseph M; McNew, Lauren A; Rosenzweig, C Nicole; Gibbons, Henry S; Currie, Bart J; Wagner, David M; Keim, Paul; Tuanyok, Apichai

2015-01-01

The pangenomic diversity in Burkholderia pseudomallei is high, with approximately 5.8% of the genome consisting of genomic islands. Genomic islands are known hotspots for recombination driven primarily by site-specific recombination associated with tRNAs. However, recombination rates in other portions of the genome are also high, a feature we expected to disrupt gene order. We analyzed the pangenome of 37 isolates of B. pseudomallei and demonstrate that the pangenome is 'open', with approximately 136 new genes identified with each new genome sequenced, and that the global core genome consists of 4568±16 homologs. Genes associated with metabolism were statistically overrepresented in the core genome, and genes associated with mobile elements, disease, and motility were primarily associated with accessory portions of the pangenome. The frequency distribution of genes present in between 1 and 37 of the genomes analyzed matches well with a model of genome evolution in which 96% of the genome has very low recombination rates but 4% of the genome recombines readily. Using homologous genes among pairs of genomes, we found that gene order was highly conserved among strains, despite the high recombination rates previously observed. High rates of gene transfer and recombination are incompatible with retaining gene order unless these processes are either highly localized to specific sites within the genome, or are characterized by symmetrical gene gain and loss. Our results demonstrate that both processes occur: localized recombination introduces many new genes at relatively few sites, and recombination throughout the genome generates the novel multi-locus sequence types previously observed while preserving gene order.

75 FR 57912 - Boulder Canyon Project-Rate Order No. WAPA-150

Federal Register 2010, 2011, 2012, 2013, 2014

2010-09-23

...-setting Formula and Approval of FY 2011 Base Charge and Rates. SUMMARY: The Deputy Secretary of Energy... existing Boulder Canyon Project (BCP) rate-setting formula and approving the base charge and rates for FY... financial and load data. The existing rate-setting formula is being extended under Rate Order No. WAPA-150...

Fractional order creep model for dam concrete considering degree of hydration

NASA Astrophysics Data System (ADS)

Huang, Yaoying; Xiao, Lei; Bao, Tengfei; Liu, Yu

2018-05-01

Concrete is a material that is an intermediate between an ideal solid and an ideal fluid. The creep of concrete is related not only to the loading age and duration, but also to its temperature and temperature history. Fractional order calculus is a powerful tool for solving physical mechanics modeling problems. Using a software element based on the generalized Kelvin model, a fractional order creep model of concrete considering the loading age and duration is established. Then, the hydration rate of cement is considered in terms of the degree of hydration, and the fractional order creep model of concrete considering the degree of hydration is established. Moreover, uniaxial tensile creep tests of dam concrete under different curing temperatures were conducted, and the results were combined with the creep test data and complex optimization method to optimize the parameters of a new creep model. The results show that the fractional tensile creep model based on hydration degree can better describe the tensile creep properties of concrete, and this model involves fewer parameters than the 8-parameter model.

The Effects of Response Option Order and Question Order on Self-Rated Health

PubMed Central

Garbarski, Dana; Schaeffer, Nora Cate; Dykema, Jennifer

2014-01-01

Objectives This study aims to assess the impact of response option order and question order on the distribution of responses to the self-rated health (SRH) question and the relationship between SRH and other health-related measures. Methods In an online panel survey, we implement a 2-by-2 between-subjects factorial experiment, manipulating the following levels of each factor: 1) order of response options (“excellent” to “poor” versus “poor” to “excellent”); and 2) order of SRH item (either preceding or following the administration of domain-specific health items). We use chi-square difference tests, polychoric correlations, and differences in means and proportions to evaluate the effect of the experimental treatments on SRH responses and the relationship between SRH and other health measures. Results Mean SRH is higher (better health) and proportion in “fair” or “poor” health lower when response options are ordered from “excellent” to “poor” and SRH is presented first compared to other experimental treatments. Presenting SRH after domain-specific health items increases its correlation with these items, particularly when response options are ordered “excellent” to “poor.” Among participants with the highest level of current health risks, SRH is worse when it is presented last versus first. Conclusion While more research on the presentation of SRH is needed across a range of surveys, we suggest that ordering response options from “poor” to “excellent” might reduce positive clustering. Given the question order effects found here, we suggest presenting SRH before domain-specific health items in order to increase inter-survey comparability, as domain-specific health items will vary across surveys. PMID:25409654

Ordered Rate Constitutive Theories: Development of Rate Constitutive Equations for Solids, Liquids, and Gases

DTIC Science & Technology

2010-08-18

the author(s) and should not contrued as an official Department of the Army position, policy or decision, unless so designated by other documentation...Daniel S. Nunez 0.50 Yong-Ting Ma 0.50 Tristan Moody 0.50 1.50FTE Equivalent: 3Total Number: Names of Post Doctorates PERCENT_SUPPORTEDNAME FTE...demonstrated that the constitutive theory for ordered thermofluids of all orders is indeed rate constitutive theory. The reseach work presented in this chapter

A reduced-order model from high-dimensional frictional hysteresis

PubMed Central

Biswas, Saurabh; Chatterjee, Anindya

2014-01-01

Hysteresis in material behaviour includes both signum nonlinearities as well as high dimensionality. Available models for component-level hysteretic behaviour are empirical. Here, we derive a low-order model for rate-independent hysteresis from a high-dimensional massless frictional system. The original system, being given in terms of signs of velocities, is first solved incrementally using a linear complementarity problem formulation. From this numerical solution, to develop a reduced-order model, basis vectors are chosen using the singular value decomposition. The slip direction in generalized coordinates is identified as the minimizer of a dissipation-related function. That function includes terms for frictional dissipation through signum nonlinearities at many friction sites. Luckily, it allows a convenient analytical approximation. Upon solution of the approximated minimization problem, the slip direction is found. A final evolution equation for a few states is then obtained that gives a good match with the full solution. The model obtained here may lead to new insights into hysteresis as well as better empirical modelling thereof. PMID:24910522

Modeling inflation rates and exchange rates in Ghana: application of multivariate GARCH models.

PubMed

Nortey, Ezekiel Nn; Ngoh, Delali D; Doku-Amponsah, Kwabena; Ofori-Boateng, Kenneth

2015-01-01

This paper was aimed at investigating the volatility and conditional relationship among inflation rates, exchange rates and interest rates as well as to construct a model using multivariate GARCH DCC and BEKK models using Ghana data from January 1990 to December 2013. The study revealed that the cumulative depreciation of the cedi to the US dollar from 1990 to 2013 is 7,010.2% and the yearly weighted depreciation of the cedi to the US dollar for the period is 20.4%. There was evidence that, the fact that inflation rate was stable, does not mean that exchange rates and interest rates are expected to be stable. Rather, when the cedi performs well on the forex, inflation rates and interest rates react positively and become stable in the long run. The BEKK model is robust to modelling and forecasting volatility of inflation rates, exchange rates and interest rates. The DCC model is robust to model the conditional and unconditional correlation among inflation rates, exchange rates and interest rates. The BEKK model, which forecasted high exchange rate volatility for the year 2014, is very robust for modelling the exchange rates in Ghana. The mean equation of the DCC model is also robust to forecast inflation rates in Ghana.

Cation ordering in orthopyroxenes and cooling rates of meteorites: Low temperature cooling rates of Estherville, Bondoc and Shaw

NASA Technical Reports Server (NTRS)

Ganguly, J.; Yang, H.; Ghose, S.

1993-01-01

The cooling rates of meteorites provide important constraints on the size of their parent bodies, and their accretionary and evolutionary histories. However, the cooling rates obtained so far from the commonly used metallographic, radiometric and fission-track methods have been sometimes quite controversial, such as in the case of the mesosiderites and the meteorite Shaw. We have undertaken a systematic study of the cooling rates of meteorites using a different approach, which involves single crystal x-ray determination of Fe(2+)-Mg ordering in orthopyroxenes (OP(x)) in meteorites, subject to bulk compositional constraints, and numerical simulation of the evolution of the ordering state as a function of cooling rate, within the framework of the thermodynamic and kinetic principles governing cation ordering. We report the results obtained for OP(x) crystals from Shaw and two mesosiderites, Estherville and Bondoc.

Validation of a RANS transition model using a high-order weighted compact nonlinear scheme

NASA Astrophysics Data System (ADS)

Tu, GuoHua; Deng, XiaoGang; Mao, MeiLiang

2013-04-01

A modified transition model is given based on the shear stress transport (SST) turbulence model and an intermittency transport equation. The energy gradient term in the original model is replaced by flow strain rate to saving computational costs. The model employs local variables only, and then it can be conveniently implemented in modern computational fluid dynamics codes. The fifth-order weighted compact nonlinear scheme and the fourth-order staggered scheme are applied to discrete the governing equations for the purpose of minimizing discretization errors, so as to mitigate the confusion between numerical errors and transition model errors. The high-order package is compared with a second-order TVD method on simulating the transitional flow of a flat plate. Numerical results indicate that the high-order package give better grid convergence property than that of the second-order method. Validation of the transition model is performed for transitional flows ranging from low speed to hypersonic speed.

Convergence of high order memory kernels in the Nakajima-Zwanzig generalized master equation and rate constants: Case study of the spin-boson model.

PubMed

Xu, Meng; Yan, Yaming; Liu, Yanying; Shi, Qiang

2018-04-28

The Nakajima-Zwanzig generalized master equation provides a formally exact framework to simulate quantum dynamics in condensed phases. Yet, the exact memory kernel is hard to obtain and calculations based on perturbative expansions are often employed. By using the spin-boson model as an example, we assess the convergence of high order memory kernels in the Nakajima-Zwanzig generalized master equation. The exact memory kernels are calculated by combining the hierarchical equation of motion approach and the Dyson expansion of the exact memory kernel. High order expansions of the memory kernels are obtained by extending our previous work to calculate perturbative expansions of open system quantum dynamics [M. Xu et al., J. Chem. Phys. 146, 064102 (2017)]. It is found that the high order expansions do not necessarily converge in certain parameter regimes where the exact kernel show a long memory time, especially in cases of slow bath, weak system-bath coupling, and low temperature. Effectiveness of the Padé and Landau-Zener resummation approaches is tested, and the convergence of higher order rate constants beyond Fermi's golden rule is investigated.

Convergence of high order memory kernels in the Nakajima-Zwanzig generalized master equation and rate constants: Case study of the spin-boson model

NASA Astrophysics Data System (ADS)

Xu, Meng; Yan, Yaming; Liu, Yanying; Shi, Qiang

2018-04-01

The Nakajima-Zwanzig generalized master equation provides a formally exact framework to simulate quantum dynamics in condensed phases. Yet, the exact memory kernel is hard to obtain and calculations based on perturbative expansions are often employed. By using the spin-boson model as an example, we assess the convergence of high order memory kernels in the Nakajima-Zwanzig generalized master equation. The exact memory kernels are calculated by combining the hierarchical equation of motion approach and the Dyson expansion of the exact memory kernel. High order expansions of the memory kernels are obtained by extending our previous work to calculate perturbative expansions of open system quantum dynamics [M. Xu et al., J. Chem. Phys. 146, 064102 (2017)]. It is found that the high order expansions do not necessarily converge in certain parameter regimes where the exact kernel show a long memory time, especially in cases of slow bath, weak system-bath coupling, and low temperature. Effectiveness of the Padé and Landau-Zener resummation approaches is tested, and the convergence of higher order rate constants beyond Fermi's golden rule is investigated.

The effect of speaking rate on serial-order sound-level errors in normal healthy controls and persons with aphasia.

PubMed

Fossett, Tepanta R D; McNeil, Malcolm R; Pratt, Sheila R; Tompkins, Connie A; Shuster, Linda I

Although many speech errors can be generated at either a linguistic or motoric level of production, phonetically well-formed sound-level serial-order errors are generally assumed to result from disruption of phonologic encoding (PE) processes. An influential model of PE (Dell, 1986; Dell, Burger & Svec, 1997) predicts that speaking rate should affect the relative proportion of these serial-order sound errors (anticipations, perseverations, exchanges). These predictions have been extended to, and have special relevance for persons with aphasia (PWA) because of the increased frequency with which speech errors occur and because their localization within the functional linguistic architecture may help in diagnosis and treatment. Supporting evidence regarding the effect of speaking rate on phonological encoding has been provided by studies using young normal language (NL) speakers and computer simulations. Limited data exist for older NL users and no group data exist for PWA. This study tested the phonologic encoding properties of Dell's model of speech production (Dell, 1986; Dell,et al., 1997), which predicts that increasing speaking rate affects the relative proportion of serial-order sound errors (i.e., anticipations, perseverations, and exchanges). The effects of speech rate on the error ratios of anticipation/exchange (AE), anticipation/perseveration (AP) and vocal reaction time (VRT) were examined in 16 normal healthy controls (NHC) and 16 PWA without concomitant motor speech disorders. The participants were recorded performing a phonologically challenging (tongue twister) speech production task at their typical and two faster speaking rates. A significant effect of increased rate was obtained for the AP but not the AE ratio. Significant effects of group and rate were obtained for VRT. Although the significant effect of rate for the AP ratio provided evidence that changes in speaking rate did affect PE, the results failed to support the model derived predictions

Implementation of Improved Transverse Shear Calculations and Higher Order Laminate Theory Into Strain Rate Dependent Analyses of Polymer Matrix Composites

NASA Technical Reports Server (NTRS)

Zhu, Lin-Fa; Kim, Soo; Chattopadhyay, Aditi; Goldberg, Robert K.

2004-01-01

A numerical procedure has been developed to investigate the nonlinear and strain rate dependent deformation response of polymer matrix composite laminated plates under high strain rate impact loadings. A recently developed strength of materials based micromechanics model, incorporating a set of nonlinear, strain rate dependent constitutive equations for the polymer matrix, is extended to account for the transverse shear effects during impact. Four different assumptions of transverse shear deformation are investigated in order to improve the developed strain rate dependent micromechanics model. The validities of these assumptions are investigated using numerical and theoretical approaches. A method to determine through the thickness strain and transverse Poisson's ratio of the composite is developed. The revised micromechanics model is then implemented into a higher order laminated plate theory which is modified to include the effects of inelastic strains. Parametric studies are conducted to investigate the mechanical response of composite plates under high strain rate loadings. Results show the transverse shear stresses cannot be neglected in the impact problem. A significant level of strain rate dependency and material nonlinearity is found in the deformation response of representative composite specimens.

Calculation and manipulation of the chirp rates of high-order harmonics

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

Murakami, M.; Mauritsson, J.; Schafer, K.J.

2005-01-01

We calculate the linear chirp rates of high-order harmonics in argon, generated by intense, 810 nm laser pulses, and explore the dependence of the chirp rate on harmonic order, driving laser intensity, and pulse duration. By using a time-frequency representation of the harmonic fields we can identify several different linear chirp contributions to the plateau harmonics. Our results, which are based on numerical integration of the time-dependent Schroedinger equation, are in good agreement with the adiabatic predictions of the strong field approximation for the chirp rates. Extending the theoretical analysis in the recent paper by Mauritsson et al. [Phys. Rev.more » A 70, 021801(R) (2004)], we also manipulate the chirp rates of the harmonics by adding a chirp to the driving pulse. We show that the chirp rate for harmonic q is given by the sum of the intrinsic chirp rate, which is determined by the new duration and peak intensity of the chirped driving pulse, and q times the external chirp rate.« less

A preliminary compressible second-order closure model for high speed flows

NASA Technical Reports Server (NTRS)

Speziale, Charles G.; Sarkar, Sutanu

1989-01-01

A preliminary version of a compressible second-order closure model that was developed in connection with the National Aero-Space Plane Project is presented. The model requires the solution of transport equations for the Favre-averaged Reynolds stress tensor and dissipation rate. Gradient transport hypotheses are used for the Reynolds heat flux, mass flux, and turbulent diffusion terms. Some brief remarks are made about the direction of future research to generalize the model.

High-Order/Low-Order methods for ocean modeling

DOE PAGES

Newman, Christopher; Womeldorff, Geoff; Chacón, Luis; ...

2015-06-01

In this study, we examine a High Order/Low Order (HOLO) approach for a z-level ocean model and show that the traditional semi-implicit and split-explicit methods, as well as a recent preconditioning strategy, can easily be cast in the framework of HOLO methods. The HOLO formulation admits an implicit-explicit method that is algorithmically scalable and second-order accurate, allowing timesteps much larger than the barotropic time scale. We show how HOLO approaches, in particular the implicit-explicit method, can provide a solid route for ocean simulation to heterogeneous computing and exascale environments.

78 FR 18335 - Central Arizona Project-Rate Order No. WAPA-158

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-26

... Project, reflected in Transmission Service Rate Schedules CAP-FT2, CAP-NFT2, and CAP-NITS2, from January 1... existing Rate Schedules CAP-FT2, CAP-NFT2, CAP-NITS2 under Rate Order No. WAPA-124,\\1\\ were approved for a... Transmission Service Rate Schedules CAP-FT2, CAP-NFT2, and CAP-NITS2 on an interim basis effective as of...

3D modeling and characterization of a calorimetric flow rate sensor for sweat rate sensing applications

NASA Astrophysics Data System (ADS)

Iftekhar, Ahmed Tashfin; Ho, Jenny Che-Ting; Mellinger, Axel; Kaya, Tolga

2017-03-01

Sweat-based physiological monitoring has been intensively explored in the last decade with the hopes of developing real-time hydration monitoring devices. Although the content of sweat (electrolytes, lactate, urea, etc.) provides significant information about the physiology, it is also very important to know the rate of sweat at the time of sweat content measurements because the sweat rate is known to alter the concentrations of sweat compounds. We developed a calorimetric based flow rate sensor using PolydimethylSiloxane that is suitable for sweat rate applications. Our simple approach on using temperature-based flow rate detection can easily be adapted to multiple sweat collection and analysis devices. Moreover, we have developed a 3D finite element analysis model of the device using COMSOL Multiphysics™ and verified the flow rate measurements. The experiment investigated flow rate values from 0.3 μl/min up to 2.1 ml/min, which covers the human sweat rate range (0.5 μl/min-10 μl/min). The 3D model simulations and analytical model calculations covered an even wider range in order to understand the main physical mechanisms of the device. With a verified 3D model, different environmental heat conditions could be further studied to shed light on the physiology of the sweat rate.

Inferring Markov chains: Bayesian estimation, model comparison, entropy rate, and out-of-class modeling.

PubMed

Strelioff, Christopher C; Crutchfield, James P; Hübler, Alfred W

2007-07-01

Markov chains are a natural and well understood tool for describing one-dimensional patterns in time or space. We show how to infer kth order Markov chains, for arbitrary k , from finite data by applying Bayesian methods to both parameter estimation and model-order selection. Extending existing results for multinomial models of discrete data, we connect inference to statistical mechanics through information-theoretic (type theory) techniques. We establish a direct relationship between Bayesian evidence and the partition function which allows for straightforward calculation of the expectation and variance of the conditional relative entropy and the source entropy rate. Finally, we introduce a method that uses finite data-size scaling with model-order comparison to infer the structure of out-of-class processes.

First-order dissolution rate law and the role of surface layers in glass performance assessment

NASA Astrophysics Data System (ADS)

Grambow, B.; Müller, R.

2001-09-01

The first-order dissolution rate law is used for nuclear waste glass performance predictions since 1984. A first discussion of the role of saturation effects was initiated at the MRS conference that year. In paper (1) it was stated that "For glass dissolution A* (the reaction affinity) cannot become zero since saturation only involves the reacting surface while soluble elements still might be extracted from the glass" [B. Grambow, J. Mater. Res. Soc. Symp. Proc. 44 (1985) 15]. Saturation of silica at the surface and condensation of surface silanol groups was considered as being responsible for the slow down of reaction rates by as much as a factor of 1000. Precipitation of Si containing secondary phases such as quartz was invoked as a mechanism for keeping final dissolution affinities higher than zero. Another (2) paper [A.B. Barkatt, P.B. Macedo, B.C. Gibson, C.J. Montrose, J. Mater. Res. Soc. Symp. Proc. 44 (1985) 3] stated that "… under repository conditions the extent of glass dissolution will be moderate due to saturation with respect to certain major elements (in particular, Si, Al and Ca). Consequently, the concentration levels of the more soluble glass constituents in the aqueous medium are expected to fall appreciable below their solubility limit." The formation of dense surface layers was considered responsible for explaining the saturation effect. The mathematical model assumed stop of reaction in closed systems, once solubility limits were achieved. For more than 15 years the question of the correctness of one or the other concept has seldom been posed and has not yet been resolved. The need of repository performance assessment for validated rate laws demands a solution, particularly since the consequences of the two concepts and research requirements for the long-term glass behavior are quite different. In concept (1) the stability of the `equilibrium surface region' is not relevant because, by definition, this region is stable chemically and after a

Predicting inpatient clinical order patterns with probabilistic topic models vs conventional order sets.

PubMed

Chen, Jonathan H; Goldstein, Mary K; Asch, Steven M; Mackey, Lester; Altman, Russ B

2017-05-01

Build probabilistic topic model representations of hospital admissions processes and compare the ability of such models to predict clinical order patterns as compared to preconstructed order sets. The authors evaluated the first 24 hours of structured electronic health record data for > 10 K inpatients. Drawing an analogy between structured items (e.g., clinical orders) to words in a text document, the authors performed latent Dirichlet allocation probabilistic topic modeling. These topic models use initial clinical information to predict clinical orders for a separate validation set of > 4 K patients. The authors evaluated these topic model-based predictions vs existing human-authored order sets by area under the receiver operating characteristic curve, precision, and recall for subsequent clinical orders. Existing order sets predict clinical orders used within 24 hours with area under the receiver operating characteristic curve 0.81, precision 16%, and recall 35%. This can be improved to 0.90, 24%, and 47% ( P  < 10 -20 ) by using probabilistic topic models to summarize clinical data into up to 32 topics. Many of these latent topics yield natural clinical interpretations (e.g., "critical care," "pneumonia," "neurologic evaluation"). Existing order sets tend to provide nonspecific, process-oriented aid, with usability limitations impairing more precise, patient-focused support. Algorithmic summarization has the potential to breach this usability barrier by automatically inferring patient context, but with potential tradeoffs in interpretability. Probabilistic topic modeling provides an automated approach to detect thematic trends in patient care and generate decision support content. A potential use case finds related clinical orders for decision support. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association.

Predicting inpatient clinical order patterns with probabilistic topic models vs conventional order sets

PubMed Central

Goldstein, Mary K; Asch, Steven M; Mackey, Lester; Altman, Russ B

2017-01-01

Objective: Build probabilistic topic model representations of hospital admissions processes and compare the ability of such models to predict clinical order patterns as compared to preconstructed order sets. Materials and Methods: The authors evaluated the first 24 hours of structured electronic health record data for > 10 K inpatients. Drawing an analogy between structured items (e.g., clinical orders) to words in a text document, the authors performed latent Dirichlet allocation probabilistic topic modeling. These topic models use initial clinical information to predict clinical orders for a separate validation set of > 4 K patients. The authors evaluated these topic model-based predictions vs existing human-authored order sets by area under the receiver operating characteristic curve, precision, and recall for subsequent clinical orders. Results: Existing order sets predict clinical orders used within 24 hours with area under the receiver operating characteristic curve 0.81, precision 16%, and recall 35%. This can be improved to 0.90, 24%, and 47% (P < 10−20) by using probabilistic topic models to summarize clinical data into up to 32 topics. Many of these latent topics yield natural clinical interpretations (e.g., “critical care,” “pneumonia,” “neurologic evaluation”). Discussion: Existing order sets tend to provide nonspecific, process-oriented aid, with usability limitations impairing more precise, patient-focused support. Algorithmic summarization has the potential to breach this usability barrier by automatically inferring patient context, but with potential tradeoffs in interpretability. Conclusion: Probabilistic topic modeling provides an automated approach to detect thematic trends in patient care and generate decision support content. A potential use case finds related clinical orders for decision support. PMID:27655861

78 FR 35022 - Parker-Davis Project-Rate Order No. WAPA-162

Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-11

... DEPARTMENT OF ENERGY Western Area Power Administration Parker-Davis Project-Rate Order No. WAPA-162 AGENCY: Western Area Power Administration, DOE. ACTION: Notice of Proposed Extension of Firm Electric and Transmission Service Formula Rates. SUMMARY: The Western Area Power Administration (Western...

Reduced Order Podolsky Model

NASA Astrophysics Data System (ADS)

Thibes, Ronaldo

2017-02-01

We perform the canonical and path integral quantizations of a lower-order derivatives model describing Podolsky's generalized electrodynamics. The physical content of the model shows an auxiliary massive vector field coupled to the usual electromagnetic field. The equivalence with Podolsky's original model is studied at classical and quantum levels. Concerning the dynamical time evolution, we obtain a theory with two first-class and two second-class constraints in phase space. We calculate explicitly the corresponding Dirac brackets involving both vector fields. We use the Senjanovic procedure to implement the second-class constraints and the Batalin-Fradkin-Vilkovisky path integral quantization scheme to deal with the symmetries generated by the first-class constraints. The physical interpretation of the results turns out to be simpler due to the reduced derivatives order permeating the equations of motion, Dirac brackets and effective action.

Fractional-order in a macroeconomic dynamic model

NASA Astrophysics Data System (ADS)

David, S. A.; Quintino, D. D.; Soliani, J.

2013-10-01

In this paper, we applied the Riemann-Liouville approach in order to realize the numerical simulations to a set of equations that represent a fractional-order macroeconomic dynamic model. It is a generalization of a dynamic model recently reported in the literature. The aforementioned equations have been simulated for several cases involving integer and non-integer order analysis, with some different values to fractional order. The time histories and the phase diagrams have been plotted to visualize the effect of fractional order approach. The new contribution of this work arises from the fact that the macroeconomic dynamic model proposed here involves the public sector deficit equation, which renders the model more realistic and complete when compared with the ones encountered in the literature. The results reveal that the fractional-order macroeconomic model can exhibit a real reasonable behavior to macroeconomics systems and might offer greater insights towards the understanding of these complex dynamic systems.

Biotransformation of trace organic chemicals during groundwater recharge: How useful are first-order rate constants?

PubMed

Regnery, J; Wing, A D; Alidina, M; Drewes, J E

2015-08-01

This study developed relationships between the attenuation of emerging trace organic chemicals (TOrC) during managed aquifer recharge (MAR) as a function of retention time, system characteristics, and operating conditions using controlled laboratory-scale soil column experiments simulating MAR. The results revealed that MAR performance in terms of TOrC attenuation is primarily determined by key environmental parameters (i.e., redox, primary substrate). Soil columns with suboxic and anoxic conditions performed poorly (i.e., less than 30% attenuation of moderately degradable TOrC) in comparison to oxic conditions (on average between 70-100% attenuation for the same compounds) within a residence time of three days. Given this dependency on redox conditions, it was investigated if key parameter-dependent rate constants are more suitable for contaminant transport modeling to properly capture the dynamic TOrC attenuation under field-scale conditions. Laboratory-derived first-order removal kinetics were determined for 19 TOrC under three different redox conditions and rate constants were applied to MAR field data. Our findings suggest that simplified first-order rate constants will most likely not provide any meaningful results if the target compounds exhibit redox dependent biotransformation behavior or if the intention is to exactly capture the decline in concentration over time and distance at field-scale MAR. However, if the intention is to calculate the percent removal after an extended time period and subsurface travel distance, simplified first-order rate constants seem to be sufficient to provide a first estimate on TOrC attenuation during MAR. Copyright © 2015 Elsevier B.V. All rights reserved.

Reduced Order Modeling Incompressible Flows

NASA Technical Reports Server (NTRS)

Helenbrook, B. T.

2010-01-01

The details: a) Need stable numerical methods; b) Round off error can be considerable; c) Not convinced modes are correct for incompressible flow. Nonetheless, can derive compact and accurate reduced-order models. Can be used to generate actuator models or full flow-field models

The impact of item order on ratings of cancer risk perception.

PubMed

Taylor, Kathryn L; Shelby, Rebecca A; Schwartz, Marc D; Ackerman, Josh; LaSalle, V Holland; Gelmann, Edward P; McGuire, Colleen

2002-07-01

Although perceived risk is central to most theories of health behavior, there is little consensus on its measurement with regard to item wording, response set, or the number of items to include. In a methodological assessment of perceived risk, we assessed the impact of changing the order of three commonly used perceived risk items: quantitative personal risk, quantitative population risk, and comparative risk. Participants were 432 men and women enrolled in an ancillary study of the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial. Three groups of consecutively enrolled participants responded to the three items in one of three question orders. Results indicated that item order was related to the perceived risk ratings of both ovarian (P < 0.05) and colorectal (P < 0.05) cancers. Perceptions of risk were significantly lower when the comparative rating was made first. The findings suggest that compelling participants to consider their own risk relative to the risk of others results in lower ratings of perceived risk. Although the use of multiple items may provide more information than when only a single method is used, different conclusions may be reached depending on the context in which an item is assessed.

77 FR 5508 - Order on Intent To Revoke Market-Based Rate Authority

Federal Register 2010, 2011, 2012, 2013, 2014

2012-02-03

.... 2001, FERC Stats. & Regs. ] 31,127, reh'g denied, Order No. 2001-A, 100 FERC ] 61,074, reconsideration... market-based rates.\\2\\ \\2\\ Order No. 2001, FERC Stats & Regs. ] 31,127 at P 222. 4. The Commission...

Estimation of rates-across-sites distributions in phylogenetic substitution models.

PubMed

Susko, Edward; Field, Chris; Blouin, Christian; Roger, Andrew J

2003-10-01

Previous work has shown that it is often essential to account for the variation in rates at different sites in phylogenetic models in order to avoid phylogenetic artifacts such as long branch attraction. In most current models, the gamma distribution is used for the rates-across-sites distributions and is implemented as an equal-probability discrete gamma. In this article, we introduce discrete distribution estimates with large numbers of equally spaced rate categories allowing us to investigate the appropriateness of the gamma model. With large numbers of rate categories, these discrete estimates are flexible enough to approximate the shape of almost any distribution. Likelihood ratio statistical tests and a nonparametric bootstrap confidence-bound estimation procedure based on the discrete estimates are presented that can be used to test the fit of a parametric family. We applied the methodology to several different protein data sets, and found that although the gamma model often provides a good parametric model for this type of data, rate estimates from an equal-probability discrete gamma model with a small number of categories will tend to underestimate the largest rates. In cases when the gamma model assumption is in doubt, rate estimates coming from the discrete rate distribution estimate with a large number of rate categories provide a robust alternative to gamma estimates. An alternative implementation of the gamma distribution is proposed that, for equal numbers of rate categories, is computationally more efficient during optimization than the standard gamma implementation and can provide more accurate estimates of site rates.

Modeling the Growth Rates of Tetragonal Lysozyme Crystal Faces

NASA Technical Reports Server (NTRS)

Li, Meirong; Nadarajah, Arunan; Pusey, Marc L.

1998-01-01

with respect to its concentration at saturation in order to apply growth rate models to this process. The measured growth rates were then compared with the predicted ones from several dislocation and 2D nucleation growth models, employing tetramer and octamer growth units in polydisperse solutions and monomer units in monodisperse solutions. For the (110) face, the calculations consistently showed that the measured growth rates followed the expected model relations with octamer growth units. For the (101) face, it is not possible to obtain a clear agreement between the predicted and measured growth rates for a single growth unit as done for the (110) face. However, the calculations do indicate that the average size of the growth unit is between a tetramer and an octamer. This suggests that tetramers, octamers and other intermediate size growth units all participate in the growth process for this face. These calculations show that it is possible to model the macroscopic protein crystal growth rates if the molecular level processes can be account for, particularly protein aggregation processes in the bulk solution. Our recent investigations of tetragonal lysozyme crystals employing high resolution atomic force microscopy scans have further confirmed the growth of these crystals by aggregate growth units corresponding to 4(sub 3) helices.

3D Higher Order Modeling in the BEM/FEM Hybrid Formulation

NASA Technical Reports Server (NTRS)

Fink, P. W.; Wilton, D. R.

2000-01-01

Higher order divergence- and curl-conforming bases have been shown to provide significant benefits, in both convergence rate and accuracy, in the 2D hybrid finite element/boundary element formulation (P. Fink and D. Wilton, National Radio Science Meeting, Boulder, CO, Jan. 2000). A critical issue in achieving the potential for accuracy of the approach is the accurate evaluation of all matrix elements. These involve products of high order polynomials and, in some instances, singular Green's functions. In the 2D formulation, the use of a generalized Gaussian quadrature method was found to greatly facilitate the computation and to improve the accuracy of the boundary integral equation self-terms. In this paper, a 3D, hybrid electric field formulation employing higher order bases and higher order elements is presented. The improvements in convergence rate and accuracy, compared to those resulting from lower order modeling, are established. Techniques developed to facilitate the computation of the boundary integral self-terms are also shown to improve the accuracy of these terms. Finally, simple preconditioning techniques are used in conjunction with iterative solution procedures to solve the resulting linear system efficiently. In order to handle the boundary integral singularities in the 3D formulation, the parent element- either a triangle or rectangle-is subdivided into a set of sub-triangles with a common vertex at the singularity. The contribution to the integral from each of the sub-triangles is computed using the Duffy transformation to remove the singularity. This method is shown to greatly facilitate t'pe self-term computation when the bases are of higher order. In addition, the sub-triangles can be further divided to achieve near arbitrary accuracy in the self-term computation. An efficient method for subdividing the parent element is presented. The accuracy obtained using higher order bases is compared to that obtained using lower order bases when the number

Wind Farm Flow Modeling using an Input-Output Reduced-Order Model

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

Annoni, Jennifer; Gebraad, Pieter; Seiler, Peter

Wind turbines in a wind farm operate individually to maximize their own power regardless of the impact of aerodynamic interactions on neighboring turbines. There is the potential to increase power and reduce overall structural loads by properly coordinating turbines. To perform control design and analysis, a model needs to be of low computational cost, but retains the necessary dynamics seen in high-fidelity models. The objective of this work is to obtain a reduced-order model that represents the full-order flow computed using a high-fidelity model. A variety of methods, including proper orthogonal decomposition and dynamic mode decomposition, can be used tomore » extract the dominant flow structures and obtain a reduced-order model. In this paper, we combine proper orthogonal decomposition with a system identification technique to produce an input-output reduced-order model. This technique is used to construct a reduced-order model of the flow within a two-turbine array computed using a large-eddy simulation.« less

High rate constitutive modeling of aluminium alloy tube

NASA Astrophysics Data System (ADS)

Salisbury, C. P.; Worswick, M. J.; Mayer, R.

2006-08-01

As the need for fuel efficient automobiles increases, car designers are investigating light-weight materials for automotive bodies that will reduce the overall automobile weight. Aluminium alloy tube is a desirable material to use in automotive bodies due to its light weight. However, aluminium suffers from lower formability than steel and its energy absorption ability in a crash event after a forming operation is largely unknown. As part of a larger study on the relationship between crashworthiness and forming processes, constitutive models for 3mm AA5754 aluminium tube were developed. A nominal strain rate of 100/s is often used to characterize overall automobile crash events, whereas strain rates on the order of 1000/s can occur locally. Therefore, tests were performed at quasi-static rates using an Instron test fixture and at strain rates of 500/s to 1500/s using a tensile split Hopkinson bar. High rate testing was then conducted at rates of 500/s, 1000/s and 1500/s at 21circC, 150circC and 300circC. The generated data was then used to determine the constitutive parameters for the Johnson-Cook and Zerilli-Armstrong material models.

A new order splitting model with stochastic lead times for deterioration items

NASA Astrophysics Data System (ADS)

Sazvar, Zeinab; Akbari Jokar, Mohammad Reza; Baboli, Armand

2014-09-01

In unreliable supply environments, the strategy of pooling lead time risks by splitting replenishment orders among multiple suppliers simultaneously is an attractive sourcing policy that has captured the attention of academic researchers and corporate managers alike. While various assumptions are considered in the models developed, researchers tend to overlook an important inventory category in order splitting models: deteriorating items. In this paper, we study an order splitting policy for a retailer that sells a deteriorating product. The inventory system is modelled as a continuous review system (s, Q) under stochastic lead time. Demand rate per unit time is assumed to be constant over an infinite planning horizon and shortages are backordered completely. We develop two inventory models. In the first model, it is assumed that all the requirements are supplied by only one source, whereas in the second, two suppliers are available. We use sensitivity analysis to determine the situations in which each sourcing policy is the most economic. We then study a real case from the European pharmaceutical industry to demonstrate the applicability and effectiveness of the proposed models. Finally, more promising directions are suggested for future research.

Kinetics of Fe2+-Mg order-disorder in orthopyroxene: experimental studies and applications to cooling rates of rocks

NASA Astrophysics Data System (ADS)

Stimpfl, M.; Ganguly, J.; Molin, G.

2005-10-01

We determined the forward rate constant (K+) for the Fe2+-Mg order-disorder between the M2 and M1 sites of orthopyroxene (OPx), which is described by the homogeneous reaction Fe2+ (M2) + Mg(M1) ↔ Mg(M2) + Fe2+ (M1), by both ordering and disordering experiments at isothermal condition and also by continuous cooling experiments. The rate constant was determined as a function of temperature in the range of 550-750°C, oxygen fugacity between quartz-fayalite-iron and Ni-NiO buffers, and at compositions of 16 and 50 mol% ferrosilite component. The K+ value derived from disordering experiment was found to be larger than that derived from ordering experiment at 550°C, while at T>580°C, these two values are essentially the same. The fO2 dependence of the rate constant can be described by the relation K+ α (fO2) n with n=5.5-6.5, which is compatible with the theoretically expected relation. The Arrhenius relation at the WI buffer condition is given by ln (C_{text{o}} {text{K}}^+) = - {41511 - 12600{text{X}}_{{text{Fe}}} }/{{T({text{K}})}} + 28.26 + 5.27{text{X}}_{{text{Fe}}}, min^{-1} where C o represents the total number of M2 + M1 sites occupied by Fe2+ and Mg per unit volume of the crystal. The above relation can be used to calculate the cooling rates of natural OPx crystals around the closure temperature ( T c) of Fe-Mg ordering, which are usually below 300°C for slowly cooled rocks. We determined the Fe-Mg ordering states of several OPx crystals (˜ Fs50) from the Central Gneissic Complex (Khtada Lake), British Columbia, which yields T c ˜290°C. Numerical simulation of the change of Fe2+-Mg ordering in OPx as a function of temperature using the above expression of rate constant and a non-linear cooling model yields quenched values of ordering states that are in agreement with the observed values for cooling rates of 11-17°C/Myr below 300°C. The inferred cooling rate is in agreement with the available geochronological constraints.

Model for the orientational ordering of the plant microtubule cortical array

NASA Astrophysics Data System (ADS)

Hawkins, Rhoda J.; Tindemans, Simon H.; Mulder, Bela M.

2010-07-01

The plant microtubule cortical array is a striking feature of all growing plant cells. It consists of a more or less homogeneously distributed array of highly aligned microtubules connected to the inner side of the plasma membrane and oriented transversely to the cell growth axis. Here, we formulate a continuum model to describe the origin of orientational order in such confined arrays of dynamical microtubules. The model is based on recent experimental observations that show that a growing cortical microtubule can interact through angle dependent collisions with pre-existing microtubules that can lead either to co-alignment of the growth, retraction through catastrophe induction or crossing over the encountered microtubule. We identify a single control parameter, which is fully determined by the nucleation rate and intrinsic dynamics of individual microtubules. We solve the model analytically in the stationary isotropic phase, discuss the limits of stability of this isotropic phase, and explicitly solve for the ordered stationary states in a simplified version of the model.

Finite driving rate and anisotropy effects in landslide modeling

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

Piegari, E.; Cataudella, V.; Di Maio, R.

2006-02-15

In order to characterize landslide frequency-size distributions and individuate hazard scenarios and their possible precursors, we investigate a cellular automaton where the effects of a finite driving rate and the anisotropy are taken into account. The model is able to reproduce observed features of landslide events, such as power-law distributions, as experimentally reported. We analyze the key role of the driving rate and show that, as it is increased, a crossover from power-law to non-power-law behaviors occurs. Finally, a systematic investigation of the model on varying its anisotropy factors is performed and the full diagram of its dynamical behaviors ismore » presented.« less

Fractional-order leaky integrate-and-fire model with long-term memory and power law dynamics.

PubMed

Teka, Wondimu W; Upadhyay, Ranjit Kumar; Mondal, Argha

2017-09-01

Pyramidal neurons produce different spiking patterns to process information, communicate with each other and transform information. These spiking patterns have complex and multiple time scale dynamics that have been described with the fractional-order leaky integrate-and-Fire (FLIF) model. Models with fractional (non-integer) order differentiation that generalize power law dynamics can be used to describe complex temporal voltage dynamics. The main characteristic of FLIF model is that it depends on all past values of the voltage that causes long-term memory. The model produces spikes with high interspike interval variability and displays several spiking properties such as upward spike-frequency adaptation and long spike latency in response to a constant stimulus. We show that the subthreshold voltage and the firing rate of the fractional-order model make transitions from exponential to power law dynamics when the fractional order α decreases from 1 to smaller values. The firing rate displays different types of spike timing adaptation caused by changes on initial values. We also show that the voltage-memory trace and fractional coefficient are the causes of these different types of spiking properties. The voltage-memory trace that represents the long-term memory has a feedback regulatory mechanism and affects spiking activity. The results suggest that fractional-order models might be appropriate for understanding multiple time scale neuronal dynamics. Overall, a neuron with fractional dynamics displays history dependent activities that might be very useful and powerful for effective information processing. Copyright © 2017 Elsevier Ltd. All rights reserved.

Point model equations for neutron correlation counting: Extension of Böhnel's equations to any order

DOE PAGES

Favalli, Andrea; Croft, Stephen; Santi, Peter

2015-06-15

Various methods of autocorrelation neutron analysis may be used to extract information about a measurement item containing spontaneously fissioning material. The two predominant approaches being the time correlation analysis (that make use of a coincidence gate) methods of multiplicity shift register logic and Feynman sampling. The common feature is that the correlated nature of the pulse train can be described by a vector of reduced factorial multiplet rates. We call these singlets, doublets, triplets etc. Within the point reactor model the multiplet rates may be related to the properties of the item, the parameters of the detector, and basic nuclearmore » data constants by a series of coupled algebraic equations – the so called point model equations. Solving, or inverting, the point model equations using experimental calibration model parameters is how assays of unknown items is performed. Currently only the first three multiplets are routinely used. In this work we develop the point model equations to higher order multiplets using the probability generating functions approach combined with the general derivative chain rule, the so called Faà di Bruno Formula. Explicit expression up to 5th order are provided, as well the general iterative formula to calculate any order. This study represents the first necessary step towards determining if higher order multiplets can add value to nondestructive measurement practice for nuclear materials control and accountancy.« less

Triple-α reaction rate constrained by stellar evolution models

NASA Astrophysics Data System (ADS)

Suda, Takuma; Hirschi, Raphael; Fujimoto, Masayuki Y.

2012-11-01

We investigate the quantitative constraint on the triple-α reaction rate based on stellar evolution theory, motivated by the recent significant revision of the rate proposed by nuclear physics calculations. Targeted stellar models were computed in order to investigate the impact of that rate in the mass range of 0.8<=M/Msolar<=25 and in the metallicity range between Z = 0 and Z = 0.02. The revised rate has a significant impact on the evolution of low-and intermediate-mass stars, while its influence on the evolution of massive stars (M > 10Msolar) is minimal. We find that employing the revised rate suppresses helium shell flashes on AGB phase for stars in the initial mass range 0.8<=M/Msolar<=6, which is contradictory to what is observed. The absence of helium shell flashes is due to the weak temperature dependence of the revised triple-α reaction cross section at the temperature involved. In our models, it is suggested that the temperature dependence of the cross section should have at least ν > 10 at T = 1-1.2×108K where the cross section is proportional to Tν. We also derive the helium ignition curve to estimate the maximum cross section to retain the low-mass first red giants. The semi-analytically derived ignition curves suggest that the reaction rate should be less than ~ 10-29 cm6 s-1 mole-2 at ~ 107.8 K, which corresponds to about three orders of magnitude larger than that of the NACRE compilation.

