Automated Design Tools for Integrated Mixed-Signal Microsystems (NeoCAD)

DTIC Science & Technology

2005-02-01

method, Model Order Reduction (MOR) tools, system-level, mixed-signal circuit synthesis and optimization tools, and parsitic extraction tools. A unique...Mission Area: Command and Control mixed signal circuit simulation parasitic extraction time-domain simulation IC design flow model order reduction... Extraction 1.2 Overall Program Milestones CHAPTER 2 FAST TIME DOMAIN MIXED-SIGNAL CIRCUIT SIMULATION 2.1 HAARSPICE Algorithms 2.1.1 Mathematical Background

A single-vendor and a single-buyer integrated inventory model with ordering cost reduction dependent on lead time

NASA Astrophysics Data System (ADS)

Vijayashree, M.; Uthayakumar, R.

2017-09-01

Lead time is one of the major limits that affect planning at every stage of the supply chain system. In this paper, we study a continuous review inventory model. This paper investigates the ordering cost reductions are dependent on lead time. This study addressed two-echelon supply chain problem consisting of a single vendor and a single buyer. The main contribution of this study is that the integrated total cost of the single vendor and the single buyer integrated system is analyzed by adopting two different (linear and logarithmic) types ordering cost reductions act dependent on lead time. In both cases, we develop effective solution procedures for finding the optimal solution and then illustrative numerical examples are given to illustrate the results. The solution procedure is to determine the optimal solutions of order quantity, ordering cost, lead time and the number of deliveries from the single vendor and the single buyer in one production run, so that the integrated total cost incurred has the minimum value. Ordering cost reduction is the main aspect of the proposed model. A numerical example is given to validate the model. Numerical example solved by using Matlab software. The mathematical model is solved analytically by minimizing the integrated total cost. Furthermore, the sensitivity analysis is included and the numerical examples are given to illustrate the results. The results obtained in this paper are illustrated with the help of numerical examples. The sensitivity of the proposed model has been checked with respect to the various major parameters of the system. Results reveal that the proposed integrated inventory model is more applicable for the supply chain manufacturing system. For each case, an algorithm procedure of finding the optimal solution is developed. Finally, the graphical representation is presented to illustrate the proposed model and also include the computer flowchart in each model.

A Control Concept for Large Flexible Spacecraft Using Order Reduction Techniques

NASA Technical Reports Server (NTRS)

Thieme, G.; Roth, H.

1985-01-01

Results found during the investigation of control problems of large flexible spacecraft are given. A triple plate configuration of such a spacecraft is defined and studied. The model is defined by modal data derived from infinite element modeling. The order reduction method applied is briefly described. An attitude control concept with low and high authority control has been developed to design an attitude controller for the reduced model. The stability and response of the original system together with the reduced controller is analyzed.

Certified dual-corrected radiation patterns of phased antenna arrays by offline–online order reduction of finite-element models

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

Sommer, A., E-mail: a.sommer@lte.uni-saarland.de; Farle, O., E-mail: o.farle@lte.uni-saarland.de; Dyczij-Edlinger, R., E-mail: edlinger@lte.uni-saarland.de

2015-10-15

This paper presents a fast numerical method for computing certified far-field patterns of phased antenna arrays over broad frequency bands as well as wide ranges of steering and look angles. The proposed scheme combines finite-element analysis, dual-corrected model-order reduction, and empirical interpolation. To assure the reliability of the results, improved a posteriori error bounds for the radiated power and directive gain are derived. Both the reduced-order model and the error-bounds algorithm feature offline–online decomposition. A real-world example is provided to demonstrate the efficiency and accuracy of the suggested approach.

High precision NC lathe feeding system rigid-flexible coupling model reduction technology

NASA Astrophysics Data System (ADS)

Xuan, He; Hua, Qingsong; Cheng, Lianjun; Zhang, Hongxin; Zhao, Qinghai; Mao, Xinkai

2017-08-01

This paper proposes the use of dynamic substructure method of reduction of order to achieve effective reduction of feed system for high precision NC lathe feeding system rigid-flexible coupling model, namely the use of ADAMS to establish the rigid flexible coupling simulation model of high precision NC lathe, and then the vibration simulation of the period by using the FD 3D damper is very effective for feed system of bolt connection reduction of multi degree of freedom model. The vibration simulation calculation is more accurate, more quickly.

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.

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.

Combining Static Analysis and Model Checking for Software Analysis

NASA Technical Reports Server (NTRS)

Brat, Guillaume; Visser, Willem; Clancy, Daniel (Technical Monitor)

2003-01-01

We present an iterative technique in which model checking and static analysis are combined to verify large software systems. The role of the static analysis is to compute partial order information which the model checker uses to reduce the state space. During exploration, the model checker also computes aliasing information that it gives to the static analyzer which can then refine its analysis. The result of this refined analysis is then fed back to the model checker which updates its partial order reduction. At each step of this iterative process, the static analysis computes optimistic information which results in an unsafe reduction of the state space. However we show that the process converges to a fired point at which time the partial order information is safe and the whole state space is explored.

Climate change air toxic co-reduction in the context of macroeconomic modelling.

PubMed

Crawford-Brown, Douglas; Chen, Pi-Cheng; Shi, Hsiu-Ching; Chao, Chia-Wei

2013-08-15

This paper examines the health implications of global PM reduction accompanying greenhouse gas emissions reductions in the 180 national economies of the global macroeconomy. A human health effects module based on empirical data on GHG emissions, PM emissions, background PM concentrations, source apportionment and human health risk coefficients is used to estimate reductions in morbidity and mortality from PM exposures globally as co-reduction of GHG reductions. These results are compared against the "fuzzy bright line" that often underlies regulatory decisions for environmental toxics, and demonstrate that the risk reduction through PM reduction would usually be considered justified in traditional risk-based decisions for environmental toxics. It is shown that this risk reduction can be on the order of more than 4 × 10(-3) excess lifetime mortality risk, with global annual cost savings of slightly more than $10B, when uniform GHG reduction measures across all sectors of the economy form the basis for climate policy ($2.2B if only Annex I nations reduce). Consideration of co-reduction of PM-10 within a climate policy framework harmonized with other environmental policies can therefore be an effective driver of climate policy. An error analysis comparing results of the current model against those of significantly more spatially resolved models at city and national scales indicates errors caused by the low spatial resolution of the global model used here may be on the order of a factor of 2. Copyright © 2013 Elsevier Ltd. All rights reserved.

Reduction Rates for Higher Americium Oxidation States in Nitric Acid

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

Grimes, Travis Shane; Mincher, Bruce Jay; Schmitt, Nicholas C

The stability of hexavalent americium was measured using multiple americium concentrations and nitric acid concentrations after contact with the strong oxidant sodium bismuthate. Contrary to our hypotheses Am(VI) was not reduced faster at higher americium concentrations, and the reduction was only zero-order at short time scales. Attempts to model the reduction kinetics using zero order kinetic models showed Am(VI) reduction in nitric acid is more complex than the autoreduction processes reported by others in perchloric acid. The classical zero-order reduction of Am(VI) was found here only for short times on the order of a few hours. We did show thatmore » the rate of Am(V) production was less than the rate of Am(VI) reduction, indicating that some Am(VI) undergoes two electron-reduction to Am(IV). We also monitored the Am(VI) reduction in contact with the organic diluent dodecane. A direct comparison of these results with those in the absence of the organic diluent showed the reduction rates for Am(VI) were not statistically different for both systems. Additional americium oxidations conducted in the presence of Ce(IV)/Ce(III) ions showed that Am(VI) is reduced without the typical growth of Am(V) observed in the systems sans Ce ion. This was an interesting result which suggests a potential new reduction/oxidation pathway for Am in the presence of Ce; however, these results were very preliminary, and will require additional experiments to understand the mechanism by which this occurs. Overall, these studies have shown that hexavalent americium is fundamentally stable enough in nitric acid to run a separations process. However, the complicated nature of the reduction pathways based on the system components is far from being rigorously understood.« less

Flexible system model reduction and control system design based upon actuator and sensor influence functions

NASA Technical Reports Server (NTRS)

Yam, Yeung; Johnson, Timothy L.; Lang, Jeffrey H.

1987-01-01

A model reduction technique based on aggregation with respect to sensor and actuator influence functions rather than modes is presented for large systems of coupled second-order differential equations. Perturbation expressions which can predict the effects of spillover on both the reduced-order plant model and the neglected plant model are derived. For the special case of collocated actuators and sensors, these expressions lead to the derivation of constraints on the controller gains that are, given the validity of the perturbation technique, sufficient to guarantee the stability of the closed-loop system. A case study demonstrates the derivation of stabilizing controllers based on the present technique. The use of control and observation synthesis in modifying the dimension of the reduced-order plant model is also discussed. A numerical example is provided for illustration.

Model reduction in integrated controls-structures design

NASA Technical Reports Server (NTRS)

Maghami, Peiman G.

1993-01-01

It is the objective of this paper to present a model reduction technique developed for the integrated controls-structures design of flexible structures. Integrated controls-structures design problems are typically posed as nonlinear mathematical programming problems, where the design variables consist of both structural and control parameters. In the solution process, both structural and control design variables are constantly changing; therefore, the dynamic characteristics of the structure are also changing. This presents a problem in obtaining a reduced-order model for active control design and analysis which will be valid for all design points within the design space. In other words, the frequency and number of the significant modes of the structure (modes that should be included) may vary considerably throughout the design process. This is also true as the locations and/or masses of the sensors and actuators change. Moreover, since the number of design evaluations in the integrated design process could easily run into thousands, any feasible order-reduction method should not require model reduction analysis at every design iteration. In this paper a novel and efficient technique for model reduction in the integrated controls-structures design process, which addresses these issues, is presented.

Kinetic modeling of liquefied petroleum gas (LPG) reduction of titania in MATLAB

NASA Astrophysics Data System (ADS)

Yin, Tan Wei; Ramakrishnan, Sivakumar; Rezan, Sheikh Abdul; Noor, Ahmad Fauzi Mohd; Izah Shoparwe, Noor; Alizadeh, Reza; Roohi, Parham

2017-04-01

In the present study, reduction of Titania (TiO2) by liquefied petroleum gas (LPG)-hydrogen-argon gas mixture was investigated by experimental and kinetic modelling in MATLAB. The reduction experiments were carried out in the temperature range of 1100-1200°C with a reduction time from 1-3 hours and 10-20 minutes of LPG flowing time. A shrinking core model (SCM) was employed for the kinetic modelling in order to determine the rate and extent of reduction. The highest experimental extent of reduction of 38% occurred at a temperature of 1200°C with 3 hours reduction time and 20 minutes of LPG flowing time. The SCM gave a predicted extent of reduction of 82.1% due to assumptions made in the model. The deviation between SCM and experimental data was attributed to porosity, thermodynamic properties and minute thermal fluctuations within the sample. In general, the reduction rates increased with increasing reduction temperature and LPG flowing time.

Modeling hexavalent chromium reduction in groundwater in field-scale transport and laboratory batch experiments

USGS Publications Warehouse

Friedly, J.C.; Davis, J.A.; Kent, D.B.

1995-01-01

A plausible and consistent model is developed to obtain a quantitative description of the gradual disappearance of hexavalent chromium (Cr(VI)) from groundwater in a small-scale field tracer test and in batch kinetic experiments using aquifer sediments under similar chemical conditions. The data exhibit three distinct timescales. Fast reduction occurs in well-stirred batch reactors in times much less than 1 hour and is followed by slow reduction over a timescale of the order of 2 days. In the field, reduction occurs on a timescale of the order of 8 days. The model is based on the following hypotheses. The chemical reduction reaction occurs very fast, and the longer timescales are caused by diffusion resistance. Diffusion into the secondary porosity of grains causes the apparent slow reduction rate in batch experiments. In the model of the field experiments, the reducing agent, heavy Fe(II)-bearing minerals, is heterogeneously distributed in thin strata located between larger nonreducing sand lenses that comprise the bulk of the aquifer solids. It is found that reducing strata of the order of centimeters thick are sufficient to contribute enough diffusion resistance to cause the observed longest timescale in the field. A one-dimensional advection/dispersion model is formulated that describes the major experimental trends. Diffusion rates are estimated in terms of an elementary physical picture of flow through a stratified medium containing identically sized spherical grains. Both reduction and sorption reactions are included. Batch simulation results are sensitive to the fraction of reductant located at or near the surface of grains, which controls the amount of rapid reduction, and the secondary porosity, which controls the rate of slow reduction observed in batch experiments. Results of Cr(VI) transport simulations are sensitive to the thickness and relative size of the reducing stratum. Transport simulation results suggest that nearly all of the reductant must be located in the reducing stratum. Within this context and as long as there is adequate reductive capacity present, the transport simulation results are insensitive to the parameters important for the batch simulations. The results illustrate how a combination of field measurements and batch laboratory studies can be used to improve predictive modeling of contaminant transport.

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.

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 dynamical model to augment the linear input/output model. Thus, the full system is decomposed into a dominant linear subsystem and a low order nonlinear subsystem. The hybrid model is then used for control design and compared with other modeling methods in CFD simulations. Numerical results indicate that the hybrid model accurately predicts the nonlinear behavior of the flow for a 2D diffuser contraction section model. It also performs best in terms of feedback control design and learning control. Since some outputs of interest (e.g., the AIP pressure recovery) are not observable during normal operations, static and dynamic estimators are designed to recreate the information from available sensor measurements. The latter also provides a state estimation for feedback controller. Based on the reduced order models and estimators, different controllers are designed to improve the aerodynamic performance of the contraction section and inlet duct. The integrated control methodology is evaluated with CFD simulations. Numerical results demonstrate the feasibility and efficacy of the active flow control based on reduced order models. Our reduced order models not only generate a good approximation of the nonlinear flow dynamics over a wide input range, but also help to design controllers that significantly improve the flow response. The tools developed for model reduction, estimator and control design can also be applied to wind tunnel experiment.

Modeling hexavalent chromium removal in a Bacillus sp. fixed-film bioreactor.

PubMed

Nkhalambayausi-Chirwa, Evans M; Wang, Yi-Tin

2004-09-30

A one-dimensional diffusion-reaction model was developed to simulate Cr(VI) reduction in a Bacillus sp. pure culture biofilm reactor with glucose as a sole supplied carbon and energy source. Substrate utilization and Cr(VI) reduction in the biofilm was best represented by a system of (second-order) partial differential equations (PDEs). The PDE system was solved by the (fourth-order) Runge-Kutta method adjusted for mass transport resistance using the (second-order) Crank-Nicholson and Backward Euler finite difference methods. A heuristic procedure (genetic search algorithm) was used to find global optimum values of Cr(VI) reduction and substrate utilization rate kinetic parameters. The fixed-film bioreactor system yielded higher values of the maximum specific Cr(VI) reduction rate coefficient and Cr(VI) reduction capacity (kmc = 0.062 1/h, and Rc = 0.13 mg/mg, respectively) than previously determined in batch reactors (kmc = 0.022 1/h and Rc = 0.012 mg/mg). The model predicted effluent Cr(VI) concentration well with 98.9% confidence (sigmay2 = 2.37 mg2/L2, N = 119) and effluent glucose with 96.4 % confidence (sigmay(w)2 = 5402 mg2/L2, N = 121, w = 100) over a wide range of Cr(VI) loadings (10-498 mg Cr(VI)/L/d). Copyright 2004 Wiley Periodicals, Inc.

An adaptive model order reduction by proper snapshot selection for nonlinear dynamical problems

NASA Astrophysics Data System (ADS)

Nigro, P. S. B.; Anndif, M.; Teixeira, Y.; Pimenta, P. M.; Wriggers, P.

2016-04-01

Model Order Reduction (MOR) methods are employed in many fields of Engineering in order to reduce the processing time of complex computational simulations. A usual approach to achieve this is the application of Galerkin projection to generate representative subspaces (reduced spaces). However, when strong nonlinearities in a dynamical system are present and this technique is employed several times along the simulation, it can be very inefficient. This work proposes a new adaptive strategy, which ensures low computational cost and small error to deal with this problem. This work also presents a new method to select snapshots named Proper Snapshot Selection (PSS). The objective of the PSS is to obtain a good balance between accuracy and computational cost by improving the adaptive strategy through a better snapshot selection in real time (online analysis). With this method, it is possible a substantial reduction of the subspace, keeping the quality of the model without the use of the Proper Orthogonal Decomposition (POD).

Trimming a hazard logic tree with a new model-order-reduction technique

USGS Publications Warehouse

Porter, Keith; Field, Edward; Milner, Kevin R

2017-01-01

The size of the logic tree within the Uniform California Earthquake Rupture Forecast Version 3, Time-Dependent (UCERF3-TD) model can challenge risk analyses of large portfolios. An insurer or catastrophe risk modeler concerned with losses to a California portfolio might have to evaluate a portfolio 57,600 times to estimate risk in light of the hazard possibility space. Which branches of the logic tree matter most, and which can one ignore? We employed two model-order-reduction techniques to simplify the model. We sought a subset of parameters that must vary, and the specific fixed values for the remaining parameters, to produce approximately the same loss distribution as the original model. The techniques are (1) a tornado-diagram approach we employed previously for UCERF2, and (2) an apparently novel probabilistic sensitivity approach that seems better suited to functions of nominal random variables. The new approach produces a reduced-order model with only 60 of the original 57,600 leaves. One can use the results to reduce computational effort in loss analyses by orders of magnitude.

A decentralized linear quadratic control design method for flexible structures

NASA Technical Reports Server (NTRS)

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

1990-01-01

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

REDUCTIVE DEHALOGENATION OF HALOMETHANES IN IRON- AND SULFATE-REDUCING SEDIMENTS. 1. REACTIVITY PATTERN ANALYSIS

EPA Science Inventory

The incorporation of reductive transformations into environmental fate models requires the characterization of natural reductants in well-characterized sediments and aquifer materials. For this purpose, reactivity patterns (i.e., the range and relative order of reactivity) for a...

Persistent model order reduction for complex dynamical systems using smooth orthogonal decomposition

NASA Astrophysics Data System (ADS)

Ilbeigi, Shahab; Chelidze, David

2017-11-01

Full-scale complex dynamic models are not effective for parametric studies due to the inherent constraints on available computational power and storage resources. A persistent reduced order model (ROM) that is robust, stable, and provides high-fidelity simulations for a relatively wide range of parameters and operating conditions can provide a solution to this problem. The fidelity of a new framework for persistent model order reduction of large and complex dynamical systems is investigated. The framework is validated using several numerical examples including a large linear system and two complex nonlinear systems with material and geometrical nonlinearities. While the framework is used for identifying the robust subspaces obtained from both proper and smooth orthogonal decompositions (POD and SOD, respectively), the results show that SOD outperforms POD in terms of stability, accuracy, and robustness.

Modelling and simulation of a heat exchanger

NASA Technical Reports Server (NTRS)

Xia, Lei; Deabreu-Garcia, J. Alex; Hartley, Tom T.

1991-01-01

Two models for two different control systems are developed for a parallel heat exchanger. First by spatially lumping a heat exchanger model, a good approximate model which has a high system order is produced. Model reduction techniques are applied to these to obtain low order models that are suitable for dynamic analysis and control design. The simulation method is discussed to ensure a valid simulation result.

Jacobian projection reduced-order models for dynamic systems with contact nonlinearities

NASA Astrophysics Data System (ADS)

Gastaldi, Chiara; Zucca, Stefano; Epureanu, Bogdan I.

2018-02-01

In structural dynamics, the prediction of the response of systems with localized nonlinearities, such as friction dampers, is of particular interest. This task becomes especially cumbersome when high-resolution finite element models are used. While state-of-the-art techniques such as Craig-Bampton component mode synthesis are employed to generate reduced order models, the interface (nonlinear) degrees of freedom must still be solved in-full. For this reason, a new generation of specialized techniques capable of reducing linear and nonlinear degrees of freedom alike is emerging. This paper proposes a new technique that exploits spatial correlations in the dynamics to compute a reduction basis. The basis is composed of a set of vectors obtained using the Jacobian of partial derivatives of the contact forces with respect to nodal displacements. These basis vectors correspond to specifically chosen boundary conditions at the contacts over one cycle of vibration. The technique is shown to be effective in the reduction of several models studied using multiple harmonics with a coupled static solution. In addition, this paper addresses another challenge common to all reduction techniques: it presents and validates a novel a posteriori error estimate capable of evaluating the quality of the reduced-order solution without involving a comparison with the full-order solution.

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

Model reductions using a projection formulation

NASA Technical Reports Server (NTRS)

De Villemagne, Christian; Skelton, Robert E.

1987-01-01

A new methodology for model reduction of MIMO systems exploits the notion of an oblique projection. A reduced model is uniquely defined by a projector whose range space and orthogonal to the null space are chosen among the ranges of generalized controllability and observability matrices. The reduced order models match various combinations (chosen by the designer) of four types of parameters of the full order system associated with (1) low frequency response, (2) high frequency response, (3) low frequency power spectral density, and (4) high frequency power spectral density. Thus, the proposed method is a computationally simple substitute for many existing methods, has an extreme flexibility to embrace combinations of existing methods and offers some new features.

Space-time least-squares Petrov-Galerkin projection in nonlinear model reduction.

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

Choi, Youngsoo; Carlberg, Kevin Thomas

Our work proposes a space-time least-squares Petrov-Galerkin (ST-LSPG) projection method for model reduction of nonlinear dynamical systems. In contrast to typical nonlinear model-reduction methods that first apply Petrov-Galerkin projection in the spatial dimension and subsequently apply time integration to numerically resolve the resulting low-dimensional dynamical system, the proposed method applies projection in space and time simultaneously. To accomplish this, the method first introduces a low-dimensional space-time trial subspace, which can be obtained by computing tensor decompositions of state-snapshot data. The method then computes discrete-optimal approximations in this space-time trial subspace by minimizing the residual arising after time discretization over allmore » space and time in a weighted ℓ 2-norm. This norm can be de ned to enable complexity reduction (i.e., hyper-reduction) in time, which leads to space-time collocation and space-time GNAT variants of the ST-LSPG method. Advantages of the approach relative to typical spatial-projection-based nonlinear model reduction methods such as Galerkin projection and least-squares Petrov-Galerkin projection include: (1) a reduction of both the spatial and temporal dimensions of the dynamical system, (2) the removal of spurious temporal modes (e.g., unstable growth) from the state space, and (3) error bounds that exhibit slower growth in time. Numerical examples performed on model problems in fluid dynamics demonstrate the ability of the method to generate orders-of-magnitude computational savings relative to spatial-projection-based reduced-order models without sacrificing accuracy.« less

Unsymmetric Lanczos model reduction and linear state function observer for flexible structures

NASA Technical Reports Server (NTRS)

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

1991-01-01

This report summarizes part of the research work accomplished during the second year of a two-year grant. The research, entitled 'Application of Lanczos Vectors to Control Design of Flexible Structures' concerns various ways to use Lanczos vectors and Krylov vectors to obtain reduced-order mathematical models for use in the dynamic response analyses and in control design studies. This report presents a one-sided, unsymmetric block Lanczos algorithm for model reduction of structural dynamics systems with unsymmetric damping matrix, and a control design procedure based on the theory of linear state function observers to design low-order controllers for flexible structures.

Discrete-time model reduction in limited frequency ranges

NASA Technical Reports Server (NTRS)

Horta, Lucas G.; Juang, Jer-Nan; Longman, Richard W.

1991-01-01

A mathematical formulation for model reduction of discrete time systems such that the reduced order model represents the system in a particular frequency range is discussed. The algorithm transforms the full order system into balanced coordinates using frequency weighted discrete controllability and observability grammians. In this form a criterion is derived to guide truncation of states based on their contribution to the frequency range of interest. Minimization of the criterion is accomplished without need for numerical optimization. Balancing requires the computation of discrete frequency weighted grammians. Close form solutions for the computation of frequency weighted grammians are developed. Numerical examples are discussed to demonstrate the algorithm.

Recent literature on structural modeling, identification, and analysis

NASA Technical Reports Server (NTRS)

Craig, Roy R., Jr.

1990-01-01

The literature on the mathematical modeling of large space structures is first reviewed, with attention given to continuum models, model order reduction, substructuring, and computational techniques. System identification and mode verification are then discussed with reference to the verification of mathematical models of large space structures. In connection with analysis, the paper surveys recent research on eigensolvers and dynamic response solvers for large-order finite-element-based models.

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.

Approximating recreation site choice: the predictive capability of a lexicographic semi-order model

Treesearch

Alan E. Watson; Joseph W. Roggenbuck

1985-01-01

The relevancy of a lexicographic semi-order model, as a basis for development of a microcomputer-based decision aid for backcountry hikers, was investigated. In an interactive microcomputer exercise, it was found that a decision aid based upon this model may assist recreationists in reduction of an alternative set to a cognitively manageable number.

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 equation. Its a recursive method that solves nonlinear ODE's by solving a LTV systems at each iteration to obtain a new closer solution. LTV models are derived for both Gosling and Lees-Edwards type models. Particular attention is given to SLLOD Lees-Edwards models because they are in a form most amenable to performing Taylor series expansion, and the most commonly used model to examine viscosity. With linear models developed a method is presented to calculate viscosity based on LTI Gosling models but is shown to have some limitations. To address these issues LTV SLLOD models are analyzed with both Balanced Truncation and POD and both show that significant order reduction is possible. By examining the singular values of both techniques it is shown that Balanced Truncation has a potential to offer greater reduction, which should be expected as it is based on the input/output mapping instead of just the state information as in POD. Obtaining reduced order systems that capture the property of interest is challenging. For Balanced Truncation reduced order models for 1-D LJ and FENE systems are obtained and are shown to capture the output of interest fairly well. However numerical challenges currently limit this analysis to small order systems. Suggestions are presented to extend this method to larger systems. In addition reduced 2nd order systems are obtained from POD. Here the challenge is extending the solution beyond the original period used for the projection, in particular identifying the manifold the solution travels along. The remaining challenges are presented and discussed.

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

DOE PAGES

Carlberg, Kevin; Tuminaro, Ray; Boggs, Paul

2015-03-11

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

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

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

Carlberg, Kevin; Tuminaro, Ray; Boggs, Paul

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

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 to the problem dimension.« less

Computations of Flow over a Hump Model Using Higher Order Method with Turbulence Modeling

NASA Technical Reports Server (NTRS)

Balakumar, P.

2005-01-01

Turbulent separated flow over a two-dimensional hump is computed by solving the RANS equations with k - omega (SST) turbulence model for the baseline, steady suction and oscillatory blowing/suction flow control cases. The flow equations and the turbulent model equations are solved using a fifth-order accurate weighted essentially. nonoscillatory (WENO) scheme for space discretization and a third order, total variation diminishing (TVD) Runge-Kutta scheme for time integration. Qualitatively the computed pressure distributions exhibit the same behavior as those observed in the experiments. The computed separation regions are much longer than those observed experimentally. However, the percentage reduction in the separation region in the steady suction case is closer to what was measured in the experiment. The computations did not predict the expected reduction in the separation length in the oscillatory case. The predicted turbulent quantities are two to three times smaller than the measured values pointing towards the deficiencies in the existing turbulent models when they are applied to strong steady/unsteady separated flows.

A-posteriori error estimation for second order mechanical systems

NASA Astrophysics Data System (ADS)

Ruiner, Thomas; Fehr, Jörg; Haasdonk, Bernard; Eberhard, Peter

2012-06-01

One important issue for the simulation of flexible multibody systems is the reduction of the flexible bodies degrees of freedom. As far as safety questions are concerned knowledge about the error introduced by the reduction of the flexible degrees of freedom is helpful and very important. In this work, an a-posteriori error estimator for linear first order systems is extended for error estimation of mechanical second order systems. Due to the special second order structure of mechanical systems, an improvement of the a-posteriori error estimator is achieved. A major advantage of the a-posteriori error estimator is that the estimator is independent of the used reduction technique. Therefore, it can be used for moment-matching based, Gramian matrices based or modal based model reduction techniques. The capability of the proposed technique is demonstrated by the a-posteriori error estimation of a mechanical system, and a sensitivity analysis of the parameters involved in the error estimation process is conducted.

A novel hybrid scattering order-dependent variance reduction method for Monte Carlo simulations of radiative transfer in cloudy atmosphere

NASA Astrophysics Data System (ADS)

Wang, Zhen; Cui, Shengcheng; Yang, Jun; Gao, Haiyang; Liu, Chao; Zhang, Zhibo

2017-03-01

We present a novel hybrid scattering order-dependent variance reduction method to accelerate the convergence rate in both forward and backward Monte Carlo radiative transfer simulations involving highly forward-peaked scattering phase function. This method is built upon a newly developed theoretical framework that not only unifies both forward and backward radiative transfer in scattering-order-dependent integral equation, but also generalizes the variance reduction formalism in a wide range of simulation scenarios. In previous studies, variance reduction is achieved either by using the scattering phase function forward truncation technique or the target directional importance sampling technique. Our method combines both of them. A novel feature of our method is that all the tuning parameters used for phase function truncation and importance sampling techniques at each order of scattering are automatically optimized by the scattering order-dependent numerical evaluation experiments. To make such experiments feasible, we present a new scattering order sampling algorithm by remodeling integral radiative transfer kernel for the phase function truncation method. The presented method has been implemented in our Multiple-Scaling-based Cloudy Atmospheric Radiative Transfer (MSCART) model for validation and evaluation. The main advantage of the method is that it greatly improves the trade-off between numerical efficiency and accuracy order by order.

Position-dependent mass, finite-gap systems, and supersymmetry

NASA Astrophysics Data System (ADS)

Bravo, Rafael; Plyushchay, Mikhail S.

2016-05-01

The ordering problem in quantum systems with position-dependent mass (PDM) is treated by inclusion of the classically fictitious similarity transformation into the kinetic term. This provides a generation of supersymmetry with the first-order supercharges from the kinetic term alone, while inclusion of the potential term allows us also to generate nonlinear supersymmetry with higher-order supercharges. A broad class of finite-gap systems with PDM is obtained by different reduction procedures, and general results on supersymmetry generation are applied to them. We show that elliptic finite-gap systems of Lamé and Darboux-Treibich-Verdier types can be obtained by reduction to Seiffert's spherical spiral and Bernoulli lemniscate in the presence of Calogero-like or harmonic oscillator potentials, or by angular momentum reduction of a free motion on some AdS2 -related surfaces in the presence of Aharonov-Bohm flux. The limiting cases include the Higgs and Mathews-Lakshmanan oscillator models as well as a reflectionless model with PDM exploited recently in the discussion of cosmological inflationary scenarios.

A Pursuit Theory Account for the Perception of Common Motion in Motion Parallax.

PubMed

Ratzlaff, Michael; Nawrot, Mark

2016-09-01

The visual system uses an extraretinal pursuit eye movement signal to disambiguate the perception of depth from motion parallax. Visual motion in the same direction as the pursuit is perceived nearer in depth while visual motion in the opposite direction as pursuit is perceived farther in depth. This explanation of depth sign applies to either an allocentric frame of reference centered on the fixation point or an egocentric frame of reference centered on the observer. A related problem is that of depth order when two stimuli have a common direction of motion. The first psychophysical study determined whether perception of egocentric depth order is adequately explained by a model employing an allocentric framework, especially when the motion parallax stimuli have common rather than divergent motion. A second study determined whether a reversal in perceived depth order, produced by a reduction in pursuit velocity, is also explained by this model employing this allocentric framework. The results show than an allocentric model can explain both the egocentric perception of depth order with common motion and the perceptual depth order reversal created by a reduction in pursuit velocity. We conclude that an egocentric model is not the only explanation for perceived depth order in these common motion conditions. © The Author(s) 2016.

Procedures for generation and reduction of linear models of a turbofan engine

NASA Technical Reports Server (NTRS)

Seldner, K.; Cwynar, D. S.

1978-01-01

A real time hybrid simulation of the Pratt & Whitney F100-PW-F100 turbofan engine was used for linear-model generation. The linear models were used to analyze the effect of disturbances about an operating point on the dynamic performance of the engine. A procedure that disturbs, samples, and records the state and control variables was developed. For large systems, such as the F100 engine, the state vector is large and may contain high-frequency information not required for control. This, reducing the full-state to a reduced-order model may be a practicable approach to simplifying the control design. A reduction technique was developed to generate reduced-order models. Selected linear and nonlinear output responses to exhaust-nozzle area and main-burner fuel flow disturbances are presented for comparison.

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

Multi-Level Reduced Order Modeling Equipped with Probabilistic Error Bounds

NASA Astrophysics Data System (ADS)

Abdo, Mohammad Gamal Mohammad Mostafa

This thesis develops robust reduced order modeling (ROM) techniques to achieve the needed efficiency to render feasible the use of high fidelity tools for routine engineering analyses. Markedly different from the state-of-the-art ROM techniques, our work focuses only on techniques which can quantify the credibility of the reduction which can be measured with the reduction errors upper-bounded for the envisaged range of ROM model application. Our objective is two-fold. First, further developments of ROM techniques are proposed when conventional ROM techniques are too taxing to be computationally practical. This is achieved via a multi-level ROM methodology designed to take advantage of the multi-scale modeling strategy typically employed for computationally taxing models such as those associated with the modeling of nuclear reactor behavior. Second, the discrepancies between the original model and ROM model predictions over the full range of model application conditions are upper-bounded in a probabilistic sense with high probability. ROM techniques may be classified into two broad categories: surrogate construction techniques and dimensionality reduction techniques, with the latter being the primary focus of this work. We focus on dimensionality reduction, because it offers a rigorous approach by which reduction errors can be quantified via upper-bounds that are met in a probabilistic sense. Surrogate techniques typically rely on fitting a parametric model form to the original model at a number of training points, with the residual of the fit taken as a measure of the prediction accuracy of the surrogate. This approach, however, does not generally guarantee that the surrogate model predictions at points not included in the training process will be bound by the error estimated from the fitting residual. Dimensionality reduction techniques however employ a different philosophy to render the reduction, wherein randomized snapshots of the model variables, such as the model parameters, responses, or state variables, are projected onto lower dimensional subspaces, referred to as the "active subspaces", which are selected to capture a user-defined portion of the snapshots variations. Once determined, the ROM model application involves constraining the variables to the active subspaces. In doing so, the contribution from the variables discarded components can be estimated using a fundamental theorem from random matrix theory which has its roots in Dixon's theory, developed in 1983. This theory was initially presented for linear matrix operators. The thesis extends this theorem's results to allow reduction of general smooth nonlinear operators. The result is an approach by which the adequacy of a given active subspace determined using a given set of snapshots, generated either using the full high fidelity model, or other models with lower fidelity, can be assessed, which provides insight to the analyst on the type of snapshots required to reach a reduction that can satisfy user-defined preset tolerance limits on the reduction errors. Reactor physics calculations are employed as a test bed for the proposed developments. The focus will be on reducing the effective dimensionality of the various data streams such as the cross-section data and the neutron flux. The developed methods will be applied to representative assembly level calculations, where the size of the cross-section and flux spaces are typically large, as required by downstream core calculations, in order to capture the broad range of conditions expected during reactor operation. (Abstract shortened by ProQuest.).

Analysis of photochemical pollution in summer and winter using a photochemical box model in the center of Tokyo, Japan.

PubMed

Huang, H; Akustu, Y; Arai, M; Tamura, M

2001-07-01

In order to give an effective and rapid analysis of the photochemical pollution and information for emission control strategies, a photochemical box model (PBM) was applied to one moderate summer episode, 11 July 1996, and one typical winter episode, 3 December 1996, in the center of Tokyo, Japan. The box model gave a good prediction of the photochemical pollution with minimal investment. As expected, the peak ozone in summer is higher than in winter. The NOx concentrations in winter are higher than those in summer. In summer, NO and NO2 have one peak in the morning. In winter, NO and NO2 show two peaks during the day. Three model runs including no reactions, a zero ozone boundary condition and dark reactions were conducted to understand the photochemical processes. The effects of emission reduction on the formation of the photochemical pollution in the center of Tokyo have been studied. The results show that the reduction of NMHC emission can decrease the ozone, however, the reduction of NOx emission can increase the ozone. It can be concluded that if the NOx emission are reduced, the reduction of NMHC should be more emphasized in order to decrease the ozone concentration in the center of Tokyo, Japan, especially the reduction of the NMHC from stationary source emission.

A numerical study of different projection-based model reduction techniques applied to computational homogenisation

NASA Astrophysics Data System (ADS)

Soldner, Dominic; Brands, Benjamin; Zabihyan, Reza; Steinmann, Paul; Mergheim, Julia

2017-10-01

Computing the macroscopic material response of a continuum body commonly involves the formulation of a phenomenological constitutive model. However, the response is mainly influenced by the heterogeneous microstructure. Computational homogenisation can be used to determine the constitutive behaviour on the macro-scale by solving a boundary value problem at the micro-scale for every so-called macroscopic material point within a nested solution scheme. Hence, this procedure requires the repeated solution of similar microscopic boundary value problems. To reduce the computational cost, model order reduction techniques can be applied. An important aspect thereby is the robustness of the obtained reduced model. Within this study reduced-order modelling (ROM) for the geometrically nonlinear case using hyperelastic materials is applied for the boundary value problem on the micro-scale. This involves the Proper Orthogonal Decomposition (POD) for the primary unknown and hyper-reduction methods for the arising nonlinearity. Therein three methods for hyper-reduction, differing in how the nonlinearity is approximated and the subsequent projection, are compared in terms of accuracy and robustness. Introducing interpolation or Gappy-POD based approximations may not preserve the symmetry of the system tangent, rendering the widely used Galerkin projection sub-optimal. Hence, a different projection related to a Gauss-Newton scheme (Gauss-Newton with Approximated Tensors- GNAT) is favoured to obtain an optimal projection and a robust reduced model.

Stochastic model of the NASA/MSFC ground facility for large space structures with uncertain parameters: The maximum entropy approach, part 2

NASA Technical Reports Server (NTRS)

Hsia, Wei Shen

1989-01-01

A validated technology data base is being developed in the areas of control/structures interaction, deployment dynamics, and system performance for Large Space Structures (LSS). A Ground Facility (GF), in which the dynamics and control systems being considered for LSS applications can be verified, was designed and built. One of the important aspects of the GF is to verify the analytical model for the control system design. The procedure is to describe the control system mathematically as well as possible, then to perform tests on the control system, and finally to factor those results into the mathematical model. The reduction of the order of a higher order control plant was addressed. The computer program was improved for the maximum entropy principle adopted in Hyland's MEOP method. The program was tested against the testing problem. It resulted in a very close match. Two methods of model reduction were examined: Wilson's model reduction method and Hyland's optimal projection (OP) method. Design of a computer program for Hyland's OP method was attempted. Due to the difficulty encountered at the stage where a special matrix factorization technique is needed in order to obtain the required projection matrix, the program was successful up to the finding of the Linear Quadratic Gaussian solution but not beyond. Numerical results along with computer programs which employed ORACLS are presented.

