Optimum surface roughness prediction for titanium alloy by adopting response surface methodology

NASA Astrophysics Data System (ADS)

Yang, Aimin; Han, Yang; Pan, Yuhang; Xing, Hongwei; Li, Jinze

Titanium alloy has been widely applied in industrial engineering products due to its advantages of great corrosion resistance and high specific strength. This paper investigated the processing parameters for finish turning of titanium alloy TC11. Firstly, a three-factor central composite design of experiment, considering the cutting speed, feed rate and depth of cut, are conducted in titanium alloy TC11 and the corresponding surface roughness are obtained. Then a mathematic model is constructed by the response surface methodology to fit the relationship between the process parameters and the surface roughness. The prediction accuracy was verified by the one-way ANOVA. Finally, the contour line of the surface roughness under different combination of process parameters are obtained and used for the optimum surface roughness prediction. Verification experimental results demonstrated that material removal rate (MRR) at the obtained optimum can be significantly improved without sacrificing the surface roughness.

Estimating cellular parameters through optimization procedures: elementary principles and applications.

PubMed

Kimura, Akatsuki; Celani, Antonio; Nagao, Hiromichi; Stasevich, Timothy; Nakamura, Kazuyuki

2015-01-01

Construction of quantitative models is a primary goal of quantitative biology, which aims to understand cellular and organismal phenomena in a quantitative manner. In this article, we introduce optimization procedures to search for parameters in a quantitative model that can reproduce experimental data. The aim of optimization is to minimize the sum of squared errors (SSE) in a prediction or to maximize likelihood. A (local) maximum of likelihood or (local) minimum of the SSE can efficiently be identified using gradient approaches. Addition of a stochastic process enables us to identify the global maximum/minimum without becoming trapped in local maxima/minima. Sampling approaches take advantage of increasing computational power to test numerous sets of parameters in order to determine the optimum set. By combining Bayesian inference with gradient or sampling approaches, we can estimate both the optimum parameters and the form of the likelihood function related to the parameters. Finally, we introduce four examples of research that utilize parameter optimization to obtain biological insights from quantified data: transcriptional regulation, bacterial chemotaxis, morphogenesis, and cell cycle regulation. With practical knowledge of parameter optimization, cell and developmental biologists can develop realistic models that reproduce their observations and thus, obtain mechanistic insights into phenomena of interest.

Optimization for minimum sensitivity to uncertain parameters

NASA Technical Reports Server (NTRS)

Pritchard, Jocelyn I.; Adelman, Howard M.; Sobieszczanski-Sobieski, Jaroslaw

1994-01-01

A procedure to design a structure for minimum sensitivity to uncertainties in problem parameters is described. The approach is to minimize directly the sensitivity derivatives of the optimum design with respect to fixed design parameters using a nested optimization procedure. The procedure is demonstrated for the design of a bimetallic beam for minimum weight with insensitivity to uncertainties in structural properties. The beam is modeled with finite elements based on two dimensional beam analysis. A sequential quadratic programming procedure used as the optimizer supplies the Lagrange multipliers that are used to calculate the optimum sensitivity derivatives. The method was perceived to be successful from comparisons of the optimization results with parametric studies.

Modeling and Optimization of NLDH/PVDF Ultrafiltration Nanocomposite Membrane Using Artificial Neural Network-Genetic Algorithm Hybrid.

PubMed

Arefi-Oskoui, Samira; Khataee, Alireza; Vatanpour, Vahid

2017-07-10

In this research, MgAl-CO 3 2- nanolayered double hydroxide (NLDH) was synthesized through a facile coprecipitation method, followed by a hydrothermal treatment. The prepared NLDHs were used as a hydrophilic nanofiller for improving the performance of the PVDF-based ultrafiltration membranes. The main objective of this research was to obtain the optimized formula of NLDH/PVDF nanocomposite membrane presenting the best performance using computational techniques as a cost-effective method. For this aim, an artificial neural network (ANN) model was developed for modeling and expressing the relationship between the performance of the nanocomposite membrane (pure water flux, protein flux and flux recovery ratio) and the affecting parameters including the NLDH, PVP 29000 and polymer concentrations. The effects of the mentioned parameters and the interaction between the parameters were investigated using the contour plot predicted with the developed model. Scanning electron microscopy (SEM), atomic force microscopy (AFM), and water contact angle techniques were applied to characterize the nanocomposite membranes and to interpret the predictions of the ANN model. The developed ANN model was introduced to genetic algorithm (GA) as a bioinspired optimizer to determine the optimum values of input parameters leading to high pure water flux, protein flux, and flux recovery ratio. The optimum values for NLDH, PVP 29000 and the PVDF concentration were determined to be 0.54, 1, and 18 wt %, respectively. The performance of the nanocomposite membrane prepared using the optimum values proposed by GA was investigated experimentally, in which the results were in good agreement with the values predicted by ANN model with error lower than 6%. This good agreement confirmed that the nanocomposite membranes prformance could be successfully modeled and optimized by ANN-GA system.

An empirical model for parameters affecting energy consumption in boron removal from boron-containing wastewaters by electrocoagulation.

PubMed

Yilmaz, A Erdem; Boncukcuoğlu, Recep; Kocakerim, M Muhtar

2007-06-01

In this study, it was investigated parameters affecting energy consumption in boron removal from boron containing wastewaters prepared synthetically, via electrocoagulation method. The solution pH, initial boron concentration, dose of supporting electrolyte, current density and temperature of solution were selected as experimental parameters affecting energy consumption. The obtained experimental results showed that boron removal efficiency reached up to 99% under optimum conditions, in which solution pH was 8.0, current density 6.0 mA/cm(2), initial boron concentration 100mg/L and solution temperature 293 K. The current density was an important parameter affecting energy consumption too. High current density applied to electrocoagulation cell increased energy consumption. Increasing solution temperature caused to decrease energy consumption that high temperature decreased potential applied under constant current density. That increasing initial boron concentration and dose of supporting electrolyte caused to increase specific conductivity of solution decreased energy consumption. As a result, it was seen that energy consumption for boron removal via electrocoagulation method could be minimized at optimum conditions. An empirical model was predicted by statistically. Experimentally obtained values were fitted with values predicted from empirical model being as following; [formula in text]. Unfortunately, the conditions obtained for optimum boron removal were not the conditions obtained for minimum energy consumption. It was determined that support electrolyte must be used for increase boron removal and decrease electrical energy consumption.

Optimization of hybrid laser - TIG welding of 316LN steel using response surface methodology (RSM)

NASA Astrophysics Data System (ADS)

Ragavendran, M.; Chandrasekhar, N.; Ravikumar, R.; Saxena, Rajesh; Vasudevan, M.; Bhaduri, A. K.

2017-07-01

In the present study, the hybrid laser - TIG welding parameters for welding of 316LN austenitic stainless steel have been investigated by combining a pulsed laser beam with a TIG welding heat source at the weld pool. Laser power, pulse frequency, pulse duration, TIG current were presumed as the welding process parameters whereas weld bead width, weld cross-sectional area and depth of penetration (DOP) were considered as the process responses. Central composite design was used to complete the design matrix and welding experiments were conducted based on the design matrix. Weld bead measurements were then carried out to generate the dataset. Multiple regression models correlating the process parameters with the responses have been developed. The accuracy of the models were found to be good. Then, the desirability approach optimization technique was employed for determining the optimum process parameters to obtain the desired weld bead profile. Validation experiments were then carried out from the determined optimum process parameters. There was good agreement between the predicted and measured values.

Optimum systems design with random input and output applied to solar water heating

NASA Astrophysics Data System (ADS)

Abdel-Malek, L. L.

1980-03-01

Solar water heating systems are evaluated. Models were developed to estimate the percentage of energy supplied from the Sun to a household. Since solar water heating systems have random input and output queueing theory, birth and death processes were the major tools in developing the models of evaluation. Microeconomics methods help in determining the optimum size of the solar water heating system design parameters, i.e., the water tank volume and the collector area.

Evaluation of the pre-posterior distribution of optimized sampling times for the design of pharmacokinetic studies.

PubMed

Duffull, Stephen B; Graham, Gordon; Mengersen, Kerrie; Eccleston, John

2012-01-01

Information theoretic methods are often used to design studies that aim to learn about pharmacokinetic and linked pharmacokinetic-pharmacodynamic systems. These design techniques, such as D-optimality, provide the optimum experimental conditions. The performance of the optimum design will depend on the ability of the investigator to comply with the proposed study conditions. However, in clinical settings it is not possible to comply exactly with the optimum design and hence some degree of unplanned suboptimality occurs due to error in the execution of the study. In addition, due to the nonlinear relationship of the parameters of these models to the data, the designs are also locally dependent on an arbitrary choice of a nominal set of parameter values. A design that is robust to both study conditions and uncertainty in the nominal set of parameter values is likely to be of use clinically. We propose an adaptive design strategy to account for both execution error and uncertainty in the parameter values. In this study we investigate designs for a one-compartment first-order pharmacokinetic model. We do this in a Bayesian framework using Markov-chain Monte Carlo (MCMC) methods. We consider log-normal prior distributions on the parameters and investigate several prior distributions on the sampling times. An adaptive design was used to find the sampling window for the current sampling time conditional on the actual times of all previous samples.

Optimization of operating parameters in polysilicon chemical vapor deposition reactor with response surface methodology

NASA Astrophysics Data System (ADS)

An, Li-sha; Liu, Chun-jiao; Liu, Ying-wen

2018-05-01

In the polysilicon chemical vapor deposition reactor, the operating parameters are complex to affect the polysilicon's output. Therefore, it is very important to address the coupling problem of multiple parameters and solve the optimization in a computationally efficient manner. Here, we adopted Response Surface Methodology (RSM) to analyze the complex coupling effects of different operating parameters on silicon deposition rate (R) and further achieve effective optimization of the silicon CVD system. Based on finite numerical experiments, an accurate RSM regression model is obtained and applied to predict the R with different operating parameters, including temperature (T), pressure (P), inlet velocity (V), and inlet mole fraction of H2 (M). The analysis of variance is conducted to describe the rationality of regression model and examine the statistical significance of each factor. Consequently, the optimum combination of operating parameters for the silicon CVD reactor is: T = 1400 K, P = 3.82 atm, V = 3.41 m/s, M = 0.91. The validation tests and optimum solution show that the results are in good agreement with those from CFD model and the deviations of the predicted values are less than 4.19%. This work provides a theoretical guidance to operate the polysilicon CVD process.

Simulate what is measured: next steps towards predictive simulations (Conference Presentation)

NASA Astrophysics Data System (ADS)

Bussmann, Michael; Kluge, Thomas; Debus, Alexander; Hübl, Axel; Garten, Marco; Zacharias, Malte; Vorberger, Jan; Pausch, Richard; Widera, René; Schramm, Ulrich; Cowan, Thomas E.; Irman, Arie; Zeil, Karl; Kraus, Dominik

2017-05-01

Simulations of laser matter interaction at extreme intensities that have predictive power are nowadays in reach when considering codes that make optimum use of high performance compute architectures. Nevertheless, this is mostly true for very specific settings where model parameters are very well known from experiment and the underlying plasma dynamics is governed by Maxwell's equations solely. When including atomic effects, prepulse influences, radiation reaction and other physical phenomena things look different. Not only is it harder to evaluate the sensitivity of the simulation result on the variation of the various model parameters but numerical models are less well tested and their combination can lead to subtle side effects that influence the simulation outcome. We propose to make optimum use of future compute hardware to compute statistical and systematic errors rather than just find the mots optimum set of parameters fitting an experiment. This requires to include experimental uncertainties which is a challenge to current state of the art techniques. Moreover, it demands better comparison to experiments as inclusion of simulating the diagnostic's response becomes important. We strongly advocate the use of open standards for finding interoperability between codes for comparison studies, building complete tool chains for simulating laser matter experiments from start to end.

Polypropylene Production Optimization in Fluidized Bed Catalytic Reactor (FBCR): Statistical Modeling and Pilot Scale Experimental Validation

PubMed Central

Khan, Mohammad Jakir Hossain; Hussain, Mohd Azlan; Mujtaba, Iqbal Mohammed

2014-01-01

Propylene is one type of plastic that is widely used in our everyday life. This study focuses on the identification and justification of the optimum process parameters for polypropylene production in a novel pilot plant based fluidized bed reactor. This first-of-its-kind statistical modeling with experimental validation for the process parameters of polypropylene production was conducted by applying ANNOVA (Analysis of variance) method to Response Surface Methodology (RSM). Three important process variables i.e., reaction temperature, system pressure and hydrogen percentage were considered as the important input factors for the polypropylene production in the analysis performed. In order to examine the effect of process parameters and their interactions, the ANOVA method was utilized among a range of other statistical diagnostic tools such as the correlation between actual and predicted values, the residuals and predicted response, outlier t plot, 3D response surface and contour analysis plots. The statistical analysis showed that the proposed quadratic model had a good fit with the experimental results. At optimum conditions with temperature of 75°C, system pressure of 25 bar and hydrogen percentage of 2%, the highest polypropylene production obtained is 5.82% per pass. Hence it is concluded that the developed experimental design and proposed model can be successfully employed with over a 95% confidence level for optimum polypropylene production in a fluidized bed catalytic reactor (FBCR). PMID:28788576

Optimization of radar imaging system parameters for geological analysis

NASA Technical Reports Server (NTRS)

Waite, W. P.; Macdonald, H. C.; Kaupp, V. H.

1981-01-01

The use of radar image simulation to model terrain variation and determine optimum sensor parameters for geological analysis is described. Optimum incidence angle is determined by the simulation, which evaluates separately the discrimination of surface features possible due to terrain geometry and that due to terrain scattering. Depending on the relative relief, slope, and scattering cross section, optimum incidence angle may vary from 20 to 80 degrees. Large incident angle imagery (more than 60 deg) is best for the widest range of geological applications, but in many cases these large angles cannot be achieved by satellite systems. Low relief regions require low incidence angles (less than 30 deg), so a satellite system serving a broad range of applications should have at least two selectable angles of incidence.

Depth variations of friction rate parameter derived from dynamic modeling of GPS afterslip associated with the 2003 Mw 6.5 Chengkung earthquake in eastern Taiwan

NASA Astrophysics Data System (ADS)

Lee, J. C.; Liu, Z. Y. C.; Shirzaei, M.

2016-12-01

The Chihshang fault lies at the plate suture between the Eurasian and the Philippine Sea plates along the Longitudinal Valley in eastern Taiwan. Here we investigate depth variation of fault frictional parameters derived from the post-seismic slip model of the 2003 Mw 6.5 Chengkung earthquake. Assuming a rate-strengthening friction, we implement an inverse dynamic modeling scheme to estimate the frictional parameter (a-b) and reference friction coefficient (μ*) in depths by taking into account: pre-seismic stress as well as co-seismic and post-seismic coulomb stress changes associated with the 2003 Chengkung earthquake. We investigate two coseismic models by Hsu et al. (2009) and Thomas et al. (2014). Model parameters, including stress gradient, depth dependent a-b and μ*, are determined from fitting the transient post-seismic geodetic signal measured at 12 continuous GPS stations. In our inversion scheme, we apply a non-linear optimization algorithm, Genetic Algorithm (GA), to search for the optimum frictional parameters. Considering the zone with velocity-strengthening frictional properties along Chihshang fault, the optimum a-b is 7-8 × 10-3 along the shallow part of the fault (0-10 km depth) and 1-2 × 10-2 in 22-28 km depth. Optimum solution for μ* is 0.3-0.4 in 0-10 km depth and reaches 0.8 in 22-28 km depth. The optimized stress gradient is 54 MPa/ km. The inferred frictional parameters are consistent with the laboratory measurements on clay-rich fault zone gouges comparable to the Lichi Melange, which is thrust over Holocene alluvial deposits across the Chihshang fault, considering the main rock composition of the Chihshang fault, at least at the upper kilometers level of the fault. Our results can facilitate further studies in particular on seismic cycle and hazard assessment of active faults.

Optimum profit model considering production, quality and sale problem

NASA Astrophysics Data System (ADS)

Chen, Chung-Ho; Lu, Chih-Lun

2011-12-01

Chen and Liu ['Procurement Strategies in the Presence of the Spot Market-an Analytical Framework', Production Planning and Control, 18, 297-309] presented the optimum profit model between the producers and the purchasers for the supply chain system with a pure procurement policy. However, their model with a simple manufacturing cost did not consider the used cost of the customer. In this study, the modified Chen and Liu's model will be addressed for determining the optimum product and process parameters. The authors propose a modified Chen and Liu's model under the two-stage screening procedure. The surrogate variable having a high correlation with the measurable quality characteristic will be directly measured in the first stage. The measurable quality characteristic will be directly measured in the second stage when the product decision cannot be determined in the first stage. The used cost of the customer will be measured by adopting Taguchi's quadratic quality loss function. The optimum purchaser's order quantity, the producer's product price and the process quality level will be jointly determined by maximising the expected profit between them.

A tuning algorithm for model predictive controllers based on genetic algorithms and fuzzy decision making.

PubMed

van der Lee, J H; Svrcek, W Y; Young, B R

2008-01-01

Model Predictive Control is a valuable tool for the process control engineer in a wide variety of applications. Because of this the structure of an MPC can vary dramatically from application to application. There have been a number of works dedicated to MPC tuning for specific cases. Since MPCs can differ significantly, this means that these tuning methods become inapplicable and a trial and error tuning approach must be used. This can be quite time consuming and can result in non-optimum tuning. In an attempt to resolve this, a generalized automated tuning algorithm for MPCs was developed. This approach is numerically based and combines a genetic algorithm with multi-objective fuzzy decision-making. The key advantages to this approach are that genetic algorithms are not problem specific and only need to be adapted to account for the number and ranges of tuning parameters for a given MPC. As well, multi-objective fuzzy decision-making can handle qualitative statements of what optimum control is, in addition to being able to use multiple inputs to determine tuning parameters that best match the desired results. This is particularly useful for multi-input, multi-output (MIMO) cases where the definition of "optimum" control is subject to the opinion of the control engineer tuning the system. A case study will be presented in order to illustrate the use of the tuning algorithm. This will include how different definitions of "optimum" control can arise, and how they are accounted for in the multi-objective decision making algorithm. The resulting tuning parameters from each of the definition sets will be compared, and in doing so show that the tuning parameters vary in order to meet each definition of optimum control, thus showing the generalized automated tuning algorithm approach for tuning MPCs is feasible.

A Sensitivity Study of the Impact of Installation Parameters and System Configuration on the Performance of Bifacial PV Arrays

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

Marion, William F; Deline, Christopher A; Asgharzadeh, Amir

In this paper, we present the effect of installation parameters (tilt angle, height above ground, and albedo) on the bifacial gain and energy yield of three south-facing photovoltaic (PV) system configurations: a single module, a row of five modules, and five rows of five modules utilizing RADIANCE-based ray tracing model. We show that height and albedo have a direct impact on the performance of bifacial systems. However, the impact of the tilt angle is more complicated. Seasonal optimum tilt angles are dependent on parameters such as height, albedo, size of the system, weather conditions, and time of the year. Formore » a single bifacial module installed in Albuquerque, NM, USA (35 degrees N) with a reasonable clearance (~1 m) from the ground, the seasonal optimum tilt angle is lowest (~5 degrees) for the summer solstice and highest (~65 degrees) for the winter solstice. For larger systems, seasonal optimum tilt angles are usually higher and can be up to 20 degrees greater than that for a single module system. Annual simulations also indicate that for larger fixed-tilt systems installed on a highly reflective ground (such as snow or a white roofing material with an albedo of ~81%), the optimum tilt angle is higher than the optimum angle of the smaller size systems. We also show that modules in larger scale systems generate lower energy due to horizon blocking and large shadowing area cast by the modules on the ground. For albedo of 21%, the center module in a large array generates up to 7% less energy than a single bifacial module. To validate our model, we utilize measured data from Sandia National Laboratories' fixed-tilt bifacial PV testbed and compare it with our simulations.« less

Optimum data weighting and error calibration for estimation of gravitational parameters

NASA Technical Reports Server (NTRS)

Lerch, F. J.

1989-01-01

A new technique was developed for the weighting of data from satellite tracking systems in order to obtain an optimum least squares solution and an error calibration for the solution parameters. Data sets from optical, electronic, and laser systems on 17 satellites in GEM-T1 (Goddard Earth Model, 36x36 spherical harmonic field) were employed toward application of this technique for gravity field parameters. Also, GEM-T2 (31 satellites) was recently computed as a direct application of the method and is summarized here. The method employs subset solutions of the data associated with the complete solution and uses an algorithm to adjust the data weights by requiring the differences of parameters between solutions to agree with their error estimates. With the adjusted weights the process provides for an automatic calibration of the error estimates for the solution parameters. The data weights derived are generally much smaller than corresponding weights obtained from nominal values of observation accuracy or residuals. Independent tests show significant improvement for solutions with optimal weighting as compared to the nominal weighting. The technique is general and may be applied to orbit parameters, station coordinates, or other parameters than the gravity model.

Improving fault image by determination of optimum seismic survey parameters using ray-based modeling

NASA Astrophysics Data System (ADS)

Saffarzadeh, Sadegh; Javaherian, Abdolrahim; Hasani, Hossein; Talebi, Mohammad Ali

2018-06-01

In complex structures such as faults, salt domes and reefs, specifying the survey parameters is more challenging and critical owing to the complicated wave field behavior involved in such structures. In the petroleum industry, detecting faults has become crucial for reservoir potential where faults can act as traps for hydrocarbon. In this regard, seismic survey modeling is employed to construct a model close to the real structure, and obtain very realistic synthetic seismic data. Seismic modeling software, the velocity model and parameters pre-determined by conventional methods enable a seismic survey designer to run a shot-by-shot virtual survey operation. A reliable velocity model of structures can be constructed by integrating the 2D seismic data, geological reports and the well information. The effects of various survey designs can be investigated by the analysis of illumination maps and flower plots. Also, seismic processing of the synthetic data output can describe the target image using different survey parameters. Therefore, seismic modeling is one of the most economical ways to establish and test the optimum acquisition parameters to obtain the best image when dealing with complex geological structures. The primary objective of this study is to design a proper 3D seismic survey orientation to achieve fault zone structures through ray-tracing seismic modeling. The results prove that a seismic survey designer can enhance the image of fault planes in a seismic section by utilizing the proposed modeling and processing approach.

Designing clinical trials to test disease-modifying agents: application to the treatment trials of Alzheimer's disease.

PubMed

Xiong, Chengjie; van Belle, Gerald; Miller, J Philip; Morris, John C

2011-02-01

Therapeutic trials of disease-modifying agents on Alzheimer's disease (AD) require novel designs and analyses involving switch of treatments for at least a portion of subjects enrolled. Randomized start and randomized withdrawal designs are two examples of such designs. Crucial design parameters such as sample size and the time of treatment switch are important to understand in designing such clinical trials. The purpose of this article is to provide methods to determine sample sizes and time of treatment switch as well as optimum statistical tests of treatment efficacy for clinical trials of disease-modifying agents on AD. A general linear mixed effects model is proposed to test the disease-modifying efficacy of novel therapeutic agents on AD. This model links the longitudinal growth from both the placebo arm and the treatment arm at the time of treatment switch for these in the delayed treatment arm or early withdrawal arm and incorporates the potential correlation on the rate of cognitive change before and after the treatment switch. Sample sizes and the optimum time for treatment switch of such trials as well as optimum test statistic for the treatment efficacy are determined according to the model. Assuming an evenly spaced longitudinal design over a fixed duration, the optimum treatment switching time in a randomized start or a randomized withdrawal trial is half way through the trial. With the optimum test statistic for the treatment efficacy and over a wide spectrum of model parameters, the optimum sample size allocations are fairly close to the simplest design with a sample size ratio of 1:1:1 among the treatment arm, the delayed treatment or early withdrawal arm, and the placebo arm. The application of the proposed methodology to AD provides evidence that much larger sample sizes are required to adequately power disease-modifying trials when compared with those for symptomatic agents, even when the treatment switch time and efficacy test are optimally chosen. The proposed method assumes that the only and immediate effect of treatment switch is on the rate of cognitive change. Crucial design parameters for the clinical trials of disease-modifying agents on AD can be optimally chosen. Government and industry officials as well as academia researchers should consider the optimum use of the clinical trials design for disease-modifying agents on AD in their effort to search for the treatments with the potential to modify the underlying pathophysiology of AD.

Inactivation disinfection property of Moringa Oleifera seed extract: optimization and kinetic studies

NASA Astrophysics Data System (ADS)

Idris, M. A.; Jami, M. S.; Hammed, A. M.

2017-05-01

This paper presents the statistical optimization study of disinfection inactivation parameters of defatted Moringa oleifera seed extract on Pseudomonas aeruginosa bacterial cells. Three level factorial design was used to estimate the optimum range and the kinetics of the inactivation process was also carried. The inactivation process involved comparing different disinfection models of Chicks-Watson, Collins-Selleck and Homs models. The results from analysis of variance (ANOVA) of the statistical optimization process revealed that only contact time was significant. The optimum disinfection range of the seed extract was 125 mg/L, 30 minutes and 120rpm agitation. At the optimum dose, the inactivation kinetics followed the Collin-Selleck model with coefficient of determination (R2) of 0.6320. This study is the first of its kind in determining the inactivation kinetics of pseudomonas aeruginosa using the defatted seed extract.

Application of describing function analysis to a model of deep brain stimulation.

PubMed

Davidson, Clare Muireann; de Paor, Annraoi M; Lowery, Madeleine M

2014-03-01

Deep brain stimulation effectively alleviates motor symptoms of medically refractory Parkinson's disease, and also relieves many other treatment-resistant movement and affective disorders. Despite its relative success as a treatment option, the basis of its efficacy remains elusive. In Parkinson's disease, increased functional connectivity and oscillatory activity occur within the basal ganglia as a result of dopamine loss. A correlative relationship between pathological oscillatory activity and the motor symptoms of the disease, in particular bradykinesia, rigidity, and tremor, has been established. Suppression of the oscillations by either dopamine replacement or DBS also correlates with an improvement in motor symptoms. DBS parameters are currently chosen empirically using a "trial and error" approach, which can be time-consuming and costly. The work presented here amalgamates concepts from theories of neural network modeling with nonlinear control engineering to describe and analyze a model of synchronous neural activity and applied stimulation. A theoretical expression for the optimum stimulation parameters necessary to suppress oscillations is derived. The effect of changing stimulation parameters (amplitude and pulse duration) on induced oscillations is studied in the model. Increasing either stimulation pulse duration or amplitude enhanced the level of suppression. The predicted parameters were found to agree well with clinical measurements reported in the literature for individual patients. It is anticipated that the simplified model described may facilitate the development of protocols to aid optimum stimulation parameter choice on a patient by patient basis.

The use of Argo for validation and tuning of mixed layer models

NASA Astrophysics Data System (ADS)

Acreman, D. M.; Jeffery, C. D.

We present results from validation and tuning of 1-D ocean mixed layer models using data from Argo floats and data from Ocean Weather Station Papa (145°W, 50°N). Model tests at Ocean Weather Station Papa showed that a bulk model could perform well provided it was tuned correctly. The Large et al. [Large, W.G., McWilliams, J.C., Doney, S.C., 1994. Oceanic vertical mixing: a review and a model with a nonlocal boundary layer parameterisation. Rev. Geophys. 32 (Novermber), 363-403] K-profile parameterisation (KPP) model also gave a good representation of mixed layer depth provided the vertical resolution was sufficiently high. Model tests using data from a single Argo float indicated a tendency for the KPP model to deepen insufficiently over an annual cycle, whereas the tuned bulk model and general ocean turbulence model (GOTM) gave a better representation of mixed layer depth. The bulk model was then tuned using data from a sample of Argo floats and a set of optimum parameters was found; these optimum parameters were consistent with the tuning at OWS Papa.

Multi-Response Optimization of WEDM Process Parameters Using Taguchi Based Desirability Function Analysis

NASA Astrophysics Data System (ADS)

Majumder, Himadri; Maity, Kalipada

2018-03-01

Shape memory alloy has a unique capability to return to its original shape after physical deformation by applying heat or thermo-mechanical or magnetic load. In this experimental investigation, desirability function analysis (DFA), a multi-attribute decision making was utilized to find out the optimum input parameter setting during wire electrical discharge machining (WEDM) of Ni-Ti shape memory alloy. Four critical machining parameters, namely pulse on time (TON), pulse off time (TOFF), wire feed (WF) and wire tension (WT) were taken as machining inputs for the experiments to optimize three interconnected responses like cutting speed, kerf width, and surface roughness. Input parameter combination TON = 120 μs., TOFF = 55 μs., WF = 3 m/min. and WT = 8 kg-F were found to produce the optimum results. The optimum process parameters for each desired response were also attained using Taguchi’s signal-to-noise ratio. Confirmation test has been done to validate the optimum machining parameter combination which affirmed DFA was a competent approach to select optimum input parameters for the ideal response quality for WEDM of Ni-Ti shape memory alloy.

Comprehensive analytical model for locally contacted rear surface passivated solar cells

NASA Astrophysics Data System (ADS)

Wolf, Andreas; Biro, Daniel; Nekarda, Jan; Stumpp, Stefan; Kimmerle, Achim; Mack, Sebastian; Preu, Ralf

2010-12-01

For optimum performance of solar cells featuring a locally contacted rear surface, the metallization fraction as well as the size and distribution of the local contacts are crucial, since Ohmic and recombination losses have to be balanced. In this work we present a set of equations which enable to calculate this trade off without the need of numerical simulations. Our model combines established analytical and empirical equations to predict the energy conversion efficiency of a locally contacted device. For experimental verification, we fabricate devices from float zone silicon wafers of different resistivity using the laser fired contact technology for forming the local rear contacts. The detailed characterization of test structures enables the determination of important physical parameters, such as the surface recombination velocity at the contacted area and the spreading resistance of the contacts. Our analytical model reproduces the experimental results very well and correctly predicts the optimum contact spacing without the use of free fitting parameters. We use our model to estimate the optimum bulk resistivity for locally contacted devices fabricated from conventional Czochralski-grown silicon material. These calculations use literature values for the stable minority carrier lifetime to account for the bulk recombination caused by the formation of boron-oxygen complexes under carrier injection.

Optimum design of structures subject to general periodic loads

NASA Technical Reports Server (NTRS)

Reiss, Robert; Qian, B.

1989-01-01

A simplified version of Icerman's problem regarding the design of structures subject to a single harmonic load is discussed. The nature of the restrictive conditions that must be placed on the design space in order to ensure an analytic optimum are discussed in detail. Icerman's problem is then extended to include multiple forcing functions with different driving frequencies. And the conditions that now must be placed upon the design space to ensure an analytic optimum are again discussed. An important finding is that all solutions to the optimality condition (analytic stationary design) are local optima, but the global optimum may well be non-analytic. The more general problem of distributing the fixed mass of a linear elastic structure subject to general periodic loads in order to minimize some measure of the steady state deflection is also considered. This response is explicitly expressed in terms of Green's functional and the abstract operators defining the structure. The optimality criterion is derived by differentiating the response with respect to the design parameters. The theory is applicable to finite element as well as distributed parameter models.

Climate-host mapping of Phytophthora ramorum, causal agent of sudden oak death

Treesearch

Glenn Fowler; Roger Magarey; Manuel Colunga

2006-01-01

Phytophthora ramorum infection was modeled using the NAPPFAST system for the conterminous United States. Parameters used to model P. ramorum infection were: leaf wetness, minimum temperature, optimum temperature and maximum temperature over a specified number of accumulated days. The model was used to create maps showing the...

Climate-Host Mapping of Phytophthora ramorum, causal agent of sudden oak death

Treesearch

Roger Magarey; Glenn Fowler; Manuel Colunga; Bill Smith; Ross Meentemeyer

2008-01-01

We modeled Phytophthora ramorum infection using the North Carolina State University- Animal and Plant Health Inspection Service Plant Pest Forecasting System (NAPPFAST) for the conterminous United States. Our infection model is based on a temperature-moisture response function. The model parameters were: leaf wetness, minimum temperature, optimum...

Hybrid heating systems optimization of residential environment to have thermal comfort conditions by numerical simulation.

PubMed

Jahantigh, Nabi; Keshavarz, Ali; Mirzaei, Masoud

2015-01-01

The aim of this study is to determine optimum hybrid heating systems parameters, such as temperature, surface area of a radiant heater and vent area to have thermal comfort conditions. DOE, Factorial design method is used to determine the optimum values for input parameters. A 3D model of a virtual standing thermal manikin with real dimensions is considered in this study. Continuity, momentum, energy, species equations for turbulent flow and physiological equation for thermal comfort are numerically solved to study heat, moisture and flow field. K - ɛRNG Model is used for turbulence modeling and DO method is used for radiation effects. Numerical results have a good agreement with the experimental data reported in the literature. The effect of various combinations of inlet parameters on thermal comfort is considered. According to Pareto graph, some of these combinations that have significant effect on the thermal comfort require no more energy can be used as useful tools. A better symmetrical velocity distribution around the manikin is also presented in the hybrid system.

Design optimum frac jobs using virtual intelligence techniques

NASA Astrophysics Data System (ADS)

Mohaghegh, Shahab; Popa, Andrei; Ameri, Sam

2000-10-01

Designing optimal frac jobs is a complex and time-consuming process. It usually involves the use of a two- or three-dimensional computer model. For the computer models to perform as intended, a wealth of input data is required. The input data includes wellbore configuration and reservoir characteristics such as porosity, permeability, stress and thickness profiles of the pay layers as well as the overburden layers. Among other essential information required for the design process is fracturing fluid type and volume, proppant type and volume, injection rate, proppant concentration and frac job schedule. Some of the parameters such as fluid and proppant types have discrete possible choices. Other parameters such as fluid and proppant volume, on the other hand, assume values from within a range of minimum and maximum values. A potential frac design for a particular pay zone is a combination of all of these parameters. Finding the optimum combination is not a trivial process. It usually requires an experienced engineer and a considerable amount of time to tune the parameters in order to achieve desirable outcome. This paper introduces a new methodology that integrates two virtual intelligence techniques, namely, artificial neural networks and genetic algorithms to automate and simplify the optimum frac job design process. This methodology requires little input from the engineer beyond the reservoir characterizations and wellbore configuration. The software tool that has been developed based on this methodology uses the reservoir characteristics and an optimization criteria indicated by the engineer, for example a certain propped frac length, and provides the detail of the optimum frac design that will result in the specified criteria. An ensemble of neural networks is trained to mimic the two- or three-dimensional frac simulator. Once successfully trained, these networks are capable of providing instantaneous results in response to any set of input parameters. These networks will be used as the fitness function for a genetic algorithm routine that will search for the best combination of the design parameters for the frac job. The genetic algorithm will search through the entire solution space and identify the optimal combination of parameters to be used in the design process. Considering the complexity of this task this methodology converges relatively fast, providing the engineer with several near-optimum scenarios for the frac job design. These scenarios, which can be achieved in just a minute or two, can be valuable initial points for the engineer to start his/her design job and save him/her hours of runs on the simulator.

Modeling polyvinyl chloride Plasma Modification by Neural Networks

NASA Astrophysics Data System (ADS)

Wang, Changquan

2018-03-01

Neural networks model were constructed to analyze the connection between dielectric barrier discharge parameters and surface properties of material. The experiment data were generated from polyvinyl chloride plasma modification by using uniform design. Discharge voltage, discharge gas gap and treatment time were as neural network input layer parameters. The measured values of contact angle were as the output layer parameters. A nonlinear mathematical model of the surface modification for polyvinyl chloride was developed based upon the neural networks. The optimum model parameters were obtained by the simulation evaluation and error analysis. The results of the optimal model show that the predicted value is very close to the actual test value. The prediction model obtained here are useful for discharge plasma surface modification analysis.

Change in optimum genetic algorithm solution with changing band discontinuities and band widths of electrically conducting copolymers

NASA Astrophysics Data System (ADS)

Kaur, Avneet; Bakhshi, A. K.

2010-04-01

The interest in copolymers stems from the fact that they present interesting electronic and optical properties leading to a variety of technological applications. In order to get a suitable copolymer for a specific application, genetic algorithm (GA) along with negative factor counting (NFC) method has recently been used. In this paper, we study the effect of change in the ratio of conduction band discontinuity to valence band discontinuity (Δ Ec/Δ Ev) on the optimum solution obtained from GA for model binary copolymers. The effect of varying bandwidths on the optimum GA solution is also investigated. The obtained results show that the optimum solution changes with varying parameters like band discontinuity and band width of constituent homopolymers. As the ratio Δ Ec/Δ Ev increases, band gap of optimum solution decreases. With increasing band widths of constituent homopolymers, the optimum solution tends to be dependent on the component with higher band gap.

High-efficiency resonant coupled wireless power transfer via tunable impedance matching

NASA Astrophysics Data System (ADS)

Anowar, Tanbir Ibne; Barman, Surajit Das; Wasif Reza, Ahmed; Kumar, Narendra

2017-10-01

For magnetic resonant coupled wireless power transfer (WPT), the axial movement of near-field coupled coils adversely degrades the power transfer efficiency (PTE) of the system and often creates sub-resonance. This paper presents a tunable impedance matching technique based on optimum coupling tuning to enhance the efficiency of resonant coupled WPT system. The optimum power transfer model is analysed from equivalent circuit model via reflected load principle, and the adequate matching are achieved through the optimum tuning of coupling coefficients at both the transmitting and receiving end of the system. Both simulations and experiments are performed to evaluate the theoretical model of the proposed matching technique, and results in a PTE over 80% at close coil proximity without shifting the original resonant frequency. Compared to the fixed coupled WPT, the extracted efficiency shows 15.1% and 19.9% improvements at the centre-to-centre misalignment of 10 and 70 cm, respectively. Applying this technique, the extracted S21 parameter shows more than 10 dB improvements at both strong and weak couplings. Through the developed model, the optimum coupling tuning also significantly improves the performance over matching techniques using frequency tracking and tunable matching circuits.

Performance mapping of a 30 cm engineering model thruster

NASA Technical Reports Server (NTRS)

Poeschel, R. L.; Vahrenkamp, R. P.

1975-01-01

A 30 cm thruster representative of the engineering model design has been tested over a wide range of operating parameters to document performance characteristics such as electrical and propellant efficiencies, double ion and beam divergence thrust loss, component equilibrium temperatures, operational stability, etc. Data obtained show that optimum power throttling, in terms of maximum thruster efficiency, is not highly sensitive to parameter selection. Consequently, considerations of stability, discharge chamber erosion, thrust losses, etc. can be made the determining factors for parameter selection in power throttling operations. Options in parameter selection based on these considerations are discussed.

Estimation of Compaction Parameters Based on Soil Classification

NASA Astrophysics Data System (ADS)

Lubis, A. S.; Muis, Z. A.; Hastuty, I. P.; Siregar, I. M.

2018-02-01

Factors that must be considered in compaction of the soil works were the type of soil material, field control, maintenance and availability of funds. Those problems then raised the idea of how to estimate the density of the soil with a proper implementation system, fast, and economical. This study aims to estimate the compaction parameter i.e. the maximum dry unit weight (γ dmax) and optimum water content (Wopt) based on soil classification. Each of 30 samples were being tested for its properties index and compaction test. All of the data’s from the laboratory test results, were used to estimate the compaction parameter values by using linear regression and Goswami Model. From the research result, the soil types were A4, A-6, and A-7 according to AASHTO and SC, SC-SM, and CL based on USCS. By linear regression, the equation for estimation of the maximum dry unit weight (γdmax *)=1,862-0,005*FINES- 0,003*LL and estimation of the optimum water content (wopt *)=- 0,607+0,362*FINES+0,161*LL. By Goswami Model (with equation Y=mLogG+k), for estimation of the maximum dry unit weight (γdmax *) with m=-0,376 and k=2,482, for estimation of the optimum water content (wopt *) with m=21,265 and k=-32,421. For both of these equations a 95% confidence interval was obtained.

Identifyability measures to select the parameters to be estimated in a solid-state fermentation distributed parameter model.

PubMed

da Silveira, Christian L; Mazutti, Marcio A; Salau, Nina P G

2016-07-08

Process modeling can lead to of advantages such as helping in process control, reducing process costs and product quality improvement. This work proposes a solid-state fermentation distributed parameter model composed by seven differential equations with seventeen parameters to represent the process. Also, parameters estimation with a parameters identifyability analysis (PIA) is performed to build an accurate model with optimum parameters. Statistical tests were made to verify the model accuracy with the estimated parameters considering different assumptions. The results have shown that the model assuming substrate inhibition better represents the process. It was also shown that eight from the seventeen original model parameters were nonidentifiable and better results were obtained with the removal of these parameters from the estimation procedure. Therefore, PIA can be useful to estimation procedure, since it may reduce the number of parameters that can be evaluated. Further, PIA improved the model results, showing to be an important procedure to be taken. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:905-917, 2016. © 2016 American Institute of Chemical Engineers.

Taguchi Optimization of Pulsed Current GTA Welding Parameters for Improved Corrosion Resistance of 5083 Aluminum Welds

NASA Astrophysics Data System (ADS)

Rastkerdar, E.; Shamanian, M.; Saatchi, A.

2013-04-01

In this study, the Taguchi method was used as a design of experiment (DOE) technique to optimize the pulsed current gas tungsten arc welding (GTAW) parameters for improved pitting corrosion resistance of AA5083-H18 aluminum alloy welds. A L9 (34) orthogonal array of the Taguchi design was used, which involves nine experiments for four parameters: peak current ( P), base current ( B), percent pulse-on time ( T), and pulse frequency ( F) with three levels was used. Pitting corrosion resistance in 3.5 wt.% NaCl solution was evaluated by anodic polarization tests at room temperature and calculating the width of the passive region (∆ E pit). Analysis of variance (ANOVA) was performed on the measured data and S/ N (signal to noise) ratios. The "bigger is better" was selected as the quality characteristic (QC). The optimum conditions were found as 170 A, 85 A, 40%, and 6 Hz for P, B, T, and F factors, respectively. The study showed that the percent pulse-on time has the highest influence on the pitting corrosion resistance (50.48%) followed by pulse frequency (28.62%), peak current (11.05%) and base current (9.86%). The range of optimum ∆ E pit at optimum conditions with a confidence level of 90% was predicted to be between 174.81 and 177.74 mVSCE. Under optimum conditions, the confirmation test was carried out, and the experimental value of ∆ E pit of 176 mVSCE was in agreement with the predicted value from the Taguchi model. In this regard, the model can be effectively used to predict the ∆ E pit of pulsed current gas tungsten arc welded joints.

Model fit versus biological relevance: Evaluating photosynthesis-temperature models for three tropical seagrass species

NASA Astrophysics Data System (ADS)

Adams, Matthew P.; Collier, Catherine J.; Uthicke, Sven; Ow, Yan X.; Langlois, Lucas; O'Brien, Katherine R.

2017-01-01

When several models can describe a biological process, the equation that best fits the data is typically considered the best. However, models are most useful when they also possess biologically-meaningful parameters. In particular, model parameters should be stable, physically interpretable, and transferable to other contexts, e.g. for direct indication of system state, or usage in other model types. As an example of implementing these recommended requirements for model parameters, we evaluated twelve published empirical models for temperature-dependent tropical seagrass photosynthesis, based on two criteria: (1) goodness of fit, and (2) how easily biologically-meaningful parameters can be obtained. All models were formulated in terms of parameters characterising the thermal optimum (Topt) for maximum photosynthetic rate (Pmax). These parameters indicate the upper thermal limits of seagrass photosynthetic capacity, and hence can be used to assess the vulnerability of seagrass to temperature change. Our study exemplifies an approach to model selection which optimises the usefulness of empirical models for both modellers and ecologists alike.

Model fit versus biological relevance: Evaluating photosynthesis-temperature models for three tropical seagrass species.

PubMed

Adams, Matthew P; Collier, Catherine J; Uthicke, Sven; Ow, Yan X; Langlois, Lucas; O'Brien, Katherine R

2017-01-04

When several models can describe a biological process, the equation that best fits the data is typically considered the best. However, models are most useful when they also possess biologically-meaningful parameters. In particular, model parameters should be stable, physically interpretable, and transferable to other contexts, e.g. for direct indication of system state, or usage in other model types. As an example of implementing these recommended requirements for model parameters, we evaluated twelve published empirical models for temperature-dependent tropical seagrass photosynthesis, based on two criteria: (1) goodness of fit, and (2) how easily biologically-meaningful parameters can be obtained. All models were formulated in terms of parameters characterising the thermal optimum (T opt ) for maximum photosynthetic rate (P max ). These parameters indicate the upper thermal limits of seagrass photosynthetic capacity, and hence can be used to assess the vulnerability of seagrass to temperature change. Our study exemplifies an approach to model selection which optimises the usefulness of empirical models for both modellers and ecologists alike.

Model fit versus biological relevance: Evaluating photosynthesis-temperature models for three tropical seagrass species

PubMed Central

Adams, Matthew P.; Collier, Catherine J.; Uthicke, Sven; Ow, Yan X.; Langlois, Lucas; O’Brien, Katherine R.

2017-01-01

When several models can describe a biological process, the equation that best fits the data is typically considered the best. However, models are most useful when they also possess biologically-meaningful parameters. In particular, model parameters should be stable, physically interpretable, and transferable to other contexts, e.g. for direct indication of system state, or usage in other model types. As an example of implementing these recommended requirements for model parameters, we evaluated twelve published empirical models for temperature-dependent tropical seagrass photosynthesis, based on two criteria: (1) goodness of fit, and (2) how easily biologically-meaningful parameters can be obtained. All models were formulated in terms of parameters characterising the thermal optimum (Topt) for maximum photosynthetic rate (Pmax). These parameters indicate the upper thermal limits of seagrass photosynthetic capacity, and hence can be used to assess the vulnerability of seagrass to temperature change. Our study exemplifies an approach to model selection which optimises the usefulness of empirical models for both modellers and ecologists alike. PMID:28051123

Determination of design and operation parameters for upper atmospheric research instrumentation to yield optimum resolution with deconvolution

NASA Technical Reports Server (NTRS)

Ioup, George E.; Ioup, Juliette W.

1991-01-01

The final report for work on the determination of design and operation parameters for upper atmospheric research instrumentation to yield optimum resolution with deconvolution is presented. Papers and theses prepared during the research report period are included. Among all the research results reported, note should be made of the specific investigation of the determination of design and operation parameters for upper atmospheric research instrumentation to yield optimum resolution with deconvolution. A methodology was developed to determine design and operation parameters for error minimization when deconvolution is included in data analysis. An error surface is plotted versus the signal-to-noise ratio (SNR) and all parameters of interest. Instrumental characteristics will determine a curve in this space. The SNR and parameter values which give the projection from the curve to the surface, corresponding to the smallest value for the error, are the optimum values. These values are constrained by the curve and so will not necessarily correspond to an absolute minimum in the error surface.

Seven-panel solar wing deployment and on-orbit maneuvering analyses

NASA Astrophysics Data System (ADS)

Hwang, Earl

2005-05-01

BSS developed a new generation high power (~20kW) solar array to meet the customer demands. The high power solar array had the north and south solar wings of which designs were identical. Each side of the solar wing consists of three main conventional solar panels and the four-side panel swing-out new design. The fully deployed solar array surface area is 966 ft2. It was a quite challenging task to define the solar array's optimum design parameters and deployment scheme for such a huge solar array's successful deployment and on-orbit maneuvering. Hence, a deployable seven-flex-panel solar wing nonlinear math model and a fully deployed solar array/bus-payload math model were developed with the Dynamic Analysis and Design System (DADS) program codes utilizing the inherited and empirical data. Performing extensive parametric analyses with the math model, the optimum design parameters and the orbit maneuvering /deployment schemes were determined to meet all the design requirements, and for the successful solar wing deployment on-orbit.

Optimized design on condensing tubes high-speed TIG welding technology magnetic control based on genetic algorithm

NASA Astrophysics Data System (ADS)

Lu, Lin; Chang, Yunlong; Li, Yingmin; Lu, Ming

2013-05-01

An orthogonal experiment was conducted by the means of multivariate nonlinear regression equation to adjust the influence of external transverse magnetic field and Ar flow rate on welding quality in the process of welding condenser pipe by high-speed argon tungsten-arc welding (TIG for short). The magnetic induction and flow rate of Ar gas were used as optimum variables, and tensile strength of weld was set to objective function on the base of genetic algorithm theory, and then an optimal design was conducted. According to the request of physical production, the optimum variables were restrained. The genetic algorithm in the MATLAB was used for computing. A comparison between optimum results and experiment parameters was made. The results showed that the optimum technologic parameters could be chosen by the means of genetic algorithm with the conditions of excessive optimum variables in the process of high-speed welding. And optimum technologic parameters of welding coincided with experiment results.

Swarm intelligence application for optimization of CO2 diffusivity in polystyrene-b-polybutadiene-b-polystyrene (SEBS) foaming

NASA Astrophysics Data System (ADS)

Sharudin, Rahida Wati; Ajib, Norshawalina Muhamad; Yusoff, Marina; Ahmad, Mohd Aizad

2017-12-01

Thermoplastic elastomer SEBS foams were prepared by using carbon dioxide (CO2) as a blowing agent and the process is classified as physical foaming method. During the foaming process, the diffusivity of CO2 need to be controlled since it is one of the parameter that will affect the final cellular structure of the foam. Conventionally, the rate of CO2 diffusion was measured experimentally by using a highly sensitive device called magnetic suspension balance (MSB). Besides, this expensive MSB machine is not easily available and measurement of CO2 diffusivity is quite complicated as well as time consuming process. Thus, to overcome these limitations, a computational method was introduced. Particle Swarm Optimization (PSO) is a part of Swarm Intelligence system which acts as a beneficial optimization tool where it can solve most of nonlinear complications. PSO model was developed for predicting the optimum foaming temperature and CO2 diffusion rate in SEBS foam. Results obtained by PSO model are compared with experimental results for CO2 diffusivity at various foaming temperature. It is shown that predicted optimum foaming temperature at 154.6 °C was not represented the best temperature for foaming as the cellular structure of SEBS foamed at corresponding temperature consisted pores with unstable dimension and the structure was not visibly perceived due to foam shrinkage. The predictions were not agreed well with experimental result when single parameter of CO2 diffusivity is considered in PSO model because it is not the only factor that affected the controllability of foam shrinkage. The modification on the PSO model by considering CO2 solubility and rigidity of SEBS as additional parameters needs to be done for obtaining the optimum temperature for SEBS foaming. Hence stable SEBS foam could be prepared.

Proceedings of the Annual Precise Time and Time Interval (PTTI) applications and Planning Meeting (20th) Held in Vienna, Virginia on 29 November-1 December 1988

DTIC Science & Technology

1988-12-01

PERFORMANCE IN REAL TIME* Dr. James A. Barnes Austron Boulder, Co. Abstract Kalman filters and ARIMA models provide optimum control and evaluation tech...estimates of the model parameters (e.g., the phi’s and theta’s for an ARIMA model ). These model parameters are often evaluated in a batch mode on a...random walk FM, and linear frequency drift. In ARIMA models , this is equivalent to an ARIMA (0,2,2) with a non-zero average sec- ond difference. Using

Optimum pelvic incidence minus lumbar lordosis value can be determined by individual pelvic incidence.

PubMed

Inami, Satoshi; Moridaira, Hiroshi; Takeuchi, Daisaku; Shiba, Yo; Nohara, Yutaka; Taneichi, Hiroshi

2016-11-01

Adult spinal deformity (ASD) classification showing that ideal pelvic incidence minus lumbar lordosis (PI-LL) value is within 10° has been received widely. But no study has focused on the optimum level of PI-LL value that reflects wide variety in PI among patients. This study was conducted to determine the optimum PI-LL value specific to an individual's PI in postoperative ASD patients. 48 postoperative ASD patients were recruited. Spino-pelvic parameters and Oswestry Disability Index (ODI) were measured at the final follow-up. Factors associated with good clinical results were determined by stepwise multiple regression model using the ODI. The patients with ODI under the 75th percentile cutoff were designated into the "good" health related quality of life (HRQOL) group. In this group, the relationship between the PI-LL and PI was assessed by regression analysis. Multiple regression analysis revealed PI-LL as significant parameters associated with ODI. Thirty-six patients with an ODI <22 points (75th percentile cutoff) were categorized into a good HRQOL group, and linear regression models demonstrated the following equation: PI-LL = 0.41PI-11.12 (r = 0.45, P = 0.0059). On the basis of this equation, in the patients with a PI = 50°, the PI-LL is 9°. Whereas in those with a PI = 30°, the optimum PI-LL is calculated to be as low as 1°. In those with a PI = 80°, PI-LL is estimated at 22°. Consequently, an optimum PI-LL is inconsistent in that it depends on the individual PI.

Modeling multilayer x-ray reflectivity using genetic algorithms

NASA Astrophysics Data System (ADS)

Sánchez del Río, M.; Pareschi, G.; Michetschläger, C.

2000-06-01

The x-ray reflectivity of a multilayer is a non-linear function of many parameters (materials, layer thickness, density, roughness). Non-linear fitting of experimental data with simulations requires the use of initial values sufficiently close to the optimum value. This is a difficult task when the topology of the space of the variables is highly structured. We apply global optimization methods to fit multilayer reflectivity. Genetic algorithms are stochastic methods based on the model of natural evolution: the improvement of a population along successive generations. A complete set of initial parameters constitutes an individual. The population is a collection of individuals. Each generation is built from the parent generation by applying some operators (selection, crossover, mutation, etc.) on the members of the parent generation. The pressure of selection drives the population to include "good" individuals. For large number of generations, the best individuals will approximate the optimum parameters. Some results on fitting experimental hard x-ray reflectivity data for Ni/C and W/Si multilayers using genetic algorithms are presented. This method can also be applied to design multilayers optimized for a target application.

