ERIC Educational Resources Information Center
Lee, Il-Sun; Byeon, Jung-Ho; Kim, Young-shin; Kwon, Yong-Ju
2014-01-01
The purpose of this study was to develop a model for measuring experimental design ability based on functional magnetic resonance imaging (fMRI) during biological inquiry. More specifically, the researchers developed an experimental design task that measures experimental design ability. Using the developed experimental design task, they measured…
Constitutive Model Calibration via Autonomous Multiaxial Experimentation (Postprint)
2016-09-17
test machine. Experimental data is reduced and finite element simulations are conducted in parallel with the test based on experimental strain...data is reduced and finite element simulations are conducted in parallel with the test based on experimental strain conditions. Optimization methods...be used directly in finite element simulations of more complex geometries. Keywords Axial/torsional experimentation • Plasticity • Constitutive model
Fischer, Kenneth J; Johnson, Joshua E; Waller, Alexander J; McIff, Terence E; Toby, E Bruce; Bilgen, Mehmet
2011-10-01
The objective of this study was to validate the MRI-based joint contact modeling methodology in the radiocarpal joints by comparison of model results with invasive specimen-specific radiocarpal contact measurements from four cadaver experiments. We used a single validation criterion for multiple outcome measures to characterize the utility and overall validity of the modeling approach. For each experiment, a Pressurex film and a Tekscan sensor were sequentially placed into the radiocarpal joints during simulated grasp. Computer models were constructed based on MRI visualization of the cadaver specimens without load. Images were also acquired during the loaded configuration used with the direct experimental measurements. Geometric surface models of the radius, scaphoid and lunate (including cartilage) were constructed from the images acquired without the load. The carpal bone motions from the unloaded state to the loaded state were determined using a series of 3D image registrations. Cartilage thickness was assumed uniform at 1.0 mm with an effective compressive modulus of 4 MPa. Validation was based on experimental versus model contact area, contact force, average contact pressure and peak contact pressure for the radioscaphoid and radiolunate articulations. Contact area was also measured directly from images acquired under load and compared to the experimental and model data. Qualitatively, there was good correspondence between the MRI-based model data and experimental data, with consistent relative size, shape and location of radioscaphoid and radiolunate contact regions. Quantitative data from the model generally compared well with the experimental data for all specimens. Contact area from the MRI-based model was very similar to the contact area measured directly from the images. For all outcome measures except average and peak pressures, at least two specimen models met the validation criteria with respect to experimental measurements for both articulations. Only the model for one specimen met the validation criteria for average and peak pressure of both articulations; however the experimental measures for peak pressure also exhibited high variability. MRI-based modeling can reliably be used for evaluating the contact area and contact force with similar confidence as in currently available experimental techniques. Average contact pressure, and peak contact pressure were more variable from all measurement techniques, and these measures from MRI-based modeling should be used with some caution.
Quantifying Astronaut Tasks: Robotic Technology and Future Space Suit Design
NASA Technical Reports Server (NTRS)
Newman, Dava
2003-01-01
The primary aim of this research effort was to advance the current understanding of astronauts' capabilities and limitations in space-suited EVA by developing models of the constitutive and compatibility relations of a space suit, based on experimental data gained from human test subjects as well as a 12 degree-of-freedom human-sized robot, and utilizing these fundamental relations to estimate a human factors performance metric for space suited EVA work. The three specific objectives are to: 1) Compile a detailed database of torques required to bend the joints of a space suit, using realistic, multi- joint human motions. 2) Develop a mathematical model of the constitutive relations between space suit joint torques and joint angular positions, based on experimental data and compare other investigators' physics-based models to experimental data. 3) Estimate the work envelope of a space suited astronaut, using the constitutive and compatibility relations of the space suit. The body of work that makes up this report includes experimentation, empirical and physics-based modeling, and model applications. A detailed space suit joint torque-angle database was compiled with a novel experimental approach that used space-suited human test subjects to generate realistic, multi-joint motions and an instrumented robot to measure the torques required to accomplish these motions in a space suit. Based on the experimental data, a mathematical model is developed to predict joint torque from the joint angle history. Two physics-based models of pressurized fabric cylinder bending are compared to experimental data, yielding design insights. The mathematical model is applied to EVA operations in an inverse kinematic analysis coupled to the space suit model to calculate the volume in which space-suited astronauts can work with their hands, demonstrating that operational human factors metrics can be predicted from fundamental space suit information.
Creep and Oxidation of Hafnium Diboride Based Ultra High Temperature Ceramics at 1500C
2015-12-01
through experimentation. Although the Literature Review showed that some theories and models have been developed based on extensive experimental results...of Some Refractory Metals & Ceramics [Fahrenholtz] ........... 14 Figure 4: Creep Strain vs Time Based on Burgers Model ...
Experimental and numerical investigations of sedimentation of porous wastewater sludge flocs.
Hriberšek, M; Zajdela, B; Hribernik, A; Zadravec, M
2011-02-01
The paper studies the properties and sedimentation characteristics of sludge flocs, as they appear in biological wastewater treatment (BWT) plants. The flocs are described as porous and permeable bodies, with their properties defined based on conducted experimental study. The derivation is based on established geometrical properties, high-speed camera data on settling velocities and non-linear numerical model, linking settling velocity with physical properties of porous flocs. The numerical model for derivation is based on generalized Stokes model, with permeability of the floc described by the Brinkman model. As a result, correlation for flocs porosity is obtained as a function of floc diameter. This data is used in establishing a CFD numerical model of sedimentation of flocs in test conditions, as recorded during experimental investigation. The CFD model is based on Euler-Lagrange formulation, where the Lagrange formulation is chosen for computation of flocs trajectories during sedimentation. The results of numerical simulations are compared with experimental results and very good agreement is observed. © 2010 Elsevier Ltd. All rights reserved.
Verification technology of remote sensing camera satellite imaging simulation based on ray tracing
NASA Astrophysics Data System (ADS)
Gu, Qiongqiong; Chen, Xiaomei; Yang, Deyun
2017-08-01
Remote sensing satellite camera imaging simulation technology is broadly used to evaluate the satellite imaging quality and to test the data application system. But the simulation precision is hard to examine. In this paper, we propose an experimental simulation verification method, which is based on the test parameter variation comparison. According to the simulation model based on ray-tracing, the experiment is to verify the model precision by changing the types of devices, which are corresponding the parameters of the model. The experimental results show that the similarity between the imaging model based on ray tracing and the experimental image is 91.4%, which can simulate the remote sensing satellite imaging system very well.
A sEMG model with experimentally based simulation parameters.
Wheeler, Katherine A; Shimada, Hiroshima; Kumar, Dinesh K; Arjunan, Sridhar P
2010-01-01
A differential, time-invariant, surface electromyogram (sEMG) model has been implemented. While it is based on existing EMG models, the novelty of this implementation is that it assigns more accurate distributions of variables to create realistic motor unit (MU) characteristics. Variables such as muscle fibre conduction velocity, jitter (the change in the interpulse interval between subsequent action potential firings) and motor unit size have been considered to follow normal distributions about an experimentally obtained mean. In addition, motor unit firing frequencies have been considered to have non-linear and type based distributions that are in accordance with experimental results. Motor unit recruitment thresholds have been considered to be related to the MU type. The model has been used to simulate single channel differential sEMG signals from voluntary, isometric contractions of the biceps brachii muscle. The model has been experimentally verified by conducting experiments on three subjects. Comparison between simulated signals and experimental recordings shows that the Root Mean Square (RMS) increases linearly with force in both cases. The simulated signals also show similar values and rates of change of RMS to the experimental signals.
NASA Astrophysics Data System (ADS)
Allman, Derek; Reiter, Austin; Bell, Muyinatu
2018-02-01
We previously proposed a method of removing reflection artifacts in photoacoustic images that uses deep learning. Our approach generally relies on using simulated photoacoustic channel data to train a convolutional neural network (CNN) that is capable of distinguishing sources from artifacts based on unique differences in their spatial impulse responses (manifested as depth-based differences in wavefront shapes). In this paper, we directly compare a CNN trained with our previous continuous transducer model to a CNN trained with an updated discrete acoustic receiver model that more closely matches an experimental ultrasound transducer. These two CNNs were trained with simulated data and tested on experimental data. The CNN trained using the continuous receiver model correctly classified 100% of sources and 70.3% of artifacts in the experimental data. In contrast, the CNN trained using the discrete receiver model correctly classified 100% of sources and 89.7% of artifacts in the experimental images. The 19.4% increase in artifact classification accuracy indicates that an acoustic receiver model that closely mimics the experimental transducer plays an important role in improving the classification of artifacts in experimental photoacoustic data. Results are promising for developing a method to display CNN-based images that remove artifacts in addition to only displaying network-identified sources as previously proposed.
Biomechanical Modeling of the Human Head
2017-10-03
between model predictions and experimental data. This report details model calibration for all materials identified in models of a human head and...14 3 Stress-strain data for the pia mater and dura mater (human subject); experimental data orig- inally presented in [28...treated as one material) based on a hyperelastic model and experimental data from [59] ............................................... 20 5 Comparison of
Bondi, Robert W; Igne, Benoît; Drennen, James K; Anderson, Carl A
2012-12-01
Near-infrared spectroscopy (NIRS) is a valuable tool in the pharmaceutical industry, presenting opportunities for online analyses to achieve real-time assessment of intermediates and finished dosage forms. The purpose of this work was to investigate the effect of experimental designs on prediction performance of quantitative models based on NIRS using a five-component formulation as a model system. The following experimental designs were evaluated: five-level, full factorial (5-L FF); three-level, full factorial (3-L FF); central composite; I-optimal; and D-optimal. The factors for all designs were acetaminophen content and the ratio of microcrystalline cellulose to lactose monohydrate. Other constituents included croscarmellose sodium and magnesium stearate (content remained constant). Partial least squares-based models were generated using data from individual experimental designs that related acetaminophen content to spectral data. The effect of each experimental design was evaluated by determining the statistical significance of the difference in bias and standard error of the prediction for that model's prediction performance. The calibration model derived from the I-optimal design had similar prediction performance as did the model derived from the 5-L FF design, despite containing 16 fewer design points. It also outperformed all other models estimated from designs with similar or fewer numbers of samples. This suggested that experimental-design selection for calibration-model development is critical, and optimum performance can be achieved with efficient experimental designs (i.e., optimal designs).
DOT National Transportation Integrated Search
2009-10-01
This report documents the results of a study that was conducted to characterize the behavior of geogrid reinforced base : course materials. The research was conducted through an experimental testing and numerical modeling programs. The : experimental...
An improved swarm optimization for parameter estimation and biological model selection.
Abdullah, Afnizanfaizal; Deris, Safaai; Mohamad, Mohd Saberi; Anwar, Sohail
2013-01-01
One of the key aspects of computational systems biology is the investigation on the dynamic biological processes within cells. Computational models are often required to elucidate the mechanisms and principles driving the processes because of the nonlinearity and complexity. The models usually incorporate a set of parameters that signify the physical properties of the actual biological systems. In most cases, these parameters are estimated by fitting the model outputs with the corresponding experimental data. However, this is a challenging task because the available experimental data are frequently noisy and incomplete. In this paper, a new hybrid optimization method is proposed to estimate these parameters from the noisy and incomplete experimental data. The proposed method, called Swarm-based Chemical Reaction Optimization, integrates the evolutionary searching strategy employed by the Chemical Reaction Optimization, into the neighbouring searching strategy of the Firefly Algorithm method. The effectiveness of the method was evaluated using a simulated nonlinear model and two biological models: synthetic transcriptional oscillators, and extracellular protease production models. The results showed that the accuracy and computational speed of the proposed method were better than the existing Differential Evolution, Firefly Algorithm and Chemical Reaction Optimization methods. The reliability of the estimated parameters was statistically validated, which suggests that the model outputs produced by these parameters were valid even when noisy and incomplete experimental data were used. Additionally, Akaike Information Criterion was employed to evaluate the model selection, which highlighted the capability of the proposed method in choosing a plausible model based on the experimental data. In conclusion, this paper presents the effectiveness of the proposed method for parameter estimation and model selection problems using noisy and incomplete experimental data. This study is hoped to provide a new insight in developing more accurate and reliable biological models based on limited and low quality experimental data.
An Integrated Miniature Pulse Tube Cryocooler at 80K
NASA Astrophysics Data System (ADS)
Chen, H. L.; Yang, L. W.; Cai, J. H.; Liang, J. T.; Zhang, L.; Zhou, Y.
2008-03-01
Two integrated models of coaxial miniature pulse tube coolers based on an experimental model are manufactured. Performance of the integrated models is compared to that of the experimental model. Reliability and stability of an integrated model are tested and improved.
A multiscale strength model for tantalum over an extended range of strain rates
NASA Astrophysics Data System (ADS)
Barton, N. R.; Rhee, M.
2013-09-01
A strength model for tantalum is developed and exercised across a range of conditions relevant to various types of experimental observations. The model is based on previous multiscale modeling work combined with experimental observations. As such, the model's parameterization includes a hybrid of quantities that arise directly from predictive sub-scale physics models and quantities that are adjusted to align the model with experimental observations. Given current computing and experimental limitations, the response regions for sub-scale physics simulations and detailed experimental observations have been largely disjoint. In formulating the new model and presenting results here, attention is paid to integrated experimental observations that probe strength response at the elevated strain rates where a previous version of the model has generally been successful in predicting experimental data [Barton et al., J. Appl. Phys. 109(7), 073501 (2011)].
Modeling and experimental study of resistive switching in vertically aligned carbon nanotubes
NASA Astrophysics Data System (ADS)
Ageev, O. A.; Blinov, Yu F.; Ilina, M. V.; Ilin, O. I.; Smirnov, V. A.
2016-08-01
Model of the resistive switching in vertically aligned carbon nanotube (VA CNT) taking into account the processes of deformation, polarization and piezoelectric charge accumulation have been developed. Origin of hysteresis in VA CNT-based structure is described. Based on modeling results the VACNTs-based structure has been created. The ration resistance of high-resistance to low-resistance states of the VACNTs-based structure amounts 48. The correlation the modeling results with experimental studies is shown. The results can be used in the development nanoelectronics devices based on VA CNTs, including the nonvolatile resistive random-access memory.
Formulation of an experimental substructure model using a Craig-Bampton based transmission simulator
NASA Astrophysics Data System (ADS)
Kammer, Daniel C.; Allen, Mathew S.; Mayes, Randy L.
2015-12-01
Experimental-analytical substructuring is attractive when there is motivation to replace one or more system subcomponents with an experimental model. This experimentally derived substructure can then be coupled to finite element models of the rest of the structure to predict the system response. The transmission simulator method couples a fixture to the component of interest during a vibration test in order to improve the experimental model for the component. The transmission simulator is then subtracted from the tested system to produce the experimental component. The method reduces ill-conditioning by imposing a least squares fit of constraints between substructure modal coordinates to connect substructures, instead of directly connecting physical interface degrees of freedom. This paper presents an alternative means of deriving the experimental substructure model, in which a Craig-Bampton representation of the transmission simulator is created and subtracted from the experimental measurements. The corresponding modal basis of the transmission simulator is described by the fixed-interface modes, rather than free modes that were used in the original approach. These modes do a better job of representing the shape of the transmission simulator as it responds within the experimental system, leading to more accurate results using fewer modes. The new approach is demonstrated using a simple finite element model based example with a redundant interface.
PDF-based heterogeneous multiscale filtration model.
Gong, Jian; Rutland, Christopher J
2015-04-21
Motivated by modeling of gasoline particulate filters (GPFs), a probability density function (PDF) based heterogeneous multiscale filtration (HMF) model is developed to calculate filtration efficiency of clean particulate filters. A new methodology based on statistical theory and classic filtration theory is developed in the HMF model. Based on the analysis of experimental porosimetry data, a pore size probability density function is introduced to represent heterogeneity and multiscale characteristics of the porous wall. The filtration efficiency of a filter can be calculated as the sum of the contributions of individual collectors. The resulting HMF model overcomes the limitations of classic mean filtration models which rely on tuning of the mean collector size. Sensitivity analysis shows that the HMF model recovers the classical mean model when the pore size variance is very small. The HMF model is validated by fundamental filtration experimental data from different scales of filter samples. The model shows a good agreement with experimental data at various operating conditions. The effects of the microstructure of filters on filtration efficiency as well as the most penetrating particle size are correctly predicted by the model.
Mohsenizadeh, Daniel N; Dehghannasiri, Roozbeh; Dougherty, Edward R
2018-01-01
In systems biology, network models are often used to study interactions among cellular components, a salient aim being to develop drugs and therapeutic mechanisms to change the dynamical behavior of the network to avoid undesirable phenotypes. Owing to limited knowledge, model uncertainty is commonplace and network dynamics can be updated in different ways, thereby giving multiple dynamic trajectories, that is, dynamics uncertainty. In this manuscript, we propose an experimental design method that can effectively reduce the dynamics uncertainty and improve performance in an interaction-based network. Both dynamics uncertainty and experimental error are quantified with respect to the modeling objective, herein, therapeutic intervention. The aim of experimental design is to select among a set of candidate experiments the experiment whose outcome, when applied to the network model, maximally reduces the dynamics uncertainty pertinent to the intervention objective.
Federal Register 2010, 2011, 2012, 2013, 2014
2010-08-31
... factors as the approved models, are validated by experimental test data, and receive the Administrator's... stage of the MEP involves applying the model against a database of experimental test cases including..., particularly the requirement for validation by experimental test data. That guidance is based on the MEP's...
Coluccelli, Nicola
2010-08-01
Modeling a real laser diode stack based on Zemax ray tracing software that operates in a nonsequential mode is reported. The implementation of the model is presented together with the geometric and optical parameters to be adjusted to calibrate the model and to match the simulated intensity irradiance profiles with the experimental profiles. The calibration of the model is based on a near-field and a far-field measurement. The validation of the model has been accomplished by comparing the simulated and experimental transverse irradiance profiles at different positions along the caustic formed by a lens. Spot sizes and waist location are predicted with a maximum error below 6%.
Model updating in flexible-link multibody systems
NASA Astrophysics Data System (ADS)
Belotti, R.; Caneva, G.; Palomba, I.; Richiedei, D.; Trevisani, A.
2016-09-01
The dynamic response of flexible-link multibody systems (FLMSs) can be predicted through nonlinear models based on finite elements, to describe the coupling between rigid- body and elastic behaviour. Their accuracy should be as high as possible to synthesize controllers and observers. Model updating based on experimental measurements is hence necessary. By taking advantage of the experimental modal analysis, this work proposes a model updating procedure for FLMSs and applies it experimentally to a planar robot. Indeed, several peculiarities of the model of FLMS should be carefully tackled. On the one hand, nonlinear models of a FLMS should be linearized about static equilibrium configurations. On the other, the experimental mode shapes should be corrected to be consistent with the elastic displacements represented in the model, which are defined with respect to a fictitious moving reference (the equivalent rigid link system). Then, since rotational degrees of freedom are also represented in the model, interpolation of the experimental data should be performed to match the model displacement vector. Model updating has been finally cast as an optimization problem in the presence of bounds on the feasible values, by also adopting methods to improve the numerical conditioning and to compute meaningful updated inertial and elastic parameters.
Wet scrubbing of biomass producer gas tars using vegetable oil
NASA Astrophysics Data System (ADS)
Bhoi, Prakashbhai Ramabhai
The overall aims of this research study were to generate novel design data and to develop an equilibrium stage-based thermodynamic model of a vegetable oil based wet scrubbing system for the removal of model tar compounds (benzene, toluene and ethylbenzene) found in biomass producer gas. The specific objectives were to design, fabricate and evaluate a vegetable oil based wet scrubbing system and to optimize the design and operating variables; i.e., packed bed height, vegetable oil type, solvent temperature, and solvent flow rate. The experimental wet packed bed scrubbing system includes a liquid distributor specifically designed to distribute a high viscous vegetable oil uniformly and a mixing section, which was designed to generate a desired concentration of tar compounds in a simulated air stream. A method and calibration protocol of gas chromatography/mass spectroscopy was developed to quantify tar compounds. Experimental data were analyzed statistically using analysis of variance (ANOVA) procedure. Statistical analysis showed that both soybean and canola oils are potential solvents, providing comparable removal efficiency of tar compounds. The experimental height equivalent to a theoretical plate (HETP) was determined as 0.11 m for vegetable oil based scrubbing system. Packed bed height and solvent temperature had highly significant effect (p0.05) effect on the removal of model tar compounds. The packing specific constants, Ch and CP,0, for the Billet and Schultes pressure drop correlation were determined as 2.52 and 2.93, respectively. The equilibrium stage based thermodynamic model predicted the removal efficiency of model tar compounds in the range of 1-6%, 1-4% and 1-2% of experimental data for benzene, toluene and ethylbenzene, respectively, for the solvent temperature of 30° C. The NRTL-PR property model and UNIFAC for estimating binary interaction parameters are recommended for modeling absorption of tar compounds in vegetable oils. Bench scale experimental data from the wet scrubbing system would be useful in the design and operation of a pilot scale vegetable oil based system. The process model, validated using experimental data, would be a key design tool for the design and optimization of a pilot scale vegetable oil based system.
Luminance-model-based DCT quantization for color image compression
NASA Technical Reports Server (NTRS)
Ahumada, Albert J., Jr.; Peterson, Heidi A.
1992-01-01
A model is developed to approximate visibility thresholds for discrete cosine transform (DCT) coefficient quantization error based on the peak-to-peak luminance of the error image. Experimentally measured visibility thresholds for R, G, and B DCT basis functions can be predicted by a simple luminance-based detection model. This model allows DCT coefficient quantization matrices to be designed for display conditions other than those of the experimental measurements: other display luminances, other veiling luminances, and other spatial frequencies (different pixel spacings, viewing distances, and aspect ratios).
EPR-based material modelling of soils
NASA Astrophysics Data System (ADS)
Faramarzi, Asaad; Alani, Amir M.
2013-04-01
In the past few decades, as a result of the rapid developments in computational software and hardware, alternative computer aided pattern recognition approaches have been introduced to modelling many engineering problems, including constitutive modelling of materials. The main idea behind pattern recognition systems is that they learn adaptively from experience and extract various discriminants, each appropriate for its purpose. In this work an approach is presented for developing material models for soils based on evolutionary polynomial regression (EPR). EPR is a recently developed hybrid data mining technique that searches for structured mathematical equations (representing the behaviour of a system) using genetic algorithm and the least squares method. Stress-strain data from triaxial tests are used to train and develop EPR-based material models for soil. The developed models are compared with some of the well-known conventional material models and it is shown that EPR-based models can provide a better prediction for the behaviour of soils. The main benefits of using EPR-based material models are that it provides a unified approach to constitutive modelling of all materials (i.e., all aspects of material behaviour can be implemented within a unified environment of an EPR model); it does not require any arbitrary choice of constitutive (mathematical) models. In EPR-based material models there are no material parameters to be identified. As the model is trained directly from experimental data therefore, EPR-based material models are the shortest route from experimental research (data) to numerical modelling. Another advantage of EPR-based constitutive model is that as more experimental data become available, the quality of the EPR prediction can be improved by learning from the additional data, and therefore, the EPR model can become more effective and robust. The developed EPR-based material models can be incorporated in finite element (FE) analysis.
Student use of model-based reasoning when troubleshooting an electronic circuit
NASA Astrophysics Data System (ADS)
Lewandowski, Heather; Stetzer, Mackenzie; van de Bogart, Kevin; Dounas-Frazer, Dimitri
2016-03-01
Troubleshooting systems is an integral part of experimental physics in both research and educational settings. Accordingly, ability to troubleshoot is an important learning goal for undergraduate physics lab courses. We investigate students' model-based reasoning on a troubleshooting task using data collected in think-aloud interviews during which pairs of students from two institutions attempted to diagnose and repair a malfunctioning circuit. Our analysis scheme was informed by the Experimental Modeling Framework, which describes physicists' use of mathematical and conceptual models when reasoning about experimental systems. We show that system and subsystem models were crucial for the evaluation of repairs to the circuit and played an important role in some troubleshooting strategies. Finally, drawing on data from interviews with electronics instructors from a broad range of institution types, we outline recommendations for model-based approaches to teaching and learning troubleshooting skills.
Student use of model-based reasoning when troubleshooting an electric circuit
NASA Astrophysics Data System (ADS)
Dounas-Frazer, Dimitri
2016-05-01
Troubleshooting systems is an integral part of experimental physics in both research and educational settings. Accordingly, ability to troubleshoot is an important learning goal for undergraduate physics lab courses. We investigate students' model-based reasoning on a troubleshooting task using data collected in think-aloud interviews during which pairs of students from two institutions attempted to diagnose and repair a malfunctioning circuit. Our analysis scheme was informed by the Experimental Modeling Framework, which describes physicists' use of mathematical and conceptual models when reasoning about experimental systems. We show that system and subsystem models were crucial for the evaluation of repairs to the circuit and played an important role in some troubleshooting strategies. Finally, drawing on data from interviews with electronics instructors from a broad range of institution types, we outline recommendations for model-based approaches to teaching and learning troubleshooting skills.
Modeling of circulating fluised beds for post-combustion carbon capture
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lee, A.; Shadle, L.; Miller, D.
2011-01-01
A compartment based model for a circulating fluidized bed reactor has been developed based on experimental observations of riser hydrodynamics. The model uses a cluster based approach to describe the two-phase behavior of circulating fluidized beds. Fundamental mass balance equations have been derived to describe the movement of both gas and solids though the system. Additional work is being performed to develop the correlations required to describe the hydrodynamics of the system. Initial testing of the model with experimental data shows promising results and highlights the importance of including end effects within the model.
Joint surface modeling with thin-plate splines.
Boyd, S K; Ronsky, J L; Lichti, D D; Salkauskas, K; Chapman, M A; Salkauskas, D
1999-10-01
Mathematical joint surface models based on experimentally determined data points can be used to investigate joint characteristics such as curvature, congruency, cartilage thickness, joint contact areas, as well as to provide geometric information well suited for finite element analysis. Commonly, surface modeling methods are based on B-splines, which involve tensor products. These methods have had success; however, they are limited due to the complex organizational aspect of working with surface patches, and modeling unordered, scattered experimental data points. An alternative method for mathematical joint surface modeling is presented based on the thin-plate spline (TPS). It has the advantage that it does not involve surface patches, and can model scattered data points without experimental data preparation. An analytical surface was developed and modeled with the TPS to quantify its interpolating and smoothing characteristics. Some limitations of the TPS include discontinuity of curvature at exactly the experimental surface data points, and numerical problems dealing with data sets in excess of 2000 points. However, suggestions for overcoming these limitations are presented. Testing the TPS with real experimental data, the patellofemoral joint of a cat was measured with multistation digital photogrammetry and modeled using the TPS to determine cartilage thicknesses and surface curvature. The cartilage thickness distribution ranged between 100 to 550 microns on the patella, and 100 to 300 microns on the femur. It was found that the TPS was an effective tool for modeling joint surfaces because no preparation of the experimental data points was necessary, and the resulting unique function representing the entire surface does not involve surface patches. A detailed algorithm is presented for implementation of the TPS.
Experimental demonstration of a measurement-based realisation of a quantum channel
NASA Astrophysics Data System (ADS)
McCutcheon, W.; McMillan, A.; Rarity, J. G.; Tame, M. S.
2018-03-01
We introduce and experimentally demonstrate a method for realising a quantum channel using the measurement-based model. Using a photonic setup and modifying the basis of single-qubit measurements on a four-qubit entangled cluster state, representative channels are realised for the case of a single qubit in the form of amplitude and phase damping channels. The experimental results match the theoretical model well, demonstrating the successful performance of the channels. We also show how other types of quantum channels can be realised using our approach. This work highlights the potential of the measurement-based model for realising quantum channels which may serve as building blocks for simulations of realistic open quantum systems.
Experimental Research on the Dense CFB's Riser and the Simulation Based on the EMMS Model
NASA Astrophysics Data System (ADS)
Wang, X. Y.; Wang, S. D.; Fan, B. G.; Liao, L. L.; Jiang, F.; Xu, X.; Wu, X. Z.; Xiao, Y. H.
2010-03-01
The flow structure in the CFB (circulating fluidized bed) riser has been investigated. Experimental studies were performed in a cold square section unit with 270 mm×270 mm×10 m. Since the drag force model based on homogeneous two-phase flow such as the Gidaspow drag model could not depict the heterogeneous structures of the gas-solid flow, the structure-dependent energy-minimization multi-scale (EMMS) model based on the heterogenerity was applied in the paper and a revised drag force model based on the EMMS model was proposed. A 2D two-fluid model was used to simulate a bench-scale square cross-section riser of a cold CFB. The typical core-annulus structure and the back-mixing near the wall of the riser were observed and the assembly and fragmentation processes of clusters were captured. By comparing with the Gidaspow drag model, the results obtained by the revised drag model based on EMMS shows better consistency with the experimental data. The model can also depict the difference from the two exit configurations. This study once again proves the key role of drag force in CFD (Computational Fluid Dynamics) simulation and also shows the availability of the revised drag model to describe the gas-solid flow in CFB risers.
An Improved Swarm Optimization for Parameter Estimation and Biological Model Selection
Abdullah, Afnizanfaizal; Deris, Safaai; Mohamad, Mohd Saberi; Anwar, Sohail
2013-01-01
One of the key aspects of computational systems biology is the investigation on the dynamic biological processes within cells. Computational models are often required to elucidate the mechanisms and principles driving the processes because of the nonlinearity and complexity. The models usually incorporate a set of parameters that signify the physical properties of the actual biological systems. In most cases, these parameters are estimated by fitting the model outputs with the corresponding experimental data. However, this is a challenging task because the available experimental data are frequently noisy and incomplete. In this paper, a new hybrid optimization method is proposed to estimate these parameters from the noisy and incomplete experimental data. The proposed method, called Swarm-based Chemical Reaction Optimization, integrates the evolutionary searching strategy employed by the Chemical Reaction Optimization, into the neighbouring searching strategy of the Firefly Algorithm method. The effectiveness of the method was evaluated using a simulated nonlinear model and two biological models: synthetic transcriptional oscillators, and extracellular protease production models. The results showed that the accuracy and computational speed of the proposed method were better than the existing Differential Evolution, Firefly Algorithm and Chemical Reaction Optimization methods. The reliability of the estimated parameters was statistically validated, which suggests that the model outputs produced by these parameters were valid even when noisy and incomplete experimental data were used. Additionally, Akaike Information Criterion was employed to evaluate the model selection, which highlighted the capability of the proposed method in choosing a plausible model based on the experimental data. In conclusion, this paper presents the effectiveness of the proposed method for parameter estimation and model selection problems using noisy and incomplete experimental data. This study is hoped to provide a new insight in developing more accurate and reliable biological models based on limited and low quality experimental data. PMID:23593445
Experimental modeling of swirl flows in power plants
NASA Astrophysics Data System (ADS)
Shtork, S. I.; Litvinov, I. V.; Gesheva, E. S.; Tsoy, M. A.; Skripkin, S. G.
2018-03-01
The article presents an overview of the methods and approaches to experimental modeling of various thermal and hydropower units - furnaces of pulverized coal boilers and flow-through elements of hydro turbines. The presented modeling approaches based on a combination of experimentation and rapid prototyping of working parts may be useful in optimizing energy equipment to improve safety and efficiency of industrial energy systems.
A global parallel model based design of experiments method to minimize model output uncertainty.
Bazil, Jason N; Buzzard, Gregory T; Rundell, Ann E
2012-03-01
Model-based experiment design specifies the data to be collected that will most effectively characterize the biological system under study. Existing model-based design of experiment algorithms have primarily relied on Fisher Information Matrix-based methods to choose the best experiment in a sequential manner. However, these are largely local methods that require an initial estimate of the parameter values, which are often highly uncertain, particularly when data is limited. In this paper, we provide an approach to specify an informative sequence of multiple design points (parallel design) that will constrain the dynamical uncertainty of the biological system responses to within experimentally detectable limits as specified by the estimated experimental noise. The method is based upon computationally efficient sparse grids and requires only a bounded uncertain parameter space; it does not rely upon initial parameter estimates. The design sequence emerges through the use of scenario trees with experimental design points chosen to minimize the uncertainty in the predicted dynamics of the measurable responses of the system. The algorithm was illustrated herein using a T cell activation model for three problems that ranged in dimension from 2D to 19D. The results demonstrate that it is possible to extract useful information from a mathematical model where traditional model-based design of experiments approaches most certainly fail. The experiments designed via this method fully constrain the model output dynamics to within experimentally resolvable limits. The method is effective for highly uncertain biological systems characterized by deterministic mathematical models with limited data sets. Also, it is highly modular and can be modified to include a variety of methodologies such as input design and model discrimination.
[RESEARCH PROGRESS OF EXPERIMENTAL ANIMAL MODELS OF AVASCULAR NECROSIS OF FEMORAL HEAD].
Yu, Kaifu; Tan, Hongbo; Xu, Yongqing
2015-12-01
To summarize the current researches and progress on experimental animal models of avascular necrosis of the femoral head. Domestic and internation literature concerning experimental animal models of avascular necrosis of the femoral head was reviewed and analyzed. The methods to prepare the experimental animal models of avascular necrosis of the femoral head can be mainly concluded as traumatic methods (including surgical, physical, and chemical insult), and non-traumatic methods (including steroid, lipopolysaccharide, steroid combined with lipopolysaccharide, steroid combined with horse serum, etc). Each method has both merits and demerits, yet no ideal methods have been developed. There are many methods to prepare the experimental animal models of avascular necrosis of the femoral head, but proper model should be selected based on the aim of research. The establishment of ideal experimental animal models needs further research in future.
NASA Technical Reports Server (NTRS)
Chambers, A. B.; Blackaby, J. R.; Miles, J. B.
1973-01-01
Experimental results for three subjects walking on a treadmill at exercise rates of up to 590 watts showed that thermal comfort could be maintained in a liquid cooled garment by using an automatic temperature controller based on sweat rate. The addition of head- and neck-cooling to an Apollo type liquid cooled garment increased its effectiveness and resulted in greater subjective comfort. The biothermal model of man developed in the second portion of the study utilized heat rates and exchange coefficients based on the experimental data, and included the cooling provisions of a liquid-cooled garment with automatic temperature control based on sweat rate. Simulation results were good approximations of the experimental results.
Formulation of an experimental substructure model using a Craig-Bampton based transmission simulator
Kammer, Daniel C.; Allen, Matthew S.; Mayes, Randall L.
2015-09-26
An experimental–analytical substructuring is attractive when there is motivation to replace one or more system subcomponents with an experimental model. This experimentally derived substructure can then be coupled to finite element models of the rest of the structure to predict the system response. The transmission simulator method couples a fixture to the component of interest during a vibration test in order to improve the experimental model for the component. The transmission simulator is then subtracted from the tested system to produce the experimental component. This method reduces ill-conditioning by imposing a least squares fit of constraints between substructure modal coordinatesmore » to connect substructures, instead of directly connecting physical interface degrees of freedom. This paper presents an alternative means of deriving the experimental substructure model, in which a Craig–Bampton representation of the transmission simulator is created and subtracted from the experimental measurements. The corresponding modal basis of the transmission simulator is described by the fixed-interface modes, rather than free modes that were used in the original approach. Moreover, these modes do a better job of representing the shape of the transmission simulator as it responds within the experimental system, leading to more accurate results using fewer modes. The new approach is demonstrated using a simple finite element model based example with a redundant interface.« less
Formulation of an experimental substructure model using a Craig-Bampton based transmission simulator
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kammer, Daniel C.; Allen, Matthew S.; Mayes, Randall L.
An experimental–analytical substructuring is attractive when there is motivation to replace one or more system subcomponents with an experimental model. This experimentally derived substructure can then be coupled to finite element models of the rest of the structure to predict the system response. The transmission simulator method couples a fixture to the component of interest during a vibration test in order to improve the experimental model for the component. The transmission simulator is then subtracted from the tested system to produce the experimental component. This method reduces ill-conditioning by imposing a least squares fit of constraints between substructure modal coordinatesmore » to connect substructures, instead of directly connecting physical interface degrees of freedom. This paper presents an alternative means of deriving the experimental substructure model, in which a Craig–Bampton representation of the transmission simulator is created and subtracted from the experimental measurements. The corresponding modal basis of the transmission simulator is described by the fixed-interface modes, rather than free modes that were used in the original approach. Moreover, these modes do a better job of representing the shape of the transmission simulator as it responds within the experimental system, leading to more accurate results using fewer modes. The new approach is demonstrated using a simple finite element model based example with a redundant interface.« less
Van Daele, Timothy; Gernaey, Krist V; Ringborg, Rolf H; Börner, Tim; Heintz, Søren; Van Hauwermeiren, Daan; Grey, Carl; Krühne, Ulrich; Adlercreutz, Patrick; Nopens, Ingmar
2017-09-01
The aim of model calibration is to estimate unique parameter values from available experimental data, here applied to a biocatalytic process. The traditional approach of first gathering data followed by performing a model calibration is inefficient, since the information gathered during experimentation is not actively used to optimize the experimental design. By applying an iterative robust model-based optimal experimental design, the limited amount of data collected is used to design additional informative experiments. The algorithm is used here to calibrate the initial reaction rate of an ω-transaminase catalyzed reaction in a more accurate way. The parameter confidence region estimated from the Fisher Information Matrix is compared with the likelihood confidence region, which is not only more accurate but also a computationally more expensive method. As a result, an important deviation between both approaches is found, confirming that linearization methods should be applied with care for nonlinear models. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 33:1278-1293, 2017. © 2017 American Institute of Chemical Engineers.
Parameter estimation for lithium ion batteries
NASA Astrophysics Data System (ADS)
Santhanagopalan, Shriram
With an increase in the demand for lithium based batteries at the rate of about 7% per year, the amount of effort put into improving the performance of these batteries from both experimental and theoretical perspectives is increasing. There exist a number of mathematical models ranging from simple empirical models to complicated physics-based models to describe the processes leading to failure of these cells. The literature is also rife with experimental studies that characterize the various properties of the system in an attempt to improve the performance of lithium ion cells. However, very little has been done to quantify the experimental observations and relate these results to the existing mathematical models. In fact, the best of the physics based models in the literature show as much as 20% discrepancy when compared to experimental data. The reasons for such a big difference include, but are not limited to, numerical complexities involved in extracting parameters from experimental data and inconsistencies in interpreting directly measured values for the parameters. In this work, an attempt has been made to implement simplified models to extract parameter values that accurately characterize the performance of lithium ion cells. The validity of these models under a variety of experimental conditions is verified using a model discrimination procedure. Transport and kinetic properties are estimated using a non-linear estimation procedure. The initial state of charge inside each electrode is also maintained as an unknown parameter, since this value plays a significant role in accurately matching experimental charge/discharge curves with model predictions and is not readily known from experimental data. The second part of the dissertation focuses on parameters that change rapidly with time. For example, in the case of lithium ion batteries used in Hybrid Electric Vehicle (HEV) applications, the prediction of the State of Charge (SOC) of the cell under a variety of road conditions is important. An algorithm to predict the SOC in time intervals as small as 5 ms is of critical demand. In such cases, the conventional non-linear estimation procedure is not time-effective. There exist methodologies in the literature, such as those based on fuzzy logic; however, these techniques require a lot of computational storage space. Consequently, it is not possible to implement such techniques on a micro-chip for integration as a part of a real-time device. The Extended Kalman Filter (EKF) based approach presented in this work is a first step towards developing an efficient method to predict online, the State of Charge of a lithium ion cell based on an electrochemical model. The final part of the dissertation focuses on incorporating uncertainty in parameter values into electrochemical models using the polynomial chaos theory (PCT).
NASA Technical Reports Server (NTRS)
Rehfield, Lawrence W.; Zischka, Peter J.; Fentress, Michael L.; Chang, Stephen
1992-01-01
Some of the unique considerations that are associated with the design and experimental evaluation of chordwise deformable wing structures are addressed. Since chordwise elastic camber deformations are desired and must be free to develop, traditional rib concepts and experimental methodology cannot be used. New rib design concepts are presented and discussed. An experimental methodology based upon the use of a flexible sling support and load application system has been created and utilized to evaluate a model box beam experimentally. Experimental data correlate extremely well with design analysis predictions based upon a beam model for the global properties of camber compliance and spanwise bending compliance. Local strain measurements exhibit trends in agreement with intuition and theory but depart slightly from theoretical perfection based upon beam-like behavior alone. It is conjectured that some additional refinement of experimental technique is needed to explain or eliminate these (minor) departures from asymmetric behavior of upper and lower box cover strains. Overall, a solid basis for the design of box structures based upon the bending method of elastic camber production has been confirmed by the experiments.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hills, Richard G.; Maniaci, David Charles; Naughton, Jonathan W.
2015-09-01
A Verification and Validation (V&V) framework is presented for the development and execution of coordinated modeling and experimental program s to assess the predictive capability of computational models of complex systems through focused, well structured, and formal processes.The elements of the framework are based on established V&V methodology developed by various organizations including the Department of Energy, National Aeronautics and Space Administration, the American Institute of Aeronautics and Astronautics, and the American Society of Mechanical Engineers. Four main topics are addressed: 1) Program planning based on expert elicitation of the modeling physics requirements, 2) experimental design for model assessment, 3)more » uncertainty quantification for experimental observations and computational model simulations, and 4) assessment of the model predictive capability. The audience for this document includes program planners, modelers, experimentalist, V &V specialist, and customers of the modeling results.« less
Assessing Consequential Scenarios in a Complex Operational Environment Using Agent Based Simulation
2017-03-16
RWISE) 93 5.1.5 Conflict Modeling, Planning, and Outcomes Experimentation Program (COMPOEX) 94 5.1.6 Joint Non -Kinetic Effects Model (JNEM)/Athena... experimental design and testing. 4.3.8 Types and Attributes of Agent-Based Model Design Patterns Using the aforementioned ABM flowchart design methodology ...speed, or flexibility during tactical US Army wargaming. The report considers methodologies to improve analysis of the human domain, identifies
Validation of radiocarpal joint contact models based on images from a clinical MRI scanner.
Johnson, Joshua E; McIff, Terence E; Lee, Phil; Toby, E Bruce; Fischer, Kenneth J
2014-01-01
This study was undertaken to assess magnetic resonance imaging (MRI)-based radiocarpal surface contact models of functional loading in a clinical MRI scanner for future in vivo studies, by comparison with experimental measures from three cadaver forearm specimens. Experimental data were acquired using a Tekscan sensor during simulated light grasp. Magnetic resonance (MR) images were used to obtain model geometry and kinematics (image registration). Peak contact pressures (PPs) and average contact pressures (APs), contact forces and contact areas were determined in the radiolunate and radioscaphoid joints. Contact area was also measured directly from MR images acquired with load and compared with model data. Based on the validation criteria (within 25% of experimental data), out of the six articulations (three specimens with two articulations each), two met the criterion for AP (0%, 14%); one for peak pressure (20%); one for contact force (5%); four for contact area with respect to experiment (8%, 13%, 19% and 23%), and three contact areas met the criterion with respect to direct measurements (14%, 21% and 21%). Absolute differences between model and experimental PPs were reasonably low (within 2.5 MPa). Overall, the results indicate that MRI-based models generated from 3T clinical MR scanner appear sufficient to obtain clinically relevant data.
A model for generating Surface EMG signal of m. Tibialis Anterior.
Siddiqi, Ariba; Kumar, Dinesh; Arjunan, Sridhar P
2014-01-01
A model that simulates surface electromyogram (sEMG) signal of m. Tibialis Anterior has been developed and tested. This has a firing rate equation that is based on experimental findings. It also has a recruitment threshold that is based on observed statistical distribution. Importantly, it has considered both, slow and fast type which has been distinguished based on their conduction velocity. This model has assumed that the deeper unipennate half of the muscle does not contribute significantly to the potential induced on the surface of the muscle and has approximated the muscle to have parallel structure. The model was validated by comparing the simulated and the experimental sEMG signal recordings. Experiments were conducted on eight subjects who performed isometric dorsiflexion at 10, 20, 30, 50, 75, and 100% maximal voluntary contraction. Normalized root mean square and median frequency of the experimental and simulated EMG signal were computed and the slopes of the linearity with the force were statistically analyzed. The gradients were found to be similar (p>0.05) for both experimental and simulated sEMG signal, validating the proposed model.
NASA Astrophysics Data System (ADS)
Afkhamipour, Morteza; Mofarahi, Masoud; Borhani, Tohid Nejad Ghaffar; Zanganeh, Masoud
2018-03-01
In this study, artificial neural network (ANN) and thermodynamic models were developed for prediction of the heat capacity ( C P ) of amine-based solvents. For ANN model, independent variables such as concentration, temperature, molecular weight and CO2 loading of amine were selected as the inputs of the model. The significance of the input variables of the ANN model on the C P values was investigated statistically by analyzing of correlation matrix. A thermodynamic model based on the Redlich-Kister equation was used to correlate the excess molar heat capacity ({C}_P^E) data as function of temperature. In addition, the effects of temperature and CO2 loading at different concentrations of conventional amines on the C P values were investigated. Both models were validated against experimental data and very good results were obtained between two mentioned models and experimental data of C P collected from various literatures. The AARD between ANN model results and experimental data of C P for 47 systems of amine-based solvents studied was 4.3%. For conventional amines, the AARD for ANN model and thermodynamic model in comparison with experimental data were 0.59% and 0.57%, respectively. The results showed that both ANN and Redlich-Kister models can be used as a practical tool for simulation and designing of CO2 removal processes by using amine solutions.
Modeling the Structure of Helical Assemblies with Experimental Constraints in Rosetta.
André, Ingemar
2018-01-01
Determining high-resolution structures of proteins with helical symmetry can be challenging due to limitations in experimental data. In such instances, structure-based protein simulations driven by experimental data can provide a valuable approach for building models of helical assemblies. This chapter describes how the Rosetta macromolecular package can be used to model homomeric protein assemblies with helical symmetry in a range of modeling scenarios including energy refinement, symmetrical docking, comparative modeling, and de novo structure prediction. Data-guided structure modeling of helical assemblies with experimental information from electron density, X-ray fiber diffraction, solid-state NMR, and chemical cross-linking mass spectrometry is also described.
A strain-mediated corrosion model for bioabsorbable metallic stents.
Galvin, E; O'Brien, D; Cummins, C; Mac Donald, B J; Lally, C
2017-06-01
This paper presents a strain-mediated phenomenological corrosion model, based on the discrete finite element modelling method which was developed for use with the ANSYS Implicit finite element code. The corrosion model was calibrated from experimental data and used to simulate the corrosion performance of a WE43 magnesium alloy stent. The model was found to be capable of predicting the experimentally observed plastic strain-mediated mass loss profile. The non-linear plastic strain model, extrapolated from the experimental data, was also found to adequately capture the corrosion-induced reduction in the radial stiffness of the stent over time. The model developed will help direct future design efforts towards the minimisation of plastic strain during device manufacture, deployment and in-service, in order to reduce corrosion rates and prolong the mechanical integrity of magnesium devices. The need for corrosion models that explore the interaction of strain with corrosion damage has been recognised as one of the current challenges in degradable material modelling (Gastaldi et al., 2011). A finite element based plastic strain-mediated phenomenological corrosion model was developed in this work and was calibrated based on the results of the corrosion experiments. It was found to be capable of predicting the experimentally observed plastic strain-mediated mass loss profile and the corrosion-induced reduction in the radial stiffness of the stent over time. To the author's knowledge, the results presented here represent the first experimental calibration of a plastic strain-mediated corrosion model of a corroding magnesium stent. Copyright © 2017 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.
Description of alpha-nucleus interaction cross sections for cosmic ray shielding studies
NASA Technical Reports Server (NTRS)
Cucinotta, Francis A.; Townsend, Lawrence W.; Wilson, John W.
1993-01-01
Nuclear interactions of high-energy alpha particles with target nuclei important for cosmic ray studies are discussed. Models for elastic, quasi-elastic, and breakup reactions are presented and compared with experimental data. Energy-dependent interaction cross sections and secondary spectra are presented based on theoretical models and the limited experimental data base.
NASA Astrophysics Data System (ADS)
Savari, Maryam; Moghaddam, Amin Hedayati; Amiri, Ahmad; Shanbedi, Mehdi; Ayub, Mohamad Nizam Bin
2017-10-01
Herein, artificial neural network and adaptive neuro-fuzzy inference system are employed for modeling the effects of important parameters on heat transfer and fluid flow characteristics of a car radiator and followed by comparing with those of the experimental results for testing data. To this end, two novel nanofluids (water/ethylene glycol-based graphene and nitrogen-doped graphene nanofluids) were experimentally synthesized. Then, Nusselt number was modeled with respect to the variation of inlet temperature, Reynolds number, Prandtl number and concentration, which were defined as the input (design) variables. To reach reliable results, we divided these data into train and test sections to accomplish modeling. Artificial networks were instructed by a major part of experimental data. The other part of primary data which had been considered for testing the appropriateness of the models was entered into artificial network models. Finally, predictad results were compared to the experimental data to evaluate validity. Confronted with high-level of validity confirmed that the proposed modeling procedure by BPNN with one hidden layer and five neurons is efficient and it can be expanded for all water/ethylene glycol-based carbon nanostructures nanofluids. Finally, we expanded our data collection from model and could present a fundamental correlation for calculating Nusselt number of the water/ethylene glycol-based nanofluids including graphene or nitrogen-doped graphene.
NASA Astrophysics Data System (ADS)
Sellami, Takwa; Jelassi, Sana; Darcherif, Abdel Moumen; Berriri, Hanen; Mimouni, Med Faouzi
2018-04-01
With the advancement of wind turbines towards complex structures, the requirement of trusty structural models has become more apparent. Hence, the vibration characteristics of the wind turbine components, like the blades and the tower, have to be extracted under vibration constraints. Although extracting the modal properties of blades is a simple task, calculating precise modal data for the whole wind turbine coupled to its tower/foundation is still a perplexing task. In this framework, this paper focuses on the investigation of the structural modeling approach of modern commercial micro-turbines. Thus, the structural model a complex designed wind turbine, which is Rutland 504, is established based on both experimental and numerical methods. A three-dimensional (3-D) numerical model of the structure was set up based on the finite volume method (FVM) using the academic finite element analysis software ANSYS. To validate the created model, experimental vibration tests were carried out using the vibration test system of TREVISE platform at ECAM-EPMI. The tests were based on the experimental modal analysis (EMA) technique, which is one of the most efficient techniques for identifying structures parameters. Indeed, the poles and residues of the frequency response functions (FRF), between input and output spectra, were calculated to extract the mode shapes and the natural frequencies of the structure. Based on the obtained modal parameters, the numerical designed model was up-dated.
Helgason, Benedikt; Viceconti, Marco; Rúnarsson, Tómas P; Brynjólfsson, Sigurour
2008-01-01
Pushout tests can be used to estimate the shear strength of the bone implant interface. Numerous such experimental studies have been published in the literature. Despite this researchers are still some way off with respect to the development of accurate numerical models to simulate implant stability. In the present work a specific experimental pushout study from the literature was simulated using two different bones implant interface models. The implant was a porous coated Ti-6Al-4V retrieved 4 weeks postoperatively from a dog model. The purpose was to find out which of the interface models could replicate the experimental results using physically meaningful input parameters. The results showed that a model based on partial bone ingrowth (ingrowth stability) is superior to an interface model based on friction and prestressing due to press fit (initial stability). Even though the present study is limited to a single experimental setup, the authors suggest that the presented methodology can be used to investigate implant stability from other experimental pushout models. This would eventually enhance the much needed understanding of the mechanical response of the bone implant interface and help to quantify how implant stability evolves with time.
Validation and upgrading of physically based mathematical models
NASA Technical Reports Server (NTRS)
Duval, Ronald
1992-01-01
The validation of the results of physically-based mathematical models against experimental results was discussed. Systematic techniques are used for: (1) isolating subsets of the simulator mathematical model and comparing the response of each subset to its experimental response for the same input conditions; (2) evaluating the response error to determine whether it is the result of incorrect parameter values, incorrect structure of the model subset, or unmodeled external effects of cross coupling; and (3) modifying and upgrading the model and its parameter values to determine the most physically appropriate combination of changes.
Mechanisms of Hydrocarbon Based Polymer Etch
NASA Astrophysics Data System (ADS)
Lane, Barton; Ventzek, Peter; Matsukuma, Masaaki; Suzuki, Ayuta; Koshiishi, Akira
2015-09-01
Dry etch of hydrocarbon based polymers is important for semiconductor device manufacturing. The etch mechanisms for oxygen rich plasma etch of hydrocarbon based polymers has been studied but the mechanism for lean chemistries has received little attention. We report on an experimental and analytic study of the mechanism for etching of a hydrocarbon based polymer using an Ar/O2 chemistry in a single frequency 13.56 MHz test bed. The experimental study employs an analysis of transients from sequential oxidation and Ar sputtering steps using OES and surface analytics to constrain conceptual models for the etch mechanism. The conceptual model is consistent with observations from MD studies and surface analysis performed by Vegh et al. and Oehrlein et al. and other similar studies. Parameters of the model are fit using published data and the experimentally observed time scales.
2006-04-17
of the droplet phase are then used for validation of theoretical models of the gas-droplet plume flow. Based on experimental and numerical results...with the continuous model adequately reproduces the Arrhenius rate at high temperatures but significantly underpredicts the theoretical rate at low...continuous model and discrete model of real gas effects, and the results on the shock -wave stand-off distance were compared with the experimental data of
NASA Astrophysics Data System (ADS)
Guy, N.; Seyedi, D. M.; Hild, F.
2018-06-01
The work presented herein aims at characterizing and modeling fracturing (i.e., initiation and propagation of cracks) in a clay-rich rock. The analysis is based on two experimental campaigns. The first one relies on a probabilistic analysis of crack initiation considering Brazilian and three-point flexural tests. The second one involves digital image correlation to characterize crack propagation. A nonlocal damage model based on stress regularization is used for the simulations. Two thresholds both based on regularized stress fields are considered. They are determined from the experimental campaigns performed on Lower Watrous rock. The results obtained with the proposed approach are favorably compared with the experimental results.
Galvanin, Federico; Ballan, Carlo C; Barolo, Massimiliano; Bezzo, Fabrizio
2013-08-01
The use of pharmacokinetic (PK) and pharmacodynamic (PD) models is a common and widespread practice in the preliminary stages of drug development. However, PK-PD models may be affected by structural identifiability issues intrinsically related to their mathematical formulation. A preliminary structural identifiability analysis is usually carried out to check if the set of model parameters can be uniquely determined from experimental observations under the ideal assumptions of noise-free data and no model uncertainty. However, even for structurally identifiable models, real-life experimental conditions and model uncertainty may strongly affect the practical possibility to estimate the model parameters in a statistically sound way. A systematic procedure coupling the numerical assessment of structural identifiability with advanced model-based design of experiments formulations is presented in this paper. The objective is to propose a general approach to design experiments in an optimal way, detecting a proper set of experimental settings that ensure the practical identifiability of PK-PD models. Two simulated case studies based on in vitro bacterial growth and killing models are presented to demonstrate the applicability and generality of the methodology to tackle model identifiability issues effectively, through the design of feasible and highly informative experiments.
Modified hyperbolic sine model for titanium dioxide-based memristive thin films
NASA Astrophysics Data System (ADS)
Abu Bakar, Raudah; Syahirah Kamarozaman, Nur; Fazlida Hanim Abdullah, Wan; Herman, Sukreen Hana
2018-03-01
Since the emergence of memristor as the newest fundamental circuit elements, studies on memristor modeling have been evolved. To date, the developed models were based on the linear model, linear ionic drift model using different window functions, tunnelling barrier model and hyperbolic-sine function based model. Although using hyperbolic-sine function model could predict the memristor electrical properties, the model was not well fitted to the experimental data. In order to improve the performance of the hyperbolic-sine function model, the state variable equation was modified. On the one hand, the addition of window function cannot provide an improved fitting. By multiplying the Yakopcic’s state variable model to Chang’s model on the other hand resulted in the closer agreement with the TiO2 thin film experimental data. The percentage error was approximately 2.15%.
Photovoltaic Grid-Connected Modeling and Characterization Based on Experimental Results.
Humada, Ali M; Hojabri, Mojgan; Sulaiman, Mohd Herwan Bin; Hamada, Hussein M; Ahmed, Mushtaq N
2016-01-01
A grid-connected photovoltaic (PV) system operates under fluctuated weather condition has been modeled and characterized based on specific test bed. A mathematical model of a small-scale PV system has been developed mainly for residential usage, and the potential results have been simulated. The proposed PV model based on three PV parameters, which are the photocurrent, IL, the reverse diode saturation current, Io, the ideality factor of diode, n. Accuracy of the proposed model and its parameters evaluated based on different benchmarks. The results showed that the proposed model fitting the experimental results with high accuracy compare to the other models, as well as the I-V characteristic curve. The results of this study can be considered valuable in terms of the installation of a grid-connected PV system in fluctuated climatic conditions.
Photovoltaic Grid-Connected Modeling and Characterization Based on Experimental Results
Humada, Ali M.; Hojabri, Mojgan; Sulaiman, Mohd Herwan Bin; Hamada, Hussein M.; Ahmed, Mushtaq N.
2016-01-01
A grid-connected photovoltaic (PV) system operates under fluctuated weather condition has been modeled and characterized based on specific test bed. A mathematical model of a small-scale PV system has been developed mainly for residential usage, and the potential results have been simulated. The proposed PV model based on three PV parameters, which are the photocurrent, IL, the reverse diode saturation current, Io, the ideality factor of diode, n. Accuracy of the proposed model and its parameters evaluated based on different benchmarks. The results showed that the proposed model fitting the experimental results with high accuracy compare to the other models, as well as the I-V characteristic curve. The results of this study can be considered valuable in terms of the installation of a grid-connected PV system in fluctuated climatic conditions. PMID:27035575
Bayesian Treed Calibration: An Application to Carbon Capture With AX Sorbent
DOE Office of Scientific and Technical Information (OSTI.GOV)
Konomi, Bledar A.; Karagiannis, Georgios; Lai, Kevin
2017-01-02
In cases where field or experimental measurements are not available, computer models can model real physical or engineering systems to reproduce their outcomes. They are usually calibrated in light of experimental data to create a better representation of the real system. Statistical methods, based on Gaussian processes, for calibration and prediction have been especially important when the computer models are expensive and experimental data limited. In this paper, we develop the Bayesian treed calibration (BTC) as an extension of standard Gaussian process calibration methods to deal with non-stationarity computer models and/or their discrepancy from the field (or experimental) data. Ourmore » proposed method partitions both the calibration and observable input space, based on a binary tree partitioning, into sub-regions where existing model calibration methods can be applied to connect a computer model with the real system. The estimation of the parameters in the proposed model is carried out using Markov chain Monte Carlo (MCMC) computational techniques. Different strategies have been applied to improve mixing. We illustrate our method in two artificial examples and a real application that concerns the capture of carbon dioxide with AX amine based sorbents. The source code and the examples analyzed in this paper are available as part of the supplementary materials.« less
Modelling of Batch Lactic Acid Fermentation in the Presence of Anionic Clay
Jinescu, Cosmin; Aruş, Vasilica Alisa; Nistor, Ileana Denisa
2014-01-01
Summary Batch fermentation of milk inoculated with lactic acid bacteria was conducted in the presence of hydrotalcite-type anionic clay under static and ultrasonic conditions. An experimental study of the effect of fermentation temperature (t=38–43 °C), clay/milk ratio (R=1–7.5 g/L) and ultrasonic field (ν=0 and 35 kHz) on process dynamics was performed. A mathematical model was selected to describe the fermentation process kinetics and its parameters were estimated based on experimental data. A good agreement between the experimental and simulated results was achieved. Consequently, the model can be employed to predict the dynamics of batch lactic acid fermentation with values of process variables in the studied ranges. A statistical analysis of the data based on a 23 factorial experiment was performed in order to express experimental and model-regressed process responses depending on t, R and ν factors. PMID:27904318
Theoretical modeling and experimental analysis of solar still integrated with evacuated tubes
NASA Astrophysics Data System (ADS)
Panchal, Hitesh; Awasthi, Anuradha
2017-06-01
In this present research work, theoretical modeling of single slope, single basin solar still integrated with evacuated tubes has been performed based on energy balance equations. Major variables like water temperature, inner glass cover temperature and distillate output has been computed based on theoretical modeling. The experimental setup has been made from locally available materials and installed at Gujarat Power Engineering and Research Institute, Mehsana, Gujarat, India (23.5880°N, 72.3693°E) with 0.04 m depth during 6 months of time interval. From the series of experiments, it is found considerable increment in average distillate output of a solar still when integrated with evacuated tubes not only during daytime but also from night time. In all experimental cases, the correlation of coefficient (r) and root mean square percentage deviation of theoretical modeling and experimental study found good agreement with 0.97 < r < 0.98 and 10.22 < e < 38.4% respectively.
Cyclic softening based on dislocation annihilation at sub-cell boundary for SA333 Grade-6 C-Mn steel
NASA Astrophysics Data System (ADS)
Bhattacharjee, S.; Dhar, S.; Acharyya, S. K.; Gupta, S. K.
2018-01-01
In this work, the response of SA333 Grade-6 C-Mn steel subjected to uniaxial and in-phase biaxial tension-torsion cyclic loading is experimented and an attempt is made to model the material behaviour. Experimentally observed cyclic softening is modelled based on ‘dislocation annihilation at low angle grain boundary’, while Ohno-Wang kinematic hardening rule is used to simulate the stress-strain hysteresis loops. The relevant material parameters are extracted from the appropriate experimental results and metallurgical investigations. The material model is plugged as user material subroutine into ABAQUS FE platform to simulate pre-saturation low cycle fatigue loops with cyclic softening and other cyclic plastic behaviour under prescribed loading. The stress-strain hysteresis loops and peak stress with cycles were compared with the experimental results and good agreements between experimental and simulated results validated the material model.