Alternatives for jet engine control

NASA Technical Reports Server (NTRS)

Sain, M. K.

1983-01-01

Tensor model order reduction, recursive tensor model identification, input design for tensor model identification, software development for nonlinear feedback control laws based upon tensors, and development of the CATNAP software package for tensor modeling, identification and simulation were studied. The last of these are discussed.

Vanishing characteristic speeds and critical dispersive points in nonlinear interfacial wave problems

NASA Astrophysics Data System (ADS)

Ratliff, Daniel J.

2017-11-01

Criticality plays a central role in the study of reductions and stability of hydrodynamical systems. At critical points, it is often the case that nonlinear reductions with dispersion arise to govern solution behavior. By considering when such models become bidirectional and lose their initial dispersive properties, it will be shown that higher order dispersive models may be supported in hydrodynamical systems. Precisely, this equation is a two-way Boussinesq equation with sixth order dispersion. The case of two layered shallow water is considered to illustrate this, and it is reasoned why such an environment is natural for such a system to emerge. Further, it is demonstrated that the regions in the parameter space for nontrivial flow, which admit this reduction, are vast and in fact form a continuum. The reduced model is then numerically simulated to illustrate how the two-way and higher dispersive properties suggest more exotic families of solitary wave solutions can emerge in stratified flows.

Improved model reduction and tuning of fractional-order PI(λ)D(μ) controllers for analytical rule extraction with genetic programming.

PubMed

Das, Saptarshi; Pan, Indranil; Das, Shantanu; Gupta, Amitava

2012-03-01

Genetic algorithm (GA) has been used in this study for a new approach of suboptimal model reduction in the Nyquist plane and optimal time domain tuning of proportional-integral-derivative (PID) and fractional-order (FO) PI(λ)D(μ) controllers. Simulation studies show that the new Nyquist-based model reduction technique outperforms the conventional H(2)-norm-based reduced parameter modeling technique. With the tuned controller parameters and reduced-order model parameter dataset, optimum tuning rules have been developed with a test-bench of higher-order processes via genetic programming (GP). The GP performs a symbolic regression on the reduced process parameters to evolve a tuning rule which provides the best analytical expression to map the data. The tuning rules are developed for a minimum time domain integral performance index described by a weighted sum of error index and controller effort. From the reported Pareto optimal front of the GP-based optimal rule extraction technique, a trade-off can be made between the complexity of the tuning formulae and the control performance. The efficacy of the single-gene and multi-gene GP-based tuning rules has been compared with the original GA-based control performance for the PID and PI(λ)D(μ) controllers, handling four different classes of representative higher-order processes. These rules are very useful for process control engineers, as they inherit the power of the GA-based tuning methodology, but can be easily calculated without the requirement for running the computationally intensive GA every time. Three-dimensional plots of the required variation in PID/fractional-order PID (FOPID) controller parameters with reduced process parameters have been shown as a guideline for the operator. Parametric robustness of the reported GP-based tuning rules has also been shown with credible simulation examples. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

Genetic Algorithm-Guided, Adaptive Model Order Reduction of Flexible Aircrafts

NASA Technical Reports Server (NTRS)

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

2017-01-01

This paper presents a methodology for automated model order reduction (MOR) of flexible aircrafts to construct linear parameter-varying (LPV) reduced order models (ROM) for aeroservoelasticity (ASE) analysis and control synthesis in broad flight parameter space. The novelty includes utilization of genetic algorithms (GAs) to automatically determine the states for reduction while minimizing the trial-and-error process and heuristics requirement to perform MOR; balanced truncation for unstable systems to achieve locally optimal realization of the full model; congruence transformation for "weak" fulfillment of state consistency across the entire flight parameter space; and ROM interpolation based on adaptive grid refinement to generate a globally functional LPV ASE ROM. The methodology is applied to the X-56A MUTT model currently being tested at NASA/AFRC for flutter suppression and gust load alleviation. Our studies indicate that X-56A ROM with less than one-seventh the number of states relative to the original model is able to accurately predict system response among all input-output channels for pitch, roll, and ASE control at various flight conditions. The GA-guided approach exceeds manual and empirical state selection in terms of efficiency and accuracy. The adaptive refinement allows selective addition of the grid points in the parameter space where flight dynamics varies dramatically to enhance interpolation accuracy without over-burdening controller synthesis and onboard memory efforts downstream. The present MOR framework can be used by control engineers for robust ASE controller synthesis and novel vehicle design.

Elastic mismatch induced reduction of the thermal conductivity of silicon with aluminum nano-inclusions

NASA Astrophysics Data System (ADS)

Donovan, Brian F.; Jensen, Wade A.; Chen, Long; Giri, Ashutosh; Poon, S. Joseph; Floro, Jerrold A.; Hopkins, Patrick E.

2018-05-01

We use aluminum nano-inclusions in silicon to demonstrate the dominance of elastic modulus mismatch induced scattering in phonon transport. We use time domain thermoreflectance to measure the thermal conductivity of thin films of silicon co-deposited with aluminum via molecular beam epitaxy resulting in a Si film with 10% clustered Al inclusions with nanoscale dimensions and a reduction in thermal conductivity of over an order of magnitude. We compare these results with well-known models in order to demonstrate that the reduction in the thermal transport is driven by elastic mismatch effects induced by aluminum in the system.

Order reduction, identification and localization studies of dynamical systems

NASA Astrophysics Data System (ADS)

Ma, Xianghong

In this thesis methods are developed for performing order reduction, system identification and induction of nonlinear localization in complex mechanical dynamic systems. General techniques are proposed for constructing low-order models of linear and nonlinear mechanical systems; in addition, novel mechanical designs are considered for inducing nonlinear localization phenomena for the purpose of enhancing their dynamical performance. The thesis is in three major parts. In the first part, the transient dynamics of an impulsively loaded multi-bay truss is numerically computed by employing the Direct Global Matrix (DGM) approach. The approach is applicable to large-scale flexible structures with periodicity. Karhunen-Loeve (K-L) decomposition is used to discretize the dynamics of the truss and to create the low-order models of the truss. The leading order K-L modes are recovered by an experiment, which shows the feasibility of K-L based order reduction technique. In the second part of the thesis, nonlinear localization in dynamical systems is studied through two applications. In the seismic base isolation study, it is shown that the dynamics are sensitive to the presence of nonlinear elements and that passive motion confinement can be induced under proper design. In the coupled rod system, numerical simulation of the transient dynamics shows that a nonlinear backlash spring can induce either nonlinear localization or delocalization in the form of beat phenomena. K-L decomposition and poincare maps are utilized to study the nonlinear effects. The study shows that nonlinear localization can be induced in complex structures through backlash. In the third and final part of the thesis, a new technique based on Green!s function method is proposed to identify the dynamics of practical bolted joints. By modeling the difference between the dynamics of the bolted structure and the corresponding unbolted one, one constructs a nonparametric model for the joint dynamics. Two applications are given with a bolted beam and a truss joint in order to show the applicability of the technique.

Monoclonal antibody disulfide reduction during manufacturing

PubMed Central

Hutterer, Katariina M.; Hong, Robert W.; Lull, Jonathon; Zhao, Xiaoyang; Wang, Tian; Pei, Rex; Le, M. Eleanor; Borisov, Oleg; Piper, Rob; Liu, Yaoqing Diana; Petty, Krista; Apostol, Izydor; Flynn, Gregory C.

2013-01-01

Manufacturing-induced disulfide reduction has recently been reported for monoclonal human immunoglobulin gamma (IgG) antibodies, a widely used modality in the biopharmaceutical industry. This effect has been tied to components of the intracellular thioredoxin reduction system that are released upon cell breakage. Here, we describe the effect of process parameters and intrinsic molecule properties on the extent of reduction. Material taken from cell cultures at the end of production displayed large variations in the extent of antibody reduction between different products, including no reduction, when subjected to the same reduction-promoting harvest conditions. Additionally, in a reconstituted model in which process variables could be isolated from product properties, we found that antibody reduction was dependent on the cell line (clone) and cell culture process. A bench-scale model using a thioredoxin/thioredoxin reductase regeneration system revealed that reduction susceptibility depended on not only antibody class but also light chain type; the model further demonstrates that the trend in reducibility was identical to DTT reduction sensitivity following the order IgG1λ > IgG1κ > IgG2λ > IgG2κ. Thus, both product attributes and process parameters contribute to the extent of antibody reduction during production. PMID:23751615

Virtual microphone sensing through vibro-acoustic modelling and Kalman filtering

NASA Astrophysics Data System (ADS)

van de Walle, A.; Naets, F.; Desmet, W.

2018-05-01

This work proposes a virtual microphone methodology which enables full field acoustic measurements for vibro-acoustic systems. The methodology employs a Kalman filtering framework in order to combine a reduced high-fidelity vibro-acoustic model with a structural excitation measurement and small set of real microphone measurements on the system under investigation. By employing model order reduction techniques, a high order finite element model can be converted in a much smaller model which preserves the desired accuracy and maintains the main physical properties of the original model. Due to the low order of the reduced-order model, it can be effectively employed in a Kalman filter. The proposed methodology is validated experimentally on a strongly coupled vibro-acoustic system. The virtual sensor vastly improves the accuracy with respect to regular forward simulation. The virtual sensor also allows to recreate the full sound field of the system, which is very difficult/impossible to do through classical measurements.

Laboratory for Engineering Man/Machine Systems (LEMS): System identification, model reduction and deconvolution filtering using Fourier based modulating signals and high order statistics

NASA Technical Reports Server (NTRS)

Pan, Jianqiang

1992-01-01

Several important problems in the fields of signal processing and model identification, such as system structure identification, frequency response determination, high order model reduction, high resolution frequency analysis, deconvolution filtering, and etc. Each of these topics involves a wide range of applications and has received considerable attention. Using the Fourier based sinusoidal modulating signals, it is shown that a discrete autoregressive model can be constructed for the least squares identification of continuous systems. Some identification algorithms are presented for both SISO and MIMO systems frequency response determination using only transient data. Also, several new schemes for model reduction were developed. Based upon the complex sinusoidal modulating signals, a parametric least squares algorithm for high resolution frequency estimation is proposed. Numerical examples show that the proposed algorithm gives better performance than the usual. Also, the problem was studied of deconvolution and parameter identification of a general noncausal nonminimum phase ARMA system driven by non-Gaussian stationary random processes. Algorithms are introduced for inverse cumulant estimation, both in the frequency domain via the FFT algorithms and in the domain via the least squares algorithm.

Implementation of Kalman filter algorithm on models reduced using singular pertubation approximation method and its application to measurement of water level

NASA Astrophysics Data System (ADS)

Rachmawati, Vimala; Khusnul Arif, Didik; Adzkiya, Dieky

2018-03-01

The systems contained in the universe often have a large order. Thus, the mathematical model has many state variables that affect the computation time. In addition, generally not all variables are known, so estimations are needed to measure the magnitude of the system that cannot be measured directly. In this paper, we discuss the model reduction and estimation of state variables in the river system to measure the water level. The model reduction of a system is an approximation method of a system with a lower order without significant errors but has a dynamic behaviour that is similar to the original system. The Singular Perturbation Approximation method is one of the model reduction methods where all state variables of the equilibrium system are partitioned into fast and slow modes. Then, The Kalman filter algorithm is used to estimate state variables of stochastic dynamic systems where estimations are computed by predicting state variables based on system dynamics and measurement data. Kalman filters are used to estimate state variables in the original system and reduced system. Then, we compare the estimation results of the state and computational time between the original and reduced system.

Physician Utilization of a Hospital Information System: A Computer Simulation Model

PubMed Central

Anderson, James G.; Jay, Stephen J.; Clevenger, Stephen J.; Kassing, David R.; Perry, Jane; Anderson, Marilyn M.

1988-01-01

The purpose of this research was to develop a computer simulation model that represents the process through which physicians enter orders into a hospital information system (HIS). Computer simulation experiments were performed to estimate the effects of two methods of order entry on outcome variables. The results of the computer simulation experiments were used to perform a cost-benefit analysis to compare the two different means of entering medical orders into the HIS. The results indicate that the use of personal order sets to enter orders into the HIS will result in a significant reduction in manpower, salaries and fringe benefits, and errors in order entry.

Assessment and Reduction of Model Parametric Uncertainties: A Case Study with A Distributed Hydrological Model

NASA Astrophysics Data System (ADS)

Gan, Y.; Liang, X. Z.; Duan, Q.; Xu, J.; Zhao, P.; Hong, Y.

2017-12-01

The uncertainties associated with the parameters of a hydrological model need to be quantified and reduced for it to be useful for operational hydrological forecasting and decision support. An uncertainty quantification framework is presented to facilitate practical assessment and reduction of model parametric uncertainties. A case study, using the distributed hydrological model CREST for daily streamflow simulation during the period 2008-2010 over ten watershed, was used to demonstrate the performance of this new framework. Model behaviors across watersheds were analyzed by a two-stage stepwise sensitivity analysis procedure, using LH-OAT method for screening out insensitive parameters, followed by MARS-based Sobol' sensitivity indices for quantifying each parameter's contribution to the response variance due to its first-order and higher-order effects. Pareto optimal sets of the influential parameters were then found by the adaptive surrogate-based multi-objective optimization procedure, using MARS model for approximating the parameter-response relationship and SCE-UA algorithm for searching the optimal parameter sets of the adaptively updated surrogate model. The final optimal parameter sets were validated against the daily streamflow simulation of the same watersheds during the period 2011-2012. The stepwise sensitivity analysis procedure efficiently reduced the number of parameters that need to be calibrated from twelve to seven, which helps to limit the dimensionality of calibration problem and serves to enhance the efficiency of parameter calibration. The adaptive MARS-based multi-objective calibration exercise provided satisfactory solutions to the reproduction of the observed streamflow for all watersheds. The final optimal solutions showed significant improvement when compared to the default solutions, with about 65-90% reduction in 1-NSE and 60-95% reduction in |RB|. The validation exercise indicated a large improvement in model performance with about 40-85% reduction in 1-NSE, and 35-90% reduction in |RB|. Overall, this uncertainty quantification framework is robust, effective and efficient for parametric uncertainty analysis, the results of which provide useful information that helps to understand the model behaviors and improve the model simulations.

Effects of rotor model degradation on the accuracy of rotorcraft real time simulation

NASA Technical Reports Server (NTRS)

Houck, J. A.; Bowles, R. L.

1976-01-01

The effects are studied of degrading a rotating blade element rotor mathematical model to meet various real-time simulation requirements of rotorcraft. Three methods of degradation were studied: reduction of number of blades, reduction of number of blade segments, and increasing the integration interval, which has the corresponding effect of increasing blade azimuthal advance angle. The three degradation methods were studied through static trim comparisons, total rotor force and moment comparisons, single blade force and moment comparisons over one complete revolution, and total vehicle dynamic response comparisons. Recommendations are made concerning model degradation which should serve as a guide for future users of this mathematical model, and in general, they are in order of minimum impact on model validity: (1) reduction of number of blade segments, (2) reduction of number of blades, and (3) increase of integration interval and azimuthal advance angle. Extreme limits are specified beyond which the rotating blade element rotor mathematical model should not be used.

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 most methods to the multiparameter case. This paper address the above shortcomings be developing a method that uses a block-box approach to the solution method, is adaptive, and is easily extensible to many parameters.« less

Reduced Order Model Basis Vector Generation: Generates Basis Vectors fro ROMs

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

Arrighi, Bill

2016-03-03

libROM is a library that implements order reduction via singular value decomposition (SVD) of sampled state vectors. It implements 2 parallel, incremental SVD algorithms and one serial, non-incremental algorithm. It also provides a mechanism for adaptive sampling of basis vectors.

Simulation and optimization of pressure swing adsorption systmes using reduced-order modeling

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

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

2009-01-01

Over the past three decades, pressure swing adsorption (PSA) processes have been widely used as energyefficient gas separation techniques, especially for high purity hydrogen purification from refinery gases. Models for PSA processes are 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 fronts moving with time. As a result, the optimization of such systems represents a significant computational challenge to current differential algebraic equation (DAE) optimization techniques and nonlinear programming algorithms. Model reduction is one approachmore » to generate cost-efficient low-order models which can be used as surrogate models in the optimization problems. This study develops a reducedorder model (ROM) based on proper orthogonal decomposition (POD), which is a low-dimensional approximation to a dynamic PDE-based model. The proposed method leads to a DAE system of significantly lower order, thus replacing the one obtained from spatial discretization and making the optimization problem computationally efficient. The method has been applied to the dynamic coupled PDE-based model of a twobed four-step PSA process for separation of hydrogen from methane. Separate ROMs have been developed for each operating step with different POD modes for each of them. A significant reduction in the order of the number of states has been achieved. The reduced-order model has been successfully used to maximize hydrogen recovery by manipulating operating pressures, step times and feed and regeneration velocities, while meeting product purity and tight bounds on these parameters. Current results indicate the proposed ROM methodology as a promising surrogate modeling technique for cost-effective optimization purposes.« less

Computational methods of robust controller design for aerodynamic flutter suppression

NASA Technical Reports Server (NTRS)

Anderson, L. R.

1981-01-01

The development of Riccati iteration, a tool for the design and analysis of linear control systems is examined. First, Riccati iteration is applied to the problem of pole placement and order reduction in two-time scale control systems. Order reduction, yielding a good approximation to the original system, is demonstrated using a 16th order linear model of a turbofan engine. Next, a numerical method for solving the Riccati equation is presented and demonstrated for a set of eighth order random examples. A literature review of robust controller design methods follows which includes a number of methods for reducing the trajectory and performance index sensitivity in linear regulators. Lastly, robust controller design for large parameter variations is discussed.

Nonlinear Model Reduction in Power Systems by Balancing of Empirical Controllability and Observability Covariances

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

Qi, Junjian; Wang, Jianhui; Liu, Hui

Abstract: In this paper, nonlinear model reduction for power systems is performed by the balancing of empirical controllability and observability covariances that are calculated around the operating region. Unlike existing model reduction methods, the external system does not need to be linearized but is directly dealt with as a nonlinear system. A transformation is found to balance the controllability and observability covariances in order to determine which states have the greatest contribution to the input-output behavior. The original system model is then reduced by Galerkin projection based on this transformation. The proposed method is tested and validated on a systemmore » comprised of a 16-machine 68-bus system and an IEEE 50-machine 145-bus system. The results show that by using the proposed model reduction the calculation efficiency can be greatly improved; at the same time, the obtained state trajectories are close to those for directly simulating the whole system or partitioning the system while not performing reduction. Compared with the balanced truncation method based on a linearized model, the proposed nonlinear model reduction method can guarantee higher accuracy and similar calculation efficiency. It is shown that the proposed method is not sensitive to the choice of the matrices for calculating the empirical covariances.« less

Drag reduction by polymers in turbulent channel flows: Energy redistribution between invariant empirical modes.

PubMed

De Angelis, Elisabetta; Casciola, Carlo M; L'vov, Victor S; Piva, Renzo; Procaccia, Itamar

2003-05-01

We address the phenomenon of drag reduction by a dilute polymeric additive to turbulent flows, using direct numerical simulations (DNS) of the FENE-P model of viscoelastic flows. It had been amply demonstrated that these model equations reproduce the phenomenon, but the results of DNS were not analyzed so far with the goal of interpreting the phenomenon. In order to construct a useful framework for the understanding of drag reduction we initiate in this paper an investigation of the most important modes that are sustained in the viscoelastic and Newtonian turbulent flows, respectively. The modes are obtained empirically using the Karhunen-Loéve decomposition, allowing us to compare the most energetic modes in the viscoelastic and Newtonian flows. The main finding of the present study is that the spatial profile of the most energetic modes is hardly changed between the two flows. What changes is the energy associated with these modes, and their relative ordering in the decreasing order from the most energetic to the least. Modes that are highly excited in one flow can be strongly suppressed in the other, and vice versa. This dramatic energy redistribution is an important clue to the mechanism of drag reduction as is proposed in this paper. In particular, there is an enhancement of the energy containing modes in the viscoelastic flow compared to the Newtonian one; drag reduction is seen in the energy containing modes rather than the dissipative modes, as proposed in some previous theories.

Reduction of Fe(III) colloids by Shewanella putrefaciens: A kinetic model

NASA Astrophysics Data System (ADS)

Bonneville, Steeve; Behrends, Thilo; van Cappellen, Philippe; Hyacinthe, Christelle; Röling, Wilfred F. M.

2006-12-01

A kinetic model for the microbial reduction of Fe(III) oxyhydroxide colloids in the presence of excess electron donor is presented. The model assumes a two-step mechanism: (1) attachment of Fe(III) colloids to the cell surface and (2) reduction of Fe(III) centers at the surface of attached colloids. The validity of the model is tested using Shewanella putrefaciens and nanohematite as model dissimilatory iron reducing bacteria and Fe(III) colloidal particles, respectively. Attachment of nanohematite to the bacteria is formally described by a Langmuir isotherm. Initial iron reduction rates are shown to correlate linearly with the relative coverage of the cell surface by nanohematite particles, hence supporting a direct electron transfer from membrane-bound reductases to mineral particles attached to the cells. Using internally consistent parameter values for the maximum attachment capacity of Fe(III) colloids to the cells, Mmax, the attachment constant, KP, and the first-order Fe(III) reduction rate constant, k, the model reproduces the initial reduction rates of a variety of fine-grained Fe(III) oxyhydroxides by S. putrefaciens. The model explains the observed dependency of the apparent Fe(III) half-saturation constant, Km∗, on the solid to cell ratio, and it predicts that initial iron reduction rates exhibit saturation with respect to both the cell density and the abundance of the Fe(III) oxyhydroxide substrate.

Effects of carbonate species on the kinetics of dechlorination of 1,1,1-trichloroethane by zero-valent iron.

PubMed

Agrawal, Abinash; Ferguson, William J; Gardner, Bruce O; Christ, John A; Bandstra, Joel Z; Tratnyek, Paul G

2002-10-15

The effect of precipitates on the reactivity of iron metal (Fe0) with 1,1,1-trichloroethane (TCA) was studied in batch systems designed to model groundwaters that contain dissolved carbonate species (i.e., C(IV)). At representative concentrations for high-C(IV) groundwaters (approximately 10(-2) M), the pH in batch reactors containing Fe0 was effectively buffered until most of the aqueous C(IV) precipitated. The precipitate was mainly FeCO3 (siderite) but may also have included some carbonate green rust. Exposure of the Fe0 to dissolved C(IV) accelerated reduction of TCA, and the products formed under these conditions consisted mainly of ethane and ethene, with minor amounts of several butenes. The kinetics of TCA reduction were first-order when C(IV)-enhanced corrosion predominated but showed mixed-order kinetics (zero- and first-order) in experiments performed with passivated Fe0 (i.e., before the onset of pitting corrosion and after repassivation by precipitation of FeCO3). All these data were described by fitting a Michaelis-Menten-type kinetic model and approximating the first-order rate constant as the ratio of the maximum reaction rate (Vm) and the concentration of TCA at half of the maximum rate (K(1/2)). The decrease in Vm/K(1/2) with increasing C(IV) exposure time was fit to a heuristic model assuming proportionality between changes in TCA reduction rate and changes in surface coverage with FeCO3.

Research on the effect of rainfall flood regulation and control of wetland park based on SWMM model—a case study of wetland park in Yuanjia village, Qishan county, Shaanxi province

NASA Astrophysics Data System (ADS)

Xu, Da; Liu, Yijie

2018-02-01

Taking the wetland park of Yuan Village in Qishan County of Shaanxi Province as the research object, this paper makes a reasonable generalization of the study area, and establishes two models of low impact development (LID) and traditional development in the park. Meantime, rainwater in the surrounding built up area is introduced to into the park for digestion. SWMM model is used to simulate the variation of the total runoff, peak flow and peak time of two development models in Wetland Park under one-hour rainfall at different recurrence periods.The runoff control effect in each single LID facility in the one-hour rainfall once during five years in the built-up area is simulated. The simulation results show that the SWMM model can not only quantify the runoff reduction effect of different LID facilities, but also provide theoretical basis and data support for the urban rainfall flood problem. LID facilities have effects on runoff reduction and peak delay. However, the combined LID facility has obvious advantages for the peak time delay and peak flow control. A single LID facility is more efficient in a single runoff volume control. The order of runoff reduction by various LID facilities is as follows: Rain garden>combined LID facility> vegetative swale> bio-retention cell > permeable pavement. The order of peak time delay effect by the LID facilities is as follows: combined LID facility> Rain garden> vegetative swale> bio-retention cell > permeable pavement. The order of peak flow reduction efficiency by various LID facilities is: combined LID facility> Rain garden> bio-retention cell > vegetative swale> permeable pavement.

Numerical solution for weight reduction model due to health campaigns in Spain

NASA Astrophysics Data System (ADS)

Mohammed, Maha A.; Noor, Noor Fadiya Mohd; Siri, Zailan; Ibrahim, Adriana Irawati Nur

2015-10-01

Transition model between three subpopulations based on Body Mass Index of Valencia community in Spain is considered. No changes in population nutritional habits and public health strategies on weight reduction until 2030 are assumed. The system of ordinary differential equations is solved using Runge-Kutta method of higher order. The numerical results obtained are compared with the predicted values of subpopulation proportion based on statistical estimation in 2013, 2015 and 2030. Relative approximate error is calculated. The consistency of the Runge-Kutta method in solving the model is discussed.

A LATIN-based model reduction approach for the simulation of cycling damage

NASA Astrophysics Data System (ADS)

Bhattacharyya, Mainak; Fau, Amelie; Nackenhorst, Udo; Néron, David; Ladevèze, Pierre

2017-11-01

The objective of this article is to introduce a new method including model order reduction for the life prediction of structures subjected to cycling damage. Contrary to classical incremental schemes for damage computation, a non-incremental technique, the LATIN method, is used herein as a solution framework. This approach allows to introduce a PGD model reduction technique which leads to a drastic reduction of the computational cost. The proposed framework is exemplified for structures subjected to cyclic loading, where damage is considered to be isotropic and micro-defect closure effects are taken into account. A difficulty herein for the use of the LATIN method comes from the state laws which can not be transformed into linear relations through an internal variable transformation. A specific treatment of this issue is introduced in this work.

Symmetry Reductions of Fourth-Order Nonlinear Diffusion Equations: Lubrication Model and Some Generalizations

NASA Astrophysics Data System (ADS)

Gandarias, M. L.; Medina, E.

Fourth-order nonlinear diffusion equations appear frequently in the description of physical processes, among these, the lubrication equation ut = (unuxxxx)x or the corresponding modified version ut = unuxxxx play an important role in the study of the interface movements. In this work we analyze the generalizations of the above equations given by ut = (f(u)uxxxx)x, ut = (f(u)uxxxx, and we find that if f(u) = un or f(u) = e-u the equations admit extra classical symmetries. The corresponding reductions are performed and some solutions are characterized.

Computational aspects of real-time simulation of rotary-wing aircraft. M.S. Thesis

NASA Technical Reports Server (NTRS)

Houck, J. A.

1976-01-01

A study was conducted to determine the effects of degrading a rotating blade element rotor mathematical model suitable for real-time simulation of rotorcraft. Three methods of degradation were studied, reduction of number of blades, reduction of number of blade segments, and increasing the integration interval, which has the corresponding effect of increasing blade azimuthal advance angle. The three degradation methods were studied through static trim comparisons, total rotor force and moment comparisons, single blade force and moment comparisons over one complete revolution, and total vehicle dynamic response comparisons. Recommendations are made concerning model degradation which should serve as a guide for future users of this mathematical model, and in general, they are in order of minimum impact on model validity: (1) reduction of number of blade segments; (2) reduction of number of blades; and (3) increase of integration interval and azimuthal advance angle. Extreme limits are specified beyond which a different rotor mathematical model should be used.

Nonlinear model-order reduction for compressible flow solvers using the Discrete Empirical Interpolation Method

NASA Astrophysics Data System (ADS)

Fosas de Pando, Miguel; Schmid, Peter J.; Sipp, Denis

2016-11-01

Nonlinear model reduction for large-scale flows is an essential component in many fluid applications such as flow control, optimization, parameter space exploration and statistical analysis. In this article, we generalize the POD-DEIM method, introduced by Chaturantabut & Sorensen [1], to address nonlocal nonlinearities in the equations without loss of performance or efficiency. The nonlinear terms are represented by nested DEIM-approximations using multiple expansion bases based on the Proper Orthogonal Decomposition. These extensions are imperative, for example, for applications of the POD-DEIM method to large-scale compressible flows. The efficient implementation of the presented model-reduction technique follows our earlier work [2] on linearized and adjoint analyses and takes advantage of the modular structure of our compressible flow solver. The efficacy of the nonlinear model-reduction technique is demonstrated to the flow around an airfoil and its acoustic footprint. We could obtain an accurate and robust low-dimensional model that captures the main features of the full flow.

Algorithms and analyses for stochastic optimization for turbofan noise reduction using parallel reduced-order modeling

NASA Astrophysics Data System (ADS)

Yang, Huanhuan; Gunzburger, Max

2017-06-01

Simulation-based optimization of acoustic liner design in a turbofan engine nacelle for noise reduction purposes can dramatically reduce the cost and time needed for experimental designs. Because uncertainties are inevitable in the design process, a stochastic optimization algorithm is posed based on the conditional value-at-risk measure so that an ideal acoustic liner impedance is determined that is robust in the presence of uncertainties. A parallel reduced-order modeling framework is developed that dramatically improves the computational efficiency of the stochastic optimization solver for a realistic nacelle geometry. The reduced stochastic optimization solver takes less than 500 seconds to execute. In addition, well-posedness and finite element error analyses of the state system and optimization problem are provided.

A Reduced Order Model for Whole-Chip Thermal Analysis of Microfluidic Lab-on-a-Chip Systems

PubMed Central

Wang, Yi; Song, Hongjun; Pant, Kapil

2013-01-01

This paper presents a Krylov subspace projection-based Reduced Order Model (ROM) for whole microfluidic chip thermal analysis, including conjugate heat transfer. Two key steps in the reduced order modeling procedure are described in detail, including (1) the acquisition of a 3D full-scale computational model in the state-space form to capture the dynamic thermal behavior of the entire microfluidic chip; and (2) the model order reduction using the Block Arnoldi algorithm to markedly lower the dimension of the full-scale model. Case studies using practically relevant thermal microfluidic chip are undertaken to establish the capability and to evaluate the computational performance of the reduced order modeling technique. The ROM is compared against the full-scale model and exhibits good agreement in spatiotemporal thermal profiles (<0.5% relative error in pertinent time scales) and over three orders-of-magnitude acceleration in computational speed. The salient model reusability and real-time simulation capability renders it amenable for operational optimization and in-line thermal control and management of microfluidic systems and devices. PMID:24443647

Symmetry Reductions, Integrability and Solitary Wave Solutions to High-Order Modified Boussinesq Equations with Damping Term

NASA Astrophysics Data System (ADS)

Yan, Zhen-Ya; Xie, Fu-Ding; Zhang, Hong-Qing

2001-07-01

Both the direct method due to Clarkson and Kruskal and the improved direct method due to Lou are extended to reduce the high-order modified Boussinesq equation with the damping term (HMBEDT) arising in the general Fermi-Pasta-Ulam model. As a result, several types of similarity reductions are obtained. It is easy to show that the nonlinear wave equation is not integrable under the sense of Ablowitz's conjecture from the reduction results obtained. In addition, kink-shaped solitary wave solutions, which are of important physical significance, are found for HMBEDT based on the obtained reduction equation. The project supported by National Natural Science Foundation of China under Grant No. 19572022, the National Key Basic Research Development Project Program of China under Grant No. G1998030600 and Doctoral Foundation of China under Grant No. 98014119

Model reduction in a subset of the original states

NASA Technical Reports Server (NTRS)

Yae, K. H.; Inman, D. J.

1992-01-01

A model reduction method is investigated to provide a smaller structural dynamic model for subsequent structural control design. A structural dynamic model is assumed to be derived from finite element analysis. It is first converted into the state space form, and is further reduced by the internal balancing method. Through the co-ordinate transformation derived from the states that are deleted during reduction, the reduced model is finally expressed with the states that are members of the original states. Therefore, the states in the final reduced model represent the degrees of freedom of the nodes that are selected by the designer. The procedure provides a more practical implementation of model reduction for applications in which specific nodes, such as sensor and/or actuator attachment points, are to be retained in the reduced model. Thus, it ensures that the reduced model is under the same input and output condition as the original physical model. The procedure is applied to two simple examples and comparisons are made between the full and reduced order models. The method can be applied to a linear, continuous and time-invariant model of structural dynamics with nonproportional viscous damping.

Development of a Logic Model to Guide Evaluations of the ASCA National Model for School Counseling Programs

ERIC Educational Resources Information Center

Martin, Ian; Carey, John

2014-01-01

A logic model was developed based on an analysis of the 2012 American School Counselor Association (ASCA) National Model in order to provide direction for program evaluation initiatives. The logic model identified three outcomes (increased student achievement/gap reduction, increased school counseling program resources, and systemic change and…

Order reduction of z-transfer functions via multipoint Jordan continued-fraction expansion

NASA Technical Reports Server (NTRS)

Lee, Ying-Chin; Hwang, Chyi; Shieh, Leang S.

1992-01-01

The order reduction problem of z-transfer functions is solved by using the multipoint Jordan continued-fraction expansion (MJCFE) technique. An efficient algorithm that does not require the use of complex algebra is presented for obtaining an MJCFE from a stable z-transfer function with expansion points selected from the unit circle and/or the positive real axis of the z-plane. The reduced-order models are exactly the multipoint Pade approximants of the original system and, therefore, they match the (weighted) time-moments of the impulse response and preserve the frequency responses of the system at some characteristic frequencies, such as gain crossover frequency, phase crossover frequency, bandwidth, etc.

Modeling Reduction of Uranium U(VI) under Variable Sulfate Concentrations by Sulfate-Reducing Bacteria

PubMed Central

Spear, John R.; Figueroa, Linda A.; Honeyman, Bruce D.

2000-01-01

The kinetics for the reduction of sulfate alone and for concurrent uranium [U(VI)] and sulfate reduction, by mixed and pure cultures of sulfate-reducing bacteria (SRB) at 21 ± 3°C were studied. The mixed culture contained the SRB Desulfovibrio vulgaris along with a Clostridium sp. determined via 16S ribosomal DNA analysis. The pure culture was Desulfovibrio desulfuricans (ATCC 7757). A zero-order model best fit the data for the reduction of sulfate from 0.1 to 10 mM. A lag time occurred below cell concentrations of 0.1 mg (dry weight) of cells/ml. For the mixed culture, average values for the maximum specific reaction rate, Vmax, ranged from 2.4 ± 0.2 μmol of sulfate/mg (dry weight) of SRB · h−1) at 0.25 mM sulfate to 5.0 ± 1.1 μmol of sulfate/mg (dry weight) of SRB · h−1 at 10 mM sulfate (average cell concentration, 0.52 mg [dry weight]/ml). For the pure culture, Vmax was 1.6 ± 0.2 μmol of sulfate/mg (dry weight) of SRB · h−1 at 1 mM sulfate (0.29 mg [dry weight] of cells/ml). When both electron acceptors were present, sulfate reduction remained zero order for both cultures, while uranium reduction was first order, with rate constants of 0.071 ± 0.003 mg (dry weight) of cells/ml · min−1 for the mixed culture and 0.137 ± 0.016 mg (dry weight) of cells/ml · min−1 (U0 = 1 mM) for the D. desulfuricans culture. Both cultures exhibited a faster rate of uranium reduction in the presence of sulfate and no lag time until the onset of U reduction in contrast to U alone. This kinetics information can be used to design an SRB-dominated biotreatment scheme for the removal of U(VI) from an aqueous source. PMID:10966381

Why does shear banding behave like first-order phase transitions? Derivation of a potential from a mechanical constitutive model.

PubMed

Sato, K; Yuan, X-F; Kawakatsu, T

2010-02-01

Numerous numerical and experimental evidence suggest that shear banding behavior looks like first-order phase transitions. In this paper, we demonstrate that this correspondence is actually established in the so-called non-local diffusive Johnson-Segalman model (the DJS model), a typical mechanical constitutive model that has been widely used for describing shear banding phenomena. In the neighborhood of the critical point, we apply the reduction procedure based on the center manifold theory to the governing equations of the DJS model. As a result, we obtain a time evolution equation of the flow field that is equivalent to the time-dependent Ginzburg-Landau (TDGL) equations for modeling thermodynamic first-order phase transitions. This result, for the first time, provides a mathematical proof that there is an analogy between the mechanical instability and thermodynamic phase transition at least in the vicinity of the critical point of the shear banding of DJS model. Within this framework, we can clearly distinguish the metastable branch in the stress-strain rate curve around the shear banding region from the globally stable branch. A simple extension of this analysis to a class of more general constitutive models is also discussed. Numerical simulations for the original DJS model and the reduced TDGL equation is performed to confirm the range of validity of our reduction theory.

A model-reduction approach in micromechanics of materials preserving the variational structure of constitutive relations

NASA Astrophysics Data System (ADS)

Michel, Jean-Claude; Suquet, Pierre

2016-05-01

In 2003 the authors proposed a model-reduction technique, called the Nonuniform Transformation Field Analysis (NTFA), based on a decomposition of the local fields of internal variables on a reduced basis of modes, to analyze the effective response of composite materials. The present study extends and improves on this approach in different directions. It is first shown that when the constitutive relations of the constituents derive from two potentials, this structure is passed to the NTFA model. Another structure-preserving model, the hybrid NTFA model of Fritzen and Leuschner, is analyzed and found to differ (slightly) from the primal NTFA model (it does not exhibit the same variational upper bound character). To avoid the "on-line" computation of local fields required by the hybrid model, new reduced evolution equations for the reduced variables are proposed, based on an expansion to second order (TSO) of the potential of the hybrid model. The coarse dynamics can then be entirely expressed in terms of quantities which can be pre-computed once for all. Roughly speaking, these pre-computed quantities depend only on the average and fluctuations per phase of the modes and of the associated stress fields. The accuracy of the new NTFA-TSO model is assessed by comparison with full-field simulations. The acceleration provided by the new coarse dynamics over the full-field computations (and over the hybrid model) is then spectacular, larger by three orders of magnitude than the acceleration due to the sole reduction of unknowns.

Improved Aviation Readiness and Inventory Reductions Through Repair Cycle Time Reductions Using Modeling and Simulation.

DTIC Science & Technology

1997-12-01

three NADEP’s within the continental United States and fleet repair sites in Italy and Japan. These facilities are located to support specific...number order. This same morning, P&E’s have a last opportunity to edit the induction file through the Planner and Estimator Cancellation Program ( PECAN

Residual acceleration data on IML-1: Development of a data reduction and dissemination plan

NASA Technical Reports Server (NTRS)

Rogers, Melissa J. B.; Alexander, J. Iwan D.