First and Higher Order Effects on Zero Order Radiative Transfer Model

NASA Astrophysics Data System (ADS)

Neelam, M.; Mohanty, B.

2014-12-01

Microwave radiative transfer model are valuable tool in understanding the complex land surface interactions. Past literature has largely focused on local sensitivity analysis for factor priotization and ignoring the interactions between the variables and uncertainties around them. Since land surface interactions are largely nonlinear, there always exist uncertainties, heterogeneities and interactions thus it is important to quantify them to draw accurate conclusions. In this effort, we used global sensitivity analysis to address the issues of variable uncertainty, higher order interactions, factor priotization and factor fixing for zero-order radiative transfer (ZRT) model. With the to-be-launched Soil Moisture Active Passive (SMAP) mission of NASA, it is very important to have a complete understanding of ZRT for soil moisture retrieval to direct future research and cal/val field campaigns. This is a first attempt to use GSA technique to quantify first order and higher order effects on brightness temperature from ZRT model. Our analyses reflect conditions observed during the growing agricultural season for corn and soybeans in two different regions in - Iowa, U.S.A and Winnipeg, Canada. We found that for corn fields in Iowa, there exist significant second order interactions between soil moisture, surface roughness parameters (RMS height and correlation length) and vegetation parameters (vegetation water content, structure and scattering albedo), whereas in Winnipeg, second order interactions are mainly due to soil moisture and vegetation parameters. But for soybean fields in both Iowa and Winnipeg, we found significant interactions only to exist between soil moisture and surface roughness parameters.

Translating landfill methane generation parameters among first-order decay models.

PubMed

Krause, Max J; Chickering, Giles W; Townsend, Timothy G

2016-11-01

Landfill gas (LFG) generation is predicted by a first-order decay (FOD) equation that incorporates two parameters: a methane generation potential (L 0 ) and a methane generation rate (k). Because non-hazardous waste landfills may accept many types of waste streams, multiphase models have been developed in an attempt to more accurately predict methane generation from heterogeneous waste streams. The ability of a single-phase FOD model to predict methane generation using weighted-average methane generation parameters and tonnages translated from multiphase models was assessed in two exercises. In the first exercise, waste composition from four Danish landfills represented by low-biodegradable waste streams was modeled in the Afvalzorg Multiphase Model and methane generation was compared to the single-phase Intergovernmental Panel on Climate Change (IPCC) Waste Model and LandGEM. In the second exercise, waste composition represented by IPCC waste components was modeled in the multiphase IPCC and compared to single-phase LandGEM and Australia's Solid Waste Calculator (SWC). In both cases, weight-averaging of methane generation parameters from waste composition data in single-phase models was effective in predicting cumulative methane generation from -7% to +6% of the multiphase models. The results underscore the understanding that multiphase models will not necessarily improve LFG generation prediction because the uncertainty of the method rests largely within the input parameters. A unique method of calculating the methane generation rate constant by mass of anaerobically degradable carbon was presented (k c ) and compared to existing methods, providing a better fit in 3 of 8 scenarios. Generally, single phase models with weighted-average inputs can accurately predict methane generation from multiple waste streams with varied characteristics; weighted averages should therefore be used instead of regional default values when comparing models. Translating multiphase

Relaxed Poisson cure rate models.

PubMed

Rodrigues, Josemar; Cordeiro, Gauss M; Cancho, Vicente G; Balakrishnan, N

2016-03-01

The purpose of this article is to make the standard promotion cure rate model (Yakovlev and Tsodikov, ) more flexible by assuming that the number of lesions or altered cells after a treatment follows a fractional Poisson distribution (Laskin, ). It is proved that the well-known Mittag-Leffler relaxation function (Berberan-Santos, ) is a simple way to obtain a new cure rate model that is a compromise between the promotion and geometric cure rate models allowing for superdispersion. So, the relaxed cure rate model developed here can be considered as a natural and less restrictive extension of the popular Poisson cure rate model at the cost of an additional parameter, but a competitor to negative-binomial cure rate models (Rodrigues et al., ). Some mathematical properties of a proper relaxed Poisson density are explored. A simulation study and an illustration of the proposed cure rate model from the Bayesian point of view are finally presented. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Phase-field-crystal model for ordered crystals

NASA Astrophysics Data System (ADS)

Alster, Eli; Elder, K. R.; Hoyt, Jeffrey J.; Voorhees, Peter W.

2017-02-01

We describe a general method to model multicomponent ordered crystals using the phase-field-crystal (PFC) formalism. As a test case, a generic B2 compound is investigated. We are able to produce a line of either first-order or second-order order-disorder phase transitions, features that have not been incorporated in existing PFC approaches. Further, it is found that the only elastic constant for B2 that depends on ordering is C11. This B2 model is then used to study antiphase boundaries (APBs). The APBs are shown to reproduce classical mean-field results. Dynamical simulations of ordering across small-angle grain boundaries predict that dislocation cores pin the evolution of APBs.

Reduced-Order Structure-Preserving Model for Parallel-Connected Three-Phase Grid-Tied Inverters

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

Johnson, Brian B; Purba, Victor; Jafarpour, Saber

Next-generation power networks will contain large numbers of grid-connected inverters satisfying a significant fraction of system load. Since each inverter model has a relatively large number of dynamic states, it is impractical to analyze complex system models where the full dynamics of each inverter are retained. To address this challenge, we derive a reduced-order structure-preserving model for parallel-connected grid-tied three-phase inverters. Here, each inverter in the system is assumed to have a full-bridge topology, LCL filter at the point of common coupling, and the control architecture for each inverter includes a current controller, a power controller, and a phase-locked loopmore » for grid synchronization. We outline a structure-preserving reduced-order inverter model with lumped parameters for the setting where the parallel inverters are each designed such that the filter components and controller gains scale linearly with the power rating. By structure preserving, we mean that the reduced-order three-phase inverter model is also composed of an LCL filter, a power controller, current controller, and PLL. We show that the system of parallel inverters can be modeled exactly as one aggregated inverter unit and this equivalent model has the same number of dynamical states as any individual inverter in the system. Numerical simulations validate the reduced-order model.« less

Effects of distribution of infection rate on epidemic models

NASA Astrophysics Data System (ADS)

Lachiany, Menachem; Louzoun, Yoram

2016-08-01

A goal of many epidemic models is to compute the outcome of the epidemics from the observed infected early dynamics. However, often, the total number of infected individuals at the end of the epidemics is much lower than predicted from the early dynamics. This discrepancy is argued to result from human intervention or nonlinear dynamics not incorporated in standard models. We show that when variability in infection rates is included in standard susciptible-infected-susceptible (SIS ) and susceptible-infected-recovered (SIR ) models the total number of infected individuals in the late dynamics can be orders lower than predicted from the early dynamics. This discrepancy holds for SIS and SIR models, where the assumption that all individuals have the same sensitivity is eliminated. In contrast with network models, fixed partnerships are not assumed. We derive a moment closure scheme capturing the distribution of sensitivities. We find that the shape of the sensitivity distribution does not affect R0 or the number of infected individuals in the early phases of the epidemics. However, a wide distribution of sensitivities reduces the total number of removed individuals in the SIR model and the steady-state infected fraction in the SIS model. The difference between the early and late dynamics implies that in order to extrapolate the expected effect of the epidemics from the initial phase of the epidemics, the rate of change in the average infectivity should be computed. These results are supported by a comparison of the theoretical model to the Ebola epidemics and by numerical simulation.

Application of long-range order to predict unfolding rates of two-state proteins.

PubMed

Harihar, B; Selvaraj, S

2011-03-01

Predicting the experimental unfolding rates of two-state proteins and models describing the unfolding rates of these proteins is quite limited because of the complexity present in the unfolding mechanism and the lack of experimental unfolding data compared with folding data. In this work, 25 two-state proteins characterized by Maxwell et al. (Protein Sci 2005;14:602–616) using a consensus set of experimental conditions were taken, and the parameter long-range order (LRO) derived from their three-dimensional structures were related with their experimental unfolding rates ln(k(u)). From the total data set of 30 proteins used by Maxwell et al. (Protein Sci 2005;14:602–616), five slow-unfolding proteins with very low unfolding rates were considered to be outliers and were not included in our data set. Except all beta structural class, LRO of both the all-alpha and mixed-class proteins showed a strong inverse correlation of r = -0.99 and -0.88, respectively, with experimental ln(k(u)). LRO shows a correlation of -0.62 with experimental ln(k(u)) for all-beta proteins. For predicting the unfolding rates, a simple statistical method has been used and linear regression equations were developed for individual structural classes of proteins using LRO, and the results obtained showed a better agreement with experimental results. Copyright © 2010 Wiley-Liss, Inc.

Adaptation of hidden Markov models for recognizing speech of reduced frame rate.

PubMed

Lee, Lee-Min; Jean, Fu-Rong

2013-12-01

The frame rate of the observation sequence in distributed speech recognition applications may be reduced to suit a resource-limited front-end device. In order to use models trained using full-frame-rate data in the recognition of reduced frame-rate (RFR) data, we propose a method for adapting the transition probabilities of hidden Markov models (HMMs) to match the frame rate of the observation. Experiments on the recognition of clean and noisy connected digits are conducted to evaluate the proposed method. Experimental results show that the proposed method can effectively compensate for the frame-rate mismatch between the training and the test data. Using our adapted model to recognize the RFR speech data, one can significantly reduce the computation time and achieve the same level of accuracy as that of a method, which restores the frame rate using data interpolation.

Model predictive control based on reduced order models applied to belt conveyor system.

PubMed

Chen, Wei; Li, Xin

2016-11-01

In the paper, a model predictive controller based on reduced order model is proposed to control belt conveyor system, which is an electro-mechanics complex system with long visco-elastic body. Firstly, in order to design low-degree controller, the balanced truncation method is used for belt conveyor model reduction. Secondly, MPC algorithm based on reduced order model for belt conveyor system is presented. Because of the error bound between the full-order model and reduced order model, two Kalman state estimators are applied in the control scheme to achieve better system performance. Finally, the simulation experiments are shown that balanced truncation method can significantly reduce the model order with high-accuracy and model predictive control based on reduced-model performs well in controlling the belt conveyor system. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Probabilistic models and uncertainty quantification for the ionization reaction rate of atomic Nitrogen

NASA Astrophysics Data System (ADS)

Miki, K.; Panesi, M.; Prudencio, E. E.; Prudhomme, S.

2012-05-01

The objective in this paper is to analyze some stochastic models for estimating the ionization reaction rate constant of atomic Nitrogen (N + e- → N+ + 2e-). Parameters of the models are identified by means of Bayesian inference using spatially resolved absolute radiance data obtained from the Electric Arc Shock Tube (EAST) wind-tunnel. The proposed methodology accounts for uncertainties in the model parameters as well as physical model inadequacies, providing estimates of the rate constant that reflect both types of uncertainties. We present four different probabilistic models by varying the error structure (either additive or multiplicative) and by choosing different descriptions of the statistical correlation among data points. In order to assess the validity of our methodology, we first present some calibration results obtained with manufactured data and then proceed by using experimental data collected at EAST experimental facility. In order to simulate the radiative signature emitted in the shock-heated air plasma, we use a one-dimensional flow solver with Park's two-temperature model that simulates non-equilibrium effects. We also discuss the implications of the choice of the stochastic model on the estimation of the reaction rate and its uncertainties. Our analysis shows that the stochastic models based on correlated multiplicative errors are the most plausible models among the four models proposed in this study. The rate of the atomic Nitrogen ionization is found to be (6.2 ± 3.3) × 1011 cm3 mol-1 s-1 at 10,000 K.

Modeling Tetragonal Lysozyme Crystal Growth Rates

NASA Technical Reports Server (NTRS)

Gorti, Sridhar; Forsythe, Elizabeth L.; Pusey, Marc L.

2003-01-01

Tetragonal lysozyme 110 face crystal growth rates, measured over 5 orders of magnitude in range, can be described using a model where growth occurs by 2D nucleation on the crystal surface for solution supersaturations of c/c(sub eq) less than or equal to 7 +/- 2. Based upon the model, the step energy per unit length, beta was estimated to be approx. 5.3 +/- 0.4 x 10(exp -7) erg/mol-cm, which for a step height of 56 A corresponds to barrier of approx. 7 +/- 1 k(sub B)T at 300 K. For supersaturations of c/c(sub eq) > 8, the model emphasizing crystal growth by 2D nucleation not only could not predict, but also consistently overestimated, the highest observable crystal growth rates. Kinetic roughening is hypothesized to occur at a cross-over supersaturation of c/c(sub eq) > 8, where crystal growth is postulated to occur by a different process such as adsorption. Under this assumption, all growth rate data indicated that a kinetic roughening transition and subsequent crystal growth by adsorption for all solution conditions, varying in buffer pH, temperature and precipitant concentration, occurs for c/c(sub eq)(T, pH, NaCl) in the range between 5 and 10, with an energy barrier for adsorption estimated to be approx. 20 k(sub B)T at 300 K. Based upon these and other estimates, we determined the size of the critical surface nucleate, at the crossover supersaturation and higher concentrations, to range from 4 to 10 molecules.

LS-DYNA Implementation of Polymer Matrix Composite Model Under High Strain Rate Impact

NASA Technical Reports Server (NTRS)

Zheng, Xia-Hua; Goldberg, Robert K.; Binienda, Wieslaw K.; Roberts, Gary D.

2003-01-01

A recently developed constitutive model is implemented into LS-DYNA as a user defined material model (UMAT) to characterize the nonlinear strain rate dependent behavior of polymers. By utilizing this model within a micromechanics technique based on a laminate analogy, an algorithm to analyze the strain rate dependent, nonlinear deformation of a fiber reinforced polymer matrix composite is then developed as a UMAT to simulate the response of these composites under high strain rate impact. The models are designed for shell elements in order to ensure computational efficiency. Experimental and numerical stress-strain curves are compared for two representative polymers and a representative polymer matrix composite, with the analytical model predicting the experimental response reasonably well.

A Randomized Trial of Displaying Paid Price Information on Imaging Study and Procedure Ordering Rates.

PubMed

Chien, Alyna T; Lehmann, Lisa Soleymani; Hatfield, Laura A; Koplan, Kate E; Petty, Carter R; Sinaiko, Anna D; Rosenthal, Meredith B; Sequist, Thomas D

2017-04-01

Prior studies have demonstrated how price transparency lowers the test-ordering rates of trainees in hospitals, and physician-targeted price transparency efforts have been viewed as a promising cost-controlling strategy. To examine the effect of displaying paid-price information on test-ordering rates for common imaging studies and procedures within an accountable care organization (ACO). Block randomized controlled trial for 1 year. A total of 1205 fully licensed clinicians (728 primary care, 477 specialists). Starting January 2014, clinicians in the Control arm received no price display; those in the intervention arms received Single or Paired Internal/External Median Prices in the test-ordering screen of their electronic health record. Internal prices were the amounts paid by insurers for the ACO's services; external paid prices were the amounts paid by insurers for the same services when delivered by unaffiliated providers. Ordering rates (orders per 100 face-to-face encounters with adult patients): overall, designated to be completed internally within the ACO, considered "inappropriate" (e.g., MRI for simple headache), and thought to be "appropriate" (e.g., screening colonoscopy). We found no significant difference in overall ordering rates across the Control, Single Median Price, or Paired Internal/External Median Prices study arms. For every 100 encounters, clinicians in the Control arm ordered 15.0 (SD 31.1) tests, those in the Single Median Price arm ordered 15.0 (SD 16.2) tests, and those in the Paired Prices arms ordered 15.7 (SD 20.5) tests (one-way ANOVA p-value 0.88). There was no difference in ordering rates for tests designated to be completed internally or considered to be inappropriate or appropriate. Displaying paid-price information did not alter how frequently primary care and specialist clinicians ordered imaging studies and procedures within an ACO. Those with a particular interest in removing waste from the health care system may want to

Mixed-order phase transition in a one-dimensional model.

PubMed

Bar, Amir; Mukamel, David

2014-01-10

We introduce and analyze an exactly soluble one-dimensional Ising model with long range interactions that exhibits a mixed-order transition, namely a phase transition in which the order parameter is discontinuous as in first order transitions while the correlation length diverges as in second order transitions. Such transitions are known to appear in a diverse classes of models that are seemingly unrelated. The model we present serves as a link between two classes of models that exhibit a mixed-order transition in one dimension, namely, spin models with a coupling constant that decays as the inverse distance squared and models of depinning transitions, thus making a step towards a unifying framework.

Thermodynamic Analysis of Chemically Reacting Mixtures-Comparison of First and Second Order Models.

PubMed

Pekař, Miloslav

2018-01-01

Recently, a method based on non-equilibrium continuum thermodynamics which derives thermodynamically consistent reaction rate models together with thermodynamic constraints on their parameters was analyzed using a triangular reaction scheme. The scheme was kinetically of the first order. Here, the analysis is further developed for several first and second order schemes to gain a deeper insight into the thermodynamic consistency of rate equations and relationships between chemical thermodynamic and kinetics. It is shown that the thermodynamic constraints on the so-called proper rate coefficient are usually simple sign restrictions consistent with the supposed reaction directions. Constraints on the so-called coupling rate coefficients are more complex and weaker. This means more freedom in kinetic coupling between reaction steps in a scheme, i.e., in the kinetic effects of other reactions on the rate of some reaction in a reacting system. When compared with traditional mass-action rate equations, the method allows a reduction in the number of traditional rate constants to be evaluated from data, i.e., a reduction in the dimensionality of the parameter estimation problem. This is due to identifying relationships between mass-action rate constants (relationships which also include thermodynamic equilibrium constants) which have so far been unknown.

Modeling of geogenic radon in Switzerland based on ordered logistic regression.

PubMed

Kropat, Georg; Bochud, François; Murith, Christophe; Palacios Gruson, Martha; Baechler, Sébastien

2017-01-01

The estimation of the radon hazard of a future construction site should ideally be based on the geogenic radon potential (GRP), since this estimate is free of anthropogenic influences and building characteristics. The goal of this study was to evaluate terrestrial gamma dose rate (TGD), geology, fault lines and topsoil permeability as predictors for the creation of a GRP map based on logistic regression. Soil gas radon measurements (SRC) are more suited for the estimation of GRP than indoor radon measurements (IRC) since the former do not depend on ventilation and heating habits or building characteristics. However, SRC have only been measured at a few locations in Switzerland. In former studies a good correlation between spatial aggregates of IRC and SRC has been observed. That's why we used IRC measurements aggregated on a 10 km × 10 km grid to calibrate an ordered logistic regression model for geogenic radon potential (GRP). As predictors we took into account terrestrial gamma doserate, regrouped geological units, fault line density and the permeability of the soil. The classification success rate of the model results to 56% in case of the inclusion of all 4 predictor variables. Our results suggest that terrestrial gamma doserate and regrouped geological units are more suited to model GRP than fault line density and soil permeability. Ordered logistic regression is a promising tool for the modeling of GRP maps due to its simplicity and fast computation time. Future studies should account for additional variables to improve the modeling of high radon hazard in the Jura Mountains of Switzerland. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Population Heterogeneity in Mutation Rate Increases the Frequency of Higher-Order Mutants and Reduces Long-Term Mutational Load

PubMed Central

Alexander, Helen K.; Mayer, Stephanie I.; Bonhoeffer, Sebastian

2017-01-01

Abstract Mutation rate is a crucial evolutionary parameter that has typically been treated as a constant in population genetic analyses. However, the propensity to mutate is likely to vary among co-existing individuals within a population, due to genetic polymorphisms, heterogeneous environmental influences, and random physiological fluctuations. We review the evidence for mutation rate heterogeneity and explore its consequences by extending classic population genetic models to allow an arbitrary distribution of mutation rate among individuals, either with or without inheritance. With this general new framework, we rigorously establish the effects of heterogeneity at various evolutionary timescales. In a single generation, variation of mutation rate about the mean increases the probability of producing zero or many simultaneous mutations on a genome. Over multiple generations of mutation and selection, heterogeneity accelerates the appearance of both deleterious and beneficial multi-point mutants. At mutation-selection balance, higher-order mutant frequencies are likewise boosted, while lower-order mutants exhibit subtler effects; nonetheless, population mean fitness is always enhanced. We quantify the dependencies on moments of the mutation rate distribution and selection coefficients, and clarify the role of mutation rate inheritance. While typical methods of estimating mutation rate will recover only the population mean, analyses assuming mutation rate is fixed to this mean could underestimate the potential for multi-locus adaptation, including medically relevant evolution in pathogenic and cancerous populations. We discuss the potential to empirically parameterize mutation rate distributions, which have to date hardly been quantified. PMID:27836985

Forecasting the mortality rates of Malaysian population using Heligman-Pollard model

NASA Astrophysics Data System (ADS)

Ibrahim, Rose Irnawaty; Mohd, Razak; Ngataman, Nuraini; Abrisam, Wan Nur Azifah Wan Mohd

2017-08-01

Actuaries, demographers and other professionals have always been aware of the critical importance of mortality forecasting due to declining trend of mortality and continuous increases in life expectancy. Heligman-Pollard model was introduced in 1980 and has been widely used by researchers in modelling and forecasting future mortality. This paper aims to estimate an eight-parameter model based on Heligman and Pollard's law of mortality. Since the model involves nonlinear equations that are explicitly difficult to solve, the Matrix Laboratory Version 7.0 (MATLAB 7.0) software will be used in order to estimate the parameters. Statistical Package for the Social Sciences (SPSS) will be applied to forecast all the parameters according to Autoregressive Integrated Moving Average (ARIMA). The empirical data sets of Malaysian population for period of 1981 to 2015 for both genders will be considered, which the period of 1981 to 2010 will be used as "training set" and the period of 2011 to 2015 as "testing set". In order to investigate the accuracy of the estimation, the forecast results will be compared against actual data of mortality rates. The result shows that Heligman-Pollard model fit well for male population at all ages while the model seems to underestimate the mortality rates for female population at the older ages.

Quantification of biodegradation for o-xylene and naphthalene using first order decay models, Michaelis-Menten kinetics and stable carbon isotopes.

PubMed

Blum, Philipp; Hunkeler, Daniel; Weede, Matthias; Beyer, Christof; Grathwohl, Peter; Morasch, Barbara

2009-04-01

At a former wood preservation plant severely contaminated with coal tar oil, in situ bulk attenuation and biodegradation rate constants for several monoaromatic (BTEX) and polyaromatic hydrocarbons (PAH) were determined using (1) classical first order decay models, (2) Michaelis-Menten degradation kinetics (MM), and (3) stable carbon isotopes, for o-xylene and naphthalene. The first order bulk attenuation rate constant for o-xylene was calculated to be 0.0025 d(-1) and a novel stable isotope-based first order model, which also accounted for the respective redox conditions, resulted in a slightly smaller biodegradation rate constant of 0.0019 d(-1). Based on MM-kinetics, the o-xylene concentration decreased with a maximum rate of k(max)=0.1 microg/L/d. The bulk attenuation rate constant of naphthalene retrieved from the classical first order decay model was 0.0038 d(-1). The stable isotope-based biodegradation rate constant of 0.0027 d(-1) was smaller in the reduced zone, while residual naphthalene in the oxic part of the plume further downgradient was degraded at a higher rate of 0.0038 d(-1). With MM-kinetics a maximum degradation rate of k(max)=12 microg/L/d was determined. Although best fits were obtained by MM-kinetics, we consider the carbon stable isotope-based approach more appropriate as it is specific for biodegradation (not overall attenuation) and at the same time accounts for the dominant electron-accepting process. For o-xylene a field based isotope enrichment factor epsilon(field) of -1.4 could be determined using the Rayleigh model, which closely matched values from laboratory studies of o-xylene degradation under sulfate-reducing conditions.

Analysis of Factors that Influence Infiltration Rates using the HELP Model

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

Dyer, J.; Shipmon, J.

The Hydrologic Evaluation of Landfill Performance (HELP) model is used by Savannah River National Laboratory (SRNL) in conjunction with PORFLOW groundwater flow simulation software to make longterm predictions of the fate and transport of radionuclides in the environment at radiological waste sites. The work summarized in this report supports preparation of the planned 2018 Performance Assessment for the E-Area Low-Level Waste Facility (LLWF) at the Savannah River Site (SRS). More specifically, this project focused on conducting a sensitivity analysis of infiltration (i.e., the rate at which water travels vertically in soil) through the proposed E-Area LLWF closure cap. A sensitivitymore » analysis was completed using HELP v3.95D to identify the cap design and material property parameters that most impact infiltration rates through the proposed closure cap for a 10,000-year simulation period. The results of the sensitivity analysis indicate that saturated hydraulic conductivity (Ksat) for select cap layers, precipitation rate, surface vegetation type, and geomembrane layer defect density are dominant factors limiting infiltration rate. Interestingly, calculated infiltration rates were substantially influenced by changes in the saturated hydraulic conductivity of the Upper Foundation and Lateral Drainage layers. For example, an order-of-magnitude decrease in Ksat for the Upper Foundation layer lowered the maximum infiltration rate from a base-case 11 inches per year to only two inches per year. Conversely, an order-of-magnitude increase in Ksat led to an increase in infiltration rate from 11 to 15 inches per year. This work and its results provide a framework for quantifying uncertainty in the radionuclide transport and dose models for the planned 2018 E-Area Performance Assessment. Future work will focus on the development of a nonlinear regression model for infiltration rate using Minitab 17® to facilitate execution of probabilistic simulations in the Gold

A higher-order Skyrme model

NASA Astrophysics Data System (ADS)

Gudnason, Sven Bjarke; Nitta, Muneto

2017-09-01

We propose a higher-order Skyrme model with derivative terms of eighth, tenth and twelfth order. Our construction yields simple and easy-to-interpret higher-order Lagrangians. We first show that a Skyrmion with higher-order terms proposed by Marleau has an instability in the form of a baby-Skyrmion string, while the static energies of our construction are positive definite, implying stability against time-independent perturbations. However, we also find that the Hamiltonians of our construction possess two kinds of dynamical instabilities, which may indicate the instability with respect to time-dependent perturbations. Different from the well-known Ostrogradsky instability, the instabilities that we find are intrinsically of nonlinear nature and also due to the fact that even powers of the inverse metric gives a ghost-like higher-order kinetic-like term. The vacuum state is, however, stable. Finally, we show that at sufficiently low energies, our Hamiltonians in the simplest cases, are stable against time-dependent perturbations.

Design of multivariable feedback control systems via spectral assignment using reduced-order models and reduced-order observers

NASA Technical Reports Server (NTRS)

Mielke, R. R.; Tung, L. J.; Carraway, P. I., III

1984-01-01

The feasibility of using reduced order models and reduced order observers with eigenvalue/eigenvector assignment procedures is investigated. A review of spectral assignment synthesis procedures is presented. Then, a reduced order model which retains essential system characteristics is formulated. A constant state feedback matrix which assigns desired closed loop eigenvalues and approximates specified closed loop eigenvectors is calculated for the reduced order model. It is shown that the eigenvalue and eigenvector assignments made in the reduced order system are retained when the feedback matrix is implemented about the full order system. In addition, those modes and associated eigenvectors which are not included in the reduced order model remain unchanged in the closed loop full order system. The full state feedback design is then implemented by using a reduced order observer. It is shown that the eigenvalue and eigenvector assignments of the closed loop full order system rmain unchanged when a reduced order observer is used. The design procedure is illustrated by an actual design problem.

Design of multivariable feedback control systems via spectral assignment using reduced-order models and reduced-order observers

NASA Technical Reports Server (NTRS)

Mielke, R. R.; Tung, L. J.; Carraway, P. I., III

1985-01-01

The feasibility of using reduced order models and reduced order observers with eigenvalue/eigenvector assignment procedures is investigated. A review of spectral assignment synthesis procedures is presented. Then, a reduced order model which retains essential system characteristics is formulated. A constant state feedback matrix which assigns desired closed loop eigenvalues and approximates specified closed loop eigenvectors is calculated for the reduced order model. It is shown that the eigenvalue and eigenvector assignments made in the reduced order system are retained when the feedback matrix is implemented about the full order system. In addition, those modes and associated eigenvectors which are not included in the reduced order model remain unchanged in the closed loop full order system. The fulll state feedback design is then implemented by using a reduced order observer. It is shown that the eigenvalue and eigenvector assignments of the closed loop full order system remain unchanged when a reduced order observer is used. The design procedure is illustrated by an actual design problem.

Molecular and Kinetic Models for High-rate Thermal Degradation of Polyethylene

DOE PAGES

Lane, J. Matthew; Moore, Nathan W.

2018-02-01

Thermal degradation of polyethylene is studied under the extremely high rate temperature ramps expected in laser-driven and X-ray ablation experiments—from 10 10 to 10 14 K/s in isochoric, condensed phases. The molecular evolution and macroscopic state variables are extracted as a function of density from reactive molecular dynamics simulations using the ReaxFF potential. The enthalpy, dissociation onset temperature, bond evolution, and observed cross-linking are shown to be rate dependent. These results are used to parametrize a kinetic rate model for the decomposition and coalescence of hydrocarbons as a function of temperature, temperature ramp rate, and density. In conclusion, the resultsmore » are contrasted to first-order random-scission macrokinetic models often assumed for pyrolysis of linear polyethylene under ambient conditions.« less

Molecular and Kinetic Models for High-rate Thermal Degradation of Polyethylene

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

Lane, J. Matthew; Moore, Nathan W.

Thermal degradation of polyethylene is studied under the extremely high rate temperature ramps expected in laser-driven and X-ray ablation experiments—from 10 10 to 10 14 K/s in isochoric, condensed phases. The molecular evolution and macroscopic state variables are extracted as a function of density from reactive molecular dynamics simulations using the ReaxFF potential. The enthalpy, dissociation onset temperature, bond evolution, and observed cross-linking are shown to be rate dependent. These results are used to parametrize a kinetic rate model for the decomposition and coalescence of hydrocarbons as a function of temperature, temperature ramp rate, and density. In conclusion, the resultsmore » are contrasted to first-order random-scission macrokinetic models often assumed for pyrolysis of linear polyethylene under ambient conditions.« less

Effects of substrate misorientation and growth rate on ordering in GaInP

NASA Astrophysics Data System (ADS)

Su, L. C.; Ho, I. H.; Stringfellow, G. B.

1994-05-01

Epitaxial layers of GaxIn1-xP with x≊0.52 have been grown by organometallic vapor-phase epitaxy on GaAs substrates misoriented from the (001) plane in the [1¯10] direction by angles ϑm, of 0°, 3°, 6°, and 9°. For each substrate orientation growth rates rg of 1, 2, and 4 μm/h have been used. The ordering was characterized using transmission electron diffraction (TED), dark-field imaging, and photoluminescence. The (110) cross-sectional images show domains of the Cu-Pt structure separated by antiphase boundaries (APBs). The domain size and shape and the degree of order are found to be strongly affected by both the substrate misorientation and the growth rate. For example, lateral domain dimensions range from 50 Å for layers grown with rg=4 μm/h and ϑm=0° to 2500 Å for rg=1 μm/h and ϑm=9°. The APBs generally propagate from the substrate/epilayer interface to the top surface at an angle to the (001) plane that increases dramatically as the angle of misorientation increases. The angle is nearly independent of growth rate. From the superspot intensities in the TED patterns, the degree of order appears to be a maximum for ϑm≊5°. Judging from the reduction in photoluminescence peak energy caused by ordering, the maximum degree of order appears to occur at ϑm≊4°.

Reduced-Order Biogeochemical Flux Model for High-Resolution Multi-Scale Biophysical Simulations

NASA Astrophysics Data System (ADS)

Smith, K.; Hamlington, P.; Pinardi, N.; Zavatarelli, M.; Milliff, R. F.

2016-12-01

Biogeochemical tracers and their interactions with upper ocean physical processes such as submesoscale circulations and small-scale turbulence are critical for understanding the role of the ocean in the global carbon cycle. These interactions can cause small-scale spatial and temporal heterogeneity in tracer distributions which can, in turn, greatly affect carbon exchange rates between the atmosphere and interior ocean. For this reason, it is important to take into account small-scale biophysical interactions when modeling the global carbon cycle. However, explicitly resolving these interactions in an earth system model (ESM) is currently infeasible due to the enormous associated computational cost. As a result, understanding and subsequently parametrizing how these small-scale heterogeneous distributions develop and how they relate to larger resolved scales is critical for obtaining improved predictions of carbon exchange rates in ESMs. In order to address this need, we have developed the reduced-order, 17 state variable Biogeochemical Flux Model (BFM-17). This model captures the behavior of open-ocean biogeochemical systems without substantially increasing computational cost, thus allowing the model to be combined with computationally-intensive, fully three-dimensional, non-hydrostatic large eddy simulations (LES). In this talk, we couple BFM-17 with the Princeton Ocean Model and show good agreement between predicted monthly-averaged results and Bermuda testbed area field data (including the Bermuda-Atlantic Time Series and Bermuda Testbed Mooring). Through these tests, we demonstrate the capability of BFM-17 to accurately model open-ocean biochemistry. Additionally, we discuss the use of BFM-17 within a multi-scale LES framework and outline how this will further our understanding of turbulent biophysical interactions in the upper ocean.

The use of ordered mixtures for improving the dissolution rate of low solubility compounds.

PubMed

Nyström, C; Westerberg, M

1986-03-01

The dissolution rate of micronized griseofulvin has been investigated, both for the agglomerated raw material and the material formulated as an ordered mixture, by means of the USP XX paddle method. During the experiments, which were performed at sink condition and constant temperature, the effects of adding a surfactant and of agitation were tested. The ordered mixture with sodium chloride gave a fast dissolution rate, practically independent of the test parameters. Micronized griseofulvin alone gave dissolution profiles that were improved by adding polysorbate 80 and by increased agitation, but the dissolution rates obtained were much lower than those for the ordered mixture. It was concluded that the rate limiting step in the dissolution of griseofulvin as the raw material is the penetration of the dissolution medium into the agglomerates. With an ordered mixture, these agglomerates were deaggregated during the mixing process, producing a system in which the entire external surface area of the primary particles was exposed to the dissolution medium. This conclusion was supported by calculation of the contact surface areas taking part in the dissolution process for the systems tested. The procedure developed in this study could be applied to preformulation work where a cohesive, low solubility drug of hydrophobic nature is to be formulated.

A New Global Geodetic Strain Rate Model

NASA Astrophysics Data System (ADS)

Kreemer, C. W.; Klein, E. C.; Blewitt, G.; Shen, Z.; Wang, M.; Chamot-Rooke, N. R.; Rabaute, A.

2012-12-01

conditions for the strain rate calculations. For the strain rate calculations we used the method of Haines and Holt. In order to equally fit the data in slowly and rapidly deforming areas, we first calculated a very smooth model by setting the a priori variances of the strain rate components very low. We then used this model as a proxy for the a priori standard deviations of the final model. To add some more constraints to the model (to make it more stable), we manipulated the a priori covariance matrix to reflect the expected style of deformation derived from (an interpolation of) shallow earthquake focal mechanisms. We will show examples of the strain rate and velocity field results. We will also highlight how and where the results can be viewed and accessed through a dedicated webportal.

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 Ability Differentiation in the Second-Order Factor Model

ERIC Educational Resources Information Center

Molenaar, Dylan; Dolan, Conor V.; van der Maas, Han L. J.

2011-01-01

In this article we present factor models to test for ability differentiation. Ability differentiation predicts that the size of IQ subtest correlations decreases as a function of the general intelligence factor. In the Schmid-Leiman decomposition of the second-order factor model, we model differentiation by introducing heteroscedastic residuals,…

Model-order reduction of lumped parameter systems via fractional calculus

NASA Astrophysics Data System (ADS)

Hollkamp, John P.; Sen, Mihir; Semperlotti, Fabio

2018-04-01

This study investigates the use of fractional order differential models to simulate the dynamic response of non-homogeneous discrete systems and to achieve efficient and accurate model order reduction. The traditional integer order approach to the simulation of non-homogeneous systems dictates the use of numerical solutions and often imposes stringent compromises between accuracy and computational performance. Fractional calculus provides an alternative approach where complex dynamical systems can be modeled with compact fractional equations that not only can still guarantee analytical solutions, but can also enable high levels of order reduction without compromising on accuracy. Different approaches are explored in order to transform the integer order model into a reduced order fractional model able to match the dynamic response of the initial system. Analytical and numerical results show that, under certain conditions, an exact match is possible and the resulting fractional differential models have both a complex and frequency-dependent order of the differential operator. The implications of this type of approach for both model order reduction and model synthesis are discussed.

Modeling decay rates of dead wood in a neotropical forest.

PubMed

Hérault, Bruno; Beauchêne, Jacques; Muller, Félix; Wagner, Fabien; Baraloto, Christopher; Blanc, Lilian; Martin, Jean-Michel

2010-09-01

Variation of dead wood decay rates among tropical trees remains one source of uncertainty in global models of the carbon cycle. Taking advantage of a broad forest plot network surveyed for tree mortality over a 23-year period, we measured the remaining fraction of boles from 367 dead trees from 26 neotropical species widely varying in wood density (0.23-1.24 g cm(-3)) and tree circumference at death time (31.5-272.0 cm). We modeled decay rates within a Bayesian framework assuming a first order differential equation to model the decomposition process and tested for the effects of forest management (selective logging vs. unexploited), of mode of death (standing vs. downed) and of topographical levels (bottomlands vs. hillsides vs. hilltops) on wood decay rates. The general decay model predicts the observed remaining fraction of dead wood (R2 = 60%) with only two biological predictors: tree circumference at death time and wood specific density. Neither selective logging nor local topography had a differential effect on wood decay rates. Including the mode of death into the model revealed that standing dead trees decomposed faster than downed dead trees, but the gain of model accuracy remains rather marginal. Overall, these results suggest that the release of carbon from tropical dead trees to the atmosphere can be simply estimated using tree circumference at death time and wood density.

Linear models of coregionalization for multivariate lattice data: Order-dependent and order-free cMCARs.

PubMed

MacNab, Ying C

2016-08-01

This paper concerns with multivariate conditional autoregressive models defined by linear combination of independent or correlated underlying spatial processes. Known as linear models of coregionalization, the method offers a systematic and unified approach for formulating multivariate extensions to a broad range of univariate conditional autoregressive models. The resulting multivariate spatial models represent classes of coregionalized multivariate conditional autoregressive models that enable flexible modelling of multivariate spatial interactions, yielding coregionalization models with symmetric or asymmetric cross-covariances of different spatial variation and smoothness. In the context of multivariate disease mapping, for example, they facilitate borrowing strength both over space and cross variables, allowing for more flexible multivariate spatial smoothing. Specifically, we present a broadened coregionalization framework to include order-dependent, order-free, and order-robust multivariate models; a new class of order-free coregionalized multivariate conditional autoregressives is introduced. We tackle computational challenges and present solutions that are integral for Bayesian analysis of these models. We also discuss two ways of computing deviance information criterion for comparison among competing hierarchical models with or without unidentifiable prior parameters. The models and related methodology are developed in the broad context of modelling multivariate data on spatial lattice and illustrated in the context of multivariate disease mapping. The coregionalization framework and related methods also present a general approach for building spatially structured cross-covariance functions for multivariate geostatistics. © The Author(s) 2016.

GROUND WATER ISSUE - CALCULATION AND USE OF FIRST-ORDER RATE CONSTANTS FOR MONITORED NATURAL ATTENUATION STUDIES

EPA Science Inventory

This issue paper explains when and how to apply first-order attenuation rate constant calculations in monitored natural attenuation (MNA) studies. First-order attenuation rate constant calculations can be an important tool for evaluating natural attenuation processes at ground-wa...

Spiking and bursting patterns of fractional-order Izhikevich model

NASA Astrophysics Data System (ADS)

Teka, Wondimu W.; Upadhyay, Ranjit Kumar; Mondal, Argha

2018-03-01

Bursting and spiking oscillations play major roles in processing and transmitting information in the brain through cortical neurons that respond differently to the same signal. These oscillations display complex dynamics that might be produced by using neuronal models and varying many model parameters. Recent studies have shown that models with fractional order can produce several types of history-dependent neuronal activities without the adjustment of several parameters. We studied the fractional-order Izhikevich model and analyzed different kinds of oscillations that emerge from the fractional dynamics. The model produces a wide range of neuronal spike responses, including regular spiking, fast spiking, intrinsic bursting, mixed mode oscillations, regular bursting and chattering, by adjusting only the fractional order. Both the active and silent phase of the burst increase when the fractional-order model further deviates from the classical model. For smaller fractional order, the model produces memory dependent spiking activity after the pulse signal turned off. This special spiking activity and other properties of the fractional-order model are caused by the memory trace that emerges from the fractional-order dynamics and integrates all the past activities of the neuron. On the network level, the response of the neuronal network shifts from random to scale-free spiking. Our results suggest that the complex dynamics of spiking and bursting can be the result of the long-term dependence and interaction of intracellular and extracellular ionic currents.

Relationship between soil erodibility and modeled infiltration rate in different soils

NASA Astrophysics Data System (ADS)

Wang, Guoqiang; Fang, Qingqing; Wu, Binbin; Yang, Huicai; Xu, Zongxue

2015-09-01

The relationship between soil erodibility, which is hard to measure, and modeled infiltration rate were rarely researched. Here, the soil erodibility factors (K and Ke in the USLE, Ki and K1 in the WEPP) were calculated and the infiltration rates were modeled based on the designed laboratory simulation experiments and proposed infiltration model, in order to build their relationship. The impacts of compost amendment on the soil erosion characteristics and relationship were also studied. Two contrasting agricultural soils (bare and cultivated fluvo-aquic soils) were used, and different poultry compost contents (control, low and high) were applied to both soils. The results indicated that the runoff rate, sediment yield rate and soil erodibility of the bare soil treatments were generally higher than those of the corresponding cultivated soil treatments. The application of composts generally decreased sediment yield and soil erodibility but did not always decrease runoff. The comparison of measured and modeled infiltration rates indicated that the model represented the infiltration processes well with an N-S coefficient of 0.84 for overall treatments. Significant negative logarithmic correlations have been found between final infiltration rate (FIR) and the four soil erodibility factors, and the relationship between USLE-K and FIR demonstrated the best correlation. The application of poultry composts would not influence the logarithmic relationship between FIR and soil erodibility. Our study provided a useful tool to estimate soil erodibility.

A New Global Geodetic Strain Rate Model

NASA Astrophysics Data System (ADS)

Kreemer, C.; Blewitt, G.; Klein, E. C.; Shen, Z.; Wang, M.; Estey, L.; Wier, S.

2013-12-01

As part of the Global Earthquake Model (GEM) effort to improve global seismic hazard models, we present a new global geodetic strain rate model. This model (GSRM v. 2) is a vast improvement on the previous model from 2004 (v. 1.2). The model is still based on a finite-element type approach and has deforming cells in between the assumed rigid plates. The new model contains ~144,700 cells of 0.25° by 0.2° dimension. We redefined the geometries of the deforming zones based on the definitions of Bird (2003) and Chamot-Rooke and Rabaute (2006). We made some adjustments to the grid geometry at places where seismicity and/or GPS velocities suggested either the presence of deforming areas or a rigid block where those previous studies did not. GSRM v.2 includes 50 plates and blocks, including many not considered by Bird (2003). The new GSRM model is based on over 20,700 horizontal geodetic velocities at over 17,000 unique locations. The GPS velocity field consists of a 1) Over 6500 velocities derived by the University of Nevada, Reno, for CGPS stations for which >2.5 years of RINEX data are available until April 2013, 2) ~1200 velocities for China from a new analysis of all data from the Crustal Movement Network of China (CMONOC), and 3) about 13,000 velocities from 212 studies published in the literature or made otherwise available to us. Velocities from all studies were combined into the same reference frame by a 6-parameter transformation using velocities at collocated stations. We model co-seismic jumps while estimating velocities, ignore periods of post-seismic deformation, and exclude time-series that reflect magmatic and anthropogenic activity. GPS velocities were used to estimate angular velocities for 36 of the 50 rigid plates and blocks (the rest being taken from the literature), and these were used as boundary conditions in the strain rate calculations. For the strain rate calculations we used the method of Haines and Holt. In order to fit the data equally well

Reduced-Order Structure-Preserving Model for Parallel-Connected Three-Phase Grid-Tied Inverters: Preprint

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

Johnson, Brian B; Purba, Victor; Jafarpour, Saber

Given that next-generation infrastructures will contain large numbers of grid-connected inverters and these interfaces will be satisfying a growing fraction of system load, it is imperative to analyze the impacts of power electronics on such systems. However, since each inverter model has a relatively large number of dynamic states, it would be impractical to execute complex system models where the full dynamics of each inverter are retained. To address this challenge, we derive a reduced-order structure-preserving model for parallel-connected grid-tied three-phase inverters. Here, each inverter in the system is assumed to have a full-bridge topology, LCL filter at the pointmore » of common coupling, and the control architecture for each inverter includes a current controller, a power controller, and a phase-locked loop for grid synchronization. We outline a structure-preserving reduced-order inverter model for the setting where the parallel inverters are each designed such that the filter components and controller gains scale linearly with the power rating. By structure preserving, we mean that the reduced-order three-phase inverter model is also composed of an LCL filter, a power controller, current controller, and PLL. That is, we show that the system of parallel inverters can be modeled exactly as one aggregated inverter unit and this equivalent model has the same number of dynamical states as an individual inverter in the paralleled system. Numerical simulations validate the reduced-order models.« less

End-to-end Coronagraphic Modeling Including a Low-order Wavefront Sensor

NASA Technical Reports Server (NTRS)

Krist, John E.; Trauger, John T.; Unwin, Stephen C.; Traub, Wesley A.