Optimization of Acid Black 172 decolorization by electrocoagulation using response surface methodology

PubMed Central

2012-01-01

This paper utilizes a statistical approach, the response surface optimization methodology, to determine the optimum conditions for the Acid Black 172 dye removal efficiency from aqueous solution by electrocoagulation. The experimental parameters investigated were initial pH: 4–10; initial dye concentration: 0–600 mg/L; applied current: 0.5-3.5 A and reaction time: 3–15 min. These parameters were changed at five levels according to the central composite design to evaluate their effects on decolorization through analysis of variance. High R2 value of 94.48% shows a high correlation between the experimental and predicted values and expresses that the second-order regression model is acceptable for Acid Black 172 dye removal efficiency. It was also found that some interactions and squares influenced the electrocoagulation performance as well as the selected parameters. Optimum dye removal efficiency of 90.4% was observed experimentally at initial pH of 7, initial dye concentration of 300 mg/L, applied current of 2 A and reaction time of 9.16 min, which is close to model predicted (90%) result. PMID:23369574

Error assessment of biogeochemical models by lower bound methods (NOMMA-1.0)

NASA Astrophysics Data System (ADS)

Sauerland, Volkmar; Löptien, Ulrike; Leonhard, Claudine; Oschlies, Andreas; Srivastav, Anand

2018-03-01

Biogeochemical models, capturing the major feedbacks of the pelagic ecosystem of the world ocean, are today often embedded into Earth system models which are increasingly used for decision making regarding climate policies. These models contain poorly constrained parameters (e.g., maximum phytoplankton growth rate), which are typically adjusted until the model shows reasonable behavior. Systematic approaches determine these parameters by minimizing the misfit between the model and observational data. In most common model approaches, however, the underlying functions mimicking the biogeochemical processes are nonlinear and non-convex. Thus, systematic optimization algorithms are likely to get trapped in local minima and might lead to non-optimal results. To judge the quality of an obtained parameter estimate, we propose determining a preferably large lower bound for the global optimum that is relatively easy to obtain and that will help to assess the quality of an optimum, generated by an optimization algorithm. Due to the unavoidable noise component in all observations, such a lower bound is typically larger than zero. We suggest deriving such lower bounds based on typical properties of biogeochemical models (e.g., a limited number of extremes and a bounded time derivative). We illustrate the applicability of the method with two real-world examples. The first example uses real-world observations of the Baltic Sea in a box model setup. The second example considers a three-dimensional coupled ocean circulation model in combination with satellite chlorophyll a.

Simulation of optimum parameters for GaN MSM UV photodetector

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

Alhelfi, Mohanad A., E-mail: mhad12344@gmail.com; Ahmed, Naser M., E-mail: nas-tiji@yahoo.com; Hashim, M. R., E-mail: roslan@usm.my

2016-07-06

In this study the optimum parameters of GaN M-S-M photodetector are discussed. The evaluation of the photodetector depends on many parameters, the most of the important parameters the quality of the GaN film and others depend on the geometry of the interdigited electrode. In this simulation work using MATLAB software with consideration of the reflection and absorption on the metal contacts, a detailed study involving various electrode spacings (S) and widths (W) reveals conclusive results in device design. The optimum interelectrode design for interdigitated MSM-PD has been specified and evaluated by effect on quantum efficiency and responsivity.

The combined theoretical and experimental approach to arrive at optimum parameters in friction stir welding

NASA Astrophysics Data System (ADS)

Jagadeesha, C. B.

2017-12-01

Even though friction stir welding was invented long back (1991) by TWI England, till now there has no method or procedure or approach developed, which helps to obtain quickly optimum or exact parameters yielding good or sound weld. An approach has developed in which an equation has been derived, by which approximate rpm can be obtained and by setting range of rpm ±100 or 50 rpm over approximate rpm and by setting welding speed equal to 60 mm/min or 50 mm/min one can conduct FSW experiment to reach optimum parameters; one can reach quickly to optimum parameters, i.e. desired rpm, and welding speed, which yield sound weld by the approach. This approach can be effectively used to obtain sound welds for all similar and dissimilar combinations of materials such as Steel, Al, Mg, Ti, etc.

Mathematical Models for the Apparent Mass of the Seated Human Body Exposed to Vertical Vibration

NASA Astrophysics Data System (ADS)

Wei, L.; Griffin, M. J.

1998-05-01

Alternative mathematical models of the vertical apparent mass of the seated human body are developed. The optimum parameters of four models (two single-degree-of-freedom models and two two-degree-of-freedom models) are derived from the mean measured apparent masses of 60 subjects (24 men, 24 women, 12 children) previously reported. The best fits were obtained by fitting the phase data with single-degree-of-freedom and two-degree-of-freedom models having rigid support structures. For these two models, curve fitting was performed on each of the 60 subjects (so as to obtain optimum model parameters for each subject), for the averages of each of the three groups of subjects, and for the entire group of subjects. The values obtained are tabulated. Use of a two-degree-of-freedom model provided a better fit to the phase of the apparent mass at frequencies greater than about 8 Hz and an improved fit to the modulus of the apparent mass at frequencies around 5 Hz. It is concluded that the two-degree-of-freedom model provides an apparent mass similar to that of the human body, but this does not imply that the body moves in the same manner as the masses in this optimized two-degree-of-freedom model.

Identification of Optimum Magnetic Behavior of NanoCrystalline CmFeAl Type Heusler Alloy Powders Using Response Surface Methodology

NASA Astrophysics Data System (ADS)

Srivastava, Y.; Srivastava, S.; Boriwal, L.

2016-09-01

Mechanical alloying is a novelistic solid state process that has received considerable attention due to many advantages over other conventional processes. In the present work, Co2FeAl healer alloy powder, prepared successfully from premix basic powders of Cobalt (Co), Iron (Fe) and Aluminum (Al) in stoichiometric of 60Co-26Fe-14Al (weight %) by novelistic mechano-chemical route. Magnetic properties of mechanically alloyed powders were characterized by vibrating sample magnetometer (VSM). 2 factor 5 level design matrix was applied to experiment process. Experimental results were used for response surface methodology. Interaction between the input process parameters and the response has been established with the help of regression analysis. Further analysis of variance technique was applied to check the adequacy of developed model and significance of process parameters. Test case study was performed with those parameters, which was not selected for main experimentation but range was same. Response surface methodology, the process parameters must be optimized to obtain improved magnetic properties. Further optimum process parameters were identified using numerical and graphical optimization techniques.

Analysis of the Optimum Usage of Slag for the Compressive Strength of Concrete.

PubMed

Lee, Han-Seung; Wang, Xiao-Yong; Zhang, Li-Na; Koh, Kyung-Taek

2015-03-18

Ground granulated blast furnace slag is widely used as a mineral admixture to replace partial Portland cement in the concrete industry. As the amount of slag increases, the late-age compressive strength of concrete mixtures increases. However, after an optimum point, any further increase in slag does not improve the late-age compressive strength. This optimum replacement ratio of slag is a crucial factor for its efficient use in the concrete industry. This paper proposes a numerical procedure to analyze the optimum usage of slag for the compressive strength of concrete. This numerical procedure starts with a blended hydration model that simulates cement hydration, slag reaction, and interactions between cement hydration and slag reaction. The amount of calcium silicate hydrate (CSH) is calculated considering the contributions from cement hydration and slag reaction. Then, by using the CSH contents, the compressive strength of the slag-blended concrete is evaluated. Finally, based on the parameter analysis of the compressive strength development of concrete with different slag inclusions, the optimum usage of slag in concrete mixtures is determined to be approximately 40% of the total binder content. The proposed model is verified through experimental results of the compressive strength of slag-blended concrete with different water-to-binder ratios and different slag inclusions.

Analysis of the Optimum Usage of Slag for the Compressive Strength of Concrete

PubMed Central

Lee, Han-Seung; Wang, Xiao-Yong; Zhang, Li-Na; Koh, Kyung-Taek

2015-01-01

Ground granulated blast furnace slag is widely used as a mineral admixture to replace partial Portland cement in the concrete industry. As the amount of slag increases, the late-age compressive strength of concrete mixtures increases. However, after an optimum point, any further increase in slag does not improve the late-age compressive strength. This optimum replacement ratio of slag is a crucial factor for its efficient use in the concrete industry. This paper proposes a numerical procedure to analyze the optimum usage of slag for the compressive strength of concrete. This numerical procedure starts with a blended hydration model that simulates cement hydration, slag reaction, and interactions between cement hydration and slag reaction. The amount of calcium silicate hydrate (CSH) is calculated considering the contributions from cement hydration and slag reaction. Then, by using the CSH contents, the compressive strength of the slag-blended concrete is evaluated. Finally, based on the parameter analysis of the compressive strength development of concrete with different slag inclusions, the optimum usage of slag in concrete mixtures is determined to be approximately 40% of the total binder content. The proposed model is verified through experimental results of the compressive strength of slag-blended concrete with different water-to-binder ratios and different slag inclusions. PMID:28787998

Understanding hydrological and nitrogen interactions by sensitivity analysis of a catchment-scale nitrogen model

NASA Astrophysics Data System (ADS)

Medici, Chiara; Wade, Andrew; Frances, Felix

2010-05-01

Nitrogen is present in both terrestrial and aquatic ecosystems and research is needed to understand its storage, transportation and transformations in river catchments world-wide because of its importance in controlling plant growth and freshwater trophic status (Vitousek et al. 2009; Chu et al. 2008; Schlesinger et al 2006; Ocampo et al. 2006; Green et al., 2004; Arheimer et al., 1996). Numerous mathematical models have been developed to describe the nitrogen dynamics, but there is a substantial gap between the outputs now expected from these models and what modellers are able to provide with scientific justification (McIntyre et al., 2005). In fact, models will always necessarily be simplification of reality; hence simplifying assumptions are sources of uncertainty that must be well understood for an accurate model results interpretation. Therefore, estimating prediction uncertainties in water quality modelling is becoming increasingly appreciated (Dean et al., 2009, Kruger et al., 2007, Rode et al., 2007). In this work the lumped LU4-N model (Medici et al., 2008; Medici et al., EGU2009-7497) is subjected to an extensive regionalised sensitivity analysis (GSA, based on Monte Carlo simulations) in application to the Fuirosos catchment, Catalonia. The main results are: 1) the hydrological model is greatly affected by the maximum static storage water content (Hu_max), which defines the amount of water held in soil that can leave the catchment only by evapotranspiration. Thus, it defines also the amount of water not retained that is free to move and supplies the other model tanks; 2) the use of several objective functions in order to take into account different hydrograph characteristic helped to constrain parameter values; 3) concerning nitrogen, to obtain a sufficient level of behavioural parameter sets for the statistical analysis, not very severe criteria could be adopted; 4) stream water concentrations are sensitive to the shallow aquifer parameters, especially the nitrification constant (Knitr-aquif) and also to the certain soil parameters, like the mineralization constant (Kmin), the annual maximum ammonium uptake (MaxUPNH4) and the mineralization, nitrification and immobilisation thresholds (Umin, Unitr and Uimmob). Moreover the results give a clear indication that the hydrological model greatly affects the streamwater nitrate and ammonium concentrations; 5) result shows that the LU4-N model succeeded in achieving near-optimum fits simultaneously to flow and nitrate, but not ammonium; 6) however, the optimum flow model has not produced a near-optimum nitrate model. The analysis of this result indicated that calibrating the flow-related parameters first, then calibrating the remaining parameters instead of calibrating all parameters together, may not be the best strategy as pointed out for another study by McIntyre et al., 2005 ; 7) a final analysis seems also to support the idea that to obtain a satisfactory nitrogen simulation necessarily the flow should be acceptably represented, which lead to the conclusion that observed stream concentrations may indirectly help to calibrated the rainfall-runoff model, or at least the parameters to which they are sensitive.

Optimization of Computational Performance and Accuracy in 3-D Transient CFD Model for CFB Hydrodynamics Predictions

NASA Astrophysics Data System (ADS)

Rampidis, I.; Nikolopoulos, A.; Koukouzas, N.; Grammelis, P.; Kakaras, E.

2007-09-01

This work aims to present a pure 3-D CFD model, accurate and efficient, for the simulation of a pilot scale CFB hydrodynamics. The accuracy of the model was investigated as a function of the numerical parameters, in order to derive an optimum model setup with respect to computational cost. The necessity of the in depth examination of hydrodynamics emerges by the trend to scale up CFBCs. This scale up brings forward numerous design problems and uncertainties, which can be successfully elucidated by CFD techniques. Deriving guidelines for setting a computational efficient model is important as the scale of the CFBs grows fast, while computational power is limited. However, the optimum efficiency matter has not been investigated thoroughly in the literature as authors were more concerned for their models accuracy and validity. The objective of this work is to investigate the parameters that influence the efficiency and accuracy of CFB computational fluid dynamics models, find the optimum set of these parameters and thus establish this technique as a competitive method for the simulation and design of industrial, large scale beds, where the computational cost is otherwise prohibitive. During the tests that were performed in this work, the influence of turbulence modeling approach, time and space density and discretization schemes were investigated on a 1.2 MWth CFB test rig. Using Fourier analysis dominant frequencies were extracted in order to estimate the adequate time period for the averaging of all instantaneous values. The compliance with the experimental measurements was very good. The basic differences between the predictions that arose from the various model setups were pointed out and analyzed. The results showed that a model with high order space discretization schemes when applied on a coarse grid and averaging of the instantaneous scalar values for a 20 sec period, adequately described the transient hydrodynamic behaviour of a pilot CFB while the computational cost was kept low. Flow patterns inside the bed such as the core-annulus flow and the transportation of clusters were at least qualitatively captured.

Comparison of various error functions in predicting the optimum isotherm by linear and non-linear regression analysis for the sorption of basic red 9 by activated carbon.

PubMed

Kumar, K Vasanth; Porkodi, K; Rocha, F

2008-01-15

A comparison of linear and non-linear regression method in selecting the optimum isotherm was made to the experimental equilibrium data of basic red 9 sorption by activated carbon. The r(2) was used to select the best fit linear theoretical isotherm. In the case of non-linear regression method, six error functions namely coefficient of determination (r(2)), hybrid fractional error function (HYBRID), Marquardt's percent standard deviation (MPSD), the average relative error (ARE), sum of the errors squared (ERRSQ) and sum of the absolute errors (EABS) were used to predict the parameters involved in the two and three parameter isotherms and also to predict the optimum isotherm. Non-linear regression was found to be a better way to obtain the parameters involved in the isotherms and also the optimum isotherm. For two parameter isotherm, MPSD was found to be the best error function in minimizing the error distribution between the experimental equilibrium data and predicted isotherms. In the case of three parameter isotherm, r(2) was found to be the best error function to minimize the error distribution structure between experimental equilibrium data and theoretical isotherms. The present study showed that the size of the error function alone is not a deciding factor to choose the optimum isotherm. In addition to the size of error function, the theory behind the predicted isotherm should be verified with the help of experimental data while selecting the optimum isotherm. A coefficient of non-determination, K(2) was explained and was found to be very useful in identifying the best error function while selecting the optimum isotherm.

Comparison the Results of Numerical Simulation And Experimental Results for Amirkabir Plasma Focus Facility

NASA Astrophysics Data System (ADS)

Goudarzi, Shervin; Amrollahi, R.; Niknam Sharak, M.

2014-06-01

In this paper the results of the numerical simulation for Amirkabir Mather-type Plasma Focus Facility (16 kV, 36μF and 115 nH) in several experiments with Argon as working gas at different working conditions (different discharge voltages and gas pressures) have been presented and compared with the experimental results. Two different models have been used for simulation: five-phase model of Lee and lumped parameter model of Gonzalez. It is seen that the results (optimum pressures and current signals) of the Lee model at different working conditions show better agreement than lumped parameter model with experimental values.

Optimization of Operating Parameters for Minimum Mechanical Specific Energy in Drilling

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

Hamrick, Todd

2011-01-01

Efficiency in drilling is measured by Mechanical Specific Energy (MSE). MSE is the measure of the amount of energy input required to remove a unit volume of rock, expressed in units of energy input divided by volume removed. It can be expressed mathematically in terms of controllable parameters; Weight on Bit, Torque, Rate of Penetration, and RPM. It is well documented that minimizing MSE by optimizing controllable factors results in maximum Rate of Penetration. Current methods for computing MSE make it possible to minimize MSE in the field only through a trial-and-error process. This work makes it possible to computemore » the optimum drilling parameters that result in minimum MSE. The parameters that have been traditionally used to compute MSE are interdependent. Mathematical relationships between the parameters were established, and the conventional MSE equation was rewritten in terms of a single parameter, Weight on Bit, establishing a form that can be minimized mathematically. Once the optimum Weight on Bit was determined, the interdependent relationship that Weight on Bit has with Torque and Penetration per Revolution was used to determine optimum values for those parameters for a given drilling situation. The improved method was validated through laboratory experimentation and analysis of published data. Two rock types were subjected to four treatments each, and drilled in a controlled laboratory environment. The method was applied in each case, and the optimum parameters for minimum MSE were computed. The method demonstrated an accurate means to determine optimum drilling parameters of Weight on Bit, Torque, and Penetration per Revolution. A unique application of micro-cracking is also presented, which demonstrates that rock failure ahead of the bit is related to axial force more than to rotation speed.« less

Study of hydrodynamic characteristics of a Sharp Eagle wave energy converter

NASA Astrophysics Data System (ADS)

Zhang, Ya-qun; Sheng, Song-wei; You, Ya-ge; Huang, Zhen-xin; Wang, Wen-sheng

2017-06-01

According to Newton's Second Law and the microwave theory, mechanical analysis of multiple buoys which form Sharp Eagle wave energy converter (WEC) is carried out. The movements of every buoy in three modes couple each other when they are affected with incident waves. Based on the above, mechanical models of the WEC are established, which are concerned with fluid forces, damping forces, hinge forces, and so on. Hydrodynamic parameters of one buoy are obtained by taking the other moving buoy as boundary conditions. Then, by taking those hydrodynamic parameters into the mechanical models, the optimum external damping and optimal capture width ratio are calculated out. Under the condition of the optimum external damping, a plenty of data are obtained, such as the displacements amplitude of each buoy in three modes (sway, heave, pitch), damping forces, hinge forces, and speed of the hydraulic cylinder. Research results provide theoretical references and basis for Sharp Eagle WECs in the design and manufacture.

Multi-criteria optimization for ultrasonic-assisted extraction of antioxidants from Pericarpium Citri Reticulatae using response surface methodology, an activity-based approach.

PubMed

Zeng, Shanshan; Wang, Lu; Zhang, Lei; Qu, Haibin; Gong, Xingchu

2013-06-01

An activity-based approach to optimize the ultrasonic-assisted extraction of antioxidants from Pericarpium Citri Reticulatae (Chenpi in Chinese) was developed. Response surface optimization based on a quantitative composition-activity relationship model showed the relationships among product chemical composition, antioxidant activity of extract, and parameters of extraction process. Three parameters of ultrasonic-assisted extraction, including the ethanol/water ratio, Chenpi amount, and alkaline amount, were investigated to give optimum extraction conditions for antioxidants of Chenpi: ethanol/water 70:30 v/v, Chenpi amount of 10 g, and alkaline amount of 28 mg. The experimental antioxidant yield under the optimum conditions was found to be 196.5 mg/g Chenpi, and the antioxidant activity was 2023.8 μmol Trolox equivalents/g of the Chenpi powder. The results agreed well with the second-order polynomial regression model. This presented approach promised great application potentials in both food and pharmaceutical industries. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Optimization of process parameters of pulsed TIG welded maraging steel C300

NASA Astrophysics Data System (ADS)

Deepak, P.; Jualeash, M. J.; Jishnu, J.; Srinivasan, P.; Arivarasu, M.; Padmanaban, R.; Thirumalini, S.

2016-09-01

Pulsed TIG welding technology provides excellent welding performance on thin sections which helps to increase productivity, enhance weld quality, minimize weld costs, and boost operator efficiency and this has drawn the attention of the welding society. Maraging C300 steel is extensively used in defence and aerospace industry and thus its welding becomes an area of paramount importance. In pulsed TIG welding, weld quality depends on the process parameters used. In this work, Pulsed TIG bead-on-plate welding is performed on a 5mm thick maraging C300 plate at different combinations of input parameters: peak current (Ip), base current (Ib) and pulsing frequency (HZ) as per box behnken design with three-levels for each factor. Response surface methodology is utilized for establishing a mathematical model for predicting the weld bead depth. The effect of Ip, Ib and HZ on the weld bead depth is investigated using the developed model. The weld bead depth is found to be affected by all the three parameters. Surface and contour plots developed from regression equation are used to optimize the processing parameters for maximizing the weld bead depth. Optimum values of Ip, Ib and HZ are obtained as 259 A, 120 A and 8 Hz respectively. Using this optimum condition, maximum bead depth of the weld is predicted to be 4.325 mm.

Modelling the performance of the monogroove with screen heat pipe for use in the radiator of the solar dynamic power system of the NASA Space Station

NASA Technical Reports Server (NTRS)

Evans, Austin Lewis

1987-01-01

A computer code to model the steady-state performance of a monogroove heat pipe for the NASA Space Station is presented, including the effects on heat pipe performance of a screen in the evaporator section which deals with transient surges in the heat input. Errors in a previous code have been corrected, and the new code adds additional loss terms in order to model several different working fluids. Good agreement with existing performance curves is obtained. From a preliminary evaluation of several of the radiator design parameters it is found that an optimum fin width could be achieved but that structural considerations limit the thickness of the fin to a value above optimum.

Transport—Reaction process in the reaction of flue gas desulfurization

NASA Astrophysics Data System (ADS)

Yan, Yan; Peng, Xiaofeng; Lee, Duu Jong

2000-12-01

A theoretical investigation was conducted to study the transport-reaction process in the spray-drying flue gas desulfurization. A transport-reaction model of single particle was proposed, which considered the water evaporation from the surface of droplet and the reaction at the same time. Based on this model, the reaction rate and the absorbent utilization can be calculated. The most appropriate particle radius and the initial absorbent concentration can be deduced through comparing the wet lifetime with the residence time, the result shows in the case that the partial pressure of vapor in the bulk flue gas is 2000Pa, the optimum initial radius and absorbent concentration are 210 310 µ m and 23% respectively. The model can supply the optimum parameters for semi-dry FGD system designed.

Optimization of palm fruit sterilization by microwave irradiation using response surface methodology

NASA Astrophysics Data System (ADS)

Sarah, M.; Madinah, I.; Salamah, S.

2018-02-01

This study reported optimization of palm fruit sterilization process by microwave irradiation. The results of fractional factorial experiments showed no significant external factors affecting temperature of microwave sterilization (MS). Response surface methodology (RSM) was employed and model equation of MS of palm fruit was built. Response surface plots and their corresponding contour plots were analyzed as well as solving model equation. The optimum process parameters for lipase reduction were obtained from MS of 1 kg palm fruit at microwave power of 486 Watt and heating time of 14 minutes. The experimental results showed reduction of lipase activity in the present work under MS treatment. The adequacy of the model equation for predicting the optimum response value was verified by validation data (P>0.15).

A method to optimize the processing algorithm of a computed radiography system for chest radiography.

PubMed

Moore, C S; Liney, G P; Beavis, A W; Saunderson, J R

2007-09-01

A test methodology using an anthropomorphic-equivalent chest phantom is described for the optimization of the Agfa computed radiography "MUSICA" processing algorithm for chest radiography. The contrast-to-noise ratio (CNR) in the lung, heart and diaphragm regions of the phantom, and the "system modulation transfer function" (sMTF) in the lung region, were measured using test tools embedded in the phantom. Using these parameters the MUSICA processing algorithm was optimized with respect to low-contrast detectability and spatial resolution. Two optimum "MUSICA parameter sets" were derived respectively for maximizing the CNR and sMTF in each region of the phantom. Further work is required to find the relative importance of low-contrast detectability and spatial resolution in chest images, from which the definitive optimum MUSICA parameter set can then be derived. Prior to this further work, a compromised optimum MUSICA parameter set was applied to a range of clinical images. A group of experienced image evaluators scored these images alongside images produced from the same radiographs using the MUSICA parameter set in clinical use at the time. The compromised optimum MUSICA parameter set was shown to produce measurably better images.

Ultraviolet resources over Northern Eurasia.

PubMed

Chubarova, Natalia; Zhdanova, Yekaterina

2013-10-05

We propose a new climatology of UV resources over Northern Eurasia, which includes the assessments of both detrimental (erythema) and positive (vitamin D synthesis) effects of ultraviolet radiation on human health. The UV resources are defined by using several classes and subclasses - UV deficiency, UV optimum, and UV excess - for 6 different skin types. To better quantifying the vitamin D irradiance threshold we accounted for an open body fraction S as a function of effective air temperature. The spatial and temporal distribution of UV resources was estimated by radiative transfer (RT) modeling (8 stream DISORT RT code) with 1×1° grid and monthly resolution. For this purpose special datasets of main input geophysical parameters (total ozone content, aerosol characteristics, surface UV albedo, UV cloud modification factor) have been created over the territory of Northern Eurasia. The new approaches were used to retrieve aerosol parameters and cloud modification factor in the UV spectral region. As a result, the UV resources were obtained for clear-sky and mean cloudy conditions for different skin types. We show that the distribution of UV deficiency, UV optimum and UV excess is regulated by various geophysical parameters (mainly, total ozone, cloudiness and open body fraction) and can significantly deviate from latitudinal dependence. We also show that the UV optimum conditions can be simultaneously observed for people with different skin types (for example, for 4-5 skin types at the same time in spring over Western Europe). These UV optimum conditions for different skin types occupy a much larger territory over Europe than that over Asia. Copyright © 2013 Elsevier B.V. All rights reserved.

Development of an Empirical Model for Optimization of Machining Parameters to Minimize Power Consumption

NASA Astrophysics Data System (ADS)

Kant Garg, Girish; Garg, Suman; Sangwan, K. S.

2018-04-01

The manufacturing sector consumes huge energy demand and the machine tools used in this sector have very less energy efficiency. Selection of the optimum machining parameters for machine tools is significant for energy saving and for reduction of environmental emission. In this work an empirical model is developed to minimize the power consumption using response surface methodology. The experiments are performed on a lathe machine tool during the turning of AISI 6061 Aluminum with coated tungsten inserts. The relationship between the power consumption and machining parameters is adequately modeled. This model is used for formulation of minimum power consumption criterion as a function of optimal machining parameters using desirability function approach. The influence of machining parameters on the energy consumption has been found using the analysis of variance. The validation of the developed empirical model is proved using the confirmation experiments. The results indicate that the developed model is effective and has potential to be adopted by the industry for minimum power consumption of machine tools.

Biological data assimilation for parameter estimation of a phytoplankton functional type model for the western North Pacific

NASA Astrophysics Data System (ADS)

Hoshiba, Yasuhiro; Hirata, Takafumi; Shigemitsu, Masahito; Nakano, Hideyuki; Hashioka, Taketo; Masuda, Yoshio; Yamanaka, Yasuhiro

2018-06-01

Ecosystem models are used to understand ecosystem dynamics and ocean biogeochemical cycles and require optimum physiological parameters to best represent biological behaviours. These physiological parameters are often tuned up empirically, while ecosystem models have evolved to increase the number of physiological parameters. We developed a three-dimensional (3-D) lower-trophic-level marine ecosystem model known as the Nitrogen, Silicon and Iron regulated Marine Ecosystem Model (NSI-MEM) and employed biological data assimilation using a micro-genetic algorithm to estimate 23 physiological parameters for two phytoplankton functional types in the western North Pacific. The estimation of the parameters was based on a one-dimensional simulation that referenced satellite data for constraining the physiological parameters. The 3-D NSI-MEM optimized by the data assimilation improved the timing of a modelled plankton bloom in the subarctic and subtropical regions compared to the model without data assimilation. Furthermore, the model was able to improve not only surface concentrations of phytoplankton but also their subsurface maximum concentrations. Our results showed that surface data assimilation of physiological parameters from two contrasting observatory stations benefits the representation of vertical plankton distribution in the western North Pacific.

Statistical Modeling Studies of Iron Recovery from Red Mud Using Thermal Plasma

NASA Astrophysics Data System (ADS)

Swagat, S. Rath; Archana, Pany; Jayasankar, K.; Ajit, K. Mitra; C. Satish, Kumar; Partha, S. Mukherjee; Barada, K. Mishra

2013-05-01

Optimization studies of plasma smelting of red mud were carried out. Reduction of the dried red mud fines was done in an extended arc plasma reactor to recover the pig iron. Lime grit and low ash metallurgical (LAM) coke were used as the flux and reductant, respectively. 2-level factorial design was used to study the influence of all parameters on the responses. Response surface modeling was done with the data obtained from statistically designed experiments. Metal recovery at optimum parameters was found to be 79.52%.

Decision Support for the Capacity Management of Bronchoscopy Devices: Optimizing the Cost-Efficient Mix of Reusable and Single-Use Devices Through Mathematical Modeling.

PubMed

Edenharter, Günther M; Gartner, Daniel; Pförringer, Dominik

2017-06-01

Increasing costs of material resources challenge hospitals to stay profitable. Particularly in anesthesia departments and intensive care units, bronchoscopes are used for various indications. Inefficient management of single- and multiple-use systems can influence the hospitals' material costs substantially. Using mathematical modeling, we developed a strategic decision support tool to determine the optimum mix of disposable and reusable bronchoscopy devices in the setting of an intensive care unit. A mathematical model with the objective to minimize costs in relation to demand constraints for bronchoscopy devices was formulated. The stochastic model decides whether single-use, multi-use, or a strategically chosen mix of both device types should be used. A decision support tool was developed in which parameters for uncertain demand such as mean, standard deviation, and a reliability parameter can be inserted. Furthermore, reprocessing costs per procedure, procurement, and maintenance costs for devices can be parameterized. Our experiments show for which demand pattern and reliability measure, it is efficient to only use reusable or disposable devices and under which circumstances the combination of both device types is beneficial. To determine the optimum mix of single-use and reusable bronchoscopy devices effectively and efficiently, managers can enter their hospital-specific parameters such as demand and prices into the decision support tool.The software can be downloaded at: https://github.com/drdanielgartner/bronchomix/.

Models of compacted fine-grained soils used as mineral liner for solid waste

NASA Astrophysics Data System (ADS)

Sivrikaya, Osman

2008-02-01

To prevent the leakage of pollutant liquids into groundwater and sublayers, the compacted fine-grained soils are commonly utilized as mineral liners or a sealing system constructed under municipal solid waste and other containment hazardous materials. This study presents the correlation equations of the compaction parameters required for construction of a mineral liner system. The determination of the characteristic compaction parameters, maximum dry unit weight ( γ dmax) and optimum water content ( w opt) requires considerable time and great effort. In this study, empirical models are described and examined to find which of the index properties correlate well with the compaction characteristics for estimating γ dmax and w opt of fine-grained soils at the standard compactive effort. The compaction data are correlated with different combinations of gravel content ( G), sand content ( S), fine-grained content (FC = clay + silt), plasticity index ( I p), liquid limit ( w L) and plastic limit ( w P) by performing multilinear regression (MLR) analyses. The obtained correlations with statistical parameters are presented and compared with the previous studies. It is found that the maximum dry unit weight and optimum water content have a considerably good correlation with plastic limit in comparison with liquid limit and plasticity index.

Model verification of large structural systems. [space shuttle model response

NASA Technical Reports Server (NTRS)

Lee, L. T.; Hasselman, T. K.

1978-01-01

A computer program for the application of parameter identification on the structural dynamic models of space shuttle and other large models with hundreds of degrees of freedom is described. Finite element, dynamic, analytic, and modal models are used to represent the structural system. The interface with math models is such that output from any structural analysis program applied to any structural configuration can be used directly. Processed data from either sine-sweep tests or resonant dwell tests are directly usable. The program uses measured modal data to condition the prior analystic model so as to improve the frequency match between model and test. A Bayesian estimator generates an improved analytical model and a linear estimator is used in an iterative fashion on highly nonlinear equations. Mass and stiffness scaling parameters are generated for an improved finite element model, and the optimum set of parameters is obtained in one step.

Modelling pathogen log10 reduction values achieved by activated sludge treatment using naïve and semi naïve Bayes network models.

PubMed

Carvajal, Guido; Roser, David J; Sisson, Scott A; Keegan, Alexandra; Khan, Stuart J

2015-11-15

Risk management for wastewater treatment and reuse have led to growing interest in understanding and optimising pathogen reduction during biological treatment processes. However, modelling pathogen reduction is often limited by poor characterization of the relationships between variables and incomplete knowledge of removal mechanisms. The aim of this paper was to assess the applicability of Bayesian belief network models to represent associations between pathogen reduction, and operating conditions and monitoring parameters and predict AS performance. Naïve Bayes and semi-naïve Bayes networks were constructed from an activated sludge dataset including operating and monitoring parameters, and removal efficiencies for two pathogens (native Giardia lamblia and seeded Cryptosporidium parvum) and five native microbial indicators (F-RNA bacteriophage, Clostridium perfringens, Escherichia coli, coliforms and enterococci). First we defined the Bayesian network structures for the two pathogen log10 reduction values (LRVs) class nodes discretized into two states (< and ≥ 1 LRV) using two different learning algorithms. Eight metrics, such as Prediction Accuracy (PA) and Area Under the receiver operating Curve (AUC), provided a comparison of model prediction performance, certainty and goodness of fit. This comparison was used to select the optimum models. The optimum Tree Augmented naïve models predicted removal efficiency with high AUC when all system parameters were used simultaneously (AUCs for C. parvum and G. lamblia LRVs of 0.95 and 0.87 respectively). However, metrics for individual system parameters showed only the C. parvum model was reliable. By contrast individual parameters for G. lamblia LRV prediction typically obtained low AUC scores (AUC < 0.81). Useful predictors for C. parvum LRV included solids retention time, turbidity and total coliform LRV. The methodology developed appears applicable for predicting pathogen removal efficiency in water treatment systems generally. Copyright © 2015 Elsevier Ltd. All rights reserved.

Mechanistic investigation in ultrasound induced enhancement of enzymatic hydrolysis of invasive biomass species.

PubMed

Borah, Arup Jyoti; Agarwal, Mayank; Poudyal, Manisha; Goyal, Arun; Moholkar, Vijayanand S

2016-08-01

This study has assessed four invasive weeds, viz. Saccharum spontaneum (SS), Mikania micrantha (MM), Lantana camara (LC) and Eichhornia crassipes (EC) for enzymatic hydrolysis prior to bioalcohol fermentation. Enzymatic hydrolysis of pretreated biomasses of weeds has been conducted with mechanical agitation and sonication under constant (non-optimum) conditions. Profiles of total reducible sugar release have been fitted to HCH-1 model of enzymatic hydrolysis using Genetic Algorithm. Trends in parameters of this model reveal physical mechanism of ultrasound-induced enhancement of enzymatic hydrolysis. Sonication accelerates hydrolysis kinetics by ∼10-fold. This effect is contributed by several causes, attributed to intense micro-convection generated during sonication: (1) increase in reaction velocity, (2) increase in enzyme-substrate affinity, (3) reduction in product inhibition, and (4) enhancement of enzyme activity due to conformational changes in its secondary structure. Enhancement effect of sonication is revealed to be independent of conditions of enzymatic hydrolysis - whether optimum or non-optimum. Copyright © 2016 Elsevier Ltd. All rights reserved.

Optimum dimensions of power solenoids for magnetic suspension

NASA Technical Reports Server (NTRS)

Kaznacheyev, B. A.

1985-01-01

Design optimization of power solenoids for controllable and stabilizable magnetic suspensions with force compensation in a wind tunnel is shown. It is assumed that the model of a levitating body is a sphere of ferromagnetic material with constant magnetic permeability. This sphere, with a radius much smaller than its distance from the solenoid above, is to be maintained in position on the solenoid axis by balance of the vertical electromagnetic force and the force of gravitation. The necessary vertical (axial) force generated by the solenoid is expressed as a function of relevant system dimensions, solenoid design parameters, and physical properties of the body. Three families of curves are obtained which depict the solenoid power for a given force as a function of the solenoid length with either outside radius or inside radius as a variable parameter and as a function of the outside radius with inside radius as a variable parameter. The curves indicate the optimum solenoid length and outside radius, for minimum power, corresponding to a given outside radius and inside radius, respectively.

An operation support expert system based on on-line dynamics simulation and fuzzy reasoning for startup schedule optimization in fossil power plants

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

Matsumoto, H.; Eki, Y.; Kaji, A.

1993-12-01

An expert system which can support operators of fossil power plants in creating the optimum startup schedule and executing it accurately is described. The optimum turbine speed-up and load-up pattern is obtained through an iterative manner which is based on fuzzy resonating using quantitative calculations as plant dynamics models and qualitative knowledge as schedule optimization rules with fuzziness. The rules represent relationships between stress margins and modification rates of the schedule parameters. Simulations analysis proves that the system provides quick and accurate plant startups.

Simulation of ethane steam cracking with severity evaluation

NASA Astrophysics Data System (ADS)

Rosli, M. N.; Aziz, N.

2016-11-01

Understanding the influence of operating parameters towards cracking severity is paramount in ensuring optimum operation of an ethylene plant. However, changing the parameters in an actual plant for data collection can be dangerous. Thus, a simulation model for ethane steam cracking furnace is developed using ASPEN Plus for the assessment. The process performance is evaluated with cracking severity factors and main product yields. Three severity factors are used for evaluation due to their ease of measurement, which are methane yield (Ymet), Ethylene-Ethane Ratio (EER) and Propylene-Ethylene Ratio (PER). The result shows that cracking severity is primarily influenced by reactor temperature. Operating the furnace with coil outlet temperature ranging between 850°C to 950°C and steam-to-hydrocarbon ratio of 0.3 to 0.5 has led to optimum main product yield.

High-performance radial AMTEC cell design for ultra-high-power solar AMTEC systems

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

Hendricks, T.J.; Huang, C.

1999-07-01

Alkali Metal Thermal to Electric Conversion (AMTEC) technology is rapidly maturing for potential application in ultra-high-power solar AMTEC systems required by potential future US Air Force (USAF) spacecraft missions in medium-earth and geosynchronous orbits (MEO and GEO). Solar thermal AMTEC power systems potentially have several important advantages over current solar photovoltaic power systems in ultra-high-power spacecraft applications for USAF MEO and GEO missions. This work presents key aspects of radial AMTEC cell design to achieve high cell performance in solar AMTEC systems delivering larger than 50 kW(e) to support high power USAF missions. These missions typically require AMTEC cell conversionmore » efficiency larger than 25%. A sophisticated design parameter methodology is described and demonstrated which establishes optimum design parameters in any radial cell design to satisfy high-power mission requirements. Specific relationships, which are distinct functions of cell temperatures and pressures, define critical dependencies between key cell design parameters, particularly the impact of parasitic thermal losses on Beta Alumina Solid Electrolyte (BASE) area requirements, voltage, number of BASE tubes, and system power production for both maximum power-per-BASE-area and optimum efficiency conditions. Finally, some high-level system tradeoffs are demonstrated using the design parameter methodology to establish high-power radial cell design requirements and philosophy. The discussion highlights how to incorporate this methodology with sophisticated SINDA/FLUINT AMTEC cell modeling capabilities to determine optimum radial AMTEC cell designs.« less

Posterior uncertainty of GEOS-5 L-band radiative transfer model parameters and brightness temperatures after calibration with SMOS observations

NASA Astrophysics Data System (ADS)

De Lannoy, G. J.; Reichle, R. H.; Vrugt, J. A.

2012-12-01

Simulated L-band (1.4 GHz) brightness temperatures are very sensitive to the values of the parameters in the radiative transfer model (RTM). We assess the optimum RTM parameter values and their (posterior) uncertainty in the Goddard Earth Observing System (GEOS-5) land surface model using observations of multi-angular brightness temperature over North America from the Soil Moisture Ocean Salinity (SMOS) mission. Two different parameter estimation methods are being compared: (i) a particle swarm optimization (PSO) approach, and (ii) an MCMC simulation procedure using the differential evolution adaptive Metropolis (DREAM) algorithm. Our results demonstrate that both methods provide similar "optimal" parameter values. Yet, DREAM exhibits better convergence properties, resulting in a reduced spread of the posterior ensemble. The posterior parameter distributions derived with both methods are used for predictive uncertainty estimation of brightness temperature. This presentation will highlight our model-data synthesis framework and summarize our initial findings.

Optimization of parameters of special asynchronous electric drives

NASA Astrophysics Data System (ADS)

Karandey, V. Yu; Popov, B. K.; Popova, O. B.; Afanasyev, V. L.

2018-03-01

The article considers the solution of the problem of parameters optimization of special asynchronous electric drives. The solution of the problem will allow one to project and create special asynchronous electric drives for various industries. The created types of electric drives will have optimum mass-dimensional and power parameters. It will allow one to realize and fulfill the set characteristics of management of technological processes with optimum level of expenses of electric energy, time of completing the process or other set parameters. The received decision allows one not only to solve a certain optimizing problem, but also to construct dependences between the optimized parameters of special asynchronous electric drives, for example, with the change of power, current in a winding of the stator or rotor, induction in a gap or steel of magnetic conductors and other parameters. On the constructed dependences, it is possible to choose necessary optimum values of parameters of special asynchronous electric drives and their components without carrying out repeated calculations.

Zener Diode Compact Model Parameter Extraction Using Xyce-Dakota Optimization.

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

Buchheit, Thomas E.; Wilcox, Ian Zachary; Sandoval, Andrew J

This report presents a detailed process for compact model parameter extraction for DC circuit Zener diodes. Following the traditional approach of Zener diode parameter extraction, circuit model representation is defined and then used to capture the different operational regions of a real diode's electrical behavior. The circuit model contains 9 parameters represented by resistors and characteristic diodes as circuit model elements. The process of initial parameter extraction, the identification of parameter values for the circuit model elements, is presented in a way that isolates the dependencies between certain electrical parameters and highlights both the empirical nature of the extraction andmore » portions of the real diode physical behavior which of the parameters are intended to represent. Optimization of the parameters, a necessary part of a robost parameter extraction process, is demonstrated using a 'Xyce-Dakota' workflow, discussed in more detail in the report. Among other realizations during this systematic approach of electrical model parameter extraction, non-physical solutions are possible and can be difficult to avoid because of the interdependencies between the different parameters. The process steps described are fairly general and can be leveraged for other types of semiconductor device model extractions. Also included in the report are recommendations for experiment setups for generating optimum dataset for model extraction and the Parameter Identification and Ranking Table (PIRT) for Zener diodes.« less

Box-Behnken Design of Experiments Investigation of Hydroxyapatite Synthesis for Orthopedic Applications

NASA Astrophysics Data System (ADS)

Kehoe, S.; Stokes, J.

2011-03-01

Physicochemical properties of hydroxyapatite (HAp) synthesized by the chemical precipitation method are heavily dependent on the chosen process parameters. A Box-Behnken three-level experimental design was therefore, chosen to determine the optimum set of process parameters and their effect on various HAp characteristics. These effects were quantified using design of experiments (DoE) to develop mathematical models using the Box-Behnken design, in terms of the chemical precipitation process parameters. Findings from this research show that the HAp possessing optimum powder characteristics for orthopedic application via a thermal spray technique can therefore be prepared using the following chemical precipitation process parameters: reaction temperature 60 °C, ripening time 48 h, and stirring speed 1500 rpm using high reagent concentrations. Ripening time and stirring speed significantly affected the final phase purity for the experimental conditions of the Box-Behnken design. An increase in both the ripening time (36-48 h) and stirring speed (1200-1500 rpm) was found to result in an increase of phase purity from 47(±2)% to 85(±2)%. Crystallinity, crystallite size, lattice parameters, and mean particle size were also optimized within the research to find desired settings to achieve results suitable for FDA regulations.

Optimum stacking sequence design of laminated composite circular plates with curvilinear fibres by a layer-wise optimization method

NASA Astrophysics Data System (ADS)

Guenanou, A.; Houmat, A.

2018-05-01

The optimum stacking sequence design for the maximum fundamental frequency of symmetrically laminated composite circular plates with curvilinear fibres is investigated for the first time using a layer-wise optimization method. The design variables are two fibre orientation angles per layer. The fibre paths are constructed using the method of shifted paths. The first-order shear deformation plate theory and a curved square p-element are used to calculate the objective function. The blending function method is used to model accurately the geometry of the circular plate. The equations of motion are derived using Lagrange's method. The numerical results are validated by means of a convergence test and comparison with published values for symmetrically laminated composite circular plates with rectilinear fibres. The material parameters, boundary conditions, number of layers and thickness are shown to influence the optimum solutions to different extents. The results should serve as a benchmark for optimum stacking sequences of symmetrically laminated composite circular plates with curvilinear fibres.

Optimum Laser Beam Characteristics for Achieving Smoother Ablations in Laser Vision Correction.

PubMed

Verma, Shwetabh; Hesser, Juergen; Arba-Mosquera, Samuel

2017-04-01

Controversial opinions exist regarding optimum laser beam characteristics for achieving smoother ablations in laser-based vision correction. The purpose of the study was to outline a rigorous simulation model for simulating shot-by-shot ablation process. The impact of laser beam characteristics like super Gaussian order, truncation radius, spot geometry, spot overlap, and lattice geometry were tested on ablation smoothness. Given the super Gaussian order, the theoretical beam profile was determined following Lambert-Beer model. The intensity beam profile originating from an excimer laser was measured with a beam profiler camera. For both, the measured and theoretical beam profiles, two spot geometries (round and square spots) were considered, and two types of lattices (reticular and triangular) were simulated with varying spot overlaps and ablated material (cornea or polymethylmethacrylate [PMMA]). The roughness in ablation was determined by the root-mean-square per square root of layer depth. Truncating the beam profile increases the roughness in ablation, Gaussian profiles theoretically result in smoother ablations, round spot geometries produce lower roughness in ablation compared to square geometry, triangular lattices theoretically produce lower roughness in ablation compared to the reticular lattice, theoretically modeled beam profiles show lower roughness in ablation compared to the measured beam profile, and the simulated roughness in ablation on PMMA tends to be lower than on human cornea. For given input parameters, proper optimum parameters for minimizing the roughness have been found. Theoretically, the proposed model can be used for achieving smoothness with laser systems used for ablation processes at relatively low cost. This model may improve the quality of results and could be directly applied for improving postoperative surface quality.

Applications of Monte Carlo method to nonlinear regression of rheological data

NASA Astrophysics Data System (ADS)

Kim, Sangmo; Lee, Junghaeng; Kim, Sihyun; Cho, Kwang Soo

2018-02-01

In rheological study, it is often to determine the parameters of rheological models from experimental data. Since both rheological data and values of the parameters vary in logarithmic scale and the number of the parameters is quite large, conventional method of nonlinear regression such as Levenberg-Marquardt (LM) method is usually ineffective. The gradient-based method such as LM is apt to be caught in local minima which give unphysical values of the parameters whenever the initial guess of the parameters is far from the global optimum. Although this problem could be solved by simulated annealing (SA), the Monte Carlo (MC) method needs adjustable parameter which could be determined in ad hoc manner. We suggest a simplified version of SA, a kind of MC methods which results in effective values of the parameters of most complicated rheological models such as the Carreau-Yasuda model of steady shear viscosity, discrete relaxation spectrum and zero-shear viscosity as a function of concentration and molecular weight.

Predicting the optimal geometry of microneedles and their array for dermal vaccination using a computational model.

PubMed

Römgens, Anne M; Bader, Dan L; Bouwstra, Joke A; Oomens, Cees W J

2016-11-01

Microneedle arrays have been developed to deliver a range of biomolecules including vaccines into the skin. These microneedles have been designed with a wide range of geometries and arrangements within an array. However, little is known about the effect of the geometry on the potency of the induced immune response. The aim of this study was to develop a computational model to predict the optimal design of the microneedles and their arrangement within an array. The three-dimensional finite element model described the diffusion and kinetics in the skin following antigen delivery with a microneedle array. The results revealed an optimum distance between microneedles based on the number of activated antigen presenting cells, which was assumed to be related to the induced immune response. This optimum depends on the delivered dose. In addition, the microneedle length affects the number of cells that will be involved in either the epidermis or dermis. By contrast, the radius at the base of the microneedle and release rate only minimally influenced the number of cells that were activated. The model revealed the importance of various geometric parameters to enhance the induced immune response. The model can be developed further to determine the optimal design of an array by adjusting its various parameters to a specific situation.

Optimization and performance evaluation for nutrient removal from palm oil mill effluent wastewater using microalgae

NASA Astrophysics Data System (ADS)

Ibrahim, Raheek I.; Wong, Z. H.; Mohammad, A. W.

2015-04-01

Palm oil mill effluent (POME) wastewater was produced in huge amounts in Malaysia, and if it discharged into the environment, it causes a serious problem regarding its high content of nutrients. This study was devoted to POME wastewater treatment with microalgae. The main objective was to find the optimum conditions (retention time, and pH) in the microalgae treatment of POME wastewater considering retention time as a most important parameter in algae treatment, since after the optimum conditions there is a diverse effect of time and pH and so, the process becomes costly. According to our knowledge, there is no existing study optimized the retention time and pH with % removal of nutrients (ammonia nitrogen NH3-N, and orthophosphorous PO43-) for microalgae treatment of POME wastewater. In order to achieve with optimization, a central composite rotatable design with a second order polynomial model was used, regression coefficients and goodness of fit results in removal percentages of nutrients (NH3-N, and PO43-) were estimated.WinQSB technique was used to optimize the surface response objective functionfor the developed model. Also experiments were done to validate the model results.The optimum conditions were found to be 18 day retention time for ammonia nitrogen, and pH of 9.22, while for orthophosphorous, 15 days were indicated as the optimum retention time with a pH value of 9.2.

Comparison of parameters affecting GNP-loaded choroidal melanoma dosimetry; Monte Carlo study

NASA Astrophysics Data System (ADS)

Sharabiani, Marjan; Asadi, Somayeh; Barghi, Amir Rahnamai; Vaezzadeh, Mehdi

2018-04-01

The current study reports the results of tumor dosimetry in the presence of gold nanoparticles (GNPs) with different sizes and concentrations. Due to limited number of works carried out on the brachytherapy of choroidal melanoma in combination with GNPs, this study was performed to determine the optimum size and concentration for GNPs which contributes the highest dose deposition in tumor region, using two phantom test cases namely water phantom and a full Monte Carlo model of human eye. Both water and human eye phantoms were simulated with MCNP5 code. Tumor dosimetry was performed for a typical point photon source with an energy of 0.38 MeV as a high energy source and 103Pd brachytherapy source with an average energy of 0.021 MeV as a low energy source in water phantom and eye phantom respectively. Such a dosimetry was done for different sizes and concentrations of GNPs. For all of the diameters, increase in concentration of GNPs resulted in an increase in dose deposited in the region of interest. In a certain concentration, GNPs with larger diameters contributed more dose to the tumor region, which was more pronounced using eye phantom. 100 nm was reported as the optimum size in order to achieve the highest energy deposition within the target. This work investigated the optimum parameters affecting macroscopic dose enhancement in GNP-aided brachytherapy of choroidal melanoma. The current work also had implications on using low energy photon sources in the presence of GNPs to acquire the highest dose enhancement. This study is conducted through four different sizes and concentrations of GNPs. Considering the sensitivity of human eye tissue, in order to report the precise optimum parameters affecting radiosensitivity, a comprehensive study on a wide range of sizes and concentrations are required.

Correlation of FMISO simulations with pimonidazole-stained tumor xenografts: A question of O{sub 2} consumption?

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

Wack, L. J., E-mail: linda-jacqueline.wack@med.uni

Purpose: To compare a dedicated simulation model for hypoxia PET against tumor microsections stained for different parameters of the tumor microenvironment. The model can readily be adapted to a variety of conditions, such as different human head and neck squamous cell carcinoma (HNSCC) xenograft tumors. Methods: Nine different HNSCC tumor models were transplanted subcutaneously into nude mice. Tumors were excised and immunoflourescently labeled with pimonidazole, Hoechst 33342, and CD31, providing information on hypoxia, perfusion, and vessel distribution, respectively. Hoechst and CD31 images were used to generate maps of perfused blood vessels on which tissue oxygenation and the accumulation of themore » hypoxia tracer FMISO were mathematically simulated. The model includes a Michaelis–Menten relation to describe the oxygen consumption inside tissue. The maximum oxygen consumption rate M{sub 0} was chosen as the parameter for a tumor-specific optimization as it strongly influences tracer distribution. M{sub 0} was optimized on each tumor slice to reach optimum correlations between FMISO concentration 4 h postinjection and pimonidazole staining intensity. Results: After optimization, high pixel-based correlations up to R{sup 2} = 0.85 were found for individual tissue sections. Experimental pimonidazole images and FMISO simulations showed good visual agreement, confirming the validity of the approach. Median correlations per tumor model varied significantly (p < 0.05), with R{sup 2} ranging from 0.20 to 0.54. The optimum maximum oxygen consumption rate M{sub 0} differed significantly (p < 0.05) between tumor models, ranging from 2.4 to 5.2 mm Hg/s. Conclusions: It is feasible to simulate FMISO distributions that match the pimonidazole retention patterns observed in vivo. Good agreement was obtained for multiple tumor models by optimizing the oxygen consumption rate, M{sub 0}, whose optimum value differed significantly between tumor models.« less

Performance optimization of a miniature Joule-Thomson cryocooler using numerical model

NASA Astrophysics Data System (ADS)

Ardhapurkar, P. M.; Atrey, M. D.

2014-09-01

The performance of a miniature Joule-Thomson cryocooler depends on the effectiveness of the heat exchanger. The heat exchanger used in such cryocooler is Hampson-type recuperative heat exchanger. The design of the efficient heat exchanger is crucial for the optimum performance of the cryocooler. In the present work, the heat exchanger is numerically simulated for the steady state conditions and the results are validated against the experimental data available from the literature. The area correction factor is identified for the calculation of effective heat transfer area which takes into account the effect of helical geometry. In order to get an optimum performance of the cryocoolers, operating parameters like mass flow rate, pressure and design parameters like heat exchanger length, helical diameter of coil, fin dimensions, fin density have to be identified. The present work systematically addresses this aspect of design for miniature J-T cryocooler.

Effect of the curvature parameter on least-squares prediction within poor data coverage: case study for Africa

NASA Astrophysics Data System (ADS)

Abd-Elmotaal, Hussein; Kühtreiber, Norbert

2016-04-01

In the framework of the IAG African Geoid Project, there are a lot of large data gaps in its gravity database. These gaps are filled initially using unequal weight least-squares prediction technique. This technique uses a generalized Hirvonen covariance function model to replace the empirically determined covariance function. The generalized Hirvonen covariance function model has a sensitive parameter which is related to the curvature parameter of the covariance function at the origin. This paper studies the effect of the curvature parameter on the least-squares prediction results, especially in the large data gaps as appearing in the African gravity database. An optimum estimation of the curvature parameter has also been carried out. A wide comparison among the results obtained in this research along with their obtained accuracy is given and thoroughly discussed.