NASA Technical Reports Server (NTRS)
Powers, E. J.; Kim, Y. C.; Hong, J. Y.; Roth, J. R.; Krawczonek, W. M.
1978-01-01
A diagnostic, based on fast Fourier-transform spectral analysis techniques, that provides experimental insight into the relationship between the experimentally observable spectral characteristics of the fluctuations and the fluctuation-induced plasma transport is described. The model upon which the diagnostic technique is based and its experimental implementation is discussed. Some characteristic results obtained during the course of an experimental study of fluctuation-induced transport in the electric field dominated NASA Lewis bumpy torus plasma are presented.
Model-based high-throughput design of ion exchange protein chromatography.
Khalaf, Rushd; Heymann, Julia; LeSaout, Xavier; Monard, Florence; Costioli, Matteo; Morbidelli, Massimo
2016-08-12
This work describes the development of a model-based high-throughput design (MHD) tool for the operating space determination of a chromatographic cation-exchange protein purification process. Based on a previously developed thermodynamic mechanistic model, the MHD tool generates a large amount of system knowledge and thereby permits minimizing the required experimental workload. In particular, each new experiment is designed to generate information needed to help refine and improve the model. Unnecessary experiments that do not increase system knowledge are avoided. Instead of aspiring to a perfectly parameterized model, the goal of this design tool is to use early model parameter estimates to find interesting experimental spaces, and to refine the model parameter estimates with each new experiment until a satisfactory set of process parameters is found. The MHD tool is split into four sections: (1) prediction, high throughput experimentation using experiments in (2) diluted conditions and (3) robotic automated liquid handling workstations (robotic workstation), and (4) operating space determination and validation. (1) Protein and resin information, in conjunction with the thermodynamic model, is used to predict protein resin capacity. (2) The predicted model parameters are refined based on gradient experiments in diluted conditions. (3) Experiments on the robotic workstation are used to further refine the model parameters. (4) The refined model is used to determine operating parameter space that allows for satisfactory purification of the protein of interest on the HPLC scale. Each section of the MHD tool is used to define the adequate experimental procedures for the next section, thus avoiding any unnecessary experimental work. We used the MHD tool to design a polishing step for two proteins, a monoclonal antibody and a fusion protein, on two chromatographic resins, in order to demonstrate it has the ability to strongly accelerate the early phases of process development. Copyright © 2016 Elsevier B.V. All rights reserved.
Park, Hahnbeom; Lee, Gyu Rie; Heo, Lim; Seok, Chaok
2014-01-01
Protein loop modeling is a tool for predicting protein local structures of particular interest, providing opportunities for applications involving protein structure prediction and de novo protein design. Until recently, the majority of loop modeling methods have been developed and tested by reconstructing loops in frameworks of experimentally resolved structures. In many practical applications, however, the protein loops to be modeled are located in inaccurate structural environments. These include loops in model structures, low-resolution experimental structures, or experimental structures of different functional forms. Accordingly, discrepancies in the accuracy of the structural environment assumed in development of the method and that in practical applications present additional challenges to modern loop modeling methods. This study demonstrates a new strategy for employing a hybrid energy function combining physics-based and knowledge-based components to help tackle this challenge. The hybrid energy function is designed to combine the strengths of each energy component, simultaneously maintaining accurate loop structure prediction in a high-resolution framework structure and tolerating minor environmental errors in low-resolution structures. A loop modeling method based on global optimization of this new energy function is tested on loop targets situated in different levels of environmental errors, ranging from experimental structures to structures perturbed in backbone as well as side chains and template-based model structures. The new method performs comparably to force field-based approaches in loop reconstruction in crystal structures and better in loop prediction in inaccurate framework structures. This result suggests that higher-accuracy predictions would be possible for a broader range of applications. The web server for this method is available at http://galaxy.seoklab.org/loop with the PS2 option for the scoring function.
Ionic polymer-metal composite torsional sensor: physics-based modeling and experimental validation
NASA Astrophysics Data System (ADS)
Aidi Sharif, Montassar; Lei, Hong; Khalid Al-Rubaiai, Mohammed; Tan, Xiaobo
2018-07-01
Ionic polymer-metal composites (IPMCs) have intrinsic sensing and actuation properties. Typical IPMC sensors are in the shape of beams and only respond to stimuli acting along beam-bending directions. Rod or tube-shaped IPMCs have been explored as omnidirectional bending actuators or sensors. In this paper, physics-based modeling is studied for a tubular IPMC sensor under pure torsional stimulus. The Poisson–Nernst–Planck model is used to describe the fundamental physics within the IPMC, where it is hypothesized that the anion concentration is coupled to the sum of shear strains induced by the torsional stimulus. Finite element simulation is conducted to solve for the torsional sensing response, where some of the key parameters are identified based on experimental measurements using an artificial neural network. Additional experimental results suggest that the proposed model is able to capture the torsional sensing dynamics for different amplitudes and rates of the torsional stimulus.
Experimental evaluation and thermodynamic system modeling of thermoelectric heat pump clothes dryer
Patel, Viral K.; Gluesenkamp, Kyle R.; Goodman, Dakota; ...
2018-02-28
Electric clothes dryers consume about 6% of US residential electricity consumption. Using a solid-state technology without refrigerant, thermoelectric (TE) heat pump dryers have the potential to be more efficient than units based on electric resistance and less expensive than units based on vapor compression. This study presents a steady state TE dryer model, and validates the model against results from an experimental prototype. The system model is composed of a TE heat pump element model coupled with a psychrometric dryer sub-model. Experimental results had energy factors (EFs) of up to 2.95 kg of dry cloth per kWh (6.51 lb c/kWh),more » with a dry time of 159 min. A faster dry time of 96 min was also achieved at an EF of 2.54 kg c/kWh (5.60 lb c/kWh). The model was able to replicate the experimental results within 5% of EF and 5% of dry time values. Finally, the results are used to identify important parameters that affect dryer performance, such as relative humidity of air leaving the drum.« less
Experimental evaluation and thermodynamic system modeling of thermoelectric heat pump clothes dryer
DOE Office of Scientific and Technical Information (OSTI.GOV)
Patel, Viral K.; Gluesenkamp, Kyle R.; Goodman, Dakota
Electric clothes dryers consume about 6% of US residential electricity consumption. Using a solid-state technology without refrigerant, thermoelectric (TE) heat pump dryers have the potential to be more efficient than units based on electric resistance and less expensive than units based on vapor compression. This study presents a steady state TE dryer model, and validates the model against results from an experimental prototype. The system model is composed of a TE heat pump element model coupled with a psychrometric dryer sub-model. Experimental results had energy factors (EFs) of up to 2.95 kg of dry cloth per kWh (6.51 lb c/kWh),more » with a dry time of 159 min. A faster dry time of 96 min was also achieved at an EF of 2.54 kg c/kWh (5.60 lb c/kWh). The model was able to replicate the experimental results within 5% of EF and 5% of dry time values. Finally, the results are used to identify important parameters that affect dryer performance, such as relative humidity of air leaving the drum.« less
Modeling and experimental result analysis for high-power VECSELs
NASA Astrophysics Data System (ADS)
Zakharian, Aramais R.; Hader, Joerg; Moloney, Jerome V.; Koch, Stephan W.; Lutgen, Stephan; Brick, Peter; Albrecht, Tony; Grotsch, Stefan; Luft, Johann; Spath, Werner
2003-06-01
We present a comparison of experimental and microscopically based model results for optically pumped vertical external cavity surface emitting semiconductor lasers. The quantum well gain model is based on a quantitative ab-initio approach that allows calculation of a complex material susceptibility dependence on the wavelength, carrier density and lattice temperature. The gain model is coupled to the macroscopic thermal transport, spatially resolved in both the radial and longitudinal directions, with temperature and carrier density dependent pump absorption. The radial distribution of the refractive index and gain due to temperature variation are computed. Thermal managment issues, highlighted by the experimental data, are discussed. Experimental results indicate a critical dependence of the input power, at which thermal roll-over occurs, on the thermal resistance of the device. This requires minimization of the substrate thickness and optimization of the design and placement of the heatsink. Dependence of the model results on the radiative and non-radiative carrier recombination lifetimes and cavity losses are evaluated.
Drug Discovery in Fish, Flies, and Worms
Strange, Kevin
2016-01-01
Abstract Nonmammalian model organisms such as the nematode Caenorhabditis elegans, the fruit fly Drosophila melanogaster, and the zebrafish Danio rerio provide numerous experimental advantages for drug discovery including genetic and molecular tractability, amenability to high-throughput screening methods and reduced experimental costs and increased experimental throughput compared to traditional mammalian models. An interdisciplinary approach that strategically combines the study of nonmammalian and mammalian animal models with diverse experimental tools has and will continue to provide deep molecular and genetic understanding of human disease and will significantly enhance the discovery and application of new therapies to treat those diseases. This review will provide an overview of C. elegans, Drosophila, and zebrafish biology and husbandry and will discuss how these models are being used for phenotype-based drug screening and for identification of drug targets and mechanisms of action. The review will also describe how these and other nonmammalian model organisms are uniquely suited for the discovery of drug-based regenerative medicine therapies. PMID:28053067
NASA Astrophysics Data System (ADS)
Lee, Bo Mi; Loh, Kenneth J.
2017-04-01
Carbon nanotubes can be randomly deposited in polymer thin film matrices to form nanocomposite strain sensors. However, a computational framework that enables the direct design of these nanocomposite thin films is still lacking. The objective of this study is to derive an experimentally validated and two-dimensional numerical model of carbon nanotube-based thin film strain sensors. This study consisted of two parts. First, multi-walled carbon nanotube (MWCNT)-Pluronic strain sensors were fabricated using vacuum filtration, and their physical, electrical, and electromechanical properties were evaluated. Second, scanning electron microscope images of the films were used for identifying topological features of the percolated MWCNT network, where the information obtained was then utilized for developing the numerical model. Validation of the numerical model was achieved by ensuring that the area ratios (of MWCNTs relative to the polymer matrix) were equivalent for both the experimental and modeled cases. Strain sensing behavior of the percolation-based model was simulated and then compared to experimental test results.
Modeling and experimental study on characterization of micromachined thermal gas inertial sensors.
Zhu, Rong; Ding, Henggao; Su, Yan; Yang, Yongjun
2010-01-01
Micromachined thermal gas inertial sensors based on heat convection are novel devices that compared with conventional micromachined inertial sensors offer the advantages of simple structures, easy fabrication, high shock resistance and good reliability by virtue of using a gaseous medium instead of a mechanical proof mass as key moving and sensing elements. This paper presents an analytical modeling for a micromachined thermal gas gyroscope integrated with signal conditioning. A simplified spring-damping model is utilized to characterize the behavior of the sensor. The model relies on the use of the fluid mechanics and heat transfer fundamentals and is validated using experimental data obtained from a test-device and simulation. Furthermore, the nonideal issues of the sensor are addressed from both the theoretical and experimental points of view. The nonlinear behavior demonstrated in experimental measurements is analyzed based on the model. It is concluded that the sources of nonlinearity are mainly attributable to the variable stiffness of the sensor system and the structural asymmetry due to nonideal fabrication.
Properties of inductive reasoning.
Heit, E
2000-12-01
This paper reviews the main psychological phenomena of inductive reasoning, covering 25 years of experimental and model-based research, in particular addressing four questions. First, what makes a case or event generalizable to other cases? Second, what makes a set of cases generalizable? Third, what makes a property or predicate projectable? Fourth, how do psychological models of induction address these results? The key results in inductive reasoning are outlined, and several recent models, including a new Bayesian account, are evaluated with respect to these results. In addition, future directions for experimental and model-based work are proposed.
NASA Astrophysics Data System (ADS)
Machado, M. R.; Adhikari, S.; Dos Santos, J. M. C.; Arruda, J. R. F.
2018-03-01
Structural parameter estimation is affected not only by measurement noise but also by unknown uncertainties which are present in the system. Deterministic structural model updating methods minimise the difference between experimentally measured data and computational prediction. Sensitivity-based methods are very efficient in solving structural model updating problems. Material and geometrical parameters of the structure such as Poisson's ratio, Young's modulus, mass density, modal damping, etc. are usually considered deterministic and homogeneous. In this paper, the distributed and non-homogeneous characteristics of these parameters are considered in the model updating. The parameters are taken as spatially correlated random fields and are expanded in a spectral Karhunen-Loève (KL) decomposition. Using the KL expansion, the spectral dynamic stiffness matrix of the beam is expanded as a series in terms of discretized parameters, which can be estimated using sensitivity-based model updating techniques. Numerical and experimental tests involving a beam with distributed bending rigidity and mass density are used to verify the proposed method. This extension of standard model updating procedures can enhance the dynamic description of structural dynamic models.
NASA Technical Reports Server (NTRS)
Hochhalter, J. D.; Glaessgen, E. H.; Ingraffea, A. R.; Aquino, W. A.
2009-01-01
Fracture processes within a material begin at the nanometer length scale at which the formation, propagation, and interaction of fundamental damage mechanisms occur. Physics-based modeling of these atomic processes quickly becomes computationally intractable as the system size increases. Thus, a multiscale modeling method, based on the aggregation of fundamental damage processes occurring at the nanoscale within a cohesive zone model, is under development and will enable computationally feasible and physically meaningful microscale fracture simulation in polycrystalline metals. This method employs atomistic simulation to provide an optimization loop with an initial prediction of a cohesive zone model (CZM). This initial CZM is then applied at the crack front region within a finite element model. The optimization procedure iterates upon the CZM until the finite element model acceptably reproduces the near-crack-front displacement fields obtained from experimental observation. With this approach, a comparison can be made between the original CZM predicted by atomistic simulation and the converged CZM that is based on experimental observation. Comparison of the two CZMs gives insight into how atomistic simulation scales.
Modeling of Sustainable Base Production by Microbial Electrolysis Cell.
Blatter, Maxime; Sugnaux, Marc; Comninellis, Christos; Nealson, Kenneth; Fischer, Fabian
2016-07-07
A predictive model for the microbial/electrochemical base formation from wastewater was established and compared to experimental conditions within a microbial electrolysis cell. A Na2 SO4 /K2 SO4 anolyte showed that model prediction matched experimental results. Using Shewanella oneidensis MR-1, a strong base (pH≈13) was generated using applied voltages between 0.3 and 1.1 V. Due to the use of bicarbonate, the pH value in the anolyte remained unchanged, which is required to maintain microbial activity. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Accurate position estimation methods based on electrical impedance tomography measurements
NASA Astrophysics Data System (ADS)
Vergara, Samuel; Sbarbaro, Daniel; Johansen, T. A.
2017-08-01
Electrical impedance tomography (EIT) is a technology that estimates the electrical properties of a body or a cross section. Its main advantages are its non-invasiveness, low cost and operation free of radiation. The estimation of the conductivity field leads to low resolution images compared with other technologies, and high computational cost. However, in many applications the target information lies in a low intrinsic dimensionality of the conductivity field. The estimation of this low-dimensional information is addressed in this work. It proposes optimization-based and data-driven approaches for estimating this low-dimensional information. The accuracy of the results obtained with these approaches depends on modelling and experimental conditions. Optimization approaches are sensitive to model discretization, type of cost function and searching algorithms. Data-driven methods are sensitive to the assumed model structure and the data set used for parameter estimation. The system configuration and experimental conditions, such as number of electrodes and signal-to-noise ratio (SNR), also have an impact on the results. In order to illustrate the effects of all these factors, the position estimation of a circular anomaly is addressed. Optimization methods based on weighted error cost functions and derivate-free optimization algorithms provided the best results. Data-driven approaches based on linear models provided, in this case, good estimates, but the use of nonlinear models enhanced the estimation accuracy. The results obtained by optimization-based algorithms were less sensitive to experimental conditions, such as number of electrodes and SNR, than data-driven approaches. Position estimation mean squared errors for simulation and experimental conditions were more than twice for the optimization-based approaches compared with the data-driven ones. The experimental position estimation mean squared error of the data-driven models using a 16-electrode setup was less than 0.05% of the tomograph radius value. These results demonstrate that the proposed approaches can estimate an object’s position accurately based on EIT measurements if enough process information is available for training or modelling. Since they do not require complex calculations it is possible to use them in real-time applications without requiring high-performance computers.
Examining the Relationships Between Education, Social Networks and Democratic Support With ABM
NASA Technical Reports Server (NTRS)
Drucker, Nick; Campbell, Kenyth
2011-01-01
This paper introduces an agent-based model that explores the relationships between education, social networks, and support for democratic ideals. This study examines two factors thai affect democratic support, education, and social networks. Current theory concerning these two variables suggests that positive relationships exist between education and democratic support and between social networks and the spread of ideas. The model contains multiple variables of democratic support, two of which are evaluated through experimentation. The model allows individual entities within the system to make "decisions" about their democratic support independent of one another. The agent based approach also allows entities to utilize their social networks to spread ideas. Current theory supports experimentation results. In addion , these results show the model is capable of reproducing real world outcomes. This paper addresses the model creation process and the experimentation procedure, as well as future research avenues and potential shortcomings of the model
Self-consistent radiation-based simulation of electric arcs: II. Application to gas circuit breakers
NASA Astrophysics Data System (ADS)
Iordanidis, A. A.; Franck, C. M.
2008-07-01
An accurate and robust method for radiative heat transfer simulation for arc applications was presented in the previous paper (part I). In this paper a self-consistent mathematical model based on computational fluid dynamics and a rigorous radiative heat transfer model is described. The model is applied to simulate switching arcs in high voltage gas circuit breakers. The accuracy of the model is proven by comparison with experimental data for all arc modes. The ablation-controlled arc model is used to simulate high current PTFE arcs burning in cylindrical tubes. Model accuracy for the lower current arcs is evaluated using experimental data on the axially blown SF6 arc in steady state and arc resistance measurements close to current zero. The complete switching process with the arc going through all three phases is also simulated and compared with the experimental data from an industrial circuit breaker switching test.
NASA Astrophysics Data System (ADS)
Sadi, Maryam
2018-01-01
In this study a group method of data handling model has been successfully developed to predict heat capacity of ionic liquid based nanofluids by considering reduced temperature, acentric factor and molecular weight of ionic liquids, and nanoparticle concentration as input parameters. In order to accomplish modeling, 528 experimental data points extracted from the literature have been divided into training and testing subsets. The training set has been used to predict model coefficients and the testing set has been applied for model validation. The ability and accuracy of developed model, has been evaluated by comparison of model predictions with experimental values using different statistical parameters such as coefficient of determination, mean square error and mean absolute percentage error. The mean absolute percentage error of developed model for training and testing sets are 1.38% and 1.66%, respectively, which indicate excellent agreement between model predictions and experimental data. Also, the results estimated by the developed GMDH model exhibit a higher accuracy when compared to the available theoretical correlations.
Experimental Evaluation of the Effects of a Research-Based Preschool Mathematics Curriculum
ERIC Educational Resources Information Center
Clements, Douglas H.; Sarama, Julie
2008-01-01
A randomized-trials design was used to evaluate the effectiveness of a preschool mathematics program based on a comprehensive model of research-based curricula development. Thirty-six preschool classrooms were assigned to experimental (Building Blocks), comparison (a different preschool mathematics curriculum), or control conditions. Children were…
A Comprehensive Validation Methodology for Sparse Experimental Data
NASA Technical Reports Server (NTRS)
Norman, Ryan B.; Blattnig, Steve R.
2010-01-01
A comprehensive program of verification and validation has been undertaken to assess the applicability of models to space radiation shielding applications and to track progress as models are developed over time. The models are placed under configuration control, and automated validation tests are used so that comparisons can readily be made as models are improved. Though direct comparisons between theoretical results and experimental data are desired for validation purposes, such comparisons are not always possible due to lack of data. In this work, two uncertainty metrics are introduced that are suitable for validating theoretical models against sparse experimental databases. The nuclear physics models, NUCFRG2 and QMSFRG, are compared to an experimental database consisting of over 3600 experimental cross sections to demonstrate the applicability of the metrics. A cumulative uncertainty metric is applied to the question of overall model accuracy, while a metric based on the median uncertainty is used to analyze the models from the perspective of model development by analyzing subsets of the model parameter space.
Understanding Leadership: An Experimental-Experiential Model
ERIC Educational Resources Information Center
Hole, George T.
2014-01-01
Books about leadership are dangerous to readers who fantasize about being leaders or apply leadership ideas as if they were proven formulas. As an antidote, I offer an experimental framework in which any leadership-management model can be tested to gain experiential understanding of the model. As a result one can gain reality-based insights about…
Plasma versus Drude Modeling of the Casimir Force: Beyond the Proximity Force Approximation
NASA Astrophysics Data System (ADS)
Hartmann, Michael; Ingold, Gert-Ludwig; Neto, Paulo A. Maia
2017-07-01
We calculate the Casimir force and its gradient between a spherical and a planar gold surface. Significant numerical improvements allow us to extend the range of accessible parameters into the experimental regime. We compare our numerically exact results with those obtained within the proximity force approximation (PFA) employed in the analysis of all Casimir force experiments reported in the literature so far. Special attention is paid to the difference between the Drude model and the dissipationless plasma model at zero frequency. It is found that the correction to PFA is too small to explain the discrepancy between the experimental data and the PFA result based on the Drude model. However, it turns out that for the plasma model, the corrections to PFA lie well outside the experimental bound obtained by probing the variation of the force gradient with the sphere radius [D. E. Krause et al., Phys. Rev. Lett. 98, 050403 (2007), 10.1103/PhysRevLett.98.050403]. The corresponding corrections based on the Drude model are significantly smaller but still in violation of the experimental bound for small distances between plane and sphere.
2011-09-01
a quality evaluation with limited data, a model -based assessment must be...that affect system performance, a multistage approach to system validation, a modeling and experimental methodology for efficiently addressing a ...affect system performance, a multistage approach to system validation, a modeling and experimental methodology for efficiently addressing a wide range
NASA Astrophysics Data System (ADS)
Pereira, A. S. N.; de Streel, G.; Planes, N.; Haond, M.; Giacomini, R.; Flandre, D.; Kilchytska, V.
2017-02-01
The Drain Induced Barrier Lowering (DIBL) behavior in Ultra-Thin Body and Buried oxide (UTBB) transistors is investigated in details in the temperature range up to 150 °C, for the first time to the best of our knowledge. The analysis is based on experimental data, physical device simulation, compact model (SPICE) simulation and previously published models. Contrary to MASTAR prediction, experiments reveal DIBL increase with temperature. Physical device simulations of different thin-film fully-depleted (FD) devices outline the generality of such behavior. SPICE simulations, with UTSOI DK2.4 model, only partially adhere to experimental trends. Several analytic models available in the literature are assessed for DIBL vs. temperature prediction. Although being the closest to experiments, Fasarakis' model overestimates DIBL(T) dependence for shortest devices and underestimates it for upsized gate lengths frequently used in ultra-low-voltage (ULV) applications. This model is improved in our work, by introducing a temperature-dependent inversion charge at threshold. The improved model shows very good agreement with experimental data, with high gain in precision for the gate lengths under test.
Experimental validation of ultrasonic guided modes in electrical cables by optical interferometry.
Mateo, Carlos; de Espinosa, Francisco Montero; Gómez-Ullate, Yago; Talavera, Juan A
2008-03-01
In this work, the dispersion curves of elastic waves propagating in electrical cables and in bare copper wires are obtained theoretically and validated experimentally. The theoretical model, based on Gazis equations formulated according to the global matrix methodology, is resolved numerically. Viscoelasticity and attenuation are modeled theoretically using the Kelvin-Voigt model. Experimental tests are carried out using interferometry. There is good agreement between the simulations and the experiments despite the peculiarities of electrical cables.
2016-06-01
characteristics, experimental design techniques, and analysis methodologies that distinguish each phase of the MBSE MEASA. To ensure consistency... methodology . Experimental design selection, simulation analysis, and trade space analysis support the final two stages. Figure 27 segments the MBSE MEASA...rounding has the potential to increase the correlation between columns of the experimental design matrix. The design methodology presented in Vieira
Bunker, Alex; Magarkar, Aniket; Viitala, Tapani
2016-10-01
Combined experimental and computational studies of lipid membranes and liposomes, with the aim to attain mechanistic understanding, result in a synergy that makes possible the rational design of liposomal drug delivery system (LDS) based therapies. The LDS is the leading form of nanoscale drug delivery platform, an avenue in drug research, known as "nanomedicine", that holds the promise to transcend the current paradigm of drug development that has led to diminishing returns. Unfortunately this field of research has, so far, been far more successful in generating publications than new drug therapies. This partly results from the trial and error based methodologies used. We discuss experimental techniques capable of obtaining mechanistic insight into LDS structure and behavior. Insight obtained purely experimentally is, however, limited; computational modeling using molecular dynamics simulation can provide insight not otherwise available. We review computational research, that makes use of the multiscale modeling paradigm, simulating the phospholipid membrane with all atom resolution and the entire liposome with coarse grained models. We discuss in greater detail the computational modeling of liposome PEGylation. Overall, we wish to convey the power that lies in the combined use of experimental and computational methodologies; we hope to provide a roadmap for the rational design of LDS based therapies. Computational modeling is able to provide mechanistic insight that explains the context of experimental results and can also take the lead and inspire new directions for experimental research into LDS development. This article is part of a Special Issue entitled: Biosimulations edited by Ilpo Vattulainen and Tomasz Róg. Copyright © 2016 Elsevier B.V. All rights reserved.
Modeling and experimental study on near-field acoustic levitation by flexural mode.
Liu, Pinkuan; Li, Jin; Ding, Han; Cao, Wenwu
2009-12-01
Near-field acoustic levitation (NFAL) has been used in noncontact handling and transportation of small objects to avoid contamination. We have performed a theoretical analysis based on nonuniform vibrating surface to quantify the levitation force produced by the air film and also conducted experimental tests to verify our model. Modal analysis was performed using ANSYS on the flexural plate radiator to obtain its natural frequency of desired mode, which is used to design the measurement system. Then, the levitation force was calculated as a function of levitation distance based on squeeze gas film theory using measured amplitude and phase distributions on the vibrator surface. Compared with previous fluid-structural analyses using a uniform piston motion, our model based on the nonuniform radiating surface of the vibrator is more realistic and fits better with experimentally measured levitation force.
Chi, Yulang; Zhang, Huanteng; Huang, Qiansheng; Lin, Yi; Ye, Guozhu; Zhu, Huimin; Dong, Sijun
2018-02-01
Environmental risks of organic chemicals have been greatly determined by their persistence, bioaccumulation, and toxicity (PBT) and physicochemical properties. Major regulations in different countries and regions identify chemicals according to their bioconcentration factor (BCF) and octanol-water partition coefficient (Kow), which frequently displays a substantial correlation with the sediment sorption coefficient (Koc). Half-life or degradability is crucial for the persistence evaluation of chemicals. Quantitative structure activity relationship (QSAR) estimation models are indispensable for predicting environmental fate and health effects in the absence of field- or laboratory-based data. In this study, 39 chemicals of high concern were chosen for half-life testing based on total organic carbon (TOC) degradation, and two widely accepted and highly used QSAR estimation models (i.e., EPI Suite and PBT Profiler) were adopted for environmental risk evaluation. The experimental results and estimated data, as well as the two model-based results were compared, based on the water solubility, Kow, Koc, BCF and half-life. Environmental risk assessment of the selected compounds was achieved by combining experimental data and estimation models. It was concluded that both EPI Suite and PBT Profiler were fairly accurate in measuring the physicochemical properties and degradation half-lives for water, soil, and sediment. However, the half-lives between the experimental and the estimated results were still not absolutely consistent. This suggests deficiencies of the prediction models in some ways, and the necessity to combine the experimental data and predicted results for the evaluation of environmental fate and risks of pollutants. Copyright © 2016. Published by Elsevier B.V.
Zelić, B; Bolf, N; Vasić-Racki, D
2006-06-01
Three different models: the unstructured mechanistic black-box model, the input-output neural network-based model and the externally recurrent neural network model were used to describe the pyruvate production process from glucose and acetate using the genetically modified Escherichia coli YYC202 ldhA::Kan strain. The experimental data were used from the recently described batch and fed-batch experiments [ Zelić B, Study of the process development for Escherichia coli-based pyruvate production. PhD Thesis, University of Zagreb, Faculty of Chemical Engineering and Technology, Zagreb, Croatia, July 2003. (In English); Zelić et al. Bioproc Biosyst Eng 26:249-258 (2004); Zelić et al. Eng Life Sci 3:299-305 (2003); Zelić et al Biotechnol Bioeng 85:638-646 (2004)]. The neural networks were built out of the experimental data obtained in the fed-batch pyruvate production experiments with the constant glucose feed rate. The model validation was performed using the experimental results obtained from the batch and fed-batch pyruvate production experiments with the constant acetate feed rate. Dynamics of the substrate and product concentration changes was estimated using two neural network-based models for biomass and pyruvate. It was shown that neural networks could be used for the modeling of complex microbial fermentation processes, even in conditions in which mechanistic unstructured models cannot be applied.
NASA Astrophysics Data System (ADS)
Niaz, Mansoor; Aguilera, Damarys; Maza, Arelys; Liendo, Gustavo
2002-07-01
Most general chemistry courses and textbooks emphasize experimental details and lack a history and philosophy of science perspective. The objective of this study is to facilitate freshman general chemistry students' understanding of atomic structure based on the work of Thomson, Rutherford, and Bohr. It is hypothesized that classroom discussions based on arguments/counterarguments of the heuristic principles, on which these scientists based their atomic models, can facilitate students' conceptual understanding. This study is based on 160 freshman students enrolled in six sections of General Chemistry I (three sections formed part of the experimental group). All three models (Thomson, Rutherford, and Bohr) were presented to the experimental and control group students in the traditional manner, as found in most textbooks. After this, the three sections of the experimental group participated in the discussion of six items with alternative responses. Students were first asked to select a response and then participate in classroom discussions leading to arguments in favor or against the selected response and finally select a new response. Three weeks after having discussed the six items, both the experimental and control groups presented a monthly exam (based on the three models) and after another 3 weeks a semester exam. Results obtained show that given the opportunity to argue and discuss, students' understanding can go beyond the simple regurgitation of experimental details. Performance of the experimental group showed contradictions, resistances, and progressive conceptual change with considerable and consistent improvement in the last item. It is concluded that if we want our students to understand scientific progress and practice, then it is important that we include the experimental details not as a rhetoric of conclusions (Schwab, 1962, The teaching of science as enquiry, Cambridge, MA, Harward University Press; Schwab, 1974, Conflicting conceptions of curriculum, Berkeley, CA, McCutchan) but as heuristic principles (Lakatos, 1970, Criticism and the growth of knowledge, Cambridge, UK, Cambridge University Press, pp. 91-195), which were based on arguments, controversies, and interpretations of the scientists.
Latash, M L; Goodman, S R
1994-01-01
The purpose of this work has been to develop a model of electromyographic (EMG) patterns during single-joint movements based on a version of the equilibrium-point hypothesis, a method for experimental reconstruction of the joint compliant characteristics, the dual-strategy hypothesis, and a kinematic model of movement trajectory. EMG patterns are considered emergent properties of hypothetical control patterns that are equally affected by the control signals and peripheral feedback reflecting actual movement trajectory. A computer model generated the EMG patterns based on simulated movement kinematics and hypothetical control signals derived from the reconstructed joint compliant characteristics. The model predictions have been compared to published recordings of movement kinematics and EMG patterns in a variety of movement conditions, including movements over different distances, at different speeds, against different-known inertial loads, and in conditions of possible unexpected decrease in the inertial load. Changes in task parameters within the model led to simulated EMG patterns qualitatively similar to the experimentally recorded EMG patterns. The model's predictive power compares it favourably to the existing models of the EMG patterns. Copyright © 1994. Published by Elsevier Ltd.
Modeling of Pressure Drop During Refrigerant Condensation in Pipe Minichannels
NASA Astrophysics Data System (ADS)
Sikora, Małgorzata; Bohdal, Tadeusz
2017-12-01
Investigations of refrigerant condensation in pipe minichannels are very challenging and complicated issue. Due to the multitude of influences very important is mathematical and computer modeling. Its allows for performing calculations for many different refrigerants under different flow conditions. A large number of experimental results published in the literature allows for experimental verification of correctness of the models. In this work is presented a mathematical model for calculation of flow resistance during condensation of refrigerants in the pipe minichannel. The model was developed in environment based on conservation equations. The results of calculations were verified by authors own experimental investigations results.
NASA Astrophysics Data System (ADS)
Paralı, Levent; Sarı, Ali; Kılıç, Ulaş; Şahin, Özge; Pěchoušek, Jiří
2017-09-01
We report an improvement of the artificial neural network (ANN) modelling of a piezoelectric actuator vibration based on the experimental data. The controlled vibrations of an actuator were obtained by utilizing the swept-sine signal excitation. The peak value in the displacement signal response was measured by a laser displacement sensor. The piezoelectric actuator was modelled in both linear and nonlinear operating range. A consistency from 90.3 up to 98.9% of ANN modelled output values and experimental ones was reached. The obtained results clearly demonstrate exact linear relationship between the ANN model and experimental values.
NASA Astrophysics Data System (ADS)
Dhote, Sharvari; Yang, Zhengbao; Zu, Jean
2018-01-01
This paper presents the modeling and experimental parametric study of a nonlinear multi-frequency broad bandwidth piezoelectric vibration-based energy harvester. The proposed harvester consists of a tri-leg compliant orthoplanar spring (COPS) and multiple masses with piezoelectric plates attached at three different locations. The vibration modes, resonant frequencies, and strain distributions are studied using the finite element analysis. The prototype is manufactured and experimentally investigated to study the effect of single as well as multiple light-weight masses on the bandwidth. The dynamic behavior of the harvester with a mass at the center is modeled numerically and characterized experimentally. The simulation and experimental results are in good agreement. A wide bandwidth with three close nonlinear vibration modes is observed during the experiments when four masses are added to the proposed harvester. The current generator with four masses shows a significant performance improvement with multiple nonlinear peaks under both forward and reverse frequency sweeps.
2007-12-21
of hydrodynamics and the physical characteristics of the polymers. The physics models include both analytical models and numerical simulations ...the experimental observations. The numerical simulations also succeed in replicating some experimental measurements. However, there is still no...become quite significant. 4.5 Documentation The complete model is coded in MatLab . In the model, all units are cgs, so distances are in
Validation of the thermal challenge problem using Bayesian Belief Networks.
DOE Office of Scientific and Technical Information (OSTI.GOV)
McFarland, John; Swiler, Laura Painton
The thermal challenge problem has been developed at Sandia National Laboratories as a testbed for demonstrating various types of validation approaches and prediction methods. This report discusses one particular methodology to assess the validity of a computational model given experimental data. This methodology is based on Bayesian Belief Networks (BBNs) and can incorporate uncertainty in experimental measurements, in physical quantities, and model uncertainties. The approach uses the prior and posterior distributions of model output to compute a validation metric based on Bayesian hypothesis testing (a Bayes' factor). This report discusses various aspects of the BBN, specifically in the context ofmore » the thermal challenge problem. A BBN is developed for a given set of experimental data in a particular experimental configuration. The development of the BBN and the method for ''solving'' the BBN to develop the posterior distribution of model output through Monte Carlo Markov Chain sampling is discussed in detail. The use of the BBN to compute a Bayes' factor is demonstrated.« less
Experiment Analysis and Modelling of Compaction Behaviour of Ag60Cu30Sn10 Mixed Metal Powders
NASA Astrophysics Data System (ADS)
Zhou, Mengcheng; Huang, Shangyu; Liu, Wei; Lei, Yu; Yan, Shiwei
2018-03-01
A novel process method combines powder compaction and sintering was employed to fabricate thin sheets of cadmium-free silver based filler metals, the compaction densification behaviour of Ag60Cu30Sn10 mixed metal powders was investigated experimentally. Based on the equivalent density method, the density-dependent Drucker-Prager Cap (DPC) model was introduced to model the powder compaction behaviour. Various experiment procedures were completed to determine the model parameters. The friction coefficients in lubricated and unlubricated die were experimentally determined. The determined material parameters were validated by experiments and numerical simulation of powder compaction process using a user subroutine (USDFLD) in ABAQUS/Standard. The good agreement between the simulated and experimental results indicates that the determined model parameters are able to describe the compaction behaviour of the multicomponent mixed metal powders, which can be further used for process optimization simulations.
NASA Technical Reports Server (NTRS)
Bardino, J.; Ferziger, J. H.; Reynolds, W. C.
1983-01-01
The physical bases of large eddy simulation and subgrid modeling are studied. A subgrid scale similarity model is developed that can account for system rotation. Large eddy simulations of homogeneous shear flows with system rotation were carried out. Apparently contradictory experimental results were explained. The main effect of rotation is to increase the transverse length scales in the rotation direction, and thereby decrease the rates of dissipation. Experimental results are shown to be affected by conditions at the turbulence producing grid, which make the initial states a function of the rotation rate. A two equation model is proposed that accounts for effects of rotation and shows good agreement with experimental results. In addition, a Reynolds stress model is developed that represents the turbulence structure of homogeneous shear flows very well and can account also for the effects of system rotation.
SBML-PET: a Systems Biology Markup Language-based parameter estimation tool.
Zi, Zhike; Klipp, Edda
2006-11-01
The estimation of model parameters from experimental data remains a bottleneck for a major breakthrough in systems biology. We present a Systems Biology Markup Language (SBML) based Parameter Estimation Tool (SBML-PET). The tool is designed to enable parameter estimation for biological models including signaling pathways, gene regulation networks and metabolic pathways. SBML-PET supports import and export of the models in the SBML format. It can estimate the parameters by fitting a variety of experimental data from different experimental conditions. SBML-PET has a unique feature of supporting event definition in the SMBL model. SBML models can also be simulated in SBML-PET. Stochastic Ranking Evolution Strategy (SRES) is incorporated in SBML-PET for parameter estimation jobs. A classic ODE Solver called ODEPACK is used to solve the Ordinary Differential Equation (ODE) system. http://sysbio.molgen.mpg.de/SBML-PET/. The website also contains detailed documentation for SBML-PET.
Saenz-Méndez, Patricia; Katz, Aline; Pérez-Kempner, María Lucía; Ventura, Oscar N; Vázquez, Marta
2017-04-01
A new homology model of human microsomal epoxide hydrolase was derived based on multiple templates. The model obtained was fully evaluated, including MD simulations and ensemble-based docking, showing that the quality of the structure is better than that of only previously known model. Particularly, a catalytic triad was clearly identified, in agreement with the experimental information available. Analysis of intermediates in the enzymatic mechanism led to the identification of key residues for substrate binding, stereoselectivity, and intermediate stabilization during the reaction. In particular, we have confirmed the role of the oxyanion hole and the conserved motif (HGXP) in epoxide hydrolases, in excellent agreement with known experimental and computational data on similar systems. The model obtained is the first one that fully agrees with all the experimental observations on the system. Proteins 2017; 85:720-730. © 2016 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
Model based manipulator control
NASA Technical Reports Server (NTRS)
Petrosky, Lyman J.; Oppenheim, Irving J.
1989-01-01
The feasibility of using model based control (MBC) for robotic manipulators was investigated. A double inverted pendulum system was constructed as the experimental system for a general study of dynamically stable manipulation. The original interest in dynamically stable systems was driven by the objective of high vertical reach (balancing), and the planning of inertially favorable trajectories for force and payload demands. The model-based control approach is described and the results of experimental tests are summarized. Results directly demonstrate that MBC can provide stable control at all speeds of operation and support operations requiring dynamic stability such as balancing. The application of MBC to systems with flexible links is also discussed.
Optimization of Nd: YAG Laser Marking of Alumina Ceramic Using RSM And ANN
NASA Astrophysics Data System (ADS)
Peter, Josephine; Doloi, B.; Bhattacharyya, B.
2011-01-01
The present research papers deals with the artificial neural network (ANN) and the response surface methodology (RSM) based mathematical modeling and also an optimization analysis on marking characteristics on alumina ceramic. The experiments have been planned and carried out based on Design of Experiment (DOE). It also analyses the influence of the major laser marking process parameters and the optimal combination of laser marking process parametric setting has been obtained. The output of the RSM optimal data is validated through experimentation and ANN predictive model. A good agreement is observed between the results based on ANN predictive model and actual experimental observations.
Physical Modeling of the Polyfrequency Filter-Compensating Device Based on the Capacitor-Coil
NASA Astrophysics Data System (ADS)
Butyrin, P. A.; Gusev, G. G.; Mikheev, D. V.; Shakirzianov, F. N.
2017-12-01
The paper presents the results of physical modeling and experimental study of the frequency characteristics of the polyfrequency filter-compensating device (PFCD) based on a capacitor-coil. The amplitude- frequency and phase-frequency characteristics of the physical PFCD model were constructed and its equivalent parameters were identified. The feasibility of a PFCD in the form of a single technical device with high technical and economic characteristics was experimentally proven. In the paper, recommendations for practical applications of the capacitor-coil-based PFCD are made and the advantages of the device over known standard passive filter-compensating devices are evaluated.
NASA Astrophysics Data System (ADS)
Grzesik, W.; Niesłony, P.; Laskowski, P.
2017-12-01
In this paper, a special procedure for the prediction of parameters of the Johnson-Cook constitutive material models is proposed based on the experimental data and specially developed MATLAB scripts which allow advanced modeling of complex 3D response surfaces. Experimental investigations concern two various strain rates of 10-3 and 101 1/s and the testing temperature ranging from the ambient up to 700 °C. As a result, a set of mathematical equations which fit the experimental data is determined. The applicability of the experimentally derived constitutive models to the FEM modeling of real machining processes of Inconel 718 alloy is verified.
NASA Astrophysics Data System (ADS)
Jaber, Khalid Mohammad; Alia, Osama Moh'd.; Shuaib, Mohammed Mahmod
2018-03-01
Finding the optimal parameters that can reproduce experimental data (such as the velocity-density relation and the specific flow rate) is a very important component of the validation and calibration of microscopic crowd dynamic models. Heavy computational demand during parameter search is a known limitation that exists in a previously developed model known as the Harmony Search-Based Social Force Model (HS-SFM). In this paper, a parallel-based mechanism is proposed to reduce the computational time and memory resource utilisation required to find these parameters. More specifically, two MATLAB-based multicore techniques (parfor and create independent jobs) using shared memory are developed by taking advantage of the multithreading capabilities of parallel computing, resulting in a new framework called the Parallel Harmony Search-Based Social Force Model (P-HS-SFM). The experimental results show that the parfor-based P-HS-SFM achieved a better computational time of about 26 h, an efficiency improvement of ? 54% and a speedup factor of 2.196 times in comparison with the HS-SFM sequential processor. The performance of the P-HS-SFM using the create independent jobs approach is also comparable to parfor with a computational time of 26.8 h, an efficiency improvement of about 30% and a speedup of 2.137 times.
A support vector machine based control application to the experimental three-tank system.
Iplikci, Serdar
2010-07-01
This paper presents a support vector machine (SVM) approach to generalized predictive control (GPC) of multiple-input multiple-output (MIMO) nonlinear systems. The possession of higher generalization potential and at the same time avoidance of getting stuck into the local minima have motivated us to employ SVM algorithms for modeling MIMO systems. Based on the SVM model, detailed and compact formulations for calculating predictions and gradient information, which are used in the computation of the optimal control action, are given in the paper. The proposed MIMO SVM-based GPC method has been verified on an experimental three-tank liquid level control system. Experimental results have shown that the proposed method can handle the control task successfully for different reference trajectories. Moreover, a detailed discussion on data gathering, model selection and effects of the control parameters have been given in this paper. 2010 ISA. Published by Elsevier Ltd. All rights reserved.
Bayesian experimental design for models with intractable likelihoods.
Drovandi, Christopher C; Pettitt, Anthony N
2013-12-01
In this paper we present a methodology for designing experiments for efficiently estimating the parameters of models with computationally intractable likelihoods. The approach combines a commonly used methodology for robust experimental design, based on Markov chain Monte Carlo sampling, with approximate Bayesian computation (ABC) to ensure that no likelihood evaluations are required. The utility function considered for precise parameter estimation is based upon the precision of the ABC posterior distribution, which we form efficiently via the ABC rejection algorithm based on pre-computed model simulations. Our focus is on stochastic models and, in particular, we investigate the methodology for Markov process models of epidemics and macroparasite population evolution. The macroparasite example involves a multivariate process and we assess the loss of information from not observing all variables. © 2013, The International Biometric Society.
Physics of human cooperation: experimental evidence and theoretical models
NASA Astrophysics Data System (ADS)
Sánchez, Angel
2018-02-01
In recent years, many physicists have used evolutionary game theory combined with a complex systems perspective in an attempt to understand social phenomena and challenges. Prominent among such phenomena is the issue of the emergence and sustainability of cooperation in a networked world of selfish or self-focused individuals. The vast majority of research done by physicists on these questions is theoretical, and is almost always posed in terms of agent-based models. Unfortunately, more often than not such models ignore a number of facts that are well established experimentally, and are thus rendered irrelevant to actual social applications. I here summarize some of the facts that any realistic model should incorporate and take into account, discuss important aspects underlying the relation between theory and experiments, and discuss future directions for research based on the available experimental knowledge.
The Effect of Modeling Based Science Education on Critical Thinking
ERIC Educational Resources Information Center
Bati, Kaan; Kaptan, Fitnat
2015-01-01
In this study to what degree the modeling based science education can influence the development of the critical thinking skills of the students was investigated. The research was based on pre-test-post-test quasi-experimental design with control group. The Modeling Based Science Education Program which was prepared with the purpose of exploring…
NASA Technical Reports Server (NTRS)
Alcorn, Charles W.; Britcher, Colin
1988-01-01
An experimental investigation is reported on slanted base ogive cylinders at zero incidence. The Mach number range is 0.05 to 0.3. All flow disturbances associated with wind tunnel supports are eliminated in this investigation by magnetically suspending the wind tunnel models. The sudden and drastic changes in the lift, pitching moment, and drag for a slight change in base slant angle are reported. Flow visualization with liquid crystals and oil is used to observe base flow patterns, which are responsible for the sudden changes in aerodynamic characteristics. Hysteretic effects in base flow pattern changes are present in this investigation and are reported. The effect of a wire support attachment on the 0 deg slanted base model is studied. Computational drag and transition location results using VSAERO and SANDRAG are presented and compared with experimental results. Base pressure measurements over the slanted bases are made with an onboard pressure transducer using remote data telemetry.
Monte Carlo calculations of positron emitter yields in proton radiotherapy.
Seravalli, E; Robert, C; Bauer, J; Stichelbaut, F; Kurz, C; Smeets, J; Van Ngoc Ty, C; Schaart, D R; Buvat, I; Parodi, K; Verhaegen, F
2012-03-21
Positron emission tomography (PET) is a promising tool for monitoring the three-dimensional dose distribution in charged particle radiotherapy. PET imaging during or shortly after proton treatment is based on the detection of annihilation photons following the ß(+)-decay of radionuclides resulting from nuclear reactions in the irradiated tissue. Therapy monitoring is achieved by comparing the measured spatial distribution of irradiation-induced ß(+)-activity with the predicted distribution based on the treatment plan. The accuracy of the calculated distribution depends on the correctness of the computational models, implemented in the employed Monte Carlo (MC) codes that describe the interactions of the charged particle beam with matter and the production of radionuclides and secondary particles. However, no well-established theoretical models exist for predicting the nuclear interactions and so phenomenological models are typically used based on parameters derived from experimental data. Unfortunately, the experimental data presently available are insufficient to validate such phenomenological hadronic interaction models. Hence, a comparison among the models used by the different MC packages is desirable. In this work, starting from a common geometry, we compare the performances of MCNPX, GATE and PHITS MC codes in predicting the amount and spatial distribution of proton-induced activity, at therapeutic energies, to the already experimentally validated PET modelling based on the FLUKA MC code. In particular, we show how the amount of ß(+)-emitters produced in tissue-like media depends on the physics model and cross-sectional data used to describe the proton nuclear interactions, thus calling for future experimental campaigns aiming at supporting improvements of MC modelling for clinical application of PET monitoring. © 2012 Institute of Physics and Engineering in Medicine
NASA Astrophysics Data System (ADS)
Kumar, Rohit; Puri, Rajeev K.
2018-03-01
Employing the quantum molecular dynamics (QMD) approach for nucleus-nucleus collisions, we test the predictive power of the energy-based clusterization algorithm, i.e., the simulating annealing clusterization algorithm (SACA), to describe the experimental data of charge distribution and various event-by-event correlations among fragments. The calculations are constrained into the Fermi-energy domain and/or mildly excited nuclear matter. Our detailed study spans over different system masses, and system-mass asymmetries of colliding partners show the importance of the energy-based clusterization algorithm for understanding multifragmentation. The present calculations are also compared with the other available calculations, which use one-body models, statistical models, and/or hybrid models.
Modeling, design, fabrication and experimentation of a GaN-based, 63Ni betavoltaic battery
NASA Astrophysics Data System (ADS)
E Munson, C., IV; Gaimard, Q.; Merghem, K.; Sundaram, S.; Rogers, D. J.; de Sanoit, J.; Voss, P. L.; Ramdane, A.; Salvestrini, J. P.; Ougazzaden, A.
2018-01-01
GaN is a durable, radiation hard and wide-bandgap semiconductor material, making it ideal for usage with betavoltaic batteries. This paper describes the design, fabrication and experimental testing of 1 cm2 GaN-based betavoltaic batteries (that achieve an output power of 2.23 nW) along with a full model that accurately simulates the device performance which is the highest to date (to the best of our knowledge) for GaN-based devices with a 63Ni source.
NASA Astrophysics Data System (ADS)
Wang, Ding; Ding, Pin-bo; Ba, Jing
2018-03-01
In Part I, a dynamic fracture compliance model (DFCM) was derived based on the poroelastic theory. The normal compliance of fractures is frequency-dependent and closely associated with the connectivity of porous media. In this paper, we first compare the DFCM with previous fractured media theories in the literature in a full frequency range. Furthermore, experimental tests are performed on synthetic rock specimens, and the DFCM is compared with the experimental data in the ultrasonic frequency band. Synthetic rock specimens saturated with water have more realistic mineral compositions and pore structures relative to previous works in comparison with natural reservoir rocks. The fracture/pore geometrical and physical parameters can be controlled to replicate approximately those of natural rocks. P- and S-wave anisotropy characteristics with different fracture and pore properties are calculated and numerical results are compared with experimental data. Although the measurement frequency is relatively high, the results of DFCM are appropriate for explaining the experimental data. The characteristic frequency of fluid pressure equilibration calculated based on the specimen parameters is not substantially less than the measurement frequency. In the dynamic fracture model, the wave-induced fluid flow behavior is an important factor for the fracture-wave interaction process, which differs from the models at the high-frequency limits, for instance, Hudson's un-relaxed model.
A new UK fission yield evaluation UKFY3.7
NASA Astrophysics Data System (ADS)
Mills, Robert William
2017-09-01
The JEFF neutron induced and spontaneous fission product yield evaluation is currently unchanged from JEFF-3.1.1, also known by its UK designation UKFY3.6A. It is based upon experimental data combined with empirically fitted mass, charge and isomeric state models which are then adjusted within the experimental and model uncertainties to conform to the physical constraints of the fission process. A new evaluation has been prepared for JEFF, called UKFY3.7, that incorporates new experimental data and replaces the current empirical models (multi-Gaussian fits of mass distribution and Wahl Zp model for charge distribution combined with parameter extrapolation), with predictions from GEF. The GEF model has the advantage that one set of parameters allows the prediction of many different fissioning nuclides at different excitation energies unlike previous models where each fissioning nuclide at a specific excitation energy had to be fitted individually to the relevant experimental data. The new UKFY3.7 evaluation, submitted for testing as part of JEFF-3.3, is described alongside initial results of testing. In addition, initial ideas for future developments allowing inclusion of new measurements types and changing from any neutron spectrum type to true neutron energy dependence are discussed. Also, a method is proposed to propagate uncertainties of fission product yields based upon the experimental data that underlies the fission yield evaluation. The covariance terms being determined from the evaluated cumulative and independent yields combined with the experimental uncertainties on the cumulative yield measurements.
Flexible manipulator control experiments and analysis
NASA Technical Reports Server (NTRS)
Yurkovich, S.; Ozguner, U.; Tzes, A.; Kotnik, P. T.
1987-01-01
Modeling and control design for flexible manipulators, both from an experimental and analytical viewpoint, are described. From the application perspective, an ongoing effort within the laboratory environment at the Ohio State University, where experimentation on a single link flexible arm is underway is described. Several unique features of this study are described here. First, the manipulator arm is slewed by a direct drive dc motor and has a rigid counterbalance appendage. Current experimentation is from two viewpoints: (1) rigid body slewing and vibration control via actuation with the hub motor, and (2) vibration suppression through the use of structure-mounted proof-mass actuation at the tip. Such an application to manipulator control is of interest particularly in design of space-based telerobotic control systems, but has received little attention to date. From an analytical viewpoint, parameter estimation techniques within the closed-loop for self-tuning adaptive control approaches are discussed. Also introduced is a control approach based on output feedback and frequency weighting to counteract effects of spillover in reduced-order model design. A model of the flexible manipulator based on experimental measurements is evaluated for such estimation and control approaches.
Pesticide regulations for agriculture: Chemically flawed regulatory practice.
Gamble, Donald S; Bruccoleri, Aldo G
2016-08-02
Two categories of pesticide soil models now exist. Government regulatory agencies use pesticide fate and transport hydrology models, including versions of PRZM.gw. They have good descriptions of pesticide transport by water flow. Their descriptions of chemical mechanisms are unrealistic, having been postulated using the universally accepted but incorrect pesticide soil science. The objective of this work is to report experimental tests of a pesticide soil model in use by regulatory agencies and to suggest possible improvements. Tests with experimentally based data explain why PRZM.gw predictions can be wrong by orders of magnitude. Predictive spreadsheet models are the other category. They are experimentally based, with chemical stoichiometry applied to integral kinetic rate laws for sorption, desorption, intra-particle diffusion, and chemical reactions. They do not account for pesticide transport through soils. Each category of models therefore lacks what the other could provide. They need to be either harmonized or replaced. Some preliminary tests indicate that an experimental mismatch between the categories of models will have to be resolved. Reports of pesticides in the environment and the medical problems that overlap geographically indicate that government regulatory practice needs to account for chemical kinetics and mechanisms. Questions about possible cause and effect links could then be investigated.
NASA Astrophysics Data System (ADS)
Zielnica, J.; Ziółkowski, A.; Cempel, C.
2003-03-01
Design and theoretical and experimental investigation of vibroisolation pads with non-linear static and dynamic responses is the objective of the paper. The analytical investigations are based on non-linear finite element analysis where the load-deflection response is traced against the shape and material properties of the analysed model of the vibroisolation pad. A new model of vibroisolation pad of antisymmetrical type was designed and analysed by the finite element method based on the second-order theory (large displacements and strains) with the assumption of material's non-linearities (Mooney-Rivlin model). Stability loss phenomenon was used in the design of the vibroisolators, and it was proved that it would be possible to design a model of vibroisolator in the form of a continuous pad with non-linear static and dynamic response, typical to vibroisolation purposes. The materials used for the vibroisolator are those of rubber, elastomers, and similar ones. The results of theoretical investigations were examined experimentally. A series of models made of soft rubber were designed for the test purposes. The experimental investigations of the vibroisolation models, under static and dynamic loads, confirmed the results of the FEM analysis.
Modeling of leishmaniasis infection dynamics: novel application to the design of effective therapies
2012-01-01
Background The WHO considers leishmaniasis as one of the six most important tropical diseases worldwide. It is caused by parasites of the genus Leishmania that are passed on to humans and animals by the phlebotomine sandfly. Despite all of the research, there is still a lack of understanding on the metabolism of the parasite and the progression of the disease. In this study, a mathematical model of disease progression was developed based on experimental data of clinical symptoms, immunological responses, and parasite load for Leishmania amazonensis in BALB/c mice. Results Four biologically significant variables were chosen to develop a differential equation model based on the GMA power-law formalism. Parameters were determined to minimize error in the model dynamics and time series experimental data. Subsequently, the model robustness was tested and the model predictions were verified by comparing them with experimental observations made in different experimental conditions. The model obtained helps to quantify relationships between the selected variables, leads to a better understanding of disease progression, and aids in the identification of crucial points for introducing therapeutic methods. Conclusions Our model can be used to identify the biological factors that must be changed to minimize parasite load in the host body, and contributes to the design of effective therapies. PMID:22222070
NASA Astrophysics Data System (ADS)
Majdalani, Samer; Guinot, Vincent; Delenne, Carole; Gebran, Hicham
2018-06-01
This paper is devoted to theoretical and experimental investigations of solute dispersion in heterogeneous porous media. Dispersion in heterogenous porous media has been reported to be scale-dependent, a likely indication that the proposed dispersion models are incompletely formulated. A high quality experimental data set of breakthrough curves in periodic model heterogeneous porous media is presented. In contrast with most previously published experiments, the present experiments involve numerous replicates. This allows the statistical variability of experimental data to be accounted for. Several models are benchmarked against the data set: the Fickian-based advection-dispersion, mobile-immobile, multirate, multiple region advection dispersion models, and a newly proposed transport model based on pure advection. A salient property of the latter model is that its solutions exhibit a ballistic behaviour for small times, while tending to the Fickian behaviour for large time scales. Model performance is assessed using a novel objective function accounting for the statistical variability of the experimental data set, while putting equal emphasis on both small and large time scale behaviours. Besides being as accurate as the other models, the new purely advective model has the advantages that (i) it does not exhibit the undesirable effects associated with the usual Fickian operator (namely the infinite solute front propagation speed), and (ii) it allows dispersive transport to be simulated on every heterogeneity scale using scale-independent parameters.
An integrated physiology model to study regional lung damage effects and the physiologic response
2014-01-01
Background This work expands upon a previously developed exercise dynamic physiology model (DPM) with the addition of an anatomic pulmonary system in order to quantify the impact of lung damage on oxygen transport and physical performance decrement. Methods A pulmonary model is derived with an anatomic structure based on morphometric measurements, accounting for heterogeneous ventilation and perfusion observed experimentally. The model is incorporated into an existing exercise physiology model; the combined system is validated using human exercise data. Pulmonary damage from blast, blunt trauma, and chemical injury is quantified in the model based on lung fluid infiltration (edema) which reduces oxygen delivery to the blood. The pulmonary damage component is derived and calibrated based on published animal experiments; scaling laws are used to predict the human response to lung injury in terms of physical performance decrement. Results The augmented dynamic physiology model (DPM) accurately predicted the human response to hypoxia, altitude, and exercise observed experimentally. The pulmonary damage parameters (shunt and diffusing capacity reduction) were fit to experimental animal data obtained in blast, blunt trauma, and chemical damage studies which link lung damage to lung weight change; the model is able to predict the reduced oxygen delivery in damage conditions. The model accurately estimates physical performance reduction with pulmonary damage. Conclusions We have developed a physiologically-based mathematical model to predict performance decrement endpoints in the presence of thoracic damage; simulations can be extended to estimate human performance and escape in extreme situations. PMID:25044032
Optimal Experimental Design for Model Discrimination
ERIC Educational Resources Information Center
Myung, Jay I.; Pitt, Mark A.
2009-01-01
Models of a psychological process can be difficult to discriminate experimentally because it is not easy to determine the values of the critical design variables (e.g., presentation schedule, stimulus structure) that will be most informative in differentiating them. Recent developments in sampling-based search methods in statistics make it…
Prediction of Radial Vibration in Switched Reluctance Machines
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lin, CJ; Fahimi, B
2013-12-01
Origins of vibration in switched reluctance machines (SRMs) are investigated. Accordingly, an input-output model based on the mechanical impulse response of the SRMis developed. The proposed model is derived using an experimental approach. Using the proposed approach, vibration of the stator frame is captured and experimentally verified.
System equivalent model mixing
NASA Astrophysics Data System (ADS)
Klaassen, Steven W. B.; van der Seijs, Maarten V.; de Klerk, Dennis
2018-05-01
This paper introduces SEMM: a method based on Frequency Based Substructuring (FBS) techniques that enables the construction of hybrid dynamic models. With System Equivalent Model Mixing (SEMM) frequency based models, either of numerical or experimental nature, can be mixed to form a hybrid model. This model follows the dynamic behaviour of a predefined weighted master model. A large variety of applications can be thought of, such as the DoF-space expansion of relatively small experimental models using numerical models, or the blending of different models in the frequency spectrum. SEMM is outlined, both mathematically and conceptually, based on a notation commonly used in FBS. A critical physical interpretation of the theory is provided next, along with a comparison to similar techniques; namely DoF expansion techniques. SEMM's concept is further illustrated by means of a numerical example. It will become apparent that the basic method of SEMM has some shortcomings which warrant a few extensions to the method. One of the main applications is tested in a practical case, performed on a validated benchmark structure; it will emphasize the practicality of the method.
NASA Astrophysics Data System (ADS)
El-Etriby, Ahmed E.; Abdel-Meguid, Mohamed E.; Hatem, Tarek M.; Bahei-El-Din, Yehia A.
2014-03-01
Ambient vibrations are major source of wasted energy, exploiting properly such vibration can be converted to valuable energy and harvested to power up devices, i.e. electronic devices. Accordingly, energy harvesting using smart structures with active piezoelectric ceramics has gained wide interest over the past few years as a method for converting such wasted energy. This paper provides numerical and experimental analysis of piezoelectric fiber based composites for energy harvesting applications proposing a multi-scale modeling approach coupled with experimental verification. The multi-scale approach suggested to predict the behavior of piezoelectric fiber-based composites use micromechanical model based on Transformation Field Analysis (TFA) to calculate the overall material properties of electrically active composite structure. Capitalizing on the calculated properties, single-phase analysis of a homogeneous structure is conducted using finite element method. The experimental work approach involves running dynamic tests on piezoelectric fiber-based composites to simulate mechanical vibrations experienced by a subway train floor tiles. Experimental results agree well with the numerical results both for static and dynamic tests.