1993-01-01

The research performed consisted of three stages: (1) identification of sensitive IML-1 experiments and sensitivity ranges by order of magnitude estimates, numerical modeling, and investigator input; (2) research and development towards reduction, supplementation, and dissemination of residual acceleration data; and (3) implementation of the plan on existing acceleration databases.

Applying multi-criteria decision-making to improve the waste reduction policy in Taiwan.

PubMed

Su, Jun-Pin; Hung, Ming-Lung; Chao, Chia-Wei; Ma, Hwong-wen

2010-01-01

Over the past two decades, the waste reduction problem has been a major issue in environmental protection. Both recycling and waste reduction policies have become increasingly important. As the complexity of decision-making has increased, it has become evident that more factors must be considered in the development and implementation of policies aimed at resource recycling and waste reduction. There are many studies focused on waste management excluding waste reduction. This study paid more attention to waste reduction. Social, economic, and management aspects of waste treatment policies were considered in this study. Further, a life-cycle assessment model was applied as an evaluation system for the environmental aspect. Results of both quantitative and qualitative analyses on the social, economic, and management aspects were integrated via the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method into the comprehensive decision-making support system of multi-criteria decision-making (MCDM). A case study evaluating the waste reduction policy in Taoyuan County is presented to demonstrate the feasibility of this model. In the case study, reinforcement of MSW sorting was shown to be the best practice. The model in this study can be applied to other cities faced with the waste reduction problems.

Optimal fixed-finite-dimensional compensator for Burgers' equation with unbounded input/output operators

NASA Technical Reports Server (NTRS)

Burns, John A.; Marrekchi, Hamadi

1993-01-01

The problem of using reduced order dynamic compensators to control a class of nonlinear parabolic distributed parameter systems was considered. Concentration was on a system with unbounded input and output operators governed by Burgers' equation. A linearized model was used to compute low-order-finite-dimensional control laws by minimizing certain energy functionals. Then these laws were applied to the nonlinear model. Standard approaches to this problem employ model/controller reduction techniques in conjunction with linear quadratic Gaussian (LQG) theory. The approach used is based on the finite dimensional Bernstein/Hyland optimal projection theory which yields a fixed-finite-order controller.

Development of Boundary Condition Independent Reduced Order Thermal Models using Proper Orthogonal Decomposition

NASA Astrophysics Data System (ADS)

Raghupathy, Arun; Ghia, Karman; Ghia, Urmila

2008-11-01

Compact Thermal Models (CTM) to represent IC packages has been traditionally developed using the DELPHI-based (DEvelopment of Libraries of PHysical models for an Integrated design) methodology. The drawbacks of this method are presented, and an alternative method is proposed. A reduced-order model that provides the complete thermal information accurately with less computational resources can be effectively used in system level simulations. Proper Orthogonal Decomposition (POD), a statistical method, can be used to reduce the order of the degree of freedom or variables of the computations for such a problem. POD along with the Galerkin projection allows us to create reduced-order models that reproduce the characteristics of the system with a considerable reduction in computational resources while maintaining a high level of accuracy. The goal of this work is to show that this method can be applied to obtain a boundary condition independent reduced-order thermal model for complex components. The methodology is applied to the 1D transient heat equation.

Steel Alloy Hot Roll Simulations and Through-Thickness Variation Using Dislocation Density-Based Modeling

NASA Astrophysics Data System (ADS)

Jansen Van Rensburg, G. J.; Kok, S.; Wilke, D. N.

2017-10-01

Different roll pass reduction schedules have different effects on the through-thickness properties of hot-rolled metal slabs. In order to assess or improve a reduction schedule using the finite element method, a material model is required that captures the relevant deformation mechanisms and physics. The model should also report relevant field quantities to assess variations in material state through the thickness of a simulated rolled metal slab. In this paper, a dislocation density-based material model with recrystallization is presented and calibrated on the material response of a high-strength low-alloy steel. The model has the ability to replicate and predict material response to a fair degree thanks to the physically motivated mechanisms it is built on. An example study is also presented to illustrate the possible effect different reduction schedules could have on the through-thickness material state and the ability to assess these effects based on finite element simulations.

An experimental investigation of internal area ruling for transonic and supersonic channel flow

NASA Technical Reports Server (NTRS)

Roberts, W. B.; Vanrintel, H. L.; Rizvi, G.

1982-01-01

A simulated transonic rotor channel model was examined experimentally to verify the flow physics of internal area ruling. Pressure measurements were performed in the high speed wind tunnel at transonic speeds with Mach 1.5 and Mach 2 nozzle blocks to get an indication of the approximate shock losses. The results showed a reduction in losses due to internal area ruling with the Mach 1.5 nozzle blocks. The reduction in total loss coefficient was of the order of 17 percent for a high blockage model and 7 percent for a cut-down model.

Network community-based model reduction for vortical flows

NASA Astrophysics Data System (ADS)

Gopalakrishnan Meena, Muralikrishnan; Nair, Aditya G.; Taira, Kunihiko

2018-06-01

A network community-based reduced-order model is developed to capture key interactions among coherent structures in high-dimensional unsteady vortical flows. The present approach is data-inspired and founded on network-theoretic techniques to identify important vortical communities that are comprised of vortical elements that share similar dynamical behavior. The overall interaction-based physics of the high-dimensional flow field is distilled into the vortical community centroids, considerably reducing the system dimension. Taking advantage of these vortical interactions, the proposed methodology is applied to formulate reduced-order models for the inter-community dynamics of vortical flows, and predict lift and drag forces on bodies in wake flows. We demonstrate the capabilities of these models by accurately capturing the macroscopic dynamics of a collection of discrete point vortices, and the complex unsteady aerodynamic forces on a circular cylinder and an airfoil with a Gurney flap. The present formulation is found to be robust against simulated experimental noise and turbulence due to its integrating nature of the system reduction.

Higher-order gravity in higher dimensions: geometrical origins of four-dimensional cosmology?

NASA Astrophysics Data System (ADS)

Troisi, Antonio

2017-03-01

Determining the cosmological field equations is still very much debated and led to a wide discussion around different theoretical proposals. A suitable conceptual scheme could be represented by gravity models that naturally generalize Einstein theory like higher-order gravity theories and higher-dimensional ones. Both of these two different approaches allow one to define, at the effective level, Einstein field equations equipped with source-like energy-momentum tensors of geometrical origin. In this paper, the possibility is discussed to develop a five-dimensional fourth-order gravity model whose lower-dimensional reduction could provide an interpretation of cosmological four-dimensional matter-energy components. We describe the basic concepts of the model, the complete field equations formalism and the 5-D to 4-D reduction procedure. Five-dimensional f( R) field equations turn out to be equivalent, on the four-dimensional hypersurfaces orthogonal to the extra coordinate, to an Einstein-like cosmological model with three matter-energy tensors related with higher derivative and higher-dimensional counter-terms. By considering the gravity model with f(R)=f_0R^n the possibility is investigated to obtain five-dimensional power law solutions. The effective four-dimensional picture and the behaviour of the geometrically induced sources are finally outlined in correspondence to simple cases of such higher-dimensional solutions.

Reduction of hexavalent chromium by fasted and fed human gastric fluid. II. Ex vivo gastric reduction modeling

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

Kirman, Christopher R., E-mail: ckirman@summittoxi

To extend previous models of hexavalent chromium [Cr(VI)] reduction by gastric fluid (GF), ex vivo experiments were conducted to address data gaps and limitations identified with respect to (1) GF dilution in the model; (2) reduction of Cr(VI) in fed human GF samples; (3) the number of Cr(VI) reduction pools present in human GF under fed, fasted, and proton pump inhibitor (PPI)-use conditions; and (4) an appropriate form for the pH-dependence of Cr(VI) reduction rate constants. Rates and capacities of Cr(VI) reduction were characterized in gastric contents from fed and fasted volunteers, and from fasted pre-operative patients treated with PPIs.more » Reduction capacities were first estimated over a 4-h reduction period. Once reduction capacity was established, a dual-spike approach was used in speciated isotope dilution mass spectrometry analyses to characterize the concentration-dependence of the 2nd order reduction rate constants. These data, when combined with previously collected data, were well described by a three-pool model (pool 1 = fast reaction with low capacity; pool 2 = slow reaction with higher capacity; pool 3 = very slow reaction with higher capacity) using pH-dependent rate constants characterized by a piecewise, log-linear relationship. These data indicate that human gastric samples, like those collected from rats and mice, contain multiple pools of reducing agents, and low concentrations of Cr(VI) (< 0.7 mg/L) are reduced more rapidly than high concentrations. The data and revised modeling results herein provide improved characterization of Cr(VI) gastric reduction kinetics, critical for Cr(VI) pharmacokinetic modeling and human health risk assessment. - Highlights: • SIDMS allows for measurement of Cr(VI) reduction rate in gastric fluid ex vivo • Human gastric fluid has three reducing pools • Cr(VI) in drinking water at < 0.7 mg/L is rapidly reduced in human gastric fluid • Reduction rate is concentration- and pH-dependent • A refined PK model is used to characterize inter-individual variability in Cr(VI) gastric reduction capacity.« less

Defeaturing CAD models using a geometry-based size field and facet-based reduction operators.

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

Quadros, William Roshan; Owen, Steven James

2010-04-01

We propose a method to automatically defeature a CAD model by detecting irrelevant features using a geometry-based size field and a method to remove the irrelevant features via facet-based operations on a discrete representation. A discrete B-Rep model is first created by obtaining a faceted representation of the CAD entities. The candidate facet entities are then marked for reduction by using a geometry-based size field. This is accomplished by estimating local mesh sizes based on geometric criteria. If the field value at a facet entity goes below a user specified threshold value then it is identified as an irrelevant featuremore » and is marked for reduction. The reduction of marked facet entities is primarily performed using an edge collapse operator. Care is taken to retain a valid geometry and topology of the discrete model throughout the procedure. The original model is not altered as the defeaturing is performed on a separate discrete model. Associativity between the entities of the discrete model and that of original CAD model is maintained in order to decode the attributes and boundary conditions applied on the original CAD entities onto the mesh via the entities of the discrete model. Example models are presented to illustrate the effectiveness of the proposed approach.« less

A model-reduction approach to the micromechanical analysis of polycrystalline materials

NASA Astrophysics Data System (ADS)

Michel, Jean-Claude; Suquet, Pierre

2016-03-01

The present study is devoted to the extension to polycrystals of a model-reduction technique introduced by the authors, called the nonuniform transformation field analysis (NTFA). This new reduced model is obtained in two steps. First the local fields of internal variables are decomposed on a reduced basis of modes as in the NTFA. Second the dissipation potential of the phases is replaced by its tangent second-order (TSO) expansion. The reduced evolution equations of the model can be entirely expressed in terms of quantities which can be pre-computed once for all. Roughly speaking, these pre-computed quantities depend only on the average and fluctuations per phase of the modes and of the associated stress fields. The accuracy of the new NTFA-TSO model is assessed by comparison with full-field simulations on two specific applications, creep of polycrystalline ice and response of polycrystalline copper to a cyclic tension-compression test. The new reduced evolution equations is faster than the full-field computations by two orders of magnitude in the two examples.

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.

Detection of Epistasis for Flowering Time Using Bayesian Multilocus Estimation in a Barley MAGIC Population

PubMed Central

Mathew, Boby; Léon, Jens; Sannemann, Wiebke; Sillanpää, Mikko J.

2018-01-01

Gene-by-gene interactions, also known as epistasis, regulate many complex traits in different species. With the availability of low-cost genotyping it is now possible to study epistasis on a genome-wide scale. However, identifying genome-wide epistasis is a high-dimensional multiple regression problem and needs the application of dimensionality reduction techniques. Flowering Time (FT) in crops is a complex trait that is known to be influenced by many interacting genes and pathways in various crops. In this study, we successfully apply Sure Independence Screening (SIS) for dimensionality reduction to identify two-way and three-way epistasis for the FT trait in a Multiparent Advanced Generation Inter-Cross (MAGIC) barley population using the Bayesian multilocus model. The MAGIC barley population was generated from intercrossing among eight parental lines and thus, offered greater genetic diversity to detect higher-order epistatic interactions. Our results suggest that SIS is an efficient dimensionality reduction approach to detect high-order interactions in a Bayesian multilocus model. We also observe that many of our findings (genomic regions with main or higher-order epistatic effects) overlap with known candidate genes that have been already reported in barley and closely related species for the FT trait. PMID:29254994

Analysis of E-marketplace Attributes: Assessing The NATO Logistics Stock Exchange

DTIC Science & Technology

2008-01-01

order processing time Reduction of stock levels Reduction of payment processing time Reduction of excessive stocks Reduction of maverick buying...satisfaction 4,02 0,151 3. Reduction of order processing time 4,27 0,317 15. Reduction of stock levels 3,87 0,484 4. Reduction of payment processing time...information exchange with partners in the supply chain Efficiency Basic Reduction of order processing time Efficiency Important Reduction of

Adaptive parametric model order reduction technique for optimization of vibro-acoustic models: Application to hearing aid design

NASA Astrophysics Data System (ADS)

Creixell-Mediante, Ester; Jensen, Jakob S.; Naets, Frank; Brunskog, Jonas; Larsen, Martin

2018-06-01

Finite Element (FE) models of complex structural-acoustic coupled systems can require a large number of degrees of freedom in order to capture their physical behaviour. This is the case in the hearing aid field, where acoustic-mechanical feedback paths are a key factor in the overall system performance and modelling them accurately requires a precise description of the strong interaction between the light-weight parts and the internal and surrounding air over a wide frequency range. Parametric optimization of the FE model can be used to reduce the vibroacoustic feedback in a device during the design phase; however, it requires solving the model iteratively for multiple frequencies at different parameter values, which becomes highly time consuming when the system is large. Parametric Model Order Reduction (pMOR) techniques aim at reducing the computational cost associated with each analysis by projecting the full system into a reduced space. A drawback of most of the existing techniques is that the vector basis of the reduced space is built at an offline phase where the full system must be solved for a large sample of parameter values, which can also become highly time consuming. In this work, we present an adaptive pMOR technique where the construction of the projection basis is embedded in the optimization process and requires fewer full system analyses, while the accuracy of the reduced system is monitored by a cheap error indicator. The performance of the proposed method is evaluated for a 4-parameter optimization of a frequency response for a hearing aid model, evaluated at 300 frequencies, where the objective function evaluations become more than one order of magnitude faster than for the full system.

A Developing Educational Psychology Service Work-Allocation Model

ERIC Educational Resources Information Center

Marsh, Alan J.; Higgins, Andrea

2018-01-01

As UK governments continue with the economic policy of deficit reduction from 2010, many Local Authorities' (LAs) Educational Psychology Services (EPSs) have begun to develop "traded" models of service delivery in order to maintain jobs and secure services. Nevertheless, EPSs still provide a core service delivery to schools, settings and…

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

Soil retention of hexavalent chromium released from construction and demolition waste in a road-base-application scenario.

PubMed

Butera, Stefania; Trapp, Stefan; Astrup, Thomas F; Christensen, Thomas H

2015-11-15

We investigated the retention of Cr(VI) in three subsoils with low organic matter content in laboratory experiments at concentration levels relevant to represent leachates from construction and demolition waste (C&DW) reused as unbound material in road construction. The retention mechanism appeared to be reduction and subsequent precipitation as Cr(III) on the soil. The reduction process was slow and in several experiments it was still proceeding at the end of the six-month experimental period. The overall retention reaction fit well with a second-order reaction governed by actual Cr(VI) concentration and reduction capacity of the soil. The experimentally determined reduction capacities and second-order kinetic parameters were used to model, for a 100-year period, the one-dimensional migration of Cr(VI) in the subsoil under a layer of C&DW. The resulting Cr(VI) concentration would be negligible below 7-70 cm depth. However, in rigid climates and with high water infiltration through the road pavement, the reduction reaction could be so slow that Cr(VI) might migrate as deep as 200 cm under the road. The reaction parameters and the model can form the basis for systematically assessing under which scenarios Cr(VI) from C&DW could lead to an environmental issue for ground- and receiving surface waters. Copyright © 2015 Elsevier B.V. All rights reserved.

Large space structure model reduction and control system design based upon actuator and sensor influence functions

NASA Technical Reports Server (NTRS)

Yam, Y.; Lang, J. H.; Johnson, T. L.; Shih, S.; Staelin, D. H.

1983-01-01

A model reduction procedure based on aggregation with respect to sensor and actuator influences rather than modes is presented for large systems of coupled second-order differential equations. Perturbation expressions which can predict the effects of spillover on both the aggregated and residual states are derived. These expressions lead to the development of control system design constraints which are sufficient to guarantee, to within the validity of the perturbations, that the residual states are not destabilized by control systems designed from the reduced model. A numerical example is provided to illustrate the application of the aggregation and control system design method.

Application of Lanczos vectors to control design of flexible structures

NASA Technical Reports Server (NTRS)

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

1990-01-01

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

Stream-wise distribution of skin-friction drag reduction on a flat plate with bubble injection

NASA Astrophysics Data System (ADS)

Qin, Shijie; Chu, Ning; Yao, Yan; Liu, Jingting; Huang, Bin; Wu, Dazhuan

2017-03-01

To investigate the stream-wise distribution of skin-friction drag reduction on a flat plate with bubble injection, both experiments and simulations of bubble drag reduction (BDR) have been conducted in this paper. Drag reductions at various flow speeds and air injection rates have been tested in cavitation tunnel experiments. Visualization of bubble flow pattern is implemented synchronously. The computational fluid dynamics (CFD) method, in the framework of Eulerian-Eulerian two fluid modeling, coupled with population balance model (PBM) is used to simulate the bubbly flow along the flat plate. A wide range of bubble sizes considering bubble breakup and coalescence is modeled based on experimental bubble distribution images. Drag and lift forces are fully modeled based on applicable closure models. Both predicted drag reductions and bubble distributions are in reasonable concordance with experimental results. Stream-wise distribution of BDR is revealed based on CFD-PBM numerical results. In particular, four distinct regions with different BDR characteristics are first identified and discussed in this study. Thresholds between regions are extracted and discussed. And it is highly necessary to fully understand the stream-wise distribution of BDR in order to establish a universal scaling law. Moreover, mechanism of stream-wise distribution of BDR is analysed based on the near-wall flow parameters. The local drag reduction is a direct result of near-wall max void fraction. And the near-wall velocity gradient modified by the presence of bubbles is considered as another important factor for bubble drag reduction.

Evaluation of Parameter Uncertainty Reduction in Groundwater Flow Modeling Using Multiple Environmental Tracers

NASA Astrophysics Data System (ADS)

Arnold, B. W.; Gardner, P.

2013-12-01

Calibration of groundwater flow models for the purpose of evaluating flow and aquifer heterogeneity typically uses observations of hydraulic head in wells and appropriate boundary conditions. Environmental tracers have a wide variety of decay rates and input signals in recharge, resulting in a potentially broad source of additional information to constrain flow rates and heterogeneity. A numerical study was conducted to evaluate the reduction in uncertainty during model calibration using observations of various environmental tracers and combinations of tracers. A synthetic data set was constructed by simulating steady groundwater flow and transient tracer transport in a high-resolution, 2-D aquifer with heterogeneous permeability and porosity using the PFLOTRAN software code. Data on pressure and tracer concentration were extracted at well locations and then used as observations for automated calibration of a flow and transport model using the pilot point method and the PEST code. Optimization runs were performed to estimate parameter values of permeability at 30 pilot points in the model domain for cases using 42 observations of: 1) pressure, 2) pressure and CFC11 concentrations, 3) pressure and Ar-39 concentrations, and 4) pressure, CFC11, Ar-39, tritium, and He-3 concentrations. Results show significantly lower uncertainty, as indicated by the 95% linear confidence intervals, in permeability values at the pilot points for cases including observations of environmental tracer concentrations. The average linear uncertainty range for permeability at the pilot points using pressure observations alone is 4.6 orders of magnitude, using pressure and CFC11 concentrations is 1.6 orders of magnitude, using pressure and Ar-39 concentrations is 0.9 order of magnitude, and using pressure, CFC11, Ar-39, tritium, and He-3 concentrations is 1.0 order of magnitude. Data on Ar-39 concentrations result in the greatest parameter uncertainty reduction because its half-life of 269 years is similar to the range of transport times (hundreds to thousands of years) in the heterogeneous synthetic aquifer domain. The slightly higher uncertainty range for the case using all of the environmental tracers simultaneously is probably due to structural errors in the model introduced by the pilot point regularization scheme. It is concluded that maximum information and uncertainty reduction for constraining a groundwater flow model is obtained using an environmental tracer whose half-life is well matched to the range of transport times through the groundwater flow system. Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

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.

Engineering Inertial and Primary-Frequency Response for Distributed Energy Resources: Preprint

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

Dall-Anese, Emiliano; Zhao, Changhong; Guggilam, Swaroop

We propose a framework to engineer synthetic-inertia and droop-control parameters for distributed energy resources (DERs) so that the system frequency in a network composed of DERs and synchronous generators conforms to prescribed transient and steady-state performance specifications. Our approach is grounded in a second-order lumped-parameter model that captures the dynamics of synchronous generators and frequency-responsive DERs endowed with inertial and droop control. A key feature of this reduced-order model is that its parameters can be related to those of the originating higher-order dynamical model. This allows one to systematically design the DER inertial and droop-control coefficients leveraging classical frequency-domain responsemore » characteristics of second-order systems. Time-domain simulations validate the accuracy of the model-reduction method and demonstrate how DER controllers can be designed to meet steady-state-regulation and transient-performance specifications.« less

Interior noise control prediction study for high-speed propeller-driven aircraft

NASA Technical Reports Server (NTRS)

Rennison, D. C.; Wilby, J. F.; Marsh, A. H.; Wilby, E. G.

1979-01-01

An analytical model was developed to predict the noise levels inside propeller-driven aircraft during cruise at M = 0.8. The model was applied to three study aircraft with fuselages of different size (wide body, narrow body and small diameter) in order to determine the noise reductions required to achieve the goal of an A-weighted sound level which does not exceed 80 dB. The model was then used to determine noise control methods which could achieve the required noise reductions. Two classes of noise control treatments were investigated: add-on treatments which can be added to existing structures, and advanced concepts which would require changes to the fuselage primary structure. Only one treatment, a double wall with limp panel, provided the required noise reductions. Weight penalties associated with the treatment were estimated for the three study aircraft.

How to simulate pedestrian behaviors in seismic evacuation for vulnerability reduction of existing buildings

NASA Astrophysics Data System (ADS)

Quagliarini, Enrico; Bernardini, Gabriele; D'Orazio, Marco

2017-07-01

Understanding and representing how individuals behave in earthquake emergencies would be essentially to assess the impact of vulnerability reduction strategies on existing buildings in seismic areas. In fact, interactions between individuals and the scenario (modified by the earthquake occurrence) are really important in order to understand the possible additional risks for people, especially during the evacuation phase. The current approach is based on "qualitative" aspects, in order to define best practice guidelines for Civil Protection and populations. On the contrary, a "quantitative" description of human response and evacuation motion in similar conditions is urgently needed. Hence, this work defines the rules for pedestrians' earthquake evacuation in urban scenarios, by taking advantages of previous results of real-world evacuation analyses. In particular, motion laws for pedestrians is defined by modifying the Social Force model equation. The proposed model could be used for evaluating individuals' evacuation process and so for defining operative strategies for interferences reduction in critical urban fabric parts (e.g.: interventions on particular buildings, evacuation strategies definition, city parts projects).

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

Hybrid Reduced Order Modeling Algorithms for Reactor Physics Calculations

NASA Astrophysics Data System (ADS)

Bang, Youngsuk

Reduced order modeling (ROM) has been recognized as an indispensable approach when the engineering analysis requires many executions of high fidelity simulation codes. Examples of such engineering analyses in nuclear reactor core calculations, representing the focus of this dissertation, include the functionalization of the homogenized few-group cross-sections in terms of the various core conditions, e.g. burn-up, fuel enrichment, temperature, etc. This is done via assembly calculations which are executed many times to generate the required functionalization for use in the downstream core calculations. Other examples are sensitivity analysis used to determine important core attribute variations due to input parameter variations, and uncertainty quantification employed to estimate core attribute uncertainties originating from input parameter uncertainties. ROM constructs a surrogate model with quantifiable accuracy which can replace the original code for subsequent engineering analysis calculations. This is achieved by reducing the effective dimensionality of the input parameter, the state variable, or the output response spaces, by projection onto the so-called active subspaces. Confining the variations to the active subspace allows one to construct an ROM model of reduced complexity which can be solved more efficiently. This dissertation introduces a new algorithm to render reduction with the reduction errors bounded based on a user-defined error tolerance which represents the main challenge of existing ROM techniques. Bounding the error is the key to ensuring that the constructed ROM models are robust for all possible applications. Providing such error bounds represents one of the algorithmic contributions of this dissertation to the ROM state-of-the-art. Recognizing that ROM techniques have been developed to render reduction at different levels, e.g. the input parameter space, the state space, and the response space, this dissertation offers a set of novel hybrid ROM algorithms which can be readily integrated into existing methods and offer higher computational efficiency and defendable accuracy of the reduced models. For example, the snapshots ROM algorithm is hybridized with the range finding algorithm to render reduction in the state space, e.g. the flux in reactor calculations. In another implementation, the perturbation theory used to calculate first order derivatives of responses with respect to parameters is hybridized with a forward sensitivity analysis approach to render reduction in the parameter space. Reduction at the state and parameter spaces can be combined to render further reduction at the interface between different physics codes in a multi-physics model with the accuracy quantified in a similar manner to the single physics case. Although the proposed algorithms are generic in nature, we focus here on radiation transport models used in support of the design and analysis of nuclear reactor cores. In particular, we focus on replacing the traditional assembly calculations by ROM models to facilitate the generation of homogenized cross-sections for downstream core calculations. The implication is that assembly calculations could be done instantaneously therefore precluding the need for the expensive evaluation of the few-group cross-sections for all possible core conditions. Given the generic natures of the algorithms, we make an effort to introduce the material in a general form to allow non-nuclear engineers to benefit from this work.

Extreme learning machine for reduced order modeling of turbulent geophysical flows.

PubMed

San, Omer; Maulik, Romit

2018-04-01

We investigate the application of artificial neural networks to stabilize proper orthogonal decomposition-based reduced order models for quasistationary geophysical turbulent flows. An extreme learning machine concept is introduced for computing an eddy-viscosity closure dynamically to incorporate the effects of the truncated modes. We consider a four-gyre wind-driven ocean circulation problem as our prototype setting to assess the performance of the proposed data-driven approach. Our framework provides a significant reduction in computational time and effectively retains the dynamics of the full-order model during the forward simulation period beyond the training data set. Furthermore, we show that the method is robust for larger choices of time steps and can be used as an efficient and reliable tool for long time integration of general circulation models.

Extreme learning machine for reduced order modeling of turbulent geophysical flows

NASA Astrophysics Data System (ADS)

San, Omer; Maulik, Romit

2018-04-01

We investigate the application of artificial neural networks to stabilize proper orthogonal decomposition-based reduced order models for quasistationary geophysical turbulent flows. An extreme learning machine concept is introduced for computing an eddy-viscosity closure dynamically to incorporate the effects of the truncated modes. We consider a four-gyre wind-driven ocean circulation problem as our prototype setting to assess the performance of the proposed data-driven approach. Our framework provides a significant reduction in computational time and effectively retains the dynamics of the full-order model during the forward simulation period beyond the training data set. Furthermore, we show that the method is robust for larger choices of time steps and can be used as an efficient and reliable tool for long time integration of general circulation models.

Biological Sulfate Reduction Rates in Hydrothermal Recharge Zones

NASA Astrophysics Data System (ADS)

Crowell, B.; Lowell, R. P.

2007-12-01

We develop a model to determine the rate of removal of seawater sulfate in the recharge regions of deep-sea hydrothermal systems as a result of biogenic sulfate reduction. The rate of sulfate reduction as a function of temperature derived from laboratory measurements on cores from the Guaymas Basin in Mexico [Jorgensen et al., 1992] is incorporated into a steady state 1-D advection-diffusion temperature equation, and a 1-D, steady- state, advection dominated conservation of solute equation. The diffusivity of sulfate in seawater is on the order of ~ 10-10 m2/s, and unless the flow speeds are < 10-12 m/s, the effects of diffusion are negligible, except within thin diffusive boundary layers. This model is then compared with a model that utilizes Gibbs free energy to quantify biogenic sulfate reduction [Bach and Edwards, 2003] in the upper oceanic crust of aging lithosphere. Using the high rates determined by Jorgensen et al. [1992], our model indicates that biological activity would reduce all seawater sulfate transported into the system within the upper 10 meters or less of the crust, which is inconsistent with the estimates of Bach and Edwards [2003]. Sulfate concentrations from ODP borehole Legs 64 and 168, at the sedimented Guaymas Basin and Juan de Fuca Ridge, respectively, show that most of the seawater sulfate is removed in the upper 100 meters. If the sulfate is assumed to all be reduced biogenically, the sulfate reduction rates at the ODP sites are at least 2 orders of magnitude less than the laboratory estimates of Jorgenson et al. [1992]. Finally, we compare the rate of seawater sulfate removal as a result of the precipitation of anhydrite, with the rate of biogenic sulfate reduction. We find that if hydrothermal recharge occurs rapidly through highly permeable faults, that biogenic sulfate reduction is negligible and that anhydrite precipitation would rapidly clog the recharge zone [Lowell and Yao, 2002]. If recharge occurs through broad zones of slow downwelling (u

Advanced moisture modeling of polymer composites.

DOT National Transportation Integrated Search

2014-04-01

Long term moisture exposure has been shown to affect the mechanical performance of polymeric composite structures. This reduction : in mechanical performance must be considered during product design in order to ensure long term structure survival. In...

Accounting for large deformations in real-time simulations of soft tissues based on reduced-order models.

PubMed

Niroomandi, S; Alfaro, I; Cueto, E; Chinesta, F

2012-01-01

Model reduction techniques have shown to constitute a valuable tool for real-time simulation in surgical environments and other fields. However, some limitations, imposed by real-time constraints, have not yet been overcome. One of such limitations is the severe limitation in time (established in 500Hz of frequency for the resolution) that precludes the employ of Newton-like schemes for solving non-linear models as the ones usually employed for modeling biological tissues. In this work we present a technique able to deal with geometrically non-linear models, based on the employ of model reduction techniques, together with an efficient non-linear solver. Examples of the performance of the technique over some examples will be given. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

High subsonic flow tests of a parallel pipe followed by a large area ratio diffuser

NASA Technical Reports Server (NTRS)

Barna, P. S.

1975-01-01

Experiments were performed on a pilot model duct system in order to explore its aerodynamic characteristics. The model was scaled from a design projected for the high speed operation mode of the Aircraft Noise Reduction Laboratory. The test results show that the model performed satisfactorily and therefore the projected design will most likely meet the specifications.

Using model order tests to determine sensory inputs in a motion study

NASA Technical Reports Server (NTRS)

Repperger, D. W.; Junker, A. M.

1977-01-01

In the study of motion effects on tracking performance, a problem of interest is the determination of what sensory inputs a human uses in controlling his tracking task. In the approach presented here a simple canonical model (FID or a proportional, integral, derivative structure) is used to model the human's input-output time series. A study of significant changes in reduction of the output error loss functional is conducted as different permutations of parameters are considered. Since this canonical model includes parameters which are related to inputs to the human (such as the error signal, its derivatives and integration), the study of model order is equivalent to the study of which sensory inputs are being used by the tracker. The parameters are obtained which have the greatest effect on reducing the loss function significantly. In this manner the identification procedure converts the problem of testing for model order into the problem of determining sensory inputs.

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

An Integrated Approach to Economic and Environmental Aspects of Air Pollution and Climate Interactions

NASA Astrophysics Data System (ADS)

Sarofim, M. C.

2007-12-01

Emissions of greenhouses gases and conventional pollutants are closely linked through shared generation processes and thus policies directed toward long-lived greenhouse gases affect emissions of conventional pollutants and, similarly, policies directed toward conventional pollutants affect emissions of greenhouse gases. Some conventional pollutants such as aerosols also have direct radiative effects. NOx and VOCs are ozone precursors, another substance with both radiative and health impacts, and these ozone precursors also interact with the chemistry of the hydroxyl radical which is the major methane sink. Realistic scenarios of future emissions and concentrations must therefore account for both air pollution and greenhouse gas policies and how they interact economically as well as atmospherically, including the regional pattern of emissions and regulation. We have modified a 16 region computable general equilibrium economic model (the MIT Emissions Prediction and Policy Analysis model) by including elasticities of substitution for ozone precursors and aerosols in order to examine these interactions between climate policy and air pollution policy on a global scale. Urban emissions are distributed based on population density, and aged using a reduced form urban model before release into an atmospheric chemistry/climate model (the earth systems component of the MIT Integrated Global Systems Model). This integrated approach enables examination of the direct impacts of air pollution on climate, the ancillary and complementary interactions between air pollution and climate policies, and the impact of different population distribution algorithms or urban emission aging schemes on global scale properties. This modeling exercise shows that while ozone levels are reduced due to NOx and VOC reductions, these reductions lead to an increase in methane concentrations that eliminates the temperature effects of the ozone reductions. However, black carbon reductions do have significant direct effects on global mean temperatures, as do ancillary reductions of greenhouse gases due to the pollution constraints imposed in the economic model. Finally, we show that the economic benefits of coordinating air pollution and climate policies rather than separate implementation are on the order of 20% of the total policy cost.

Continuous piecewise-linear, reduced-order electrochemical model for lithium-ion batteries in real-time applications

NASA Astrophysics Data System (ADS)

Farag, Mohammed; Fleckenstein, Matthias; Habibi, Saeid

2017-02-01

Model-order reduction and minimization of the CPU run-time while maintaining the model accuracy are critical requirements for real-time implementation of lithium-ion electrochemical battery models. In this paper, an isothermal, continuous, piecewise-linear, electrode-average model is developed by using an optimal knot placement technique. The proposed model reduces the univariate nonlinear function of the electrode's open circuit potential dependence on the state of charge to continuous piecewise regions. The parameterization experiments were chosen to provide a trade-off between extensive experimental characterization techniques and purely identifying all parameters using optimization techniques. The model is then parameterized in each continuous, piecewise-linear, region. Applying the proposed technique cuts down the CPU run-time by around 20%, compared to the reduced-order, electrode-average model. Finally, the model validation against real-time driving profiles (FTP-72, WLTP) demonstrates the ability of the model to predict the cell voltage accurately with less than 2% error.

Finite-dimensional approximation for optimal fixed-order compensation of distributed parameter systems

NASA Technical Reports Server (NTRS)

Bernstein, Dennis S.; Rosen, I. G.

1988-01-01

In controlling distributed parameter systems it is often desirable to obtain low-order, finite-dimensional controllers in order to minimize real-time computational requirements. Standard approaches to this problem employ model/controller reduction techniques in conjunction with LQG theory. In this paper we consider the finite-dimensional approximation of the infinite-dimensional Bernstein/Hyland optimal projection theory. This approach yields fixed-finite-order controllers which are optimal with respect to high-order, approximating, finite-dimensional plant models. The technique is illustrated by computing a sequence of first-order controllers for one-dimensional, single-input/single-output, parabolic (heat/diffusion) and hereditary systems using spline-based, Ritz-Galerkin, finite element approximation. Numerical studies indicate convergence of the feedback gains with less than 2 percent performance degradation over full-order LQG controllers for the parabolic system and 10 percent degradation for the hereditary system.

Modeling of Thermochemical Behavior in an Industrial-Scale Rotary Hearth Furnace for Metallurgical Dust Recycling

NASA Astrophysics Data System (ADS)

Wu, Yu-Liang; Jiang, Ze-Yi; Zhang, Xin-Xin; Xue, Qing-Guo; Yu, Ai-Bing; Shen, Yan-Song

2017-10-01

Metallurgical dusts can be recycled through direct reduction in rotary hearth furnaces (RHFs) via addition into carbon-based composite pellets. While iron in the dust is recycled, several heavy and alkali metal elements harmful for blast furnace operation, including Zn, Pb, K, and Na, can also be separated and then recycled. However, there is a lack of understanding on thermochemical behavior related to direct reduction in an industrial-scale RHF, especially removal behavior of Zn, Pb, K, and Na, leading to technical issues in industrial practice. In this work, an integrated model of the direct reduction process in an industrial-scale RHF is described. The integrated model includes three mathematical submodels and one physical model, specifically, a three-dimensional (3-D) CFD model of gas flow and heat transfer in an RHF chamber, a one-dimensional (1-D) CFD model of direct reduction inside a pellet, an energy/mass equilibrium model, and a reduction physical experiment using a Si-Mo furnace. The model is validated by comparing the simulation results with measurements in terms of furnace temperature, furnace pressure, and pellet indexes. The model is then used for describing in-furnace phenomena and pellet behavior in terms of heat transfer, direct reduction, and removal of a range of heavy and alkali metal elements under industrial-scale RHF conditions. The results show that the furnace temperature in the preheating section should be kept at a higher level in an industrial-scale RHF compared with that in a pilot-scale RHF. The removal rates of heavy and alkali metal elements inside the composite pellet are all faster than iron metallization, specifically in the order of Pb, Zn, K, and Na.

Model reduction for Space Station Freedom

NASA Technical Reports Server (NTRS)

Williams, Trevor

1992-01-01

Model reduction is an important practical problem in the control of flexible spacecraft, and a considerable amount of work has been carried out on this topic. Two of the best known methods developed are modal truncation and internal balancing. Modal truncation is simple to implement but can give poor results when the structure possesses clustered natural frequencies, as often occurs in practice. Balancing avoids this problem but has the disadvantages of high computational cost, possible numerical sensitivity problems, and no physical interpretation for the resulting balanced 'modes'. The purpose of this work is to examine the performance of the subsystem balancing technique developed by the investigator when tested on a realistic flexible space structure, in this case a model of the Permanently Manned Configuration (PMC) of Space Station Freedom. This method retains the desirable properties of standard balancing while overcoming the three difficulties listed above. It achieves this by first decomposing the structural model into subsystems of highly correlated modes. Each subsystem is approximately uncorrelated from all others, so balancing them separately and then combining yields comparable results to balancing the entire structure directly. The operation count reduction obtained by the new technique is considerable: a factor of roughly r(exp 2) if the system decomposes into r equal subsystems. Numerical accuracy is also improved significantly, as the matrices being operated on are of reduced dimension, and the modes of the reduced-order model now have a clear physical interpretation; they are, to first order, linear combinations of repeated-frequency modes.

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 dynamic coupled PDE-based model of a two-bed four-step PSA process for separation of hydrogen from methane. Separate ROMs have been developed for each operating step with different POD modes for each of them. A significant reduction in the order of the number of states has been achieved. The gas-phase mole fraction, solid-state loading and temperature profiles from the low-order ROM and from the high-order simulations have been compared. Moreover, the profiles for a different set of inputs and parameter values fed to the same ROM were compared with the accurate profiles from the high-order simulations. Current results indicate the proposed ROM methodology as a promising surrogate modeling technique for cost-effective optimization purposes. Moreover, deviations from the ROM for different set of inputs and parameters suggest that a recalibration of the model is required for the optimization studies. Results for these will also be presented with the aforementioned results.« less

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.