2012-01-01

To evaluate space-based coronagraphic techniques, end-to-end modeling is necessary to simulate realistic fields containing speckles caused by wavefront errors. Real systems will suffer from pointing errors and thermal and motioninduced mechanical stresses that introduce time-variable wavefront aberrations that can reduce the field contrast. A loworder wavefront sensor (LOWFS) is needed to measure these changes at a sufficiently high rate to maintain the contrast level during observations. We implement here a LOWFS and corresponding low-order wavefront control subsystem (LOWFCS) in end-to-end models of a space-based coronagraph. Our goal is to be able to accurately duplicate the effect of the LOWFS+LOWFCS without explicitly evaluating the end-to-end model at numerous time steps.

Reduced-Order Modeling: New Approaches for Computational Physics

NASA Technical Reports Server (NTRS)

Beran, Philip S.; Silva, Walter A.

2001-01-01

In this paper, we review the development of new reduced-order modeling techniques and discuss their applicability to various problems in computational physics. Emphasis is given to methods ba'sed on Volterra series representations and the proper orthogonal decomposition. Results are reported for different nonlinear systems to provide clear examples of the construction and use of reduced-order models, particularly in the multi-disciplinary field of computational aeroelasticity. Unsteady aerodynamic and aeroelastic behaviors of two- dimensional and three-dimensional geometries are described. Large increases in computational efficiency are obtained through the use of reduced-order models, thereby justifying the initial computational expense of constructing these models and inotivatim,- their use for multi-disciplinary design analysis.

Reduced-Order Biogeochemical Flux Model for High-Resolution Multi-Scale Biophysical Simulations

NASA Astrophysics Data System (ADS)

Smith, Katherine; Hamlington, Peter; Pinardi, Nadia; Zavatarelli, Marco

2017-04-01

Biogeochemical tracers and their interactions with upper ocean physical processes such as submesoscale circulations and small-scale turbulence are critical for understanding the role of the ocean in the global carbon cycle. These interactions can cause small-scale spatial and temporal heterogeneity in tracer distributions that can, in turn, greatly affect carbon exchange rates between the atmosphere and interior ocean. For this reason, it is important to take into account small-scale biophysical interactions when modeling the global carbon cycle. However, explicitly resolving these interactions in an earth system model (ESM) is currently infeasible due to the enormous associated computational cost. As a result, understanding and subsequently parameterizing how these small-scale heterogeneous distributions develop and how they relate to larger resolved scales is critical for obtaining improved predictions of carbon exchange rates in ESMs. In order to address this need, we have developed the reduced-order, 17 state variable Biogeochemical Flux Model (BFM-17) that follows the chemical functional group approach, which allows for non-Redfield stoichiometric ratios and the exchange of matter through units of carbon, nitrate, and phosphate. This model captures the behavior of open-ocean biogeochemical systems without substantially increasing computational cost, thus allowing the model to be combined with computationally-intensive, fully three-dimensional, non-hydrostatic large eddy simulations (LES). In this talk, we couple BFM-17 with the Princeton Ocean Model and show good agreement between predicted monthly-averaged results and Bermuda testbed area field data (including the Bermuda-Atlantic Time-series Study and Bermuda Testbed Mooring). Through these tests, we demonstrate the capability of BFM-17 to accurately model open-ocean biochemistry. Additionally, we discuss the use of BFM-17 within a multi-scale LES framework and outline how this will further our understanding

Modeling Randomness in Judging Rating Scales with a Random-Effects Rating Scale Model

ERIC Educational Resources Information Center

Wang, Wen-Chung; Wilson, Mark; Shih, Ching-Lin

2006-01-01

This study presents the random-effects rating scale model (RE-RSM) which takes into account randomness in the thresholds over persons by treating them as random-effects and adding a random variable for each threshold in the rating scale model (RSM) (Andrich, 1978). The RE-RSM turns out to be a special case of the multidimensional random…

Modelling of Dynamic Rock Fracture Process with a Rate-Dependent Combined Continuum Damage-Embedded Discontinuity Model Incorporating Microstructure

NASA Astrophysics Data System (ADS)

Saksala, Timo

2016-10-01

This paper deals with numerical modelling of rock fracture under dynamic loading. For this end, a combined continuum damage-embedded discontinuity model is applied in finite element modelling of crack propagation in rock. In this model, the strong loading rate sensitivity of rock is captured by the rate-dependent continuum scalar damage model that controls the pre-peak nonlinear hardening part of rock behaviour. The post-peak exponential softening part of the rock behaviour is governed by the embedded displacement discontinuity model describing the mode I, mode II and mixed mode fracture of rock. Rock heterogeneity is incorporated in the present approach by random description of the rock mineral texture based on the Voronoi tessellation. The model performance is demonstrated in numerical examples where the uniaxial tension and compression tests on rock are simulated. Finally, the dynamic three-point bending test of a semicircular disc is simulated in order to show that the model correctly predicts the strain rate-dependent tensile strengths as well as the failure modes of rock in this test. Special emphasis is laid on modelling the loading rate sensitivity of tensile strength of Laurentian granite.

Ordered rate constitutive theories for thermoviscoelastic solids with memory in Lagrangian description using Gibbs potential

NASA Astrophysics Data System (ADS)

Surana, K. S.; Reddy, J. N.; Nunez, Daniel

2015-11-01

This paper presents ordered rate constitutive theories of orders m and n, i.e., ( m, n) for finite deformation of homogeneous, isotropic, compressible and incompressible thermoviscoelastic solids with memory in Lagrangian description using entropy inequality in Gibbs potential Ψ as an alternate approach of deriving constitutive theories using entropy inequality in terms of Helmholtz free energy density Φ. Second Piola-Kirchhoff stress σ [0] and Green's strain tensor ɛ [0] are used as conjugate pair. We consider Ψ, heat vector q, entropy density η and rates of upto orders m and n of σ [0] and ɛ [0], i.e., σ [ i]; i = 0, 1, . . . , m and ɛ [ j]; j = 0, 1, . . . , n. We choose Ψ, ɛ [ n], q and η as dependent variables in the constitutive theories with ɛ [ j]; j = 0, 1, . . . , n - 1, σ [ i]; i = 0, 1, . . . , m, temperature gradient g and temperature θ as their argument tensors. Rationale for this choice is explained in the paper. Entropy inequality, decomposition of σ [0] into equilibrium and deviatoric stresses, the conditions resulting from entropy inequality and the theory of generators and invariants are used in the derivations of ordered rate constitutive theories of orders m and n in stress and strain tensors. Constitutive theories for the heat vector q (of up to orders m and n - 1) that are consistent (in terms of the argument tensors) with the constitutive theories for ɛ [ n] (of up to orders m and n) are also derived. Many simplified forms of the rate theories of orders ( m, n) are presented. Material coefficients are derived by considering Taylor series expansions of the coefficients in the linear combinations representing ɛ [ n] and q using the combined generators of the argument tensors about a known configuration {{\\underline{\\varOmega}}} in the combined invariants of the argument tensors and temperature. It is shown that the rate constitutive theories of order one ( m = 1, n = 1) when further simplified result in constitutive

Dynamical models of happiness with fractional order

NASA Astrophysics Data System (ADS)

Song, Lei; Xu, Shiyun; Yang, Jianying

2010-03-01

This present study focuses on a dynamical model of happiness described through fractional-order differential equations. By categorizing people of different personality and different impact factor of memory (IFM) with different set of model parameters, it is demonstrated via numerical simulations that such fractional-order models could exhibit various behaviors with and without external circumstance. Moreover, control and synchronization problems of this model are discussed, which correspond to the control of emotion as well as emotion synchronization in real life. This study is an endeavor to combine the psychological knowledge with control problems and system theories, and some implications for psychotherapy as well as hints of a personal approach to life are both proposed.

Adaptive tracking for complex systems using reduced-order models

NASA Technical Reports Server (NTRS)

Carnigan, Craig R.

1990-01-01

Reduced-order models are considered in the context of parameter adaptive controllers for tracking workspace trajectories. A dual-arm manipulation task is used to illustrate the methodology and provide simulation results. A parameter adaptive controller is designed to track a payload trajectory using a four-parameter model instead of the full-order, nine-parameter model. Several simulations with different payload-to-arm mass ratios are used to illustrate the capabilities of the reduced-order model in tracking the desired trajectory.

Quantifying predictability variations in a low-order ocean-atmosphere model - A dynamical systems approach

NASA Technical Reports Server (NTRS)

Nese, Jon M.; Dutton, John A.

1993-01-01

The predictability of the weather and climatic states of a low-order moist general circulation model is quantified using a dynamic systems approach, and the effect of incorporating a simple oceanic circulation on predictability is evaluated. The predictability and the structure of the model attractors are compared using Liapunov exponents, local divergence rates, and the correlation and Liapunov dimensions. It was found that the activation of oceanic circulation increases the average error doubling time of the atmosphere and the coupled ocean-atmosphere system by 10 percent and decreases the variance of the largest local divergence rate by 20 percent. When an oceanic circulation develops, the average predictability of annually averaged states is improved by 25 percent and the variance of the largest local divergence rate decreases by 25 percent.

Terminology modeling for an enterprise laboratory orders catalog.

PubMed

Zhou, Li; Goldberg, Howard; Pabbathi, Deepika; Wright, Adam; Goldman, Debora S; Van Putten, Cheryl; Barley, Amanda; Rocha, Roberto A

2009-11-14

Laboratory test orders are used in a variety of clinical information systems at Partners HealthCare. At present, each site at Partners manages its own set of laboratory orders with locally defined codes. Our current plan is to implement an enterprise catalog, where laboratory test orders are mapped to reference terminologies and codes from different sites are mapped to each other. This paper describes the terminology modeling effort that preceded the implementation of the enterprise laboratory orders catalog. In particular, we present our experience in adapting HL7's "Common Terminology Services 2 - Upper Level Class Model" as a terminology metamodel for guiding the development of fully specified laboratory orders and related services.

Rate-independent dissipation in phase-field modelling of displacive transformations

NASA Astrophysics Data System (ADS)

Tůma, K.; Stupkiewicz, S.; Petryk, H.

2018-05-01

In this paper, rate-independent dissipation is introduced into the phase-field framework for modelling of displacive transformations, such as martensitic phase transformation and twinning. The finite-strain phase-field model developed recently by the present authors is here extended beyond the limitations of purely viscous dissipation. The variational formulation, in which the evolution problem is formulated as a constrained minimization problem for a global rate-potential, is enhanced by including a mixed-type dissipation potential that combines viscous and rate-independent contributions. Effective computational treatment of the resulting incremental problem of non-smooth optimization is developed by employing the augmented Lagrangian method. It is demonstrated that a single Lagrange multiplier field suffices to handle the dissipation potential vertex and simultaneously to enforce physical constraints on the order parameter. In this way, the initially non-smooth problem of evolution is converted into a smooth stationarity problem. The model is implemented in a finite-element code and applied to solve two- and three-dimensional boundary value problems representative for shape memory alloys.

Model Order Reduction of Aeroservoelastic Model of Flexible Aircraft

NASA Technical Reports Server (NTRS)

Wang, Yi; Song, Hongjun; Pant, Kapil; Brenner, Martin J.; Suh, Peter

2016-01-01

This paper presents a holistic model order reduction (MOR) methodology and framework that integrates key technological elements of sequential model reduction, consistent model representation, and model interpolation for constructing high-quality linear parameter-varying (LPV) aeroservoelastic (ASE) reduced order models (ROMs) of flexible aircraft. The sequential MOR encapsulates a suite of reduction techniques, such as truncation and residualization, modal reduction, and balanced realization and truncation to achieve optimal ROMs at grid points across the flight envelope. The consistence in state representation among local ROMs is obtained by the novel method of common subspace reprojection. Model interpolation is then exploited to stitch ROMs at grid points to build a global LPV ASE ROM feasible to arbitrary flight condition. The MOR method is applied to the X-56A MUTT vehicle with flexible wing being tested at NASA/AFRC for flutter suppression and gust load alleviation. Our studies demonstrated that relative to the fullorder model, our X-56A ROM can accurately and reliably capture vehicles dynamics at various flight conditions in the target frequency regime while the number of states in ROM can be reduced by 10X (from 180 to 19), and hence, holds great promise for robust ASE controller synthesis and novel vehicle design.

Adaptive tracking for complex systems using reduced-order models

NASA Technical Reports Server (NTRS)

Carignan, Craig R.

1990-01-01

Reduced-order models are considered in the context of parameter adaptive controllers for tracking workspace trajectories. A dual-arm manipulation task is used to illustrate the methodology and provide simulation results. A parameter adaptive controller is designed to track the desired position trajectory of a payload using a four-parameter model instead of a full-order, nine-parameter model. Several simulations with different payload-to-arm mass ratios are used to illustrate the capabilities of the reduced-order model in tracking the desired trajectory.

Inverse modelling of radionuclide release rates using gamma dose rate observations

NASA Astrophysics Data System (ADS)

Hamburger, Thomas; Evangeliou, Nikolaos; Stohl, Andreas; von Haustein, Christoph; Thummerer, Severin; Wallner, Christian

2015-04-01

Severe accidents in nuclear power plants such as the historical accident in Chernobyl 1986 or the more recent disaster in the Fukushima Dai-ichi nuclear power plant in 2011 have drastic impacts on the population and environment. Observations and dispersion modelling of the released radionuclides help to assess the regional impact of such nuclear accidents. Modelling the increase of regional radionuclide activity concentrations, which results from nuclear accidents, underlies a multiplicity of uncertainties. One of the most significant uncertainties is the estimation of the source term. That is, the time dependent quantification of the released spectrum of radionuclides during the course of the nuclear accident. The quantification of the source term may either remain uncertain (e.g. Chernobyl, Devell et al., 1995) or rely on estimates given by the operators of the nuclear power plant. Precise measurements are mostly missing due to practical limitations during the accident. The release rates of radionuclides at the accident site can be estimated using inverse modelling (Davoine and Bocquet, 2007). The accuracy of the method depends amongst others on the availability, reliability and the resolution in time and space of the used observations. Radionuclide activity concentrations are observed on a relatively sparse grid and the temporal resolution of available data may be low within the order of hours or a day. Gamma dose rates, on the other hand, are observed routinely on a much denser grid and higher temporal resolution and provide therefore a wider basis for inverse modelling (Saunier et al., 2013). We present a new inversion approach, which combines an atmospheric dispersion model and observations of radionuclide activity concentrations and gamma dose rates to obtain the source term of radionuclides. We use the Lagrangian particle dispersion model FLEXPART (Stohl et al., 1998; Stohl et al., 2005) to model the atmospheric transport of the released radionuclides. The

Local order parameters for use in driving homogeneous ice nucleation with all-atom models of water

NASA Astrophysics Data System (ADS)

Reinhardt, Aleks; Doye, Jonathan P. K.; Noya, Eva G.; Vega, Carlos

2012-11-01

We present a local order parameter based on the standard Steinhardt-Ten Wolde approach that is capable both of tracking and of driving homogeneous ice nucleation in simulations of all-atom models of water. We demonstrate that it is capable of forcing the growth of ice nuclei in supercooled liquid water simulated using the TIP4P/2005 model using over-biassed umbrella sampling Monte Carlo simulations. However, even with such an order parameter, the dynamics of ice growth in deeply supercooled liquid water in all-atom models of water are shown to be very slow, and so the computation of free energy landscapes and nucleation rates remains extremely challenging.

The 4th order GISS model of the global atmosphere

NASA Technical Reports Server (NTRS)

Kalnay-Rivas, E.; Bayliss, A.; Storch, J.

1977-01-01

The new GISS 4th order model of the global atmosphere is described. It is based on 4th order quadratically conservative differences with the periodic application of a 16th order filter on the sea level pressure and potential temperature equations, a combination which is approximately enstrophy conserving. Several short range forecasts indicate a significant improvement over 2nd order forecasts with the same resolution (approximately 400 km). However the 4th order forecasts are somewhat inferior to 2nd order forecasts with double resolution. This is probably due to the presence of short waves in the range between 1000 km and 2000 km, which are computed more accurately by the 2nd order high resolution model. An operation count of the schemes indicates that with similar code optimization, the 4th order model will require approximately the same amount of computer time as the 2nd order model with the same resolution. It is estimated that the 4th order model with a grid size of 200 km provides enough accuracy to make horizontal truncation errors negligible over a period of a week for all synoptic scales (waves longer than 1000 km).

Constrained reduced-order models based on proper orthogonal decomposition

DOE PAGES

Reddy, Sohail R.; Freno, Brian Andrew; Cizmas, Paul G. A.; ...

2017-04-09

A novel approach is presented to constrain reduced-order models (ROM) based on proper orthogonal decomposition (POD). The Karush–Kuhn–Tucker (KKT) conditions were applied to the traditional reduced-order model to constrain the solution to user-defined bounds. The constrained reduced-order model (C-ROM) was applied and validated against the analytical solution to the first-order wave equation. C-ROM was also applied to the analysis of fluidized beds. Lastly, it was shown that the ROM and C-ROM produced accurate results and that C-ROM was less sensitive to error propagation through time than the ROM.

An Investigation of the Factor Structure and Convergent and Discriminant Validity of the Five-Factor Model Rating Form

ERIC Educational Resources Information Center

Samuel, Douglas B.; Mullins-Sweatt, Stephanie N.; Widiger, Thomas A.

2013-01-01

The Five-Factor Model Rating Form (FFMRF) is a one-page measure designed to provide an efficient assessment of the higher order domains of the Five Factor Model (FFM) as well as the more specific, lower order facets proposed by McCrae and Costa. Although previous research has suggested that the FFMRF's assessment of the lower order facets converge…

Crystal Thermoelasticity at Extreme Loading Rates and Pressures: Analysis of Higher-Order Energy Potentials

DTIC Science & Technology

2015-07-01

ARL-RP-0526 ● JULY 2015 US Army Research Laboratory Crystal Thermoelasticity at Extreme Loading Rates and Pressures : Analysis of...ARL-RP-0526 ● JULY 2015 US Army Research Laboratory Crystal Thermoelasticity at Extreme Loading Rates and Pressures : Analysis of...2015 4. TITLE AND SUBTITLE Crystal Thermoelasticity at Extreme Loading Rates and Pressures : Analysis of Higher-Order Energy Potentials 5a. CONTRACT

Modelling Limit Order Execution Times from Market Data

NASA Astrophysics Data System (ADS)

Kim, Adlar; Farmer, Doyne; Lo, Andrew

2007-03-01

Although the term ``liquidity'' is widely used in finance literatures, its meaning is very loosely defined and there is no quantitative measure for it. Generally, ``liquidity'' means an ability to quickly trade stocks without causing a significant impact on the stock price. From this definition, we identified two facets of liquidity -- 1.execution time of limit orders, and 2.price impact of market orders. The limit order is an order to transact a prespecified number of shares at a prespecified price, which will not cause an immediate execution. On the other hand, the market order is an order to transact a prespecified number of shares at a market price, which will cause an immediate execution, but are subject to price impact. Therefore, when the stock is liquid, market participants will experience quick limit order executions and small market order impacts. As a first step to understand market liquidity, we studied the facet of liquidity related to limit order executions -- execution times. In this talk, we propose a novel approach of modeling limit order execution times and show how they are affected by size and price of orders. We used q-Weibull distribution, which is a generalized form of Weibull distribution that can control the fatness of tail to model limit order execution times.

Strain Rate Dependant Material Model for Orthotropic Metals

NASA Astrophysics Data System (ADS)

Vignjevic, Rade

2016-08-01

In manufacturing processes anisotropic metals are often exposed to the loading with high strain rates in the range from 102 s-1 to 106 s-1 (e.g. stamping, cold spraying and explosive forming). These types of loading often involve generation and propagation of shock waves within the material. The material behaviour under such a complex loading needs to be accurately modelled, in order to optimise the manufacturing process and achieve appropriate properties of the manufactured component. The presented research is related to development and validation of a thermodynamically consistent physically based constitutive model for metals under high rate loading. The model is capable of modelling damage, failure and formation and propagation of shock waves in anisotropic metals. The model has two main parts: the strength part which defines the material response to shear deformation and an equation of state (EOS) which defines the material response to isotropic volumetric deformation [1]. The constitutive model was implemented into the transient nonlinear finite element code DYNA3D [2] and our in house SPH code. Limited model validation was performed by simulating a number of high velocity material characterisation and validation impact tests. The new damage model was developed in the framework of configurational continuum mechanics and irreversible thermodynamics with internal state variables. The use of the multiplicative decomposition of deformation gradient makes the model applicable to arbitrary plastic and damage deformations. To account for the physical mechanisms of failure, the concept of thermally activated damage initially proposed by Tuller and Bucher [3], Klepaczko [4] was adopted as the basis for the new damage evolution model. This makes the proposed damage/failure model compatible with the Mechanical Threshold Strength (MTS) model Follansbee and Kocks [5], 1988; Chen and Gray [6] which was used to control evolution of flow stress during plastic deformation. In

Improved first-order uncertainty method for water-quality modeling

USGS Publications Warehouse

Melching, C.S.; Anmangandla, S.

1992-01-01

Uncertainties are unavoidable in water-quality modeling and subsequent management decisions. Monte Carlo simulation and first-order uncertainty analysis (involving linearization at central values of the uncertain variables) have been frequently used to estimate probability distributions for water-quality model output due to their simplicity. Each method has its drawbacks: Monte Carlo simulation's is mainly computational time; and first-order analysis are mainly questions of accuracy and representativeness, especially for nonlinear systems and extreme conditions. An improved (advanced) first-order method is presented, where the linearization point varies to match the output level whose exceedance probability is sought. The advanced first-order method is tested on the Streeter-Phelps equation to estimate the probability distribution of critical dissolved-oxygen deficit and critical dissolved oxygen using two hypothetical examples from the literature. The advanced first-order method provides a close approximation of the exceedance probability for the Streeter-Phelps model output estimated by Monte Carlo simulation using less computer time - by two orders of magnitude - regardless of the probability distributions assumed for the uncertain model parameters.

Inverse modelling of radionuclide release rates using gamma dose rate observations

NASA Astrophysics Data System (ADS)

Hamburger, Thomas; Stohl, Andreas; von Haustein, Christoph; Thummerer, Severin; Wallner, Christian

2014-05-01

relatively sparse grid and the temporal resolution of available data may be low within the order of hours or a day. Gamma dose rates on the other hand are observed routinely on a much denser grid and higher temporal resolution. Gamma dose rate measurements contain no explicit information on the observed spectrum of radionuclides and have to be interpreted carefully. Nevertheless, they provide valuable information for the inverse evaluation of the source term due to their availability (Saunier et al., 2013). We present a new inversion approach combining an atmospheric dispersion model and observations of radionuclide activity concentrations and gamma dose rates to obtain the source term of radionuclides. We use the Lagrangian particle dispersion model FLEXPART (Stohl et al., 1998; Stohl et al., 2005) to model the atmospheric transport of the released radionuclides. The gamma dose rates are calculated from the modelled activity concentrations. The inversion method uses a Bayesian formulation considering uncertainties for the a priori source term and the observations (Eckhardt et al., 2008). The a priori information on the source term is a first guess. The gamma dose rate observations will be used with inverse modelling to improve this first guess and to retrieve a reliable source term. The details of this method will be presented at the conference. This work is funded by the Bundesamt für Strahlenschutz BfS, Forschungsvorhaben 3612S60026. References Davoine, X. and Bocquet, M., Atmos. Chem. Phys., 7, 1549-1564, 2007. Devell, L., et al., OCDE/GD(96)12, 1995. Eckhardt, S., et al., Atmos. Chem. Phys., 8, 3881-3897, 2008. Saunier, O., et al., Atmos. Chem. Phys., 13, 11403-11421, 2013. Stohl, A., et al., Atmos. Environ., 32, 4245-4264, 1998. Stohl, A., et al., Atmos. Chem. Phys., 5, 2461-2474, 2005. Stohl, A., et al., Atmos. Chem. Phys., 12, 2313-2343, 2012.

Mean Abnormal Result Rate: Proof of Concept of a New Metric for Benchmarking Selectivity in Laboratory Test Ordering.

PubMed

Naugler, Christopher T; Guo, Maggie

2016-04-01

There is a need to develop and validate new metrics to access the appropriateness of laboratory test requests. The mean abnormal result rate (MARR) is a proposed measure of ordering selectivity, the premise being that higher mean abnormal rates represent more selective test ordering. As a validation of this metric, we compared the abnormal rate of lab tests with the number of tests ordered on the same requisition. We hypothesized that requisitions with larger numbers of requested tests represent less selective test ordering and therefore would have a lower overall abnormal rate. We examined 3,864,083 tests ordered on 451,895 requisitions and found that the MARR decreased from about 25% if one test was ordered to about 7% if nine or more tests were ordered, consistent with less selectivity when more tests were ordered. We then examined the MARR for community-based testing for 1,340 family physicians and found both a wide variation in MARR as well as an inverse relationship between the total tests ordered per year per physician and the physician-specific MARR. The proposed metric represents a new utilization metric for benchmarking relative selectivity of test orders among physicians. © American Society for Clinical Pathology, 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Oxygen consumption rates by different oenological tannins in a model wine solution.

PubMed

Pascual, Olga; Vignault, Adeline; Gombau, Jordi; Navarro, Maria; Gómez-Alonso, Sergio; García-Romero, Esteban; Canals, Joan Miquel; Hermosín-Gutíerrez, Isidro; Teissedre, Pierre-Louis; Zamora, Fernando

2017-11-01

The kinetics of oxygen consumption by different oenological tannins were measured in a model wine solution using the non-invasive method based on luminiscence. The results indicate that the oxygen consumption rate follows second-order kinetics depending on tannin and oxygen concentrations. They also confirm that the oxygen consumption rate is influenced by temperature in accordance with Arrhenius law. The indications are that ellagitannins are the fastest oxygen consumers of the different oenological tannins, followed in decreasing order by quebracho tannins, skin tannins, seed tannins and finally gallotannins. This methodology can therefore be proposed as an index for determining the effectiveness of different commercial tannins in protecting wines against oxidation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Beyond Rating Curves: Time Series Models for in-Stream Turbidity Prediction

NASA Astrophysics Data System (ADS)

Wang, L.; Mukundan, R.; Zion, M.; Pierson, D. C.

2012-12-01

The New York City Department of Environmental Protection (DEP) manages New York City's water supply, which is comprised of over 20 reservoirs and supplies over 1 billion gallons of water per day to more than 9 million customers. DEP's "West of Hudson" reservoirs located in the Catskill Mountains are unfiltered per a renewable filtration avoidance determination granted by the EPA. While water quality is usually pristine, high volume storm events occasionally cause the reservoirs to become highly turbid. A logical strategy for turbidity control is to temporarily remove the turbid reservoirs from service. While effective in limiting delivery of turbid water and reducing the need for in-reservoir alum flocculation, this strategy runs the risk of negatively impacting water supply reliability. Thus, it is advantageous for DEP to understand how long a particular turbidity event will affect their system. In order to understand the duration, intensity and total load of a turbidity event, predictions of future in-stream turbidity values are important. Traditionally, turbidity predictions have been carried out by applying streamflow observations/forecasts to a flow-turbidity rating curve. However, predictions from rating curves are often inaccurate due to inter- and intra-event variability in flow-turbidity relationships. Predictions can be improved by applying an autoregressive moving average (ARMA) time series model in combination with a traditional rating curve. Since 2003, DEP and the Upstate Freshwater Institute have compiled a relatively consistent set of 15-minute turbidity observations at various locations on Esopus Creek above Ashokan Reservoir. Using daily averages of this data and streamflow observations at nearby USGS gauges, flow-turbidity rating curves were developed via linear regression. Time series analysis revealed that the linear regression residuals may be represented using an ARMA(1,2) process. Based on this information, flow-turbidity regressions with

Third-Order Memristive Morris-Lecar Model of Barnacle Muscle Fiber

NASA Astrophysics Data System (ADS)

Rajamani, Vetriveeran; Sah, Maheshwar Pd.; Mannan, Zubaer Ibna; Kim, Hyongsuk; Chua, Leon

This paper presents a detailed analysis of various oscillatory behaviors observed in relation to the calcium and potassium ions in the third-order Morris-Lecar model of giant barnacle muscle fiber. Since, both the calcium and potassium ions exhibit all of the characteristics of memristor fingerprints, we claim that the time-varying calcium and potassium ions in the third-order Morris-Lecar model are actually time-invariant calcium and potassium memristors in the third-order memristive Morris-Lecar model. We confirmed the existence of a small unstable limit cycle oscillation in both the second-order and the third-order Morris-Lecar model by numerically calculating the basin of attraction of the asymptotically stable equilibrium point associated with two subcritical Hopf bifurcation points. We also describe a comprehensive analysis of the generation of oscillations in third-order memristive Morris-Lecar model via small-signal circuit analysis and a subcritical Hopf bifurcation phenomenon.

A Model-Based Approach for Visualizing the Dimensional Structure of Ordered Successive Categories Preference Data

ERIC Educational Resources Information Center

DeSarbo, Wayne S.; Park, Joonwook; Scott, Crystal J.

2008-01-01

A cyclical conditional maximum likelihood estimation procedure is developed for the multidimensional unfolding of two- or three-way dominance data (e.g., preference, choice, consideration) measured on ordered successive category rating scales. The technical description of the proposed model and estimation procedure are discussed, as well as the…

Estimating reaction rate coefficients within a travel-time modeling framework.

PubMed

Gong, R; Lu, C; Wu, W-M; Cheng, H; Gu, B; Watson, D; Jardine, P M; Brooks, S C; Criddle, C S; Kitanidis, P K; Luo, J

2011-01-01

A generalized, efficient, and practical approach based on the travel-time modeling framework is developed to estimate in situ reaction rate coefficients for groundwater remediation in heterogeneous aquifers. The required information for this approach can be obtained by conducting tracer tests with injection of a mixture of conservative and reactive tracers and measurements of both breakthrough curves (BTCs). The conservative BTC is used to infer the travel-time distribution from the injection point to the observation point. For advection-dominant reactive transport with well-mixed reactive species and a constant travel-time distribution, the reactive BTC is obtained by integrating the solutions to advective-reactive transport over the entire travel-time distribution, and then is used in optimization to determine the in situ reaction rate coefficients. By directly working on the conservative and reactive BTCs, this approach avoids costly aquifer characterization and improves the estimation for transport in heterogeneous aquifers which may not be sufficiently described by traditional mechanistic transport models with constant transport parameters. Simplified schemes are proposed for reactive transport with zero-, first-, nth-order, and Michaelis-Menten reactions. The proposed approach is validated by a reactive transport case in a two-dimensional synthetic heterogeneous aquifer and a field-scale bioremediation experiment conducted at Oak Ridge, Tennessee. The field application indicates that ethanol degradation for U(VI)-bioremediation is better approximated by zero-order reaction kinetics than first-order reaction kinetics. Copyright © 2010 The Author(s). Journal compilation © 2010 National Ground Water Association.

Estimating Reaction Rate Coefficients Within a Travel-Time Modeling Framework

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

Gong, R; Lu, C; Luo, Jian

A generalized, efficient, and practical approach based on the travel-time modeling framework is developed to estimate in situ reaction rate coefficients for groundwater remediation in heterogeneous aquifers. The required information for this approach can be obtained by conducting tracer tests with injection of a mixture of conservative and reactive tracers and measurements of both breakthrough curves (BTCs). The conservative BTC is used to infer the travel-time distribution from the injection point to the observation point. For advection-dominant reactive transport with well-mixed reactive species and a constant travel-time distribution, the reactive BTC is obtained by integrating the solutions to advective-reactive transportmore » over the entire travel-time distribution, and then is used in optimization to determine the in situ reaction rate coefficients. By directly working on the conservative and reactive BTCs, this approach avoids costly aquifer characterization and improves the estimation for transport in heterogeneous aquifers which may not be sufficiently described by traditional mechanistic transport models with constant transport parameters. Simplified schemes are proposed for reactive transport with zero-, first-, nth-order, and Michaelis-Menten reactions. The proposed approach is validated by a reactive transport case in a two-dimensional synthetic heterogeneous aquifer and a field-scale bioremediation experiment conducted at Oak Ridge, Tennessee. The field application indicates that ethanol degradation for U(VI)-bioremediation is better approximated by zero-order reaction kinetics than first-order reaction kinetics.« less

Demonstration of reduced-order urban scale building energy models

DOE PAGES

Heidarinejad, Mohammad; Mattise, Nicholas; Dahlhausen, Matthew; ...

2017-09-08

The aim of this study is to demonstrate a developed framework to rapidly create urban scale reduced-order building energy models using a systematic summary of the simplifications required for the representation of building exterior and thermal zones. These urban scale reduced-order models rely on the contribution of influential variables to the internal, external, and system thermal loads. OpenStudio Application Programming Interface (API) serves as a tool to automate the process of model creation and demonstrate the developed framework. The results of this study show that the accuracy of the developed reduced-order building energy models varies only up to 10% withmore » the selection of different thermal zones. In addition, to assess complexity of the developed reduced-order building energy models, this study develops a novel framework to quantify complexity of the building energy models. Consequently, this study empowers the building energy modelers to quantify their building energy model systematically in order to report the model complexity alongside the building energy model accuracy. An exhaustive analysis on four university campuses suggests that the urban neighborhood buildings lend themselves to simplified typical shapes. Specifically, building energy modelers can utilize the developed typical shapes to represent more than 80% of the U.S. buildings documented in the CBECS database. One main benefits of this developed framework is the opportunity for different models including airflow and solar radiation models to share the same exterior representation, allowing a unifying exchange data. Altogether, the results of this study have implications for a large-scale modeling of buildings in support of urban energy consumption analyses or assessment of a large number of alternative solutions in support of retrofit decision-making in the building industry.« less

Demonstration of reduced-order urban scale building energy models

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

Heidarinejad, Mohammad; Mattise, Nicholas; Dahlhausen, Matthew

The aim of this study is to demonstrate a developed framework to rapidly create urban scale reduced-order building energy models using a systematic summary of the simplifications required for the representation of building exterior and thermal zones. These urban scale reduced-order models rely on the contribution of influential variables to the internal, external, and system thermal loads. OpenStudio Application Programming Interface (API) serves as a tool to automate the process of model creation and demonstrate the developed framework. The results of this study show that the accuracy of the developed reduced-order building energy models varies only up to 10% withmore » the selection of different thermal zones. In addition, to assess complexity of the developed reduced-order building energy models, this study develops a novel framework to quantify complexity of the building energy models. Consequently, this study empowers the building energy modelers to quantify their building energy model systematically in order to report the model complexity alongside the building energy model accuracy. An exhaustive analysis on four university campuses suggests that the urban neighborhood buildings lend themselves to simplified typical shapes. Specifically, building energy modelers can utilize the developed typical shapes to represent more than 80% of the U.S. buildings documented in the CBECS database. One main benefits of this developed framework is the opportunity for different models including airflow and solar radiation models to share the same exterior representation, allowing a unifying exchange data. Altogether, the results of this study have implications for a large-scale modeling of buildings in support of urban energy consumption analyses or assessment of a large number of alternative solutions in support of retrofit decision-making in the building industry.« less

Pseudo-second order models for the adsorption of safranin onto activated carbon: comparison of linear and non-linear regression methods.

PubMed

Kumar, K Vasanth

2007-04-02

Kinetic experiments were carried out for the sorption of safranin onto activated carbon particles. The kinetic data were fitted to pseudo-second order model of Ho, Sobkowsk and Czerwinski, Blanchard et al. and Ritchie by linear and non-linear regression methods. Non-linear method was found to be a better way of obtaining the parameters involved in the second order rate kinetic expressions. Both linear and non-linear regression showed that the Sobkowsk and Czerwinski and Ritchie's pseudo-second order models were the same. Non-linear regression analysis showed that both Blanchard et al. and Ho have similar ideas on the pseudo-second order model but with different assumptions. The best fit of experimental data in Ho's pseudo-second order expression by linear and non-linear regression method showed that Ho pseudo-second order model was a better kinetic expression when compared to other pseudo-second order kinetic expressions.

Evaluation of Geometrically Nonlinear Reduced Order Models with Nonlinear Normal Modes

DOE PAGES

Kuether, Robert J.; Deaner, Brandon J.; Hollkamp, Joseph J.; ...

2015-09-15

Several reduced-order modeling strategies have been developed to create low-order models of geometrically nonlinear structures from detailed finite element models, allowing one to compute the dynamic response of the structure at a dramatically reduced cost. But, the parameters of these reduced-order models are estimated by applying a series of static loads to the finite element model, and the quality of the reduced-order model can be highly sensitive to the amplitudes of the static load cases used and to the type/number of modes used in the basis. Our paper proposes to combine reduced-order modeling and numerical continuation to estimate the nonlinearmore » normal modes of geometrically nonlinear finite element models. Not only does this make it possible to compute the nonlinear normal modes far more quickly than existing approaches, but the nonlinear normal modes are also shown to be an excellent metric by which the quality of the reduced-order model can be assessed. Hence, the second contribution of this work is to demonstrate how nonlinear normal modes can be used as a metric by which nonlinear reduced-order models can be compared. Moreover, various reduced-order models with hardening nonlinearities are compared for two different structures to demonstrate these concepts: a clamped–clamped beam model, and a more complicated finite element model of an exhaust panel cover.« less

75 FR 55292 - Amendment to Egg Research and Promotion Order and Regulations To Increase the Rate of Assessment...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-09-10

...] Amendment to Egg Research and Promotion Order and Regulations To Increase the Rate of Assessment and.... SUMMARY: This proposed rule would amend the Egg Research and Promotion Order (Order) to increase the assessment rate on egg producers paying assessments to the American Egg Board (AEB) from 10 cents to 15 cents...

Hybrid reduced order modeling for assembly calculations

DOE PAGES

Bang, Youngsuk; Abdel-Khalik, Hany S.; Jessee, Matthew A.; ...

2015-08-14

While the accuracy of assembly calculations has greatly improved due to the increase in computer power enabling more refined description of the phase space and use of more sophisticated numerical algorithms, the computational cost continues to increase which limits the full utilization of their effectiveness for routine engineering analysis. Reduced order modeling is a mathematical vehicle that scales down the dimensionality of large-scale numerical problems to enable their repeated executions on small computing environment, often available to end users. This is done by capturing the most dominant underlying relationships between the model's inputs and outputs. Previous works demonstrated the usemore » of the reduced order modeling for a single physics code, such as a radiation transport calculation. This paper extends those works to coupled code systems as currently employed in assembly calculations. Finally, numerical tests are conducted using realistic SCALE assembly models with resonance self-shielding, neutron transport, and nuclides transmutation/depletion models representing the components of the coupled code system.« less

Stable static structures in models with higher-order derivatives

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

Bazeia, D., E-mail: bazeia@fisica.ufpb.br; Departamento de Física, Universidade Federal de Campina Grande, 58109-970 Campina Grande, PB; Lobão, A.S.

2015-09-15

We investigate the presence of static solutions in generalized models described by a real scalar field in four-dimensional space–time. We study models in which the scalar field engenders higher-order derivatives and spontaneous symmetry breaking, inducing the presence of domain walls. Despite the presence of higher-order derivatives, the models keep to equations of motion second-order differential equations, so we focus on the presence of first-order equations that help us to obtain analytical solutions and investigate linear stability on general grounds. We then illustrate the general results with some specific examples, showing that the domain wall may become compact and that themore » zero mode may split. Moreover, if the model is further generalized to include k-field behavior, it may contribute to split the static structure itself.« less

REVEAL: An Extensible Reduced Order Model Builder for Simulation and Modeling

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

Agarwal, Khushbu; Sharma, Poorva; Ma, Jinliang

2013-04-30

Many science domains need to build computationally efficient and accurate representations of high fidelity, computationally expensive simulations. These computationally efficient versions are known as reduced-order models. This paper presents the design and implementation of a novel reduced-order model (ROM) builder, the REVEAL toolset. This toolset generates ROMs based on science- and engineering-domain specific simulations executed on high performance computing (HPC) platforms. The toolset encompasses a range of sampling and regression methods that can be used to generate a ROM, automatically quantifies the ROM accuracy, and provides support for an iterative approach to improve ROM accuracy. REVEAL is designed to bemore » extensible in order to utilize the core functionality with any simulator that has published input and output formats. It also defines programmatic interfaces to include new sampling and regression techniques so that users can ‘mix and match’ mathematical techniques to best suit the characteristics of their model. In this paper, we describe the architecture of REVEAL and demonstrate its usage with a computational fluid dynamics model used in carbon capture.« less

Mesoscopic modeling of DNA denaturation rates: Sequence dependence and experimental comparison

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

Dahlen, Oda, E-mail: oda.dahlen@ntnu.no; Erp, Titus S. van, E-mail: titus.van.erp@ntnu.no

Using rare event simulation techniques, we calculated DNA denaturation rate constants for a range of sequences and temperatures for the Peyrard-Bishop-Dauxois (PBD) model with two different parameter sets. We studied a larger variety of sequences compared to previous studies that only consider DNA homopolymers and DNA sequences containing an equal amount of weak AT- and strong GC-base pairs. Our results show that, contrary to previous findings, an even distribution of the strong GC-base pairs does not always result in the fastest possible denaturation. In addition, we applied an adaptation of the PBD model to study hairpin denaturation for which experimentalmore » data are available. This is the first quantitative study in which dynamical results from the mesoscopic PBD model have been compared with experiments. Our results show that present parameterized models, although giving good results regarding thermodynamic properties, overestimate denaturation rates by orders of magnitude. We believe that our dynamical approach is, therefore, an important tool for verifying DNA models and for developing next generation models that have higher predictive power than present ones.« less

A Reduced-Order Model For Zero-Mass Synthetic Jet Actuators

NASA Technical Reports Server (NTRS)

Yamaleev, Nail K.; Carpenter, Mark H.; Vatsa, Veer S.

2007-01-01

Accurate details of the general performance of fluid actuators is desirable over a range of flow conditions, within some predetermined error tolerance. Designers typically model actuators with different levels of fidelity depending on the acceptable level of error in each circumstance. Crude properties of the actuator (e.g., peak mass rate and frequency) may be sufficient for some designs, while detailed information is needed for other applications (e.g., multiple actuator interactions). This work attempts to address two primary objectives. The first objective is to develop a systematic methodology for approximating realistic 3-D fluid actuators, using quasi-1-D reduced-order models. Near full fidelity can be achieved with this approach at a fraction of the cost of full simulation and only a modest increase in cost relative to most actuator models used today. The second objective, which is a direct consequence of the first, is to determine the approximate magnitude of errors committed by actuator model approximations of various fidelities. This objective attempts to identify which model (ranging from simple orifice exit boundary conditions to full numerical simulations of the actuator) is appropriate for a given error tolerance.