Experimental and AI-based numerical modeling of contaminant transport in porous media
NASA Astrophysics Data System (ADS)
Nourani, Vahid; Mousavi, Shahram; Sadikoglu, Fahreddin; Singh, Vijay P.
2017-10-01
This study developed a new hybrid artificial intelligence (AI)-meshless approach for modeling contaminant transport in porous media. The key innovation of the proposed approach is that both black box and physically-based models are combined for modeling contaminant transport. The effectiveness of the approach was evaluated using experimental and real world data. Artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) were calibrated to predict temporal contaminant concentrations (CCs), and the effect of noisy and de-noised data on the model performance was evaluated. Then, considering the predicted CCs at test points (TPs, in experimental study) and piezometers (in Myandoab plain) as interior conditions, the multiquadric radial basis function (MQ-RBF), as a meshless approach which solves partial differential equation (PDE) of contaminant transport in porous media, was employed to estimate the CC values at any point within the study area where there was no TP or piezometer. Optimal values of the dispersion coefficient in the advection-dispersion PDE and shape coefficient of MQ-RBF were determined using the imperialist competitive algorithm. In temporal contaminant transport modeling, de-noised data enhanced the performance of ANN and ANFIS methods in terms of the determination coefficient, up to 6 and 5%, respectively, in the experimental study and up to 39 and 18%, respectively, in the field study. Results showed that the efficiency of ANFIS-meshless model was more than ANN-meshless model up to 2 and 13% in the experimental and field studies, respectively.
Development of a Lumped Element Circuit Model for Approximation of Dielectric Barrier Discharges
2011-08-01
dielectric barrier discharge (DBD) plasmas. Based on experimental observations, it is assumed that nanosecond pulsed DBDs, which have been proposed...species for pulsed direct current (DC) dielectric barrier discharge (DBD) plasmas. Based on experimental observations, it is assumed that nanosecond...momentum-based approaches. Given the fundamental differences between the novel pulsed discharge approach and the more conventional momentum-based
Zhang, Taolin; Zhou, Xiaodong; Yang, Lizhong
2016-03-05
This work investigated experimentally and theoretically the fire hazards of thermal-insulation materials used in diesel locomotives under different radiation heat fluxes. Based on the experimental results, the critical heat flux for ignition was determined to be 6.15 kW/m² and 16.39 kW/m² for pure polyurethane and aluminum-polyurethane respectively. A theoretical model was established for both to predict the fire behaviors under different circumstances. The fire behavior of the materials was evaluated based on the flashover and the total heat release rate (HRR). The fire hazards levels were classified based on different experimental results. It was found that the fire resistance performance of aluminum-polyurethane is much better than that of pure-polyurethane under various external heat fluxes. The concentration of toxic pyrolysis volatiles generated from aluminum-polyurethane materials is much higher than that of pure polyurethane materials, especially when the heat flux is below 50 kW/m². The hazard index HI during peak width time was proposed based on the comprehensive impact of time and concentrations. The predicted HI in this model coincides with the existed N-gas and FED models which are generally used to evaluate the fire gas hazard in previous researches. The integrated model named HNF was proposed as well to estimate the fire hazards of materials by interpolation and weighted average calculation.
Zhang, Taolin; Zhou, Xiaodong; Yang, Lizhong
2016-01-01
This work investigated experimentally and theoretically the fire hazards of thermal-insulation materials used in diesel locomotives under different radiation heat fluxes. Based on the experimental results, the critical heat flux for ignition was determined to be 6.15 kW/m2 and 16.39 kW/m2 for pure polyurethane and aluminum-polyurethane respectively. A theoretical model was established for both to predict the fire behaviors under different circumstances. The fire behavior of the materials was evaluated based on the flashover and the total heat release rate (HRR). The fire hazards levels were classified based on different experimental results. It was found that the fire resistance performance of aluminum-polyurethane is much better than that of pure-polyurethane under various external heat fluxes. The concentration of toxic pyrolysis volatiles generated from aluminum-polyurethane materials is much higher than that of pure polyurethane materials, especially when the heat flux is below 50 kW/m2. The hazard index HI during peak width time was proposed based on the comprehensive impact of time and concentrations. The predicted HI in this model coincides with the existed N-gas and FED models which are generally used to evaluate the fire gas hazard in previous researches. The integrated model named HNF was proposed as well to estimate the fire hazards of materials by interpolation and weighted average calculation. PMID:28773295
NASA Astrophysics Data System (ADS)
Zhu, Jun
Ru and Pt are candidate additional component for improving the high temperature properties of Ni-base superalloys. A thermodynamic description of the Ni-Al-Cr-Ru-Pt system, serving as an essential knowledge base for better alloy design and processing control, was developed in the present study by means of thermodynamic modeling coupled with experimental investigations of phase equilibria. To deal with the order/disorder transition occurring in the Ni-base superalloys, a physical sound model, Cluster/Site Approximation (CSA) was used to describe the fcc phases. The CSA offers computational advantages, without loss of accuracy, over the Cluster Variation Method (CVM) in the calculation of multicomponent phase diagrams. It has been successfully applied to fcc phases in calculating technologically important Ni-Al-Cr phase diagrams. Our effort in this study focused on the two key ternary systems: Ni-Al-Ru and Ni-Al-Pt. The CSA calculated Ni-Al-Ru ternary phase diagrams are in good agreement with the experimental results in the literature and from the current study. A thermodynamic description of quaternary Ni-Al-Cr-Ru was obtained based on the descriptions of the lower order systems and the calculated results agree with experimental data available in literature and in the current study. The Ni-Al-Pt system was thermodynamically modeled based on the limited experimental data available in the literature and obtained from the current study. With the help of the preliminary description, a number of alloy compositions were selected for further investigation. The information obtained was used to improve the current modeling. A thermodynamic description of the Ni-Al-Cr-Pt quaternary was then obtained via extrapolation from its constituent lower order systems. The thermodynamic description for Ni-base superalloy containing Al, Cr, Ru and Pt was obtained via extrapolation. It is believed to be reliable and useful to guide the alloy design and further experimental investigation.
GROMOS polarizable charge-on-spring models for liquid urea: COS/U and COS/U2
NASA Astrophysics Data System (ADS)
Lin, Zhixiong; Bachmann, Stephan J.; van Gunsteren, Wilfred F.
2015-03-01
Two one-site polarizable urea models, COS/U and COS/U2, based on the charge-on-spring model are proposed. The models are parametrized against thermodynamic properties of urea-water mixtures in combination with the polarizable COS/G2 and COS/D2 models for liquid water, respectively, and have the same functional form of the inter-atomic interaction function and are based on the same parameter calibration procedure and type of experimental data as used to develop the GROMOS biomolecular force field. Thermodynamic, dielectric, and dynamic properties of urea-water mixtures simulated using the polarizable models are closer to experimental data than using the non-polarizable models. The COS/U and COS/U2 models may be used in biomolecular simulations of protein denaturation.
Vinnakota, Kalyan C; Beard, Daniel A; Dash, Ranjan K
2009-01-01
Identification of a complex biochemical system model requires appropriate experimental data. Models constructed on the basis of data from the literature often contain parameters that are not identifiable with high sensitivity and therefore require additional experimental data to identify those parameters. Here we report the application of a local sensitivity analysis to design experiments that will improve the identifiability of previously unidentifiable model parameters in a model of mitochondrial oxidative phosphorylation and tricaboxylic acid cycle. Experiments were designed based on measurable biochemical reactants in a dilute suspension of purified cardiac mitochondria with experimentally feasible perturbations to this system. Experimental perturbations and variables yielding the most number of parameters above a 5% sensitivity level are presented and discussed.
NASA Astrophysics Data System (ADS)
Xiong, Chun-Hua; Sun, Jiu-Xun; Wang, Dai-Peng; Dong, Yan
2018-02-01
There are many models for researching charge transport in semiconductors and improving their performance. Most of them give good descriptions of the experimental data at room temperature. But it is still an open question which model is correct. In this paper, numerical calculations based on three modified versions of a classical model were made, and compared with experimental data for typical devices at room or low temperatures. Although their results are very similar to each other at room temperatures, only the version considering exciton effects by using a hydrogen-like model can give qualitative descriptions to recent experimental data at low temperatures. Moreover, the mobility was researched in detail by comparing the constant model and temperature dependence model. Then, we found the performance increases with the mobility of each charge carrier type being independent to the mobility of the other one. This paper provides better insight into understanding the physical mechanism of carrier transport in semiconductors, and the results show that exciton effects should be considered in modeling organic solar cells.
Optimizing Experimental Design for Comparing Models of Brain Function
Daunizeau, Jean; Preuschoff, Kerstin; Friston, Karl; Stephan, Klaas
2011-01-01
This article presents the first attempt to formalize the optimization of experimental design with the aim of comparing models of brain function based on neuroimaging data. We demonstrate our approach in the context of Dynamic Causal Modelling (DCM), which relates experimental manipulations to observed network dynamics (via hidden neuronal states) and provides an inference framework for selecting among candidate models. Here, we show how to optimize the sensitivity of model selection by choosing among experimental designs according to their respective model selection accuracy. Using Bayesian decision theory, we (i) derive the Laplace-Chernoff risk for model selection, (ii) disclose its relationship with classical design optimality criteria and (iii) assess its sensitivity to basic modelling assumptions. We then evaluate the approach when identifying brain networks using DCM. Monte-Carlo simulations and empirical analyses of fMRI data from a simple bimanual motor task in humans serve to demonstrate the relationship between network identification and the optimal experimental design. For example, we show that deciding whether there is a feedback connection requires shorter epoch durations, relative to asking whether there is experimentally induced change in a connection that is known to be present. Finally, we discuss limitations and potential extensions of this work. PMID:22125485
Thermomechanical Characterization and Modeling of Superelastic Shape Memory Alloy Beams and Frames
NASA Astrophysics Data System (ADS)
Watkins, Ryan
Of existing applications, the majority of shape memory alloy (SMA) devices consist of beam (orthodontic wire, eye glasses frames, catheter guide wires) and framed structures (cardiovascular stents, vena cava filters). Although uniaxial tension data is often sufficient to model basic beam behavior (which has been the main focus of the research community), the tension-compression asymmetry and complex phase transformation behavior of SMAs suggests more information is necessary to properly model higher complexity states of loading. In this work, SMA beams are experimentally characterized under general loading conditions (including tension, compression, pure bending, and buckling); furthermore, a model is developed with respect to general beam deformation based on the relevant phenomena observed in the experimental characterization. Stress induced phase transformation within superelastic SMA beams is shown to depend on not only the loading mode, but also kinematic constraints imposed by beam geometry (such as beam cross-section and length). In the cases of tension and pure bending, the structural behavior is unstable and corresponds to phase transformation localization and propagation. This unstable behavior is the result of a local level up--down--up stress/strain response in tension, which is measured here using a novel composite-based experimental technique. In addition to unstable phase transformation, intriguing post-buckling straightening is observed in short SMA columns during monotonic loading (termed unbuckling here). Based on this phenomenological understanding of SMA beam behavior, a trilinear based material law is developed in the context of a Shanley column model and is found to capture many of the relevant features of column buckling, including the experimentally observed unbuckling behavior. Due to the success of this model, it is generalized within the context of beam theory and, in conjunction with Bloch wave stability analysis, is used to model and design SMA honeycombs.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Balanin, A. L.; Boyarinov, V. F.; Glushkov, E. S.
The application of experimental information on measured axial distributions of fission reaction rates for development of 3D numerical models of the ASTRA critical facility taking into account azimuthal asymmetry of the assembly simulating a HTGR with annular core is substantiated. Owing to the presence of the bottom reflector and the absence of the top reflector, the application of 2D models based on experimentally determined buckling is impossible for calculation of critical assemblies of the ASTRA facility; therefore, an alternative approach based on the application of the extrapolated assembly height is proposed. This approach is exemplified by the numerical analysis ofmore » experiments on measurement of efficiency of control rods mockups and protection system (CPS).« less
NASA Astrophysics Data System (ADS)
Velarde, P.; Valverde, L.; Maestre, J. M.; Ocampo-Martinez, C.; Bordons, C.
2017-03-01
In this paper, a performance comparison among three well-known stochastic model predictive control approaches, namely, multi-scenario, tree-based, and chance-constrained model predictive control is presented. To this end, three predictive controllers have been designed and implemented in a real renewable-hydrogen-based microgrid. The experimental set-up includes a PEM electrolyzer, lead-acid batteries, and a PEM fuel cell as main equipment. The real experimental results show significant differences from the plant components, mainly in terms of use of energy, for each implemented technique. Effectiveness, performance, advantages, and disadvantages of these techniques are extensively discussed and analyzed to give some valid criteria when selecting an appropriate stochastic predictive controller.
Optimization of Nd: YAG Laser Marking of Alumina Ceramic Using RSM And ANN
DOE Office of Scientific and Technical Information (OSTI.GOV)
Peter, Josephine; Doloi, B.; Bhattacharyya, B.
The present research papers deals with the artificial neural network (ANN) and the response surface methodology (RSM) based mathematical modeling and also an optimization analysis on marking characteristics on alumina ceramic. The experiments have been planned and carried out based on Design of Experiment (DOE). It also analyses the influence of the major laser marking process parameters and the optimal combination of laser marking process parametric setting has been obtained. The output of the RSM optimal data is validated through experimentation and ANN predictive model. A good agreement is observed between the results based on ANN predictive model and actualmore » experimental observations.« less
Research on flow stress model and dynamic recrystallization model of X12CrMoWVNbN10-1-1 steel
NASA Astrophysics Data System (ADS)
Sui, Da-shan; Wang, Wei; Fu, Bo; Cui, Zhen-shan
2013-05-01
Plastic deformation behavior of X12CrMoWVNbN10-1-1 ferrite heat-resistant steel was studied systematically at high temperature. The stress-strain curves were measured at the temperature of 950°C-1250°C and strain rate of 0.0005s-1-0.1s-1 by Gleeble thermo-mechanical simulator. The flow stress model and dynamic recrystallization model were established based on Laasraoui two-stage model. The activation energy was calculated and the parameters were determined accordingly based on the experimental results and Sellars creep equation. The verification was performed to prove the models and it indicated the calculated results were identical to the experimental data.
Artificial Neural Network Approach in Laboratory Test Reporting: Learning Algorithms.
Demirci, Ferhat; Akan, Pinar; Kume, Tuncay; Sisman, Ali Riza; Erbayraktar, Zubeyde; Sevinc, Suleyman
2016-08-01
In the field of laboratory medicine, minimizing errors and establishing standardization is only possible by predefined processes. The aim of this study was to build an experimental decision algorithm model open to improvement that would efficiently and rapidly evaluate the results of biochemical tests with critical values by evaluating multiple factors concurrently. The experimental model was built by Weka software (Weka, Waikato, New Zealand) based on the artificial neural network method. Data were received from Dokuz Eylül University Central Laboratory. "Training sets" were developed for our experimental model to teach the evaluation criteria. After training the system, "test sets" developed for different conditions were used to statistically assess the validity of the model. After developing the decision algorithm with three iterations of training, no result was verified that was refused by the laboratory specialist. The sensitivity of the model was 91% and specificity was 100%. The estimated κ score was 0.950. This is the first study based on an artificial neural network to build an experimental assessment and decision algorithm model. By integrating our trained algorithm model into a laboratory information system, it may be possible to reduce employees' workload without compromising patient safety. © American Society for Clinical Pathology, 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Fast flexible modeling of RNA structure using internal coordinates.
Flores, Samuel Coulbourn; Sherman, Michael A; Bruns, Christopher M; Eastman, Peter; Altman, Russ Biagio
2011-01-01
Modeling the structure and dynamics of large macromolecules remains a critical challenge. Molecular dynamics (MD) simulations are expensive because they model every atom independently, and are difficult to combine with experimentally derived knowledge. Assembly of molecules using fragments from libraries relies on the database of known structures and thus may not work for novel motifs. Coarse-grained modeling methods have yielded good results on large molecules but can suffer from difficulties in creating more detailed full atomic realizations. There is therefore a need for molecular modeling algorithms that remain chemically accurate and economical for large molecules, do not rely on fragment libraries, and can incorporate experimental information. RNABuilder works in the internal coordinate space of dihedral angles and thus has time requirements proportional to the number of moving parts rather than the number of atoms. It provides accurate physics-based response to applied forces, but also allows user-specified forces for incorporating experimental information. A particular strength of RNABuilder is that all Leontis-Westhof basepairs can be specified as primitives by the user to be satisfied during model construction. We apply RNABuilder to predict the structure of an RNA molecule with 160 bases from its secondary structure, as well as experimental information. Our model matches the known structure to 10.2 Angstroms RMSD and has low computational expense.
NASA Technical Reports Server (NTRS)
Storey, Jedediah M.; Kirk, Daniel; Gutierrez, Hector; Marsell, Brandon; Schallhorn, Paul; Lapilli, Gabriel D.
2015-01-01
Experimental and numerical results are presented from a new cryogenic fluid slosh program at the Florida Institute of Technology (FIT). Water and cryogenic liquid nitrogen are used in various ground-based tests with an approximately 30 cm diameter spherical tank to characterize damping, slosh mode frequencies, and slosh forces. The experimental results are compared to a computational fluid dynamics (CFD) model for validation. An analytical model is constructed from prior work for comparison. Good agreement is seen between experimental, numerical, and analytical results.
Experimental study of the oscillation of spheres in an acoustic levitator.
Andrade, Marco A B; Pérez, Nicolás; Adamowski, Julio C
2014-10-01
The spontaneous oscillation of solid spheres in a single-axis acoustic levitator is experimentally investigated by using a high speed camera to record the position of the levitated sphere as a function of time. The oscillations in the axial and radial directions are systematically studied by changing the sphere density and the acoustic pressure amplitude. In order to interpret the experimental results, a simple model based on a spring-mass system is applied in the analysis of the sphere oscillatory behavior. This model requires the knowledge of the acoustic pressure distribution, which was obtained numerically by using a linear finite element method (FEM). Additionally, the linear acoustic pressure distribution obtained by FEM was compared with that measured with a laser Doppler vibrometer. The comparison between numerical and experimental pressure distributions shows good agreement for low values of pressure amplitude. When the pressure amplitude is increased, the acoustic pressure distribution becomes nonlinear, producing harmonics of the fundamental frequency. The experimental results of the spheres oscillations for low pressure amplitudes are consistent with the results predicted by the simple model based on a spring-mass system.
Ravikumar, Balaguru; Parri, Elina; Timonen, Sanna; Airola, Antti; Wennerberg, Krister
2017-01-01
Due to relatively high costs and labor required for experimental profiling of the full target space of chemical compounds, various machine learning models have been proposed as cost-effective means to advance this process in terms of predicting the most potent compound-target interactions for subsequent verification. However, most of the model predictions lack direct experimental validation in the laboratory, making their practical benefits for drug discovery or repurposing applications largely unknown. Here, we therefore introduce and carefully test a systematic computational-experimental framework for the prediction and pre-clinical verification of drug-target interactions using a well-established kernel-based regression algorithm as the prediction model. To evaluate its performance, we first predicted unmeasured binding affinities in a large-scale kinase inhibitor profiling study, and then experimentally tested 100 compound-kinase pairs. The relatively high correlation of 0.77 (p < 0.0001) between the predicted and measured bioactivities supports the potential of the model for filling the experimental gaps in existing compound-target interaction maps. Further, we subjected the model to a more challenging task of predicting target interactions for such a new candidate drug compound that lacks prior binding profile information. As a specific case study, we used tivozanib, an investigational VEGF receptor inhibitor with currently unknown off-target profile. Among 7 kinases with high predicted affinity, we experimentally validated 4 new off-targets of tivozanib, namely the Src-family kinases FRK and FYN A, the non-receptor tyrosine kinase ABL1, and the serine/threonine kinase SLK. Our sub-sequent experimental validation protocol effectively avoids any possible information leakage between the training and validation data, and therefore enables rigorous model validation for practical applications. These results demonstrate that the kernel-based modeling approach offers practical benefits for probing novel insights into the mode of action of investigational compounds, and for the identification of new target selectivities for drug repurposing applications. PMID:28787438
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mayer, Carl R.
Al-SiC nanolaminate composites show promise as high performance coating materials due to their combination of strength and toughness. Although a significant amount of modeling effort has been focused on materials with an idealized flat nanostructure, experimentally these materials exhibit complex undulating layer geometries. This work utilizes FIB tomography to characterize this nanostructure in 3D and finite element modeling to determine the effect that this complex structure has on the mechanical behavior of these materials. A sufficiently large volume was characterized such that a 1 × 2 μm micropillar could be generated from the dataset and compared directly to experimental results.more » The mechanical response from this nanostructure was then compared to pillar models using simplified structures with perfectly flat layers, layers with sinusoidal waviness, and layers with arc segment waviness. The arc segment based layer geometry showed the best agreement with the experimentally determined structure, indicating it would be the most appropriate geometry for future modeling efforts. - Highlights: •FIB tomography was used to determine the structure of an Al-SiC nanolaminate in 3D. •FEM was used to compare the deformation of the nanostructure to experimental results. •Idealized structures from literature were compared to the FIB determined structure. •Arc segment based structures approximated the FIB determined structure most closely.« less
3-D and quasi-2-D discrete element modeling of grain commingling in a bucket elevator boot system
USDA-ARS?s Scientific Manuscript database
Unwanted grain commingling impedes new quality-based grain handling systems and has proven to be an expensive and time consuming issue to study experimentally. Experimentally validated models may reduce the time and expense of studying grain commingling while providing additional insight into detail...
Entropy-Based Search Algorithm for Experimental Design
NASA Astrophysics Data System (ADS)
Malakar, N. K.; Knuth, K. H.
2011-03-01
The scientific method relies on the iterated processes of inference and inquiry. The inference phase consists of selecting the most probable models based on the available data; whereas the inquiry phase consists of using what is known about the models to select the most relevant experiment. Optimizing inquiry involves searching the parameterized space of experiments to select the experiment that promises, on average, to be maximally informative. In the case where it is important to learn about each of the model parameters, the relevance of an experiment is quantified by Shannon entropy of the distribution of experimental outcomes predicted by a probable set of models. If the set of potential experiments is described by many parameters, we must search this high-dimensional entropy space. Brute force search methods will be slow and computationally expensive. We present an entropy-based search algorithm, called nested entropy sampling, to select the most informative experiment for efficient experimental design. This algorithm is inspired by Skilling's nested sampling algorithm used in inference and borrows the concept of a rising threshold while a set of experiment samples are maintained. We demonstrate that this algorithm not only selects highly relevant experiments, but also is more efficient than brute force search. Such entropic search techniques promise to greatly benefit autonomous experimental design.
Mechanical properties of multifunctional structure with viscoelastic components based on FVE model
NASA Astrophysics Data System (ADS)
Hao, Dong; Zhang, Lin; Yu, Jing; Mao, Daiyong
2018-02-01
Based on the models of Lion and Kardelky (2004) and Hofer and Lion (2009), a finite viscoelastic (FVE) constitutive model, considering the predeformation-, frequency- and amplitude-dependent properties, has been proposed in our earlier paper [1]. FVE model is applied to investigating the dynamic characteristics of the multifunctional structure with the viscoelastic components. Combing FVE model with the finite element theory, the dynamic model of the multifunctional structure could be obtained. Additionally, the parametric identification and the experimental verification are also given via the frequency-sweep tests. The results show that the computational data agree well with the experimental data. FVE model has made a success of expressing the dynamic characteristics of the viscoelastic materials utilized in the multifunctional structure. The multifunctional structure technology has been verified by in-orbit experiments.
A ferrofluid based energy harvester: Computational modeling, analysis, and experimental validation
NASA Astrophysics Data System (ADS)
Liu, Qi; Alazemi, Saad F.; Daqaq, Mohammed F.; Li, Gang
2018-03-01
A computational model is described and implemented in this work to analyze the performance of a ferrofluid based electromagnetic energy harvester. The energy harvester converts ambient vibratory energy into an electromotive force through a sloshing motion of a ferrofluid. The computational model solves the coupled Maxwell's equations and Navier-Stokes equations for the dynamic behavior of the magnetic field and fluid motion. The model is validated against experimental results for eight different configurations of the system. The validated model is then employed to study the underlying mechanisms that determine the electromotive force of the energy harvester. Furthermore, computational analysis is performed to test the effect of several modeling aspects, such as three-dimensional effect, surface tension, and type of the ferrofluid-magnetic field coupling on the accuracy of the model prediction.
Uncertainty Modeling for Structural Control Analysis and Synthesis
NASA Technical Reports Server (NTRS)
Campbell, Mark E.; Crawley, Edward F.
1996-01-01
The development of an accurate model of uncertainties for the control of structures that undergo a change in operational environment, based solely on modeling and experimentation in the original environment is studied. The application used throughout this work is the development of an on-orbit uncertainty model based on ground modeling and experimentation. A ground based uncertainty model consisting of mean errors and bounds on critical structural parameters is developed. The uncertainty model is created using multiple data sets to observe all relevant uncertainties in the system. The Discrete Extended Kalman Filter is used as an identification/parameter estimation method for each data set, in addition to providing a covariance matrix which aids in the development of the uncertainty model. Once ground based modal uncertainties have been developed, they are localized to specific degrees of freedom in the form of mass and stiffness uncertainties. Two techniques are presented: a matrix method which develops the mass and stiffness uncertainties in a mathematical manner; and a sensitivity method which assumes a form for the mass and stiffness uncertainties in macroelements and scaling factors. This form allows the derivation of mass and stiffness uncertainties in a more physical manner. The mass and stiffness uncertainties of the ground based system are then mapped onto the on-orbit system, and projected to create an analogous on-orbit uncertainty model in the form of mean errors and bounds on critical parameters. The Middeck Active Control Experiment is introduced as experimental verification for the localization and projection methods developed. In addition, closed loop results from on-orbit operations of the experiment verify the use of the uncertainty model for control analysis and synthesis in space.
NASA Astrophysics Data System (ADS)
Wang, Huan-huan; Wang, Jian; Liu, Feng; Cao, Hai-juan; Wang, Xiang-jun
2014-12-01
A test environment is established to obtain experimental data for verifying the positioning model which was derived previously based on the pinhole imaging model and the theory of binocular stereo vision measurement. The model requires that the optical axes of the two cameras meet at one point which is defined as the origin of the world coordinate system, thus simplifying and optimizing the positioning model. The experimental data are processed and tables and charts are given for comparing the positions of objects measured with DGPS with a measurement accuracy of 10 centimeters as the reference and those measured with the positioning model. Sources of visual measurement model are analyzed, and the effects of the errors of camera and system parameters on the accuracy of positioning model were probed, based on the error transfer and synthesis rules. A conclusion is made that measurement accuracy of surface surveillances based on binocular stereo vision measurement is better than surface movement radars, ADS-B (Automatic Dependent Surveillance-Broadcast) and MLAT (Multilateration).
van den Bruinhorst, Adriaan; Spyriouni, Theodora; Hill, Jörg-Rüdiger; Kroon, Maaike C
2018-01-11
The liquid range and applicability of deep eutectic solvents (DESs) are determined by their physicochemical properties. In this work, the physicochemical properties of glycolic acid:proline and malic acid:proline were evaluated experimentally and with MD simulations at five different ratios. Both DESs exhibited esterification upon preparation, which affected the viscosity in particular. In order to minimize oligomer formation and water release, three different experimental preparation methods were explored, but none could prevent esterification. The experimental and calculated densities of the DESs were found to be in good agreement. The measured and modeled glass transition temperature showed similar trends with composition, as did the experimental viscosity and the calculated diffusivities. The MD simulations provided additional insight at the atomistic level, showing that at acid-rich compositions, the acid-acid hydrogen bonding (HB) interactions prevail. Malic acid-based DESs show stronger acid-acid HB interactions than glycolic acid-based ones, possibly explaining its extreme viscosity. Upon the addition of proline, the interspecies interactions become predominant, confirming the formation of the widely assumed HB network between the DESs constituents in the liquid phase.
A Novel GMM-Based Behavioral Modeling Approach for Smartwatch-Based Driver Authentication.
Yang, Ching-Han; Chang, Chin-Chun; Liang, Deron
2018-03-28
All drivers have their own distinct driving habits, and usually hold and operate the steering wheel differently in different driving scenarios. In this study, we proposed a novel Gaussian mixture model (GMM)-based method that can improve the traditional GMM in modeling driving behavior. This new method can be applied to build a better driver authentication system based on the accelerometer and orientation sensor of a smartwatch. To demonstrate the feasibility of the proposed method, we created an experimental system that analyzes driving behavior using the built-in sensors of a smartwatch. The experimental results for driver authentication-an equal error rate (EER) of 4.62% in the simulated environment and an EER of 7.86% in the real-traffic environment-confirm the feasibility of this approach.
Wilmoth, Jared L; Doak, Peter W; Timm, Andrea; Halsted, Michelle; Anderson, John D; Ginovart, Marta; Prats, Clara; Portell, Xavier; Retterer, Scott T; Fuentes-Cabrera, Miguel
2018-01-01
The factors leading to changes in the organization of microbial assemblages at fine spatial scales are not well characterized or understood. However, they are expected to guide the succession of community development and function toward specific outcomes that could impact human health and the environment. In this study, we put forward a combined experimental and agent-based modeling framework and use it to interpret unique spatial organization patterns of H1-Type VI secretion system (T6SS) mutants of P . aeruginosa under spatial confinement. We find that key parameters, such as T6SS-mediated cell contact and lysis, spatial localization, relative species abundance, cell density and local concentrations of growth substrates and metabolites are influenced by spatial confinement. The model, written in the accessible programming language NetLogo, can be adapted to a variety of biological systems of interest and used to simulate experiments across a broad parameter space. It was implemented and run in a high-throughput mode by deploying it across multiple CPUs, with each simulation representing an individual well within a high-throughput microwell array experimental platform. The microfluidics and agent-based modeling framework we present in this paper provides an effective means by which to connect experimental studies in microbiology to model development. The work demonstrates progress in coupling experimental results to simulation while also highlighting potential sources of discrepancies between real-world experiments and idealized models.
Wilmoth, Jared L.; Doak, Peter W.; Timm, Andrea; Halsted, Michelle; Anderson, John D.; Ginovart, Marta; Prats, Clara; Portell, Xavier; Retterer, Scott T.; Fuentes-Cabrera, Miguel
2018-01-01
The factors leading to changes in the organization of microbial assemblages at fine spatial scales are not well characterized or understood. However, they are expected to guide the succession of community development and function toward specific outcomes that could impact human health and the environment. In this study, we put forward a combined experimental and agent-based modeling framework and use it to interpret unique spatial organization patterns of H1-Type VI secretion system (T6SS) mutants of P. aeruginosa under spatial confinement. We find that key parameters, such as T6SS-mediated cell contact and lysis, spatial localization, relative species abundance, cell density and local concentrations of growth substrates and metabolites are influenced by spatial confinement. The model, written in the accessible programming language NetLogo, can be adapted to a variety of biological systems of interest and used to simulate experiments across a broad parameter space. It was implemented and run in a high-throughput mode by deploying it across multiple CPUs, with each simulation representing an individual well within a high-throughput microwell array experimental platform. The microfluidics and agent-based modeling framework we present in this paper provides an effective means by which to connect experimental studies in microbiology to model development. The work demonstrates progress in coupling experimental results to simulation while also highlighting potential sources of discrepancies between real-world experiments and idealized models. PMID:29467721
NASA Astrophysics Data System (ADS)
Vrabec, Jadran; Kedia, Gaurav Kumar; Buchhauser, Ulrich; Meyer-Pittroff, Roland; Hasse, Hans
2009-02-01
For the design and optimization of CO 2 recovery from alcoholic fermentation processes by distillation, models for vapor-liquid equilibria (VLE) are needed. Two such thermodynamic models, the Peng-Robinson equation of state (EOS) and a model based on Henry's law constants, are proposed for the ternary mixture N 2 + O 2 + CO 2. Pure substance parameters of the Peng-Robinson EOS are taken from the literature, whereas the binary parameters of the Van der Waals one-fluid mixing rule are adjusted to experimental binary VLE data. The Peng-Robinson EOS describes both binary and ternary experimental data well, except at high pressures approaching the critical region. A molecular model is validated by simulation using binary and ternary experimental VLE data. On the basis of this model, the Henry's law constants of N 2 and O 2 in CO 2 are predicted by molecular simulation. An easy-to-use thermodynamic model, based on those Henry's law constants, is developed to reliably describe the VLE in the CO 2-rich region.
NASA Astrophysics Data System (ADS)
Aswan, D. M.; Lufri, L.; Sumarmin, R.
2018-04-01
This research intends to determine the effect of Problem Based Learning models on students' critical thinking skills and competences. This study was a quasi-experimental research. The population of the study was the students of class VIII SMPN 1 Subdistrict Gunuang Omeh. Random sample selection is done by randomizing the class. Sample class that was chosen VIII3 as an experimental class given that treatment study based on problems and class VIII1 as control class that treatment usually given study. Instrument that used to consist of critical thinking test, cognitive tests, observation sheet of affective and psychomotor. Independent t-test and Mann Whitney U test was used for the analysis. Results showed that there was significant difference (sig <0.05) between control and experimental group. The conclusion of this study was Problem Based Learning models affected the students’ critical thinking skills and competences.
NASA Astrophysics Data System (ADS)
Joshi, Pranit Satish; Mahapatra, Pallab Sinha; Pattamatta, Arvind
2017-12-01
Experiments and numerical simulation of natural convection heat transfer with nanosuspensions are presented in this work. The investigations are carried out for three different types of nanosuspensions: namely, spherical-based (alumina/water), tubular-based (multi-walled carbon nanotube/water), and flake-based (graphene/water). A comparison with in-house experiments is made for all the three nanosuspensions at different volume fractions and for the Rayleigh numbers in the range of 7 × 105-1 × 107. Different models such as single component homogeneous, single component non-homogeneous, and multicomponent non-homogeneous are used in the present study. From the present numerical investigation, it is observed that for lower volume fractions (˜0.1%) of nanosuspensions considered, single component models are in close agreement with the experimental results. Single component models which are based on the effective properties of the nanosuspensions alone can predict heat transfer characteristics very well within the experimental uncertainty. Whereas for higher volume fractions (˜0.5%), the multi-component model predicts closer results to the experimental observation as it incorporates drag-based slip force which becomes prominent. The enhancement observed at lower volume fractions for non-spherical particles is attributed to the percolation chain formation, which perturbs the boundary layer and thereby increases the local Nusselt number values.
Numerical modelling and experimental study of liquid evaporation during gel formation
NASA Astrophysics Data System (ADS)
Pokusaev, B. G.; Khramtsov, D. P.
2017-11-01
Gels are promising materials in biotechnology and medicine as a medium for storing cells for bioprinting applications. Gel is a two-phase system consisting of solid medium and liquid phase. Understanding of a gel structure evolution and gel aging during liquid evaporation is a crucial step in developing new additive bioprinting technologies. A numerical and experimental study of liquid evaporation was performed. In experimental study an evaporation process of an agarose gel layer located on Petri dish was observed and mass difference was detected using electronic scales. Numerical model was based on a smoothed particle hydrodynamics method. Gel in a model was represented as a solid-liquid system and liquid evaporation was modelled due to capillary forces and heat transfer. Comparison of experimental data and numerical results demonstrated that model can adequately represent evaporation process in agarose gel.
Data for Room Fire Model Comparisons
Peacock, Richard D.; Davis, Sanford; Babrauskas, Vytenis
1991-01-01
With the development of models to predict fire growth and spread in buildings, there has been a concomitant evolution in the measurement and analysis of experimental data in real-scale fires. This report presents the types of analyses that can be used to examine large-scale room fire test data to prepare the data for comparison with zone-based fire models. Five sets of experimental data which can be used to test the limits of a typical two-zone fire model are detailed. A standard set of nomenclature describing the geometry of the building and the quantities measured in each experiment is presented. Availability of ancillary data (such as smaller-scale test results) is included. These descriptions, along with the data (available in computer-readable form) should allow comparisons between the experiment and model predictions. The base of experimental data ranges in complexity from one room tests with individual furniture items to a series of tests conducted in a multiple story hotel equipped with a zoned smoke control system. PMID:28184121
Data for Room Fire Model Comparisons.
Peacock, Richard D; Davis, Sanford; Babrauskas, Vytenis
1991-01-01
With the development of models to predict fire growth and spread in buildings, there has been a concomitant evolution in the measurement and analysis of experimental data in real-scale fires. This report presents the types of analyses that can be used to examine large-scale room fire test data to prepare the data for comparison with zone-based fire models. Five sets of experimental data which can be used to test the limits of a typical two-zone fire model are detailed. A standard set of nomenclature describing the geometry of the building and the quantities measured in each experiment is presented. Availability of ancillary data (such as smaller-scale test results) is included. These descriptions, along with the data (available in computer-readable form) should allow comparisons between the experiment and model predictions. The base of experimental data ranges in complexity from one room tests with individual furniture items to a series of tests conducted in a multiple story hotel equipped with a zoned smoke control system.
NASA Astrophysics Data System (ADS)
Hu, Kun; Zhu, Qi-zhi; Chen, Liang; Shao, Jian-fu; Liu, Jian
2018-06-01
As confining pressure increases, crystalline rocks of moderate porosity usually undergo a transition in failure mode from localized brittle fracture to diffused damage and ductile failure. This transition has been widely reported experimentally for several decades; however, satisfactory modeling is still lacking. The present paper aims at modeling the brittle-ductile transition process of rocks under conventional triaxial compression. Based on quantitative analyses of experimental results, it is found that there is a quite satisfactory linearity between the axial inelastic strain at failure and the confining pressure prescribed. A micromechanics-based frictional damage model is then formulated using an associated plastic flow rule and a strain energy release rate-based damage criterion. The analytical solution to the strong plasticity-damage coupling problem is provided and applied to simulate the nonlinear mechanical behaviors of Tennessee marble, Indiana limestone and Jinping marble, each presenting a brittle-ductile transition in stress-strain curves.
NASA Technical Reports Server (NTRS)
Oglebay, J. C.
1977-01-01
A thermal analytic model for a 30-cm engineering model mercury-ion thruster was developed and calibrated using the experimental test results of tests of a pre-engineering model 30-cm thruster. A series of tests, performed later, simulated a wide range of thermal environments on an operating 30-cm engineering model thruster, which was instrumented to measure the temperature distribution within it. The modified analytic model is described and analytic and experimental results compared for various operating conditions. Based on the comparisons, it is concluded that the analytic model can be used as a preliminary design tool to predict thruster steady-state temperature distributions for stage and mission studies and to define the thermal interface bewteen the thruster and other elements of a spacecraft.
A polychromatic adaption of the Beer-Lambert model for spectral decomposition
NASA Astrophysics Data System (ADS)
Sellerer, Thorsten; Ehn, Sebastian; Mechlem, Korbinian; Pfeiffer, Franz; Herzen, Julia; Noël, Peter B.
2017-03-01
We present a semi-empirical forward-model for spectral photon-counting CT which is fully compatible with state-of-the-art maximum-likelihood estimators (MLE) for basis material line integrals. The model relies on a minimum calibration effort to make the method applicable in routine clinical set-ups with the need for periodic re-calibration. In this work we present an experimental verifcation of our proposed method. The proposed method uses an adapted Beer-Lambert model, describing the energy dependent attenuation of a polychromatic x-ray spectrum using additional exponential terms. In an experimental dual-energy photon-counting CT setup based on a CdTe detector, the model demonstrates an accurate prediction of the registered counts for an attenuated polychromatic spectrum. Thereby deviations between model and measurement data lie within the Poisson statistical limit of the performed acquisitions, providing an effectively unbiased forward-model. The experimental data also shows that the model is capable of handling possible spectral distortions introduced by the photon-counting detector and CdTe sensor. The simplicity and high accuracy of the proposed model provides a viable forward-model for MLE-based spectral decomposition methods without the need of costly and time-consuming characterization of the system response.
NASA Astrophysics Data System (ADS)
Maghareh, Amin; Silva, Christian E.; Dyke, Shirley J.
2018-05-01
Hydraulic actuators play a key role in experimental structural dynamics. In a previous study, a physics-based model for a servo-hydraulic actuator coupled with a nonlinear physical system was developed. Later, this dynamical model was transformed into controllable canonical form for position tracking control purposes. For this study, a nonlinear device is designed and fabricated to exhibit various nonlinear force-displacement profiles depending on the initial condition and the type of materials used as replaceable coupons. Using this nonlinear system, the controllable canonical dynamical model is experimentally validated for a servo-hydraulic actuator coupled with a nonlinear physical system.
Bochmann, Esther S; Steffens, Kristina E; Gryczke, Andreas; Wagner, Karl G
2018-03-01
Simulation of HME processes is a valuable tool for increased process understanding and ease of scale-up. However, the experimental determination of all required input parameters is tedious, namely the melt rheology of the amorphous solid dispersion (ASD) in question. Hence, a procedure to simplify the application of hot-melt extrusion (HME) simulation for forming amorphous solid dispersions (ASD) is presented. The commercial 1D simulation software Ludovic ® was used to conduct (i) simulations using a full experimental data set of all input variables including melt rheology and (ii) simulations using model-based melt viscosity data based on the ASDs glass transition and the physical properties of polymeric matrix only. Both types of HME computation were further compared to experimental HME results. Variation in physical properties (e.g. heat capacity, density) and several process characteristics of HME (residence time distribution, energy consumption) among the simulations and experiments were evaluated. The model-based melt viscosity was calculated by using the glass transition temperature (T g ) of the investigated blend and the melt viscosity of the polymeric matrix by means of a T g -viscosity correlation. The results of measured melt viscosity and model-based melt viscosity were similar with only few exceptions, leading to similar HME simulation outcomes. At the end, the experimental effort prior to HME simulation could be minimized and the procedure enables a good starting point for rational development of ASDs by means of HME. As model excipients, Vinylpyrrolidone-vinyl acetate copolymer (COP) in combination with various APIs (carbamazepine, dipyridamole, indomethacin, and ibuprofen) or polyethylene glycol (PEG 1500) as plasticizer were used to form the ASDs. Copyright © 2017 Elsevier B.V. All rights reserved.
Optimal Experimental Design for Model Discrimination
Myung, Jay I.; Pitt, Mark A.
2009-01-01
Models of a psychological process can be difficult to discriminate experimentally because it is not easy to determine the values of the critical design variables (e.g., presentation schedule, stimulus structure) that will be most informative in differentiating them. Recent developments in sampling-based search methods in statistics make it possible to determine these values, and thereby identify an optimal experimental design. After describing the method, it is demonstrated in two content areas in cognitive psychology in which models are highly competitive: retention (i.e., forgetting) and categorization. The optimal design is compared with the quality of designs used in the literature. The findings demonstrate that design optimization has the potential to increase the informativeness of the experimental method. PMID:19618983
Experimental Learning Enhancing Improvisation Skills
ERIC Educational Resources Information Center
Pereira Christopoulos, Tania; Wilner, Adriana; Trindade Bestetti, Maria Luisa
2016-01-01
Purpose: This study aims to present improvisation training and experimentation as an alternative method to deal with unexpected events in which structured processes do not seem to work. Design/Methodology/Approach: Based on the literature of sensemaking and improvisation, the study designs a framework and process model of experimental learning…
NASA Astrophysics Data System (ADS)
Eriksen, Trygve E.; Shoesmith, David W.; Jonsson, Mats
2012-01-01
Radiation induced dissolution of uranium dioxide (UO 2) nuclear fuel and the consequent release of radionuclides to intruding groundwater are key-processes in the safety analysis of future deep geological repositories for spent nuclear fuel. For several decades, these processes have been studied experimentally using both spent fuel and various types of simulated spent fuels. The latter have been employed since it is difficult to draw mechanistic conclusions from real spent nuclear fuel experiments. Several predictive modelling approaches have been developed over the last two decades. These models are largely based on experimental observations. In this work we have performed a critical review of the modelling approaches developed based on the large body of chemical and electrochemical experimental data. The main conclusions are: (1) the use of measured interfacial rate constants give results in generally good agreement with experimental results compared to simulations where homogeneous rate constants are used; (2) the use of spatial dose rate distributions is particularly important when simulating the behaviour over short time periods; and (3) the steady-state approach (the rate of oxidant consumption is equal to the rate of oxidant production) provides a simple but fairly accurate alternative, but errors in the reaction mechanism and in the kinetic parameters used may not be revealed by simple benchmarking. It is essential to use experimentally determined rate constants and verified reaction mechanisms, irrespective of whether the approach is chemical or electrochemical.
Wang, Tianmiao; Wu, Yao; Liang, Jianhong; Han, Chenhao; Chen, Jiao; Zhao, Qiteng
2015-04-24
Skid-steering mobile robots are widely used because of their simple mechanism and robustness. However, due to the complex wheel-ground interactions and the kinematic constraints, it is a challenge to understand the kinematics and dynamics of such a robotic platform. In this paper, we develop an analysis and experimental kinematic scheme for a skid-steering wheeled vehicle based-on a laser scanner sensor. The kinematics model is established based on the boundedness of the instantaneous centers of rotation (ICR) of treads on the 2D motion plane. The kinematic parameters (the ICR coefficient , the path curvature variable and robot speed ), including the effect of vehicle dynamics, are introduced to describe the kinematics model. Then, an exact but costly dynamic model is used and the simulation of this model's stationary response for the vehicle shows a qualitative relationship for the specified parameters and . Moreover, the parameters of the kinematic model are determined based-on a laser scanner localization experimental analysis method with a skid-steering robotic platform, Pioneer P3-AT. The relationship between the ICR coefficient and two physical factors is studied, i.e., the radius of the path curvature and the robot speed . An empirical function-based relationship between the ICR coefficient of the robot and the path parameters is derived. To validate the obtained results, it is empirically demonstrated that the proposed kinematics model significantly improves the dead-reckoning performance of this skid-steering robot.
NASA Astrophysics Data System (ADS)
Chen, Peng; Liu, Yuwei; Gao, Bingkun; Jiang, Chunlei
2018-03-01
A semiconductor laser employed with two-external-cavity feedback structure for laser self-mixing interference (SMI) phenomenon is investigated and analyzed. The SMI model with two directions based on F-P cavity is deduced, and numerical simulation and experimental verification were conducted. Experimental results show that the SMI with the structure of two-external-cavity feedback under weak light feedback is similar to the sum of two SMIs.
Effect of processing parameters on FDM process
NASA Astrophysics Data System (ADS)
Chari, V. Srinivasa; Venkatesh, P. R.; Krupashankar, Dinesh, Veena
2018-04-01
This paper focused on the process parameters on fused deposition modeling (FDM). Infill, resolution, temperature are the process variables considered for experimental studies. Compression strength, Hardness test microstructure are the outcome parameters, this experimental study done based on the taguchi's L9 orthogonal array is used. Taguchi array used to build the 9 different models and also to get the effective output results on the under taken parameters. The material used for this experimental study is Polylactic Acid (PLA).
Experimental Errors in QSAR Modeling Sets: What We Can Do and What We Cannot Do.
Zhao, Linlin; Wang, Wenyi; Sedykh, Alexander; Zhu, Hao
2017-06-30
Numerous chemical data sets have become available for quantitative structure-activity relationship (QSAR) modeling studies. However, the quality of different data sources may be different based on the nature of experimental protocols. Therefore, potential experimental errors in the modeling sets may lead to the development of poor QSAR models and further affect the predictions of new compounds. In this study, we explored the relationship between the ratio of questionable data in the modeling sets, which was obtained by simulating experimental errors, and the QSAR modeling performance. To this end, we used eight data sets (four continuous endpoints and four categorical endpoints) that have been extensively curated both in-house and by our collaborators to create over 1800 various QSAR models. Each data set was duplicated to create several new modeling sets with different ratios of simulated experimental errors (i.e., randomizing the activities of part of the compounds) in the modeling process. A fivefold cross-validation process was used to evaluate the modeling performance, which deteriorates when the ratio of experimental errors increases. All of the resulting models were also used to predict external sets of new compounds, which were excluded at the beginning of the modeling process. The modeling results showed that the compounds with relatively large prediction errors in cross-validation processes are likely to be those with simulated experimental errors. However, after removing a certain number of compounds with large prediction errors in the cross-validation process, the external predictions of new compounds did not show improvement. Our conclusion is that the QSAR predictions, especially consensus predictions, can identify compounds with potential experimental errors. But removing those compounds by the cross-validation procedure is not a reasonable means to improve model predictivity due to overfitting.
Experimental Errors in QSAR Modeling Sets: What We Can Do and What We Cannot Do
2017-01-01
Numerous chemical data sets have become available for quantitative structure–activity relationship (QSAR) modeling studies. However, the quality of different data sources may be different based on the nature of experimental protocols. Therefore, potential experimental errors in the modeling sets may lead to the development of poor QSAR models and further affect the predictions of new compounds. In this study, we explored the relationship between the ratio of questionable data in the modeling sets, which was obtained by simulating experimental errors, and the QSAR modeling performance. To this end, we used eight data sets (four continuous endpoints and four categorical endpoints) that have been extensively curated both in-house and by our collaborators to create over 1800 various QSAR models. Each data set was duplicated to create several new modeling sets with different ratios of simulated experimental errors (i.e., randomizing the activities of part of the compounds) in the modeling process. A fivefold cross-validation process was used to evaluate the modeling performance, which deteriorates when the ratio of experimental errors increases. All of the resulting models were also used to predict external sets of new compounds, which were excluded at the beginning of the modeling process. The modeling results showed that the compounds with relatively large prediction errors in cross-validation processes are likely to be those with simulated experimental errors. However, after removing a certain number of compounds with large prediction errors in the cross-validation process, the external predictions of new compounds did not show improvement. Our conclusion is that the QSAR predictions, especially consensus predictions, can identify compounds with potential experimental errors. But removing those compounds by the cross-validation procedure is not a reasonable means to improve model predictivity due to overfitting. PMID:28691113
Pharmacokinetic modeling in aquatic animals. 1. Models and concepts
Barron, M.G.; Stehly, Guy R.; Hayton, W.L.
1990-01-01
While clinical and toxicological applications of pharmacokinetics have continued to evolve both conceptually and experimentally, pharmacokinetics modeling in aquatic animals has not progressed accordingly. In this paper we present methods and concepts of pharmacokinetic modeling in aquatic animals using multicompartmental, clearance-based, non-compartmental and physiologically-based pharmacokinetic models. These models should be considered as alternatives to traditional approaches, which assume that the animal acts as a single homogeneous compartment based on apparent monoexponential elimination.
Experimental and AI-based numerical modeling of contaminant transport in porous media.
Nourani, Vahid; Mousavi, Shahram; Sadikoglu, Fahreddin; Singh, Vijay P
2017-10-01
This study developed a new hybrid artificial intelligence (AI)-meshless approach for modeling contaminant transport in porous media. The key innovation of the proposed approach is that both black box and physically-based models are combined for modeling contaminant transport. The effectiveness of the approach was evaluated using experimental and real world data. Artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) were calibrated to predict temporal contaminant concentrations (CCs), and the effect of noisy and de-noised data on the model performance was evaluated. Then, considering the predicted CCs at test points (TPs, in experimental study) and piezometers (in Myandoab plain) as interior conditions, the multiquadric radial basis function (MQ-RBF), as a meshless approach which solves partial differential equation (PDE) of contaminant transport in porous media, was employed to estimate the CC values at any point within the study area where there was no TP or piezometer. Optimal values of the dispersion coefficient in the advection-dispersion PDE and shape coefficient of MQ-RBF were determined using the imperialist competitive algorithm. In temporal contaminant transport modeling, de-noised data enhanced the performance of ANN and ANFIS methods in terms of the determination coefficient, up to 6 and 5%, respectively, in the experimental study and up to 39 and 18%, respectively, in the field study. Results showed that the efficiency of ANFIS-meshless model was more than ANN-meshless model up to 2 and 13% in the experimental and field studies, respectively. Copyright © 2017. Published by Elsevier B.V.
ERIC Educational Resources Information Center
Düsmez, Ihsan; Barut, Yasar
2016-01-01
The research is an experimental study which has experimental and control groups, and based on pre-test, post-test, monitoring test model. Research group consists of second and third grade students of Primary School Education and Psychological Counseling undergraduate programmes in Giresun University Faculty of Educational Sciences. The research…
The Lα (λ = 121.6 nm) solar plage contrasts calculations.
NASA Astrophysics Data System (ADS)
Bruevich, E. A.
1991-06-01
The results of calculations of Lα plage contrasts based on experimental data are presented. A three-component model ideology of Lα solar flux using "Prognoz-10" and SME daily smoothed values of Lα solar flux are applied. The values of contrast are discussed and compared with experimental values based on "Skylab" data.
An innovative seismic bracing system based on a superelastic shape memory alloy ring
NASA Astrophysics Data System (ADS)
Gao, Nan; Jeon, Jong-Su; Hodgson, Darel E.; DesRoches, Reginald
2016-05-01
Shape memory alloys (SMAs) have great potential in seismic applications because of their remarkable superelasticity. Seismic bracing systems based on SMAs can mitigate the damage caused by earthquakes. The current study investigates a bracing system based on an SMA ring which is capable of both re-centering and energy dissipation. This lateral force resisting system is a cross-braced system consisting of an SMA ring and four tension-only cable assemblies, which can be applied to both new construction and seismic retrofit. The performance of this bracing system is examined through a quasi-static cyclic loading test and finite element (FE) analysis. This paper describes the experimental design in detail, discusses the experimental results, compares the performance with other bracing systems based on SMAs, and presents an Abaqus FE model calibrated on the basis of experimental results to simulate the superelastic behavior of the SMA ring. The experimental results indicate that the seismic performance of this system is promising in terms of damping and re-centering. The FE model can be used in the simulation of building structures using the proposed bracing system.
A comparison of arcjet plume properties to model predictions
NASA Technical Reports Server (NTRS)
Cappelli, M. A.; Liebeskind, J. G.; Hanson, R. K.; Butler, G. W.; King, D. Q.
1993-01-01
This paper describes an experimental study of the plasma plume properties of a 1 kW class hydrogen arcjet thruster and the comparison of measured temperature and velocity field to model predictions. The experiments are based on laser-induced fluorescence excitation of the Balmer-alpha transition. The model is based on a single-fluid magnetohydrodynamic description of the flow originally developed to predict arcjet thruster performance. Excellent agreement between model predictions and experimental velocity is found, despite the complex nature of the flow. Measured and predicted exit plane temperatures are in disagreement by as much as 2000K over a range of operating conditions. The possible sources for this discrepancy are discussed.
A hybrid phenomenological model for ferroelectroelastic ceramics. Part II: Morphotropic PZT ceramics
NASA Astrophysics Data System (ADS)
Stark, S.; Neumeister, P.; Balke, H.
2016-10-01
In this part II of a two part series, the rate-independent hybrid phenomenological constitutive model introduced in part I is modified to account for the material behavior of morphotropic lead zirconate titanate ceramics (PZT ceramics). The modifications are based on a discussion of the available literature results regarding the micro-structure of these materials. In particular, a monoclinic phase and a highly simplified representation of the hierarchical structure of micro-domains and nano-domains observed experimentally are incorporated into the model. It is shown that experimental data for the commercially available morphotropic PZT material PIC151 (PI Ceramic GmbH, Lederhose, Germany) can be reproduced and predicted based on the modified hybrid model.
Artificial intelligence in process control: Knowledge base for the shuttle ECS model
NASA Technical Reports Server (NTRS)
Stiffler, A. Kent
1989-01-01
The general operation of KATE, an artificial intelligence controller, is outlined. A shuttle environmental control system (ECS) demonstration system for KATE is explained. The knowledge base model for this system is derived. An experimental test procedure is given to verify parameters in the model.
The Spiritual and Social Attitudes of Students towards Integrated Problem Based Learning Models
ERIC Educational Resources Information Center
Bachtiar, Suhaedir; Zubaidah, Siti; Corebima, Aloysius Duran; Indriwati, Sri Endah
2018-01-01
This research aimed to investigate the spiritual and social attitudes of students with different academic abilities towards four educational models: problem based learning (PBL); numbered heads together (NHT); integrated PBL and NHT; and multi-strategies model. This quasi-experimental investigation employed a pretest-posttest non-equivalent…
Mazaheri, Davood; Shojaosadati, Seyed Abbas; Zamir, Seyed Morteza; Mousavi, Seyyed Mohammad
2018-04-21
In this work, mathematical modeling of ethanol production in solid-state fermentation (SSF) has been done based on the variation in the dry weight of solid medium. This method was previously used for mathematical modeling of enzyme production; however, the model should be modified to predict the production of a volatile compound like ethanol. The experimental results of bioethanol production from the mixture of carob pods and wheat bran by Zymomonas mobilis in SSF were used for the model validation. Exponential and logistic kinetic models were used for modeling the growth of microorganism. In both cases, the model predictions matched well with the experimental results during the exponential growth phase, indicating the good ability of solid medium weight variation method for modeling a volatile product formation in solid-state fermentation. In addition, using logistic model, better predictions were obtained.
Using fuzzy rule-based knowledge model for optimum plating conditions search
NASA Astrophysics Data System (ADS)
Solovjev, D. S.; Solovjeva, I. A.; Litovka, Yu V.; Arzamastsev, A. A.; Glazkov, V. P.; L’vov, A. A.
2018-03-01
The paper discusses existing approaches to plating process modeling in order to decrease the distribution thickness of plating surface cover. However, these approaches do not take into account the experience, knowledge, and intuition of the decision-makers when searching the optimal conditions of electroplating technological process. The original approach to optimal conditions search for applying the electroplating coatings, which uses the rule-based model of knowledge and allows one to reduce the uneven product thickness distribution, is proposed. The block diagrams of a conventional control system of a galvanic process as well as the system based on the production model of knowledge are considered. It is shown that the fuzzy production model of knowledge in the control system makes it possible to obtain galvanic coatings of a given thickness unevenness with a high degree of adequacy to the experimental data. The described experimental results confirm the theoretical conclusions.
Figueroa-Torres, Gonzalo M; Pittman, Jon K; Theodoropoulos, Constantinos
2017-10-01
Microalgal starch and lipids, carbon-based storage molecules, are useful as potential biofuel feedstocks. In this work, cultivation strategies maximising starch and lipid formation were established by developing a multi-parameter kinetic model describing microalgal growth as well as starch and lipid formation, in conjunction with laboratory-scale experiments. Growth dynamics are driven by nitrogen-limited mixotrophic conditions, known to increase cellular starch and lipid contents whilst enhancing biomass growth. Model parameters were computed by fitting model outputs to a range of experimental datasets from batch cultures of Chlamydomonas reinhardtii. Predictive capabilities of the model were established against different experimental data. The model was subsequently used to compute optimal nutrient-based cultivation strategies in terms of initial nitrogen and carbon concentrations. Model-based optimal strategies yielded a significant increase of 261% for starch (0.065gCL -1 ) and 66% for lipid (0.08gCL -1 ) production compared to base-case conditions (0.018gCL -1 starch, 0.048gCL -1 lipids). Copyright © 2017 Elsevier Ltd. All rights reserved.
Gamma Prime Precipitate Evolution During Aging of a Model Nickel-Based Superalloy
NASA Astrophysics Data System (ADS)
Goodfellow, A. J.; Galindo-Nava, E. I.; Christofidou, K. A.; Jones, N. G.; Martin, T.; Bagot, P. A. J.; Boyer, C. D.; Hardy, M. C.; Stone, H. J.
2018-03-01
The microstructural stability of nickel-based superalloys is critical for maintaining alloy performance during service in gas turbine engines. In this study, the precipitate evolution in a model polycrystalline Ni-based superalloy during aging to 1000 hours has been studied via transmission electron microscopy, atom probe tomography, and neutron diffraction. Variations in phase composition and precipitate morphology, size, and volume fraction were observed during aging, while the constrained lattice misfit remained constant at approximately zero. The experimental composition of the γ matrix phase was consistent with thermodynamic equilibrium predictions, while significant differences were identified between the experimental and predicted results from the γ' phase. These results have implications for the evolution of mechanical properties in service and their prediction using modeling methods.
NASA Astrophysics Data System (ADS)
Song, Di; Kang, Guozheng; Kan, Qianhua; Yu, Chao; Zhang, Chuanzeng
2015-08-01
Based on the experimental observations for the uniaxial low-cycle stress fatigue failure of super-elastic NiTi shape memory alloy microtubes (Song et al 2015 Smart Mater. Struct. 24 075004) and a new definition of damage variable corresponding to the variation of accumulated dissipation energy, a phenomenological damage model is proposed to describe the damage evolution of the NiTi microtubes during cyclic loading. Then, with a failure criterion of Dc = 1, the fatigue lives of the NiTi microtubes are predicted by the damage-based model, the predicted lives are in good agreement with the experimental ones, and all of the points are located within an error band of 1.5 times.
USDA-ARS?s Scientific Manuscript database
For the purpose of developing an improved experimental model for studies of foot-and-mouth disease virus (FMDV) infection in cattle, three different experimental systems based on natural or simulated-natural virus exposure were compared under standardized experimental conditions. Antemortem infecti...
ERIC Educational Resources Information Center
Cepni, Salih; Sahin, Cigdem; Ipek, Hava
2010-01-01
The purpose of this study was to test the influences of prepared instructional material based on the 5E instructional model combined with CCT, CC, animations, worksheets and POE on conceptual changes about floating and sinking concepts. The experimental group was taught with teaching material based on the 5E instructional model enriched with…
Visual Literacy and the Integration of Parametric Modeling in the Problem-Based Curriculum
ERIC Educational Resources Information Center
Assenmacher, Matthew Benedict
2013-01-01
This quasi-experimental study investigated the application of visual literacy skills in the form of parametric modeling software in relation to traditional forms of sketching. The study included two groups of high school technical design students. The control and experimental groups involved in the study consisted of two randomly selected groups…
Chudasama, Vaishali L.; Ovacik, Meric A.; Abernethy, Darrell R.