From integrability to conformal symmetry: Bosonic superconformal Toda theories

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

Bo-Yu Hou; Liu Chao

In this paper the authors study the conformal integrable models obtained from conformal reductions of WZNW theory associated with second order constraints. These models are called bosonic superconformal Toda models due to their conformal spectra and their resemblance to the usual Toda theories. From the reduction procedure they get the equations of motion and the linearized Lax equations in a generic Z gradation of the underlying Lie algebra. Then, in the special case of principal gradation, they derive the classical r matrix, fundamental Poisson relation, exchange algebra of chiral operators and find out the classical vertex operators. The result showsmore » that their model is very similar to the ordinary Toda theories in that one can obtain various conformal properties of the model from its integrability.« less

Algorithm Considerations for Evaluating Phosphorus Transport and Environmental Management Strategies Using a Grid-Based Spatial Watershed Model

DTIC Science & Technology

2007-11-01

term modeling simulations are needed in order to predict 1) the effects of BMPs on seasonal and annual changes in particulate and soluble P loading...and 2) the effects of past soil management practices on decadal changes in soil P and soluble P in the runoff as a result of BMPs. SWAT P...field observations of very slow (on the order of 50 years) reductions in soil P levels via crop uptake after complete cessation of P fertilizer subsidies

Dimension reduction method for SPH equations

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

Tartakovsky, Alexandre M.; Scheibe, Timothy D.

2011-08-26

Smoothed Particle Hydrodynamics model of a complex multiscale processe often results in a system of ODEs with an enormous number of unknowns. Furthermore, a time integration of the SPH equations usually requires time steps that are smaller than the observation time by many orders of magnitude. A direct solution of these ODEs can be extremely expensive. Here we propose a novel dimension reduction method that gives an approximate solution of the SPH ODEs and provides an accurate prediction of the average behavior of the modeled system. The method consists of two main elements. First, effective equationss for evolution of averagemore » variables (e.g. average velocity, concentration and mass of a mineral precipitate) are obtained by averaging the SPH ODEs over the entire computational domain. These effective ODEs contain non-local terms in the form of volume integrals of functions of the SPH variables. Second, a computational closure is used to close the system of the effective equations. The computational closure is achieved via short bursts of the SPH model. The dimension reduction model is used to simulate flow and transport with mixing controlled reactions and mineral precipitation. An SPH model is used model transport at the porescale. Good agreement between direct solutions of the SPH equations and solutions obtained with the dimension reduction method for different boundary conditions confirms the accuracy and computational efficiency of the dimension reduction model. The method significantly accelerates SPH simulations, while providing accurate approximation of the solution and accurate prediction of the average behavior of the system.« less

A patient-specific model of the biomechanics of hip reduction for neonatal Developmental Dysplasia of the Hip: Investigation of strategies for low to severe grades of Developmental Dysplasia of the Hip.

PubMed

Huayamave, Victor; Rose, Christopher; Serra, Sheila; Jones, Brendan; Divo, Eduardo; Moslehy, Faissal; Kassab, Alain J; Price, Charles T

2015-07-16

A physics-based computational model of neonatal Developmental Dysplasia of the Hip (DDH) following treatment with the Pavlik Harness (PV) was developed to obtain muscle force contribution in order to elucidate biomechanical factors influencing the reduction of dislocated hips. Clinical observation suggests that reduction occurs in deep sleep involving passive muscle action. Consequently, a set of five (5) adductor muscles were identified as mediators of reduction using the PV. A Fung/Hill-type model was used to characterize muscle response. Four grades (1-4) of dislocation were considered, with one (1) being a low subluxation and four (4) a severe dislocation. A three-dimensional model of the pelvis-femur lower limb of a representative 10 week-old female was generated based on CT-scans with the aid of anthropomorphic scaling of anatomical landmarks. The model was calibrated to achieve equilibrium at 90° flexion and 80° abduction. The hip was computationally dislocated according to the grade under investigation, the femur was restrained to move in an envelope consistent with PV restraints, and the dynamic response under passive muscle action and the effect of gravity was resolved. Model results with an anteversion angle of 50° show successful reduction Grades 1-3, while Grade 4 failed to reduce with the PV. These results are consistent with a previous study based on a simplified anatomically-consistent synthetic model and clinical reports of very low success of the PV for Grade 4. However our model indicated that it is possible to achieve reduction of Grade 4 dislocation by hyperflexion and the resultant external rotation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Modelling of aflatoxin G1 reduction by kefir grain using response surface methodology.

PubMed

Ansari, Farzaneh; Khodaiyan, Faramarz; Rezaei, Karamatollah; Rahmani, Anosheh

2015-01-01

Aflatoxin G1 (AFG1) is one of the main toxic contaminants in pistachio nuts and causes potential health hazards. Hence, AFG1 reduction is one of the main concerns in food safety. Kefir-grains contain symbiotic association of microorganisms well known for their aflatoxin decontamination effects. In this study, a central composite design (CCD) using response surface methodology (RSM) was applied to develop a model in order to predict AFG1 reduction in pistachio nuts by kefir-grain (already heated at 70 and 110°C). The independent variables were: toxin concentration (X1: 5, 10, 15, 20 and 25 ng/g), kefir-grain level (X2: 5, 10, 20, 10 and 25%), contact time (X3: 0, 2, 4, 6 and 8 h), and incubation temperature (X4: 20, 30, 40, 50 and 60°C). There was a significant reduction in AFG1 (p < 0.05) when pre-heat-treated kefir-grain used. The variables including X1, X3 and the interactions between X2-X4 as well as X3-X4 have significant effects on AFG1 reduction. The model provided a good prediction of AFG1 reduction under the assay conditions. Optimization was used to enhance the efficiency of kefir-grain on AFG1 reduction. The optimum conditions for the highest AFG1 reduction (96.8%) were predicted by the model as follows: toxin concentration = 20 ng/g, kefir-grain level = 10%, contact time = 6 h, and incubation temperature = 30°C which validated practically in six replications.

Automatic simplification of systems of reaction-diffusion equations by a posteriori analysis.

PubMed

Maybank, Philip J; Whiteley, Jonathan P

2014-02-01

Many mathematical models in biology and physiology are represented by systems of nonlinear differential equations. In recent years these models have become increasingly complex in order to explain the enormous volume of data now available. A key role of modellers is to determine which components of the model have the greatest effect on a given observed behaviour. An approach for automatically fulfilling this role, based on a posteriori analysis, has recently been developed for nonlinear initial value ordinary differential equations [J.P. Whiteley, Model reduction using a posteriori analysis, Math. Biosci. 225 (2010) 44-52]. In this paper we extend this model reduction technique for application to both steady-state and time-dependent nonlinear reaction-diffusion systems. Exemplar problems drawn from biology are used to demonstrate the applicability of the technique. Copyright © 2014 Elsevier Inc. All rights reserved.

High-order rogue wave solutions of the classical massive Thirring model equations

NASA Astrophysics Data System (ADS)

Guo, Lijuan; Wang, Lihong; Cheng, Yi; He, Jingsong

2017-11-01

The nth-order solutions of the classical massive Thirring model (MTM) equations are derived by using the n-fold Darboux transformation. These solutions are expressed by the ratios of the two determinants consisted of 2n eigenfunctions under the reduction conditions. Using this method, rogue waves are constructed explicitly up to the third-order. Three patterns, i.e., fundamental, triangular and circular patterns, of the rogue waves are discussed. The parameter μ in the MTM model plays the role of the mass in the relativistic field theory while in optics it is related to the medium periodic constant, which also results in a significant rotation and a remarkable lengthening of the first-order rogue wave. These results provide new opportunities to observe rouge waves by using a combination of electromagnetically induced transparency and the Bragg scattering four-wave mixing because of large amplitudes.

Smelting reduction and kinetics analysis of magnetic iron in copper slag using waste cooking oil.

PubMed

Li, Bo; Wang, Xubin; Wang, Hua; Wei, Yonggang; Hu, Jianhang

2017-05-25

To improve the recovery of copper, the viscosity of copper molten slag is decreased by the reduction of magnetic iron, which, in turn, accelerates the settling and separation of copper droplets from the slag. A new technology is proposed in which waste cooking oil is used as a reductant to reduce magnetic iron in the copper smelting slag and consequently reduce carbon emissions in the copper smelting process. A kinetic model of the reduction of magnetic iron in copper slag by waste cooking oil was built using experimental data, and the accuracy of the model was verified. The results indicated that the magnetic iron content in the copper slag decreased with increasing reduction time and an increase in temperature more efficiently reduced magnetic iron in the copper slag. The magnetic iron in the copper slag gradually transformed to fayalite, and the viscosity of the copper molten slag decreased as the magnetic iron content decreased during the reduction process. The reduction of magnetic iron in the copper molten slag using waste cooking oil was a first-order reaction, and the rate-limiting step was the mass transfer of Fe 3 O 4 through the liquid boundary layer.

Dependence and physical exercise: Spanish validation of the Exercise Dependence Scale-Revised (EDS-R).

PubMed

Sicilia, Alvaro; González-Cutre, David

2011-05-01

The purpose of this study was to validate the Spanish version of the Exercise Dependence Scale-Revised (EDS-R). To achieve this goal, a sample of 531 sport center users was used and the psychometric properties of the EDS-R were examined through different analyses. The results supported both the first-order seven-factor model and the higher-order model (seven first-order factors and one second-order factor). The structure of both models was invariant across age. Correlations among the subscales indicated a related factor model, supporting construct validity of the scale. Alpha values over .70 (except for Reduction in Other Activities) and suitable levels of temporal stability were obtained. Users practicing more than three days per week had higher scores in all subscales than the group practicing with a frequency of three days or fewer. The findings of this study provided reliability and validity for the EDS-R in a Spanish context.

Inactivation of Alicyclobacillus acidoterrestris ATCC 49025 spores in apple juice by pulsed light. Influence of initial contamination and required reduction levels.

PubMed

Ferrario, Mariana I; Guerrero, Sandra N

The purpose of this study was to analyze the response of different initial contamination levels of Alicyclobacillus acidoterrestris ATCC 49025 spores in apple juice as affected by pulsed light treatment (PL, batch mode, xenon lamp, 3pulses/s, 0-71.6J/cm 2 ). Biphasic and Weibull frequency distribution models were used to characterize the relationship between inoculum size and treatment time with the reductions achieved after PL exposure. Additionally, a second order polynomial model was computed to relate required PL processing time to inoculum size and requested log reductions. PL treatment caused up to 3.0-3.5 log reductions, depending on the initial inoculum size. Inactivation curves corresponding to PL-treated samples were adequately characterized by both Weibull and biphasic models (R adj 2 94-96%), and revealed that lower initial inoculum sizes were associated with higher inactivation rates. According to the polynomial model, the predicted time for PL treatment increased exponentially with inoculum size. Copyright © 2017 Asociación Argentina de Microbiología. Publicado por Elsevier España, S.L.U. All rights reserved.

Integrated modeling approach using SELECT and SWAT models to simulate source loading and in-stream conditions of fecal indicator bacteria.

NASA Astrophysics Data System (ADS)

Ranatunga, T.

2016-12-01

Modeling of fate and transport of fecal bacteria in a watershed is generally a processed based approach that considers releases from manure, point sources, and septic systems. Overland transport with water and sediments, infiltration into soils, transport in the vadose zone and groundwater, die-off and growth processes, and in-stream transport are considered as the other major processes in bacteria simulation. This presentation will discuss a simulation of fecal indicator bacteria (E.coli) source loading and in-stream conditions of a non-tidal watershed (Cedar Bayou Watershed) in South Central Texas using two models; Spatially Explicit Load Enrichment Calculation Tool (SELECT) and Soil and Water Assessment Tool (SWAT). Furthermore, it will discuss a probable approach of bacteria source load reduction in order to meet the water quality standards in the streams. The selected watershed is listed as having levels of fecal indicator bacteria that posed a risk for contact recreation and wading by the Texas Commission of Environmental Quality (TCEQ). The SELECT modeling approach was used in estimating the bacteria source loading from land categories. Major bacteria sources considered were, failing septic systems, discharges from wastewater treatment facilities, excreta from livestock (Cattle, Horses, Sheep and Goat), excreta from Wildlife (Feral Hogs, and Deer), Pet waste (mainly from Dogs), and runoff from urban surfaces. The estimated source loads were input to the SWAT model in order to simulate the transport through the land and in-stream conditions. The calibrated SWAT model was then used to estimate the indicator bacteria in-stream concentrations for future years based on H-GAC's regional land use, population and household projections (up to 2040). Based on the in-stream reductions required to meet the water quality standards, the corresponding required source load reductions were estimated.

Water Quality Assessment in the Harbin Reach of the Songhuajiang River (China) Based on a Fuzzy Rough Set and an Attribute Recognition Theoretical Model

PubMed Central

An, Yan; Zou, Zhihong; Li, Ranran

2014-01-01

A large number of parameters are acquired during practical water quality monitoring. If all the parameters are used in water quality assessment, the computational complexity will definitely increase. In order to reduce the input space dimensions, a fuzzy rough set was introduced to perform attribute reduction. Then, an attribute recognition theoretical model and entropy method were combined to assess water quality in the Harbin reach of the Songhuajiang River in China. A dataset consisting of ten parameters was collected from January to October in 2012. Fuzzy rough set was applied to reduce the ten parameters to four parameters: BOD5, NH3-N, TP, and F. coli (Reduct A). Considering that DO is a usual parameter in water quality assessment, another reduct, including DO, BOD5, NH3-N, TP, TN, F, and F. coli (Reduct B), was obtained. The assessment results of Reduct B show a good consistency with those of Reduct A, and this means that DO is not always necessary to assess water quality. The results with attribute reduction are not exactly the same as those without attribute reduction, which can be attributed to the α value decided by subjective experience. The assessment results gained by the fuzzy rough set obviously reduce computational complexity, and are acceptable and reliable. The model proposed in this paper enhances the water quality assessment system. PMID:24675643

Determining Reduced Order Models for Optimal Stochastic Reduced Order Models

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

Bonney, Matthew S.; Brake, Matthew R.W.

2015-08-01

The use of parameterized reduced order models(PROMs) within the stochastic reduced order model (SROM) framework is a logical progression for both methods. In this report, five different parameterized reduced order models are selected and critiqued against the other models along with truth model for the example of the Brake-Reuss beam. The models are: a Taylor series using finite difference, a proper orthogonal decomposition of the the output, a Craig-Bampton representation of the model, a method that uses Hyper-Dual numbers to determine the sensitivities, and a Meta-Model method that uses the Hyper-Dual results and constructs a polynomial curve to better representmore » the output data. The methods are compared against a parameter sweep and a distribution propagation where the first four statistical moments are used as a comparison. Each method produces very accurate results with the Craig-Bampton reduction having the least accurate results. The models are also compared based on time requirements for the evaluation of each model where the Meta- Model requires the least amount of time for computation by a significant amount. Each of the five models provided accurate results in a reasonable time frame. The determination of which model to use is dependent on the availability of the high-fidelity model and how many evaluations can be performed. Analysis of the output distribution is examined by using a large Monte-Carlo simulation along with a reduced simulation using Latin Hypercube and the stochastic reduced order model sampling technique. Both techniques produced accurate results. The stochastic reduced order modeling technique produced less error when compared to an exhaustive sampling for the majority of methods.« less

Controls/CFD Interdisciplinary Research Software Generates Low-Order Linear Models for Control Design From Steady-State CFD Results

NASA Technical Reports Server (NTRS)

Melcher, Kevin J.

1997-01-01

The NASA Lewis Research Center is developing analytical methods and software tools to create a bridge between the controls and computational fluid dynamics (CFD) disciplines. Traditionally, control design engineers have used coarse nonlinear simulations to generate information for the design of new propulsion system controls. However, such traditional methods are not adequate for modeling the propulsion systems of complex, high-speed vehicles like the High Speed Civil Transport. To properly model the relevant flow physics of high-speed propulsion systems, one must use simulations based on CFD methods. Such CFD simulations have become useful tools for engineers that are designing propulsion system components. The analysis techniques and software being developed as part of this effort are an attempt to evolve CFD into a useful tool for control design as well. One major aspect of this research is the generation of linear models from steady-state CFD results. CFD simulations, often used during the design of high-speed inlets, yield high resolution operating point data. Under a NASA grant, the University of Akron has developed analytical techniques and software tools that use these data to generate linear models for control design. The resulting linear models have the same number of states as the original CFD simulation, so they are still very large and computationally cumbersome. Model reduction techniques have been successfully applied to reduce these large linear models by several orders of magnitude without significantly changing the dynamic response. The result is an accurate, easy to use, low-order linear model that takes less time to generate than those generated by traditional means. The development of methods for generating low-order linear models from steady-state CFD is most complete at the one-dimensional level, where software is available to generate models with different kinds of input and output variables. One-dimensional methods have been extended somewhat so that linear models can also be generated from two- and three-dimensional steady-state results. Standard techniques are adequate for reducing the order of one-dimensional CFD-based linear models. However, reduction of linear models based on two- and three-dimensional CFD results is complicated by very sparse, ill-conditioned matrices. Some novel approaches are being investigated to solve this problem.

High-Performance Integrated Control of water quality and quantity in urban water reservoirs

NASA Astrophysics Data System (ADS)

Galelli, S.; Castelletti, A.; Goedbloed, A.

2015-11-01

This paper contributes a novel High-Performance Integrated Control framework to support the real-time operation of urban water supply storages affected by water quality problems. We use a 3-D, high-fidelity simulation model to predict the main water quality dynamics and inform a real-time controller based on Model Predictive Control. The integration of the simulation model into the control scheme is performed by a model reduction process that identifies a low-order, dynamic emulator running 4 orders of magnitude faster. The model reduction, which relies on a semiautomatic procedural approach integrating time series clustering and variable selection algorithms, generates a compact and physically meaningful emulator that can be coupled with the controller. The framework is used to design the hourly operation of Marina Reservoir, a 3.2 Mm3 storm-water-fed reservoir located in the center of Singapore, operated for drinking water supply and flood control. Because of its recent formation from a former estuary, the reservoir suffers from high salinity levels, whose behavior is modeled with Delft3D-FLOW. Results show that our control framework reduces the minimum salinity levels by nearly 40% and cuts the average annual deficit of drinking water supply by about 2 times the active storage of the reservoir (about 4% of the total annual demand).

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 dissertation improves the implementation of physics-based reduced-order models by introducing different blending approaches that combine the pre-computed models generated (offline) at different setpoints in order to produce good electrochemical estimates (online) along the cell state-of-charge, temperature and C-rate range.

Fast model updating coupling Bayesian inference and PGD model reduction

NASA Astrophysics Data System (ADS)

Rubio, Paul-Baptiste; Louf, François; Chamoin, Ludovic

2018-04-01

The paper focuses on a coupled Bayesian-Proper Generalized Decomposition (PGD) approach for the real-time identification and updating of numerical models. The purpose is to use the most general case of Bayesian inference theory in order to address inverse problems and to deal with different sources of uncertainties (measurement and model errors, stochastic parameters). In order to do so with a reasonable CPU cost, the idea is to replace the direct model called for Monte-Carlo sampling by a PGD reduced model, and in some cases directly compute the probability density functions from the obtained analytical formulation. This procedure is first applied to a welding control example with the updating of a deterministic parameter. In the second application, the identification of a stochastic parameter is studied through a glued assembly example.

Development of homotopy algorithms for fixed-order mixed H2/H(infinity) controller synthesis

NASA Technical Reports Server (NTRS)

Whorton, M.; Buschek, H.; Calise, A. J.

1994-01-01

A major difficulty associated with H-infinity and mu-synthesis methods is the order of the resulting compensator. Whereas model and/or controller reduction techniques are sometimes applied, performance and robustness properties are not preserved. By directly constraining compensator order during the optimization process, these properties are better preserved, albeit at the expense of computational complexity. This paper presents a novel homotopy algorithm to synthesize fixed-order mixed H2/H-infinity compensators. Numerical results are presented for a four-disk flexible structure to evaluate the efficiency of the algorithm.

An Eigensystem Realization Algorithm (ERA) for modal parameter identification and model reduction

NASA Technical Reports Server (NTRS)

Juang, J. N.; Pappa, R. S.

1985-01-01

A method, called the Eigensystem Realization Algorithm (ERA), is developed for modal parameter identification and model reduction of dynamic systems from test data. A new approach is introduced in conjunction with the singular value decomposition technique to derive the basic formulation of minimum order realization which is an extended version of the Ho-Kalman algorithm. The basic formulation is then transformed into modal space for modal parameter identification. Two accuracy indicators are developed to quantitatively identify the system modes and noise modes. For illustration of the algorithm, examples are shown using simulation data and experimental data for a rectangular grid structure.

Mechanistic investigation of Fe(III) oxide reduction by low molecular weight organic sulfur species

NASA Astrophysics Data System (ADS)

Eitel, Eryn M.; Taillefert, Martial

2017-10-01

Low molecular weight organic sulfur species, often referred to as thiols, are known to be ubiquitous in aquatic environments and represent important chemical reductants of Fe(III) oxides. Thiols are excellent electron shuttles used during dissimilatory iron reduction, and in this capacity could indirectly affect the redox state of sediments, release adsorbed contaminants via reductive dissolution, and influence the carbon cycle through alteration of bacterial respiration processes. Interestingly, the reduction of Fe(III) oxides by thiols has not been previously investigated in environmentally relevant conditions, likely due to analytical limitations associated with the detection of thiols and their oxidized products. In this study, a novel electrochemical method was developed to simultaneously determine thiol/disulfide pair concentrations in situ during the reduction of ferrihydrite in batch reactors. First order rate laws with respect to initial thiol concentration were confirmed for Fe(III) oxyhydroxide reduction by four common thiols: cysteine, homocysteine, cysteamine, and glutathione. Zero order was determined for both Fe(III) oxyhydroxide and proton concentration at circumneutral pH. A kinetic model detailing the molecular mechanism of the reaction was optimized with proposed intermediate surface structures. Although metal oxide overall reduction rate constants were inversely proportional to the complexity of the thiol structure, the extent of metal reduction increased with structure complexity, indicating that surface complexes play a significant role in the ability of these thiols to reduce iron. Taken together, these results demonstrate the importance of considering the molecular reaction mechanism at the iron oxide surface when investigating the potential for thiols to act as electron shuttles during dissimilatory iron reduction in natural environments.

Modelling of auctioning mechanism for solar photovoltaic capacity

NASA Astrophysics Data System (ADS)

Poullikkas, Andreas

2016-10-01

In this work, a modified optimisation model for the integration of renewable energy sources for power-generation (RES-E) technologies in power-generation systems on a unit commitment basis is developed. The purpose of the modified optimisation procedure is to account for RES-E capacity auctions for different solar photovoltaic (PV) capacity electricity prices. The optimisation model developed uses a genetic algorithm (GA) technique for the calculation of the required RES-E levy (or green tax) in the electricity bills. Also, the procedure enables the estimation of the level of the adequate (or eligible) feed-in-tariff to be offered to future RES-E systems, which do not participate in the capacity auctioning procedure. In order to demonstrate the applicability of the optimisation procedure developed the case of PV capacity auctioning for commercial systems is examined. The results indicated that the required green tax, in order to promote the use of RES-E technologies, which is charged to the electricity customers through their electricity bills, is reduced with the reduction in the final auctioning price. This has a significant effect related to the reduction of electricity bills.

Engineering Inertial and Primary-Frequency Response for Distributed Energy Resources

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

Dall-Anese, Emiliano; Zhao, Changhong; Guggilam, Swaroop

We propose a framework to engineer synthetic-inertia and droop-control parameters for distributed energy resources (DERs) so that the system frequency in a network composed of DERs and synchronous generators conforms to prescribed transient and steady-state performance specifications. Our approach is grounded in a second-order lumped-parameter model that captures the dynamics of synchronous generators and frequency-responsive DERs endowed with inertial and droop control. A key feature of this reduced-order model is that its parameters can be related to those of the originating higherorder dynamical model. This allows one to systematically design the DER inertial and droop-control coefficients leveraging classical frequency-domain responsemore » characteristics of second-order systems. Time-domain simulations validate the accuracy of the model-reduction method and demonstrate how DER controllers can be designed to meet steady-state-regulation and transient-performance specifications.« less

LPV Modeling of a Flexible Wing Aircraft Using Modal Alignment and Adaptive Gridding Methods

NASA Technical Reports Server (NTRS)

Al-Jiboory, Ali Khudhair; Zhu, Guoming; Swei, Sean Shan-Min; Su, Weihua; Nguyen, Nhan T.

2017-01-01

One of the earliest approaches in gain-scheduling control is the gridding based approach, in which a set of local linear time-invariant models are obtained at various gridded points corresponding to the varying parameters within the flight envelop. In order to ensure smooth and effective Linear Parameter-Varying control, aligning all the flexible modes within each local model and maintaining small number of representative local models over the gridded parameter space are crucial. In addition, since the flexible structural models tend to have large dimensions, a tractable model reduction process is necessary. In this paper, the notion of s-shifted H2- and H Infinity-norm are introduced and used as a metric to measure the model mismatch. A new modal alignment algorithm is developed which utilizes the defined metric for aligning all the local models over the entire gridded parameter space. Furthermore, an Adaptive Grid Step Size Determination algorithm is developed to minimize the number of local models required to represent the gridded parameter space. For model reduction, we propose to utilize the concept of Composite Modal Cost Analysis, through which the collective contribution of each flexible mode is computed and ranked. Therefore, a reduced-order model is constructed by retaining only those modes with significant contribution. The NASA Generic Transport Model operating at various flight speeds is studied for verification purpose, and the analysis and simulation results demonstrate the effectiveness of the proposed modeling approach.

Low-rank approximation in the numerical modeling of the Farley-Buneman instability in ionospheric plasma

NASA Astrophysics Data System (ADS)

Dolgov, S. V.; Smirnov, A. P.; Tyrtyshnikov, E. E.

2014-04-01

We consider numerical modeling of the Farley-Buneman instability in the Earth's ionosphere plasma. The ion behavior is governed by the kinetic Vlasov equation with the BGK collisional term in the four-dimensional phase space, and since the finite difference discretization on a tensor product grid is used, this equation becomes the most computationally challenging part of the scheme. To relax the complexity and memory consumption, an adaptive model reduction using the low-rank separation of variables, namely the Tensor Train format, is employed. The approach was verified via a prototype MATLAB implementation. Numerical experiments demonstrate the possibility of efficient separation of space and velocity variables, resulting in the solution storage reduction by a factor of order tens.

An integrated production-inventory model for the singlevendor two-buyer problem with partial backorder, stochastic demand, and service level constraints

NASA Astrophysics Data System (ADS)

Arfawi Kurdhi, Nughthoh; Adi Diwiryo, Toray; Sutanto

2016-02-01

This paper presents an integrated single-vendor two-buyer production-inventory model with stochastic demand and service level constraints. Shortage is permitted in the model, and partial backordered partial lost sale. The lead time demand is assumed follows a normal distribution and the lead time can be reduced by adding crashing cost. The lead time and ordering cost reductions are interdependent with logaritmic function relationship. A service level constraint policy corresponding to each buyer is considered in the model in order to limit the level of inventory shortages. The purpose of this research is to minimize joint total cost inventory model by finding the optimal order quantity, safety stock, lead time, and the number of lots delivered in one production run. The optimal production-inventory policy gained by the Lagrange method is shaped to account for the service level restrictions. Finally, a numerical example and effects of the key parameters are performed to illustrate the results of the proposed model.

Active control of turbulent boundary layer-induced sound transmission through the cavity-backed double panels

NASA Astrophysics Data System (ADS)

Caiazzo, A.; Alujević, N.; Pluymers, B.; Desmet, W.

2018-05-01

This paper presents a theoretical study of active control of turbulent boundary layer (TBL) induced sound transmission through the cavity-backed double panels. The aerodynamic model used is based on the Corcos wall pressure distribution. The structural-acoustic model encompasses a source panel (skin panel), coupled through an acoustic cavity to the radiating panel (trim panel). The radiating panel is backed by a larger acoustic enclosure (the back cavity). A feedback control unit is located inside the acoustic cavity between the two panels. It consists of a control force actuator and a sensor mounted at the actuator footprint on the radiating panel. The control actuator can react off the source panel. It is driven by an amplified velocity signal measured by the sensor. A fully coupled analytical structural-acoustic model is developed to study the effects of the active control on the sound transmission into the back cavity. The stability and performance of the active control system are firstly studied on a reduced order model. In the reduced order model only two fundamental modes of the fully coupled system are assumed. Secondly, a full order model is considered with a number of modes large enough to yield accurate simulation results up to 1000 Hz. It is shown that convincing reductions of the TBL-induced vibrations of the radiating panel and the sound pressure inside the back cavity can be expected. The reductions are more pronounced for a certain class of systems, which is characterised by the fundamental natural frequency of the skin panel larger than the fundamental natural frequency of the trim panel.

Application of Reduced Order Transonic Aerodynamic Influence Coefficient Matrix for Design Optimization

NASA Technical Reports Server (NTRS)

Pak, Chan-gi; Li, Wesley W.

2009-01-01

Supporting the Aeronautics Research Mission Directorate guidelines, the National Aeronautics and Space Administration [NASA] Dryden Flight Research Center is developing a multidisciplinary design, analysis, and optimization [MDAO] tool. This tool will leverage existing tools and practices, and allow the easy integration and adoption of new state-of-the-art software. Today s modern aircraft designs in transonic speed are a challenging task due to the computation time required for the unsteady aeroelastic analysis using a Computational Fluid Dynamics [CFD] code. Design approaches in this speed regime are mainly based on the manual trial and error. Because of the time required for unsteady CFD computations in time-domain, this will considerably slow down the whole design process. These analyses are usually performed repeatedly to optimize the final design. As a result, there is considerable motivation to be able to perform aeroelastic calculations more quickly and inexpensively. This paper will describe the development of unsteady transonic aeroelastic design methodology for design optimization using reduced modeling method and unsteady aerodynamic approximation. The method requires the unsteady transonic aerodynamics be represented in the frequency or Laplace domain. Dynamically linear assumption is used for creating Aerodynamic Influence Coefficient [AIC] matrices in transonic speed regime. Unsteady CFD computations are needed for the important columns of an AIC matrix which corresponded to the primary modes for the flutter. Order reduction techniques, such as Guyan reduction and improved reduction system, are used to reduce the size of problem transonic flutter can be found by the classic methods, such as Rational function approximation, p-k, p, root-locus etc. Such a methodology could be incorporated into MDAO tool for design optimization at a reasonable computational cost. The proposed technique is verified using the Aerostructures Test Wing 2 actually designed, built, and tested at NASA Dryden Flight Research Center. The results from the full order model and the approximate reduced order model are analyzed and compared.

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.

Numerical Study of the Reduction Process in an Oxygen Blast Furnace

NASA Astrophysics Data System (ADS)

Zhang, Zongliang; Meng, Jiale; Guo, Lei; Guo, Zhancheng

2016-02-01

Based on computational fluid dynamics, chemical reaction kinetics, principles of transfer in metallurgy, and other principles, a multi-fluid model for a traditional blast furnace was established. The furnace conditions were simulated with this multi-fluid mathematical model, and the model was verified with the comparison of calculation and measurement. Then a multi-fluid model for an oxygen blast furnace in the gasifier-full oxygen blast furnace process was established based on this traditional blast furnace model. With the established multi-fluid model for an oxygen blast furnace, the basic characteristics of iron ore reduction process in the oxygen blast furnace were summarized, including the changing process of the iron ore reduction degree and the compositions of the burden, etc. The study found that compared to the traditional blast furnace, the magnetite reserve zone in the furnace shaft under oxygen blast furnace condition was significantly reduced, which is conducive to the efficient operation of blast furnace. In order to optimize the oxygen blast furnace design and operating parameters, the iron ore reduction process in the oxygen blast furnace was researched under different shaft tuyere positions, different recycling gas temperatures, and different allocation ratios of recycling gas between the hearth tuyere and the shaft tuyere. The results indicate that these three factors all have a substantial impact on the ore reduction process in the oxygen blast furnace. Moderate shaft tuyere position, high recycling gas temperature, and high recycling gas allocation ratio between hearth and shaft could significantly promote the reduction of iron ore, reduce the scope of the magnetite reserve zone, and improve the performance of oxygen blast furnace. Based on the above findings, the recommendations for improvement of the oxygen blast furnace design and operation were proposed.

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

PubMed

Tasaki, Ken

2005-02-24

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

Vibration and noise characteristics of an elevated box girder paved with different track structures

NASA Astrophysics Data System (ADS)

Li, Xiaozhen; Liang, Lin; Wang, Dangxiong

2018-07-01

The vibration and noise of elevated concrete box girders (ECBGs) are now among the most concerned issues in the field of urban rail transit (URT) systems. The track structure, belonging to critical load-transfer components, directly affects the characteristics of loading transmission into bridge, as well as the noise radiation from such system, which further determines the reduction of vibration and noise in ECBGs significantly. In order to investigate the influence of different track structures on the vibration and structure-borne noise of ECBGs, a frequency-domain theoretical model of vehicle-track coupled system, taking into account the effect of multiple wheels, is firstly established in the present work. The analysis of track structures focuses on embedded sleepers, trapezoidal sleepers, and steel-spring floating slabs (SSFS). Next, a vibration and noise field test was performed, with regard to a 30 m simple supported ECBG (with the embedded-sleeper track structure) of an URT system. Based on the tested results, two numerical models, involving a finite element model for the vibration analysis, as well as a statistical energy analysis (SEA) model for the prediction of the noise radiation, are established and validated. The results of the numerical simulations and the field tests are well matched, which offers opportunities to predict the vibration and structure-borne noise of ECBGs by the proposed modelling methodology. From the comparison between the different types of track structures, the spatial distribution and reduction effect of vibration and noise are lastly studied. The force applied on ECBG is substantially determined by both the wheel-rail force (external factor) and the transmission rate of track structure (internal factor). The SSFS track is the most effective for vibration and noise reduction of ECBGs, followed in descending order by the trapezoidal-sleeper and embedded-sleeper tracks. The above result provides a theoretical basis for the vibration and noise reduction design of urban rail transit systems.

Advanced Risk Reduction Tool (ARRT) Special Case Study Report: Science and Engineering Technical Assessments (SETA) Program

NASA Technical Reports Server (NTRS)

Kirsch, Paul J.; Hayes, Jane; Zelinski, Lillian

2000-01-01

This special case study report presents the Science and Engineering Technical Assessments (SETA) team's findings for exploring the correlation between the underlying models of Advanced Risk Reduction Tool (ARRT) relative to how it identifies, estimates, and integrates Independent Verification & Validation (IV&V) activities. The special case study was conducted under the provisions of SETA Contract Task Order (CTO) 15 and the approved technical approach documented in the CTO-15 Modification #1 Task Project Plan.

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.

A Systematic Approach to Combustion Model Reduction and Lumping.

DTIC Science & Technology

1991-08-01

very large values. In order to eliminate the unspecified threeshold on the sensitivities, Thomas and Bowes (1961) and Adler and Enig (1964) proposed...way to the stable node. The geometric definition of thermal runaway due to Adler and Enig (1964) and both sensitivity-based definitions by Boddington...where V denotes the time of the temperature maximum. Instead of looking for a positive second-order derivative before V ( Adler 1 and Enig, 1964

Low-dimensional, morphologically accurate models of subthreshold membrane potential

PubMed Central

Kellems, Anthony R.; Roos, Derrick; Xiao, Nan; Cox, Steven J.

2009-01-01

The accurate simulation of a neuron’s ability to integrate distributed synaptic input typically requires the simultaneous solution of tens of thousands of ordinary differential equations. For, in order to understand how a cell distinguishes between input patterns we apparently need a model that is biophysically accurate down to the space scale of a single spine, i.e., 1 μm. We argue here that one can retain this highly detailed input structure while dramatically reducing the overall system dimension if one is content to accurately reproduce the associated membrane potential at a small number of places, e.g., at the site of action potential initiation, under subthreshold stimulation. The latter hypothesis permits us to approximate the active cell model with an associated quasi-active model, which in turn we reduce by both time-domain (Balanced Truncation) and frequency-domain (ℋ2 approximation of the transfer function) methods. We apply and contrast these methods on a suite of typical cells, achieving up to four orders of magnitude in dimension reduction and an associated speed-up in the simulation of dendritic democratization and resonance. We also append a threshold mechanism and indicate that this reduction has the potential to deliver an accurate quasi-integrate and fire model. PMID:19172386

On distribution reduction and algorithm implementation in inconsistent ordered information systems.

PubMed

Zhang, Yanqin

2014-01-01

As one part of our work in ordered information systems, distribution reduction is studied in inconsistent ordered information systems (OISs). Some important properties on distribution reduction are studied and discussed. The dominance matrix is restated for reduction acquisition in dominance relations based information systems. Matrix algorithm for distribution reduction acquisition is stepped. And program is implemented by the algorithm. The approach provides an effective tool for the theoretical research and the applications for ordered information systems in practices. For more detailed and valid illustrations, cases are employed to explain and verify the algorithm and the program which shows the effectiveness of the algorithm in complicated information systems.

Response in the water quality of the Salton Sea, California, to changes in phosphorus loading: An empirical modeling approach

USGS Publications Warehouse

Robertson, Dale M.; Schladow, S.G.

2008-01-01

Salton Sea, California, like many other lakes, has become eutrophic because of excessive nutrient loading, primarily phosphorus (P). A Total Maximum Daily Load (TMDL) is being prepared for P to reduce the input of P to the Sea. In order to better understand how P-load reductions should affect the average annual water quality of this terminal saline lake, three different eutrophication programs (BATHTUB, WiLMS, and the Seepage Lake Model) were applied. After verifying that specific empirical models within these programs were applicable to this saline lake, each model was calibrated using water-quality and nutrient-loading data for 1999 and then used to simulate the effects of specific P-load reductions. Model simulations indicate that a 50% decrease in external P loading would decrease near-surface total phosphorus concentrations (TP) by 25-50%. Application of other empirical models demonstrated that this decrease in loading should decrease near-surface chlorophyll a concentrations (Chl a) by 17-63% and increase Secchi depths (SD) by 38-97%. The wide range in estimated responses in Chl a and SD were primarily caused by uncertainty in how non-algal turbidity would respond to P-load reductions. If only the models most applicable to the Salton Sea are considered, a 70-90% P-load reduction is required for the Sea to be classified as moderately eutrophic (trophic state index of 55). These models simulate steady-state conditions in the Sea; therefore, it is difficult to ascertain how long it would take for the simulated changes to occur after load reductions. ?? 2008 Springer Science+Business Media B.V.