First-Order Frameworks for Managing Models in Engineering Optimization

NASA Technical Reports Server (NTRS)

Alexandrov, Natlia M.; Lewis, Robert Michael

2000-01-01

Approximation/model management optimization (AMMO) is a rigorous methodology for attaining solutions of high-fidelity optimization problems with minimal expense in high- fidelity function and derivative evaluation. First-order AMMO frameworks allow for a wide variety of models and underlying optimization algorithms. Recent demonstrations with aerodynamic optimization achieved three-fold savings in terms of high- fidelity function and derivative evaluation in the case of variable-resolution models and five-fold savings in the case of variable-fidelity physics models. The savings are problem dependent but certain trends are beginning to emerge. We give an overview of the first-order frameworks, current computational results, and an idea of the scope of the first-order framework applicability.

Evaluation of rate law approximations in bottom-up kinetic models of metabolism.

PubMed

Du, Bin; Zielinski, Daniel C; Kavvas, Erol S; Dräger, Andreas; Tan, Justin; Zhang, Zhen; Ruggiero, Kayla E; Arzumanyan, Garri A; Palsson, Bernhard O

2016-06-06

The mechanistic description of enzyme kinetics in a dynamic model of metabolism requires specifying the numerical values of a large number of kinetic parameters. The parameterization challenge is often addressed through the use of simplifying approximations to form reaction rate laws with reduced numbers of parameters. Whether such simplified models can reproduce dynamic characteristics of the full system is an important question. In this work, we compared the local transient response properties of dynamic models constructed using rate laws with varying levels of approximation. These approximate rate laws were: 1) a Michaelis-Menten rate law with measured enzyme parameters, 2) a Michaelis-Menten rate law with approximated parameters, using the convenience kinetics convention, 3) a thermodynamic rate law resulting from a metabolite saturation assumption, and 4) a pure chemical reaction mass action rate law that removes the role of the enzyme from the reaction kinetics. We utilized in vivo data for the human red blood cell to compare the effect of rate law choices against the backdrop of physiological flux and concentration differences. We found that the Michaelis-Menten rate law with measured enzyme parameters yields an excellent approximation of the full system dynamics, while other assumptions cause greater discrepancies in system dynamic behavior. However, iteratively replacing mechanistic rate laws with approximations resulted in a model that retains a high correlation with the true model behavior. Investigating this consistency, we determined that the order of magnitude differences among fluxes and concentrations in the network were greatly influential on the network dynamics. We further identified reaction features such as thermodynamic reversibility, high substrate concentration, and lack of allosteric regulation, which make certain reactions more suitable for rate law approximations. Overall, our work generally supports the use of approximate rate laws when

A bilayer Double Semion model with symmetry-enriched topological order

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

Ortiz, L., E-mail: lauraort@ucm.es; Martin-Delgado, M.A.

2016-12-15

We construct a new model of two-dimensional quantum spin systems that combines intrinsic topological orders and a global symmetry called flavour symmetry. It is referred as the bilayer Doubled Semion model (bDS) and is an instance of symmetry-enriched topological order. A honeycomb bilayer lattice is introduced to combine a Double Semion Topological Order with a global spin–flavour symmetry to get the fractionalization of its quasiparticles. The bDS model exhibits non-trivial braiding self-statistics of excitations and its dual model constitutes a Symmetry-Protected Topological Order with novel edge states. This dual model gives rise to a bilayer Non-Trivial Paramagnet that is invariantmore » under the flavour symmetry and the well-known spin flip symmetry.« less

Reduced order modeling of fluid/structure interaction.

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

Barone, Matthew Franklin; Kalashnikova, Irina; Segalman, Daniel Joseph

2009-11-01

This report describes work performed from October 2007 through September 2009 under the Sandia Laboratory Directed Research and Development project titled 'Reduced Order Modeling of Fluid/Structure Interaction.' This project addresses fundamental aspects of techniques for construction of predictive Reduced Order Models (ROMs). A ROM is defined as a model, derived from a sequence of high-fidelity simulations, that preserves the essential physics and predictive capability of the original simulations but at a much lower computational cost. Techniques are developed for construction of provably stable linear Galerkin projection ROMs for compressible fluid flow, including a method for enforcing boundary conditions that preservesmore » numerical stability. A convergence proof and error estimates are given for this class of ROM, and the method is demonstrated on a series of model problems. A reduced order method, based on the method of quadratic components, for solving the von Karman nonlinear plate equations is developed and tested. This method is applied to the problem of nonlinear limit cycle oscillations encountered when the plate interacts with an adjacent supersonic flow. A stability-preserving method for coupling the linear fluid ROM with the structural dynamics model for the elastic plate is constructed and tested. Methods for constructing efficient ROMs for nonlinear fluid equations are developed and tested on a one-dimensional convection-diffusion-reaction equation. These methods are combined with a symmetrization approach to construct a ROM technique for application to the compressible Navier-Stokes equations.« less

Reverse time migration by Krylov subspace reduced order modeling

NASA Astrophysics Data System (ADS)

Basir, Hadi Mahdavi; Javaherian, Abdolrahim; Shomali, Zaher Hossein; Firouz-Abadi, Roohollah Dehghani; Gholamy, Shaban Ali

2018-04-01

Imaging is a key step in seismic data processing. To date, a myriad of advanced pre-stack depth migration approaches have been developed; however, reverse time migration (RTM) is still considered as the high-end imaging algorithm. The main limitations associated with the performance cost of reverse time migration are the intensive computation of the forward and backward simulations, time consumption, and memory allocation related to imaging condition. Based on the reduced order modeling, we proposed an algorithm, which can be adapted to all the aforementioned factors. Our proposed method benefit from Krylov subspaces method to compute certain mode shapes of the velocity model computed by as an orthogonal base of reduced order modeling. Reverse time migration by reduced order modeling is helpful concerning the highly parallel computation and strongly reduces the memory requirement of reverse time migration. The synthetic model results showed that suggested method can decrease the computational costs of reverse time migration by several orders of magnitudes, compared with reverse time migration by finite element method.

Fitting Cure Rate Model to Breast Cancer Data of Cancer Research Center.

PubMed

Baghestani, Ahmad Reza; Zayeri, Farid; Akbari, Mohammad Esmaeil; Shojaee, Leyla; Khadembashi, Naghmeh; Shahmirzalou, Parviz

2015-01-01

The Cox PH model is one of the most significant statistical models in studying survival of patients. But, in the case of patients with long-term survival, it may not be the most appropriate. In such cases, a cure rate model seems more suitable. The purpose of this study was to determine clinical factors associated with cure rate of patients with breast cancer. In order to find factors affecting cure rate (response), a non-mixed cure rate model with negative binomial distribution for latent variable was used. Variables selected were recurrence cancer, status for HER2, estrogen receptor (ER) and progesterone receptor (PR), size of tumor, grade of cancer, stage of cancer, type of surgery, age at the diagnosis time and number of removed positive lymph nodes. All analyses were performed using PROC MCMC processes in the SAS 9.2 program. The mean (SD) age of patients was equal to 48.9 (11.1) months. For these patients, 1, 5 and 10-year survival rates were 95, 79 and 50 percent respectively. All of the mentioned variables were effective in cure fraction. Kaplan-Meier curve showed cure model's use competence. Unlike other variables, existence of ER and PR positivity will increase probability of cure in patients. In the present study, Weibull distribution was used for the purpose of analysing survival times. Model fitness with other distributions such as log-N and log-logistic and other distributions for latent variable is recommended.

A Novel Fractional Order Model for the Dynamic Hysteresis of Piezoelectrically Actuated Fast Tool Servo

PubMed Central

Zhu, Zhiwei; Zhou, Xiaoqin

2012-01-01

The main contribution of this paper is the development of a linearized model for describing the dynamic hysteresis behaviors of piezoelectrically actuated fast tool servo (FTS). A linearized hysteresis force model is proposed and mathematically described by a fractional order differential equation. Combining the dynamic modeling of the FTS mechanism, a linearized fractional order dynamic hysteresis (LFDH) model for the piezoelectrically actuated FTS is established. The unique features of the LFDH model could be summarized as follows: (a) It could well describe the rate-dependent hysteresis due to its intrinsic characteristics of frequency-dependent nonlinear phase shifts and amplitude modulations; (b) The linearization scheme of the LFDH model would make it easier to implement the inverse dynamic control on piezoelectrically actuated micro-systems. To verify the effectiveness of the proposed model, a series of experiments are conducted. The toolpaths of the FTS for creating two typical micro-functional surfaces involving various harmonic components with different frequencies and amplitudes are scaled and employed as command signals for the piezoelectric actuator. The modeling errors in the steady state are less than ±2.5% within the full span range which is much smaller than certain state-of-the-art modeling methods, demonstrating the efficiency and superiority of the proposed model for modeling dynamic hysteresis effects. Moreover, it indicates that the piezoelectrically actuated micro systems would be more suitably described as a fractional order dynamic system.

Reduced-order modeling for hyperthermia: an extended balanced-realization-based approach.

PubMed

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

1998-09-01

Accurate thermal models are needed in hyperthermia cancer treatments for such tasks as actuator and sensor placement design, parameter estimation, and feedback temperature control. The complexity of the human body produces full-order models which are too large for effective execution of these tasks, making use of reduced-order models necessary. However, standard balanced-realization (SBR)-based model reduction techniques require a priori knowledge of the particular placement of actuators and sensors for model reduction. Since placement design is intractable (computationally) on the full-order models, SBR techniques must use ad hoc placements. To alleviate this problem, an extended balanced-realization (EBR)-based model-order reduction approach is presented. The new technique allows model order reduction to be performed over all possible placement designs and does not require ad hoc placement designs. It is shown that models obtained using the EBR method are more robust to intratreatment changes in the placement of the applied power field than those models obtained using the SBR method.

New higher-order Godunov code for modelling performance of two-stage light gas guns

NASA Technical Reports Server (NTRS)

Bogdanoff, D. W.; Miller, R. J.

1995-01-01

A new quasi-one-dimensional Godunov code for modeling two-stage light gas guns is described. The code is third-order accurate in space and second-order accurate in time. A very accurate Riemann solver is used. Friction and heat transfer to the tube wall for gases and dense media are modeled and a simple nonequilibrium turbulence model is used for gas flows. The code also models gunpowder burn in the first-stage breech. Realistic equations of state (EOS) are used for all media. The code was validated against exact solutions of Riemann's shock-tube problem, impact of dense media slabs at velocities up to 20 km/sec, flow through a supersonic convergent-divergent nozzle and burning of gunpowder in a closed bomb. Excellent validation results were obtained. The code was then used to predict the performance of two light gas guns (1.5 in. and 0.28 in.) in service at the Ames Research Center. The code predictions were compared with measured pressure histories in the powder chamber and pump tube and with measured piston and projectile velocities. Very good agreement between computational fluid dynamics (CFD) predictions and measurements was obtained. Actual powder-burn rates in the gun were found to be considerably higher (60-90 percent) than predicted by the manufacturer and the behavior of the piston upon yielding appears to differ greatly from that suggested by low-strain rate tests.

A model for predicting wear rates in tooth enamel.

PubMed

Borrero-Lopez, Oscar; Pajares, Antonia; Constantino, Paul J; Lawn, Brian R

2014-09-01

It is hypothesized that wear of enamel is sensitive to the presence of sharp particulates in oral fluids and masticated foods. To this end, a generic model for predicting wear rates in brittle materials is developed, with specific application to tooth enamel. Wear is assumed to result from an accumulation of elastic-plastic micro-asperity events. Integration over all such events leads to a wear rate relation analogous to Archard׳s law, but with allowance for variation in asperity angle and compliance. The coefficient K in this relation quantifies the wear severity, with an arbitrary distinction between 'mild' wear (low K) and 'severe' wear (high K). Data from the literature and in-house wear-test experiments on enamel specimens in lubricant media (water, oil) with and without sharp third-body particulates (silica, diamond) are used to validate the model. Measured wear rates can vary over several orders of magnitude, depending on contact asperity conditions, accounting for the occurrence of severe enamel removal in some human patients (bruxing). Expressions for the depth removal rate and number of cycles to wear down occlusal enamel in the low-crowned tooth forms of some mammals are derived, with tooth size and enamel thickness as key variables. The role of 'hard' versus 'soft' food diets in determining evolutionary paths in different hominin species is briefly considered. A feature of the model is that it does not require recourse to specific material removal mechanisms, although processes involving microplastic extrusion and microcrack coalescence are indicated. Published by Elsevier Ltd.

Reduced Order Modeling in General Relativity

NASA Astrophysics Data System (ADS)

Tiglio, Manuel

2014-03-01

Reduced Order Modeling is an emerging yet fast developing filed in gravitational wave physics. The main goals are to enable fast modeling and parameter estimation of any detected signal, along with rapid matched filtering detecting. I will focus on the first two. Some accomplishments include being able to replace, with essentially no lost of physical accuracy, the original models with surrogate ones (which are not effective ones, that is, they do not simplify the physics but go on a very different track, exploiting the particulars of the waveform family under consideration and state of the art dimensional reduction techniques) which are very fast to evaluate. For example, for EOB models they are at least around 3 orders of magnitude faster than solving the original equations, with physically equivalent results. For numerical simulations the speedup is at least 11 orders of magnitude. For parameter estimation our current numbers are about bringing ~100 days for a single SPA inspiral binary neutron star Bayesian parameter estimation analysis to under a day. More recently, it has been shown that the full precessing problem for, say, 200 cycles, can be represented, through some new ideas, by a remarkably compact set of carefully chosen reduced basis waveforms (~10-100, depending on the accuracy requirements). I will highlight what I personally believe are the challenges to face next in this subarea of GW physics and where efforts should be directed. This talk will summarize work in collaboration with: Harbir Antil (GMU), Jonathan Blackman (Caltech), Priscila Canizares (IoA, Cambridge, UK), Sarah Caudill (UWM), Jonathan Gair (IoA. Cambridge. UK), Scott Field (UMD), Chad R. Galley (Caltech), Frank Herrmann (Germany), Han Hestahven (EPFL, Switzerland), Jason Kaye (Brown, Stanford & Courant). Evan Ochsner (UWM), Ricardo Nochetto (UMD), Vivien Raymond (LIGO, Caltech), Rory Smith (LIGO, Caltech) Bela Ssilagyi (Caltech) and MT (UMD & Caltech).

On the ambiguity of the reaction rate constants in multivariate curve resolution for reversible first-order reaction systems.

PubMed

Schröder, Henning; Sawall, Mathias; Kubis, Christoph; Selent, Detlef; Hess, Dieter; Franke, Robert; Börner, Armin; Neymeyr, Klaus

2016-07-13

If for a chemical reaction with a known reaction mechanism the concentration profiles are accessible only for certain species, e.g. only for the main product, then often the reaction rate constants cannot uniquely be determined from the concentration data. This is a well-known fact which includes the so-called slow-fast ambiguity. This work combines the question of unique or non-unique reaction rate constants with factor analytic methods of chemometrics. The idea is to reduce the rotational ambiguity of pure component factorizations by considering only those concentration factors which are possible solutions of the kinetic equations for a properly adapted set of reaction rate constants. The resulting set of reaction rate constants corresponds to those solutions of the rate equations which appear as feasible factors in a pure component factorization. The new analysis of the ambiguity of reaction rate constants extends recent research activities on the Area of Feasible Solutions (AFS). The consistency with a given chemical reaction scheme is shown to be a valuable tool in order to reduce the AFS. The new methods are applied to model and experimental data. Copyright © 2016 Elsevier B.V. All rights reserved.

Time-dependent Models for Blazar Emission with the Second-order Fermi Acceleration

NASA Astrophysics Data System (ADS)

Asano, Katsuaki; Takahara, Fumio; Kusunose, Masaaki; Toma, Kenji; Kakuwa, Jun

2014-01-01

The second-order Fermi acceleration (Fermi-II) driven by turbulence may be responsible for the electron acceleration in blazar jets. We test this model with time-dependent simulations. The hard electron spectrum predicted by the Fermi-II process agrees with the hard photon spectrum of 1ES 1101-232. For other blazars that show softer spectra, the Fermi-II model requires radial evolution of the electron injection rate and/or diffusion coefficient in the outflow. Such evolutions can yield a curved electron spectrum, which can reproduce the synchrotron spectrum of Mrk 421 from the radio to the X-ray regime. The photon spectrum in the GeV energy range of Mrk 421 is hard to fit with a synchrotron self-Compton model. However, if we introduce an external radio photon field with a luminosity of 4.9 × 1038 erg s-1, GeV photons are successfully produced via inverse Compton scattering. The temporal variability of the diffusion coefficient or injection rate causes flare emission. The observed synchronicity of X-ray and TeV flares implies a decrease of the magnetic field in the flaring source region.

Time-dependent models for blazar emission with the second-order Fermi acceleration

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

Asano, Katsuaki; Takahara, Fumio; Toma, Kenji

The second-order Fermi acceleration (Fermi-II) driven by turbulence may be responsible for the electron acceleration in blazar jets. We test this model with time-dependent simulations. The hard electron spectrum predicted by the Fermi-II process agrees with the hard photon spectrum of 1ES 1101–232. For other blazars that show softer spectra, the Fermi-II model requires radial evolution of the electron injection rate and/or diffusion coefficient in the outflow. Such evolutions can yield a curved electron spectrum, which can reproduce the synchrotron spectrum of Mrk 421 from the radio to the X-ray regime. The photon spectrum in the GeV energy range ofmore » Mrk 421 is hard to fit with a synchrotron self-Compton model. However, if we introduce an external radio photon field with a luminosity of 4.9 × 10{sup 38} erg s{sup –1}, GeV photons are successfully produced via inverse Compton scattering. The temporal variability of the diffusion coefficient or injection rate causes flare emission. The observed synchronicity of X-ray and TeV flares implies a decrease of the magnetic field in the flaring source region.« less

Design of experiments for zeroth and first-order reaction rates.

PubMed

Amo-Salas, Mariano; Martín-Martín, Raúl; Rodríguez-Aragón, Licesio J

2014-09-01

This work presents optimum designs for reaction rates experiments. In these experiments, time at which observations are to be made and temperatures at which reactions are to be run need to be designed. Observations are performed along time under isothermal conditions. Each experiment needs a fixed temperature and so the reaction can be measured at the designed times. For these observations under isothermal conditions over the same reaction a correlation structure has been considered. D-optimum designs are the aim of our work for zeroth and first-order reaction rates. Temperatures for the isothermal experiments and observation times, to obtain the most accurate estimates of the unknown parameters, are provided in these designs. D-optimum designs for a single observation in each isothermal experiment or for several correlated observations have been obtained. Robustness of the optimum designs for ranges of the correlation parameter and comparisons of the information gathered by different designs are also shown. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

First-order kinetic gas generation model parameters for wet landfills.

PubMed

Faour, Ayman A; Reinhart, Debra R; You, Huaxin

2007-01-01

Landfill gas collection data from wet landfill cells were analyzed and first-order gas generation model parameters were estimated for the US EPA landfill gas emissions model (LandGEM). Parameters were determined through statistical comparison of predicted and actual gas collection. The US EPA LandGEM model appeared to fit the data well, provided it is preceded by a lag phase, which on average was 1.5 years. The first-order reaction rate constant, k, and the methane generation potential, L(o), were estimated for a set of landfills with short-term waste placement and long-term gas collection data. Mean and 95% confidence parameter estimates for these data sets were found using mixed-effects model regression followed by bootstrap analysis. The mean values for the specific methane volume produced during the lag phase (V(sto)), L(o), and k were 33 m(3)/Megagrams (Mg), 76 m(3)/Mg, and 0.28 year(-1), respectively. Parameters were also estimated for three full scale wet landfills where waste was placed over many years. The k and L(o) estimated for these landfills were 0.21 year(-1), 115 m(3)/Mg, 0.11 year(-1), 95 m(3)/Mg, and 0.12 year(-1) and 87 m(3)/Mg, respectively. A group of data points from wet landfills cells with short-term data were also analyzed. A conservative set of parameter estimates was suggested based on the upper 95% confidence interval parameters as a k of 0.3 year(-1) and a L(o) of 100 m(3)/Mg if design is optimized and the lag is minimized.

A fully-implicit high-order system thermal-hydraulics model for advanced non-LWR safety analyses

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

Hu, Rui

An advanced system analysis tool is being developed for advanced reactor safety analysis. This paper describes the underlying physics and numerical models used in the code, including the governing equations, the stabilization schemes, the high-order spatial and temporal discretization schemes, and the Jacobian Free Newton Krylov solution method. The effects of the spatial and temporal discretization schemes are investigated. Additionally, a series of verification test problems are presented to confirm the high-order schemes. Furthermore, it is demonstrated that the developed system thermal-hydraulics model can be strictly verified with the theoretical convergence rates, and that it performs very well for amore » wide range of flow problems with high accuracy, efficiency, and minimal numerical diffusions.« less

A fully-implicit high-order system thermal-hydraulics model for advanced non-LWR safety analyses

DOE PAGES

Hu, Rui

2016-11-19

An advanced system analysis tool is being developed for advanced reactor safety analysis. This paper describes the underlying physics and numerical models used in the code, including the governing equations, the stabilization schemes, the high-order spatial and temporal discretization schemes, and the Jacobian Free Newton Krylov solution method. The effects of the spatial and temporal discretization schemes are investigated. Additionally, a series of verification test problems are presented to confirm the high-order schemes. Furthermore, it is demonstrated that the developed system thermal-hydraulics model can be strictly verified with the theoretical convergence rates, and that it performs very well for amore » wide range of flow problems with high accuracy, efficiency, and minimal numerical diffusions.« less

Projection-Based Reduced Order Modeling for Spacecraft Thermal Analysis

NASA Technical Reports Server (NTRS)

Qian, Jing; Wang, Yi; Song, Hongjun; Pant, Kapil; Peabody, Hume; Ku, Jentung; Butler, Charles D.

2015-01-01

This paper presents a mathematically rigorous, subspace projection-based reduced order modeling (ROM) methodology and an integrated framework to automatically generate reduced order models for spacecraft thermal analysis. Two key steps in the reduced order modeling procedure are described: (1) the acquisition of a full-scale spacecraft model in the ordinary differential equation (ODE) and differential algebraic equation (DAE) form to resolve its dynamic thermal behavior; and (2) the ROM to markedly reduce the dimension of the full-scale model. Specifically, proper orthogonal decomposition (POD) in conjunction with discrete empirical interpolation method (DEIM) and trajectory piece-wise linear (TPWL) methods are developed to address the strong nonlinear thermal effects due to coupled conductive and radiative heat transfer in the spacecraft environment. Case studies using NASA-relevant satellite models are undertaken to verify the capability and to assess the computational performance of the ROM technique in terms of speed-up and error relative to the full-scale model. ROM exhibits excellent agreement in spatiotemporal thermal profiles (<0.5% relative error in pertinent time scales) along with salient computational acceleration (up to two orders of magnitude speed-up) over the full-scale analysis. These findings establish the feasibility of ROM to perform rational and computationally affordable thermal analysis, develop reliable thermal control strategies for spacecraft, and greatly reduce the development cycle times and costs.

Modeling shear-induced particle ordering and deformation in a dense soft particle suspension

NASA Astrophysics Data System (ADS)

Liao, Chih-Tang; Wu, Yi-Fan; Chien, Wei; Huang, Jung-Ren; Chen, Yeng-Long

2017-11-01

We apply the lattice Boltzmann method and the bead-spring network model of deformable particles (DPs) to study shear-induced particle ordering and deformation and the corresponding rheological behavior for dense DP suspensions confined in a narrow gap under steady external shear. The particle configuration is characterized with small-angle scattering intensity, the real-space 2D local order parameter, and the particle shape factors including deformation, stretching and tilt angles. We investigate how particle ordering and deformation vary with the particle volume fraction ϕ (=0.45-0.65) and the external shear rate characterized with the capillary number Ca (=0.003-0.191). The degree of particle deformation increases mildly with ϕ but significantly with Ca. Under moderate shear rate (Ca  =  0.105), the inter-particle structure evolves from string-like ordering to layered hexagonal close packing (HCP) as ϕ increases. A long wavelength particle slithering motion emerges for sufficiently large ϕ. For ϕ  =  0.61, the structure maintains layered HCP for Ca  =  0.031-0.143 but gradually becomes disordered for larger and smaller Ca. The correlation in particle zigzag movements depends sensitively on ϕ and particle ordering. Layer-by-layer analysis reveals how the non-slippery hard walls affect particle ordering and deformation. The shear-induced reconfiguration of DPs observed in the simulation agrees qualitatively with experimental results of sheared uniform emulsions. The apparent suspension viscosity increases with ϕ but exhibits much weaker dependence compared to hard-sphere suspensions, indicating that particle deformation and unjamming under shear can significantly reduce the viscous stress. Furthermore, the suspension shear-thins, corresponding to increased inter-DP ordering and particle deformation with Ca. This work provides useful insights into the microstructure-rheology relationship of concentrated deformable particle suspensions.

Modeling shear-induced particle ordering and deformation in a dense soft particle suspension.

PubMed

Liao, Chih-Tang; Wu, Yi-Fan; Chien, Wei; Huang, Jung-Ren; Chen, Yeng-Long

2017-11-01

We apply the lattice Boltzmann method and the bead-spring network model of deformable particles (DPs) to study shear-induced particle ordering and deformation and the corresponding rheological behavior for dense DP suspensions confined in a narrow gap under steady external shear. The particle configuration is characterized with small-angle scattering intensity, the real-space 2D local order parameter, and the particle shape factors including deformation, stretching and tilt angles. We investigate how particle ordering and deformation vary with the particle volume fraction ϕ (=0.45-0.65) and the external shear rate characterized with the capillary number Ca (=0.003-0.191). The degree of particle deformation increases mildly with ϕ but significantly with Ca. Under moderate shear rate (Ca  =  0.105), the inter-particle structure evolves from string-like ordering to layered hexagonal close packing (HCP) as ϕ increases. A long wavelength particle slithering motion emerges for sufficiently large ϕ. For ϕ  =  0.61, the structure maintains layered HCP for Ca  =  0.031-0.143 but gradually becomes disordered for larger and smaller Ca. The correlation in particle zigzag movements depends sensitively on ϕ and particle ordering. Layer-by-layer analysis reveals how the non-slippery hard walls affect particle ordering and deformation. The shear-induced reconfiguration of DPs observed in the simulation agrees qualitatively with experimental results of sheared uniform emulsions. The apparent suspension viscosity increases with ϕ but exhibits much weaker dependence compared to hard-sphere suspensions, indicating that particle deformation and unjamming under shear can significantly reduce the viscous stress. Furthermore, the suspension shear-thins, corresponding to increased inter-DP ordering and particle deformation with Ca. This work provides useful insights into the microstructure-rheology relationship of concentrated deformable particle suspensions.

Performance analysis of 60-min to 1-min integration time rain rate conversion models in Malaysia

NASA Astrophysics Data System (ADS)

Ng, Yun-Yann; Singh, Mandeep Singh Jit; Thiruchelvam, Vinesh

2018-01-01

Utilizing the frequency band above 10 GHz is in focus nowadays as a result of the fast expansion of radio communication systems in Malaysia. However, rain fade is the critical factor in attenuation of signal propagation for frequencies above 10 GHz. Malaysia is located in a tropical and equatorial region with high rain intensity throughout the year, and this study will review rain distribution and evaluate the performance of 60-min to 1-min integration time rain rate conversion methods for Malaysia. Several conversion methods such as Segal, Chebil & Rahman, Burgeono, Emiliani, Lavergnat and Gole (LG), Simplified Moupfouma, Joo et al., fourth order polynomial fit and logarithmic model have been chosen to evaluate the performance to predict 1-min rain rate for 10 sites in Malaysia. After the completion of this research, the results show that Chebil & Rahman model, Lavergnat & Gole model, Fourth order polynomial fit and Logarithmic model have shown the best performances in 60-min to 1-min rain rate conversion over 10 sites. In conclusion, it is proven that there is no single model which can claim to perform the best across 10 sites. By averaging RMSE and SC-RMSE over 10 sites, Chebil and Rahman model is the best method.

Parallel Nonnegative Least Squares Solvers for Model Order Reduction

DTIC Science & Technology

2016-03-01

NNLS problems that arise when the Energy Conserving Sampling and Weighting hyper -reduction procedure is used when constructing a reduced-order model...ScaLAPACK and performance results are presented. nonnegative least squares, model order reduction, hyper -reduction, Energy Conserving Sampling and...optimal solution. ........................................ 20 Table 6 Reduced mesh sizes produced for each solver in the ECSW hyper -reduction step

A Finite-Rate-Catalytic Model For Hypersonic Flows Informed By Molecular Dynamics

NASA Astrophysics Data System (ADS)

Schwartzentruber, T. E.; Valentini, P.; Norman, P.; Sorensen, C.

2011-05-01

The implementation of a finite-rate catalytic (FRC) wall boundary condition within a general 3D unstructured CFD solver is described. A set of one-step gas-surface chemical equations and atomistic parameters that deter- mine the reaction rates must be prescribed as input to the model. The chemical rate equations are solved at each wall face in the CFD simulation and result in a net production of species at the wall. In order for a finite- rate gas-surface reaction model to be consistent at equilibrium, it is determined that not all forward and back- ward rates can be specified arbitrarily. Provided that the forward rates for each surface recombination are as- signed, the backward rates must be determined using equilibrium constants that are consistent with the gas- phase chemistry model and thermodynamics. Reactive molecular dynamics (MD) simulations are performed us- ing the ReaxFFSiO potential to investigate oxygen-silica interactions. β-quartz and amorphous SiO2 surfaces are accommodated to a high temperature gas via MD simulation and reach a steady-state surface coverage. In addition to stable surface reconstructions a number of active sites are observed on which recombination occurs. Single collision MD simulations are performed where gas-phase oxygen atoms interact with the most dominant active site. Probabilities of recombination are found to have an exponential trend with gas-surface system temperature. The MD simulations are used to determine the activation energy for Eley-Rideal recombination of oxygen on a specific silica active site which is an important input parameter for the FRC model.

Is surgical case order associated with increased infection rate after spine surgery?

PubMed

Gruskay, Jordan; Kepler, Christopher; Smith, Jeremy; Radcliff, Kristen; Vaccaro, Alexander

2012-06-01

Retrospective database review. To determine whether surgical site infections are associated with case order in spinal surgery. Postoperative wound infection is the most common complication after spinal surgery, with incidence varying from 0.5% to 20%. The addition of instrumentation, use of preoperative prophylactic antibiotics, length of procedure, and intraoperative blood loss have all been found to influence infection rate. No previous study has attempted to correlate case order with infection risk after surgery. A total of 6666 spine surgery cases occurring between January 2005 and December 2009 were studied. Subjects were classified into 2 categories: fusion and decompression. Case order was determined, with each procedure labeled 1 to 5 depending on the number of previous cases in the room. Variables such as the American Society of Anesthesiologists score, number of operative levels, wound class, age, sex, and length of surgery were also tracked. A step-down binary regression was used to analyze each variable as a potential risk factor for infection. Decompression cases had a 2.4% incidence of infection. Longer surgical time and higher case order were found to be significant risk factors for lumbar decompressions. Fusion cases had a 3.5% incidence of infection. Posterior approach and revision cases were significant risk factors for infection in cervical cases. For lumbar fusion cases, longer surgical time, higher American Society of Anesthesiologists score, and older age were all significant risk factors for infection. Decompressive procedures performed later in the day carry a higher risk for postoperative infection. No similar trend was shown for fusion procedures. Our results identify potential modifiable risk factors contributing to infection rates in spinal procedures. Specific risk factors, although not defined in this study, might be related to contamination of the operating room, cross-contamination between health care providers during the course of

First-order inflation. [in cosmology

NASA Technical Reports Server (NTRS)

Turner, Michael S.

1992-01-01

I discuss the most recent model of inflation. In first-order inflation the inflationary epoch is associated with a first-order phase transition, with the most likely candidate being GUT symmetry breaking. The transition from the false-vacuum inflationary phase to the true-vacuum radiation-dominated phase proceeds through the nucleation and percolation of true-vacuum bubbles. The first successful and simplest model of first-order inflation, extended inflation, is discussed in some detail: evolution of the cosmic-scale factor, reheating, density perturbations, and the production of gravitational waves both from quantum fluctuations and bubble collisions. Particular attention is paid to the most critical issue in any model of first-order inflation: the requirements on the nucleation rate to ensure a graceful transition from the inflationary phase to the radiation-dominated phase.

Cooling rate dependence of structural order in Al90Sm10 metallic glass

NASA Astrophysics Data System (ADS)

Sun, Yang; Zhang, Yue; Zhang, Feng; Ye, Zhuo; Ding, Zejun; Wang, Cai-Zhuang; Ho, Kai-Ming

2016-07-01

The atomic structure of Al90Sm10 metallic glass is studied using molecular dynamics simulations. By performing a long sub-Tg annealing, we developed a glass model closer to the experiments than the models prepared by continuous cooling. Using the cluster alignment method, we found that "3661" cluster is the dominating short-range order in the glass samples. The connection and arrangement of "3661" clusters, which define the medium-range order in the system, are enhanced significantly in the sub-Tg annealed sample as compared with the fast cooled glass samples. Unlike some strong binary glass formers such as Cu64.5Zr35.5, the clusters representing the short-range order do not form an interconnected interpenetrating network in Al90Sm10, which has only marginal glass formability.

Finite-Strain Fractional-Order Viscoelastic (FOV) Material Models and Numerical Methods for Solving Them

NASA Technical Reports Server (NTRS)

Freed, Alan D.; Diethelm, Kai; Gray, Hugh R. (Technical Monitor)

2002-01-01

Fraction-order viscoelastic (FOV) material models have been proposed and studied in 1D since the 1930's, and were extended into three dimensions in the 1970's under the assumption of infinitesimal straining. It was not until 1997 that Drozdov introduced the first finite-strain FOV constitutive equations. In our presentation, we shall continue in this tradition by extending the standard, FOV, fluid and solid, material models introduced in 1971 by Caputo and Mainardi into 3D constitutive formula applicable for finite-strain analyses. To achieve this, we generalize both the convected and co-rotational derivatives of tensor fields to fractional order. This is accomplished by defining them first as body tensor fields and then mapping them into space as objective Cartesian tensor fields. Constitutive equations are constructed using both variants for fractional rate, and their responses are contrasted in simple shear. After five years of research and development, we now possess a basic suite of numerical tools necessary to study finite-strain FOV constitutive equations and their iterative refinement into a mature collection of material models. Numerical methods still need to be developed for efficiently solving fraction al-order integrals, derivatives, and differential equations in a finite element setting where such constitutive formulae would need to be solved at each Gauss point in each element of a finite model, which can number into the millions in today's analysis.

Microbial Mortality Rates in Support of Model Development in Three Distinct Ocean Regimes

NASA Astrophysics Data System (ADS)

Connell, P. E.; Gellene, A. G.; Campbell, V.; Hu, S. K.; Arrigo, K. R.; Caron, D. A.

2016-02-01

Quantitative assessments of trophic interactions have become increasingly important in plankton research with the recognition that delicate balances between predators and prey strongly influence biogeochemical cycles. As the modeling community continues to increase the complexity of ecosystem models in order to improve their predictive power, understanding the balances of production and loss across spatial and seasonal scales is critical. We measured the growth and mortality rates of the total phytoplankton community and key picophytoplankton groups (Synechococcus, Prochlorococcus, and photosynthetic picoeukaryotes) using a modified dilution method, as well as bacterial mortality rates via FLB (fluorescently-labeled bacteria) disappearance incubations. Community composition was assessed using microscopy and flow cytometry. Measurements were conducted in three climatic regions: coastal waters of the Southern California Bight, The Chukchi Sea, and the North Pacific Subtropical Gyre. Local seasonal variability was also assessed quarterly (January, April, July, October) in the Bight. These measurements provided insight into the relative turnover rates of key microbial groups and the microbial population dynamics of disparate ocean regimes. This study will aid our ability to construct predictive ecosystem models through the application of community composition and rate data to model parameterization.

A transfer-rate epidemiological model

NASA Astrophysics Data System (ADS)

Zhang, Lin; Hu, Hailong; Li, Yantao; Qu, Zehui

2018-05-01

Everywhere in the world, thousands of lives are taken by infectious viruses every year. It is very meaningful to study the communication model to help medical workers to formulate timely and effective interventions. In this paper, we proposed a model with considering the different influences to the virus's spreading, which are from the different kinds of connects between people. What's more, the infection and curation rates in our model are more in line with real life. We simulate the real spreading of B-Yamagata from 2014 to 2017 and find the trends of infection rate during one year.

Time series models on analysing mortality rates and acute childhood lymphoid leukaemia.

PubMed

Kis, Maria

2005-01-01

In this paper we demonstrate applying time series models on medical research. The Hungarian mortality rates were analysed by autoregressive integrated moving average models and seasonal time series models examined the data of acute childhood lymphoid leukaemia.The mortality data may be analysed by time series methods such as autoregressive integrated moving average (ARIMA) modelling. This method is demonstrated by two examples: analysis of the mortality rates of ischemic heart diseases and analysis of the mortality rates of cancer of digestive system. Mathematical expressions are given for the results of analysis. The relationships between time series of mortality rates were studied with ARIMA models. Calculations of confidence intervals for autoregressive parameters by tree methods: standard normal distribution as estimation and estimation of the White's theory and the continuous time case estimation. Analysing the confidence intervals of the first order autoregressive parameters we may conclude that the confidence intervals were much smaller than other estimations by applying the continuous time estimation model.We present a new approach to analysing the occurrence of acute childhood lymphoid leukaemia. We decompose time series into components. The periodicity of acute childhood lymphoid leukaemia in Hungary was examined using seasonal decomposition time series method. The cyclic trend of the dates of diagnosis revealed that a higher percent of the peaks fell within the winter months than in the other seasons. This proves the seasonal occurrence of the childhood leukaemia in Hungary.

A Model-Free Diagnostic for Single-Peakedness of Item Responses Using Ordered Conditional Means.

PubMed

Polak, Marike; de Rooij, Mark; Heiser, Willem J

2012-09-01

In this article we propose a model-free diagnostic for single-peakedness (unimodality) of item responses. Presuming a unidimensional unfolding scale and a given item ordering, we approximate item response functions of all items based on ordered conditional means (OCM). The proposed OCM methodology is based on Thurstone & Chave's (1929) criterion of irrelevance, which is a graphical, exploratory method for evaluating the "relevance" of dichotomous attitude items. We generalized this criterion to graded response items and quantified the relevance by fitting a unimodal smoother. The resulting goodness-of-fit was used to determine item fit and aggregated scale fit. Based on a simulation procedure, cutoff values were proposed for the measures of item fit. These cutoff values showed high power rates and acceptable Type I error rates. We present 2 applications of the OCM method. First, we apply the OCM method to personality data from the Developmental Profile; second, we analyze attitude data collected by Roberts and Laughlin (1996) concerning opinions of capital punishment.

A bilayer Double Semion Model with Symmetry-Enriched Topological Order

NASA Astrophysics Data System (ADS)

Ortiz, Laura; Martin-Delgado, Miguel Angel

We construct a new model of two-dimensional quantum spin systems that combines intrinsic topological orders and a global symmetry called flavour symmetry. It is referred as the bilayer Doubled Semion model (bDS) and is an instance of symmetry-enriched topological order. A honeycomb bilayer lattice is introduced to combine a Double Semion Topolgical Order with a global spin-flavour symmetry to get the fractionalization of its quasiparticles. The bDS model exhibits non-trival braiding self-statistics of excitations and its dual model constitutes a Symmetry-Protected Topological Order with novel edge states. This dual model gives rise to a bilayer Non-Trivial Paramagnet that is invariant under the flavour symmetry and the well-known spin flip symmetry. We acknowledge financial support from the Spanish MINECO Grants FIS2012-33152, FIS2015-67411, and the CAM research consortium QUITEMAD+, Grant No. S2013/ICE-2801. The research of M.A.M.-D. has been supported in part by the U.S. Army Research Office throu.

Documentation of the Fourth Order Band Model

NASA Technical Reports Server (NTRS)

Kalnay-Rivas, E.; Hoitsma, D.

1979-01-01

A general circulation model is presented which uses quadratically conservative, fourth order horizontal space differences on an unstaggered grid and second order vertical space differences with a forward-backward or a smooth leap frog time scheme to solve the primitive equations of motion. The dynamic equations for motion, finite difference equations, a discussion of the structure and flow chart of the program code, a program listing, and three relevent papers are given.

Advanced Fluid Reduced Order Models for Compressible Flow.

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

Tezaur, Irina Kalashnikova; Fike, Jeffrey A.; Carlberg, Kevin Thomas

This report summarizes fiscal year (FY) 2017 progress towards developing and implementing within the SPARC in-house finite volume flow solver advanced fluid reduced order models (ROMs) for compressible captive-carriage flow problems of interest to Sandia National Laboratories for the design and qualification of nuclear weapons components. The proposed projection-based model order reduction (MOR) approach, known as the Proper Orthogonal Decomposition (POD)/Least- Squares Petrov-Galerkin (LSPG) method, can substantially reduce the CPU-time requirement for these simulations, thereby enabling advanced analyses such as uncertainty quantification and de- sign optimization. Following a description of the project objectives and FY17 targets, we overview briefly themore » POD/LSPG approach to model reduction implemented within SPARC . We then study the viability of these ROMs for long-time predictive simulations in the context of a two-dimensional viscous laminar cavity problem, and describe some FY17 enhancements to the proposed model reduction methodology that led to ROMs with improved predictive capabilities. Also described in this report are some FY17 efforts pursued in parallel to the primary objective of determining whether the ROMs in SPARC are viable for the targeted application. These include the implemen- tation and verification of some higher-order finite volume discretization methods within SPARC (towards using the code to study the viability of ROMs on three-dimensional cavity problems) and a novel structure-preserving constrained POD/LSPG formulation that can improve the accuracy of projection-based reduced order models. We conclude the report by summarizing the key takeaways from our FY17 findings, and providing some perspectives for future work.« less

Higher order turbulence closure models

NASA Technical Reports Server (NTRS)

Amano, Ryoichi S.; Chai, John C.; Chen, Jau-Der

1988-01-01

Theoretical models are developed and numerical studies conducted on various types of flows including both elliptic and parabolic. The purpose of this study is to find better higher order closure models for the computations of complex flows. This report summarizes three new achievements: (1) completion of the Reynolds-stress closure by developing a new pressure-strain correlation; (2) development of a parabolic code to compute jets and wakes; and, (3) application to a flow through a 180 deg turnaround duct by adopting a boundary fitted coordinate system. In the above mentioned models near-wall models are developed for pressure-strain correlation and third-moment, and incorporated into the transport equations. This addition improved the results considerably and is recommended for future computations. A new parabolic code to solve shear flows without coordinate tranformations is developed and incorporated in this study. This code uses the structure of the finite volume method to solve the governing equations implicitly. The code was validated with the experimental results available in the literature.

Transport coefficient computation based on input/output reduced order models

NASA Astrophysics Data System (ADS)

Hurst, Joshua L.

The guiding purpose of this thesis is to address the optimal material design problem when the material description is a molecular dynamics model. The end goal is to obtain a simplified and fast model that captures the property of interest such that it can be used in controller design and optimization. The approach is to examine model reduction analysis and methods to capture a specific property of interest, in this case viscosity, or more generally complex modulus or complex viscosity. This property and other transport coefficients are defined by a input/output relationship and this motivates model reduction techniques that are tailored to preserve input/output behavior. In particular Singular Value Decomposition (SVD) based methods are investigated. First simulation methods are identified that are amenable to systems theory analysis. For viscosity, these models are of the Gosling and Lees-Edwards type. They are high order nonlinear Ordinary Differential Equations (ODEs) that employ Periodic Boundary Conditions. Properties can be calculated from the state trajectories of these ODEs. In this research local linear approximations are rigorously derived and special attention is given to potentials that are evaluated with Periodic Boundary Conditions (PBC). For the Gosling description LTI models are developed from state trajectories but are found to have limited success in capturing the system property, even though it is shown that full order LTI models can be well approximated by reduced order LTI models. For the Lees-Edwards SLLOD type model nonlinear ODEs will be approximated by a Linear Time Varying (LTV) model about some nominal trajectory and both balanced truncation and Proper Orthogonal Decomposition (POD) will be used to assess the plausibility of reduced order models to this system description. An immediate application of the derived LTV models is Quasilinearization or Waveform Relaxation. Quasilinearization is a Newton's method applied to the ODE operator

Modelling the influence of time and temperature on the respiration rate of fresh oyster mushrooms.