2015-01-01
Systems models of biological networks show promise for informing drug target selection/qualification, identifying lead compounds and factors regulating disease progression, rationalizing combinatorial regimens, and explaining sources of intersubject variability and adverse drug reactions. However, most models of biological systems are qualitative and are not easily coupled with dynamical models of drug exposure-response relationships. In this proof-of-concept study, logic-based modeling of signal transduction pathways in U266 multiple myeloma (MM) cells is used to guide the development of a simple dynamical model linking bortezomib exposure to cellular outcomes. Bortezomib is a commonly used first-line agent in MM treatment; however, knowledge of the signal transduction pathways regulating bortezomib-mediated cell cytotoxicity is incomplete. A Boolean network model of 66 nodes was constructed that includes major survival and apoptotic pathways and was updated using responses to several chemical probes. Simulated responses to bortezomib were in good agreement with experimental data, and a reduction algorithm was used to identify key signaling proteins. Bortezomib-mediated apoptosis was not associated with suppression of nuclear factor κB (NFκB) protein inhibition in this cell line, which contradicts a major hypothesis of bortezomib pharmacodynamics. A pharmacodynamic model was developed that included three critical proteins (phospho-NFκB, BclxL, and cleaved poly (ADP ribose) polymerase). Model-fitted protein dynamics and cell proliferation profiles agreed with experimental data, and the model-predicted IC50 (3.5 nM) is comparable to the experimental value (1.5 nM). The cell-based pharmacodynamic model successfully links bortezomib exposure to MM cellular proliferation via protein dynamics, and this model may show utility in exploring bortezomib-based combination regimens. PMID:26163548
A System Computational Model of Implicit Emotional Learning
Puviani, Luca; Rama, Sidita
2016-01-01
Nowadays, the experimental study of emotional learning is commonly based on classical conditioning paradigms and models, which have been thoroughly investigated in the last century. Unluckily, models based on classical conditioning are unable to explain or predict important psychophysiological phenomena, such as the failure of the extinction of emotional responses in certain circumstances (for instance, those observed in evaluative conditioning, in post-traumatic stress disorders and in panic attacks). In this manuscript, starting from the experimental results available from the literature, a computational model of implicit emotional learning based both on prediction errors computation and on statistical inference is developed. The model quantitatively predicts (a) the occurrence of evaluative conditioning, (b) the dynamics and the resistance-to-extinction of the traumatic emotional responses, (c) the mathematical relation between classical conditioning and unconditioned stimulus revaluation. Moreover, we discuss how the derived computational model can lead to the development of new animal models for resistant-to-extinction emotional reactions and novel methodologies of emotions modulation. PMID:27378898
A System Computational Model of Implicit Emotional Learning.
Puviani, Luca; Rama, Sidita
2016-01-01
Nowadays, the experimental study of emotional learning is commonly based on classical conditioning paradigms and models, which have been thoroughly investigated in the last century. Unluckily, models based on classical conditioning are unable to explain or predict important psychophysiological phenomena, such as the failure of the extinction of emotional responses in certain circumstances (for instance, those observed in evaluative conditioning, in post-traumatic stress disorders and in panic attacks). In this manuscript, starting from the experimental results available from the literature, a computational model of implicit emotional learning based both on prediction errors computation and on statistical inference is developed. The model quantitatively predicts (a) the occurrence of evaluative conditioning, (b) the dynamics and the resistance-to-extinction of the traumatic emotional responses, (c) the mathematical relation between classical conditioning and unconditioned stimulus revaluation. Moreover, we discuss how the derived computational model can lead to the development of new animal models for resistant-to-extinction emotional reactions and novel methodologies of emotions modulation.
A physiologically based model for tramadol pharmacokinetics in horses.
Abbiati, Roberto Andrea; Cagnardi, Petra; Ravasio, Giuliano; Villa, Roberto; Manca, Davide
2017-09-21
This work proposes an application of a minimal complexity physiologically based pharmacokinetic model to predict tramadol concentration vs time profiles in horses. Tramadol is an opioid analgesic also used for veterinary treatments. Researchers and medical doctors can profit from the application of mathematical models as supporting tools to optimize the pharmacological treatment of animal species. The proposed model is based on physiology but adopts the minimal compartmental architecture necessary to describe the experimental data. The model features a system of ordinary differential equations, where most of the model parameters are either assigned or individualized for a given horse, using literature data and correlations. Conversely, residual parameters, whose value is unknown, are regressed exploiting experimental data. The model proved capable of simulating pharmacokinetic profiles with accuracy. In addition, it provides further insights on un-observable tramadol data, as for instance tramadol concentration in the liver or hepatic metabolism and renal excretion extent. Copyright © 2017 Elsevier Ltd. All rights reserved.
ERIC Educational Resources Information Center
Soulios, Ioannis; Psillos, Dimitris
2016-01-01
In this study we present the structure and implementation of a model-based inquiry teaching-learning sequence (TLS) integrating expressive, experimental and exploratory modelling pedagogies in a cyclic manner, with the aim of enhancing primary education student teachers' epistemological beliefs about the aspects, nature, purpose and change of…
ERIC Educational Resources Information Center
Blank, Rolf K.; Smithson, John; Porter, Andrew; Nunnaley, Diana; Osthoff, Eric
2006-01-01
The instructional improvement model Data on Enacted Curriculum was tested with an experimental design using randomized place-based trials. The improvement model is based on using data on instructional practices and achievement to guide professional development and decisions to refocus on instruction. The model was tested in 50 U.S. middle schools…
NASA Astrophysics Data System (ADS)
Wang, Zuo-Cai; Xin, Yu; Ren, Wei-Xin
2016-08-01
This paper proposes a new nonlinear joint model updating method for shear type structures based on the instantaneous characteristics of the decomposed structural dynamic responses. To obtain an accurate representation of a nonlinear system's dynamics, the nonlinear joint model is described as the nonlinear spring element with bilinear stiffness. The instantaneous frequencies and amplitudes of the decomposed mono-component are first extracted by the analytical mode decomposition (AMD) method. Then, an objective function based on the residuals of the instantaneous frequencies and amplitudes between the experimental structure and the nonlinear model is created for the nonlinear joint model updating. The optimal values of the nonlinear joint model parameters are obtained by minimizing the objective function using the simulated annealing global optimization method. To validate the effectiveness of the proposed method, a single-story shear type structure subjected to earthquake and harmonic excitations is simulated as a numerical example. Then, a beam structure with multiple local nonlinear elements subjected to earthquake excitation is also simulated. The nonlinear beam structure is updated based on the global and local model using the proposed method. The results show that the proposed local nonlinear model updating method is more effective for structures with multiple local nonlinear elements. Finally, the proposed method is verified by the shake table test of a real high voltage switch structure. The accuracy of the proposed method is quantified both in numerical and experimental applications using the defined error indices. Both the numerical and experimental results have shown that the proposed method can effectively update the nonlinear joint model.
Model-based metabolism design: constraints for kinetic and stoichiometric models
Stalidzans, Egils; Seiman, Andrus; Peebo, Karl; Komasilovs, Vitalijs; Pentjuss, Agris
2018-01-01
The implementation of model-based designs in metabolic engineering and synthetic biology may fail. One of the reasons for this failure is that only a part of the real-world complexity is included in models. Still, some knowledge can be simplified and taken into account in the form of optimization constraints to improve the feasibility of model-based designs of metabolic pathways in organisms. Some constraints (mass balance, energy balance, and steady-state assumption) serve as a basis for many modelling approaches. There are others (total enzyme activity constraint and homeostatic constraint) proposed decades ago, but which are frequently ignored in design development. Several new approaches of cellular analysis have made possible the application of constraints like cell size, surface, and resource balance. Constraints for kinetic and stoichiometric models are grouped according to their applicability preconditions in (1) general constraints, (2) organism-level constraints, and (3) experiment-level constraints. General constraints are universal and are applicable for any system. Organism-level constraints are applicable for biological systems and usually are organism-specific, but these constraints can be applied without information about experimental conditions. To apply experimental-level constraints, peculiarities of the organism and the experimental set-up have to be taken into account to calculate the values of constraints. The limitations of applicability of particular constraints for kinetic and stoichiometric models are addressed. PMID:29472367
PSO-based PID Speed Control of Traveling Wave Ultrasonic Motor under Temperature Disturbance
NASA Astrophysics Data System (ADS)
Arifin Mat Piah, Kamal; Yusoff, Wan Azhar Wan; Azmi, Nur Iffah Mohamed; Romlay, Fadhlur Rahman Mohd
2018-03-01
Traveling wave ultrasonic motors (TWUSMs) have a time varying dynamics characteristics. Temperature rise in TWUSMs remains a problem particularly in sustaining optimum speed performance. In this study, a PID controller is used to control the speed of TWUSM under temperature disturbance. Prior to developing the controller, a linear approximation model which relates the speed to the temperature is developed based on the experimental data. Two tuning methods are used to determine PID parameters: conventional Ziegler-Nichols(ZN) and particle swarm optimization (PSO). The comparison of speed control performance between PSO-PID and ZN-PID is presented. Modelling, simulation and experimental work is carried out utilizing Fukoku-Shinsei USR60 as the chosen TWUSM. The results of the analyses and experimental work reveal that PID tuning using PSO-based optimization has the advantage over the conventional Ziegler-Nichols method.
NASA Astrophysics Data System (ADS)
Brown, Alexander; Eviston, Connor
2017-02-01
Multiple FEM models of complex eddy current coil geometries were created and validated to calculate the change of impedance due to the presence of a notch. Capable realistic simulations of eddy current inspections are required for model assisted probability of detection (MAPOD) studies, inversion algorithms, experimental verification, and tailored probe design for NDE applications. An FEM solver was chosen to model complex real world situations including varying probe dimensions and orientations along with complex probe geometries. This will also enable creation of a probe model library database with variable parameters. Verification and validation was performed using other commercially available eddy current modeling software as well as experimentally collected benchmark data. Data analysis and comparison showed that the created models were able to correctly model the probe and conductor interactions and accurately calculate the change in impedance of several experimental scenarios with acceptable error. The promising results of the models enabled the start of an eddy current probe model library to give experimenters easy access to powerful parameter based eddy current models for alternate project applications.
Designing novel cellulase systems through agent-based modeling and global sensitivity analysis.
Apte, Advait A; Senger, Ryan S; Fong, Stephen S
2014-01-01
Experimental techniques allow engineering of biological systems to modify functionality; however, there still remains a need to develop tools to prioritize targets for modification. In this study, agent-based modeling (ABM) was used to build stochastic models of complexed and non-complexed cellulose hydrolysis, including enzymatic mechanisms for endoglucanase, exoglucanase, and β-glucosidase activity. Modeling results were consistent with experimental observations of higher efficiency in complexed systems than non-complexed systems and established relationships between specific cellulolytic mechanisms and overall efficiency. Global sensitivity analysis (GSA) of model results identified key parameters for improving overall cellulose hydrolysis efficiency including: (1) the cellulase half-life, (2) the exoglucanase activity, and (3) the cellulase composition. Overall, the following parameters were found to significantly influence cellulose consumption in a consolidated bioprocess (CBP): (1) the glucose uptake rate of the culture, (2) the bacterial cell concentration, and (3) the nature of the cellulase enzyme system (complexed or non-complexed). Broadly, these results demonstrate the utility of combining modeling and sensitivity analysis to identify key parameters and/or targets for experimental improvement.
Designing novel cellulase systems through agent-based modeling and global sensitivity analysis
Apte, Advait A; Senger, Ryan S; Fong, Stephen S
2014-01-01
Experimental techniques allow engineering of biological systems to modify functionality; however, there still remains a need to develop tools to prioritize targets for modification. In this study, agent-based modeling (ABM) was used to build stochastic models of complexed and non-complexed cellulose hydrolysis, including enzymatic mechanisms for endoglucanase, exoglucanase, and β-glucosidase activity. Modeling results were consistent with experimental observations of higher efficiency in complexed systems than non-complexed systems and established relationships between specific cellulolytic mechanisms and overall efficiency. Global sensitivity analysis (GSA) of model results identified key parameters for improving overall cellulose hydrolysis efficiency including: (1) the cellulase half-life, (2) the exoglucanase activity, and (3) the cellulase composition. Overall, the following parameters were found to significantly influence cellulose consumption in a consolidated bioprocess (CBP): (1) the glucose uptake rate of the culture, (2) the bacterial cell concentration, and (3) the nature of the cellulase enzyme system (complexed or non-complexed). Broadly, these results demonstrate the utility of combining modeling and sensitivity analysis to identify key parameters and/or targets for experimental improvement. PMID:24830736
Cunningham, J C; Sinka, I C; Zavaliangos, A
2004-08-01
In this first of two articles on the modeling of tablet compaction, the experimental inputs related to the constitutive model of the powder and the powder/tooling friction are determined. The continuum-based analysis of tableting makes use of an elasto-plastic model, which incorporates the elements of yield, plastic flow potential, and hardening, to describe the mechanical behavior of microcrystalline cellulose over the range of densities experienced during tableting. Specifically, a modified Drucker-Prager/cap plasticity model, which includes material parameters such as cohesion, internal friction, and hydrostatic yield pressure that evolve with the internal state variable relative density, was applied. Linear elasticity is assumed with the elastic parameters, Young's modulus, and Poisson's ratio dependent on the relative density. The calibration techniques were developed based on a series of simple mechanical tests including diametrical compression, simple compression, and die compaction using an instrumented die. The friction behavior is measured using an instrumented die and the experimental data are analyzed using the method of differential slices. The constitutive model and frictional properties are essential experimental inputs to the finite element-based model described in the companion article. Copyright 2004 Wiley-Liss, Inc. and the American Pharmacists Association J Pharm Sci 93:2022-2039, 2004
NASA Astrophysics Data System (ADS)
Pelamatti, Alice; Goiffon, Vincent; Chabane, Aziouz; Magnan, Pierre; Virmontois, Cédric; Saint-Pé, Olivier; de Boisanger, Michel Breart
2016-11-01
The charge transfer time represents the bottleneck in terms of temporal resolution in Pinned Photodiode (PPD) CMOS image sensors. This work focuses on the modeling and estimation of this key parameter. A simple numerical model of charge transfer in PPDs is presented. The model is based on a Montecarlo simulation and takes into account both charge diffusion in the PPD and the effect of potential obstacles along the charge transfer path. This work also presents a new experimental approach for the estimation of the charge transfer time, called pulsed Storage Gate (SG) method. This method, which allows reproduction of a ;worst-case; transfer condition, is based on dedicated SG pixel structures and is particularly suitable to compare transfer efficiency performances for different pixel geometries.
Dynamic soft tissue deformation estimation based on energy analysis
NASA Astrophysics Data System (ADS)
Gao, Dedong; Lei, Yong; Yao, Bin
2016-10-01
The needle placement accuracy of millimeters is required in many needle-based surgeries. The tissue deformation, especially that occurring on the surface of organ tissue, affects the needle-targeting accuracy of both manual and robotic needle insertions. It is necessary to understand the mechanism of tissue deformation during needle insertion into soft tissue. In this paper, soft tissue surface deformation is investigated on the basis of continuum mechanics, where a geometry model is presented to quantitatively approximate the volume of tissue deformation. The energy-based method is presented to the dynamic process of needle insertion into soft tissue based on continuum mechanics, and the volume of the cone is exploited to quantitatively approximate the deformation on the surface of soft tissue. The external work is converted into potential, kinetic, dissipated, and strain energies during the dynamic rigid needle-tissue interactive process. The needle insertion experimental setup, consisting of a linear actuator, force sensor, needle, tissue container, and a light, is constructed while an image-based method for measuring the depth and radius of the soft tissue surface deformations is introduced to obtain the experimental data. The relationship between the changed volume of tissue deformation and the insertion parameters is created based on the law of conservation of energy, with the volume of tissue deformation having been obtained using image-based measurements. The experiments are performed on phantom specimens, and an energy-based analytical fitted model is presented to estimate the volume of tissue deformation. The experimental results show that the energy-based analytical fitted model can predict the volume of soft tissue deformation, and the root mean squared errors of the fitting model and experimental data are 0.61 and 0.25 at the velocities 2.50 mm/s and 5.00 mm/s. The estimating parameters of the soft tissue surface deformations are proven to be useful for compensating the needle-targeting error in the rigid needle insertion procedure, especially for percutaneous needle insertion into organs.
An individual-based model of zebrafish population dynamics accounting for energy dynamics.
Beaudouin, Rémy; Goussen, Benoit; Piccini, Benjamin; Augustine, Starrlight; Devillers, James; Brion, François; Péry, Alexandre R R
2015-01-01
Developing population dynamics models for zebrafish is crucial in order to extrapolate from toxicity data measured at the organism level to biological levels relevant to support and enhance ecological risk assessment. To achieve this, a dynamic energy budget for individual zebrafish (DEB model) was coupled to an individual based model of zebrafish population dynamics (IBM model). Next, we fitted the DEB model to new experimental data on zebrafish growth and reproduction thus improving existing models. We further analysed the DEB-model and DEB-IBM using a sensitivity analysis. Finally, the predictions of the DEB-IBM were compared to existing observations on natural zebrafish populations and the predicted population dynamics are realistic. While our zebrafish DEB-IBM model can still be improved by acquiring new experimental data on the most uncertain processes (e.g. survival or feeding), it can already serve to predict the impact of compounds at the population level.
An Individual-Based Model of Zebrafish Population Dynamics Accounting for Energy Dynamics
Beaudouin, Rémy; Goussen, Benoit; Piccini, Benjamin; Augustine, Starrlight; Devillers, James; Brion, François; Péry, Alexandre R. R.
2015-01-01
Developing population dynamics models for zebrafish is crucial in order to extrapolate from toxicity data measured at the organism level to biological levels relevant to support and enhance ecological risk assessment. To achieve this, a dynamic energy budget for individual zebrafish (DEB model) was coupled to an individual based model of zebrafish population dynamics (IBM model). Next, we fitted the DEB model to new experimental data on zebrafish growth and reproduction thus improving existing models. We further analysed the DEB-model and DEB-IBM using a sensitivity analysis. Finally, the predictions of the DEB-IBM were compared to existing observations on natural zebrafish populations and the predicted population dynamics are realistic. While our zebrafish DEB-IBM model can still be improved by acquiring new experimental data on the most uncertain processes (e.g. survival or feeding), it can already serve to predict the impact of compounds at the population level. PMID:25938409
GROMOS polarizable charge-on-spring models for liquid urea: COS/U and COS/U2
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lin, Zhixiong; Bachmann, Stephan J.; Gunsteren, Wilfred F. van, E-mail: wfvgn@igc.phys.chem.ethz.ch
2015-03-07
Two one-site polarizable urea models, COS/U and COS/U2, based on the charge-on-spring model are proposed. The models are parametrized against thermodynamic properties of urea-water mixtures in combination with the polarizable COS/G2 and COS/D2 models for liquid water, respectively, and have the same functional form of the inter-atomic interaction function and are based on the same parameter calibration procedure and type of experimental data as used to develop the GROMOS biomolecular force field. Thermodynamic, dielectric, and dynamic properties of urea-water mixtures simulated using the polarizable models are closer to experimental data than using the non-polarizable models. The COS/U and COS/U2 modelsmore » may be used in biomolecular simulations of protein denaturation.« less
PREdator: a python based GUI for data analysis, evaluation and fitting
2014-01-01
The analysis of a series of experimental data is an essential procedure in virtually every field of research. The information contained in the data is extracted by fitting the experimental data to a mathematical model. The type of the mathematical model (linear, exponential, logarithmic, etc.) reflects the physical laws that underlie the experimental data. Here, we aim to provide a readily accessible, user-friendly python script for data analysis, evaluation and fitting. PREdator is presented at the example of NMR paramagnetic relaxation enhancement analysis.
1981-08-01
electro - optic effect is investigated both theoretically and experimentally. The theoretical approach is based upon W.A. Harrison’s ’Bond-Orbital Model’. The separate electronic and lattice contributions to the second-order, electro - optic susceptibility are examined within the context of this model and formulae which can accommodate any crystal structure are presented. In addition, a method for estimating the lattice response to a low frequency (dc) electric field is outlined. Finally, experimental measurements of the electro -
NASA Technical Reports Server (NTRS)
Stankovic, Ana V.
2003-01-01
Professor Stankovic will be developing and refining Simulink based models of the PM alternator and comparing the simulation results with experimental measurements taken from the unit. Her first task is to validate the models using the experimental data. Her next task is to develop alternative control techniques for the application of the Brayton Cycle PM Alternator in a nuclear electric propulsion vehicle. The control techniques will be first simulated using the validated models then tried experimentally with hardware available at NASA. Testing and simulation of a 2KW PM synchronous generator with diode bridge output is described. The parameters of a synchronous PM generator have been measured and used in simulation. Test procedures have been developed to verify the PM generator model with diode bridge output. Experimental and simulation results are in excellent agreement.
Comparison of existing models to simulate anaerobic digestion of lipid-rich waste.
Béline, F; Rodriguez-Mendez, R; Girault, R; Bihan, Y Le; Lessard, P
2017-02-01
Models for anaerobic digestion of lipid-rich waste taking inhibition into account were reviewed and, if necessary, adjusted to the ADM1 model framework in order to compare them. Experimental data from anaerobic digestion of slaughterhouse waste at an organic loading rate (OLR) ranging from 0.3 to 1.9kgVSm -3 d -1 were used to compare and evaluate models. Experimental data obtained at low OLRs were accurately modeled whatever the model thereby validating the stoichiometric parameters used and influent fractionation. However, at higher OLRs, although inhibition parameters were optimized to reduce differences between experimental and simulated data, no model was able to accurately simulate accumulation of substrates and intermediates, mainly due to the wrong simulation of pH. A simulation using pH based on experimental data showed that acetogenesis and methanogenesis were the most sensitive steps to LCFA inhibition and enabled identification of the inhibition parameters of both steps. Copyright © 2016 Elsevier Ltd. All rights reserved.
PHYSIOLOCIGALLY BASED PHARMACOKINETIC (PBPK) MODELING AND MODE OF ACTION IN DOSE-RESPONSE ASSESSMENT
PHYSIOLOGICALLY BASED PHARMACOKINETIC (PBPK) MODELING AND MODE OF ACTION IN DOSE-RESPONSE ASSESSMENT. Barton HA. Experimental Toxicology Division, National Health and Environmental Effects Laboratory, ORD, U.S. EPA
Dose-response analysis requires quantitatively linking infor...
An (almost) solvable model for bacterial pattern formation
NASA Astrophysics Data System (ADS)
Grammaticos, B.; Badoual, M.; Aubert, M.
2007-10-01
We present a simple model for the description of ring-like concentric structures in bacterial colonies. We model the differences between Bacillus subtilis and Proteus mirabilis colonies by using a different dependence of the duration of the consolidation phase on the concentration of agar. We compare our results to experimental data from these two bacterial species colonies and obtain a good agreement. Based on this analysis, we formulate a hypothesis on the connection of the diffusion constant that appears in the model to the experimental agar concentration.
Inverse problems in the design, modeling and testing of engineering systems
NASA Technical Reports Server (NTRS)
Alifanov, Oleg M.
1991-01-01
Formulations, classification, areas of application, and approaches to solving different inverse problems are considered for the design of structures, modeling, and experimental data processing. Problems in the practical implementation of theoretical-experimental methods based on solving inverse problems are analyzed in order to identify mathematical models of physical processes, aid in input data preparation for design parameter optimization, help in design parameter optimization itself, and to model experiments, large-scale tests, and real tests of engineering systems.
Bódalo, A; Gómez, J L.; Gómez, E; Bastida, J; Máximo, M F.; Montiel, M C.
2001-03-08
In this paper the possibility of continuous resolution of DL-phenylalanine, catalyzed by L-aminoacylase in a ultrafiltration membrane reactor (UFMR) is presented. A simple design model, based on previous kinetic studies, has been demonstrated to be capable of describing the behavior of the experimental system. The model has been used to determine the optimal experimental conditions to carry out the asymmetrical hydrolysis of N-acetyl-DL-phenylalanine.
Prediction of turning stability using receptance coupling
NASA Astrophysics Data System (ADS)
Jasiewicz, Marcin; Powałka, Bartosz
2018-01-01
This paper presents an issue of machining stability prediction of dynamic "lathe - workpiece" system evaluated using receptance coupling method. Dynamic properties of the lathe components (the spindle and the tailstock) are assumed to be constant and can be determined experimentally based on the results of the impact test. Hence, the variable of the system "machine tool - holder - workpiece" is the machined part, which can be easily modelled analytically. The method of receptance coupling enables a synthesis of experimental (spindle, tailstock) and analytical (machined part) models, so impact testing of the entire system becomes unnecessary. The paper presents methodology of analytical and experimental models synthesis, evaluation of the stability lobes and experimental validation procedure involving both the determination of the dynamic properties of the system and cutting tests. In the summary the experimental verification results would be presented and discussed.
NASA Astrophysics Data System (ADS)
Norinder, Ulf
1990-12-01
An experimental design based 3-D QSAR analysis using a combination of principal component and PLS analysis is presented and applied to human corticosteroid-binding globulin complexes. The predictive capability of the created model is good. The technique can also be used as guidance when selecting new compounds to be investigated.
ERIC Educational Resources Information Center
Toker, Betül; Avci, Rasit
2015-01-01
This study examined the effectiveness of a cognitive-behavioral theory (CBT) psycho-educational group program on the academic procrastination behaviors of university students and the persistence of any training effect. This was a quasi-experimental research based on an experimental and control group pretest, posttest, and followup test model.…
Role of hydrogen in volatile behaviour of defects in SiO2-based electronic devices
NASA Astrophysics Data System (ADS)
Wimmer, Yannick; El-Sayed, Al-Moatasem; Gös, Wolfgang; Grasser, Tibor; Shluger, Alexander L.
2016-06-01
Charge capture and emission by point defects in gate oxides of metal-oxide-semiconductor field-effect transistors (MOSFETs) strongly affect reliability and performance of electronic devices. Recent advances in experimental techniques used for probing defect properties have led to new insights into their characteristics. In particular, these experimental data show a repeated dis- and reappearance (the so-called volatility) of the defect-related signals. We use multiscale modelling to explain the charge capture and emission as well as defect volatility in amorphous SiO2 gate dielectrics. We first briefly discuss the recent experimental results and use a multiphonon charge capture model to describe the charge-trapping behaviour of defects in silicon-based MOSFETs. We then link this model to ab initio calculations that investigate the three most promising defect candidates. Statistical distributions of defect characteristics obtained from ab initio calculations in amorphous SiO2 are compared with the experimentally measured statistical properties of charge traps. This allows us to suggest an atomistic mechanism to explain the experimentally observed volatile behaviour of defects. We conclude that the hydroxyl-E' centre is a promising candidate to explain all the observed features, including defect volatility.
Design and experimental evaluation of robust controllers for a two-wheeled robot
NASA Astrophysics Data System (ADS)
Kralev, J.; Slavov, Ts.; Petkov, P.
2016-11-01
The paper presents the design and experimental evaluation of two alternative μ-controllers for robust vertical stabilisation of a two-wheeled self-balancing robot. The controllers design is based on models derived by identification from closed-loop experimental data. In the first design, a signal-based uncertainty representation obtained directly from the identification procedure is used, which leads to a controller of order 29. In the second design the signal uncertainty is approximated by an input multiplicative uncertainty, which leads to a controller of order 50, subsequently reduced to 30. The performance of the two μ-controllers is compared with the performance of a conventional linear quadratic controller with 17th-order Kalman filter. A proportional-integral controller of the rotational motion around the vertical axis is implemented as well. The control code is generated using Simulink® controller models and is embedded in a digital signal processor. Results from the simulation of the closed-loop system as well as experimental results obtained during the real-time implementation of the designed controllers are given. The theoretical investigation and experimental results confirm that the closed-loop system achieves robust performance in respect to the uncertainties related to the identified robot model.
Wilmoth, Jared L.; Doak, Peter W.; Timm, Andrea; ...
2018-02-06
The factors leading to changes in the organization of microbial assemblages at fine spatial scales are not well characterized or understood. However, they are expected to guide the succession of community development and function toward specific outcomes that could impact human health and the environment. In this study, we put forward a combined experimental and agent-based modeling framework and use it to interpret unique spatial organization patterns of H1-Type VI secretion system (T6SS) mutants of P. aeruginosa under spatial confinement. We find that key parameters, such as T6SS-mediated cell contact and lysis, spatial localization, relative species abundance, cell density andmore » local concentrations of growth substrates and metabolites are influenced by spatial confinement. The model, written in the accessible programming language NetLogo, can be adapted to a variety of biological systems of interest and used to simulate experiments across a broad parameter space. It was implemented and run in a high-throughput mode by deploying it across multiple CPUs, with each simulation representing an individual well within a high-throughput microwell array experimental platform. The microfluidics and agent-based modeling framework we present in this paper provides an effective means by which to connect experimental studies in microbiology to model development. The work demonstrates progress in coupling experimental results to simulation while also highlighting potential sources of discrepancies between real-world experiments and idealized models.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wilmoth, Jared L.; Doak, Peter W.; Timm, Andrea
The factors leading to changes in the organization of microbial assemblages at fine spatial scales are not well characterized or understood. However, they are expected to guide the succession of community development and function toward specific outcomes that could impact human health and the environment. In this study, we put forward a combined experimental and agent-based modeling framework and use it to interpret unique spatial organization patterns of H1-Type VI secretion system (T6SS) mutants of P. aeruginosa under spatial confinement. We find that key parameters, such as T6SS-mediated cell contact and lysis, spatial localization, relative species abundance, cell density andmore » local concentrations of growth substrates and metabolites are influenced by spatial confinement. The model, written in the accessible programming language NetLogo, can be adapted to a variety of biological systems of interest and used to simulate experiments across a broad parameter space. It was implemented and run in a high-throughput mode by deploying it across multiple CPUs, with each simulation representing an individual well within a high-throughput microwell array experimental platform. The microfluidics and agent-based modeling framework we present in this paper provides an effective means by which to connect experimental studies in microbiology to model development. The work demonstrates progress in coupling experimental results to simulation while also highlighting potential sources of discrepancies between real-world experiments and idealized models.« less
Exploring the Argumentation Pattern in Modeling-Based Learning about Apparent Motion of Mars
ERIC Educational Resources Information Center
Park, Su-Kyeong
2016-01-01
This study proposed an analytic framework for coding students' dialogic argumentation and investigated the characteristics of the small-group argumentation pattern observed in modeling-based learning. The participants were 122 second grade high school students in South Korea divided into an experimental and a comparison group. Modeling-based…
NASA Technical Reports Server (NTRS)
Yeager, W. T., Jr.; Hamouda, M. N. H.; Mantay, W. R.
1983-01-01
A research effort of analysis and testing was conducted to investigate the ground resonance phenomenon of a soft in-plane hingeless rotor. Experimental data were obtained using a 9 ft. (2.74 m) diameter model rotor in hover and forward flight. Eight model rotor configurations were investigated. Configuration parameters included pitch flap coupling, blade sweep and droop, and precone of the blade feathering axis. An analysis based on a comprehensive analytical model of rotorcraft aerodynamics and dynamics was used. The moving block was used to experimentally determine the regressing lead lag mode damping. Good agreement was obtained between the analysis and test. Both analysis and experiment indicated ground resonance instability in hover. An outline of the analysis, a description of the experimental model and procedures, and comparison of the analytical and experimental data are presented.
NASA Astrophysics Data System (ADS)
Song, Huixu; Shi, Zhaoyao; Chen, Hongfang; Sun, Yanqiang
2018-01-01
This paper presents a novel experimental approach and a simple model for verifying that spherical mirror of laser tracking system could lessen the effect of rotation errors of gimbal mount axes based on relative motion thinking. Enough material and evidence are provided to support that this simple model could replace complex optical system in laser tracking system. This experimental approach and model interchange the kinematic relationship between spherical mirror and gimbal mount axes in laser tracking system. Being fixed stably, gimbal mount axes' rotation error motions are replaced by spatial micro-displacements of spherical mirror. These motions are simulated by driving spherical mirror along the optical axis and vertical direction with the use of precision positioning platform. The effect on the laser ranging measurement accuracy of displacement caused by the rotation errors of gimbal mount axes could be recorded according to the outcome of laser interferometer. The experimental results show that laser ranging measurement error caused by the rotation errors is less than 0.1 μm if radial error motion and axial error motion are under 10 μm. The method based on relative motion thinking not only simplifies the experimental procedure but also achieves that spherical mirror owns the ability to reduce the effect of rotation errors of gimbal mount axes in laser tracking system.
NASA Technical Reports Server (NTRS)
Geng, Tao; Paxson, Daniel E.; Zheng, Fei; Kuznetsov, Andrey V.; Roberts, William L.
2008-01-01
Pulsed combustion is receiving renewed interest as a potential route to higher performance in air breathing propulsion systems. Pulsejets offer a simple experimental device with which to study unsteady combustion phenomena and validate simulations. Previous computational fluid dynamic (CFD) simulation work focused primarily on the pulsejet combustion and exhaust processes. This paper describes a new inlet sub-model which simulates the fluidic and mechanical operation of a valved pulsejet head. The governing equations for this sub-model are described. Sub-model validation is provided through comparisons of simulated and experimentally measured reed valve motion, and time averaged inlet mass flow rate. The updated pulsejet simulation, with the inlet sub-model implemented, is validated through comparison with experimentally measured combustion chamber pressure, inlet mass flow rate, operational frequency, and thrust. Additionally, the simulated pulsejet exhaust flowfield, which is dominated by a starting vortex ring, is compared with particle imaging velocimetry (PIV) measurements on the bases of velocity, vorticity, and vortex location. The results show good agreement between simulated and experimental data. The inlet sub-model is shown to be critical for the successful modeling of pulsejet operation. This sub-model correctly predicts both the inlet mass flow rate and its phase relationship with the combustion chamber pressure. As a result, the predicted pulsejet thrust agrees very well with experimental data.
ERIC Educational Resources Information Center
Arslan Buyruk, Arzu; Ogan Bekiroglu, Feral
2018-01-01
The focus of this study was to evaluate the impact of model-based inquiry on pre-service physics teachers' conceptual understanding of dynamics. Theoretical framework of this research was based on models-of-data theory. True-experimental design using quantitative and qualitative research methods was carried out for this research. Participants of…
Simulation of energy buildups in solid-state regenerative amplifiers for 2-μm emitting lasers
NASA Astrophysics Data System (ADS)
Springer, Ramon; Alexeev, Ilya; Heberle, Johannes; Pflaum, Christoph
2018-02-01
A numerical model for solid-state regenerative amplifiers is presented, which is able to precisely simulate the quantitative energy buildup of stretched femtosecond pulses over passed roundtrips in the cavity. In detail, this model is experimentally validated with a Ti:Sapphire regenerative amplifier. Additionally, the simulation of a Ho:YAG based regenerative amplifier is conducted and compared to experimental data from literature. Furthermore, a bifurcation study of the investigated Ho:YAG system is performed, which leads to the identification of stable and instable operation regimes. The presented numerical model exhibits a well agreement to the experimental results from the Ti:Sapphire regenerative amplifier. Also, the gained pulse energy from the Ho:YAG system could be approximated closely, while the mismatch is explained with the monochromatic calculation of pulse amplification. Since the model is applicable to other solid-state gain media, it allows for the efficient design of future amplification systems based on regenerative amplification.
An Integrated Finite Element-based Simulation Framework: From Hole Piercing to Hole Expansion
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hu, Xiaohua; Sun, Xin; Golovashchenko, Segey F.
An integrated finite element-based modeling framework is developed to predict the hole expansion ratio (HER) of AA6111-T4 sheet by considering the piercing-induced damages around the hole edge. Using damage models and parameters calibrated from previously reported tensile stretchability studies, the predicted HER correlates well with experimentally measured HER values for different hole piercing clearances. The hole piercing model shows burrs are not generated on the sheared surface for clearances less than 20%, which corresponds well with the experimental data on pierced holes cross-sections. Finite-element-calculated HER also is not especially sensitive to piercing clearances less than this value. However, as clearancesmore » increase to 30% and further to 40%, the HER values are predicted to be considerably smaller, also consistent with experimental measurements. Upon validation, the integrated modeling framework is used to examine the effects of different hole piercing and hole expansion conditions on the critical HERs for AA6111-T4.« less
NASA Astrophysics Data System (ADS)
Bieliński, Henryk
2016-09-01
The current paper presents the experimental validation of the generalized model of the two-phase thermosyphon loop. The generalized model is based on mass, momentum, and energy balances in the evaporators, rising tube, condensers and the falling tube. The theoretical analysis and the experimental data have been obtained for a new designed variant. The variant refers to a thermosyphon loop with both minichannels and conventional tubes. The thermosyphon loop consists of an evaporator on the lower vertical section and a condenser on the upper vertical section. The one-dimensional homogeneous and separated two-phase flow models were used in calculations. The latest minichannel heat transfer correlations available in literature were applied. A numerical analysis of the volumetric flow rate in the steady-state has been done. The experiment was conducted on a specially designed test apparatus. Ultrapure water was used as a working fluid. The results show that the theoretical predictions are in good agreement with the measured volumetric flow rate at steady-state.
Garitte, B.; Shao, H.; Wang, X. R.; ...
2017-01-09
Process understanding and parameter identification using numerical methods based on experimental findings are a key aspect of the international cooperative project DECOVALEX. Comparing the predictions from numerical models against experimental results increases confidence in the site selection and site evaluation process for a radioactive waste repository in deep geological formations. In the present phase of the project, DECOVALEX-2015, eight research teams have developed and applied models for simulating an in-situ heater experiment HE-E in the Opalinus Clay in the Mont Terri Rock Laboratory in Switzerland. The modelling task was divided into two study stages, related to prediction and interpretation ofmore » the experiment. A blind prediction of the HE-E experiment was performed based on calibrated parameter values for both the Opalinus Clay, that were based on the modelling of another in-situ experiment (HE-D), and modelling of laboratory column experiments on MX80 granular bentonite and a sand/bentonite mixture .. After publication of the experimental data, additional coupling functions were analysed and considered in the different models. Moreover, parameter values were varied to interpret the measured temperature, relative humidity and pore pressure evolution. The analysis of the predictive and interpretative results reveals the current state of understanding and predictability of coupled THM behaviours associated with geologic nuclear waste disposal in clay formations.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Garitte, B.; Shao, H.; Wang, X. R.
Process understanding and parameter identification using numerical methods based on experimental findings are a key aspect of the international cooperative project DECOVALEX. Comparing the predictions from numerical models against experimental results increases confidence in the site selection and site evaluation process for a radioactive waste repository in deep geological formations. In the present phase of the project, DECOVALEX-2015, eight research teams have developed and applied models for simulating an in-situ heater experiment HE-E in the Opalinus Clay in the Mont Terri Rock Laboratory in Switzerland. The modelling task was divided into two study stages, related to prediction and interpretation ofmore » the experiment. A blind prediction of the HE-E experiment was performed based on calibrated parameter values for both the Opalinus Clay, that were based on the modelling of another in-situ experiment (HE-D), and modelling of laboratory column experiments on MX80 granular bentonite and a sand/bentonite mixture .. After publication of the experimental data, additional coupling functions were analysed and considered in the different models. Moreover, parameter values were varied to interpret the measured temperature, relative humidity and pore pressure evolution. The analysis of the predictive and interpretative results reveals the current state of understanding and predictability of coupled THM behaviours associated with geologic nuclear waste disposal in clay formations.« less
Tissue Anisotropy Modeling Using Soft Composite Materials.
Chanda, Arnab; Callaway, Christian
2018-01-01
Soft tissues in general exhibit anisotropic mechanical behavior, which varies in three dimensions based on the location of the tissue in the body. In the past, there have been few attempts to numerically model tissue anisotropy using composite-based formulations (involving fibers embedded within a matrix material). However, so far, tissue anisotropy has not been modeled experimentally. In the current work, novel elastomer-based soft composite materials were developed in the form of experimental test coupons, to model the macroscopic anisotropy in tissue mechanical properties. A soft elastomer matrix was fabricated, and fibers made of a stiffer elastomer material were embedded within the matrix material to generate the test coupons. The coupons were tested on a mechanical testing machine, and the resulting stress-versus-stretch responses were studied. The fiber volume fraction (FVF), fiber spacing, and orientations were varied to estimate the changes in the mechanical responses. The mechanical behavior of the soft composites was characterized using hyperelastic material models such as Mooney-Rivlin's, Humphrey's, and Veronda-Westmann's model and also compared with the anisotropic mechanical behavior of the human skin, pelvic tissues, and brain tissues. This work lays the foundation for the experimental modelling of tissue anisotropy, which combined with microscopic studies on tissues can lead to refinements in the simulation of localized fiber distribution and orientations, and enable the development of biofidelic anisotropic tissue phantom materials for various tissue engineering and testing applications.
Tissue Anisotropy Modeling Using Soft Composite Materials
Callaway, Christian
2018-01-01
Soft tissues in general exhibit anisotropic mechanical behavior, which varies in three dimensions based on the location of the tissue in the body. In the past, there have been few attempts to numerically model tissue anisotropy using composite-based formulations (involving fibers embedded within a matrix material). However, so far, tissue anisotropy has not been modeled experimentally. In the current work, novel elastomer-based soft composite materials were developed in the form of experimental test coupons, to model the macroscopic anisotropy in tissue mechanical properties. A soft elastomer matrix was fabricated, and fibers made of a stiffer elastomer material were embedded within the matrix material to generate the test coupons. The coupons were tested on a mechanical testing machine, and the resulting stress-versus-stretch responses were studied. The fiber volume fraction (FVF), fiber spacing, and orientations were varied to estimate the changes in the mechanical responses. The mechanical behavior of the soft composites was characterized using hyperelastic material models such as Mooney-Rivlin's, Humphrey's, and Veronda-Westmann's model and also compared with the anisotropic mechanical behavior of the human skin, pelvic tissues, and brain tissues. This work lays the foundation for the experimental modelling of tissue anisotropy, which combined with microscopic studies on tissues can lead to refinements in the simulation of localized fiber distribution and orientations, and enable the development of biofidelic anisotropic tissue phantom materials for various tissue engineering and testing applications. PMID:29853996
Chan, Chung-Hung; Yusoff, Rozita; Ngoh, Gek-Cheng
2013-09-01
A modeling technique based on absorbed microwave energy was proposed to model microwave-assisted extraction (MAE) of antioxidant compounds from cocoa (Theobroma cacao L.) leaves. By adapting suitable extraction model at the basis of microwave energy absorbed during extraction, the model can be developed to predict extraction profile of MAE at various microwave irradiation power (100-600 W) and solvent loading (100-300 ml). Verification with experimental data confirmed that the prediction was accurate in capturing the extraction profile of MAE (R-square value greater than 0.87). Besides, the predicted yields from the model showed good agreement with the experimental results with less than 10% deviation observed. Furthermore, suitable extraction times to ensure high extraction yield at various MAE conditions can be estimated based on absorbed microwave energy. The estimation is feasible as more than 85% of active compounds can be extracted when compared with the conventional extraction technique. Copyright © 2013 Elsevier Ltd. All rights reserved.
An Approach to the Evaluation of Hypermedia.
ERIC Educational Resources Information Center
Knussen, Christina; And Others
1991-01-01
Discusses methods that may be applied to the evaluation of hypermedia, based on six models described by Lawton. Techniques described include observation, self-report measures, interviews, automated measures, psychometric tests, checklists and criterion-based techniques, process models, Experimentally Measuring Usability (EMU), and a naturalistic…
NASA Astrophysics Data System (ADS)
Golovanova, O. A.; Chikanova, E. S.; Fedoseev, V. B.
2018-05-01
The processes occurring in aqueous salt solutions have been investigated based on thermodynamic and experimental modeling. The self-organization in a drying drop of dehydrated liquids is analyzed using the fractal theory, due to which the quantitative characteristics of the crystallization processes in a small volume are obtained.
The fundamental processes for injection of CaCO3 and Ca(OH)2 for the removal of SO2 from combustion gases of coal-fired boilers are analyzed on the basis of experimental data and a comprehensive theoretical model. Sulfation data were obtained in a 30-kW isothermal gas-particle t...
Experimental confirmation of a PDE-based approach to design of feedback controls
NASA Technical Reports Server (NTRS)
Banks, H. T.; Smith, Ralph C.; Brown, D. E.; Silcox, R. J.; Metcalf, Vern L.
1995-01-01
Issues regarding the experimental implementation of partial differential equation based controllers are discussed in this work. While the motivating application involves the reduction of vibration levels for a circular plate through excitation of surface-mounted piezoceramic patches, the general techniques described here will extend to a variety of applications. The initial step is the development of a PDE model which accurately captures the physics of the underlying process. This model is then discretized to yield a vector-valued initial value problem. Optimal control theory is used to determine continuous-time voltages to the patches, and the approximations needed to facilitate discrete time implementation are addressed. Finally, experimental results demonstrating the control of both transient and steady state vibrations through these techniques are presented.
Mechanisms of carbon dimer formation in colliding laser-produced carbon plasmas
NASA Astrophysics Data System (ADS)
Sizyuk, Tatyana; Oliver, John; Diwakar, Prasoon K.
2017-07-01
It has been demonstrated that the hot stagnation region formed during the collision of laser-produced carbon plasmas is rich with carbon dimers which have been shown to be synthesized into large carbon macromolecules such as carbon fullerene onions and nanotubes. In this study, we developed and integrated experimental and multidimensional modeling techniques to access the temporal and spatial resolution of colliding plasma characteristics that elucidated the mechanism for early carbon dimer formation. Plume evolution imaging, monochromatic imaging, and optical emission spectroscopy of graphite-produced, carbon plasmas were performed. Experimental results were compared with the results of the 3D comprehensive modeling using our HEIGHTS simulation package. The results are explained based on a fundamental analysis of plasma evolution, colliding layer formation, stagnation, and expansion. The precise mechanisms of the plasma collision, plume propagation, and particle formation are discussed based on the experimental and modeling results.
Jinghao Li; John F. Hunt; Shaoqin Gong; Zhiyong Cai
2017-01-01
This paper presents an analysis of 3-dimensional engineered structural panels (3DESP) made from wood-fiber-based laminated paper composites. Since the existing models for calculating the mechanical behavior of core configurations within sandwich panels are very complex, a new simplified orthogonal model (SOM) using an equivalent element has been developed. This model...
ERIC Educational Resources Information Center
Fazio, C.; Guastella, I.; Tarantino, G.
2007-01-01
In this paper, we describe a pedagogical approach to elastic body movement based on measurements of the contact times between a metallic rod and small bodies colliding with it and on modelling of the experimental results by using a microcomputer-based laboratory and simulation tools. The experiments and modelling activities have been built in the…
Rathnayaka, C M; Karunasena, H C P; Senadeera, W; Gu, Y T
2018-03-14
Numerical modelling has gained popularity in many science and engineering streams due to the economic feasibility and advanced analytical features compared to conventional experimental and theoretical models. Food drying is one of the areas where numerical modelling is increasingly applied to improve drying process performance and product quality. This investigation applies a three dimensional (3-D) Smoothed Particle Hydrodynamics (SPH) and Coarse-Grained (CG) numerical approach to predict the morphological changes of different categories of food-plant cells such as apple, grape, potato and carrot during drying. To validate the model predictions, experimental findings from in-house experimental procedures (for apple) and sources of literature (for grape, potato and carrot) have been utilised. The subsequent comaprison indicate that the model predictions demonstrate a reasonable agreement with the experimental findings, both qualitatively and quantitatively. In this numerical model, a higher computational accuracy has been maintained by limiting the consistency error below 1% for all four cell types. The proposed meshfree-based approach is well-equipped to predict the morphological changes of plant cellular structure over a wide range of moisture contents (10% to 100% dry basis). Compared to the previous 2-D meshfree-based models developed for plant cell drying, the proposed model can draw more useful insights on the morphological behaviour due to the 3-D nature of the model. In addition, the proposed computational modelling approach has a high potential to be used as a comprehensive tool in many other tissue morphology related investigations.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Liu, Yongming; Oskay, Caglar
This report outlines the research activities that were carried out for the integrated experimental and simulation investigation of creep-fatigue damage mechanism and life prediction of Nickel-based alloy, Inconel 617 at high temperatures (950° and 850°). First, a novel experimental design using a hybrid control technique is proposed. The newly developed experimental technique can generate different combinations of creep and fatigue damage by changing the experimental design parameters. Next, detailed imaging analysis and statistical data analysis are performed to quantify the failure mechanisms of the creep fatigue of alloy 617 at high temperatures. It is observed that the creep damage ismore » directly associated with the internal voids at the grain boundaries and the fatigue damage is directly related to the surface cracking. It is also observed that the classical time fraction approach does not has a good correlation with the experimental observed damage features. An effective time fraction parameter is seen to have an excellent correlation with the material microstructural damage. Thus, a new empirical damage interaction diagram is proposed based on the experimental observations. Following this, a macro level viscoplastic model coupled with damage is developed to simulate the stress/strain response under creep fatigue loadings. A damage rate function based on the hysteresis energy and creep energy is proposed to capture the softening behavior of the material and a good correlation with life prediction and material hysteresis behavior is observed. The simulation work is extended to include the microstructural heterogeneity. A crystal plasticity finite element model considering isothermal and large deformation conditions at the microstructural scale has been developed for fatigue, creep-fatigue as well as creep deformation and rupture at high temperature. The model considers collective dislocation glide and climb of the grains and progressive damage accumulation of the grain boundaries. The glide model incorporates a slip resistance evolution model that characterizes the solute-drag creep effects and can capture well the stress-strain and stress time response of fatigue and creep-fatigue tests at various strain ranges and hold times. In order to accurately capture the creep strains that accumulate particularly at relatively low stress levels, a dislocation climb model has been incorporated into the crystal plasticity modeling framework. The dislocation climb model parameters are calibrated and verified through experimental creep tests performed at 950°. In addition, a cohesive zone model has been fully implemented in the context of the crystal plasticity finite element model to capture the intergranular creep damage. The parameters of the cohesive zone model have been calibrated using available experimental data. The numerical simulations illustrate the capability of the proposed model in capturing damage initiation and growth under creep loads as compared to the experimental observations. The microscale analysis sheds light on the crack initiation sites and propagation patterns within the microstructure. The model is also utilized to investigate the hybrid-controlled creep-fatigue tests and has been found to capture reasonably well the stress-strain response with different hold times and hold stress magnitudes.« less
NASA Astrophysics Data System (ADS)
Butler, Samuel D.; Marciniak, Michael A.
2014-09-01
Since the development of the Torrance-Sparrow bidirectional re ectance distribution function (BRDF) model in 1967, several BRDF models have been created. Previous attempts to categorize BRDF models have relied upon somewhat vague descriptors, such as empirical, semi-empirical, and experimental. Our approach is to instead categorize BRDF models based on functional form: microfacet normal distribution, geometric attenua- tion, directional-volumetric and Fresnel terms, and cross section conversion factor. Several popular microfacet models are compared to a standardized notation for a microfacet BRDF model. A library of microfacet model components is developed, allowing for creation of unique microfacet models driven by experimentally measured BRDFs.
Hodyna, Diana; Kovalishyn, Vasyl; Rogalsky, Sergiy; Blagodatnyi, Volodymyr; Petko, Kirill; Metelytsia, Larisa
2016-09-01
Predictive QSAR models for the inhibitors of B. subtilis and Ps. aeruginosa among imidazolium-based ionic liquids were developed using literary data. The regression QSAR models were created through Artificial Neural Network and k-nearest neighbor procedures. The classification QSAR models were constructed using WEKA-RF (random forest) method. The predictive ability of the models was tested by fivefold cross-validation; giving q(2) = 0.77-0.92 for regression models and accuracy 83-88% for classification models. Twenty synthesized samples of 1,3-dialkylimidazolium ionic liquids with predictive value of activity level of antimicrobial potential were evaluated. For all asymmetric 1,3-dialkylimidazolium ionic liquids, only compounds containing at least one radical with alkyl chain length of 12 carbon atoms showed high antibacterial activity. However, the activity of symmetric 1,3-dialkylimidazolium salts was found to have opposite relationship with the length of aliphatic radical being maximum for compounds based on 1,3-dioctylimidazolium cation. The obtained experimental results suggested that the application of classification QSAR models is more accurate for the prediction of activity of new imidazolium-based ILs as potential antibacterials. © 2016 John Wiley & Sons A/S.
Testability of evolutionary game dynamics based on experimental economics data
NASA Astrophysics Data System (ADS)
Wang, Yijia; Chen, Xiaojie; Wang, Zhijian
2017-11-01
Understanding the dynamic processes of a real game system requires an appropriate dynamics model, and rigorously testing a dynamics model is nontrivial. In our methodological research, we develop an approach to testing the validity of game dynamics models that considers the dynamic patterns of angular momentum and speed as measurement variables. Using Rock-Paper-Scissors (RPS) games as an example, we illustrate the geometric patterns in the experiment data. We then derive the related theoretical patterns from a series of typical dynamics models. By testing the goodness-of-fit between the experimental and theoretical patterns, we show that the validity of these models can be evaluated quantitatively. Our approach establishes a link between dynamics models and experimental systems, which is, to the best of our knowledge, the most effective and rigorous strategy for ascertaining the testability of evolutionary game dynamics models.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Rongle Zhang; Jie Chang; Yuanyuan Xu
A new kinetic model of the Fischer-Tropsch synthesis (FTS) is proposed to describe the non-Anderson-Schulz-Flory (ASF) product distribution. The model is based on the double-polymerization monomers hypothesis, in which the surface C{sub 2}{asterisk} species acts as a chain-growth monomer in the light-product range, while C{sub 1}{asterisk} species acts as a chain-growth monomer in the heavy-product range. The detailed kinetic model in the Langmuir-Hinshelwood-Hougen-Watson type based on the elementary reactions is derived for FTS and the water-gas-shift reaction. Kinetic model candidates are evaluated by minimization of multiresponse objective functions with a genetic algorithm approach. The model of hydrocarbon product distribution ismore » consistent with experimental data (
NASA Astrophysics Data System (ADS)
Gurrala, Praveen; Downs, Andrew; Chen, Kun; Song, Jiming; Roberts, Ron
2018-04-01
Full wave scattering models for ultrasonic waves are necessary for the accurate prediction of voltage signals received from complex defects/flaws in practical nondestructive evaluation (NDE) measurements. We propose the high-order Nyström method accelerated by the multilevel fast multipole algorithm (MLFMA) as an improvement to the state-of-the-art full-wave scattering models that are based on boundary integral equations. We present numerical results demonstrating improvements in simulation time and memory requirement. Particularly, we demonstrate the need for higher order geom-etry and field approximation in modeling NDE measurements. Also, we illustrate the importance of full-wave scattering models using experimental pulse-echo data from a spherical inclusion in a solid, which cannot be modeled accurately by approximation-based scattering models such as the Kirchhoff approximation.
An empirically-based model for the lift coefficients of twisted airfoils with leading-edge tubercles
NASA Astrophysics Data System (ADS)
Ni, Zao; Su, Tsung-chow; Dhanak, Manhar
2018-04-01
Experimental data for untwisted airfoils are utilized to propose a model for predicting the lift coefficients of twisted airfoils with leading-edge tubercles. The effectiveness of the empirical model is verified through comparison with results of a corresponding computational fluid-dynamic (CFD) study. The CFD study is carried out for both twisted and untwisted airfoils with tubercles, the latter shown to compare well with available experimental data. Lift coefficients of twisted airfoils predicted from the proposed empirically-based model match well with the corresponding coefficients determined using the verified CFD study. Flow details obtained from the latter provide better insight into the underlying mechanism and behavior at stall of twisted airfoils with leading edge tubercles.
[Advance in researches on the effect of forest on hydrological process].
Zhang, Zhiqiang; Yu, Xinxiao; Zhao, Yutao; Qin, Yongsheng
2003-01-01
According to the effects of forest on hydrological process, forest hydrology can be divided into three related aspects: experimental research on the effects of forest changing on hydrological process quantity and water quality; mechanism study on the effects of forest changing on hydrological cycle, and establishing and exploitating physical-based distributed forest hydrological model for resource management and engineering construction. Orientation experiment research can not only support the first-hand data for forest hydrological model, but also make clear the precipitation-runoff mechanisms. Research on runoff mechanisms can be valuable for the exploitation and improvement of physical based hydrological models. Moreover, the model can also improve the experimental and runoff mechanism researches. A review of above three aspects are summarized in this paper.
Amidoxime Polymers for Uranium Adsorption: Influence of Comonomers and Temperature
Ladshaw, Austin P.; Wiechert, Alexander I.; Das, Sadananda; ...
2017-11-04
Recovering uranium from seawater has been the subject of many studies for decades, and has recently seen significant progress in materials development since the U.S. Department of Energy (DOE) has become involved. With DOE direction, the uranium uptake for amidoxime-based polymer adsorbents has more than tripled in capacity. In an effort to better understand how these new adsorbent materials behave under different environmental stimuli, several experimental and modeling based studies have been employed to investigate impacts of competing ions, salinity, pH, and other factors on uranium uptake. For this study, the effect of temperature and type of comonomer on uraniummore » adsorption by three different amidoxime adsorbents (AF1, 38H, AI8) was examined. Experimental measurements of uranium uptake were taken in 1–L batch reactors from 10 to 40 °C. A chemisorption model was developed and applied in order to estimate unknown system parameters through optimization. Experimental results demonstrated that the overall uranium chemisorption process for all three materials is endothermic, which was also mirrored in the model results. Model simulations show very good agreement with the data and were able to predict the temperature effect on uranium adsorption as experimental conditions changed. Here, this model may be used for predicting uranium uptake by other amidoxime materials.« less
Amidoxime Polymers for Uranium Adsorption: Influence of Comonomers and Temperature
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ladshaw, Austin P.; Wiechert, Alexander I.; Das, Sadananda
Recovering uranium from seawater has been the subject of many studies for decades, and has recently seen significant progress in materials development since the U.S. Department of Energy (DOE) has become involved. With DOE direction, the uranium uptake for amidoxime-based polymer adsorbents has more than tripled in capacity. In an effort to better understand how these new adsorbent materials behave under different environmental stimuli, several experimental and modeling based studies have been employed to investigate impacts of competing ions, salinity, pH, and other factors on uranium uptake. For this study, the effect of temperature and type of comonomer on uraniummore » adsorption by three different amidoxime adsorbents (AF1, 38H, AI8) was examined. Experimental measurements of uranium uptake were taken in 1–L batch reactors from 10 to 40 °C. A chemisorption model was developed and applied in order to estimate unknown system parameters through optimization. Experimental results demonstrated that the overall uranium chemisorption process for all three materials is endothermic, which was also mirrored in the model results. Model simulations show very good agreement with the data and were able to predict the temperature effect on uranium adsorption as experimental conditions changed. Here, this model may be used for predicting uranium uptake by other amidoxime materials.« less
Amidoxime Polymers for Uranium Adsorption: Influence of Comonomers and Temperature
Wiechert, Alexander I.; Das, Sadananda; Yiacoumi, Sotira
2017-01-01
Recovering uranium from seawater has been the subject of many studies for decades, and has recently seen significant progress in materials development since the U.S. Department of Energy (DOE) has become involved. With DOE direction, the uranium uptake for amidoxime-based polymer adsorbents has more than tripled in capacity. In an effort to better understand how these new adsorbent materials behave under different environmental stimuli, several experimental and modeling based studies have been employed to investigate impacts of competing ions, salinity, pH, and other factors on uranium uptake. For this study, the effect of temperature and type of comonomer on uranium adsorption by three different amidoxime adsorbents (AF1, 38H, AI8) was examined. Experimental measurements of uranium uptake were taken in 1−L batch reactors from 10 to 40 °C. A chemisorption model was developed and applied in order to estimate unknown system parameters through optimization. Experimental results demonstrated that the overall uranium chemisorption process for all three materials is endothermic, which was also mirrored in the model results. Model simulations show very good agreement with the data and were able to predict the temperature effect on uranium adsorption as experimental conditions changed. This model may be used for predicting uranium uptake by other amidoxime materials. PMID:29113060
DOE Office of Scientific and Technical Information (OSTI.GOV)
McKone, Thomas E.; Maddalena, Randy L.