Comparisons of non-Gaussian statistical models in DNA methylation analysis.

PubMed

Ma, Zhanyu; Teschendorff, Andrew E; Yu, Hong; Taghia, Jalil; Guo, Jun

2014-06-16

As a key regulatory mechanism of gene expression, DNA methylation patterns are widely altered in many complex genetic diseases, including cancer. DNA methylation is naturally quantified by bounded support data; therefore, it is non-Gaussian distributed. In order to capture such properties, we introduce some non-Gaussian statistical models to perform dimension reduction on DNA methylation data. Afterwards, non-Gaussian statistical model-based unsupervised clustering strategies are applied to cluster the data. Comparisons and analysis of different dimension reduction strategies and unsupervised clustering methods are presented. Experimental results show that the non-Gaussian statistical model-based methods are superior to the conventional Gaussian distribution-based method. They are meaningful tools for DNA methylation analysis. Moreover, among several non-Gaussian methods, the one that captures the bounded nature of DNA methylation data reveals the best clustering performance.

Comparisons of Non-Gaussian Statistical Models in DNA Methylation Analysis

PubMed Central

Ma, Zhanyu; Teschendorff, Andrew E.; Yu, Hong; Taghia, Jalil; Guo, Jun

2014-01-01

As a key regulatory mechanism of gene expression, DNA methylation patterns are widely altered in many complex genetic diseases, including cancer. DNA methylation is naturally quantified by bounded support data; therefore, it is non-Gaussian distributed. In order to capture such properties, we introduce some non-Gaussian statistical models to perform dimension reduction on DNA methylation data. Afterwards, non-Gaussian statistical model-based unsupervised clustering strategies are applied to cluster the data. Comparisons and analysis of different dimension reduction strategies and unsupervised clustering methods are presented. Experimental results show that the non-Gaussian statistical model-based methods are superior to the conventional Gaussian distribution-based method. They are meaningful tools for DNA methylation analysis. Moreover, among several non-Gaussian methods, the one that captures the bounded nature of DNA methylation data reveals the best clustering performance. PMID:24937687

Finite element dynamic analysis of soft tissues using state-space model.

PubMed

Iorga, Lucian N; Shan, Baoxiang; Pelegri, Assimina A

2009-04-01

A finite element (FE) model is employed to investigate the dynamic response of soft tissues under external excitations, particularly corresponding to the case of harmonic motion imaging. A solid 3D mixed 'u-p' element S8P0 is implemented to capture the near-incompressibility inherent in soft tissues. Two important aspects in structural modelling of these tissues are studied; these are the influence of viscous damping on the dynamic response and, following FE-modelling, a developed state-space formulation that valuates the efficiency of several order reduction methods. It is illustrated that the order of the mathematical model can be significantly reduced, while preserving the accuracy of the observed system dynamics. Thus, the reduced-order state-space representation of soft tissues for general dynamic analysis significantly reduces the computational cost and provides a unitary framework for the 'forward' simulation and 'inverse' estimation of soft tissues. Moreover, the results suggest that damping in soft-tissue is significant, effectively cancelling the contribution of all but the first few vibration modes.

Quality tracing in meat supply chains

PubMed Central

Mack, Miriam; Dittmer, Patrick; Veigt, Marius; Kus, Mehmet; Nehmiz, Ulfert; Kreyenschmidt, Judith

2014-01-01

The aim of this study was the development of a quality tracing model for vacuum-packed lamb that is applicable in different meat supply chains. Based on the development of relevant sensory parameters, the predictive model was developed by combining a linear primary model and the Arrhenius model as the secondary model. Then a process analysis was conducted to define general requirements for the implementation of the temperature-based model into a meat supply chain. The required hardware and software for continuous temperature monitoring were developed in order to use the model under practical conditions. Further on a decision support tool was elaborated in order to use the model as an effective tool in combination with the temperature monitoring equipment for the improvement of quality and storage management within the meat logistics network. Over the long term, this overall procedure will support the reduction of food waste and will improve the resources efficiency of food production. PMID:24797136

Quality tracing in meat supply chains.

PubMed

Mack, Miriam; Dittmer, Patrick; Veigt, Marius; Kus, Mehmet; Nehmiz, Ulfert; Kreyenschmidt, Judith

2014-06-13

The aim of this study was the development of a quality tracing model for vacuum-packed lamb that is applicable in different meat supply chains. Based on the development of relevant sensory parameters, the predictive model was developed by combining a linear primary model and the Arrhenius model as the secondary model. Then a process analysis was conducted to define general requirements for the implementation of the temperature-based model into a meat supply chain. The required hardware and software for continuous temperature monitoring were developed in order to use the model under practical conditions. Further on a decision support tool was elaborated in order to use the model as an effective tool in combination with the temperature monitoring equipment for the improvement of quality and storage management within the meat logistics network. Over the long term, this overall procedure will support the reduction of food waste and will improve the resources efficiency of food production.

Power flow prediction in vibrating systems via model reduction

NASA Astrophysics Data System (ADS)

Li, Xianhui

This dissertation focuses on power flow prediction in vibrating systems. Reduced order models (ROMs) are built based on rational Krylov model reduction which preserve power flow information in the original systems over a specified frequency band. Stiffness and mass matrices of the ROMs are obtained by projecting the original system matrices onto the subspaces spanned by forced responses. A matrix-free algorithm is designed to construct ROMs directly from the power quantities at selected interpolation frequencies. Strategies for parallel implementation of the algorithm via message passing interface are proposed. The quality of ROMs is iteratively refined according to the error estimate based on residual norms. Band capacity is proposed to provide a priori estimate of the sizes of good quality ROMs. Frequency averaging is recast as ensemble averaging and Cauchy distribution is used to simplify the computation. Besides model reduction for deterministic systems, details of constructing ROMs for parametric and nonparametric random systems are also presented. Case studies have been conducted on testbeds from Harwell-Boeing collections. Input and coupling power flow are computed for the original systems and the ROMs. Good agreement is observed in all cases.

48 CFR 8.405-4 - Price reductions.

Code of Federal Regulations, 2013 CFR

2013-10-01

... activities may request a price reduction at any time before placing an order, establishing a BPA, or in conjunction with the annual BPA review. However, the ordering activity shall seek a price reduction when the order or BPA exceeds the simplified acquisition threshold. Schedule contractors are not required to pass...

48 CFR 8.405-4 - Price reductions.

Code of Federal Regulations, 2014 CFR

2014-10-01

... activities may request a price reduction at any time before placing an order, establishing a BPA, or in conjunction with the annual BPA review. However, the ordering activity shall seek a price reduction when the order or BPA exceeds the simplified acquisition threshold. Schedule contractors are not required to pass...

48 CFR 8.405-4 - Price reductions.

Code of Federal Regulations, 2012 CFR

2012-10-01

... activities may request a price reduction at any time before placing an order, establishing a BPA, or in conjunction with the annual BPA review. However, the ordering activity shall seek a price reduction when the order or BPA exceeds the simplified acquisition threshold. Schedule contractors are not required to pass...

48 CFR 8.405-4 - Price reductions.

Code of Federal Regulations, 2011 CFR

2011-10-01

... activities may request a price reduction at any time before placing an order, establishing a BPA, or in conjunction with the annual BPA review. However, the ordering activity shall seek a price reduction when the order or BPA exceeds the simplified acquisition threshold. Schedule contractors are not required to pass...

Catalytic reduction of hexavalent chromium by a novel nitrogen-functionalized magnetic ordered mesoporous carbon doped with Pd nanoparticles.

PubMed

Li, Sisi; Tang, Lin; Zeng, Guangming; Wang, Jiajia; Deng, Yaocheng; Wang, Jingjing; Xie, Zhihong; Zhou, Yaoyu

2016-11-01

Hexavalent chromium Cr(VI) is a toxic water pollutant which can cause serious influence to the health of the human and animals. Therefore, developing new methods to remove hexavalent chromium in water attracts great attention of scholars. In our research, we successfully synthesized a new type of magnetic mesoporous carbon hybrid nitrogen (Fe-NMC) loaded with catalyst Pd nanoparticles (NPs), which performed excellent catalytic reduction efficiency toward Cr(VI). The characterization of Pd/Fe-NMC composite was investigated in detail using scanning electron microscope (SEM), high-resolution transmission electron microscopy (HRTEM), Fourier transform infrared spectroscopy (FTIR), and nitrogen adsorption-desorption measurements. According to the experimental results, we dealt with in-depth discussion and studied on the mechanism of hexavalent chromium removed by Pd/Fe-NMC composite. Furthermore, the batch experiments were conducted to investigate the catalytic reduction ability of composite. It was found that the chromium reduction process conforms to pseudo-first-order reaction kinetics model when the concentrations of chromium and sodium formate were low. It took only 20 min for the Pd/Fe-NMC composite to reach 99.8 % reduction of Cr(VI) (50 mg/L). The results suggested that the Pd/Fe-NMC composite may exhibit significantly improved catalytic activity for the hexavalent chromium reduction at industrial wastewater.

Chromium (VI) reduction in acetate- and molasses-amended natural media: empirical model development

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

Hansen, Scott; Boukhalfa, Hakim; Karra, Satish

Stimulating indigenous microbes to reduce heavy metals from highly toxic oxidized species to more benign reduced species is a promising groundwater remediation technique that has already seen successful field applications. Designing such a bio-remediation scheme requires a model incorporating the kinetics of nonlinear bio-geochemical interactions between multiple species. With this motivation, we performed a set of microcosm experiments in natural sediments and their indigenous pore water and microbes, generating simultaneous time series for concentrations of Cr(VI), an electron donor (both molasses and acetate were considered), and biomass. Molasses was found to undergo a rapid direct abiotic reaction which eliminated allmore » Cr(VI) before any biomass had time to grow. This was not found in the acetate microcosms, and a distinct zero-order bio-reduction process was observed. Existing models were found inappropriate and a new set of three coupled governing equations representing these process dynamics were developed and their parameters calibrated against the time series from the acetate-amended microcosms. Cell suspension batch experiments were also performed to calibrate bio-reduction rates in the absence of electron donor and sediment. The donor used to initially grow the cells (molasses or acetate) was found not to impact the reduction rate constants in suspension, which were orders of magnitude larger than those explaining the natural media microcosm experiments. This suggests the limited utility of kinetics determined in suspension for remedial design. Scoping studies on the natural media microcosms were also performed, suggesting limited impact of foreign abiotic material and minimal effect of diffusion limitation in the vertical dimension. These analyses may be of independent value to future researchers.« less

Physical phenomena in mercury ion thrusters

NASA Technical Reports Server (NTRS)

Wilbur, P. J.

1979-01-01

Experimental tests results demonstrating that reductions in screen grid thickness enhance the performance of ion thruster grids are presented. Shaping of the screen hole cross section is shown on the other hand not to affect performance substantially. The effect of the magnetic field in the vicinity of the hollow cathode on cathode performance is studied and test results are presented that show reductions in keeper voltages of a few volts can be realized by judicious applications of fields on the order of 100 gauss. The plasma downstream of a SERT 2 thruster operating without high voltage is studied. A model describing electron escape from the thruster under these conditions is discussed. A model defining the performance of the baffle aperture of an ion thruster is refined and experimental verification of the model is undertaken.

Micro-Arcsec mission: implications of the monitoring, diagnostic and calibration of the instrument response in the data reduction chain. .

NASA Astrophysics Data System (ADS)

Busonero, D.; Gai, M.

The goals of 21st century high angular precision experiments rely on the limiting performance associated to the selected instrumental configuration and observational strategy. Both global and narrow angle micro-arcsec space astrometry require that the instrument contributions to the overall error budget has to be less than the desired micro-arcsec level precision. Appropriate modelling of the astrometric response is required for optimal definition of the data reduction and calibration algorithms, in order to ensure high sensitivity to the astrophysical source parameters and in general high accuracy. We will refer to the framework of the SIM-Lite and the Gaia mission, the most challenging space missions of the next decade in the narrow angle and global astrometry field, respectively. We will focus our dissertation on the Gaia data reduction issues and instrument calibration implications. We describe selected topics in the framework of the Astrometric Instrument Modelling for the Gaia mission, evidencing their role in the data reduction chain and we give a brief overview of the Astrometric Instrument Model Data Analysis Software System, a Java-based pipeline under development by our team.

First field-based atmospheric observation of the reduction of reactive mercury driven by sunlight

NASA Astrophysics Data System (ADS)

de Foy, Benjamin; Tong, Yindong; Yin, Xiufeng; Zhang, Wei; Kang, Shichang; Zhang, Qianggong; Zhang, Guoshuai; Wang, Xuejun; Schauer, James J.

2016-06-01

Hourly speciated measurements of atmospheric mercury made in a remote, high-altitude site in the Tibetan Plateau revealed the first field observations of the reduction of reactive mercury in the presence of sunlight in the atmosphere. Measurements were collected over four winter months on the shore of Nam Co Lake in the inland Tibetan Plateau. The data was analyzed to identify sources and atmospheric transformations of the speciated mercury compounds. The absence of local anthropogenic sources provided a unique opportunity to examine chemical transformations of mercury. An optimization algorithm was used to determine the parameters of a chemical box model that would match the measured reactive mercury concentrations. This required the presence of a photolytic reduction reaction previously observed in laboratory studies and in power plant plumes. In addition, the model estimated the role of vertical mixing in diluting reactive gaseous mercury during the day, and the role of bromine chemistry in oxidizing gaseous elemental mercury to produce reactive gaseous mercury. This work provides further evidence of the need to add the photolytic reduction reaction of oxidized mercury into atmospheric transport models in order to better simulate mercury deposition.

Modifying high-order aeroelastic math model of a jet transport using maximum likelihood estimation

NASA Technical Reports Server (NTRS)

Anissipour, Amir A.; Benson, Russell A.

1989-01-01

The design of control laws to damp flexible structural modes requires accurate math models. Unlike the design of control laws for rigid body motion (e.g., where robust control is used to compensate for modeling inaccuracies), structural mode damping usually employs narrow band notch filters. In order to obtain the required accuracy in the math model, maximum likelihood estimation technique is employed to improve the accuracy of the math model using flight data. Presented here are all phases of this methodology: (1) pre-flight analysis (i.e., optimal input signal design for flight test, sensor location determination, model reduction technique, etc.), (2) data collection and preprocessing, and (3) post-flight analysis (i.e., estimation technique and model verification). In addition, a discussion is presented of the software tools used and the need for future study in this field.

An electrochemical series of redox couples in silicate melts - A review and applications to geochemistry

NASA Technical Reports Server (NTRS)

Schreiber, Henry D.

1987-01-01

An electrochemical series for redox couples in a glass-forming oxide melt is developed. This series is a quantitative numerical scale of reference reduction potentials of the redox couples in a silicate melt that is a model for basaltic magmas. The redox couples are ordered in terms of their reference reduction potentials; the order appears to be relatively independent of the exact melt composition and temperature. Thus, upon calibration to a desired composition, oxygen fugacity, and temperature, this electrochemical series can provide estimates of redox state proportions in basaltic magmas on different planetary bodies. The geochemical electrochemical series can also be used to understand the interrelationship of the redox state of the magma and the presence of volatile species such as oxygen, water, sulfur gases, and carbon gases.

Application of reduced order modeling techniques to problems in heat conduction, isoelectric focusing and differential algebraic equations

NASA Astrophysics Data System (ADS)

Mathai, Pramod P.

This thesis focuses on applying and augmenting 'Reduced Order Modeling' (ROM) techniques to large scale problems. ROM refers to the set of mathematical techniques that are used to reduce the computational expense of conventional modeling techniques, like finite element and finite difference methods, while minimizing the loss of accuracy that typically accompanies such a reduction. The first problem that we address pertains to the prediction of the level of heat dissipation in electronic and MEMS devices. With the ever decreasing feature sizes in electronic devices, and the accompanied rise in Joule heating, the electronics industry has, since the 1990s, identified a clear need for computationally cheap heat transfer modeling techniques that can be incorporated along with the electronic design process. We demonstrate how one can create reduced order models for simulating heat conduction in individual components that constitute an idealized electronic device. The reduced order models are created using Krylov Subspace Techniques (KST). We introduce a novel 'plug and play' approach, based on the small gain theorem in control theory, to interconnect these component reduced order models (according to the device architecture) to reliably and cheaply replicate whole device behavior. The final aim is to have this technique available commercially as a computationally cheap and reliable option that enables a designer to optimize for heat dissipation among competing VLSI architectures. Another place where model reduction is crucial to better design is Isoelectric Focusing (IEF) - the second problem in this thesis - which is a popular technique that is used to separate minute amounts of proteins from the other constituents that are present in a typical biological tissue sample. Fundamental questions about how to design IEF experiments still remain because of the high dimensional and highly nonlinear nature of the differential equations that describe the IEF process as well as the uncertainty in the parameters of the differential equations. There is a clear need to design better experiments for IEF without the current overhead of expensive chemicals and labor. We show how with a simpler modeling of the underlying chemistry, we can still achieve the accuracy that has been achieved in existing literature for modeling small ranges of pH (hydrogen ion concentration) in IEF, but with far less computational time. We investigate a further reduction of time by modeling the IEF problem using the Proper Orthogonal Decomposition (POD) technique and show why POD may not be sufficient due to the underlying constraints. The final problem that we address in this thesis addresses a certain class of dynamics with high stiffness - in particular, differential algebraic equations. With the help of simple examples, we show how the traditional POD procedure will fail to model certain high stiffness problems due to a particular behavior of the vector field which we will denote as twist. We further show how a novel augmentation to the traditional POD algorithm can model-reduce problems with twist in a computationally cheap manner without any additional data requirements.

Large-Scale Optimization for Bayesian Inference in Complex Systems

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

Willcox, Karen; Marzouk, Youssef

2013-11-12

The SAGUARO (Scalable Algorithms for Groundwater Uncertainty Analysis and Robust Optimization) Project focused on the development of scalable numerical algorithms for large-scale Bayesian inversion in complex systems that capitalize on advances in large-scale simulation-based optimization and inversion methods. The project was a collaborative effort among MIT, the University of Texas at Austin, Georgia Institute of Technology, and Sandia National Laboratories. The research was directed in three complementary areas: efficient approximations of the Hessian operator, reductions in complexity of forward simulations via stochastic spectral approximations and model reduction, and employing large-scale optimization concepts to accelerate sampling. The MIT--Sandia component of themore » SAGUARO Project addressed the intractability of conventional sampling methods for large-scale statistical inverse problems by devising reduced-order models that are faithful to the full-order model over a wide range of parameter values; sampling then employs the reduced model rather than the full model, resulting in very large computational savings. Results indicate little effect on the computed posterior distribution. On the other hand, in the Texas--Georgia Tech component of the project, we retain the full-order model, but exploit inverse problem structure (adjoint-based gradients and partial Hessian information of the parameter-to-observation map) to implicitly extract lower dimensional information on the posterior distribution; this greatly speeds up sampling methods, so that fewer sampling points are needed. We can think of these two approaches as ``reduce then sample'' and ``sample then reduce.'' In fact, these two approaches are complementary, and can be used in conjunction with each other. Moreover, they both exploit deterministic inverse problem structure, in the form of adjoint-based gradient and Hessian information of the underlying parameter-to-observation map, to achieve their speedups.« less

Final Report: Large-Scale Optimization for Bayesian Inference in Complex Systems

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

Ghattas, Omar

2013-10-15

The SAGUARO (Scalable Algorithms for Groundwater Uncertainty Analysis and Robust Optimiza- tion) Project focuses on the development of scalable numerical algorithms for large-scale Bayesian inversion in complex systems that capitalize on advances in large-scale simulation-based optimiza- tion and inversion methods. Our research is directed in three complementary areas: efficient approximations of the Hessian operator, reductions in complexity of forward simulations via stochastic spectral approximations and model reduction, and employing large-scale optimization concepts to accelerate sampling. Our efforts are integrated in the context of a challenging testbed problem that considers subsurface reacting flow and transport. The MIT component of the SAGUAROmore » Project addresses the intractability of conventional sampling methods for large-scale statistical inverse problems by devising reduced-order models that are faithful to the full-order model over a wide range of parameter values; sampling then employs the reduced model rather than the full model, resulting in very large computational savings. Results indicate little effect on the computed posterior distribution. On the other hand, in the Texas-Georgia Tech component of the project, we retain the full-order model, but exploit inverse problem structure (adjoint-based gradients and partial Hessian information of the parameter-to- observation map) to implicitly extract lower dimensional information on the posterior distribution; this greatly speeds up sampling methods, so that fewer sampling points are needed. We can think of these two approaches as "reduce then sample" and "sample then reduce." In fact, these two approaches are complementary, and can be used in conjunction with each other. Moreover, they both exploit deterministic inverse problem structure, in the form of adjoint-based gradient and Hessian information of the underlying parameter-to-observation map, to achieve their speedups.« less

Network Reduction Algorithm for Developing Distribution Feeders for Real-Time Simulators

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

Nagarajan, Adarsh; Nelson, Austin A; Prabakar, Kumaraguru

As advanced grid-support functions (AGF) become more widely used in grid-connected photovoltaic (PV) inverters, utilities are increasingly interested in their impacts when implemented in the field. These effects can be understood by modeling feeders in real-time simulators and test PV inverters using power hardware-in-the-loop (PHIL) techniques. This paper presents a novel feeder model reduction algorithm using a ruin & reconstruct methodology that enables large feeders to be solved and operated on real-time computing platforms. Two Hawaiian Electric feeder models in Synergi Electric's load flow software were converted to reduced order models in OpenDSS, and subsequently implemented in the OPAL-RT real-timemore » digital testing platform. Smart PV inverters were added to the realtime model with AGF responses modeled after characterizing commercially available hardware inverters. Finally, hardware inverters were tested in conjunction with the real-time model using PHIL techniques so that the effects of AGFs on the feeders could be analyzed.« less

Network Reduction Algorithm for Developing Distribution Feeders for Real-Time Simulators: Preprint

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

Nagarajan, Adarsh; Nelson, Austin; Prabakar, Kumaraguru

As advanced grid-support functions (AGF) become more widely used in grid-connected photovoltaic (PV) inverters, utilities are increasingly interested in their impacts when implemented in the field. These effects can be understood by modeling feeders in real-time systems and testing PV inverters using power hardware-in-the-loop (PHIL) techniques. This paper presents a novel feeder model reduction algorithm using a Monte Carlo method that enables large feeders to be solved and operated on real-time computing platforms. Two Hawaiian Electric feeder models in Synergi Electric's load flow software were converted to reduced order models in OpenDSS, and subsequently implemented in the OPAL-RT real-time digitalmore » testing platform. Smart PV inverters were added to the real-time model with AGF responses modeled after characterizing commercially available hardware inverters. Finally, hardware inverters were tested in conjunction with the real-time model using PHIL techniques so that the effects of AGFs on the choice feeders could be analyzed.« less

A predictive model for failure properties of thermoset resins

NASA Technical Reports Server (NTRS)

Caruthers, James M.; Bowles, Kenneth J.

1989-01-01

A predictive model for the three-dimensional failure behavior of engineering polymers has been developed in a recent NASA-sponsored research program. This model acknowledges the underlying molecular deformation mechanisms and thus accounts for the effects of different chemical compositions, crosslink density, functionality of the curing agent, etc., on the complete nonlinear stress-strain response including yield. The material parameters required by the model can be determined from test-tube quantities of a new resin in only a few days. Thus, we can obtain a first-order prediction of the applicability of a new resin for an advanced aerospace application without synthesizing the large quantities of material needed for failure testing. This technology will effect order-of-magnitude reductions in the time and expense required to develop new engineering polymers.

Control-structure interaction study for the Space Station solar dynamic power module

NASA Technical Reports Server (NTRS)

Cheng, J.; Ianculescu, G.; Ly, J.; Kim, M.

1991-01-01

The authors investigate the feasibility of using a conventional PID (proportional plus integral plus derivative) controller design to perform the pointing and tracking functions for the Space Station Freedom solar dynamic power module. Using this simple controller design, the control/structure interaction effects were also studied without assuming frequency bandwidth separation. From the results, the feasibility of a simple solar dynamic control solution with a reduced-order model, which satisfies the basic system pointing and stability requirements, is suggested. However, the conventional control design approach is shown to be very much influenced by the order of reduction of the plant model, i.e., the number of the retained elastic modes from the full-order model. This suggests that, for complex large space structures, such as the Space Station Freedom solar dynamic, the conventional control system design methods may not be adequate.

Aeroservoelastic modeling and applications using minimum-state approximations of the unsteady aerodynamics

NASA Technical Reports Server (NTRS)

Tiffany, Sherwood H.; Karpel, Mordechay

1989-01-01

Various control analysis, design, and simulation techniques for aeroelastic applications require the equations of motion to be cast in a linear time-invariant state-space form. Unsteady aerodynamics forces have to be approximated as rational functions of the Laplace variable in order to put them in this framework. For the minimum-state method, the number of denominator roots in the rational approximation. Results are shown of applying various approximation enhancements (including optimization, frequency dependent weighting of the tabular data, and constraint selection) with the minimum-state formulation to the active flexible wing wind-tunnel model. The results demonstrate that good models can be developed which have an order of magnitude fewer augmenting aerodynamic equations more than traditional approaches. This reduction facilitates the design of lower order control systems, analysis of control system performance, and near real-time simulation of aeroservoelastic phenomena.

Noise reduction of a tilt-rotor aircraft including effects on weight and performance

NASA Technical Reports Server (NTRS)

Gibs, J.; Stepniewski, W. Z.; Spencer, R.; Kohler, G.

1973-01-01

Various methods for far-field noise reduction of a tilt-rotor acoustic signature and the performance and weight tradeoffs which result from modification of the noise sources are considered in this report. In order to provide a realistic approach for the investigation, the Boeing tilt-rotor flight research aircraft (Model 222), was selected as the baseline. This aircraft has undergone considerable engineering development. Its rotor has been manufactured and tested in the Ames full-scale wind tunnel. The study reflects the current state-of-the-art of aircraft design for far-field acoustic signature reduction and is not based solely on an engineering feasibility aircraft. This report supplements a previous study investigating reduction of noise signature through the management of the terminal flight trajectory.

Noise reduction and image enhancement using a hardware implementation of artificial neural networks

NASA Astrophysics Data System (ADS)

David, Robert; Williams, Erin; de Tremiolles, Ghislain; Tannhof, Pascal

1999-03-01

In this paper, we present a neural based solution developed for noise reduction and image enhancement using the ZISC, an IBM hardware processor which implements the Restricted Coulomb Energy algorithm and the K-Nearest Neighbor algorithm. Artificial neural networks present the advantages of processing time reduction in comparison with classical models, adaptability, and the weighted property of pattern learning. The goal of the developed application is image enhancement in order to restore old movies (noise reduction, focus correction, etc.), to improve digital television images, or to treat images which require adaptive processing (medical images, spatial images, special effects, etc.). Image results show a quantitative improvement over the noisy image as well as the efficiency of this system. Further enhancements are being examined to improve the output of the system.

2nd-order optical model of the isotopic dependence of heavy ion absorption cross sections for radiation transport studies

NASA Astrophysics Data System (ADS)

Cucinotta, Francis A.; Yan, Congchong; Saganti, Premkumar B.

2018-01-01

Heavy ion absorption cross sections play an important role in radiation transport codes used in risk assessment and for shielding studies of galactic cosmic ray (GCR) exposures. Due to the GCR primary nuclei composition and nuclear fragmentation leading to secondary nuclei heavy ions of charge number, Z with 3 ≤ Z ≥ 28 and mass numbers, A with 6 ≤ A ≥ 60 representing about 190 isotopes occur in GCR transport calculations. In this report we describe methods for developing a data-base of isotopic dependent heavy ion absorption cross sections for interactions. Calculations of a 2nd-order optical model solution to coupled-channel solutions to the Eikonal form of the nucleus-nucleus scattering amplitude are compared to 1st-order optical model solutions. The 2nd-order model takes into account two-body correlations in the projectile and target ground-states, which are ignored in the 1st-order optical model. Parameter free predictions are described using one-body and two-body ground state form factors for the isotopes considered and the free nucleon-nucleon scattering amplitude. Root mean square (RMS) matter radii for protons and neutrons are taken from electron and muon scattering data and nuclear structure models. We report on extensive comparisons to experimental data for energy-dependent absorption cross sections for over 100 isotopes of elements from Li to Fe interacting with carbon and aluminum targets. Agreement between model and experiments are generally within 10% for the 1st-order optical model and improved to less than 5% in the 2nd-order optical model in the majority of comparisons. Overall the 2nd-order optical model leads to a reduction in absorption compared to the 1st-order optical model for heavy ion interactions, which influences estimates of nuclear matter radii.

Numerical study of anomalous dynamic scaling behaviour of (1+1)-dimensional Das Sarma-Tamborenea model

NASA Astrophysics Data System (ADS)

Xun, Zhi-Peng; Tang, Gang; Han, Kui; Hao, Da-Peng; Xia, Hui; Zhou, Wei; Yang, Xi-Quan; Wen, Rong-Ji; Chen, Yu-Ling

2010-07-01

In order to discuss the finite-size effect and the anomalous dynamic scaling behaviour of Das Sarma-Tamborenea growth model, the (1+1)-dimensional Das Sarma-Tamborenea model is simulated on a large length scale by using the kinetic Monte-Carlo method. In the simulation, noise reduction technique is used in order to eliminate the crossover effect. Our results show that due to the existence of the finite-size effect, the effective global roughness exponent of the (1+1)-dimensional Das Sarma-Tamborenea model systematically decreases with system size L increasing when L > 256. This finding proves the conjecture by Aarao Reis[Aarao Reis F D A 2004 Phys. Rev. E 70 031607]. In addition, our simulation results also show that the Das Sarma-Tamborenea model in 1+1 dimensions indeed exhibits intrinsic anomalous scaling behaviour.

The performance of a reduced-order adaptive controller when used in multi-antenna hyperthermia treatments with nonlinear temperature-dependent perfusion.

PubMed

Cheng, Kung-Shan; Yuan, Yu; Li, Zhen; Stauffer, Paul R; Maccarini, Paolo; Joines, William T; Dewhirst, Mark W; Das, Shiva K

2009-04-07

In large multi-antenna systems, adaptive controllers can aid in steering the heat focus toward the tumor. However, the large number of sources can greatly increase the steering time. Additionally, controller performance can be degraded due to changes in tissue perfusion which vary non-linearly with temperature, as well as with time and spatial position. The current work investigates whether a reduced-order controller with the assumption of piecewise constant perfusion is robust to temperature-dependent perfusion and achieves steering in a shorter time than required by a full-order controller. The reduced-order controller assumes that the optimal heating setting lies in a subspace spanned by the best heating vectors (virtual sources) of an initial, approximate, patient model. An initial, approximate, reduced-order model is iteratively updated by the controller, using feedback thermal images, until convergence of the heat focus to the tumor. Numerical tests were conducted in a patient model with a right lower leg sarcoma, heated in a 10-antenna cylindrical mini-annual phased array applicator operating at 150 MHz. A half-Gaussian model was used to simulate temperature-dependent perfusion. Simulated magnetic resonance temperature images were used as feedback at each iteration step. Robustness was validated for the controller, starting from four approximate initial models: (1) a 'standard' constant perfusion lower leg model ('standard' implies a model that exactly models the patient with the exception that perfusion is considered constant, i.e., not temperature dependent), (2) a model with electrical and thermal tissue properties varied from 50% higher to 50% lower than the standard model, (3) a simplified constant perfusion pure-muscle lower leg model with +/-50% deviated properties and (4) a standard model with the tumor position in the leg shifted by 1.5 cm. Convergence to the desired focus of heating in the tumor was achieved for all four simulated models. The controller accomplished satisfactory therapeutic outcomes: approximately 80% of the tumor was heated to temperatures 43 degrees C and approximately 93% was maintained at temperatures <41 degrees C. Compared to the controller without model reduction, a approximately 9-25 fold reduction in convergence time was accomplished using approximately 2-3 orthonormal virtual sources. In the situations tested, the controller was robust to the presence of temperature-dependent perfusion. The results of this work can help to lay the foundation for real-time thermal control of multi-antenna hyperthermia systems in clinical situations where perfusion can change rapidly with temperature.

Vibration reduction in a tilting rotor using centrifugal pendulum vibration absorbers

NASA Astrophysics Data System (ADS)

Shi, Chengzhi; Shaw, Steven W.; Parker, Robert G.

2016-12-01

This paper investigates vibration reduction in a rigid rotor with tilting, rotational, and translational motions using centrifugal pendulum vibration absorbers (CPVAs). A linearized vibration model is derived for the system consisting of the rotor and multiple sets of absorbers tuned to different orders. Each group of absorbers lies in a given plane perpendicular to the rotor rotation axis. Gyroscopic system modal analysis is applied to derive the steady-state response of the absorbers and the rotor to external, rotor-order, periodic forces and torques with frequency mΩ, where Ω is the mean rotor speed and m is the engine order (rotor-order). It is found that an absorber group with tuning order m is effective at reducing the rotor translational, tilting, and rotational vibrations, provided certain conditions are met. When the periodic force and torque are caused by N substructures that are equally spaced around the rotor, the rotor translational and tilting vibrations at order j are addressed by two absorber groups with tuning orders jN±1. In this case, the rotor rotational vibration at order j can be attenuated by an absorber group with tuning order jN. The results show how the response depends on the load amplitudes and order, the rotor speed, and design parameters associated with the sets of absorbers, most importantly, their tuning, mass, and plane of placement. In the ideal case with zero damping and exact tuning of the absorber sets, the vibrations can be eliminated for a range of loads over which the linearized model holds. The response for systems with detuned absorbers is also determined, which is relevant to applications where small detuning is employed due to robustness issues, and to allow for a larger range of operating loads over which the absorbers are effective. The system also exhibits undesirable resonances very close to these tuning conditions, an issue that is difficult to resolve and deserves further investigation.

Identifying critical life stage transitions for biological control of long-lived perennial Vincetoxicum species

USDA-ARS?s Scientific Manuscript database

Demographic matrix modeling of invasive plant populations can be a powerful tool to identify key life stage transitions for targeted disruption in order to cause population decline. This approach can provide quantitative estimates of reductions in select vital rates needed to reduce population growt...

Cost-effectiveness analysis of risk-reduction measures to reach water safety targets.

PubMed

Lindhe, Andreas; Rosén, Lars; Norberg, Tommy; Bergstedt, Olof; Pettersson, Thomas J R

2011-01-01

Identifying the most suitable risk-reduction measures in drinking water systems requires a thorough analysis of possible alternatives. In addition to the effects on the risk level, also the economic aspects of the risk-reduction alternatives are commonly considered important. Drinking water supplies are complex systems and to avoid sub-optimisation of risk-reduction measures, the entire system from source to tap needs to be considered. There is a lack of methods for quantification of water supply risk reduction in an economic context for entire drinking water systems. The aim of this paper is to present a novel approach for risk assessment in combination with economic analysis to evaluate risk-reduction measures based on a source-to-tap approach. The approach combines a probabilistic and dynamic fault tree method with cost-effectiveness analysis (CEA). The developed approach comprises the following main parts: (1) quantification of risk reduction of alternatives using a probabilistic fault tree model of the entire system; (2) combination of the modelling results with CEA; and (3) evaluation of the alternatives with respect to the risk reduction, the probability of not reaching water safety targets and the cost-effectiveness. The fault tree method and CEA enable comparison of risk-reduction measures in the same quantitative unit and consider costs and uncertainties. The approach provides a structured and thorough analysis of risk-reduction measures that facilitates transparency and long-term planning of drinking water systems in order to avoid sub-optimisation of available resources for risk reduction. Copyright © 2010 Elsevier Ltd. All rights reserved.

Mathematical analysis of a lymphatic filariasis model with quarantine and treatment.

PubMed

Mwamtobe, Peter M; Simelane, Simphiwe M; Abelman, Shirley; Tchuenche, Jean M

2017-03-16

Lymphatic filariasis is a globally neglected tropical parasitic disease which affects individuals of all ages and leads to an altered lymphatic system and abnormal enlargement of body parts. A mathematical model of lymphatic filariaris with intervention strategies is developed and analyzed. Control of infections is analyzed within the model through medical treatment of infected-acute individuals and quarantine of infected-chronic individuals. We derive the effective reproduction number, [Formula: see text] and its interpretation/investigation suggests that treatment contributes to a reduction in lymphatic filariasis cases faster than quarantine. However, this reduction is greater when the two intervention approaches are applied concurrently. Numerical simulations are carried out to monitor the dynamics of the filariasis model sub-populations for various parameter values of the associated reproduction threshold. Lastly, sensitivity analysis on key parameters that drive the disease dynamics is performed in order to identify their relative importance on the disease transmission.

On the Numerical Formulation of Parametric Linear Fractional Transformation (LFT) Uncertainty Models for Multivariate Matrix Polynomial Problems

NASA Technical Reports Server (NTRS)

Belcastro, Christine M.

1998-01-01

Robust control system analysis and design is based on an uncertainty description, called a linear fractional transformation (LFT), which separates the uncertain (or varying) part of the system from the nominal system. These models are also useful in the design of gain-scheduled control systems based on Linear Parameter Varying (LPV) methods. Low-order LFT models are difficult to form for problems involving nonlinear parameter variations. This paper presents a numerical computational method for constructing and LFT model for a given LPV model. The method is developed for multivariate polynomial problems, and uses simple matrix computations to obtain an exact low-order LFT representation of the given LPV system without the use of model reduction. Although the method is developed for multivariate polynomial problems, multivariate rational problems can also be solved using this method by reformulating the rational problem into a polynomial form.

Restoration of dimensional reduction in the random-field Ising model at five dimensions

NASA Astrophysics Data System (ADS)

Fytas, Nikolaos G.; Martín-Mayor, Víctor; Picco, Marco; Sourlas, Nicolas

2017-04-01

The random-field Ising model is one of the few disordered systems where the perturbative renormalization group can be carried out to all orders of perturbation theory. This analysis predicts dimensional reduction, i.e., that the critical properties of the random-field Ising model in D dimensions are identical to those of the pure Ising ferromagnet in D -2 dimensions. It is well known that dimensional reduction is not true in three dimensions, thus invalidating the perturbative renormalization group prediction. Here, we report high-precision numerical simulations of the 5D random-field Ising model at zero temperature. We illustrate universality by comparing different probability distributions for the random fields. We compute all the relevant critical exponents (including the critical slowing down exponent for the ground-state finding algorithm), as well as several other renormalization-group invariants. The estimated values of the critical exponents of the 5D random-field Ising model are statistically compatible to those of the pure 3D Ising ferromagnet. These results support the restoration of dimensional reduction at D =5 . We thus conclude that the failure of the perturbative renormalization group is a low-dimensional phenomenon. We close our contribution by comparing universal quantities for the random-field problem at dimensions 3 ≤D <6 to their values in the pure Ising model at D -2 dimensions, and we provide a clear verification of the Rushbrooke equality at all studied dimensions.