PubMed

Azevedo, Sílvia; Cunha, Luís M; Fonseca, Susana C

2015-12-01

The respiration rate of mushrooms is an important indicator of postharvest senescence. Storage temperature plays a major role in their rate of respiration and, therefore, in their postharvest life. In this context, reliable predictions of respiration rates are critical for the development of modified atmosphere packaging that ultimately will maximise the quality of the product to be presented to consumers. This work was undertaken to study the influence of storage time and temperature on the respiration rate of oyster mushrooms. For that purpose, oyster mushrooms were stored at constant temperatures of 2, 6, 10, 14 and 18 ℃ under ambient atmosphere. Respiration rate data were measured with 8-h intervals up to 240 h. A decrease of respiration rate was found after cutting of the carpophores. Therefore, time effect on respiration rate was modelled using a first-order decay model. The results also show the positive influence of temperature on mushroom respiration rate. The model explaining the effect of time on oyster mushroom's respiration rate included the temperature dependence according to the Arrhenius equation, and the inclusion of a parameter describing the decrease of the respiration rate, from the initial time until equilibrium. These yielded an overall model that fitted well to the experimental data. Moreover, results show that the overall model is useful to predict respiration rate of oyster mushrooms at different temperatures and times, using the initial respiration rate of mushrooms. Furthermore, predictive modelling can be relevant for the choice of an appropriate packaging system for fresh oyster mushrooms. © The Author(s) 2014.

A parametric model order reduction technique for poroelastic finite element models.

PubMed

Lappano, Ettore; Polanz, Markus; Desmet, Wim; Mundo, Domenico

2017-10-01

This research presents a parametric model order reduction approach for vibro-acoustic problems in the frequency domain of systems containing poroelastic materials (PEM). The method is applied to the Finite Element (FE) discretization of the weak u-p integral formulation based on the Biot-Allard theory and makes use of reduced basis (RB) methods typically employed for parametric problems. The parametric reduction is obtained rewriting the Biot-Allard FE equations for poroelastic materials using an affine representation of the frequency (therefore allowing for RB methods) and projecting the frequency-dependent PEM system on a global reduced order basis generated with the proper orthogonal decomposition instead of standard modal approaches. This has proven to be better suited to describe the nonlinear frequency dependence and the strong coupling introduced by damping. The methodology presented is tested on two three-dimensional systems: in the first experiment, the surface impedance of a PEM layer sample is calculated and compared with results of the literature; in the second, the reduced order model of a multilayer system coupled to an air cavity is assessed and the results are compared to those of the reference FE model.

Regional oxygen reduction and denitrification rates in groundwater from multi-model residence time distributions, San Joaquin Valley, USA

USGS Publications Warehouse

Green, Christopher T.; Jurgens, Bryant; Zhang, Yong; Starn, Jeffrey; Singleton, Michael J.; Esser, Bradley K.

2016-01-01

Rates of oxygen and nitrate reduction are key factors in determining the chemical evolution of groundwater. Little is known about how these rates vary and covary in regional groundwater settings, as few studies have focused on regional datasets with multiple tracers and methods of analysis that account for effects of mixed residence times on apparent reaction rates. This study provides insight into the characteristics of residence times and rates of O2 reduction and denitrification (NO3− reduction) by comparing reaction rates using multi-model analytical residence time distributions (RTDs) applied to a data set of atmospheric tracers of groundwater age and geochemical data from 141 well samples in the Central Eastern San Joaquin Valley, CA. The RTD approach accounts for mixtures of residence times in a single sample to provide estimates of in-situ rates. Tracers included SF6, CFCs, 3H, He from 3H (tritiogenic He),14C, and terrigenic He. Parameter estimation and multi-model averaging were used to establish RTDs with lower error variances than those produced by individual RTD models. The set of multi-model RTDs was used in combination with NO3− and dissolved gas data to estimate zero order and first order rates of O2 reduction and denitrification. Results indicated that O2 reduction and denitrification rates followed approximately log-normal distributions. Rates of O2 and NO3− reduction were correlated and, on an electron milliequivalent basis, denitrification rates tended to exceed O2 reduction rates. Estimated historical NO3− trends were similar to historical measurements. Results show that the multi-model approach can improve estimation of age distributions, and that relatively easily measured O2 rates can provide information about trends in denitrification rates, which are more difficult to estimate.

Regional oxygen reduction and denitrification rates in groundwater from multi-model residence time distributions, San Joaquin Valley, USA

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

Green, Christopher T.; Jurgens, Bryant C.; Zhang, Yong

Rates of oxygen and nitrate reduction are key factors in determining the chemical evolution of groundwater. Little is known about how these rates vary and covary in regional groundwater settings, as few studies have focused on regional datasets with multiple tracers and methods of analysis that account for effects of mixed residence times on apparent reaction rates. This study provides insight into the characteristics of residence times and rates of O 2 reduction and denitrification (NO 3 – reduction) by comparing reaction rates using multi-model analytical residence time distributions (RTDs) applied to a data set of atmospheric tracers of groundwatermore » age and geochemical data from 141 well samples in the Central Eastern San Joaquin Valley, CA. The RTD approach accounts for mixtures of residence times in a single sample to provide estimates of in-situ rates. Tracers included SF 6, CFCs, 3H, He from 3H (tritiogenic He), 14C, and terrigenic He. Parameter estimation and multi-model averaging were used to establish RTDs with lower error variances than those produced by individual RTD models. The set of multi-model RTDs was used in combination with NO 3 – and dissolved gas data to estimate zero order and first order rates of O 2 reduction and denitrification. Results indicated that O 2 reduction and denitrification rates followed approximately log-normal distributions. Rates of O 2 and NO 3 – reduction were correlated and, on an electron milliequivalent basis, denitrification rates tended to exceed O 2 reduction rates. Estimated historical NO 3 – trends were similar to historical measurements. Here, results show that the multi-model approach can improve estimation of age distributions, and that relatively easily measured O 2 rates can provide information about trends in denitrification rates, which are more difficult to estimate.« less

Regional oxygen reduction and denitrification rates in groundwater from multi-model residence time distributions, San Joaquin Valley, USA

DOE PAGES

Green, Christopher T.; Jurgens, Bryant C.; Zhang, Yong; ...

2016-05-14

Rates of oxygen and nitrate reduction are key factors in determining the chemical evolution of groundwater. Little is known about how these rates vary and covary in regional groundwater settings, as few studies have focused on regional datasets with multiple tracers and methods of analysis that account for effects of mixed residence times on apparent reaction rates. This study provides insight into the characteristics of residence times and rates of O 2 reduction and denitrification (NO 3 – reduction) by comparing reaction rates using multi-model analytical residence time distributions (RTDs) applied to a data set of atmospheric tracers of groundwatermore » age and geochemical data from 141 well samples in the Central Eastern San Joaquin Valley, CA. The RTD approach accounts for mixtures of residence times in a single sample to provide estimates of in-situ rates. Tracers included SF 6, CFCs, 3H, He from 3H (tritiogenic He), 14C, and terrigenic He. Parameter estimation and multi-model averaging were used to establish RTDs with lower error variances than those produced by individual RTD models. The set of multi-model RTDs was used in combination with NO 3 – and dissolved gas data to estimate zero order and first order rates of O 2 reduction and denitrification. Results indicated that O 2 reduction and denitrification rates followed approximately log-normal distributions. Rates of O 2 and NO 3 – reduction were correlated and, on an electron milliequivalent basis, denitrification rates tended to exceed O 2 reduction rates. Estimated historical NO 3 – trends were similar to historical measurements. Here, results show that the multi-model approach can improve estimation of age distributions, and that relatively easily measured O 2 rates can provide information about trends in denitrification rates, which are more difficult to estimate.« less

Cooling rate dependence of structural order in Al 90Sm 10 metallic glass

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

Sun, Yang; Zhang, Yue; Zhang, Feng

2016-07-07

Here, the atomic structure of Al 90Sm 10 metallic glass is studied using molecular dynamics simulations. By performing a long sub-T g annealing, we developed a glass model closer to the experiments than the models prepared by continuous cooling. Using the cluster alignment method, we found that “3661” cluster is the dominating short-range order in the glass samples. The connection and arrangement of “3661” clusters, which define the medium-range order in the system, are enhanced significantly in the sub-T g annealed sample as compared with the fast cooled glass samples. Unlike some strong binary glass formers such as Cu 64.5Zrmore » 35.5, the clusters representing the short-range order do not form an interconnected interpenetrating network in Al 90Sm 10, which has only marginal glass formability.« less

Building Higher-Order Markov Chain Models with EXCEL

ERIC Educational Resources Information Center

Ching, Wai-Ki; Fung, Eric S.; Ng, Michael K.

2004-01-01

Categorical data sequences occur in many applications such as forecasting, data mining and bioinformatics. In this note, we present higher-order Markov chain models for modelling categorical data sequences with an efficient algorithm for solving the model parameters. The algorithm can be implemented easily in a Microsoft EXCEL worksheet. We give a…

Space-Time Earthquake Rate Models for One-Year Hazard Forecasts in Oklahoma

NASA Astrophysics Data System (ADS)

Llenos, A. L.; Michael, A. J.

2017-12-01

The recent one-year seismic hazard assessments for natural and induced seismicity in the central and eastern US (CEUS) (Petersen et al., 2016, 2017) rely on earthquake rate models based on declustered catalogs (i.e., catalogs with foreshocks and aftershocks removed), as is common practice in probabilistic seismic hazard analysis. However, standard declustering can remove over 90% of some induced sequences in the CEUS. Some of these earthquakes may still be capable of causing damage or concern (Petersen et al., 2015, 2016). The choices of whether and how to decluster can lead to seismicity rate estimates that vary by up to factors of 10-20 (Llenos and Michael, AGU, 2016). Therefore, in order to improve the accuracy of hazard assessments, we are exploring ways to make forecasts based on full, rather than declustered, catalogs. We focus on Oklahoma, where earthquake rates began increasing in late 2009 mainly in central Oklahoma and ramped up substantially in 2013 with the expansion of seismicity into northern Oklahoma and southern Kansas. We develop earthquake rate models using the space-time Epidemic-Type Aftershock Sequence (ETAS) model (Ogata, JASA, 1988; Ogata, AISM, 1998; Zhuang et al., JASA, 2002), which characterizes both the background seismicity rate as well as aftershock triggering. We examine changes in the model parameters over time, focusing particularly on background rate, which reflects earthquakes that are triggered by external driving forces such as fluid injection rather than other earthquakes. After the model parameters are fit to the seismicity data from a given year, forecasts of the full catalog for the following year can then be made using a suite of 100,000 ETAS model simulations based on those parameters. To evaluate this approach, we develop pseudo-prospective yearly forecasts for Oklahoma from 2013-2016 and compare them with the observations using standard Collaboratory for the Study of Earthquake Predictability tests for consistency.

Kinetics of silicide formation over a wide range of heating rates spanning six orders of magnitude

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

Molina-Ruiz, Manel; Lopeandía, Aitor F.; Gonzalez-Silveira, Marta

Kinetic processes involving intermediate phase formation are often assumed to follow an Arrhenius temperature dependence. This behavior is usually inferred from limited data over narrow temperature intervals, where the exponential dependence is generally fully satisfied. However, direct evidence over wide temperature intervals is experimentally challenging and data are scarce. Here, we report a study of silicide formation between a 12 nm film of palladium and 15 nm of amorphous silicon in a wide range of heating rates, spanning six orders of magnitude, from 0.1 to 10{sup 5 }K/s, or equivalently more than 300 K of variation in reaction temperature. The calorimetric traces exhibit severalmore » distinct exothermic events related to interdiffusion, nucleation of Pd{sub 2}Si, crystallization of amorphous silicon, and vertical growth of Pd{sub 2}Si. Interestingly, the thickness of the initial nucleation layer depends on the heating rate revealing enhanced mass diffusion at the fastest heating rates during the initial stages of the reaction. In spite of this, the formation of the silicide strictly follows an Arrhenius temperature dependence over the whole temperature interval explored. A kinetic model is used to fit the calorimetric data over the complete heating rate range. Calorimetry is complemented by structural analysis through transmission electron microscopy and both standard and in-situ synchrotron X-ray diffraction.« less

A Reduced-Order Model for Efficient Simulation of Synthetic Jet Actuators

NASA Technical Reports Server (NTRS)

Yamaleev, Nail K.; Carpenter, Mark H.

2003-01-01

A new reduced-order model of multidimensional synthetic jet actuators that combines the accuracy and conservation properties of full numerical simulation methods with the efficiency of simplified zero-order models is proposed. The multidimensional actuator is simulated by solving the time-dependent compressible quasi-1-D Euler equations, while the diaphragm is modeled as a moving boundary. The governing equations are approximated with a fourth-order finite difference scheme on a moving mesh such that one of the mesh boundaries coincides with the diaphragm. The reduced-order model of the actuator has several advantages. In contrast to the 3-D models, this approach provides conservation of mass, momentum, and energy. Furthermore, the new method is computationally much more efficient than the multidimensional Navier-Stokes simulation of the actuator cavity flow, while providing practically the same accuracy in the exterior flowfield. The most distinctive feature of the present model is its ability to predict the resonance characteristics of synthetic jet actuators; this is not practical when using the 3-D models because of the computational cost involved. Numerical results demonstrating the accuracy of the new reduced-order model and its limitations are presented.

Earthquake models using rate and state friction and fast multipoles

NASA Astrophysics Data System (ADS)

Tullis, T.

2003-04-01

The most realistic current earthquake models employ laboratory-derived non-linear constitutive laws. These are the rate and state friction laws having both a non-linear viscous or direct effect and an evolution effect in which frictional resistance depends on time of stationary contact and has a memory of past slip velocity that fades with slip. The frictional resistance depends on the log of the slip velocity as well as the log of stationary hold time, and the fading memory involves an approximately exponential decay with slip. Due to the nonlinearly of these laws, analytical earthquake models are not attainable and numerical models are needed. The situation is even more difficult if true dynamic models are sought that deal with inertial forces and slip velocities on the order of 1 m/s as are observed during dynamic earthquake slip. Additional difficulties that exist if the dynamic slip phase of earthquakes is modeled arise from two sources. First, many physical processes might operate during dynamic slip, but they are only poorly understood, the relative importance of the processes is unknown, and the processes are even more nonlinear than those described by the current rate and state laws. Constitutive laws describing such behaviors are still being developed. Second, treatment of inertial forces and the influence that dynamic stresses from elastic waves may have on slip on the fault requires keeping track of the history of slip on remote parts of the fault as far into the past as it takes waves to travel from there. This places even more stringent requirements on computer time. Challenges for numerical modeling of complete earthquake cycles are that both time steps and mesh sizes must be small. Time steps must be milliseconds during dynamic slip, and yet models must represent earthquake cycles 100 years or more in length; methods using adaptive step sizes are essential. Element dimensions need to be on the order of meters, both to approximate continuum behavior

Atmospheric Turbulence Modeling for Aero Vehicles: Fractional Order Fits

NASA Technical Reports Server (NTRS)

Kopasakis, George

2015-01-01

Atmospheric turbulence models are necessary for the design of both inlet/engine and flight controls, as well as for studying coupling between the propulsion and the vehicle structural dynamics for supersonic vehicles. Models based on the Kolmogorov spectrum have been previously utilized to model atmospheric turbulence. In this paper, a more accurate model is developed in its representative fractional order form, typical of atmospheric disturbances. This is accomplished by first scaling the Kolmogorov spectral to convert them into finite energy von Karman forms and then by deriving an explicit fractional circuit-filter type analog for this model. This circuit model is utilized to develop a generalized formulation in frequency domain to approximate the fractional order with the products of first order transfer functions, which enables accurate time domain simulations. The objective of this work is as follows. Given the parameters describing the conditions of atmospheric disturbances, and utilizing the derived formulations, directly compute the transfer function poles and zeros describing these disturbances for acoustic velocity, temperature, pressure, and density. Time domain simulations of representative atmospheric turbulence can then be developed by utilizing these computed transfer functions together with the disturbance frequencies of interest.

Atmospheric Turbulence Modeling for Aero Vehicles: Fractional Order Fits

NASA Technical Reports Server (NTRS)

Kopasakis, George

2010-01-01

Atmospheric turbulence models are necessary for the design of both inlet/engine and flight controls, as well as for studying coupling between the propulsion and the vehicle structural dynamics for supersonic vehicles. Models based on the Kolmogorov spectrum have been previously utilized to model atmospheric turbulence. In this paper, a more accurate model is developed in its representative fractional order form, typical of atmospheric disturbances. This is accomplished by first scaling the Kolmogorov spectral to convert them into finite energy von Karman forms and then by deriving an explicit fractional circuit-filter type analog for this model. This circuit model is utilized to develop a generalized formulation in frequency domain to approximate the fractional order with the products of first order transfer functions, which enables accurate time domain simulations. The objective of this work is as follows. Given the parameters describing the conditions of atmospheric disturbances, and utilizing the derived formulations, directly compute the transfer function poles and zeros describing these disturbances for acoustic velocity, temperature, pressure, and density. Time domain simulations of representative atmospheric turbulence can then be developed by utilizing these computed transfer functions together with the disturbance frequencies of interest.

A contribution toward rational modeling of the pressure-strain-rate correlation

NASA Technical Reports Server (NTRS)

Lee, Moon Joo

1990-01-01

A novel method of obtaining an analytical expression of the 'linear part' of the pressure-strain-rate tensor in terms of the anisotropy tensor of the Reynolds stresses has been developed, where the coefficients of the seven independent tensor terms are functions of the invariants of the Reynolds-stress anisotropy. The coefficients are evaluated up to fourth order in the anisotropy of the Reynolds stresses to provide guidance for development of a turbulence model.

Terminology Modeling for an Enterprise Laboratory Orders Catalog

PubMed Central

Zhou, Li; Goldberg, Howard; Pabbathi, Deepika; Wright, Adam; Goldman, Debora S.; Van Putten, Cheryl; Barley, Amanda; Rocha, Roberto A.

2009-01-01

Laboratory test orders are used in a variety of clinical information systems at Partners HealthCare. At present, each site at Partners manages its own set of laboratory orders with locally defined codes. Our current plan is to implement an enterprise catalog, where laboratory test orders are mapped to reference terminologies and codes from different sites are mapped to each other. This paper describes the terminology modeling effort that preceded the implementation of the enterprise laboratory orders catalog. In particular, we present our experience in adapting HL7’s “Common Terminology Services 2 – Upper Level Class Model” as a terminology metamodel for guiding the development of fully specified laboratory orders and related services. PMID:20351950

Grain-Size Based Additivity Models for Scaling Multi-rate Uranyl Surface Complexation in Subsurface Sediments

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

Zhang, Xiaoying; Liu, Chongxuan; Hu, Bill X.

This study statistically analyzed a grain-size based additivity model that has been proposed to scale reaction rates and parameters from laboratory to field. The additivity model assumed that reaction properties in a sediment including surface area, reactive site concentration, reaction rate, and extent can be predicted from field-scale grain size distribution by linearly adding reaction properties for individual grain size fractions. This study focused on the statistical analysis of the additivity model with respect to reaction rate constants using multi-rate uranyl (U(VI)) surface complexation reactions in a contaminated sediment as an example. Experimental data of rate-limited U(VI) desorption in amore » stirred flow-cell reactor were used to estimate the statistical properties of multi-rate parameters for individual grain size fractions. The statistical properties of the rate constants for the individual grain size fractions were then used to analyze the statistical properties of the additivity model to predict rate-limited U(VI) desorption in the composite sediment, and to evaluate the relative importance of individual grain size fractions to the overall U(VI) desorption. The result indicated that the additivity model provided a good prediction of the U(VI) desorption in the composite sediment. However, the rate constants were not directly scalable using the additivity model, and U(VI) desorption in individual grain size fractions have to be simulated in order to apply the additivity model. An approximate additivity model for directly scaling rate constants was subsequently proposed and evaluated. The result found that the approximate model provided a good prediction of the experimental results within statistical uncertainty. This study also found that a gravel size fraction (2-8mm), which is often ignored in modeling U(VI) sorption and desorption, is statistically significant to the U(VI) desorption in the sediment.« less

A Bayesian Hierarchical Modeling Scheme for Estimating Erosion Rates Under Current Climate Conditions

NASA Astrophysics Data System (ADS)

Lowman, L.; Barros, A. P.

2014-12-01

Computational modeling of surface erosion processes is inherently difficult because of the four-dimensional nature of the problem and the multiple temporal and spatial scales that govern individual mechanisms. Landscapes are modified via surface and fluvial erosion and exhumation, each of which takes place over a range of time scales. Traditional field measurements of erosion/exhumation rates are scale dependent, often valid for a single point-wise location or averaging over large aerial extents and periods with intense and mild erosion. We present a method of remotely estimating erosion rates using a Bayesian hierarchical model based upon the stream power erosion law (SPEL). A Bayesian approach allows for estimating erosion rates using the deterministic relationship given by the SPEL and data on channel slopes and precipitation at the basin and sub-basin scale. The spatial scale associated with this framework is the elevation class, where each class is characterized by distinct morphologic behavior observed through different modes in the distribution of basin outlet elevations. Interestingly, the distributions of first-order outlets are similar in shape and extent to the distribution of precipitation events (i.e. individual storms) over a 14-year period between 1998-2011. We demonstrate an application of the Bayesian hierarchical modeling framework for five basins and one intermontane basin located in the central Andes between 5S and 20S. Using remotely sensed data of current annual precipitation rates from the Tropical Rainfall Measuring Mission (TRMM) and topography from a high resolution (3 arc-seconds) digital elevation map (DEM), our erosion rate estimates are consistent with decadal-scale estimates based on landslide mapping and sediment flux observations and 1-2 orders of magnitude larger than most millennial and million year timescale estimates from thermochronology and cosmogenic nuclides.

Order reduction for a model of marine bacteriophage evolution

NASA Astrophysics Data System (ADS)

Pagliarini, Silvia; Korobeinikov, Andrei

2017-02-01

A typical mechanistic model of viral evolution necessary includes several time scales which can differ by orders of magnitude. Such a diversity of time scales makes analysis of these models difficult. Reducing the order of a model is highly desirable when handling such a model. A typical approach applied to such slow-fast (or singularly perturbed) systems is the time scales separation technique. Constructing the so-called quasi-steady-state approximation is the usual first step in applying the technique. While this technique is commonly applied, in some cases its straightforward application can lead to unsatisfactory results. In this paper we construct the quasi-steady-state approximation for a model of evolution of marine bacteriophages based on the Beretta-Kuang model. We show that for this particular model the quasi-steady-state approximation is able to produce only qualitative but not quantitative fit.

On rate-state and Coulomb failure models

USGS Publications Warehouse

Gomberg, J.; Beeler, N.; Blanpied, M.

2000-01-01

We examine the predictions of Coulomb failure stress and rate-state frictional models. We study the change in failure time (clock advance) Δt due to stress step perturbations (i.e., coseismic static stress increases) added to "background" stressing at a constant rate (i.e., tectonic loading) at time t0. The predictability of Δt implies a predictable change in seismicity rate r(t)/r0, testable using earthquake catalogs, where r0 is the constant rate resulting from tectonic stressing. Models of r(t)/r0, consistent with general properties of aftershock sequences, must predict an Omori law seismicity decay rate, a sequence duration that is less than a few percent of the mainshock cycle time and a return directly to the background rate. A Coulomb model requires that a fault remains locked during loading, that failure occur instantaneously, and that Δt is independent of t0. These characteristics imply an instantaneous infinite seismicity rate increase of zero duration. Numerical calculations of r(t)/r0 for different state evolution laws show that aftershocks occur on faults extremely close to failure at the mainshock origin time, that these faults must be "Coulomb-like," and that the slip evolution law can be precluded. Real aftershock population characteristics also may constrain rate-state constitutive parameters; a may be lower than laboratory values, the stiffness may be high, and/or normal stress may be lower than lithostatic. We also compare Coulomb and rate-state models theoretically. Rate-state model fault behavior becomes more Coulomb-like as constitutive parameter a decreases relative to parameter b. This is because the slip initially decelerates, representing an initial healing of fault contacts. The deceleration is more pronounced for smaller a, more closely simulating a locked fault. Even when the rate-state Δt has Coulomb characteristics, its magnitude may differ by some constant dependent on b. In this case, a rate-state model behaves like a modified

The economic impact of state ordered avoided cost rates for photovoltaic generated electricity

NASA Astrophysics Data System (ADS)

Bottaro, D.; Wheatley, N. J.

Various methods the states have devised to implement federal policy regarding the Public Utility Regulatory Policies Act (PURPA) of 1978, which requires that utilities pay their full 'avoided costs' to small power producers for the energy and capacity provided, are examined. The actions of several states are compared with rates estimated using utility expansion and rate-setting models, and the potential break-even capital costs of a photovoltaic system are estimated using models which calculate photovoltaic worth. The potential for the development of photovoltaics has been increased by the PURPA regulations more from the guarantee of utility purchase of photovoltaic power than from the high buy-back rates paid. The buy-back rate is high partly because of the surprisingly high effective capacity of photovoltaic systems in some locations.

Parameterized reduced-order models using hyper-dual numbers.

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

Fike, Jeffrey A.; Brake, Matthew Robert

2013-10-01

The goal of most computational simulations is to accurately predict the behavior of a real, physical system. Accurate predictions often require very computationally expensive analyses and so reduced order models (ROMs) are commonly used. ROMs aim to reduce the computational cost of the simulations while still providing accurate results by including all of the salient physics of the real system in the ROM. However, real, physical systems often deviate from the idealized models used in simulations due to variations in manufacturing or other factors. One approach to this issue is to create a parameterized model in order to characterize themore » effect of perturbations from the nominal model on the behavior of the system. This report presents a methodology for developing parameterized ROMs, which is based on Craig-Bampton component mode synthesis and the use of hyper-dual numbers to calculate the derivatives necessary for the parameterization.« less

Low order physical models of vertical axis wind turbines

NASA Astrophysics Data System (ADS)

Craig, Anna; Dabiri, John; Koseff, Jeffrey

2016-11-01

In order to examine the ability of low-order physical models of vertical axis wind turbines to accurately reproduce key flow characteristics, experiments were conducted on rotating turbine models, rotating solid cylinders, and stationary porous flat plates (of both uniform and non-uniform porosities). From examination of the patterns of mean flow, the wake turbulence spectra, and several quantitative metrics, it was concluded that the rotating cylinders represent a reasonably accurate analog for the rotating turbines. In contrast, from examination of the patterns of mean flow, it was found that the porous flat plates represent only a limited analog for rotating turbines (for the parameters examined). These findings have implications for both laboratory experiments and numerical simulations, which have previously used analogous low order models in order to reduce experimental/computational costs. NSF GRF and SGF to A.C; ONR N000141211047 and the Gordon and Betty Moore Foundation Grant GBMF2645 to J.D.; and the Bob and Norma Street Environmental Fluid Mechanics Laboratory at Stanford University.

A Mathematical Modelling Approach to One-Day Cricket Batting Orders

PubMed Central

Bukiet, Bruce; Ovens, Matthews

2006-01-01

While scoring strategies and player performance in cricket have been studied, there has been little published work about the influence of batting order with respect to One-Day cricket. We apply a mathematical modelling approach to compute efficiently the expected performance (runs distribution) of a cricket batting order in an innings. Among other applications, our method enables one to solve for the probability of one team beating another or to find the optimal batting order for a set of 11 players. The influence of defence and bowling ability can be taken into account in a straightforward manner. In this presentation, we outline how we develop our Markov Chain approach to studying the progress of runs for a batting order of non- identical players along the lines of work in baseball modelling by Bukiet et al., 1997. We describe the issues that arise in applying such methods to cricket, discuss ideas for addressing these difficulties and note limitations on modelling batting order for One-Day cricket. By performing our analysis on a selected subset of the possible batting orders, we apply the model to quantify the influence of batting order in a game of One Day cricket using available real-world data for current players. Key Points Batting order does effect the expected runs distribution in one-day cricket. One-day cricket has fewer data points than baseball, thus extreme values have greater effect on estimated probabilities. Dismissals rare and probabilities very small by comparison to baseball. Probability distribution for lower order batsmen is potentially skewed due to increased risk taking. Full enumeration of all possible line-ups is impractical using a single average computer. PMID:24357943

A mathematical modelling approach to one-day cricket batting orders.

PubMed

Bukiet, Bruce; Ovens, Matthews

2006-01-01

While scoring strategies and player performance in cricket have been studied, there has been little published work about the influence of batting order with respect to One-Day cricket. We apply a mathematical modelling approach to compute efficiently the expected performance (runs distribution) of a cricket batting order in an innings. Among other applications, our method enables one to solve for the probability of one team beating another or to find the optimal batting order for a set of 11 players. The influence of defence and bowling ability can be taken into account in a straightforward manner. In this presentation, we outline how we develop our Markov Chain approach to studying the progress of runs for a batting order of non- identical players along the lines of work in baseball modelling by Bukiet et al., 1997. We describe the issues that arise in applying such methods to cricket, discuss ideas for addressing these difficulties and note limitations on modelling batting order for One-Day cricket. By performing our analysis on a selected subset of the possible batting orders, we apply the model to quantify the influence of batting order in a game of One Day cricket using available real-world data for current players. Key PointsBatting order does effect the expected runs distribution in one-day cricket.One-day cricket has fewer data points than baseball, thus extreme values have greater effect on estimated probabilities.Dismissals rare and probabilities very small by comparison to baseball.Probability distribution for lower order batsmen is potentially skewed due to increased risk taking.Full enumeration of all possible line-ups is impractical using a single average computer.

Modeling of the reactant conversion rate in a turbulent shear flow

NASA Technical Reports Server (NTRS)

Frankel, S. H.; Madnia, C. K.; Givi, P.

1992-01-01

Results are presented of direct numerical simulations (DNS) of spatially developing shear flows under the influence of infinitely fast chemical reactions of the type A + B yields Products. The simulation results are used to construct the compositional structure of the scalar field in a statistical manner. The results of this statistical analysis indicate that the use of a Beta density for the probability density function (PDF) of an appropriate Shvab-Zeldovich mixture fraction provides a very good estimate of the limiting bounds of the reactant conversion rate within the shear layer. This provides a strong justification for the implementation of this density in practical modeling of non-homogeneous turbulent reacting flows. However, the validity of the model cannot be generalized for predictions of higher order statistical quantities. A closed form analytical expression is presented for predicting the maximum rate of reactant conversion in non-homogeneous reacting turbulence.

Ordering policy for stock-dependent demand rate under progressive payment scheme: a comment

NASA Astrophysics Data System (ADS)

Glock, Christoph H.; Ries, Jörg M.; Schwindl, Kurt

2015-04-01

In a recent paper, Soni and Shah developed a model for finding the optimal ordering policy for a retailer facing stock-dependent demand and a supplier offering a progressive payment scheme. In this comment, we correct several errors in the formulation of the models of Soni and Shah and modify some assumptions to increase the model's applicability. Numerical examples illustrate the benefits of our modifications.

Cooling rate dependence of structural order in Ni62Nb38 metallic glass

NASA Astrophysics Data System (ADS)

Wen, Tongqi; Sun, Yang; Ye, Beilin; Tang, Ling; Yang, Zejin; Ho, Kai-Ming; Wang, Cai-Zhuang; Wang, Nan

2018-01-01

Molecular dynamics (MD) simulations are performed to study the structure of Ni62Nb38 bulk metallic glass at the atomistic level. Structural analysis based on the cluster alignment method is carried out and a new Ni-centered distorted-icosahedra (DISICO) motif is excavated. We show that the short-range order and medium-range order in the glass are enhanced with lower cooling rate. Almost 50% of the clusters around the Ni atoms in the well-annealed Ni62Nb38 glass sample from our MD simulations can be classified as DISICO. It is revealed that the structural distortion with respect to the perfect icosahedra is driven by chemical ordering in the distorted region of the DISICO motif. The relationship between the structure, energy, and dynamics in this glass-forming alloy during the cooling and annealing processes is also established.

Sensitivity of mineral dissolution rates to physical weathering : A modeling approach

NASA Astrophysics Data System (ADS)

Opolot, Emmanuel; Finke, Peter

2015-04-01

There is continued interest on accurate estimation of natural weathering rates owing to their importance in soil formation, nutrient cycling, estimation of acidification in soils, rivers and lakes, and in understanding the role of silicate weathering in carbon sequestration. At the same time a challenge does exist to reconcile discrepancies between laboratory-determined weathering rates and natural weathering rates. Studies have consistently reported laboratory rates to be in orders of magnitude faster than the natural weathering rates (White, 2009). These discrepancies have mainly been attributed to (i) changes in fluid composition (ii) changes in primary mineral surfaces (reactive sites) and (iii) the formation of secondary phases; that could slow natural weathering rates. It is indeed difficult to measure the interactive effect of the intrinsic factors (e.g. mineral composition, surface area) and extrinsic factors (e.g. solution composition, climate, bioturbation) occurring at the natural setting, in the laboratory experiments. A modeling approach could be useful in this case. A number of geochemical models (e.g. PHREEQC, EQ3/EQ6) already exist and are capable of estimating mineral dissolution / precipitation rates as a function of time and mineral mass. However most of these approaches assume a constant surface area in a given volume of water (White, 2009). This assumption may become invalid especially at long time scales. One of the widely used weathering models is the PROFILE model (Sverdrup and Warfvinge, 1993). The PROFILE model takes into account the mineral composition, solution composition and surface area in determining dissolution / precipitation rates. However there is less coupling with other processes (e.g. physical weathering, clay migration, bioturbation) which could directly or indirectly influence dissolution / precipitation rates. We propose in this study a coupling between chemical weathering mechanism (defined as a function of reactive area

The Ising model coupled to 2d orders

NASA Astrophysics Data System (ADS)

Glaser, Lisa

2018-04-01

In this article we make first steps in coupling matter to causal set theory in the path integral. We explore the case of the Ising model coupled to the 2d discrete Einstein Hilbert action, restricted to the 2d orders. We probe the phase diagram in terms of the Wick rotation parameter β and the Ising coupling j and find that the matter and the causal sets together give rise to an interesting phase structure. The couplings give rise to five different phases. The causal sets take on random or crystalline characteristics as described in Surya (2012 Class. Quantum Grav. 29 132001) and the Ising model can be correlated or uncorrelated on the random orders and correlated, uncorrelated or anti-correlated on the crystalline orders. We find that at least one new phase transition arises, in which the Ising spins push the causal set into the crystalline phase.

Higher-order QCD predictions for dark matter production at the LHC in simplified models with s-channel mediators.

PubMed

Backović, Mihailo; Krämer, Michael; Maltoni, Fabio; Martini, Antony; Mawatari, Kentarou; Pellen, Mathieu

Weakly interacting dark matter particles can be pair-produced at colliders and detected through signatures featuring missing energy in association with either QCD/EW radiation or heavy quarks. In order to constrain the mass and the couplings to standard model particles, accurate and precise predictions for production cross sections and distributions are of prime importance. In this work, we consider various simplified models with s -channel mediators. We implement such models in the FeynRules/MadGraph5_aMC@NLO framework, which allows to include higher-order QCD corrections in realistic simulations and to study their effect systematically. As a first phenomenological application, we present predictions for dark matter production in association with jets and with a top-quark pair at the LHC, at next-to-leading order accuracy in QCD, including matching/merging to parton showers. Our study shows that higher-order QCD corrections to dark matter production via s -channel mediators have a significant impact not only on total production rates, but also on shapes of distributions. We also show that the inclusion of next-to-leading order effects results in a sizeable reduction of the theoretical uncertainties.

Generalized modeling of the fractional-order memcapacitor and its character analysis

NASA Astrophysics Data System (ADS)

Guo, Zhang; Si, Gangquan; Diao, Lijie; Jia, Lixin; Zhang, Yanbin

2018-06-01

Memcapacitor is a new type of memory device generalized from the memristor. This paper proposes a generalized fractional-order memcapacitor model by introducing the fractional calculus into the model. The generalized formulas are studied and the two fractional-order parameter α, β are introduced where α mostly affects the fractional calculus value of charge q within the generalized Ohm's law and β generalizes the state equation which simulates the physical mechanism of a memcapacitor into the fractional sense. This model will be reduced to the conventional memcapacitor as α = 1 , β = 0 and to the conventional memristor as α = 0 , β = 1 . Then the numerical analysis of the fractional-order memcapacitor is studied. And the characteristics and output behaviors of the fractional-order memcapacitor applied with sinusoidal charge are derived. The analysis results have shown that there are four basic v - q and v - i curve patterns when the fractional order α, β respectively equal to 0 or 1, moreover all v - q and v - i curves of the other fractional-order models are transition curves between the four basic patterns.

Latent Partially Ordered Classification Models and Normal Mixtures

ERIC Educational Resources Information Center

Tatsuoka, Curtis; Varadi, Ferenc; Jaeger, Judith

2013-01-01

Latent partially ordered sets (posets) can be employed in modeling cognitive functioning, such as in the analysis of neuropsychological (NP) and educational test data. Posets are cognitively diagnostic in the sense that classification states in these models are associated with detailed profiles of cognitive functioning. These profiles allow for…

Kinetic rate laws as derived from order parameter theory I: Theoretical concepts

NASA Astrophysics Data System (ADS)

Salje, Ekhard

1988-03-01

A theoretical concept is outlined, which links the kinetics of structural transformations with thermodynamic theories of structural phase transitions. Starting from Landau theory and Markovian processes, the general rate laws for crystals with long correlation lengths are derived. The rate laws in Ginzburg-Landau theory are 269_2004_Article_BF00311038_TeX2GIFE1.gif 1{text{n }}Δ Q - 1{text{n }}fleft( Q right) ∝ - t/tau {text{ for }}T ≪ T_c {text{ and }}T ≫ T_c and Q 2∝ for T ≈ T c . The physical meaning of the time constant τ and the correction term f( Q) are explained. Fluctuations of the order parameter lead to damping behaviour with explicit dependence on the wavelength of the fluctuation wave and modulation-dependent variations of the lattice strain. Lattice relaxations and activation processes are discussed. Typical rate laws are found to follow 269_2004_Article_BF00311038_TeX2GIFE2.gif begin{gathered} ln Δ Q = rlnΔ t, \\ lnQ/Q + {1\\varepsilon }/{2k_B T}left( {Q^2 - Q_0^2 } right) = {Δ t}/{tau *} \\ which leads for short time intervals to a linear rate law 269_2004_Article_BF00311038_TeX2GIFE3.gif Δ Q ∝ Δ t It is shown that linear terms in the Landau potential are equivalent to a logarithmic decay of the excess entropy Δ S ∝ ln Δ t which is also expected to be the dominant rate law in field-induced pseudo-spin glasses: 269_2004_Article_BF00311038_TeX2GIFE4.gif Δ Q ∝ 1{text{n }}Δ t{text{ and }}1{text{n}}left( {Δ {text{Q}} \\cdot Δ {text{t}}} right) = A{text{ }}Δ t + B Fluctuations lead to spatially heterogeneous distributions of the order parameter. A two phase field is found in this case where the nucleation energy is overcome by fluctuation processes. Random fields, arising, for example, from lattice imperfections, lead also to spacially inhomogeneous material. The dominant microstructure is the lattice modulation mostly in the form of a cross hatched pattern (tweed) but also in the form of incommensurate modulations.

The Meaning of Higher-Order Factors in Reflective-Measurement Models

ERIC Educational Resources Information Center

Eid, Michael; Koch, Tobias

2014-01-01

Higher-order factor analysis is a widely used approach for analyzing the structure of a multidimensional test. Whenever first-order factors are correlated researchers are tempted to apply a higher-order factor model. But is this reasonable? What do the higher-order factors measure? What is their meaning? Willoughby, Holochwost, Blanton, and Blair…

An "Emergent Model" for Rate of Change

ERIC Educational Resources Information Center

Herbert, Sandra; Pierce, Robyn

2008-01-01

Does speed provide a "model for" rate of change in other contexts? Does JavaMathWorlds (JMW), animated simulation software, assist in the development of the "model for" rate of change? This project investigates the transference of understandings of rate gained in a motion context to a non-motion context. Students were 27 14-15 year old students at…

Fractional Order Modeling of Atmospheric Turbulence - A More Accurate Modeling Methodology for Aero Vehicles

NASA Technical Reports Server (NTRS)

Kopasakis, George

2014-01-01

The presentation covers a recently developed methodology to model atmospheric turbulence as disturbances for aero vehicle gust loads and for controls development like flutter and inlet shock position. The approach models atmospheric turbulence in their natural fractional order form, which provides for more accuracy compared to traditional methods like the Dryden model, especially for high speed vehicle. The presentation provides a historical background on atmospheric turbulence modeling and the approaches utilized for air vehicles. This is followed by the motivation and the methodology utilized to develop the atmospheric turbulence fractional order modeling approach. Some examples covering the application of this method are also provided, followed by concluding remarks.

Cooling rate dependence of structural order in Ni 62 Nb 38 metallic glass

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

Wen, Tongqi; Sun, Yang; Ye, Beilin

In this article, molecular dynamics (MD) simulations are performed to study the structure of Ni 62Nb 38 bulk metallic glass at the atomistic level. Structural analysis based on the cluster alignment method is carried out and a new Ni-centered distorted-icosahedra (DISICO) motif is excavated. We show that the short-range order and medium-range order in the glass are enhanced with lower cooling rate. Almost 50% of the clusters around the Ni atoms in the well-annealed Ni 62Nb 38 glass sample from our MD simulations can be classified as DISICO. It is revealed that the structural distortion with respect to the perfectmore » icosahedra is driven by chemical ordering in the distorted region of the DISICO motif. The relationship between the structure, energy, and dynamics in this glass-forming alloy during the cooling and annealing processes is also established.« less

Cooling rate dependence of structural order in Ni 62 Nb 38 metallic glass

DOE PAGES

Wen, Tongqi; Sun, Yang; Ye, Beilin; ...

2018-01-31

In this article, molecular dynamics (MD) simulations are performed to study the structure of Ni 62Nb 38 bulk metallic glass at the atomistic level. Structural analysis based on the cluster alignment method is carried out and a new Ni-centered distorted-icosahedra (DISICO) motif is excavated. We show that the short-range order and medium-range order in the glass are enhanced with lower cooling rate. Almost 50% of the clusters around the Ni atoms in the well-annealed Ni 62Nb 38 glass sample from our MD simulations can be classified as DISICO. It is revealed that the structural distortion with respect to the perfectmore » icosahedra is driven by chemical ordering in the distorted region of the DISICO motif. The relationship between the structure, energy, and dynamics in this glass-forming alloy during the cooling and annealing processes is also established.« less

On Local Homogeneity and Stochastically Ordered Mixed Rasch Models

ERIC Educational Resources Information Center

Kreiner, Svend; Hansen, Mogens; Hansen, Carsten Rosenberg

2006-01-01

Mixed Rasch models add latent classes to conventional Rasch models, assuming that the Rasch model applies within each class and that relative difficulties of items are different in two or more latent classes. This article considers a family of stochastically ordered mixed Rasch models, with ordinal latent classes characterized by increasing total…

Stabilized high-order Galerkin methods based on a parameter-free dynamic SGS model for LES

NASA Astrophysics Data System (ADS)

Marras, Simone; Nazarov, Murtazo; Giraldo, Francis X.