2007-01-01
The role of terrestrial vegetation in transferring chemicals from soil and air into specific plant tissues (stems, leaves, roots, etc.) is still not well characterized. We provide here a critical review of plant-to-soil bioconcentration ratio (BCR) estimates based on models and experimental data. This review includes the conceptual and theoretical formulations of the bioconcentration ratio, constructing and calibrating empirical and mathematical algorithms to describe this ratio and the experimental data used to quantify BCRs and calibrate the model performance. We first evaluate the theoretical basis for the BCR concept and BCR models and consider how lack of knowledge and datamore » limits reliability and consistency of BCR estimates. We next consider alternate modeling strategies for BCR. A key focus of this evaluation is the relative contributions to overall uncertainty from model uncertainty versus variability in the experimental data used to develop and test the models. As a case study, we consider a single chemical, hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX), and focus on variability of bioconcentration measurements obtained from 81 experiments with different plant species, different plant tissues, different experimental conditions, and different methods for reporting concentrations in the soil and plant tissues. We use these observations to evaluate both the magnitude of experimental variability in plant bioconcentration and compare this to model uncertainty. Among these 81 measurements, the variation of the plant/soil BCR has a geometric standard deviation (GSD) of 3.5 and a coefficient of variability (CV-ratio of arithmetic standard deviation to mean) of 1.7. These variations are significant but low relative to model uncertainties--which have an estimated GSD of 10 with a corresponding CV of 14.« less
Ernstbrunner, L; Werthel, J-D; Hatta, T; Thoreson, A R; Resch, H; An, K-N; Moroder, P
2016-10-01
The bony shoulder stability ratio (BSSR) allows for quantification of the bony stabilisers in vivo. We aimed to biomechanically validate the BSSR, determine whether joint incongruence affects the stability ratio (SR) of a shoulder model, and determine the correct parameters (glenoid concavity versus humeral head radius) for calculation of the BSSR in vivo. Four polyethylene balls (radii: 19.1 mm to 38.1 mm) were used to mould four fitting sockets in four different depths (3.2 mm to 19.1mm). The SR was measured in biomechanical congruent and incongruent experimental series. The experimental SR of a congruent system was compared with the calculated SR based on the BSSR approach. Differences in SR between congruent and incongruent experimental conditions were quantified. Finally, the experimental SR was compared with either calculated SR based on the socket concavity or plastic ball radius. The experimental SR is comparable with the calculated SR (mean difference 10%, sd 8%; relative values). The experimental incongruence study observed almost no differences (2%, sd 2%). The calculated SR on the basis of the socket concavity radius is superior in predicting the experimental SR (mean difference 10%, sd 9%) compared with the calculated SR based on the plastic ball radius (mean difference 42%, sd 55%). The present biomechanical investigation confirmed the validity of the BSSR. Incongruence has no significant effect on the SR of a shoulder model. In the event of an incongruent system, the calculation of the BSSR on the basis of the glenoid concavity radius is recommended.Cite this article: L. Ernstbrunner, J-D. Werthel, T. Hatta, A. R. Thoreson, H. Resch, K-N. An, P. Moroder. Biomechanical analysis of the effect of congruence, depth and radius on the stability ratio of a simplistic 'ball-and-socket' joint model. Bone Joint Res 2016;5:453-460. DOI: 10.1302/2046-3758.510.BJR-2016-0078.R1. © 2016 Ernstbrunner et al.
Biophysics of cadherin adhesion.
Leckband, Deborah; Sivasankar, Sanjeevi
2012-01-01
Since the identification of cadherins and the publication of the first crystal structures, the mechanism of cadherin adhesion, and the underlying structural basis have been studied with a number of different experimental techniques, different classical cadherin subtypes, and cadherin fragments. Earlier studies based on biophysical measurements and structure determinations resulted in seemingly contradictory findings regarding cadherin adhesion. However, recent experimental data increasingly reveal parallels between structures, solution binding data, and adhesion-based biophysical measurements that are beginning to both reconcile apparent differences and generate a more comprehensive model of cadherin-mediated cell adhesion. This chapter summarizes the functional, structural, and biophysical findings relevant to cadherin junction assembly and adhesion. We emphasize emerging parallels between findings obtained with different experimental approaches. Although none of the current models accounts for all of the available experimental and structural data, this chapter discusses possible origins of apparent discrepancies, highlights remaining gaps in current knowledge, and proposes challenges for further study.
NASA Astrophysics Data System (ADS)
Nieto, Paulino José García; García-Gonzalo, Esperanza; Vilán, José Antonio Vilán; Robleda, Abraham Segade
2015-12-01
The main aim of this research work is to build a new practical hybrid regression model to predict the milling tool wear in a regular cut as well as entry cut and exit cut of a milling tool. The model was based on Particle Swarm Optimization (PSO) in combination with support vector machines (SVMs). This optimization mechanism involved kernel parameter setting in the SVM training procedure, which significantly influences the regression accuracy. Bearing this in mind, a PSO-SVM-based model, which is based on the statistical learning theory, was successfully used here to predict the milling tool flank wear (output variable) as a function of the following input variables: the time duration of experiment, depth of cut, feed, type of material, etc. To accomplish the objective of this study, the experimental dataset represents experiments from runs on a milling machine under various operating conditions. In this way, data sampled by three different types of sensors (acoustic emission sensor, vibration sensor and current sensor) were acquired at several positions. A second aim is to determine the factors with the greatest bearing on the milling tool flank wear with a view to proposing milling machine's improvements. Firstly, this hybrid PSO-SVM-based regression model captures the main perception of statistical learning theory in order to obtain a good prediction of the dependence among the flank wear (output variable) and input variables (time, depth of cut, feed, etc.). Indeed, regression with optimal hyperparameters was performed and a determination coefficient of 0.95 was obtained. The agreement of this model with experimental data confirmed its good performance. Secondly, the main advantages of this PSO-SVM-based model are its capacity to produce a simple, easy-to-interpret model, its ability to estimate the contributions of the input variables, and its computational efficiency. Finally, the main conclusions of this study are exposed.
Porcine experimental model for perforator flap raising in reconstructive microsurgery.
González-García, José A; Chiesa-Estomba, Carlos M; Álvarez, Leire; Altuna, Xabier; García-Iza, Leire; Thomas, Izaskun; Sistiaga, Jon A; Larruscain, Ekhiñe
2018-07-01
Perforator free flap-based reconstruction of the head and neck is a challenging surgical procedure and needs a steep learning curve. A reproducible mammal large animal model with similarities to human anatomy is relevant for perforator flap raising and microanastomosis. The aim of this study was to assess the feasibility of a swine model for perforator-based free flaps in reconstructive microsurgery. Eleven procedures were performed under general anesthesia in a porcine model, elevating a skin flap vascularized by perforating musculocutaneous branches of the superior epigastric artery to evaluate the relevance of this model for head and neck reconstructive microsurgery. The anterior abdominal skin perforator-based free flap in a swine model irrigated by the superior epigastric artery was elevated in eleven procedures. In six of these procedures, we could perform an arterial and venous microanastomosis to the great vessels located in the base of the neck. The porcine experimental model of superior epigastric artery perforator-based free flap reconstruction offers relevant similarities to the human deep inferior epigastric artery perforator flap. We could demonstrate this model as acceptable for perforator free flap training due to the necessity of perforator and pedicle dissection and transfer to a distant area. Copyright © 2018 Elsevier Inc. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kumar, A.S.; Sidener, S.E.; Hamilton, M.L.
1999-10-01
Dynamic finite element modeling of the fracture behavior of fatigue-precracked Charpy specimens in both unirradiated and irradiated conditions was performed using a computer code, ABAQUS Explicit, to predict the upper shelf energy of precracked specimens of a given size from experimental data obtained for a different size. A tensile fracture-strain based method for modeling crack extension and propagation was used. It was found that the predicted upper shelf energies of full and half size precracked specimens based on third size data were in reasonable agreement with their respective experimental values. Similar success was achieved for predicting the upper shelf energymore » of subsize precracked specimens based on full size data.« less
Error-Rate Estimation Based on Multi-Signal Flow Graph Model and Accelerated Radiation Tests
Wang, Yueke; Xing, Kefei; Deng, Wei; Zhang, Zelong
2016-01-01
A method of evaluating the single-event effect soft-error vulnerability of space instruments before launched has been an active research topic in recent years. In this paper, a multi-signal flow graph model is introduced to analyze the fault diagnosis and meantime to failure (MTTF) for space instruments. A model for the system functional error rate (SFER) is proposed. In addition, an experimental method and accelerated radiation testing system for a signal processing platform based on the field programmable gate array (FPGA) is presented. Based on experimental results of different ions (O, Si, Cl, Ti) under the HI-13 Tandem Accelerator, the SFER of the signal processing platform is approximately 10−3(error/particle/cm2), while the MTTF is approximately 110.7 h. PMID:27583533
Error-Rate Estimation Based on Multi-Signal Flow Graph Model and Accelerated Radiation Tests.
He, Wei; Wang, Yueke; Xing, Kefei; Deng, Wei; Zhang, Zelong
2016-01-01
A method of evaluating the single-event effect soft-error vulnerability of space instruments before launched has been an active research topic in recent years. In this paper, a multi-signal flow graph model is introduced to analyze the fault diagnosis and meantime to failure (MTTF) for space instruments. A model for the system functional error rate (SFER) is proposed. In addition, an experimental method and accelerated radiation testing system for a signal processing platform based on the field programmable gate array (FPGA) is presented. Based on experimental results of different ions (O, Si, Cl, Ti) under the HI-13 Tandem Accelerator, the SFER of the signal processing platform is approximately 10-3(error/particle/cm2), while the MTTF is approximately 110.7 h.
Tong, Xuming; Chen, Jinghang; Miao, Hongyu; Li, Tingting; Zhang, Le
2015-01-01
Agent-based models (ABM) and differential equations (DE) are two commonly used methods for immune system simulation. However, it is difficult for ABM to estimate key parameters of the model by incorporating experimental data, whereas the differential equation model is incapable of describing the complicated immune system in detail. To overcome these problems, we developed an integrated ABM regression model (IABMR). It can combine the advantages of ABM and DE by employing ABM to mimic the multi-scale immune system with various phenotypes and types of cells as well as using the input and output of ABM to build up the Loess regression for key parameter estimation. Next, we employed the greedy algorithm to estimate the key parameters of the ABM with respect to the same experimental data set and used ABM to describe a 3D immune system similar to previous studies that employed the DE model. These results indicate that IABMR not only has the potential to simulate the immune system at various scales, phenotypes and cell types, but can also accurately infer the key parameters like DE model. Therefore, this study innovatively developed a complex system development mechanism that could simulate the complicated immune system in detail like ABM and validate the reliability and efficiency of model like DE by fitting the experimental data. PMID:26535589
Protein Modelling: What Happened to the “Protein Structure Gap”?
Schwede, Torsten
2013-01-01
Computational modeling and prediction of three-dimensional macromolecular structures and complexes from their sequence has been a long standing vision in structural biology as it holds the promise to bypass part of the laborious process of experimental structure solution. Over the last two decades, a paradigm shift has occurred: starting from a situation where the “structure knowledge gap” between the huge number of protein sequences and small number of known structures has hampered the widespread use of structure-based approaches in life science research, today some form of structural information – either experimental or computational – is available for the majority of amino acids encoded by common model organism genomes. Template based homology modeling techniques have matured to a point where they are now routinely used to complement experimental techniques. With the scientific focus of interest moving towards larger macromolecular complexes and dynamic networks of interactions, the integration of computational modeling methods with low-resolution experimental techniques allows studying large and complex molecular machines. Computational modeling and prediction techniques are still facing a number of challenges which hamper the more widespread use by the non-expert scientist. For example, it is often difficult to convey the underlying assumptions of a computational technique, as well as the expected accuracy and structural variability of a specific model. However, these aspects are crucial to understand the limitations of a model, and to decide which interpretations and conclusions can be supported. PMID:24010712
Sfakiotakis, Stelios; Vamvuka, Despina
2015-12-01
The pyrolysis of six waste biomass samples was studied and the fuels were kinetically evaluated. A modified independent parallel reactions scheme (IPR) and a distributed activation energy model (DAEM) were developed and their validity was assessed and compared by checking their accuracy of fitting the experimental results, as well as their prediction capability in different experimental conditions. The pyrolysis experiments were carried out in a thermogravimetric analyzer and a fitting procedure, based on least squares minimization, was performed simultaneously at different experimental conditions. A modification of the IPR model, considering dependence of the pre-exponential factor on heating rate, was proved to give better fit results for the same number of tuned kinetic parameters, comparing to the known IPR model and very good prediction results for stepwise experiments. Fit of calculated data to the experimental ones using the developed DAEM model was also proved to be very good. Copyright © 2015 Elsevier Ltd. All rights reserved.
Using entropy measures to characterize human locomotion.
Leverick, Graham; Szturm, Tony; Wu, Christine Q
2014-12-01
Entropy measures have been widely used to quantify the complexity of theoretical and experimental dynamical systems. In this paper, the value of using entropy measures to characterize human locomotion is demonstrated based on their construct validity, predictive validity in a simple model of human walking and convergent validity in an experimental study. Results show that four of the five considered entropy measures increase meaningfully with the increased probability of falling in a simple passive bipedal walker model. The same four entropy measures also experienced statistically significant increases in response to increasing age and gait impairment caused by cognitive interference in an experimental study. Of the considered entropy measures, the proposed quantized dynamical entropy (QDE) and quantization-based approximation of sample entropy (QASE) offered the best combination of sensitivity to changes in gait dynamics and computational efficiency. Based on these results, entropy appears to be a viable candidate for assessing the stability of human locomotion.
NASA Astrophysics Data System (ADS)
Avitabile, P.; O'Callahan, J.
2003-07-01
Inclusion of rotational effects is critical for the accuracy of the predicted system characteristics, in almost all system modelling studies. However, experimentally derived information for the description of one or more of the components for the system will generally not have any rotational effects included in the description of the component. The lack of rotational effects has long affected the results from any system model development whether using a modal-based approach or an impedance-based approach. Several new expansion processes are described herein for the development of FRFs needed for impedance-based system models. These techniques expand experimentally derived mode shapes, residual modes from the modal parameter estimation process and FRFs directly to allow for the inclusion of the necessary rotational dof. The FRFs involving translational to rotational dofs are developed as well as the rotational to rotational dof. Examples are provided to show the use of these techniques.
NASA Astrophysics Data System (ADS)
Junker, Philipp; Jaeger, Stefanie; Kastner, Oliver; Eggeler, Gunther; Hackl, Klaus
2015-07-01
In this work, we present simulations of shape memory alloys which serve as first examples demonstrating the predicting character of energy-based material models. We begin with a theoretical approach for the derivation of the caloric parts of the Helmholtz free energy. Afterwards, experimental results for DSC measurements are presented. Then, we recall a micromechanical model based on the principle of the minimum of the dissipation potential for the simulation of polycrystalline shape memory alloys. The previously determined caloric parts of the Helmholtz free energy close the set of model parameters without the need of parameter fitting. All quantities are derived directly from experiments. Finally, we compare finite element results for tension tests to experimental data and show that the model identified by thermal measurements can predict mechanically induced phase transformations and thus rationalize global material behavior without any further assumptions.
Potential formulation of sleep dynamics
NASA Astrophysics Data System (ADS)
Phillips, A. J. K.; Robinson, P. A.
2009-02-01
A physiologically based model of the mechanisms that control the human sleep-wake cycle is formulated in terms of an equivalent nonconservative mechanical potential. The potential is analytically simplified and reduced to a quartic two-well potential, matching the bifurcation structure of the original model. This yields a dynamics-based model that is analytically simpler and has fewer parameters than the original model, allowing easier fitting to experimental data. This model is first demonstrated to semiquantitatively match the dynamics of the physiologically based model from which it is derived, and is then fitted directly to a set of experimentally derived criteria. These criteria place rigorous constraints on the parameter values, and within these constraints the model is shown to reproduce normal sleep-wake dynamics and recovery from sleep deprivation. Furthermore, this approach enables insights into the dynamics by direct analogies to phenomena in well studied mechanical systems. These include the relation between friction in the mechanical system and the timecourse of neurotransmitter action, and the possible relation between stochastic resonance and napping behavior. The model derived here also serves as a platform for future investigations of sleep-wake phenomena from a dynamical perspective.
Experimental validation of flexible robot arm modeling and control
NASA Technical Reports Server (NTRS)
Ulsoy, A. Galip
1989-01-01
Flexibility is important for high speed, high precision operation of lightweight manipulators. Accurate dynamic modeling of flexible robot arms is needed. Previous work has mostly been based on linear elasticity with prescribed rigid body motions (i.e., no effect of flexible motion on rigid body motion). Little or no experimental validation of dynamic models for flexible arms is available. Experimental results are also limited for flexible arm control. Researchers include the effects of prismatic as well as revolute joints. They investigate the effect of full coupling between the rigid and flexible motions, and of axial shortening, and consider the control of flexible arms using only additional sensors.
Experimental Evaluation of Equivalent-Fluid Models for Melamine Foam
NASA Technical Reports Server (NTRS)
Allen, Albert R.; Schiller, Noah H.
2016-01-01
Melamine foam is a soft porous material commonly used in noise control applications. Many models exist to represent porous materials at various levels of fidelity. This work focuses on rigid frame equivalent fluid models, which represent the foam as a fluid with a complex speed of sound and density. There are several empirical models available to determine these frequency dependent parameters based on an estimate of the material flow resistivity. Alternatively, these properties can be experimentally educed using an impedance tube setup. Since vibroacoustic models are generally sensitive to these properties, this paper assesses the accuracy of several empirical models relative to impedance tube measurements collected with melamine foam samples. Diffuse field sound absorption measurements collected using large test articles in a laboratory are also compared with absorption predictions determined using model-based and measured foam properties. Melamine foam slabs of various thicknesses are considered.
A High-Resolution Integrated Model of the National Ignition Campaign Cryogenic Layered Experiments
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jones, O. S.; Callahan, D. A.; Cerjan, C. J.
A detailed simulation-based model of the June 2011 National Ignition Campaign (NIC) cryogenic DT experiments is presented. The model is based on integrated hohlraum-capsule simulations that utilize the best available models for the hohlraum wall, ablator, and DT equations of state and opacities. The calculated radiation drive was adjusted by changing the input laser power to match the experimentally measured shock speeds, shock merger times, peak implosion velocity, and bangtime. The crossbeam energy transfer model was tuned to match the measured time-dependent symmetry. Mid-mode mix was included by directly modeling the ablator and ice surface perturbations up to mode 60.more » Simulated experimental values were extracted from the simulation and compared against the experiment. The model adjustments brought much of the simulated data into closer agreement with the experiment, with the notable exception of the measured yields, which were 15-40% of the calculated yields.« less
A High-Resolution Integrated Model of the National Ignition Campaign Cryogenic Layered Experiments
Jones, O. S.; Callahan, D. A.; Cerjan, C. J.; ...
2012-05-29
A detailed simulation-based model of the June 2011 National Ignition Campaign (NIC) cryogenic DT experiments is presented. The model is based on integrated hohlraum-capsule simulations that utilize the best available models for the hohlraum wall, ablator, and DT equations of state and opacities. The calculated radiation drive was adjusted by changing the input laser power to match the experimentally measured shock speeds, shock merger times, peak implosion velocity, and bangtime. The crossbeam energy transfer model was tuned to match the measured time-dependent symmetry. Mid-mode mix was included by directly modeling the ablator and ice surface perturbations up to mode 60.more » Simulated experimental values were extracted from the simulation and compared against the experiment. The model adjustments brought much of the simulated data into closer agreement with the experiment, with the notable exception of the measured yields, which were 15-40% of the calculated yields.« less
Towards an Integrated Model of the NIC Layered Implosions
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jones, O S; Callahan, D A; Cerjan, C J
A detailed simulation-based model of the June 2011 National Ignition Campaign (NIC) cryogenic DT experiments is presented. The model is based on integrated hohlraum-capsule simulations that utilize the best available models for the hohlraum wall, ablator, and DT equations of state and opacities. The calculated radiation drive was adjusted by changing the input laser power to match the experimentally measured shock speeds, shock merger times, peak implosion velocity, and bangtime. The crossbeam energy transfer model was tuned to match the measured time-dependent symmetry. Mid-mode mix was included by directly modeling the ablator and ice surface perturbations up to mode 60.more » Simulated experimental values were extracted from the simulation and compared against the experiment. The model adjustments brought much of the simulated data into closer agreement with the experiment, with the notable exception of the measured yields, which were 15-45% of the calculated yields.« less
BiGG Models: A platform for integrating, standardizing and sharing genome-scale models
King, Zachary A.; Lu, Justin; Drager, Andreas; ...
2015-10-17
In this study, genome-scale metabolic models are mathematically structured knowledge bases that can be used to predict metabolic pathway usage and growth phenotypes. Furthermore, they can generate and test hypotheses when integrated with experimental data. To maximize the value of these models, centralized repositories of high-quality models must be established, models must adhere to established standards and model components must be linked to relevant databases. Tools for model visualization further enhance their utility. To meet these needs, we present BiGG Models (http://bigg.ucsd.edu), a completely redesigned Biochemical, Genetic and Genomic knowledge base. BiGG Models contains more than 75 high-quality, manually-curated genome-scalemore » metabolic models. On the website, users can browse, search and visualize models. BiGG Models connects genome-scale models to genome annotations and external databases. Reaction and metabolite identifiers have been standardized across models to conform to community standards and enable rapid comparison across models. Furthermore, BiGG Models provides a comprehensive application programming interface for accessing BiGG Models with modeling and analysis tools. As a resource for highly curated, standardized and accessible models of metabolism, BiGG Models will facilitate diverse systems biology studies and support knowledge-based analysis of diverse experimental data.« less
BiGG Models: A platform for integrating, standardizing and sharing genome-scale models
King, Zachary A.; Lu, Justin; Dräger, Andreas; Miller, Philip; Federowicz, Stephen; Lerman, Joshua A.; Ebrahim, Ali; Palsson, Bernhard O.; Lewis, Nathan E.
2016-01-01
Genome-scale metabolic models are mathematically-structured knowledge bases that can be used to predict metabolic pathway usage and growth phenotypes. Furthermore, they can generate and test hypotheses when integrated with experimental data. To maximize the value of these models, centralized repositories of high-quality models must be established, models must adhere to established standards and model components must be linked to relevant databases. Tools for model visualization further enhance their utility. To meet these needs, we present BiGG Models (http://bigg.ucsd.edu), a completely redesigned Biochemical, Genetic and Genomic knowledge base. BiGG Models contains more than 75 high-quality, manually-curated genome-scale metabolic models. On the website, users can browse, search and visualize models. BiGG Models connects genome-scale models to genome annotations and external databases. Reaction and metabolite identifiers have been standardized across models to conform to community standards and enable rapid comparison across models. Furthermore, BiGG Models provides a comprehensive application programming interface for accessing BiGG Models with modeling and analysis tools. As a resource for highly curated, standardized and accessible models of metabolism, BiGG Models will facilitate diverse systems biology studies and support knowledge-based analysis of diverse experimental data. PMID:26476456
NASA Astrophysics Data System (ADS)
Dewalque, Florence; Schwartz, Cédric; Denoël, Vincent; Croisier, Jean-Louis; Forthomme, Bénédicte; Brüls, Olivier
2018-02-01
This paper studies the dynamics of tape springs which are characterised by a highly geometrical nonlinear behaviour including buckling, the formation of folds and hysteresis. An experimental set-up is designed to capture these complex nonlinear phenomena. The experimental data are acquired by the means of a 3D motion analysis system combined with a synchronised force plate. Deployment tests show that the motion can be divided into three phases characterised by different types of folds, frequencies of oscillation and damping behaviours. Furthermore, the reproducibility quality of the dynamic and quasi-static results is validated by performing a large number of tests. In parallel, a nonlinear finite element model is developed. The required model parameters are identified based on simple experimental tests such as static deformed configurations and small amplitude vibration tests. In the end, the model proves to be well correlated with the experimental results in opposite sense bending, while in equal sense, both the experimental set-up and the numerical model are particularly sensitive to the initial conditions.
Computational Insights into the O2-evolving complex of photosystem II
Sproviero, Eduardo M.; McEvoy, James P.; Gascón, José A.; Brudvig, Gary W.; Batista, Victor S.
2009-01-01
Mechanistic investigations of the water-splitting reaction of the oxygen-evolving complex (OEC) of photosystem II (PSII) are fundamentally informed by structural studies. Many physical techniques have provided important insights into the OEC structure and function, including X-ray diffraction (XRD) and extended X-ray absorption fine structure (EXAFS) spectroscopy as well as mass spectrometry (MS), electron paramagnetic resonance (EPR) spectroscopy and Fourier transform infrared spectroscopy applied in conjunction with mutagenesis studies. However, experimental studies have yet to yield consensus as to the exact configuration of the catalytic metal cluster and its ligation scheme. Computational modeling studies, including density functional (DFT) theory combined with quantum mechanics/molecular mechanics (QM/MM) hybrid methods for explicitly including the influence of the surrounding protein, have proposed chemically satisfactory models of the fully ligated OEC within PSII that are maximally consistent with experimental results. The inorganic core of these models is similar to the crystallographic model upon which they were based but comprises important modifications due to structural refinement, hydration and proteinaceous ligation which improve agreement with a wide range of experimental data. The computational models are useful for rationalizing spectroscopic and crystallographic results and for building a complete structure-based mechanism of water-splitting in PSII as described by the intermediate oxidation states of the OEC. This review summarizes these recent advances in QM/MM modeling of PSII within the context of recent experimental studies. PMID:18483777
Rowe, Rachel K.; Harrison, Jordan L.; Thomas, Theresa C.; Pauly, James R.; Adelson, P. David; Lifshitz, Jonathan
2013-01-01
The use of animal modeling in traumatic brain injury (TBI) research is justified by the lack of sufficiently comprehensive in vitro and computer modeling that incorporates all components of the neurovascular unit. Valid animal modeling of TBI requires accurate replication of both the mechanical forces and secondary injury conditions observed in human patients. Regulatory requirements for animal modeling emphasize the administration of appropriate anesthetics and analgesics unless withholding these drugs is scientifically justified. The objective of this review is to present scientific justification for standardizing the use of anesthetics and analgesics, within a study, when modeling TBI in order to preserve study validity. Evidence for the interference of anesthetics and analgesics in the natural course of brain injury calls for consistent consideration of pain management regimens when conducting TBI research. Anesthetics administered at the time of or shortly after induction of brain injury can alter cognitive, motor, and histological outcomes following TBI. A consistent anesthesia protocol based on experimental objectives within each individual study is imperative when conducting TBI studies to control for the confounding effects of anesthesia on outcome parameters. Experimental studies that replicate the clinical condition are essential to gain further understanding and evaluate possible treatments for TBI. However, with animal models of TBI it is essential that investigators assure a uniform drug delivery protocol that minimizes confounding variables, while minimizing pain and suffering. PMID:23877609
Water age and stream solute dynamics at the Hubbard Brook Experimental Forest (US)
NASA Astrophysics Data System (ADS)
Botter, Gianluca; Benettin, Paolo; McGuire, Kevin; Rinaldo, Andrea
2016-04-01
The contribution discusses experimental and modeling results from a headwater catchment at the Hubbard Brook Experimental Forest (New Hampshire, USA) to explore the link between stream solute dynamics and water age. A theoretical framework based on water age dynamics, which represents a general basis for characterizing solute transport at the catchment scale, is used to model both conservative and weathering-derived solutes. Based on the available information about the hydrology of the site, an integrated transport model was developed and used to estimate the relevant hydrochemical fluxes. The model was designed to reproduce the deuterium content of streamflow and allowed for the estimate of catchment water storage and dynamic travel time distributions (TTDs). Within this framework, dissolved silicon and sodium concentration in streamflow were simulated by implementing first-order chemical kinetics based explicitly on dynamic TTD, thus upscaling local geochemical processes to catchment scale. Our results highlight the key role of water stored within the subsoil glacial material in both the short-term and long-term solute circulation at Hubbard Brook. The analysis of the results provided by the calibrated model allowed a robust estimate of the emerging concentration-discharge relationship, streamflow age distributions (including the fraction of event water) and storage size, and their evolution in time due to hydrologic variability.
Müftüler, Mine; İnce, Mustafa Levent
2015-08-01
This study examined how a physical activity course based on the Trans-Contextual Model affected the variables of perceived autonomy support, autonomous motivation, determinants of leisure-time physical activity behavior, basic psychological needs satisfaction, and leisure-time physical activity behaviors. The participants were 70 Turkish university students (M age=23.3 yr., SD=3.2). A pre-test-post-test control group design was constructed. Initially, the participants were randomly assigned into an experimental (n=35) and a control (n=35) group. The experimental group followed a 12 wk. trans-contextual model-based intervention. The participants were pre- and post-tested in terms of Trans-Contextual Model constructs and of self-reported leisure-time physical activity behaviors. Multivariate analyses showed significant increases over the 12 wk. period for perceived autonomy support from instructor and peers, autonomous motivation in leisure-time physical activity setting, positive intention and perceived behavioral control over leisure-time physical activity behavior, more fulfillment of psychological needs, and more engagement in leisure-time physical activity behavior in the experimental group. These results indicated that the intervention was effective in developing leisure-time physical activity and indicated that the Trans-Contextual Model is a useful way to conceptualize these relationships.
20180312 - Structure-based QSAR Models to Predict Systemic Toxicity Points of Departure (SOT)
Human health risk assessment associated with environmental chemical exposure is limited by the tens of thousands of chemicals with little or no experimental in vivo toxicity data. Data gap filling techniques, such as quantitative structure activity relationship (QSAR) models base...
The BCD of response time analysis in experimental economics.
Spiliopoulos, Leonidas; Ortmann, Andreas
2018-01-01
For decisions in the wild, time is of the essence. Available decision time is often cut short through natural or artificial constraints, or is impinged upon by the opportunity cost of time. Experimental economists have only recently begun to conduct experiments with time constraints and to analyze response time (RT) data, in contrast to experimental psychologists. RT analysis has proven valuable for the identification of individual and strategic decision processes including identification of social preferences in the latter case, model comparison/selection, and the investigation of heuristics that combine speed and performance by exploiting environmental regularities. Here we focus on the benefits, challenges, and desiderata of RT analysis in strategic decision making. We argue that unlocking the potential of RT analysis requires the adoption of process-based models instead of outcome-based models, and discuss how RT in the wild can be captured by time-constrained experiments in the lab. We conclude that RT analysis holds considerable potential for experimental economics, deserves greater attention as a methodological tool, and promises important insights on strategic decision making in naturally occurring environments.
Investigation of Compressibility Effect for Aeropropulsive Shear Flows
NASA Technical Reports Server (NTRS)
Balasubramanyam, M. S.; Chen, C. P.
2005-01-01
Rocket Based Combined Cycle (RBCC) engines operate within a wide range of Mach numbers and altitudes. Fundamental fluid dynamic mechanisms involve complex choking, mass entrainment, stream mixing and wall interactions. The Propulsion Research Center at the University of Alabama in Huntsville is involved in an on- going experimental and numerical modeling study of non-axisymmetric ejector-based combined cycle propulsion systems. This paper attempts to address the modeling issues related to mixing, shear layer/wall interaction in a supersonic Strutjet/ejector flow field. Reynolds Averaged Navier-Stokes (RANS) solutions incorporating turbulence models are sought and compared to experimental measurements to characterize detailed flow dynamics. The effect of compressibility on fluids mixing and wall interactions were investigated using an existing CFD methodology. The compressibility correction to conventional incompressible two- equation models is found to be necessary for the supersonic mixing aspect of the ejector flows based on 2-D simulation results. 3-D strut-base flows involving flow separations were also investigated.
A physiologically based pharmacokinetic model for ionic silver and silver nanoparticles
Bachler, Gerald; von Goetz, Natalie; Hungerbühler, Konrad
2013-01-01
Silver is a strong antibiotic that is increasingly incorporated into consumer products as a bulk, salt, or nanosilver, thus potentially causing side-effects related to human exposure. However, the fate and behavior of (nano)silver in the human body is presently not well understood. In order to aggregate the existing experimental information, a physiologically based pharmacokinetic model (PBPK) was developed in this study for ionic silver and nanosilver. The structure of the model was established on the basis of toxicokinetic data from intravenous studies. The number of calibrated parameters was minimized in order to enhance the predictive capability of the model. We validated the model structure for both silver forms by reproducing exposure conditions (dermal, oral, and inhalation) of in vivo experiments and comparing simulated and experimentally assessed organ concentrations. Therefore, the percutaneous, intestinal, or pulmonary absorption fraction was estimated based on the blood silver concentration of the respective experimental data set. In all of the cases examined, the model could successfully predict the biodistribution of ionic silver and 15–150 nm silver nanoparticles, which were not coated with substances designed to prolong the circulatory time (eg, polyethylene glycol). Furthermore, the results of our model indicate that: (1) within the application domain of our model, the particle size and coating had a minor influence on the biodistribution; (2) in vivo, it is more likely that silver nanoparticles are directly stored as insoluble salt particles than dissolve into Ag+; and (3) compartments of the mononuclear phagocytic system play a minor role in exposure levels that are relevant for human consumers. We also give an example of how the model can be used in exposure and risk assessments based on five different exposure scenarios, namely dietary intake, use of three separate consumer products, and occupational exposure. PMID:24039420
NASA Astrophysics Data System (ADS)
Bian, Yunqiang; Ren, Weitong; Song, Feng; Yu, Jiafeng; Wang, Jihua
2018-05-01
Structure-based models or Gō-like models, which are built from one or multiple particular experimental structures, have been successfully applied to the folding of proteins and RNAs. Recently, a variant termed the hybrid atomistic model advances the description of backbone and side chain interactions of traditional structure-based models, by borrowing the description of local interactions from classical force fields. In this study, we assessed the validity of this model in the folding problem of human telomeric DNA G-quadruplex, where local dihedral terms play important roles. A two-state model was developed and a set of molecular dynamics simulations was conducted to study the folding dynamics of sequence Htel24, which was experimentally validated to adopt two different (3 + 1) hybrid G-quadruplex topologies in K+ solution. Consistent with the experimental observations, the hybrid-1 conformation was found to be more stable and the hybrid-2 conformation was kinetically more favored. The simulations revealed that the hybrid-2 conformation folded in a higher cooperative manner, which may be the reason why it was kinetically more accessible. Moreover, by building a Markov state model, a two-quartet G-quadruplex state and a misfolded state were identified as competing states to complicate the folding process of Htel24. Besides, the simulations also showed that the transition between hybrid-1 and hybrid-2 conformations may proceed an ensemble of hairpin structures. The hybrid atomistic structure-based model reproduced the kinetic partitioning folding dynamics of Htel24 between two different folds, and thus can be used to study the complex folding processes of other G-quadruplex structures.
ERIC Educational Resources Information Center
Harper, Gary W.; Bangi, Audrey K.; Sanchez, Bernadette; Doll, Mimi; Pedraza, Ana
2009-01-01
This article describes a quasi-experimental evaluation of a community-based, culturally and ecologically tailored HIV prevention intervention for Mexican American female adolescents grounded in the AIDS risk reduction model. A total of 378 Mexican American female adolescents (mean age = 15.2) participated in either the nine-session SHERO's (a…
A Numerical/Experimental Study on the Impact and CAI Behaviour of Glass Reinforced Compsite Plates
NASA Astrophysics Data System (ADS)
Perillo, Giovanni; Jørgensen, Jens K.; Cristiano, Roberta; Riccio, Aniello
2018-04-01
This paper focuses on the development of an advance numerical model specifically for simulating low velocity impact events and related stiffness reduction on composite structures. The model is suitable for low cost thick composite structures like wind turbine blade and maritime vessels. The model consist of a combination of inter and intra laminar models. The intra-laminar model present a combination of Puck and Hashin failure theories for the evaluation of the fibre and matrix failure. The inter-laminar damage is instead simulated by Cohesive Zone Method based on energy approach. Basic material properties, easily measurable according to standardized tests, are required. The model has been used to simulate impact and compression after impact tests. Experimental tests have been carried out on thick E-Glass/Epoxy composite commonly used in the wind turbine industry. The clustering effect as well as the consequence of the impact energy have been experimentally tested. The accuracy of numerical model has been verified against experimental data showing a very good accuracy of the model.
Compartmental and Data-Based Modeling of Cerebral Hemodynamics: Linear Analysis.
Henley, B C; Shin, D C; Zhang, R; Marmarelis, V Z
Compartmental and data-based modeling of cerebral hemodynamics are alternative approaches that utilize distinct model forms and have been employed in the quantitative study of cerebral hemodynamics. This paper examines the relation between a compartmental equivalent-circuit and a data-based input-output model of dynamic cerebral autoregulation (DCA) and CO2-vasomotor reactivity (DVR). The compartmental model is constructed as an equivalent-circuit utilizing putative first principles and previously proposed hypothesis-based models. The linear input-output dynamics of this compartmental model are compared with data-based estimates of the DCA-DVR process. This comparative study indicates that there are some qualitative similarities between the two-input compartmental model and experimental results.
SPH modelling of depth-limited turbulent open channel flows over rough boundaries.
Kazemi, Ehsan; Nichols, Andrew; Tait, Simon; Shao, Songdong
2017-01-10
A numerical model based on the smoothed particle hydrodynamics method is developed to simulate depth-limited turbulent open channel flows over hydraulically rough beds. The 2D Lagrangian form of the Navier-Stokes equations is solved, in which a drag-based formulation is used based on an effective roughness zone near the bed to account for the roughness effect of bed spheres and an improved sub-particle-scale model is applied to account for the effect of turbulence. The sub-particle-scale model is constructed based on the mixing-length assumption rather than the standard Smagorinsky approach to compute the eddy-viscosity. A robust in/out-flow boundary technique is also proposed to achieve stable uniform flow conditions at the inlet and outlet boundaries where the flow characteristics are unknown. The model is applied to simulate uniform open channel flows over a rough bed composed of regular spheres and validated by experimental velocity data. To investigate the influence of the bed roughness on different flow conditions, data from 12 experimental tests with different bed slopes and uniform water depths are simulated, and a good agreement has been observed between the model and experimental results of the streamwise velocity and turbulent shear stress. This shows that both the roughness effect and flow turbulence should be addressed in order to simulate the correct mechanisms of turbulent flow over a rough bed boundary and that the presented smoothed particle hydrodynamics model accomplishes this successfully. © 2016 The Authors International Journal for Numerical Methods in Fluids Published by John Wiley & Sons Ltd.
Structure and conformational dynamics of scaffolded DNA origami nanoparticles
2017-05-08
all-atom molecular dynamics and coarse-grained finite element modeling to DX-based nanoparticles to elucidate their fine-scale and global conforma... finite element (FE) modeling approach CanDo is also routinely used to predict the 3D equilibrium conformation of programmed DNA assemblies based on a...model with both experimental cryo-electron microscopy (cryo-EM) data and all-atom modeling. MATERIALS AND METHODS Lattice-free finite element model
Engelhardt, Benjamin; Kschischo, Maik; Fröhlich, Holger
2017-06-01
Ordinary differential equations (ODEs) are a popular approach to quantitatively model molecular networks based on biological knowledge. However, such knowledge is typically restricted. Wrongly modelled biological mechanisms as well as relevant external influence factors that are not included into the model are likely to manifest in major discrepancies between model predictions and experimental data. Finding the exact reasons for such observed discrepancies can be quite challenging in practice. In order to address this issue, we suggest a Bayesian approach to estimate hidden influences in ODE-based models. The method can distinguish between exogenous and endogenous hidden influences. Thus, we can detect wrongly specified as well as missed molecular interactions in the model. We demonstrate the performance of our Bayesian dynamic elastic-net with several ordinary differential equation models from the literature, such as human JAK-STAT signalling, information processing at the erythropoietin receptor, isomerization of liquid α -Pinene, G protein cycling in yeast and UV-B triggered signalling in plants. Moreover, we investigate a set of commonly known network motifs and a gene-regulatory network. Altogether our method supports the modeller in an algorithmic manner to identify possible sources of errors in ODE-based models on the basis of experimental data. © 2017 The Author(s).
Hu, Jing; Zhang, Xiaolong; Liu, Xiaoming; Tang, Jinshan
2015-06-01
Discovering hot regions in protein-protein interaction is important for drug and protein design, while experimental identification of hot regions is a time-consuming and labor-intensive effort; thus, the development of predictive models can be very helpful. In hot region prediction research, some models are based on structure information, and others are based on a protein interaction network. However, the prediction accuracy of these methods can still be improved. In this paper, a new method is proposed for hot region prediction, which combines density-based incremental clustering with feature-based classification. The method uses density-based incremental clustering to obtain rough hot regions, and uses feature-based classification to remove the non-hot spot residues from the rough hot regions. Experimental results show that the proposed method significantly improves the prediction performance of hot regions. Copyright © 2015 Elsevier Ltd. All rights reserved.
NASA Technical Reports Server (NTRS)
Salem, Jonathan A.
2002-01-01
A generalized reliability model was developed for use in the design of structural components made from brittle, homogeneous anisotropic materials such as single crystals. The model is based on the Weibull distribution and incorporates a variable strength distribution and any equivalent stress failure criteria. In addition to the reliability model, an energy based failure criterion for elastically anisotropic materials was formulated. The model is different from typical Weibull-based models in that it accounts for strength anisotropy arising from fracture toughness anisotropy and thereby allows for strength and reliability predictions of brittle, anisotropic single crystals subjected to multiaxial stresses. The model is also applicable to elastically isotropic materials exhibiting strength anisotropy due to an anisotropic distribution of flaws. In order to develop and experimentally verify the model, the uniaxial and biaxial strengths of a single crystal nickel aluminide were measured. The uniaxial strengths of the <100> and <110> crystal directions were measured in three and four-point flexure. The biaxial strength was measured by subjecting <100> plates to a uniform pressure in a test apparatus that was developed and experimentally verified. The biaxial strengths of the single crystal plates were estimated by extending and verifying the displacement solution for a circular, anisotropic plate to the case of a variable radius and thickness. The best correlation between the experimental strength data and the model predictions occurred when an anisotropic stress analysis was combined with the normal stress criterion and the strength parameters associated with the <110> crystal direction.
Helbling, Ignacio M; Ibarra, Juan C D; Luna, Julio A
2012-02-28
A mathematical modeling of controlled release of drug from one-layer torus-shaped devices is presented. Analytical solutions based on Refined Integral Method (RIM) are derived. The validity and utility of the model are ascertained by comparison of the simulation results with matrix-type vaginal rings experimental release data reported in the literature. For the comparisons, the pair-wise procedure is used to measure quantitatively the fit of the theoretical predictions to the experimental data. A good agreement between the model prediction and the experimental data is observed. A comparison with a previously reported model is also presented. More accurate results are achieved for small A/C(s) ratios. Copyright © 2011 Elsevier B.V. All rights reserved.
NASA Technical Reports Server (NTRS)
Zeitlin, C.; Heilbronn, L.; Miller, J.; Schimmerling, W.; Townsend, L. W.; Tripathi, R. K.; Wilson, J. W.
1996-01-01
The results of a Monte Carlo model for calculating fragment fluences and LET spectra are compared to data taken with 600 MeV/nucleon iron ions incident on an accelerator beamline configured for irradiation of biological samples, with no target and with 2, 5 and 8 cm of polyethylene. The model uses a multi-generation nuclear fragmentation code, coupled with a formulation of ionization energy loss based on the Bethe-Bloch equation. In the region where the data are reliable and the experimental acceptance is well understood, many of the features of the experimental spectra are well replicated by the model. To obtain good agreement with the experimental data, the model must allow for at least two generations of fragment production in the target.
ERIC Educational Resources Information Center
Broder, Arndt; Schutz, Julia
2009-01-01
Recent reviews of recognition receiver operating characteristics (ROCs) claim that their curvilinear shape rules out threshold models of recognition. However, the shape of ROCs based on confidence ratings is not diagnostic to refute threshold models, whereas ROCs based on experimental bias manipulations are. Also, fitting predicted frequencies to…
Modeling the Monthly Water Balance of a First Order Coastal Forested Watershed
S. V. Harder; Devendra M. Amatya; T. J. Callahan; Carl C. Trettin
2006-01-01
A study has been conducted to evaluate a spreadsheet-based conceptual Thornthwaite monthly water balance model and the process-based DRAINMOD model for their reliability in predicting monthly water budgets of a poorly drained, first order forested watershed at the Santee Experimental Forest located along the Lower Coastal Plain of South Carolina. Measured precipitation...
ERIC Educational Resources Information Center
Sripongwiwat, Supathida; Bunterm, Tassanee; Srisawat, Niwat; Tang, Keow Ngang
2016-01-01
The aim of this study was to examine the effect, after intervention on both experimental and control groups, of constructionism and neurocognitive-based teaching model, and conventional teaching model, on the science learning outcomes and creative thinking of Grade 11 students. The researchers developed a constructionism and neurocognitive-based…
ERIC Educational Resources Information Center
Zangori, Laura; Forbes, Cory T.; Schwarz, Christina V.
2015-01-01
Opportunities to generate model-based explanations are crucial for elementary students, yet are rarely foregrounded in elementary science learning environments despite evidence that early learners can reason from models when provided with scaffolding. We used a quasi-experimental research design to investigate the comparative impact of a scaffold…
Modeling Complex Marine Ecosystems: An Investigation of Two Teaching Approaches with Fifth Graders
ERIC Educational Resources Information Center
Papaevripidou, M.; Constantinou, C. P.; Zacharia, Z. C.
2007-01-01
This study investigated acquisition and transfer of the modeling ability of fifth graders in various domains. Teaching interventions concentrated on the topic of marine ecosystems either through a modeling-based approach or a worksheet-based approach. A quasi-experimental (pre-post comparison study) design was used. The control group (n = 17)…
NASA Astrophysics Data System (ADS)
Chhetri, Nikita; Chatterjee, Somenath
2018-01-01
Solar cells/photovoltaic, a renewable energy source, is appraised to be the most effective alternative to the conventional electrical energy generator. A cost-effective alternative of crystalline wafer-based solar cell is thin-film polycrystalline-based solar cell. This paper reports the numerical analysis of dependency of the solar cell parameters (i.e., efficiency, fill factor, open-circuit voltage and short-circuit current density) on grain size for thin-film-based polycrystalline silicon (Si) solar cells. A minority carrier lifetime model is proposed to do a correlation between the grains, grain boundaries and lifetime for thin-film-based polycrystalline Si solar cells in MATLAB environment. As observed, the increment in the grain size diameter results in increase in minority carrier lifetime in polycrystalline Si thin film. A non-equivalent series resistance double-diode model is used to find the dark as well as light (AM1.5) current-voltage (I-V) characteristics for thin-film-based polycrystalline Si solar cells. To optimize the effectiveness of the proposed model, a successive approximation method is used and the corresponding fitting parameters are obtained. The model is validated with the experimentally obtained results reported elsewhere. The experimentally reported solar cell parameters can be found using the proposed model described here.
A molecular-field-based similarity study of non-nucleoside HIV-1 reverse transcriptase inhibitors
NASA Astrophysics Data System (ADS)
Mestres, Jordi; Rohrer, Douglas C.; Maggiora, Gerald M.
1999-01-01
This article describes a molecular-field-based similarity method for aligning molecules by matching their steric and electrostatic fields and an application of the method to the alignment of three structurally diverse non-nucleoside HIV-1 reverse transcriptase inhibitors. A brief description of the method, as implemented in the program MIMIC, is presented, including a discussion of pairwise and multi-molecule similarity-based matching. The application provides an example that illustrates how relative binding orientations of molecules can be determined in the absence of detailed structural information on their target protein. In the particular system studied here, availability of the X-ray crystal structures of the respective ligand-protein complexes provides a means for constructing an 'experimental model' of the relative binding orientations of the three inhibitors. The experimental model is derived by using MIMIC to align the steric fields of the three protein P66 subunit main chains, producing an overlay with a 1.41 Å average rms distance between the corresponding Cα's in the three chains. The inter-chain residue similarities for the backbone structures show that the main-chain conformations are conserved in the region of the inhibitor-binding site, with the major deviations located primarily in the 'finger' and RNase H regions. The resulting inhibitor structure overlay provides an experimental-based model that can be used to evaluate the quality of the direct a priori inhibitor alignment obtained using MIMIC. It is found that the 'best' pairwise alignments do not always correspond to the experimental model alignments. Therefore, simply combining the best pairwise alignments will not necessarily produce the optimal multi-molecule alignment. However, the best simultaneous three-molecule alignment was found to reproduce the experimental inhibitor alignment model. A pairwise consistency index has been derived which gauges the quality of combining the pairwise alignments and aids in efficiently forming the optimal multi-molecule alignment analysis. Two post-alignment procedures are described that provide information on feature-based and field-based pharmacophoric patterns. The former corresponds to traditional pharmacophore models and is derived from the contribution of individual atoms to the total similarity. The latter is based on molecular regions rather than atoms and is constructed by computing the percent contribution to the similarity of individual points in a regular lattice surrounding the molecules, which when contoured and colored visually depict regions of highly conserved similarity. A discussion of how the information provided by each of the procedures is useful in drug design is also presented.
Modelling of the UV Index on vertical and 40° tilted planes for different orientations.
Serrano, D; Marín, M J; Utrillas, M P; Tena, F; Martínez-Lozano, J A
2012-02-01
In this study, estimated data of the UV Index on vertical planes are presented for the latitude of Valencia, Spain. For that purpose, the UVER values have been generated on vertical planes by means of four different geometrical models a) isotropic, b) Perez, c) Gueymard, d) Muneer, based on values of the global horizontal UVER and the diffuse horizontal UVER, measured experimentally. The UVER values, obtained by any model, overestimate the experimental values for all orientations, with the exception of the Perez model for the East plane. The results show statistical values of the MAD parameter (Mean Absolute Deviation) between 10% and 25%, the Perez model being the one that obtained a lower MAD for all levels. As for the statistic RMSD parameter (Root Mean Square Deviation), the results show values between 17% and 32%, and again the Perez model provides the best results in all vertical planes. The difference between the estimated UV Index and the experimental UV Index, for vertical and 40° tilted planes, was also calculated. 40° is an angle close to the latitude of Burjassot, Valencia, (39.5°), which, according to various studies, is the optimum angle to capture maximum radiation on tilted planes. We conclude that the models provide a good estimate of the UV Index, as they coincide or differ in one unit compared to the experimental values in 99% of cases, and this is valid for all orientations. Finally, we examined the relation between the UV Index on vertical and 40° tilted planes, both the experimental and estimated by the Perez model, and the experimental UV Index on a horizontal plane at 12 GMT. Based on the results, we can conclude that it is possible to estimate with a good approximation the UV Index on vertical and 40° tilted planes in different directions on the basis of the experimental horizontal UVI value, thus justifying the interest of this study. This journal is © The Royal Society of Chemistry and Owner Societies 2012
Estimation of Supercapacitor Energy Storage Based on Fractional Differential Equations.
Kopka, Ryszard
2017-12-22
In this paper, new results on using only voltage measurements on supercapacitor terminals for estimation of accumulated energy are presented. For this purpose, a study based on application of fractional-order models of supercapacitor charging/discharging circuits is undertaken. Parameter estimates of the models are then used to assess the amount of the energy accumulated in supercapacitor. The obtained results are compared with energy determined experimentally by measuring voltage and current on supercapacitor terminals. All the tests are repeated for various input signal shapes and parameters. Very high consistency between estimated and experimental results fully confirm suitability of the proposed approach and thus applicability of the fractional calculus to modelling of supercapacitor energy storage.
Simulated Students and Classroom Use of Model-Based Intelligent Tutoring
NASA Technical Reports Server (NTRS)
Koedinger, Kenneth R.
2008-01-01
Two educational uses of models and simulations: 1) Students create models and use simulations ; and 2) Researchers create models of learners to guide development of reliably effective materials. Cognitive tutors simulate and support tutoring - data is crucial to create effective model. Pittsburgh Science of Learning Center: Resources for modeling, authoring, experimentation. Repository of data and theory. Examples of advanced modeling efforts: SimStudent learns rule-based model. Help-seeking model: Tutors metacognition. Scooter uses machine learning detectors of student engagement.
System Identification of a Heaving Point Absorber: Design of Experiment and Device Modeling
Bacelli, Giorgio; Coe, Ryan; Patterson, David; ...
2017-04-01
Empirically based modeling is an essential aspect of design for a wave energy converter. These models are used in structural, mechanical and control design processes, as well as for performance prediction. The design of experiments and methods used to produce models from collected data have a strong impact on the quality of the model. This study considers the system identification and model validation process based on data collected from a wave tank test of a model-scale wave energy converter. Experimental design and data processing techniques based on general system identification procedures are discussed and compared with the practices often followedmore » for wave tank testing. The general system identification processes are shown to have a number of advantages. The experimental data is then used to produce multiple models for the dynamics of the device. These models are validated and their performance is compared against one and other. Furthermore, while most models of wave energy converters use a formulation with wave elevation as an input, this study shows that a model using a hull pressure sensor to incorporate the wave excitation phenomenon has better accuracy.« less
System Identification of a Heaving Point Absorber: Design of Experiment and Device Modeling
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bacelli, Giorgio; Coe, Ryan; Patterson, David
Empirically based modeling is an essential aspect of design for a wave energy converter. These models are used in structural, mechanical and control design processes, as well as for performance prediction. The design of experiments and methods used to produce models from collected data have a strong impact on the quality of the model. This study considers the system identification and model validation process based on data collected from a wave tank test of a model-scale wave energy converter. Experimental design and data processing techniques based on general system identification procedures are discussed and compared with the practices often followedmore » for wave tank testing. The general system identification processes are shown to have a number of advantages. The experimental data is then used to produce multiple models for the dynamics of the device. These models are validated and their performance is compared against one and other. Furthermore, while most models of wave energy converters use a formulation with wave elevation as an input, this study shows that a model using a hull pressure sensor to incorporate the wave excitation phenomenon has better accuracy.« less
Controlled experiments for dense gas diffusion: Experimental design and execution, model comparison
DOE Office of Scientific and Technical Information (OSTI.GOV)
Egami, R.; Bowen, J.; Coulombe, W.
1995-07-01
An experimental baseline CO2 release experiment at the DOE Spill Test Facility on the Nevada Test Site in Southern Nevada is described. This experiment was unique in its use of CO2 as a surrogate gas representative of a variety of specific chemicals. Introductory discussion places the experiment in historical perspective. CO2 was selected as a surrogate gas to provide a data base suitable for evaluation of model scenarios involving a variety of specific dense gases. The experiment design and setup are described, including design rationale and quality assurance methods employed. Resulting experimental data are summarized. Data usefulness is examined throughmore » a preliminary comparison of experimental results with simulations performed using the SLAV and DEGADIS dense gas models.« less
Simulation and analysis of a model dinoflagellate predator-prey system
NASA Astrophysics Data System (ADS)
Mazzoleni, M. J.; Antonelli, T.; Coyne, K. J.; Rossi, L. F.
2015-12-01
This paper analyzes the dynamics of a model dinoflagellate predator-prey system and uses simulations to validate theoretical and experimental studies. A simple model for predator-prey interactions is derived by drawing upon analogies from chemical kinetics. This model is then modified to account for inefficiencies in predation. Simulation results are shown to closely match the model predictions. Additional simulations are then run which are based on experimental observations of predatory dinoflagellate behavior, and this study specifically investigates how the predatory dinoflagellate Karlodinium veneficum uses toxins to immobilize its prey and increase its feeding rate. These simulations account for complex dynamics that were not included in the basic models, and the results from these computational simulations closely match the experimentally observed predatory behavior of K. veneficum and reinforce the notion that predatory dinoflagellates utilize toxins to increase their feeding rate.
Geng, Zongyu; Yang, Feng; Chen, Xi; Wu, Nianqiang
2016-01-01
It remains a challenge to accurately calibrate a sensor subject to environmental drift. The calibration task for such a sensor is to quantify the relationship between the sensor’s response and its exposure condition, which is specified by not only the analyte concentration but also the environmental factors such as temperature and humidity. This work developed a Gaussian Process (GP)-based procedure for the efficient calibration of sensors in drifting environments. Adopted as the calibration model, GP is not only able to capture the possibly nonlinear relationship between the sensor responses and the various exposure-condition factors, but also able to provide valid statistical inference for uncertainty quantification of the target estimates (e.g., the estimated analyte concentration of an unknown environment). Built on GP’s inference ability, an experimental design method was developed to achieve efficient sampling of calibration data in a batch sequential manner. The resulting calibration procedure, which integrates the GP-based modeling and experimental design, was applied on a simulated chemiresistor sensor to demonstrate its effectiveness and its efficiency over the traditional method. PMID:26924894
eSBMTools 1.0: enhanced native structure-based modeling tools.
Lutz, Benjamin; Sinner, Claude; Heuermann, Geertje; Verma, Abhinav; Schug, Alexander
2013-11-01
Molecular dynamics simulations provide detailed insights into the structure and function of biomolecular systems. Thus, they complement experimental measurements by giving access to experimentally inaccessible regimes. Among the different molecular dynamics techniques, native structure-based models (SBMs) are based on energy landscape theory and the principle of minimal frustration. Typically used in protein and RNA folding simulations, they coarse-grain the biomolecular system and/or simplify the Hamiltonian resulting in modest computational requirements while achieving high agreement with experimental data. eSBMTools streamlines running and evaluating SBM in a comprehensive package and offers high flexibility in adding experimental- or bioinformatics-derived restraints. We present a software package that allows setting up, modifying and evaluating SBM for both RNA and proteins. The implemented workflows include predicting protein complexes based on bioinformatics-derived inter-protein contact information, a standardized setup of protein folding simulations based on the common PDB format, calculating reaction coordinates and evaluating the simulation by free-energy calculations with weighted histogram analysis method or by phi-values. The modules interface with the molecular dynamics simulation program GROMACS. The package is open source and written in architecture-independent Python2. http://sourceforge.net/projects/esbmtools/. alexander.schug@kit.edu. Supplementary data are available at Bioinformatics online.
Modelling strategies to predict the multi-scale effects of rural land management change
NASA Astrophysics Data System (ADS)
Bulygina, N.; Ballard, C. E.; Jackson, B. M.; McIntyre, N.; Marshall, M.; Reynolds, B.; Wheater, H. S.
2011-12-01
Changes to the rural landscape due to agricultural land management are ubiquitous, yet predicting the multi-scale effects of land management change on hydrological response remains an important scientific challenge. Much empirical research has been of little generic value due to inadequate design and funding of monitoring programmes, while the modelling issues challenge the capability of data-based, conceptual and physics-based modelling approaches. In this paper we report on a major UK research programme, motivated by a national need to quantify effects of agricultural intensification on flood risk. Working with a consortium of farmers in upland Wales, a multi-scale experimental programme (from experimental plots to 2nd order catchments) was developed to address issues of upland agricultural intensification. This provided data support for a multi-scale modelling programme, in which highly detailed physics-based models were conditioned on the experimental data and used to explore effects of potential field-scale interventions. A meta-modelling strategy was developed to represent detailed modelling in a computationally-efficient manner for catchment-scale simulation; this allowed catchment-scale quantification of potential management options. For more general application to data-sparse areas, alternative approaches were needed. Physics-based models were developed for a range of upland management problems, including the restoration of drained peatlands, afforestation, and changing grazing practices. Their performance was explored using literature and surrogate data; although subject to high levels of uncertainty, important insights were obtained, of practical relevance to management decisions. In parallel, regionalised conceptual modelling was used to explore the potential of indices of catchment response, conditioned on readily-available catchment characteristics, to represent ungauged catchments subject to land management change. Although based in part on speculative relationships, significant predictive power was derived from this approach. Finally, using a formal Bayesian procedure, these different sources of information were combined with local flow data in a catchment-scale conceptual model application , i.e. using small-scale physical properties, regionalised signatures of flow and available flow measurements.
Flexoelectricity in Nanostructures: Theory, Nanofabrication and Characterization
2017-09-13
public release; distribution is unlimited. Major Goals: The objective of this project is to investigate, theoretically and experimentally , the... experimental approach. Accomplishments: In this report, we investigated the thermal polarization effect where the temperature- dependent dielectric...through an analytical model, which was experimentally verified. Secondly, based on the existence of the converse flexoelectric effect in materials, BST
Exploring Experimental Design: An Excel-Based Simulation Using Steller Sea Lion Behavior
ERIC Educational Resources Information Center
Ryan, Wendy L.; St. Iago-McRae, Ezry
2016-01-01
Experimentation is the foundation of science and an important process for students to understand and experience. However, it can be difficult to teach some aspects of experimentation within the time and resource constraints of an academic semester. Interactive models can be a useful tool in bridging this gap. This freely accessible simulation…
Square and rectangular concrete columns confined by CFRP: Experimental and numerical investigation
NASA Astrophysics Data System (ADS)
Monti, G.; Nistico, N.
2008-05-01
The results of an experimental and theoretical investigation into the deformation behavior of CFRP-confined square and rectangular concrete columns under axial loads are presented. Three types of columns are considered: unwrapped; fully wrapped; and fully wrapped, with L-slaped steel angles placed at the corners. A mechanical deformation model for them is proposed, which is based on a nonuniform distribution of the stresses caused by the confining device. The results given by the model are in a good agreement with the experimental results obtained.
NASA Astrophysics Data System (ADS)
Shurupov, A. V.; Zavalova, V. E.; Kozlov, A. V.; Shurupov, M. A.; Povareshkin, M. N.; Kozlov, A. A.; Shurupova, N. P.
2018-01-01
Experimental models of microsecond duration powerful generators of current pulses on the basis of explosive magnetic generators and voltage impulse generator have been developed for the electromagnetic pulse effects on energy facilities to verify their stability. Exacerbation of voltage pulse carried out through the use of electro explosive current interrupter made of copper wires with diameters of 80 and 120 μm. Experimental results of these models investigation are represented. Voltage fronts about 100 ns and the electric field strength of 800 kV/m are registered.
QCT/FEA predictions of femoral stiffness are strongly affected by boundary condition modeling
Rossman, Timothy; Kushvaha, Vinod; Dragomir-Daescu, Dan
2015-01-01
Quantitative computed tomography-based finite element models of proximal femora must be validated with cadaveric experiments before using them to assess fracture risk in osteoporotic patients. During validation it is essential to carefully assess whether the boundary condition modeling matches the experimental conditions. This study evaluated proximal femur stiffness results predicted by six different boundary condition methods on a sample of 30 cadaveric femora and compared the predictions with experimental data. The average stiffness varied by 280% among the six boundary conditions. Compared with experimental data the predictions ranged from overestimating the average stiffness by 65% to underestimating it by 41%. In addition we found that the boundary condition that distributed the load to the contact surfaces similar to the expected contact mechanics predictions had the best agreement with experimental stiffness. We concluded that boundary conditions modeling introduced large variations in proximal femora stiffness predictions. PMID:25804260
2017-03-30
experimental evaluations for hosting DDDAS-like applications in public cloud infrastructures . Finally, we report on ongoing work towards using the DDDAS...developed and their experimental evaluations for hosting DDDAS-like applications in public cloud infrastructures . Finally, we report on ongoing work towards...Dynamic resource management, model learning, simulation-based optimizations, cloud infrastructures for DDDAS applications. I. INTRODUCTION Critical cyber
ERIC Educational Resources Information Center
Yurt, Eyup; Sunbul, Ali Murat
2012-01-01
In this study, the effect of modeling based activities using virtual environments and concrete objects on spatial thinking and mental rotation skills was investigated. The study was designed as a pretest-posttest model with a control group, which is one of the experimental research models. The study was carried out on sixth grade students…
ERIC Educational Resources Information Center
Choi, Jeong Hoon; Meisenheimer, Jessica M.; McCart, Amy B.; Sailor, Wayne
2017-01-01
The present investigation examines the schoolwide applications model (SAM) as a potentially effective school reform model for increasing equity-based inclusive education practices while enhancing student reading and math achievement for all students. A 3-year quasi-experimental comparison group analysis using latent growth modeling (LGM) was used…
NASA Astrophysics Data System (ADS)
Hamid, H.