Restoration of dimensional reduction in the random-field Ising model at five dimensions.

PubMed

Fytas, Nikolaos G; Martín-Mayor, Víctor; Picco, Marco; Sourlas, Nicolas

2017-04-01

The random-field Ising model is one of the few disordered systems where the perturbative renormalization group can be carried out to all orders of perturbation theory. This analysis predicts dimensional reduction, i.e., that the critical properties of the random-field Ising model in D dimensions are identical to those of the pure Ising ferromagnet in D-2 dimensions. It is well known that dimensional reduction is not true in three dimensions, thus invalidating the perturbative renormalization group prediction. Here, we report high-precision numerical simulations of the 5D random-field Ising model at zero temperature. We illustrate universality by comparing different probability distributions for the random fields. We compute all the relevant critical exponents (including the critical slowing down exponent for the ground-state finding algorithm), as well as several other renormalization-group invariants. The estimated values of the critical exponents of the 5D random-field Ising model are statistically compatible to those of the pure 3D Ising ferromagnet. These results support the restoration of dimensional reduction at D=5. We thus conclude that the failure of the perturbative renormalization group is a low-dimensional phenomenon. We close our contribution by comparing universal quantities for the random-field problem at dimensions 3≤D<6 to their values in the pure Ising model at D-2 dimensions, and we provide a clear verification of the Rushbrooke equality at all studied dimensions.

Risk-Based Prioritization of Research for Aviation Security Using Logic-Evolved Decision Analysis

NASA Technical Reports Server (NTRS)

Eisenhawer, S. W.; Bott, T. F.; Sorokach, M. R.; Jones, F. P.; Foggia, J. R.

2004-01-01

The National Aeronautics and Space Administration is developing advanced technologies to reduce terrorist risk for the air transportation system. Decision support tools are needed to help allocate assets to the most promising research. An approach to rank ordering technologies (using logic-evolved decision analysis), with risk reduction as the metric, is presented. The development of a spanning set of scenarios using a logic-gate tree is described. Baseline risk for these scenarios is evaluated with an approximate reasoning model. Illustrative risk and risk reduction results are presented.

Patulin reduction in apple juice from concentrate by UV radiation and comparison of kinetic degradation models between apple juice and apple cider.

PubMed

Assatarakul, Kitipong; Churey, John J; Manns, David C; Worobo, Randy W

2012-04-01

Patulin, a mycotoxin produced by several genera of fungi, including Byssochlamys, Aspergillus, and Penicillium, has been an important concern in apple cider and apple juice due to its toxicity and health consequences. In this study, the effects of UV on the patulin level, physical and chemical properties, and sensory attributes in apple juice from concentrate were investigated. Kinetic modeling of patulin reduction by UV radiation in apple juice from concentrate was calculated and compared with the degradation rate observed previously in apple cider. From an initial patulin contamination of approximately 1,000 ppb (μg/liter), the UV exposure, ranging from 14.2 mJ/cm(2) (one pass) to 99.4 mJ/cm(2) (seven passes), was successful in reducing patulin levels by 72.57% ± 2.76% to 5.14% ± 0.70%, respectively. Patulin reduction by UV radiation followed first-order kinetic modeling in a fashion similar to first-order microbial inactivation. An exponential correlation between UV exposure and the percentage of patulin remaining was observed, giving an r(2) value of 0.9950. Apple juice was repeatedly exposed to 14.2 mJ/cm(2) for each treatment, and patulin levels were significantly decreased when compared with the level obtained with the previous UV exposure treatment. While there were no significant differences in the percentages of titratable acidity and ascorbic acid (P > 0.05), there were minor yet random sampling differences in pH and degrees Brix (1 °Brix is 1 g of sucrose in 100 g of solution; the °Brix represents the soluble solids content of the solution as percentage by weight [%, wt/wt]) (P ≤ 0.05). A significant difference (P ≤ 0.05) in sensory perception for the finished apple juice was detected between the control and the full seven-pass UV radiation treatment using an experienced consumer panel and a triangle test. Patulin reduction by UV radiation from both the current study and a previous study involving apple cider was compared, which showed that both matrices strongly fit a first-order kinetic degradation model. However, the kinetic constant for degradation in apple juice was approximately 5.5 times greater than that observed in an apple cider matrix.

Kinetics of abiotic nitrous oxide production via oxidation of hydroxylamine by particulate metals in seawater

NASA Astrophysics Data System (ADS)

Cavazos, A. R.; Taillefert, M.; Glass, J. B.

2016-12-01

The oceans are a significant of nitrous oxide (N2O) to the atmosphere. Current models of global oceanic N2­O flux focus on microbial N2O cycling and often ignore abiotic reactions, such as the thermodynamically favorable oxidation of the nitrification intermediate hydroxylamine (NH2OH) by Mn(IV) or Fe(III). At circumneutral pH, NH2OH oxidation is more thermodynamically favorable via Mn(IV) than Fe(III) reduction. We characterized the kinetics of NH2OH oxidation in synthetic ocean water at pH 5.1-8.8 using microsensor electrodes to measure real-time N2O production. N2O production rates and yield were greater when NH2OH was oxidized by Mn(IV) than Fe(III). Accordingly, the reduction of Mn(IV) was first order with respect to NH2OH whereas the reduction of Fe(III) was zero order with respect to NH2OH. Interestingly, the order of the reaction with respect to Mn(IV) appears to be negative whereas the reaction is second order with respect to Fe(III). The inverse order with respect to Mn(IV) may be due to the aggregation of particles in seawater, which decreases their surface area and changes their reactivity. Finally, the reaction is first order with respect to protons with Fe(III) as the oxidant but zero order with Mn(IV). The stronger effect of the pH on the reaction with Fe(III) as the oxidant compared to Mn(IV) reflects the stoichiometry of these two reactions, as each mole of N2O produced by Fe(III) reduction consumes eight protons while each mole of N2O produced with Mn(IV) as the oxidant requires only four protons. Our data show that abiotic NH2OH oxidation by Mn(IV) or Fe(III) particles may represent a significant source of N2O in seawater. These findings suggest that abiotic N2O production in marine waters may be significant in areas of the oceans where particulate metals originating from aerosols, dust, or rivers may react with NH2OH released from ammonia-oxidizing microorganisms.

Computerized Provider Order Entry Reduces Length of Stay in a Community Hospital

PubMed Central

Peters, K.; Shaha, S.H.

2014-01-01

Summary Objective Does computerized provider order entry (CPOE) improve clinical, cost, and efficiency outcomes as quantified in shortened hospital length of stay (LOS)? Most prior studies were done in university settings with home-grown electronic records, and are now 20 years old. This study asked whether CPOE exerts a downward force on LOS in the current era of HITECH incentives, using a vendor product in a community hospital. Methods The methodology retrospectively evaluated correlation between CPOE and LOS on a perpatient, per-visit basis over 22 consecutive quarters, organized by discipline. All orders from all areas were eligible, except verbals, and medication orders in the emergency department which were not available via CPOE. These results were compared with quarterly case mix indices organized by discipline. Correlational and regression analyses were cross-checked to ensure validity of R-square coefficients, and data were smoothed for ease of display. Standard models were used to calculate the inflection point. Results Gains in CPOE adoption occurred iteratively house-wide, and in each discipline. LOS decreased in a sigmoid shaped curve. The inflection point shows that once CPOE adoption approaches 60%, further lowering of LOS accelerates. Overall there was a 20.2% reduction in LOS correlated with adoption of CPOE. Case mix index increased during the study period showing that reductions in LOS occurred despite increased patient complexity and resource utilization. Conclusions There was a 20.2% reduction in LOS correlated with rising adoption of CPOE. CPOE contributes to improved clinical, cost, and efficiency outcomes as quantified in reduced LOS, over and above other processes introduced to lower LOS. CPOE enabled a reduction in LOS despite an increase in the case mix index during the time frame of this study. PMID:25298809

A comparative study of the tail ion distribution with reduced Fokker-Planck models

NASA Astrophysics Data System (ADS)

McDevitt, C. J.; Tang, Xian-Zhu; Guo, Zehua; Berk, H. L.

2014-03-01

A series of reduced models are used to study the fast ion tail in the vicinity of a transition layer between plasmas at disparate temperatures and densities, which is typical of the gas and pusher interface in inertial confinement fusion targets. Emphasis is placed on utilizing progressively more comprehensive models in order to identify the essential physics for computing the fast ion tail at energies comparable to the Gamow peak. The resulting fast ion tail distribution is subsequently used to compute the fusion reactivity as a function of collisionality and temperature. While a significant reduction of the fusion reactivity in the hot spot compared to the nominal Maxwellian case is present, this reduction is found to be partially recovered by an increase of the fusion reactivity in the neighboring cold region.

Evaluation of Cost Leadership Strategy in Shipping Enterprises with Simulation Model

NASA Astrophysics Data System (ADS)

Ferfeli, Maria V.; Vaxevanou, Anthi Z.; Damianos, Sakas P.

2009-08-01

The present study will attempt the evaluation of cost leadership strategy that prevails in certain shipping enterprises and the creation of simulation models based on strategic model STAIR. The above model is an alternative method of strategic applications evaluation. This is held in order to be realised if the strategy of cost leadership creates competitive advantage [1] and this will be achieved via the technical simulation which appreciates the interactions between the operations of an enterprise and the decision-making strategy in conditions of uncertainty with reduction of undertaken risk.

Characterising microbial reduction of arsenate sorbed to ferrihydrite and its concurrence with iron reduction.

PubMed

Huang, Jen-How

2018-03-01

A series of model anoxic incubations were performed to understand the concurrence between arsenate and ferrihydrite reduction by Shewanella putrefaciens strain CN-32 at different concentrations of arsenate, ferrihydrite and lactate, and with given ΔG rxn for arsenate and ferrihydrite reduction in non-growth conditions. The reduction kinetics of arsenate sorbed to ferrihydrite is predominately controlled by the availability of dissolved arsenate, which is measured by the integral of dissolved arsenate concentrations against incubation time and shown to correlate with the first order rate constants. High lactate concentrations slightly slowed down the rate of arsenate reduction due to the competition with arsenate for microbial contact. Under all experimental conditions, simultaneous arsenate and ferrihydrite reduction occurred following addition of S. putrefaciens inoculums and suggested no apparent competition between these two enzymatic reductions. Ferrous ions released from iron reduction might retard microbial arsenate reduction at high arsenate and ferrihydrite concentrations due to formation of ferrous arsenate. At high arsenate to ferrihydrite ratios, reductive dissolution of ferrihydrite shifted arsenate from sorption to dissolution and hence accelerated arsenate reduction. The interaction between microbial arsenate and ferrihydrite reduction did not correlate with ΔG rxn , but instead was governed by other factors such as geochemical and microbial parameters. Copyright © 2017 Elsevier Ltd. All rights reserved.

Dynamic emulation modelling for the optimal operation of water systems: an overview

NASA Astrophysics Data System (ADS)

Castelletti, A.; Galelli, S.; Giuliani, M.

2014-12-01

Despite sustained increase in computing power over recent decades, computational limitations remain a major barrier to the effective and systematic use of large-scale, process-based simulation models in rational environmental decision-making. Whereas complex models may provide clear advantages when the goal of the modelling exercise is to enhance our understanding of the natural processes, they introduce problems of model identifiability caused by over-parameterization and suffer from high computational burden when used in management and planning problems. As a result, increasing attention is now being devoted to emulation modelling (or model reduction) as a way of overcoming these limitations. An emulation model, or emulator, is a low-order approximation of the process-based model that can be substituted for it in order to solve high resource-demanding problems. In this talk, an overview of emulation modelling within the context of the optimal operation of water systems will be provided. Particular emphasis will be given to Dynamic Emulation Modelling (DEMo), a special type of model complexity reduction in which the dynamic nature of the original process-based model is preserved, with consequent advantages in a wide range of problems, particularly feedback control problems. This will be contrasted with traditional non-dynamic emulators (e.g. response surface and surrogate models) that have been studied extensively in recent years and are mainly used for planning purposes. A number of real world numerical experiences will be used to support the discussion ranging from multi-outlet water quality control in water reservoir through erosion/sedimentation rebalancing in the operation of run-off-river power plants to salinity control in lake and reservoirs.

NASA Langley Low Speed Aeroacoustic Wind Tunnel: Background Noise and Flow Survey Results Prior to FY05 Construction of Facilities Modifications

NASA Technical Reports Server (NTRS)

Booth, Earl R., Jr.; Henderson, Brenda S.

2005-01-01

The NASA Langley Research Center Low Speed Aeroacoustic Wind Tunnel is a premier facility for model-scale testing of jet noise reduction concepts at realistic flow conditions. However, flow inside the open jet test section is less than optimum. A Construction of Facilities project, scheduled for FY 05, will replace the flow collector with a new design intended to reduce recirculation in the open jet test section. The reduction of recirculation will reduce background noise levels measured by a microphone array impinged by the recirculation flow and will improve flow characteristics in the open jet tunnel flow. In order to assess the degree to which this modification is successful, background noise levels and tunnel flow are documented, in order to establish a baseline, in this report.

Future-year ozone prediction for the United States using updated models and inputs.

PubMed

Collet, Susan; Kidokoro, Toru; Karamchandani, Prakash; Shah, Tejas; Jung, Jaegun

2017-08-01

The relationship between emission reductions and changes in ozone can be studied using photochemical grid models. These models are updated with new information as it becomes available. The primary objective of this study was to update the previous Collet et al. studies by using the most up-to-date (at the time the study was done) modeling emission tools, inventories, and meteorology available to conduct ozone source attribution and sensitivity studies. Results show future-year, 2030, design values for 8-hr ozone concentrations were lower than base-year values, 2011. The ozone source attribution results for selected cities showed that boundary conditions were the dominant contributors to ozone concentrations at the western U.S. locations, and were important for many of the eastern U.S. Point sources were generally more important in the eastern United States than in the western United States. The contributions of on-road mobile emissions were less than 5 ppb at a majority of the cities selected for analysis. The higher-order decoupled direct method (HDDM) results showed that in most of the locations selected for analysis, NOx emission reductions were more effective than VOC emission reductions in reducing ozone levels. The source attribution results from this study provide useful information on the important source categories and provide some initial guidance on future emission reduction strategies. The relationship between emission reductions and changes in ozone can be studied using photochemical grid models, which are updated with new available information. This study was to update the previous Collet et al. studies by using the most current, at the time the study was done, models and inventory to conduct ozone source attribution and sensitivity studies. The source attribution results from this study provide useful information on the important source categories and provide some initial guidance on future emission reduction strategies.

The sometimes competing retrieval and Van Hamme & Wasserman models predict the selective role of within-compound associations in retrospective revaluation.

PubMed

Witnauer, James; Rhodes, L Jack; Kysor, Sarah; Narasiwodeyar, Sanjay

2017-11-21

The correlation between blocking and within-compound memory is stronger when compound training occurs before elemental training (i.e., backward blocking) than when the phases are reversed (i.e., forward blocking; Melchers et al., 2004, 2006). This trial order effect is often interpreted as problematic for performance-focused models that assume a critical role for within-compound associations in both retrospective revaluation and traditional cue competition. The present manuscript revisits this issue using a computational modeling approach. The fit of sometimes competing retrieval (SOCR; Stout & Miller, 2007) was compared to the fit of an acquisition-focused model of retrospective revaluation and cue competition. These simulations reveal that SOCR explains this trial order effect in some situations based on its use of local error reduction. Published by Elsevier B.V.

Cooperating reduction machines

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

Kluge, W.E.

1983-11-01

This paper presents a concept and a system architecture for the concurrent execution of program expressions of a concrete reduction language based on lamda-expressions. If formulated appropriately, these expressions are well-suited for concurrent execution, following a demand-driven model of computation. In particular, recursive program expressions with nonlinear expansion may, at run time, recursively be partitioned into a hierarchy of independent subexpressions which can be reduced by a corresponding hierarchy of virtual reduction machines. This hierarchy unfolds and collapses dynamically, with virtual machines recursively assuming the role of masters that create and eventually terminate, or synchronize with, slaves. The paper alsomore » proposes a nonhierarchically organized system of reduction machines, each featuring a stack architecture, that effectively supports the allocation of virtual machines to the real machines of the system in compliance with their hierarchical order of creation and termination. 25 references.« less

Characterization of Sodium Mobility and Binding by 23 Na NMR Spectroscopy in a Model Lipoproteic Emulsion Gel for Sodium Reduction.

PubMed

Okada, Kyle S; Lee, Youngsoo

2017-07-01

The effects of formulation and processing parameters on sodium availability in a model lipid/protein-based emulsion gel were studied for purposes of sodium reduction. Heat-set model gels were prepared with varying levels of protein, lipid, and NaCl contents and high pressure homogenization treatments. Single quantum and double quantum-filtered 23 Na NMR spectroscopy experiments were used to characterize sodium mobility, structural order around "bound" (restricted mobility) sodium, and sodium binding, which have been correlated to saltiness perception in food systems previously. Total sodium mobility was lower in gels with higher protein or fat content, and was not affected by changes in homogenization pressure. The gels with increased protein, fat, or homogenization pressure had increased structure surrounding "bound" sodium and more relative "bound" sodium due to increased interfacial protein interactions. The data obtained in this study provide information on factors affecting sodium availability, which can be applied towards sodium reduction in lipid/protein-based foods. © 2017 Institute of Food Technologists®.

Alternatives for jet engine control

NASA Technical Reports Server (NTRS)

Sain, M. K.

1983-01-01

The technical progress of researches on alternatives for jet engine control, is reported. The principal new activities involved the initial testing of an input design method for choosing the inputs to a non-linear system to aid the approximation of its tensor parameters, and the beginning of order reduction studies designed to remove unnecessary monomials from tensor models.

Micromechanism Based Modeling of Structural Life in Metal Matrix Composites

DTIC Science & Technology

1997-03-23

wWchJndttees-^anätational eigenstrain ; and the embrittlement of material at the metal-ox^ interface, in addition, the influence of various heat...of two factors: the development of a surface layer consisting primarily of stoichiometric Ti02 which induces a dilatational eigenstrain ; and the...as the dilatational eigenstrain in order to capture the life reduction mechanism. As shown in Fig. 5, for the case of monotonic loading, the model

Effect of residential air-to-air heat and moisture exchangers on indoor humidity

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

Barringer, C.G.; McGugan, C.A.

1989-01-01

A project was undertaken to develop guidelines for the selection of residential heat and moisture recovery ventilation systems (HRVs) in order to maintain an acceptable indoor humidity for various climatic conditions. These guidelines were developed from reviews on ventilation requirements, HRV performance specifications, and from computer modeling. Space conditions within three house/occupancy models for several types of HRV were simulated for three climatic conditions (Lake Charles, LA; Seattle, WA; and Winnipeg, MB) in order to determine the impact of the HRVs on indoor relative humidity and space-conditioning loads. Results show that when reduction of cooling cost is the main consideration,more » exchangers with moisture recovery are preferable to sensible HRVs. For reduction of heating costs, moisture recovery should be done for ventilation rates greater than about 15 L/s and average winter temperatures less than about (minus) 10{degrees}C if internal moisture generation rates are low. For houses with higher ventilation rates and colder average winter temperatures, exchangers with moisture recovery should be used.« less

Anaerobic treatability of high oil and grease rendering wastewater.

PubMed

Nakhla, George; Al-Sabawi, Mustafa; Bassi, Amerjeet; Liu, Victor

2003-08-29

This study evaluated the use of a new biosurfactant, BOD-Balance, derived from cactus for the treatment of oil-and-grease-laden rendering wastewater anaerobically. Batch laboratory experimental results and preliminary full-scale data are presented. The biosurfactant affected a significant increase in the COD degradation rate for the raw wastewater. However, after reduction of the oil and grease (O&G) by dissolved air flotation, the biosurfactant did not exhibit any advantages. Modeling of the data indicated that various COD fractions, i.e. both soluble and particulate as well as total COD at various testing conditions conformed well to both zero-order and first-order models. The biosurfactant affected a 164-238 and 164-247% increase in COD and particulate COD biodegradation rate for the raw wastewater. The reduction of O&G concentration to <800 mg/l increased total and soluble COD degradation rates by 106%. Results from the full-scale mesophilic anaerobic digestion system indicated that the addition of the biosurfactant at doses of 130-200 mg/l decreased O&G concentrations from 66,300 to 10,200 mg/l over a 2-month-period.

Ultrasound speckle reduction based on fractional order differentiation.

PubMed

Shao, Dangguo; Zhou, Ting; Liu, Fan; Yi, Sanli; Xiang, Yan; Ma, Lei; Xiong, Xin; He, Jianfeng

2017-07-01

Ultrasound images show a granular pattern of noise known as speckle that diminishes their quality and results in difficulties in diagnosis. To preserve edges and features, this paper proposes a fractional differentiation-based image operator to reduce speckle in ultrasound. An image de-noising model based on fractional partial differential equations with balance relation between k (gradient modulus threshold that controls the conduction) and v (the order of fractional differentiation) was constructed by the effective combination of fractional calculus theory and a partial differential equation, and the numerical algorithm of it was achieved using a fractional differential mask operator. The proposed algorithm has better speckle reduction and structure preservation than the three existing methods [P-M model, the speckle reducing anisotropic diffusion (SRAD) technique, and the detail preserving anisotropic diffusion (DPAD) technique]. And it is significantly faster than bilateral filtering (BF) in producing virtually the same experimental results. Ultrasound phantom testing and in vivo imaging show that the proposed method can improve the quality of an ultrasound image in terms of tissue SNR, CNR, and FOM values.

Impact of Adverse Events Following Immunization in Viet Nam in 2013 on chronic hepatitis B infection.

PubMed

Li, Xi; Wiesen, Eric; Diorditsa, Sergey; Toda, Kohei; Duong, Thi Hong; Nguyen, Lien Huong; Nguyen, Van Cuong; Nguyen, Tran Hien

2016-02-03

Adverse Events Following Immunization in Viet Nam in 2013 led to substantial reductions in hepatitis B vaccination coverage (both the birth dose and the three-dose series). In order to estimate the impact of the reduction in vaccination coverage on hepatitis B transmission and future mortality, a widely-used mathematical model was applied to the data from Viet Nam. Using the model, we estimated the number of chronic infections and deaths that are expected to occur in the birth cohort in 2013 and the number of excessive infections and deaths attributable to the drop in immunization coverage in 2013. An excess of 90,137 chronic infections and 17,456 future deaths were estimated to occur in the 2013 birth cohort due to the drop in vaccination coverage. This analysis highlights the importance of maintaining high vaccination coverage and swiftly responding to reported Adverse Events Following Immunization in order to regain consumer confidence in the hepatitis B vaccine. Copyright © 2015 World Health Organization; licensee Elsevier. Published by Elsevier Ltd.. All rights reserved.

Investigation of plasma behavior during noble gas injection in the end-cell of GAMMA 10/PDX by using the multi-fluid code ‘LINDA’

NASA Astrophysics Data System (ADS)

Islam, M. S.; Nakashima, Y.; Hatayama, A.

2017-12-01

The linear divertor analysis with fluid model (LINDA) code has been developed in order to simulate plasma behavior in the end-cell of linear fusion device GAMMA 10/PDX. This paper presents the basic structure and simulated results of the LINDA code. The atomic processes of hydrogen and impurities have been included in the present model in order to investigate energy loss processes and mechanism of plasma detachment. A comparison among Ar, Kr and Xe shows that Xe is the most effective gas on the reduction of electron and ion temperature. Xe injection leads to strong reduction in the temperature of electron and ion. The energy loss terms for both the electron and the ion are enhanced significantly during Xe injection. It is shown that the major energy loss channels for ion and electron are charge-exchange loss and radiative power loss of the radiator gas, respectively. These outcomes indicate that Xe injection in the plasma edge region is effective for reducing plasma energy and generating detached plasma in linear device GAMMA 10/PDX.

Abel's Theorem Simplifies Reduction of Order

ERIC Educational Resources Information Center

Green, William R.

2011-01-01

We give an alternative to the standard method of reduction or order, in which one uses one solution of a homogeneous, linear, second order differential equation to find a second, linearly independent solution. Our method, based on Abel's Theorem, is shorter, less complex and extends to higher order equations.

A statistical model to estimate the impact of a hepatitis A vaccination programme.

PubMed

Oviedo, Manuel; Pilar Muñoz, M; Domínguez, Angela; Borras, Eva; Carmona, Gloria

2008-11-11

A program of routine hepatitis A+B vaccination in preadolescents was introduced in 1998 in Catalonia, a region situated in the northeast of Spain. The objective of this study was to quantify the reduction in the incidence of hepatitis A in order to differentiate the natural reduction of the incidence of hepatitis A from that produced due to the vaccination programme and to predict the evolution of the disease in forthcoming years. A generalized linear model (GLM) using negative binomial regression was used to estimate the incidence rates of hepatitis A in Catalonia by year, age group and vaccination. Introduction of the vaccine reduced cases by 5.5 by year (p-value<0.001), but there was a significant interaction between the year of report and vaccination that smoothed this reduction (p-value<0.001). The reduction was not equal in all age groups, being greater in the 12-18 years age group, which fell from a mean rate of 8.15 per 100,000 person/years in the pre-vaccination period (1992-1998) to 1.4 in the vaccination period (1999-2005). The model predicts the evolution accurately for the group of vaccinated subjects. Negative binomial regression is more appropriate than Poisson regression when observed variance exceeds the observed mean (overdispersed count data), can cause a variable apparently contribute more on the model of what really makes it.

Patient-Specific Computational Modeling of Keratoconus Progression and Differential Responses to Collagen Cross-linking

PubMed Central

Sinha Roy, Abhijit

2011-01-01

Purpose. To model keratoconus (KC) progression and investigate the differential responses of central and eccentric cones to standard and alternative collagen cross-linking (CXL) patterns. Methods. Three-dimensional finite element models (FEMs) were generated with clinical tomography and IOP measurements. Graded reductions in regional corneal hyperelastic properties and thickness were imposed separately in the less affected eye of a KC patient. Topographic results, including maximum curvature and first-surface, higher-order aberrations (HOAs), were compared to those of the more affected contralateral eye. In two eyes with central and eccentric cones, a standard broad-beam CXL protocol was simulated with 200- and 300-μm treatment depths and compared to spatially graded broad-beam and cone-centered CXL simulations. Results. In a model of KC progression, maximum curvature and HOA increased as regional corneal hyperelastic properties were decreased. A topographic cone could be generated without a reduction in corneal thickness. Simulation of standard 9-mm-diameter CXL produced decreases in corneal curvature comparable to clinical reports and affected cone location. A 100-μm increase in CXL depth enhanced flattening by 24% to 34% and decreased HOA by 22% to 31%. Topographic effects were greatest with cone-centered CXL simulations. Conclusions. Progressive hyperelastic weakening of a cornea with subclinical KC produced topographic features of manifest KC. The clinical phenomenon of topographic flattening after CXL was replicated. The magnitude and higher-order optics of this response depended on IOP and the spatial distribution of stiffening relative to the cone location. Smaller diameter simulated treatments centered on the cone provided greater reductions in curvature and HOA than a standard broad-beam CXL pattern. PMID:22039252

Greenhouse Gas Mitigation Options in ISEEM Global Energy Model: 2010-2050 Scenario Analysis for Least-Cost Carbon Reduction in Iron and Steel Sector

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

Karali, Nihan; Xu, Tengfang; Sathaye, Jayant

The goal of the modeling work carried out in this project was to quantify long-term scenarios for the future emission reduction potentials in the iron and steel sector. The main focus of the project is to examine the impacts of carbon reduction options in the U.S. iron and steel sector under a set of selected scenarios. In order to advance the understanding of carbon emission reduction potential on the national and global scales, and to evaluate the regional impacts of potential U.S. mitigation strategies (e.g., commodity and carbon trading), we also included and examined the carbon reduction scenarios in China’smore » and India’s iron and steel sectors in this project. For this purpose, a new bottom-up energy modeling framework, the Industrial Sector Energy Efficiency Modeling (ISEEM), (Karali et al. 2012) was used to provide detailed annual projections starting from 2010 through 2050. We used the ISEEM modeling framework to carry out detailed analysis, on a country-by-country basis, for the U.S., China’s, and India’s iron and steel sectors. The ISEEM model applicable to iron and steel section, called ISEEM-IS, is developed to estimate and evaluate carbon emissions scenarios under several alternative mitigation options - including policies (e.g., carbon caps), commodity trading, and carbon trading. The projections will help us to better understand emission reduction potentials with technological and economic implications. The database for input of ISEEM-IS model consists of data and information compiled from various resources such as World Steel Association (WSA), the U.S. Geological Survey (USGS), China Steel Year Books, India Bureau of Mines (IBM), Energy Information Administration (EIA), and recent LBNL studies on bottom-up techno-economic analysis of energy efficiency measures in the iron and steel sector of the U.S., China, and India, including long-term steel production in China. In the ISEEM-IS model, production technology and manufacturing details are represented, in addition to the extensive data compiled from recent studies on bottom-up representation of efficiency measures for the sector. We also defined various mitigation scenarios including long-term production trends to project country-specific production, energy use, trading, carbon emissions, and costs of mitigation. Such analyses can provide useful information to assist policy-makers when considering and shaping future emissions mitigation strategies and policies. The technical objective is to analyze the costs of production and CO 2 emission reduction in the U.S, China, and India’s iron and steel sectors under different emission reduction scenarios, using the ISEEM-IS as a cost optimization model. The scenarios included in this project correspond to various CO 2 emission reduction targets for the iron and steel sector under different strategies such as simple CO 2 emission caps (e.g., specific reduction goals), emission reduction via commodity trading, and emission reduction via carbon trading.« less

Modeling and control of flexible structures

NASA Technical Reports Server (NTRS)

Gibson, J. S.; Mingori, D. L.

1988-01-01

This monograph presents integrated modeling and controller design methods for flexible structures. The controllers, or compensators, developed are optimal in the linear-quadratic-Gaussian sense. The performance objectives, sensor and actuator locations and external disturbances influence both the construction of the model and the design of the finite dimensional compensator. The modeling and controller design procedures are carried out in parallel to ensure compatibility of these two aspects of the design problem. Model reduction techniques are introduced to keep both the model order and the controller order as small as possible. A linear distributed, or infinite dimensional, model is the theoretical basis for most of the text, but finite dimensional models arising from both lumped-mass and finite element approximations also play an important role. A central purpose of the approach here is to approximate an optimal infinite dimensional controller with an implementable finite dimensional compensator. Both convergence theory and numerical approximation methods are given. Simple examples are used to illustrate the theory.

Practical recipes for the model order reduction, dynamical simulation and compressive sampling of large-scale open quantum systems

NASA Astrophysics Data System (ADS)

Sidles, John A.; Garbini, Joseph L.; Harrell, Lee E.; Hero, Alfred O.; Jacky, Jonathan P.; Malcomb, Joseph R.; Norman, Anthony G.; Williamson, Austin M.

2009-06-01

Practical recipes are presented for simulating high-temperature and nonequilibrium quantum spin systems that are continuously measured and controlled. The notion of a spin system is broadly conceived, in order to encompass macroscopic test masses as the limiting case of large-j spins. The simulation technique has three stages: first the deliberate introduction of noise into the simulation, then the conversion of that noise into an equivalent continuous measurement and control process, and finally, projection of the trajectory onto state-space manifolds having reduced dimensionality and possessing a Kähler potential of multilinear algebraic form. These state-spaces can be regarded as ruled algebraic varieties upon which a projective quantum model order reduction (MOR) is performed. The Riemannian sectional curvature of ruled Kählerian varieties is analyzed, and proved to be non-positive upon all sections that contain a rule. These manifolds are shown to contain Slater determinants as a special case and their identity with Grassmannian varieties is demonstrated. The resulting simulation formalism is used to construct a positive P-representation for the thermal density matrix. Single-spin detection by magnetic resonance force microscopy (MRFM) is simulated, and the data statistics are shown to be those of a random telegraph signal with additive white noise. Larger-scale spin-dust models are simulated, having no spatial symmetry and no spatial ordering; the high-fidelity projection of numerically computed quantum trajectories onto low dimensionality Kähler state-space manifolds is demonstrated. The reconstruction of quantum trajectories from sparse random projections is demonstrated, the onset of Donoho-Stodden breakdown at the Candès-Tao sparsity limit is observed, a deterministic construction for sampling matrices is given and methods for quantum state optimization by Dantzig selection are given.

Evaluation of Airframe Noise Reduction Concepts via Simulations Using a Lattice Boltzmann Approach

NASA Technical Reports Server (NTRS)

Fares, Ehab; Casalino, Damiano; Khorrami, Mehdi R.

2015-01-01

Unsteady computations are presented for a high-fidelity, 18% scale, semi-span Gulfstream aircraft model in landing configuration, i.e. flap deflected at 39 degree and main landing gear deployed. The simulations employ the lattice Boltzmann solver PowerFLOW® to simultaneously capture the flow physics and acoustics in the near field. Sound propagation to the far field is obtained using a Ffowcs Williams and Hawkings acoustic analogy approach. In addition to the baseline geometry, which was presented previously, various noise reduction concepts for the flap and main landing gear are simulated. In particular, care is taken to fully resolve the complex geometrical details associated with these concepts in order to capture the resulting intricate local flow field thus enabling accurate prediction of their acoustic behavior. To determine aeroacoustic performance, the farfield noise predicted with the concepts applied is compared to high-fidelity simulations of the untreated baseline configurations. To assess the accuracy of the computed results, the aerodynamic and aeroacoustic impact of the noise reduction concepts is evaluated numerically and compared to experimental results for the same model. The trends and effectiveness of the simulated noise reduction concepts compare well with measured values and demonstrate that the computational approach is capable of capturing the primary effects of the acoustic treatment on a full aircraft model.

Antipathogen genes and the replacement of disease-vectoring mosquito populations: a model-based evaluation

PubMed Central

Robert, Michael A; Okamoto, Kenichi W; Gould, Fred; Lloyd, Alun L

2014-01-01

Recently, genetic strategies aimed at controlling populations of disease-vectoring mosquitoes have received considerable attention as alternatives to traditional measures. Theoretical studies have shown that female-killing (FK), antipathogen (AP), and reduce and replace (R&R) strategies can each decrease the number competent vectors. In this study, we utilize a mathematical model to evaluate impacts on competent Aedes aegypti populations of FK, AP, and R&R releases as well as hybrid strategies that result from combinations of these three approaches. We show that while the ordering of efficacy of these strategies depends upon population life history parameters, sex ratio of releases, and switch time in combination strategies, AP-only and R&R/AP releases typically lead to the greatest long-term reduction in competent vectors. R&R-only releases are often less effective at long-term reduction of competent vectors than AP-only releases or R&R/AP releases. Furthermore, the reduction in competent vectors caused by AP-only releases is easier to maintain than that caused by FK-only or R&R-only releases even when the AP gene confers a fitness cost. We discuss the roles that density dependence and inclusion of females play in the order of efficacy of the strategies. We anticipate that our results will provide added impetus to continue developing AP strategies. PMID:25558284

Geometry-dependent viscosity reduction in sheared active fluids

NASA Astrophysics Data System (ADS)

Słomka, Jonasz; Dunkel, Jörn

2017-04-01

We investigate flow pattern formation and viscosity reduction mechanisms in active fluids by studying a generalized Navier-Stokes model that captures the experimentally observed bulk vortex dynamics in microbial suspensions. We present exact analytical solutions including stress-free vortex lattices and introduce a computational framework that allows the efficient treatment of higher-order shear boundary conditions. Large-scale parameter scans identify the conditions for spontaneous flow symmetry breaking, geometry-dependent viscosity reduction, and negative-viscosity states amenable to energy harvesting in confined suspensions. The theory uses only generic assumptions about the symmetries and long-wavelength structure of active stress tensors, suggesting that inviscid phases may be achievable in a broad class of nonequilibrium fluids by tuning confinement geometry and pattern scale selection.

Hydrological modelling in a drinking water catchment area as a means of evaluating pathogen risk reduction

NASA Astrophysics Data System (ADS)

Bergion, Viktor; Sokolova, Ekaterina; Åström, Johan; Lindhe, Andreas; Sörén, Kaisa; Rosén, Lars

2017-01-01

Waterborne outbreaks of gastrointestinal diseases are of great concern to drinking water producers and can give rise to substantial costs to the society. The World Health Organisation promotes an approach where the emphasis is on mitigating risks close to the contamination source. In order to handle microbial risks efficiently, there is a need for systematic risk management. In this paper we present a framework for microbial risk management of drinking water systems. The framework incorporates cost-benefit analysis as a decision support method. The hydrological Soil and Water Assessment Tool (SWAT) model, which was set up for the Stäket catchment area in Sweden, was used to simulate the effects of four different mitigation measures on microbial concentrations. The modelling results showed that the two mitigation measures that resulted in a significant (p < 0.05) reduction of Cryptosporidium spp. and Escherichia coli concentrations were a vegetative filter strip linked to cropland and improved treatment (by one Log10 unit) at the wastewater treatment plants. The mitigation measure with a vegetative filter strip linked to grazing areas resulted in a significant reduction of Cryptosporidium spp., but not of E. coli concentrations. The mitigation measure with enhancing the removal efficiency of all on-site wastewater treatment systems (total removal of 2 Log10 units) did not achieve any significant reduction of E. coli or Cryptosporidium spp. concentrations. The SWAT model was useful when characterising the effect of different mitigation measures on microbial concentrations. Hydrological modelling implemented within an appropriate risk management framework is a key decision support element as it identifies the most efficient alternative for microbial risk reduction.

Projected Impact of Mexico's Sugar-Sweetened Beverage Tax Policy on Diabetes and Cardiovascular Disease: A Modeling Study.