QSPR modeling: graph connectivity indices versus line graph connectivity indices

PubMed

Basak; Nikolic; Trinajstic; Amic; Beslo

2000-07-01

Five QSPR models of alkanes were reinvestigated. Properties considered were molecular surface-dependent properties (boiling points and gas chromatographic retention indices) and molecular volume-dependent properties (molar volumes and molar refractions). The vertex- and edge-connectivity indices were used as structural parameters. In each studied case we computed connectivity indices of alkane trees and alkane line graphs and searched for the optimum exponent. Models based on indices with an optimum exponent and on the standard value of the exponent were compared. Thus, for each property we generated six QSPR models (four for alkane trees and two for the corresponding line graphs). In all studied cases QSPR models based on connectivity indices with optimum exponents have better statistical characteristics than the models based on connectivity indices with the standard value of the exponent. The comparison between models based on vertex- and edge-connectivity indices gave in two cases (molar volumes and molar refractions) better models based on edge-connectivity indices and in three cases (boiling points for octanes and nonanes and gas chromatographic retention indices) better models based on vertex-connectivity indices. Thus, it appears that the edge-connectivity index is more appropriate to be used in the structure-molecular volume properties modeling and the vertex-connectivity index in the structure-molecular surface properties modeling. The use of line graphs did not improve the predictive power of the connectivity indices. Only in one case (boiling points of nonanes) a better model was obtained with the use of line graphs.

Optimization of Maillard Reaction in Model System of Glucosamine and Cysteine Using Response Surface Methodology

PubMed Central

Arachchi, Shanika Jeewantha Thewarapperuma; Kim, Ye-Joo; Kim, Dae-Wook; Oh, Sang-Chul; Lee, Yang-Bong

2017-01-01

Sulfur-containing amino acids play important roles in good flavor generation in Maillard reaction of non-enzymatic browning, so aqueous model systems of glucosamine and cysteine were studied to investigate the effects of reaction temperature, initial pH, reaction time, and concentration ratio of glucosamine and cysteine. Response surface methodology was applied to optimize the independent reaction parameters of cysteine and glucosamine in Maillard reaction. Box-Behnken factorial design was used with 30 runs of 16 factorial levels, 8 axial levels and 6 central levels. The degree of Maillard reaction was determined by reading absorption at 425 nm in a spectrophotometer and Hunter’s L, a, and b values. ΔE was consequently set as the fifth response factor. In the statistical analyses, determination coefficients (R2) for their absorbance, Hunter’s L, a, b values, and ΔE were 0.94, 0.79, 0.73, 0.96, and 0.79, respectively, showing that the absorbance and Hunter’s b value were good dependent variables for this model system. The optimum processing parameters were determined to yield glucosamine-cysteine Maillard reaction product with higher absorbance and higher colour change. The optimum estimated absorbance was achieved at the condition of initial pH 8.0, 111°C reaction temperature, 2.47 h reaction time, and 1.30 concentration ratio. The optimum condition for colour change measured by Hunter’s b value was 2.41 h reaction time, 114°C reaction temperature, initial pH 8.3, and 1.26 concentration ratio. These results can provide the basic information for Maillard reaction of aqueous model system between glucosamine and cysteine. PMID:28401086

Optimization of Maillard Reaction in Model System of Glucosamine and Cysteine Using Response Surface Methodology.

PubMed

Arachchi, Shanika Jeewantha Thewarapperuma; Kim, Ye-Joo; Kim, Dae-Wook; Oh, Sang-Chul; Lee, Yang-Bong

2017-03-01

Sulfur-containing amino acids play important roles in good flavor generation in Maillard reaction of non-enzymatic browning, so aqueous model systems of glucosamine and cysteine were studied to investigate the effects of reaction temperature, initial pH, reaction time, and concentration ratio of glucosamine and cysteine. Response surface methodology was applied to optimize the independent reaction parameters of cysteine and glucosamine in Maillard reaction. Box-Behnken factorial design was used with 30 runs of 16 factorial levels, 8 axial levels and 6 central levels. The degree of Maillard reaction was determined by reading absorption at 425 nm in a spectrophotometer and Hunter's L, a, and b values. ΔE was consequently set as the fifth response factor. In the statistical analyses, determination coefficients (R 2 ) for their absorbance, Hunter's L, a, b values, and ΔE were 0.94, 0.79, 0.73, 0.96, and 0.79, respectively, showing that the absorbance and Hunter's b value were good dependent variables for this model system. The optimum processing parameters were determined to yield glucosamine-cysteine Maillard reaction product with higher absorbance and higher colour change. The optimum estimated absorbance was achieved at the condition of initial pH 8.0, 111°C reaction temperature, 2.47 h reaction time, and 1.30 concentration ratio. The optimum condition for colour change measured by Hunter's b value was 2.41 h reaction time, 114°C reaction temperature, initial pH 8.3, and 1.26 concentration ratio. These results can provide the basic information for Maillard reaction of aqueous model system between glucosamine and cysteine.

Electrode performance parameters for a radioisotope-powered AMTEC for space power applications

NASA Technical Reports Server (NTRS)

Underwood, M. L.; O'Connor, D.; Williams, R. M.; Jeffries-Nakamura, B.; Ryan, M. A.; Bankston, C. P.

1992-01-01

The alkali metal thermoelastic converter (AMTEC) is a device for the direct conversion of heat to electricity. Recently a design of an AMTEC using a radioisotope heat source was described, but the optimum condenser temperature was hotter than the temperatures used in the laboratory to develop the electrode performance model. Now laboratory experiments have confirmed the dependence of two model parameters over a broader range of condenser and electrode temperatures for two candidate electrode compositions. One parameter, the electrochemical exchange current density at the reaction interface, is independent of the condenser temperature, and depends only upon the collision rate of sodium at the reaction zone. The second parameter, a morphological parameter, which measures the mass transport resistance through the electrode, is independent of condenser and electrode temperatures for molybdenum electrodes. For rhodium-tungsten electrodes, however, this parameter increases for decreasing electrode temperature, indicating an activated mass transport mechanism such as surface diffusion.

Evaluation of mechanical losses in a linear motor pressure wave generator

NASA Astrophysics Data System (ADS)

Jacob, Subhash; Rangasamy, Karunanithi; Jonnalagadda, Kranthi Kumar; Chakkala, Damu; Achanur, Mallappa; Govindswamy, Jagadish; Gour, Abhay Singh

2012-06-01

A moving magnet linear motor compressor or pressure wave generator (PWG) of 2 cc swept volume with dual opposed piston configuration has been developed to operate miniature pulse tube coolers. Prelimnary experiments yielded only a no-load cold end temperature of 180 K. Auxiliary tests and the interpretation of detailed modeling of a PWG suggest that much of the PV power has been lost in the form of blow-by at piston seals due to large and non-optimum clearance seal gap between piston and cylinder. The results of experimental parameters simulated using Sage provide the optimum seal gap value for maximizing the delivered PV power.

Development of genetic algorithm-based optimization module in WHAT system for hydrograph analysis and model application

NASA Astrophysics Data System (ADS)

Lim, Kyoung Jae; Park, Youn Shik; Kim, Jonggun; Shin, Yong-Chul; Kim, Nam Won; Kim, Seong Joon; Jeon, Ji-Hong; Engel, Bernard A.

2010-07-01

Many hydrologic and water quality computer models have been developed and applied to assess hydrologic and water quality impacts of land use changes. These models are typically calibrated and validated prior to their application. The Long-Term Hydrologic Impact Assessment (L-THIA) model was applied to the Little Eagle Creek (LEC) watershed and compared with the filtered direct runoff using BFLOW and the Eckhardt digital filter (with a default BFI max value of 0.80 and filter parameter value of 0.98), both available in the Web GIS-based Hydrograph Analysis Tool, called WHAT. The R2 value and the Nash-Sutcliffe coefficient values were 0.68 and 0.64 with BFLOW, and 0.66 and 0.63 with the Eckhardt digital filter. Although these results indicate that the L-THIA model estimates direct runoff reasonably well, the filtered direct runoff values using BFLOW and Eckhardt digital filter with the default BFI max and filter parameter values do not reflect hydrological and hydrogeological situations in the LEC watershed. Thus, a BFI max GA-Analyzer module (BFI max Genetic Algorithm-Analyzer module) was developed and integrated into the WHAT system for determination of the optimum BFI max parameter and filter parameter of the Eckhardt digital filter. With the automated recession curve analysis method and BFI max GA-Analyzer module of the WHAT system, the optimum BFI max value of 0.491 and filter parameter value of 0.987 were determined for the LEC watershed. The comparison of L-THIA estimates with filtered direct runoff using an optimized BFI max and filter parameter resulted in an R2 value of 0.66 and the Nash-Sutcliffe coefficient value of 0.63. However, L-THIA estimates calibrated with the optimized BFI max and filter parameter increased by 33% and estimated NPS pollutant loadings increased by more than 20%. This indicates L-THIA model direct runoff estimates can be incorrect by 33% and NPS pollutant loading estimation by more than 20%, if the accuracy of the baseflow separation method is not validated for the study watershed prior to model comparison. This study shows the importance of baseflow separation in hydrologic and water quality modeling using the L-THIA model.

Laser cutting metallic plates using a 2kW direct diode laser source

NASA Astrophysics Data System (ADS)

Fallahi Sichani, E.; Hauschild, D.; Meinschien, J.; Powell, J.; Assunção, E. G.; Blackburn, J.; Khan, A. H.; Kong, C. Y.

2015-07-01

This paper investigates the feasibility of using a 2kW direct diode laser source for producing high-quality cuts in a variety of materials. Cutting trials were performed in a two-stage experimental procedure. The first phase of trials was based on a one-factor-at-a-time change of process parameters aimed at exploring the process window and finding a semi-optimum set of parameters for each material/thickness combination. In the second phase, a full factorial experimental matrix was performed for each material and thickness, as a result of which, the optimum cutting parameters were identified. Characteristic values of the optimum cuts were then measured as per BS EN ISO 9013:2002.

Optimization control of LNG regasification plant using Model Predictive Control

NASA Astrophysics Data System (ADS)

Wahid, A.; Adicandra, F. F.

2018-03-01

Optimization of liquified natural gas (LNG) regasification plant is important to minimize costs, especially operational costs. Therefore, it is important to choose optimum LNG regasification plant design and maintaining the optimum operating conditions through the implementation of model predictive control (MPC). Optimal tuning parameter for MPC such as P (prediction horizon), M (control of the horizon) and T (sampling time) are achieved by using fine-tuning method. The optimal criterion for design is the minimum amount of energy used and for control is integral of square error (ISE). As a result, the optimum design is scheme 2 which is developed by Devold with an energy savings of 40%. To maintain the optimum conditions, required MPC with P, M and T as follows: tank storage pressure: 90, 2, 1; product pressure: 95, 2, 1; temperature vaporizer: 65, 2, 2; and temperature heater: 35, 6, 5, with ISE value at set point tracking respectively 0.99, 1792.78, 34.89 and 7.54, or improvement of control performance respectively 4.6%, 63.5%, 3.1% and 58.2% compared to PI controller performance. The energy savings that MPC controllers can make when there is a disturbance in temperature rise 1°C of sea water is 0.02 MW.

The dimensional reduction method for identification of parameters that trade-off due to similar model roles.

PubMed

Davidson, Shaun M; Docherty, Paul D; Murray, Rua

2017-03-01

Parameter identification is an important and widely used process across the field of biomedical engineering. However, it is susceptible to a number of potential difficulties, such as parameter trade-off, causing premature convergence at non-optimal parameter values. The proposed Dimensional Reduction Method (DRM) addresses this issue by iteratively reducing the dimension of hyperplanes where trade off occurs, and running subsequent identification processes within these hyperplanes. The DRM was validated using clinical data to optimize 4 parameters of the widely used Bergman Minimal Model of glucose and insulin kinetics, as well as in-silico data to optimize 5 parameters of the Pulmonary Recruitment (PR) Model. Results were compared with the popular Levenberg-Marquardt (LMQ) Algorithm using a Monte-Carlo methodology, with both methods afforded equivalent computational resources. The DRM converged to a lower or equal residual value in all tests run using the Bergman Minimal Model and actual patient data. For the PR model, the DRM attained significantly lower overall median parameter error values and lower residuals in the vast majority of tests. This shows the DRM has potential to provide better resolution of optimum parameter values for the variety of biomedical models in which significant levels of parameter trade-off occur. Copyright © 2017 Elsevier Inc. All rights reserved.

Optimization of seismic isolation systems via harmony search

NASA Astrophysics Data System (ADS)

Melih Nigdeli, Sinan; Bekdaş, Gebrail; Alhan, Cenk

2014-11-01

In this article, the optimization of isolation system parameters via the harmony search (HS) optimization method is proposed for seismically isolated buildings subjected to both near-fault and far-fault earthquakes. To obtain optimum values of isolation system parameters, an optimization program was developed in Matlab/Simulink employing the HS algorithm. The objective was to obtain a set of isolation system parameters within a defined range that minimizes the acceleration response of a seismically isolated structure subjected to various earthquakes without exceeding a peak isolation system displacement limit. Several cases were investigated for different isolation system damping ratios and peak displacement limitations of seismic isolation devices. Time history analyses were repeated for the neighbouring parameters of optimum values and the results proved that the parameters determined via HS were true optima. The performance of the optimum isolation system was tested under a second set of earthquakes that was different from the first set used in the optimization process. The proposed optimization approach is applicable to linear isolation systems. Isolation systems composed of isolation elements that are inherently nonlinear are the subject of a future study. Investigation of the optimum isolation system parameters has been considered in parametric studies. However, obtaining the best performance of a seismic isolation system requires a true optimization by taking the possibility of both near-fault and far-fault earthquakes into account. HS optimization is proposed here as a viable solution to this problem.

Inverse modeling approach for evaluation of kinetic parameters of a biofilm reactor using tabu search.

PubMed

Kumar, B Shiva; Venkateswarlu, Ch

2014-08-01

The complex nature of biological reactions in biofilm reactors often poses difficulties in analyzing such reactors experimentally. Mathematical models could be very useful for their design and analysis. However, application of biofilm reactor models to practical problems proves somewhat ineffective due to the lack of knowledge of accurate kinetic models and uncertainty in model parameters. In this work, we propose an inverse modeling approach based on tabu search (TS) to estimate the parameters of kinetic and film thickness models. TS is used to estimate these parameters as a consequence of the validation of the mathematical models of the process with the aid of measured data obtained from an experimental fixed-bed anaerobic biofilm reactor involving the treatment of pharmaceutical industry wastewater. The results evaluated for different modeling configurations of varying degrees of complexity illustrate the effectiveness of TS for accurate estimation of kinetic and film thickness model parameters of the biofilm process. The results show that the two-dimensional mathematical model with Edward kinetics (with its optimum parameters as mu(max)rho(s)/Y = 24.57, Ks = 1.352 and Ki = 102.36) and three-parameter film thickness expression (with its estimated parameters as a = 0.289 x 10(-5), b = 1.55 x 10(-4) and c = 15.2 x 10(-6)) better describes the biofilm reactor treating the industry wastewater.

The expression of the skeletal muscle force-length relationship in vivo: a simulation study.

PubMed

Winter, Samantha L; Challis, John H

2010-02-21

The force-length relationship is one of the most important mechanical characteristics of skeletal muscle in humans and animals. For a physiologically realistic joint range of motion and therefore range of muscle fibre lengths only part of the force-length curve may be used in vivo, i.e. only a section of the force-length curve is expressed. A generalised model of a mono-articular muscle-tendon complex was used to examine the effect of various muscle architecture parameters on the expressed section of the force-length relationship for a 90 degrees joint range of motion. The parameters investigated were: the ratio of tendon resting length to muscle fibre optimum length (L(TR):L(F.OPT)) (varied from 0.5 to 11.5), the ratio of muscle fibre optimum length to average moment arm (L(F.OPT):r) (varied from 0.5 to 5), the normalised tendon strain at maximum isometric force (c) (varied from 0 to 0.08), the muscle fibre pennation angle (theta) (varied from 0 degrees to 45 degrees) and the joint angle at which the optimum muscle fibre length occurred (phi). The range of values chosen for each parameter was based on values reported in the literature for five human mono-articular muscles with different functional roles. The ratios L(TR):L(F.OPT) and L(F.OPT):r were important in determining the amount of variability in the expressed section of the force-length relationship. The modelled muscle operated over only one limb at intermediate values of these two ratios (L(TR):L(F.OPT)=5; L(F.OPT):r=3), whether this was the ascending or descending limb was determined by the precise values of the other parameters. It was concluded that inter-individual variability in the expressed section of the force-length relationship is possible, particularly for muscles with intermediate values of L(TR):L(F.OPT) and L(F.OPT):r such as the brachialis and vastus lateralis. Understanding the potential for inter-individual variability in the expressed section is important when using muscle models to simulate movement. (c) 2009 Elsevier Ltd. All rights reserved.

Optimum survival strategies against zombie infestations - a population dynamics approach

NASA Astrophysics Data System (ADS)

Mota, Bruno

2014-03-01

We model a zombie infestation by three coupled ODEs that jointly describe the time evolution of three populations: regular humans, zombies, and survivors (humans that have survived at least one zombie encounter). This can be generalized to take into account more levels of expertise and/or skill degradation. We compute the fixed points, and stability thereof, that correspond to one of three possible outcomes: human extinction, zombie extermination or, if one allows for a human non-zero birth-rate, co-habitation. We obtain analytically the optimum strategy for humans in terms of the model's parameters (essentially, whether to flee and hide, or fight). Zombies notwithstanding, this can also be seen as a toy model for infections of immune system cells, such as CD4+ T cells in AIDS, and macrophages in tuberculosis, whereby cells are both the target of infection, and mediate the acquired immunity response against the same infection. I thank FAPERJ for financial support.

The Dynamics Of Plucking

NASA Astrophysics Data System (ADS)

Griffel, D. H.

1994-08-01

A mathematical model of the excitation of a vibrating system by a plucking action is studied. The mechanism is of the type used in musical instruments. The effectiveness of the mechanism is computed over a considerable range of the relevant parameters. As the speed of the pluck is increased, with other parameters held fixed, the amplitude of the vibration produced rises to a maximum and then decreases to zero. The optimum speed increases with the stiffness of the plectrum. Other aspects of the behaviour of the system are discussed.

Biosorption of toxic lead (II) ions using tomato waste (Solanum lycopersicum) activated by NaOH

NASA Astrophysics Data System (ADS)

Permatasari, Diah; Heraldy, Eddy; Lestari, Witri Wahyu

2016-02-01

This research present to uptake lead (II) ion from aqueous solutions by activated tomato waste. Biosorbent were characterized by applying Fourier Transform Infrared Spectroscopy (FTIR) and Surface Area Analyzer (SAA). The biosorption investigated with parameters including the concentration of NaOH, effects of solution pH, biosorbent dosage, contact time,and initial metal concentration. Experimental data were analyzed in terms of two kinetic model such us the pseudo-first order and pseudo-second order. Langmuir and Freundlich isotherm models were applied todescribe the biosorption process. According to the experiment, the optimum concentration of NaOH was achieved at 0.1 M. The maximum % lead (II) removal was achieved at pH 4 with 94.5%. Optimum biosorbentdosage were found as 0.1 g/25 mL solution while optimum contact time were found at 75 minutes. The results showed that the biosorption processes of Lead (II) followed pseudo-second order kinetics. Langmuir adsorption isotherm was found fit the adsorption data with amaximum capacity of 24.079 mg/g with anadsorption energy of 28.046 kJ/mol.

A hybrid optimization approach to the estimation of distributed parameters in two-dimensional confined aquifers

USGS Publications Warehouse

Heidari, M.; Ranjithan, S.R.

1998-01-01

In using non-linear optimization techniques for estimation of parameters in a distributed ground water model, the initial values of the parameters and prior information about them play important roles. In this paper, the genetic algorithm (GA) is combined with the truncated-Newton search technique to estimate groundwater parameters for a confined steady-state ground water model. Use of prior information about the parameters is shown to be important in estimating correct or near-correct values of parameters on a regional scale. The amount of prior information needed for an accurate solution is estimated by evaluation of the sensitivity of the performance function to the parameters. For the example presented here, it is experimentally demonstrated that only one piece of prior information of the least sensitive parameter is sufficient to arrive at the global or near-global optimum solution. For hydraulic head data with measurement errors, the error in the estimation of parameters increases as the standard deviation of the errors increases. Results from our experiments show that, in general, the accuracy of the estimated parameters depends on the level of noise in the hydraulic head data and the initial values used in the truncated-Newton search technique.In using non-linear optimization techniques for estimation of parameters in a distributed ground water model, the initial values of the parameters and prior information about them play important roles. In this paper, the genetic algorithm (GA) is combined with the truncated-Newton search technique to estimate groundwater parameters for a confined steady-state ground water model. Use of prior information about the parameters is shown to be important in estimating correct or near-correct values of parameters on a regional scale. The amount of prior information needed for an accurate solution is estimated by evaluation of the sensitivity of the performance function to the parameters. For the example presented here, it is experimentally demonstrated that only one piece of prior information of the least sensitive parameter is sufficient to arrive at the global or near-global optimum solution. For hydraulic head data with measurement errors, the error in the estimation of parameters increases as the standard deviation of the errors increases. Results from our experiments show that, in general, the accuracy of the estimated parameters depends on the level of noise in the hydraulic head data and the initial values used in the truncated-Newton search technique.

Determination of optimum parameters of the technological process for plates forming from V95 and V-1461 alloys in creep applied in aircrafts constructed by “Sukhoi design bureau”

NASA Astrophysics Data System (ADS)

Raevskaya, G. A.; Zakharchenko, K.; Larichkin, A.

2017-10-01

The research is devoted to the scientific justification of metal processing by pressure with the help of thick monolithic plates forming (thickness 40 mm) from the V95 (analog 7475) (Al-Zn-Mg-Cu) and V-1461 (analog 2099) (Al-Cu-Li-Zn) alloys in creep and close-to-superplasticity. Optimum parameters of the technological process of plate forming are described. The effect of temperature on the magnitude of mechanical stresses (relaxation) during the tests of materials on pure bending is experimentally determined. Forming of thick plates (40 mm) on the UFP-1M unit, and the control of the obtained surface, in comparison with the given electronic model, made it possible to experimentally determine the time and number of forming stages. Mechanical properties of the material after the technological process and heat treatment are preliminary evaluated. The efficiency of using the obtained parameters of the technological process and treatment of metals by pressure in such methods in general is shown.

A Bottom-Up Optimization Approach for Friction Stir Welding Parameters of Dissimilar AA2024-T351 and AA7075-T651 Alloys

NASA Astrophysics Data System (ADS)

Anil Kumar, K. S.; Murigendrappa, S. M.; Kumar, Hemantha

2017-07-01

In the present study, optimum friction stir weld parameters such as plunge depth, tool rotation speed and traverse speed for butt weld of dissimilar aluminum alloy plates, typically 2024-T351 and 7075-T651, are investigated using a bottom-up approach. In the approach, optimum FSW parameters are achieved by varying any one parameter for every trial while remaining parameters are kept constant. The specimens are extracted from the friction stir-welded plates for studying the tensile, hardness and microstructure properties. Optimum friction stir weld individual parameters are selected based on the highest ultimate tensile strength of the friction stir-welded butt joint specimens produced by varying in each case one parameter and keeping the other two constant. The microstructure samples were investigated for presence of defects, grain refinement at the weld nugget (WN), bonding between the two materials and interface of WN, TMAZ (thermomechanically affected zone) of both advancing and retreating sides of the dissimilar joints using optical microscopy and scanning electron microscopy analyses. In the experimental investigations, the optimum FSW parameters such as plunge depth, 6.2 mm, rotation speed, 650 rpm and traverse speed of 150 mm/min result in ultimate tensile strength, 435 MPa, yield strength, 290 MPa, weld joint efficiency, 92% and maximum elongation, 13%. The microstructure of optimized sample in the WN region revealed alternate lamellae material flow pattern with better metallurgical properties, defect free and very fine equiaxed grain size of about 3-5 µm.

Optimum Damping in a Non-Linear Base Isolation System

NASA Astrophysics Data System (ADS)

Jangid, R. S.

1996-02-01

Optimum isolation damping for minimum acceleration of a base-isolated structure subjected to earthquake ground excitation is investigated. The stochastic model of the El-Centro1940 earthquake, which preserves the non-stationary evolution of amplitude and frequency content of ground motion, is used as an earthquake excitation. The base isolated structure consists of a linear flexible shear type multi-storey building supported on a base isolation system. The resilient-friction base isolator (R-FBI) is considered as an isolation system. The non-stationary stochastic response of the system is obtained by the time dependent equivalent linearization technique as the force-deformation of the R-FBI system is non-linear. The optimum damping of the R-FBI system is obtained under important parametric variations; i.e., the coefficient of friction of the R-FBI system, the period and damping of the superstructure; the effective period of base isolation. The criterion selected for optimality is the minimization of the top floor root mean square (r.m.s.) acceleration. It is shown that the above parameters have significant effects on optimum isolation damping.

Tissue multifractality and hidden Markov model based integrated framework for optimum precancer detection

NASA Astrophysics Data System (ADS)

Mukhopadhyay, Sabyasachi; Das, Nandan K.; Kurmi, Indrajit; Pradhan, Asima; Ghosh, Nirmalya; Panigrahi, Prasanta K.

2017-10-01

We report the application of a hidden Markov model (HMM) on multifractal tissue optical properties derived via the Born approximation-based inverse light scattering method for effective discrimination of precancerous human cervical tissue sites from the normal ones. Two global fractal parameters, generalized Hurst exponent and the corresponding singularity spectrum width, computed by multifractal detrended fluctuation analysis (MFDFA), are used here as potential biomarkers. We develop a methodology that makes use of these multifractal parameters by integrating with different statistical classifiers like the HMM and support vector machine (SVM). It is shown that the MFDFA-HMM integrated model achieves significantly better discrimination between normal and different grades of cancer as compared to the MFDFA-SVM integrated model.

Wiener-Hammerstein system identification - an evolutionary approach

NASA Astrophysics Data System (ADS)

Naitali, Abdessamad; Giri, Fouad

2016-01-01

The problem of identifying parametric Wiener-Hammerstein (WH) systems is addressed within the evolutionary optimisation context. Specifically, a hybrid culture identification method is developed that involves model structure adaptation using genetic recombination and model parameter learning using particle swarm optimisation. The method enjoys three interesting features: (1) the risk of premature convergence of model parameter estimates to local optima is significantly reduced, due to the constantly maintained diversity of model candidates; (2) no prior knowledge is needed except for upper bounds on the system structure indices; (3) the method is fully autonomous as no interaction is needed with the user during the optimum search process. The performances of the proposed method will be illustrated and compared to alternative methods using a well-established WH benchmark.

Modeling the compliance of polyurethane nanofiber tubes for artificial common bile duct

NASA Astrophysics Data System (ADS)

Moazeni, Najmeh; Vadood, Morteza; Semnani, Dariush; Hasani, Hossein

2018-02-01

The common bile duct is one of the body’s most sensitive organs and a polyurethane nanofiber tube can be used as a prosthetic of the common bile duct. The compliance is one of the most important properties of prosthetic which should be adequately compliant as long as possible to keep the behavioral integrity of prosthetic. In the present paper, the prosthetic compliance was measured and modeled using regression method and artificial neural network (ANN) based on the electrospinning process parameters such as polymer concentration, voltage, tip-to-collector distance and flow rate. Whereas, the ANN model contains different parameters affecting on the prediction accuracy directly, the genetic algorithm (GA) was used to optimize the ANN parameters. Finally, it was observed that the optimized ANN model by GA can predict the compliance with high accuracy (mean absolute percentage error = 8.57%). Moreover, the contribution of variables on the compliance was investigated through relative importance analysis and the optimum values of parameters for ideal compliance were determined.

Overview of SDCM - The Spacecraft Design and Cost Model

NASA Technical Reports Server (NTRS)

Ferebee, Melvin J.; Farmer, Jeffery T.; Andersen, Gregory C.; Flamm, Jeffery D.; Badi, Deborah M.

1988-01-01

The Spacecraft Design and Cost Model (SDCM) is a computer-aided design and analysis tool for synthesizing spacecraft configurations, integrating their subsystems, and generating information concerning on-orbit servicing and costs. SDCM uses a bottom-up method in which the cost and performance parameters for subsystem components are first calculated; the model then sums the contributions from individual components in order to obtain an estimate of sizes and costs for each candidate configuration within a selected spacecraft system. An optimum spacraft configuration can then be selected.

Performance testing of a vertical Bridgman furnace using experiments and numerical modeling

NASA Astrophysics Data System (ADS)

Rosch, W. R.; Fripp, A. L.; Debnam, W. J.; Pendergrass, T. K.

1997-04-01

This paper details a portion of the work performed in preparation for the growth of lead tin telluride crystals during a Space Shuttle flight. A coordinated effort of experimental measurements and numerical modeling was completed to determine the optimum growth parameters and the performance of the furnace. This work was done using NASA's Advanced Automated Directional Solidification Furnace, but the procedures used should be equally valid for other vertical Bridgman furnaces.

Preparation of activated petroleum coke for removal of naphthenic acids model compounds: Box-Behnken design optimization of KOH activation process.

PubMed

Niasar, Hojatallah Seyedy; Li, Hanning; Das, Sreejon; Kasanneni, Tirumala Venkateswara Rao; Ray, Madhumita B; Xu, Chunbao Charles

2018-04-01

This study employed Box-Behnken design and response surface methodology to optimize activation parameters for the production of activated petroleum coke (APC) adsorbent from petroleum coke (PC) to achieve highest adsorption capacity for three model naphthenic acids. Activated petroleum coke (APC) adsorbent with a BET surface area of 1726 m 2 /g and total pore volume of 0.85 cc/g was produced at the optimum activation conditions (KOH/coke mass ratio) of 3.0, activation temperature 790 °C, and activation time 3.47 h). Effects of the activation parameters on the adsorption pefromances (adsortion capaciy and kinetics) were investigated. With the APC obtained at the optimum activation condition, the maximum adsorption capacity of 451, 362, and 320 (mg/g) was achieved for 2-naphthoic acid, diphenylacetic acid and cyclohexanepentanoic acid (CP), respectively. Although, generally APC adsorbents with a higher specific surface area and pore volume provide better adsorption capacity, the textural properties (surface areas and pore volume) are not the only parameters determining the APC adsorbents' adsorption capacity. Other parameters such as surface functionalities play effective roles on the adsorption capacity of the produced APC adsorbents for NAs. The KOH activation process, in particular the acid washing step, distinctly reduced the sulfur and metals contents in the raw PC, decreasing the leaching potential of metals from APC adsorbents during adsorption. Copyright © 2018 Elsevier Ltd. All rights reserved.

Estimating of aquifer parameters from the single-well water-level measurements in response to advancing longwall mine by using particle swarm optimization

NASA Astrophysics Data System (ADS)

Buyuk, Ersin; Karaman, Abdullah

2017-04-01

We estimated transmissivity and storage coefficient values from the single well water-level measurements positioned ahead of the mining face by using particle swarm optimization (PSO) technique. The water-level response to the advancing mining face contains an semi-analytical function that is not suitable for conventional inversion shemes because the partial derivative is difficult to calculate . Morever, the logaritmic behaviour of the model create difficulty for obtaining an initial model that may lead to a stable convergence. The PSO appears to obtain a reliable solution that produce a reasonable fit between water-level data and model function response. Optimization methods have been used to find optimum conditions consisting either minimum or maximum of a given objective function with regard to some criteria. Unlike PSO, traditional non-linear optimization methods have been used for many hydrogeologic and geophysical engineering problems. These methods indicate some difficulties such as dependencies to initial model, evolution of the partial derivatives that is required while linearizing the model and trapping at local optimum. Recently, Particle swarm optimization (PSO) became the focus of modern global optimization method that is inspired from the social behaviour of birds of swarms, and appears to be a reliable and powerful algorithms for complex engineering applications. PSO that is not dependent on an initial model, and non-derivative stochastic process appears to be capable of searching all possible solutions in the model space either around local or global optimum points.

Multi objective optimization model for minimizing production cost and environmental impact in CNC turning process

NASA Astrophysics Data System (ADS)

Widhiarso, Wahyu; Rosyidi, Cucuk Nur

2018-02-01

Minimizing production cost in a manufacturing company will increase the profit of the company. The cutting parameters will affect total processing time which then will affect the production cost of machining process. Besides affecting the production cost and processing time, the cutting parameters will also affect the environment. An optimization model is needed to determine the optimum cutting parameters. In this paper, we develop an optimization model to minimize the production cost and the environmental impact in CNC turning process. The model is used a multi objective optimization. Cutting speed and feed rate are served as the decision variables. Constraints considered are cutting speed, feed rate, cutting force, output power, and surface roughness. The environmental impact is converted from the environmental burden by using eco-indicator 99. Numerical example is given to show the implementation of the model and solved using OptQuest of Oracle Crystal Ball software. The results of optimization indicate that the model can be used to optimize the cutting parameters to minimize the production cost and the environmental impact.

Development of cubic Bezier curve and curve-plane intersection method for parametric submarine hull form design to optimize hull resistance using CFD

NASA Astrophysics Data System (ADS)

Chrismianto, Deddy; Zakki, Ahmad Fauzan; Arswendo, Berlian; Kim, Dong Joon

2015-12-01

Optimization analysis and computational fluid dynamics (CFDs) have been applied simultaneously, in which a parametric model plays an important role in finding the optimal solution. However, it is difficult to create a parametric model for a complex shape with irregular curves, such as a submarine hull form. In this study, the cubic Bezier curve and curve-plane intersection method are used to generate a solid model of a parametric submarine hull form taking three input parameters into account: nose radius, tail radius, and length-height hull ratio ( L/ H). Application program interface (API) scripting is also used to write code in the ANSYS design modeler. The results show that the submarine shape can be generated with some variation of the input parameters. An example is given that shows how the proposed method can be applied successfully to a hull resistance optimization case. The parametric design of the middle submarine type was chosen to be modified. First, the original submarine model was analyzed, in advance, using CFD. Then, using the response surface graph, some candidate optimal designs with a minimum hull resistance coefficient were obtained. Further, the optimization method in goal-driven optimization (GDO) was implemented to find the submarine hull form with the minimum hull resistance coefficient ( C t ). The minimum C t was obtained. The calculated difference in C t values between the initial submarine and the optimum submarine is around 0.26%, with the C t of the initial submarine and the optimum submarine being 0.001 508 26 and 0.001 504 29, respectively. The results show that the optimum submarine hull form shows a higher nose radius ( r n ) and higher L/ H than those of the initial submarine shape, while the radius of the tail ( r t ) is smaller than that of the initial shape.

Designing nacre-like materials for simultaneous stiffness, strength and toughness: Optimum materials, composition, microstructure and size

NASA Astrophysics Data System (ADS)

Barthelat, Francois

2014-12-01

Nacre, bone and spider silk are staggered composites where inclusions of high aspect ratio reinforce a softer matrix. Such staggered composites have emerged through natural selection as the best configuration to produce stiffness, strength and toughness simultaneously. As a result, these remarkable materials are increasingly serving as model for synthetic composites with unusual and attractive performance. While several models have been developed to predict basic properties for biological and bio-inspired staggered composites, the designer is still left to struggle with finding optimum parameters. Unresolved issues include choosing optimum properties for inclusions and matrix, and resolving the contradictory effects of certain design variables. Here we overcome these difficulties with a multi-objective optimization for simultaneous high stiffness, strength and energy absorption in staggered composites. Our optimization scheme includes material properties for inclusions and matrix as design variables. This process reveals new guidelines, for example the staggered microstructure is only advantageous if the tablets are at least five times stronger than the interfaces, and only if high volume concentrations of tablets are used. We finally compile the results into a step-by-step optimization procedure which can be applied for the design of any type of high-performance staggered composite and at any length scale. The procedure produces optimum designs which are consistent with the materials and microstructure of natural nacre, confirming that this natural material is indeed optimized for mechanical performance.

Quality assessment and artificial neural networks modeling for characterization of chemical and physical parameters of potable water.

PubMed

Salari, Marjan; Salami Shahid, Esmaeel; Afzali, Seied Hosein; Ehteshami, Majid; Conti, Gea Oliveri; Derakhshan, Zahra; Sheibani, Solmaz Nikbakht

2018-04-22

Today, due to the increase in the population, the growth of industry and the variety of chemical compounds, the quality of drinking water has decreased. Five important river water quality properties such as: dissolved oxygen (DO), total dissolved solids (TDS), total hardness (TH), alkalinity (ALK) and turbidity (TU) were estimated by parameters such as: electric conductivity (EC), temperature (T), and pH that could be measured easily with almost no costs. Simulate water quality parameters were examined with two methods of modeling include mathematical and Artificial Neural Networks (ANN). Mathematical methods are based on polynomial fitting with least square method and ANN modeling algorithms are feed-forward networks. All conditions/circumstances covered by neural network modeling were tested for all parameters in this study, except for Alkalinity. All optimum ANN models developed to simulate water quality parameters had precision value as R-value close to 0.99. The ANN model extended to simulate alkalinity with R-value equals to 0.82. Moreover, Surface fitting techniques were used to refine data sets. Presented models and equations are reliable/useable tools for studying water quality parameters at similar rivers, as a proper replacement for traditional water quality measuring equipment's. Copyright © 2018 Elsevier Ltd. All rights reserved.

An EOQ model for weibull distribution deterioration with time-dependent cubic demand and backlogging

NASA Astrophysics Data System (ADS)

Santhi, G.; Karthikeyan, K.

2017-11-01

In this article we introduce an economic order quantity model with weibull deterioration and time dependent cubic demand rate where holding costs as a linear function of time. Shortages are allowed in the inventory system are partially and fully backlogging. The objective of this model is to minimize the total inventory cost by using the optimal order quantity and the cycle length. The proposed model is illustrated by numerical examples and the sensitivity analysis is performed to study the effect of changes in parameters on the optimum solutions.

Optimum testing intervals of building emergency power supply systems in tall buildings in the Hong Kong Special Administrative Region

NASA Astrophysics Data System (ADS)

Kwok, Yu Fat

The main objective of this study is to develop a model for the determination of optimum testing interval (OTI) of non-redundant standby plants. This study focuses on the emergency power generators in tall buildings in Hong Kong. The model for the reliability, which is developed, is applicable to any non-duplicated standby plant. In a tall building, the mobilisation of occupants is constrained by its height and the building internal layout. Occupant's safety, amongst other safety considerations, highly depends on the reliability of the fire detection and protection system, which in turn is dependent on the reliability of the emergency power generation plants. A thorough literature survey shows that the practice used in determining OTI in nuclear plants is generally applicable. Historically, the OTI in these plants is determined by balancing the testing downtime and reliability gained from frequent testing. However, testing downtime does not exist in plants like emergency power generator. Subsequently, sophisticated models have taken repairing downtime into consideration. In this study, the algorithms for the determination of OTI, and hence reliability of standby plants, are reconsidered. A new concept is introduced into the subject. A new model is developed for such purposes which embraces more realistic factors found in practice. System aging and the finite life cycle of the standby plant are considered. Somewhat more pragmatic is that the Optimum Overhauling Interval can also be determined from this new model. System unavailability grow with time, but can be reset by test or overhaul. Contrary to fixed testing intervals, OTI is determined whenever system point unavailability exceeds certain level, which depends on the reliability requirement of the standby system. An optimum testing plan for lowering this level to the 'minimum useful unavailability' level (see section 9.1 for more elaboration) can be determined by the new model presented. Cost effectiveness is accounted for by a new parameter 'tau min', the minimum testing interval (MTI). The MTI optimises the total number of tests and the total number of overhauls, when the costs for each are available. The model sets up criteria for test and overhaul and to 'announce' end of system life. The usefulness of the model is validated by a detailed analysis of the operating parameters from 8,500 maintenance records collected for emergency power generation plants in high rise buildings in Hong Kong. (Abstract shortened by UMI.)

Process optimization via response surface methodology in the treatment of metal working industry wastewater with electrocoagulation.

PubMed

Guvenc, Senem Yazici; Okut, Yusuf; Ozak, Mert; Haktanir, Birsu; Bilgili, Mehmet Sinan

2017-02-01

In this study, process parameters in chemical oxygen demand (COD) and turbidity removal from metal working industry (MWI) wastewater were optimized by electrocoagulation (EC) using aluminum, iron and steel electrodes. The effects of process variables on COD and turbidity were investigated by developing a mathematical model using central composite design method, which is one of the response surface methodologies. Variance analysis was conducted to identify the interaction between process variables and model responses and the optimum conditions for the COD and turbidity removal. Second-order regression models were developed via the Statgraphics Centurion XVI.I software program to predict COD and turbidity removal efficiencies. Under the optimum conditions, removal efficiencies obtained from aluminum electrodes were found to be 76.72% for COD and 99.97% for turbidity, while the removal efficiencies obtained from iron electrodes were found to be 76.55% for COD and 99.9% for turbidity and the removal efficiencies obtained from steel electrodes were found to be 65.75% for COD and 99.25% for turbidity. Operational costs at optimum conditions were found to be 4.83, 1.91 and 2.91 €/m 3 for aluminum, iron and steel electrodes, respectively. Iron electrode was found to be more suitable for MWI wastewater treatment in terms of operational cost and treatment efficiency.

Optimization of the structural and control system for LSS with reduced-order model

NASA Technical Reports Server (NTRS)

Khot, N. S.

1989-01-01

The objective is the simultaneous design of the structural and control system for space structures. The minimum weight of the structure is the objective function, and the constraints are placed on the closed loop distribution of the frequencies and the damping parameters. The controls approach used is linear quadratic regulator with constant feedback. A reduced-order control system is used. The effect of uncontrolled modes is taken into consideration by the model error sensitivity suppression (MESS) technique which modified the weighting parameters for the control forces. For illustration, an ACOSS-FOUR structure is designed for a different number of controlled modes with specified values for the closed loop damping parameters and frequencies. The dynamic response of the optimum designs for an initial disturbance is compared.

Black hole algorithm for determining model parameter in self-potential data

NASA Astrophysics Data System (ADS)

Sungkono; Warnana, Dwa Desa

2018-01-01

Analysis of self-potential (SP) data is increasingly popular in geophysical method due to its relevance in many cases. However, the inversion of SP data is often highly nonlinear. Consequently, local search algorithms commonly based on gradient approaches have often failed to find the global optimum solution in nonlinear problems. Black hole algorithm (BHA) was proposed as a solution to such problems. As the name suggests, the algorithm was constructed based on the black hole phenomena. This paper investigates the application of BHA to solve inversions of field and synthetic self-potential (SP) data. The inversion results show that BHA accurately determines model parameters and model uncertainty. This indicates that BHA is highly potential as an innovative approach for SP data inversion.

Statistical optimization of process parameters for the production of tannase by Aspergillus flavus under submerged fermentation.

PubMed

Mohan, S K; Viruthagiri, T; Arunkumar, C

2014-04-01

Production of tannase by Aspergillus flavus (MTCC 3783) using tamarind seed powder as substrate was studied in submerged fermentation. Plackett-Burman design was applied for the screening of 12 medium nutrients. From the results, the significant nutrients were identified as tannic acid, magnesium sulfate, ferrous sulfate and ammonium sulfate. Further the optimization of process parameters was carried out using response surface methodology (RSM). RSM has been applied for designing of experiments to evaluate the interactive effects through a full 31 factorial design. The optimum conditions were tannic acid concentration, 3.22 %; fermentation period, 96 h; temperature, 35.1 °C; and pH 5.4. Higher value of the regression coefficient (R 2  = 0.9638) indicates excellent evaluation of experimental data by second-order polynomial regression model. The RSM revealed that a maximum tannase production of 139.3 U/ml was obtained at the optimum conditions.

Electrode performance parameters for a radioisotope-powered AMTEC for space power applications

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

Underwood, M.L.; O'Connor, D.; Williams, R.M.

1992-08-01

The alkali metal thermoelastic converter (AMTEC) is a device for the direct conversion of heat to electricity. Recently a design of an AMTEC using a radioisotope heat source was described, but the optimum condenser temperature was hotter than the temperatures used in the laboratory to develop the electrode performance model. Now laboratory experiments have confirmed the dependence of two model parameters over a broader range of condenser and electrode temperatures for two candidate electrode compositions. One parameter, the electrochemical exchange current density at the reaction interface, is independent of the condenser temperature, and depends only upon the collision rate ofmore » sodium at the reaction zone. The second parameter, a morphological parameter, which measures the mass transport resistance through the electrode, is independent of condenser and electrode temperatures for molybdenum electrodes. For rhodium-tungsten electrodes, however, this parameter increases for decreasing electrode temperature, indicating an activated mass transport mechanism such as surface diffusion. 21 refs.« less

Land-surface parameter optimisation using data assimilation techniques: the adJULES system V1.0

NASA Astrophysics Data System (ADS)

Raoult, Nina M.; Jupp, Tim E.; Cox, Peter M.; Luke, Catherine M.

2016-08-01

Land-surface models (LSMs) are crucial components of the Earth system models (ESMs) that are used to make coupled climate-carbon cycle projections for the 21st century. The Joint UK Land Environment Simulator (JULES) is the land-surface model used in the climate and weather forecast models of the UK Met Office. JULES is also extensively used offline as a land-surface impacts tool, forced with climatologies into the future. In this study, JULES is automatically differentiated with respect to JULES parameters using commercial software from FastOpt, resulting in an analytical gradient, or adjoint, of the model. Using this adjoint, the adJULES parameter estimation system has been developed to search for locally optimum parameters by calibrating against observations. This paper describes adJULES in a data assimilation framework and demonstrates its ability to improve the model-data fit using eddy-covariance measurements of gross primary production (GPP) and latent heat (LE) fluxes. adJULES also has the ability to calibrate over multiple sites simultaneously. This feature is used to define new optimised parameter values for the five plant functional types (PFTs) in JULES. The optimised PFT-specific parameters improve the performance of JULES at over 85 % of the sites used in the study, at both the calibration and evaluation stages. The new improved parameters for JULES are presented along with the associated uncertainties for each parameter.

A method for subject-specific modelling and optimisation of the cushioning properties of insole materials used in diabetic footwear.

PubMed

Chatzistergos, Panagiotis E; Naemi, Roozbeh; Chockalingam, Nachiappan

2015-06-01

This study aims to develop a numerical method that can be used to investigate the cushioning properties of different insole materials on a subject-specific basis. Diabetic footwear and orthotic insoles play an important role for the reduction of plantar pressure in people with diabetes (type-2). Despite that, little information exists about their optimum cushioning properties. A new in-vivo measurement based computational procedure was developed which entails the generation of 2D subject-specific finite element models of the heel pad based on ultrasound indentation. These models are used to inverse engineer the material properties of the heel pad and simulate the contact between plantar soft tissue and a flat insole. After its validation this modelling procedure was utilised to investigate the importance of plantar soft tissue stiffness, thickness and loading for the correct selection of insole material. The results indicated that heel pad stiffness and thickness influence plantar pressure but not the optimum insole properties. On the other hand loading appears to significantly influence the optimum insole material properties. These results indicate that parameters that affect the loading of the plantar soft tissues such as body mass or a person's level of physical activity should be carefully considered during insole material selection. Copyright © 2015 IPEM. Published by Elsevier Ltd. All rights reserved.

Investigating the Effect of Compaction Characteristics on the Erodibility of Cohesive Soils Using the JET Method

NASA Astrophysics Data System (ADS)

Asghari Tabrizi, A.; LaRocque, L. A.; Chaudhry, M.; Imran, J.

2013-12-01

Several flood disasters occur every year all over the world, mostly due to levee and dam failure which result in human fatalities as well as devastating economic damages. To model and predict earthen embankment failures for the preparation of emergency action plans and risk assessments, the soil erodibility by flowing water is an essential parameter. The determination of erodibility becomes even more complicated for cohesive soils because of the large number of parameters controlling their erosion behavior (e.g. clay content, plasticity, compaction effort, compaction water content) and the difficulty of estimating these parameters. In this study the effect of the compaction energy and compaction water content on the erodibility of a sandy loam soil was assessed. Soil samples were prepared in a standard diameter compaction mold, 101.6 mm, for three levels of compaction effort and water content (i.e. low, medium, and high) with two replications for each case (18 tests total) and examined using the jet erosion test (JET). Observations from qualitative and statistical analyses of the data are: 1) a wide range of erodibility, from very erodible to very resistant, was produced by changes in the compaction characteristics; 2) for a given compaction energy, the erosion resistance based on the detachment rate coefficient kd tends to become minimum near the optimum compaction water content. On the dry side of optimum compaction water content, kd decreases with steep gradients by increasing the water content, while it increases with a flatter gradient on the wet side; 3) At a given water content, the soil erosion resistance increases with compaction efforts; 4) compaction water content influences soil erosibility more than compaction energy, especially on the dry side of the optimum compaction water content; and 5) for a given compaction effort, the critical shear stress increases with water content up to an optimum water content and then it decreases which is in consistent with the kd trends.

Micro - ring resonator with variety of gap width for acid rain sensing application: preliminary study

NASA Astrophysics Data System (ADS)

Mulyanti, B.; Ramza, H.; Pawinanto, R. E.; Rahman, J. A.; Ab-Rahman, M. S.; Putro, W. S.; Hasanah, L.; Pantjawati, A. B.

2017-05-01

The acid rain is an environmental disaster that it will be intimidates human life. The development micro-ring resonator sensor created from SOI (Silicon on insulator) and it used to detect acid rain index. In this study, the LUMERICAL software was used to simulate SOI material micro-ring resonator. The result shows the optimum values of fixed parameters from ring resonator have dependent variable in gap width. The layers under ring resonator with silicone (Si) and wafer layer of silicone material (Si) were added to seen three conditions of capability model. Model - 3 is an additional of bottom layer that gives the significant effect on the factor of quality. The optimum value is a peak value that given by the FSR calculation. FSR = 0, it means that is not shows the light propagation in the ring resonator and none of the light coming out on the bus - line.

Software Would Largely Automate Design of Kalman Filter

NASA Technical Reports Server (NTRS)

Chuang, Jason C. H.; Negast, William J.

2005-01-01

Embedded Navigation Filter Automatic Designer (ENFAD) is a computer program being developed to automate the most difficult tasks in designing embedded software to implement a Kalman filter in a navigation system. The most difficult tasks are selection of error states of the filter and tuning of filter parameters, which are timeconsuming trial-and-error tasks that require expertise and rarely yield optimum results. An optimum selection of error states and filter parameters depends on navigation-sensor and vehicle characteristics, and on filter processing time. ENFAD would include a simulation module that would incorporate all possible error states with respect to a given set of vehicle and sensor characteristics. The first of two iterative optimization loops would vary the selection of error states until the best filter performance was achieved in Monte Carlo simulations. For a fixed selection of error states, the second loop would vary the filter parameter values until an optimal performance value was obtained. Design constraints would be satisfied in the optimization loops. Users would supply vehicle and sensor test data that would be used to refine digital models in ENFAD. Filter processing time and filter accuracy would be computed by ENFAD.

Optimization of reaction parameters of radiation induced grafting of 1-vinylimidazole onto poly(ethylene-co-tetraflouroethene) using response surface method

NASA Astrophysics Data System (ADS)

Nasef, Mohamed Mahmoud; Aly, Amgad Ahmed; Saidi, Hamdani; Ahmad, Arshad

2011-11-01

Radiation induced grafting of 1-vinylimidazole (1-VIm) onto poly(ethylene-co-tetraflouroethene) (ETFE) was investigated. The grafting parameters such as absorbed dose, monomer concentration, grafting time and temperature were optimized using response surface method (RSM). The Box-Behnken module available in the design expert software was used to investigate the effect of reaction conditions (independent parameters) varied in four levels on the degree of grafting ( G%) (response parameter). The model yielded a polynomial equation that relates the linear, quadratic and interaction effects of the independent parameters to the response parameter. The analysis of variance (ANOVA) was used to evaluate the results of the model and detect the significant values for the independent parameters. The optimum parameters to achieve a maximum G% were found to be monomer concentration of 55 vol%, absorbed dose of 100 kGy, time in the range of 14-20 h and a temperature of 61 °C. Fourier transform infrared (FTIR), thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC) were used to investigate the properties of the obtained films and provide evidence for grafting.

Determination of effect factor for effective parameter on saccharification of lignocellulosic material by concentrated acid

NASA Astrophysics Data System (ADS)

Aghili, Sina; Nodeh, Ali Arasteh

2015-12-01

Tamarisk usage as a new group of lignocelluloses material to produce fermentable sugars in bio ethanol process was studied. The overall aim of this work was to establish the optimum condition for acid hydrolysis of this new material and a mathematical model predicting glucose release as a function of operation variable. Sulfuric acid concentration in the range of 20 to 60%(w/w), process temperature between 60 to 95oC, hydrolysis time from 120 to 240 min and solid content 5,10,15%(w/w) were used as hydrolysis conditions. HPLC was used to analysis of the product. This analysis indicated that glucose was the main fermentable sugar and was increase with time, temperature and solid content and acid concentration was a parabola influence in glucose production. The process was modeled by a quadratic equation. Curve study and model were found that 42% acid concentration, 15 % solid content and 90oC were optimum condition.

Optimum allocation of test resources and comparison of breeding strategies for hybrid wheat.

PubMed

Longin, C Friedrich H; Mi, Xuefei; Melchinger, Albrecht E; Reif, Jochen C; Würschum, Tobias

2014-10-01

The use of a breeding strategy combining the evaluation of line per se with testcross performance maximizes annual selection gain for hybrid wheat breeding. Recent experimental studies confirmed a high commercial potential for hybrid wheat requiring the design of optimum breeding strategies. Our objectives were to (1) determine the optimum allocation of the type and number of testers, the number of test locations and the number of doubled haploid lines for different breeding strategies, (2) identify the best breeding strategy and (3) elaborate key parameters for an efficient hybrid wheat breeding program. We performed model calculations using the selection gain for grain yield as target variable to optimize the number of lines, testers and test locations in four different breeding strategies. A breeding strategy (BS2) combining the evaluation of line per se performance and general combining ability (GCA) had a far larger annual selection gain across all considered scenarios than a breeding strategy (BS1) focusing only on GCA. In the combined strategy, the production of testcross seed conducted in parallel with the first yield trial for line per se performance (BS2rapid) resulted in a further increase of the annual selection gain. For the current situation in hybrid wheat, this relative superiority of the strategy BS2rapid amounted to 67 % in annual selection gain compared to BS1. Varying a large number of parameters, we identified the high costs for hybrid seed production and the low variance of GCA in hybrid wheat breeding as key parameters limiting selection gain in BS2rapid.