2018-01-01
The purpose of this study is to analyze an improvement of students’ mathematical critical thinking (CT) ability in Real Analysis course by using Rigorous Teaching and Learning (RTL) model with informal argument. In addition, this research also attempted to understand students’ CT on their initial mathematical ability (IMA). This study was conducted at a private university in academic year 2015/2016. The study employed the quasi-experimental method with pretest-posttest control group design. The participants of the study were 83 students in which 43 students were in the experimental group and 40 students were in the control group. The finding of the study showed that students in experimental group outperformed students in control group on mathematical CT ability based on their IMA (high, medium, low) in learning Real Analysis. In addition, based on medium IMA the improvement of mathematical CT ability of students who were exposed to RTL model with informal argument was greater than that of students who were exposed to CI (conventional instruction). There was also no effect of interaction between RTL model and CI model with both (high, medium, and low) IMA increased mathematical CT ability. Finally, based on (high, medium, and low) IMA there was a significant improvement in the achievement of all indicators of mathematical CT ability of students who were exposed to RTL model with informal argument than that of students who were exposed to CI.
Frost formation on an airfoil: A mathematical model 1
NASA Technical Reports Server (NTRS)
Dietenberger, M.; Kumar, P.; Luers, J.
1979-01-01
A computer model to predict the frost formation process on a flat plate was developed for application to most environmental conditions under which frost occurs. The model was analytically based on a generalized frost thermal conductivity expression, on frost density and thickness rate equations, and on modified heat and mass transfer coefficients designed to fit the available experimental data. The broad experimental ranges reflected by the extremes in ambient humidities, wall temperatures, and convective flow properties in the various publications which were examined served to severely test the flexibility of the model. An efficient numerical integration scheme was developed to solve for the frost surface temperature, density, and thickness under the changing environmental conditions. The comparison of results with experimental data was very encouraging.
Modular, Semantics-Based Composition of Biosimulation Models
ERIC Educational Resources Information Center
Neal, Maxwell Lewis
2010-01-01
Biosimulation models are valuable, versatile tools used for hypothesis generation and testing, codification of biological theory, education, and patient-specific modeling. Driven by recent advances in computational power and the accumulation of systems-level experimental data, modelers today are creating models with an unprecedented level of…
NASA Astrophysics Data System (ADS)
Hufner, D. R.; Augustine, M. R.
2018-05-01
A novel experimental method was developed to simulate underwater explosion pressure pulses within a laboratory environment. An impact-based experimental apparatus was constructed; capable of generating pressure pulses with basic character similar to underwater explosions, while also allowing the pulse to be tuned to different intensities. Having the capability to vary the shock impulse was considered essential to producing various levels of shock-induced damage without the need to modify the fixture. The experimental apparatus and test method are considered ideal for investigating the shock response of composite material systems and/or experimental validation of new material models. One such test program is presented herein, in which a series of E-glass/Vinylester laminates were subjected to a range of shock pulses that induced varying degrees of damage. Analysis-test correlations were performed using a rate-dependent constitutive model capable of representing anisotropic damage and ultimate yarn failure. Agreement between analytical predictions and experimental results was considered acceptable.
Moving object detection using dynamic motion modelling from UAV aerial images.
Saif, A F M Saifuddin; Prabuwono, Anton Satria; Mahayuddin, Zainal Rasyid
2014-01-01
Motion analysis based moving object detection from UAV aerial image is still an unsolved issue due to inconsideration of proper motion estimation. Existing moving object detection approaches from UAV aerial images did not deal with motion based pixel intensity measurement to detect moving object robustly. Besides current research on moving object detection from UAV aerial images mostly depends on either frame difference or segmentation approach separately. There are two main purposes for this research: firstly to develop a new motion model called DMM (dynamic motion model) and secondly to apply the proposed segmentation approach SUED (segmentation using edge based dilation) using frame difference embedded together with DMM model. The proposed DMM model provides effective search windows based on the highest pixel intensity to segment only specific area for moving object rather than searching the whole area of the frame using SUED. At each stage of the proposed scheme, experimental fusion of the DMM and SUED produces extracted moving objects faithfully. Experimental result reveals that the proposed DMM and SUED have successfully demonstrated the validity of the proposed methodology.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Horstemeyer, Mark R.; Chaudhuri, Santanu
2015-09-30
A multiscale modeling Internal State Variable (ISV) constitutive model was developed that captures the fundamental structure-property relationships. The macroscale ISV model used lower length scale simulations (Butler-Volmer and Electronics Structures results) in order to inform the ISVs at the macroscale. The chemomechanical ISV model was calibrated and validated from experiments with magnesium (Mg) alloys that were investigated under corrosive environments coupled with experimental electrochemical studies. Because the ISV chemomechanical model is physically based, it can be used for other material systems to predict corrosion behavior. As such, others can use the chemomechanical model for analyzing corrosion effects on their designs.
Puente, Gabriela F; Urteaga, Raúl; Bonetto, Fabián J
2005-10-01
We performed a comprehensive numerical and experimental analysis of dissociation effects in an air bubble in water acoustically levitated in a spherical resonator. Our numerical approach is based on suitable models for the different effects considered. We compared model predictions with experimental results obtained in our laboratory in the whole phase parameter space, for acoustic pressures from the bubble dissolution limit up to bubble extinction. The effects were taken into account simultaneously to consider the transition from nonsonoluminescence to sonoluminescence bubbles. The model includes (1) inside the bubble, transient and spatially nonuniform heat transfer using a collocation points method, dissociation of O2 and N2, and mass diffusion of vapor in the noncondensable gases; (2) at the bubble interface, nonequilibrium evaporation and condensation of water and a temperature jump due to the accommodation coefficient; (3) in the liquid, transient and spatially nonuniform heat transfer using a collocation points method, and mass diffusion of the gas in the liquid. The model is completed with a Rayleigh-Plesset equation with liquid compressible terms and vapor mass transfer. We computed the boundary for the shape instability based on the temporal evolution of the computed radius. The model is valid for an arbitrary number of dissociable gases dissolved in the liquid. We also obtained absolute measurements for R(t) using two photodetectors and Mie scattering calculations. The robust technique used allows the estimation of experimental results of absolute R0 and P(a). The technique is based on identifying the bubble dissolution limit coincident with the parametric instability in (P(a),R0) parameter space. We take advantage of the fact that this point can be determined experimentally with high precision and replicability. We computed the equilibrium concentration of the different gaseous species and water vapor during collapse as a function of P(a) and R0. The model obtains from first principles the result that in sonoluminescence the bubble is practically 100% argon for air dissolved in water. Therefore, the dissociation reactions in air bubbles must be taken into account for quantitative computations of maximum temperatures. The agreement found between the numerical and experimental data is very good in the whole parameter space explored. We do not fit any parameter in the model. We believe that we capture all the relevant physics with the model.
Development of a Computationally Efficient, High Fidelity, Finite Element Based Hall Thruster Model
NASA Technical Reports Server (NTRS)
Jacobson, David (Technical Monitor); Roy, Subrata
2004-01-01
This report documents the development of a two dimensional finite element based numerical model for efficient characterization of the Hall thruster plasma dynamics in the framework of multi-fluid model. Effect of the ionization and the recombination has been included in the present model. Based on the experimental data, a third order polynomial in electron temperature is used to calculate the ionization rate. The neutral dynamics is included only through the neutral continuity equation in the presence of a uniform neutral flow. The electrons are modeled as magnetized and hot, whereas ions are assumed magnetized and cold. The dynamics of Hall thruster is also investigated in the presence of plasma-wall interaction. The plasma-wall interaction is a function of wall potential, which in turn is determined by the secondary electron emission and sputtering yield. The effect of secondary electron emission and sputter yield has been considered simultaneously, Simulation results are interpreted in the light of experimental observations and available numerical solutions in the literature.
NASA Astrophysics Data System (ADS)
Andreaus, Ugo; Spagnuolo, Mario; Lekszycki, Tomasz; Eugster, Simon R.
2018-04-01
We present a finite element discrete model for pantographic lattices, based on a continuous Euler-Bernoulli beam for modeling the fibers composing the pantographic sheet. This model takes into account large displacements, rotations and deformations; the Euler-Bernoulli beam is described by using nonlinear interpolation functions, a Green-Lagrange strain for elongation and a curvature depending on elongation. On the basis of the introduced discrete model of a pantographic lattice, we perform some numerical simulations. We then compare the obtained results to an experimental BIAS extension test on a pantograph printed with polyamide PA2200. The pantographic structures involved in the numerical as well as in the experimental investigations are not proper fabrics: They are composed by just a few fibers for theoretically allowing the use of the Euler-Bernoulli beam theory in the description of the fibers. We compare the experiments to numerical simulations in which we allow the fibers to elastically slide one with respect to the other in correspondence of the interconnecting pivot. We present as result a very good agreement between the numerical simulation, based on the introduced model, and the experimental measures.
Characterization of piezoelectric device for implanted pacemaker energy harvesting
NASA Astrophysics Data System (ADS)
Jay, Sunny; Caballero, Manuel; Quinn, William; Barrett, John; Hill, Martin
2016-10-01
Novel implanted cardiac pacemakers that are powered by energy harvesters driven by the cardiac motion and have a 40 year lifetime are currently under development. To satisfy space constraints and energy requirements of the device, silicon-based MEMS energy harvesters are being developed in the EU project (MANpower1). Such MEMS harvesters for vibration frequencies below 50 Hz have not been widely reported. In this paper, an analytical model and a 3D finite element model (FEM) to predict displacement and open circuit voltage, validated through experimental analysis using an off-the-shelf low frequency energy harvester, are presented. The harvester was excited through constant amplitude sinusoidal base displacement over a range of 20 to 70 Hz passing through its first mode natural frequency at 47 Hz. At resonance both models predict displacements with an error of less than 2% when compared to the experimental result. Comparing the two models, the application of the experimentally measured damping ratio differs for accurate displacement prediction and the differences in symmetry in the measured and modelled displacement and voltage data around the resonance frequency indicate the two piezoelectric voltage models use different fundamental equations.
Jbabdi, Saad; Sotiropoulos, Stamatios N; Savio, Alexander M; Graña, Manuel; Behrens, Timothy EJ
2012-01-01
In this article, we highlight an issue that arises when using multiple b-values in a model-based analysis of diffusion MR data for tractography. The non-mono-exponential decay, commonly observed in experimental data, is shown to induce over-fitting in the distribution of fibre orientations when not considered in the model. Extra fibre orientations perpendicular to the main orientation arise to compensate for the slower apparent signal decay at higher b-values. We propose a simple extension to the ball and stick model based on a continuous Gamma distribution of diffusivities, which significantly improves the fitting and reduces the over-fitting. Using in-vivo experimental data, we show that this model outperforms a simpler, noise floor model, especially at the interfaces between brain tissues, suggesting that partial volume effects are a major cause of the observed non-mono-exponential decay. This model may be helpful for future data acquisition strategies that may attempt to combine multiple shells to improve estimates of fibre orientations in white matter and near the cortex. PMID:22334356
Mutant mice: experimental organisms as materialised models in biomedicine.
Huber, Lara; Keuck, Lara K
2013-09-01
Animal models have received particular attention as key examples of material models. In this paper, we argue that the specificities of establishing animal models-acknowledging their status as living beings and as epistemological tools-necessitate a more complex account of animal models as materialised models. This becomes particularly evident in animal-based models of diseases that only occur in humans: in these cases, the representational relation between animal model and human patient needs to be generated and validated. The first part of this paper presents an account of how disease-specific animal models are established by drawing on the example of transgenic mice models for Alzheimer's disease. We will introduce an account of validation that involves a three-fold process including (1) from human being to experimental organism; (2) from experimental organism to animal model; and (3) from animal model to human patient. This process draws upon clinical relevance as much as scientific practices and results in disease-specific, yet incomplete, animal models. The second part of this paper argues that the incompleteness of models can be described in terms of multi-level abstractions. We qualify this notion by pointing to different experimental techniques and targets of modelling, which give rise to a plurality of models for a specific disease. Copyright © 2013 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Gambino, James; Tarver, Craig; Springer, H. Keo; White, Bradley; Fried, Laurence
2017-06-01
We present a novel method for optimizing parameters of the Ignition and Growth reactive flow (I&G) model for high explosives. The I&G model can yield accurate predictions of experimental observations. However, calibrating the model is a time-consuming task especially with multiple experiments. In this study, we couple the differential evolution global optimization algorithm to simulations of shock initiation experiments in the multi-physics code ALE3D. We develop parameter sets for HMX based explosives LX-07 and LX-10. The optimization finds the I&G model parameters that globally minimize the difference between calculated and experimental shock time of arrival at embedded pressure gauges. This work was performed under the auspices of the U.S. DOE by LLNL under contract DE-AC52-07NA27344. LLNS, LLC LLNL-ABS- 724898.
Snitkin, Evan S; Dudley, Aimée M; Janse, Daniel M; Wong, Kaisheen; Church, George M; Segrè, Daniel
2008-01-01
Background Understanding the response of complex biochemical networks to genetic perturbations and environmental variability is a fundamental challenge in biology. Integration of high-throughput experimental assays and genome-scale computational methods is likely to produce insight otherwise unreachable, but specific examples of such integration have only begun to be explored. Results In this study, we measured growth phenotypes of 465 Saccharomyces cerevisiae gene deletion mutants under 16 metabolically relevant conditions and integrated them with the corresponding flux balance model predictions. We first used discordance between experimental results and model predictions to guide a stage of experimental refinement, which resulted in a significant improvement in the quality of the experimental data. Next, we used discordance still present in the refined experimental data to assess the reliability of yeast metabolism models under different conditions. In addition to estimating predictive capacity based on growth phenotypes, we sought to explain these discordances by examining predicted flux distributions visualized through a new, freely available platform. This analysis led to insight into the glycerol utilization pathway and the potential effects of metabolic shortcuts on model results. Finally, we used model predictions and experimental data to discriminate between alternative raffinose catabolism routes. Conclusions Our study demonstrates how a new level of integration between high throughput measurements and flux balance model predictions can improve understanding of both experimental and computational results. The added value of a joint analysis is a more reliable platform for specific testing of biological hypotheses, such as the catabolic routes of different carbon sources. PMID:18808699
NASA Technical Reports Server (NTRS)
Meitner, P. L.; Glassman, A. J.
1980-01-01
An off-design performance loss model is developed for variable-area (pivoted vane) radial turbines. The variation in stator loss with stator area is determined by a viscous loss model while the variation in rotor loss due to stator area variation (for no stator end-clearance gap) is determined through analytical matching of experimental data. An incidence loss model is also based on matching of the experimental data. A stator vane end-clearance leakage model is developed and sample calculations are made to show the predicted effects of stator vane end-clearance leakage on performance.
Fatigue Assessment of Nickel-Titanium Peripheral Stents: Comparison of Multi-Axial Fatigue Models
NASA Astrophysics Data System (ADS)
Allegretti, Dario; Berti, Francesca; Migliavacca, Francesco; Pennati, Giancarlo; Petrini, Lorenza
2018-03-01
Peripheral Nickel-Titanium (NiTi) stents exploit super-elasticity to treat femoropopliteal artery atherosclerosis. The stent is subject to cyclic loads, which may lead to fatigue fracture and treatment failure. The complexity of the loading conditions and device geometry, coupled with the nonlinear material behavior, may induce multi-axial and non-proportional deformation. Finite element analysis can assess the fatigue risk, by comparing the device state of stress with the material fatigue limit. The most suitable fatigue model is not fully understood for NiTi devices, due to its complex thermo-mechanical behavior. This paper assesses the fatigue behavior of NiTi stents through computational models and experimental validation. Four different strain-based models are considered: the von Mises criterion and three critical plane models (Fatemi-Socie, Brown-Miller, and Smith-Watson-Topper models). Two stents, made of the same material with different cell geometries are manufactured, and their fatigue behavior is experimentally characterized. The comparison between experimental and numerical results highlights an overestimation of the failure risk by the von Mises criterion. On the contrary, the selected critical plane models, even if based on different damage mechanisms, give a better fatigue life estimation. Further investigations on crack propagation mechanisms of NiTi stents are required to properly select the most reliable fatigue model.
Fatigue Assessment of Nickel-Titanium Peripheral Stents: Comparison of Multi-Axial Fatigue Models
NASA Astrophysics Data System (ADS)
Allegretti, Dario; Berti, Francesca; Migliavacca, Francesco; Pennati, Giancarlo; Petrini, Lorenza
2018-02-01
Peripheral Nickel-Titanium (NiTi) stents exploit super-elasticity to treat femoropopliteal artery atherosclerosis. The stent is subject to cyclic loads, which may lead to fatigue fracture and treatment failure. The complexity of the loading conditions and device geometry, coupled with the nonlinear material behavior, may induce multi-axial and non-proportional deformation. Finite element analysis can assess the fatigue risk, by comparing the device state of stress with the material fatigue limit. The most suitable fatigue model is not fully understood for NiTi devices, due to its complex thermo-mechanical behavior. This paper assesses the fatigue behavior of NiTi stents through computational models and experimental validation. Four different strain-based models are considered: the von Mises criterion and three critical plane models (Fatemi-Socie, Brown-Miller, and Smith-Watson-Topper models). Two stents, made of the same material with different cell geometries are manufactured, and their fatigue behavior is experimentally characterized. The comparison between experimental and numerical results highlights an overestimation of the failure risk by the von Mises criterion. On the contrary, the selected critical plane models, even if based on different damage mechanisms, give a better fatigue life estimation. Further investigations on crack propagation mechanisms of NiTi stents are required to properly select the most reliable fatigue model.
Automatic Parametrization of Somatosensory Evoked Potentials With Chirp Modeling.
Vayrynen, Eero; Noponen, Kai; Vipin, Ashwati; Thow, X Y; Al-Nashash, Hasan; Kortelainen, Jukka; All, Angelo
2016-09-01
In this paper, an approach using polynomial phase chirp signals to model somatosensory evoked potentials (SEPs) is proposed. SEP waveforms are assumed as impulses undergoing group velocity dispersion while propagating along a multipath neural connection. Mathematical analysis of pulse dispersion resulting in chirp signals is performed. An automatic parameterization of SEPs is proposed using chirp models. A Particle Swarm Optimization algorithm is used to optimize the model parameters. Features describing the latencies and amplitudes of SEPs are automatically derived. A rat model is then used to evaluate the automatic parameterization of SEPs in two experimental cases, i.e., anesthesia level and spinal cord injury (SCI). Experimental results show that chirp-based model parameters and the derived SEP features are significant in describing both anesthesia level and SCI changes. The proposed automatic optimization based approach for extracting chirp parameters offers potential for detailed SEP analysis in future studies. The method implementation in Matlab technical computing language is provided online.
ERIC Educational Resources Information Center
Hirsch, Jorge E.; Scalapino, Douglas J.
1983-01-01
Discusses ways computers are being used in condensed-matter physics by experimenters and theorists. Experimenters use them to control experiments and to gather and analyze data. Theorists use them for detailed predictions based on realistic models and for studies on systems not realizable in practice. (JN)
Experimental Evaluation of the Thermal Performance of a Water Shield for a Surface Power Reactor
NASA Technical Reports Server (NTRS)
Pearson, J. Boise; Stewart, Eric T.; Reid, Robert S.
2007-01-01
A water based shielding system is being investigated for use on initial lunar surface power systems. The use of water may lower overall cost (as compared to development cost for other materials) and simplify operations in the setup and handling. The thermal hydraulic performance of the shield is of significant interest. The mechanism for transferring heat through the shield is natural convection. Natural convection in a representative lunar surface reactor shield design is evaluated at various power levels in the Water Shield Testbed (WST) at the NASA Marshall Space Flight Center. The experimental data from the WST is used to anchor a CFD model. Performance of a water shield on the lunar surface is then predicted by CFD models anchored to test data. The accompanying viewgraph presentation includes the following topics: 1) Testbed Configuration; 2) Core Heater Placement and Instrumentation; 3) Thermocouple Placement; 4) Core Thermocouple Placement; 5) Outer Tank Thermocouple Placement; 6) Integrated Testbed; 7) Methodology; 8) Experimental Results: Core Temperatures; 9) Experimental Results; Outer Tank Temperatures; 10) CFD Modeling; 11) CFD Model: Anchored to Experimental Results (1-g); 12) CFD MOdel: Prediction for 1/6-g; and 13) CFD Model: Comparison of 1-g to 1/6-g.
The Role of Additional Pulses in Electropermeabilization Protocols
Suárez, Cecilia; Soba, Alejandro; Maglietti, Felipe; Olaiz, Nahuel; Marshall, Guillermo
2014-01-01
Electropermeabilization (EP) based protocols such as those applied in medicine, food processing or environmental management, are well established and widely used. The applied voltage, as well as tissue electric conductivity, are of utmost importance for assessing final electropermeabilized area and thus EP effectiveness. Experimental results from literature report that, under certain EP protocols, consecutive pulses increase tissue electric conductivity and even the permeabilization amount. Here we introduce a theoretical model that takes into account this effect in the application of an EP-based protocol, and its validation with experimental measurements. The theoretical model describes the electric field distribution by a nonlinear Laplace equation with a variable conductivity coefficient depending on the electric field, the temperature and the quantity of pulses, and the Penne's Bioheat equation for temperature variations. In the experiments, a vegetable tissue model (potato slice) is used for measuring electric currents and tissue electropermeabilized area in different EP protocols. Experimental measurements show that, during sequential pulses and keeping constant the applied voltage, the electric current density and the blackened (electropermeabilized) area increase. This behavior can only be attributed to a rise in the electric conductivity due to a higher number of pulses. Accordingly, we present a theoretical modeling of an EP protocol that predicts correctly the increment in the electric current density observed experimentally during the addition of pulses. The model also demonstrates that the electric current increase is due to a rise in the electric conductivity, in turn induced by temperature and pulse number, with no significant changes in the electric field distribution. The EP model introduced, based on a novel formulation of the electric conductivity, leads to a more realistic description of the EP phenomenon, hopefully providing more accurate predictions of treatment outcomes. PMID:25437512
NASA Astrophysics Data System (ADS)
Frollo, Ivan; Krafčík, Andrej; Andris, Peter; Přibil, Jiří; Dermek, Tomáš
2015-12-01
Circular samples are the frequent objects of "in-vitro" investigation using imaging method based on magnetic resonance principles. The goal of our investigation is imaging of thin planar layers without using the slide selection procedure, thus only 2D imaging or imaging of selected layers of samples in circular vessels, eppendorf tubes,.. compulsorily using procedure "slide selection". In spite of that the standard imaging methods was used, some specificity arise when mathematical modeling of these procedure is introduced. In the paper several mathematical models were presented that were compared with real experimental results. Circular magnetic samples were placed into the homogenous magnetic field of a low field imager based on nuclear magnetic resonance. For experimental verification an MRI 0.178 Tesla ESAOTE Opera imager was used.
Modelling irradiation-induced softening in BCC iron by crystal plasticity approach
NASA Astrophysics Data System (ADS)
Xiao, Xiazi; Terentyev, Dmitry; Yu, Long; Song, Dingkun; Bakaev, A.; Duan, Huiling
2015-11-01
Crystal plasticity model (CPM) for BCC iron to account for radiation-induced strain softening is proposed. CPM is based on the plastically-driven and thermally-activated removal of dislocation loops. Atomistic simulations are applied to parameterize dislocation-defect interactions. Combining experimental microstructures, defect-hardening/absorption rules from atomistic simulations, and CPM fitted to properties of non-irradiated iron, the model achieves a good agreement with experimental data regarding radiation-induced strain softening and flow stress increase under neutron irradiation.
Control of experimental uncertainties in filtered Rayleigh scattering measurements
NASA Technical Reports Server (NTRS)
Forkey, Joseph N.; Finkelstein, N. D.; Lempert, Walter R.; Miles, Richard B.
1995-01-01
Filtered Rayleigh Scattering is a technique which allows for measurement of velocity, temperature, and pressure in unseeded flows, spatially resolved in 2-dimensions. We present an overview of the major components of a Filtered Rayleigh Scattering system. In particular, we develop and discuss a detailed theoretical model along with associated model parameters and related uncertainties. Based on this model, we then present experimental results for ambient room air and for a Mach 2 free jet, including spatially resolved measurements of velocity, temperature, and pressure.
Data-driven reverse engineering of signaling pathways using ensembles of dynamic models.
Henriques, David; Villaverde, Alejandro F; Rocha, Miguel; Saez-Rodriguez, Julio; Banga, Julio R
2017-02-01
Despite significant efforts and remarkable progress, the inference of signaling networks from experimental data remains very challenging. The problem is particularly difficult when the objective is to obtain a dynamic model capable of predicting the effect of novel perturbations not considered during model training. The problem is ill-posed due to the nonlinear nature of these systems, the fact that only a fraction of the involved proteins and their post-translational modifications can be measured, and limitations on the technologies used for growing cells in vitro, perturbing them, and measuring their variations. As a consequence, there is a pervasive lack of identifiability. To overcome these issues, we present a methodology called SELDOM (enSEmbLe of Dynamic lOgic-based Models), which builds an ensemble of logic-based dynamic models, trains them to experimental data, and combines their individual simulations into an ensemble prediction. It also includes a model reduction step to prune spurious interactions and mitigate overfitting. SELDOM is a data-driven method, in the sense that it does not require any prior knowledge of the system: the interaction networks that act as scaffolds for the dynamic models are inferred from data using mutual information. We have tested SELDOM on a number of experimental and in silico signal transduction case-studies, including the recent HPN-DREAM breast cancer challenge. We found that its performance is highly competitive compared to state-of-the-art methods for the purpose of recovering network topology. More importantly, the utility of SELDOM goes beyond basic network inference (i.e. uncovering static interaction networks): it builds dynamic (based on ordinary differential equation) models, which can be used for mechanistic interpretations and reliable dynamic predictions in new experimental conditions (i.e. not used in the training). For this task, SELDOM's ensemble prediction is not only consistently better than predictions from individual models, but also often outperforms the state of the art represented by the methods used in the HPN-DREAM challenge.
Data-driven reverse engineering of signaling pathways using ensembles of dynamic models
Henriques, David; Villaverde, Alejandro F.; Banga, Julio R.
2017-01-01
Despite significant efforts and remarkable progress, the inference of signaling networks from experimental data remains very challenging. The problem is particularly difficult when the objective is to obtain a dynamic model capable of predicting the effect of novel perturbations not considered during model training. The problem is ill-posed due to the nonlinear nature of these systems, the fact that only a fraction of the involved proteins and their post-translational modifications can be measured, and limitations on the technologies used for growing cells in vitro, perturbing them, and measuring their variations. As a consequence, there is a pervasive lack of identifiability. To overcome these issues, we present a methodology called SELDOM (enSEmbLe of Dynamic lOgic-based Models), which builds an ensemble of logic-based dynamic models, trains them to experimental data, and combines their individual simulations into an ensemble prediction. It also includes a model reduction step to prune spurious interactions and mitigate overfitting. SELDOM is a data-driven method, in the sense that it does not require any prior knowledge of the system: the interaction networks that act as scaffolds for the dynamic models are inferred from data using mutual information. We have tested SELDOM on a number of experimental and in silico signal transduction case-studies, including the recent HPN-DREAM breast cancer challenge. We found that its performance is highly competitive compared to state-of-the-art methods for the purpose of recovering network topology. More importantly, the utility of SELDOM goes beyond basic network inference (i.e. uncovering static interaction networks): it builds dynamic (based on ordinary differential equation) models, which can be used for mechanistic interpretations and reliable dynamic predictions in new experimental conditions (i.e. not used in the training). For this task, SELDOM’s ensemble prediction is not only consistently better than predictions from individual models, but also often outperforms the state of the art represented by the methods used in the HPN-DREAM challenge. PMID:28166222
Cheng, Mingjian; Guo, Ya; Li, Jiangting; Zheng, Xiaotong; Guo, Lixin
2018-04-20
We introduce an alternative distribution to the gamma-gamma (GG) distribution, called inverse Gaussian gamma (IGG) distribution, which can efficiently describe moderate-to-strong irradiance fluctuations. The proposed stochastic model is based on a modulation process between small- and large-scale irradiance fluctuations, which are modeled by gamma and inverse Gaussian distributions, respectively. The model parameters of the IGG distribution are directly related to atmospheric parameters. The accuracy of the fit among the IGG, log-normal, and GG distributions with the experimental probability density functions in moderate-to-strong turbulence are compared, and results indicate that the newly proposed IGG model provides an excellent fit to the experimental data. As the receiving diameter is comparable with the atmospheric coherence radius, the proposed IGG model can reproduce the shape of the experimental data, whereas the GG and LN models fail to match the experimental data. The fundamental channel statistics of a free-space optical communication system are also investigated in an IGG-distributed turbulent atmosphere, and a closed-form expression for the outage probability of the system is derived with Meijer's G-function.
Metainference: A Bayesian inference method for heterogeneous systems.
Bonomi, Massimiliano; Camilloni, Carlo; Cavalli, Andrea; Vendruscolo, Michele
2016-01-01
Modeling a complex system is almost invariably a challenging task. The incorporation of experimental observations can be used to improve the quality of a model and thus to obtain better predictions about the behavior of the corresponding system. This approach, however, is affected by a variety of different errors, especially when a system simultaneously populates an ensemble of different states and experimental data are measured as averages over such states. To address this problem, we present a Bayesian inference method, called "metainference," that is able to deal with errors in experimental measurements and with experimental measurements averaged over multiple states. To achieve this goal, metainference models a finite sample of the distribution of models using a replica approach, in the spirit of the replica-averaging modeling based on the maximum entropy principle. To illustrate the method, we present its application to a heterogeneous model system and to the determination of an ensemble of structures corresponding to the thermal fluctuations of a protein molecule. Metainference thus provides an approach to modeling complex systems with heterogeneous components and interconverting between different states by taking into account all possible sources of errors.
Experimental Models of Ocular Infection with Toxoplasma Gondii
Dukaczewska, Agata; Tedesco, Roberto; Liesenfeld, Oliver
2015-01-01
Ocular toxoplasmosis is a vision-threatening disease and the major cause of posterior uveitis worldwide. In spite of the continuing global burden of ocular toxoplasmosis, many critical aspects of disease including the therapeutic approach to ocular toxoplasmosis are still under debate. To assist in addressing many aspects of the disease, numerous experimental models of ocular toxoplasmosis have been established. In this article, we present an overview on in vitro, ex vivo, and in vivo models of ocular toxoplasmosis available to date. Experimental studies on ocular toxoplasmosis have recently focused on mice. However, the majority of murine models established so far are based on intraperitoneal and intraocular infection with Toxoplasma gondii. We therefore also present results obtained in an in vivo model using peroral infection of C57BL/6 and NMRI mice that reflects the natural route of infection and mimics the disease course in humans. While advances have been made in ex vivo model systems or larger animals to investigate specific aspects of ocular toxoplasmosis, laboratory mice continue to be the experimental model of choice for the investigation of ocular toxoplasmosis. PMID:26716018
NASA Astrophysics Data System (ADS)
Huismann, Tyler D.
Due to the rapidly expanding role of electric propulsion (EP) devices, it is important to evaluate their integration with other spacecraft systems. Specifically, EP device plumes can play a major role in spacecraft integration, and as such, accurate characterization of plume structure bears on mission success. This dissertation addresses issues related to accurate prediction of plume structure in a particular type of EP device, a Hall thruster. This is done in two ways: first, by coupling current plume simulation models with current models that simulate a Hall thruster's internal plasma behavior; second, by improving plume simulation models and thereby increasing physical fidelity. These methods are assessed by comparing simulated results to experimental measurements. Assessment indicates the two methods improve plume modeling capabilities significantly: using far-field ion current density as a metric, these approaches used in conjunction improve agreement with measurements by a factor of 2.5, as compared to previous methods. Based on comparison to experimental measurements, recent computational work on discharge chamber modeling has been largely successful in predicting properties of internal thruster plasmas. This model can provide detailed information on plasma properties at a variety of locations. Frequently, experimental data is not available at many locations that are of interest regarding computational models. Excepting the presence of experimental data, there are limited alternatives for scientifically determining plasma properties that are necessary as inputs into plume simulations. Therefore, this dissertation focuses on coupling current models that simulate internal thruster plasma behavior with plume simulation models. Further, recent experimental work on atom-ion interactions has provided a better understanding of particle collisions within plasmas. This experimental work is used to update collision models in a current plume simulation code. Previous versions of the code assume an unknown dependence between particles' pre-collision velocities and post-collision scattering angles. This dissertation focuses on updating several of these types of collisions by assuming a curve fit based on the measurements of atom-ion interactions, such that previously unknown angular dependences are well-characterized.
Robust independent modal space control of a coupled nano-positioning piezo-stage
NASA Astrophysics Data System (ADS)
Zhu, Wei; Yang, Fufeng; Rui, Xiaoting
2018-06-01
In order to accurately control a coupled 3-DOF nano-positioning piezo-stage, this paper designs a hybrid controller. In this controller, a hysteresis observer based on a Bouc-Wen model is established to compensate the hysteresis nonlinearity of the piezoelectric actuator first. Compared to hysteresis compensations using Preisach model and Prandt-Ishlinskii model, the compensation method using the hysteresis observer is computationally lighter. Then, based on the proposed dynamics model, by constructing the modal filter, a robust H∞ independent modal space controller is designed and utilized to decouple the piezo-stage and deal with the unmodeled dynamics, disturbance, and hysteresis compensation error. The effectiveness of the proposed controller is demonstrated experimentally. The experimental results show that the proposed controller can significantly achieve the high-precision positioning.
Hollow carbon spheres in microwaves: Bio inspired absorbing coating
NASA Astrophysics Data System (ADS)
Bychanok, D.; Li, S.; Sanchez-Sanchez, A.; Gorokhov, G.; Kuzhir, P.; Ogrin, F. Y.; Pasc, A.; Ballweg, T.; Mandel, K.; Szczurek, A.; Fierro, V.; Celzard, A.
2016-01-01
The electromagnetic response of a heterostructure based on a monolayer of hollow glassy carbon spheres packed in 2D was experimentally surveyed with respect to its response to microwaves, namely, the Ka-band (26-37 GHz) frequency range. Such an ordered monolayer of spheres mimics the well-known "moth-eye"-like coating structures, which are widely used for designing anti-reflective surfaces, and was modelled with the long-wave approximation. Based on the experimental and modelling results, we demonstrate that carbon hollow spheres may be used for building an extremely lightweight, almost perfectly absorbing, coating for Ka-band applications.
Adaptation of acoustic model experiments of STM via smartphones and tablets
NASA Astrophysics Data System (ADS)
Thees, Michael; Hochberg, Katrin; Kuhn, Jochen; Aeschlimann, Martin
2017-10-01
The importance of Scanning Tunneling Microscopy (STM) in today's research and industry leads to the question of how to include such a key technology in physics education. Manfred Euler has developed an acoustic model experiment to illustrate the fundamental measuring principles based on an analogy between quantum mechanics and acoustics. Based on earlier work we applied mobile devices such as smartphones and tablets instead of using a computer to record and display the experimental data and thus converted Euler's experimental setup into a low-cost experiment that is easy to build and handle by students themselves.
Dissipative particle dynamics simulations of polymersomes.
Ortiz, Vanessa; Nielsen, Steven O; Discher, Dennis E; Klein, Michael L; Lipowsky, Reinhard; Shillcock, Julian
2005-09-22
A DPD model of PEO-based block copolymer vesicles in water is developed by introducing a new density based coarse graining and by using experimental data for interfacial tension. Simulated as a membrane patch, the DPD model is in excellent agreement with experimental data for both the area expansion modulus and the scaling of hydrophobic core thickness with molecular weight. Rupture simulations of polymer vesicles, or "polymersomes", are presented to illustrate the system sizes feasible with DPD. The results should provide guidance for theoretical derivations of scaling laws and also illustrate how spherical polymer vesicles might be studied in simulation.
Electrical coupled Morris-Lecar neurons: From design to pattern analysis
DOE Office of Scientific and Technical Information (OSTI.GOV)
Binczak, S.; Behdad, R.; Rossé, M.
2016-06-08
In this study, an experimental electronic neuron based on Morris-Lecar model is presented, able to become an experimental unit tool to study collective association of robust coupled neurons. The circuit design is given according to the ionic currents of this model. A weak coupling of such neurons under Multisim Software can generate clusters based on the boundary conditions of the neurons and their initial conditions. For this study, we work in the region close to the fold bifurcation of limit cycles. In this region two limit cycles exist, one of the cycles is stable and another one is unstable.
Quantitative comparisons of analogue models of brittle wedge dynamics
NASA Astrophysics Data System (ADS)
Schreurs, Guido
2010-05-01
Analogue model experiments are widely used to gain insights into the evolution of geological structures. In this study, we present a direct comparison of experimental results of 14 analogue modelling laboratories using prescribed set-ups. A quantitative analysis of the results will document the variability among models and will allow an appraisal of reproducibility and limits of interpretation. This has direct implications for comparisons between structures in analogue models and natural field examples. All laboratories used the same frictional analogue materials (quartz and corundum sand) and prescribed model-building techniques (sieving and levelling). Although each laboratory used its own experimental apparatus, the same type of self-adhesive foil was used to cover the base and all the walls of the experimental apparatus in order to guarantee identical boundary conditions (i.e. identical shear stresses at the base and walls). Three experimental set-ups using only brittle frictional materials were examined. In each of the three set-ups the model was shortened by a vertical wall, which moved with respect to the fixed base and the three remaining sidewalls. The minimum width of the model (dimension parallel to mobile wall) was also prescribed. In the first experimental set-up, a quartz sand wedge with a surface slope of ˜20° was pushed by a mobile wall. All models conformed to the critical taper theory, maintained a stable surface slope and did not show internal deformation. In the next two experimental set-ups, a horizontal sand pack consisting of alternating quartz sand and corundum sand layers was shortened from one side by the mobile wall. In one of the set-ups a thin rigid sheet covered part of the model base and was attached to the mobile wall (i.e. a basal velocity discontinuity distant from the mobile wall). In the other set-up a basal rigid sheet was absent and the basal velocity discontinuity was located at the mobile wall. In both types of experiments, models accommodated initial shortening by a forward- and a backward-verging thrust. Further shortening was taken up by in-sequence formation of forward-verging thrusts. In all experiments, boundary stresses created significant drag of structures along the sidewalls. We therefore compared the surface slope and the location, dip angle and spacing of thrusts in sections through the central part of the model. All models show very similar cross-sectional evolutions demonstrating reproducibility of first-order experimental observations. Nevertheless, there are significant along-strike variations of structures in map view highlighting the limits of interpretations of analogue model results. These variations may be related to the human factor, differences in model width and/or differences in laboratory temperature and especially humidity affecting the mechanical properties of the granular materials. GeoMod2008 Analogue Team: Susanne Buiter, Caroline Burberry, Jean-Paul Callot, Cristian Cavozzi, Mariano Cerca, Ernesto Cristallini, Alexander Cruden, Jian-Hong Chen, Leonardo Cruz, Jean-Marc Daniel, Victor H. Garcia, Caroline Gomes, Céline Grall, Cecilia Guzmán, Triyani Nur Hidayah, George Hilley, Chia-Yu Lu, Matthias Klinkmüller, Hemin Koyi, Jenny Macauley, Bertrand Maillot, Catherine Meriaux, Faramarz Nilfouroushan, Chang-Chih Pan, Daniel Pillot, Rodrigo Portillo, Matthias Rosenau, Wouter P. Schellart, Roy Schlische, Andy Take, Bruno Vendeville, Matteo Vettori, M. Vergnaud, Shih-Hsien Wang, Martha Withjack, Daniel Yagupsky, Yasuhiro Yamada
Sperlich, Alexander; Werner, Arne; Genz, Arne; Amy, Gary; Worch, Eckhard; Jekel, Martin
2005-03-01
Breakthrough curves (BTC) for the adsorption of arsenate and salicylic acid onto granulated ferric hydroxide (GFH) in fixed-bed adsorbers were experimentally determined and modeled using the homogeneous surface diffusion model (HSDM). The input parameters for the HSDM, the Freundlich isotherm constants and mass transfer coefficients for film and surface diffusion, were experimentally determined. The BTC for salicylic acid revealed a shape typical for trace organic compound adsorption onto activated carbon, and model results agreed well with the experimental curves. Unlike salicylic acid, arsenate BTCs showed a non-ideal shape with a leveling off at c/c0 approximately 0.6. Model results based on the experimentally derived parameters over-predicted the point of arsenic breakthrough for all simulated curves, lab-scale or full-scale, and were unable to catch the shape of the curve. The use of a much lower surface diffusion coefficient D(S) for modeling led to an improved fit of the later stages of the BTC shape, pointing on a time-dependent D(S). The mechanism for this time dependence is still unknown. Surface precipitation was discussed as one possible removal mechanism for arsenate besides pure adsorption interfering the determination of Freundlich constants and D(S). Rapid small-scale column tests (RSSCT) proved to be a powerful experimental alternative to the modeling procedure for arsenic.
Wang, Tianmiao; Wu, Yao; Liang, Jianhong; Han, Chenhao; Chen, Jiao; Zhao, Qiteng
2015-01-01
Skid-steering mobile robots are widely used because of their simple mechanism and robustness. However, due to the complex wheel-ground interactions and the kinematic constraints, it is a challenge to understand the kinematics and dynamics of such a robotic platform. In this paper, we develop an analysis and experimental kinematic scheme for a skid-steering wheeled vehicle based-on a laser scanner sensor. The kinematics model is established based on the boundedness of the instantaneous centers of rotation (ICR) of treads on the 2D motion plane. The kinematic parameters (the ICR coefficient χ, the path curvature variable λ and robot speed v), including the effect of vehicle dynamics, are introduced to describe the kinematics model. Then, an exact but costly dynamic model is used and the simulation of this model’s stationary response for the vehicle shows a qualitative relationship for the specified parameters χ and λ. Moreover, the parameters of the kinematic model are determined based-on a laser scanner localization experimental analysis method with a skid-steering robotic platform, Pioneer P3-AT. The relationship between the ICR coefficient χ and two physical factors is studied, i.e., the radius of the path curvature λ and the robot speed v. An empirical function-based relationship between the ICR coefficient of the robot and the path parameters is derived. To validate the obtained results, it is empirically demonstrated that the proposed kinematics model significantly improves the dead-reckoning performance of this skid–steering robot. PMID:25919370
Automation of energy demand forecasting
NASA Astrophysics Data System (ADS)
Siddique, Sanzad
Automation of energy demand forecasting saves time and effort by searching automatically for an appropriate model in a candidate model space without manual intervention. This thesis introduces a search-based approach that improves the performance of the model searching process for econometrics models. Further improvements in the accuracy of the energy demand forecasting are achieved by integrating nonlinear transformations within the models. This thesis introduces machine learning techniques that are capable of modeling such nonlinearity. Algorithms for learning domain knowledge from time series data using the machine learning methods are also presented. The novel search based approach and the machine learning models are tested with synthetic data as well as with natural gas and electricity demand signals. Experimental results show that the model searching technique is capable of finding an appropriate forecasting model. Further experimental results demonstrate an improved forecasting accuracy achieved by using the novel machine learning techniques introduced in this thesis. This thesis presents an analysis of how the machine learning techniques learn domain knowledge. The learned domain knowledge is used to improve the forecast accuracy.
Introducing memory and association mechanism into a biologically inspired visual model.
Qiao, Hong; Li, Yinlin; Tang, Tang; Wang, Peng
2014-09-01
A famous biologically inspired hierarchical model (HMAX model), which was proposed recently and corresponds to V1 to V4 of the ventral pathway in primate visual cortex, has been successfully applied to multiple visual recognition tasks. The model is able to achieve a set of position- and scale-tolerant recognition, which is a central problem in pattern recognition. In this paper, based on some other biological experimental evidence, we introduce the memory and association mechanism into the HMAX model. The main contributions of the work are: 1) mimicking the active memory and association mechanism and adding the top down adjustment to the HMAX model, which is the first try to add the active adjustment to this famous model and 2) from the perspective of information, algorithms based on the new model can reduce the computation storage and have a good recognition performance. The new model is also applied to object recognition processes. The primary experimental results show that our method is efficient with a much lower memory requirement.
Saas, Philippe; Daguindau, Etienne; Perruche, Sylvain
2016-06-01
The objectives of this review are to summarize the experimental data obtained using apoptotic cell-based therapies, and then to discuss future clinical developments. Indeed, apoptotic cells exhibit immunomodulatory properties that are reviewed here by focusing on more recent mechanisms. These immunomodulatory mechanisms are in particular linked to the clearance of apoptotic cells (called also efferocytosis) by phagocytes, such as macrophages, and the induction of regulatory T cells. Thus, apoptotic cell-based therapies have been used to prevent or treat experimental inflammatory diseases. Based on these studies, we have identified critical steps to design future clinical trials. This includes: the administration route, the number and schedule of administration, the appropriate apoptotic cell type to be used, as well as the apoptotic signal. We also have analyzed the clinical relevancy of apoptotic-cell-based therapies in experimental models. Additional experimental data are required concerning the treatment of inflammatory diseases (excepted for sepsis) before considering future clinical trials. In contrast, apoptotic cells have been shown to favor engraftment and to reduce acute graft-versus-host disease (GvHD) in different relevant models of transplantation. This has led to the conduct of a phase 1/2a clinical trial to alleviate GvHD. The absence of toxic effects obtained in this trial may support the development of other clinical studies based on this new cell therapy. Stem Cells 2016;34:1464-1473. © 2016 AlphaMed Press.
Tsipa, Argyro; Koutinas, Michalis; Usaku, Chonlatep; Mantalaris, Athanasios
2018-05-02
Currently, design and optimisation of biotechnological bioprocesses is performed either through exhaustive experimentation and/or with the use of empirical, unstructured growth kinetics models. Whereas, elaborate systems biology approaches have been recently explored, mixed-substrate utilisation is predominantly ignored despite its significance in enhancing bioprocess performance. Herein, bioprocess optimisation for an industrially-relevant bioremediation process involving a mixture of highly toxic substrates, m-xylene and toluene, was achieved through application of a novel experimental-modelling gene regulatory network - growth kinetic (GRN-GK) hybrid framework. The GRN model described the TOL and ortho-cleavage pathways in Pseudomonas putida mt-2 and captured the transcriptional kinetics expression patterns of the promoters. The GRN model informed the formulation of the growth kinetics model replacing the empirical and unstructured Monod kinetics. The GRN-GK framework's predictive capability and potential as a systematic optimal bioprocess design tool, was demonstrated by effectively predicting bioprocess performance, which was in agreement with experimental values, when compared to four commonly used models that deviated significantly from the experimental values. Significantly, a fed-batch biodegradation process was designed and optimised through the model-based control of TOL Pr promoter expression resulting in 61% and 60% enhanced pollutant removal and biomass formation, respectively, compared to the batch process. This provides strong evidence of model-based bioprocess optimisation at the gene level, rendering the GRN-GK framework as a novel and applicable approach to optimal bioprocess design. Finally, model analysis using global sensitivity analysis (GSA) suggests an alternative, systematic approach for model-driven strain modification for synthetic biology and metabolic engineering applications. Copyright © 2018. Published by Elsevier Inc.
Electrical conductivity modeling and experimental study of densely packed SWCNT networks.
Jack, D A; Yeh, C-S; Liang, Z; Li, S; Park, J G; Fielding, J C
2010-05-14
Single-walled carbon nanotube (SWCNT) networks have become a subject of interest due to their ability to support structural, thermal and electrical loadings, but to date their application has been hindered due, in large part, to the inability to model macroscopic responses in an industrial product with any reasonable confidence. This paper seeks to address the relationship between macroscale electrical conductivity and the nanostructure of a dense network composed of SWCNTs and presents a uniquely formulated physics-based computational model for electrical conductivity predictions. The proposed model incorporates physics-based stochastic parameters for the individual nanotubes to construct the nanostructure such as: an experimentally obtained orientation distribution function, experimentally derived length and diameter distributions, and assumed distributions of chirality and registry of individual CNTs. Case studies are presented to investigate the relationship between macroscale conductivity and nanostructured variations in the bulk stochastic length, diameter and orientation distributions. Simulation results correspond nicely with those available in the literature for case studies of conductivity versus length and conductivity versus diameter. In addition, predictions for the increasing anisotropy of the bulk conductivity as a function of the tube orientation distribution are in reasonable agreement with our experimental results. Examples are presented to demonstrate the importance of incorporating various stochastic characteristics in bulk conductivity predictions. Finally, a design consideration for industrial applications is discussed based on localized network power emission considerations and may lend insight to the design engineer to better predict network failure under high current loading applications.
Finite Element Method-Based Kinematics and Closed-Loop Control of Soft, Continuum Manipulators.
Bieze, Thor Morales; Largilliere, Frederick; Kruszewski, Alexandre; Zhang, Zhongkai; Merzouki, Rochdi; Duriez, Christian
2018-06-01
This article presents a modeling methodology and experimental validation for soft manipulators to obtain forward kinematic model (FKM) and inverse kinematic model (IKM) under quasi-static conditions (in the literature, these manipulators are usually classified as continuum robots. However, their main characteristic of interest in this article is that they create motion by deformation, as opposed to the classical use of articulations). It offers a way to obtain the kinematic characteristics of this type of soft robots that is suitable for offline path planning and position control. The modeling methodology presented relies on continuum mechanics, which does not provide analytic solutions in the general case. Our approach proposes a real-time numerical integration strategy based on finite element method with a numerical optimization based on Lagrange multipliers to obtain FKM and IKM. To reduce the dimension of the problem, at each step, a projection of the model to the constraint space (gathering actuators, sensors, and end-effector) is performed to obtain the smallest number possible of mathematical equations to be solved. This methodology is applied to obtain the kinematics of two different manipulators with complex structural geometry. An experimental comparison is also performed in one of the robots, between two other geometric approaches and the approach that is showcased in this article. A closed-loop controller based on a state estimator is proposed. The controller is experimentally validated and its robustness is evaluated using Lypunov stability method.
Analytical modeling and experimental validation of a magnetorheological mount
NASA Astrophysics Data System (ADS)
Nguyen, The; Ciocanel, Constantin; Elahinia, Mohammad
2009-03-01
Magnetorheological (MR) fluid has been increasingly researched and applied in vibration isolation devices. To date, the suspension system of several high performance vehicles has been equipped with MR fluid based dampers and research is ongoing to develop MR fluid based mounts for engine and powertrain isolation. MR fluid based devices have received attention due to the MR fluid's capability to change its properties in the presence of a magnetic field. This characteristic places MR mounts in the class of semiactive isolators making them a desirable substitution for the passive hydraulic mounts. In this research, an analytical model of a mixed-mode MR mount was constructed. The magnetorheological mount employs flow (valve) mode and squeeze mode. Each mode is powered by an independent electromagnet, so one mode does not affect the operation of the other. The analytical model was used to predict the performance of the MR mount with different sets of parameters. Furthermore, in order to produce the actual prototype, the analytical model was used to identify the optimal geometry of the mount. The experimental phase of this research was carried by fabricating and testing the actual MR mount. The manufactured mount was tested to evaluate the effectiveness of each mode individually and in combination. The experimental results were also used to validate the ability of the analytical model in predicting the response of the MR mount. Based on the observed response of the mount a suitable controller can be designed for it. However, the control scheme is not addressed in this study.
Zhang, Zhongheng; Ni, Hongying; Xu, Xiao
2014-08-01
Propensity score (PS) analysis has been increasingly used in critical care medicine; however, its validation has not been systematically investigated. The present study aimed to compare effect sizes in PS-based observational studies vs. randomized controlled trials (RCTs) (or meta-analysis of RCTs). Critical care observational studies using PS were systematically searched in PubMed from inception to April 2013. Identified PS-based studies were matched to one or more RCTs in terms of population, intervention, comparison, and outcome. The effect sizes of experimental treatments were compared for PS-based studies vs. RCTs (or meta-analysis of RCTs) with sign test. Furthermore, ratio of odds ratio (ROR) was calculated from the interaction term of treatment × study type in a logistic regression model. A ROR < 1 indicates greater benefit for experimental treatment in RCTs compared with PS-based studies. RORs of each comparison were pooled by using meta-analytic approach with random-effects model. A total of 20 PS-based studies were identified and matched to RCTs. Twelve of the 20 comparisons showed greater beneficial effect for experimental treatment in RCTs than that in PS-based studies (sign test P = 0.503). The difference was statistically significant in four comparisons. ROR can be calculated from 13 comparisons, of which four showed significantly greater beneficial effect for experimental treatment in RCTs. The pooled ROR was 0.71 (95% CI: 0.63, 0.79; P = 0.002), suggesting that RCTs (or meta-analysis of RCTs) were more likely to report beneficial effect for the experimental treatment than PS-based studies. The result remained unchanged in sensitivity analysis and meta-regression. In critical care literature, PS-based observational study is likely to report less beneficial effect of experimental treatment compared with RCTs (or meta-analysis of RCTs). Copyright © 2014 Elsevier Inc. All rights reserved.
Research Methods in Healthcare Epidemiology and Antimicrobial Stewardship-Mathematical Modeling.
Barnes, Sean L; Kasaie, Parastu; Anderson, Deverick J; Rubin, Michael
2016-11-01
Mathematical modeling is a valuable methodology used to study healthcare epidemiology and antimicrobial stewardship, particularly when more traditional study approaches are infeasible, unethical, costly, or time consuming. We focus on 2 of the most common types of mathematical modeling, namely compartmental modeling and agent-based modeling, which provide important advantages-such as shorter developmental timelines and opportunities for extensive experimentation-over observational and experimental approaches. We summarize these advantages and disadvantages via specific examples and highlight recent advances in the methodology. A checklist is provided to serve as a guideline in the development of mathematical models in healthcare epidemiology and antimicrobial stewardship. Infect Control Hosp Epidemiol 2016;1-7.
Integrated research in constitutive modelling at elevated temperatures, part 2
NASA Technical Reports Server (NTRS)
Haisler, W. E.; Allen, D. H.
1986-01-01
Four current viscoplastic models are compared experimentally with Inconel 718 at 1100 F. A series of tests were performed to create a sufficient data base from which to evaluate material constants. The models used include Bodner's anisotropic model; Krieg, Swearengen, and Rhode's model; Schmidt and Miller's model; and Walker's exponential model.
Micromechanical model for protein materials: From macromolecules to macroscopic fibers
NASA Astrophysics Data System (ADS)
Puglisi, G.; De Tommasi, D.; Pantano, M. F.; Pugno, N. M.; Saccomandi, G.
2017-10-01
We propose a model for the mechanical behavior of protein materials. Based on a limited number of experimental macromolecular parameters (persistence and contour length) we obtain the macroscopic behavior of keratin fibers (human, cow, and rabbit hair), taking into account the damage and residual stretches effects that are fundamental in many functions of life. We also show the capability of our approach to describe the main dissipation and permanent strain effects observed in the more complex spider silk fibers. The comparison between our results and the data obtained experimentally from cyclic tests demonstrates that our model is robust and is able to reproduce with a remarkable accuracy the experimental behavior of all protein materials we tested.
Model-Based Experimental Development of Passive Compliant Robot Legs from Fiberglass Composites
Lin, Shang-Chang; Hu, Chia-Jui; Lin, Pei-Chun
2015-01-01
We report on the methodology of developing compliant, half-circular, and composite robot legs with designable stiffness. First, force-displacement experiments on flat cantilever composites made by one or multifiberglass cloths are executed. By mapping the cantilever mechanics to the virtual spring model, the equivalent elastic moduli of the composites can be derived. Next, by using the model that links the curved beam mechanics back to the virtual spring, the resultant stiffness of the composite in a half-circular shape can be estimated without going through intensive experimental tryouts. The overall methodology has been experimentally validated, and the fabricated composites were used on a hexapod robot to perform walking and leaping behaviors. PMID:27065748
Katsogiannis, Konstantinos Alexandros G; Vladisavljević, Goran T; Georgiadou, Stella; Rahmani, Ramin
2016-10-26
The effect of pore induction on increasing electrospun fibrous network specific surface area was investigated in this study. Theoretical models based on the available surface area of the fibrous network and exclusion of the surface area lost due to fiber-to-fiber contacts were developed. The models for calculation of the excluded area are based on Hertzian, Derjaguin-Muller-Toporov (DMT), and Johnson-Kendall-Roberts (JKR) contact models. Overall, the theoretical models correlated the network specific surface area to the material properties including density, surface tension, Young's modulus, Poisson's ratio, as well as network physical properties, such as density and geometrical characteristics including fiber radius, fiber aspect ratio and network thickness. Pore induction proved to increase the network specific surface area up to 52%, compared to the maximum surface area that could be achieved by nonporous fiber network with the same physical properties and geometrical characteristics. The model based on Johnson-Kendall-Roberts contact model describes accurately the fiber-to-fiber contact area under the experimental conditions used for pore generation. The experimental results and the theoretical model based on Johnson-Kendall-Roberts contact model show that the increase in network surface area due to pore induction can reach to up to 58%.
TAP score: torsion angle propensity normalization applied to local protein structure evaluation
Tosatto, Silvio CE; Battistutta, Roberto
2007-01-01
Background Experimentally determined protein structures may contain errors and require validation. Conformational criteria based on the Ramachandran plot are mainly used to distinguish between distorted and adequately refined models. While the readily available criteria are sufficient to detect totally wrong structures, establishing the more subtle differences between plausible structures remains more challenging. Results A new criterion, called TAP score, measuring local sequence to structure fitness based on torsion angle propensities normalized against the global minimum and maximum is introduced. It is shown to be more accurate than previous methods at estimating the validity of a protein model in terms of commonly used experimental quality parameters on two test sets representing the full PDB database and a subset of obsolete PDB structures. Highly selective TAP thresholds are derived to recognize over 90% of the top experimental structures in the absence of experimental information. Both a web server and an executable version of the TAP score are available at . Conclusion A novel procedure for energy normalization (TAP) has significantly improved the possibility to recognize the best experimental structures. It will allow the user to more reliably isolate problematic structures in the context of automated experimental structure determination. PMID:17504537
Microstructure-Based Computational Modeling of Mechanical Behavior of Polymer Micro/Nano Composites
2013-12-01
K. ......... 165 Fig. 5.11. Comparison between experimental data and calibrated numerical models for displacement control tests, at three different...displacement control simulation) for all mesh densities for both work-conjugate and non work-conjugate. ........................ 302 Fig. 9.3. Damage...some large deformation experimental tests (and also accepting the non -uniformity of the strain field). In the established well-known theorem for
NASA Technical Reports Server (NTRS)
Andrews, E. H., Jr.; Mackley, E. A.
1976-01-01
An aerodynamic engine inlet analysis was performed on the experimental results obtained at nominal Mach numbers of 5, 6, and 7 from the NASA Hypersonic Research Engine (HRE) Aerothermodynamic Integration Model (AIM). Incorporation on the AIM of the mixed-compression inlet design represented the final phase of an inlet development program of the HRE Project. The purpose of this analysis was to compare the AIM inlet experimental results with theoretical results. Experimental performance was based on measured surface pressures used in a one-dimensional force-momentum theorem. Results of the analysis indicate that surface static-pressure measurements agree reasonably well with theoretical predictions except in the regions where the theory predicts large pressure discontinuities. Experimental and theoretical results both based on the one-dimensional force-momentum theorem yielded inlet performance parameters as functions of Mach number that exhibited reasonable agreement. Previous predictions of inlet unstart that resulted from pressure disturbances created by fuel injection and combustion appeared to be pessimistic.
Assessing first-order emulator inference for physical parameters in nonlinear mechanistic models
Hooten, Mevin B.; Leeds, William B.; Fiechter, Jerome; Wikle, Christopher K.
2011-01-01
We present an approach for estimating physical parameters in nonlinear models that relies on an approximation to the mechanistic model itself for computational efficiency. The proposed methodology is validated and applied in two different modeling scenarios: (a) Simulation and (b) lower trophic level ocean ecosystem model. The approach we develop relies on the ability to predict right singular vectors (resulting from a decomposition of computer model experimental output) based on the computer model input and an experimental set of parameters. Critically, we model the right singular vectors in terms of the model parameters via a nonlinear statistical model. Specifically, we focus our attention on first-order models of these right singular vectors rather than the second-order (covariance) structure.