PubMed

Sánchez-Romero, Luz Maria; Penko, Joanne; Coxson, Pamela G; Fernández, Alicia; Mason, Antoinette; Moran, Andrew E; Ávila-Burgos, Leticia; Odden, Michelle; Barquera, Simón; Bibbins-Domingo, Kirsten

2016-11-01

Rates of diabetes in Mexico are among the highest worldwide. In 2014, Mexico instituted a nationwide tax on sugar-sweetened beverages (SSBs) in order to reduce the high level of SSB consumption, a preventable cause of diabetes and cardiovascular disease (CVD). We used an established computer simulation model of CVD and country-specific data on demographics, epidemiology, SSB consumption, and short-term changes in consumption following the SSB tax in order to project potential long-range health and economic impacts of SSB taxation in Mexico. We used the Cardiovascular Disease Policy Model-Mexico, a state transition model of Mexican adults aged 35-94 y, to project the potential future effects of reduced SSB intake on diabetes incidence, CVD events, direct diabetes healthcare costs, and mortality over 10 y. Model inputs included short-term changes in SSB consumption in response to taxation (price elasticity) and data from government and market research surveys and public healthcare institutions. Two main scenarios were modeled: a 10% reduction in SSB consumption (corresponding to the reduction observed after tax implementation) and a 20% reduction in SSB consumption (possible with increases in taxation levels and/or additional measures to curb consumption). Given uncertainty about the degree to which Mexicans will replace calories from SSBs with calories from other sources, we evaluated a range of values for calorie compensation. We projected that a 10% reduction in SSB consumption with 39% calorie compensation among Mexican adults would result in about 189,300 (95% uncertainty interval [UI] 155,400-218,100) fewer incident type 2 diabetes cases, 20,400 fewer incident strokes and myocardial infarctions, and 18,900 fewer deaths occurring from 2013 to 2022. This scenario predicts that the SSB tax could save Mexico 983 million international dollars (95% UI $769 million-$1,173 million). The largest relative and absolute reductions in diabetes and CVD events occurred in the youngest age group modeled (35-44 y). This study's strengths include the use of an established mathematical model of CVD and use of contemporary Mexican vital statistics, data from health surveys, healthcare costs, and SSB price elasticity estimates as well as probabilistic and deterministic sensitivity analyses to account for uncertainty. The limitations of the study include reliance on US-based studies for certain inputs where Mexico-specific data were lacking (specifically the associations between risk factors and CVD outcomes [from the Framingham Heart Study] and SSB calorie compensation assumptions), limited data on healthcare costs other than those related to diabetes, and lack of information on long-term SSB price elasticity that is specific to geographic and economic subgroups. Mexico's high diabetes prevalence represents a public health crisis. While the long-term impact of Mexico's SSB tax is not yet known, these projections, based on observed consumption reductions, suggest that Mexico's SSB tax may substantially decrease morbidity and mortality from diabetes and CVD while reducing healthcare costs.

Assessing the interaction between mountain forests and snow avalanches at Nevados de Chillán, Chile and its implications for ecosystem-based disaster risk reduction

NASA Astrophysics Data System (ADS)

Casteller, Alejandro; Häfelfinger, Thomas; Cortés Donoso, Erika; Podvin, Karen; Kulakowski, Dominik; Bebi, Peter

2018-04-01

Gravitational natural hazards such as snow avalanches, rockfalls, shallow landslides and volcanic activity represent a risk to mountain communities around the world. In particular, where documentary records about these processes are rare, decisions on risk management and land-use planning have to be based on a variety of other sources including vegetation, tree-ring data and natural hazard process models. We used a combination of these methods in order to evaluate dynamics of natural hazards with a focus on snow avalanches at Valle Las Trancas, in the Biobío region in Chile. Along this valley, natural hazards threaten not only the local human population, but also the numerous tourists attracted by outdoor recreational activities. Given the regional scarcity of documentary records, tree-ring methods were applied in order to reconstruct the local history of snow avalanches and debris flow events, which are the most important weather-related processes at respective tracks. A recent version of the model Rapid Mass MovementS (RAMMS), which includes influences of forest structure, was used to calculate different avalanche parameters such as runout distances and maximum pressures, taking into consideration the presence or absence of forest along the tracks as well as different modeled return periods. Our results show that local Nothofagus broadleaf forests contribute to a reduction of avalanche runout distances as well as impact pressure on present infrastructure, thus constituting a valuable ecosystem disaster risk reduction measure that can substitute or complement other traditional measures such as snow sheds.

Optimal sensor placement for control of a supersonic mixed-compression inlet with variable geometry

NASA Astrophysics Data System (ADS)

Moore, Kenneth Thomas

A method of using fluid dynamics models for the generation of models that are useable for control design and analysis is investigated. The problem considered is the control of the normal shock location in the VDC inlet, which is a mixed-compression, supersonic, variable-geometry inlet of a jet engine. A quasi-one-dimensional set of fluid equations incorporating bleed and moving walls is developed. An object-oriented environment is developed for simulation of flow systems under closed-loop control. A public interface between the controller and fluid classes is defined. A linear model representing the dynamics of the VDC inlet is developed from the finite difference equations, and its eigenstructure is analyzed. The order of this model is reduced using the square root balanced model reduction method to produce a reduced-order linear model that is suitable for control design and analysis tasks. A modification to this method that improves the accuracy of the reduced-order linear model for the purpose of sensor placement is presented and analyzed. The reduced-order linear model is used to develop a sensor placement method that quantifies as a function of the sensor location the ability of a sensor to provide information on the variable of interest for control. This method is used to develop a sensor placement metric for the VDC inlet. The reduced-order linear model is also used to design a closed loop control system to control the shock position in the VDC inlet. The object-oriented simulation code is used to simulate the nonlinear fluid equations under closed-loop control.

Model reduction of the numerical analysis of Low Impact Developments techniques

NASA Astrophysics Data System (ADS)

Brunetti, Giuseppe; Šimůnek, Jirka; Wöhling, Thomas; Piro, Patrizia

2017-04-01

Mechanistic models have proven to be accurate and reliable tools for the numerical analysis of the hydrological behavior of Low Impact Development (LIDs) techniques. However, their widespread adoption is limited by their complexity and computational cost. Recent studies have tried to address this issue by investigating the application of new techniques, such as surrogate-based modeling. However, current results are still limited and fragmented. One of such approaches, the Model Order Reduction (MOR) technique, can represent a valuable tool for reducing the computational complexity of a numerical problems by computing an approximation of the original model. While this technique has been extensively used in water-related problems, no studies have evaluated its use in LIDs modeling. Thus, the main aim of this study is to apply the MOR technique for the development of a reduced order model (ROM) for the numerical analysis of the hydrologic behavior of LIDs, in particular green roofs. The model should be able to correctly reproduce all the hydrological processes of a green roof while reducing the computational cost. The proposed model decouples the subsurface water dynamic of a green roof in a) one-dimensional (1D) vertical flow through a green roof itself and b) one-dimensional saturated lateral flow along the impervious rooftop. The green roof is horizontally discretized in N elements. Each element represents a vertical domain, which can have different properties or boundary conditions. The 1D Richards equation is used to simulate flow in the substrate and drainage layers. Simulated outflow from the vertical domain is used as a recharge term for saturated lateral flow, which is described using the kinematic wave approximation of the Boussinesq equation. The proposed model has been compared with the mechanistic model HYDRUS-2D, which numerically solves the Richards equation for the whole domain. The HYDRUS-1D code has been used for the description of vertical flow, while a Finite Volume Scheme has been adopted for lateral flow. Two scenarios involving flat and steep green roofs were analyzed. Results confirmed the accuracy of the reduced order model, which was able to reproduce both subsurface outflow and the moisture distribution in the green roof, significantly reducing the computational cost.

An adaptive algorithm for the detection of microcalcifications in simulated low-dose mammography.

PubMed

Treiber, O; Wanninger, F; Führ, H; Panzer, W; Regulla, D; Winkler, G

2003-02-21

This paper uses the task of microcalcification detection as a benchmark problem to assess the potential for dose reduction in x-ray mammography. We present the results of a newly developed algorithm for detection of microcalcifications as a case study for a typical commercial film-screen system (Kodak Min-R 2000/2190). The first part of the paper deals with the simulation of dose reduction for film-screen mammography based on a physical model of the imaging process. Use of a more sensitive film-screen system is expected to result in additional smoothing of the image. We introduce two different models of that behaviour, called moderate and strong smoothing. We then present an adaptive, model-based microcalcification detection algorithm. Comparing detection results with ground-truth images obtained under the supervision of an expert radiologist allows us to establish the soundness of the detection algorithm. We measure the performance on the dose-reduced images in order to assess the loss of information due to dose reduction. It turns out that the smoothing behaviour has a strong influence on detection rates. For moderate smoothing. a dose reduction by 25% has no serious influence on the detection results. whereas a dose reduction by 50% already entails a marked deterioration of the performance. Strong smoothing generally leads to an unacceptable loss of image quality. The test results emphasize the impact of the more sensitive film-screen system and its characteristics on the problem of assessing the potential for dose reduction in film-screen mammography. The general approach presented in the paper can be adapted to fully digital mammography.

An adaptive algorithm for the detection of microcalcifications in simulated low-dose mammography

NASA Astrophysics Data System (ADS)

Treiber, O.; Wanninger, F.; Führ, H.; Panzer, W.; Regulla, D.; Winkler, G.

2003-02-01

This paper uses the task of microcalcification detection as a benchmark problem to assess the potential for dose reduction in x-ray mammography. We present the results of a newly developed algorithm for detection of microcalcifications as a case study for a typical commercial film-screen system (Kodak Min-R 2000/2190). The first part of the paper deals with the simulation of dose reduction for film-screen mammography based on a physical model of the imaging process. Use of a more sensitive film-screen system is expected to result in additional smoothing of the image. We introduce two different models of that behaviour, called moderate and strong smoothing. We then present an adaptive, model-based microcalcification detection algorithm. Comparing detection results with ground-truth images obtained under the supervision of an expert radiologist allows us to establish the soundness of the detection algorithm. We measure the performance on the dose-reduced images in order to assess the loss of information due to dose reduction. It turns out that the smoothing behaviour has a strong influence on detection rates. For moderate smoothing, a dose reduction by 25% has no serious influence on the detection results, whereas a dose reduction by 50% already entails a marked deterioration of the performance. Strong smoothing generally leads to an unacceptable loss of image quality. The test results emphasize the impact of the more sensitive film-screen system and its characteristics on the problem of assessing the potential for dose reduction in film-screen mammography. The general approach presented in the paper can be adapted to fully digital mammography.

Determination of thermal inactivation kinetics of hepatitis A virus in blue mussel (Mytilus edulis) homogenate.

PubMed

Bozkurt, Hayriye; D'Souza, Doris H; Davidson, P Michael

2014-05-01

Hepatitis A virus (HAV) is a food-borne enteric virus responsible for outbreaks of hepatitis associated with shellfish consumption. The objectives of this study were to determine the thermal inactivation behavior of HAV in blue mussels, to compare the first-order and Weibull models to describe the data, to calculate Arrhenius activation energy for each model, and to evaluate model efficiency by using selected statistical criteria. The times required to reduce the population by 1 log cycle (D-values) calculated from the first-order model (50 to 72°C) ranged from 1.07 to 54.17 min for HAV. Using the Weibull model, the times required to destroy 1 log unit (tD = 1) of HAV at the same temperatures were 1.57 to 37.91 min. At 72°C, the treatment times required to achieve a 6-log reduction were 7.49 min for the first-order model and 8.47 min for the Weibull model. The z-values (changes in temperature required for a 90% change in the log D-values) calculated for HAV were 15.88 ± 3.97°C (R(2), 0.94) with the Weibull model and 12.97 ± 0.59°C (R(2), 0.93) with the first-order model. The calculated activation energies for the first-order model and the Weibull model were 165 and 153 kJ/mol, respectively. The results revealed that the Weibull model was more appropriate for representing the thermal inactivation behavior of HAV in blue mussels. Correct understanding of the thermal inactivation behavior of HAV could allow precise determination of the thermal process conditions to prevent food-borne viral outbreaks associated with the consumption of contaminated mussels.

Reductive dehalogenation of endosulfan by cast iron: Kinetics, pathways and modeling.

PubMed

Lama, Yangdup; Sinha, Alok; Singh, Gurdeep; Masto, Reginald E

2016-05-01

Cast iron has been a material of choice for in-situ remediation of groundwater. In this study interaction of endosulfan with High Carbon Iron Filings (HCIF) was studied in batch reactors. Decline in total concentration (Ct) could be related to aqueous concentration (Ca) by equation dCt/dt = k1.M.Ca(n), where reaction rate constant (k1) and order (n) were found to be 1.246 × 10(-4) L g(-1) iron h(-1) and 1.47, respectively. Partitioning of endosulfan to HCIF could be explained by Freundlich isotherm. The process of simultaneous reductive dehalogenation and adsorption/desorption was successfully modelled. The reductive dehalogenation of endosulfan resulted in by-products identified as [(3a, alpha,7beta,7a alpha,8s)-4,5,6,7,8 Pentachloro 3a,4,7,7a-tetrahydro] (C9H3Cl5O3) and Benzofuran,4,5,7-trichloro-2,3-dihydro-2-methyl (C9H7Cl3O). Copyright © 2015 Elsevier Ltd. All rights reserved.

Revised estimates for ozone reduction by shuttle operation

NASA Technical Reports Server (NTRS)

Potter, A. E.

1978-01-01

Previous calculations by five different modeling groups of the effect of space shuttle operations on the ozone layer yielded an estimate of 0.2 percent ozone reduction for the Northern Hemisphere at 60 launches per year. Since these calculations were made, the accepted rate constant for the reaction between hydroperoxyl and nitric oxide to yield hydroxyl and nitrogen dioxide, HO2 + NO yields OH + NO2, was revised upward by more than an order of magnitude, with a resultant increase in the predicted ozone reduction for chlorofluoromethanes by a factor of approximately 2. New calculations of the shuttle effect were made with use of the new rate constant data, again by five different modeling groups. The new value of the shuttle effect on the ozone layer was found to be 0.25 percent. The increase resulting from the revised rate constant is considerably less for space shuttle operations than for chlorofluoromethane production, because the new rate constant also increases the calculated rate of downward transport of shuttle exhaust products out of the stratosphere.

Spatiotemporal control to eliminate cardiac alternans using isostable reduction

NASA Astrophysics Data System (ADS)

Wilson, Dan; Moehlis, Jeff

2017-03-01

Cardiac alternans, an arrhythmia characterized by a beat-to-beat alternation of cardiac action potential durations, is widely believed to facilitate the transition from normal cardiac function to ventricular fibrillation and sudden cardiac death. Alternans arises due to an instability of a healthy period-1 rhythm, and most dynamical control strategies either require extensive knowledge of the cardiac system, making experimental validation difficult, or are model independent and sacrifice important information about the specific system under study. Isostable reduction provides an alternative approach, in which the response of a system to external perturbations can be used to reduce the complexity of a cardiac system, making it easier to work with from an analytical perspective while retaining many of its important features. Here, we use isostable reduction strategies to reduce the complexity of partial differential equation models of cardiac systems in order to develop energy optimal strategies for the elimination of alternans. Resulting control strategies require significantly less energy to terminate alternans than comparable strategies and do not require continuous state feedback.

Simplifying silicon burning: Application of quasi-equilibrium to (alpha) network nucleosynthesis

NASA Technical Reports Server (NTRS)

Hix, W. R.; Thielemann, F.-K.; Khokhlov, A. M.; Wheeler, J. C.

1997-01-01

While the need for accurate calculation of nucleosynthesis and the resulting rate of thermonuclear energy release within hydrodynamic models of stars and supernovae is clear, the computational expense of these nucleosynthesis calculations often force a compromise in accuracy to reduce the computational cost. To redress this trade-off of accuracy for speed, the authors present an improved nuclear network which takes advantage of quasi- equilibrium in order to reduce the number of independent nuclei, and hence the computational cost of nucleosynthesis, without significant reduction in accuracy. In this paper they will discuss the first application of this method, the further reduction in size of the minimal alpha network. The resultant QSE- reduced alpha network is twice as fast as the conventional alpha network it replaces and requires the tracking of half as many abundance variables, while accurately estimating the rate of energy generation. Such reduction in cost is particularly necessary for future generation of multi-dimensional models for supernovae.

A dynamic modelling framework towards the solution of reduction in smoking prevalence

NASA Astrophysics Data System (ADS)

Halim, Tisya Farida Abdul; Sapiri, Hasimah; Abidin, Norhaslinda Zainal

2016-10-01

This paper presents a hypothetical framework towards the solution for reduction in smoking prevalence in Malaysia. The framework is design to assist in decision making process related to reduction in smoking prevalence using SD and OCT. In general, this framework is developed using SD approach where OCT is embedded in the policy evaluation process. Smoking prevalence is one of the determinant which plays an important role in measuring a successful implementation of anti-smoking strategies. Therefore, it is critical to determine the optimal value of smoking prevalence in order to trim down the hazardous effects of smoking to society. Conversely, smoking problem becomes increasingly complex since many issues that ranged from behavioral to economical need to be considered simultaneously. Thus, a hypothetical framework of the control model embedded in the SD methodology is expected to obtain the minimum value of smoking prevalence which the output in turn will provide a guideline for tobacco researchers as well as decision makers for policy design and evaluation.

Civil helicopter noise assessment study Boeing-Vertol model 347. [recommendations for reduction of helicopter noise levels

NASA Technical Reports Server (NTRS)

Hinterkeuser, E. G.; Sternfeld, H., Jr.

1974-01-01

A study was conducted to forecast the noise restrictions which may be imposed on civil transport helicopters in the 1975-1985 time period. Certification and community acceptance criteria were predicted. A 50 passenger tandem rotor helicopter based on the Boeing-Vertol Model 347 was studied to determine the noise reductions required, and the means of achieving them. Some of the important study recommendations are: (1) certification limits should be equivalent to 95 EPNdb at data points located at 500 feet to each side of the touchdown/takeoff point, and 1000 feet from this point directly under the approach and departure flight path. (2) community acceptance should be measured as Equivalent Noise Level (Leq), based on dBA, with separate limits for day and night operations, and (3) in order to comply with the above guidelines, the Model 347 helicopter will require studies and tests leading to several modifications.

On the competing affects of shear heating and grainsize reduction in lithospheric shear zone formation

NASA Astrophysics Data System (ADS)

Foley, B. J.

2017-12-01

Grain-size reduction is thought to play an important role in shear localization within the lithosphere, as mylonites are commonly seen in regions that have undergone intense deformation. However, flow in lithospheric shear zones can also cause heating due to the energy dissipated by deformation. As grain growth is strongly enhanced by warmer temperatures, shear heating may impede grainsize reduction and the formation of mylonite zones. I use models of simple shear, with length-scales representative of lithospheric shear zones and plate boundaries, including shear heating and grainsize evolution. Grain-damage theory is used to represent the evolution of grainsize. The models are used to determine conditions where grainsize reduction dominates versus those where shear heating dominates; if grainsize reduction dominates, then heating is held in check by the drop in viscosity brought about by small grains. On the other hand, if heating dominates then grain-reduction is prevented by fast grain-growth rates. From the numerical models, simple scaling laws are developed that give the stready-state grainsize and temperature rise as a function of strain-rate, background temperature, and parameters for grain-growth and grain-reduction. I find that for parameter ranges constrained by field observations of shear zones and rock deformation experiments, grainsize reduction dominated over shear heating. Very high strain-rates or driving stresses, above what is typically expected in natural shear zones, are needed for shear heating to dominate over grainsize reduction. Also explored is the timescale to reach steady-state grainsize and temperature conditions in a shear zone. For realistic driving stress or strain-rate, timescales to reach steady-state are often very long, on the order of hundreds of millions of years or longer. This might indicate that natural shear zones do not reach steady-state, or that additional processes are important in initiating lithospheric shear localization.

Characterization of Regular Wave, Irregular Wave, and Large-Amplitude Wave Group Kinematics in an Experimental Basin

DTIC Science & Technology

2011-02-01

seakeeping was the transient wave technique, developed analytically by Davis and Zarnick (1964). At the David Taylor Model Basin, Davis and Zarnick, and...Gersten and Johnson (1969) applied the transient wave technique to regular wave model experiments for heave and pitch, at zero forward speed. These...tests demonstrated a potential reduction by an order of magnitude of the total necessary testing time. The transient wave technique was also applied to

Simulation and evaluation of pollution load reduction scenarios for water environmental management: a case study of inflow river of Taihu Lake, China.

PubMed

Zhang, Ruibin; Qian, Xin; Zhu, Wenting; Gao, Hailong; Hu, Wei; Wang, Jinhua

2014-09-09

In the beginning of the 21st century, the deterioration of water quality in Taihu Lake, China, has caused widespread concern. The primary source of pollution in Taihu Lake is river inflows. Effective pollution load reduction scenarios need to be implemented in these rivers in order to improve the water quality of Taihu Lake. It is important to select appropriate pollution load reduction scenarios for achieving particular goals. The aim of this study was to facilitate the selection of appropriate scenarios. The QUAL2K model for river water quality was used to simulate the effects of a range of pollution load reduction scenarios in the Wujin River, which is one of the major inflow rivers of Taihu Lake. The model was calibrated for the year 2010 and validated for the year 2011. Various pollution load reduction scenarios were assessed using an analytic hierarchy process, and increasing rates of evaluation indicators were predicted using the Delphi method. The results showed that control of pollution from the source is the optimal method for pollution prevention and control, and the method of "Treatment after Pollution" has bad environmental, social and ecological effects. The method applied in this study can assist for environmental managers to select suitable pollution load reduction scenarios for achieving various objectives.

Simulation and Evaluation of Pollution Load Reduction Scenarios for Water Environmental Management: A Case Study of Inflow River of Taihu Lake, China

PubMed Central

Zhang, Ruibin; Qian, Xin; Zhu, Wenting; Gao, Hailong; Hu, Wei; Wang, Jinhua

2014-01-01

In the beginning of the 21st century, the deterioration of water quality in Taihu Lake, China, has caused widespread concern. The primary source of pollution in Taihu Lake is river inflows. Effective pollution load reduction scenarios need to be implemented in these rivers in order to improve the water quality of Taihu Lake. It is important to select appropriate pollution load reduction scenarios for achieving particular goals. The aim of this study was to facilitate the selection of appropriate scenarios. The QUAL2K model for river water quality was used to simulate the effects of a range of pollution load reduction scenarios in the Wujin River, which is one of the major inflow rivers of Taihu Lake. The model was calibrated for the year 2010 and validated for the year 2011. Various pollution load reduction scenarios were assessed using an analytic hierarchy process, and increasing rates of evaluation indicators were predicted using the Delphi method. The results showed that control of pollution from the source is the optimal method for pollution prevention and control, and the method of “Treatment after Pollution” has bad environmental, social and ecological effects. The method applied in this study can assist for environmental managers to select suitable pollution load reduction scenarios for achieving various objectives. PMID:25207492

Optimal aeroassisted coplanar orbital transfer using an energy model

NASA Technical Reports Server (NTRS)

Halyo, Nesim; Taylor, Deborah B.

1989-01-01

The atmospheric portion of the trajectories for the aeroassisted coplanar orbit transfer was investigated. The equations of motion for the problem are expressed using reduced order model and total vehicle energy, kinetic plus potential, as the independent variable rather than time. The order reduction is achieved analytically without an approximation of the vehicle dynamics. In this model, the problem of coplanar orbit transfer is seen as one in which a given amount of energy must be transferred from the vehicle to the atmosphere during the trajectory without overheating the vehicle. An optimal control problem is posed where a linear combination of the integrated square of the heating rate and the vehicle drag is the cost function to be minimized. The necessary conditions for optimality are obtained. These result in a 4th order two-point-boundary-value problem. A parametric study of the optimal guidance trajectory in which the proportion of the heating rate term versus the drag varies is made. Simulations of the guidance trajectories are presented.

Microbially Mediated Kinetic Sulfur Isotope Fractionation: Reactive Transport Modeling Benchmark

NASA Astrophysics Data System (ADS)

Wanner, C.; Druhan, J. L.; Cheng, Y.; Amos, R. T.; Steefel, C. I.; Ajo Franklin, J. B.

2014-12-01

Microbially mediated sulfate reduction is a ubiquitous process in many subsurface systems. Isotopic fractionation is characteristic of this anaerobic process, since sulfate reducing bacteria (SRB) favor the reduction of the lighter sulfate isotopologue (S32O42-) over the heavier isotopologue (S34O42-). Detection of isotopic shifts have been utilized as a proxy for the onset of sulfate reduction in subsurface systems such as oil reservoirs and aquifers undergoing uranium bioremediation. Reactive transport modeling (RTM) of kinetic sulfur isotope fractionation has been applied to field and laboratory studies. These RTM approaches employ different mathematical formulations in the representation of kinetic sulfur isotope fractionation. In order to test the various formulations, we propose a benchmark problem set for the simulation of kinetic sulfur isotope fractionation during microbially mediated sulfate reduction. The benchmark problem set is comprised of four problem levels and is based on a recent laboratory column experimental study of sulfur isotope fractionation. Pertinent processes impacting sulfur isotopic composition such as microbial sulfate reduction and dispersion are included in the problem set. To date, participating RTM codes are: CRUNCHTOPE, TOUGHREACT, MIN3P and THE GEOCHEMIST'S WORKBENCH. Preliminary results from various codes show reasonable agreement for the problem levels simulating sulfur isotope fractionation in 1D.

Computer-Aided Engineering for Electric-Drive Vehicle Batteries (CAEBAT) |

Science.gov Websites

Battery Cell under Quasi-Static Indentation Tests," J. Power Sources, Submitted. J. Marcicki -Ion Cell under Mechanical Abuse," J. Power Sources, 290, p. 102-113 (2015). http://dx.doi.org Model Order Reduction," J. Power Sources, 273(1), p.1226-1236 (2015). http://dx.doi.org/10.1016

Reduction method with system analysis for multiobjective optimization-based design

NASA Technical Reports Server (NTRS)

Azarm, S.; Sobieszczanski-Sobieski, J.

1993-01-01

An approach for reducing the number of variables and constraints, which is combined with System Analysis Equations (SAE), for multiobjective optimization-based design is presented. In order to develop a simplified analysis model, the SAE is computed outside an optimization loop and then approximated for use by an operator. Two examples are presented to demonstrate the approach.

Simulation of nitrate reduction in groundwater - An upscaling approach from small catchments to the Baltic Sea basin

NASA Astrophysics Data System (ADS)

Hansen, A. L.; Donnelly, C.; Refsgaard, J. C.; Karlsson, I. B.

2018-01-01

This paper describes a modeling approach proposed to simulate the impact of local-scale, spatially targeted N-mitigation measures for the Baltic Sea Basin. Spatially targeted N-regulations aim at exploiting the considerable spatial differences in the natural N-reduction taking place in groundwater and surface water. While such measures can be simulated using local-scale physically-based catchment models, use of such detailed models for the 1.8 million km2 Baltic Sea basin is not feasible due to constraints on input data and computing power. Large-scale models that are able to simulate the Baltic Sea basin, on the other hand, do not have adequate spatial resolution to simulate some of the field-scale measures. Our methodology combines knowledge and results from two local-scale physically-based MIKE SHE catchment models, the large-scale and more conceptual E-HYPE model, and auxiliary data in order to enable E-HYPE to simulate how spatially targeted regulation of agricultural practices may affect N-loads to the Baltic Sea. We conclude that the use of E-HYPE with this upscaling methodology enables the simulation of the impact on N-loads of applying a spatially targeted regulation at the Baltic Sea basin scale to the correct order-of-magnitude. The E-HYPE model together with the upscaling methodology therefore provides a sound basis for large-scale policy analysis; however, we do not expect it to be sufficiently accurate to be useful for the detailed design of local-scale measures.

A study of low cost approaches to scientific experiment implementation for shuttle launched and serviced automated spacecraft

NASA Technical Reports Server (NTRS)

1975-01-01

Cost reductions that can be obtained in experiment instrumentation by the use of standardized electronics and by the relaxation of instrument reliability requirements are studied. The feasibility of using standardized equipment for experiment instrumentation is assessed and a system design approach that most effectively incorporates standardized equipment is developed. The level and form of modularization that is appropriate for the standardized equipment is determined. Mission assurance aspects of instrument development are examined to determine the cost reductions that might be derived from the relaxation of reliability requirements and to formulate a systematic approach to the optimization of mission assurance cost reductions. The results of the analyses are applied to a representative model HEAO payload in order to provide a concrete example of the cost reductions that can be achieved by a standardized approach to the instrument electronics.

Theoretical calculation on ICI reduction using digital coherent superposition of optical OFDM subcarrier pairs in the presence of laser phase noise.

PubMed

Yi, Xingwen; Xu, Bo; Zhang, Jing; Lin, Yun; Qiu, Kun

2014-12-15

Digital coherent superposition (DCS) of optical OFDM subcarrier pairs with Hermitian symmetry can reduce the inter-carrier-interference (ICI) noise resulted from phase noise. In this paper, we show two different implementations of DCS-OFDM that have the same performance in the presence of laser phase noise. We complete the theoretical calculation on ICI reduction by using the model of pure Wiener phase noise. By Taylor expansion of the ICI, we show that the ICI power is cancelled to the second order by DCS. The fourth order term is further derived out and only decided by the ratio of laser linewidth to OFDM subcarrier symbol rate, which can greatly simplify the system design. Finally, we verify our theoretical calculations in simulations and use the analytical results to predict the system performance. DCS-OFDM is expected to be beneficial to certain optical fiber transmissions.

Turbulent drag reduction for external flows

NASA Technical Reports Server (NTRS)

Bushnell, D. M.

1985-01-01

A summary of turbulent drag reduction approaches applicable to external flows is given. Because relatively recent and exhaustive reviews exist for laminar flow control and polymer (hydrodynamic) drag reduction, the focus here is upon the emerging areas of nonplanar geometry and large-eddy alteration. Turbulent control techniques for air generally result in modest (but technologically significant) drag reductions (order of 20 percent or less), whereas hydrodynamic approaches can yield drag reductions the order of 70 percent. Suggestions are included for alternative concepts and optimization of existing approaches.

Turbulent drag reduction for external flows

NASA Technical Reports Server (NTRS)

Bushnell, D. M.

1983-01-01

Paper presents a review and summary of turbulent drag reduction approaches applicable to external flows. Because relatively recent and exhaustive reviews exist for laminar flow control and polymer (hydrodynamic) drag reduction, the paper focuses upon the emerging areas of nonplanar geometry and large eddy alteration. Turbulent control techniques for air generally result in modest (but technologically significant) drag reductions (order of 20 percent or less) whereas hydrodynamic approaches can yield drag reductions the order of 70 percent. Paper also includes suggestions for alternative concepts and optimization of existing approaches.

Reducing computation in an i-vector speaker recognition system using a tree-structured universal background model

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

McClanahan, Richard; De Leon, Phillip L.

The majority of state-of-the-art speaker recognition systems (SR) utilize speaker models that are derived from an adapted universal background model (UBM) in the form of a Gaussian mixture model (GMM). This is true for GMM supervector systems, joint factor analysis systems, and most recently i-vector systems. In all of the identified systems, the posterior probabilities and sufficient statistics calculations represent a computational bottleneck in both enrollment and testing. We propose a multi-layered hash system, employing a tree-structured GMM–UBM which uses Runnalls’ Gaussian mixture reduction technique, in order to reduce the number of these calculations. Moreover, with this tree-structured hash, wemore » can trade-off reduction in computation with a corresponding degradation of equal error rate (EER). As an example, we also reduce this computation by a factor of 15× while incurring less than 10% relative degradation of EER (or 0.3% absolute EER) when evaluated with NIST 2010 speaker recognition evaluation (SRE) telephone data.« less

Reducing computation in an i-vector speaker recognition system using a tree-structured universal background model

DOE PAGES

McClanahan, Richard; De Leon, Phillip L.

2014-08-20

The majority of state-of-the-art speaker recognition systems (SR) utilize speaker models that are derived from an adapted universal background model (UBM) in the form of a Gaussian mixture model (GMM). This is true for GMM supervector systems, joint factor analysis systems, and most recently i-vector systems. In all of the identified systems, the posterior probabilities and sufficient statistics calculations represent a computational bottleneck in both enrollment and testing. We propose a multi-layered hash system, employing a tree-structured GMM–UBM which uses Runnalls’ Gaussian mixture reduction technique, in order to reduce the number of these calculations. Moreover, with this tree-structured hash, wemore » can trade-off reduction in computation with a corresponding degradation of equal error rate (EER). As an example, we also reduce this computation by a factor of 15× while incurring less than 10% relative degradation of EER (or 0.3% absolute EER) when evaluated with NIST 2010 speaker recognition evaluation (SRE) telephone data.« less

Equivalent reduced model technique development for nonlinear system dynamic response

NASA Astrophysics Data System (ADS)

Thibault, Louis; Avitabile, Peter; Foley, Jason; Wolfson, Janet

2013-04-01

The dynamic response of structural systems commonly involves nonlinear effects. Often times, structural systems are made up of several components, whose individual behavior is essentially linear compared to the total assembled system. However, the assembly of linear components using highly nonlinear connection elements or contact regions causes the entire system to become nonlinear. Conventional transient nonlinear integration of the equations of motion can be extremely computationally intensive, especially when the finite element models describing the components are very large and detailed. In this work, the equivalent reduced model technique (ERMT) is developed to address complicated nonlinear contact problems. ERMT utilizes a highly accurate model reduction scheme, the System equivalent reduction expansion process (SEREP). Extremely reduced order models that provide dynamic characteristics of linear components, which are interconnected with highly nonlinear connection elements, are formulated with SEREP for the dynamic response evaluation using direct integration techniques. The full-space solution will be compared to the response obtained using drastically reduced models to make evident the usefulness of the technique for a variety of analytical cases.

Impact of stream restoration on flood waves

NASA Astrophysics Data System (ADS)

Sholtes, J.; Doyle, M.

2008-12-01

Restoration of channelized or incised streams has the potential to reduce downstream flooding via storing and dissipating the energy of flood waves. Restoration design elements such as restoring meanders, reducing slope, restoring floodplain connectivity, re-introducing in-channel woody debris, and re-vegetating banks and the floodplain have the capacity to attenuate flood waves via energy dissipation and channel and floodplain storage. Flood discharge hydrographs measured up and downstream of several restored reaches of varying stream order and located in both urban and rural catchments are coupled with direct measurements of stream roughness at various stages to directly measure changes to peak discharge, flood wave celerity, and dispersion. A one-dimensional unsteady flow routing model, HEC-RAS, is calibrated and used to compare attenuation characteristics between pre and post restoration conditions. Modeled sensitivity results indicate that a restoration project placed on a smaller order stream demonstrates the highest relative reduction in peak discharge of routed flood waves compared to one of equal length on a higher order stream. Reductions in bed slope, extensions in channel length, and increases in channel and floodplain roughness follow restoration placement with the watershed in relative importance. By better understanding how design, scale, and location of restored reaches within a catchment hydraulically impact flood flows, this study contributes both to restoration design and site decision making. It also quantifies the effect of reach scale stream restoration on flood wave attenuation.

Significant and Sustained Reduction in Chemotherapy Errors Through Improvement Science.

PubMed

Weiss, Brian D; Scott, Melissa; Demmel, Kathleen; Kotagal, Uma R; Perentesis, John P; Walsh, Kathleen E

2017-04-01

A majority of children with cancer are now cured with highly complex chemotherapy regimens incorporating multiple drugs and demanding monitoring schedules. The risk for error is high, and errors can occur at any stage in the process, from order generation to pharmacy formulation to bedside drug administration. Our objective was to describe a program to eliminate errors in chemotherapy use among children. To increase reporting of chemotherapy errors, we supplemented the hospital reporting system with a new chemotherapy near-miss reporting system. After the model for improvement, we then implemented several interventions, including a daily chemotherapy huddle, improvements to the preparation and delivery of intravenous therapy, headphones for clinicians ordering chemotherapy, and standards for chemotherapy administration throughout the hospital. Twenty-two months into the project, we saw a centerline shift in our U chart of chemotherapy errors that reached the patient from a baseline rate of 3.8 to 1.9 per 1,000 doses. This shift has been sustained for > 4 years. In Poisson regression analyses, we found an initial increase in error rates, followed by a significant decline in errors after 16 months of improvement work ( P < .001). After the model for improvement, our improvement efforts were associated with significant reductions in chemotherapy errors that reached the patient. Key drivers for our success included error vigilance through a huddle, standardization, and minimization of interruptions during ordering.

Cognitive workload reduction in hospital information systems : Decision support for order set optimization.

PubMed

Gartner, Daniel; Zhang, Yiye; Padman, Rema

2018-06-01

Order sets are a critical component in hospital information systems that are expected to substantially reduce physicians' physical and cognitive workload and improve patient safety. Order sets represent time interval-clustered order items, such as medications prescribed at hospital admission, that are administered to patients during their hospital stay. In this paper, we develop a mathematical programming model and an exact and a heuristic solution procedure with the objective of minimizing physicians' cognitive workload associated with prescribing order sets. Furthermore, we provide structural insights into the problem which lead us to a valid lower bound on the order set size. In a case study using order data on Asthma patients with moderate complexity from a major pediatric hospital, we compare the hospital's current solution with the exact and heuristic solutions on a variety of performance metrics. Our computational results confirm our lower bound and reveal that using a time interval decomposition approach substantially reduces computation times for the mathematical program, as does a K -means clustering based decomposition approach which, however, does not guarantee optimality because it violates the lower bound. The results of comparing the mathematical program with the current order set configuration in the hospital indicates that cognitive workload can be reduced by about 20.2% by allowing 1 to 5 order sets, respectively. The comparison of the K -means based decomposition with the hospital's current configuration reveals a cognitive workload reduction of about 19.5%, also by allowing 1 to 5 order sets, respectively. We finally provide a decision support system to help practitioners analyze the current order set configuration, the results of the mathematical program and the heuristic approach.

Reduced-order modeling with sparse polynomial chaos expansion and dimension reduction for evaluating the impact of CO2 and brine leakage on groundwater

NASA Astrophysics Data System (ADS)

Liu, Y.; Zheng, L.; Pau, G. S. H.

2016-12-01

A careful assessment of the risk associated with geologic CO2 storage is critical to the deployment of large-scale storage projects. While numerical modeling is an indispensable tool for risk assessment, there has been increasing need in considering and addressing uncertainties in the numerical models. However, uncertainty analyses have been significantly hindered by the computational complexity of the model. As a remedy, reduced-order models (ROM), which serve as computationally efficient surrogates for high-fidelity models (HFM), have been employed. The ROM is constructed at the expense of an initial set of HFM simulations, and afterwards can be relied upon to predict the model output values at minimal cost. The ROM presented here is part of National Risk Assessment Program (NRAP) and intends to predict the water quality change in groundwater in response to hypothetical CO2 and brine leakage. The HFM based on which the ROM is derived is a multiphase flow and reactive transport model, with 3-D heterogeneous flow field and complex chemical reactions including aqueous complexation, mineral dissolution/precipitation, adsorption/desorption via surface complexation and cation exchange. Reduced-order modeling techniques based on polynomial basis expansion, such as polynomial chaos expansion (PCE), are widely used in the literature. However, the accuracy of such ROMs can be affected by the sparse structure of the coefficients of the expansion. Failing to identify vanishing polynomial coefficients introduces unnecessary sampling errors, the accumulation of which deteriorates the accuracy of the ROMs. To address this issue, we treat the PCE as a sparse Bayesian learning (SBL) problem, and the sparsity is obtained by detecting and including only the non-zero PCE coefficients one at a time by iteratively selecting the most contributing coefficients. The computational complexity due to predicting the entire 3-D concentration fields is further mitigated by a dimension reduction procedure-proper orthogonal decomposition (POD). Our numerical results show that utilizing the sparse structure and POD significantly enhances the accuracy and efficiency of the ROMs, laying the basis for further analyses that necessitate a large number of model simulations.