2015-11-01

The high order spectral element approximation of the Euler equations is stabilized via a dynamic sub-grid scale model (Dyn-SGS). This model was originally designed for linear finite elements to solve compressible flows at large Mach numbers. We extend its application to high-order spectral elements to solve the Euler equations of low Mach number stratified flows. The major justification of this work is twofold: stabilization and large eddy simulation are achieved via one scheme only. Because the diffusion coefficients of the regularization stresses obtained via Dyn-SGS are residual-based, the effect of the artificial diffusion is minimal in the regions where the solution is smooth. The direct consequence is that the nominal convergence rate of the high-order solution of smooth problems is not degraded. To our knowledge, this is the first application in atmospheric modeling of a spectral element model stabilized by an eddy viscosity scheme that, by construction, may fulfill stabilization requirements, can model turbulence via LES, and is completely free of a user-tunable parameter. From its derivation, it will be immediately clear that Dyn-SGS is independent of the numerical method; it could be implemented in a discontinuous Galerkin, finite volume, or other environments alike. Preliminary discontinuous Galerkin results are reported as well. The straightforward extension to non-linear scalar problems is also described. A suite of 1D, 2D, and 3D test cases is used to assess the method, with some comparison against the results obtained with the most known Lilly-Smagorinsky SGS model.

Genetic Algorithm-Based Model Order Reduction of Aeroservoelastic Systems with Consistant States

NASA Technical Reports Server (NTRS)

Zhu, Jin; Wang, Yi; Pant, Kapil; Suh, Peter M.; Brenner, Martin J.

2017-01-01

This paper presents a model order reduction framework to construct linear parameter-varying reduced-order models of flexible aircraft for aeroservoelasticity analysis and control synthesis in broad two-dimensional flight parameter space. Genetic algorithms are used to automatically determine physical states for reduction and to generate reduced-order models at grid points within parameter space while minimizing the trial-and-error process. In addition, balanced truncation for unstable systems is used in conjunction with the congruence transformation technique to achieve locally optimal realization and weak fulfillment of state consistency across the entire parameter space. Therefore, aeroservoelasticity reduced-order models at any flight condition can be obtained simply through model interpolation. The methodology is applied to the pitch-plant model of the X-56A Multi-Use Technology Testbed currently being tested at NASA Armstrong Flight Research Center for flutter suppression and gust load alleviation. The present studies indicate that the reduced-order model with more than 12× reduction in the number of states relative to the original model is able to accurately predict system response among all input-output channels. The genetic-algorithm-guided approach exceeds manual and empirical state selection in terms of efficiency and accuracy. The interpolated aeroservoelasticity reduced order models exhibit smooth pole transition and continuously varying gains along a set of prescribed flight conditions, which verifies consistent state representation obtained by congruence transformation. The present model order reduction framework can be used by control engineers for robust aeroservoelasticity controller synthesis and novel vehicle design.

Model Following and High Order Augmentation for Rotorcraft Control, Applied via Partial Authority

NASA Astrophysics Data System (ADS)

Spires, James Michael

This dissertation consists of two main studies, a few small studies, and design documentation, all aimed at improving rotorcraft control by employing multi-input multi-output (MIMO) command-modelfollowing control as a baseline, together with a selectable (and de-selectable) MIMO high order compensator that augments the baseline. Two methods of MIMO command-model-following control design are compared for rotorcraft flight control. The first, Explicit Model Following (EMF), employs SISO inverse plants with a dynamic decoupling matrix, which is a purely feed-forward approach to inverting the plant. The second is Dynamic Inversion (DI), which involves both feed-forward and feedback path elements to invert the plant. The EMF design is purely linear, while the DI design has some nonlinear elements in vertical rate control. For each of these methods, an architecture is presented that provides angular rate model-following with selectable vertical rate model-following. Implementation challenges of both EMF and DI are covered, and methods of dealing with them are presented. These two MIMO model-following approaches are evaluated regarding (1) fidelity to the command model, and (2) turbulence rejection. Both are found to provide good tracking of commands and reduction of cross coupling. Next, an architecture and design methodology for high order compensator (HOC) augmentation of a baseline controller for rotorcraft is presented. With this architecture, the HOC compensator is selectable and can easily be authority-limited, which might ease certification. Also, the plant for this augmentative MIMO compensator design is a stabilized helicopter system, so good flight test data could be safely gathered for more accurate plant identification. The design methodology is carried out twice on an example helicopter model, once with turbulence rejection as the objective, and once with the additional objective of closely following pilot commands. The turbulence rejection HOC is feedback

The Birth Order Puzzle.

ERIC Educational Resources Information Center

Zajonc, R. B.; And Others

1979-01-01

Discusses the controversy of the relationship between birth order and intellectual performance through a detailed evaluation of the confluence model which assumes that the rate of intellectual growth is a function of the intellectual environment within the family and associated with the special circumstances of last children. (CM)

Lattice Boltzmann model for high-order nonlinear partial differential equations

NASA Astrophysics Data System (ADS)

Chai, Zhenhua; He, Nanzhong; Guo, Zhaoli; Shi, Baochang

2018-01-01

In this paper, a general lattice Boltzmann (LB) model is proposed for the high-order nonlinear partial differential equation with the form ∂tϕ +∑k=1mαk∂xkΠk(ϕ ) =0 (1 ≤k ≤m ≤6 ), αk are constant coefficients, Πk(ϕ ) are some known differential functions of ϕ . As some special cases of the high-order nonlinear partial differential equation, the classical (m)KdV equation, KdV-Burgers equation, K (n ,n ) -Burgers equation, Kuramoto-Sivashinsky equation, and Kawahara equation can be solved by the present LB model. Compared to the available LB models, the most distinct characteristic of the present model is to introduce some suitable auxiliary moments such that the correct moments of equilibrium distribution function can be achieved. In addition, we also conducted a detailed Chapman-Enskog analysis, and found that the high-order nonlinear partial differential equation can be correctly recovered from the proposed LB model. Finally, a large number of simulations are performed, and it is found that the numerical results agree with the analytical solutions, and usually the present model is also more accurate than the existing LB models [H. Lai and C. Ma, Sci. China Ser. G 52, 1053 (2009), 10.1007/s11433-009-0149-3; H. Lai and C. Ma, Phys. A (Amsterdam) 388, 1405 (2009), 10.1016/j.physa.2009.01.005] for high-order nonlinear partial differential equations.

Lattice Boltzmann model for high-order nonlinear partial differential equations.

PubMed

Chai, Zhenhua; He, Nanzhong; Guo, Zhaoli; Shi, Baochang

2018-01-01

In this paper, a general lattice Boltzmann (LB) model is proposed for the high-order nonlinear partial differential equation with the form ∂_{t}ϕ+∑_{k=1}^{m}α_{k}∂_{x}^{k}Π_{k}(ϕ)=0 (1≤k≤m≤6), α_{k} are constant coefficients, Π_{k}(ϕ) are some known differential functions of ϕ. As some special cases of the high-order nonlinear partial differential equation, the classical (m)KdV equation, KdV-Burgers equation, K(n,n)-Burgers equation, Kuramoto-Sivashinsky equation, and Kawahara equation can be solved by the present LB model. Compared to the available LB models, the most distinct characteristic of the present model is to introduce some suitable auxiliary moments such that the correct moments of equilibrium distribution function can be achieved. In addition, we also conducted a detailed Chapman-Enskog analysis, and found that the high-order nonlinear partial differential equation can be correctly recovered from the proposed LB model. Finally, a large number of simulations are performed, and it is found that the numerical results agree with the analytical solutions, and usually the present model is also more accurate than the existing LB models [H. Lai and C. Ma, Sci. China Ser. G 52, 1053 (2009)1672-179910.1007/s11433-009-0149-3; H. Lai and C. Ma, Phys. A (Amsterdam) 388, 1405 (2009)PHYADX0378-437110.1016/j.physa.2009.01.005] for high-order nonlinear partial differential equations.

Regression-based reduced-order models to predict transient thermal output for enhanced geothermal systems

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

Mudunuru, Maruti Kumar; Karra, Satish; Harp, Dylan Robert

Reduced-order modeling is a promising approach, as many phenomena can be described by a few parameters/mechanisms. An advantage and attractive aspect of a reduced-order model is that it is computational inexpensive to evaluate when compared to running a high-fidelity numerical simulation. A reduced-order model takes couple of seconds to run on a laptop while a high-fidelity simulation may take couple of hours to run on a high-performance computing cluster. The goal of this paper is to assess the utility of regression-based reduced-order models (ROMs) developed from high-fidelity numerical simulations for predicting transient thermal power output for an enhanced geothermal reservoirmore » while explicitly accounting for uncertainties in the subsurface system and site-specific details. Numerical simulations are performed based on equally spaced values in the specified range of model parameters. Key sensitive parameters are then identified from these simulations, which are fracture zone permeability, well/skin factor, bottom hole pressure, and injection flow rate. We found the fracture zone permeability to be the most sensitive parameter. The fracture zone permeability along with time, are used to build regression-based ROMs for the thermal power output. The ROMs are trained and validated using detailed physics-based numerical simulations. Finally, predictions from the ROMs are then compared with field data. We propose three different ROMs with different levels of model parsimony, each describing key and essential features of the power production curves. The coefficients in the proposed regression-based ROMs are developed by minimizing a non-linear least-squares misfit function using the Levenberg–Marquardt algorithm. The misfit function is based on the difference between numerical simulation data and reduced-order model. ROM-1 is constructed based on polynomials up to fourth order. ROM-1 is able to accurately reproduce the power output of numerical simulations

Regression-based reduced-order models to predict transient thermal output for enhanced geothermal systems

DOE PAGES

Mudunuru, Maruti Kumar; Karra, Satish; Harp, Dylan Robert; ...

2017-07-10

Reduced-order modeling is a promising approach, as many phenomena can be described by a few parameters/mechanisms. An advantage and attractive aspect of a reduced-order model is that it is computational inexpensive to evaluate when compared to running a high-fidelity numerical simulation. A reduced-order model takes couple of seconds to run on a laptop while a high-fidelity simulation may take couple of hours to run on a high-performance computing cluster. The goal of this paper is to assess the utility of regression-based reduced-order models (ROMs) developed from high-fidelity numerical simulations for predicting transient thermal power output for an enhanced geothermal reservoirmore » while explicitly accounting for uncertainties in the subsurface system and site-specific details. Numerical simulations are performed based on equally spaced values in the specified range of model parameters. Key sensitive parameters are then identified from these simulations, which are fracture zone permeability, well/skin factor, bottom hole pressure, and injection flow rate. We found the fracture zone permeability to be the most sensitive parameter. The fracture zone permeability along with time, are used to build regression-based ROMs for the thermal power output. The ROMs are trained and validated using detailed physics-based numerical simulations. Finally, predictions from the ROMs are then compared with field data. We propose three different ROMs with different levels of model parsimony, each describing key and essential features of the power production curves. The coefficients in the proposed regression-based ROMs are developed by minimizing a non-linear least-squares misfit function using the Levenberg–Marquardt algorithm. The misfit function is based on the difference between numerical simulation data and reduced-order model. ROM-1 is constructed based on polynomials up to fourth order. ROM-1 is able to accurately reproduce the power output of numerical simulations

Reduced-order modeling of soft robots

PubMed Central

Chenevier, Jean; González, David; Aguado, J. Vicente; Chinesta, Francisco

2018-01-01

We present a general strategy for the modeling and simulation-based control of soft robots. Although the presented methodology is completely general, we restrict ourselves to the analysis of a model robot made of hyperelastic materials and actuated by cables or tendons. To comply with the stringent real-time constraints imposed by control algorithms, a reduced-order modeling strategy is proposed that allows to minimize the amount of online CPU cost. Instead, an offline training procedure is proposed that allows to determine a sort of response surface that characterizes the response of the robot. Contrarily to existing strategies, the proposed methodology allows for a fully non-linear modeling of the soft material in a hyperelastic setting as well as a fully non-linear kinematic description of the movement without any restriction nor simplifying assumption. Examples of different configurations of the robot were analyzed that show the appeal of the method. PMID:29470496

Critical comparison of several order-book models for stock-market fluctuations

NASA Astrophysics Data System (ADS)

Slanina, F.

2008-01-01

Far-from-equilibrium models of interacting particles in one dimension are used as a basis for modelling the stock-market fluctuations. Particle types and their positions are interpreted as buy and sel orders placed on a price axis in the order book. We revisit some modifications of well-known models, starting with the Bak-Paczuski-Shubik model. We look at the four decades old Stigler model and investigate its variants. One of them is the simplified version of the Genoa artificial market. The list of studied models is completed by the models of Maslov and Daniels et al. Generically, in all cases we compare the return distribution, absolute return autocorrelation and the value of the Hurst exponent. It turns out that none of the models reproduces satisfactorily all the empirical data, but the most promising candidates for further development are the Genoa artificial market and the Maslov model with moderate order evaporation.

Atmospheric Turbulence Modeling for Aerospace Vehicles: Fractional Order Fit

NASA Technical Reports Server (NTRS)

Kopasakis, George (Inventor)

2015-01-01

An improved model for simulating atmospheric disturbances is disclosed. A scale Kolmogorov spectral may be scaled to convert the Kolmogorov spectral into a finite energy von Karman spectral and a fractional order pole-zero transfer function (TF) may be derived from the von Karman spectral. Fractional order atmospheric turbulence may be approximated with an integer order pole-zero TF fit, and the approximation may be stored in memory.

Modeling the self-assembly of ordered nanoporous materials

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

Monson, Peter; Auerbach, Scott

This report describes progress on a collaborative project on the multiscale modeling of the assembly processes in the synthesis of nanoporous materials. Such materials are of enormous importance in modern technology with application in the chemical process industries, biomedicine and biotechnology as well as microelectronics. The project focuses on two important classes of materials: i) microporous crystalline materials, such as zeolites, and ii) ordered mesoporous materials. In the first case the pores are part of the crystalline structure, while in the second the structures are amorphous on the atomistic length scale but where surfactant templating gives rise to order onmore » the length scale of 2 - 20 nm. We have developed a modeling framework that encompasses both these kinds of materials. Our models focus on the assembly of corner sharing silica tetrahedra in the presence of structure directing agents. We emphasize a balance between sufficient realism in the models and computational tractibility given the complex many-body phenomena. We use both on-lattice and off-lattice models and the primary computational tools are Monte Carlo simulations with sampling techniques and ensembles appropriate to specific situations. Our modeling approach is the first to capture silica polymerization, nanopore crystallization, and mesopore formation through computer-simulated self assembly.« less

Modelling stock order flows with non-homogeneous intensities from high-frequency data

NASA Astrophysics Data System (ADS)

Gorshenin, Andrey K.; Korolev, Victor Yu.; Zeifman, Alexander I.; Shorgin, Sergey Ya.; Chertok, Andrey V.; Evstafyev, Artem I.; Korchagin, Alexander Yu.

2013-10-01

A micro-scale model is proposed for the evolution of such information system as the limit order book in financial markets. Within this model, the flows of orders (claims) are described by doubly stochastic Poisson processes taking account of the stochastic character of intensities of buy and sell orders that determine the price discovery mechanism. The proposed multiplicative model of stochastic intensities makes it possible to analyze the characteristics of the order flows as well as the instantaneous proportion of the forces of buyers and sellers, that is, the imbalance process, without modelling the external information background. The proposed model gives the opportunity to link the micro-scale (high-frequency) dynamics of the limit order book with the macro-scale models of stock price processes of the form of subordinated Wiener processes by means of limit theorems of probability theory and hence, to use the normal variance-mean mixture models of the corresponding heavy-tailed distributions. The approach can be useful in different areas with similar properties (e.g., in plasma physics).

Numerical modelling of landscape and sediment flux response to precipitation rate change

NASA Astrophysics Data System (ADS)

Armitage, John J.; Whittaker, Alexander C.; Zakari, Mustapha; Campforts, Benjamin

2018-02-01

Laboratory-scale experiments of erosion have demonstrated that landscapes have a natural (or intrinsic) response time to a change in precipitation rate. In the last few decades there has been growth in the development of numerical models that attempt to capture landscape evolution over long timescales. However, there is still an uncertainty regarding the validity of the basic assumptions of mass transport that are made in deriving these models. In this contribution we therefore return to a principal assumption of sediment transport within the mass balance for surface processes; we explore the sensitivity of the classic end-member landscape evolution models and the sediment fluxes they produce to a change in precipitation rates. One end-member model takes the mathematical form of a kinetic wave equation and is known as the stream power model, in which sediment is assumed to be transported immediately out of the model domain. The second end-member model is the transport model and it takes the form of a diffusion equation, assuming that the sediment flux is a function of the water flux and slope. We find that both of these end-member models have a response time that has a proportionality to the precipitation rate that follows a negative power law. However, for the stream power model the exponent on the water flux term must be less than one, and for the transport model the exponent must be greater than one, in order to match the observed concavity of natural systems. This difference in exponent means that the transport model generally responds more rapidly to an increase in precipitation rates, on the order of 105 years for post-perturbation sediment fluxes to return to within 50 % of their initial values, for theoretical landscapes with a scale of 100×100 km. Additionally from the same starting conditions, the amplitude of the sediment flux perturbation in the transport model is greater, with much larger sensitivity to catchment size. An important finding is that

Analytical Modeling of the High Strain Rate Deformation of Polymer Matrix Composites

NASA Technical Reports Server (NTRS)

Goldberg, Robert K.; Roberts, Gary D.; Gilat, Amos

2003-01-01

The results presented here are part of an ongoing research program to develop strain rate dependent deformation and failure models for the analysis of polymer matrix composites subject to high strain rate impact loads. State variable constitutive equations originally developed for metals have been modified in order to model the nonlinear, strain rate dependent deformation of polymeric matrix materials. To account for the effects of hydrostatic stresses, which are significant in polymers, the classical 5 plasticity theory definitions of effective stress and effective plastic strain are modified by applying variations of the Drucker-Prager yield criterion. To verify the revised formulation, the shear and tensile deformation of a representative toughened epoxy is analyzed across a wide range of strain rates (from quasi-static to high strain rates) and the results are compared to experimentally obtained values. For the analyzed polymers, both the tensile and shear stress-strain curves computed using the analytical model correlate well with values obtained through experimental tests. The polymer constitutive equations are implemented within a strength of materials based micromechanics method to predict the nonlinear, strain rate dependent deformation of polymer matrix composites. In the micromechanics, the unit cell is divided up into a number of independently analyzed slices, and laminate theory is then applied to obtain the effective deformation of the unit cell. The composite mechanics are verified by analyzing the deformation of a representative polymer matrix composite (composed using the representative polymer analyzed for the correlation of the polymer constitutive equations) for several fiber orientation angles across a variety of strain rates. The computed values compare favorably to experimentally obtained results.

Ability, Breadth, and Parsimony in Computational Models of Higher-Order Cognition

ERIC Educational Resources Information Center

Cassimatis, Nicholas L.; Bello, Paul; Langley, Pat

2008-01-01

Computational models will play an important role in our understanding of human higher-order cognition. How can a model's contribution to this goal be evaluated? This article argues that three important aspects of a model of higher-order cognition to evaluate are (a) its ability to reason, solve problems, converse, and learn as well as people do;…

Reduced order model of a blended wing body aircraft configuration

NASA Astrophysics Data System (ADS)

Stroscher, F.; Sika, Z.; Petersson, O.

2013-12-01

This paper describes the full development process of a numerical simulation model for the ACFA2020 (Active Control for Flexible 2020 Aircraft) blended wing body (BWB) configuration. Its requirements are the prediction of aeroelastic and flight dynamic response in time domain, with relatively small model order. Further, the model had to be parameterized with regard to multiple fuel filling conditions, as well as flight conditions. High efforts have been conducted in high-order aerodynamic analysis, for subsonic and transonic regime, by several project partners. The integration of the unsteady aerodynamic databases was one of the key issues in aeroelastic modeling.

Inventory model with two rates of production for deteriorating items with permissible delay in payments

NASA Astrophysics Data System (ADS)

Roy, Ajanta; Samanta, G. P.

2011-08-01

Goyal (1985) ['Economic Order Quantity Under Conditions of Permissible Delay in Payments', Journal of Operational research Society, 36, 35-38] assumed that unit selling price and unit purchasing price are equal. But in real-life the scenario is different. The purpose of this article is to reflect the real life problem by allowing unit selling price and purchasing price to be unequal. Our model is a continuous production control inventory model for deteriorating items in which two different rates of production are available. The results are illustrated with the help of a numerical example. We discuss the sensitivity of the solution together with the changes of the values of the parameters associated with the model. Our model may be applicable in many manufacturing planning situations where management practices for deterioration are stringent; e.g. the two-production rate will be more profitable than the one-production rate in the manufacture of cold, asthma and allergy medicine. Our proposed model might be applicable to develop a prototype advance planning system for those manufacturers to integrate the management science techniques into commercial planning.

Estimating distributions with increasing failure rate in an imperfect repair model.

PubMed

Kvam, Paul H; Singh, Harshinder; Whitaker, Lyn R

2002-03-01

A failed system is repaired minimally if after failure, it is restored to the working condition of an identical system of the same age. We extend the nonparametric maximum likelihood estimator (MLE) of a system's lifetime distribution function to test units that are known to have an increasing failure rate. Such items comprise a significant portion of working components in industry. The order-restricted MLE is shown to be consistent. Similar results hold for the Brown-Proschan imperfect repair model, which dictates that a failed component is repaired perfectly with some unknown probability, and is otherwise repaired minimally. The estimators derived are motivated and illustrated by failure data in the nuclear industry. Failure times for groups of emergency diesel generators and motor-driven pumps are analyzed using the order-restricted methods. The order-restricted estimators are consistent and show distinct differences from the ordinary MLEs. Simulation results suggest significant improvement in reliability estimation is available in many cases when component failure data exhibit the IFR property.

Stripe order in the underdoped region of the two-dimensional Hubbard model

NASA Astrophysics Data System (ADS)

Zheng, Bo-Xiao; Chung, Chia-Min; Corboz, Philippe; Ehlers, Georg; Qin, Ming-Pu; Noack, Reinhard M.; Shi, Hao; White, Steven R.; Zhang, Shiwei; Chan, Garnet Kin-Lic

2017-12-01

Competing inhomogeneous orders are a central feature of correlated electron materials, including the high-temperature superconductors. The two-dimensional Hubbard model serves as the canonical microscopic physical model for such systems. Multiple orders have been proposed in the underdoped part of the phase diagram, which corresponds to a regime of maximum numerical difficulty. By combining the latest numerical methods in exhaustive simulations, we uncover the ordering in the underdoped ground state. We find a stripe order that has a highly compressible wavelength on an energy scale of a few kelvin, with wavelength fluctuations coupled to pairing order. The favored filled stripe order is different from that seen in real materials. Our results demonstrate the power of modern numerical methods to solve microscopic models, even in challenging settings.

Modeling and analysis of fractional order DC-DC converter.

PubMed

Radwan, Ahmed G; Emira, Ahmed A; AbdelAty, Amr M; Azar, Ahmad Taher

2017-07-11

Due to the non-idealities of commercial inductors, the demand for a better model that accurately describe their dynamic response is elevated. So, the fractional order models of Buck, Boost and Buck-Boost DC-DC converters are presented in this paper. The detailed analysis is made for the two most common modes of converter operation: Continuous Conduction Mode (CCM) and Discontinuous Conduction Mode (DCM). Closed form time domain expressions are derived for inductor currents, voltage gain, average current, conduction time and power efficiency where the effect of the fractional order inductor is found to be strongly present. For example, the peak inductor current at steady state increases with decreasing the inductor order. Advanced Design Systems (ADS) circuit simulations are used to verify the derived formulas, where the fractional order inductor is simulated using Valsa Constant Phase Element (CPE) approximation and Generalized Impedance Converter (GIC). Different simulation results are introduced with good matching to the theoretical formulas for the three DC-DC converter topologies under different fractional orders. A comprehensive comparison with the recently published literature is presented to show the advantages and disadvantages of each approach. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

An order statistics approach to the halo model for galaxies

NASA Astrophysics Data System (ADS)

Paul, Niladri; Paranjape, Aseem; Sheth, Ravi K.

2017-04-01

We use the halo model to explore the implications of assuming that galaxy luminosities in groups are randomly drawn from an underlying luminosity function. We show that even the simplest of such order statistics models - one in which this luminosity function p(L) is universal - naturally produces a number of features associated with previous analyses based on the 'central plus Poisson satellites' hypothesis. These include the monotonic relation of mean central luminosity with halo mass, the lognormal distribution around this mean and the tight relation between the central and satellite mass scales. In stark contrast to observations of galaxy clustering; however, this model predicts no luminosity dependence of large-scale clustering. We then show that an extended version of this model, based on the order statistics of a halo mass dependent luminosity function p(L|m), is in much better agreement with the clustering data as well as satellite luminosities, but systematically underpredicts central luminosities. This brings into focus the idea that central galaxies constitute a distinct population that is affected by different physical processes than are the satellites. We model this physical difference as a statistical brightening of the central luminosities, over and above the order statistics prediction. The magnitude gap between the brightest and second brightest group galaxy is predicted as a by-product, and is also in good agreement with observations. We propose that this order statistics framework provides a useful language in which to compare the halo model for galaxies with more physically motivated galaxy formation models.

AN OVERVIEW OF REDUCED ORDER MODELING TECHNIQUES FOR SAFETY APPLICATIONS

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

Mandelli, D.; Alfonsi, A.; Talbot, P.

2016-10-01

The RISMC project is developing new advanced simulation-based tools to perform Computational Risk Analysis (CRA) for the existing fleet of U.S. nuclear power plants (NPPs). These tools numerically model not only the thermal-hydraulic behavior of the reactors primary and secondary systems, but also external event temporal evolution and component/system ageing. Thus, this is not only a multi-physics problem being addressed, but also a multi-scale problem (both spatial, µm-mm-m, and temporal, seconds-hours-years). As part of the RISMC CRA approach, a large amount of computationally-expensive simulation runs may be required. An important aspect is that even though computational power is growing, themore » overall computational cost of a RISMC analysis using brute-force methods may be not viable for certain cases. A solution that is being evaluated to assist the computational issue is the use of reduced order modeling techniques. During the FY2015, we investigated and applied reduced order modeling techniques to decrease the RISMC analysis computational cost by decreasing the number of simulation runs; for this analysis improvement we used surrogate models instead of the actual simulation codes. This article focuses on the use of reduced order modeling techniques that can be applied to RISMC analyses in order to generate, analyze, and visualize data. In particular, we focus on surrogate models that approximate the simulation results but in a much faster time (microseconds instead of hours/days).« less

Predicting Statistical Response and Extreme Events in Uncertainty Quantification through Reduced-Order Models

NASA Astrophysics Data System (ADS)

Qi, D.; Majda, A.

2017-12-01

A low-dimensional reduced-order statistical closure model is developed for quantifying the uncertainty in statistical sensitivity and intermittency in principal model directions with largest variability in high-dimensional turbulent system and turbulent transport models. Imperfect model sensitivity is improved through a recent mathematical strategy for calibrating model errors in a training phase, where information theory and linear statistical response theory are combined in a systematic fashion to achieve the optimal model performance. The idea in the reduced-order method is from a self-consistent mathematical framework for general systems with quadratic nonlinearity, where crucial high-order statistics are approximated by a systematic model calibration procedure. Model efficiency is improved through additional damping and noise corrections to replace the expensive energy-conserving nonlinear interactions. Model errors due to the imperfect nonlinear approximation are corrected by tuning the model parameters using linear response theory with an information metric in a training phase before prediction. A statistical energy principle is adopted to introduce a global scaling factor in characterizing the higher-order moments in a consistent way to improve model sensitivity. Stringent models of barotropic and baroclinic turbulence are used to display the feasibility of the reduced-order methods. Principal statistical responses in mean and variance can be captured by the reduced-order models with accuracy and efficiency. Besides, the reduced-order models are also used to capture crucial passive tracer field that is advected by the baroclinic turbulent flow. It is demonstrated that crucial principal statistical quantities like the tracer spectrum and fat-tails in the tracer probability density functions in the most important large scales can be captured efficiently with accuracy using the reduced-order tracer model in various dynamical regimes of the flow field with

Mixture of autoregressive modeling orders and its implication on single trial EEG classification

PubMed Central

Atyabi, Adham; Shic, Frederick; Naples, Adam

2016-01-01

Autoregressive (AR) models are of commonly utilized feature types in Electroencephalogram (EEG) studies due to offering better resolution, smoother spectra and being applicable to short segments of data. Identifying correct AR’s modeling order is an open challenge. Lower model orders poorly represent the signal while higher orders increase noise. Conventional methods for estimating modeling order includes Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC) and Final Prediction Error (FPE). This article assesses the hypothesis that appropriate mixture of multiple AR orders is likely to better represent the true signal compared to any single order. Better spectral representation of underlying EEG patterns can increase utility of AR features in Brain Computer Interface (BCI) systems by increasing timely & correctly responsiveness of such systems to operator’s thoughts. Two mechanisms of Evolutionary-based fusion and Ensemble-based mixture are utilized for identifying such appropriate mixture of modeling orders. The classification performance of the resultant AR-mixtures are assessed against several conventional methods utilized by the community including 1) A well-known set of commonly used orders suggested by the literature, 2) conventional order estimation approaches (e.g., AIC, BIC and FPE), 3) blind mixture of AR features originated from a range of well-known orders. Five datasets from BCI competition III that contain 2, 3 and 4 motor imagery tasks are considered for the assessment. The results indicate superiority of Ensemble-based modeling order mixture and evolutionary-based order fusion methods within all datasets. PMID:28740331

Modeling and prediction of relaxation of polar order in high-activity nonlinear optical polymers

NASA Astrophysics Data System (ADS)

Guenthner, Andrew J.; Lindsay, Geoffrey A.; Wright, Michael E.; Fallis, Stephen; Ashley, Paul R.; Sanghadasa, Mohan

2007-09-01

Mach-Zehnder optical modulators were fabricated using the CLD and FTC chromophores in polymer-on-silicon optical waveguides. Up to 17 months of oven-ageing stability are reported for the poled polymer films. Modulators containing an FTC-polyimide had the best over all aging performance. To model and extrapolate the ageing data, a relaxation correlation function attributed to A. K. Jonscher was compared to the well-established stretched exponential correlation function. Both models gave a good fit to the data. The Jonscher model predicted a slower relaxation rate in the out years. Analysis showed that collecting data for a longer period relative to the relaxation time was more important for generating useful predictions than the precision with which individual model parameters could be estimated. Thus from a practical standpoint, time-temperature superposition must be assumed in order to generate meaningful predictions. For this purpose, Arrhenius-type expressions were found to relate the model time constants to the ageing temperatures.

First-Order Parametric Model of Reflectance Spectra for Dyed Fabrics

DTIC Science & Technology

2016-02-19

Unclassified Unlimited 31 Daniel Aiken (202) 279-5293 Parametric modeling Inverse /direct analysis This report describes a first-order parametric model of...Appendix: Dielectric Response Functions for Dyes Obtained by Inverse Analysis ……………………………...…………………………………………………….19 1 First-Order Parametric...which provides for both their inverse and direct modeling1. The dyes considered contain spectral features that are of interest to the U.S. Navy for

Reduced order modeling and active flow control of an inlet duct

NASA Astrophysics Data System (ADS)

Ge, Xiaoqing

Many aerodynamic applications require the modeling of compressible flows in or around a body, e.g., the design of aircraft, inlet or exhaust duct, wind turbines, or tall buildings. Traditional methods use wind tunnel experiments and computational fluid dynamics (CFD) to investigate the spatial and temporal distribution of the flows. Although they provide a great deal of insight into the essential characteristics of the flow field, they are not suitable for control analysis and design due to the high physical/computational cost. Many model reduction methods have been studied to reduce the complexity of the flow model. There are two main approaches: linearization based input/output modeling and proper orthogonal decomposition (POD) based model reduction. The former captures mostly the local behavior near a steady state, which is suitable to model laminar flow dynamics. The latter obtains a reduced order model by projecting the governing equation onto an "optimal" subspace and is able to model complex nonlinear flow phenomena. In this research we investigate various model reduction approaches and compare them in flow modeling and control design. We propose an integrated model-based control methodology and apply it to the reduced order modeling and active flow control of compressible flows within a very aggressive (length to exit diameter ratio, L/D, of 1.5) inlet duct and its upstream contraction section. The approach systematically applies reduced order modeling, estimator design, sensor placement and control design to improve the aerodynamic performance. The main contribution of this work is the development of a hybrid model reduction approach that attempts to combine the best features of input/output model identification and POD method. We first identify a linear input/output model by using a subspace algorithm. We next project the difference between CFD response and the identified model response onto a set of POD basis. This trajectory is fit to a nonlinear

Testing higher-order Lagrangian perturbation theory against numerical simulations. 2: Hierarchical models

NASA Technical Reports Server (NTRS)

Melott, A. L.; Buchert, T.; Weib, A. G.

1995-01-01

We present results showing an improvement of the accuracy of perturbation theory as applied to cosmological structure formation for a useful range of scales. The Lagrangian theory of gravitational instability of Friedmann-Lemaitre cosmogonies is compared with numerical simulations. We study the dynamics of hierarchical models as a second step. In the first step we analyzed the performance of the Lagrangian schemes for pancake models, the difference being that in the latter models the initial power spectrum is truncated. This work probed the quasi-linear and weakly non-linear regimes. We here explore whether the results found for pancake models carry over to hierarchical models which are evolved deeply into the non-linear regime. We smooth the initial data by using a variety of filter types and filter scales in order to determine the optimal performance of the analytical models, as has been done for the 'Zel'dovich-approximation' - hereafter TZA - in previous work. We find that for spectra with negative power-index the second-order scheme performs considerably better than TZA in terms of statistics which probe the dynamics, and slightly better in terms of low-order statistics like the power-spectrum. However, in contrast to the results found for pancake models, where the higher-order schemes get worse than TZA at late non-linear stages and on small scales, we here find that the second-order model is as robust as TZA, retaining the improvement at later stages and on smaller scales. In view of these results we expect that the second-order truncated Lagrangian model is especially useful for the modelling of standard dark matter models such as Hot-, Cold-, and Mixed-Dark-Matter.

Generalized first-order kinetic model for biosolids decomposition and oxidation during hydrothermal treatment.

PubMed

Shanableh, A

2005-01-01

The main objective of this study was to develop generalized first-order kinetic models to represent hydrothermal decomposition and oxidation of biosolids within a wide range of temperatures (200-450 degrees C). A lumping approach was used in which oxidation of the various organic ingredients was characterized by the chemical oxygen demand (COD), and decomposition was characterized by the particulate (i.e., nonfilterable) chemical oxygen demand (PCOD). Using the Arrhenius equation (k = k(o)e(-Ea/RT)), activation energy (Ea) levels were derived from 42 continuous-flow hydrothermal treatment experiments conducted at temperatures in the range of 200-450 degrees C. Using predetermined values for k(o) in the Arrhenius equation, the activation energies of the various organic ingredients were separated into 42 values for oxidation and a similar number for decomposition. The activation energy values were then classified into levels representing the relative ease at which the organic ingredients of the biosolids were oxidized or decomposed. The resulting simple first-order kinetic models adequately represented, within the experimental data range, hydrothermal decomposition of the organic particles as measured by PCOD and oxidation of the organic content as measured by COD. The modeling approach presented in the paper provide a simple and general framework suitable for assessing the relative reaction rates of the various organic ingredients of biosolids.

Photocatalytic degradation of carbofuran by TiO2-coated activated carbon: Model for kinetic, electrical energy per order and economic analysis.

PubMed

Vishnuganth, M A; Remya, Neelancherry; Kumar, Mathava; Selvaraju, N

2016-10-01

The photocatalytic removal of carbofuran (CBF) from aqueous solution in the presence of granular activated carbon supported TiO2 (GAC-TiO2) catalyst was investigated under batch-mode experiments. The presence of GAC enhanced the photocatalytic efficiency of the TiO2 catalyst. Experiments were conducted at different concentrations of CBF to clarify the dependence of apparent rate constant (kapp) in the pseudo first-order kinetics on CBF photodegradation. The general relationship between the adsorption equilibrium constant (K) and reaction rate constant (kr) were explained by using the modified Langmuir-Hinshelwood (L-H) model. From the observed kinetics, it was observed that the surface reaction was the rate limiting step in the GAC-TiO2 catalyzed photodegradation of CBF. The values of K and kr for this pseudo first-order reaction were found to be 0.1942 L  mg(-1) and 1.51 mg L(-1) min(-1), respectively. In addition, the dependence of kapp on the half-life time was determined by calculating the electrical energy per order experimentally (EEO experimental) and also by modeling (EEO model). The batch-mode experimental outcomes revealed the possibility of 100% CBF removal (under optimized conditions and at an initial concentration of 50 mg L(-1) and 100 mg L(-1)) at a contact time of 90 min and 120 min, respectively. Both L-H kinetic model and EEO model fitted well with the batch-mode experimental data and also elucidated successfully the phenomena of photocatalytic degradation in the presence of GAC-TiO2 catalyst. Copyright © 2016 Elsevier Ltd. All rights reserved.

Reduced-order model for dynamic optimization of pressure swing adsorption processes

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

Agarwal, A.; Biegler, L.; Zitney, S.

2007-01-01

Over the past decades, pressure swing adsorption (PSA) processes have been widely used as energy-efficient gas and liquid separation techniques, especially for high purity hydrogen purification from refinery gases. The separation processes are based on solid-gas equilibrium and operate under periodic transient conditions. Models for PSA processes are therefore multiple instances of partial differential equations (PDEs) in time and space with periodic boundary conditions that link the processing steps together. The solution of this coupled stiff PDE system is governed by steep concentrations and temperature fronts moving with time. As a result, the optimization of such systems for either designmore » or operation represents a significant computational challenge to current differential algebraic equation (DAE) optimization techniques and nonlinear programming algorithms. Model reduction is one approach to generate cost-efficient low-order models which can be used as surrogate models in the optimization problems. The study develops a reduced-order model (ROM) based on proper orthogonal decomposition (POD), which is a low-dimensional approximation to a dynamic PDE-based model. Initially, a representative ensemble of solutions of the dynamic PDE system is constructed by solving a higher-order discretization of the model using the method of lines, a two-stage approach that discretizes the PDEs in space and then integrates the resulting DAEs over time. Next, the ROM method applies the Karhunen-Loeve expansion to derive a small set of empirical eigenfunctions (POD modes) which are used as basis functions within a Galerkin's projection framework to derive a low-order DAE system that accurately describes the dominant dynamics of the PDE system. The proposed method leads to a DAE system of significantly lower order, thus replacing the one obtained from spatial discretization before and making optimization problem computationally-efficient. The method has been applied to the

Equivalence of interest rate models and lattice gases.

PubMed

Pirjol, Dan

2012-04-01

We consider the class of short rate interest rate models for which the short rate is proportional to the exponential of a Gaussian Markov process x(t) in the terminal measure r(t)=a(t)exp[x(t)]. These models include the Black-Derman-Toy and Black-Karasinski models in the terminal measure. We show that such interest rate models are equivalent to lattice gases with attractive two-body interaction, V(t(1),t(2))=-Cov[x(t(1)),x(t(2))]. We consider in some detail the Black-Karasinski model with x(t) as an Ornstein-Uhlenbeck process, and show that it is similar to a lattice gas model considered by Kac and Helfand, with attractive long-range two-body interactions, V(x,y)=-α(e(-γ|x-y|)-e(-γ(x+y))). An explicit solution for the model is given as a sum over the states of the lattice gas, which is used to show that the model has a phase transition similar to that found previously in the Black-Derman-Toy model in the terminal measure.

Equivalence of interest rate models and lattice gases

NASA Astrophysics Data System (ADS)

Pirjol, Dan

2012-04-01

We consider the class of short rate interest rate models for which the short rate is proportional to the exponential of a Gaussian Markov process x(t) in the terminal measure r(t)=a(t)exp[x(t)]. These models include the Black-Derman-Toy and Black-Karasinski models in the terminal measure. We show that such interest rate models are equivalent to lattice gases with attractive two-body interaction, V(t1,t2)=-Cov[x(t1),x(t2)]. We consider in some detail the Black-Karasinski model with x(t) as an Ornstein-Uhlenbeck process, and show that it is similar to a lattice gas model considered by Kac and Helfand, with attractive long-range two-body interactions, V(x,y)=-α(e-γ|x-y|-e-γ(x+y)). An explicit solution for the model is given as a sum over the states of the lattice gas, which is used to show that the model has a phase transition similar to that found previously in the Black-Derman-Toy model in the terminal measure.

Universal Rate Model Selector: A Method to Quickly Find the Best-Fit Kinetic Rate Model for an Experimental Rate Profile

DTIC Science & Technology

2017-08-01

as an official Department of the Army position unless so designated by other authorizing documents. REPORT DOCUMENTATION PAGE Form Approved OMB...processes to find a kinetic rate model that provides a high degree of correlation with experimental data. Furthermore, the use of kinetic rate... correlation 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES 19a. NAME OF RESPONSIBLE PERSON Renu B

Second order closure modeling of turbulent buoyant wall plumes

NASA Technical Reports Server (NTRS)

Zhu, Gang; Lai, Ming-Chia; Shih, Tsan-Hsing

1992-01-01

Non-intrusive measurements of scalar and momentum transport in turbulent wall plumes, using a combined technique of laser Doppler anemometry and laser-induced fluorescence, has shown some interesting features not present in the free jet or plumes. First, buoyancy-generation of turbulence is shown to be important throughout the flow field. Combined with low-Reynolds-number turbulence and near-wall effect, this may raise the anisotropic turbulence structure beyond the prediction of eddy-viscosity models. Second, the transverse scalar fluxes do not correspond only to the mean scalar gradients, as would be expected from gradient-diffusion modeling. Third, higher-order velocity-scalar correlations which describe turbulent transport phenomena could not be predicted using simple turbulence models. A second-order closure simulation of turbulent adiabatic wall plumes, taking into account the recent progress in scalar transport, near-wall effect and buoyancy, is reported in the current study to compare with the non-intrusive measurements. In spite of the small velocity scale of the wall plumes, the results showed that low-Reynolds-number correction is not critically important to predict the adiabatic cases tested and cannot be applied beyond the maximum velocity location. The mean and turbulent velocity profiles are very closely predicted by the second-order closure models. but the scalar field is less satisfactory, with the scalar fluctuation level underpredicted. Strong intermittency of the low-Reynolds-number flow field is suspected of these discrepancies. The trends in second- and third-order velocity-scalar correlations, which describe turbulent transport phenomena, are also predicted in general, with the cross-streamwise correlations better than the streamwise one. Buoyancy terms modeling the pressure-correlation are shown to improve the prediction slightly. The effects of equilibrium time-scale ratio and boundary condition are also discussed.

Model Order Reduction Algorithm for Estimating the Absorption Spectrum

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

Van Beeumen, Roel; Williams-Young, David B.; Kasper, Joseph M.

The ab initio description of the spectral interior of the absorption spectrum poses both a theoretical and computational challenge for modern electronic structure theory. Due to the often spectrally dense character of this domain in the quantum propagator’s eigenspectrum for medium-to-large sized systems, traditional approaches based on the partial diagonalization of the propagator often encounter oscillatory and stagnating convergence. Electronic structure methods which solve the molecular response problem through the solution of spectrally shifted linear systems, such as the complex polarization propagator, offer an alternative approach which is agnostic to the underlying spectral density or domain location. This generality comesmore » at a seemingly high computational cost associated with solving a large linear system for each spectral shift in some discretization of the spectral domain of interest. In this work, we present a novel, adaptive solution to this high computational overhead based on model order reduction techniques via interpolation. Model order reduction reduces the computational complexity of mathematical models and is ubiquitous in the simulation of dynamical systems and control theory. The efficiency and effectiveness of the proposed algorithm in the ab initio prediction of X-ray absorption spectra is demonstrated using a test set of challenging water clusters which are spectrally dense in the neighborhood of the oxygen K-edge. On the basis of a single, user defined tolerance we automatically determine the order of the reduced models and approximate the absorption spectrum up to the given tolerance. We also illustrate that, for the systems studied, the automatically determined model order increases logarithmically with the problem dimension, compared to a linear increase of the number of eigenvalues within the energy window. Furthermore, we observed that the computational cost of the proposed algorithm only scales quadratically with respect

Decreased rates of hypoglycemia following implementation of a comprehensive computerized insulin order set and titration algorithm in the inpatient setting.