Digital Model of Fourier and Fresnel Quantized Holograms

NASA Astrophysics Data System (ADS)

Boriskevich, Anatoly A.; Erokhovets, Valery K.; Tkachenko, Vadim V.

Some models schemes of Fourier and Fresnel quantized protective holograms with visual effects are suggested. The condition to arrive at optimum relationship between the quality of reconstructed images, and the coefficient of data reduction about a hologram, and quantity of iterations in the reconstructing hologram process has been estimated through computer model. Higher protection level is achieved by means of greater number both bi-dimensional secret keys (more than 2128) in form of pseudorandom amplitude and phase encoding matrixes, and one-dimensional encoding key parameters for every image of single-layer or superimposed holograms.

Portable refrigerant charge meter and method for determining the actual refrigerant charge in HVAC systems

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

Gao, Zhiming; Abdelaziz, Omar; LaClair, Tim L.

A refrigerant charge meter and a method for determining the actual refrigerant charge in HVAC systems are described. The meter includes means for determining an optimum refrigerant charge from system subcooling and system component parameters. The meter also includes means for determining the ratio of the actual refrigerant charge to the optimum refrigerant charge. Finally, the meter includes means for determining the actual refrigerant charge from the optimum refrigerant charge and the ratio of the actual refrigerant charge to the optimum refrigerant charge.

Reducing physical size limits for low-frequency horn loudspeaker systems

NASA Astrophysics Data System (ADS)

Honeycutt, Richard Allison

From 1881 until the present day, many excellent scholars have studied acoustic horns. This dissertation begins by discussing over eighty results of such study. Next, the methods of modeling horn behavior are examined with an emphasis on the prediction of throat impedance. Because of the time constraints in a product-design environment, in which the results of this study may be used, boundary-element and cascaded-section types of analysis were not considered due to their time intensiveness. Of the methods studied, an analytical process based upon Olson's adaptation of Webster's analysis is selected as the most accurate of the rapid methods, although other good methods exist. Reasons and extent of inaccuracy are discussed. The concept of interleaved horn loading is introduced: it involves using two horns of different parameters, fed by a single driver, with a view toward interleaving and thus smoothing the impedance peaks of the separate horns to produce a smoother response. The validity of the technique is demonstrated both theoretically and practically. Then the reactance annulling technique is explained and tested experimentally. It is found to work well, but the exact parameter values involved are not found to be critical. Finally, the considerations involved in building a practical working system are discussed, and a preliminary working model reviewed. Future work could be directed toward finding the optimum parameter values for the two "parallel horns" whose impedances are to be interleaved, as well as the system parameters that determine these optimum values. Also, further experimental investigation or ported loading of the back air chamber would be useful.

Simulation Framework to Estimate the Performance of CO2 and O2 Sensing from Space and Airborne Platforms for the ASCENDS Mission Requirements Analysis

NASA Technical Reports Server (NTRS)

Plitau, Denis; Prasad, Narasimha S.

2012-01-01

The Active Sensing of CO2 Emissions over Nights Days and Seasons (ASCENDS) mission recommended by the NRC Decadal Survey has a desired accuracy of 0.3% in carbon dioxide mixing ratio (XCO2) retrievals requiring careful selection and optimization of the instrument parameters. NASA Langley Research Center (LaRC) is investigating 1.57 micron carbon dioxide as well as the 1.26-1.27 micron oxygen bands for our proposed ASCENDS mission requirements investigation. Simulation studies are underway for these bands to select optimum instrument parameters. The simulations are based on a multi-wavelength lidar modeling framework being developed at NASA LaRC to predict the performance of CO2 and O2 sensing from space and airborne platforms. The modeling framework consists of a lidar simulation module and a line-by-line calculation component with interchangeable lineshape routines to test the performance of alternative lineshape models in the simulations. As an option the line-by-line radiative transfer model (LBLRTM) program may also be used for line-by-line calculations. The modeling framework is being used to perform error analysis, establish optimum measurement wavelengths as well as to identify the best lineshape models to be used in CO2 and O2 retrievals. Several additional programs for HITRAN database management and related simulations are planned to be included in the framework. The description of the modeling framework with selected results of the simulation studies for CO2 and O2 sensing is presented in this paper.

Application of response surface methodology for optimization of biosorption of fluoride from groundwater using Shorea robusta flower petal

NASA Astrophysics Data System (ADS)

Biswas, G.; Kumari, M.; Adhikari, K.; Dutta, S.

2017-12-01

Fluoride pollution in groundwater is a major concern in rural areas. The flower petal of Shorea robusta, commonly known as sal tree, is used in the present study both in its native form and Ca-impregnated activated form to eradicate excess fluoride from simulated wastewater. Response surface methodology (RSM) was used for experimental designing and analyzing optimum condition for carbonization vis-à-vis calcium impregnation for preparation of adsorbent. During carbonization, temperature, time and weight ratio of calcium chloride to sal flower petal (SFP) have been considered as input factors and percentage removal of fluoride as response. Optimum condition for carbonization has been obtained as temperature, 500 °C; time, 1 h and weight ratio, 2.5 and the sample prepared has been termed as calcium-impregnated carbonized sal flower petal (CCSFP). Optimum condition as analyzed by one-factor-at-a-time (OFAT) method is initial fluoride concentration, 2.91 mg/L; pH 3 and adsorbent dose, 4 g/L. CCSFP shows maximum removal of 98.5% at this condition. RSM has also been used for finding out optimum condition for defluoridation considering initial concentration, pH and adsorbent dose as input parameters. The optimum condition as analyzed by RSM is: initial concentration, 5 mg/L; pH 3.5 and adsorbent dose, 2 g/L. Kinetic and equilibrium data follow Ho pseudo-second-order kinetic model and Freundlich isotherm model, respectively. Adsorption capacity of CCSFP has been found to be 5.465 mg/g. At optimized condition, CCSFP has been found to remove fluoride (80.4%) efficiently from groundwater collected from Bankura district in West Bengal, a fluoride-contaminated province in India.

Survey of dissolved air flotation system efficiency for reduce of pollution of vegetable oil industry wastewater.

PubMed

Keramati, H; Alidadi, H; Parvaresh, A R; Movahedian, H; Mahvi, A H

2008-10-01

The aim of this research was to sudy the reduction of pollution of vegetable oil manufacturing wastewater with DAF system. At first phase of this examination, the optimum dosage of the coagulants was determined. The coagulants that used in this study were Alum and Ferric Chloride. The second phase was flotation in this series of examinations, oil, COD, total solid, volatile solid, fixed solid and suspended solid measured in raw wastewater and the effluent of the DAF pilot. Optimum value of pH for alum and ferric chloride obtained 7.5 and 5.5, respectively. Optimum dosage for these obtained 30 and 32 mg L(-1) in this research. Mean removal for the parameters ofoil, COD, total solid, volatile solid, fixed solid and suspended solid obtained 75.85, 78.27, 77.32, 82.47, 73.52 and 85.53%, respectively. With pressure rising from 3 to 4 and 5 atm removing rate of COD, total solid, volatile solid, fixed solid parameters reduced, but oil and suspended solid have increase. In addition, following increase of flotation time up to 120 sec all of the measured parameters have increase in removing rate. Optimum A/S for removal of COD, total solid, volatile solid, fixed solid parameters obtained 0.001 and for oil and suspended solid obtained 0.0015.

Multi-objective optimization of MOSFETs channel widths and supply voltage in the proposed dual edge-triggered static D flip-flop with minimum average power and delay by using fuzzy non-dominated sorting genetic algorithm-II.

PubMed

Keivanian, Farshid; Mehrshad, Nasser; Bijari, Abolfazl

2016-01-01

D Flip-Flop as a digital circuit can be used as a timing element in many sophisticated circuits. Therefore the optimum performance with the lowest power consumption and acceptable delay time will be critical issue in electronics circuits. The newly proposed Dual-Edge Triggered Static D Flip-Flop circuit layout is defined as a multi-objective optimization problem. For this, an optimum fuzzy inference system with fuzzy rules is proposed to enhance the performance and convergence of non-dominated sorting Genetic Algorithm-II by adaptive control of the exploration and exploitation parameters. By using proposed Fuzzy NSGA-II algorithm, the more optimum values for MOSFET channel widths and power supply are discovered in search space than ordinary NSGA types. What is more, the design parameters involving NMOS and PMOS channel widths and power supply voltage and the performance parameters including average power consumption and propagation delay time are linked. To do this, the required mathematical backgrounds are presented in this study. The optimum values for the design parameters of MOSFETs channel widths and power supply are discovered. Based on them the power delay product quantity (PDP) is 6.32 PJ at 125 MHz Clock Frequency, L = 0.18 µm, and T = 27 °C.

Improving the Fit of a Land-Surface Model to Data Using its Adjoint

NASA Astrophysics Data System (ADS)

Raoult, Nina; Jupp, Tim; Cox, Peter; Luke, Catherine

2016-04-01

Land-surface models (LSMs) are crucial components of the Earth System Models (ESMs) which are used to make coupled climate-carbon cycle projections for the 21st century. The Joint UK Land Environment Simulator (JULES) is the land-surface model used in the climate and weather forecast models of the UK Met Office. In this study, JULES is automatically differentiated using commercial software from FastOpt, resulting in an analytical gradient, or adjoint, of the model. Using this adjoint, the adJULES parameter estimation system has been developed, to search for locally optimum parameter sets by calibrating against observations. We present an introduction to the adJULES system and demonstrate its ability to improve the model-data fit using eddy covariance measurements of gross primary production (GPP) and latent heat (LE) fluxes. adJULES also has the ability to calibrate over multiple sites simultaneously. This feature is used to define new optimised parameter values for the 5 Plant Functional Types (PFTS) in JULES. The optimised PFT-specific parameters improve the performance of JULES over 90% of the FLUXNET sites used in the study. These reductions in error are shown and compared to reductions found due to site-specific optimisations. Finally, we show that calculation of the 2nd derivative of JULES allows us to produce posterior probability density functions of the parameters and how knowledge of parameter values is constrained by observations.

Optimisation of dispersion parameters of Gaussian plume model for CO₂ dispersion.

PubMed

Liu, Xiong; Godbole, Ajit; Lu, Cheng; Michal, Guillaume; Venton, Philip

2015-11-01

The carbon capture and storage (CCS) and enhanced oil recovery (EOR) projects entail the possibility of accidental release of carbon dioxide (CO2) into the atmosphere. To quantify the spread of CO2 following such release, the 'Gaussian' dispersion model is often used to estimate the resulting CO2 concentration levels in the surroundings. The Gaussian model enables quick estimates of the concentration levels. However, the traditionally recommended values of the 'dispersion parameters' in the Gaussian model may not be directly applicable to CO2 dispersion. This paper presents an optimisation technique to obtain the dispersion parameters in order to achieve a quick estimation of CO2 concentration levels in the atmosphere following CO2 blowouts. The optimised dispersion parameters enable the Gaussian model to produce quick estimates of CO2 concentration levels, precluding the necessity to set up and run much more complicated models. Computational fluid dynamics (CFD) models were employed to produce reference CO2 dispersion profiles in various atmospheric stability classes (ASC), different 'source strengths' and degrees of ground roughness. The performance of the CFD models was validated against the 'Kit Fox' field measurements, involving dispersion over a flat horizontal terrain, both with low and high roughness regions. An optimisation model employing a genetic algorithm (GA) to determine the best dispersion parameters in the Gaussian plume model was set up. Optimum values of the dispersion parameters for different ASCs that can be used in the Gaussian plume model for predicting CO2 dispersion were obtained.

Geological terrain models

NASA Technical Reports Server (NTRS)

Kaupp, V. H.; Macdonald, H. C.; Waite, W. P.

1981-01-01

The initial phase of a program to determine the best interpretation strategy and sensor configuration for a radar remote sensing system for geologic applications is discussed. In this phase, terrain modeling and radar image simulation were used to perform parametric sensitivity studies. A relatively simple computer-generated terrain model is presented, and the data base, backscatter file, and transfer function for digital image simulation are described. Sets of images are presented that simulate the results obtained with an X-band radar from an altitude of 800 km and at three different terrain-illumination angles. The simulations include power maps, slant-range images, ground-range images, and ground-range images with statistical noise incorporated. It is concluded that digital image simulation and computer modeling provide cost-effective methods for evaluating terrain variations and sensor parameter changes, for predicting results, and for defining optimum sensor parameters.

MASTOS: Mammography Simulation Tool for design Optimization Studies.

PubMed

Spyrou, G; Panayiotakis, G; Tzanakos, G

2000-01-01

Mammography is a high quality imaging technique for the detection of breast lesions, which requires dedicated equipment and optimum operation. The design parameters of a mammography unit have to be decided and evaluated before the construction of such a high cost of apparatus. The optimum operational parameters also must be defined well before the real breast examination. MASTOS is a software package, based on Monte Carlo methods, that is designed to be used as a simulation tool in mammography. The input consists of the parameters that have to be specified when using a mammography unit, and also the parameters specifying the shape and composition of the breast phantom. In addition, the input may specify parameters needed in the design of a new mammographic apparatus. The main output of the simulation is a mammographic image and calculations of various factors that describe the image quality. The Monte Carlo simulation code is PC-based and is driven by an outer shell of a graphical user interface. The entire software package is a simulation tool for mammography and can be applied in basic research and/or in training in the fields of medical physics and biomedical engineering as well as in the performance evaluation of new designs of mammography units and in the determination of optimum standards for the operational parameters of a mammography unit.

Reliability, Risk and Cost Trade-Offs for Composite Designs

NASA Technical Reports Server (NTRS)

Shiao, Michael C.; Singhal, Surendra N.; Chamis, Christos C.

1996-01-01

Risk and cost trade-offs have been simulated using a probabilistic method. The probabilistic method accounts for all naturally-occurring uncertainties including those in constituent material properties, fabrication variables, structure geometry and loading conditions. The probability density function of first buckling load for a set of uncertain variables is computed. The probabilistic sensitivity factors of uncertain variables to the first buckling load is calculated. The reliability-based cost for a composite fuselage panel is defined and minimized with respect to requisite design parameters. The optimization is achieved by solving a system of nonlinear algebraic equations whose coefficients are functions of probabilistic sensitivity factors. With optimum design parameters such as the mean and coefficient of variation (representing range of scatter) of uncertain variables, the most efficient and economical manufacturing procedure can be selected. In this paper, optimum values of the requisite design parameters for a predetermined cost due to failure occurrence are computationally determined. The results for the fuselage panel analysis show that the higher the cost due to failure occurrence, the smaller the optimum coefficient of variation of fiber modulus (design parameter) in longitudinal direction.

Modeling of crude oil biodegradation using two phase partitioning bioreactor.

PubMed

Fakhru'l-Razi, A; Peyda, Mazyar; Ab Karim Ghani, Wan Azlina Wan; Abidin, Zurina Zainal; Zakaria, Mohamad Pauzi; Moeini, Hassan

2014-01-01

In this work, crude oil biodegradation has been optimized in a solid-liquid two phase partitioning bioreactor (TPPB) by applying a response surface methodology based d-optimal design. Three key factors including phase ratio, substrate concentration in solid organic phase, and sodium chloride concentration in aqueous phase were taken as independent variables, while the efficiency of the biodegradation of absorbed crude oil on polymer beads was considered to be the dependent variable. Commercial thermoplastic polyurethane (Desmopan®) was used as the solid phase in the TPPB. The designed experiments were carried out batch wise using a mixed acclimatized bacterial consortium. Optimum combinations of key factors with a statistically significant cubic model were used to maximize biodegradation in the TPPB. The validity of the model was successfully verified by the good agreement between the model-predicted and experimental results. When applying the optimum parameters, gas chromatography-mass spectrometry showed a significant reduction in n-alkanes and low molecular weight polycyclic aromatic hydrocarbons. This consequently highlights the practical applicability of TPPB in crude oil biodegradation. © 2014 American Institute of Chemical Engineers.

Extraction kinetic modelling of total polyphenols and total anthocyanins from saffron floral bio-residues: Comparison of extraction methods.

PubMed

Da Porto, Carla; Natolino, Andrea

2018-08-30

Analysis of the extraction kinetic modelling for natural compounds is essential for industrial application. The second order rate model was applied to estimate the extraction kinetics of conventional solid-liquid extraction (CSLE), ultrasound-assisted extraction (UAE) and microwave-assisted extraction (MAE) of total polyphenols (TPC) from saffron floral bio-residues at different solid-to-liquid ratios (R S/L )(1:10, 1:20, 1:30, 1:50 g ml -1 ), ethanol 59% as solvent and 66 °C temperature. The optimum solid-to-liquid ratios for TPC kinetics were 1:20 for CLSE, 1:30 for UAE and 1:50 for MAE. The kinetics of total anthocyanins (TA) and antioxidant activity (AA) were investigated for the optimum R S/L for each method. The results showed a good prediction of the model for extraction kinetics in all experiments (R 2  > 0.99; NRMS 0.65-3.35%). The kinetic parameters were calculated and discussed. UAE, compared with the other methods, had the greater efficiency for TPC, TA and AA. Copyright © 2018 Elsevier Ltd. All rights reserved.

Enhancing Degradation of Low Density Polyethylene Films by Curvularia lunata SG1 Using Particle Swarm Optimization Strategy.

PubMed

Raut, Sangeeta; Raut, Smita; Sharma, Manisha; Srivastav, Chaitanya; Adhikari, Basudam; Sen, Sudip Kumar

2015-09-01

In the present study, artificial neural network (ANN) modelling coupled with particle swarm optimization (PSO) algorithm was used to optimize the process variables for enhanced low density polyethylene (LDPE) degradation by Curvularia lunata SG1. In the non-linear ANN model, temperature, pH, contact time and agitation were used as input variables and polyethylene bio-degradation as the output variable. Further, on application of PSO to the ANN model, the optimum values of the process parameters were as follows: pH = 7.6, temperature = 37.97 °C, agitation rate = 190.48 rpm and incubation time = 261.95 days. A comparison between the model results and experimental data gave a high correlation coefficient ([Formula: see text]). Significant enhancement of LDPE bio-degradation using C. lunata SG1by about 48 % was achieved under optimum conditions. Thus, the novelty of the work lies in the application of combination of ANN-PSO as optimization strategy to enhance the bio-degradation of LDPE.

Improving the Fit of a Land-Surface Model to Data Using its Adjoint

NASA Astrophysics Data System (ADS)

Raoult, N.; Jupp, T. E.; Cox, P. M.; Luke, C.

2015-12-01

Land-surface models (LSMs) are of growing importance in the world of climate prediction. They are crucial components of larger Earth system models that are aimed at understanding the effects of land surface processes on the global carbon cycle. The Joint UK Land Environment Simulator (JULES) is the land-surface model used by the UK Met Office. It has been automatically differentiated using commercial software from FastOpt, resulting in an analytical gradient, or 'adjoint', of the model. Using this adjoint, the adJULES parameter estimation system has been developed, to search for locally optimum parameter sets by calibrating against observations. adJULES presents an opportunity to confront JULES with many different observations, and make improvements to the model parameterisation. In the newest version of adJULES, multiple sites can be used in the calibration, to giving a generic set of parameters that can be generalised over plant functional types. We present an introduction to the adJULES system and its applications to data from a variety of flux tower sites. We show that calculation of the 2nd derivative of JULES allows us to produce posterior probability density functions of the parameters and how knowledge of parameter values is constrained by observations.

Parameter optimization of electrochemical machining process using black hole algorithm

NASA Astrophysics Data System (ADS)

Singh, Dinesh; Shukla, Rajkamal

2017-12-01

Advanced machining processes are significant as higher accuracy in machined component is required in the manufacturing industries. Parameter optimization of machining processes gives optimum control to achieve the desired goals. In this paper, electrochemical machining (ECM) process is considered to evaluate the performance of the considered process using black hole algorithm (BHA). BHA considers the fundamental idea of a black hole theory and it has less operating parameters to tune. The two performance parameters, material removal rate (MRR) and overcut (OC) are considered separately to get optimum machining parameter settings using BHA. The variations of process parameters with respect to the performance parameters are reported for better and effective understanding of the considered process using single objective at a time. The results obtained using BHA are found better while compared with results of other metaheuristic algorithms, such as, genetic algorithm (GA), artificial bee colony (ABC) and bio-geography based optimization (BBO) attempted by previous researchers.

Kinetic characterization, optimum conditions for catalysis and substrate preference of secretory phospholipase A2 from Glycine max in model membrane systems.

PubMed

Mariani, María Elisa; Madoery, Ricardo Román; Fidelio, Gerardo Daniel

2015-01-01

Two secretory phospholipase A2 (sPLA2s) from Glycine max, GmsPLA2-IXA-1 and GmsPLA2-XIB-2, have been purified as recombinant proteins and the activity was evaluated in order to obtain the optimum conditions for catalysis using mixed micelles and lipid monolayers as substrate. Both sPLA2s showed a maximum enzyme activity at pH 7 and a requirement of Ca(2+) in the micromolar range. These parameters were similar to those found for animal sPLA2s but a surprising optimum temperature for catalysis at 60 °C was observed. The effect of negative interfacial charges on the hydrolysis of organized substrates was evaluated through initial rate measurements using short chain phospholipids with different head groups. The enzymes showed subtle differences in the specificity for phospholipids with different head groups (DLPC, DLPG, DLPE, DLPA) in presence or absence of NaCl. Both recombinant enzymes showed lower activity toward anionic phospholipids and a preference for the zwitterionic ones. The values of the apparent kinetic parameters (Vmax and KM) demonstrated that these enzymes have more affinity for phosphatidylcholine compared with phosphatidylglycerol, in contrast with the results observed for pancreatic sPLA2. A hopping mode of catalysis was proposed for the action of these sPLA2 on mixed phospholipid/triton micelles. On the other hand, Langmuir-monolayers assays indicated an optimum lateral surface pressure for activity in between 13 and 16 mN/m for both recombinant enzymes. Copyright © 2014 Elsevier B.V. and Société française de biochimie et biologie Moléculaire (SFBBM). All rights reserved.

Efficacy of multiple exposure with low level He-Ne laser dose on acute wound healing: a pre-clinical study

NASA Astrophysics Data System (ADS)

Prabhu, Vijendra; Rao, Bola Sadashiva S.; Mahato, Krishna Kishore

2014-02-01

Investigations on the use of Low Level Laser Therapy (LLLT) for wound healing especially with the red laser light have demonstrated its pro-healing potential on a variety of pre-clinical and surgical wounds. However, until now, in LLLT the effect of multiple exposure of low dose laser irradiation on acute wound healing on well-designed pre-clinical model is not much explored. The present study aimed to investigate the effect of multiple exposure of low dose Helium Neon laser on healing progression of full thickness excision wounds in Swiss albino mice. Further, the efficacy of the multiple exposure of low dose laser irradiation was compared with the single exposure of optimum dose. Full thickness excision wounds (circular) of 15 mm diameter were created, and subsequently illuminated with the multiple exposures (1, 2, 3, 4 and 5 exposure/ week until healing) of He-Ne (632.8 nm, 4.02 mWcm-2) laser at 0.5 Jcm-2 along with single exposure of optimum laser dose (2 J/cm-2) and un-illuminated controls. Classical biophysical parameters such as contraction kinetics, area under the curve and the mean healing time were documented as the assessment parameters to examine the efficacy of multiple exposures with low level laser dose. Experimental findings substantiated that either single or multiple exposures of 0.5 J/cm2 failed to produce any detectable alterations on wound contraction, area under the curve and mean healing time compared to single exposure of optimum dose (2 Jcm-2) and un-illuminated controls. Single exposure of optimum, laser dose was found to be ideal for acute wound healing.

TiO₂ beads and TiO₂-chitosan beads for urease immobilization.

PubMed

Ispirli Doğaç, Yasemin; Deveci, Ilyas; Teke, Mustafa; Mercimek, Bedrettin

2014-09-01

The aim of the present study is to synthesize TiO2 beads for urease immobilization. Two different strategies were used to immobilize the urease on TiO2 beads. In the first method (A), urease enzyme was immobilized onto TiO2 beads by adsorption and then crosslinking. In the second method (B), TiO2 beads were coated with chitosan-urease mixture. To determine optimum conditions of immobilization, different parameters were investigated. The parameters of optimization were initial enzyme concentration (0.5; 1; 1.5; 2mg/ml), alginate concentration (1; 2; 3%), glutaraldehyde concentration (1; 2; 3% v/v) and chitosan concentration (2; 3; 4 mg/ml). The optimum enzyme concentrations were determined as 1.5mg/ml for A and 1.0mg/ml for B. The other optimum conditions were found 2.0% (w/v) for alginate concentration (both A and B); 3.0mg/ml for chitosan concentration (B) and 2.0% (v/v) for glutaraldehyde concentration (A). The optimum temperature (20-60°C), optimum pH (3.0-10.0), kinetic parameters, thermal stability (4-70°C), pH stability (4.0-9.0), operational stability (0-230 min) and reusability (20 times) were investigated for characterization. The optimum temperatures were 30°C (A), 40°C (B) and 35°C (soluble). The temperature profiles of the immobilized ureases were spread over a large area. The optimum pH values for the soluble urease and immobilized urease prepared by using methods (A) and (B) were found to be 7.5, 7.0, 7.0, respectively. The thermal stabilities of immobilized enzyme sets were studied and they maintained 50% activity at 65°C. However, at this temperature free urease protected only 15% activity. Copyright © 2014 Elsevier B.V. All rights reserved.

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

Raoult, Nina M.; Jupp, Tim E.; Cox, Peter M.

Land-surface models (LSMs) are crucial components of the Earth system models (ESMs) that are used to make coupled climate–carbon cycle projections for the 21st century. The Joint UK Land Environment Simulator (JULES) is the land-surface model used in the climate and weather forecast models of the UK Met Office. JULES is also extensively used offline as a land-surface impacts tool, forced with climatologies into the future. In this study, JULES is automatically differentiated with respect to JULES parameters using commercial software from FastOpt, resulting in an analytical gradient, or adjoint, of the model. Using this adjoint, the adJULES parameter estimationmore » system has been developed to search for locally optimum parameters by calibrating against observations. This paper describes adJULES in a data assimilation framework and demonstrates its ability to improve the model–data fit using eddy-covariance measurements of gross primary production (GPP) and latent heat (LE) fluxes. adJULES also has the ability to calibrate over multiple sites simultaneously. This feature is used to define new optimised parameter values for the five plant functional types (PFTs) in JULES. The optimised PFT-specific parameters improve the performance of JULES at over 85 % of the sites used in the study, at both the calibration and evaluation stages. Furthermore, the new improved parameters for JULES are presented along with the associated uncertainties for each parameter.« less

The Effect of the Air-Delivery Method on Parameters of the Precessing Vortex Core in a Hydrodynamic Vortex Chamber

NASA Astrophysics Data System (ADS)

Alekseenko, S. V.; Shtork, S. I.; Yusupov, R. R.

2018-03-01

The effect of the method of gas-phase injection into a swirled fluid flow on parameters of a precessing vortex core is studied experimentally. Conditions of the appearance of the vortex-core precession effect were modeled in a hydrodynamic sudden expansion vortex chamber. The dependences of the vortexcore precession frequency, flow-pulsation level, and full pressure differential in the vortex chamber on the consumption gas content in the flow have been obtained. The results of measurements permit one to determine optimum conditions for the most effective control of vortex-core precession.

Independent-particle models for light negative atomic ions

NASA Technical Reports Server (NTRS)

Ganas, P. S.; Talman, J. D.; Green, A. E. S.

1980-01-01

For the purposes of astrophysical, aeronomical, and laboratory application, a precise independent-particle model for electrons in negative atomic ions of the second and third period is discussed. The optimum-potential model (OPM) of Talman et al. (1979) is first used to generate numerical potentials for eight of these ions. Results for total energies and electron affinities are found to be very close to Hartree-Fock solutions. However, the OPM and HF electron affinities both depart significantly from experimental affinities. For this reason, two analytic potentials are developed whose inner energy levels are very close to the OPM and HF levels but whose last electron eigenvalues are adjusted precisely with the magnitudes of experimental affinities. These models are: (1) a four-parameter analytic characterization of the OPM potential and (2) a two-parameter potential model of the Green, Sellin, Zachor type. The system O(-) or e-O, which is important in upper atmospheric physics is examined in some detail.

Helicopter vibration suppression using simple pendulum absorbers on the rotor blade

NASA Technical Reports Server (NTRS)

Pierce, G. A.; Hanouva, M. N. H.

1982-01-01

A comprehensive anaytical design procedure for the installation of simple pendulums on the blades of a helicopter rotor to suppress the root reactions is presented. A frequency response anaysis is conducted of typical rotor blades excited by a harmonic variation of spanwise airload distributions as well as a concentrated load at the tip. The results presented included the effect of pendulum tuning on the minimization of the hub reactions. It is found that a properly designed flapping pendulum attenuates the root out-of-plane force and moment whereas the optimum designed lead-lag pendulum attenuates the root in-plane reactions. For optimum pendulum tuning the parameters to be determined are the pendulum uncoupled natural frequency, the pendulum spanwise location and its mass. It is found that the optimum pendulum frequency is in the vicinity of the excitation frequency. For the optimum pendulum a parametric study is conducted. The parameters varied include prepitch, pretwist, precone and pendulum hinge offset.

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

PubMed

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

2014-09-01

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

Throughput and latency programmable optical transceiver by using DSP and FEC control.

PubMed

Tanimura, Takahito; Hoshida, Takeshi; Kato, Tomoyuki; Watanabe, Shigeki; Suzuki, Makoto; Morikawa, Hiroyuki

2017-05-15

We propose and experimentally demonstrate a proof-of-concept of a programmable optical transceiver that enables simultaneous optimization of multiple programmable parameters (modulation format, symbol rate, power allocation, and FEC) for satisfying throughput, signal quality, and latency requirements. The proposed optical transceiver also accommodates multiple sub-channels that can transport different optical signals with different requirements. Multi-degree-of-freedom of the parameters often leads to difficulty in finding the optimum combination among the parameters due to an explosion of the number of combinations. The proposed optical transceiver reduces the number of combinations and finds feasible sets of programmable parameters by using constraints of the parameters combined with a precise analytical model. For precise BER prediction with the specified set of parameters, we model the sub-channel BER as a function of OSNR, modulation formats, symbol rates, and power difference between sub-channels. Next, we formulate simple constraints of the parameters and combine the constraints with the analytical model to seek feasible sets of programmable parameters. Finally, we experimentally demonstrate the end-to-end operation of the proposed optical transceiver with offline manner including low-density parity-check (LDPC) FEC encoding and decoding under a specific use case with latency-sensitive application and 40-km transmission.

A modeling study by response surface methodology and artificial neural network on culture parameters optimization for thermostable lipase production from a newly isolated thermophilic Geobacillus sp. strain ARM.

PubMed

Ebrahimpour, Afshin; Abd Rahman, Raja Noor Zaliha Raja; Ean Ch'ng, Diana Hooi; Basri, Mahiran; Salleh, Abu Bakar

2008-12-23

Thermostable bacterial lipases occupy a place of prominence among biocatalysts owing to their novel, multifold applications and resistance to high temperature and other operational conditions. The capability of lipases to catalyze a variety of novel reactions in both aqueous and nonaqueous media presents a fascinating field for research, creating interest to isolate novel lipase producers and optimize lipase production. The most important stages in a biological process are modeling and optimization to improve a system and increase the efficiency of the process without increasing the cost. Different production media were tested for lipase production by a newly isolated thermophilic Geobacillus sp. strain ARM (DSM 21496 = NCIMB 41583). The maximum production was obtained in the presence of peptone and yeast extract as organic nitrogen sources, olive oil as carbon source and lipase production inducer, sodium and calcium as metal ions, and gum arabic as emulsifier and lipase production inducer. The best models for optimization of culture parameters were achieved by multilayer full feedforward incremental back propagation network and modified response surface model using backward elimination, where the optimum condition was: growth temperature (52.3 degrees C), medium volume (50 ml), inoculum size (1%), agitation rate (static condition), incubation period (24 h) and initial pH (5.8). The experimental lipase activity was 0.47 Uml(-1) at optimum condition (4.7-fold increase), which compared well to the maximum predicted values by ANN (0.47 Uml(-1)) and RSM (0.476 Uml(-1)), whereas R2 and AAD were determined as 0.989 and 0.059% for ANN, and 0.95 and 0.078% for RSM respectively. Lipase production is the result of a synergistic combination of effective parameters interactions. These parameters are in equilibrium and the change of one parameter can be compensated by changes of other parameters to give the same results. Though both RSM and ANN models provided good quality predictions in this study, yet the ANN showed a clear superiority over RSM for both data fitting and estimation capabilities. On the other hand, ANN has the disadvantage of requiring large amounts of training data in comparison with RSM. This problem was solved by using statistical experimental design, to reduce the number of experiments.

Multivariable optimization of an auto-thermal ammonia synthesis reactor using genetic algorithm

NASA Astrophysics Data System (ADS)

Anh-Nga, Nguyen T.; Tuan-Anh, Nguyen; Tien-Dung, Vu; Kim-Trung, Nguyen

2017-09-01

The ammonia synthesis system is an important chemical process used in the manufacture of fertilizers, chemicals, explosives, fibers, plastics, refrigeration. In the literature, many works approaching the modeling, simulation and optimization of an auto-thermal ammonia synthesis reactor can be found. However, they just focus on the optimization of the reactor length while keeping the others parameters constant. In this study, the other parameters are also considered in the optimization problem such as the temperature of feed gas enters the catalyst zone. The optimal problem requires the maximization of a multivariable objective function which subjects to a number of equality constraints involving the solution of coupled differential equations and also inequality constraints. The solution of an optimization problem can be found through, among others, deterministic or stochastic approaches. The stochastic methods, such as evolutionary algorithm (EA), which is based on natural phenomenon, can overcome the drawbacks such as the requirement of the derivatives of the objective function and/or constraints, or being not efficient in non-differentiable or discontinuous problems. Genetic algorithm (GA) which is a class of EA, exceptionally simple, robust at numerical optimization and is more likely to find a true global optimum. In this study, the genetic algorithm is employed to find the optimum profit of the process. The inequality constraints were treated using penalty method. The coupled differential equations system was solved using Runge-Kutta 4th order method. The results showed that the presented numerical method could be applied to model the ammonia synthesis reactor. The optimum economic profit obtained from this study are also compared to the results from the literature. It suggests that the process should be operated at higher temperature of feed gas in catalyst zone and the reactor length is slightly longer.

Characterization and recycling of cadmium from waste nickel-cadmium batteries.

PubMed

Huang, Kui; Li, Jia; Xu, Zhenming

2010-11-01

A severe threat was posed due to improper and inefficient recycling of waste batteries in China. The present work considered the fundamental aspects of the recycling of cadmium from waste nickel-cadmium batteries by means of vacuum metallurgy separation in scale-up. In the first stage of this work, the characterization of waste nickel-cadmium batteries was carried out. Five types of batteries from different brands and models were selected and their components were characterized in relation to their elemental chemical composition and main phase. In the second stage of this work, the parameters affecting the recycling of cadmium by means of vacuum metallurgy separation were investigated and a L(16) (4(4)) orthogonal design was applied to optimize the parameters. With the thermodynamics theory and numerical analysis, it can be seen that the orthogonal design is an effective tool for investigating the parameters affecting the recycling of cadmium. The optimum operating parameters for the recycling of cadmium obtained by orthogonal design and verification test were 1073 K (temperature), 2.5h (heating time), 2 wt.% (the addition of carbon powder), and 30 mm (the loaded height), respectively, with recycling efficiency approaching 99.98%. The XRD and ICP-AES analyzed results show that the condensed product was characterized as metallic cadmium, and cadmium purity was 99.99% under the optimum condition. Copyright © 2010. Published by Elsevier Ltd. All rights reserved.

Taguchi optimization of bismuth-telluride based thermoelectric cooler

NASA Astrophysics Data System (ADS)

Anant Kishore, Ravi; Kumar, Prashant; Sanghadasa, Mohan; Priya, Shashank

2017-07-01

In the last few decades, considerable effort has been made to enhance the figure-of-merit (ZT) of thermoelectric (TE) materials. However, the performance of commercial TE devices still remains low due to the fact that the module figure-of-merit not only depends on the material ZT, but also on the operating conditions and configuration of TE modules. This study takes into account comprehensive set of parameters to conduct the numerical performance analysis of the thermoelectric cooler (TEC) using a Taguchi optimization method. The Taguchi method is a statistical tool that predicts the optimal performance with a far less number of experimental runs than the conventional experimental techniques. Taguchi results are also compared with the optimized parameters obtained by a full factorial optimization method, which reveals that the Taguchi method provides optimum or near-optimum TEC configuration using only 25 experiments against 3125 experiments needed by the conventional optimization method. This study also shows that the environmental factors such as ambient temperature and cooling coefficient do not significantly affect the optimum geometry and optimum operating temperature of TECs. The optimum TEC configuration for simultaneous optimization of cooling capacity and coefficient of performance is also provided.

Design of compact long-period gratings imprinted in optimized photonic crystal fibers

NASA Astrophysics Data System (ADS)

Seraji, F. E.; Chehreghani Anzabi, L.; Farsinezhad, S.

2009-10-01

To imprint a long-period grating (LPG) in a photonic crystal fiber (PCF) with an optimum response, first the parameters of the PCF should be optimized. In this paper, by using a semi-analytical enhanced improved vectorial effective index method, the optimized PCF parameters are determined by dividing the single-mode operation of the PCF into two regions in terms of air-hole spacing Λ ( Λ>3 μm and Λ≤3 μm). For each region appropriate expressions are suggested to evaluate the PCF parameters. By calculating the effective refractive index difference between the optimized core and cladding of the PCF under a phase-matching condition, the optimum grating period in terms of the PCF parameters is obtained.

Cytology 3D structure formation based on optical microscopy images

NASA Astrophysics Data System (ADS)

Pronichev, A. N.; Polyakov, E. V.; Shabalova, I. P.; Djangirova, T. V.; Zaitsev, S. M.

2017-01-01

The article the article is devoted to optimization of the parameters of imaging of biological preparations in optical microscopy using a multispectral camera in visible range of electromagnetic radiation. A model for the image forming of virtual preparations was proposed. The optimum number of layers was determined for the object scan in depth and holistic perception of its switching according to the results of the experiment.

Selection of optimum median-filter-based ambiguity removal algorithm parameters for NSCAT. [NASA scatterometer

NASA Technical Reports Server (NTRS)

Shaffer, Scott; Dunbar, R. Scott; Hsiao, S. Vincent; Long, David G.

1989-01-01

The NASA Scatterometer, NSCAT, is an active spaceborne radar designed to measure the normalized radar backscatter coefficient (sigma0) of the ocean surface. These measurements can, in turn, be used to infer the surface vector wind over the ocean using a geophysical model function. Several ambiguous wind vectors result because of the nature of the model function. A median-filter-based ambiguity removal algorithm will be used by the NSCAT ground data processor to select the best wind vector from the set of ambiguous wind vectors. This process is commonly known as dealiasing or ambiguity removal. The baseline NSCAT ambiguity removal algorithm and the method used to select the set of optimum parameter values are described. An extensive simulation of the NSCAT instrument and ground data processor provides a means of testing the resulting tuned algorithm. This simulation generates the ambiguous wind-field vectors expected from the instrument as it orbits over a set of realistic meoscale wind fields. The ambiguous wind field is then dealiased using the median-based ambiguity removal algorithm. Performance is measured by comparison of the unambiguous wind fields with the true wind fields. Results have shown that the median-filter-based ambiguity removal algorithm satisfies NSCAT mission requirements.

Analysis and optimization of machining parameters of laser cutting for polypropylene composite

NASA Astrophysics Data System (ADS)

Deepa, A.; Padmanabhan, K.; Kuppan, P.

2017-11-01

Present works explains about machining of self-reinforced Polypropylene composite fabricated using hot compaction method. The objective of the experiment is to find optimum machining parameters for Polypropylene (PP). Laser power and Machining speed were the parameters considered in response to tensile test and Flexure test. Taguchi method is used for experimentation. Grey Relational Analysis (GRA) is used for multiple process parameter optimization. ANOVA (Analysis of Variance) is used to find impact for process parameter. Polypropylene has got the great application in various fields like, it is used in the form of foam in model aircraft and other radio-controlled vehicles, thin sheets (∼2-20μm) used as a dielectric, PP is also used in piping system, it is also been used in hernia and pelvic organ repair or protect new herrnis in the same location.

A support vector regression-firefly algorithm-based model for limiting velocity prediction in sewer pipes.

PubMed

Ebtehaj, Isa; Bonakdari, Hossein

2016-01-01

Sediment transport without deposition is an essential consideration in the optimum design of sewer pipes. In this study, a novel method based on a combination of support vector regression (SVR) and the firefly algorithm (FFA) is proposed to predict the minimum velocity required to avoid sediment settling in pipe channels, which is expressed as the densimetric Froude number (Fr). The efficiency of support vector machine (SVM) models depends on the suitable selection of SVM parameters. In this particular study, FFA is used by determining these SVM parameters. The actual effective parameters on Fr calculation are generally identified by employing dimensional analysis. The different dimensionless variables along with the models are introduced. The best performance is attributed to the model that employs the sediment volumetric concentration (C(V)), ratio of relative median diameter of particles to hydraulic radius (d/R), dimensionless particle number (D(gr)) and overall sediment friction factor (λ(s)) parameters to estimate Fr. The performance of the SVR-FFA model is compared with genetic programming, artificial neural network and existing regression-based equations. The results indicate the superior performance of SVR-FFA (mean absolute percentage error = 2.123%; root mean square error =0.116) compared with other methods.

Family of columns isospectral to gravity-loaded columns with tip force: A discrete approach

NASA Astrophysics Data System (ADS)

Ramachandran, Nirmal; Ganguli, Ranjan

2018-06-01

A discrete model is introduced to analyze transverse vibration of straight, clamped-free (CF) columns of variable cross-sectional geometry under the influence of gravity and a constant axial force at the tip. The discrete model is used to determine critical combinations of loading parameters - a gravity parameter and a tip force parameter - that cause onset of dynamic instability in the CF column. A methodology, based on matrix-factorization, is described to transform the discrete model into a family of models corresponding to weightless and unloaded clamped-free (WUCF) columns, each with a transverse vibration spectrum isospectral to the original model. Characteristics of models in this isospectral family are dependent on three transformation parameters. A procedure is discussed to convert the isospectral discrete model description into geometric description of realistic columns i.e. from the discrete model, we construct isospectral WUCF columns with rectangular cross-sections varying in width and depth. As part of numerical studies to demonstrate efficacy of techniques presented, frequency parameters of a uniform column and three types of tapered CF columns under different combinations of loading parameters are obtained from the discrete model. Critical combinations of these parameters for a typical tapered column are derived. These results match with published results. Example CF columns, under arbitrarily-chosen combinations of loading parameters are considered and for each combination, isospectral WUCF columns are constructed. Role of transformation parameters in determining characteristics of isospectral columns is discussed and optimum values are deduced. Natural frequencies of these WUCF columns computed using Finite Element Method (FEM) match well with those of the given gravity-loaded CF column with tip force, hence confirming isospectrality.

Constraint Optimization Problem For The Cutting Of A Cobalt Chrome Refractory Material

NASA Astrophysics Data System (ADS)

Lebaal, Nadhir; Schlegel, Daniel; Folea, Milena

2011-05-01

This paper shows a complete approach to solve a given problem, from the experimentation to the optimization of different cutting parameters. In response to an industrial problem of slotting FSX 414, a Cobalt-based refractory material, we have implemented a design of experiment to determine the most influent parameters on the tool life, the surface roughness and the cutting forces. After theses trials, an optimization approach has been implemented to find the lowest manufacturing cost while respecting the roughness constraints and cutting force limitation constraints. The optimization approach is based on the Response Surface Method (RSM) using the Sequential Quadratic programming algorithm (SQP) for a constrained problem. To avoid a local optimum and to obtain an accurate solution at low cost, an efficient strategy, which allows improving the RSM accuracy in the vicinity of the global optimum, is presented. With these models and these trials, we could apply and compare our optimization methods in order to get the lowest cost for the best quality, i.e. a satisfying surface roughness and limited cutting forces.

Performance characteristics of aerodynamically optimum turbines for wind energy generators

NASA Technical Reports Server (NTRS)

Rohrbach, C.; Worobel, R.

1975-01-01

This paper presents a brief discussion of the aerodynamic methodology for wind energy generator turbines, an approach to the design of aerodynamically optimum wind turbines covering a broad range of design parameters, some insight on the effect on performance of nonoptimum blade shapes which may represent lower fabrication costs, the annual wind turbine energy for a family of optimum wind turbines, and areas of needed research. On the basis of the investigation, it is concluded that optimum wind turbines show high performance over a wide range of design velocity ratios; that structural requirements impose constraints on blade geometry; that variable pitch wind turbines provide excellent power regulation and that annual energy output is insensitive to design rpm and solidity of optimum wind turbines.

SPECT System Optimization Against A Discrete Parameter Space

PubMed Central

Meng, L. J.; Li, N.

2013-01-01

In this paper, we present an analytical approach for optimizing the design of a static SPECT system or optimizing the sampling strategy with a variable/adaptive SPECT imaging hardware against an arbitrarily given set of system parameters. This approach has three key aspects. First, it is designed to operate over a discretized system parameter space. Second, we have introduced an artificial concept of virtual detector as the basic building block of an imaging system. With a SPECT system described as a collection of the virtual detectors, one can convert the task of system optimization into a process of finding the optimum imaging time distribution (ITD) across all virtual detectors. Thirdly, the optimization problem (finding the optimum ITD) could be solved with a block-iterative approach or other non-linear optimization algorithms. In essence, the resultant optimum ITD could provide a quantitative measure of the relative importance (or effectiveness) of the virtual detectors and help to identify the system configuration or sampling strategy that leads to an optimum imaging performance. Although we are using SPECT imaging as a platform to demonstrate the system optimization strategy, this development also provides a useful framework for system optimization problems in other modalities, such as positron emission tomography (PET) and X-ray computed tomography (CT) [1, 2]. PMID:23587609

Land-surface parameter optimisation using data assimilation techniques: the adJULES system V1.0

DOE PAGES

Raoult, Nina M.; Jupp, Tim E.; Cox, Peter M.; ...

2016-08-25

Land-surface models (LSMs) are crucial components of the Earth system models (ESMs) that are used to make coupled climate–carbon cycle projections for the 21st century. The Joint UK Land Environment Simulator (JULES) is the land-surface model used in the climate and weather forecast models of the UK Met Office. JULES is also extensively used offline as a land-surface impacts tool, forced with climatologies into the future. In this study, JULES is automatically differentiated with respect to JULES parameters using commercial software from FastOpt, resulting in an analytical gradient, or adjoint, of the model. Using this adjoint, the adJULES parameter estimationmore » system has been developed to search for locally optimum parameters by calibrating against observations. This paper describes adJULES in a data assimilation framework and demonstrates its ability to improve the model–data fit using eddy-covariance measurements of gross primary production (GPP) and latent heat (LE) fluxes. adJULES also has the ability to calibrate over multiple sites simultaneously. This feature is used to define new optimised parameter values for the five plant functional types (PFTs) in JULES. The optimised PFT-specific parameters improve the performance of JULES at over 85 % of the sites used in the study, at both the calibration and evaluation stages. Furthermore, the new improved parameters for JULES are presented along with the associated uncertainties for each parameter.« less

Studies on mathematical modeling of the leaching process in order to efficiently recover lead from the sulfate/oxide lead paste.

PubMed

Buzatu, Traian; Ghica, Gabriel Valeriu; Petrescu, Ionuţ Mircea; Iacob, Gheorghe; Buzatu, Mihai; Niculescu, Florentina

2017-02-01

Increasing global lead consumption has been mainly supported by the acid battery manufacturing industry. As the lead demand will continue to grow, to provide the necessary lead will require an efficient approach to recycling lead acid batteries. In this paper was performed a mathematical modeling of the process parameters for lead recovery from spent lead-acid batteries. The results of the mathematical modeling compare well with the experimental data. The experimental method applied consists in the solubilisation of the sulfate/oxide paste with sodium hydroxide solutions followed by electrolytic processing for lead recovery. The parameters taken into considerations were NaOH molarity (4M, 6M and 8M), solid/liquid ratio - S/L (1/10, 1/30 and 1/50) and temperature (40°C, 60°C and 80°C). The optimal conditions resulted by mathematical modeling of the electrolytic process of lead deposition from alkaline solutions have been established by using a second-order orthogonal program, in order to obtain a maximum efficiency of current without exceeding an imposed energy specific consumption. The optimum value for the leaching recovery efficiency, obtained through mathematical modeling, was 89.647%, with an error of δ y =3.623 which leads to a maximum recovery efficiency of 86.024%. The optimum values for each variable that ensure the lead extraction efficiency equal to 89.647% are the following: 3M - NaOH, 1/35 - S/L, 70°C - temperature. Copyright © 2016 Elsevier Ltd. All rights reserved.

Integrating stimulation practices with geo-mechanical properties in liquid-rich plays of Eagle Ford Shale

NASA Astrophysics Data System (ADS)

Yusuf, Ahmed

Many of the techniques for hydraulically fracturing design were attempted in the liquid-rich Eagle Ford developments. This study shows why different results were observed due to the variation of geomechanical stresses of the rock across a play and related reservoir properties. An optimum treatment for a liquids-rich objective is much different than that for a gas shale due primarily to the multiphase flow and higher viscosities encountered. This study presents a new treatment workflow for liquids-rich window of Eagle Ford Shale. Review and integration of data from multiple sets across the play are used as input to a 3D hydraulic fracture simulator to model key fracture parameters which control production enhancement. These results are then used within a production analysis and forecast, well optimization, and economic model to compare treatment designs with the best placement of proppant to deliver both high initial production and long term ultimate recoveries. A key focus for this workflow is to maximize proppant transport to achieve a continuous - optimum conductive - fracture half length. Often, due to the complexity of unconventional deposition, it is difficult to maintain complete connectivity of a proppant pack back to the wellbore. As a result, much of the potential of the fracture network is lost. Understanding the interaction of a hydraulic fracture and the rock fabric helps with designing this behavior to achieve the best results. These results are used to determine optimum well spacing to effectively develop within a selected reservoir acreage. Currently, numerous wells exist with over two years of production history in much of the Eagle Ford shale formation. Results from this study are used to compare values from field production to demonstrate the importance of employing a diligent workflow in integrating reservoir and operational parameters to the fracture design. A proper understanding and application of hydraulic fracturing modeling is achieved using the methodology presented in this study.

Optimization and Prediction of Ultimate Tensile Strength in Metal Active Gas Welding.

PubMed

Ampaiboon, Anusit; Lasunon, On-Uma; Bubphachot, Bopit

2015-01-01

We investigated the effect of welding parameters on ultimate tensile strength of structural steel, ST37-2, welded by Metal Active Gas welding. A fractional factorial design was used for determining the significance of six parameters: wire feed rate, welding voltage, welding speed, travel angle, tip-to-work distance, and shielded gas flow rate. A regression model to predict ultimate tensile strength was developed. Finally, we verified optimization of the process parameters experimentally. We achieved an optimum tensile strength (558 MPa) and wire feed rate, 19 m/min, had the greatest effect, followed by tip-to-work distance, 7 mm, welding speed, 200 mm/min, welding voltage, 30 V, and travel angle, 60°. Shield gas flow rate, 10 L/min, was slightly better but had little effect in the 10-20 L/min range. Tests showed that our regression model was able to predict the ultimate tensile strength within 4%.

A generalized analysis of solar space heating

NASA Astrophysics Data System (ADS)

Clark, J. A.

A life-cycle model is developed for solar space heating within the United States. The model consists of an analytical relationship among five dimensionless parameters that include all pertinent technical, climatological, solar, operating and economic factors that influence the performance of a solar space heating system. An important optimum condition presented is the break-even metered cost of conventional fuel at which the cost of the solar system is equal to that of a conventional heating system. The effect of Federal (1980) and State (1979) income tax credits on these costs is determined. A parameter that includes both solar availability and solar system utilization is derived and plotted on a map of the U.S. This parameter shows the most favorable present locations for solar space heating application to be in the Central and Mountain States. The data employed are related to the rehabilitated solar data recently made available by the National Climatic Center.

Optimum design of bridges with superelastic-friction base isolators against near-field earthquakes

NASA Astrophysics Data System (ADS)

Ozbulut, Osman E.; Hurlebaus, Stefan

2010-04-01

The seismic response of a multi-span continuous bridge isolated with novel superelastic-friction base isolator (S-FBI) is investigated under near-field earthquakes. The isolation system consists of a flat steel-Teflon sliding bearing and a superelastic NiTi shape memory alloy (SMA) device. Sliding bearings limit the maximum seismic forces transmitted to the superstructure to a certain value that is a function of friction coefficient of sliding interface. Superelastic SMA device provides restoring capability to the isolation system together with additional damping characteristics. The key design parameters of an S-FBI system are the natural period of the isolated, yielding displacement of SMA device, and the friction coefficient of the sliding bearings. The goal of this study is to obtain optimal values for each design parameter by performing sensitivity analyses of the isolated bridge. First, a three-span continuous bridge is modeled as a two-degrees-of-freedom with S-FBI system. A neuro-fuzzy model is used to capture rate-dependent nonlinear behavior of SMA device. A time-dependent method which employs wavelets to adjust accelerograms to match a target response spectrum with minimum changes on the other characteristics of ground motions is used to generate ground motions used in the simulations. Then, a set of nonlinear time history analyses of the isolated bridge is performed. The variation of the peak response quantities of the isolated bridge is shown as a function of design parameters. Also, the influence of temperature variations on the effectiveness of S-FBI system is evaluated. The results show that the optimum design of the isolated bridge with S-FBI system can be achieved by a judicious specification of design parameters.