Proximate and Ultimate Limiting Nutrients in the Mississippi River Plume: Implications for Hypoxia Reduction Through Nutrient Management

NASA Astrophysics Data System (ADS)

Fennel, K.; Laurent, A.

2016-02-01

A large hypoxic area (15,000 km2 on average) forms every summer over the Texas-Louisiana shelf in the northern Gulf of Mexico due to decay of organic matter that is primarily derived from nutrient inputs from the Mississippi/Atchafalaya River System. Efforts are underway to reduce the extent of hypoxic conditions through nutrient management in the watershed; for example, an interagency Hypoxia Task Force is developing Action Plans with input from various stakeholders that set out targets for hypoxia reduction. An open question is by how much nutrient loads would have to be decreased in order to produce the desired reductions in hypoxia and when these would be measurable over natural variability. We have performed a large number of multi-year nutrient load reduction scenarios with a regional biogeochemical model for the region. The model is based on the Regional Ocean Modeling System (ROMS), explicitly includes nitrogen (N) and phosphorus (P) species as inorganic nutrients, and has been shown to realistically reproduce the key processes responsible for hypoxia generation. We have quantified the effects of differential reductions in river N and P loads on hypoxic extent. An assessment of the effects of N versus P reductions is important because, thus far, nutrient management efforts have focused on N, yet P is known to limit primary production in spring and early summer. A debate is ongoing as to whether targets for P reductions should be set and whether nutrient reduction efforts should focus solely on P, which results primarily from urban and industrial point sources and is uncoupled from agricultural fertilizer application. Our results strongly indicate that N is the `ultimate' limiting nutrient to primary production determining the areal extent and duration of hypoxic conditions in a cumulative sense, while P is temporarily limiting in spring. Although reductions in river P load would decrease hypoxic extent in early summer, they would have a much smaller effect than N reductions on the cumulative extent and duration of hypoxic conditions. Combined reductions of N and P have the greatest effect.

Proximate versus ultimate limiting nutrients in the Mississippi River Plume and Implications for Hypoxia Reductions through Nutrient Management

NASA Astrophysics Data System (ADS)

Fennel, Katja; Laurent, Arnaud

2016-04-01

A large hypoxic area (15,000 km2 on average) forms every summer over the Texas-Louisiana shelf in the northern Gulf of Mexico due to decay of organic matter that is primarily derived from nutrient inputs from the Mississippi/Atchafalaya River System. Efforts are underway to reduce the extent of hypoxic conditions through nutrient management in the watershed; for example, an interagency Hypoxia Task Force is developing Action Plans with input from various stakeholders that set out targets for hypoxia reduction. An open question is how far nutrient loads would have to be decreased in order to produce the desired reductions in hypoxia and when these would be measurable given significant natural variability. We have simulated a large number of multi-year nutrient load reduction scenarios with a regional biogeochemical model for the region. The model is based on the Regional Ocean Modeling System (ROMS), explicitly includes nitrogen (N) and phosphorus (P) species as inorganic nutrients, and has been shown to realistically reproduce the key processes responsible for hypoxia generation. We have quantified the effects of differential reductions in river N and P loads on hypoxic extent. An assessment of the effects of N versus P reductions is important because, thus far, nutrient management efforts have focused on N, yet P is known to limit primary production in spring and early summer. A debate is ongoing as to whether targets for P reductions should be set and whether nutrient reduction efforts should focus solely on P, which results primarily from urban and industrial point sources and is uncoupled from agricultural fertilizer application. Our results strongly indicate that N is the 'ultimate' limiting nutrient to primary production determining the areal extent and duration of hypoxic conditions in a cumulative sense, while P is temporarily limiting in spring. Although reductions in river P load would decrease hypoxic extent in early summer, they would have a much smaller effect than N reductions on the cumulative extent and duration of hypoxic conditions. Combined reductions of N and P have the greatest effect.

Magnetic field effect on the structural properties of a peptide model: Molecular dynamics simulation study

NASA Astrophysics Data System (ADS)

Housaindokht, Mohammad Reza; Moosavi, Fatemeh

2018-06-01

The effect of magnetization on the properties of a system containing a peptide model is studied by molecular dynamics simulation at a range of 298-318 K. Two mole fractions of 0.001 and 0.002 of peptide were simulated and the variation of hydrogen bond number, orientational ordering parameter, gyration radius, mean square displacement, as well as radial distribution function, were under consideration. The results show that applying magnetic field will increase the number of hydrogen bonds between water molecules by clustering them and decreases the interaction of water and peptide. This reduction may cause more available free space and enhance the movement of the peptide. As a result, the diffusion coefficient of the peptide becomes greater and its conformation changes. Orientational ordering parameter besides radius of gyration demonstrates that peptide is expanded by static magnetic field and its orientational ordering parameter is affected.

Current status and future trends of SO2 and NOx pollution during the 12th FYP period in Guiyang city of China

NASA Astrophysics Data System (ADS)

Tian, Hezhong; Qiu, Peipei; Cheng, Ke; Gao, Jiajia; Lu, Long; Liu, Kaiyun; Liu, Xingang

2013-04-01

In order to investigate the future trends of SO2 and NOx pollution in Guiyang city of China, the MM5/CALMET/CALPUFF modeling system is applied to assess the effects of air pollution improvement that would result from reduction targets for SO2 and NOx emissions during the 12th Five-Year Plan (2011-2015). Three scenarios are established for the objective year 2015 based on the reference emissions in base year 2010. Scenario analysis and modeling results show that emissions are projected to increase by 26.5% for SO2 and 138.0% for NOx in 2015 Business-As-Usual (BAU) relative to base year 2010, respectively, which will lead to a substantial worsening tendency of SO2 and NOx pollution. In comparison, both the 2015 Policy Reduction (PR) and 2015 Intensive Policy Reduction (IPR) scenarios would contribute to improve the urban air quality. Under 2015 PR scenario, the maximum annual average concentration of SO2 and NOx will reduce by 54.9% and 31.7%, respectively, relative to the year 2010, with only 2.1% of all individual gridded receptors exceed the national air quality standard limits; while the maximum annual average concentrations of SO2 and NOx can reduce further under 2015 IPR scenario and comply well with standards limits. In view of the technical feasibility and cost-effectiveness, the emission reduction targets set in the 2015 PR scenario are regarded as more reasonable in order to further improve the air quality in Guiyang during the 12th FYP period and a series of comprehensive countermeasures should be effectively implemented.

A new approach for crystallization of copper(ii) oxide hollow nanostructures with superior catalytic and magnetic response

NASA Astrophysics Data System (ADS)

Singh, Inderjeet; Landfester, Katharina; Chandra, Amreesh; Muñoz-Espí, Rafael

2015-11-01

We report the synthesis of copper(ii) oxide hollow nanostructures at ambient pressure and close to room temperature by applying the soft templating effect provided by the confinement of droplets in miniemulsion systems. Particle growth can be explained by considering a mechanism that involves both diffusion and reaction control. The catalytic reduction of p-nitrophenol in aqueous media is used as a model reaction to prove the catalytic activity of the materials: the synthesized hollow structures show nearly 100 times higher rate constants than solid CuO microspheres. The kinetic behavior and the order of the reduction reaction change due to the increase of the surface area of the hollow structures. The synthesis also leads to modification of physical properties such as magnetism.We report the synthesis of copper(ii) oxide hollow nanostructures at ambient pressure and close to room temperature by applying the soft templating effect provided by the confinement of droplets in miniemulsion systems. Particle growth can be explained by considering a mechanism that involves both diffusion and reaction control. The catalytic reduction of p-nitrophenol in aqueous media is used as a model reaction to prove the catalytic activity of the materials: the synthesized hollow structures show nearly 100 times higher rate constants than solid CuO microspheres. The kinetic behavior and the order of the reduction reaction change due to the increase of the surface area of the hollow structures. The synthesis also leads to modification of physical properties such as magnetism. Electronic supplementary information (ESI) available: Associated structural and morphological analysis, XPS characterization, BET surface area, catalytic measurements, recycle tests of the catalyst, and magnetic characterizations. See DOI: 10.1039/c5nr05579b

Accelerated solution of discrete ordinates approximation to the Boltzmann transport equation via model reduction

DOE PAGES

Tencer, John; Carlberg, Kevin; Larsen, Marvin; ...

2017-06-17

Radiation heat transfer is an important phenomenon in many physical systems of practical interest. When participating media is important, the radiative transfer equation (RTE) must be solved for the radiative intensity as a function of location, time, direction, and wavelength. In many heat-transfer applications, a quasi-steady assumption is valid, thereby removing time dependence. The dependence on wavelength is often treated through a weighted sum of gray gases (WSGG) approach. The discrete ordinates method (DOM) is one of the most common methods for approximating the angular (i.e., directional) dependence. The DOM exactly solves for the radiative intensity for a finite numbermore » of discrete ordinate directions and computes approximations to integrals over the angular space using a quadrature rule; the chosen ordinate directions correspond to the nodes of this quadrature rule. This paper applies a projection-based model-reduction approach to make high-order quadrature computationally feasible for the DOM for purely absorbing applications. First, the proposed approach constructs a reduced basis from (high-fidelity) solutions of the radiative intensity computed at a relatively small number of ordinate directions. Then, the method computes inexpensive approximations of the radiative intensity at the (remaining) quadrature points of a high-order quadrature using a reduced-order model constructed from the reduced basis. Finally, this results in a much more accurate solution than might have been achieved using only the ordinate directions used to compute the reduced basis. One- and three-dimensional test problems highlight the efficiency of the proposed method.« less

Accelerated solution of discrete ordinates approximation to the Boltzmann transport equation via model reduction

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

Tencer, John; Carlberg, Kevin; Larsen, Marvin

Radiation heat transfer is an important phenomenon in many physical systems of practical interest. When participating media is important, the radiative transfer equation (RTE) must be solved for the radiative intensity as a function of location, time, direction, and wavelength. In many heat-transfer applications, a quasi-steady assumption is valid, thereby removing time dependence. The dependence on wavelength is often treated through a weighted sum of gray gases (WSGG) approach. The discrete ordinates method (DOM) is one of the most common methods for approximating the angular (i.e., directional) dependence. The DOM exactly solves for the radiative intensity for a finite numbermore » of discrete ordinate directions and computes approximations to integrals over the angular space using a quadrature rule; the chosen ordinate directions correspond to the nodes of this quadrature rule. This paper applies a projection-based model-reduction approach to make high-order quadrature computationally feasible for the DOM for purely absorbing applications. First, the proposed approach constructs a reduced basis from (high-fidelity) solutions of the radiative intensity computed at a relatively small number of ordinate directions. Then, the method computes inexpensive approximations of the radiative intensity at the (remaining) quadrature points of a high-order quadrature using a reduced-order model constructed from the reduced basis. Finally, this results in a much more accurate solution than might have been achieved using only the ordinate directions used to compute the reduced basis. One- and three-dimensional test problems highlight the efficiency of the proposed method.« less

Health policy model: long-term predictive results associated with the management of hepatitis C virus-induced diseases in Italy.

PubMed

Mennini, Francesco Saverio; Marcellusi, Andrea; Andreoni, Massimo; Gasbarrini, Antonio; Salomone, Salvatore; Craxì, Antonio

2014-01-01

At present, there are no specific nationwide epidemiological studies representing the whole Italian population. This study is aimed at describing the epidemiological and economic burden that HCV will generate in the next few years in Italy. Furthermore, the impact that future anti-HCV treatments may have on the burden of disease was considered. This analysis was developed for the period 2012-2030 from the perspective of the Italian National Health Service (NHS). A published system dynamic model was adapted for Italy in order to quantify the HCV-infected population in terms of disease progression and the associated costs from 1950 to 2030. The model structure was based on transition probabilities reflecting the natural history of the disease. In order to estimate the efficacy of current anti-HCV treatment strategies for genotypes 1 and 4, the sustained virological response (SVR) rate in registration clinical trials for both boceprevir and telaprevir was estimated. It was assumed that the efficacy for patients treated with peginterferon + ribavirin was equal to the placebo arm of a randomized clinical trial (RCT) relating to boceprevir and telaprevir. For genotypes 2/3 patients it was assumed that treatment efficacy with dual therapy was equal to a SVR rate from the literature. According to the aim of this study, only direct health care costs (hospital admissions, drugs, treatment, and care of patients) incurred by the Italian NHS have been included in the model. Costs have been extrapolated using the published scientific literature available in Italy and actualized with the 2012 ISTAT (Istituto Nazionale di Statistica) Price Index system for monetary revaluation. Three different scenarios were assumed in order to evaluate the impact of future anti-HCV treatments on the burden of disease. Overall, in Italy, 1.2 million infected subjects were estimated in 2012. Of these, about 211,000 patients were diagnosed, while only about 11,800 subjects were actually being treated with anti-HCV drugs. A reduction of health care costs is associated with a prevalence decrease. Indeed, once the spending peak is reached during this decade (about €527 million), the model predicts a cost reduction in the following 18 years. In 2030, based on the more effective treatments currently available, the direct health care cost associated with the management of HCV patients may reach €346 million (-34.3% compared to 2012). The first scenario (new treatment in 2015 with SVR =90% and same number of treated patients) was associated with a significant reduction in HCV-induced clinical consequences (prevalence =-3%) and a decrease in direct health care expenses, corresponding to €11.1 million. The second scenario (increase in treated patients to 12,790) produced an incremental cost reduction of €7.3 million, reaching a net decrease equal to €18.4 million. In the third scenario (treated patients =16,770), a higher net direct health care cost decrease versus the base-case (€44.0 million) was estimated. Our model showed that the introduction of new treatments that are more effective could result in a quasi-eradication of HCV, with a very strong reduction in prevalence.

Strong anti-gravity Life in the shock wave

NASA Astrophysics Data System (ADS)

Fabbrichesi, Marco; Roland, Kaj

1992-12-01

Strong anti-gravity is the vanishing of the net force between two massive particles at rest, to all orders in Newton's constant. We study this phenomenon and show that it occurs in any effective theory of gravity which is obtained from a higher-dimensional model by compactification on a manifold with flat directions. We find the exact solution of the Einstein equations in the presence of a point-like source of strong anti-gravity by dimensional reduction of a shock-wave solution in the higher-dimensional model.

Modeling of switching regulator power stages with and without zero-inductor-current dwell time

NASA Technical Reports Server (NTRS)

Lee, F. C.; Yu, Y.; Triner, J. E.

1976-01-01

State space techniques are employed to derive accurate models for buck, boost, and buck/boost converter power stages operating with and without zero-inductor-current dwell time. A generalized procedure is developed which treats the continuous-inductor-current mode without the dwell time as a special case of the discontinuous-current mode, when the dwell time vanishes. An abrupt change of system behavior including a reduction of the system order when the dwell time appears is shown both analytically and experimentally.

38 CFR 9.3 - Waiver or reduction of coverage.

Code of Federal Regulations, 2011 CFR

2011-07-01

...-time coverage is called or ordered to active duty or active duty for training under a call or order... paid. Termination or reduction of coverage is effective for the entire remaining period of active duty... termination of duty, a member reenters duty (in the same or another uniformed service), a waiver or reduction...

Robust Combining of Disparate Classifiers Through Order Statistics

NASA Technical Reports Server (NTRS)

Tumer, Kagan; Ghosh, Joydeep

2001-01-01

Integrating the outputs of multiple classifiers via combiners or meta-learners has led to substantial improvements in several difficult pattern recognition problems. In this article we investigate a family of combiners based on order statistics, for robust handling of situations where there are large discrepancies in performance of individual classifiers. Based on a mathematical modeling of how the decision boundaries are affected by order statistic combiners, we derive expressions for the reductions in error expected when simple output combination methods based on the the median, the maximum and in general, the ith order statistic, are used. Furthermore, we analyze the trim and spread combiners, both based on linear combinations of the ordered classifier outputs, and show that in the presence of uneven classifier performance, they often provide substantial gains over both linear and simple order statistics combiners. Experimental results on both real world data and standard public domain data sets corroborate these findings.

Elastic Measurements of Amorphous Silicon Films at mK Temperatures

NASA Astrophysics Data System (ADS)

Fefferman, Andrew; Maldonado, Ana; Collin, Eddy; Liu, Xiao; Metcalf, Tom; Jernigan, Glenn

2017-06-01

The low-temperature properties of glass are distinct from those of crystals due to the presence of poorly understood low-energy excitations. The tunneling model proposes that these are atoms tunneling between nearby equilibria, forming tunneling two-level systems (TLSs). This model is rather successful, but it does not explain the remarkably universal value of the mechanical dissipation Q^{-1} near 1 K. The only known exceptions to this universality are the Q^{-1} of certain thin films of amorphous silicon, carbon and germanium. Recently, it was found that Q^{-1} of amorphous silicon (a-Si) films can be reduced by two orders of magnitude by increasing the temperature of the substrate during deposition. According to the tunneling model, the reduction in Q^{-1} at 1 K implies a reduction in P0γ 2, where P0 is the density of TLSs and γ is their coupling to phonons. In this preliminary report, we demonstrate elastic measurements of a-Si films down to 20 mK. This will allow us, in future work, to determine whether P0 or γ is responsible for the reduction in Q^{-1} with deposition temperature.

Mechanical principles of effects of botulinum toxin on muscle length-force characteristics: an assessment by finite element modeling.

PubMed

Turkoglu, Ahu N; Huijing, Peter A; Yucesoy, Can A

2014-05-07

Recent experiments involving muscle force measurements over a range of muscle lengths show that effects of botulinum toxin (BTX) are complex e.g., force reduction varies as a function of muscle length. We hypothesized that altered conditions of sarcomeres within active parts of partially paralyzed muscle is responsible for this effect. Using finite element modeling, the aim was to test this hypothesis and to study principles of how partial activation as a consequence of BTX affects muscle mechanics. In order to model the paralyzing effect of BTX, only 50% of the fascicles (most proximal, or middle, or most distal) of the modeled muscle were activated. For all muscle lengths, a vast majority of sarcomeres of these BTX-cases were at higher lengths than identical sarcomeres of the BTX-free muscle. Due to such "longer sarcomere effect", activated muscle parts show an enhanced potential of active force exertion (up to 14.5%). Therefore, a muscle force reduction originating exclusively from the paralyzed muscle fiber populations, is compromised by the changes of active sarcomeres leading to a smaller net force reduction. Moreover, such "compromise to force reduction" varies as a function of muscle length and is a key determinant of muscle length dependence of force reduction caused by BTX. Due to longer sarcomere effect, muscle optimum length tends to shift to a lower muscle length. Muscle fiber-extracellular matrix interactions occurring via their mutual connections along full peripheral fiber lengths (i.e., myofascial force transmission) are central to these effects. Our results may help improving our understanding of mechanisms of how the toxin secondarily affects the muscle mechanically. Copyright © 2014 Elsevier Ltd. All rights reserved.

Numerical study and ex vivo assessment of HIFU treatment time reduction through optimization of focal point trajectory

NASA Astrophysics Data System (ADS)

Grisey, A.; Yon, S.; Pechoux, T.; Letort, V.; Lafitte, P.

2017-03-01

Treatment time reduction is a key issue to expand the use of high intensity focused ultrasound (HIFU) surgery, especially for benign pathologies. This study aims at quantitatively assessing the potential reduction of the treatment time arising from moving the focal point during long pulses. In this context, the optimization of the focal point trajectory is crucial to achieve a uniform thermal dose repartition and avoid boiling. At first, a numerical optimization algorithm was used to generate efficient trajectories. Thermal conduction was simulated in 3D with a finite difference code and damages to the tissue were modeled using the thermal dose formula. Given an initial trajectory, the thermal dose field was first computed, then, making use of Pontryagin's maximum principle, the trajectory was iteratively refined. Several initial trajectories were tested. Then, an ex vivo study was conducted in order to validate the efficicency of the resulting optimized strategies. Single pulses were performed at 3MHz on fresh veal liver samples with an Echopulse and the size of each unitary lesion was assessed by cutting each sample along three orthogonal planes and measuring the dimension of the whitened area based on photographs. We propose a promising approach to significantly shorten HIFU treatment time: the numerical optimization algorithm was shown to provide a reliable insight on trajectories that can improve treatment strategies. The model must now be improved in order to take in vivo conditions into account and extensively validated.

Efficient model reduction of parametrized systems by matrix discrete empirical interpolation

NASA Astrophysics Data System (ADS)

Negri, Federico; Manzoni, Andrea; Amsallem, David

2015-12-01

In this work, we apply a Matrix version of the so-called Discrete Empirical Interpolation (MDEIM) for the efficient reduction of nonaffine parametrized systems arising from the discretization of linear partial differential equations. Dealing with affinely parametrized operators is crucial in order to enhance the online solution of reduced-order models (ROMs). However, in many cases such an affine decomposition is not readily available, and must be recovered through (often) intrusive procedures, such as the empirical interpolation method (EIM) and its discrete variant DEIM. In this paper we show that MDEIM represents a very efficient approach to deal with complex physical and geometrical parametrizations in a non-intrusive, efficient and purely algebraic way. We propose different strategies to combine MDEIM with a state approximation resulting either from a reduced basis greedy approach or Proper Orthogonal Decomposition. A posteriori error estimates accounting for the MDEIM error are also developed in the case of parametrized elliptic and parabolic equations. Finally, the capability of MDEIM to generate accurate and efficient ROMs is demonstrated on the solution of two computationally-intensive classes of problems occurring in engineering contexts, namely PDE-constrained shape optimization and parametrized coupled problems.

On the origin and removal of interference patterns in coated multimode fibres

NASA Astrophysics Data System (ADS)

Padilla Michel, Yazmin; Pulwer, Silvio; Saffari, Pouneh; Ksianzou, Viachaslau; Schrader, Sigurd

2016-07-01

In this study, we present the experimental investigations on interference patterns, such as those already reported in VIMOS-IFU, and up to now no appropriate explanation has been presented. These interference patterns are produced in multimode fibres coated with acrylate or polyimide, which is the preferred coating material for the fibres used in IFUs. Our experiments show that, under specific conditions, cladding modes interact with the coating and produce interference. Our results show that the conditions at which the fibre is held during data acquisition has an impact in the output spectrum. Altering the positioning conditions of the fibre leads to the changes into the interference pattern, therefore, fibres should be carefully manipulated in order to minimise this potential problem and improve the performance of these instruments. Finally we present a simple way of predicting and modelling this interference produced from the visible to the near infrared spectra. This model can be included in the data reduction pipeline in order to remove the interference patterns. These results should be of interest for the optimisation of the data reduction pipelines of instruments using optical fibres. Considering these results will benefit innovations and developments of high performance fibre systems.

The Semireduced Mechanism for Nitric Oxide Reduction by Non-Heme Diiron Complexes: Modeling Flavodiiron Nitric Oxide Reductases.

PubMed

White, Corey J; Speelman, Amy L; Kupper, Claudia; Demeshko, Serhiy; Meyer, Franc; Shanahan, James P; Alp, E Ercan; Hu, Michael; Zhao, Jiyong; Lehnert, Nicolai

2018-02-21

Flavodiiron nitric oxide reductases (FNORs) are a subclass of flavodiiron proteins (FDPs) capable of preferential binding and subsequent reduction of NO to N 2 O. FNORs are found in certain pathogenic bacteria, equipping them with resistance to nitrosative stress, generated as a part of the immune defense in humans, and allowing them to proliferate. Here, we report the spectroscopic characterization and detailed reactivity studies of the diiron dinitrosyl model complex [Fe 2 (BPMP)(OPr)(NO) 2 ](OTf) 2 for the FNOR active site that is capable of reducing NO to N 2 O [Zheng et al., J. Am. Chem. Soc. 2013, 135, 4902-4905]. Using UV-vis spectroscopy, cyclic voltammetry, and spectro-electrochemistry, we show that one reductive equivalent is in fact sufficient for the quantitative generation of N 2 O, following a semireduced reaction mechanism. This reaction is very efficient and produces N 2 O with a first-order rate constant k > 10 2 s -1 . Further isotope labeling studies confirm an intramolecular N-N coupling mechanism, consistent with the rapid time scale of the reduction and a very low barrier for N-N bond formation. Accordingly, the reaction proceeds at -80 °C, allowing for the direct observation of the mixed-valent product of the reaction. At higher temperatures, the initial reaction product is unstable and decays, ultimately generating the diferrous complex [Fe 2 (BPMP)(OPr) 2 ](OTf) and an unidentified ferric product. These results combined offer deep insight into the mechanism of NO reduction by the relevant model complex [Fe 2 (BPMP)(OPr)(NO) 2 ] 2+ and provide direct evidence that the semireduced mechanism would constitute a highly efficient pathway to accomplish NO reduction to N 2 O in FNORs and in synthetic catalysts.

Nanotransition Materials (NTMs): Photocatalysis, Validated High Effective Sorbent Models Study for Organic Dye Degradation and Precise Mathematical Data’s at Standardized Level

PubMed Central

Khan, Farheen; Wahab, Rizwan; Hagar, Mohamed; Alnoman, Rua; Lutfullah; Rashid, Mohd

2018-01-01

The present work describes the synthesis of copper oxide nanoparticles (CuONPs) via a solution process with the aim of applying the nano-adsorbent for the reduction of methylene blue (MB) dye in alkaline media. These NPs were characterized via Field emission scanning electron microscopy (FE-SEM), X-ray diffraction, high-resolution Transmission electron microscopy (TEM), and ultra violet UV-visible spectroscopy to confirm their morphology and crystalline and optical properties in order to design an adsorption-degradation process. The photocatalytic CuONPs exhibited dynamic properties, great adsorption affinity during the chemisorption process, and operated at various modes with a strong interaction between the adsorbent and the adsorptive species, and equilibrium isotherm, kinetic isotherm, and thermodynamic activities in the presence of UV light. All basic quantities, such as concentration, pH, adsorbent dose, time, and temperature, were determined by an optimization process. The best-fitted adsorption Langmuir model (R2 = 0.9988) and performance, including adsorption capacity (350.87 mg/g), photocatalytic efficiency (90.74%), and degradation rate constant (Ks = 2.23 ×10−2 min−1), illustrate good feasibility with respect to sorption-reduction reactions but followed a pseudo-second-order kinetic on the adsorbent surface, reaching an equilibrium point in 80 min. The thermodynamic analysis suggests that the adsorption reaction is spontaneous and endothermic in nature. The thermodynamic parameters such as enthalpy (∆H°), entropy (∆S°), and Gibbs free energy (∆G°) give effective results to support a chemical reduction reaction at 303 K temperature. The equilibrium isotherm and kinetic and thermodynamic models with error function analysis explore the potential, acceptability, accuracy, access to adsorbents, and novelty of an unrivaled-sorption system. PMID:29495511

Characterization of caries progression on dentin after irradiation with Nd:YAG laser by FTIR spectroscopy and fluorescence imaging

NASA Astrophysics Data System (ADS)

Ana, P. A.; Brito, A. M. M.; Zezell, D. M.; Lins, E. C. C. C.

2015-06-01

Considering the use of high intensity lasers for preventing dental caries, this blind in vitro study evaluated the compositional and fluorescence effects promoted by Nd:YAG laser (λ=1064 nm) when applied for prevention of progression of dentin caries, in association or not with topical application of acidulated phosphate fluoride (APF). Sixty bovine root dentin slabs were prepared and demineralized by 32h in order to create early caries lesions. After, the slabs were distributed into six experimental groups: G1- untreated and not submitted to a pH-cycling model; G2- untreated and submitted to a pH-cycling model; G3- acidulated phosphate fluoride application (APF); G4- Nd:YAG irradiation (84.9 J/cm2, 60 mJ/pulse); G5- treated with Nd:YAG+APF; G6- treated with APF+Nd:YAG. After treatments, the samples of groups G2 to G6 were submitted to a 4-day pH-cycling model in order to simulate the progression of early caries lesions. All samples were characterized by the micro-attenuated total reflection technique of Fourier transformed infrared spectroscopy (μATR-FTIR), using a diamond crystal, and by a fluorescence imaging system (FIS), in which it was used an illuminating system at λ= 405±30 nm. Demineralization promoted reduction in carbonate and phosphate contents, exposing the organic matter; as well, it was observed a significant reduction of fluorescence intensity. Nd:YAG laser promoted additional chemical changes, and increased the fluorescence intensity even with the development of caries lesions. It was concluded that the compositional changes promoted by Nd:YAG, when associated to APF, are responsible for the reduction of demineralization progression observed on root dentin.

C. botulinum inactivation kinetics implemented in a computational model of a high-pressure sterilization process.

PubMed

Juliano, Pablo; Knoerzer, Kai; Fryer, Peter J; Versteeg, Cornelis

2009-01-01

High-pressure, high-temperature (HPHT) processing is effective for microbial spore inactivation using mild preheating, followed by rapid volumetric compression heating and cooling on pressure release, enabling much shorter processing times than conventional thermal processing for many food products. A computational thermal fluid dynamic (CTFD) model has been developed to model all processing steps, including the vertical pressure vessel, an internal polymeric carrier, and food packages in an axis-symmetric geometry. Heat transfer and fluid dynamic equations were coupled to four selected kinetic models for the inactivation of C. botulinum; the traditional first-order kinetic model, the Weibull model, an nth-order model, and a combined discrete log-linear nth-order model. The models were solved to compare the resulting microbial inactivation distributions. The initial temperature of the system was set to 90 degrees C and pressure was selected at 600 MPa, holding for 220 s, with a target temperature of 121 degrees C. A representation of the extent of microbial inactivation throughout all processing steps was obtained for each microbial model. Comparison of the models showed that the conventional thermal processing kinetics (not accounting for pressure) required shorter holding times to achieve a 12D reduction of C. botulinum spores than the other models. The temperature distribution inside the vessel resulted in a more uniform inactivation distribution when using a Weibull or an nth-order kinetics model than when using log-linear kinetics. The CTFD platform could illustrate the inactivation extent and uniformity provided by the microbial models. The platform is expected to be useful to evaluate models fitted into new C. botulinum inactivation data at varying conditions of pressure and temperature, as an aid for regulatory filing of the technology as well as in process and equipment design.

Adaptation of water resource systems to an uncertain future

NASA Astrophysics Data System (ADS)

Walsh, Claire L.; Blenkinsop, Stephen; Fowler, Hayley J.; Burton, Aidan; Dawson, Richard J.; Glenis, Vassilis; Manning, Lucy J.; Jahanshahi, Golnaz; Kilsby, Chris G.

2016-05-01

Globally, water resources management faces significant challenges from changing climate and growing populations. At local scales, the information provided by climate models is insufficient to support the water sector in making future adaptation decisions. Furthermore, projections of change in local water resources are wrought with uncertainties surrounding natural variability, future greenhouse gas emissions, model structure, population growth, and water consumption habits. To analyse the magnitude of these uncertainties, and their implications for local-scale water resource planning, we present a top-down approach for testing climate change adaptation options using probabilistic climate scenarios and demand projections. An integrated modelling framework is developed which implements a new, gridded spatial weather generator, coupled with a rainfall-runoff model and water resource management simulation model. We use this to provide projections of the number of days and associated uncertainty that will require implementation of demand saving measures such as hose pipe bans and drought orders. Results, which are demonstrated for the Thames Basin, UK, indicate existing water supplies are sensitive to a changing climate and an increasing population, and that the frequency of severe demand saving measures are projected to increase. Considering both climate projections and population growth, the median number of drought order occurrences may increase 5-fold by the 2050s. The effectiveness of a range of demand management and supply options have been tested and shown to provide significant benefits in terms of reducing the number of demand saving days. A decrease in per capita demand of 3.75 % reduces the median frequency of drought order measures by 50 % by the 2020s. We found that increased supply arising from various adaptation options may compensate for increasingly variable flows; however, without reductions in overall demand for water resources such options will be insufficient on their own to adapt to uncertainties in the projected changes in climate and population. For example, a 30 % reduction in overall demand by 2050 has a greater impact on reducing the frequency of drought orders than any of the individual or combinations of supply options; hence, a portfolio of measures is required.

Modelling road dust emission abatement measures using the NORTRIP model: Vehicle speed and studded tyre reduction

NASA Astrophysics Data System (ADS)

Norman, M.; Sundvor, I.; Denby, B. R.; Johansson, C.; Gustafsson, M.; Blomqvist, G.; Janhäll, S.

2016-06-01

Road dust emissions in Nordic countries still remain a significant contributor to PM10 concentrations mainly due to the use of studded tyres. A number of measures have been introduced in these countries in order to reduce road dust emissions. These include speed reductions, reductions in studded tyre use, dust binding and road cleaning. Implementation of such measures can be costly and some confidence in the impact of the measures is required to weigh the costs against the benefits. Modelling tools are thus required that can predict the impact of these measures. In this paper the NORTRIP road dust emission model is used to simulate real world abatement measures that have been carried out in Oslo and Stockholm. In Oslo both vehicle speed and studded tyre share reductions occurred over a period from 2004 to 2006 on a major arterial road, RV4. In Stockholm a studded tyre ban on Hornsgatan in 2010 saw a significant reduction in studded tyre share together with a reduction in traffic volume. The model is found to correctly simulate the impact of these measures on the PM10 concentrations when compared to available kerbside measurement data. Importantly meteorology can have a significant impact on the concentrations through both surface and dispersion conditions. The first year after the implementation of the speed reduction on RV4 was much drier than the previous year, resulting in higher mean concentrations than expected. The following year was much wetter with significant rain and snow fall leading to wet or frozen road surfaces for 83% of the four month study period. This significantly reduced the net PM10 concentrations, by 58%, compared to the expected values if meteorological conditions had been similar to the previous years. In the years following the studded tyre ban on Hornsgatan road wear production through studded tyres decreased by 72%, due to a combination of reduced traffic volume and reduced studded tyre share. However, after accounting for exhaust contributions and the impact of meteorological conditions in the model calculations then the net mean reduction in PM10 concentrations was only ∼50%, in agreement with observations. The NORTRIP model is shown to be able to reproduce the impacts of both traffic measures and meteorology on traffic induced PM10 concentrations, making it a unique and valuable tool for predicting the impact of measures for air quality management applications.

Stereo Sound Field Controller Design Using Partial Model Matching on the Frequency Domain

NASA Astrophysics Data System (ADS)

Kumon, Makoto; Miike, Katsuhiro; Eguchi, Kazuki; Mizumoto, Ikuro; Iwai, Zenta

The objective of sound field control is to make the acoustic characteristics of a listening room close to those of the desired system. Conventional methods apply feedforward controllers, such as digital filters, to achieve this objective. However, feedback controllers are also necessary in order to attenuate noise or to compensate the uncertainty of the acoustic characteristics of the listening room. Since acoustic characteristics are well modeled on the frequency domain, it is efficient to design controllers with respect to frequency responses, but it is difficult to design a multi input multi output (MIMO) control system on a wide frequency domain. In the present study, a partial model matching method on the frequency domain was adopted because this method requires only sampled data, rather than complex mathematical models of the plant, in order to design controllers for MIMO systems. The partial model matching method was applied to design two-degree-of-freedom controllers for acoustic equalization and noise reduction. Experiments demonstrated effectiveness of the proposed method.

Ordered phases in the Holstein-Hubbard model: Interplay of strong Coulomb interaction and electron-phonon coupling

NASA Astrophysics Data System (ADS)

Murakami, Yuta; Werner, Philipp; Tsuji, Naoto; Aoki, Hideo

2013-09-01

We study the Holstein-Hubbard model at half filling to explore ordered phases including superconductivity (SC), antiferromagnetism (AF), and charge order (CO) in situations where the electron-electron and electron-phonon interactions are strong (comparable to the electronic bandwidth). The model is solved in the dynamical mean-field approximation with a continuous-time quantum Monte Carlo impurity solver. We determine the superconducting transition temperature Tc and the SC order parameter and show that the phonon-induced retardation or the strong Coulomb interaction leads to a significant reduction and shift of the Tc dome against the effective electron-electron interaction Ueff given by the Hubbard U reduced by the phonon-mediated attraction in the static limit. This behavior is analyzed by comparison to an effective static model in the polaron representation with a renormalized bandwidth. In addition, we discuss the superconducting gap Δ and 2Δ/Tc to reveal the effect of the retardation and the Coulomb interaction. We also determine the finite-temperature phase diagram including AF and CO. In the moderate-coupling regime, there is a hysteretic region of AF and CO around Ueff=0, while the two phases are separated by a paramagnetic metal in the weak-coupling regime and a paramagnetic insulator in the strong-coupling regime.

The sensitivities of emissions reductions for the mitigation of UK PM2.5

NASA Astrophysics Data System (ADS)

Vieno, M.; Heal, M. R.; Williams, M. L.; Carnell, E. J.; Nemitz, E.; Stedman, J. R.; Reis, S.

2016-01-01

The reduction of ambient concentrations of fine particulate matter (PM2.5) is a key objective for air pollution control policies in the UK and elsewhere. Long-term exposure to PM2.5 has been identified as a major contributor to adverse human health effects in epidemiological studies and underpins ambient PM2.5 legislation. As a range of emission sources and atmospheric chemistry transport processes contribute to PM2.5 concentrations, atmospheric chemistry transport models are an essential tool to assess emissions control effectiveness. The EMEP4UK atmospheric chemistry transport model was used to investigate the impact of reductions in UK anthropogenic emissions of primary PM2.5, NH3, NOx, SOx or non-methane VOC on surface concentrations of PM2.5 in the UK for a recent year (2010) and for a future current legislation emission (CLE) scenario (2030). In general, the sensitivity to UK mitigation is rather small. A 30 % reduction in UK emissions of any one of the above components yields (for the 2010 simulation) a maximum reduction in PM2.5 in any given location of ˜ 0.6 µg m-3 (equivalent to ˜ 6 % of the modelled PM2.5). On average across the UK, the sensitivity of PM2.5 concentrations to a 30 % reduction in UK emissions of individual contributing components, for both the 2010 and 2030 CLE baselines, increases in the order NMVOC, NOx, SOx, NH3 and primary PM2.5; however there are strong spatial differences in the PM2.5 sensitivities across the UK. Consequently, the sensitivity of PM2.5 to individual component emissions reductions varies between area and population weighting. Reductions in NH3 have the greatest effect on area-weighted PM2.5. A full UK population weighting places greater emphasis on reductions of primary PM2.5 emissions, which is simulated to be the most effective single-component control on PM2.5 for the 2030 scenario. An important conclusion is that weighting corresponding to the average exposure indicator metric (using data from the 45 model grids containing a monitor whose measurements are used to calculate the UK AEI) further increases the emphasis on the effectiveness of primary PM2.5 emissions reductions (and of NOx emissions reductions) relative to the effectiveness of NH3 emissions reductions. Reductions in primary PM2.5 have the largest impact on the AEI in both 2010 and the 2030 CLE scenario. The summation of the modelled reductions to the UK PM2.5 AEI from 30 % reductions in UK emissions of primary PM2.5, NH3, SOx, NOx and VOC totals 1.17 and 0.82 µg m-3 for the 2010 and 2030 CLE simulations, respectively (not accounting for non-linearity).