PubMed

Sinha Gregory, Naina; Seley, Jane Jeffrie; Gerber, Linda M; Tang, Chin; Brillon, David

2016-12-01

More than one-third of hospitalized patients have hyperglycemia. Despite evidence that improving glycemic control leads to better outcomes, achieving recognized targets remains a challenge. The objective of this study was to evaluate the implementation of a computerized insulin order set and titration algorithm on rates of hypoglycemia and overall inpatient glycemic control. A prospective observational study evaluating the impact of a glycemic order set and titration algorithm in an academic medical center in non-critical care medical and surgical inpatients. The initial intervention was hospital-wide implementation of a comprehensive insulin order set. The secondary intervention was initiation of an insulin titration algorithm in two pilot medicine inpatient units. Point of care testing blood glucose reports were analyzed. These reports included rates of hypoglycemia (BG < 70 mg/dL) and hyperglycemia (BG >200 mg/dL in phase 1, BG > 180 mg/dL in phase 2). In the first phase of the study, implementation of the insulin order set was associated with decreased rates of hypoglycemia (1.92% vs 1.61%; p < 0.001) and increased rates of hyperglycemia (24.02% vs 27.27%; p < 0.001) from 2010 to 2011. In the second phase, addition of a titration algorithm was associated with decreased rates of hypoglycemia (2.57% vs 1.82%; p = 0.039) and increased rates of hyperglycemia (31.76% vs 41.33%; p < 0.001) from 2012 to 2013. A comprehensive computerized insulin order set and titration algorithm significantly decreased rates of hypoglycemia. This significant reduction in hypoglycemia was associated with increased rates of hyperglycemia. Hardwiring the algorithm into the electronic medical record may foster adoption.

Power and transmission rate orders and related documents. Office of Power Marketing Coordination, data compiled January 1, 1980-December 31, 1981

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

None

This publication contains the power and transmission rate orders and related documents issued by the Department of Energy. It covers calendar years 1980 and 1981. The first publication, DOE/CE-007 covering the period from March through December 1979, was published July 1981. This publication is a compilation of all rate orders issued by the Assistant Secretary for Resource Applications and the Assistant Secretary for Conservation and Renewable Energy during calendar years 1980 and 1981 under Delegation Order No. 0204-33. It also includes all final approvals, remands, and disapprovals by the FERC, and a petition to the FERC for reconsideration by amore » Power Marketing Administration during 1980 and 1981. Also included are two delegation orders along with an amendment and a supplement to one delegation order, a departmental order on financial reporting, and Power and Transmission Rate Adjustment Procedures relating to federal power marketing.« less

Is First-Order Vector Autoregressive Model Optimal for fMRI Data?

PubMed

Ting, Chee-Ming; Seghouane, Abd-Krim; Khalid, Muhammad Usman; Salleh, Sh-Hussain

2015-09-01

We consider the problem of selecting the optimal orders of vector autoregressive (VAR) models for fMRI data. Many previous studies used model order of one and ignored that it may vary considerably across data sets depending on different data dimensions, subjects, tasks, and experimental designs. In addition, the classical information criteria (IC) used (e.g., the Akaike IC (AIC)) are biased and inappropriate for the high-dimensional fMRI data typically with a small sample size. We examine the mixed results on the optimal VAR orders for fMRI, especially the validity of the order-one hypothesis, by a comprehensive evaluation using different model selection criteria over three typical data types--a resting state, an event-related design, and a block design data set--with varying time series dimensions obtained from distinct functional brain networks. We use a more balanced criterion, Kullback's IC (KIC) based on Kullback's symmetric divergence combining two directed divergences. We also consider the bias-corrected versions (AICc and KICc) to improve VAR model selection in small samples. Simulation results show better small-sample selection performance of the proposed criteria over the classical ones. Both bias-corrected ICs provide more accurate and consistent model order choices than their biased counterparts, which suffer from overfitting, with KICc performing the best. Results on real data show that orders greater than one were selected by all criteria across all data sets for the small to moderate dimensions, particularly from small, specific networks such as the resting-state default mode network and the task-related motor networks, whereas low orders close to one but not necessarily one were chosen for the large dimensions of full-brain networks.

A delta-rule model of numerical and non-numerical order processing.

PubMed

Verguts, Tom; Van Opstal, Filip

2014-06-01

Numerical and non-numerical order processing share empirical characteristics (distance effect and semantic congruity), but there are also important differences (in size effect and end effect). At the same time, models and theories of numerical and non-numerical order processing developed largely separately. Currently, we combine insights from 2 earlier models to integrate them in a common framework. We argue that the same learning principle underlies numerical and non-numerical orders, but that environmental features determine the empirical differences. Implications for current theories on order processing are pointed out. PsycINFO Database Record (c) 2014 APA, all rights reserved.

A multi-species reactive transport model to estimate biogeochemical rates based on single-well push-pull test data

NASA Astrophysics Data System (ADS)

Phanikumar, Mantha S.; McGuire, Jennifer T.

2010-08-01

Push-pull tests are a popular technique to investigate various aquifer properties and microbial reaction kinetics in situ. Most previous studies have interpreted push-pull test data using approximate analytical solutions to estimate (generally first-order) reaction rate coefficients. Though useful, these analytical solutions may not be able to describe important complexities in rate data. This paper reports the development of a multi-species, radial coordinate numerical model (PPTEST) that includes the effects of sorption, reaction lag time and arbitrary reaction order kinetics to estimate rates in the presence of mixing interfaces such as those created between injected "push" water and native aquifer water. The model has the ability to describe an arbitrary number of species and user-defined reaction rate expressions including Monod/Michelis-Menten kinetics. The FORTRAN code uses a finite-difference numerical model based on the advection-dispersion-reaction equation and was developed to describe the radial flow and transport during a push-pull test. The accuracy of the numerical solutions was assessed by comparing numerical results with analytical solutions and field data available in the literature. The model described the observed breakthrough data for tracers (chloride and iodide-131) and reactive components (sulfate and strontium-85) well and was found to be useful for testing hypotheses related to the complex set of processes operating near mixing interfaces.

Forecasting the mortality rates using Lee-Carter model and Heligman-Pollard model

NASA Astrophysics Data System (ADS)

Ibrahim, R. I.; Ngataman, N.; Abrisam, W. N. A. Wan Mohd

2017-09-01

Improvement in life expectancies has driven further declines in mortality. The sustained reduction in mortality rates and its systematic underestimation has been attracting the significant interest of researchers in recent years because of its potential impact on population size and structure, social security systems, and (from an actuarial perspective) the life insurance and pensions industry worldwide. Among all forecasting methods, the Lee-Carter model has been widely accepted by the actuarial community and Heligman-Pollard model has been widely used by researchers in modelling and forecasting future mortality. Therefore, this paper only focuses on Lee-Carter model and Heligman-Pollard model. The main objective of this paper is to investigate how accurately these two models will perform using Malaysian data. Since these models involves nonlinear equations that are explicitly difficult to solve, the Matrix Laboratory Version 8.0 (MATLAB 8.0) software will be used to estimate the parameters of the models. Autoregressive Integrated Moving Average (ARIMA) procedure is applied to acquire the forecasted parameters for both models as the forecasted mortality rates are obtained by using all the values of forecasted parameters. To investigate the accuracy of the estimation, the forecasted results will be compared against actual data of mortality rates. The results indicate that both models provide better results for male population. However, for the elderly female population, Heligman-Pollard model seems to underestimate to the mortality rates while Lee-Carter model seems to overestimate to the mortality rates.

Numerical modeling of higher order magnetic moments in UXO discrimination

USGS Publications Warehouse

Sanchez, V.; Yaoguo, L.; Nabighian, M.N.; Wright, D.L.

2008-01-01

The surface magnetic anomaly observed in unexploded ordnance (UXO) clearance is mainly dipolar, and consequently, the dipole is the only magnetic moment regularly recovered in UXO discrimination. The dipole moment contains information about the intensity of magnetization but lacks information about the shape of the target. In contrast, higher order moments, such as quadrupole and octupole, encode asymmetry properties of the magnetization distribution within the buried targets. In order to improve our understanding of magnetization distribution within UXO and non-UXO objects and to show its potential utility in UXO clearance, we present a numerical modeling study of UXO and related metallic objects. The tool for the modeling is a nonlinear integral equation describing magnetization within isolated compact objects of high susceptibility. A solution for magnetization distribution then allows us to compute the magnetic multipole moments of the object, analyze their relationships, and provide a depiction of the anomaly produced by different moments within the object. Our modeling results show the presence of significant higher order moments for more asymmetric objects, and the fields of these higher order moments are well above the noise level of magnetic gradient data. The contribution from higher order moments may provide a practical tool for improved UXO discrimination. ?? 2008 IEEE.

Low-Order Modeling of Internal Heat Transfer in Biomass Particle Pyrolysis

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

Wiggins, Gavin M.; Ciesielski, Peter N.; Daw, C. Stuart

2016-06-16

We present a computationally efficient, one-dimensional simulation methodology for biomass particle heating under conditions typical of fast pyrolysis. Our methodology is based on identifying the rate limiting geometric and structural factors for conductive heat transport in biomass particle models with realistic morphology to develop low-order approximations that behave appropriately. Comparisons of transient temperature trends predicted by our one-dimensional method with three-dimensional simulations of woody biomass particles reveal good agreement, if the appropriate equivalent spherical diameter and bulk thermal properties are used. We conclude that, for particle sizes and heating regimes typical of fast pyrolysis, it is possible to simulate biomassmore » particle heating with reasonable accuracy and minimal computational overhead, even when variable size, aspherical shape, anisotropic conductivity, and complex, species-specific internal pore geometry are incorporated.« less

Robust simulation of buckled structures using reduced order modeling

NASA Astrophysics Data System (ADS)

Wiebe, R.; Perez, R. A.; Spottswood, S. M.

2016-09-01

Lightweight metallic structures are a mainstay in aerospace engineering. For these structures, stability, rather than strength, is often the critical limit state in design. For example, buckling of panels and stiffeners may occur during emergency high-g maneuvers, while in supersonic and hypersonic aircraft, it may be induced by thermal stresses. The longstanding solution to such challenges was to increase the sizing of the structural members, which is counter to the ever present need to minimize weight for reasons of efficiency and performance. In this work we present some recent results in the area of reduced order modeling of post- buckled thin beams. A thorough parametric study of the response of a beam to changing harmonic loading parameters, which is useful in exposing complex phenomena and exercising numerical models, is presented. Two error metrics that use but require no time stepping of a (computationally expensive) truth model are also introduced. The error metrics are applied to several interesting forcing parameter cases identified from the parametric study and are shown to yield useful information about the quality of a candidate reduced order model. Parametric studies, especially when considering forcing and structural geometry parameters, coupled environments, and uncertainties would be computationally intractable with finite element models. The goal is to make rapid simulation of complex nonlinear dynamic behavior possible for distributed systems via fast and accurate reduced order models. This ability is crucial in allowing designers to rigorously probe the robustness of their designs to account for variations in loading, structural imperfections, and other uncertainties.

Mixed-order phase transition in a minimal, diffusion-based spin model.

PubMed

Fronczak, Agata; Fronczak, Piotr

2016-07-01

In this paper we exactly solve, within the grand canonical ensemble, a minimal spin model with the hybrid phase transition. We call the model diffusion based because its Hamiltonian can be recovered from a simple dynamic procedure, which can be seen as an equilibrium statistical mechanics representation of a biased random walk. We outline the derivation of the phase diagram of the model, in which the triple point has the hallmarks of the hybrid transition: discontinuity in the average magnetization and algebraically diverging susceptibilities. At this point, two second-order transition curves meet in equilibrium with the first-order curve, resulting in a prototypical mixed-order behavior.

Prediction of in vivo neutral detergent fiber digestibility and digestion rate of potentially digestible neutral detergent fiber: comparison of models.

PubMed

Huhtanen, P; Seppälä, A; Ahvenjärvi, S; Rinne, M

2008-10-01

Eleven 1-pool, seven 2-pool, and three 3-pool models were compared in fitting gas production data and predicting in vivo NDF digestibility and effective first-order digestion rate of potentially digestible NDF (pdNDF). Isolated NDF from 15 grass silages harvested at different stages of maturity was incubated in triplicate in rumen fluid-buffer solution for 72 h to estimate the digestion kinetics from cumulative gas production profiles. In vivo digestibility was estimated by the total fecal collection method in sheep fed at a maintenance level of feeding. The concentration of pdNDF was estimated by a 12-d in situ incubation. The parameter values from gas production profiles and pdNDF were used in a 2-compartment rumen model to predict pdNDF digestibility using 50 h of rumen residence time distributed in a ratio of 0.4:0.6 between the non-escapable and escapable pools. The effective first-order digestion rate was computed both from observed in vivo and model-predicted pdNDF digestibility assuming the passage kinetic model described above. There were marked differences between the models in fitting the gas production data. The fit improved with increasing number of pools, suggesting that silage pdNDF is not a homogenous substrate. Generally, the models predicted in vivo NDF digestibility and digestion rate accurately. However, a good fit of gas production data was not necessarily translated into improved predictions of the in vivo data. The models overestimating the asymptotic gas volumes tended to underestimate the in vivo digestibility. Investigating the time-related residuals during the later phases of fermentation is important when the data are used to estimate the first-order digestion rate of pdNDF. Relatively simple models such as the France model or even a single exponential model with discrete lag period satisfied the minimum criteria for a good model. Further, the comparison of feedstuffs on the basis of parameter values is more unequivocal than in the case

Reduced-Order Model Based Feedback Control For Modified Hasegawa-Wakatani Model

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

Goumiri, I. R.; Rowley, C. W.; Ma, Z.

2013-01-28

In this work, the development of model-based feedback control that stabilizes an unstable equilibrium is obtained for the Modi ed Hasegawa-Wakatani (MHW) equations, a classic model in plasma turbulence. First, a balanced truncation (a model reduction technique that has proven successful in ow control design problems) is applied to obtain a low dimensional model of the linearized MHW equation. Then a modelbased feedback controller is designed for the reduced order model using linear quadratic regulators (LQR). Finally, a linear quadratic gaussian (LQG) controller, which is more resistant to disturbances is deduced. The controller is applied on the non-reduced, nonlinear MHWmore » equations to stabilize the equilibrium and suppress the transition to drift-wave induced turbulence.« less

Predicting changes in reported notifiable disease rates for New Zealand using a SIR modelling approach

NASA Astrophysics Data System (ADS)

McBride, Graham; Slaney, David; Tait, Andrew

2013-04-01

The New Zealand health system has defined as 'notifiable' over 50 diseases. Of these campylobacteriosis is the most commonly reported comprising 41% of all notifications in 2011 (presently about 150 illness cases per 100,000 population per annum). Furthermore, the incidence of this mild illness, which is potentially waterborne, is under-reported by at least an order-of-magnitude. Increased downstream pathogen loads and/or disease incidence have been found to be associated with increased rainfall, particularly in agricultural landscapes. Therefore, given the predominance of agricultural land uses in New Zealand, transmission and exposure to its agent (thermotolerant Campylobacter bacteria) may be affected by changing rainfall and temperature patterns associated with climate change. Reporting rates for other potentially water-borne zoonoses are also noticeable (for example, the reported rate for cryptosporidiosis for 2011 was 14 per 100,000 population). The distribution of Cryptosporidium oocysts in the environment may be influenced by climate change because it has often been implicated in drinking-water contamination, and heavy rainfall events have been found to be associated with increased pathogen loads in rivers and disease incidence. Given this background, which may also be applicable to other countries with agriculturally-dominated landscapes, a New Zealand study was initiated to develop a decision-support system for the projected effects of climate change on a selected suite of environmentally-transmitted pathogens, including Campylobacter and Cryptosporodium oocysts. Herein we report on the manner in which a linear SIR (Susceptible-Ill-Recovered) model previously developed for campylobacteriosis can be extended to cryptosporidiosis, applied to changes in pathogen contact rate and hence reported illness, and coupled to climate change projections associated with different greenhouse gas emission scenarios. The resulting SIR model outputs provided projected

Polynomial order selection in random regression models via penalizing adaptively the likelihood.

PubMed

Corrales, J D; Munilla, S; Cantet, R J C

2015-08-01

Orthogonal Legendre polynomials (LP) are used to model the shape of additive genetic and permanent environmental effects in random regression models (RRM). Frequently, the Akaike (AIC) and the Bayesian (BIC) information criteria are employed to select LP order. However, it has been theoretically shown that neither AIC nor BIC is simultaneously optimal in terms of consistency and efficiency. Thus, the goal was to introduce a method, 'penalizing adaptively the likelihood' (PAL), as a criterion to select LP order in RRM. Four simulated data sets and real data (60,513 records, 6675 Colombian Holstein cows) were employed. Nested models were fitted to the data, and AIC, BIC and PAL were calculated for all of them. Results showed that PAL and BIC identified with probability of one the true LP order for the additive genetic and permanent environmental effects, but AIC tended to favour over parameterized models. Conversely, when the true model was unknown, PAL selected the best model with higher probability than AIC. In the latter case, BIC never favoured the best model. To summarize, PAL selected a correct model order regardless of whether the 'true' model was within the set of candidates. © 2015 Blackwell Verlag GmbH.

A frictional population model of seismicity rate change

USGS Publications Warehouse

Gomberg, J.; Reasenberg, P.; Cocco, M.; Belardinelli, M.E.

2005-01-01

We study models of seismicity rate changes caused by the application of a static stress perturbation to a population of faults and discuss our results with respect to the model proposed by Dieterich (1994). These models assume distribution of nucleation sites (e.g., faults) obeying rate-state frictional relations that fail at constant rate under tectonic loading alone, and predicts a positive static stress step at time to will cause an immediate increased seismicity rate that decays according to Omori's law. We show one way in which the Dieterich model may be constructed from simple general idead, illustratted using numerically computed synthetic seismicity and mathematical formulation. We show that seismicity rate change predicted by these models (1) depend on the particular relationship between the clock-advanced failure and fault maturity, (2) are largest for the faults closest to failure at to, (3) depend strongly on which state evolution law faults obey, and (4) are insensitive to some types of population hetrogeneity. We also find that if individual faults fail repeatedly and populations are finite, at timescales much longer than typical aftershock durations, quiescence follows at seismicity rate increase regardless of the specific frictional relations. For the examined models the quiescence duration is comparable to the ratio of stress change to stressing rate ????/??,which occurs after a time comparable to the average recurrence interval of the individual faults in the population and repeats in the absence of any new load may pertubations; this simple model may partly explain observations of repeated clustering of earthquakes. Copyright 2005 by the American Geophysical Union.

Predictive Finite Rate Model for Oxygen-Carbon Interactions at High Temperature

NASA Astrophysics Data System (ADS)

Poovathingal, Savio

An oxidation model for carbon surfaces is developed to predict ablation rates for carbon heat shields used in hypersonic vehicles. Unlike existing empirical models, the approach used here was to probe gas-surface interactions individually and then based on an understanding of the relevant fundamental processes, build a predictive model that would be accurate over a wide range of pressures and temperatures, and even microstructures. Initially, molecular dynamics was used to understand the oxidation processes on the surface. The molecular dynamics simulations were compared to molecular beam experiments and good qualitative agreement was observed. The simulations reproduced cylindrical pitting observed in the experiments where oxidation was rapid and primarily occurred around a defect. However, the studies were limited to small systems at low temperatures and could simulate time scales only of the order of nanoseconds. Molecular beam experiments at high surface temperature indicated that a majority of surface reaction products were produced through thermal mechanisms. Since the reactions were thermal, they occurred over long time scales which were computationally prohibitive for molecular dynamics to simulate. The experiments provided detailed dynamical data on the scattering of O, O2, CO, and CO2 and it was found that the data from molecular beam experiments could be used directly to build a model. The data was initially used to deduce surface reaction probabilities at 800 K. The reaction probabilities were then incorporated into the direct simulation Monte Carlo (DSMC) method. Simulations were performed where the microstructure was resolved and dissociated oxygen convected and diffused towards it. For a gas-surface temperature of 800 K, it was found that despite CO being the dominant surface reaction product, a gas-phase reaction forms significant CO2 within the microstructure region. It was also found that surface area did not play any role in concentration of

A Geometric Method for Model Reduction of Biochemical Networks with Polynomial Rate Functions.

PubMed

Samal, Satya Swarup; Grigoriev, Dima; Fröhlich, Holger; Weber, Andreas; Radulescu, Ovidiu

2015-12-01

Model reduction of biochemical networks relies on the knowledge of slow and fast variables. We provide a geometric method, based on the Newton polytope, to identify slow variables of a biochemical network with polynomial rate functions. The gist of the method is the notion of tropical equilibration that provides approximate descriptions of slow invariant manifolds. Compared to extant numerical algorithms such as the intrinsic low-dimensional manifold method, our approach is symbolic and utilizes orders of magnitude instead of precise values of the model parameters. Application of this method to a large collection of biochemical network models supports the idea that the number of dynamical variables in minimal models of cell physiology can be small, in spite of the large number of molecular regulatory actors.

Rate-induced solubility and suppression of the first-order phase transition in olivine LiFePO4.

PubMed

Zhang, Xiaoyu; van Hulzen, Martijn; Singh, Deepak P; Brownrigg, Alex; Wright, Jonathan P; van Dijk, Niels H; Wagemaker, Marnix

2014-05-14

The impact of ultrahigh (dis)charge rates on the phase transition mechanism in LiFePO4 Li-ion electrodes is revealed by in situ synchrotron diffraction. At high rates the solubility limits in both phases increase dramatically, causing a fraction of the electrode to bypass the first-order phase transition. The small transforming fraction demonstrates that nucleation rates are consequently not limiting the transformation rate. In combination with the small fraction of the electrode that transforms at high rates, this indicates that higher performances may be achieved by further optimizing the ionic/electronic transport in LiFePO4 electrodes.

Scavenging and recombination kinetics in a radiation spur: The successive ordered scavenging events

NASA Astrophysics Data System (ADS)

Al-Samra, Eyad H.; Green, Nicholas J. B.

2018-03-01

This study describes stochastic models to investigate the successive ordered scavenging events in a spur of four radicals, a model system based on a radiation spur. Three simulation models have been developed to obtain the probabilities of the ordered scavenging events: (i) a Monte Carlo random flight (RF) model, (ii) hybrid simulations in which the reaction rate coefficient is used to generate scavenging times for the radicals and (iii) the independent reaction times (IRT) method. The results of these simulations are found to be in agreement with one another. In addition, a detailed master equation treatment is also presented, and used to extract simulated rate coefficients of the ordered scavenging reactions from the RF simulations. These rate coefficients are transient, the rate coefficients obtained for subsequent reactions are effectively equal, and in reasonable agreement with the simple correction for competition effects that has recently been proposed.

75 FR 61744 - The Order of St. Benedict of New Hampshire; Supplemental Notice That Initial Market-Based Rate...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-10-06

... DEPARTMENT OF ENERGY Federal Energy Regulatory Commission [Docket No. ER10-2750-000] The Order of St. Benedict of New Hampshire; Supplemental Notice That Initial Market-Based Rate Filing Includes... above-referenced proceeding of The Order of St. Benedict of New Hampshire's application for market...

A model of clearance rate regulation in mussels

NASA Astrophysics Data System (ADS)

Fréchette, Marcel

2012-10-01

Clearance rate regulation has been modelled as an instantaneous response to food availability, independent of the internal state of the animals. This view is incompatible with latent effects during ontogeny and phenotypic flexibility in clearance rate. Internal-state regulation of clearance rate is required to account for these patterns. Here I develop a model of internal-state based regulation of clearance rate. External factors such as suspended sediments are included in the model. To assess the relative merits of instantaneous regulation and internal-state regulation, I modelled blue mussel clearance rate and growth using a DEB model. In the usual standard feeding module, feeding is governed by a Holling's Type II response to food concentration. In the internal-state feeding module, gill ciliary activity and thus clearance rate are driven by internal reserve level. Factors such as suspended sediments were not included in the simulations. The two feeding modules were compared on the basis of their ability to capture the impact of latent effects, of environmental heterogeneity in food abundance and of physiological flexibility on clearance rate and individual growth. The Holling feeding module was unable to capture the effect of any of these sources of variability. In contrast, the internal-state feeding module did so without any modification or ad hoc calibration. Latent effects, however, appeared transient. With simple annual variability in temperature and food concentration, the relationship between clearance rate and food availability predicted by the internal-state feeding module was quite similar to that observed in Norwegian fjords. I conclude that in contrast with the usual Holling feeding module, internal-state regulation of clearance rate is consistent with well-documented growth and clearance rate patterns.

Second-order closure PBL model with new third-order moments: Comparison with LES data

NASA Technical Reports Server (NTRS)

Canuto, V. M.; Minotti, F.; Ronchi, C.; Ypma, R. M.; Zeman, O.

1994-01-01

This paper contains two parts. In the first part, a new set of diagnostic equations is derived for the third-order moments for a buoyancy-driven flow, by exact inversion of the prognostic equations for the third-order moment equations in the stationary case. The third-order moments exhibit a universal structure: they all are a linear combination of the derivatives of all the second-order moments, bar-w(exp 2), bar-w theta, bar-theta(exp 2), and bar-q(exp 2). Each term of the sum contains a turbulent diffusivity D(sub t), which also exhibits a universal structure of the form D(sub t) = a nu(sub t) + b bar-w theta. Since the sign of the convective flux changes depending on stable or unstable stratification, D(sub t) varies according to the type of stratification. Here nu(sub t) approximately equal to wl (l is a mixing length and w is an rms velocity) represents the 'mechanical' part, while the 'buoyancy' part is represented by the convective flux bar-w theta. The quantities a and b are functions of the variable N(sub tau)(exp 2), where N(exp 2) = g alpha derivative of Theta with respect to z and tau is the turbulence time scale. The new expressions for the third-order moments generalize those of Zeman and Lumley, which were subsequently adopted by Sun and Ogura, Chen and Cotton, and Finger and Schmidt in their treatments of the convective boundary layer. In the second part, the new expressions for the third-order moments are used to solve the ensemble average equations describing a purely convective boundary laye r heated from below at a constant rate. The computed second- and third-order moments are then compared with the corresponding Large Eddy Simulation (LES) results, most of which are obtained by running a new LES code, and part of which are taken from published results. The ensemble average results compare favorably with the LES data.

Low-Order Modeling of Dynamic Stall on Airfoils in Incompressible Flow

NASA Astrophysics Data System (ADS)

Narsipur, Shreyas

Unsteady aerodynamics has been a topic of research since the late 1930's and has increased in popularity among researchers studying dynamic stall in helicopters, insect/bird flight, micro air vehicles, wind-turbine aerodynamics, and ow-energy harvesting devices. Several experimental and computational studies have helped researchers gain a good understanding of the unsteady ow phenomena, but have proved to be expensive and time-intensive for rapid design and analysis purposes. Since the early 1970's, the push to develop low-order models to solve unsteady ow problems has resulted in several semi-empirical models capable of effectively analyzing unsteady aerodynamics in a fraction of the time required by high-order methods. However, due to the various complexities associated with time-dependent flows, several empirical constants and curve fits derived from existing experimental and computational results are required by the semi-empirical models to be an effective analysis tool. The aim of the current work is to develop a low-order model capable of simulating incompressible dynamic-stall type ow problems with a focus on accurately modeling the unsteady ow physics with the aim of reducing empirical dependencies. The lumped-vortex-element (LVE) algorithm is used as the baseline unsteady inviscid model to which augmentations are applied to model unsteady viscous effects. The current research is divided into two phases. The first phase focused on augmentations aimed at modeling pure unsteady trailing-edge boundary-layer separation and stall without leading-edge vortex (LEV) formation. The second phase is targeted at including LEV shedding capabilities to the LVE algorithm and combining with the trailing-edge separation model from phase one to realize a holistic, optimized, and robust low-order dynamic stall model. In phase one, initial augmentations to theory were focused on modeling the effects of steady trailing-edge separation by implementing a non-linear decambering

Exact variational nonlocal stress modeling with asymptotic higher-order strain gradients for nanobeams

NASA Astrophysics Data System (ADS)

Lim, C. W.; Wang, C. M.

2007-03-01

This article presents a complete and asymptotic representation of the one-dimensional nanobeam model with nonlocal stress via an exact variational principle approach. An asymptotic governing differential equation of infinite-order strain gradient model and the corresponding infinite number of boundary conditions are derived and discussed. For practical applications, it explores and presents a reduced higher-order solution to the asymptotic nonlocal model. It is also identified here and explained at length that most publications on this subject have inaccurately employed an excessively simplified lower-order model which furnishes intriguing solutions under certain loading and boundary conditions where the results become identical to the classical solution, i.e., without the small-scale effect at all. Various nanobeam examples are solved to demonstrate the difference between using the simplified lower-order nonlocal model and the asymptotic higher-order strain gradient nonlocal stress model. An important conclusion is the discovery of significant over- or underestimation of stress levels using the lower-order model, particularly at the vicinity of the clamped end of a cantilevered nanobeam under a tip point load. The consequence is that the design of a nanobeam based on the lower-order strain gradient model could be flawed in predicting the nonlocal stress at the clamped end where it could, depending on the magnitude of the small-scale parameter, significantly over- or underestimate the failure criteria of a nanobeam which are governed by the level of stress.

Identification of Low Order Equivalent System Models From Flight Test Data

NASA Technical Reports Server (NTRS)

Morelli, Eugene A.

2000-01-01

Identification of low order equivalent system dynamic models from flight test data was studied. Inputs were pilot control deflections, and outputs were aircraft responses, so the models characterized the total aircraft response including bare airframe and flight control system. Theoretical investigations were conducted and related to results found in the literature. Low order equivalent system modeling techniques using output error and equation error parameter estimation in the frequency domain were developed and validated on simulation data. It was found that some common difficulties encountered in identifying closed loop low order equivalent system models from flight test data could be overcome using the developed techniques. Implications for data requirements and experiment design were discussed. The developed methods were demonstrated using realistic simulation cases, then applied to closed loop flight test data from the NASA F-18 High Alpha Research Vehicle.

Venus gravity and topography: 60th degree and order model

NASA Technical Reports Server (NTRS)

Konopliv, A. S.; Borderies, N. J.; Chodas, P. W.; Christensen, E. J.; Sjogren, W. L.; Williams, B. G.; Balmino, G.; Barriot, J. P.

1993-01-01

We have combined the most recent Pioneer Venus Orbiter (PVO) and Magellan (MGN) data with the earlier 1978-1982 PVO data set to obtain a new 60th degree and order spherical harmonic gravity model and a 120th degree and order spherical harmonic topography model. Free-air gravity maps are shown over regions where the most marked improvement has been obtained (Ishtar-Terra, Alpha, Bell and Artemis). Gravity versus topography relationships are presented as correlations per degree and axes orientation.

Reduced order modeling of head related transfer functions for virtual acoustic displays

NASA Astrophysics Data System (ADS)

Willhite, Joel A.; Frampton, Kenneth D.; Grantham, D. Wesley

2003-04-01

The purpose of this work is to improve the computational efficiency in acoustic virtual applications by creating and testing reduced order models of the head related transfer functions used in localizing sound sources. State space models of varying order were generated from zero-elevation Head Related Impulse Responses (HRIRs) using Kungs Single Value Decomposition (SVD) technique. The inputs to the models are the desired azimuths of the virtual sound sources (from minus 90 deg to plus 90 deg, in 10 deg increments) and the outputs are the left and right ear impulse responses. Trials were conducted in an anechoic chamber in which subjects were exposed to real sounds that were emitted by individual speakers across a numbered speaker array, phantom sources generated from the original HRIRs, and phantom sound sources generated with the different reduced order state space models. The error in the perceived direction of the phantom sources generated from the reduced order models was compared to errors in localization using the original HRIRs.

Hindered disulfide bonds to regulate release rate of model drug from mesoporous silica.

PubMed

Nadrah, Peter; Maver, Uroš; Jemec, Anita; Tišler, Tatjana; Bele, Marjan; Dražić, Goran; Benčina, Mojca; Pintar, Albin; Planinšek, Odon; Gaberšček, Miran

2013-05-01

With the advancement of drug delivery systems based on mesoporous silica nanoparticles (MSNs), a simple and efficient method regulating the drug release kinetics is needed. We developed redox-responsive release systems with three levels of hindrance around the disulfide bond. A model drug (rhodamine B dye) was loaded into MSNs' mesoporous voids. The pore opening was capped with β-cyclodextrin in order to prevent leakage of drug. Indeed, in absence of a reducing agent the systems exhibited little leakage, while the addition of dithiothreitol cleaved the disulfide bonds and enabled the release of cargo. The release rate and the amount of released dye were tuned by the level of hindrance around disulfide bonds, with the increased hindrance causing a decrease in the release rate as well as in the amount of released drug. Thus, we demonstrated the ability of the present mesoporous systems to intrinsically control the release rate and the amount of the released cargo by only minor structural variations. Furthermore, an in vivo experiment on zebrafish confirmed that the present model delivery system is nonteratogenic.

A second-order impact model for forest fire regimes.

PubMed

Maggi, Stefano; Rinaldi, Sergio

2006-09-01

We present a very simple "impact" model for the description of forest fires and show that it can mimic the known characteristics of wild fire regimes in savannas, boreal forests, and Mediterranean forests. Moreover, the distribution of burned biomasses in model generated fires resemble those of burned areas in numerous large forests around the world. The model has also the merits of being the first second-order model for forest fires and the first example of the use of impact models in the study of ecosystems.

Implications of two Holocene time-dependent geomagnetic models for cosmogenic nuclide production rate scaling

NASA Astrophysics Data System (ADS)

Lifton, Nathaniel

2016-01-01

The geomagnetic field is a major influence on in situ cosmogenic nuclide production rates at a given location (in addition to atmospheric pressure and, to a lesser extent, solar modulation effects). A better understanding of how past fluctuations in these influences affected production rates should allow more accurate application of cosmogenic nuclides. As such, this work explores the cosmogenic nuclide production rate scaling implications of two recent time-dependent spherical harmonic geomagnetic models spanning the Holocene. Korte and Constable (2011, Phys. Earth Planet. Inter.188, 247-259) and Korte et al. (2011, Earth Planet. Sci. Lett. 312, 497-505) recently updated earlier spherical harmonic paleomagnetic models with new paleomagnetic data from sediment cores in addition to new archeomagnetic and volcanic data. These updated models offer improved resolution and accuracy over the previous versions, in part due to increased temporal and spatial data coverage. In addition, Pavón-Carrasco et al. (2014, Earth Planet. Sci. Lett. 388, 98-109) developed another time-dependent spherical harmonic model of the Holocene geomagnetic field, based solely on archeomagnetic and volcanic paleomagnetic data from the same underlying paleomagnetic database as the Korte et al. models, but extending to 14 ka. With the new models as input, trajectory-traced estimates of effective vertical cutoff rigidity (RC - the standard method for ordering cosmic ray data) yield significantly different time-integrated scaling predictions when compared to each other and to results using the earlier models. In addition, predictions of each new model using RC are tested empirically using recently published production rate calibration data for both 10Be and 3He, and compared to predictions using corresponding time-varying geocentric dipolar RC formulations and a static geocentric axial dipole (GAD) model. Results for the few calibration sites from geomagnetically sensitive regions suggest that the

Some analytical models to estimate maternal age at birth using age-specific fertility rates.

PubMed

Pandey, A; Suchindran, C M

1995-01-01

"A class of analytical models to study the distribution of maternal age at different births from the data on age-specific fertility rates has been presented. Deriving the distributions and means of maternal age at birth of any specific order, final parity and at next-to-last birth, we have extended the approach to estimate parity progression ratios and the ultimate parity distribution of women in the population.... We illustrate computations of various components of the model expressions with the current fertility experiences of the United States for 1970." excerpt

CHLORINE DEMAND AND TTHM FORMATION KINETICS: A SECOND-ORDER MODEL

EPA Science Inventory

Much effort has been expended in attempting to develop mathematical models for chlorine demand in water and wastewater. Most of these efforts have centered around the use of first-order functions or modifications of first-order functions. Recently there has also been interest i...

A Simple and Accurate Rate-Driven Infiltration Model

NASA Astrophysics Data System (ADS)

Cui, G.; Zhu, J.

2017-12-01

In this study, we develop a novel Rate-Driven Infiltration Model (RDIMOD) for simulating infiltration into soils. Unlike traditional methods, RDIMOD avoids numerically solving the highly non-linear Richards equation or simply modeling with empirical parameters. RDIMOD employs infiltration rate as model input to simulate one-dimensional infiltration process by solving an ordinary differential equation. The model can simulate the evolutions of wetting front, infiltration rate, and cumulative infiltration on any surface slope including vertical and horizontal directions. Comparing to the results from the Richards equation for both vertical infiltration and horizontal infiltration, RDIMOD simply and accurately predicts infiltration processes for any type of soils and soil hydraulic models without numerical difficulty. Taking into account the accuracy, capability, and computational effectiveness and stability, RDIMOD can be used in large-scale hydrologic and land-atmosphere modeling.

Impact of Physics Parameterization Ordering in a Global Atmosphere Model

NASA Astrophysics Data System (ADS)

Donahue, Aaron S.; Caldwell, Peter M.

2018-02-01

Because weather and climate models must capture a wide variety of spatial and temporal scales, they rely heavily on parameterizations of subgrid-scale processes. The goal of this study is to demonstrate that the assumptions used to couple these parameterizations have an important effect on the climate of version 0 of the Energy Exascale Earth System Model (E3SM) General Circulation Model (GCM), a close relative of version 1 of the Community Earth System Model (CESM1). Like most GCMs, parameterizations in E3SM are sequentially split in the sense that parameterizations are called one after another with each subsequent process feeling the effect of the preceding processes. This coupling strategy is noncommutative in the sense that the order in which processes are called impacts the solution. By examining a suite of 24 simulations with deep convection, shallow convection, macrophysics/microphysics, and radiation parameterizations reordered, process order is shown to have a big impact on predicted climate. In particular, reordering of processes induces differences in net climate feedback that are as big as the intermodel spread in phase 5 of the Coupled Model Intercomparison Project. One reason why process ordering has such a large impact is that the effect of each process is influenced by the processes preceding it. Where output is written is therefore an important control on apparent model behavior. Application of k-means clustering demonstrates that the positioning of macro/microphysics and shallow convection plays a critical role on the model solution.

Low-order modeling of internal heat transfer in biomass particle pyrolysis

DOE PAGES

Wiggins, Gavin M.; Daw, C. Stuart; Ciesielski, Peter N.

2016-05-11

We present a computationally efficient, one-dimensional simulation methodology for biomass particle heating under conditions typical of fast pyrolysis. Our methodology is based on identifying the rate limiting geometric and structural factors for conductive heat transport in biomass particle models with realistic morphology to develop low-order approximations that behave appropriately. Comparisons of transient temperature trends predicted by our one-dimensional method with three-dimensional simulations of woody biomass particles reveal good agreement, if the appropriate equivalent spherical diameter and bulk thermal properties are used. Here, we conclude that, for particle sizes and heating regimes typical of fast pyrolysis, it is possible to simulatemore » biomass particle heating with reasonable accuracy and minimal computational overhead, even when variable size, aspherical shape, anisotropic conductivity, and complex, species-specific internal pore geometry are incorporated.« less

Noise models for low counting rate coherent diffraction imaging.

PubMed

Godard, Pierre; Allain, Marc; Chamard, Virginie; Rodenburg, John

2012-11-05

Coherent diffraction imaging (CDI) is a lens-less microscopy method that extracts the complex-valued exit field from intensity measurements alone. It is of particular importance for microscopy imaging with diffraction set-ups where high quality lenses are not available. The inversion scheme allowing the phase retrieval is based on the use of an iterative algorithm. In this work, we address the question of the choice of the iterative process in the case of data corrupted by photon or electron shot noise. Several noise models are presented and further used within two inversion strategies, the ordered subset and the scaled gradient. Based on analytical and numerical analysis together with Monte-Carlo studies, we show that any physical interpretations drawn from a CDI iterative technique require a detailed understanding of the relationship between the noise model and the used inversion method. We observe that iterative algorithms often assume implicitly a noise model. For low counting rates, each noise model behaves differently. Moreover, the used optimization strategy introduces its own artefacts. Based on this analysis, we develop a hybrid strategy which works efficiently in the absence of an informed initial guess. Our work emphasises issues which should be considered carefully when inverting experimental data.

75 FR 59707 - Electric Quarterly Reports; BM2 LLC; DJGW, LLC; Order on Intent To Revoke Market-Based Rate...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-09-28

.... 2001, FERC Stats. & Regs. ] 31,127, reh'g denied, Order No. 2001-A, 100 FERC ] 61,074, reconsideration...-based rates.\\[2]\\ \\2\\ Order No. 2001, FERC Stats & Regs. ] 31,127 at P 222. 4. The Commission further...

A second-order frequency-aided digital phase-locked loop for Doppler rate tracking

NASA Astrophysics Data System (ADS)

Chie, C. M.

1980-08-01

A second-order digital phase-locked loop (DPLL) has a finite lock range which is a function of the frequency of the incoming signal to be tracked. For this reason, it is not capable of tracking an input with Doppler rate for an indefinite period of time. In this correspondence, an analytical expression for the hold-in time is derived. In addition, an all-digital scheme to alleviate this problem is proposed based on the information obtained from estimating the input signal frequency.

Calibrating reaction rates for the CREST model

NASA Astrophysics Data System (ADS)

Handley, Caroline A.; Christie, Michael A.

2017-01-01

The CREST reactive-burn model uses entropy-dependent reaction rates that, until now, have been manually tuned to fit shock-initiation and detonation data in hydrocode simulations. This paper describes the initial development of an automatic method for calibrating CREST reaction-rate coefficients, using particle swarm optimisation. The automatic method is applied to EDC32, to help develop the first CREST model for this conventional high explosive.

Influence of model order reduction methods on dynamical-optical simulations

NASA Astrophysics Data System (ADS)

Störkle, Johannes; Eberhard, Peter

2017-04-01

In this work, the influence of model order reduction (MOR) methods on optical aberrations is analyzed within a dynamical-optical simulation of a high precision optomechanical system. Therefore, an integrated modeling process and new methods have to be introduced for the computation and investigation of the overall dynamical-optical behavior. For instance, this optical system can be a telescope optic or a lithographic objective. In order to derive a simplified mechanical model for transient time simulations with low computational cost, the method of elastic multibody systems in combination with MOR methods can be used. For this, software tools and interfaces are defined and created. Furthermore, mechanical and optical simulation models are derived and implemented. With these, on the one hand, the mechanical sensitivity can be investigated for arbitrary external excitations and on the other hand, the related optical behavior can be predicted. In order to clarify these methods, academic examples are chosen and the influences of the MOR methods and simulation strategies are analyzed. Finally, the systems are investigated with respect to the mechanical-optical frequency responses, and in conclusion, some recommendations for the application of reduction methods are given.

Reduced-order modeling of piezoelectric energy harvesters with nonlinear circuits under complex conditions

NASA Astrophysics Data System (ADS)

Xiang, Hong-Jun; Zhang, Zhi-Wei; Shi, Zhi-Fei; Li, Hong

2018-04-01

A fully coupled modeling approach is developed for piezoelectric energy harvesters in this work based on the use of available robust finite element packages and efficient reducing order modeling techniques. At first, the harvester is modeled using finite element packages. The dynamic equilibrium equations of harvesters are rebuilt by extracting system matrices from the finite element model using built-in commands without any additional tools. A Krylov subspace-based scheme is then applied to obtain a reduced-order model for improving simulation efficiency but preserving the key features of harvesters. Co-simulation of the reduced-order model with nonlinear energy harvesting circuits is achieved in a system level. Several examples in both cases of harmonic response and transient response analysis are conducted to validate the present approach. The proposed approach allows to improve the simulation efficiency by several orders of magnitude. Moreover, the parameters used in the equivalent circuit model can be conveniently obtained by the proposed eigenvector-based model order reduction technique. More importantly, this work establishes a methodology for modeling of piezoelectric energy harvesters with any complicated mechanical geometries and nonlinear circuits. The input load may be more complex also. The method can be employed by harvester designers to optimal mechanical structures or by circuit designers to develop novel energy harvesting circuits.