Global optimization and reflectivity data fitting for x-ray multilayer mirrors by means of genetic algorithms

NASA Astrophysics Data System (ADS)

Sanchez del Rio, Manuel; Pareschi, Giovanni

2001-01-01

The x-ray reflectivity of a multilayer is a non-linear function of many parameters (materials, layer thicknesses, densities, roughness). Non-linear fitting of experimental data with simulations requires to use initial values sufficiently close to the optimum value. This is a difficult task when the space topology of the variables is highly structured, as in our case. The application of global optimization methods to fit multilayer reflectivity data is presented. Genetic algorithms are stochastic methods based on the model of natural evolution: the improvement of a population along successive generations. A complete set of initial parameters constitutes an individual. The population is a collection of individuals. Each generation is built from the parent generation by applying some operators (e.g. selection, crossover, mutation) on the members of the parent generation. The pressure of selection drives the population to include 'good' individuals. For large number of generations, the best individuals will approximate the optimum parameters. Some results on fitting experimental hard x-ray reflectivity data for Ni/C multilayers recorded at the ESRF BM5 are presented. This method could be also applied to the help in the design of multilayers optimized for a target application, like for an astronomical grazing-incidence hard X-ray telescopes.

An improved computer model for prediction of axial gas turbine performance losses

NASA Technical Reports Server (NTRS)

Jenkins, R. M.

1984-01-01

The calculation model performs a rapid preliminary pitchline optimization of axial gas turbine annular flowpath geometry, as well as an initial estimate of blade profile shapes, given only a minimum of thermodynamic cycle requirements. No geometric parameters need be specified. The following preliminary design data are determined: (1) the optimum flowpath geometry, within mechanical stress limits; (2) initial estimates of cascade blade shapes; and (3) predictions of expected turbine performance. The model uses an inverse calculation technique whereby blade profiles are generated by designing channels to yield a specified velocity distribution on the two walls. Velocity distributions are then used to calculate the cascade loss parameters. Calculated blade shapes are used primarily to determine whether the assumed velocity loadings are physically realistic. Model verification is accomplished by comparison of predicted turbine geometry and performance with an array of seven NASA single-stage axial gas turbine configurations.

Modeling and numerical analysis of a magneto-inertial fusion concept with the target created through FRC merging

NASA Astrophysics Data System (ADS)

Li, Chenguang; Yang, Xianjun

2016-10-01

The Magnetized Plasma Fusion Reactor concept is proposed as a magneto-inertial fusion approach based on the target plasma created through the collision merging of two oppositely translating field reversed configuration plasmas, which is then compressed by the imploding liner driven by the pulsed-power driver. The target creation process is described by a two-dimensional magnetohydrodynamics model, resulting in the typical target parameters. The implosion process and the fusion reaction are modeled by a simple zero-dimensional model, taking into account the alpha particle heating and the bremsstrahlung radiation loss. The compression on the target can be 2D cylindrical or 2.4D with the additive axial contraction taken into account. The dynamics of the liner compression and fusion burning are simulated and the optimum fusion gain and the associated target parameters are predicted. The scientific breakeven could be achieved at the optimized conditions.

Analytical and regression models of glass rod drawing process

NASA Astrophysics Data System (ADS)

Alekseeva, L. B.

2018-03-01

The process of drawing glass rods (light guides) is being studied. The parameters of the process affecting the quality of the light guide have been determined. To solve the problem, mathematical models based on general equations of continuum mechanics are used. The conditions for the stable flow of the drawing process have been found, which are determined by the stability of the motion of the glass mass in the formation zone to small uncontrolled perturbations. The sensitivity of the formation zone to perturbations of the drawing speed and viscosity is estimated. Experimental models of the drawing process, based on the regression analysis methods, have been obtained. These models make it possible to customize a specific production process to obtain light guides of the required quality. They allow one to find the optimum combination of process parameters in the chosen area and to determine the required accuracy of maintaining them at a specified level.

Performance Analysis and Optimization of Concentrating Solar Thermoelectric Generator

NASA Astrophysics Data System (ADS)

Lamba, Ravita; Manikandan, S.; Kaushik, S. C.

2018-06-01

A thermodynamic model for a concentrating solar thermoelectric generator considering the Thomson effect combined with Fourier heat conduction, Peltier, and Joule heating has been developed and optimized in MATLAB environment. The temperatures at the hot and cold junctions of the thermoelectric generator were evaluated by solving the energy balance equations at both junctions. The effects of the solar concentration ratio, input electrical current, number of thermocouples, and electrical load resistance ratio on the power output and energy and exergy efficiencies of the system were studied. Optimization studies were carried out for the STEG system, and the optimum number of thermocouples, concentration ratio, and resistance ratio determined. The results showed that the optimum values of these parameters are different for conditions of maximum power output and maximum energy and exergy efficiency. The optimum values of the concentration ratio and load resistance ratio for maximum energy efficiency of 5.85% and maximum exergy efficiency of 6.29% were found to be 180 and 1.3, respectively, with corresponding power output of 4.213 W. Furthermore, at higher concentration ratio (C = 600), the optimum number of thermocouples was found to be 101 for maximum power output of 13.75 W, maximum energy efficiency of 5.73%, and maximum exergy efficiency of 6.16%. Moreover, the optimum number of thermocouple was the same for conditions of maximum power output and energy and exergy efficiency. The results of this study may provide insight for design of actual concentrated solar thermoelectric generator systems.

On the residual stress modeling of shot-peened AISI 4340 steel: finite element and response surface methods

NASA Astrophysics Data System (ADS)

Asgari, Ali; Dehestani, Pouya; Poruraminaie, Iman

2018-02-01

Shot peening is a well-known process in applying the residual stress on the surface of industrial parts. The induced residual stress improves fatigue life. In this study, the effects of shot peening parameters such as shot diameter, shot speed, friction coefficient, and the number of impacts on the applied residual stress will be evaluated. To assess these parameters effect, firstly the shot peening process has been simulated by finite element method. Then, effects of the process parameters on the residual stress have been evaluated by response surface method as a statistical approach. Finally, a strong model is presented to predict the maximum residual stress induced by shot peening process in AISI 4340 steel. Also, the optimum parameters for the maximum residual stress are achieved. The results indicate that effect of shot diameter on the induced residual stress is increased by increasing the shot speed. Also, enhancing the friction coefficient magnitude always cannot lead to increase in the residual stress.

Vibroacoustic test plan evaluation: Parameter variation study

NASA Technical Reports Server (NTRS)

Stahle, C. V.; Gongloef, H. R.

1976-01-01

Statistical decision models are shown to provide a viable method of evaluating the cost effectiveness of alternate vibroacoustic test plans and the associated test levels. The methodology developed provides a major step toward the development of a realistic tool to quantitatively tailor test programs to specific payloads. Testing is considered at the no test, component, subassembly, or system level of assembly. Component redundancy and partial loss of flight data are considered. Most and probabilistic costs are considered, and incipient failures resulting from ground tests are treated. Optimums defining both component and assembly test levels are indicated for the modified test plans considered. modeling simplifications must be considered in interpreting the results relative to a particular payload. New parameters introduced were a no test option, flight by flight failure probabilities, and a cost to design components for higher vibration requirements. Parameters varied were the shuttle payload bay internal acoustic environment, the STS launch cost, the component retest/repair cost, and the amount of redundancy in the housekeeping section of the payload reliability model.

Automated design optimization of supersonic airplane wing structures under dynamic constraints

NASA Technical Reports Server (NTRS)

Fox, R. L.; Miura, H.; Rao, S. S.

1972-01-01

The problems of the preliminary and first level detail design of supersonic aircraft wings are stated as mathematical programs and solved using automated optimum design techniques. The problem is approached in two phases: the first is a simplified equivalent plate model in which the envelope, planform and structural parameters are varied to produce a design, the second is a finite element model with fixed configuration in which the material distribution is varied. Constraints include flutter, aeroelastically computed stresses and deflections, natural frequency and a variety of geometric limitations.

Computer-aided study of key factors determining high mechanical properties of nanostructured surface layers in metal-ceramic composites

NASA Astrophysics Data System (ADS)

Konovalenko, Igor S.; Shilko, Evgeny V.; Ovcharenko, Vladimir E.; Psakhie, Sergey G.

2017-12-01

The paper presents the movable cellular automaton method. It is based on numerical models of surface layers of the metal-ceramic composite NiCr-TiC modified under electron beam irradiation in inert gas plasmas. The models take into account different geometric, concentration and mechanical parameters of ceramic and metallic components. The authors study the contributions of key structural factors in mechanical properties of surface layers and determine the ranges of their variations by providing the optimum balance of strength, strain hardening and fracture toughness.

An improved state-parameter analysis of ecosystem models using data assimilation

USGS Publications Warehouse

Chen, M.; Liu, S.; Tieszen, L.L.; Hollinger, D.Y.

2008-01-01

Much of the effort spent in developing data assimilation methods for carbon dynamics analysis has focused on estimating optimal values for either model parameters or state variables. The main weakness of estimating parameter values alone (i.e., without considering state variables) is that all errors from input, output, and model structure are attributed to model parameter uncertainties. On the other hand, the accuracy of estimating state variables may be lowered if the temporal evolution of parameter values is not incorporated. This research develops a smoothed ensemble Kalman filter (SEnKF) by combining ensemble Kalman filter with kernel smoothing technique. SEnKF has following characteristics: (1) to estimate simultaneously the model states and parameters through concatenating unknown parameters and state variables into a joint state vector; (2) to mitigate dramatic, sudden changes of parameter values in parameter sampling and parameter evolution process, and control narrowing of parameter variance which results in filter divergence through adjusting smoothing factor in kernel smoothing algorithm; (3) to assimilate recursively data into the model and thus detect possible time variation of parameters; and (4) to address properly various sources of uncertainties stemming from input, output and parameter uncertainties. The SEnKF is tested by assimilating observed fluxes of carbon dioxide and environmental driving factor data from an AmeriFlux forest station located near Howland, Maine, USA, into a partition eddy flux model. Our analysis demonstrates that model parameters, such as light use efficiency, respiration coefficients, minimum and optimum temperatures for photosynthetic activity, and others, are highly constrained by eddy flux data at daily-to-seasonal time scales. The SEnKF stabilizes parameter values quickly regardless of the initial values of the parameters. Potential ecosystem light use efficiency demonstrates a strong seasonality. Results show that the simultaneous parameter estimation procedure significantly improves model predictions. Results also show that the SEnKF can dramatically reduce the variance in state variables stemming from the uncertainty of parameters and driving variables. The SEnKF is a robust and effective algorithm in evaluating and developing ecosystem models and in improving the understanding and quantification of carbon cycle parameters and processes. ?? 2008 Elsevier B.V.

Preparation of Curcumin Loaded Egg Albumin Nanoparticles Using Acetone and Optimization of Desolvation Process.

PubMed

Aniesrani Delfiya, D S; Thangavel, K; Amirtham, D

2016-04-01

In this study, acetone was used as a desolvating agent to prepare the curcumin-loaded egg albumin nanoparticles. Response surface methodology was employed to analyze the influence of process parameters namely concentration (5-15%w/v) and pH (5-7) of egg albumin solution on solubility, curcumin loading and entrapment efficiency, nanoparticles yield and particle size. Optimum processing conditions obtained from response surface analysis were found to be the egg albumin solution concentration of 8.85%w/v and pH of 5. At this optimum condition, the solubility of 33.57%, curcumin loading of 4.125%, curcumin entrapment efficiency of 55.23%, yield of 72.85% and particles size of 232.6 nm were obtained and these values were related to the values which are predicted using polynomial model equations. Thus, the model equations generated for each response was validated and it can be used to predict the response values at any concentration and pH.

Adsorption of Ni(II) onto Chemically Modified Spent Grated Coconut (Cocos Nucifera)

NASA Astrophysics Data System (ADS)

Hamzah, F. I.; Khalid, K.; Hanafiah, M. A. K. M.

2017-06-01

A new adsorbent of plant waste origin from coconut processing food factory was explored for removing Ni(II) from aqueous solutions. Several parameters such as pH, dosage, concentration and contact time were studied to obtain optimum conditions for treatment of Ni(II) contaminated wastewater. Spent grated coconut (Cocos nucifera) treated with sulfuric acid (SSGC) showed good adsorption capacity for Ni(II) ion. The amount adsorbed was affected by solution pH with the highest value achieved at pH 5. Other optimum conditions found were; dosage of 0.02 g, and 60 min of equilibrium time. Ni(II) adsorption obeyed the pseudo-second order kinetic model which suggested that chemisorption mechanism occurred in the adsorption process. The equilibrium data presented a better fitting to the Langmuir isotherm model, an indication that monolayer adsorption occurred onto a homogeneous surface. The maximum adsorption capacity, qmax was 97.09 mg g-1, thus SSGC can be classified as good and comparable with other plant waste adsorbents.

Effect of magnetic dipolar interactions on nanoparticle heating efficiency: Implications for cancer hyperthermia

PubMed Central

Branquinho, Luis C.; Carrião, Marcus S.; Costa, Anderson S.; Zufelato, Nicholas; Sousa, Marcelo H.; Miotto, Ronei; Ivkov, Robert; Bakuzis, Andris F.

2013-01-01

Nanostructured magnetic systems have many applications, including potential use in cancer therapy deriving from their ability to heat in alternating magnetic fields. In this work we explore the influence of particle chain formation on the normalized heating properties, or specific loss power (SLP) of both low- (spherical) and high- (parallelepiped) anisotropy ferrite-based magnetic fluids. Analysis of ferromagnetic resonance (FMR) data shows that high particle concentrations correlate with increasing chain length producing decreasing SLP. Monte Carlo simulations corroborate the FMR results. We propose a theoretical model describing dipole interactions valid for the linear response regime to explain the observed trends. This model predicts optimum particle sizes for hyperthermia to about 30% smaller than those previously predicted, depending on the nanoparticle parameters and chain size. Also, optimum chain lengths depended on nanoparticle surface-to-surface distance. Our results might have important implications to cancer treatment and could motivate new strategies to optimize magnetic hyperthermia. PMID:24096272

Process optimization and analysis of product inhibition kinetics of crude glycerol fermentation for 1,3-Dihydroxyacetone production.

PubMed

Dikshit, Pritam Kumar; Padhi, Susant Kumar; Moholkar, Vijayanand S

2017-11-01

In present study, statistical optimization of biodiesel-derived crude glycerol fermentation to DHA by immobilized G. oxydans cells over polyurethane foam is reported. Effect of DHA (product) inhibition on crude glycerol fermentation was analyzed using conventional biokinetic models and new model that accounts for both substrate and product inhibition. Optimum values of fermentation parameters were: pH=4.7, temperature=31°C, initial substrate concentration=20g/L. At optimum conditions, DHA yield was 89% (17.83g/L). Effect of product inhibition on fermentation was trivial for DHA concentrations ≤30g/L. At higher concentrations (≥50g/L), kinetics and yield of fermentation showed marked reduction with sharp drop in V max and K S values. Inhibition effect was more pronounced for immobilized cells due to restricted transport of fermentation mixture across polyurethane foam. Retention of fermentation mixture in immobilized matrix resulted in higher localized DHA concentration that possibly enhanced inhibition effect. Copyright © 2017 Elsevier Ltd. All rights reserved.

Regularization of soft-X-ray imaging in the DIII-D tokamak

DOE PAGES

Wingen, A.; Shafer, M. W.; Unterberg, E. A.; ...

2015-03-02

We developed an image inversion scheme for the soft X-ray imaging system (SXRIS) diagnostic at the DIII-D tokamak in order to obtain the local soft X-ray emission at a poloidal cross-section from the spatially line-integrated image taken by the SXRIS camera. The scheme uses the Tikhonov regularization method since the inversion problem is generally ill-posed. The regularization technique uses the generalized singular value decomposition to determine a solution that depends on a free regularization parameter. The latter has to be chosen carefully, and the so called {\\it L-curve} method to find the optimum regularization parameter is outlined. A representative testmore » image is used to study the properties of the inversion scheme with respect to inversion accuracy, amount/strength of regularization, image noise and image resolution. Moreover, the optimum inversion parameters are identified, while the L-curve method successfully computes the optimum regularization parameter. Noise is found to be the most limiting issue, but sufficient regularization is still possible at noise to signal ratios up to 10%-15%. Finally, the inversion scheme is applied to measured SXRIS data and the line-integrated SXRIS image is successfully inverted.« less

Process optimization of rolling for zincked sheet technology using response surface methodology and genetic algorithm

NASA Astrophysics Data System (ADS)

Ji, Liang-Bo; Chen, Fang

2017-07-01

Numerical simulation and intelligent optimization technology were adopted for rolling and extrusion of zincked sheet. By response surface methodology (RSM), genetic algorithm (GA) and data processing technology, an efficient optimization of process parameters for rolling of zincked sheet was investigated. The influence trend of roller gap, rolling speed and friction factor effects on reduction rate and plate shortening rate were analyzed firstly. Then a predictive response surface model for comprehensive quality index of part was created using RSM. Simulated and predicted values were compared. Through genetic algorithm method, the optimal process parameters for the forming of rolling were solved. They were verified and the optimum process parameters of rolling were obtained. It is feasible and effective.

Concerning the electrosynthesis of hydrogen peroxide and peroxodisulfates. Section 2: Optimization of electrolysis cells using an electrolyzer for peroxodisulfuric acid as an example

NASA Technical Reports Server (NTRS)

Schleiff, M.; Thiele, W.; Matschiner, H.

1986-01-01

The model is presented of an electrolyzer for peroxodisulfuric acid, and it is analyzed mathematically. Its application for engineering and economic optimization is investigated in detail. The mathematical analysis leads to conclusions concerning the change in position of the optimum with respect to the various target functions due to changes of the individual design-caused and economic parameters.

Research on the critical parameters initialization of optical PMD compensator in high bit-rate systems

NASA Astrophysics Data System (ADS)

Zhao, Wenyu; Zhang, Haiyi; Ji, Yuefeng; Xu, Daxiong

2004-05-01

Based on the proposed polarization mode dispersion (PMD) compensation simulation model and statistical analysis method (Monte-Carlo), the critical parameters initialization of two typical optical domain PMD compensators, which include optical PMD method with fixed compensation differential group delay (DGD) and that with variable compensation DGD, are detailedly investigated by numerical method. In the simulation, the line PMD values are chosen as 3ps, 4ps and 5ps and run samples are set to 1000 in order to achieve statistical evaluation for PMD compensated systems, respectively. The simulation results show that for the PMD value pre-known systems, the value of the fixed DGD compensator should be set to 1.5~1.6 times of line PMD value in order to reach the optimum performance, but for the second kind of PMD compensator, the DGD range of lower limit should be 1.5~1.6 times of line PMD provided that of upper limit is set to 3 times of line PMD, if no effective ways are chosen to resolve the problem of local minimum in optimum process. Another conclusion can be drawn from the simulation is that, although the second PMD compensator holds higher PMD compensation performance, it will spend more feedback loops to look up the optimum DGD value in the real PMD compensation realization, and this will bring more requirements on adjustable DGD device, not only wider adjustable range, but rapid adjusting speed for real time PMD equalization.

A Preliminary Assessment of Soviet Development of Optimum Signal Discrimination Techniques: Optimum Space-Time Processing

DTIC Science & Technology

1982-10-01

thermal noise and radioastronomy is probably the application Shirman had in mind for that work. Kuriksha considers a wide class of two-dimensional...this point has been discussed In terms of EM wave propagation, signal detection, and parameter estimation in such fields as radar and radioastronomy

Scaling laws and technology development strategies for biorefineries and bioenergy plants.

PubMed

Jack, Michael W

2009-12-01

The economies of scale of larger biorefineries or bioenergy plants compete with the diseconomies of scale of transporting geographically distributed biomass to a central location. This results in an optimum plant size that depends on the scaling parameters of the two contributions. This is a fundamental aspect of biorefineries and bioenergy plants and has important consequences for technology development as "bigger is better" is not necessarily true. In this paper we explore the consequences of these scaling effects via a simplified model of biomass transportation and plant costs. Analysis of this model suggests that there is a need for much more sophisticated technology development strategies to exploit the consequences of these scaling effects. We suggest three potential strategies in terms of the scaling parameters of the system.

Dark matter effective field theory scattering in direct detection experiments

DOE PAGES

Schneck, K.

2015-05-01

We examine the consequences of the effective field theory (EFT) of dark matter–nucleon scattering for current and proposed direct detection experiments. Exclusion limits on EFT coupling constants computed using the optimum interval method are presented for SuperCDMS Soudan, CDMS II, and LUX, and the necessity of combining results from multiple experiments in order to determine dark matter parameters is discussed. We demonstrate that spectral differences between the standard dark matter model and a general EFT interaction can produce a bias when calculating exclusion limits and when developing signal models for likelihood and machine learning techniques. We also discuss the implicationsmore » of the EFT for the next-generation (G2) direct detection experiments and point out regions of complementarity in the EFT parameter space.« less

Dark matter effective field theory scattering in direct detection experiments

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

Schneck, K.; Cabrera, B.; Cerdeño, D. G.

2015-05-18

We examine the consequences of the effective field theory (EFT) of dark matter-nucleon scattering for current and proposed direct detection experiments. Exclusion limits on EFT coupling constants computed using the optimum interval method are presented for SuperCDMS Soudan, CDMS II, and LUX, and the necessity of combining results from multiple experiments in order to determine dark matter parameters is discussed. Here. we demonstrate that spectral differences between the standard dark matter model and a general EFT interaction can produce a bias when calculating exclusion limits and when developing signal models for likelihood and machine learning techniques. In conclusion, we discussmore » the implications of the EFT for the next-generation (G2) direct detection experiments and point out regions of complementarity in the EFT parameter space.« less

Dark matter effective field theory scattering in direct detection experiments

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

Schneck, K.; Cabrera, B.; Cerdeño, D. G.

2015-05-18

We examine the consequences of the effective field theory (EFT) of dark matter–nucleon scattering for current and proposed direct detection experiments. Exclusion limits on EFT coupling constants computed using the optimum interval method are presented for SuperCDMS Soudan, CDMS II, and LUX, and the necessity of combining results from multiple experiments in order to determine dark matter parameters is discussed. We demonstrate that spectral differences between the standard dark matter model and a general EFT interaction can produce a bias when calculating exclusion limits and when developing signal models for likelihood and machine learning techniques. We also discuss the implicationsmore » of the EFT for the next-generation (G2) direct detection experiments and point out regions of complementarity in the EFT parameter space.« less

Influence of Wire Electrical Discharge Machining (WEDM) process parameters on surface roughness

NASA Astrophysics Data System (ADS)

Yeakub Ali, Mohammad; Banu, Asfana; Abu Bakar, Mazilah

2018-01-01

In obtaining the best quality of engineering components, the quality of machined parts surface plays an important role. It improves the fatigue strength, wear resistance, and corrosion of workpiece. This paper investigates the effects of wire electrical discharge machining (WEDM) process parameters on surface roughness of stainless steel using distilled water as dielectric fluid and brass wire as tool electrode. The parameters selected are voltage open, wire speed, wire tension, voltage gap, and off time. Empirical model was developed for the estimation of surface roughness. The analysis revealed that off time has a major influence on surface roughness. The optimum machining parameters for minimum surface roughness were found to be at a 10 V open voltage, 2.84 μs off time, 12 m/min wire speed, 6.3 N wire tension, and 54.91 V voltage gap.

Optimization and design of pigments for heat-insulating coatings

NASA Astrophysics Data System (ADS)

Wang, Guang-Hai; Zhang, Yue

2010-12-01

This paper reports that heat insulating property of infrared reflective coatings is obtained through the use of pigments which diffuse near-infrared thermal radiation. Suitable structure and size distribution of pigments would attain maximum diffuse infrared radiation and reduce the pigment volume concentration required. The optimum structure and size range of pigments for reflective infrared coatings are studied by using Kubelka—Munk theory, Mie model and independent scattering approximation. Taking titania particle as the pigment embedded in an inorganic coating, the computational results show that core-shell particles present excellent scattering ability, more so than solid and hollow spherical particles. The optimum radius range of core-shell particles is around 0.3 ~ 1.6 μm. Furthermore, the influence of shell thickness on optical parameters of the coating is also obvious and the optimal thickness of shell is 100-300 nm.

Improved helicopter aeromechanical stability analysis using segmented constrained layer damping and hybrid optimization

NASA Astrophysics Data System (ADS)

Liu, Qiang; Chattopadhyay, Aditi

2000-06-01

Aeromechanical stability plays a critical role in helicopter design and lead-lag damping is crucial to this design. In this paper, the use of segmented constrained damping layer (SCL) treatment and composite tailoring is investigated for improved rotor aeromechanical stability using formal optimization technique. The principal load-carrying member in the rotor blade is represented by a composite box beam, of arbitrary thickness, with surface bonded SCLs. A comprehensive theory is used to model the smart box beam. A ground resonance analysis model and an air resonance analysis model are implemented in the rotor blade built around the composite box beam with SCLs. The Pitt-Peters dynamic inflow model is used in air resonance analysis under hover condition. A hybrid optimization technique is used to investigate the optimum design of the composite box beam with surface bonded SCLs for improved damping characteristics. Parameters such as stacking sequence of the composite laminates and placement of SCLs are used as design variables. Detailed numerical studies are presented for aeromechanical stability analysis. It is shown that optimum blade design yields significant increase in rotor lead-lag regressive modal damping compared to the initial system.

Influence parameters of impact grinding mills

NASA Technical Reports Server (NTRS)

Hoeffl, K.; Husemann, K.; Goldacker, H.

1984-01-01

Significant parameters for impact grinding mills were investigated. Final particle size was used to evaluate grinding results. Adjustment of the parameters toward increased charge load results in improved efficiency; however, it was not possible to define a single, unified set to optimum grinding conditions.

An observational philosophy for GEOS-C satellite altimetry

NASA Technical Reports Server (NTRS)

Weiffenbach, G. C.

1972-01-01

The parameters necessary for obtaining a 10 cm accuracy for GEOS-C satellite altimetry are outlined. These data include oceanographic parameters, instrument calibration, pulse propagation, sea surface effects, and optimum design.

Computer programs for generation and evaluation of near-optimum vertical flight profiles

NASA Technical Reports Server (NTRS)

Sorensen, J. A.; Waters, M. H.; Patmore, L. C.

1983-01-01

Two extensive computer programs were developed. The first, called OPTIM, generates a reference near-optimum vertical profile, and it contains control options so that the effects of various flight constraints on cost performance can be examined. The second, called TRAGEN, is used to simulate an aircraft flying along an optimum or any other vertical reference profile. TRAGEN is used to verify OPTIM's output, examine the effects of uncertainty in the values of parameters (such as prevailing wind) which govern the optimum profile, or compare the cost performance of profiles generated by different techniques. A general description of these programs, the efforts to add special features to them, and sample results of their usage are presented.

A parameter for the assessment of the segmentation of TEM tomography reconstructed volumes based on mutual information.

PubMed

Okariz, Ana; Guraya, Teresa; Iturrondobeitia, Maider; Ibarretxe, Julen

2017-12-01

A method is proposed and verified for selecting the optimum segmentation of a TEM reconstruction among the results of several segmentation algorithms. The selection criterion is the accuracy of the segmentation. To do this selection, a parameter for the comparison of the accuracies of the different segmentations has been defined. It consists of the mutual information value between the acquired TEM images of the sample and the Radon projections of the segmented volumes. In this work, it has been proved that this new mutual information parameter and the Jaccard coefficient between the segmented volume and the ideal one are correlated. In addition, the results of the new parameter are compared to the results obtained from another validated method to select the optimum segmentation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Thermomechanical conditions and stresses on the friction stir welding tool

NASA Astrophysics Data System (ADS)

Atthipalli, Gowtam

Friction stir welding has been commercially used as a joining process for aluminum and other soft materials. However, the use of this process in joining of hard alloys is still developing primarily because of the lack of cost effective, long lasting tools. Here I have developed numerical models to understand the thermo mechanical conditions experienced by the FSW tool and to improve its reusability. A heat transfer and visco-plastic flow model is used to calculate the torque, and traverse force on the tool during FSW. The computed values of torque and traverse force are validated using the experimental results for FSW of AA7075, AA2524, AA6061 and Ti-6Al-4V alloys. The computed torque components are used to determine the optimum tool shoulder diameter based on the maximum use of torque and maximum grip of the tool on the plasticized workpiece material. The estimation of the optimum tool shoulder diameter for FSW of AA6061 and AA7075 was verified with experimental results. The computed values of traverse force and torque are used to calculate the maximum shear stress on the tool pin to determine the load bearing ability of the tool pin. The load bearing ability calculations are used to explain the failure of H13 steel tool during welding of AA7075 and commercially pure tungsten during welding of L80 steel. Artificial neural network (ANN) models are developed to predict the important FSW output parameters as function of selected input parameters. These ANN consider tool shoulder radius, pin radius, pin length, welding velocity, tool rotational speed and axial pressure as input parameters. The total torque, sliding torque, sticking torque, peak temperature, traverse force, maximum shear stress and bending stress are considered as the output for ANN models. These output parameters are selected since they define the thermomechanical conditions around the tool during FSW. The developed ANN models are used to understand the effect of various input parameters on the total torque and traverse force during FSW of AA7075 and 1018 mild steel. The ANN models are also used to determine tool safety factor for wide range of input parameters. A numerical model is developed to calculate the strain and strain rates along the streamlines during FSW. The strain and strain rate values are calculated for FSW of AA2524. Three simplified models are also developed for quick estimation of output parameters such as material velocity field, torque and peak temperature. The material velocity fields are computed by adopting an analytical method of calculating velocities for flow of non-compressible fluid between two discs where one is rotating and other is stationary. The peak temperature is estimated based on a non-dimensional correlation with dimensionless heat input. The dimensionless heat input is computed using known welding parameters and material properties. The torque is computed using an analytical function based on shear strength of the workpiece material. These simplified models are shown to be able to predict these output parameters successfully.

Pulsed Inductive Plasma Acceleration: Performance Optimization Criteria

NASA Technical Reports Server (NTRS)

Polzin, Kurt A.

2014-01-01

Optimization criteria for pulsed inductive plasma acceleration are developed using an acceleration model consisting of a set of coupled circuit equations describing the time-varying current in the thruster and a one-dimensional momentum equation. The model is nondimensionalized, resulting in the identification of several scaling parameters that are varied to optimize the performance of the thruster. The analysis reveals the benefits of underdamped current waveforms and leads to a performance optimization criterion that requires the matching of the natural period of the discharge and the acceleration timescale imposed by the inertia of the working gas. In addition, the performance increases when a greater fraction of the propellant is initially located nearer to the inductive acceleration coil. While the dimensionless model uses a constant temperature formulation in calculating performance, the scaling parameters that yield the optimum performance are shown to be relatively invariant if a self-consistent description of energy in the plasma is instead used.

Study of a two-bed silica gel-water adsorption chiller: performance analysis

NASA Astrophysics Data System (ADS)

Sah, Ramesh P.; Choudhury, Biplab; Das, Ranadip K.

2018-01-01

In this study, a lumped parameter simulation model has been developed for analysis of the thermal performance of a single-stage two-bed adsorption chiller. Since silica gel has low regeneration temperature and water has high latent heat of vaporisation, silica gel-water pair has been chosen as the working pair of the adsorption chiller. Low-grade waste heat or solar heat at around 70-80°C can be used to run this adsorption chiller. In this model, the effects of operating parameters on the performance of the chiller have been studied. The simulated results show that the cooling capacity of the chiller has an optimum value of 5.95 kW for a cycle time of 1600 s with the hot, cooling, and chilled water inlet temperatures at 85°C, 25°C, and 14°C, respectively. The present model can be utilised to investigate and optimise adsorption chillers.

A Grobner Basis Solution for Lightning Ground Flash Fraction Retrieval

NASA Technical Reports Server (NTRS)

Solakiewicz, Richard; Attele, Rohan; Koshak, William

2011-01-01

A Bayesian inversion method was previously introduced for retrieving the fraction of ground flashes in a set of flashes observed from a (low earth orbiting or geostationary) satellite lightning imager. The method employed a constrained mixed exponential distribution model to describe the lightning optical measurements. To obtain the optimum model parameters, a scalar function was minimized by a numerical method. In order to improve this optimization, we introduce a Grobner basis solution to obtain analytic representations of the model parameters that serve as a refined initialization scheme to the numerical optimization. Using the Grobner basis, we show that there are exactly 2 solutions involving the first 3 moments of the (exponentially distributed) data. When the mean of the ground flash optical characteristic (e.g., such as the Maximum Group Area, MGA) is larger than that for cloud flashes, then a unique solution can be obtained.

Optimization of injection molding process parameters for a plastic cell phone housing component

NASA Astrophysics Data System (ADS)

Rajalingam, Sokkalingam; Vasant, Pandian; Khe, Cheng Seong; Merican, Zulkifli; Oo, Zeya

2016-11-01

To produce thin-walled plastic items, injection molding process is one of the most widely used application tools. However, to set optimal process parameters is difficult as it may cause to produce faulty items on injected mold like shrinkage. This study aims at to determine such an optimum injection molding process parameters which can reduce the fault of shrinkage on a plastic cell phone cover items. Currently used setting of machines process produced shrinkage and mis-specified length and with dimensions below the limit. Thus, for identification of optimum process parameters, maintaining closer targeted length and width setting magnitudes with minimal variations, more experiments are needed. The mold temperature, injection pressure and screw rotation speed are used as process parameters in this research. For optimal molding process parameters the Response Surface Methods (RSM) is applied. The major contributing factors influencing the responses were identified from analysis of variance (ANOVA) technique. Through verification runs it was found that the shrinkage defect can be minimized with the optimal setting found by RSM.

Hardware-Based Non-Optimum Factors for Launch Vehicle Structural Design

NASA Technical Reports Server (NTRS)

Wu, K. Chauncey; Cerro, Jeffrey A.

2010-01-01

During aerospace vehicle conceptual and preliminary design, empirical non-optimum factors are typically applied to predicted structural component weights to account for undefined manufacturing and design details. Non-optimum factors are developed here for 32 aluminum-lithium 2195 orthogrid panels comprising the liquid hydrogen tank barrel of the Space Shuttle External Tank using measured panel weights and manufacturing drawings. Minimum values for skin thickness, axial and circumferential blade stiffener thickness and spacing, and overall panel thickness are used to estimate individual panel weights. Panel non-optimum factors computed using a coarse weights model range from 1.21 to 1.77, and a refined weights model (including weld lands and skin and stiffener transition details) yields non-optimum factors of between 1.02 and 1.54. Acreage panels have an average 1.24 non-optimum factor using the coarse model, and 1.03 with the refined version. The observed consistency of these acreage non-optimum factors suggests that relatively simple models can be used to accurately predict large structural component weights for future launch vehicles.

Optimizing the current ramp-up phase for the hybrid ITER scenario

NASA Astrophysics Data System (ADS)

Hogeweij, G. M. D.; Artaud, J.-F.; Casper, T. A.; Citrin, J.; Imbeaux, F.; Köchl, F.; Litaudon, X.; Voitsekhovitch, I.; the ITM-TF ITER Scenario Modelling Group

2013-01-01

The current ramp-up phase for the ITER hybrid scenario is analysed with the CRONOS integrated modelling suite. The simulations presented in this paper show that the heating systems available at ITER allow, within the operational limits, the attainment of a hybrid q profile at the end of the current ramp-up. A reference ramp-up scenario is reached by a combination of NBI, ECCD (UPL) and LHCD. A heating scheme with only NBI and ECCD can also reach the target q profile; however, LHCD can play a crucial role in reducing the flux consumption during the ramp-up phase. The optimum heating scheme depends on the chosen transport model, and on assumptions of parameters like ne peaking, edge Te,i and Zeff. The sensitivity of the current diffusion on parameters that are not easily controlled, shows that development of real-time control is important to reach the target q profile. A first step in that direction has been indicated in this paper. Minimizing resistive flux consumption and optimizing the q profile turn out to be conflicting requirements. A trade-off between these two requirements has to be made. In this paper it is shown that fast current ramp with L-mode current overshoot is at the one extreme, i.e. the optimum q profile at the cost of increased resistive flux consumption, whereas early H-mode transition is at the other extreme.

Optimization of Designs for Nanotube-based Scanning Probes

NASA Technical Reports Server (NTRS)

Harik, V. M.; Gates, T. S.; Bushnell, Dennis M. (Technical Monitor)

2002-01-01

Optimization of designs for nanotube-based scanning probes, which may be used for high-resolution characterization of nanostructured materials, is examined. Continuum models to analyze the nanotube deformations are proposed to help guide selection of the optimum probe. The limitations on the use of these models that must be accounted for before applying to any design problem are presented. These limitations stem from the underlying assumptions and the expected range of nanotube loading, end conditions, and geometry. Once the limitations are accounted for, the key model parameters along with the appropriate classification of nanotube structures may serve as a basis for the design optimization of nanotube-based probe tips.

An algorithm on simultaneous optimization of performance and mass parameters of open-cycle liquid-propellant engine of launch vehicles

NASA Astrophysics Data System (ADS)

Eskandari, M. A.; Mazraeshahi, H. K.; Ramesh, D.; Montazer, E.; Salami, E.; Romli, F. I.

2017-12-01

In this paper, a new method for the determination of optimum parameters of open-cycle liquid-propellant engine of launch vehicles is introduced. The parameters affecting the objective function, which is the ratio of specific impulse to gross mass of the launch vehicle, are chosen to achieve maximum specific impulse as well as minimum mass for the structure of engine, tanks, etc. The proposed algorithm uses constant integration of thrust with respect to time for launch vehicle with specific diameter and length to calculate the optimum working condition. The results by this novel algorithm are compared to those obtained from using Genetic Algorithm method and they are also validated against the results of existing launch vehicle.

Intelligent Modeling Combining Adaptive Neuro Fuzzy Inference System and Genetic Algorithm for Optimizing Welding Process Parameters

NASA Astrophysics Data System (ADS)

Gowtham, K. N.; Vasudevan, M.; Maduraimuthu, V.; Jayakumar, T.

2011-04-01

Modified 9Cr-1Mo ferritic steel is used as a structural material for steam generator components of power plants. Generally, tungsten inert gas (TIG) welding is preferred for welding of these steels in which the depth of penetration achievable during autogenous welding is limited. Therefore, activated flux TIG (A-TIG) welding, a novel welding technique, has been developed in-house to increase the depth of penetration. In modified 9Cr-1Mo steel joints produced by the A-TIG welding process, weld bead width, depth of penetration, and heat-affected zone (HAZ) width play an important role in determining the mechanical properties as well as the performance of the weld joints during service. To obtain the desired weld bead geometry and HAZ width, it becomes important to set the welding process parameters. In this work, adaptative neuro fuzzy inference system is used to develop independent models correlating the welding process parameters like current, voltage, and torch speed with weld bead shape parameters like depth of penetration, bead width, and HAZ width. Then a genetic algorithm is employed to determine the optimum A-TIG welding process parameters to obtain the desired weld bead shape parameters and HAZ width.

Cost and performance model for redox flow batteries

NASA Astrophysics Data System (ADS)

Viswanathan, Vilayanur; Crawford, Alasdair; Stephenson, David; Kim, Soowhan; Wang, Wei; Li, Bin; Coffey, Greg; Thomsen, Ed; Graff, Gordon; Balducci, Patrick; Kintner-Meyer, Michael; Sprenkle, Vincent

2014-02-01

A cost model is developed for all vanadium and iron-vanadium redox flow batteries. Electrochemical performance modeling is done to estimate stack performance at various power densities as a function of state of charge and operating conditions. This is supplemented with a shunt current model and a pumping loss model to estimate actual system efficiency. The operating parameters such as power density, flow rates and design parameters such as electrode aspect ratio and flow frame channel dimensions are adjusted to maximize efficiency and minimize capital costs. Detailed cost estimates are obtained from various vendors to calculate cost estimates for present, near-term and optimistic scenarios. The most cost-effective chemistries with optimum operating conditions for power or energy intensive applications are determined, providing a roadmap for battery management systems development for redox flow batteries. The main drivers for cost reduction for various chemistries are identified as a function of the energy to power ratio of the storage system. Levelized cost analysis further guide suitability of various chemistries for different applications.

Optimization of space manufacturing systems

NASA Technical Reports Server (NTRS)

Akin, D. L.

1979-01-01

Four separate analyses are detailed: transportation to low earth orbit, orbit-to-orbit optimization, parametric analysis of SPS logistics based on earth and lunar source locations, and an overall program option optimization implemented with linear programming. It is found that smaller vehicles are favored for earth launch, with the current Space Shuttle being right at optimum payload size. Fully reusable launch vehicles represent a savings of 50% over the Space Shuttle; increased reliability with less maintenance could further double the savings. An optimization of orbit-to-orbit propulsion systems using lunar oxygen for propellants shows that ion propulsion is preferable by a 3:1 cost margin over a mass driver reaction engine at optimum values; however, ion engines cannot yet operate in the lower exhaust velocity range where the optimum lies, and total program costs between the two systems are ambiguous. Heavier payloads favor the use of a MDRE. A parametric model of a space manufacturing facility is proposed, and used to analyze recurring costs, total costs, and net present value discounted cash flows. Parameters studied include productivity, effects of discounting, materials source tradeoffs, economic viability of closed-cycle habitats, and effects of varying degrees of nonterrestrial SPS materials needed from earth. Finally, candidate optimal scenarios are chosen, and implemented in a linear program with external constraints in order to arrive at an optimum blend of SPS production strategies in order to maximize returns.

Selecting statistical model and optimum maintenance policy: a case study of hydraulic pump.

PubMed

Ruhi, S; Karim, M R

2016-01-01

Proper maintenance policy can play a vital role for effective investigation of product reliability. Every engineered object such as product, plant or infrastructure needs preventive and corrective maintenance. In this paper we look at a real case study. It deals with the maintenance of hydraulic pumps used in excavators by a mining company. We obtain the data that the owner had collected and carry out an analysis and building models for pump failures. The data consist of both failure and censored lifetimes of the hydraulic pump. Different competitive mixture models are applied to analyze a set of maintenance data of a hydraulic pump. Various characteristics of the mixture models, such as the cumulative distribution function, reliability function, mean time to failure, etc. are estimated to assess the reliability of the pump. Akaike Information Criterion, adjusted Anderson-Darling test statistic, Kolmogrov-Smirnov test statistic and root mean square error are considered to select the suitable models among a set of competitive models. The maximum likelihood estimation method via the EM algorithm is applied mainly for estimating the parameters of the models and reliability related quantities. In this study, it is found that a threefold mixture model (Weibull-Normal-Exponential) fits well for the hydraulic pump failures data set. This paper also illustrates how a suitable statistical model can be applied to estimate the optimum maintenance period at a minimum cost of a hydraulic pump.

Bayesian calibration of terrestrial ecosystem models: A study of advanced Markov chain Monte Carlo methods

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

Lu, Dan; Ricciuto, Daniel; Walker, Anthony

Calibration of terrestrial ecosystem models is important but challenging. Bayesian inference implemented by Markov chain Monte Carlo (MCMC) sampling provides a comprehensive framework to estimate model parameters and associated uncertainties using their posterior distributions. The effectiveness and efficiency of the method strongly depend on the MCMC algorithm used. In this study, a Differential Evolution Adaptive Metropolis (DREAM) algorithm was used to estimate posterior distributions of 21 parameters for the data assimilation linked ecosystem carbon (DALEC) model using 14 years of daily net ecosystem exchange data collected at the Harvard Forest Environmental Measurement Site eddy-flux tower. The DREAM is a multi-chainmore » method and uses differential evolution technique for chain movement, allowing it to be efficiently applied to high-dimensional problems, and can reliably estimate heavy-tailed and multimodal distributions that are difficult for single-chain schemes using a Gaussian proposal distribution. The results were evaluated against the popular Adaptive Metropolis (AM) scheme. DREAM indicated that two parameters controlling autumn phenology have multiple modes in their posterior distributions while AM only identified one mode. The calibration of DREAM resulted in a better model fit and predictive performance compared to the AM. DREAM provides means for a good exploration of the posterior distributions of model parameters. Lastly, it reduces the risk of false convergence to a local optimum and potentially improves the predictive performance of the calibrated model.« less

Bayesian calibration of terrestrial ecosystem models: A study of advanced Markov chain Monte Carlo methods

DOE PAGES

Lu, Dan; Ricciuto, Daniel; Walker, Anthony; ...

2017-02-22

Calibration of terrestrial ecosystem models is important but challenging. Bayesian inference implemented by Markov chain Monte Carlo (MCMC) sampling provides a comprehensive framework to estimate model parameters and associated uncertainties using their posterior distributions. The effectiveness and efficiency of the method strongly depend on the MCMC algorithm used. In this study, a Differential Evolution Adaptive Metropolis (DREAM) algorithm was used to estimate posterior distributions of 21 parameters for the data assimilation linked ecosystem carbon (DALEC) model using 14 years of daily net ecosystem exchange data collected at the Harvard Forest Environmental Measurement Site eddy-flux tower. The DREAM is a multi-chainmore » method and uses differential evolution technique for chain movement, allowing it to be efficiently applied to high-dimensional problems, and can reliably estimate heavy-tailed and multimodal distributions that are difficult for single-chain schemes using a Gaussian proposal distribution. The results were evaluated against the popular Adaptive Metropolis (AM) scheme. DREAM indicated that two parameters controlling autumn phenology have multiple modes in their posterior distributions while AM only identified one mode. The calibration of DREAM resulted in a better model fit and predictive performance compared to the AM. DREAM provides means for a good exploration of the posterior distributions of model parameters. Lastly, it reduces the risk of false convergence to a local optimum and potentially improves the predictive performance of the calibrated model.« less

[Functional load distribution in cases of different types of removable dentures fastening].

PubMed

Zhulev, E N; Klokov, A A

2007-01-01

Questions of studying of a biomechanics of system prosthesis - prosthetic region using of mathematical modelling are surveyed. The original way of definition of physical parameters of a mucosa of an edentulous alveolar process is offered. Modelling of a leaky adhering of prosthesis basis to a mucosa as free saddle situation shows, that a abutment teeth and an edentulous alveolar part of a jaw are in an optimum situation at sliding resilient fastening of a removable partial denture. Rigid bond in the given situation on the contrary promotes development of an overload of abutment teeth and their inclination distally.

Optimisation of Ferrochrome Addition Using Multi-Objective Evolutionary and Genetic Algorithms for Stainless Steel Making via AOD Converter

NASA Astrophysics Data System (ADS)

Behera, Kishore Kumar; Pal, Snehanshu

2018-03-01

This paper describes a new approach towards optimum utilisation of ferrochrome added during stainless steel making in AOD converter. The objective of optimisation is to enhance end blow chromium content of steel and reduce the ferrochrome addition during refining. By developing a thermodynamic based mathematical model, a study has been conducted to compute the optimum trade-off between ferrochrome addition and end blow chromium content of stainless steel using a predator prey genetic algorithm through training of 100 dataset considering different input and output variables such as oxygen, argon, nitrogen blowing rate, duration of blowing, initial bath temperature, chromium and carbon content, weight of ferrochrome added during refining. Optimisation is performed within constrained imposed on the input parameters whose values fall within certain ranges. The analysis of pareto fronts is observed to generate a set of feasible optimal solution between the two conflicting objectives that provides an effective guideline for better ferrochrome utilisation. It is found out that after a certain critical range, further addition of ferrochrome does not affect the chromium percentage of steel. Single variable response analysis is performed to study the variation and interaction of all individual input parameters on output variables.

Bar piezoelectric ceramic transformers.

PubMed

Erhart, Jiří; Pulpan, Půlpán; Rusin, Luboš

2013-07-01

Bar-shaped piezoelectric ceramic transformers (PTs) working in the longitudinal vibration mode (k31 mode) were studied. Two types of the transformer were designed--one with the electrode divided into two segments of different length, and one with the electrodes divided into three symmetrical segments. Parameters of studied transformers such as efficiency, transformation ratio, and input and output impedances were measured. An analytical model was developed for PT parameter calculation for both two- and three-segment PTs. Neither type of bar PT exhibited very high efficiency (maximum 72% for three-segment PT design) at a relatively high transformation ratio (it is 4 for two-segment PT and 2 for three-segment PT at the fundamental resonance mode). The optimum resistive loads were 20 and 10 kΩ for two- and three-segment PT designs for the fundamental resonance, respectively, and about one order of magnitude smaller for the higher overtone (i.e., 2 kΩ and 500 Ω, respectively). The no-load transformation ratio was less than 27 (maximum for two-segment electrode PT design). The optimum input electrode aspect ratios (0.48 for three-segment PT and 0.63 for two-segment PT) were calculated numerically under no-load conditions.

Design Considerations For Imaging Charge-Coupled Device (ICCD) Star Sensors

NASA Astrophysics Data System (ADS)

McAloon, K. J.

1981-04-01

A development program is currently underway to produce a precision star sensor using imaging charge coupled device (ICCD) technology. The effort is the critical component development phase for the Air Force Multi-Mission Attitude Determination and Autonomous Navigation System (MADAN). A number of unique considerations have evolved in designing an arcsecond accuracy sensor around an ICCD detector. Three tiers of performance criteria are involved: at the spacecraft attitude determination system level, at the star sensor level, and at the detector level. Optimum attitude determination system performance involves a tradeoff between Kalman filter iteration time and sensor ICCD integration time. The ICCD star sensor lends itself to the use of a new approach in the functional interface between the attitude determination system and the sensor. At the sensor level image data processing tradeoffs are important for optimum sensor performance. These tradeoffs involve the sensor optic configuration, the optical point spread function (PSF) size and shape, the PSF position locator, and the microprocessor locator algorithm. Performance modelling of the sensor mandates the use of computer simulation programs. Five key performance parameters at the ICCD detector level are defined. ICCD error characteristics have also been isolated to five key parameters.

Nisin production of Lactococcus lactis N8 with hemin-stimulated cell respiration in fed-batch fermentation system.

PubMed

Kördikanlıoğlu, Burcu; Şimşek, Ömer; Saris, Per E J

2015-01-01

In this study, nisin production of Lactococcus lactis N8 was optimized by independent variables of glucose, hemin and oxygen concentrations in fed-batch fermentation in which respiration of cells was stimulated with hemin. Response surface model was able to explain the changes of the nisin production of L. lactis N8 in fed-batch fermentation system with high fidelity (R(2) 98%) and insignificant lack of fit. Accordingly, the equation developed indicated the optimum parameters for glucose, hemin, and dissolved oxygen were 8 g L(-1) h(-1) , 3 μg mL(-1) and 40%, respectively. While 1711 IU mL(-1) nisin was produced by L. lactis N8 in control fed-batch fermentation, 5410 IU mL(-1) nisin production was achieved within the relevant optimum parameters where the respiration of cell was stimulated with hemin. Accordingly, nisin production was enhanced 3.1 fold in fed-batch fermentation using hemin. In conclusion the nisin production of L. lactis N8 was enhanced extensively as a result of increasing the biomass by stimulating the cell respiration with adding the hemin in the fed-batch fermentation. © 2015 American Institute of Chemical Engineers.

A Novel Equation-of-State to Model Microemulsion Phase Behavior for Enhanced Oil Recovery Application

NASA Astrophysics Data System (ADS)

Ghosh, Soumyadeep

Surfactant-polymer (SP) floods have significant potential to recover waterflood residual oil in shallow oil reservoirs. A thorough understanding of surfactant-oil-brine phase behavior is critical to the design of chemical EOR floods. While considerable progress has been made in developing surfactants and polymers that increase the potential of a chemical enhanced oil recovery (EOR) project, very little progress has been made to predict phase behavior as a function of formulation variables such as pressure, temperature, and oil equivalent alkane carbon number (EACN). The empirical Hand's plot is still used today to model the microemulsion phase behavior with little predictive capability as these and other formulation variables change. Such models could lead to incorrect recovery predictions and improper flood designs. Reservoir crudes also contain acidic components (primarily naphthenic acids), which undergo neutralization to form soaps in the presence of alkali. The generated soaps perform synergistically with injected synthetic surfactants to mobilize waterflood residual oil in what is termed alkali-surfactant-polymer (ASP) flooding. The addition of alkali, however, complicates the measurement and prediction of the microemulsion phase behavior that forms with acidic crudes. In this dissertation, we account for pressure changes in the hydrophilic-lipophilic difference (HLD) equation. This new HLD equation is coupled with the net-average curvature (NAC) model to predict phase volumes, solubilization ratios, and microemulsion phase transitions (Winsor II-, III, and II+). This dissertation presents the first modified HLD-NAC model to predict microemulsion phase behavior for live crudes, including optimal solubilization ratio and the salinity width of the three-phase Winsor III region at different temperatures and pressures. This new equation-of-state-like model could significantly aid the design and forecast of chemical floods where key variables change dynamically, and in screening of potential candidate reservoirs for chemical EOR. The modified HLD-NAC model is also extended here for ASP flooding. We use an empirical equation to calculate the acid distribution coefficient from the molecular structure of the soap. Key HLD-NAC parameters like optimum salinities and optimum solubilization ratios are calculated from soap mole fraction weighted equations. The model is tuned to data from phase behavior experiments with real crudes to demonstrate the procedure. We also examine the ability of the new model to predict fish plots and activity charts that show the evolution of the three-phase region. The modified HLD-NAC equations are then made dimensionless to develop important microemulsion phase behavior relationships and for use in tuning the new model to measured data. Key dimensionless groups that govern phase behavior and their effects are identified and analyzed. A new correlation was developed to predict optimum solubilization ratios at different temperatures, pressures and oil EACN with an average relative error of 10.55%. The prediction of optimum salinities with the modified HLD approach resulted in average relative errors of 2.35%. We also present a robust method to precisely determine optimum salinities and optimum solubilization ratios from salinity scan data with average relative errors of 1.17% and 2.44% for the published data examined.

Development of Non-Optimum Factors for Launch Vehicle Propellant Tank Bulkhead Weight Estimation

NASA Technical Reports Server (NTRS)

Wu, K. Chauncey; Wallace, Matthew L.; Cerro, Jeffrey A.