NASA Astrophysics Data System (ADS)
Bonne, François; Alamir, Mazen; Hoa, Christine; Bonnay, Patrick; Bon-Mardion, Michel; Monteiro, Lionel
2015-12-01
In this article, we present a new Simulink library of cryogenics components (such as valve, phase separator, mixer, heat exchanger...) to assemble to generate model-based control schemes. Every component is described by its algebraic or differential equation and can be assembled with others to build the dynamical model of a complete refrigerator or the model of a subpart of it. The obtained model can be used to automatically design advanced model based control scheme. It also can be used to design a model based PI controller. Advanced control schemes aim to replace classical user experience designed approaches usually based on many independent PI controllers. This is particularly useful in the case where cryoplants are submitted to large pulsed thermal loads, expected to take place in future fusion reactors such as those expected in the cryogenic cooling systems of the International Thermonuclear Experimental Reactor (ITER) or the Japan Torus-60 Super Advanced Fusion Experiment (JT- 60SA). The paper gives the example of the generation of the dynamical model of the 400W@1.8K refrigerator and shows how to build a Constrained Model Predictive Control for it. Based on the scheme, experimental results will be given. This work is being supported by the French national research agency (ANR) through the ANR-13-SEED-0005 CRYOGREEN program.
de la Garza-Rodea, Anabel Sofía; Padilla-Sánchez, Luis; de la Garza-Aguilar, Javier; Neri-Vela, Rolando
2007-01-01
The progress of medicine has largely been due to research, and for surgery, in particular, the experimental surgical laboratory has been considered fundamental to the surgeon's education. In this study, a general view of experimental surgery is given in animal models based on bioethical norms as well as to design, create and apply different surgical procedures before performing in humans. Experimental surgery also facilitates surgical teaching and promotes the surgeon's scientific reasoning. Methods. This is a retrospective and descriptive study. Data were collected from direct and indirect sources of available publications on the historical, bioethical and educational aspects of medicine, focusing on surgery. The important facts corresponding to the field of experimental surgery and applicable in Mexico were selected. Concepts of experimental surgical models and of the experimental surgery laboratory were described. Bioethical considerations are emphasized for care of experimental animals. Finally, this work focuses on the importance of surgical experimentation in current and future development of the surgical researcher. Conclusions. Experimentation with animal models in a surgical laboratory is essential for surgical teaching and promotes development of the scientific thought in the surgeon. It is necessary for surgical research and is fundamental for making progress in surgery, treatment and medicine as science.
A model of yeast glycolysis based on a consistent kinetic characterisation of all its enzymes
Smallbone, Kieran; Messiha, Hanan L.; Carroll, Kathleen M.; Winder, Catherine L.; Malys, Naglis; Dunn, Warwick B.; Murabito, Ettore; Swainston, Neil; Dada, Joseph O.; Khan, Farid; Pir, Pınar; Simeonidis, Evangelos; Spasić, Irena; Wishart, Jill; Weichart, Dieter; Hayes, Neil W.; Jameson, Daniel; Broomhead, David S.; Oliver, Stephen G.; Gaskell, Simon J.; McCarthy, John E.G.; Paton, Norman W.; Westerhoff, Hans V.; Kell, Douglas B.; Mendes, Pedro
2013-01-01
We present an experimental and computational pipeline for the generation of kinetic models of metabolism, and demonstrate its application to glycolysis in Saccharomyces cerevisiae. Starting from an approximate mathematical model, we employ a “cycle of knowledge” strategy, identifying the steps with most control over flux. Kinetic parameters of the individual isoenzymes within these steps are measured experimentally under a standardised set of conditions. Experimental strategies are applied to establish a set of in vivo concentrations for isoenzymes and metabolites. The data are integrated into a mathematical model that is used to predict a new set of metabolite concentrations and reevaluate the control properties of the system. This bottom-up modelling study reveals that control over the metabolic network most directly involved in yeast glycolysis is more widely distributed than previously thought. PMID:23831062
NASA Astrophysics Data System (ADS)
Iqbal, S.; Benim, A. C.; Fischer, S.; Joos, F.; Kluβ, D.; Wiedermann, A.
2016-10-01
Turbulent reacting flows in a generic swirl gas turbine combustor model are investigated both numerically and experimentally. In the investigation, an emphasis is placed upon the external flue gas recirculation, which is a promising technology for increasing the efficiency of the carbon capture and storage process, which, however, can change the combustion behaviour significantly. A further emphasis is placed upon the investigation of alternative fuels such as biogas and syngas in comparison to the conventional natural gas. Flames are also investigated numerically using the open source CFD software OpenFOAM. In the numerical simulations, a laminar flamelet model based on mixture fraction and reaction progress variable is adopted. As turbulence model, the SST model is used within a URANS concept. Computational results are compared with the experimental data, where a fair agreement is observed.
Research the Gait Characteristics of Human Walking Based on a Robot Model and Experiment
NASA Astrophysics Data System (ADS)
He, H. J.; Zhang, D. N.; Yin, Z. W.; Shi, J. H.
2017-02-01
In order to research the gait characteristics of human walking in different walking ways, a robot model with a single degree of freedom is put up in this paper. The system control models of the robot are established through Matlab/Simulink toolbox. The gait characteristics of straight, uphill, turning, up the stairs, down the stairs up and down areanalyzed by the system control models. To verify the correctness of the theoretical analysis, an experiment was carried out. The comparison between theoretical results and experimental results shows that theoretical results are better agreement with the experimental ones. Analyze the reasons leading to amplitude error and phase error and give the improved methods. The robot model and experimental ways can provide foundation to further research the various gait characteristics of the exoskeleton robot.
Lee, Hasup; Baek, Minkyung; Lee, Gyu Rie; Park, Sangwoo; Seok, Chaok
2017-03-01
Many proteins function as homo- or hetero-oligomers; therefore, attempts to understand and regulate protein functions require knowledge of protein oligomer structures. The number of available experimental protein structures is increasing, and oligomer structures can be predicted using the experimental structures of related proteins as templates. However, template-based models may have errors due to sequence differences between the target and template proteins, which can lead to functional differences. Such structural differences may be predicted by loop modeling of local regions or refinement of the overall structure. In CAPRI (Critical Assessment of PRotein Interactions) round 30, we used recently developed features of the GALAXY protein modeling package, including template-based structure prediction, loop modeling, model refinement, and protein-protein docking to predict protein complex structures from amino acid sequences. Out of the 25 CAPRI targets, medium and acceptable quality models were obtained for 14 and 1 target(s), respectively, for which proper oligomer or monomer templates could be detected. Symmetric interface loop modeling on oligomer model structures successfully improved model quality, while loop modeling on monomer model structures failed. Overall refinement of the predicted oligomer structures consistently improved the model quality, in particular in interface contacts. Proteins 2017; 85:399-407. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
Experimental Validation of the Transverse Shear Behavior of a Nomex Core for Sandwich Panels
NASA Astrophysics Data System (ADS)
Farooqi, M. I.; Nasir, M. A.; Ali, H. M.; Ali, Y.
2017-05-01
This work deals with determination of the transverse shear moduli of a Nomex® honeycomb core of sandwich panels. Their out-of-plane shear characteristics depend on the transverse shear moduli of the honeycomb core. These moduli were determined experimentally, numerically, and analytically. Numerical simulations were performed by using a unit cell model and three analytical approaches. Analytical calculations showed that two of the approaches provided reasonable predictions for the transverse shear modulus as compared with experimental results. However, the approach based upon the classical lamination theory showed large deviations from experimental data. Numerical simulations also showed a trend similar to that resulting from the analytical models.
Modeling changes in biomass composition during microwave-based alkali pretreatment of switchgrass.
Keshwani, Deepak R; Cheng, Jay J
2010-01-01
This study used two different approaches to model changes in biomass composition during microwave-based pretreatment of switchgrass: kinetic modeling using a time-dependent rate coefficient, and a Mamdani-type fuzzy inference system. In both modeling approaches, the dielectric loss tangent of the alkali reagent and pretreatment time were used as predictors for changes in amounts of lignin, cellulose, and xylan during the pretreatment. Training and testing data sets for development and validation of the models were obtained from pretreatment experiments conducted using 1-3% w/v NaOH (sodium hydroxide) and pretreatment times ranging from 5 to 20 min. The kinetic modeling approach for lignin and xylan gave comparable results for training and testing data sets, and the differences between the predictions and experimental values were within 2%. The kinetic modeling approach for cellulose was not as effective, and the differences were within 5-7%. The time-dependent rate coefficients of the kinetic models estimated from experimental data were consistent with the heterogeneity of individual biomass components. The Mamdani-type fuzzy inference was shown to be an effective approach to model the pretreatment process and yielded predictions with less than 2% deviation from the experimental values for lignin and with less than 3% deviation from the experimental values for cellulose and xylan. The entropies of the fuzzy outputs from the Mamdani-type fuzzy inference system were calculated to quantify the uncertainty associated with the predictions. Results indicate that there is no significant difference between the entropies associated with the predictions for lignin, cellulose, and xylan. It is anticipated that these models could be used in process simulations of bioethanol production from lignocellulosic materials.
Interaction model between capsule robot and intestine based on nonlinear viscoelasticity.
Zhang, Cheng; Liu, Hao; Tan, Renjia; Li, Hongyi
2014-03-01
Active capsule endoscope could also be called capsule robot, has been developed from laboratory research to clinical application. However, the system still has defects, such as poor controllability and failing to realize automatic checks. The imperfection of the interaction model between capsule robot and intestine is one of the dominating reasons causing the above problems. A model is hoped to be established for the control method of the capsule robot in this article. It is established based on nonlinear viscoelasticity. The interaction force of the model consists of environmental resistance, viscous resistance and Coulomb friction. The parameters of the model are identified by experimental investigation. Different methods are used in the experiment to obtain different values of the same parameter at different velocities. The model is proved to be valid by experimental verification. The achievement in this article is the attempted perfection of an interaction model. It is hoped that the model can optimize the control method of the capsule robot in the future.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wendt, Fabian F; Robertson, Amy N; Jonkman, Jason
During the course of the Offshore Code Comparison Collaboration, Continued, with Correlation (OC5) project, which focused on the validation of numerical methods through comparison against tank test data, the authors created a numerical FAST model of the 1:50-scale DeepCwind semisubmersible system that was tested at the Maritime Research Institute Netherlands ocean basin in 2013. This paper discusses several model calibration studies that were conducted to identify model adjustments that improve the agreement between the numerical simulations and the experimental test data. These calibration studies cover wind-field-specific parameters (coherence, turbulence), hydrodynamic and aerodynamic modeling approaches, as well as rotor model (blade-pitchmore » and blade-mass imbalances) and tower model (structural tower damping coefficient) adjustments. These calibration studies were conducted based on relatively simple calibration load cases (wave only/wind only). The agreement between the final FAST model and experimental measurements is then assessed based on more-complex combined wind and wave validation cases.« less
An electrical circuit model for additive-modified SnO2 ceramics
NASA Astrophysics Data System (ADS)
Karami Horastani, Zahra; Alaei, Reza; Karami, Amirhossein
2018-05-01
In this paper an electrical circuit model for additive-modified metal oxide ceramics based on their physical structures and electrical resistivities is presented. The model predicts resistance of the sample at different additive concentrations and different temperatures. To evaluate the model two types of composite ceramics, SWCNT/SnO2 with SWCNT concentrations of 0.3, 0.6, 1.2, 2.4 and 3.8%wt, and Ag/SnO2 with Ag concentrations of 0.3, 0.5, 0.8 and 1.5%wt, were prepared and their electrical resistances versus temperature were experimentally measured. It is shown that the experimental data are in good agreement with the results obtained from the model. The proposed model can be used in the design process of ceramic-based gas sensors, and it also clarifies the role of additive in gas sensing process of additive-modified metal oxide gas sensors. Furthermore the model can be used in the system level modeling of designs in which these sensors are also present.
Testing an H-mode Pedestal Model Using DIII-D Data
NASA Astrophysics Data System (ADS)
Kritz, A. H.; Onjun, T.; Bateman, G.; Guzdar, P. N.; Mahajan, S. M.; Osborne, T.
2004-11-01
Tests against experimental data are carried out for a model of the pedestal at the edge of H-mode plasmas based on double-Beltrami solutions of the two-fluid Hall-MHD equations for the interaction of the magnetic and velocity fields.(S.M. Mahajan and Z. Yoshida, PRL 81 (1998) 4863, Phys. Plasmas 7 (2000) 635.) The width and height of the pedestal predicted by the model are tested against experimental data from the DIII-D tokamak. The model for the pedestal width, which has a particularly simple form, namely, inversely proportional to the square root of the density, does not appear to capture the parameter dependence of the experimental data. When the model for the pedestal temperature is rescaled to optimize agreement with data, the RMS error is found to be comparable with the RMS error found using other pedestal models.(T. Onjun, G. Bateman, A.H. Kritz, G. Hammett, Phys. Plasmas 9 (2002) 5018.)
Model Based Inference for Wire Chafe Diagnostics
NASA Technical Reports Server (NTRS)
Schuet, Stefan R.; Wheeler, Kevin R.; Timucin, Dogan A.; Wysocki, Philip F.; Kowalski, Marc Edward
2009-01-01
Presentation for Aging Aircraft conference covering chafing fault diagnostics using Time Domain Reflectometry. Laboratory setup and experimental methods are presented, along with initial results that summarize fault modeling and detection capabilities.
NASA Astrophysics Data System (ADS)
Hidayat, Taufiq; Shishin, Denis; Decterov, Sergei A.; Hayes, Peter C.; Jak, Evgueni
2017-01-01
Uncertainty in the metal price and competition between producers mean that the daily operation of a smelter needs to target high recovery of valuable elements at low operating cost. Options for the improvement of the plant operation can be examined and decision making can be informed based on accurate information from laboratory experimentation coupled with predictions using advanced thermodynamic models. Integrated high-temperature experimental and thermodynamic modelling research on phase equilibria and thermodynamics of copper-containing systems have been undertaken at the Pyrometallurgy Innovation Centre (PYROSEARCH). The experimental phase equilibria studies involve high-temperature equilibration, rapid quenching and direct measurement of phase compositions using electron probe X-ray microanalysis (EPMA). The thermodynamic modelling deals with the development of accurate thermodynamic database built through critical evaluation of experimental data, selection of solution models, and optimization of models parameters. The database covers the Al-Ca-Cu-Fe-Mg-O-S-Si chemical system. The gas, slag, matte, liquid and solid metal phases, spinel solid solution as well as numerous solid oxide and sulphide phases are included. The database works within the FactSage software environment. Examples of phase equilibria data and thermodynamic models of selected systems, as well as possible implementation of the research outcomes to selected copper making processes are presented.
ERIC Educational Resources Information Center
Shacham, Mordechai; Cutlip, Michael B.; Brauner, Neima
2009-01-01
A continuing challenge to the undergraduate chemical engineering curriculum is the time-effective incorporation and use of computer-based tools throughout the educational program. Computing skills in academia and industry require some proficiency in programming and effective use of software packages for solving 1) single-model, single-algorithm…
Theory and experiments in model-based space system anomaly management
NASA Astrophysics Data System (ADS)
Kitts, Christopher Adam
This research program consists of an experimental study of model-based reasoning methods for detecting, diagnosing and resolving anomalies that occur when operating a comprehensive space system. Using a first principles approach, several extensions were made to the existing field of model-based fault detection and diagnosis in order to develop a general theory of model-based anomaly management. Based on this theory, a suite of algorithms were developed and computationally implemented in order to detect, diagnose and identify resolutions for anomalous conditions occurring within an engineering system. The theory and software suite were experimentally verified and validated in the context of a simple but comprehensive, student-developed, end-to-end space system, which was developed specifically to support such demonstrations. This space system consisted of the Sapphire microsatellite which was launched in 2001, several geographically distributed and Internet-enabled communication ground stations, and a centralized mission control complex located in the Space Technology Center in the NASA Ames Research Park. Results of both ground-based and on-board experiments demonstrate the speed, accuracy, and value of the algorithms compared to human operators, and they highlight future improvements required to mature this technology.
Prediction of frozen food properties during freezing using product composition.
Boonsupthip, W; Heldman, D R
2007-06-01
Frozen water fraction (FWF), as a function of temperature, is an important parameter for use in the design of food freezing processes. An FWF-prediction model, based on concentrations and molecular weights of specific product components, has been developed. Published food composition data were used to determine the identity and composition of key components. The model proposed in this investigation had been verified using published experimental FWF data and initial freezing temperature data, and by comparison to outputs from previously published models. It was found that specific food components with significant influence on freezing temperature depression of food products included low molecular weight water-soluble compounds with molality of 50 micromol per 100 g food or higher. Based on an analysis of 200 high-moisture food products, nearly 45% of the experimental initial freezing temperature data were within an absolute difference (AD) of +/- 0.15 degrees C and standard error (SE) of +/- 0.65 degrees C when compared to values predicted by the proposed model. The predicted relationship between temperature and FWF for all analyzed food products provided close agreements with experimental data (+/- 0.06 SE). The proposed model provided similar prediction capability for high- and intermediate-moisture food products. In addition, the proposed model provided statistically better prediction of initial freezing temperature and FWF than previous published models.
Antioxidant Capacity: Experimental Determination by EPR Spectroscopy and Mathematical Modeling.
Polak, Justyna; Bartoszek, Mariola; Chorążewski, Mirosław
2015-07-22
A new method of determining antioxidant capacity based on a mathematical model is presented in this paper. The model was fitted to 1000 data points of electron paramagnetic resonance (EPR) spectroscopy measurements of various food product samples such as tea, wine, juice, and herbs with Trolox equivalent antioxidant capacity (TEAC) values from 20 to 2000 μmol TE/100 mL. The proposed mathematical equation allows for a determination of TEAC of food products based on a single EPR spectroscopy measurement. The model was tested on the basis of 80 EPR spectroscopy measurements of herbs, tea, coffee, and juice samples. The proposed model works for both strong and weak antioxidants (TEAC values from 21 to 2347 μmol TE/100 mL). The determination coefficient between TEAC values obtained experimentally and TEAC values calculated with proposed mathematical equation was found to be R(2) = 0.98. Therefore, the proposed new method of TEAC determination based on a mathematical model is a good alternative to the standard EPR method due to its being fast, accurate, inexpensive, and simple to perform.
Collignon, Bertrand; Séguret, Axel; Halloy, José
2016-01-01
Collective motion is one of the most ubiquitous behaviours displayed by social organisms and has led to the development of numerous models. Recent advances in the understanding of sensory system and information processing by animals impels one to revise classical assumptions made in decisional algorithms. In this context, we present a model describing the three-dimensional visual sensory system of fish that adjust their trajectory according to their perception field. Furthermore, we introduce a stochastic process based on a probability distribution function to move in targeted directions rather than on a summation of influential vectors as is classically assumed by most models. In parallel, we present experimental results of zebrafish (alone or in group of 10) swimming in both homogeneous and heterogeneous environments. We use these experimental data to set the parameter values of our model and show that this perception-based approach can simulate the collective motion of species showing cohesive behaviour in heterogeneous environments. Finally, we discuss the advances of this multilayer model and its possible outcomes in biological, physical and robotic sciences. PMID:26909173
Mass transfer effect of the stalk contraction-relaxation cycle of Vorticella convallaria
NASA Astrophysics Data System (ADS)
Zhou, Jiazhong; Admiraal, David; Ryu, Sangjin
2014-11-01
Vorticella convallaria is a genus of protozoa living in freshwater. Its stalk contracts and coil pulling the cell body towards the substrate at a remarkable speed, and then relaxes to its extended state much more slowly than the contraction. However, the reason for Vorticella's stalk contraction is still unknown. It is presumed that water flow induced by the stalk contraction-relaxation cycle may augment mass transfer near the substrate. We investigated this hypothesis using an experimental model with particle tracking velocimetry and a computational fluid dynamics model. In both approaches, Vorticella was modeled as a solid sphere translating perpendicular to a solid surface in water. After having been validated by the experimental model and verified by grid convergence index test, the computational model simulated water flow during the cycle based on the measured time course of stalk length changes of Vorticella. Based on the simulated flow field, we calculated trajectories of particles near the model Vorticella, and then evaluated the mass transfer effect of Vorticella's stalk contraction based on the particles' motion. We acknowlege support from Laymann Seed Grant of the University of Nebraska-Lincoln.
NASA Astrophysics Data System (ADS)
Haddag, B.; Kagnaya, T.; Nouari, M.; Cutard, T.
2013-01-01
Modelling machining operations allows estimating cutting parameters which are difficult to obtain experimentally and in particular, include quantities characterizing the tool-workpiece interface. Temperature is one of these quantities which has an impact on the tool wear, thus its estimation is important. This study deals with a new modelling strategy, based on two steps of calculation, for analysis of the heat transfer into the cutting tool. Unlike the classical methods, considering only the cutting tool with application of an approximate heat flux at the cutting face, estimated from experimental data (e.g. measured cutting force, cutting power), the proposed approach consists of two successive 3D Finite Element calculations and fully independent on the experimental measurements; only the definition of the behaviour of the tool-workpiece couple is necessary. The first one is a 3D thermomechanical modelling of the chip formation process, which allows estimating cutting forces, chip morphology and its flow direction. The second calculation is a 3D thermal modelling of the heat diffusion into the cutting tool, by using an adequate thermal loading (applied uniform or non-uniform heat flux). This loading is estimated using some quantities obtained from the first step calculation, such as contact pressure, sliding velocity distributions and contact area. Comparisons in one hand between experimental data and the first calculation and at the other hand between measured temperatures with embedded thermocouples and the second calculation show a good agreement in terms of cutting forces, chip morphology and cutting temperature.
Model-Based Estimation of Knee Stiffness
Pfeifer, Serge; Vallery, Heike; Hardegger, Michael; Riener, Robert; Perreault, Eric J.
2013-01-01
During natural locomotion, the stiffness of the human knee is modulated continuously and subconsciously according to the demands of activity and terrain. Given modern actuator technology, powered transfemoral prostheses could theoretically provide a similar degree of sophistication and function. However, experimentally quantifying knee stiffness modulation during natural gait is challenging. Alternatively, joint stiffness could be estimated in a less disruptive manner using electromyography (EMG) combined with kinetic and kinematic measurements to estimate muscle force, together with models that relate muscle force to stiffness. Here we present the first step in that process, where we develop such an approach and evaluate it in isometric conditions, where experimental measurements are more feasible. Our EMG-guided modeling approach allows us to consider conditions with antagonistic muscle activation, a phenomenon commonly observed in physiological gait. Our validation shows that model-based estimates of knee joint stiffness coincide well with experimental data obtained using conventional perturbation techniques. We conclude that knee stiffness can be accurately estimated in isometric conditions without applying perturbations, which presents an important step towards our ultimate goal of quantifying knee stiffness during gait. PMID:22801482
NASA Astrophysics Data System (ADS)
Ramazani, Ali; Mukherjee, Krishnendu; Prahl, Ulrich; Bleck, Wolfgang
2012-10-01
The flow behavior of dual-phase (DP) steels is modeled on the finite-element method (FEM) framework on the microscale, considering the effect of the microstructure through the representative volume element (RVE) approach. Two-dimensional RVEs were created from microstructures of experimentally obtained DP steels with various ferrite grain sizes. The flow behavior of single phases was modeled through the dislocation-based work-hardening approach. The volume change during austenite-to-martensite transformation was modeled, and the resultant prestrained areas in the ferrite were considered to be the storage place of transformation-induced, geometrically necessary dislocations (GNDs). The flow curves of DP steels with varying ferrite grain sizes, but constant martensite fractions, were obtained from the literature. The flow curves of simulations that take into account the GND are in better agreement with those of experimental flow curves compared with those of predictions without consideration of the GND. The experimental results obeyed the Hall-Petch relationship between yield stress and flow stress and the simulations predicted this as well.
Ruel, Jean; Lachance, Geneviève
2010-01-01
This paper presents an experimental study of three bioreactor configurations. The bioreactor is intended to be used for the development of tissue-engineered heart valve substitutes. Therefore it must be able to reproduce physiological flow and pressure waveforms accurately. A detailed analysis of three bioreactor arrangements is presented using mathematical models based on the windkessel (WK) approach. First, a review of the many applications of this approach in medical studies enhances its fundamental nature and its usefulness. Then the models are developed with reference to the actual components of the bioreactor. This study emphasizes different conflicting issues arising in the design process of a bioreactor for biomedical purposes, where an optimization process is essential to reach a compromise satisfying all conditions. Two important aspects are the need for a simple system providing ease of use and long-term sterility, opposed to the need for an advanced (thus more complex) architecture capable of a more accurate reproduction of the physiological environment. Three classic WK architectures are analyzed, and experimental results enhance the advantages and limitations of each one. PMID:21977286
Burton, Brett M; Aras, Kedar K; Good, Wilson W; Tate, Jess D; Zenger, Brian; MacLeod, Rob S
2018-05-21
The biophysical basis for electrocardiographic evaluation of myocardial ischemia stems from the notion that ischemic tissues develop, with relative uniformity, along the endocardial aspects of the heart. These injured regions of subendocardial tissue give rise to intramural currents that lead to ST segment deflections within electrocardiogram (ECG) recordings. The concept of subendocardial ischemic regions is often used in clinical practice, providing a simple and intuitive description of ischemic injury; however, such a model grossly oversimplifies the presentation of ischemic disease-inadvertently leading to errors in ECG-based diagnoses. Furthermore, recent experimental studies have brought into question the subendocardial ischemia paradigm suggesting instead a more distributed pattern of tissue injury. These findings come from experiments and so have both the impact and the limitations of measurements from living organisms. Computer models have often been employed to overcome the constraints of experimental approaches and have a robust history in cardiac simulation. To this end, we have developed a computational simulation framework aimed at elucidating the effects of ischemia on measurable cardiac potentials. To validate our framework, we simulated, visualized, and analyzed 226 experimentally derived acute myocardial ischemic events. Simulation outcomes agreed both qualitatively (feature comparison) and quantitatively (correlation, average error, and significance) with experimentally obtained epicardial measurements, particularly under conditions of elevated ischemic stress. Our simulation framework introduces a novel approach to incorporating subject-specific, geometric models and experimental results that are highly resolved in space and time into computational models. We propose this framework as a means to advance the understanding of the underlying mechanisms of ischemic disease while simultaneously putting in place the computational infrastructure necessary to study and improve ischemia models aimed at reducing diagnostic errors in the clinic.
On the Limitations of Breakthrough Curve Analysis in Fixed-Bed Adsorption
NASA Technical Reports Server (NTRS)
Knox, James C.; Ebner, Armin D.; LeVan, M. Douglas; Coker, Robert F.; Ritter, James A.
2016-01-01
This work examined in detail the a priori prediction of the axial dispersion coefficient from available correlations versus obtaining it and also mass transfer information from experimental breakthrough data and the consequences that may arise when doing so based on using a 1-D axially dispersed plug flow model and its associated Danckwerts outlet boundary condition. These consequences mainly included determining the potential for erroneous extraction of the axial dispersion coefficient and/or the LDF mass transfer coefficient from experimental data, especially when non-plug flow conditions prevailed in the bed. Two adsorbent/adsorbate cases were considered, i.e., carbon dioxide and water vapor in zeolite 5A, because they both experimentally exhibited significant non-plug flow behavior, and the water-zeolite 5A system exhibited unusual concentration front sharpening that destroyed the expected constant pattern behavior (CPB) when modeled with the 1-D axially dispersed plug flow model. Overall, this work showed that it was possible to extract accurate mass transfer and dispersion information from experimental breakthrough curves using a 1-D axial dispersed plug flow model when they were measured both inside and outside the bed. To ensure the extracted information was accurate, the inside the bed breakthrough curves and their derivatives from the model were plotted to confirm whether or not the adsorbate/adsorbent system was exhibiting CPB or any concentration front sharpening near the bed exit. Even when concentration front sharpening was occurring with the water-zeolite 5A system, it was still possible to use the experimental inside and outside the bed breakthrough curves to extract fundamental mass transfer and dispersion information from the 1-D axial dispersed plug flow model based on the systematic methodology developed in this work.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Andronov, V.A.; Zhidov, I.G.; Meskov, E.E.
The report presents the basic results of some calculations, theoretical and experimental efforts in the study of Rayleigh-Taylor, Kelvin-Helmholtz, Richtmyer-Meshkov instabilities and the turbulent mixing which is caused by their evolution. Since the late forties the VNIIEF has been conducting these investigations. This report is based on the data which were published in different times in Russian and foreign journals. The first part of the report deals with calculations an theoretical techniques for the description of hydrodynamic instabilities applied currently, as well as with the results of several individual problems and their comparison with the experiment. These methods can bemore » divided into two types: direct numerical simulation methods and phenomenological methods. The first type includes the regular 2D and 3D gasdynamical techniques as well as the techniques based on small perturbation approximation and on incompressible liquid approximation. The second type comprises the techniques based on various phenomenological turbulence models. The second part of the report describes the experimental methods and cites the experimental results of Rayleigh-Taylor and Richtmyer-Meskov instability studies as well as of turbulent mixing. The applied methods were based on thin-film gaseous models, on jelly models and liquid layer models. The research was done for plane and cylindrical geometries. As drivers, the shock tubes of different designs were used as well as gaseous explosive mixtures, compressed air and electric wire explosions. The experimental results were applied in calculational-theoretical technique calibrations. The authors did not aim at covering all VNIIEF research done in this field of science. To a great extent the choice of the material depended on the personal contribution of the author in these studies.« less
A Combined Experimental and Computational Approach to Subject-Specific Analysis of Knee Joint Laxity
Harris, Michael D.; Cyr, Adam J.; Ali, Azhar A.; Fitzpatrick, Clare K.; Rullkoetter, Paul J.; Maletsky, Lorin P.; Shelburne, Kevin B.
2016-01-01
Modeling complex knee biomechanics is a continual challenge, which has resulted in many models of varying levels of quality, complexity, and validation. Beyond modeling healthy knees, accurately mimicking pathologic knee mechanics, such as after cruciate rupture or meniscectomy, is difficult. Experimental tests of knee laxity can provide important information about ligament engagement and overall contributions to knee stability for development of subject-specific models to accurately simulate knee motion and loading. Our objective was to provide combined experimental tests and finite-element (FE) models of natural knee laxity that are subject-specific, have one-to-one experiment to model calibration, simulate ligament engagement in agreement with literature, and are adaptable for a variety of biomechanical investigations (e.g., cartilage contact, ligament strain, in vivo kinematics). Calibration involved perturbing ligament stiffness, initial ligament strain, and attachment location until model-predicted kinematics and ligament engagement matched experimental reports. Errors between model-predicted and experimental kinematics averaged <2 deg during varus–valgus (VV) rotations, <6 deg during internal–external (IE) rotations, and <3 mm of translation during anterior–posterior (AP) displacements. Engagement of the individual ligaments agreed with literature descriptions. These results demonstrate the ability of our constraint models to be customized for multiple individuals and simultaneously call attention to the need to verify that ligament engagement is in good general agreement with literature. To facilitate further investigations of subject-specific or population based knee joint biomechanics, data collected during the experimental and modeling phases of this study are available for download by the research community. PMID:27306137
Models of cooperative dynamics from biomolecules to magnets
NASA Astrophysics Data System (ADS)
Mobley, David Lowell
This work details application of computer models to several biological systems (prion diseases and Alzheimer's disease) and a magnetic system. These share some common themes, which are discussed. Here, simple lattice-based models are applied to aggregation of misfolded protein in prion diseases like Mad Cow disease. These can explain key features of the diseases. The modeling is based on aggregation being essential in establishing the time-course of infectivity. Growth of initial aggregates is assumed to dominate the experimentally observed lag phase. Subsequent fission, regrowth, and fission set apart the exponential doubling phase in disease progression. We explore several possible modes of growth for 2-D aggregates and suggest the model providing the best explanation for the experimental data. We develop testable predictions from this model. Like prion disease, Alzheimer's disease (AD) is an amyloid disease characterized by large aggregates in the brain. However, evidence increasingly points away from these as the toxic agent and towards oligomers of the Abeta peptide. We explore one possible toxicity mechanism---insertion of Abeta into cell membranes and formation of harmful ion channels. We find that mutations in this peptide which cause familial Alzheimer's disease (FAD) also affect the insertion of this peptide into membranes in a fairly consistent way, suggesting that this toxicity mechanism may be relevant biologically. We find a particular inserted configuration which may be especially harmful and develop testable predictions to verify whether or not this is the case. Nucleation is an essential feature of our models for prion disease, in that it protects normal, healthy individuals from getting prion disease. Nucleation is important in many other areas, and we modify our lattice-based nucleation model to apply to a hysteretic magnetic system where nucleation has been suggested to be important. From a simple model, we find qualitative agreement with experiment, and make testable experimental predictions concerning time-dependence and temperature-dependence of the major hysteresis loop and reversal curves which have been experimentally verified. We argue why this model may be suitable for systems like these and explain implications for Ising-like models. We suggest implications for future modeling work. Finally, we present suggestions for future work in all three areas.
He, Wei; Yurkevich, Igor V; Canham, Leigh T; Loni, Armando; Kaplan, Andrey
2014-11-03
We develop an analytical model based on the WKB approach to evaluate the experimental results of the femtosecond pump-probe measurements of the transmittance and reflectance obtained on thin membranes of porous silicon. The model allows us to retrieve a pump-induced nonuniform complex dielectric function change along the membrane depth. We show that the model fitting to the experimental data requires a minimal number of fitting parameters while still complying with the restriction imposed by the Kramers-Kronig relation. The developed model has a broad range of applications for experimental data analysis and practical implementation in the design of devices involving a spatially nonuniform dielectric function, such as in biosensing, wave-guiding, solar energy harvesting, photonics and electro-optical devices.
Development of a model counter-rotating type horizontal-axis tidal turbine
NASA Astrophysics Data System (ADS)
Huang, B.; Yoshida, K.; Kanemoto, T.
2016-05-01
In the past decade, the tidal energies have caused worldwide concern as it can provide regular and predictable renewable energy resource for power generation. The majority of technologies for exploiting the tidal stream energy are based on the concept of the horizontal axis tidal turbine (HATT). A unique counter-rotating type HATT was proposed in the present work. The original blade profiles were designed according to the developed blade element momentum theory (BEMT). CFD simulations and experimental tests were adopted to the performance of the model counter-rotating type HATT. The experimental data provides an evidence of validation of the CFD model. Further optimization of the blade profiles was also carried out based on the CFD results.
NASA Astrophysics Data System (ADS)
Liu, Cheng-Lin; Sun, Ze; Lu, Gui-Min; Yu, Jian-Guo
2018-05-01
Gas-evolving vertical electrode system is a typical electrochemical industrial reactor. Gas bubbles are released from the surfaces of the anode and affect the electrolyte flow pattern and even the cell performance. In the current work, the hydrodynamics induced by the air bubbles in a cold model was experimentally and numerically investigated. Particle image velocimetry and volumetric three-component velocimetry techniques were applied to experimentally visualize the hydrodynamics characteristics and flow fields in a two-dimensional (2D) plane and a three-dimensional (3D) space, respectively. Measurements were performed at different gas rates. Furthermore, the corresponding mathematical model was developed under identical conditions for the qualitative and quantitative analyses. The experimental measurements were compared with the numerical results based on the mathematical model. The study of the time-averaged flow field, three velocity components, instantaneous velocity and turbulent intensity indicate that the numerical model qualitatively reproduces liquid motion. The 3D model predictions capture the flow behaviour more accurately than the 2D model in this study.
Liu, Cheng-Lin; Sun, Ze; Lu, Gui-Min; Yu, Jian-Guo
2018-05-01
Gas-evolving vertical electrode system is a typical electrochemical industrial reactor. Gas bubbles are released from the surfaces of the anode and affect the electrolyte flow pattern and even the cell performance. In the current work, the hydrodynamics induced by the air bubbles in a cold model was experimentally and numerically investigated. Particle image velocimetry and volumetric three-component velocimetry techniques were applied to experimentally visualize the hydrodynamics characteristics and flow fields in a two-dimensional (2D) plane and a three-dimensional (3D) space, respectively. Measurements were performed at different gas rates. Furthermore, the corresponding mathematical model was developed under identical conditions for the qualitative and quantitative analyses. The experimental measurements were compared with the numerical results based on the mathematical model. The study of the time-averaged flow field, three velocity components, instantaneous velocity and turbulent intensity indicate that the numerical model qualitatively reproduces liquid motion. The 3D model predictions capture the flow behaviour more accurately than the 2D model in this study.
Lu, Gui-Min; Yu, Jian-Guo
2018-01-01
Gas-evolving vertical electrode system is a typical electrochemical industrial reactor. Gas bubbles are released from the surfaces of the anode and affect the electrolyte flow pattern and even the cell performance. In the current work, the hydrodynamics induced by the air bubbles in a cold model was experimentally and numerically investigated. Particle image velocimetry and volumetric three-component velocimetry techniques were applied to experimentally visualize the hydrodynamics characteristics and flow fields in a two-dimensional (2D) plane and a three-dimensional (3D) space, respectively. Measurements were performed at different gas rates. Furthermore, the corresponding mathematical model was developed under identical conditions for the qualitative and quantitative analyses. The experimental measurements were compared with the numerical results based on the mathematical model. The study of the time-averaged flow field, three velocity components, instantaneous velocity and turbulent intensity indicate that the numerical model qualitatively reproduces liquid motion. The 3D model predictions capture the flow behaviour more accurately than the 2D model in this study. PMID:29892347
NASA Astrophysics Data System (ADS)
Timmel, K.; Kratzsch, C.; Asad, A.; Schurmann, D.; Schwarze, R.; Eckert, S.
2017-07-01
The present paper reports about numerical simulations and model experiments concerned with the fluid flow in the continuous casting process of steel. This work was carried out in the LIMMCAST project in the framework of the Helmholtz alliance LIMTECH. A brief description of the LIMMCAST facilities used for the experimental modeling at HZDR is given here. Ultrasonic and inductive techniques and the X-ray radioscopy were employed for flow measurements or visualizations of two-phase flow regimes occurring in the submerged entry nozzle and the mold. Corresponding numerical simulations were performed at TUBAF taking into account the dimensions and properties of the model experiments. Numerical models were successfully validated using the experimental data base. The reasonable and in many cases excellent agreement of numerical with experimental data allows to extrapolate the models to real casting configurations. Exemplary results will be presented here showing the effect of electromagnetic brakes or electromagnetic stirrers on the flow in the mold or illustrating the properties of two-phase flows resulting from an Ar injection through the stopper rod.
NASA Astrophysics Data System (ADS)
Mi, Ye
1998-12-01
The major objective of this thesis is focused on theoretical and experimental investigations of identifying and characterizing vertical and horizontal flow regimes in two-phase flows. A methodology of flow regime identification with impedance-based neural network systems and a comprehensive model of vertical slug flow have been developed. Vertical slug flow has been extensively investigated and characterized with geometric, kinematic and hydrodynamic parameters. A multi-sensor impedance void-meter and a multi-sensor magnetic flowmeter were developed. The impedance void-meter was cross-calibrated with other reliable techniques for void fraction measurements. The performance of the impedance void-meter to measure the void propagation velocity was evaluated by the drift flux model. It was proved that the magnetic flowmeter was applicable to vertical slug flow measurements. Separable signals from these instruments allow us to unearth most characteristics of vertical slug flow. A methodology of vertical flow regime identification was developed. Supervised neural network and self-organizing neural network systems were employed. First, they were trained with results from an idealized simulation of impedance in a two-phase mixture. The simulation was mainly based on Mishima and Ishii's flow regime map, the drift flux model, and the newly developed model of slug flow. Then, these trained systems were tested with impedance signals. The results showed that the neural network systems were appropriate classifiers of vertical flow regimes. The theoretical models and experimental databases used in the simulation were reliable. Furthermore, this approach was applied successfully to horizontal flow identification. A comprehensive model was developed to predict important characteristics of vertical slug flow. It was realized that the void fraction of the liquid slug is determined by the relative liquid motion between the Taylor bubble tail and the Taylor bubble wake. Relying on this understanding and experimental results, a special relationship was built for the void fraction of the liquid slug. The prediction of the void fraction of the liquid slug was considerably improved. Experimental characterization of vertical slug flows was performed extensively with the impedance void-meter and the magnetic flowmeter. The theoretical predictions were compared with the experimental results. The agreements between them are very satisfactory.
NASA Astrophysics Data System (ADS)
Sciazko, Anna; Komatsu, Yosuke; Brus, Grzegorz; Kimijima, Shinji; Szmyd, Janusz S.
2014-09-01
For a mathematical model based on the result of physical measurements, it becomes possible to determine their influence on the final solution and its accuracy. However, in classical approaches, the influence of different model simplifications on the reliability of the obtained results are usually not comprehensively discussed. This paper presents a novel approach to the study of methane/steam reforming kinetics based on an advanced methodology called the Orthogonal Least Squares method. The kinetics of the reforming process published earlier are divergent among themselves. To obtain the most probable values of kinetic parameters and enable direct and objective model verification, an appropriate calculation procedure needs to be proposed. The applied Generalized Least Squares (GLS) method includes all the experimental results into the mathematical model which becomes internally contradicted, as the number of equations is greater than number of unknown variables. The GLS method is adopted to select the most probable values of results and simultaneously determine the uncertainty coupled with all the variables in the system. In this paper, the evaluation of the reaction rate after the pre-determination of the reaction rate, which was made by preliminary calculation based on the obtained experimental results over a Nickel/Yttria-stabilized Zirconia catalyst, was performed.
Dehdari, Tahereh; Rahimi, Tahereh; Aryaeian, Naheed; Gohari, Mahmood Reza
2014-03-01
To determine the effectiveness of nutrition education intervention based on Pender's Health Promotion Model in improving the frequency and nutrient intake of breakfast consumption among female Iranian students. The quasi-experimental study based on Pender's Health Promotion Model was conducted during April-June 2011. Information (data) was collected by self-administered questionnaire. In addition, a 3 d breakfast record was analysed. P < 0·05 was considered significant. Two middle schools in average-income areas of Qom, Iran. One hundred female middle-school students. There was a significant reduction in immediate competing demands and preferences, perceived barriers and negative activity-related affect constructs in the experimental group after education compared with the control group. In addition, perceived benefit, perceived self-efficacy, positive activity-related affect, interpersonal influences, situational influences, commitment to a plan of action, frequency and intakes of macronutrients and most micronutrients of breakfast consumption were also significantly higher in the experimental group compared with the control group after the nutrition education intervention. Constructs of Pender's Health Promotion Model provide a suitable source for designing strategies and content of a nutrition education intervention for improving the frequency and nutrient intake of breakfast consumption among female students.
Savaşan, Ayşegül; Çam, Olcay
2017-06-01
People with alcohol dependency have lower self-esteem than controls and when their alcohol use increases, their self-esteem decreases. Coping skills in alcohol related issues are predicted to reduce vulnerability to relapse. It is important to adapt care to individual needs so as to prevent a return to the cycle of alcohol use. The Tidal Model focuses on providing support and services to people who need to live a constructive life. The aim of the randomized study was to determine the effect of the psychiatric nursing approach based on the Tidal Model on coping and self-esteem in people with alcohol dependency. The study was semi-experimental in design with a control group, and was conducted on 36 individuals (18 experimental, 18 control). An experimental and a control group were formed by assigning persons to each group using the stratified randomization technique in the order in which they were admitted to hospital. The Coping Inventory (COPE) and the Coopersmith Self-Esteem Inventory (CSEI) were used as measurement instruments. The measurement instruments were applied before the application and three months after the application. In addition to routine treatment and follow-up, the psychiatric nursing approach based on the Tidal Model was applied to the experimental group in the One-to-One Sessions. The psychiatric nursing approach based on the Tidal Model is an approach which is effective in increasing the scores of people with alcohol dependency in positive reinterpretation and growth, active coping, restraint, emotional social support and planning and reducing their scores in behavioral disengagement. It was seen that self-esteem rose, but the difference from the control group did not reach significance. The psychiatric nursing approach based on the Tidal Model has an effect on people with alcohol dependency in maintaining their abstinence. The results of the study may provide practices on a theoretical basis for improving coping behaviors and self-esteem and facilitating the recovery process of alcohol dependents with implications for mental health nursing. Copyright © 2017 Elsevier Inc. All rights reserved.
Gu, Wenwen; Chen, Ying; Li, Yu
2017-08-01
Based on the experimental subcooled liquid vapor pressures (P L ) of 17 polychlorinated naphthalene (PCN) congeners, one type of three-dimensional quantitative structure-activity relationship (3D-QSAR) models, comparative molecular similarity indices analysis (CoMSIA), was constructed with Sybyl software. Full factor experimental design was used to obtain the final regulation scheme for PCN, and then carry out modification of PCN-2 to significantly lower its P L . The contour maps of CoMSIA model showed that the migration ability of PCN decreases when the Cl atoms at the 2-, 3-, 4-, 5-, 6-, 7- and 8-positions of PCNs are replaced by electropositive groups. After modification of PCN-2, 12 types of new modified PCN-2 compounds were obtained with lnP L values two orders of magnitude lower than that of PCN-2. In addition, there are significant differences between the calculated total energies and energy gaps of the new modified compounds and those of PCN-2.
NASA Technical Reports Server (NTRS)
Manchiraju, Sivom; Gaydosh, Darrell; Benafan, Othmane; Noebe, Ronald; Vaidyanathan, Raj; Anderson, Peter M.
2011-01-01
A recent microstructure-based FEM model that couples crystal-based plasticity, the B2<-> MB190 phase transformation and anisotropic elasticity at the grain scale is calibrated to recent data for polycrystalline NiTi (49.9 at.% Ni). Inputs include anisotropic elastic properties, texture and differential scanning calorimetry data, as well as a subset of recent isothermal deformation and load-biased thermal cycling data. The model is assessed against additional experimental data. Several experimental trends are captured - in particular, the transformation strain during thermal cycling monotonically increases and reaches a peak with increasing bias stress. This is achieved, in part, by modifying the martensite hardening matrix proposed by Patoor et al. [Patoor E, Eberhardt A, Berveiller M. J Phys IV 1996;6:277]. Some experimental trends are underestimated - in particular, the ratcheting of macrostrain during thermal cycling. This may reflect a model limitation that transformation-plasticity coupling is captured on a coarse (grain) scale but not on a fine (martensitic plate) scale.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bai, Xian-Xu, E-mail: bai@hfut.edu.cn; Wereley, Norman M.; Hu, Wei
A single-degree-of-freedom (SDOF) semi-active vibration control system based on a magnetorheological (MR) damper with an inner bypass is investigated in this paper. The MR damper employing a pair of concentric tubes, between which the key structure, i.e., the inner bypass, is formed and MR fluids are energized, is designed to provide large dynamic range (i.e., ratio of field-on damping force to field-off damping force) and damping force range. The damping force performance of the MR damper is modeled using phenomenological model and verified by the experimental tests. In order to assess its feasibility and capability in vibration control systems, themore » mathematical model of a SDOF semi-active vibration control system based on the MR damper and skyhook control strategy is established. Using an MTS 244 hydraulic vibration exciter system and a dSPACE DS1103 real-time simulation system, experimental study for the SDOF semi-active vibration control system is also conducted. Simulation results are compared to experimental measurements.« less
Studying light-harvesting models with superconducting circuits.
Potočnik, Anton; Bargerbos, Arno; Schröder, Florian A Y N; Khan, Saeed A; Collodo, Michele C; Gasparinetti, Simone; Salathé, Yves; Creatore, Celestino; Eichler, Christopher; Türeci, Hakan E; Chin, Alex W; Wallraff, Andreas
2018-03-02
The process of photosynthesis, the main source of energy in the living world, converts sunlight into chemical energy. The high efficiency of this process is believed to be enabled by an interplay between the quantum nature of molecular structures in photosynthetic complexes and their interaction with the environment. Investigating these effects in biological samples is challenging due to their complex and disordered structure. Here we experimentally demonstrate a technique for studying photosynthetic models based on superconducting quantum circuits, which complements existing experimental, theoretical, and computational approaches. We demonstrate a high degree of freedom in design and experimental control of our approach based on a simplified three-site model of a pigment protein complex with realistic parameters scaled down in energy by a factor of 10 5 . We show that the excitation transport between quantum-coherent sites disordered in energy can be enabled through the interaction with environmental noise. We also show that the efficiency of the process is maximized for structured noise resembling intramolecular phononic environments found in photosynthetic complexes.
NASA Astrophysics Data System (ADS)
Babakhani, Peyman; Bridge, Jonathan; Doong, Ruey-an; Phenrat, Tanapon
2017-06-01
The continuing rapid expansion of industrial and consumer processes based on nanoparticles (NP) necessitates a robust model for delineating their fate and transport in groundwater. An ability to reliably specify the full parameter set for prediction of NP transport using continuum models is crucial. In this paper we report the reanalysis of a data set of 493 published column experiment outcomes together with their continuum modeling results. Experimental properties were parameterized into 20 factors which are commonly available. They were then used to predict five key continuum model parameters as well as the effluent concentration via artificial neural network (ANN)-based correlations. The Partial Derivatives (PaD) technique and Monte Carlo method were used for the analysis of sensitivities and model-produced uncertainties, respectively. The outcomes shed light on several controversial relationships between the parameters, e.g., it was revealed that the trend of Katt with average pore water velocity was positive. The resulting correlations, despite being developed based on a "black-box" technique (ANN), were able to explain the effects of theoretical parameters such as critical deposition concentration (CDC), even though these parameters were not explicitly considered in the model. Porous media heterogeneity was considered as a parameter for the first time and showed sensitivities higher than those of dispersivity. The model performance was validated well against subsets of the experimental data and was compared with current models. The robustness of the correlation matrices was not completely satisfactory, since they failed to predict the experimental breakthrough curves (BTCs) at extreme values of ionic strengths.
Integrated PK-PD and agent-based modeling in oncology.
Wang, Zhihui; Butner, Joseph D; Cristini, Vittorio; Deisboeck, Thomas S
2015-04-01
Mathematical modeling has become a valuable tool that strives to complement conventional biomedical research modalities in order to predict experimental outcome, generate new medical hypotheses, and optimize clinical therapies. Two specific approaches, pharmacokinetic-pharmacodynamic (PK-PD) modeling, and agent-based modeling (ABM), have been widely applied in cancer research. While they have made important contributions on their own (e.g., PK-PD in examining chemotherapy drug efficacy and resistance, and ABM in describing and predicting tumor growth and metastasis), only a few groups have started to combine both approaches together in an effort to gain more insights into the details of drug dynamics and the resulting impact on tumor growth. In this review, we focus our discussion on some of the most recent modeling studies building on a combined PK-PD and ABM approach that have generated experimentally testable hypotheses. Some future directions are also discussed.
Integrated PK-PD and Agent-Based Modeling in Oncology
Wang, Zhihui; Butner, Joseph D.; Cristini, Vittorio
2016-01-01
Mathematical modeling has become a valuable tool that strives to complement conventional biomedical research modalities in order to predict experimental outcome, generate new medical hypotheses, and optimize clinical therapies. Two specific approaches, pharmacokinetic-pharmacodynamic (PK-PD) modeling, and agent-based modeling (ABM), have been widely applied in cancer research. While they have made important contributions on their own (e.g., PK-PD in examining chemotherapy drug efficacy and resistance, and ABM in describing and predicting tumor growth and metastasis), only a few groups have started to combine both approaches together in an effort to gain more insights into the details of drug dynamics and the resulting impact on tumor growth. In this review, we focus our discussion on some of the most recent modeling studies building on a combined PK-PD and ABM approach that have generated experimentally testable hypotheses. Some future directions are also discussed. PMID:25588379
A combined-slip predictive control of vehicle stability with experimental verification
NASA Astrophysics Data System (ADS)
Jalali, Milad; Hashemi, Ehsan; Khajepour, Amir; Chen, Shih-ken; Litkouhi, Bakhtiar
2018-02-01
In this paper, a model predictive vehicle stability controller is designed based on a combined-slip LuGre tyre model. Variations in the lateral tyre forces due to changes in tyre slip ratios are considered in the prediction model of the controller. It is observed that the proposed combined-slip controller takes advantage of the more accurate tyre model and can adjust tyre slip ratios based on lateral forces of the front axle. This results in an interesting closed-loop response that challenges the notion of braking only the wheels on one side of the vehicle in differential braking. The performance of the proposed controller is evaluated in software simulations and is compared to a similar pure-slip controller. Furthermore, experimental tests are conducted on a rear-wheel drive electric Chevrolet Equinox equipped with differential brakes to evaluate the closed-loop response of the model predictive control controller.
Modeling of Density-Dependent Flow based on the Thermodynamically Constrained Averaging Theory
NASA Astrophysics Data System (ADS)
Weigand, T. M.; Schultz, P. B.; Kelley, C. T.; Miller, C. T.; Gray, W. G.
2016-12-01
The thermodynamically constrained averaging theory (TCAT) has been used to formulate general classes of porous medium models, including new models for density-dependent flow. The TCAT approach provides advantages that include a firm connection between the microscale, or pore scale, and the macroscale; a thermodynamically consistent basis; explicit inclusion of factors such as a diffusion that arises from gradients associated with pressure and activity and the ability to describe both high and low concentration displacement. The TCAT model is presented and closure relations for the TCAT model are postulated based on microscale averages and a parameter estimation is performed on a subset of the experimental data. Due to the sharpness of the fronts, an adaptive moving mesh technique was used to ensure grid independent solutions within the run time constraints. The optimized parameters are then used for forward simulations and compared to the set of experimental data not used for the parameter estimation.
NASA Astrophysics Data System (ADS)
Sutton, Jonathan E.; Guo, Wei; Katsoulakis, Markos A.; Vlachos, Dionisios G.
2016-04-01
Kinetic models based on first principles are becoming common place in heterogeneous catalysis because of their ability to interpret experimental data, identify the rate-controlling step, guide experiments and predict novel materials. To overcome the tremendous computational cost of estimating parameters of complex networks on metal catalysts, approximate quantum mechanical calculations are employed that render models potentially inaccurate. Here, by introducing correlative global sensitivity analysis and uncertainty quantification, we show that neglecting correlations in the energies of species and reactions can lead to an incorrect identification of influential parameters and key reaction intermediates and reactions. We rationalize why models often underpredict reaction rates and show that, despite the uncertainty being large, the method can, in conjunction with experimental data, identify influential missing reaction pathways and provide insights into the catalyst active site and the kinetic reliability of a model. The method is demonstrated in ethanol steam reforming for hydrogen production for fuel cells.
NASA Astrophysics Data System (ADS)
Huang, J. H.; Wang, X. J.; Wang, J.
2016-02-01
The primary purpose of this paper is to propose a mathematical model of PLZT ceramic with coupled multi-physics fields, e.g. thermal, electric, mechanical and light field. To this end, the coupling relationships of multi-physics fields and the mechanism of some effects resulting in the photostrictive effect are analyzed theoretically, based on which a mathematical model considering coupled multi-physics fields is established. According to the analysis and experimental results, the mathematical model can explain the hysteresis phenomenon and the variation trend of the photo-induced voltage very well and is in agreement with the experimental curves. In addition, the PLZT bimorph is applied as an energy transducer for a photovoltaic-electrostatic hybrid actuated micromirror, and the relation of the rotation angle and the photo-induced voltage is discussed based on the novel photostrictive mathematical model.
Pandey, Daya Shankar; Pan, Indranil; Das, Saptarshi; Leahy, James J; Kwapinski, Witold
2015-03-01
A multi-gene genetic programming technique is proposed as a new method to predict syngas yield production and the lower heating value for municipal solid waste gasification in a fluidized bed gasifier. The study shows that the predicted outputs of the municipal solid waste gasification process are in good agreement with the experimental dataset and also generalise well to validation (untrained) data. Published experimental datasets are used for model training and validation purposes. The results show the effectiveness of the genetic programming technique for solving complex nonlinear regression problems. The multi-gene genetic programming are also compared with a single-gene genetic programming model to show the relative merits and demerits of the technique. This study demonstrates that the genetic programming based data-driven modelling strategy can be a good candidate for developing models for other types of fuels as well. Copyright © 2014 Elsevier Ltd. All rights reserved.
Realizing Haldane model in Fe-based honeycomb ferromagnetic insulators
NASA Astrophysics Data System (ADS)
Kim, Heung-Sik; Kee, Hae-Young
2017-12-01
The topological Haldane model on a honeycomb lattice is a prototype of systems hosting topological phases of matter without external fields. It is the simplest model exhibiting the quantum Hall effect without Landau levels, which motivated theoretical and experimental explorations of topological insulators and superconductors. Despite its simplicity, its realization in condensed matter systems has been elusive due to a seemingly difficult condition of spinless fermions with sublattice-dependent magnetic flux terms. While there have been theoretical proposals including elaborate atomic-scale engineering, identifying candidate topological Haldane model materials has not been successful, and the first experimental realization was recently made in ultracold atoms. Here, we suggest that a series of Fe-based honeycomb ferromagnetic insulators, AFe2(PO4)2 (A=Ba, Cs, K, La) possess Chern bands described by the topological Haldane model. How to detect the quantum anomalous Hall effect is also discussed.
Bayesian analysis of physiologically based toxicokinetic and toxicodynamic models.
Hack, C Eric
2006-04-17
Physiologically based toxicokinetic (PBTK) and toxicodynamic (TD) models of bromate in animals and humans would improve our ability to accurately estimate the toxic doses in humans based on available animal studies. These mathematical models are often highly parameterized and must be calibrated in order for the model predictions of internal dose to adequately fit the experimentally measured doses. Highly parameterized models are difficult to calibrate and it is difficult to obtain accurate estimates of uncertainty or variability in model parameters with commonly used frequentist calibration methods, such as maximum likelihood estimation (MLE) or least squared error approaches. The Bayesian approach called Markov chain Monte Carlo (MCMC) analysis can be used to successfully calibrate these complex models. Prior knowledge about the biological system and associated model parameters is easily incorporated in this approach in the form of prior parameter distributions, and the distributions are refined or updated using experimental data to generate posterior distributions of parameter estimates. The goal of this paper is to give the non-mathematician a brief description of the Bayesian approach and Markov chain Monte Carlo analysis, how this technique is used in risk assessment, and the issues associated with this approach.
NASA Astrophysics Data System (ADS)
Tabourot, Laurent; Charleux, Ludovic; Balland, Pascale; Sène, Ndèye Awa; Andreasson, Eskil
2018-05-01
This paper is based on the hypothesis that introducing distribution of mechanical properties is beneficial for modeling all kinds of mechanical behavior, even of ordinary metallic materials. To bring proof of its admissibility, it has to be first shown that modeling based on this assertion is able to efficiently describe standard mechanical behavior of materials. Searching for typical study case, it has been assessed that at a low scale, yield stresses could be strongly distributed in ultrathin aluminum foils used in packaging industry, offering opportunities to identifying their distribution and showing its role on the mechanical properties. Considering initially reduced modeling allow to establish a valuable connection between the hardening curve and the distribution of local yield stresses. This serves for finding initial value of distribution parameters in a more sophisticated identification procedure. With finally limited number of representative classes of local yield stresses, concretely 3 is enough, it is shown that a 3D finite element simulation involving limited numbers of elements returns realistic behavior of an ultrathin aluminum foil exerted to tensile test, in reference to experimental results. This gives way to large possibilities in modeling in order to give back complex experimental evidence.
Dermol, Janja; Miklavčič, Damijan
2014-12-01
High voltage electric pulses cause electroporation of the cell membrane. Consequently, flow of the molecules across the membrane increases. In our study we investigated possibility to predict the percentage of the electroporated cells in an inhomogeneous electric field on the basis of the experimental results obtained when cells were exposed to a homogeneous electric field. We compared and evaluated different mathematical models previously suggested by other authors for interpolation of the results (symmetric sigmoid, asymmetric sigmoid, hyperbolic tangent and Gompertz curve). We investigated the density of the cells and observed that it has the most significant effect on the electroporation of the cells while all four of the mathematical models yielded similar results. We were able to predict electroporation of cells exposed to an inhomogeneous electric field based on mathematical modeling and using mathematical formulations of electroporation probability obtained experimentally using exposure to the homogeneous field of the same density of cells. Models describing cell electroporation probability can be useful for development and presentation of treatment planning for electrochemotherapy and non-thermal irreversible electroporation. Copyright © 2014 Elsevier B.V. All rights reserved.
Stress-based animal models of depression: Do we actually know what we are doing?
Yin, Xin; Guven, Nuri; Dietis, Nikolas
2016-12-01
Depression is one of the leading causes of disability and a significant health-concern worldwide. Much of our current understanding on the pathogenesis of depression and the pharmacology of antidepressant drugs is based on pre-clinical models. Three of the most popular stress-based rodent models are the forced swimming test, the chronic mild stress paradigm and the learned helplessness model. Despite their recognizable advantages and limitations, they are associated with an immense variability due to the high number of design parameters that define them. Only few studies have reported how minor modifications of these parameters affect the model phenotype. Thus, the existing variability in how these models are used has been a strong barrier for drug development as well as benchmark and evaluation of these pre-clinical models of depression. It also has been the source of confusing variability in the experimental outcomes between research groups using the same models. In this review, we summarize the known variability in the experimental protocols, identify the main and relevant parameters for each model and describe the variable values using characteristic examples. Our view of depression and our efforts to discover novel and effective antidepressants is largely based on our detailed knowledge of these testing paradigms, and requires a sound understanding around the importance of individual parameters to optimize and improve these pre-clinical models. Copyright © 2016 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Kayumov, R. A.; Muhamedova, I. Z.; Tazyukov, B. F.; Shakirzjanov, F. R.
2018-03-01
In this paper, based on the analysis of some experimental data, a study and selection of hereditary models of deformation of reinforced polymeric composite materials, such as organic plastic, carbon plastic and a matrix of film-fabric composite, was pursued. On the basis of an analysis of a series of experiments it has been established that organo-plastic samples behave like viscoelastic bodies. It is shown that for sufficiently large load levels, the behavior of the material in question should be described by the relations of the nonlinear theory of heredity. An attempt to describe the process of deformation by means of linear relations of the theory of heredity leads to large discrepancies between the experimental and calculated deformation values. The use of the theory of accumulation of micro-damages leads to much better description of the experimental results. With the help of the hierarchical approach, a good approximation of the experimental values was successful only in the first three sections of loading.