Material failure modelling in metals at high strain rates

NASA Astrophysics Data System (ADS)

Panov, Vili

2005-07-01

Plate impact tests have been conducted on the OFHC Cu using single-stage gas gun. Using stress gauges, which were supported with PMMA blocks on the back of the target plates, stress-time histories have been recorded. After testing, micro structural observations of the softly recovered OFHC Cu spalled specimen were carried out and evolution of damage has been examined. To account for the physical mechanisms of failure, the concept that thermal activation in material separation during fracture processes has been adopted as basic mechanism for this material failure model development. With this basic assumption, the proposed model is compatible with the Mechanical Threshold Stress model and therefore in this development it was incorporated into the MTS material model in DYNA3D. In order to analyse proposed criterion a series of FE simulations have been performed for OFHC Cu. The numerical analysis results clearly demonstrate the ability of the model to predict the spall process and experimentally observed tensile damage and failure. It is possible to simulate high strain rate deformation processes and dynamic failure in tension for wide range of temperature. The proposed cumulative criterion, introduced in the DYNA3D code, is able to reproduce the ``pull-back'' stresses of the free surface caused by creation of the internal spalling, and enables one to analyse numerically the spalling over a wide range of impact velocities.

Relationship between medication event rates and the Leapfrog computerized physician order entry evaluation tool.

PubMed

Leung, Alexander A; Keohane, Carol; Lipsitz, Stuart; Zimlichman, Eyal; Amato, Mary; Simon, Steven R; Coffey, Michael; Kaufman, Nathan; Cadet, Bismarck; Schiff, Gordon; Seger, Diane L; Bates, David W

2013-06-01

The Leapfrog CPOE evaluation tool has been promoted as a means of monitoring computerized physician order entry (CPOE). We sought to determine the relationship between Leapfrog scores and the rates of preventable adverse drug events (ADE) and potential ADE. A cross-sectional study of 1000 adult admissions in five community hospitals from October 1, 2008 to September 30, 2010 was performed. Observed rates of preventable ADE and potential ADE were compared with scores reported by the Leapfrog CPOE evaluation tool. The primary outcome was the rate of preventable ADE and the secondary outcome was the composite rate of preventable ADE and potential ADE. Leapfrog performance scores were highly related to the primary outcome. A 43% relative reduction in the rate of preventable ADE was predicted for every 5% increase in Leapfrog scores (rate ratio 0.57; 95% CI 0.37 to 0.88). In absolute terms, four fewer preventable ADE per 100 admissions were predicted for every 5% increase in overall Leapfrog scores (rate difference -4.2; 95% CI -7.4 to -1.1). A statistically significant relationship between Leapfrog scores and the secondary outcome, however, was not detected. Our findings support the use of the Leapfrog tool as a means of evaluating and monitoring CPOE performance after implementation, as addressed by current certification standards. Scores from the Leapfrog CPOE evaluation tool closely relate to actual rates of preventable ADE. Leapfrog testing may alert providers to potential vulnerabilities and highlight areas for further improvement.

Stochastic optimization for modeling physiological time series: application to the heart rate response to exercise

NASA Astrophysics Data System (ADS)

Zakynthinaki, M. S.; Stirling, J. R.

2007-01-01

Stochastic optimization is applied to the problem of optimizing the fit of a model to the time series of raw physiological (heart rate) data. The physiological response to exercise has been recently modeled as a dynamical system. Fitting the model to a set of raw physiological time series data is, however, not a trivial task. For this reason and in order to calculate the optimal values of the parameters of the model, the present study implements the powerful stochastic optimization method ALOPEX IV, an algorithm that has been proven to be fast, effective and easy to implement. The optimal parameters of the model, calculated by the optimization method for the particular athlete, are very important as they characterize the athlete's current condition. The present study applies the ALOPEX IV stochastic optimization to the modeling of a set of heart rate time series data corresponding to different exercises of constant intensity. An analysis of the optimization algorithm, together with an analytic proof of its convergence (in the absence of noise), is also presented.

Reduced-order model based feedback control of the modified Hasegawa-Wakatani model

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

Goumiri, I. R.; Rowley, C. W.; Ma, Z.

2013-04-15

In this work, the development of model-based feedback control that stabilizes an unstable equilibrium is obtained for the Modified Hasegawa-Wakatani (MHW) equations, a classic model in plasma turbulence. First, a balanced truncation (a model reduction technique that has proven successful in flow control design problems) is applied to obtain a low dimensional model of the linearized MHW equation. Then, a model-based feedback controller is designed for the reduced order model using linear quadratic regulators. Finally, a linear quadratic Gaussian controller which is more resistant to disturbances is deduced. The controller is applied on the non-reduced, nonlinear MHW equations to stabilizemore » the equilibrium and suppress the transition to drift-wave induced turbulence.« less

Equilibrium points, stability and numerical solutions of fractional-order predator-prey and rabies models

NASA Astrophysics Data System (ADS)

Ahmed, E.; El-Sayed, A. M. A.; El-Saka, H. A. A.

2007-01-01

In this paper we are concerned with the fractional-order predator-prey model and the fractional-order rabies model. Existence and uniqueness of solutions are proved. The stability of equilibrium points are studied. Numerical solutions of these models are given. An example is given where the equilibrium point is a centre for the integer order system but locally asymptotically stable for its fractional-order counterpart.

A study of the second and third order closure models of turbulence for prediction of separated shear flows

NASA Technical Reports Server (NTRS)

Amano, R. S.

1985-01-01

The hybrid model of the Reynolds-stress turbulence closure is tested for the computation of the flows over a step and disk. Here it is attempted to improve the redistributive action of the turbulence energy among the Reynolds stresses. By evaluating the existing models for the pressure-strain correlation, better coefficients are obtained for the prediction of separating shear flows. Furthermore, the diffusion rate of the Reynolds stresses is reevaluated adopting several algebraic correlations for the triple-velocity products. The models of Cormack et al., Daly-Harlow, Hanjalic-Launder, and Shir were tested for the reattaching shear flows. It was generally observed that all these algebraic models give considerably low values of the triple-velocity products. This is attributed to the fact that none of the algebraic models can take the convective effect of the triple-velocity products into account in the separating shear flows, thus resulting in much lower diffusion rate than Reynolds stresses. In order to improve the evaluation of these quantities correction factors are introduced based on the comparison with some experimental data.

Modeling of pickup ion distributions in the Halley cometosheath: Empirical limits on rates of ionization, diffusion, loss and creation of fast neutral atoms

NASA Technical Reports Server (NTRS)

Huddleston, D. E.; Neugebauer, M.; Goldstein, B. E.

1994-01-01

The shape of the velocity distribution of water group ions observed by the Giotto ion mass spectrometer on its approach to comet Halley is modeled to derive empirical values for the rates of ionization, energy diffusion, and loss in the midcometosheath. The model includes the effect of rapid pitch angle scattering into a bispherical shell distribution as well as the effect of the magnetization of the plasma on the charge exchange loss rate. It is found that the average rate of ionization of cometary neutrals in this region of the cometosheath appears to be of the order of a factor 3 faster than the `standard' rates approx. 1 x 10(exp -6)/s that are generally assumed to model the observations in most regions of the comet environment. For the region of the coma studied in the present work (approx. 1 - 2 x 10(exp 5) km from the nucleus), the inferred energy diffusion coefficient is D(sub 0) approx. equals 0.0002 to 0.0005 sq km/cu s, which is generally lower than values used in other models. The empirically obtained loss rate appears to be about an order of magnitude greater than can be explained by charge exchange with the `standard' cross section of approx. 2 x 10(exp -15)sq cm. However such cross sections are not well known and for water group ion/water group neutral interactions, rates as high as 8 x 10(exp -15) sq cm have previously been suggested in the literature. Assuming the entire loss rate is due to charge exchange yields a rate of creation of fast neutral atoms of the order of approx. 10(exp -4)/s or higher, depending on the level of velocity diffusion. The fast neutrals may, in turn, be partly responsible for the higher-than-expected ionization rate.

Automatic Black-Box Model Order Reduction using Radial Basis Functions

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

Stephanson, M B; Lee, J F; White, D A

Finite elements methods have long made use of model order reduction (MOR), particularly in the context of fast freqeucny sweeps. In this paper, we discuss a black-box MOR technique, applicable to a many solution methods and not restricted only to spectral responses. We also discuss automated methods for generating a reduced order model that meets a given error tolerance. Numerical examples demonstrate the effectiveness and wide applicability of the method. With the advent of improved computing hardware and numerous fast solution techniques, the field of computational electromagnetics are progressed rapidly in terms of the size and complexity of problems thatmore » can be solved. Numerous applications, however, require the solution of a problem for many different configurations, including optimization, parameter exploration, and uncertainly quantification, where the parameters that may be changed include frequency, material properties, geometric dimensions, etc. In such cases, thousands of solutions may be needed, so solve times of even a few minutes can be burdensome. Model order reduction (MOR) may alleviate this difficulty by creating a small model that can be evaluated quickly. Many MOR techniques have been applied to electromagnetic problems over the past few decades, particularly in the context of fast frequency sweeps. Recent works have extended these methods to allow more than one parameter and to allow the parameters to represent material and geometric properties. There are still limitations with these methods, however. First, they almost always assume that the finite element method is used to solve the problem, so that the system matrix is a known function of the parameters. Second, although some authors have presented adaptive methods (e.g., [2]), the order of the model is often determined before the MOR process begins, with little insight about what order is actually needed to reach the desired accuracy. Finally, it not clear how to efficiently extend

Tracking Skill Acquisition with Cognitive Diagnosis Models: A Higher-Order, Hidden Markov Model with Covariates

ERIC Educational Resources Information Center

Wang, Shiyu; Yang, Yan; Culpepper, Steven Andrew; Douglas, Jeffrey A.

2018-01-01

A family of learning models that integrates a cognitive diagnostic model and a higher-order, hidden Markov model in one framework is proposed. This new framework includes covariates to model skill transition in the learning environment. A Bayesian formulation is adopted to estimate parameters from a learning model. The developed methods are…

Cooling rate dependence of structural order in Al{sub 90}Sm{sub 10} metallic glass

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

Sun, Yang; Ames Laboratory, US Department of Energy, Ames, Iowa 50011; Zhang, Yue

2016-07-07

The atomic structure of Al{sub 90}Sm{sub 10} metallic glass is studied using molecular dynamics simulations. By performing a long sub-T{sub g} annealing, we developed a glass model closer to the experiments than the models prepared by continuous cooling. Using the cluster alignment method, we found that “3661” cluster is the dominating short-range order in the glass samples. The connection and arrangement of “3661” clusters, which define the medium-range order in the system, are enhanced significantly in the sub-T{sub g} annealed sample as compared with the fast cooled glass samples. Unlike some strong binary glass formers such as Cu{sub 64.5}Zr{sub 35.5},more » the clusters representing the short-range order do not form an interconnected interpenetrating network in Al{sub 90}Sm{sub 10,} which has only marginal glass formability.« less

Enforcing elemental mass and energy balances for reduced order models

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

Ma, J.; Agarwal, K.; Sharma, P.

2012-01-01

Development of economically feasible gasification and carbon capture, utilization and storage (CCUS) technologies requires a variety of software tools to optimize the designs of not only the key devices involved (e., g., gasifier, CO{sub 2} adsorber) but also the entire power generation system. High-fidelity models such as Computational Fluid Dynamics (CFD) models are capable of accurately simulating the detailed flow dynamics, heat transfer, and chemistry inside the key devices. However, the integration of CFD models within steady-state process simulators, and subsequent optimization of the integrated system, still presents significant challenges due to the scale differences in both time and length,more » as well the high computational cost. A reduced order model (ROM) generated from a high-fidelity model can serve as a bridge between the models of different scales. While high-fidelity models are built upon the principles of mass, momentum, and energy conservations, ROMs are usually developed based on regression-type equations and hence their predictions may violate the mass and energy conservation laws. A high-fidelity model may also have the mass and energy balance problem if it is not tightly converged. Conservations of mass and energy are important when a ROM is integrated to a flowsheet for the process simulation of the entire chemical or power generation system, especially when recycle streams are connected to the modeled device. As a part of the Carbon Capture Simulation Initiative (CCSI) project supported by the U.S. Department of Energy, we developed a software framework for generating ROMs from CFD simulations and integrating them with Process Modeling Environments (PMEs) for system-wide optimization. This paper presents a method to correct the results of a high-fidelity model or a ROM such that the elemental mass and energy are conserved perfectly. Correction factors for the flow rates of individual species in the product streams are solved using a

Assessing first-order emulator inference for physical parameters in nonlinear mechanistic models

USGS Publications Warehouse

Hooten, Mevin B.; Leeds, William B.; Fiechter, Jerome; Wikle, Christopher K.

2011-01-01

We present an approach for estimating physical parameters in nonlinear models that relies on an approximation to the mechanistic model itself for computational efficiency. The proposed methodology is validated and applied in two different modeling scenarios: (a) Simulation and (b) lower trophic level ocean ecosystem model. The approach we develop relies on the ability to predict right singular vectors (resulting from a decomposition of computer model experimental output) based on the computer model input and an experimental set of parameters. Critically, we model the right singular vectors in terms of the model parameters via a nonlinear statistical model. Specifically, we focus our attention on first-order models of these right singular vectors rather than the second-order (covariance) structure.

Robust consensus control with guaranteed rate of convergence using second-order Hurwitz polynomials

NASA Astrophysics Data System (ADS)

Fruhnert, Michael; Corless, Martin

2017-10-01

This paper considers homogeneous networks of general, linear time-invariant, second-order systems. We consider linear feedback controllers and require that the directed graph associated with the network contains a spanning tree and systems are stabilisable. We show that consensus with a guaranteed rate of convergence can always be achieved using linear state feedback. To achieve this, we provide a new and simple derivation of the conditions for a second-order polynomial with complex coefficients to be Hurwitz. We apply this result to obtain necessary and sufficient conditions to achieve consensus with networks whose graph Laplacian matrix may have complex eigenvalues. Based on the conditions found, methods to compute feedback gains are proposed. We show that gains can be chosen such that consensus is achieved robustly over a variety of communication structures and system dynamics. We also consider the use of static output feedback.

Impact of Physics Parameterization Ordering in a Global Atmosphere Model

DOE PAGES

Donahue, Aaron S.; Caldwell, Peter M.

2018-02-02

Because weather and climate models must capture a wide variety of spatial and temporal scales, they rely heavily on parameterizations of subgrid-scale processes. The goal of this study is to demonstrate that the assumptions used to couple these parameterizations have an important effect on the climate of version 0 of the Energy Exascale Earth System Model (E3SM) General Circulation Model (GCM), a close relative of version 1 of the Community Earth System Model (CESM1). Like most GCMs, parameterizations in E3SM are sequentially split in the sense that parameterizations are called one after another with each subsequent process feeling the effectmore » of the preceding processes. This coupling strategy is noncommutative in the sense that the order in which processes are called impacts the solution. By examining a suite of 24 simulations with deep convection, shallow convection, macrophysics/microphysics, and radiation parameterizations reordered, process order is shown to have a big impact on predicted climate. In particular, reordering of processes induces differences in net climate feedback that are as big as the intermodel spread in phase 5 of the Coupled Model Intercomparison Project. One reason why process ordering has such a large impact is that the effect of each process is influenced by the processes preceding it. Where output is written is therefore an important control on apparent model behavior. Application of k-means clustering demonstrates that the positioning of macro/microphysics and shallow convection plays a critical role on the model solution.« less

Impact of Physics Parameterization Ordering in a Global Atmosphere Model

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

Donahue, Aaron S.; Caldwell, Peter M.

Because weather and climate models must capture a wide variety of spatial and temporal scales, they rely heavily on parameterizations of subgrid-scale processes. The goal of this study is to demonstrate that the assumptions used to couple these parameterizations have an important effect on the climate of version 0 of the Energy Exascale Earth System Model (E3SM) General Circulation Model (GCM), a close relative of version 1 of the Community Earth System Model (CESM1). Like most GCMs, parameterizations in E3SM are sequentially split in the sense that parameterizations are called one after another with each subsequent process feeling the effectmore » of the preceding processes. This coupling strategy is noncommutative in the sense that the order in which processes are called impacts the solution. By examining a suite of 24 simulations with deep convection, shallow convection, macrophysics/microphysics, and radiation parameterizations reordered, process order is shown to have a big impact on predicted climate. In particular, reordering of processes induces differences in net climate feedback that are as big as the intermodel spread in phase 5 of the Coupled Model Intercomparison Project. One reason why process ordering has such a large impact is that the effect of each process is influenced by the processes preceding it. Where output is written is therefore an important control on apparent model behavior. Application of k-means clustering demonstrates that the positioning of macro/microphysics and shallow convection plays a critical role on the model solution.« less

First and second order semi-Markov chains for wind speed modeling

NASA Astrophysics Data System (ADS)

Prattico, F.; Petroni, F.; D'Amico, G.

2012-04-01

The increasing interest in renewable energy leads scientific research to find a better way to recover most of the available energy. Particularly, the maximum energy recoverable from wind is equal to 59.3% of that available (Betz law) at a specific pitch angle and when the ratio between the wind speed in output and in input is equal to 1/3. The pitch angle is the angle formed between the airfoil of the blade of the wind turbine and the wind direction. Old turbine and a lot of that actually marketed, in fact, have always the same invariant geometry of the airfoil. This causes that wind turbines will work with an efficiency that is lower than 59.3%. New generation wind turbines, instead, have a system to variate the pitch angle by rotating the blades. This system able the wind turbines to recover, at different wind speed, always the maximum energy, working in Betz limit at different speed ratios. A powerful system control of the pitch angle allows the wind turbine to recover better the energy in transient regime. A good stochastic model for wind speed is then needed to help both the optimization of turbine design and to assist the system control to predict the value of the wind speed to positioning the blades quickly and correctly. The possibility to have synthetic data of wind speed is a powerful instrument to assist designer to verify the structures of the wind turbines or to estimate the energy recoverable from a specific site. To generate synthetic data, Markov chains of first or higher order are often used [1,2,3]. In particular in [3] is presented a comparison between a first-order Markov chain and a second-order Markov chain. A similar work, but only for the first-order Markov chain, is conduced by [2], presenting the probability transition matrix and comparing the energy spectral density and autocorrelation of real and synthetic wind speed data. A tentative to modeling and to join speed and direction of wind is presented in [1], by using two models, first-order

A simplified parsimonious higher order multivariate Markov chain model

NASA Astrophysics Data System (ADS)

Wang, Chao; Yang, Chuan-sheng

2017-09-01

In this paper, a simplified parsimonious higher-order multivariate Markov chain model (SPHOMMCM) is presented. Moreover, parameter estimation method of TPHOMMCM is give. Numerical experiments shows the effectiveness of TPHOMMCM.

Application of first order rate kinetics to explain changes in bloom toxicity—the importance of understanding cell toxin quotas

NASA Astrophysics Data System (ADS)

Orr, Philip T.; Willis, Anusuya; Burford, Michele A.

2018-04-01

Cyanobacteria are oxygenic photosynthetic Gram-negative bacteria that can form potentially toxic blooms in eutrophic and slow flowing aquatic ecosystems. Bloom toxicity varies spatially and temporally, but understanding the mechanisms that drive these changes remains largely a mystery. Changes in bloom toxicity may result from changes in intracellular toxin pool sizes of cyanotoxins with differing molecular toxicities, and/or from changes in the cell concentrations of toxic and non-toxic cyanobacterial species or strains within bloom populations. We show here how first-order rate kinetics at the cellular level can be used to explain how environmental conditions drive changes in bloom toxicity at the ecological level. First order rate constants can be calculated for changes in cell concentration (μ c: specific cell division rate) or the volumetric biomass concentration (μ g: specific growth rate) between short time intervals throughout the cell cycle. Similar first order rate constants can be calculated for changes in nett volumetric cyanotoxin concentration (μ tox: specific cyanotoxin production rate) over similar time intervals. How μ c (or μ g ) covaries with μ tox over the cell cycle shows conclusively when cyanotoxins are being produced and metabolised, and how the toxicity of cells change in response to environment stressors. When μ tox/μ c>1, cyanotoxin cell quotas increase and individual cells become more toxic because the nett cyanotoxin production rate is higher than the cell division rate. When μ tox/μ c=1, cell cyanotoxin quotas remains fixed because the nett cyanotoxin production rate matches the cell division rate. When μ tox/μ c<1, the cyanotoxin cell quota decreases because either the nett cyanotoxin production rate is lower than the cell division rate, or metabolic breakdown and/or secretion of cyanotoxins is occurring. These fundamental equations describe cyanotoxin metabolism dynamics at the cellular level and provide the necessary

Collaborative Research and Development (CR&D). Task Order 0049: Tribological Modeling

DTIC Science & Technology

2008-05-01

scratch test for TiN on stainless steel with better substrate mechanical properties. This present study was focused on the study of stress distribution...AFRL-RX-WP-TR-2010-4189 COLLABORATIVE RESEARCH AND DEVELOPMENT (CR&D) Task Order 0049: Tribological Modeling Young Sup Kang Universal...SUBTITLE COLLABORATIVE RESEARCH AND DEVELOPMENT (CR&D) Task Order 0049: Tribological Modeling 5a. CONTRACT NUMBER F33615-03-D-5801-0049 5b

Performance of a reduced-order FSI model for flow-induced vocal fold vibration

NASA Astrophysics Data System (ADS)

Chang, Siyuan; Luo, Haoxiang; Luo's lab Team

2016-11-01

Vocal fold vibration during speech production involves a three-dimensional unsteady glottal jet flow and three-dimensional nonlinear tissue mechanics. A full 3D fluid-structure interaction (FSI) model is computationally expensive even though it provides most accurate information about the system. On the other hand, an efficient reduced-order FSI model is useful for fast simulation and analysis of the vocal fold dynamics, which is often needed in procedures such as optimization and parameter estimation. In this work, we study the performance of a reduced-order model as compared with the corresponding full 3D model in terms of its accuracy in predicting the vibration frequency and deformation mode. In the reduced-order model, we use a 1D flow model coupled with a 3D tissue model. Two different hyperelastic tissue behaviors are assumed. In addition, the vocal fold thickness and subglottal pressure are varied for systematic comparison. The result shows that the reduced-order model provides consistent predictions as the full 3D model across different tissue material assumptions and subglottal pressures. However, the vocal fold thickness has most effect on the model accuracy, especially when the vocal fold is thin. Supported by the NSF.

Volatility modeling for IDR exchange rate through APARCH model with student-t distribution

NASA Astrophysics Data System (ADS)

Nugroho, Didit Budi; Susanto, Bambang

2017-08-01

The aim of this study is to empirically investigate the performance of APARCH(1,1) volatility model with the Student-t error distribution on five foreign currency selling rates to Indonesian rupiah (IDR), including the Swiss franc (CHF), the Euro (EUR), the British pound (GBP), Japanese yen (JPY), and the US dollar (USD). Six years daily closing rates over the period of January 2010 to December 2016 for a total number of 1722 observations have analysed. The Bayesian inference using the efficient independence chain Metropolis-Hastings and adaptive random walk Metropolis methods in the Markov chain Monte Carlo (MCMC) scheme has been applied to estimate the parameters of model. According to the DIC criterion, this study has found that the APARCH(1,1) model under Student-t distribution is a better fit than the model under normal distribution for any observed rate return series. The 95% highest posterior density interval suggested the APARCH models to model the IDR/JPY and IDR/USD volatilities. In particular, the IDR/JPY and IDR/USD data, respectively, have significant negative and positive leverage effect in the rate returns. Meanwhile, the optimal power coefficient of volatility has been found to be statistically different from 2 in adopting all rate return series, save the IDR/EUR rate return series.

Decreasing the temporal complexity for nonlinear, implicit reduced-order models by forecasting

DOE PAGES

Carlberg, Kevin; Ray, Jaideep; van Bloemen Waanders, Bart

2015-02-14

Implicit numerical integration of nonlinear ODEs requires solving a system of nonlinear algebraic equations at each time step. Each of these systems is often solved by a Newton-like method, which incurs a sequence of linear-system solves. Most model-reduction techniques for nonlinear ODEs exploit knowledge of system's spatial behavior to reduce the computational complexity of each linear-system solve. However, the number of linear-system solves for the reduced-order simulation often remains roughly the same as that for the full-order simulation. We propose exploiting knowledge of the model's temporal behavior to (1) forecast the unknown variable of the reduced-order system of nonlinear equationsmore » at future time steps, and (2) use this forecast as an initial guess for the Newton-like solver during the reduced-order-model simulation. To compute the forecast, we propose using the Gappy POD technique. As a result, the goal is to generate an accurate initial guess so that the Newton solver requires many fewer iterations to converge, thereby decreasing the number of linear-system solves in the reduced-order-model simulation.« less

Average inactivity time model, associated orderings and reliability properties

NASA Astrophysics Data System (ADS)

Kayid, M.; Izadkhah, S.; Abouammoh, A. M.

2018-02-01

In this paper, we introduce and study a new model called 'average inactivity time model'. This new model is specifically applicable to handle the heterogeneity of the time of the failure of a system in which some inactive items exist. We provide some bounds for the mean average inactivity time of a lifespan unit. In addition, we discuss some dependence structures between the average variable and the mixing variable in the model when original random variable possesses some aging behaviors. Based on the conception of the new model, we introduce and study a new stochastic order. Finally, to illustrate the concept of the model, some interesting reliability problems are reserved.

The confluence model: birth order as a within-family or between-family dynamic?

PubMed

Zajonc, R B; Sulloway, Frank J

2007-09-01

The confluence model explains birth-order differences in intellectual performance by quantifying the changing dynamics within the family. Wichman, Rodgers, and MacCallum (2006) claimed that these differences are a between-family phenomenon--and hence are not directly related to birth order itself. The study design and analyses presented by Wichman et al. nevertheless suffer from crucial shortcomings, including their use of unfocused tests, which cause statistically significant trends to be overlooked. In addition, Wichman et al. treated birth-order effects as a linear phenomenon thereby ignoring the confluence model's prediction that these two samples may manifest opposing results based on age. This article cites between- and within-family data that demonstrate systematic birth-order effects as predicted by the confluence model. The corpus of evidence invoked here offers strong support for the assumption of the confluence model that birth-order differences in intellectual performance are primarily a within-family phenomenon.

A Simultaneous Equation Demand Model for Block Rates

NASA Astrophysics Data System (ADS)

Agthe, Donald E.; Billings, R. Bruce; Dobra, John L.; Raffiee, Kambiz

1986-01-01

This paper examines the problem of simultaneous-equations bias in estimation of the water demand function under an increasing block rate structure. The Hausman specification test is used to detect the presence of simultaneous-equations bias arising from correlation of the price measures with the regression error term in the results of a previously published study of water demand in Tucson, Arizona. An alternative simultaneous equation model is proposed for estimating the elasticity of demand in the presence of block rate pricing structures and availability of service charges. This model is used to reestimate the price and rate premium elasticities of demand in Tucson, Arizona for both the usual long-run static model and for a simple short-run demand model. The results from these simultaneous equation models are consistent with a priori expectations and are unbiased.

A tridiagonal parsimonious higher order multivariate Markov chain model

NASA Astrophysics Data System (ADS)

Wang, Chao; Yang, Chuan-sheng

2017-09-01

In this paper, we present a tridiagonal parsimonious higher-order multivariate Markov chain model (TPHOMMCM). Moreover, estimation method of the parameters in TPHOMMCM is give. Numerical experiments illustrate the effectiveness of TPHOMMCM.

Monitoring by forward scatter radar techniques: an improved second-order analytical model

NASA Astrophysics Data System (ADS)

Falconi, Marta Tecla; Comite, Davide; Galli, Alessandro; Marzano, Frank S.; Pastina, Debora; Lombardo, Pierfrancesco

2017-10-01

In this work, a second-order phase approximation is introduced to provide an improved analytical model of the signal received in forward scatter radar systems. A typical configuration with a rectangular metallic object illuminated while crossing the baseline, in far- or near-field conditions, is considered. An improved second-order model is compared with a simplified one already proposed by the authors and based on a paraxial approximation. A phase error analysis is carried out to investigate benefits and limitations of the second-order modeling. The results are validated by developing full-wave numerical simulations implementing the relevant scattering problem on a commercial tool.

A cloud model-radiative model combination for determining microwave TB-rain rate relations

NASA Technical Reports Server (NTRS)

Szejwach, Gerard; Adler, Robert F.; Jobard, Esabelle; Mack, Robert A.

1986-01-01

The development of a cloud model-radiative transfer model combination for computing average brightness temperature, T(B), is discussed. The cloud model and radiative transfer model used in this study are described. The relations between rain rate, cloud and rain water, cloud and precipitation ice, and upwelling radiance are investigated. The effects of the rain rate relations on T(B) under different climatological conditions are examined. The model-derived T(B) results are compared to the 92 and 183 GHz aircraft observations of Hakkarinen and Adler (1984, 1986) and the radar-estimated rain rate of Hakkarinen and Adler (1986); good correlation between the data is detected.

Calving laws and strain rates: a comparison between modelled relationships and observations from InSAR velocity maps from across Greenland.

NASA Astrophysics Data System (ADS)

Lea, James; Nick, Faezeh; Benn, Douglas; Kirchner, Nina

2017-04-01

Calving is a major mechanism of cryospheric ice mass loss and a significant contributor to global sea level change, though it is currently poorly understood as a process. Longitudinal strain rate is often cited as a first order control on calving, however multiple different calving laws (not always including the strain rate) have been used to represent this in numerical models of ice sheets. This study seeks to investigate how (1) different calving laws within a 1D flowline model predict strain rate will evolve within increasing terminus thickness for steady state and transient simulations, and (2) how these relationships compare with observed strains (derived from MEaSUREs Greenland InSAR velocity maps; Joughin et al., 2010 [updated 2016]) and depths (from BedMachine v.2 subglacial topography data; Morlighem et al., 2014). We identify that systematic relationships with terminus thickness exist for height above buoyancy, waterline and full-depth crevasse calving laws amongst others for both steady state and transient simulations. However, analysis of observed near-terminus strain rates for multiple Greenlandic glaciers using a variety of metrics (with a range of bed depths predicted by BedMachine) does not reproduce the shape or magnitude of any of these modelled relationships. Relationships between strain rate and depth derived from simple 1D model simulations therefore cannot be realistically compared to current real-world observations. This suggests that the magnitude of observed strain rates at an individual point, or area-averaged conditions near a real-world terminus are not meaningful in determining the potential for calving when taken in isolation. To improve understanding of first/second order calving processes, future modelling work should therefore look to analyse how/if the distribution of strain across the terminus region impacts calving as part of 2D-planform/3D models.

The affects on Titan atmospheric modeling by variable molecular reaction rates

NASA Astrophysics Data System (ADS)

Hamel, Mark D.

The main effort of this thesis is to study the production and loss of molecular ions in the ionosphere of Saturn's largest moon Titan. Titan's atmosphere is subject to complex photochemical processes that can lead to the production of higher order hydrocarbons and nitriles. Ion-molecule chemistry plays an important role in this process but remains poorly understood. In particular, current models that simulate the photochemistry of Titan's atmosphere overpredict the abundance of the ionosphere's main ions suggesting a flaw in the modeling process. The objective of this thesis is to determine which reactions are most important for production and loss of the two primary ions, C2H5+ and HCNH+, and what is the impact of uncertainty in the reaction rates on the production and loss of these ions. In reviewing the literature, there is a contention about what reactions are really necessary to illuminate what is occurring in the atmosphere. Approximately seven hundred reactions are included in the model used in this discussion (INT16). This paper studies what reactions are fundamental to the atmospheric processes in Titan's upper atmosphere, and also to the reactions that occur in the lower bounds of the ionosphere which are used to set a baseline molecular density for all species, and reflects what is expected at those altitudes on Titan. This research was conducted through evaluating reaction rates and cross sections available in the scientific literature and through conducting model simulations of the photochemistry in Titan's atmosphere under a range of conditions constrained by the literature source. The objective of this study is to determine the dependence of ion densities of C2H5+ and HCNH+ on the uncertainty in the reaction rates that involve these two ions in Titan's atmosphere.

Lessons from a low-order coupled chemistry meteorology model and applications to a high-dimensional chemical transport model

NASA Astrophysics Data System (ADS)

Haussaire, Jean-Matthieu; Bocquet, Marc

2016-04-01

Atmospheric chemistry models are becoming increasingly complex, with multiphasic chemistry, size-resolved particulate matter, and possibly coupled to numerical weather prediction models. In the meantime, data assimilation methods have also become more sophisticated. Hence, it will become increasingly difficult to disentangle the merits of data assimilation schemes, of models, and of their numerical implementation in a successful high-dimensional data assimilation study. That is why we believe that the increasing variety of problems encountered in the field of atmospheric chemistry data assimilation puts forward the need for simple low-order models, albeit complex enough to capture the relevant dynamics, physics and chemistry that could impact the performance of data assimilation schemes. Following this analysis, we developped a low-order coupled chemistry meteorology model named L95-GRS [1]. The advective wind is simulated by the Lorenz-95 model, while the chemistry is made of 6 reactive species and simulates ozone concentrations. With this model, we carried out data assimilation experiments to estimate the state of the system as well as the forcing parameter of the wind and the emissions of chemical compounds. This model proved to be a powerful playground giving insights on the hardships of online and offline estimation of atmospheric pollution. Building on the results on this low-order model, we test advanced data assimilation methods on a state-of-the-art chemical transport model to check if the conclusions obtained with our low-order model still stand. References [1] Haussaire, J.-M. and Bocquet, M.: A low-order coupled chemistry meteorology model for testing online and offline data assimilation schemes, Geosci. Model Dev. Discuss., 8, 7347-7394, doi:10.5194/gmdd-8-7347-2015, 2015.

ICA model order selection of task co-activation networks.

PubMed

Ray, Kimberly L; McKay, D Reese; Fox, Peter M; Riedel, Michael C; Uecker, Angela M; Beckmann, Christian F; Smith, Stephen M; Fox, Peter T; Laird, Angela R

2013-01-01

Independent component analysis (ICA) has become a widely used method for extracting functional networks in the brain during rest and task. Historically, preferred ICA dimensionality has widely varied within the neuroimaging community, but typically varies between 20 and 100 components. This can be problematic when comparing results across multiple studies because of the impact ICA dimensionality has on the topology of its resultant components. Recent studies have demonstrated that ICA can be applied to peak activation coordinates archived in a large neuroimaging database (i.e., BrainMap Database) to yield whole-brain task-based co-activation networks. A strength of applying ICA to BrainMap data is that the vast amount of metadata in BrainMap can be used to quantitatively assess tasks and cognitive processes contributing to each component. In this study, we investigated the effect of model order on the distribution of functional properties across networks as a method for identifying the most informative decompositions of BrainMap-based ICA components. Our findings suggest dimensionality of 20 for low model order ICA to examine large-scale brain networks, and dimensionality of 70 to provide insight into how large-scale networks fractionate into sub-networks. We also provide a functional and organizational assessment of visual, motor, emotion, and interoceptive task co-activation networks as they fractionate from low to high model-orders.

ICA model order selection of task co-activation networks

PubMed Central

Ray, Kimberly L.; McKay, D. Reese; Fox, Peter M.; Riedel, Michael C.; Uecker, Angela M.; Beckmann, Christian F.; Smith, Stephen M.; Fox, Peter T.; Laird, Angela R.

2013-01-01

Independent component analysis (ICA) has become a widely used method for extracting functional networks in the brain during rest and task. Historically, preferred ICA dimensionality has widely varied within the neuroimaging community, but typically varies between 20 and 100 components. This can be problematic when comparing results across multiple studies because of the impact ICA dimensionality has on the topology of its resultant components. Recent studies have demonstrated that ICA can be applied to peak activation coordinates archived in a large neuroimaging database (i.e., BrainMap Database) to yield whole-brain task-based co-activation networks. A strength of applying ICA to BrainMap data is that the vast amount of metadata in BrainMap can be used to quantitatively assess tasks and cognitive processes contributing to each component. In this study, we investigated the effect of model order on the distribution of functional properties across networks as a method for identifying the most informative decompositions of BrainMap-based ICA components. Our findings suggest dimensionality of 20 for low model order ICA to examine large-scale brain networks, and dimensionality of 70 to provide insight into how large-scale networks fractionate into sub-networks. We also provide a functional and organizational assessment of visual, motor, emotion, and interoceptive task co-activation networks as they fractionate from low to high model-orders. PMID:24339802

Malaria transmission rates estimated from serological data.

PubMed Central

Burattini, M. N.; Massad, E.; Coutinho, F. A.

1993-01-01

A mathematical model was used to estimate malaria transmission rates based on serological data. The model is minimally stochastic and assumes an age-dependent force of infection for malaria. The transmission rates estimated were applied to a simple compartmental model in order to mimic the malaria transmission. The model has shown a good retrieving capacity for serological and parasite prevalence data. PMID:8270011

Tuning algorithms for fractional order internal model controllers for time delay processes

NASA Astrophysics Data System (ADS)

Muresan, Cristina I.; Dutta, Abhishek; Dulf, Eva H.; Pinar, Zehra; Maxim, Anca; Ionescu, Clara M.

2016-03-01

This paper presents two tuning algorithms for fractional-order internal model control (IMC) controllers for time delay processes. The two tuning algorithms are based on two specific closed-loop control configurations: the IMC control structure and the Smith predictor structure. In the latter, the equivalency between IMC and Smith predictor control structures is used to tune a fractional-order IMC controller as the primary controller of the Smith predictor structure. Fractional-order IMC controllers are designed in both cases in order to enhance the closed-loop performance and robustness of classical integer order IMC controllers. The tuning procedures are exemplified for both single-input-single-output as well as multivariable processes, described by first-order and second-order transfer functions with time delays. Different numerical examples are provided, including a general multivariable time delay process. Integer order IMC controllers are designed in each case, as well as fractional-order IMC controllers. The simulation results show that the proposed fractional-order IMC controller ensures an increased robustness to modelling uncertainties. Experimental results are also provided, for the design of a multivariable fractional-order IMC controller in a Smith predictor structure for a quadruple-tank system.

Performance of a reduced-order FSI model for flow-induced vocal fold vibration

NASA Astrophysics Data System (ADS)

Luo, Haoxiang; Chang, Siyuan; Chen, Ye; Rousseau, Bernard; PhonoSim Team

2017-11-01

Vocal fold vibration during speech production involves a three-dimensional unsteady glottal jet flow and three-dimensional nonlinear tissue mechanics. A full 3D fluid-structure interaction (FSI) model is computationally expensive even though it provides most accurate information about the system. On the other hand, an efficient reduced-order FSI model is useful for fast simulation and analysis of the vocal fold dynamics, which can be applied in procedures such as optimization and parameter estimation. In this work, we study performance of a reduced-order model as compared with the corresponding full 3D model in terms of its accuracy in predicting the vibration frequency and deformation mode. In the reduced-order model, we use a 1D flow model coupled with a 3D tissue model that is the same as in the full 3D model. Two different hyperelastic tissue behaviors are assumed. In addition, the vocal fold thickness and subglottal pressure are varied for systematic comparison. The result shows that the reduced-order model provides consistent predictions as the full 3D model across different tissue material assumptions and subglottal pressures. However, the vocal fold thickness has most effect on the model accuracy, especially when the vocal fold is thin.

Simple stochastic order-book model of swarm behavior in continuous double auction

NASA Astrophysics Data System (ADS)

Ichiki, Shingo; Nishinari, Katsuhiro

2015-02-01

In this study, we present a simple stochastic order-book model for investors' swarm behaviors seen in the continuous double auction mechanism, which is employed by major global exchanges. Our study shows a characteristic called 'fat tail' seen in the data obtained from our model that incorporates the investors' swarm behaviors. Our model captures two swarm behaviors: one is investors' behavior to follow a trend in the historical price movement, and another is investors' behavior to send orders that contradict a trend in the historical price movement. In order to capture the features of influence by the swarm behaviors, from price data derived from our simulations using these models, we analyzed the price movement range, that is, how much the price is moved when it is continuously moved in a single direction. Depending on the type of swarm behavior, we saw a difference in the cumulative frequency distribution of this price movement range. In particular, for the model of investors who followed a trend in the historical price movement, we saw the power law in the tail of the cumulative frequency distribution of this price movement range. In addition, we analyzed the shape of the tail of the cumulative frequency distribution. The result demonstrated that one of the reasons the trend following of price occurs is that orders temporarily swarm on the order book in accordance with past price trends.

Computational procedure of optimal inventory model involving controllable backorder rate and variable lead time with defective units

NASA Astrophysics Data System (ADS)

Lee, Wen-Chuan; Wu, Jong-Wuu; Tsou, Hsin-Hui; Lei, Chia-Ling

2012-10-01

This article considers that the number of defective units in an arrival order is a binominal random variable. We derive a modified mixture inventory model with backorders and lost sales, in which the order quantity and lead time are decision variables. In our studies, we also assume that the backorder rate is dependent on the length of lead time through the amount of shortages and let the backorder rate be a control variable. In addition, we assume that the lead time demand follows a mixture of normal distributions, and then relax the assumption about the form of the mixture of distribution functions of the lead time demand and apply the minimax distribution free procedure to solve the problem. Furthermore, we develop an algorithm procedure to obtain the optimal ordering strategy for each case. Finally, three numerical examples are also given to illustrate the results.

Effects of competition among fertility centers on pregnancy and high-order multiple gestation rates.

PubMed

Steiner, Anne Z; Paulson, Richard J; Hartmann, Katherine E

2005-05-01

To measure the effect of competition among fertility centers on pregnancy and high-order multiple (HOM) gestation rates after IVF. Retrospective cohort study. Four hundred eight fertility clinics registered with the Society for Assisted Reproductive Technology as providing IVF services in 2000. Competition was defined as number of clinics in a geographically defined area. Demand for services was based on the population of reproductive-aged women. Three hundred eighty-one fertility clinics reporting clinical outcomes. Pregnancy rates, HOM gestation rates, population of reproductive-aged women, and number of competing clinics were calculated for each clinic from Society for Assisted Reproductive Technology and census data. The clinic HOM gestation rate (percentage of pregnancies that were HOM) and age-adjusted pregnancy rate. The number of clinics in an area of competition ranged from 1 to 22. The HOM gestation rate per clinic ranged from 0% to 50%. As demand increased, competition increased. As competition increased, the number of HOM pregnancies per clinic decreased. In areas of low competition (1 to 2 clinics) the clinic HOM gestation rate was 8.43%, in areas of intermediate competition (3-7 clinics) 8.39%, and in areas of high competition (8-22 clinics) 8.24%. In areas with intermediate demand, high levels of competition resulted in fewer HOM pregnancies than intermediate competition (relative risk 0.56, 95% confidence interval 0.36-0.89) or low levels of competition (RR 0.57, 95% confidence interval 0.35-0.94). Age-adjusted pregnancy rates did not differ by level of competition. According to these data, the risk of HOM gestation decreases with increasing competition among clinics; however, pregnancy rates are unaffected.

Z3 topological order in the face-centered-cubic quantum plaquette model

NASA Astrophysics Data System (ADS)

Devakul, Trithep

2018-04-01

We examine the topological order in the resonating singlet valence plaquette (RSVP) phase of the hard-core quantum plaquette model (QPM) on the face centered cubic (FCC) lattice. To do this, we construct a Rohksar-Kivelson type Hamiltonian of local plaquette resonances. This model is shown to exhibit a Z3 topological order, which we show by identifying a Z3 topological constant (which leads to a 33-fold topological ground state degeneracy on the 3-torus) and topological pointlike charge and looplike magnetic excitations which obey Z3 statistics. We also consider an exactly solvable generalization of this model, which makes the geometrical origin of the Z3 order explicitly clear. For other models and lattices, such generalizations produce a wide variety of topological phases, some of which are novel fracton phases.

Fuzzy time series forecasting model with natural partitioning length approach for predicting the unemployment rate under different degree of confidence

NASA Astrophysics Data System (ADS)

Ramli, Nazirah; Mutalib, Siti Musleha Ab; Mohamad, Daud

2017-08-01

Fuzzy time series forecasting model has been proposed since 1993 to cater for data in linguistic values. Many improvement and modification have been made to the model such as enhancement on the length of interval and types of fuzzy logical relation. However, most of the improvement models represent the linguistic term in the form of discrete fuzzy sets. In this paper, fuzzy time series model with data in the form of trapezoidal fuzzy numbers and natural partitioning length approach is introduced for predicting the unemployment rate. Two types of fuzzy relations are used in this study which are first order and second order fuzzy relation. This proposed model can produce the forecasted values under different degree of confidence.