2012-01-01

Non-optimum factors are used during aerospace conceptual and preliminary design to account for the increased weights of as-built structures due to future manufacturing and design details. Use of higher-fidelity non-optimum factors in these early stages of vehicle design can result in more accurate predictions of a concept s actual weights and performance. To help achieve this objective, non-optimum factors are calculated for the aluminum-alloy gores that compose the ogive and ellipsoidal bulkheads of the Space Shuttle Super-Lightweight Tank propellant tanks. Minimum values for actual gore skin thicknesses and weld land dimensions are extracted from selected production drawings, and are used to predict reference gore weights. These actual skin thicknesses are also compared to skin thicknesses predicted using classical structural mechanics and tank proof-test pressures. Both coarse and refined weights models are developed for the gores. The coarse model is based on the proof pressure-sized skin thicknesses, and the refined model uses the actual gore skin thicknesses and design detail dimensions. To determine the gore non-optimum factors, these reference weights are then compared to flight hardware weights reported in a mass properties database. When manufacturing tolerance weight estimates are taken into account, the gore non-optimum factors computed using the coarse weights model range from 1.28 to 2.76, with an average non-optimum factor of 1.90. Application of the refined weights model yields non-optimum factors between 1.00 and 1.50, with an average non-optimum factor of 1.14. To demonstrate their use, these calculated non-optimum factors are used to predict heavier, more realistic gore weights for a proposed heavy-lift launch vehicle s propellant tank bulkheads. These results indicate that relatively simple models can be developed to better estimate the actual weights of large structures for future launch vehicles.

Determination of Optimum Operation Parameters for Low-Intensity Pulsed Ultrasound and Low-Level Laser Based Treatment to Induce Proliferation of Osteoblast and Fibroblast Cells.

PubMed

Coskun, Mehmet Emre; Coskun, Kubra Acikalin; Tutar, Yusuf

2018-05-01

The aim of this study was to determine the optimum operating parameters (pulse duration, energy levels, and application time) to promote induction of osteoblast and fibroblast cell proliferation and to maintain cell viability treated with low-intensity pulsed ultrasound (LIPUS) and low-level laser therapy (LLLT). The positive effects of LIPUS and LLLT on cellular activity have been reported in recent years. Comparisons between experimental parameters of previous studies are difficult because scientific studies reported frequencies and the duty cycles of LIPUS and wavelengths and doses of LLLT in a wide range of parameters. However, optimum amount of energy and optimum time exposure must be determined to induce bone and tissue cell proliferation for effective healing process and to avoid cell damage. Fibroblast and osteoblast cell cultures were irradiated with LIPUS (10-50% pulse and continuous mode at 1 and 3 MHz for 1, 3, and 5 min) and LLLT (4, 8, and 16 J at 50, 100, 200, 300, 400, and 500 mW). Cell cultures were analyzed using XTT assay. For both cell types, LIPUS treatment with 10% pulse (1:9 duty cycle), 3 MHz, and for 1 min and LLLT treatment over 100 mV for 4, 8, and 16 J modalities contributed to the growth, and may help bone repair and tissue healing process optimally. Bio-stimulating effects of LLLT irradiation promote proliferation and maintain cell viability better than LIPUS treatment without causing thermal response for both cell types, and the therapeutic modality above 200 mV has maximum effectiveness.

Techno-economic assessment of pellets produced from steam pretreated biomass feedstock

DOE PAGES

Shahrukh, Hassan; Oyedun, Adetoyese Olajire; Kumar, Amit; ...

2016-03-10

Minimum production cost and optimum plant size are determined for pellet plants for three types of biomass feedstock e forest residue, agricultural residue, and energy crops. The life cycle cost from harvesting to the delivery of the pellets to the co-firing facility is evaluated. The cost varies from 95 to 105 t -1 for regular pellets and 146–156 t -1 for steam pretreated pellets. The difference in the cost of producing regular and steam pretreated pellets per unit energy is in the range of 2e3 GJ -1. The economic optimum plant size (i.e., the size at which pellet production costmore » is minimum) is found to be 190 kt for regular pellet production and 250 kt for steam pretreated pellet. Furthermore, sensitivity and uncertainty analyses were carried out to identify sensitivity parameters and effects of model error.« less

Optimum Parameters of a Tuned Liquid Column Damper in a Wind Turbine Subject to Stochastic Load

NASA Astrophysics Data System (ADS)

Alkmim, M. H.; de Morais, M. V. G.; Fabro, A. T.

2017-12-01

Parameter optimization for tuned liquid column dampers (TLCD), a class of passive structural control, have been previously proposed in the literature for reducing vibration in wind turbines, and several other applications. However, most of the available work consider the wind excitation as either a deterministic harmonic load or random load with white noise spectra. In this paper, a global direct search optimization algorithm to reduce vibration of a tuned liquid column damper (TLCD), a class of passive structural control device, is presented. The objective is to find optimized parameters for the TLCD under stochastic load from different wind power spectral density. A verification is made considering the analytical solution of undamped primary system under white noise excitation by comparing with result from the literature. Finally, it is shown that different wind profiles can significantly affect the optimum TLCD parameters.

Subsurface water parameters: optimization approach to their determination from remotely sensed water color data.

PubMed

Jain, S C; Miller, J R

1976-04-01

A method, using an optimization scheme, has been developed for the interpretation of spectral albedo (or spectral reflectance) curves obtained from remotely sensed water color data. This method used a two-flow model of the radiation flow and solves for the albedo. Optimization fitting of predicted to observed reflectance data is performed by a quadratic interpolation method for the variables chlorophyll concentration and scattering coefficient. The technique is applied to airborne water color data obtained from Kawartha Lakes, Sargasso Sea, and Nova Scotia coast. The modeled spectral albedo curves are compared to those obtained experimentally, and the computed optimum water parameters are compared to ground truth values. It is shown that the backscattered spectral signal contains information that can be interpreted to give quantitative estimates of the chlorophyll concentration and turbidity in the waters studied.

Energy harvesting from sea waves with consideration of airy and JONSWAP theory and optimization of energy harvester parameters

NASA Astrophysics Data System (ADS)

Mirab, Hadi; Fathi, Reza; Jahangiri, Vahid; Ettefagh, Mir Mohammad; Hassannejad, Reza

2015-12-01

One of the new methods for powering low-power electronic devices at sea is a wave energy harvesting system. In this method, piezoelectric material is employed to convert the mechanical energy of sea waves into electrical energy. The advantage of this method is based on avoiding a battery charging system. Studies have been done on energy harvesting from sea waves, however, considering energy harvesting with random JONSWAP wave theory, then determining the optimum values of energy harvested is new. This paper does that by implementing the JONSWAP wave model, calculating produced power, and realistically showing that output power is decreased in comparison with the more simple airy wave model. In addition, parameters of the energy harvester system are optimized using a simulated annealing algorithm, yielding increased produced power.

Machinability Study on Milling Kenaf Fiber Reinforced Plastic Composite Materials using Design of Experiments

NASA Astrophysics Data System (ADS)

Azmi, H.; Haron, C. H. C.; Ghani, J. A.; Suhaily, M.; Yuzairi, A. R.

2018-04-01

The surface roughness (Ra) and delamination factor (Fd) of a milled kenaf reinforced plastic composite materials are depending on the milling parameters (spindle speed, feed rate and depth of cut). Therefore, a study was carried out to investigate the relationship between the milling parameters and their effects on a kenaf reinforced plastic composite materials. The composite panels were fabricated using vacuum assisted resin transfer moulding (VARTM) method. A full factorial design of experiments was use as an initial step to screen the significance of the parameters on the defects using Analysis of Variance (ANOVA). If the curvature of the collected data shows significant, Response Surface Methodology (RSM) is then applied for obtaining a quadratic modelling equation that has more reliable in expressing the optimization. Thus, the objective of this research is obtaining an optimum setting of milling parameters and modelling equations to minimize the surface roughness (Ra) and delamination factor (Fd) of milled kenaf reinforced plastic composite materials. The spindle speed and feed rate contributed the most in affecting the surface roughness and the delamination factor of the kenaf composite materials.

Optimization of CO2 laser cutting parameters on Austenitic type Stainless steel sheet

NASA Astrophysics Data System (ADS)

Parthiban, A.; Sathish, S.; Chandrasekaran, M.; Ravikumar, R.

2017-03-01

Thin AISI 316L stainless steel sheet widely used in sheet metal processing industries for specific applications. CO2 laser cutting is one of the most popular sheet metal cutting processes for cutting of sheets in different profile. In present work various cutting parameters such as laser power (2000 watts-4000 watts), cutting speed (3500mm/min - 5500 mm/min) and assist gas pressure (0.7 Mpa-0.9Mpa) for cutting of AISI 316L 2mm thickness stainless sheet. This experimentation was conducted based on Box-Behenken design. The aim of this work is to develop a mathematical model kerf width for straight and curved profile through response surface methodology. The developed mathematical models for straight and curved profile have been compared. The Quadratic models have the best agreement with experimental data, and also the shape of the profile a substantial role in achieving to minimize the kerf width. Finally the numerical optimization technique has been used to find out best optimum laser cutting parameter for both straight and curved profile cut.

Fast and Versatile Fabrication of PMMA Microchip Electrophoretic Devices by Laser Engraving

PubMed Central

Gabriel, Ellen Flávia Moreira; Coltro, Wendell Karlos Tomazelli; Garcia, Carlos D.

2014-01-01

This paper describes the effects of different modes and engraving parameters on the dimensions of microfluidic structures produced in PMMA using laser engraving. The engraving modes included raster and vector while the explored engraving parameters included power, speed, frequency, resolution, line-width and number of passes. Under the optimum conditions, the technique was applied to produce channels suitable for CE separations. Taking advantage of the possibility to cut-through the substrates, the laser was also used to define solution reservoirs (buffer, sample, and waste) and a PDMS-based decoupler. The final device was used to perform the analysis of a model mixture of phenolic compounds within 200 s with baseline resolution. PMID:25113407

Real-time flood forecasts & risk assessment using a possibility-theory based fuzzy neural network

NASA Astrophysics Data System (ADS)

Khan, U. T.

2016-12-01

Globally floods are one of the most devastating natural disasters and improved flood forecasting methods are essential for better flood protection in urban areas. Given the availability of high resolution real-time datasets for flood variables (e.g. streamflow and precipitation) in many urban areas, data-driven models have been effectively used to predict peak flow rates in river; however, the selection of input parameters for these types of models is often subjective. Additionally, the inherit uncertainty associated with data models along with errors in extreme event observations means that uncertainty quantification is essential. Addressing these concerns will enable improved flood forecasting methods and provide more accurate flood risk assessments. In this research, a new type of data-driven model, a quasi-real-time updating fuzzy neural network is developed to predict peak flow rates in urban riverine watersheds. A possibility-to-probability transformation is first used to convert observed data into fuzzy numbers. A possibility theory based training regime is them used to construct the fuzzy parameters and the outputs. A new entropy-based optimisation criterion is used to train the network. Two existing methods to select the optimum input parameters are modified to account for fuzzy number inputs, and compared. These methods are: Entropy-Wavelet-based Artificial Neural Network (EWANN) and Combined Neural Pathway Strength Analysis (CNPSA). Finally, an automated algorithm design to select the optimum structure of the neural network is implemented. The overall impact of each component of training this network is to replace the traditional ad hoc network configuration methods, with one based on objective criteria. Ten years of data from the Bow River in Calgary, Canada (including two major floods in 2005 and 2013) are used to calibrate and test the network. The EWANN method selected lagged peak flow as a candidate input, whereas the CNPSA method selected lagged precipitation and lagged mean daily flow as candidate inputs. Model performance metric show that the CNPSA method had higher performance (with an efficiency of 0.76). Model output was used to assess the risk of extreme peak flows for a given day using an inverse possibility-to-probability transformation.

Optimum design of a Lanchester damper for a viscously damped single degree of freedom system subjected to inertial excitation

NASA Astrophysics Data System (ADS)

Bapat, V. A.; Prabhu, P.

1980-11-01

The problem of designing an optimum Lanchester damper for a viscously damped single degree of freedom system subjected to inertial harmonic excitation is investigated. Two criteria are used for optimizing the performance of the damper: (i) minimum motion transmissibility; (ii) minimum force transmissibility. Explicit expressions are developed for determining the absorber parameters.

Reliability Based Design for a Raked Wing Tip of an Airframe

NASA Technical Reports Server (NTRS)

Patnaik, Surya N.; Pai, Shantaram S.; Coroneos, Rula M.

2011-01-01

A reliability-based optimization methodology has been developed to design the raked wing tip of the Boeing 767-400 extended range airliner made of composite and metallic materials. Design is formulated for an accepted level of risk or reliability. The design variables, weight and the constraints became functions of reliability. Uncertainties in the load, strength and the material properties, as well as the design variables, were modeled as random parameters with specified distributions, like normal, Weibull or Gumbel functions. The objective function and constraint, or a failure mode, became derived functions of the risk-level. Solution to the problem produced the optimum design with weight, variables and constraints as a function of the risk-level. Optimum weight versus reliability traced out an inverted-S shaped graph. The center of the graph corresponded to a 50 percent probability of success, or one failure in two samples. Under some assumptions, this design would be quite close to the deterministic optimum solution. The weight increased when reliability exceeded 50 percent, and decreased when the reliability was compromised. A design could be selected depending on the level of risk acceptable to a situation. The optimization process achieved up to a 20-percent reduction in weight over traditional design.

Kinetic approach to the study of froth flotation applied to a lepidolite ore

NASA Astrophysics Data System (ADS)

Vieceli, Nathália; Durão, Fernando O.; Guimarães, Carlos; Nogueira, Carlos A.; Pereira, Manuel F. C.; Margarido, Fernanda

2016-07-01

The number of published studies related to the optimization of lithium extraction from low-grade ores has increased as the demand for lithium has grown. However, no study related to the kinetics of the concentration stage of lithium-containing minerals by froth flotation has yet been reported. To establish a factorial design of batch flotation experiments, we conducted a set of kinetic tests to determine the most selective alternative collector, define a range of pulp pH values, and estimate a near-optimum flotation time. Both collectors (Aeromine 3000C and Armeen 12D) provided the required flotation selectivity, although this selectivity was lost in the case of pulp pH values outside the range between 2 and 4. Cumulative mineral recovery curves were used to adjust a classical kinetic model that was modified with a non-negative parameter representing a delay time. The computation of the near-optimum flotation time as the maximizer of a separation efficiency (SE) function must be performed with caution. We instead propose to define the near-optimum flotation time as the time interval required to achieve 95%-99% of the maximum value of the SE function.

Comparison of COD removal from pharmaceutical wastewater by electrocoagulation, photoelectrocoagulation, peroxi-electrocoagulation and peroxi-photoelectrocoagulation processes.

PubMed

Farhadi, Sajjad; Aminzadeh, Behnoush; Torabian, Ali; Khatibikamal, Vahid; Alizadeh Fard, Mohammad

2012-06-15

This work makes a comparison between electrocoagulation (EC), photoelectrocoagulation, peroxi-electrocoagulation and peroxi-photoelectrocoagulation processes to investigate the removal of chemical oxygen demand (COD) from pharmaceutical wastewater. The effects of operational parameters such as initial pH, current density, applied voltage, amount of hydrogen peroxide and electrolysis time on COD removal efficiency were investigated and the optimum operating range for each of these operating variables was experimentally determined. In electrocoagulation process, the optimum values of pH and voltage were determined to be 7 and 40 V, respectively. Desired pH and hydrogen peroxide concentration in the Fenton-based processes were found to be 3 and 300 mg/L, respectively. The amounts of COD, pH, electrical conductivity, temperature and total dissolved solids (TDS) were on-line monitored. Results indicated that under the optimum operating range for each process, the COD removal efficiency was in order of peroxi-electrocoagulation > peroxi-photoelectrocoagulation > photoelectrocoagulation>electrocoagulation. Finally, a kinetic study was carried out using the linear pseudo-second-order model and results showed that the pseudo-second-order equation provided the best correlation for the COD removal rate. Copyright © 2012 Elsevier B.V. All rights reserved.

A generalized analysis of solar space heating in the United States

NASA Astrophysics Data System (ADS)

Clark, J. A.

A life-cycle model is developed for solar space heating within the United States that is based on the solar design data from the Los Alamos Scientific Laboratory. The model consists of an analytical relationship among five dimensionless parameters that include all pertinent technical, climatological, solar, operating and economic factors that influence the performance of a Solar Space Heating System. An important optimum condition presented is the 'Breakeven' metered cost of conventional fuel at which the cost of the solar system is equal to that of a conventional heating system. The effect of Federal (1980) and State (1979) income tax credits on these costs is determined. A parameter that includes both solar availability and solar system utilization is derived and plotted on a map of the U.S. This parameter shows the most favorable present locations for solar space heating application to be in the Central and Mountain States. The data employed are related to the rehabilitated solar data recently made available by the National Climatic Center (SOLMET).

A semi-empirical model relating micro structure to acoustic properties of bimodal porous material

NASA Astrophysics Data System (ADS)

Mosanenzadeh, Shahrzad Ghaffari; Doutres, Olivier; Naguib, Hani E.; Park, Chul B.; Atalla, Noureddine

2015-01-01

Complex morphology of open cell porous media makes it difficult to link microstructural parameters and acoustic behavior of these materials. While morphology determines the overall sound absorption and noise damping effectiveness of a porous structure, little is known on the influence of microstructural configuration on the macroscopic properties. In the present research, a novel bimodal porous structure was designed and developed solely for modeling purposes. For the developed porous structure, it is possible to have direct control on morphological parameters and avoid complications raised by intricate pore geometries. A semi-empirical model is developed to relate microstructural parameters to macroscopic characteristics of porous material using precise characterization results based on the designed bimodal porous structures. This model specifically links macroscopic parameters including static airflow resistivity ( σ ) , thermal characteristic length ( Λ ' ) , viscous characteristic length ( Λ ) , and dynamic tortuosity ( α ∞ ) to microstructural factors such as cell wall thickness ( 2 t ) and reticulation rate ( R w ) . The developed model makes it possible to design the morphology of porous media to achieve optimum sound absorption performance based on the application in hand. This study makes the base for understanding the role of microstructural geometry and morphological factors on the overall macroscopic parameters of porous materials specifically for acoustic capabilities. The next step is to include other microstructural parameters as well to generalize the developed model. In the present paper, pore size was kept constant for eight categories of bimodal foams to study the effect of secondary porous structure on macroscopic properties and overall acoustic behavior of porous media.

Optimal time points sampling in pathway modelling.

PubMed

Hu, Shiyan

2004-01-01

Modelling cellular dynamics based on experimental data is at the heart of system biology. Considerable progress has been made to dynamic pathway modelling as well as the related parameter estimation. However, few of them gives consideration for the issue of optimal sampling time selection for parameter estimation. Time course experiments in molecular biology rarely produce large and accurate data sets and the experiments involved are usually time consuming and expensive. Therefore, to approximate parameters for models with only few available sampling data is of significant practical value. For signal transduction, the sampling intervals are usually not evenly distributed and are based on heuristics. In the paper, we investigate an approach to guide the process of selecting time points in an optimal way to minimize the variance of parameter estimates. In the method, we first formulate the problem to a nonlinear constrained optimization problem by maximum likelihood estimation. We then modify and apply a quantum-inspired evolutionary algorithm, which combines the advantages of both quantum computing and evolutionary computing, to solve the optimization problem. The new algorithm does not suffer from the morass of selecting good initial values and being stuck into local optimum as usually accompanied with the conventional numerical optimization techniques. The simulation results indicate the soundness of the new method.

The design of optimum remote-sensing instruments

NASA Technical Reports Server (NTRS)

Peckham, G. E.; Flower, D. A.

1983-01-01

Remote-sensing instruments allow values for certain properties of a target to be retrieved from measurements of radiation emitted, reflected or transmitted by the target. The retrieval accuracy is affected by random variations in the many target properties which affect the measurements. A method is described, by which statistical properties of the target and theoretical models of its electromagnetic behavior can be used to choose values for the instrument parameters which maximize the retrieval accuracy. The technique is applicable to a wide range of remote-sensing instruments.

Designing an optimum pulsed magnetic field by a resistance/self-inductance/capacitance discharge system and alignment of carbon nanotubes embedded in polypyrrole matrix

NASA Astrophysics Data System (ADS)

Kazemikia, Kaveh; Bonabi, Fahimeh; Asadpoorchallo, Ali; Shokrzadeh, Majid

2015-02-01

In this work, an optimized pulsed magnetic field production apparatus is designed based on a RLC (Resistance/Self-inductance/Capacitance) discharge circuit. An algorithm for designing an optimum magnetic coil is presented. The coil is designed to work at room temperature. With a minor physical reinforcement, the magnetic flux density can be set up to 12 Tesla with 2 ms duration time. In our design process, the magnitude and the length of the magnetic pulse are the desired parameters. The magnetic field magnitude in the RLC circuit is maximized on the basis of the optimal design of the coil. The variables which are used in the optimization process are wire diameter and the number of coil layers. The coil design ensures the critically damped response of the RLC circuit. The electrical, mechanical, and thermal constraints are applied to the design process. A locus of probable magnetic flux density values versus wire diameter and coil layer is provided to locate the optimum coil parameters. Another locus of magnetic flux density values versus capacitance and initial voltage of the RLC circuit is extracted to locate the optimum circuit parameters. Finally, the application of high magnetic fields on carbon nanotube-PolyPyrrole (CNT-PPy) nano-composite is presented. Scanning probe microscopy technique is used to observe the orientation of CNTs after exposure to a magnetic field. The result shows alignment of CNTs in a 10.3 Tesla, 1.5 ms magnetic pulse.

Exclusive queueing model including the choice of service windows

NASA Astrophysics Data System (ADS)

Tanaka, Masahiro; Yanagisawa, Daichi; Nishinari, Katsuhiro

2018-01-01

In a queueing system involving multiple service windows, choice behavior is a significant concern. This paper incorporates the choice of service windows into a queueing model with a floor represented by discrete cells. We contrived a logit-based choice algorithm for agents considering the numbers of agents and the distances to all service windows. Simulations were conducted with various parameters of agent choice preference for these two elements and for different floor configurations, including the floor length and the number of service windows. We investigated the model from the viewpoint of transit times and entrance block rates. The influences of the parameters on these factors were surveyed in detail and we determined that there are optimum floor lengths that minimize the transit times. In addition, we observed that the transit times were determined almost entirely by the entrance block rates. The results of the presented model are relevant to understanding queueing systems including the choice of service windows and can be employed to optimize facility design and floor management.

Optimization of the trienzyme extraction for the microbiological assay of folate in vegetables.

PubMed

Chen, Liwen; Eitenmiller, Ronald R

2007-05-16

Response surface methodology was applied to optimize the trienzyme digestion for the extraction of folate from vegetables. Trienzyme extraction is a combined enzymatic digestion by protease, alpha-amylase, and conjugase (gamma-glutamyl hydrolase) to liberate the carbohydrate and protein-bound folates from food matrices for total folate analysis. It is the extraction method used in AOAC Official Method 2004.05 for assay of total folate in cereal grain products. Certified reference material (CRM) 485 mixed vegetables was used to represent the matrix of vegetables. Regression and ridge analysis were performed by statistical analysis software. The predicted second-order polynomial model was adequate (R2 = 0.947), without significant lack of fit (p > 0.1). Both protease and alpha-amylase have significant effects on the extraction. Ridge analysis gave an optimum trienzyme digestion time: Pronase, 1.5 h; alpha-amylase, 1.5 h; and conjugase, 3 h. The experimental value for CRM 485 under this optimum digestion was close to the predicted value from the model, confirming the validity and adequacy of the model. The optimized trienzyme digestion condition was applied to five vegetables and yielded higher folate levels than the trienzyme digestion parameters employed in AOAC Official Method 2004.05.

Predictive control strategies for wind turbine system based on permanent magnet synchronous generator.

PubMed

Maaoui-Ben Hassine, Ikram; Naouar, Mohamed Wissem; Mrabet-Bellaaj, Najiba

2016-05-01

In this paper, Model Predictive Control and Dead-beat predictive control strategies are proposed for the control of a PMSG based wind energy system. The proposed MPC considers the model of the converter-based system to forecast the possible future behavior of the controlled variables. It allows selecting the voltage vector to be applied that leads to a minimum error by minimizing a predefined cost function. The main features of the MPC are low current THD and robustness against parameters variations. The Dead-beat predictive control is based on the system model to compute the optimum voltage vector that ensures zero-steady state error. The optimum voltage vector is then applied through Space Vector Modulation (SVM) technique. The main advantages of the Dead-beat predictive control are low current THD and constant switching frequency. The proposed control techniques are presented and detailed for the control of back-to-back converter in a wind turbine system based on PMSG. Simulation results (under Matlab-Simulink software environment tool) and experimental results (under developed prototyping platform) are presented in order to show the performances of the considered control strategies. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Study of Montmorillonite Clay for the Removal of Copper (II) by Adsorption: Full Factorial Design Approach and Cascade Forward Neural Network

PubMed Central

Turan, Nurdan Gamze; Ozgonenel, Okan

2013-01-01

An intensive study has been made of the removal efficiency of Cu(II) from industrial leachate by biosorption of montmorillonite. A 24 factorial design and cascade forward neural network (CFNN) were used to display the significant levels of the analyzed factors on the removal efficiency. The obtained model based on 24 factorial design was statistically tested using the well-known methods. The statistical analysis proves that the main effects of analyzed parameters were significant by an obtained linear model within a 95% confidence interval. The proposed CFNN model requires less experimental data and minimum calculations. Moreover, it is found to be cost-effective due to inherent advantages of its network structure. Optimization of the levels of the analyzed factors was achieved by minimizing adsorbent dosage and contact time, which were costly, and maximizing Cu(II) removal efficiency. The suggested optimum conditions are initial pH at 6, adsorbent dosage at 10 mg/L, and contact time at 10 min using raw montmorillonite with the Cu(II) removal of 80.7%. At the optimum values, removal efficiency was increased to 88.91% if the modified montmorillonite was used. PMID:24453833

Response surface methodology modeling to improve degradation of Chlorpyrifos in agriculture runoff using TiO2 solar photocatalytic in a raceway pond reactor.

PubMed

Amiri, Hoda; Nabizadeh, Ramin; Silva Martinez, Susana; Jamaleddin Shahtaheri, Seyed; Yaghmaeian, Kamyar; Badiei, Alireza; Nazmara, Shahrokh; Naddafi, Kazem

2018-01-01

This paper deals with the use of a raceway pond reactor (RPR) as an alternative photoreactor for solar photocatalytic applications. Raceway pond reactors are common low-cost reactors which can treat large volumes of water. The experiments were carried out with TiO 2 in the agriculture effluent spiked with Chlorpyrifos (CPF) at circumneutral pH. The Response Surface Methodology (RSM) was used to find the optimum process parameters to maximize CPF oxidation from the mathematical model equations developed in this study using R software. By ANOVA, p-value of lack of fit > 0.05 indicated that, the equation was well-fitted. The theoretical efficiency of CPF removal, under the optimum oxidation conditions with UV solar energy of around 697 ± 5.33 lux, was 84.01%, which is in close agreement with the mean experimental value (80 ± 1.42%) confirming that the response model was suitable for the optimization. As far as the authors know, this is the first study of CPF removal using RPR in agriculture runoff at circumneutral pH. Copyright © 2017. Published by Elsevier Inc.

Analytical network process based optimum cluster head selection in wireless sensor network.

PubMed

Farman, Haleem; Javed, Huma; Jan, Bilal; Ahmad, Jamil; Ali, Shaukat; Khalil, Falak Naz; Khan, Murad

2017-01-01

Wireless Sensor Networks (WSNs) are becoming ubiquitous in everyday life due to their applications in weather forecasting, surveillance, implantable sensors for health monitoring and other plethora of applications. WSN is equipped with hundreds and thousands of small sensor nodes. As the size of a sensor node decreases, critical issues such as limited energy, computation time and limited memory become even more highlighted. In such a case, network lifetime mainly depends on efficient use of available resources. Organizing nearby nodes into clusters make it convenient to efficiently manage each cluster as well as the overall network. In this paper, we extend our previous work of grid-based hybrid network deployment approach, in which merge and split technique has been proposed to construct network topology. Constructing topology through our proposed technique, in this paper we have used analytical network process (ANP) model for cluster head selection in WSN. Five distinct parameters: distance from nodes (DistNode), residual energy level (REL), distance from centroid (DistCent), number of times the node has been selected as cluster head (TCH) and merged node (MN) are considered for CH selection. The problem of CH selection based on these parameters is tackled as a multi criteria decision system, for which ANP method is used for optimum cluster head selection. Main contribution of this work is to check the applicability of ANP model for cluster head selection in WSN. In addition, sensitivity analysis is carried out to check the stability of alternatives (available candidate nodes) and their ranking for different scenarios. The simulation results show that the proposed method outperforms existing energy efficient clustering protocols in terms of optimum CH selection and minimizing CH reselection process that results in extending overall network lifetime. This paper analyzes that ANP method used for CH selection with better understanding of the dependencies of different components involved in the evaluation process.

Analytical network process based optimum cluster head selection in wireless sensor network

PubMed Central

Javed, Huma; Jan, Bilal; Ahmad, Jamil; Ali, Shaukat; Khalil, Falak Naz; Khan, Murad

2017-01-01

Wireless Sensor Networks (WSNs) are becoming ubiquitous in everyday life due to their applications in weather forecasting, surveillance, implantable sensors for health monitoring and other plethora of applications. WSN is equipped with hundreds and thousands of small sensor nodes. As the size of a sensor node decreases, critical issues such as limited energy, computation time and limited memory become even more highlighted. In such a case, network lifetime mainly depends on efficient use of available resources. Organizing nearby nodes into clusters make it convenient to efficiently manage each cluster as well as the overall network. In this paper, we extend our previous work of grid-based hybrid network deployment approach, in which merge and split technique has been proposed to construct network topology. Constructing topology through our proposed technique, in this paper we have used analytical network process (ANP) model for cluster head selection in WSN. Five distinct parameters: distance from nodes (DistNode), residual energy level (REL), distance from centroid (DistCent), number of times the node has been selected as cluster head (TCH) and merged node (MN) are considered for CH selection. The problem of CH selection based on these parameters is tackled as a multi criteria decision system, for which ANP method is used for optimum cluster head selection. Main contribution of this work is to check the applicability of ANP model for cluster head selection in WSN. In addition, sensitivity analysis is carried out to check the stability of alternatives (available candidate nodes) and their ranking for different scenarios. The simulation results show that the proposed method outperforms existing energy efficient clustering protocols in terms of optimum CH selection and minimizing CH reselection process that results in extending overall network lifetime. This paper analyzes that ANP method used for CH selection with better understanding of the dependencies of different components involved in the evaluation process. PMID:28719616

Simplified analysis and optimization of space base and space shuttle heat rejection systems

NASA Technical Reports Server (NTRS)

Wulff, W.

1972-01-01

A simplified radiator system analysis was performed to predict steady state radiator system performance. The system performance was found to be describable in terms of five non-dimensional system parameters. The governing differential equations are integrated numerically to yield the enthalpy rejection for the coolant fluid. The simplified analysis was extended to produce the derivatives of the coolant exit temperature with respect to the governing system parameters. A procedure was developed to find the optimum set of system parameters which yields the lowest possible coolant exit temperature for either a given projected area or a given total mass. The process can be inverted to yield either the minimum area or the minimum mass, together with the optimum geometry, for a specified heat rejection rate.

Retention prediction and separation optimization under multilinear gradient elution in liquid chromatography with Microsoft Excel macros.

PubMed

Fasoula, S; Zisi, Ch; Gika, H; Pappa-Louisi, A; Nikitas, P

2015-05-22

A package of Excel VBA macros have been developed for modeling multilinear gradient retention data obtained in single or double gradient elution mode by changing organic modifier(s) content and/or eluent pH. For this purpose, ten chromatographic models were used and four methods were adopted for their application. The methods were based on (a) the analytical expression of the retention time, provided that this expression is available, (b) the retention times estimated using the Nikitas-Pappa approach, (c) the stepwise approximation, and (d) a simple numerical approximation involving the trapezoid rule for integration of the fundamental equation for gradient elution. For all these methods, Excel VBA macros have been written and implemented using two different platforms; the fitting and the optimization platform. The fitting platform calculates not only the adjustable parameters of the chromatographic models, but also the significance of these parameters and furthermore predicts the analyte elution times. The optimization platform determines the gradient conditions that lead to the optimum separation of a mixture of analytes by using the Solver evolutionary mode, provided that proper constraints are set in order to obtain the optimum gradient profile in the minimum gradient time. The performance of the two platforms was tested using experimental and artificial data. It was found that using the proposed spreadsheets, fitting, prediction, and optimization can be performed easily and effectively under all conditions. Overall, the best performance is exhibited by the analytical and Nikitas-Pappa's methods, although the former cannot be used under all circumstances. Copyright © 2015 Elsevier B.V. All rights reserved.

Optimization of Fermentation Medium for Extracellular Lipase Production from Aspergillus niger Using Response Surface Methodology

PubMed Central

Jia, Jia; Yang, Xiaofeng; Wu, Zhiliang; Zhang, Qian; Lin, Zhi; Guo, Hongtao; Lin, Carol Sze Ki; Wang, Jianying; Wang, Yunshan

2015-01-01

Lipase produced by Aspergillus niger is widely used in various industries. In this study, extracellular lipase production from an industrial producing strain of A. niger was improved by medium optimization. The secondary carbon source, nitrogen source, and lipid were found to be the three most influential factors for lipase production by single-factor experiments. According to the statistical approach, the optimum values of three most influential parameters were determined: 10.5 g/L corn starch, 35.4 g/L soybean meal, and 10.9 g/L soybean oil. Using this optimum medium, the best lipase activity was obtained at 2,171 U/mL, which was 16.4% higher than using the initial medium. All these results confirmed the validity of the model. Furthermore, results of the Box-Behnken Design and quadratic models analysis indicated that the carbon to nitrogen (C/N) ratio significantly influenced the enzyme production, which also suggested that more attention should be paid to the C/N ratio for the optimization of enzyme production. PMID:26366414

Shelf-life prediction of canned "nasi uduk" using accelerated shelf-life test (ASLT) - Arrhenius model

NASA Astrophysics Data System (ADS)

Kurniadi, Muhamad; Salam, Nur; Kusumaningrum, Annisa; Nursiwi, Asri; Angwar, Mukhamad; Susanto, Agus; Nurhikmat, Asep; Triwiyono, Frediansyah, Andri

2017-01-01

"Nasi Uduk" is one of the Indonesian traditional food made from rice, steamed with coconut milk and seasoning. For optimizing shelf-life, canned "nasi uduk" for military and disaster-response ration, was packed using cylindrical cans of 72,63 × 53,04 mm (Ø × h) in size. One of the important aspects on quality assessment of preserved product was its rancidity. The aim of this research was to determine shelf-life of canned "nasi uduk" using ASLT method of Arrhenius model. Storage temperatures set up at 35, 45 and 55°C for 35 days. Optimization of sterilization process was conducted to achieve the optimum conditions of sterilization. Target lethality value (Fo), microorganism total plate count (TPC) and rancidity levels (TBA) were used as parameters in this research. The results showed that the optimum sterilization conditions were 121 °C for 20 minutes, TPC value of 9.5 × 101 CFU/ml and Fo value 4.14 minutes. Predicted shelf-life of canned "nasi uduk" was 9.6 months which was average TBA value still bellow of the critical point.

Separation of tartronic and glyceric acids by simulated moving bed chromatography.

PubMed

Coelho, Lucas C D; Filho, Nelson M L; Faria, Rui P V; Ferreira, Alexandre F P; Ribeiro, Ana M; Rodrigues, Alírio E

2018-08-17

The SMB unit developed by the Laboratory of Separation and Reaction Engineering (FlexSMB-LSRE ® ) was used to perform tartronic acid (TTA) and glyceric acid (GCA) separation and to validate the mathematical model in order to determine the optimum operating parameters of an industrial unit. The purity of the raffinate and extract streams in the experiments performed were 80% and 100%, respectively. The TTA and GCA productivities were 79 and 115 kg per liter of adsorbent per day, respectively and only 0.50 cubic meters of desorbent were required per kilogram of products. Under the optimum operating conditions, which were determined through an extensive simulation study based on the mathematical model developed to predict the performance of a real SMB unit, it was possible to achieve a productivity of 86 kg of TTA and 176 kg of GCA per cubic meter of adsorbent per day (considering the typical commercial purity value of 97% for both compounds) with an eluent consumption of 0.30 cubic meters per kilogram of products. Copyright © 2018 Elsevier B.V. All rights reserved.

Numerical Study of Pyrolysis of Biomass in Fluidized Beds

NASA Technical Reports Server (NTRS)

Bellan, Josette; Lathouwers, Danny

2003-01-01

A report presents a numerical-simulation study of pyrolysis of biomass in fluidized-bed reactors, performed by use of the mathematical model described in Model of Fluidized Bed Containing Reacting Solids and Gases (NPO-30163), which appears elsewhere in this issue of NASA Tech Briefs. The purpose of the study was to investigate the effect of various operating conditions on the efficiency of production of condensable tar from biomass. The numerical results indicate that for a fixed particle size, the fluidizing-gas temperature is the foremost parameter that affects the tar yield. For the range of fluidizing-gas temperatures investigated, and under the assumption that the pyrolysis rate exceeds the feed rate, the optimum steady-state tar collection was found to occur at 750 K. In cases in which the assumption was not valid, the optimum temperature for tar collection was found to be only slightly higher. Scaling up of the reactor was found to exert a small negative effect on tar collection at the optimal operating temperature. It is also found that slightly better scaling is obtained by use of shallower fluidized beds with greater fluidization velocities.

Implementation of smart phone video plethysmography and dependence on lighting parameters.

PubMed

Fletcher, Richard Ribón; Chamberlain, Daniel; Paggi, Nicholas; Deng, Xinyue

2015-08-01

The remote measurement of heart rate (HR) and heart rate variability (HRV) via a digital camera (video plethysmography) has emerged as an area of great interest for biomedical and health applications. While a few implementations of video plethysmography have been demonstrated on smart phones under controlled lighting conditions, it has been challenging to create a general scalable solution due to the large variability in smart phone hardware performance, software architecture, and the variable response to lighting parameters. In this context, we present a selfcontained smart phone implementation of video plethysmography for Android OS, which employs both stochastic and deterministic algorithms, and we use this to study the effect of lighting parameters (illuminance, color spectrum) on the accuracy of the remote HR measurement. Using two different phone models, we present the median HR error for five different video plethysmography algorithms under three different types of lighting (natural sunlight, compact fluorescent, and halogen incandescent) and variations in brightness. For most algorithms, we found the optimum light brightness to be in the range 1000-4000 lux and the optimum lighting types to be compact fluorescent and natural light. Moderate errors were found for most algorithms with some devices under conditions of low-brightness (<;500 lux) and highbrightness (>4000 lux). Our analysis also identified camera frame rate jitter as a major source of variability and error across different phone models, but this can be largely corrected through non-linear resampling. Based on testing with six human subjects, our real-time Android implementation successfully predicted the measured HR with a median error of -0.31 bpm, and an inter-quartile range of 2.1bpm.

Genetic variation maintained in multilocus models of additive quantitative traits under stabilizing selection.

PubMed Central

Bürger, R; Gimelfarb, A

1999-01-01

Stabilizing selection for an intermediate optimum is generally considered to deplete genetic variation in quantitative traits. However, conflicting results from various types of models have been obtained. While classical analyses assuming a large number of independent additive loci with individually small effects indicated that no genetic variation is preserved under stabilizing selection, several analyses of two-locus models showed the contrary. We perform a complete analysis of a generalization of Wright's two-locus quadratic-optimum model and investigate numerically the ability of quadratic stabilizing selection to maintain genetic variation in additive quantitative traits controlled by up to five loci. A statistical approach is employed by choosing randomly 4000 parameter sets (allelic effects, recombination rates, and strength of selection) for a given number of loci. For each parameter set we iterate the recursion equations that describe the dynamics of gamete frequencies starting from 20 randomly chosen initial conditions until an equilibrium is reached, record the quantities of interest, and calculate their corresponding mean values. As the number of loci increases from two to five, the fraction of the genome expected to be polymorphic declines surprisingly rapidly, and the loci that are polymorphic increasingly are those with small effects on the trait. As a result, the genetic variance expected to be maintained under stabilizing selection decreases very rapidly with increased number of loci. The equilibrium structure expected under stabilizing selection on an additive trait differs markedly from that expected under selection with no constraints on genotypic fitness values. The expected genetic variance, the expected polymorphic fraction of the genome, as well as other quantities of interest, are only weakly dependent on the selection intensity and the level of recombination. PMID:10353920

Influence of Powder Injection Parameters in High-Pressure Cold Spray

NASA Astrophysics Data System (ADS)

Ozdemir, Ozan C.; Widener, Christian A.

2017-10-01

High-pressure cold spray systems are becoming widely accepted for use in the structural repair of surface defects of expensive machinery parts used in industrial and military equipment. The deposition quality of cold spray repairs is typically validated using coupon testing and through destructive analysis of mock-ups or first articles for a defined set of parameters. In order to provide a reliable repair, it is important to not only maintain the same processing parameters, but also to have optimum fixed parameters, such as the particle injection location. This study is intended to provide insight into the sensitivity of the way that the powder is injected upstream of supersonic nozzles in high-pressure cold spray systems and the effects of variations in injection parameters on the nature of the powder particle kinetics. Experimentally validated three-dimensional computational fluid dynamics (3D CFD) models are implemented to study the particle impact conditions for varying powder feeder tube size, powder feeder tube axial misalignment, and radial powder feeder injection location on the particle velocity and the deposition shape of aluminum alloy 6061. Outputs of the models are statistically analyzed to explore the shape of the spray plume distribution and resulting coating buildup.

[Study on new extraction technology of astragaloside IV].

PubMed

Sun, Haiyan; Guan, Su; Huang, Min

2005-08-01

To explore the possibility and the optimal extraction technology of astragaloside IV by SFE-CO2. According the content of astragaloside IV, the optimum extraction technology parameters such as extraction temperature, pressure, extraction time, velocity of fluid and co-solvent were investigated and the result was compared with that of water extraction. The optimum technical parameters were as follows: Extracting pressure 40 Mpa, temperature 45 degrees C, extracting time 2h, co-solvent was 95% ethanol and its dosage was 4ml/g, the ratio of CO2 fluid was 10 kg/kg x h. Extraction technology of astragaloside IV by SFE-CO2 is reliable, stable.

Optimization of radial-type superconducting magnetic bearing using the Taguchi method

NASA Astrophysics Data System (ADS)

Ai, Liwang; Zhang, Guomin; Li, Wanjie; Liu, Guole; Liu, Qi

2018-07-01

It is important and complicated to model and optimize the levitation behavior of superconducting magnetic bearing (SMB). That is due to the nonlinear constitutive relationships of superconductor and ferromagnetic materials, the relative movement between the superconducting stator and PM rotor, and the multi-parameter (e.g., air-gap, critical current density, and remanent flux density, etc.) affecting the levitation behavior. In this paper, we present a theoretical calculation and optimization method of the levitation behavior for radial-type SMB. A simplified model of levitation force calculation is established using 2D finite element method with H-formulation. In the model, the boundary condition of superconducting stator is imposed by harmonic series expressions to describe the traveling magnetic field generated by the moving PM rotor. Also, experimental measurements of the levitation force are performed and validate the model method. A statistical method called Taguchi method is adopted to carry out an optimization of load capacity for SMB. Then the factor effects of six optimization parameters on the target characteristics are discussed and the optimum parameters combination is determined finally. The results show that the levitation behavior of SMB is greatly improved and the Taguchi method is suitable for optimizing the SMB.

Geological and mechanical properties on the 3-D fault patch of the rapid creeping Chihshang Fault: a plate suture between Luzon arc and Eurasia in eastern Taiwan

NASA Astrophysics Data System (ADS)

Lee, J. C.; Mu, C. H.; Huang, W. J.; Liu, Z. Y. C.; Shirzaei, M.

2017-12-01

The 35-km-long Chihshang Fault is a rapidly creeping thrust at plate suture between the converging Philippine and Eurasian plates in eastern Taiwan. We combined geological investigation, geodetic data, seismological information, and a rate-dependant friction model, to illustrate the mechanical frictional properties and their variations along the strike and the depth (30-km-deep) of the fault. During the interseismic period, the Chihshang Fault is characterized by three different slip behaviours at different depths: 1) abundant micro-seismicity and semi-continuous rapid slip at the depth of 10-20 km seismogenic zone; 2) visco-elastic aseismic slip zone beneath 25 km; 3) seasonal locked/creep switch at depth of 0-2 km. Using elastic dislocation model, 1-D diffusion model, Coulomb stress criterion, and rate-dependent frictional law, we simulate the surface creep curves from the creep meters data. The result shows a rate-strengthening zone with positive frictional property (a-b) in the upper 500 meters of fault, which appears to be locked during the dry season. We tend to interpret it as a result of 300-500 m thick of unconsolidated gravels layers in the footwall of the Chihshang Fault. We also implement an inverse dynamic modeling scheme to estimate the frictional parameter () in depths by taking into account pre-seismic stress and coulomb stress changes associated with co- and post-seismic deformation of the 2003 Mw 6.5 Chengkung earthquake. Model parameters are determined from fitting the transient post-seismic geodetic signal measured at 12 continuous GPS stations. We apply a non-linear optimization algorithm, Genetic Algorithm (GA), to search for the optimum parameters. The optimum is 1.4 ×10-2 along the shallow part of the fault (0-10 km depth) and 1.2 × 10-2 in 22-28 km depth. The inferred frictional parameters are consistent with the laboratory measurements on clay rich fault zone gouges comparable to the Lichi mélange, considering the main rock composition of the Chihshang fault. Our results indicate a possibly strong influence from the surface cover of a few hundreds meter thick unconsolidated deposits (i.e., late Quaternary gravel) and the clay rich fault gouge (i.e. the Lichi Melange) on frictional properties.

Sorption of water alkalinity and hardness from high-strength wastewater on bifunctional activated carbon: process optimization, kinetics and equilibrium studies.

PubMed

Amosa, Mutiu K

2016-08-01

Sorption optimization and mechanism of hardness and alkalinity on bifunctional empty fruit bunch-based powdered activation carbon (PAC) were studied. The PAC possessed both high surface area and ion-exchange properties, and it was utilized in the treatment of biotreated palm oil mill effluent. Batch adsorption experiments designed with Design Expert(®) were conducted in correlating the singular and interactive effects of the three adsorption parameters: PAC dosage, agitation speed and contact time. The sorption trends of the two contaminants were sequentially assessed through a full factorial design with three factor interaction models and a central composite design with polynomial models of quadratic order. Analysis of variance revealed the significant factors on each design response with very high R(2) values indicating good agreement between model and experimental values. The optimum operating conditions of the two contaminants differed due to their different regions of operating interests, thus necessitating the utility of desirability factor to get consolidated optimum operation conditions. The equilibrium data for alkalinity and hardness sorption were better represented by the Langmuir isotherm, while the pseudo-second-order kinetic model described the adsorption rates and behavior better. It was concluded that chemisorption contributed majorly to the adsorption process.

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

NASA Astrophysics Data System (ADS)

Dakshinamurthy, Devika; Gupta, Srinivasa

2018-04-01

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

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

Applegate, Matthew B.; Alonzo, Carlo; Georgakoudi, Irene

High resolution three-dimensional voids can be directly written into transparent silk fibroin hydrogels using ultrashort pulses of near-infrared (NIR) light. Here, we propose a simple finite-element model that can be used to predict the size and shape of individual features under various exposure conditions. We compare predicted and measured feature volumes for a wide range of parameters and use the model to determine optimum conditions for maximum material removal. The simplicity of the model implies that the mechanism of multiphoton induced void creation in silk is due to direct absorption of light energy rather than diffusion of heat or othermore » photoproducts, and confirms that multiphoton absorption of NIR light in silk is purely a 3-photon process.« less

Optimum parallel step-sector bearing lubricated with an incompressible fluid

NASA Technical Reports Server (NTRS)

Hamrock, B. J.

1983-01-01

The dimensionless parameters normally associated with a step sector thrust bearing are the film thickness ratio, the dimensionless step location, the number of sectors, the radius ratio, and the angular extent of the lubrication feed groove. The optimum number of sectors and the parallel step configuration for a step sector thrust bearing while considering load capacity or stiffness and assuming an incompressible fluid are presented.

[Application of wavelet transform-radial basis function neural network in NIRS for determination of rifampicin and isoniazide tablets].

PubMed

Lu, Jia-hui; Zhang, Yi-bo; Zhang, Zhuo-yong; Meng, Qing-fan; Guo, Wei-liang; Teng, Li-rong

2008-06-01

A calibration model (WT-RBFNN) combination of wavelet transform (WT) and radial basis function neural network (RBFNN) was proposed for synchronous and rapid determination of rifampicin and isoniazide in Rifampicin and Isoniazide tablets by near infrared reflectance spectroscopy (NIRS). The approximation coefficients were used for input data in RBFNN. The network parameters including the number of hidden layer neurons and spread constant (SC) were investigated. WT-RBFNN model which compressed the original spectra data, removed the noise and the interference of background, and reduced the randomness, the capabilities of prediction were well optimized. The root mean square errors of prediction (RMSEP) for the determination of rifampicin and isoniazide obtained from the optimum WT-RBFNN model are 0.00639 and 0.00587, and the root mean square errors of cross-calibration (RMSECV) for them are 0.00604 and 0.00457, respectively which are superior to those obtained by the optimum RBFNN and PLS models. Regression coefficient (R) between NIRS predicted values and RP-HPLC values for rifampicin and isoniazide are 0.99522 and 0.99392, respectively and the relative error is lower than 2.300%. It was verified that WT-RBFNN model is a suitable approach to dealing with NIRS. The proposed WT-RBFNN model is convenient, and rapid and with no pollution for the determination of rifampicin and isoniazide tablets.

Design Optimization of a Hybrid Electric Vehicle Powertrain

NASA Astrophysics Data System (ADS)

Mangun, Firdause; Idres, Moumen; Abdullah, Kassim

2017-03-01

This paper presents an optimization work on hybrid electric vehicle (HEV) powertrain using Genetic Algorithm (GA) method. It focused on optimization of the parameters of powertrain components including supercapacitors to obtain maximum fuel economy. Vehicle modelling is based on Quasi-Static-Simulation (QSS) backward-facing approach. A combined city (FTP-75)-highway (HWFET) drive cycle is utilized for the design process. Seeking global optimum solution, GA was executed with different initial settings to obtain sets of optimal parameters. Starting from a benchmark HEV, optimization results in a smaller engine (2 l instead of 3 l) and a larger battery (15.66 kWh instead of 2.01 kWh). This leads to a reduction of 38.3% in fuel consumption and 30.5% in equivalent fuel consumption. Optimized parameters are also compared with actual values for HEV in the market.

Modelling of 10 Gbps Free Space Optics Communication Link Using Array of Receivers in Moderate and Harsh Weather Conditions

NASA Astrophysics Data System (ADS)

Gupta, Amit; Shaina, Nagpal

2017-08-01

Intersymbol interference and attenuation of signal are two major parameters affecting the quality of transmission in Free Space Optical (FSO) Communication link. In this paper, the impact of these parameters on FSO communication link is analysed for delivering high-quality data transmission. The performance of the link is investigated under the influence of amplifier in the link. The performance parameters of the link like minimum bit error rate, received signal power and Quality factor are examined by employing erbium-doped fibre amplifier in the link. The effects of amplifier are visualized with the amount of received power. Further, the link is simulated for moderate weather conditions at various attenuation levels on transmitted signal. Finally, the designed link is analysed in adverse weather conditions by using high-power laser source for optimum performance.

ConvAn: a convergence analyzing tool for optimization of biochemical networks.

PubMed

Kostromins, Andrejs; Mozga, Ivars; Stalidzans, Egils

2012-01-01

Dynamic models of biochemical networks usually are described as a system of nonlinear differential equations. In case of optimization of models for purpose of parameter estimation or design of new properties mainly numerical methods are used. That causes problems of optimization predictability as most of numerical optimization methods have stochastic properties and the convergence of the objective function to the global optimum is hardly predictable. Determination of suitable optimization method and necessary duration of optimization becomes critical in case of evaluation of high number of combinations of adjustable parameters or in case of large dynamic models. This task is complex due to variety of optimization methods, software tools and nonlinearity features of models in different parameter spaces. A software tool ConvAn is developed to analyze statistical properties of convergence dynamics for optimization runs with particular optimization method, model, software tool, set of optimization method parameters and number of adjustable parameters of the model. The convergence curves can be normalized automatically to enable comparison of different methods and models in the same scale. By the help of the biochemistry adapted graphical user interface of ConvAn it is possible to compare different optimization methods in terms of ability to find the global optima or values close to that as well as the necessary computational time to reach them. It is possible to estimate the optimization performance for different number of adjustable parameters. The functionality of ConvAn enables statistical assessment of necessary optimization time depending on the necessary optimization accuracy. Optimization methods, which are not suitable for a particular optimization task, can be rejected if they have poor repeatability or convergence properties. The software ConvAn is freely available on www.biosystems.lv/convan. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

The Role of Radial Clearance on the Performance of Foil Air Bearings

NASA Technical Reports Server (NTRS)

Radil, Kevin; Howard, Samuel; Dykas, Brian

2002-01-01

Load capacity tests were conducted to determine how radial clearance variations affect the load capacity coefficient of foil air bearings. Two Generation III foil air bearings with the same design but possessing different initial radial clearances were tested at room temperature against an as-ground PS304 coated journal operating at 30,000 rpm. Increases in radial clearance were accomplished by reducing the journal's outside diameter via an in-place grinding system. From each load capacity test the bearing load capacity coefficient was calculated from the rule-of-thumb (ROT) model developed for foil air bearings. The test results indicate that, in terms of the load capacity coefficient, radial clearance has a direct impact on the performance of the foil air bearing. Each test bearing exhibited an optimum radial clearance that resulted in a maximum load capacity coefficient. Relative to this optimum value are two separate operating regimes that are governed by different modes of failure. Bearings operating with radial clearances less than the optimum exhibit load capacity coefficients that are a strong function of radial clearance and are prone to a thermal runaway failure mechanism and bearing seizure. Conversely, a bearing operating with a radial clearance twice the optimum suffered only a 20 percent decline in its maximum load capacity coefficient and did not experience any thermal management problems. However, it is unknown to what degree these changes in radial clearance had on other performance parameters, such as the stiffness and damping properties of the bearings.

Dynamic analysis of I cross beam section dissimilar plate joined by TIG welding

NASA Astrophysics Data System (ADS)

Sani, M. S. M.; Nazri, N. A.; Rani, M. N. Abdul; Yunus, M. A.