Dynamic Characterization and Modeling of Potting Materials for Electronics Assemblies
NASA Astrophysics Data System (ADS)
Joshi, Vasant; Lee, Gilbert; Santiago, Jaime
2015-06-01
Prediction of survivability of encapsulated electronic components subject to impact relies on accurate modeling. Both static and dynamic characterization of encapsulation material is needed to generate a robust material model. Current focus is on potting materials to mitigate high rate loading on impact. In this effort, encapsulation scheme consists of layers of polymeric material Sylgard 184 and Triggerbond Epoxy-20-3001. Experiments conducted for characterization of materials include conventional tension and compression tests, Hopkinson bar, dynamic material analyzer (DMA) and a non-conventional accelerometer based resonance tests for obtaining high frequency data. For an ideal material, data can be fitted to Williams-Landel-Ferry (WLF) model. A new temperature-time shift (TTS) macro was written to compare idealized temperature shift factor (WLF model) with experimental incremental shift factors. Deviations can be observed by comparison of experimental data with the model fit to determine the actual material behavior. Similarly, another macro written for obtaining Ogden model parameter from Hopkinson Bar tests indicates deviations from experimental high strain rate data. In this paper, experimental results for different materials used for mitigating impact, and ways to combine data from resonance, DMA and Hopkinson bar together with modeling refinements will be presented.
Development of novel therapies for MG: Studies in animal models.
Souroujon, M C; Brenner, T; Fuchs, S
2010-08-01
Experimental myasthenia gravis (MG) in animals, and in particular experimental autoimmune MG in rodents, serves as excellent models to study possible novel therapeutic modalities for MG. The current treatments for MG are based on cholinesterase inhibitors, general immunosuppressants, and corticosteroids, broad immunomodulatory therapies such as plasma exchange or intravenous immunoglobulins (IVIGs), and thymectomy for selected patients. This stresses the need for immunotherapies that would specifically or preferentially suppress the undesirable autoimmune response without widely affecting the entire immune system as most available treatments do. The available animal models for MG enable to perform preclinical studies in which novel therapeutic approaches can be tested. In this review, we describe the different therapeutic approaches that were so far tested in experimental models of MG and discuss their underlying mechanisms of action. These include antigen - acetylcholine receptor (AChR)-dependent treatments aimed at specifically abrogating the humoral and cellular anti-AChR responses as well as immunomodulatory approaches that could be used either alone or in conjunction with antigen-specific treatments or alternatively serve as steroid sparing agents. The antigen-specific treatments are based on fragments or peptides derived from the acetylcholine receptor (AChR) that would theoretically deviate the anti-AChR autoimmune response away from the muscle target or on ways to target AChR-specific T- and B- cell responses or antibodies. The immunomodulatory modalities include cell-based and non-cell-based ways to affect or manipulate key players in the autoimmune process such as regulatory T cells, dendritic cells, cytokine networks, and chemokine and costimulatory signaling as well as complement pathways. We also describe approaches that attempt to affect the cholinergic balance, which is impaired at the neuromuscular junction. In addition to enabling to test the feasibility of novel approaches, experimental MG enables to perform analyses of existing treatment modalities, which cannot be performed in human MG patients. These include studies on the mode of action of various immunosuppressants and on IVIGs. Hopefully, the vast repertoire of therapeutic approaches that are studied in experimental models of MG will pave the way to clinical studies that will eventually improve the management of MG.
Optimization-Based Inverse Identification of the Parameters of a Concrete Cap Material Model
NASA Astrophysics Data System (ADS)
Král, Petr; Hokeš, Filip; Hušek, Martin; Kala, Jiří; Hradil, Petr
2017-10-01
Issues concerning the advanced numerical analysis of concrete building structures in sophisticated computing systems currently require the involvement of nonlinear mechanics tools. The efforts to design safer, more durable and mainly more economically efficient concrete structures are supported via the use of advanced nonlinear concrete material models and the geometrically nonlinear approach. The application of nonlinear mechanics tools undoubtedly presents another step towards the approximation of the real behaviour of concrete building structures within the framework of computer numerical simulations. However, the success rate of this application depends on having a perfect understanding of the behaviour of the concrete material models used and having a perfect understanding of the used material model parameters meaning. The effective application of nonlinear concrete material models within computer simulations often becomes very problematic because these material models very often contain parameters (material constants) whose values are difficult to obtain. However, getting of the correct values of material parameters is very important to ensure proper function of a concrete material model used. Today, one possibility, which permits successful solution of the mentioned problem, is the use of optimization algorithms for the purpose of the optimization-based inverse material parameter identification. Parameter identification goes hand in hand with experimental investigation while it trying to find parameter values of the used material model so that the resulting data obtained from the computer simulation will best approximate the experimental data. This paper is focused on the optimization-based inverse identification of the parameters of a concrete cap material model which is known under the name the Continuous Surface Cap Model. Within this paper, material parameters of the model are identified on the basis of interaction between nonlinear computer simulations, gradient based and nature inspired optimization algorithms and experimental data, the latter of which take the form of a load-extension curve obtained from the evaluation of uniaxial tensile test results. The aim of this research was to obtain material model parameters corresponding to the quasi-static tensile loading which may be further used for the research involving dynamic and high-speed tensile loading. Based on the obtained results it can be concluded that the set goal has been reached.
NASA Technical Reports Server (NTRS)
Fusaro, Robert L.; Jones, Steven P.; Jansen, Ralph
1996-01-01
A complete evaluation of the tribological characteristics of a given material/mechanical system is a time-consuming operation since the friction and wear process is extremely systems sensitive. As a result, experimental designs (i.e., Latin Square, Taguchi) have been implemented in an attempt to not only reduce the total number of experimental combinations needed to fully characterize a material/mechanical system, but also to acquire life data for a system without having to perform an actual life test. Unfortunately, these experimental designs still require a great deal of experimental testing and the output does not always produce meaningful information. In order to further reduce the amount of experimental testing required, this study employs a computer neural network model to investigate different material/mechanical systems. The work focuses on the modeling of the wear behavior, while showing the feasibility of using neural networks to predict life data. The model is capable of defining which input variables will influence the tribological behavior of the particular material/mechanical system being studied based on the specifications of the overall system.
Analysis of neutral beam driven impurity flow reversal in PLT
DOE Office of Scientific and Technical Information (OSTI.GOV)
Malik, M.A.; Stacey, W.M. Jr.; Thomas, C.E.
1986-10-01
The Stacey-Sigmar impurity transport theory for tokamak plasmas is applied to the analysis of experimental data from the PLT tokamak with a tungsten limiter. The drag term, which is a central piece in the theory, is evaluated from the recently developed gyroviscous theory for radial momentum transfer. An effort is made to base the modeling of the experiment on measured quantities. Where measured data is not available, recourse is made to extrapolation or numerical modeling. The theoretical and the experimental tungsten fluxes are shown to agree very closely within the uncertainties of the experimental data.
A Robust Adaptive Autonomous Approach to Optimal Experimental Design
NASA Astrophysics Data System (ADS)
Gu, Hairong
Experimentation is the fundamental tool of scientific inquiries to understand the laws governing the nature and human behaviors. Many complex real-world experimental scenarios, particularly in quest of prediction accuracy, often encounter difficulties to conduct experiments using an existing experimental procedure for the following two reasons. First, the existing experimental procedures require a parametric model to serve as the proxy of the latent data structure or data-generating mechanism at the beginning of an experiment. However, for those experimental scenarios of concern, a sound model is often unavailable before an experiment. Second, those experimental scenarios usually contain a large number of design variables, which potentially leads to a lengthy and costly data collection cycle. Incompetently, the existing experimental procedures are unable to optimize large-scale experiments so as to minimize the experimental length and cost. Facing the two challenges in those experimental scenarios, the aim of the present study is to develop a new experimental procedure that allows an experiment to be conducted without the assumption of a parametric model while still achieving satisfactory prediction, and performs optimization of experimental designs to improve the efficiency of an experiment. The new experimental procedure developed in the present study is named robust adaptive autonomous system (RAAS). RAAS is a procedure for sequential experiments composed of multiple experimental trials, which performs function estimation, variable selection, reverse prediction and design optimization on each trial. Directly addressing the challenges in those experimental scenarios of concern, function estimation and variable selection are performed by data-driven modeling methods to generate a predictive model from data collected during the course of an experiment, thus exempting the requirement of a parametric model at the beginning of an experiment; design optimization is performed to select experimental designs on the fly of an experiment based on their usefulness so that fewest designs are needed to reach useful inferential conclusions. Technically, function estimation is realized by Bayesian P-splines, variable selection is realized by Bayesian spike-and-slab prior, reverse prediction is realized by grid-search and design optimization is realized by the concepts of active learning. The present study demonstrated that RAAS achieves statistical robustness by making accurate predictions without the assumption of a parametric model serving as the proxy of latent data structure while the existing procedures can draw poor statistical inferences if a misspecified model is assumed; RAAS also achieves inferential efficiency by taking fewer designs to acquire useful statistical inferences than non-optimal procedures. Thus, RAAS is expected to be a principled solution to real-world experimental scenarios pursuing robust prediction and efficient experimentation.
Stochastic molecular model of enzymatic hydrolysis of cellulose for ethanol production
2013-01-01
Background During cellulosic ethanol production, cellulose hydrolysis is achieved by synergistic action of cellulase enzyme complex consisting of multiple enzymes with different mode of actions. Enzymatic hydrolysis of cellulose is one of the bottlenecks in the commercialization of the process due to low hydrolysis rates and high cost of enzymes. A robust hydrolysis model that can predict hydrolysis profile under various scenarios can act as an important forecasting tool to improve the hydrolysis process. However, multiple factors affecting hydrolysis: cellulose structure and complex enzyme-substrate interactions during hydrolysis make it diffucult to develop mathematical kinetic models that can simulate hydrolysis in presence of multiple enzymes with high fidelity. In this study, a comprehensive hydrolysis model based on stochastic molecular modeling approch in which each hydrolysis event is translated into a discrete event is presented. The model captures the structural features of cellulose, enzyme properties (mode of actions, synergism, inhibition), and most importantly dynamic morphological changes in the substrate that directly affect the enzyme-substrate interactions during hydrolysis. Results Cellulose was modeled as a group of microfibrils consisting of elementary fibrils bundles, where each elementary fibril was represented as a three dimensional matrix of glucose molecules. Hydrolysis of cellulose was simulated based on Monte Carlo simulation technique. Cellulose hydrolysis results predicted by model simulations agree well with the experimental data from literature. Coefficients of determination for model predictions and experimental values were in the range of 0.75 to 0.96 for Avicel hydrolysis by CBH I action. Model was able to simulate the synergistic action of multiple enzymes during hydrolysis. The model simulations captured the important experimental observations: effect of structural properties, enzyme inhibition and enzyme loadings on the hydrolysis and degree of synergism among enzymes. Conclusions The model was effective in capturing the dynamic behavior of cellulose hydrolysis during action of individual as well as multiple cellulases. Simulations were in qualitative and quantitative agreement with experimental data. Several experimentally observed phenomena were simulated without the need for any additional assumptions or parameter changes and confirmed the validity of using the stochastic molecular modeling approach to quantitatively and qualitatively describe the cellulose hydrolysis. PMID:23638989
Construction of an Exploratory List of Chemicals to Initiate the Search for Halon Alternatives
1991-06-01
of owne-depletion effectiveness is based on atmospheric modeling. The only experimental work is the determination of possible reaction paths and...results, and additional relevant comments. These compounds should be tested in a selective series of experiments based on the insights used in the...will generate initial information with regard to the relative ordering of the compounds in terms of screen properties. Careful experimentation will
MIQSTURE: An Experimental Online Language for Army Tactical Intelligence Information Processing
1978-07-01
algorithms. The most critical component of an active information processing model for Army tactical intelligence is the user interface, which must be based on...1976)** defined some preliminary notions of an active information model centered around a data base that can introspect about its contents and...34An Introspective Data Base for an Active Information Model." OSI Technical Note N76-017, 17 November 1976 1-4 L4 beyond optimistic expectations and
Cultivating engineering innovation ability based on optoelectronic experimental platform
NASA Astrophysics Data System (ADS)
Li, Dangjuan; Wu, Shenjiang
2017-08-01
As the supporting experimental platform of the Xi'an Technological University education reform experimental class, "optical technological innovation experimental platform" integrated the design and comprehensive experiments of the optical multi-class courses. On the basis of summing up the past two years teaching experience, platform pilot projects were improve. It has played a good role by making the use of an open teaching model in the cultivating engineering innovation spirit and scientific thinking of the students.
NASA Technical Reports Server (NTRS)
Bahler, D. D.; Owen, H. A., Jr.; Wilson, T. G.
1978-01-01
A model describing the turning-on period of a power switching transistor in an energy storage voltage step-up converter is presented. Comparisons between an experimental layout and the circuit model during the turning-on interval demonstrate the ability of the model to closely predict the effects of circuit topology on the performance of the converter. A phenomenon of particular importance that is observed in the experimental circuits and is predicted by the model is the deleterious feedback effect of the parasitic emitter lead inductance on the base current waveform during the turning-on interval.
Frequency response function (FRF) based updating of a laser spot welded structure
NASA Astrophysics Data System (ADS)
Zin, M. S. Mohd; Rani, M. N. Abdul; Yunus, M. A.; Sani, M. S. M.; Wan Iskandar Mirza, W. I. I.; Mat Isa, A. A.
2018-04-01
The objective of this paper is to present frequency response function (FRF) based updating as a method for matching the finite element (FE) model of a laser spot welded structure with a physical test structure. The FE model of the welded structure was developed using CQUAD4 and CWELD element connectors, and NASTRAN was used to calculate the natural frequencies, mode shapes and FRF. Minimization of the discrepancies between the finite element and experimental FRFs was carried out using the exceptional numerical capability of NASTRAN Sol 200. The experimental work was performed under free-free boundary conditions using LMS SCADAS. Avast improvement in the finite element FRF was achieved using the frequency response function (FRF) based updating with two different objective functions proposed.
NASA Astrophysics Data System (ADS)
Berge, Bruno; Broutin, Jérôme; Gaton, Hilario; Malet, Géraldine; Simon, Eric; Thieblemont, Florent
2013-03-01
This paper presents experimental results on several liquid lenses based on Electrowetting which are commercially available. It will be shown that larger aperture lenses are basically of the same optical quality than smaller lenses, sometimes reaching the diffraction limit, then opening new kind of applications areas for variable lenses in laser science. Regarding response time, actual performances of liquids lenses based on Electrowetting are presented and compared to a model simulating the internal fluid reorganization, seen as the main source of delay between electrical actuation and optical evolution of the lens. This simplified analytical model is supporting experimental results in various situations (focus and tilt variations), in static and dynamic regimes.
A new region-edge based level set model with applications to image segmentation
NASA Astrophysics Data System (ADS)
Zhi, Xuhao; Shen, Hong-Bin
2018-04-01
Level set model has advantages in handling complex shapes and topological changes, and is widely used in image processing tasks. The image segmentation oriented level set models can be grouped into region-based models and edge-based models, both of which have merits and drawbacks. Region-based level set model relies on fitting to color intensity of separated regions, but is not sensitive to edge information. Edge-based level set model evolves by fitting to local gradient information, but can get easily affected by noise. We propose a region-edge based level set model, which considers saliency information into energy function and fuses color intensity with local gradient information. The evolution of the proposed model is implemented by a hierarchical two-stage protocol, and the experimental results show flexible initialization, robust evolution and precise segmentation.
Hybrid ABC Optimized MARS-Based Modeling of the Milling Tool Wear from Milling Run Experimental Data
García Nieto, Paulino José; García-Gonzalo, Esperanza; Ordóñez Galán, Celestino; Bernardo Sánchez, Antonio
2016-01-01
Milling cutters are important cutting tools used in milling machines to perform milling operations, which are prone to wear and subsequent failure. In this paper, a practical new hybrid model to predict the milling tool wear in a regular cut, as well as entry cut and exit cut, of a milling tool is proposed. The model was based on the optimization tool termed artificial bee colony (ABC) in combination with multivariate adaptive regression splines (MARS) technique. This optimization mechanism involved the parameter setting in the MARS training procedure, which significantly influences the regression accuracy. Therefore, an ABC–MARS-based model was successfully used here to predict the milling tool flank wear (output variable) as a function of the following input variables: the time duration of experiment, depth of cut, feed, type of material, etc. Regression with optimal hyperparameters was performed and a determination coefficient of 0.94 was obtained. The ABC–MARS-based model's goodness of fit to experimental data confirmed the good performance of this model. This new model also allowed us to ascertain the most influential parameters on the milling tool flank wear with a view to proposing milling machine's improvements. Finally, conclusions of this study are exposed. PMID:28787882
García Nieto, Paulino José; García-Gonzalo, Esperanza; Ordóñez Galán, Celestino; Bernardo Sánchez, Antonio
2016-01-28
Milling cutters are important cutting tools used in milling machines to perform milling operations, which are prone to wear and subsequent failure. In this paper, a practical new hybrid model to predict the milling tool wear in a regular cut, as well as entry cut and exit cut, of a milling tool is proposed. The model was based on the optimization tool termed artificial bee colony (ABC) in combination with multivariate adaptive regression splines (MARS) technique. This optimization mechanism involved the parameter setting in the MARS training procedure, which significantly influences the regression accuracy. Therefore, an ABC-MARS-based model was successfully used here to predict the milling tool flank wear (output variable) as a function of the following input variables: the time duration of experiment, depth of cut, feed, type of material, etc . Regression with optimal hyperparameters was performed and a determination coefficient of 0.94 was obtained. The ABC-MARS-based model's goodness of fit to experimental data confirmed the good performance of this model. This new model also allowed us to ascertain the most influential parameters on the milling tool flank wear with a view to proposing milling machine's improvements. Finally, conclusions of this study are exposed.
Modeling of metastable phase formation diagrams for sputtered thin films.
Chang, Keke; Music, Denis; To Baben, Moritz; Lange, Dennis; Bolvardi, Hamid; Schneider, Jochen M
2016-01-01
A method to model the metastable phase formation in the Cu-W system based on the critical surface diffusion distance has been developed. The driver for the formation of a second phase is the critical diffusion distance which is dependent on the solubility of W in Cu and on the solubility of Cu in W. Based on comparative theoretical and experimental data, we can describe the relationship between the solubilities and the critical diffusion distances in order to model the metastable phase formation. Metastable phase formation diagrams for Cu-W and Cu-V thin films are predicted and validated by combinatorial magnetron sputtering experiments. The correlative experimental and theoretical research strategy adopted here enables us to efficiently describe the relationship between the solubilities and the critical diffusion distances in order to model the metastable phase formation during magnetron sputtering.
A New Hybrid Viscoelastic Soft Tissue Model based on Meshless Method for Haptic Surgical Simulation
Bao, Yidong; Wu, Dongmei; Yan, Zhiyuan; Du, Zhijiang
2013-01-01
This paper proposes a hybrid soft tissue model that consists of a multilayer structure and many spheres for surgical simulation system based on meshless. To improve accuracy of the model, tension is added to the three-parameter viscoelastic structure that connects the two spheres. By using haptic device, the three-parameter viscoelastic model (TPM) produces accurate deformationand also has better stress-strain, stress relaxation and creep properties. Stress relaxation and creep formulas have been obtained by mathematical formula derivation. Comparing with the experimental results of the real pig liver which were reported by Evren et al. and Amy et al., the curve lines of stress-strain, stress relaxation and creep of TPM are close to the experimental data of the real liver. Simulated results show that TPM has better real-time, stability and accuracy. PMID:24339837
NASA Astrophysics Data System (ADS)
Mo, Shaoxing; Lu, Dan; Shi, Xiaoqing; Zhang, Guannan; Ye, Ming; Wu, Jianfeng; Wu, Jichun
2017-12-01
Global sensitivity analysis (GSA) and uncertainty quantification (UQ) for groundwater modeling are challenging because of the model complexity and significant computational requirements. To reduce the massive computational cost, a cheap-to-evaluate surrogate model is usually constructed to approximate and replace the expensive groundwater models in the GSA and UQ. Constructing an accurate surrogate requires actual model simulations on a number of parameter samples. Thus, a robust experimental design strategy is desired to locate informative samples so as to reduce the computational cost in surrogate construction and consequently to improve the efficiency in the GSA and UQ. In this study, we develop a Taylor expansion-based adaptive design (TEAD) that aims to build an accurate global surrogate model with a small training sample size. TEAD defines a novel hybrid score function to search informative samples, and a robust stopping criterion to terminate the sample search that guarantees the resulted approximation errors satisfy the desired accuracy. The good performance of TEAD in building global surrogate models is demonstrated in seven analytical functions with different dimensionality and complexity in comparison to two widely used experimental design methods. The application of the TEAD-based surrogate method in two groundwater models shows that the TEAD design can effectively improve the computational efficiency of GSA and UQ for groundwater modeling.
SiC-VJFETs power switching devices: an improved model and parameter optimization technique
NASA Astrophysics Data System (ADS)
Ben Salah, T.; Lahbib, Y.; Morel, H.
2009-12-01
Silicon carbide junction field effect transistor (SiC-JFETs) is a mature power switch newly applied in several industrial applications. SiC-JFETs are often simulated by Spice model in order to predict their electrical behaviour. Although such a model provides sufficient accuracy for some applications, this paper shows that it presents serious shortcomings in terms of the neglect of the body diode model, among many others in circuit model topology. Simulation correction is then mandatory and a new model should be proposed. Moreover, this paper gives an enhanced model based on experimental dc and ac data. New devices are added to the conventional circuit model giving accurate static and dynamic behaviour, an effect not accounted in the Spice model. The improved model is implemented into VHDL-AMS language and steady-state dynamic and transient responses are simulated for many SiC-VJFETs samples. Very simple and reliable optimization algorithm based on the optimization of a cost function is proposed to extract the JFET model parameters. The obtained parameters are verified by comparing errors between simulations results and experimental data.
HUMAN BODY SHAPE INDEX BASED ON AN EXPERIMENTALLY DERIVED MODEL OF HUMAN GROWTH
Lebiedowska, Maria K.; Alter, Katharine E.; Stanhope, Steven J.
2009-01-01
Objectives To test the assumption of geometrically similar growth by developing experimentally derived models of human body growth during the age interval of 5–18 years; to use the derived growth models to establish a new Human Body Shape Index (HBSI) based on natural age related changes in HBS; and to compare various metrics of relative body weight (body mass index, ponderal index, HBSI) in a sample of 5–18 year old children. Study design Non-disabled Polish children (N=847) participated in this descriptive study. To model growth, the best fit between body height (H) and body mass (M) was calculated for each sex with the allometric equation M= miHχ. HBSI and HBSI were calculated separately for girls and boys, using sex-specific values for χ and a general HBSI from combined data. The customary body mass and ponderal indices were calculated and compared to HBSI values. Results The models of growth were M=13.11H2.84 (R2=.90) and M=13.64H2.68 (R2=.91) for girls and boys respectively. HBSI values contained less inherent variability and were influenced least by growth (age and height) than customary indices. Conclusion Age-related growth during childhood is sex-specific and not geometrically similar. Therefore, indices of human body shape formulated from experimentally derived models of human growth are superior to customary geometric similarity-based indices for the characterization of human body shape in children during the formative growth years. PMID:18154897
Human body shape index based on an experimentally derived model of human growth.
Lebiedowska, Maria K; Alter, Katharine E; Stanhope, Steven J
2008-01-01
To test the assumption of geometrically similar growth by developing experimentally derived models of human body growth during the age interval of 5 to 18 years; to use these derived growth models to establish a new human body shape index (HBSI) based on natural age-related changes in human body shape (HBS); and to compare various metrics of relative body weight (body mass index [BMI], ponderal index [PI], and HBSI) in a sample of 5- to 18-year-old children. Nondisabled Polish children (n = 847) participated in this descriptive study. To model growth, the best fit between body height (H) and body mass (M) was calculated for each sex using the allometric equation M = m(i) H(chi). HBSI was calculated separately for girls and boys, using sex-specific values for chi and a general HBSI from combined data. The customary BMI and PI were calculated and compared with HBSI values. The models of growth were M = 13.11H(2.84) (R2 = 0.90) for girls and M = 13.64H(2.68) (R2 = 0.91) for boys. HBSI values contained less inherent variability and were less influenced by growth (age and height) compared with BMI and PI. Age-related growth during childhood is sex-specific and not geometrically similar. Therefore, indices of HBS formulated from experimentally derived models of human growth are superior to customary geometric similarity-based indices for characterizing HBS in children during the formative growth years.
Modeling to predict pilot performance during CDTI-based in-trail following experiments
NASA Technical Reports Server (NTRS)
Sorensen, J. A.; Goka, T.
1984-01-01
A mathematical model was developed of the flight system with the pilot using a cockpit display of traffic information (CDTI) to establish and maintain in-trail spacing behind a lead aircraft during approach. Both in-trail and vertical dynamics were included. The nominal spacing was based on one of three criteria (Constant Time Predictor; Constant Time Delay; or Acceleration Cue). This model was used to simulate digitally the dynamics of a string of multiple following aircraft, including response to initial position errors. The simulation was used to predict the outcome of a series of in-trail following experiments, including pilot performance in maintaining correct longitudinal spacing and vertical position. The experiments were run in the NASA Ames Research Center multi-cab cockpit simulator facility. The experimental results were then used to evaluate the model and its prediction accuracy. Model parameters were adjusted, so that modeled performance matched experimental results. Lessons learned in this modeling and prediction study are summarized.
The Langley Research Center CSI phase-0 evolutionary model testbed-design and experimental results
NASA Technical Reports Server (NTRS)
Belvin, W. K.; Horta, Lucas G.; Elliott, K. B.
1991-01-01
A testbed for the development of Controls Structures Interaction (CSI) technology is described. The design philosophy, capabilities, and early experimental results are presented to introduce some of the ongoing CSI research at NASA-Langley. The testbed, referred to as the Phase 0 version of the CSI Evolutionary model (CEM), is the first stage of model complexity designed to show the benefits of CSI technology and to identify weaknesses in current capabilities. Early closed loop test results have shown non-model based controllers can provide an order of magnitude increase in damping in the first few flexible vibration modes. Model based controllers for higher performance will need to be robust to model uncertainty as verified by System ID tests. Data are presented that show finite element model predictions of frequency differ from those obtained from tests. Plans are also presented for evolution of the CEM to study integrated controller and structure design as well as multiple payload dynamics.
Barbarich-Marsteller, Nicole C.; Underwood, Mark D.; Foltin, Richard W.; Myers, Michael M.; Walsh, B. Timothy; Barrett, Jeffrey S.; Marsteller, Douglas A.
2018-01-01
Objective Activity-based anorexia is a translational rodent model that results in severe weight loss, hyperactivity, and voluntary self-starvation. The goal of our investigation was to identify vulnerable and resistant phenotypes of activity-based anorexia in adolescent female rats. Method Sprague-Dawley rats were maintained under conditions of restricted access to food (N = 64; or unlimited access, N = 16) until experimental exit, predefined as a target weight loss of 30–35% or meeting predefined criteria for animal health. Nonlinear mixed effects statistical modeling was used to describe wheel running behavior, time to event analysis was used to assess experimental exit, and a regressive partitioning algorithm was used to classify phenotypes. Results Objective criteria were identified for distinguishing novel phenotypes of activity-based anorexia, including a vulnerable phenotype that conferred maximal hyperactivity, minimal food intake, and the shortest time to experimental exit, and a resistant phenotype that conferred minimal activity and the longest time to experimental exit. Discussion The identification of objective criteria for defining vulnerable and resistant phenotypes of activity-based anorexia in adolescent female rats provides an important framework for studying the neural mechanisms that promote vulnerability to or protection against the development of self-starvation and hyperactivity during adolescence. Ultimately, future studies using these novel phenotypes may provide important translational insights into the mechanisms that promote these maladaptive behaviors characteristic of anorexia nervosa. PMID:23853140
Barbarich-Marsteller, Nicole C; Underwood, Mark D; Foltin, Richard W; Myers, Michael M; Walsh, B Timothy; Barrett, Jeffrey S; Marsteller, Douglas A
2013-11-01
Activity-based anorexia is a translational rodent model that results in severe weight loss, hyperactivity, and voluntary self-starvation. The goal of our investigation was to identify vulnerable and resistant phenotypes of activity-based anorexia in adolescent female rats. Sprague-Dawley rats were maintained under conditions of restricted access to food (N = 64; or unlimited access, N = 16) until experimental exit, predefined as a target weight loss of 30-35% or meeting predefined criteria for animal health. Nonlinear mixed effects statistical modeling was used to describe wheel running behavior, time to event analysis was used to assess experimental exit, and a regressive partitioning algorithm was used to classify phenotypes. Objective criteria were identified for distinguishing novel phenotypes of activity-based anorexia, including a vulnerable phenotype that conferred maximal hyperactivity, minimal food intake, and the shortest time to experimental exit, and a resistant phenotype that conferred minimal activity and the longest time to experimental exit. The identification of objective criteria for defining vulnerable and resistant phenotypes of activity-based anorexia in adolescent female rats provides an important framework for studying the neural mechanisms that promote vulnerability to or protection against the development of self-starvation and hyperactivity during adolescence. Ultimately, future studies using these novel phenotypes may provide important translational insights into the mechanisms that promote these maladaptive behaviors characteristic of anorexia nervosa. Copyright © 2013 Wiley Periodicals, Inc.
Affective Dynamics of Leadership: An Experimental Test of Affect Control Theory
ERIC Educational Resources Information Center
Schroder, Tobias; Scholl, Wolfgang
2009-01-01
Affect Control Theory (ACT; Heise 1979, 2007) states that people control social interactions by striving to maintain culturally shared feelings about the situation. The theory is based on mathematical models of language-based impression formation. In a laboratory experiment, we tested the predictive power of a new German-language ACT model with…
Impact of Model-Based Teaching on Argumentation Skills
ERIC Educational Resources Information Center
Ogan-Bekiroglu, Feral; Belek, Deniz Eren
2014-01-01
The purpose of this study was to examine effects of model-based teaching on students' argumentation skills. Experimental design guided to the research. The participants of the study were pre-service physics teachers. The argumentative intervention lasted seven weeks. Data for this research were collected via video recordings and written arguments.…
ERIC Educational Resources Information Center
Psycharis, Sarantos
2016-01-01
Computational experiment approach considers models as the fundamental instructional units of Inquiry Based Science and Mathematics Education (IBSE) and STEM Education, where the model take the place of the "classical" experimental set-up and simulation replaces the experiment. Argumentation in IBSE and STEM education is related to the…
NASA Technical Reports Server (NTRS)
Conley, Julianne M.; Leonard, B. P.
1994-01-01
The modified mixing length (MML) turbulence model was installed in the Proteus Navier-Stokes code, then modified to make it applicable to a wider range of flows typical of aerospace propulsion applications. The modifications are based on experimental data for three flat-plate flows having zero, mild adverse, and strong adverse pressure gradients. Three transonic diffuser test cases were run with the new version of the model in order to evaluate its performance. All results are compared with experimental data and show improvements over calculations made using the Baldwin-Lomax turbulence model, the standard algebraic model in Proteus.
Model identification methodology for fluid-based inerters
NASA Astrophysics Data System (ADS)
Liu, Xiaofu; Jiang, Jason Zheng; Titurus, Branislav; Harrison, Andrew
2018-06-01
Inerter is the mechanical dual of the capacitor via the force-current analogy. It has the property that the force across the terminals is proportional to their relative acceleration. Compared with flywheel-based inerters, fluid-based forms have advantages of improved durability, inherent damping and simplicity of design. In order to improve the understanding of the physical behaviour of this fluid-based device, especially caused by the hydraulic resistance and inertial effects in the external tube, this work proposes a comprehensive model identification methodology. Firstly, a modelling procedure is established, which allows the topological arrangement of the mechanical networks to be obtained by mapping the damping, inertance and stiffness effects directly to their respective hydraulic counterparts. Secondly, an experimental sequence is followed, which separates the identification of friction, stiffness and various damping effects. Furthermore, an experimental set-up is introduced, where two pressure gauges are used to accurately measure the pressure drop across the external tube. The theoretical models with improved confidence are obtained using the proposed methodology for a helical-tube fluid inerter prototype. The sources of remaining discrepancies are further analysed.
Theoretical and experimental study of a thruster discharging a weight
NASA Astrophysics Data System (ADS)
Michaels, Dan; Gany, Alon
2014-06-01
An innovative concept for a rocket type thruster that can be beneficial for spacecraft trajectory corrections and station keeping was investigated both experimentally and theoretically. It may also be useful for divert and attitude control systems (DACS). The thruster is based on a combustion chamber discharging a weight through an exhaust tube. Calculations with granular double-base propellant and a solid ejected weight reveal that a specific impulse based on the propellant mass of well above 400 s can be obtained. An experimental thruster was built in order to demonstrate the new idea and validate the model. The thruster impulse was measured both directly with a load cell and indirectly by using a pressure transducer and high speed photography of the weight as it exits the tube, with both ways producing very similar total impulse measurement. The good correspondence between the computations and the measured data validates the model as a useful tool for studying and designing such a thruster.
Soulis, Konstantinos X; Valiantzas, John D; Ntoulas, Nikolaos; Kargas, George; Nektarios, Panayiotis A
2017-09-15
In spite of the well-known green roof benefits, their widespread adoption in the management practices of urban drainage systems requires the use of adequate analytical and modelling tools. In the current study, green roof runoff modeling was accomplished by developing, testing, and jointly using a simple conceptual model and a physically based numerical simulation model utilizing HYDRUS-1D software. The use of such an approach combines the advantages of the conceptual model, namely simplicity, low computational requirements, and ability to be easily integrated in decision support tools with the capacity of the physically based simulation model to be easily transferred in conditions and locations other than those used for calibrating and validating it. The proposed approach was evaluated with an experimental dataset that included various green roof covers (either succulent plants - Sedum sediforme, or xerophytic plants - Origanum onites, or bare substrate without any vegetation) and two substrate depths (either 8 cm or 16 cm). Both the physically based and the conceptual models matched very closely the observed hydrographs. In general, the conceptual model performed better than the physically based simulation model but the overall performance of both models was sufficient in most cases as it is revealed by the Nash-Sutcliffe Efficiency index which was generally greater than 0.70. Finally, it was showcased how a physically based and a simple conceptual model can be jointly used to allow the use of the simple conceptual model for a wider set of conditions than the available experimental data and in order to support green roof design. Copyright © 2017 Elsevier Ltd. All rights reserved.
Numerical modelling of distributed vibration sensor based on phase-sensitive OTDR
NASA Astrophysics Data System (ADS)
Masoudi, A.; Newson, T. P.
2017-04-01
A Distributed Vibration Sensor Based on Phase-Sensitive OTDR is numerically modeled. The advantage of modeling the building blocks of the sensor individually and combining the blocks to analyse the behavior of the sensing system is discussed. It is shown that the numerical model can accurately imitate the response of the experimental setup to dynamic perturbations a signal processing procedure similar to that used to extract the phase information from sensing setup.
3D reconstruction of the magnetic vector potential using model based iterative reconstruction
DOE Office of Scientific and Technical Information (OSTI.GOV)
Prabhat, K. C.; Aditya Mohan, K.; Phatak, Charudatta
Lorentz transmission electron microscopy (TEM) observations of magnetic nanoparticles contain information on the magnetic and electrostatic potentials. Vector field electron tomography (VFET) can be used to reconstruct electromagnetic potentials of the nanoparticles from their corresponding LTEM images. The VFET approach is based on the conventional filtered back projection approach to tomographic reconstructions and the availability of an incomplete set of measurements due to experimental limitations means that the reconstructed vector fields exhibit significant artifacts. In this paper, we outline a model-based iterative reconstruction (MBIR) algorithm to reconstruct the magnetic vector potential of magnetic nanoparticles. We combine a forward model formore » image formation in TEM experiments with a prior model to formulate the tomographic problem as a maximum a-posteriori probability estimation problem (MAP). The MAP cost function is minimized iteratively to determine the vector potential. Here, a comparative reconstruction study of simulated as well as experimental data sets show that the MBIR approach yields quantifiably better reconstructions than the VFET approach.« less
NASA Astrophysics Data System (ADS)
Wang, Weiguang; Shu, Gequn; Tian, Hua; Zhu, Xiuping
2018-06-01
A stationary and a transient two-dimensional models, based on the universal conservation laws and coupled with electrochemical reactions, are firstly applied to describe a single thermally-regenerative ammonia-based flow battery (TR-AFB), and emphasis is placed on studying the effects of reactant concentrations, physical properties of the electrolyte, flow rates and geometric parameters of flow channels on the battery performance. The model includes several experimental parameters measured by cyclic voltammetry (CV), chronoamperometry (CA) and Tafel plot. The results indicate that increasing NH3 concentration has a decisive effect on the improvement of power production and is beneficial to use higher Cu2+ concentrations, but the endurance of membrane and self-discharge need to be considered at the same time. It is also suggested that appropriately reducing the initial Cu(NH3)42+ concentration can promote power and energy densities and mitigate cyclical fluctuation. The relation between the energy and power densities is given, and the models are validated by some experimental data.
3D reconstruction of the magnetic vector potential using model based iterative reconstruction.
Prabhat, K C; Aditya Mohan, K; Phatak, Charudatta; Bouman, Charles; De Graef, Marc
2017-11-01
Lorentz transmission electron microscopy (TEM) observations of magnetic nanoparticles contain information on the magnetic and electrostatic potentials. Vector field electron tomography (VFET) can be used to reconstruct electromagnetic potentials of the nanoparticles from their corresponding LTEM images. The VFET approach is based on the conventional filtered back projection approach to tomographic reconstructions and the availability of an incomplete set of measurements due to experimental limitations means that the reconstructed vector fields exhibit significant artifacts. In this paper, we outline a model-based iterative reconstruction (MBIR) algorithm to reconstruct the magnetic vector potential of magnetic nanoparticles. We combine a forward model for image formation in TEM experiments with a prior model to formulate the tomographic problem as a maximum a-posteriori probability estimation problem (MAP). The MAP cost function is minimized iteratively to determine the vector potential. A comparative reconstruction study of simulated as well as experimental data sets show that the MBIR approach yields quantifiably better reconstructions than the VFET approach. Copyright © 2017 Elsevier B.V. All rights reserved.
3D reconstruction of the magnetic vector potential using model based iterative reconstruction
Prabhat, K. C.; Aditya Mohan, K.; Phatak, Charudatta; ...
2017-07-03
Lorentz transmission electron microscopy (TEM) observations of magnetic nanoparticles contain information on the magnetic and electrostatic potentials. Vector field electron tomography (VFET) can be used to reconstruct electromagnetic potentials of the nanoparticles from their corresponding LTEM images. The VFET approach is based on the conventional filtered back projection approach to tomographic reconstructions and the availability of an incomplete set of measurements due to experimental limitations means that the reconstructed vector fields exhibit significant artifacts. In this paper, we outline a model-based iterative reconstruction (MBIR) algorithm to reconstruct the magnetic vector potential of magnetic nanoparticles. We combine a forward model formore » image formation in TEM experiments with a prior model to formulate the tomographic problem as a maximum a-posteriori probability estimation problem (MAP). The MAP cost function is minimized iteratively to determine the vector potential. Here, a comparative reconstruction study of simulated as well as experimental data sets show that the MBIR approach yields quantifiably better reconstructions than the VFET approach.« less
Antolín, Diego; Medrano, Nicolás; Calvo, Belén; Martínez, Pedro A
2017-08-04
This paper presents a low-cost high-efficiency solar energy harvesting system to power outdoor wireless sensor nodes. It is based on a Voltage Open Circuit (VOC) algorithm that estimates the open-circuit voltage by means of a multilayer perceptron neural network model trained using local experimental characterization data, which are acquired through a novel low cost characterization system incorporated into the deployed node. Both units-characterization and modelling-are controlled by the same low-cost microcontroller, providing a complete solution which can be understood as a virtual pilot cell, with identical characteristics to those of the specific small solar cell installed on the sensor node, that besides allows an easy adaptation to changes in the actual environmental conditions, panel aging, etc. Experimental comparison to a classical pilot panel based VOC algorithm show better efficiency under the same tested conditions.
NASA Astrophysics Data System (ADS)
Peng, Chong; Wang, Lun; Liao, T. Warren
2015-10-01
Currently, chatter has become the critical factor in hindering machining quality and productivity in machining processes. To avoid cutting chatter, a new method based on dynamic cutting force simulation model and support vector machine (SVM) is presented for the prediction of chatter stability lobes. The cutting force is selected as the monitoring signal, and the wavelet energy entropy theory is used to extract the feature vectors. A support vector machine is constructed using the MATLAB LIBSVM toolbox for pattern classification based on the feature vectors derived from the experimental cutting data. Then combining with the dynamic cutting force simulation model, the stability lobes diagram (SLD) can be estimated. Finally, the predicted results are compared with existing methods such as zero-order analytical (ZOA) and semi-discretization (SD) method as well as actual cutting experimental results to confirm the validity of this new method.
Theoretical and Experimental Estimations of Volumetric Inductive Phase Shift in Breast Cancer Tissue
NASA Astrophysics Data System (ADS)
González, C. A.; Lozano, L. M.; Uscanga, M. C.; Silva, J. G.; Polo, S. M.
2013-04-01
Impedance measurements based on magnetic induction for breast cancer detection has been proposed in some studies. This study evaluates theoretical and experimentally the use of a non-invasive technique based on magnetic induction for detection of patho-physiological conditions in breast cancer tissue associated to its volumetric electrical conductivity changes through inductive phase shift measurements. An induction coils-breast 3D pixel model was designed and tested. The model involves two circular coils coaxially centered and a human breast volume centrally placed with respect to the coils. A time-harmonic numerical simulation study addressed the effects of frequency-dependent electrical properties of tumoral tissue on the volumetric inductive phase shift of the breast model measured with the circular coils as inductor and sensor elements. Experimentally; five female volunteer patients with infiltrating ductal carcinoma previously diagnosed by the radiology and oncology departments of the Specialty Clinic for Women of the Mexican Army were measured by an experimental inductive spectrometer and the use of an ergonomic inductor-sensor coil designed to estimate the volumetric inductive phase shift in human breast tissue. Theoretical and experimental inductive phase shift estimations were developed at four frequencies: 0.01, 0.1, 1 and 10 MHz. The theoretical estimations were qualitatively in agreement with the experimental findings. Important increments in volumetric inductive phase shift measurements were evident at 0.01MHz in theoretical and experimental observations. The results suggest that the tested technique has the potential to detect pathological conditions in breast tissue associated to cancer by non-invasive monitoring. Further complementary studies are warranted to confirm the observations.
KiMoSys: a web-based repository of experimental data for KInetic MOdels of biological SYStems
2014-01-01
Background The kinetic modeling of biological systems is mainly composed of three steps that proceed iteratively: model building, simulation and analysis. In the first step, it is usually required to set initial metabolite concentrations, and to assign kinetic rate laws, along with estimating parameter values using kinetic data through optimization when these are not known. Although the rapid development of high-throughput methods has generated much omics data, experimentalists present only a summary of obtained results for publication, the experimental data files are not usually submitted to any public repository, or simply not available at all. In order to automatize as much as possible the steps of building kinetic models, there is a growing requirement in the systems biology community for easily exchanging data in combination with models, which represents the main motivation of KiMoSys development. Description KiMoSys is a user-friendly platform that includes a public data repository of published experimental data, containing concentration data of metabolites and enzymes and flux data. It was designed to ensure data management, storage and sharing for a wider systems biology community. This community repository offers a web-based interface and upload facility to turn available data into publicly accessible, centralized and structured-format data files. Moreover, it compiles and integrates available kinetic models associated with the data. KiMoSys also integrates some tools to facilitate the kinetic model construction process of large-scale metabolic networks, especially when the systems biologists perform computational research. Conclusions KiMoSys is a web-based system that integrates a public data and associated model(s) repository with computational tools, providing the systems biology community with a novel application facilitating data storage and sharing, thus supporting construction of ODE-based kinetic models and collaborative research projects. The web application implemented using Ruby on Rails framework is freely available for web access at http://kimosys.org, along with its full documentation. PMID:25115331
Sensitivity analysis of navy aviation readiness based sparing model
2017-09-01
variability. (See Figure 4.) Figure 4. Research design flowchart 18 Figure 4 lays out the four steps of the methodology , starting in the upper left-hand...as a function of changes in key inputs. We develop NAVARM Experimental Designs (NED), a computational tool created by applying a state-of-the-art...experimental design to the NAVARM model. Statistical analysis of the resulting data identifies the most influential cost factors. Those are, in order of
Paolo Benettin; Scott W. Bailey; John L. Campbell; Mark B. Green; Andrea Rinaldo; Gene E. Likens; Kevin J. McGuire; Gianluca Botter
2015-01-01
We combine experimental and modeling results from a headwater catchment at the Hubbard Brook Experimental Forest (HBEF), New Hampshire, USA, to explore the link between stream solute dynamics and water age. A theoretical framework based on water age dynamics, which represents a general basis for characterizing solute transport at the catchment scale, is here applied to...
NASA Astrophysics Data System (ADS)
Dudin, S. M.; Novitskiy, D. V.
2018-05-01
The works of researchers at VNIIgaz, Giprovostokneft, Kuibyshev NIINP, Grozny Petroleum Institute, etc., are devoted to modeling heterogeneous medium flows in pipelines under laboratory conditions. In objective consideration, the empirical relationships obtained and the calculation procedures for pipelines transporting multiphase products are a bank of experimental data on the problem of pipeline transportation of multiphase systems. Based on the analysis of the published works, the main design requirements for experimental installations designed to study the flow regimes of gas-liquid flows in pipelines were formulated, which were taken into account by the authors when creating the experimental stand. The article describes the results of experimental studies of the flow regimes of a gas-liquid mixture in a pipeline, and also gives a methodological description of the experimental installation. Also the article describes the software of the experimental scientific and educational stand developed with the participation of the authors.
The flaws and human harms of animal experimentation.
Akhtar, Aysha
2015-10-01
Nonhuman animal ("animal") experimentation is typically defended by arguments that it is reliable, that animals provide sufficiently good models of human biology and diseases to yield relevant information, and that, consequently, its use provides major human health benefits. I demonstrate that a growing body of scientific literature critically assessing the validity of animal experimentation generally (and animal modeling specifically) raises important concerns about its reliability and predictive value for human outcomes and for understanding human physiology. The unreliability of animal experimentation across a wide range of areas undermines scientific arguments in favor of the practice. Additionally, I show how animal experimentation often significantly harms humans through misleading safety studies, potential abandonment of effective therapeutics, and direction of resources away from more effective testing methods. The resulting evidence suggests that the collective harms and costs to humans from animal experimentation outweigh potential benefits and that resources would be better invested in developing human-based testing methods.
Holmes, N G; Wieman, Carl E; Bonn, D A
2015-09-08
The ability to make decisions based on data, with its inherent uncertainties and variability, is a complex and vital skill in the modern world. The need for such quantitative critical thinking occurs in many different contexts, and although it is an important goal of education, that goal is seldom being achieved. We argue that the key element for developing this ability is repeated practice in making decisions based on data, with feedback on those decisions. We demonstrate a structure for providing suitable practice that can be applied in any instructional setting that involves the acquisition of data and relating that data to scientific models. This study reports the results of applying that structure in an introductory physics laboratory course. Students in an experimental condition were repeatedly instructed to make and act on quantitative comparisons between datasets, and between data and models, an approach that is common to all science disciplines. These instructions were slowly faded across the course. After the instructions had been removed, students in the experimental condition were 12 times more likely to spontaneously propose or make changes to improve their experimental methods than a control group, who performed traditional experimental activities. The students in the experimental condition were also four times more likely to identify and explain a limitation of a physical model using their data. Students in the experimental condition also showed much more sophisticated reasoning about their data. These differences between the groups were seen to persist into a subsequent course taken the following year.
Holmes, N. G.; Wieman, Carl E.; Bonn, D. A.
2015-01-01
The ability to make decisions based on data, with its inherent uncertainties and variability, is a complex and vital skill in the modern world. The need for such quantitative critical thinking occurs in many different contexts, and although it is an important goal of education, that goal is seldom being achieved. We argue that the key element for developing this ability is repeated practice in making decisions based on data, with feedback on those decisions. We demonstrate a structure for providing suitable practice that can be applied in any instructional setting that involves the acquisition of data and relating that data to scientific models. This study reports the results of applying that structure in an introductory physics laboratory course. Students in an experimental condition were repeatedly instructed to make and act on quantitative comparisons between datasets, and between data and models, an approach that is common to all science disciplines. These instructions were slowly faded across the course. After the instructions had been removed, students in the experimental condition were 12 times more likely to spontaneously propose or make changes to improve their experimental methods than a control group, who performed traditional experimental activities. The students in the experimental condition were also four times more likely to identify and explain a limitation of a physical model using their data. Students in the experimental condition also showed much more sophisticated reasoning about their data. These differences between the groups were seen to persist into a subsequent course taken the following year. PMID:26283351
Caccavale, Justin; Fiumara, David; Stapf, Michael; Sweitzer, Liedeke; Anderson, Hannah J; Gorky, Jonathan; Dhurjati, Prasad; Galileo, Deni S
2017-12-11
Glioblastoma multiforme (GBM) is a devastating brain cancer for which there is no known cure. Its malignancy is due to rapid cell division along with high motility and invasiveness of cells into the brain tissue. Simple 2-dimensional laboratory assays (e.g., a scratch assay) commonly are used to measure the effects of various experimental perturbations, such as treatment with chemical inhibitors. Several mathematical models have been developed to aid the understanding of the motile behavior and proliferation of GBM cells. However, many are mathematically complicated, look at multiple interdependent phenomena, and/or use modeling software not freely available to the research community. These attributes make the adoption of models and simulations of even simple 2-dimensional cell behavior an uncommon practice by cancer cell biologists. Herein, we developed an accurate, yet simple, rule-based modeling framework to describe the in vitro behavior of GBM cells that are stimulated by the L1CAM protein using freely available NetLogo software. In our model L1CAM is released by cells to act through two cell surface receptors and a point of signaling convergence to increase cell motility and proliferation. A simple graphical interface is provided so that changes can be made easily to several parameters controlling cell behavior, and behavior of the cells is viewed both pictorially and with dedicated graphs. We fully describe the hierarchical rule-based modeling framework, show simulation results under several settings, describe the accuracy compared to experimental data, and discuss the potential usefulness for predicting future experimental outcomes and for use as a teaching tool for cell biology students. It is concluded that this simple modeling framework and its simulations accurately reflect much of the GBM cell motility behavior observed experimentally in vitro in the laboratory. Our framework can be modified easily to suit the needs of investigators interested in other similar intrinsic or extrinsic stimuli that influence cancer or other cell behavior. This modeling framework of a commonly used experimental motility assay (scratch assay) should be useful to both researchers of cell motility and students in a cell biology teaching laboratory.
Erosion of graphite surface exposed to hot supersonic hydrogen gas
NASA Technical Reports Server (NTRS)
Sharma, O. P.
1972-01-01
A theoretical model based on laminar boundary layer flow equations was developed to predict the erosion rate of a graphite (AGCarb-101) surface exposed to a hot supersonic stream of hydrogen gas. The supersonic flow in the nozzle outside the boundary layer formed over the surface of the specimen was determined by assuming one-dimensional isentropic conditions. An overall surface reaction rate expression based on experimental studies was used to describe the interaction of hydrogen with graphite. A satisfactory agreement was found between the results of the computation, and the available experimental data. Some shortcomings of the model and further possible improvements are discussed.
Fan, Ang-Xiao; Dakpé, Stéphanie; Dao, Tien Tuan; Pouletaut, Philippe; Rachik, Mohamed; Ho Ba Tho, Marie Christine
2017-07-01
Finite element simulation of facial mimics provides objective indicators about soft tissue functions for improving diagnosis, treatment and follow-up of facial disorders. There is a lack of in vivo experimental data for model development and validation. In this study, the contribution of the paired Zygomaticus Major (ZM) muscle contraction on the facial mimics was investigated using in vivo experimental data derived from MRI. Maximal relative differences of 7.7% and 37% were noted between MRI-based measurements and numerical outcomes for ZM and skin deformation behaviors respectively. This study opens a new direction to simulate facial mimics with in vivo data.
Erosion of graphite surface exposed to hot supersonic hydrogen gas
NASA Technical Reports Server (NTRS)
Sharma, O. P.
1972-01-01
A theoretical model based on laminar boundary layer flow equations is developed to predict the erosion rate of a graphite (AGCarb-101) surface exposed to a hot supersonic stream of hydrogen gas. The supersonic flow in the nozzle outside the boundary layer formed over the surface of the specimen is determined by assuming one-dimensional isentropic conditions. An overall surface reaction rate expression based on the experimental studies by Clarke and Fox is used to describe the interaction of hydrogen with graphite. A satisfactory agreement is found between the results of the computation, and the available experimental data. Some shortcomings of the model, and further possible improvements are discussed.
Zhu, A-Xing; Chen, La-Jiao; Qin, Cheng-Zhi; Wang, Ping; Liu, Jun-Zhi; Li, Run-Kui; Cai, Qiang-Guo
2012-07-01
With the increase of severe soil erosion problem, soil and water conservation has become an urgent concern for sustainable development. Small watershed experimental observation is the traditional paradigm for soil and water control. However, the establishment of experimental watershed usually takes long time, and has the limitations of poor repeatability and high cost. Moreover, the popularization of the results from the experimental watershed is limited for other areas due to the differences in watershed conditions. Therefore, it is not sufficient to completely rely on this old paradigm for soil and water loss control. Recently, scenario analysis based on watershed modeling has been introduced into watershed management, which can provide information about the effectiveness of different management practices based on the quantitative simulation of watershed processes. Because of its merits such as low cost, short period, and high repeatability, scenario analysis shows great potential in aiding the development of watershed management strategy. This paper elaborated a new paradigm using watershed modeling and scenario analysis for soil and water conservation, illustrated this new paradigm through two cases for practical watershed management, and explored the future development of this new soil and water conservation paradigm.
Ahmed, Hafiz; Salgado, Ivan; Ríos, Héctor
2018-02-01
Robust synchronization of master slave chaotic systems are considered in this work. First an approximate model of the error system is obtained using the ultra-local model concept. Then a Continuous Singular Terminal Sliding-Mode (CSTSM) Controller is designed for the purpose of synchronization. The proposed approach is output feedback-based and uses fixed-time higher order sliding-mode (HOSM) differentiator for state estimation. Numerical simulation and experimental results are given to show the effectiveness of the proposed technique. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.
Karri, Rama Rao; Sahu, J N
2018-01-15
Zn (II) is one the common pollutant among heavy metals found in industrial effluents. Removal of pollutant from industrial effluents can be accomplished by various techniques, out of which adsorption was found to be an efficient method. Applications of adsorption limits itself due to high cost of adsorbent. In this regard, a low cost adsorbent produced from palm oil kernel shell based agricultural waste is examined for its efficiency to remove Zn (II) from waste water and aqueous solution. The influence of independent process variables like initial concentration, pH, residence time, activated carbon (AC) dosage and process temperature on the removal of Zn (II) by palm kernel shell based AC from batch adsorption process are studied systematically. Based on the design of experimental matrix, 50 experimental runs are performed with each process variable in the experimental range. The optimal values of process variables to achieve maximum removal efficiency is studied using response surface methodology (RSM) and artificial neural network (ANN) approaches. A quadratic model, which consists of first order and second order degree regressive model is developed using the analysis of variance and RSM - CCD framework. The particle swarm optimization which is a meta-heuristic optimization is embedded on the ANN architecture to optimize the search space of neural network. The optimized trained neural network well depicts the testing data and validation data with R 2 equal to 0.9106 and 0.9279 respectively. The outcomes indicates that the superiority of ANN-PSO based model predictions over the quadratic model predictions provided by RSM. Copyright © 2017 Elsevier Ltd. All rights reserved.
Nejad, Mina Motaghi; Nejad, Ghodratollah Shakeri; Tavakol, Heshmatollah; Cheraghi, Maria
2017-06-01
The aim of the study was to determine the effect of the training program based on the Precede model and its main components on improving the quality of life in patients with asthma. It was a randomized quasi-experimental study done on 120 patients with asthma who were referred to the Imam Khomeini hospital in Ahvaz who were selected using the convenience sampling method and were randomly divided into intervention and control groups. The data collection tool consisted of two questionnaires. The first questionnaire evaluated the quality of life in patients with asthma and the other one was developed by the researcher based on the structures of the Precede model. Training intervention was conducted during four sessions twice a week and each session was carried out for an hour based on the structures of the Precede model. In order to achieve the results, SPSS software, even t -test, and χ 2 were used. The results showed that after the training intervention in the experimental group, the mean scores of predisposing factors ( p < 0.001), enabling factors, reinforcing factors and behavioral factors were significantly increased ( p < 0.001) as compared to the control group. A significant difference was observed in the mean scores of quality of life in two groups after the intervention ( p < 0.001), and the quality of life of patients in the experimental group was improved after the training intervention. The design and implementation of the training program based on the Precede model can have a positive effect on the improvement of quality of life in patients with asthma.
Strauß, Jakob Friedrich; Crain, Philip; Schulenburg, Hinrich; Telschow, Arndt
2016-08-01
Most mathematical models on the evolution of virulence are based on epidemiological models that assume parasite transmission follows the mass action principle. In experimental evolution, however, mass action is often violated due to controlled infection protocols. This "theory-experiment mismatch" raises the question whether there is a need for new mathematical models to accommodate the particular characteristics of experimental evolution. Here, we explore the experimental evolution model system of Bacillus thuringiensis as a parasite and Caenorhabditis elegans as a host. Recent experimental studies with strict control of parasite transmission revealed that one-sided adaptation of B. thuringiensis with non-evolving hosts selects for intermediate or no virulence, sometimes coupled with parasite extinction. In contrast, host-parasite coevolution selects for high virulence and for hosts with strong resistance against B. thuringiensis. In order to explain the empirical results, we propose a new mathematical model that mimics the basic experimental set-up. The key assumptions are: (i) controlled parasite transmission (no mass action), (ii) discrete host generations, and (iii) context-dependent cost of toxin production. Our model analysis revealed the same basic trends as found in the experiments. Especially, we could show that resistant hosts select for highly virulent bacterial strains. Moreover, we found (i) that the evolved level of virulence is independent of the initial level of virulence, and (ii) that the average amount of bacteria ingested significantly affects the evolution of virulence with fewer bacteria ingested selecting for highly virulent strains. These predictions can be tested in future experiments. This study highlights the usefulness of custom-designed mathematical models in the analysis and interpretation of empirical results from experimental evolution. Copyright © 2016 The Authors. Published by Elsevier GmbH.. All rights reserved.
Computational Biochemistry-Enzyme Mechanisms Explored.
Culka, Martin; Gisdon, Florian J; Ullmann, G Matthias
2017-01-01
Understanding enzyme mechanisms is a major task to achieve in order to comprehend how living cells work. Recent advances in biomolecular research provide huge amount of data on enzyme kinetics and structure. The analysis of diverse experimental results and their combination into an overall picture is, however, often challenging. Microscopic details of the enzymatic processes are often anticipated based on several hints from macroscopic experimental data. Computational biochemistry aims at creation of a computational model of an enzyme in order to explain microscopic details of the catalytic process and reproduce or predict macroscopic experimental findings. Results of such computations are in part complementary to experimental data and provide an explanation of a biochemical process at the microscopic level. In order to evaluate the mechanism of an enzyme, a structural model is constructed which can be analyzed by several theoretical approaches. Several simulation methods can and should be combined to get a reliable picture of the process of interest. Furthermore, abstract models of biological systems can be constructed combining computational and experimental data. In this review, we discuss structural computational models of enzymatic systems. We first discuss various models to simulate enzyme catalysis. Furthermore, we review various approaches how to characterize the enzyme mechanism both qualitatively and quantitatively using different modeling approaches. © 2017 Elsevier Inc. All rights reserved.
Ng, Candy K S; Osuna-Sanchez, Hector; Valéry, Eric; Sørensen, Eva; Bracewell, Daniel G
2012-06-15
An integrated experimental and modeling approach for the design of high productivity protein A chromatography is presented to maximize productivity in bioproduct manufacture. The approach consists of four steps: (1) small-scale experimentation, (2) model parameter estimation, (3) productivity optimization and (4) model validation with process verification. The integrated use of process experimentation and modeling enables fewer experiments to be performed, and thus minimizes the time and materials required in order to gain process understanding, which is of key importance during process development. The application of the approach is demonstrated for the capture of antibody by a novel silica-based high performance protein A adsorbent named AbSolute. In the example, a series of pulse injections and breakthrough experiments were performed to develop a lumped parameter model, which was then used to find the best design that optimizes the productivity of a batch protein A chromatographic process for human IgG capture. An optimum productivity of 2.9 kg L⁻¹ day⁻¹ for a column of 5mm diameter and 8.5 cm length was predicted, and subsequently verified experimentally, completing the whole process design approach in only 75 person-hours (or approximately 2 weeks). Copyright © 2012 Elsevier B.V. All rights reserved.
Shen, Xiao-jun; Sun, Jing-sheng; Li, Ming-si; Zhang, Ji-yang; Wang, Jing-lei; Li, Dong-wei
2015-02-01
It is important to improve the real-time irrigation forecasting precision by predicting real-time water consumption of cotton mulched with plastic film under drip irrigation based on meteorological data and cotton growth status. The model parameters for calculating ET0 based on Hargreaves formula were determined using historical meteorological data from 1953 to 2008 in Shihezi reclamation area. According to the field experimental data of growing season in 2009-2010, the model of computing crop coefficient Kc was established based on accumulated temperature. On the basis of crop water requirement (ET0) and Kc, a real-time irrigation forecast model was finally constructed, and it was verified by the field experimental data in 2011. The results showed that the forecast model had high forecasting precision, and the average absolute values of relative error between the predicted value and measured value were about 3.7%, 2.4% and 1.6% during seedling, squaring and blossom-boll forming stages, respectively. The forecast model could be used to modify the predicted values in time according to the real-time meteorological data and to guide the water management in local film-mulched cotton field under drip irrigation.