2018-04-01

In this paper, finite element (FE) joint modelling technique for prediction of dynamic properties of sheet metal jointed by tungsten inert gas (TTG) will be presented. I cross section dissimilar flat plate with different series of aluminium alloy; AA7075 and AA6061 joined by TTG are used. In order to find the most optimum set of TTG welding dissimilar plate, the finite element model with three types of joint modelling were engaged in this study; bar element (CBAR), beam element and spot weld element connector (CWELD). Experimental modal analysis (EMA) was carried out by impact hammer excitation on the dissimilar plates that welding by TTG method. Modal properties of FE model with joints were compared and validated with model testing. CWELD element was chosen to represent weld model for TTG joints due to its accurate prediction of mode shapes and contains an updating parameter for weld modelling compare to other weld modelling. Model updating was performed to improve correlation between EMA and FEA and before proceeds to updating, sensitivity analysis was done to select the most sensitive updating parameter. After perform model updating, average percentage of error of the natural frequencies for CWELD model is improved significantly.

Multi-objective thermodynamic optimisation of supercritical CO2 Brayton cycles integrated with solar central receivers

NASA Astrophysics Data System (ADS)

Vasquez Padilla, Ricardo; Soo Too, Yen Chean; Benito, Regano; McNaughton, Robbie; Stein, Wes

2018-01-01

In this paper, optimisation of the supercritical CO? Brayton cycles integrated with a solar receiver, which provides heat input to the cycle, was performed. Four S-CO? Brayton cycle configurations were analysed and optimum operating conditions were obtained by using a multi-objective thermodynamic optimisation. Four different sets, each including two objective parameters, were considered individually. The individual multi-objective optimisation was performed by using Non-dominated Sorting Genetic Algorithm. The effect of reheating, solar receiver pressure drop and cycle parameters on the overall exergy and cycle thermal efficiency was analysed. The results showed that, for all configurations, the overall exergy efficiency of the solarised systems achieved at maximum value between 700°C and 750°C and the optimum value is adversely affected by the solar receiver pressure drop. In addition, the optimum cycle high pressure was in the range of 24.2-25.9 MPa, depending on the configurations and reheat condition.

Simultaneous Intrinsic and Extrinsic Parameter Identification of a Hand-Mounted Laser-Vision Sensor

PubMed Central

Lee, Jong Kwang; Kim, Kiho; Lee, Yongseok; Jeong, Taikyeong

2011-01-01

In this paper, we propose a simultaneous intrinsic and extrinsic parameter identification of a hand-mounted laser-vision sensor (HMLVS). A laser-vision sensor (LVS), consisting of a camera and a laser stripe projector, is used as a sensor component of the robotic measurement system, and it measures the range data with respect to the robot base frame using the robot forward kinematics and the optical triangulation principle. For the optimal estimation of the model parameters, we applied two optimization techniques: a nonlinear least square optimizer and a particle swarm optimizer. Best-fit parameters, including both the intrinsic and extrinsic parameters of the HMLVS, are simultaneously obtained based on the least-squares criterion. From the simulation and experimental results, it is shown that the parameter identification problem considered was characterized by a highly multimodal landscape; thus, the global optimization technique such as a particle swarm optimization can be a promising tool to identify the model parameters for a HMLVS, while the nonlinear least square optimizer often failed to find an optimal solution even when the initial candidate solutions were selected close to the true optimum. The proposed optimization method does not require good initial guesses of the system parameters to converge at a very stable solution and it could be applied to a kinematically dissimilar robot system without loss of generality. PMID:22164104

Finite element analysis of flowfield in the single hole film cooling technique.

PubMed

Bazdidi-Tehrani, F; Mahmoodi, A A

2001-05-01

Film cooling is currently used in gas turbine hot sections, such as the combustor wall and the turbine blades, to prevent those sections from failing at elevated temperatures. In the single hole film cooling method, coolant air is injected from a hole into the mainstream and thus the flow is naturally three dimensional. In this paper, the Navier-Stokes and the energy equations are solved on a flat plate by the Finite Element Method (FEM) using brick elements. Algebraic equations are obtained by use of the Petrov-Galerkin method. The pressure term is removed from the momentum equations, by employing the Penalty method. The governing equations are transient and the flow is incompressible and turbulent. The model of turbulence in the near wall region is the wall function method, and in the fully turbulent region is the k-epsilon model. The system of the algebraic equations are solved by the Frontal method. The coolant injection angle and the blowing rate are among the parameters which are studied. In order to examine the present computer code, the results are compared with the Blasius (exact) solution and also with the empirical 1/7th power-law and good agreement is shown. Also, the optimum cooling performance is shown to be at 35 degree angle of coolant injection and the optimum blowing rate is 0.5. The film cooling effectiveness data, at the optimum conditions, is directly compared with the experimental results of Goldstein et al. and good agreement is demonstrated.

Study of components and statistical reaction mechanism in simulation of nuclear process for optimized production of {sup 64}Cu and {sup 67}Ga medical radioisotopes using TALYS, EMPIRE and LISE++ nuclear reaction and evaporation codes

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

Nasrabadi, M. N., E-mail: mnnasrabadi@ast.ui.ac.ir; Sepiani, M.

2015-03-30

Production of medical radioisotopes is one of the most important tasks in the field of nuclear technology. These radioactive isotopes are mainly produced through variety nuclear process. In this research, excitation functions and nuclear reaction mechanisms are studied for simulation of production of these radioisotopes in the TALYS, EMPIRE and LISE++ reaction codes, then parameters and different models of nuclear level density as one of the most important components in statistical reaction models are adjusted for optimum production of desired radioactive yields.

Study of components and statistical reaction mechanism in simulation of nuclear process for optimized production of 64Cu and 67Ga medical radioisotopes using TALYS, EMPIRE and LISE++ nuclear reaction and evaporation codes

NASA Astrophysics Data System (ADS)

Nasrabadi, M. N.; Sepiani, M.

2015-03-01

Production of medical radioisotopes is one of the most important tasks in the field of nuclear technology. These radioactive isotopes are mainly produced through variety nuclear process. In this research, excitation functions and nuclear reaction mechanisms are studied for simulation of production of these radioisotopes in the TALYS, EMPIRE & LISE++ reaction codes, then parameters and different models of nuclear level density as one of the most important components in statistical reaction models are adjusted for optimum production of desired radioactive yields.

Hybrid simulated annealing and its application to optimization of hidden Markov models for visual speech recognition.

PubMed

Lee, Jong-Seok; Park, Cheol Hoon

2010-08-01

We propose a novel stochastic optimization algorithm, hybrid simulated annealing (SA), to train hidden Markov models (HMMs) for visual speech recognition. In our algorithm, SA is combined with a local optimization operator that substitutes a better solution for the current one to improve the convergence speed and the quality of solutions. We mathematically prove that the sequence of the objective values converges in probability to the global optimum in the algorithm. The algorithm is applied to train HMMs that are used as visual speech recognizers. While the popular training method of HMMs, the expectation-maximization algorithm, achieves only local optima in the parameter space, the proposed method can perform global optimization of the parameters of HMMs and thereby obtain solutions yielding improved recognition performance. The superiority of the proposed algorithm to the conventional ones is demonstrated via isolated word recognition experiments.

Optimization principles and the figure of merit for triboelectric generators.

PubMed

Peng, Jun; Kang, Stephen Dongmin; Snyder, G Jeffrey

2017-12-01

Energy harvesting with triboelectric nanogenerators is a burgeoning field, with a growing portfolio of creative application schemes attracting much interest. Although power generation capabilities and its optimization are one of the most important subjects, a satisfactory elemental model that illustrates the basic principles and sets the optimization guideline remains elusive. We use a simple model to clarify how the energy generation mechanism is electrostatic induction but with a time-varying character that makes the optimal matching for power generation more restrictive. By combining multiple parameters into dimensionless variables, we pinpoint the optimum condition with only two independent parameters, leading to predictions of the maximum limit of power density, which allows us to derive the triboelectric material and device figure of merit. We reveal the importance of optimizing device capacitance, not only load resistance, and minimizing the impact of parasitic capacitance. Optimized capacitances can lead to an overall increase in power density of more than 10 times.

Using of material-technological modelling for designing production of closed die forgings

NASA Astrophysics Data System (ADS)

Ibrahim, K.; Vorel, I.; Jeníček, Š.; Káňa, J.; Aišman, D.; Kotěšovec, V.

2017-02-01

Production of forgings is a complex and demanding process which consists of a number of forging operations and, in many cases, includes post-forge heat treatment. An optimized manufacturing line is a prerequisite for obtaining prime-quality products which in turn are essential to profitable operation of a forging company. Problems may, however, arise from modifications to the manufacturing route due to changing customer needs. As a result, the production may have to be suspended temporarily to enable changeover and optimization. Using material-technological modelling, the required modifications can be tested and optimized under laboratory conditions outside the plant without disrupting the production. Thanks to material-technological modelling, the process parameters can be varied rapidly in response to changes in market requirements. Outcomes of the modelling runs include optimum parameters for the forging part’s manufacturing route, values of mechanical properties, and results of microstructure analysis. This article describes the use of material-technological modelling for exploring the impact of the amount of deformation and the rate of cooling of a particular forged part from the finish-forging temperature on its microstructure and related mechanical properties.

Pneumatic tyres interacting with deformable terrains

NASA Astrophysics Data System (ADS)

Bekakos, C. A.; Papazafeiropoulos, G.; O'Boy, D. J.; Prins, J.

2016-09-01

In this study, a numerical model of a deformable tyre interacting with a deformable road has been developed with the use of the finite element code ABAQUS (v. 6.13). Two tyre models with different widths, not necessarily identical to any real industry tyres, have been created purely for research use. The behaviour of these tyres under various vertical loads and different inflation pressures is studied, initially in contact with a rigid surface and then with a deformable terrain. After ensuring that the tyre model gives realistic results in terms of the interaction with a rigid surface, the rolling process of the tyre on a deformable road was studied. The effects of friction coefficient, inflation pressure, rebar orientation and vertical load on the overall performance are reported. Regarding the modelling procedure, a sequence of models were analysed, using the coupling implicit - explicit method. The numerical results reveal that not only there is significant dependence of the final tyre response on the various initial driving parameters, but also special conditions emerge, where the desired response of the tyre results from specific optimum combination of these parameters.

Learning to wait: A laboratory investigation

USGS Publications Warehouse

Oprea, R.; Friedman, D.; Anderson, S.T.

2009-01-01

Human subjects decide when to sink a fixed cost C to seize an irreversible investment opportunity whose value V is governed by Brownian motion. The optimal policy is to invest when V first crosses a threshold V* = (1 + w*) C, where the wait option premium w* depends on drift, volatility, and expiration hazard parameters. Subjects in the Low w* treatment on average invest at values quite close to optimum. Subjects in the two Medium and the High w* treatments invested at values below optimum, but with the predicted ordering, and values approached the optimum by the last block of 20 periods. ?? 2009 The Review of Economic Studies Limited.

A first course in optimum design of yacht sails

NASA Astrophysics Data System (ADS)

Sugimoto, Takeshi

1993-03-01

The optimum sail geometry is analytically obtained for the case of maximizing the thrust under equality and inequality constraints on the lift and the heeling moment. A single mainsail is assumed to be set close-hauled in uniform wind and upright on the flat sea surface. The governing parameters are the mast height and the gap between the sail foot and the sea surface. The lifting line theory is applied to analyze the aerodynamic forces acting on a sail. The design method consists of the variational principle and a feasibility study. Almost triangular sails are found to be optimum. Their advantages are discussed.

Optimisation of warpage on plastic injection moulding part using response surface methodology (RSM) and genetic algorithm method (GA)

NASA Astrophysics Data System (ADS)

Miza, A. T. N. A.; Shayfull, Z.; Nasir, S. M.; Fathullah, M.; Hazwan, M. H. M.

2017-09-01

In this study, Computer Aided Engineering was used for injection moulding simulation. The method of Design of experiment (DOE) was utilize according to the Latin Square orthogonal array. The relationship between the injection moulding parameters and warpage were identify based on the experimental data that used. Response Surface Methodology (RSM) was used as to validate the model accuracy. Then, the RSM and GA method were combine as to examine the optimum injection moulding process parameter. Therefore the optimisation of injection moulding is largely improve and the result shown an increasing accuracy and also reliability. The propose method by combining RSM and GA method also contribute in minimising the warpage from occur.

Fast and versatile fabrication of PMMA microchip electrophoretic devices by laser engraving.

PubMed

Moreira Gabriel, Ellen Flávia; Tomazelli Coltro, Wendell Karlos; Garcia, Carlos D

2014-08-01

This paper describes the effects of different modes and engraving parameters on the dimensions of microfluidic structures produced in PMMA using laser engraving. The engraving modes included raster and vector, while the explored engraving parameters included power, speed, frequency, resolution, line-width, and number of passes. Under the optimum conditions, the technique was applied to produce channels suitable for CE separations. Taking advantage of the possibility to cut-through the substrates, the laser was also used to define solution reservoirs (buffer, sample, and waste) and a PDMS-based decoupler. The final device was used to perform the analysis of a model mixture of phenolic compounds within 200 s with baseline resolution. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Determination of optimal tool parameters for hot mandrel bending of pipe elbows

NASA Astrophysics Data System (ADS)

Tabakajew, Dmitri; Homberg, Werner

2018-05-01

Seamless pipe elbows are important components in mechanical, plant and apparatus engineering. Typically, they are produced by the so-called `Hamburg process'. In this hot forming process, the initial pipes are subsequently pushed over an ox-horn-shaped bending mandrel. The geometric shape of the mandrel influences the diameter, bending radius and wall thickness distribution of the pipe elbow. This paper presents the numerical simulation model of the hot mandrel bending process created to ensure that the optimum mandrel geometry can be determined at an early stage. A fundamental analysis was conducted to determine the influence of significant parameters on the pipe elbow quality. The chosen methods and approach as well as the corresponding results are described in this paper.

Sustainable fisheries in shallow lakes: an independent empirical test of the Chinese mitten crab yield model

NASA Astrophysics Data System (ADS)

Wang, Haijun; Liang, Xiaomin; Wang, Hongzhu

2017-07-01

Next to excessive nutrient loading, intensive aquaculture is one of the major anthropogenic impacts threatening lake ecosystems. In China, particularly in the shallow lakes of mid-lower Changjiang (Yangtze) River, continuous overstocking of the Chinese mitten crab ( Eriocheir sinensis) could deteriorate water quality and exhaust natural resources. A series of crab yield models and a general optimum-stocking rate model have been established, which seek to benefit both crab culture and the environment. In this research, independent investigations were carried out to evaluate the crab yield models and modify the optimum-stocking model. Low percentage errors (average 47%, median 36%) between observed and calculated crab yields were obtained. Specific values were defined for adult crab body mass (135 g/ind.) and recapture rate (18% and 30% in lakes with submerged macrophyte biomass above and below 1 000 g/m2) to modify the optimum-stocking model. Analysis based on the modified optimum-stocking model indicated that the actual stocking rates in most lakes were much higher than the calculated optimum-stocking rates. This implies that, for most lakes, the current stocking rates should be greatly reduced to maintain healthy lake ecosystems.

Three-dimensional models of conventional and vertical junction laser-photovoltaic energy converters

NASA Technical Reports Server (NTRS)

Heinbockel, John H.; Walker, Gilbert H.

1988-01-01

Three-dimensional models of both conventional planar junction and vertical junction photovoltaic energy converters have been constructed. The models are a set of linear partial differential equations and take into account many photoconverter design parameters. The model is applied to Si photoconverters; however, the model may be used with other semiconductors. When used with a Nd laser, the conversion efficiency of the Si vertical junction photoconverter is 47 percent, whereas the efficiency for the conventional planar Si photoconverter is only 17 percent. A parametric study of the Si vertical junction photoconverter is then done in order to describe the optimum converter for use with the 1.06-micron Nd laser. The efficiency of this optimized vertical junction converter is 44 percent at 1 kW/sq cm.

Comparative studies on adsorptive removal of heavy metal ions by biosorbent, bio-char and activated carbon obtained from low cost agro-residue.

PubMed

Kırbıyık, Çisem; Pütün, Ayşe Eren; Pütün, Ersan

2016-01-01

In this study, Fe(III) and Cr(III) metal ion adsorption processes were carried out with three adsorbents in batch experiments and their adsorption performance was compared. These adsorbents were sesame stalk without pretreatment, bio-char derived from thermal decomposition of biomass, and activated carbon which was obtained from chemical activation of biomass. Scanning electron microscopy and Fourier transform-infrared techniques were used for characterization of adsorbents. The optimum conditions for the adsorption process were obtained by observing the influences of solution pH, adsorbent dosage, initial solution concentration, contact time and temperature. The optimum adsorption efficiencies were determined at pH 2.8 and pH 4.0 for Fe(III) and Cr(III) metal ion solutions, respectively. The experimental data were modelled by different isotherm models and the equilibriums were well described by the Langmuir adsorption isotherm model. The pseudo-first-order, pseudo-second-order kinetic, intra-particle diffusion and Elovich models were applied to analyze the kinetic data and to evaluate rate constants. The pseudo-second-order kinetic model gave a better fit than the others. The thermodynamic parameters, such as Gibbs free energy change ΔG°, standard enthalpy change ΔH° and standard entropy change ΔS° were evaluated. The thermodynamic study showed the adsorption was a spontaneous endothermic process.

Influence of the Configuration Elements of a Model of a Supersonic Passenger Aircraft on the Parameters of Sonic Boom

NASA Astrophysics Data System (ADS)

Volkov, V. F.

2017-03-01

The author gives results of parametric calculations of shock-boom levels in the case of flow with a free-stream Mach number of 2.03 past configurations of a supersonic aircraft. The calculations are aimed at investigating the influence of the relative position of basic elements and their geometric shape on the aerodynamic quality of the configuration and on the parameters of shock boom at great distances from the perturbation source. The geometric models of the configurations were formed by combining and joining component elements: the body, the front wing, and the rear tapered wing with root dogtooth extension. From an analysis of all the considered models of tandem configurations with account of the resolvability of shock waves in a perturbed profile compared to the monoplane configuration, the optimum configuration has been singled out that ensures a reduction of 24% in the intensity level of shock boom with an increase of 0.24% in its aerodynamic quality.

Optimization of automotive Rankine cycle waste heat recovery under various engine operating condition

NASA Astrophysics Data System (ADS)

Punov, Plamen; Milkov, Nikolay; Danel, Quentin; Perilhon, Christelle; Podevin, Pierre; Evtimov, Teodossi

2017-02-01

An optimization study of the Rankine cycle as a function of diesel engine operating mode is presented. The Rankine cycle here, is studied as a waste heat recovery system which uses the engine exhaust gases as heat source. The engine exhaust gases parameters (temperature, mass flow and composition) were defined by means of numerical simulation in advanced simulation software AVL Boost. Previously, the engine simulation model was validated and the Vibe function parameters were defined as a function of engine load. The Rankine cycle output power and efficiency was numerically estimated by means of a simulation code in Python(x,y). This code includes discretized heat exchanger model and simplified model of the pump and the expander based on their isentropic efficiency. The Rankine cycle simulation revealed the optimum value of working fluid mass flow and evaporation pressure according to the heat source. Thus, the optimal Rankine cycle performance was obtained over the engine operating map.

Changing space and sound: Parametric design and variable acoustics

NASA Astrophysics Data System (ADS)

Norton, Christopher William

This thesis examines the potential for parametric design software to create performance based design using acoustic metrics as the design criteria. A former soundstage at the University of Southern California used by the Thornton School of Music is used as a case study for a multiuse space for orchestral, percussion, master class and recital use. The criteria used for each programmatic use include reverberation time, bass ratio, and the early energy ratios of the clarity index and objective support. Using a panelized ceiling as a design element to vary the parameters of volume, panel orientation and type of absorptive material, the relationships between these parameters and the design criteria are explored. These relationships and subsequently derived equations are applied to Grasshopper parametric modeling software for Rhino 3D (a NURBS modeling software). Using the target reverberation time and bass ratio for each programmatic use as input for the parametric model, the genomic optimization function of Grasshopper - Galapagos - is run to identify the optimum ceiling geometry and material distribution.

Structure-activity relationships for serotonin transporter and dopamine receptor selectivity.

PubMed

Agatonovic-Kustrin, Snezana; Davies, Paul; Turner, Joseph V

2009-05-01

Antipsychotic medications have a diverse pharmacology with affinity for serotonergic, dopaminergic, adrenergic, histaminergic and cholinergic receptors. Their clinical use now also includes the treatment of mood disorders, thought to be mediated by serotonergic receptor activity. The aim of our study was to characterise the molecular properties of antipsychotic agents, and to develop a model that would indicate molecular specificity for the dopamine (D(2)) receptor and the serotonin (5-HT) transporter. Back-propagation artificial neural networks (ANNs) were trained on a dataset of 47 ligands categorically assigned antidepressant or antipsychotic utility. The structure of each compound was encoded with 63 calculated molecular descriptors. ANN parameters including hidden neurons and input descriptors were optimised based on sensitivity analyses, with optimum models containing between four and 14 descriptors. Predicted binding preferences were in excellent agreement with clinical antipsychotic or antidepressant utility. Validated models were further tested by use of an external prediction set of five drugs with unknown mechanism of action. The SAR models developed revealed the importance of simple molecular characteristics for differential binding to the D(2) receptor and the 5-HT transporter. These included molecular size and shape, solubility parameters, hydrogen donating potential, electrostatic parameters, stereochemistry and presence of nitrogen. The developed models and techniques employed are expected to be useful in the rational design of future therapeutic agents.

Novozyme 435-catalyzed asymmetric acylation of (R, S)-3-n- butylphthalide in hexane.

PubMed

He, Laping; Li, Cuiqin; Gao, Bing

2009-01-01

The asymmetric acylation of (R, S)-3-n-butylphthalide could be efficiently catalyzed by Novozyme 435. The effect of various reaction parameters such as water activity, temperature, molar ratio of acetic anhydride to (R, S)-3-n-butylphthalide, and reaction time on the asymmetric acylation were studied. The optimums of the reaction parameters were water activity 0.62, temperature 30 degrees C, molar ratio of acetic anhydride to (R, S)-3-n-butylphthalide 8:1, and reaction time 48 h, respectively. Under the optimum conditions, enantiopure 3-n-butylphthalide with an optical purity of 95.7% enantiomeric excess and 49.1% yield could be obtained. Furthermore, the enantiomeric excess of product was over 98%.

Three-meter telescope study

NASA Technical Reports Server (NTRS)

Wissinger, A.; Scott, R. M.; Peters, W.; Augustyn, W., Jr.; Arnold, R.; Offner, A.; Damast, M.; Boyce, B.; Kinnaird, R.; Mangus, J. D.

1971-01-01

A means is presented whereby the effect of various changes in the most important parameters of a three meter aperature space astronomy telescope can be evaluated to determine design trends and to optimize the optical design configuration. Methods are defined for evaluating the theoretical optical performance of axisymmetric, centrally obscured telescopes based upon the intended astronomy research usage. A series of design parameter variations is presented to determine the optimum telescope configuration. The design optimum requires very fast primary mirrors, so the study also examines the current state of the art in fabricating large, fast primary mirrors. The conclusion is that a 3-meter primary mirror having a focal ratio as low as f/2 is feasible using currently established techniques.

Experimental investigation of optimum beam size for FSO uplink

NASA Astrophysics Data System (ADS)

Kaushal, Hemani; Kaddoum, Georges; Jain, Virander Kumar; Kar, Subrat

2017-10-01

In this paper, the effect of transmitter beam size on the performance of free space optical (FSO) communication has been determined experimentally. Irradiance profile for varying turbulence strength is obtained using optical turbulence generating (OTG) chamber inside laboratory environment. Based on the results, an optimum beam size is investigated using the semi-analytical method. Moreover, the combined effects of atmospheric scintillation and beam wander induced pointing errors are considered in order to determine the optimum beam size that minimizes the bit error rate (BER) of the system for a fixed transmitter power and link length. The results show that the optimum beam size for FSO uplink depends upon Fried parameter and outer scale of the turbulence. Further, it is observed that the optimum beam size increases with the increase in zenith angle but has negligible effect with the increase in fade threshold level at low turbulence levels and has a marginal effect at high turbulence levels. Finally, the obtained outcome is useful for FSO system design and BER performance analysis.

Optimization of Bleaching Parameters in Refining Process of Kenaf Seed Oil with a Central Composite Design Model.

PubMed

Chew, Sook Chin; Tan, Chin Ping; Nyam, Kar Lin

2017-07-01

Kenaf seed oil has been suggested to be used as nutritious edible oil due to its unique fatty acid composition and nutritional value. The objective of this study was to optimize the bleaching parameters of the chemical refining process for kenaf seed oil, namely concentration of bleaching earth (0.5 to 2.5% w/w), temperature (30 to 110 °C) and time (5 to 65 min) based on the responses of total oxidation value (TOTOX) and color reduction using response surface methodology. The results indicated that the corresponding response surface models were highly statistical significant (P < 0.0001) and sufficient to describe and predict TOTOX value and color reduction with R 2 of 0.9713 and 0.9388, respectively. The optimal parameters in the bleaching stage of kenaf seed oil were: 1.5% w/w of the concentration of bleaching earth, temperature of 70 °C, and time of 40 min. These optimum parameters produced bleached kenaf seed oil with TOTOX value of 8.09 and color reduction of 32.95%. There were no significant differences (P > 0.05) between experimental and predicted values, indicating the adequacy of the fitted models. © 2017 Institute of Food Technologists®.

Conservation tillage, optimal water and organic nutrient supply enhance soil microbial activities during wheat (Triticum Aestivum L.) cultivation

PubMed Central

Sharma, Pankaj; Singh, Geeta; Singh, Rana P.

2011-01-01

The field experiments were conducted on sandy loam soil at New Delhi, during 2007 and 2008 to investigate the effect of conservation tillage, irrigation regimes (sub-optimal, optimal and supra-optimal water regimes), and integrated nutrient management (INM) practices on soil biological parameters in wheat cultivation. The conservation tillage soils has shown significant (p<0.05) increase in soil respiration (81.1%), soil microbial biomass carbon (SMBC) (104%) and soil dehydrogenase (DH) (59.2%) compared to the conventional tillage soil. Optimum water supply (3-irrigations) enhanced soil respiration over sub-optimum and supra-optimum irrigations by 13.32% and 79% respectively. Soil dehydrogenase (DH) activity in optimum water regime has also increased by 23.33% and 8.18% respectively over the other two irrigation regimes. Similarly, SMBC has also increased by 12.14% and 27.17% respectively in soil with optimum water supply compared to that of sub-optimum and supra-optimum water regime fields. The maximum increase in soil microbial activities is found when sole organic source (50% Farm Yard Manure+25% biofertilizer+25% Green Manure) has been used in combination with the conservation tillage and the optimum water supply. Study demonstrated that microbial activity could be regulated by tillage, water and nitrogen management in the soil in a sustainable manner. PMID:24031665

Experimental Study of Characteristics of Micro-Hole Porous Skins for Turbulent Skin Friction Reduction

NASA Technical Reports Server (NTRS)

Hwang, Danny P.

2002-01-01

Characteristics of micro-hole porous skins for the turbulent skin friction reduction technology called the micro-blowing technique (MBT) were assessed experimentally at Mach 0.4 and blowing fractions from zero to 0.005. The objective of this study was to provide guidelines for the selection of porous plates for MBT. The hole angle, pattern, diameter, aspect ratio, and porosity were the parameters considered for this study. The additional effort to angle and stagger the holes was experimentally determined to be unwarranted in terms of skin friction benefit; therefore, these parameters were systematically eliminated from the parametric study. The impact of the remaining three parameters was evaluated by fixing two parameters at the reference values while varying the third parameter. The best hole-diameter Reynolds number was found to be around 400, with an optimum aspect ratio of about 6. The optimum porosity was not conclusively discerned because the range of porosities in the test plates considered was not great enough. However, the porosity was estimated to be about 15 percent or less.

Tuned dynamics stabilizes an idealized regenerative axial-torsional model of rotary drilling

NASA Astrophysics Data System (ADS)

Gupta, Sunit K.; Wahi, Pankaj

2018-01-01

We present an exact stability analysis of a dynamical system idealizing rotary drilling. This system comprises lumped parameter axial-torsional modes of the drill-string coupled via the cutting forces and torques. The kinematics of cutting is modeled through a functional description of the cut surface which evolves as per a partial differential equation (PDE). Linearization of this model is straightforward as opposed to the traditional state-dependent delay (SDDE) model and both the approaches result in the same characteristic equation. A systematic study on the key system parameters influencing the stability characteristics reveals that torsional damping is very critical and stable drilling is, in general, not possible in its absence. The stable regime increases as the natural frequency of the axial mode approaches that of the torsional mode and a 1:1 internal resonance leads to a significant improvement in the system stability. Hence, from a practical point of view, a drill-string with 1:1 internal resonance is desirable to avoid vibrations during rotary drilling. For the non-resonant case, axial damping reduces the stable range of operating parameters while for the resonant case, an optimum value of axial damping (equal to the torsional damping) results in the largest stable regime. Interestingly, the resonant (tuned) system has a significant parameter regime corresponding to stable operation even in the absence of damping.

Isotherm Modelling, Kinetic Study and Optimization of Batch Parameters Using Response Surface Methodology for Effective Removal of Cr(VI) Using Fungal Biomass

PubMed Central

Chidambaram, Ramalingam

2015-01-01

Biosorption is a promising alternative method to replace the existing conventional technique for Cr(VI) removal from the industrial effluent. In the present experimental design, the removal of Cr(VI) from the aqueous solution was studied by Aspergillus niger MSR4 under different environmental conditions in the batch systems. The optimum conditions of biosorption were determined by investigating pH (2.0) and temperature (27°C). The effects of parameters such as biomass dosage (g/L), initial Cr(VI) concentration (mg/L) and contact time (min) on Cr(VI) biosorption were analyzed using a three parameter Box–Behnken design (BBD). The experimental data well fitted to the Langmuir isotherm, in comparison to the other isotherm models tested. The results of the D-R isotherm model suggested that a chemical ion-exchange mechanism was involved in the biosorption process. The biosorption process followed the pseudo-second-order kinetic model, which indicates that the rate limiting step is chemisorption process. Fourier transform infrared (FT-IR) spectroscopic studies revealed the possible involvement of functional groups, such as hydroxyl, carboxyl, amino and carbonyl group in the biosorption process. The thermodynamic parameters for Cr(VI) biosorption were also calculated, and the negative ∆Gº values indicated the spontaneous nature of biosorption process. PMID:25786227

Prototyping of Dental Structures Using Laser Milling

NASA Astrophysics Data System (ADS)

Andreev, A. O.; Kosenko, M. S.; Petrovskiy, V. N.; Mironov, V. D.

2016-02-01

The results of experimental studies of the effect of an ytterbium fiber laser radiation parameters on processing efficiency and quality of ZrO2 ceramics widely used in stomatology are presented. Laser operating conditions with optimum characteristics for obtaining high quality final surfaces and rapid material removal of dental structures are determined. The ability of forming thin-walled ceramic structures by laser milling technology (a minimum wall thickness of 50 μm) is demonstrated. The examples of three-dimensional dental structures created in computer 3D-models of human teeth using laser milling are shown.

Shape Optimization of Rubber Bushing Using Differential Evolution Algorithm

PubMed Central

2014-01-01

The objective of this study is to design rubber bushing at desired level of stiffness characteristics in order to achieve the ride quality of the vehicle. A differential evolution algorithm based approach is developed to optimize the rubber bushing through integrating a finite element code running in batch mode to compute the objective function values for each generation. Two case studies were given to illustrate the application of proposed approach. Optimum shape parameters of 2D bushing model were determined by shape optimization using differential evolution algorithm. PMID:25276848

Biaxial strain in graphene adhered to shallow depressions.

PubMed

Metzger, Constanze; Rémi, Sebastian; Liu, Mengkun; Kusminskiy, Silvia V; Castro Neto, Antonio H; Swan, Anna K; Goldberg, Bennett B

2010-01-01

Measurements on graphene exfoliated over a substrate prepatterned with shallow depressions demonstrate that graphene does not remain free-standing but instead adheres to the substrate despite the induced biaxial strain. The strain is homogeneous over the depression bottom as determined by Raman measurements. We find higher Raman shifts and Gruneisen parameters of the phonons underlying the G and 2D bands under biaxial strain than previously reported. Interference modeling is used to determine the vertical position of the graphene and to calculate the optimum dielectric substrate stack for maximum Raman signal.

Experimental and Numerical Analysis of Screw Fixation in Anterior Cruciate Ligament Reconstruction

NASA Astrophysics Data System (ADS)

Chizari, Mahmoud; Wang, Bin; Snow, Martyn; Barrett, Mel

2008-09-01

This paper reports the results of an experimental and finite element analysis of tibial screw fixation in anterior cruciate ligament (ACL) reconstruction. The mechanical properties of the bone and tendon graft are obtained from experiments using porcine bone and bovine tendon. The results of the numerical study are compared with those from mechanical testing. Analysis shows that the model may be used to establish the optimum placement of the tunnel in anterior cruciate ligament reconstruction by predicting mechanical parameters such as stress, strain and displacement at regions in the tunnel wall.

The assessment of UV resources over Northern Eurasia

NASA Astrophysics Data System (ADS)

Chubarova, Natalia; Zhdanova, Yekaterina

2013-05-01

The spatial and temporal distribution of UV resources was assessed over Northern Eurasia by using RT modeling (8 stream DISORT RT code) with 1×1 degree grid and month resolution. For this purpose a special dataset of main input geophysical parameters (total ozone content, aerosol characteristics, surface UV albedo, and UV cloud modification factor) has been developed. To define the UV resources both erythemally-weighted and vitamin D irradiances were used. In order to better quantify vitamin D irradiance threshold we accounted for a body exposure fraction S as a function of surface effective temperature. The UV resources are defined by using several classes and subclasses: UV deficiency, UV optimum, and UV excess. They were evaluated for clear and typical cloudy conditions for different skin types. We show that for typical cloudy conditions in winter (January) there are only few regions in Europe at the south of Spain (southward 43°N) with conditions of UV optimum for people with skin type 2 and no such conditions for people with skin type 4. In summer (July) UV optimum for skin 2 is observed northward 63°N with a boundary biased towards higher latitudes at the east, while for skin type 4 these conditions are observed over the most territory of Northern Eurasia.

Enzymatic synthesis of farnesyl laurate in organic solvent: initial water activity, kinetics mechanism, optimization of continuous operation using packed bed reactor and mass transfer studies.

PubMed

Rahman, N K; Kamaruddin, A H; Uzir, M H

2011-08-01

The influence of water activity and water content was investigated with farnesyl laurate synthesis catalyzed by Lipozyme RM IM. Lipozyme RM IM activity depended strongly on initial water activity value. The best results were achieved for a reaction medium with an initial water activity of 0.11 since it gives the best conversion value of 96.80%. The rate constants obtained in the kinetics study using Ping-Pong-Bi-Bi and Ordered-Bi-Bi mechanisms with dead-end complex inhibition of lauric acid were compared. The corresponding parameters were found to obey the Ordered-Bi-Bi mechanism with dead-end complex inhibition of lauric acid. Kinetic parameters were calculated based on this model as follows: V (max) = 5.80 mmol l(-1) min(-1) g enzyme(-1), K (m,A) = 0.70 mmol l(-1) g enzyme(-1), K (m,B) = 115.48 mmol l(-1) g enzyme(-1), K (i) = 11.25 mmol l(-1) g enzyme(-1). The optimum conditions for the esterification of farnesol with lauric acid in a continuous packed bed reactor were found as the following: 18.18 cm packed bed height and 0.9 ml/min substrate flow rate. The optimum molar conversion of lauric acid to farnesyl laurate was 98.07 ± 0.82%. The effect of mass transfer in the packed bed reactor has also been studied using two models for cases of reaction limited and mass transfer limited. A very good agreement between the mass transfer limited model and the experimental data obtained indicating that the esterification in a packed bed reactor was mass transfer limited.

Determination of kinetic parameters of 1,3-propanediol fermentation by Clostridium diolis using statistically optimized medium.

PubMed

Kaur, Guneet; Srivastava, Ashok K; Chand, Subhash

2012-09-01

1,3-propanediol (1,3-PD) is a chemical compound of immense importance primarily used as a raw material for fiber and textile industry. It can be produced by the fermentation of glycerol available abundantly as a by-product from the biodiesel plant. The present study was aimed at determination of key kinetic parameters of 1,3-PD fermentation by Clostridium diolis. Initial experiments on microbial growth inhibition were followed by optimization of nutrient medium recipe by statistical means. Batch kinetic data from studies in bioreactor using optimum concentration of variables obtained from statistical medium design was used for estimation of kinetic parameters of 1,3-PD production. Direct use of raw glycerol from biodiesel plant without any pre-treatment for 1,3-PD production using this strain investigated for the first time in this work gave results comparable to commercial glycerol. The parameter values obtained in this study would be used to develop a mathematical model for 1,3-PD to be used as a guide for designing various reactor operating strategies for further improving 1,3-PD production. An outline of protocol for model development has been discussed in the present work.

Experimental and Mathematical Modeling for Prediction of Tool Wear on the Machining of Aluminium 6061 Alloy by High Speed Steel Tools

NASA Astrophysics Data System (ADS)

Okokpujie, Imhade Princess; Ikumapayi, Omolayo M.; Okonkwo, Ugochukwu C.; Salawu, Enesi Y.; Afolalu, Sunday A.; Dirisu, Joseph O.; Nwoke, Obinna N.; Ajayi, Oluseyi O.

2017-12-01

In recent machining operation, tool life is one of the most demanding tasks in production process, especially in the automotive industry. The aim of this paper is to study tool wear on HSS in end milling of aluminium 6061 alloy. The experiments were carried out to investigate tool wear with the machined parameters and to developed mathematical model using response surface methodology. The various machining parameters selected for the experiment are spindle speed (N), feed rate (f), axial depth of cut (a) and radial depth of cut (r). The experiment was designed using central composite design (CCD) in which 31 samples were run on SIEG 3/10/0010 CNC end milling machine. After each experiment the cutting tool was measured using scanning electron microscope (SEM). The obtained optimum machining parameter combination are spindle speed of 2500 rpm, feed rate of 200 mm/min, axial depth of cut of 20 mm, and radial depth of cut 1.0mm was found out to achieved the minimum tool wear as 0.213 mm. The mathematical model developed predicted the tool wear with 99.7% which is within the acceptable accuracy range for tool wear prediction.

[Optimization of succinic acid fermentation with Actinobacillus succinogenes by response surface methodology].

PubMed

Shen, Naikun; Qin, Yan; Wang, Qingyan; Xie, Nengzhong; Mi, Huizhi; Zhu, Qixia; Liao, Siming; Huang, Ribo

2013-10-01

Succinic acid is an important C4 platform chemical in the synthesis of many commodity and special chemicals. In the present work, different compounds were evaluated for succinic acid production by Actinobacillus succinogenes GXAS 137. Important parameters were screened by the single factor experiment and Plackeet-Burman design. Subsequently, the highest production of succinic acid was approached by the path of steepest ascent. Then, the optimum values of the parameters were obtained by Box-Behnken design. The results show that the important parameters were glucose, yeast extract and MgCO3 concentrations. The optimum condition was as follows (g/L): glucose 70.00, yeast extract 9.20 and MgCO3 58.10. Succinic acid yield reached 47.64 g/L at the optimal condition. Succinic acid increased by 29.14% than that before the optimization (36.89 g/L). Response surface methodology was proven to be a powerful tool to optimize succinic acid production.

A study of the parameters affecting the effectiveness of Moringa oleifera in drinking water purification

NASA Astrophysics Data System (ADS)

Pritchard, M.; Craven, T.; Mkandawire, T.; Edmondson, A. S.; O'Neill, J. G.

The powder obtained from the seeds of the Moringa oleifera tree has been shown to be an effective primary coagulant for water treatment. When the seeds are dried, dehusked, crushed and added to water, the powder acts as a coagulant binding colloidal particles and bacteria to form agglomerated particles (flocs), which settle allowing the clarified supernatant to be poured off. Very little research has been undertaken on the parameters affecting the effectiveness of M. oleifera, especially in Malawi, for purification of drinking water and there is a great need for further testing in this area. Conclusive data needs to be compiled to demonstrate the effects of various water parameters have on the efficiency of the seeds. A parametric study was undertaken at Leeds Metropolitan University, UK, with the aim to establish the most appropriate dosing method; the optimum dosage for removal of turbidity; the influence of pH and temperature; together with the shelf life of the M. oleifera seeds. The study revealed that the most suitable dosing method was to mix the powder into a concentrated paste, hence forming a stock suspension. The optimum M. oleifera dose, for turbidity values between 40 and 200 NTU, ranged between 30 and 55 mg/l. With turbidity set at 130 NTU and a M. oleifera dose within the optimum range at 50 mg/l, pH levels were varied between 4 and 9. It was discovered that the coagulant performance was not too sensitive to pH fluctuations when conditions were within the optimum range. The most efficient coagulation, determined by the greatest reduction in turbidity, occurred at pH 6.5. Alkaline conditions were overall more favourable than acidic conditions; pH 9 had an efficiency of 65% of optimum, whilst at pH 5 the efficiency dropped to around 55%. The efficiency further dropped at pH 4, where the powder only produced results of around 10% of optimum conditions. A temperature range of 4-60 °C was studied in this research. Colder waters (<15 °C) were found to hinder the effectiveness of the coagulation process. The higher the temperature the more effective was the coagulation. It was also found that the age of the seeds, up to 18 months, did not have any noticeable effect on dose level and percentage reduction in turbidity, although at 18 months the seeds had a narrower dosing range to produce near-optimum reduction. Seeds aged 24 months showed a significant decline in coagulant efficiency.

White Gaussian Noise - Models for Engineers

NASA Astrophysics Data System (ADS)

Jondral, Friedrich K.

2018-04-01

This paper assembles some information about white Gaussian noise (WGN) and its applications. It starts from a description of thermal noise, i. e. the irregular motion of free charge carriers in electronic devices. In a second step, mathematical models of WGN processes and their most important parameters, especially autocorrelation functions and power spectrum densities, are introduced. In order to proceed from mathematical models to simulations, we discuss the generation of normally distributed random numbers. The signal-to-noise ratio as the most important quality measure used in communications, control or measurement technology is accurately introduced. As a practical application of WGN, the transmission of quadrature amplitude modulated (QAM) signals over additive WGN channels together with the optimum maximum likelihood (ML) detector is considered in a demonstrative and intuitive way.

Optimization of Well Configuration for a Sedimentary Enhanced Geothermal Reservoir

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

Zhou, Mengnan; Cho, JaeKyoung; Zerpa, Luis E.

The extraction of geothermal energy in the form of hot water from sedimentary rock formations could expand the current geothermal energy resources toward new regions. From previous work, we observed that sedimentary geothermal reservoirs with relatively low permeability would require the application of enhancement techniques (e.g., well hydraulic stimulation) to achieve commercial production/injection rates. In this paper we extend our previous work to develop a methodology to determine the optimum well configuration that maximizes the hydraulic performance of the geothermal system. The geothermal systems considered consist of one vertical well doublet system with hydraulic fractures, and three horizontal well configurationsmore » with open-hole completion, longitudinal fractures and transverse fractures, respectively. A commercial thermal reservoir simulation is used to evaluate the geothermal reservoir performance using as design parameters the well spacing and the length of the horizontal wells. The results obtained from the numerical simulations are used to build a response surface model based on the multiple linear regression method. The optimum configuration of the sedimentary geothermal systems is obtained from the analysis of the response surface model. The proposed methodology is applied to a case study based on a reservoir model of the Lyons sandstone formation, located in the Wattenberg field, Denver-Julesburg basin, Colorado.« less

Biodegradation of toluene vapor in coir based upflow packed bed reactor by Trichoderma asperellum isolate.

PubMed

Gopinath, M; Mohanapriya, C; Sivakumar, K; Baskar, G; Muthukumaran, C; Dhanasekar, R

2016-03-01

In the present study, a new biofiltration system involving a selective microbial strain isolated from aerated municipal sewage water attached with coir as packing material was developed for toluene degradation. The selected fungal isolate was identified as Trichoderma asperellum by 16S ribosomal RNA (16S rRNA) sequencing method, and pylogenetic tree was constructed using BLASTn search. Effect of various factors on growth and toluene degradation by newly isolated T. asperellum was studied in batch studies, and the optimum conditions were found to be pH 7.0, temperature 30 °C, and initial toluene concentration 1.5 (v/v)%. Continuous removal of gaseous toluene was monitored in upflow packed bed reactor (UFPBR) using T. asperellum. Effect of various parameters like column height, flow rate, and the inlet toluene concentration were studied to evaluate the performance of the biofilter. The maximum elimination capacity (257 g m(-3) h(-1)) was obtained with the packing height of 100 cm with the empty bed residence time of 5 min. Under these optimum conditions, the T. asperellum showed better toluene removal efficiency. Kinetic models have been developed for toluene degradation by T. asperellum using macrokinetic approach of the plug flow model incorporated with Monod model.

Light intensity alters the extent of arsenic toxicity in Helianthus annuus L. seedlings.

PubMed

Yadav, Geeta; Srivastava, Prabhat Kumar; Singh, Vijay Pratap; Prasad, Sheo Mohan

2014-06-01

The present study is aimed at assessing the extent of arsenic (As) toxicity under three different light intensities-optimum (400 μmole photon m(-2) s(-1)), sub-optimum (225 μmole photon m(-2) s(-1)), and low (75 μmole photon m(-2) s(-1))-exposed to Helianthus annuus L. var. DRSF-113 seedlings by examining various physiological and biochemical parameters. Irrespective of the light intensities under which H. annuus L. seedlings were grown, there was an As dose (low, i.e., 6 mg kg(-1) soil, As1; and high, i.e., 12 mg kg(-1) soil, As2)-dependent decrease in all the growth parameters, viz., fresh mass, shoot length, and root length. Optimum light-grown seedlings exhibited better growth performance than the sub-optimum and low light-grown seedlings; however, low light-grown plants had maximum root and shoot lengths. Accumulation of As in the plant tissues depended upon its concentration used, proximity of the plant tissue, and intensity of the light. Greater intensity of light allowed greater assimilation of photosynthates accompanied by more uptake of nutrients along with As from the medium. The levels of chlorophyll a, b, and carotenoids declined with increasing concentrations of As. Seedlings acquired maximum Chl a and b under optimum light which were more compatible to face As1 and As2 doses of As, also evident from the overall status of enzymatic (SOD, POD, CAT, and GST) and non-enzymatic antioxidant (Pro).

An Experimental Study of Dependence of Optimum TBM Cutter Spacing on Pre-set Penetration Depth in Sandstone Fragmentation

NASA Astrophysics Data System (ADS)

Han, D. Y.; Cao, P.; Liu, J.; Zhu, J. B.

2017-12-01

Cutter spacing is an essential parameter in the TBM design. However, few efforts have been made to study the optimum cutter spacing incorporating penetration depth. To investigate the influence of pre-set penetration depth and cutter spacing on sandstone breakage and TBM performance, a series of sequential laboratory indentation tests were performed in a biaxial compression state. Effects of parameters including penetration force, penetration depth, chip mass, chip size distribution, groove volume, specific energy and maximum angle of lateral crack were investigated. Results show that the total mass of chips, the groove volume and the observed optimum cutter spacing increase with increasing pre-set penetration depth. It is also found that the total mass of chips could be an alternative means to determine optimum cutter spacing. In addition, analysis of chip size distribution suggests that the mass of large chips is dominated by both cutter spacing and pre-set penetration depth. After fractal dimension analysis, we found that cutter spacing and pre-set penetration depth have negligible influence on the formation of small chips and that small chips are formed due to squeezing of cutters and surface abrasion caused by shear failure. Analysis on specific energy indicates that the observed optimum spacing/penetration ratio is 10 for the sandstone, at which, the specific energy and the maximum angle of lateral cracks are smallest. The findings in this paper contribute to better understanding of the coupled effect of cutter spacing and pre-set penetration depth on TBM performance and rock breakage, and provide some guidelines for cutter arrangement.

Warpage investigation on side arms using response surface methodology (RSM) and glow-worm swarm optimizations (GSO)

NASA Astrophysics Data System (ADS)

Sow, C. K.; Fathullah, M.; Nasir, S. M.; Shayfull, Z.; Shazzuan, S.

2017-09-01

This paper discusses on an analysis run via injection moulding process in determination of the optimum processing parameters used for manufacturing side arms of catheters in minimizing the warpage issues. The optimization method used was RSM. Moreover, in this research tries to find the most significant factor affecting the warpage. From the previous literature review,4 most significant parameters on warpage defect was selected. Those parameters were melt temperature, packing time, packing pressure, mould temperature and cooling time. At the beginning, side arm was drawn using software of CATIA V5. Then, software Mouldflow and Design Expert were employed to analyses on the popular warpage issues. After that, GSO artificial intelligence was apply using the mathematical model from Design Expert for more optimization on RSM result. Recommended parameter settings from the simulation work were then compared with the optimization work of RSM and GSO. The result show that the warpage on the side arm was improved by 3.27 %

Genetic algorithms for the application of Activated Sludge Model No. 1.

PubMed

Kim, S; Lee, H; Kim, J; Kim, C; Ko, J; Woo, H; Kim, S

2002-01-01

The genetic algorithm (GA) has been integrated into the IWA ASM No. 1 to calibrate important stoichiometric and kinetic parameters. The evolutionary feature of GA was used to configure the multiple local optima as well as the global optimum. The objective function of optimization was designed to minimize the difference between estimated and measured effluent concentrations at the activated sludge system. Both steady state and dynamic data of the simulation benchmark were used for calibration using denitrification layout. Depending upon the confidence intervals and objective functions, the proposed method provided distributions of parameter space. Field data have been collected and applied to validate calibration capacity of GA. Dynamic calibration was suggested to capture periodic variations of inflow concentrations. Also, in order to verify this proposed method in real wastewater treatment plant, measured data sets for substrate concentrations were obtained from Haeundae wastewater treatment plant and used to estimate parameters in the dynamic system. The simulation results with calibrated parameters matched well with the observed concentrations of effluent COD.

The behavior of gain and saturation characteristics versus temperature in a copper bromide laser

NASA Astrophysics Data System (ADS)

Mohammadpour Lima, S.; Behrouzinia, S.; Salem, M. K.; Elahei, M.; Khorasani, K.; Dorranian, D.

2017-05-01

A pair of copper bromide lasers in an oscillator-amplifier configuration was used to investigate the temperature dependence of the small-signal gain, saturation intensity, and output power of the laser. The observations were explained in terms of the electron temperature and energy levels of transition. An optimum electrical input power of 1.6 kW and a corresponding operational temperature of 510 °C were determined for the maximum values of these parameters. The balance between the microscopic parameters, such as stimulated emission cross-section, laser upper-level lifetime, and population inversion, which determine the behavior of the amplifying parameters and laser output power with respect to the operational temperature, has been investigated. We used the steady-state rate equation from the Hargrove model to determine the amplifying parameters, instead of the Frantz-Nodvik formula. The power extracted from the amplifier exceeds that achieved with the same device as the oscillator by more than 60%.

SVD-aided pseudo principal-component analysis: A new method to speed up and improve determination of the optimum kinetic model from time-resolved data

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

Oang, Key Young; Yang, Cheolhee; Muniyappan, Srinivasan

Determination of the optimum kinetic model is an essential prerequisite for characterizing dynamics and mechanism of a reaction. Here, we propose a simple method, termed as singular value decomposition-aided pseudo principal-component analysis (SAPPA), to facilitate determination of the optimum kinetic model from time-resolved data by bypassing any need to examine candidate kinetic models. We demonstrate the wide applicability of SAPPA by examining three different sets of experimental time-resolved data and show that SAPPA can efficiently determine the optimum kinetic model. In addition, the results of SAPPA for both time-resolved X-ray solution scattering (TRXSS) and transient absorption (TA) data of themore » same protein reveal that global structural changes of protein, which is probed by TRXSS, may occur more slowly than local structural changes around the chromophore, which is probed by TA spectroscopy.« less

Production Process of Biocompatible Magnesium Alloy Tubes Using Extrusion and Dieless Drawing Processes

NASA Astrophysics Data System (ADS)

Kustra, Piotr; Milenin, Andrij; Płonka, Bartłomiej; Furushima, Tsuyoshi

2016-06-01

Development of technological production process of biocompatible magnesium tubes for medical applications is the subject of the present paper. The technology consists of two stages—extrusion and dieless drawing process, respectively. Mg alloys for medical applications such as MgCa0.8 are characterized by low technological plasticity during deformation that is why optimization of production parameters is necessary to obtain good quality product. Thus, authors developed yield stress and ductility model for the investigated Mg alloy and then used the numerical simulations to evaluate proper manufacturing conditions. Grid Extrusion3d software developed by authors was used to determine optimum process parameters for extrusion—billet temperature 400 °C and extrusion velocity 1 mm/s. Based on those parameters the tube with external diameter 5 mm without defects was manufactured. Then, commercial Abaqus software was used for modeling dieless drawing. It was shown that the reduction in the area of 60% can be realized for MgCa0.8 magnesium alloy. Tubes with the final diameter of 3 mm were selected as a case study, to present capabilities of proposed processes.

Iterative optimization method for design of quantitative magnetization transfer imaging experiments.

PubMed

Levesque, Ives R; Sled, John G; Pike, G Bruce

2011-09-01

Quantitative magnetization transfer imaging (QMTI) using spoiled gradient echo sequences with pulsed off-resonance saturation can be a time-consuming technique. A method is presented for selection of an optimum experimental design for quantitative magnetization transfer imaging based on the iterative reduction of a discrete sampling of the Z-spectrum. The applicability of the technique is demonstrated for human brain white matter imaging at 1.5 T and 3 T, and optimal designs are produced to target specific model parameters. The optimal number of measurements and the signal-to-noise ratio required for stable parameter estimation are also investigated. In vivo imaging results demonstrate that this optimal design approach substantially improves parameter map quality. The iterative method presented here provides an advantage over free form optimal design methods, in that pragmatic design constraints are readily incorporated. In particular, the presented method avoids clustering and repeated measures in the final experimental design, an attractive feature for the purpose of magnetization transfer model validation. The iterative optimal design technique is general and can be applied to any method of quantitative magnetization transfer imaging. Copyright © 2011 Wiley-Liss, Inc.

Optimization of isolation of cellulose from orange peel using sodium hydroxide and chelating agents.

PubMed

Bicu, Ioan; Mustata, Fanica

2013-10-15

Response surface methodology was used to optimize cellulose recovery from orange peel using sodium hydroxide (NaOH) as isolation reagent, and to minimize its ash content using ethylenediaminetetraacetic acid (EDTA) as chelating agent. The independent variables were NaOH charge, EDTA charge and cooking time. Other two constant parameters were cooking temperature (98 °C) and liquid-to-solid ratio (7.5). The dependent variables were cellulose yield and ash content. A second-order polynomial model was used for plotting response surfaces and for determining optimum cooking conditions. The analysis of coefficient values for independent variables in the regression equation showed that NaOH and EDTA charges were major factors influencing the cellulose yield and ash content, respectively. Optimum conditions were defined by: NaOH charge 38.2%, EDTA charge 9.56%, and cooking time 317 min. The predicted cellulose yield was 24.06% and ash content 0.69%. A good agreement between the experimental values and the predicted was observed. Copyright © 2013 Elsevier Ltd. All rights reserved.

Determination of reaction rates and activation energy in aerobic composting processes for yard waste.

PubMed

Uma, R N; Manjula, G; Meenambal, T

2007-04-01

The reaction rates and activation energy in aerobic composting processes for yard waste were determined using specifically designed reactors. Different mixture ratios were fixed before the commencement of the process. The C/N ratio was found to be optimum for a mixture ratio of 1:6 containing one part of coir pith to six parts of other waste which included yard waste, yeast sludge, poultry yard waste and decomposing culture (Pleurotosis). The path of stabilization of the wastes was continuously monitored by observing various parameters such as temperature, pH, Electrical Conductivity, C.O.D, VS at regular time intervals. Kinetic analysis was done to determine the reaction rates and activation energy for the optimum mixture ratio under forced aeration condition. The results of the analysis clearly indicated that the temperature dependence of the reaction rates followed the Arrhenius equation. The temperature coefficients were also determined. The degradation of the organic fraction of the yard waste could be predicted using first order reaction model.

A glycerol-free process to produce biodiesel by supercritical methyl acetate technology: an optimization study via Response Surface Methodology.

PubMed

Tan, Kok Tat; Lee, Keat Teong; Mohamed, Abdul Rahman

2010-02-01

In this study, fatty acid methyl esters (FAME) have been successfully produced from transesterification reaction between triglycerides and methyl acetate, instead of alcohol. In this non-catalytic supercritical methyl acetate (SCMA) technology, triacetin which is a valuable biodiesel additive is produced as side product rather than glycerol, which has lower commercial value. Besides, the properties of the biodiesel (FAME and triacetin) were found to be superior compared to those produced from conventional catalytic reactions (FAME only). In this study, the effects of various important parameters on the yield of biodiesel were optimized by utilizing Response Surface Methodology (RSM) analysis. The mathematical model developed was found to be adequate and statistically accurate to predict the optimum yield of biodiesel. The optimum conditions were found to be 399 degrees C for reaction temperature, 30 mol/mol of methyl acetate to oil molar ratio and reaction time of 59 min to achieve 97.6% biodiesel yield.

Numerical model for the locomotion of spirilla.

PubMed

Ramia, M

1991-11-01

The swimming of trailing, leading, and bipolar spirilla (with realistic flagellar centerline geometries) is considered. A boundary element method is used to predict the instantaneous swimming velocity, counter-rotation angular velocity, and power dissipation of a given organism as functions of time and the geometry of the organism. Based on such velocities, swimming trajectories have been deduced enabling a realistic definition of mean swimming speeds. The power dissipation normalized in terms of the square of the mean swimming speed is considered to be a measure of hydrodynamic efficiency. In addition, kinematic efficiency is defined as the extent of deviation of the swimming motion from that of a previously proposed ideal corkscrew mechanism. The dependence of these efficiencies on the organism's geometry is examined giving estimates of its optimum dimensions. It is concluded that appreciable correlation exists between the two alternative definitions for many of the geometrical parameters considered. Furthermore, the organism having the deduced optimum dimensions closely resembles the real organism as experimentally observed.

Numerical model for the locomotion of spirilla

PubMed Central

Ramia, M.

1991-01-01

The swimming of trailing, leading, and bipolar spirilla (with realistic flagellar centerline geometries) is considered. A boundary element method is used to predict the instantaneous swimming velocity, counter-rotation angular velocity, and power dissipation of a given organism as functions of time and the geometry of the organism. Based on such velocities, swimming trajectories have been deduced enabling a realistic definition of mean swimming speeds. The power dissipation normalized in terms of the square of the mean swimming speed is considered to be a measure of hydrodynamic efficiency. In addition, kinematic efficiency is defined as the extent of deviation of the swimming motion from that of a previously proposed ideal corkscrew mechanism. The dependence of these efficiencies on the organism's geometry is examined giving estimates of its optimum dimensions. It is concluded that appreciable correlation exists between the two alternative definitions for many of the geometrical parameters considered. Furthermore, the organism having the deduced optimum dimensions closely resembles the real organism as experimentally observed. PMID:19431804

First-Order Altitude Effects on the Cruise Efficiency of Subsonic Transport Aircraft

NASA Technical Reports Server (NTRS)

Guynn, Mark D.

2011-01-01

Aircraft fuel efficiency is a function of many different parameters, including characteristics of the engines, characteristics of the airframe, and the conditions under which the aircraft is operated. For a given vehicle, the airframe and engine characteristics are for the most part fixed quantities and efficiency is primarily a function of operational conditions. One important influence on cruise efficiency is cruise altitude. Various future scenarios have been postulated for cruise altitude, from the freedom to fly at optimum altitudes to altitude restrictions imposed for environmental reasons. This report provides background on the fundamental relationships determining aircraft cruise efficiency and examines the sensitivity of efficiency to cruise altitude. Analytical models of two current aircraft designs are used to derive quantitative results. Efficiency penalties are found to be generally less than 1% when within roughly 2000 ft of the optimum cruise altitude. Even the restrictive scenario of constant altitude cruise is found to result in a modest fuel consumption penalty if the fixed altitude is in an appropriate range.

Sensitivity method for integrated structure/active control law design

NASA Technical Reports Server (NTRS)

Gilbert, Michael G.

1987-01-01

The development is described of an integrated structure/active control law design methodology for aeroelastic aircraft applications. A short motivating introduction to aeroservoelasticity is given along with the need for integrated structures/controls design algorithms. Three alternative approaches to development of an integrated design method are briefly discussed with regards to complexity, coordination and tradeoff strategies, and the nature of the resulting solutions. This leads to the formulation of the proposed approach which is based on the concepts of sensitivity of optimum solutions and multi-level decompositions. The concept of sensitivity of optimum is explained in more detail and compared with traditional sensitivity concepts of classical control theory. The analytical sensitivity expressions for the solution of the linear, quadratic cost, Gaussian (LQG) control problem are summarized in terms of the linear regulator solution and the Kalman Filter solution. Numerical results for a state space aeroelastic model of the DAST ARW-II vehicle are given, showing the changes in aircraft responses to variations of a structural parameter, in this case first wing bending natural frequency.

Application of multi response optimization with grey relational analysis and fuzzy logic method

NASA Astrophysics Data System (ADS)

Winarni, Sri; Wahyu Indratno, Sapto

2018-01-01

Multi-response optimization is an optimization process by considering multiple responses simultaneously. The purpose of this research is to get the optimum point on multi-response optimization process using grey relational analysis and fuzzy logic method. The optimum point is determined from the Fuzzy-GRG (Grey Relational Grade) variable which is the conversion of the Signal to Noise Ratio of the responses involved. The case study used in this research are case optimization of electrical process parameters in electrical disharge machining. It was found that the combination of treatments resulting to optimum MRR and SR was a 70 V gap voltage factor, peak current 9 A and duty factor 0.8.

Development of a fixed bed gasifier model and optimal operating conditions determination

NASA Astrophysics Data System (ADS)

Dahmani, Manel; Périlhon, Christelle; Marvillet, Christophe; Hajjaji, Noureddine; Houas, Ammar; Khila, Zouhour

2017-02-01

The main objective of this study was to develop a fixed bed gasifier model of palm waste and to identify the optimal operating conditions to produce electricity from synthesis gas. First, the gasifier was simulated using Aspen PlusTM software. Gasification is a thermo-chemical process that has long been used, but it remains a perfectible technology. It means incomplete combustion of biomass solid fuel into synthesis gas through partial oxidation. The operating parameters (temperature and equivalence ratio (ER)) were thereafter varied to investigate their effect on the synthesis gas composition and to provide guidance for future research and development efforts in process design. The equivalence ratio is defined as the ratio of the amount of air actually supplied to the gasifier and the stoichiometric amount of air. Increasing ER decreases the production of CO and H2 and increases the production of CO2 and H2O while an increase in temperature increases the fraction of CO and H2. The results show that the optimum temperature to have a syngas able to be effectively used for power generation is 900°C and the optimum equivalence ratio is 0.1.

Coupling of Helmholtz resonators to improve acoustic liners for turbofan engines at low frequency

NASA Technical Reports Server (NTRS)

Dean, L. W.

1975-01-01

An analytical and test program was conducted to evaluate means for increasing the effectiveness of low frequency sound absorbing liners for aircraft turbine engines. Three schemes for coupling low frequency absorber elements were considered. These schemes were analytically modeled and their impedance was predicted over a frequency range of 50 to 1,000 Hz. An optimum and two off-optimum designs of the most promising, a parallel coupled scheme, were fabricated and tested in a flow duct facility. Impedance measurements were in good agreement with predicted values and validated the procedure used to transform modeled parameters to hardware designs. Measurements of attenuation for panels of coupled resonators were consistent with predictions based on measured impedance. All coupled resonator panels tested showed an increase in peak attenuation of about 50% and an increase in attenuation bandwidth of one one-third octave band over that measured for an uncoupled panel. These attenuation characteristics equate to about 35% greater reduction in source perceived noise level (PNL), relative to the uncoupled panel, or a reduction in treatment length of about 24% for constant PNL reduction. The increased effectiveness of the coupled resonator concept for attenuation of low frequency broad spectrum noise is demonstrated.

At-line monitoring of key parameters of nisin fermentation by near infrared spectroscopy, chemometric modeling and model improvement.

PubMed

Guo, Wei-Liang; Du, Yi-Ping; Zhou, Yong-Can; Yang, Shuang; Lu, Jia-Hui; Zhao, Hong-Yu; Wang, Yao; Teng, Li-Rong

2012-03-01

An analytical procedure has been developed for at-line (fast off-line) monitoring of 4 key parameters including nisin titer (NT), the concentration of reducing sugars, cell concentration and pH during a nisin fermentation process. This procedure is based on near infrared (NIR) spectroscopy and Partial Least Squares (PLS). Samples without any preprocessing were collected at intervals of 1 h during fifteen batch of fermentations. These fermentation processes were implemented in 3 different 5 l fermentors at various conditions. NIR spectra of the samples were collected in 10 min. And then, PLS was used for modeling the relationship between NIR spectra and the key parameters which were determined by reference methods. Monte Carlo Partial Least Squares (MCPLS) was applied to identify the outliers and select the most efficacious methods for preprocessing spectra, wavelengths and the suitable number of latent variables (n (LV)). Then, the optimum models for determining NT, concentration of reducing sugars, cell concentration and pH were established. The correlation coefficients of calibration set (R (c)) were 0.8255, 0.9000, 0.9883 and 0.9581, respectively. These results demonstrated that this method can be successfully applied to at-line monitor of NT, concentration of reducing sugars, cell concentration and pH during nisin fermentation processes.

Dynamic modeling the composting process of the mixture of poultry manure and wheat straw.

PubMed

Petric, Ivan; Mustafić, Nesib

2015-09-15

Due to lack of understanding of the complex nature of the composting process, there is a need to provide a valuable tool that can help to improve the prediction of the process performance but also its optimization. Therefore, the main objective of this study is to develop a comprehensive mathematical model of the composting process based on microbial kinetics. The model incorporates two different microbial populations that metabolize the organic matter in two different substrates. The model was validated by comparison of the model and experimental data obtained from the composting process of the mixture of poultry manure and wheat straw. Comparison of simulation results and experimental data for five dynamic state variables (organic matter conversion, oxygen concentration, carbon dioxide concentration, substrate temperature and moisture content) showed that the model has very good predictions of the process performance. According to simulation results, the optimum values for air flow rate and ambient air temperature are 0.43 l min(-1) kg(-1)OM and 28 °C, respectively. On the basis of sensitivity analysis, the maximum organic matter conversion is the most sensitive among the three objective functions. Among the twelve examined parameters, μmax,1 is the most influencing parameter and X1 is the least influencing parameter. Copyright © 2015 Elsevier Ltd. All rights reserved.

Modeling parameters that characterize pacing of elite female 800-m freestyle swimmers.

PubMed

Lipińska, Patrycja; Allen, Sian V; Hopkins, Will G

2016-01-01

Pacing offers a potential avenue for enhancement of endurance performance. We report here a novel method for characterizing pacing in 800-m freestyle swimming. Websites provided 50-m lap and race times for 192 swims of 20 elite female swimmers between 2000 and 2013. Pacing for each swim was characterized with five parameters derived from a linear model: linear and quadratic coefficients for effect of lap number, reductions from predicted time for first and last laps, and lap-time variability (standard error of the estimate). Race-to-race consistency of the parameters was expressed as intraclass correlation coefficients (ICCs). The average swim was a shallow negative quadratic with slowest time in the eleventh lap. First and last laps were faster by 6.4% and 3.6%, and lap-time variability was ±0.64%. Consistency between swimmers ranged from low-moderate for the linear and quadratic parameters (ICC = 0.29 and 0.36) to high for the last-lap parameter (ICC = 0.62), while consistency for race time was very high (ICC = 0.80). Only ~15% of swimmers had enough swims (~15 or more) to provide reasonable evidence of optimum parameter values in plots of race time vs. each parameter. The modest consistency of most of the pacing parameters and lack of relationships between parameters and performance suggest that swimmers usually compensated for changes in one parameter with changes in another. In conclusion, pacing in 800-m elite female swimmers can be characterized with five parameters, but identifying an optimal pacing profile is generally impractical.

Reduced complexity structural modeling for automated airframe synthesis

NASA Technical Reports Server (NTRS)

Hajela, Prabhat

1987-01-01

A procedure is developed for the optimum sizing of wing structures based on representing the built-up finite element assembly of the structure by equivalent beam models. The reduced-order beam models are computationally less demanding in an optimum design environment which dictates repetitive analysis of several trial designs. The design procedure is implemented in a computer program requiring geometry and loading information to create the wing finite element model and its equivalent beam model, and providing a rapid estimate of the optimum weight obtained from a fully stressed design approach applied to the beam. The synthesis procedure is demonstrated for representative conventional-cantilever and joined wing configurations.

Importance of optimizing chromatographic conditions and mass spectrometric parameters for supercritical fluid chromatography/mass spectrometry.

PubMed

Fujito, Yuka; Hayakawa, Yoshihiro; Izumi, Yoshihiro; Bamba, Takeshi

2017-07-28

Supercritical fluid chromatography/mass spectrometry (SFC/MS) has great potential in high-throughput and the simultaneous analysis of a wide variety of compounds, and it has been widely used in recent years. The use of MS for detection provides the advantages of high sensitivity and high selectivity. However, the sensitivity of MS detection depends on the chromatographic conditions and MS parameters. Thus, optimization of MS parameters corresponding to the SFC condition is mandatory for maximizing performance when connecting SFC to MS. The aim of this study was to reveal a way to decide the optimum composition of the mobile phase and the flow rate of the make-up solvent for MS detection in a wide range of compounds. Additionally, we also showed the basic concept for determination of the optimum values of the MS parameters focusing on the MS detection sensitivity in SFC/MS analysis. To verify the versatility of these findings, a total of 441 pesticides with a wide polarity range (logP ow from -4.21 to 7.70) and pKa (acidic, neutral and basic). In this study, a new SFC-MS interface was used, which can transfer the entire volume of eluate into the MS by directly coupling the SFC with the MS. This enabled us to compare the sensitivity or optimum MS parameters for MS detection between LC/MS and SFC/MS for the same sample volume introduced into the MS. As a result, it was found that the optimum values of some MS parameters were completely different from those of LC/MS, and that SFC/MS-specific optimization of the analytical conditions is required. Lastly, we evaluated the sensitivity of SFC/MS using fully optimized analytical conditions. As a result, we confirmed that SFC/MS showed much higher sensitivity than LC/MS when the analytical conditions were fully optimized for SFC/MS; and the high sensitivity also increase the number of the compounds that can be detected with good repeatability in real sample analysis. This result indicates that SFC/MS has potential for practical use in the multiresidue analysis of a wide range of compounds that requires high sensitivity. Copyright © 2017 Elsevier B.V. All rights reserved.

Optimization of binder addition and particle size for densification of coffee husks briquettes using response surface methodology

NASA Astrophysics Data System (ADS)

Raudah; Zulkifli

2018-03-01

The present research focuses on establishing the optimum conditions in converting coffee husk into a densified biomass fuel using starch as a binding agent. A Response Surface Methodology (RSM) approach using Box-Behnken experimental design with three levels (-1, 0, and +1) was employed to obtain the optimum level for each parameter. The briquettes wereproduced by compressing the mixture of coffee husk-starch in a piston and die assembly with the pressure of 2000 psi. Furthermore, starch percentage, pyrolysis time, and particle size were the input parameters for the algorithm. Bomb calorimeter was used to determine the heating value (HHV) of the solid fuel. The result of the study indicated that a combination of 34.71 mesh particle size, 110.93 min pyrolysis time, and 8% starch concentration werethe optimum variables.The HHV and density of the fuel were up to 5644.66 calgr-1 and 0.7069 grcm-3,respectively. The study showed that further research should be conducted to improve the briquette density therefore the coffee husk could be convert into commercialsolid fuel to replace the dependent on fossil fuel.

Extraction of bioactives from Orthosiphon stamineus using microwave and ultrasound-assisted techniques: Process optimization and scale up.

PubMed

Chan, Chung-Hung; See, Tiam-You; Yusoff, Rozita; Ngoh, Gek-Cheng; Kow, Kien-Woh

2017-04-15

This work demonstrated the optimization and scale up of microwave-assisted extraction (MAE) and ultrasonic-assisted extraction (UAE) of bioactive compounds from Orthosiphon stamineus using energy-based parameters such as absorbed power density and absorbed energy density (APD-AED) and response surface methodology (RSM). The intensive optimum conditions of MAE obtained at 80% EtOH, 50mL/g, APD of 0.35W/mL, AED of 250J/mL can be used to determine the optimum conditions of the scale-dependent parameters i.e. microwave power and treatment time at various extraction scales (100-300mL solvent loading). The yields of the up scaled conditions were consistent with less than 8% discrepancy and they were about 91-98% of the Soxhlet extraction yield. By adapting APD-AED method in the case of UAE, the intensive optimum conditions of the extraction, i.e. 70% EtOH, 30mL/g, APD of 0.22W/mL, AED of 450J/mL are able to achieve similar scale up results. Copyright © 2016 Elsevier Ltd. All rights reserved.

Analytically optimal parameters of dynamic vibration absorber with negative stiffness

NASA Astrophysics Data System (ADS)

Shen, Yongjun; Peng, Haibo; Li, Xianghong; Yang, Shaopu

2017-02-01

In this paper the optimal parameters of a dynamic vibration absorber (DVA) with negative stiffness is analytically studied. The analytical solution is obtained by Laplace transform method when the primary system is subjected to harmonic excitation. The research shows there are still two fixed points independent of the absorber damping in the amplitude-frequency curve of the primary system when the system contains negative stiffness. Then the optimum frequency ratio and optimum damping ratio are respectively obtained based on the fixed-point theory. A new strategy is proposed to obtain the optimum negative stiffness ratio and make the system remain stable at the same time. At last the control performance of the presented DVA is compared with those of three existing typical DVAs, which were presented by Den Hartog, Ren and Sims respectively. The comparison results in harmonic and random excitation show that the presented DVA in this paper could not only reduce the peak value of the amplitude-frequency curve of the primary system significantly, but also broaden the efficient frequency range of vibration mitigation.

The unlikely high efficiency of a molecular motor based on active motion

NASA Astrophysics Data System (ADS)

Ebeling, W.

2015-07-01

The efficiency of a simple model of a motor converting chemical into mechanical energy is studied analytically. The model motor shows interesting properties corresponding qualitatively to motors investigated in experiments. The efficiency increases with the load and may for low loss reach high values near to 100 percent in a narrow regime of optimal load. It is shown that the optimal load and the maximal efficiency depend by universal power laws on the dimensionless loss parameter. Stochastic effects decrease the stability of motor regimes with high efficiency and make them unlikely. Numerical studies show efficiencies below the theoretical optimum and demonstrate that special ratchet profiles my stabilize efficient regimes.

Bioreactors with immobilized lipases: state of the art.

PubMed

Balcão, V M; Paiva, A L; Malcata, F X

1996-05-01

This review attempts to provide an updated compilation of studies reported in the literature pertaining to reactors containing lipases in immobilized forms, in a way that helps the reader direct a bibliographic search and develop an integrated perspective of the subject. Highlights are given to industrial applications of lipases (including control and economic considerations), as well as to methods of immobilization and configurations of reactors in which lipases are used. Features associated with immobilized lipase kinetics such as enzyme activities, adsorption properties, optimum operating conditions, and estimates of the lumped parameters in classical kinetic formulations (Michaelis-Menten model for enzyme action and first-order model for enzyme decay) are presented in the text in a systematic tabular form.

Rocket ascent G-limited moment-balanced optimization program (RAGMOP)

NASA Technical Reports Server (NTRS)

Lyons, J. T.; Woltosz, W. S.; Abercrombie, G. E.; Gottlieb, R. G.

1972-01-01

This document describes the RAGMOP (Rocket Ascent G-limited Momentbalanced Optimization Program) computer program for parametric ascent trajectory optimization. RAGMOP computes optimum polynomial-form attitude control histories, launch azimuth, engine burn-time, and gross liftoff weight for space shuttle type vehicles using a search-accelerated, gradient projection parameter optimization technique. The trajectory model available in RAGMOP includes a rotating oblate earth model, the option of input wind tables, discrete and/or continuous throttling for the purposes of limiting the thrust acceleration and/or the maximum dynamic pressure, limitation of the structural load indicators (the product of dynamic pressure with angle-of-attack and sideslip angle), and a wide selection of intermediate and terminal equality constraints.

Geothermal reservoir engineering research

NASA Technical Reports Server (NTRS)

Ramey, H. J., Jr.; Kruger, P.; Brigham, W. E.; London, A. L.

1974-01-01

The Stanford University research program on the study of stimulation and reservoir engineering of geothermal resources commenced as an interdisciplinary program in September, 1972. The broad objectives of this program have been: (1) the development of experimental and computational data to evaluate the optimum performance of fracture-stimulated geothermal reservoirs; (2) the development of a geothermal reservoir model to evaluate important thermophysical, hydrodynamic, and chemical parameters based on fluid-energy-volume balances as part of standard reservoir engineering practice; and (3) the construction of a laboratory model of an explosion-produced chimney to obtain experimental data on the processes of in-place boiling, moving flash fronts, and two-phase flow in porous and fractured hydrothermal reservoirs.

Wind flow characteristics in the wakes of large wind turbines. Volume 1: Analytical model development

NASA Technical Reports Server (NTRS)

Eberle, W. R.

1981-01-01

A computer program to calculate the wake downwind of a wind turbine was developed. Turbine wake characteristics are useful for determining optimum arrays for wind turbine farms. The analytical model is based on the characteristics of a turbulent coflowing jet with modification for the effects of atmospheric turbulence. The program calculates overall wake characteristics, wind profiles, and power recovery for a wind turbine directly in the wake of another turbine, as functions of distance downwind of the turbine. The calculation procedure is described in detail, and sample results are presented to illustrate the general behavior of the wake and the effects of principal input parameters.

Protein Subcellular Localization with Gaussian Kernel Discriminant Analysis and Its Kernel Parameter Selection.

PubMed

Wang, Shunfang; Nie, Bing; Yue, Kun; Fei, Yu; Li, Wenjia; Xu, Dongshu

2017-12-15

Kernel discriminant analysis (KDA) is a dimension reduction and classification algorithm based on nonlinear kernel trick, which can be novelly used to treat high-dimensional and complex biological data before undergoing classification processes such as protein subcellular localization. Kernel parameters make a great impact on the performance of the KDA model. Specifically, for KDA with the popular Gaussian kernel, to select the scale parameter is still a challenging problem. Thus, this paper introduces the KDA method and proposes a new method for Gaussian kernel parameter selection depending on the fact that the differences between reconstruction errors of edge normal samples and those of interior normal samples should be maximized for certain suitable kernel parameters. Experiments with various standard data sets of protein subcellular localization show that the overall accuracy of protein classification prediction with KDA is much higher than that without KDA. Meanwhile, the kernel parameter of KDA has a great impact on the efficiency, and the proposed method can produce an optimum parameter, which makes the new algorithm not only perform as effectively as the traditional ones, but also reduce the computational time and thus improve efficiency.

Optimization of microwave-assisted extraction of total extract, stevioside and rebaudioside-A from Stevia rebaudiana (Bertoni) leaves, using response surface methodology (RSM) and artificial neural network (ANN) modelling.

PubMed

Ameer, Kashif; Bae, Seong-Woo; Jo, Yunhee; Lee, Hyun-Gyu; Ameer, Asif; Kwon, Joong-Ho

2017-08-15

Stevia rebaudiana (Bertoni) consists of stevioside and rebaudioside-A (Reb-A). We compared response surface methodology (RSM) and artificial neural network (ANN) modelling for their estimation and predictive capabilities in building effective models with maximum responses. A 5-level 3-factor central composite design was used to optimize microwave-assisted extraction (MAE) to obtain maximum yield of target responses as a function of extraction time (X 1 : 1-5min), ethanol concentration, (X 2 : 0-100%) and microwave power (X 3 : 40-200W). Maximum values of the three output parameters: 7.67% total extract yield, 19.58mg/g stevioside yield, and 15.3mg/g Reb-A yield, were obtained under optimum extraction conditions of 4min X 1 , 75% X 2 , and 160W X 3 . The ANN model demonstrated higher efficiency than did the RSM model. Hence, RSM can demonstrate interaction effects of inherent MAE parameters on target responses, whereas ANN can reliably model the MAE process with better predictive and estimation capabilities. Copyright © 2017. Published by Elsevier Ltd.

Optimization of Experimental Conditions of the Pulsed Current GTAW Parameters for Mechanical Properties of SDSS UNS S32760 Welds Based on the Taguchi Design Method

NASA Astrophysics Data System (ADS)

Yousefieh, M.; Shamanian, M.; Saatchi, A.

2012-09-01

Taguchi design method with L9 orthogonal array was implemented to optimize the pulsed current gas tungsten arc welding parameters for the hardness and the toughness of super duplex stainless steel (SDSS, UNS S32760) welds. In this regard, the hardness and the toughness were considered as performance characteristics. Pulse current, background current, % on time, and pulse frequency were chosen as main parameters. Each parameter was varied at three different levels. As a result of pooled analysis of variance, the pulse current is found to be the most significant factor for both the hardness and the toughness of SDSS welds by percentage contribution of 71.81 for hardness and 78.18 for toughness. The % on time (21.99%) and the background current (17.81%) had also the next most significant effect on the hardness and the toughness, respectively. The optimum conditions within the selected parameter values for hardness were found as the first level of pulse current (100 A), third level of background current (70 A), first level of % on time (40%), and first level of pulse frequency (1 Hz), while they were found as the second level of pulse current (120 A), second level of background current (60 A), second level of % on time (60%), and third level of pulse frequency (5 Hz) for toughness. The Taguchi method was found to be a promising tool to obtain the optimum conditions for such studies. Finally, in order to verify experimental results, confirmation tests were carried out at optimum working conditions. Under these conditions, there were good agreements between the predicted and the experimental results for the both hardness and toughness.

Wing Shaping and Gust Load Controls of Flexible Aircraft: An LPV Approach

NASA Technical Reports Server (NTRS)

Hammerton, Jared R.; Su, Weihua; Zhu, Guoming; Swei, Sean Shan-Min

2018-01-01

In the proposed paper, the optimum wing shape of a highly flexible aircraft under varying flight conditions will be controlled by a linear parameter-varying approach. The optimum shape determined under multiple objectives, including flight performance, ride quality, and control effort, will be determined as well. This work is an extension of work done previously by the authors, and updates the existing optimization and utilizes the results to generate a robust flight controller.

Development of mathematical models and optimization of the process parameters of laser surface hardened EN25 steel using elitist non-dominated sorting genetic algorithm

NASA Astrophysics Data System (ADS)

Vignesh, S.; Dinesh Babu, P.; Surya, G.; Dinesh, S.; Marimuthu, P.

2018-02-01

The ultimate goal of all production entities is to select the process parameters that would be of maximum strength, minimum wear and friction. The friction and wear are serious problems in most of the industries which are influenced by the working set of parameters, oxidation characteristics and mechanism involved in formation of wear. The experimental input parameters such as sliding distance, applied load, and temperature are utilized in finding out the optimized solution for achieving the desired output responses such as coefficient of friction, wear rate, and volume loss. The optimization is performed with the help of a novel method, Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) based on an evolutionary algorithm. The regression equations obtained using Response Surface Methodology (RSM) are used in determining the optimum process parameters. Further, the results achieved through desirability approach in RSM are compared with that of the optimized solution obtained through NSGA-II. The results conclude that proposed evolutionary technique is much effective and faster than the desirability approach.

Determination of optimum process parameters for peroxidase-catalysed treatment of bisphenol A and application to the removal of bisphenol derivatives.

PubMed

Yamada, Kazunori; Ikeda, Naoya; Takano, Yoko; Kashiwada, Ayumi; Matsuda, Kiyomi; Hirata, Mitsuo

2010-03-01

Systematic investigations were carried out to determine the optimum process parameters such as the hydrogen peroxide (H2O2) concentration, concentration and molar mass of poly(ethylene glycol) (PEG) as an additive, pH value, temperature and enzyme dose for treatment of bisphenol A (BPA) with horseradish peroxidase (HRP). The HRP-catalysed treatment of BPA was effectively enhanced by adding PEG, and BPA was completely converted into phenoxy radicals by HRP dose of 0.10 U/cm3. The optimum conditions for HRP-catalysed treatment of BPA at 0.3 mM was determined to be 0.3 mM for H2O2 and 0.10 mg/cm3 for PEG with a molar mass of 1.0 x 10(4) in a pH 6.0 buffer at 30 degrees C. Different kinds of bisphenol derivatives were completely or effectively treated by HRP under the optimum conditions determined for treatment of BPA, although the HRP dose was further increased as necessary for some of them. The aggregation of water-insoluble oligomers generated by the enzymatic radicalization and radical coupling reaction was enhanced by decreasing the pH values to 4.0 with HCl after the enzymatic treatment, and BPA and bisphenol derivatives were removed from aqueous solutions by filtering out the oligomer precipitates.

Study of hole characteristics in Laser Trepan Drilling of ZTA

NASA Astrophysics Data System (ADS)

Saini, Surendra K.; Dubey, Avanish K.; Upadhyay, B. N.; Choubey, A.

2018-07-01

Zirconia Toughened Alumina ceramic is widely used for aerospace components, combustion chambers, heat exchangers, bearings and pumps mainly due to its improved mechanical and thermal properties. To make holes in thick section Zirconia Toughened Alumina ceramics is a major challenge due to its unfavorable machining characteristics. Recent researches have explored that laser machining can overcome the machining limitations of advanced materials having improved mechanical properties. In present research, authors have analyzed the effect of Laser Trepan Drilling on hole characteristics of 6.0 mm thick Zirconia Toughened Alumina. Effect of significant process parameters on hole characteristics such as hole circularity at top and bottom, hole taper, and spatter size have been studied. The optimum ranges of these parameters have been suggested on the basis of empirical modeling and optimization.

Component and System Sensitivity Considerations for Design of a Lunar ISRU Oxygen Production Plant

NASA Technical Reports Server (NTRS)

Linne, Diane L.; Gokoglu, Suleyman; Hegde, Uday G.; Balasubramaniam, Ramaswamy; Santiago-Maldonado, Edgardo

2009-01-01

Component and system sensitivities of some design parameters of ISRU system components are analyzed. The differences between terrestrial and lunar excavation are discussed, and a qualitative comparison of large and small excavators is started. The effect of excavator size on the size of the ISRU plant's regolith hoppers is presented. Optimum operating conditions of both hydrogen and carbothermal reduction reactors are explored using recently developed analytical models. Design parameters such as batch size, conversion fraction, and maximum particle size are considered for a hydrogen reduction reactor while batch size, conversion fraction, number of melt zones, and methane flow rate are considered for a carbothermal reduction reactor. For both reactor types the effect of reactor operation on system energy and regolith delivery requirements is presented.

Optimization of extraction of linarin from Flos chrysanthemi indici by response surface methodology and artificial neural network.

PubMed

Pan, Hongye; Zhang, Qing; Cui, Keke; Chen, Guoquan; Liu, Xuesong; Wang, Longhu

2017-05-01

The extraction of linarin from Flos chrysanthemi indici by ethanol was investigated. Two modeling techniques, response surface methodology and artificial neural network, were adopted to optimize the process parameters, such as, ethanol concentration, extraction period, extraction frequency, and solvent to material ratio. We showed that both methods provided good predictions, but artificial neural network provided a better and more accurate result. The optimum process parameters include, ethanol concentration of 74%, extraction period of 2 h, extraction three times, solvent to material ratio of 12 mL/g. The experiment yield of linarin was 90.5% that deviated less than 1.6% from that obtained by predicted result. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A kinetic model of municipal sludge degradation during non-catalytic wet oxidation.

PubMed

Prince-Pike, Arrian; Wilson, David I; Baroutian, Saeid; Andrews, John; Gapes, Daniel J

2015-12-15

Wet oxidation is a successful process for the treatment of municipal sludge. In addition, the resulting effluent from wet oxidation is a useful carbon source for subsequent biological nutrient removal processes in wastewater treatment. Owing to limitations with current kinetic models, this study produced a kinetic model which predicts the concentrations of key intermediate components during wet oxidation. The model was regressed from lab-scale experiments and then subsequently validated using data from a wet oxidation pilot plant. The model was shown to be accurate in predicting the concentrations of each component, and produced good results when applied to a plant 500 times larger in size. A statistical study was undertaken to investigate the validity of the regressed model parameters. Finally the usefulness of the model was demonstrated by suggesting optimum operating conditions such that volatile fatty acids were maximised. Copyright © 2015 Elsevier Ltd. All rights reserved.

Growth of non-toxigenic Clostridium botulinum mutant LNT01 in cooked beef: One-step kinetic analysis and comparison with C. sporogenes and C. perfringens.

PubMed

Huang, Lihan

2018-05-01

The objective of this study was to investigate the growth kinetics of Clostridium botulinum LNT01, a non-toxigenic mutant of C. botulinum 62A, in cooked ground beef. The spores of C. botulinum LNT01 were inoculated to ground beef and incubated anaerobically under different temperature conditions to observe growth and develop growth curves. A one-step kinetic analysis method was used to analyze the growth curves simultaneously to minimize the global residual error. The data analysis was performed using the USDA IPMP-Global Fit, with the Huang model as the primary model and the cardinal parameters model as the secondary model. The results of data analysis showed that the minimum, optimum, and maximum growth temperatures of this mutant are 11.5, 36.4, and 44.3 °C, and the estimated optimum specific growth rate is 0.633 ln CFU/g per h, or 0.275 log CFU/g per h. The maximum cell density is 7.84 log CFU/g. The models and kinetic parameters were validated using additional isothermal and dynamic growth curves. The resulting residual errors of validation followed a Laplace distribution, with about 60% of the residual errors within ±0.5 log CFU/g of experimental observations, suggesting that the models could predict the growth of C. botulinum LNT01 in ground beef with reasonable accuracy. Comparing with C. perfringens, C. botulinum LNT01 grows at much slower rates and with much longer lag times. Its growth kinetics is also very similar to C. sporogenes in ground beef. The results of computer simulation using kinetic models showed that, while prolific growth of C. perfringens may occur in ground beef during cooling, no growth of C. botulinum LNT01 or C. sporogenes would occur under the same cooling conditions. The models developed in this study may be used for prediction of the growth and risk assessments of proteolytic C. botulinum in cooked meats. Published by Elsevier Ltd.

Size effects on miniature Stirling cycle cryocoolers

NASA Astrophysics Data System (ADS)

Yang, Xiaoqin; Chung, J. N.

2005-08-01

Size effects on the performance of Stirling cycle cryocoolers were investigated by examining each individual loss associated with the regenerator and combining these effects. For the fixed cycle parameters and given regenerator length scale, it was found that only for a specific range of the hydrodynamic diameter the system can produce net refrigeration and there is an optimum hydraulic diameter at which the maximum net refrigeration is achieved. When the hydraulic diameter is less than the optimum value, the regenerator performance is controlled by the pressure drop loss; when the hydraulic diameter is greater than the optimum value, the system performance is controlled by the thermal losses. It was also found that there exists an optimum ratio between the hydraulic diameter and the length of the regenerator that offers the maximum net refrigeration. As the regenerator length is decreased, the optimum hydraulic diameter-to-length ratio increases; and the system performance is increased that is controlled by the pressure drop loss and heat conduction loss. Choosing appropriate regenerator characteristic sizes in small-scale systems are more critical than in large-scale ones.

Optimum Design of Aerospace Structural Components Using Neural Networks

NASA Technical Reports Server (NTRS)

Berke, L.; Patnaik, S. N.; Murthy, P. L. N.

1993-01-01

The application of artificial neural networks to capture structural design expertise is demonstrated. The principal advantage of a trained neural network is that it requires a trivial computational effort to produce an acceptable new design. For the class of problems addressed, the development of a conventional expert system would be extremely difficult. In the present effort, a structural optimization code with multiple nonlinear programming algorithms and an artificial neural network code NETS were used. A set of optimum designs for a ring and two aircraft wings for static and dynamic constraints were generated using the optimization codes. The optimum design data were processed to obtain input and output pairs, which were used to develop a trained artificial neural network using the code NETS. Optimum designs for new design conditions were predicted using the trained network. Neural net prediction of optimum designs was found to be satisfactory for the majority of the output design parameters. However, results from the present study indicate that caution must be exercised to ensure that all design variables are within selected error bounds.

Validity of the two-level model for Viterbi decoder gap-cycle performance

NASA Technical Reports Server (NTRS)

Dolinar, S.; Arnold, S.

1990-01-01

A two-level model has previously been proposed for approximating the performance of a Viterbi decoder which encounters data received with periodically varying signal-to-noise ratio. Such cyclically gapped data is obtained from the Very Large Array (VLA), either operating as a stand-alone system or arrayed with Goldstone. This approximate model predicts that the decoder error rate will vary periodically between two discrete levels with the same period as the gap cycle. It further predicts that the length of the gapped portion of the decoder error cycle for a constraint length K decoder will be about K-1 bits shorter than the actual duration of the gap. The two-level model for Viterbi decoder performance with gapped data is subjected to detailed validation tests. Curves showing the cyclical behavior of the decoder error burst statistics are compared with the simple square-wave cycles predicted by the model. The validity of the model depends on a parameter often considered irrelevant in the analysis of Viterbi decoder performance, the overall scaling of the received signal or the decoder's branch-metrics. Three scaling alternatives are examined: optimum branch-metric scaling and constant branch-metric scaling combined with either constant noise-level scaling or constant signal-level scaling. The simulated decoder error cycle curves roughly verify the accuracy of the two-level model for both the case of optimum branch-metric scaling and the case of constant branch-metric scaling combined with constant noise-level scaling. However, the model is not accurate for the case of constant branch-metric scaling combined with constant signal-level scaling.

An improved hybrid of particle swarm optimization and the gravitational search algorithm to produce a kinetic parameter estimation of aspartate biochemical pathways.

PubMed

Ismail, Ahmad Muhaimin; Mohamad, Mohd Saberi; Abdul Majid, Hairudin; Abas, Khairul Hamimah; Deris, Safaai; Zaki, Nazar; Mohd Hashim, Siti Zaiton; Ibrahim, Zuwairie; Remli, Muhammad Akmal

2017-12-01

Mathematical modelling is fundamental to understand the dynamic behavior and regulation of the biochemical metabolisms and pathways that are found in biological systems. Pathways are used to describe complex processes that involve many parameters. It is important to have an accurate and complete set of parameters that describe the characteristics of a given model. However, measuring these parameters is typically difficult and even impossible in some cases. Furthermore, the experimental data are often incomplete and also suffer from experimental noise. These shortcomings make it challenging to identify the best-fit parameters that can represent the actual biological processes involved in biological systems. Computational approaches are required to estimate these parameters. The estimation is converted into multimodal optimization problems that require a global optimization algorithm that can avoid local solutions. These local solutions can lead to a bad fit when calibrating with a model. Although the model itself can potentially match a set of experimental data, a high-performance estimation algorithm is required to improve the quality of the solutions. This paper describes an improved hybrid of particle swarm optimization and the gravitational search algorithm (IPSOGSA) to improve the efficiency of a global optimum (the best set of kinetic parameter values) search. The findings suggest that the proposed algorithm is capable of narrowing down the search space by exploiting the feasible solution areas. Hence, the proposed algorithm is able to achieve a near-optimal set of parameters at a fast convergence speed. The proposed algorithm was tested and evaluated based on two aspartate pathways that were obtained from the BioModels Database. The results show that the proposed algorithm outperformed other standard optimization algorithms in terms of accuracy and near-optimal kinetic parameter estimation. Nevertheless, the proposed algorithm is only expected to work well in small scale systems. In addition, the results of this study can be used to estimate kinetic parameter values in the stage of model selection for different experimental conditions. Copyright © 2017 Elsevier B.V. All rights reserved.

Predicting optimum crop designs using crop models and seasonal climate forecasts.

PubMed

Rodriguez, D; de Voil, P; Hudson, D; Brown, J N; Hayman, P; Marrou, H; Meinke, H

2018-02-02

Expected increases in food demand and the need to limit the incorporation of new lands into agriculture to curtail emissions, highlight the urgency to bridge productivity gaps, increase farmers profits and manage risks in dryland cropping. A way to bridge those gaps is to identify optimum combination of genetics (G), and agronomic managements (M) i.e. crop designs (GxM), for the prevailing and expected growing environment (E). Our understanding of crop stress physiology indicates that in hindsight, those optimum crop designs should be known, while the main problem is to predict relevant attributes of the E, at the time of sowing, so that optimum GxM combinations could be informed. Here we test our capacity to inform that "hindsight", by linking a tested crop model (APSIM) with a skillful seasonal climate forecasting system, to answer "What is the value of the skill in seasonal climate forecasting, to inform crop designs?" Results showed that the GCM POAMA-2 was reliable and skillful, and that when linked with APSIM, optimum crop designs could be informed. We conclude that reliable and skillful GCMs that are easily interfaced with crop simulation models, can be used to inform optimum crop designs, increase farmers profits and reduce risks.

Reduction of tablet weight variability by optimizing paddle speed in the forced feeder of a high-speed rotary tablet press.

PubMed

Peeters, Elisabeth; De Beer, Thomas; Vervaet, Chris; Remon, Jean-Paul

2015-04-01

Tableting is a complex process due to the large number of process parameters that can be varied. Knowledge and understanding of the influence of these parameters on the final product quality is of great importance for the industry, allowing economic efficiency and parametric release. The aim of this study was to investigate the influence of paddle speeds and fill depth at different tableting speeds on the weight and weight variability of tablets. Two excipients possessing different flow behavior, microcrystalline cellulose (MCC) and dibasic calcium phosphate dihydrate (DCP), were selected as model powders. Tablets were manufactured via a high-speed rotary tablet press using design of experiments (DoE). During each experiment also the volume of powder in the forced feeder was measured. Analysis of the DoE revealed that paddle speeds are of minor importance for tablet weight but significantly affect volume of powder inside the feeder in case of powders with excellent flowability (DCP). The opposite effect of paddle speed was observed for fairly flowing powders (MCC). Tableting speed played a role in weight and weight variability, whereas changing fill depth exclusively influenced tablet weight. The DoE approach allowed predicting the optimum combination of process parameters leading to minimum tablet weight variability. Monte Carlo simulations allowed assessing the probability to exceed the acceptable response limits if factor settings were varied around their optimum. This multi-dimensional combination and interaction of input variables leading to response criteria with acceptable probability reflected the design space.

Explicit analytical tuning rules for digital PID controllers via the magnitude optimum criterion.

PubMed

Papadopoulos, Konstantinos G; Yadav, Praveen K; Margaris, Nikolaos I

2017-09-01

Analytical tuning rules for digital PID type-I controllers are presented regardless of the process complexity. This explicit solution allows control engineers 1) to make an accurate examination of the effect of the controller's sampling time to the control loop's performance both in the time and frequency domain 2) to decide when the control has to be I, PI and when the derivative, D, term has to be added or omitted 3) apply this control action to a series of stable benchmark processes regardless of their complexity. The former advantages are considered critical in industry applications, since 1) most of the times the choice of the digital controller's sampling time is based on heuristics and past criteria, 2) there is little a-priori knowledge of the controlled process making the choice of the type of the controller a trial and error exercise 3) model parameters change often depending on the control loop's operating point making in this way, the problem of retuning the controller's parameter a much challenging issue. Basis of the proposed control law is the principle of the PID tuning via the Magnitude Optimum criterion. The final control law involves the controller's sampling time T s within the explicit solution of the controller's parameters. Finally, the potential of the proposed method is justified by comparing its performance with the conventional PID tuning when controlling the same process. Further investigation regarding the choice of the controller's sampling time T s is also presented and useful conclusions for control engineers are derived. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Laser Treatment of Benign Prostatic Hyperplasia: Dosimetric and Thermodynamic Considerations

NASA Astrophysics Data System (ADS)

Anvari, Bahman

1993-01-01

Benign prostatic hyperplasia (BPH) is the most commonly occurring neoplastic disease in the aging human male. Currently, surgical treatment of BPH is the primary therapeutic method. However, due to surgical complications, less invasive methods of treatment are desirable. In recent years, thermal coagulation of the hyperplastic prostate by a laser has received a considerable amount of attention. Nevertheless, the optimum laser irradiation parameters that lead to a successful and safe treatment of BPH have not been determined. This dissertation studies the physics of laser coagulation of prostate from both basic science and practical perspectives. Optical properties of prostatic tissue are determined over a spectrum of wavelengths. Knowledge of these properties allows for selection of appropriate laser wavelengths and provides a basis for performing dose equivalency studies among various types of lasers. Furthermore, knowledge of optical properties are needed for development of computer simulation models that predict the extent of thermal injury during laser irradiation of prostate. A computer model of transurethral heating of prostate that can be used to guide the clinical studies in determining an optimum dosimetry is then presented. Studies of the effects of non-laser heating devices, optical properties, blood perfusion, surface irrigation, and beam geometry are performed to examine the extent of heat propagation within the prostate. An in vitro model for transurethral laser irradiation of prostate is also presented to examine the effects of an 810 nm diode laser, thermal boundary conditions, and energy deposition rate during Nd:YAG laser irradiation. Results of these studies suggest that in the presence of laminar irrigation, the convective boundary condition is dominated by thermal diffusion as opposed to the bulk motion of the irrigation fluid. Distinct phases of thermal events are also identified during the laser irradiation. The in vivo studies of transurethral laser irradiation of prostate in canine models are also performed to search for an optimum dosimetry that will result in a maximum zone of coagulation necrosis.

A Semi-Infinite Programming based algorithm for determining T-optimum designs for model discrimination

PubMed Central

Duarte, Belmiro P.M.; Wong, Weng Kee; Atkinson, Anthony C.

2016-01-01

T-optimum designs for model discrimination are notoriously difficult to find because of the computational difficulty involved in solving an optimization problem that involves two layers of optimization. Only a handful of analytical T-optimal designs are available for the simplest problems; the rest in the literature are found using specialized numerical procedures for a specific problem. We propose a potentially more systematic and general way for finding T-optimal designs using a Semi-Infinite Programming (SIP) approach. The strategy requires that we first reformulate the original minimax or maximin optimization problem into an equivalent semi-infinite program and solve it using an exchange-based method where lower and upper bounds produced by solving the outer and the inner programs, are iterated to convergence. A global Nonlinear Programming (NLP) solver is used to handle the subproblems, thus finding the optimal design and the least favorable parametric configuration that minimizes the residual sum of squares from the alternative or test models. We also use a nonlinear program to check the global optimality of the SIP-generated design and automate the construction of globally optimal designs. The algorithm is successfully used to produce results that coincide with several T-optimal designs reported in the literature for various types of model discrimination problems with normally distributed errors. However, our method is more general, merely requiring that the parameters of the model be estimated by a numerical optimization. PMID:27330230

A Semi-Infinite Programming based algorithm for determining T-optimum designs for model discrimination.

PubMed

Duarte, Belmiro P M; Wong, Weng Kee; Atkinson, Anthony C

2015-03-01

T-optimum designs for model discrimination are notoriously difficult to find because of the computational difficulty involved in solving an optimization problem that involves two layers of optimization. Only a handful of analytical T-optimal designs are available for the simplest problems; the rest in the literature are found using specialized numerical procedures for a specific problem. We propose a potentially more systematic and general way for finding T-optimal designs using a Semi-Infinite Programming (SIP) approach. The strategy requires that we first reformulate the original minimax or maximin optimization problem into an equivalent semi-infinite program and solve it using an exchange-based method where lower and upper bounds produced by solving the outer and the inner programs, are iterated to convergence. A global Nonlinear Programming (NLP) solver is used to handle the subproblems, thus finding the optimal design and the least favorable parametric configuration that minimizes the residual sum of squares from the alternative or test models. We also use a nonlinear program to check the global optimality of the SIP-generated design and automate the construction of globally optimal designs. The algorithm is successfully used to produce results that coincide with several T-optimal designs reported in the literature for various types of model discrimination problems with normally distributed errors. However, our method is more general, merely requiring that the parameters of the model be estimated by a numerical optimization.

Optimization of solid content, carbon/nitrogen ratio and food/inoculum ratio for biogas production from food waste.

PubMed

Dadaser-Celik, Filiz; Azgin, Sukru Taner; Yildiz, Yalcin Sevki

2016-12-01

Biogas production from food waste has been used as an efficient waste treatment option for years. The methane yields from decomposition of waste are, however, highly variable under different operating conditions. In this study, a statistical experimental design method (Taguchi OA 9 ) was implemented to investigate the effects of simultaneous variations of three parameters on methane production. The parameters investigated were solid content (SC), carbon/nitrogen ratio (C/N) and food/inoculum ratio (F/I). Two sets of experiments were conducted with nine anaerobic reactors operating under different conditions. Optimum conditions were determined using statistical analysis, such as analysis of variance (ANOVA). A confirmation experiment was carried out at optimum conditions to investigate the validity of the results. Statistical analysis showed that SC was the most important parameter for methane production with a 45% contribution, followed by F/I ratio with a 35% contribution. The optimum methane yield of 151 l kg -1 volatile solids (VS) was achieved after 24 days of digestion when SC was 4%, C/N was 28 and F/I were 0.3. The confirmation experiment provided a methane yield of 167 l kg -1 VS after 24 days. The analysis showed biogas production from food waste may be increased by optimization of operating conditions. © The Author(s) 2016.

Parameter optimization and stretch enhancement of AISI 316 sheet using rapid prototyping technique

NASA Astrophysics Data System (ADS)

Moayedfar, M.; Rani, A. M.; Hanaei, H.; Ahmad, A.; Tale, A.

2017-10-01

Incremental sheet forming is a flexible manufacturing process which uses the indenter point-to-point force to shape the sheet metal workpiece into manufactured parts in batch production series. However, the problem sometimes arising from this process is the low plastic point in the stress-strain diagram of the material which leads the low stretching amount before ultra-tensile strain point. Hence, a set of experiments is designed to find the optimum forming parameters in this process for optimum sheet thickness distribution while both sides of the sheet are considered for the surface quality improvement. A five-axis high-speed CNC milling machine is employed to deliver the proper motion based on the programming system while the clamping system for holding the sheet metal was a blank mould. Finally, an electron microscope and roughness machine are utilized to evaluate the surface structure of final parts, illustrate any defect may cause during the forming process and examine the roughness of the final part surface accordingly. The best interaction between parameters is obtained with the optimum values which lead the maximum sheet thickness distribution of 4.211e-01 logarithmic elongation when the depth was 24mm with respect to the design. This study demonstrates that this rapid forming method offers an alternative solution for surface quality improvement of 65% avoiding the low probability of cracks and low probability of crystal structure changes.

Predicting the Impact of Multiwalled Carbon Nanotubes on the Cement Hydration Products and Durability of Cementitious Matrix Using Artificial Neural Network Modeling Technique

PubMed Central

Fakhim, Babak; Hassani, Abolfazl; Rashidi, Alimorad; Ghodousi, Parviz

2013-01-01

In this study the feasibility of using the artificial neural networks modeling in predicting the effect of MWCNT on amount of cement hydration products and improving the quality of cement hydration products microstructures of cement paste was investigated. To determine the amount of cement hydration products thermogravimetric analysis was used. Two critical parameters of TGA test are PHPloss and CHloss. In order to model the TGA test results, the ANN modeling was performed on these parameters separately. In this study, 60% of data are used for model calibration and the remaining 40% are used for model verification. Based on the highest efficiency coefficient and the lowest root mean square error, the best ANN model was chosen. The results of TGA test implied that the cement hydration is enhanced in the presence of the optimum percentage (0.3 wt%) of MWCNT. Moreover, since the efficiency coefficient of the modeling results of CH and PHP loss in both the calibration and verification stages was more than 0.96, it was concluded that the ANN could be used as an accurate tool for modeling the TGA results. Another finding of this study was that the ANN prediction in higher ages was more precise. PMID:24489487

Adsorptive removal of aniline by granular activated carbon from aqueous solutions with catechol and resorcinol.

PubMed

Suresh, S; Srivastava, V C; Mishrab, I M

2012-01-01

In the present paper, the removal of aniline by adsorption process onto granular activated carbon (GAC) is reported from aqueous solutions containing catechol and resorcinol separately. The Taguchi experimental design was applied to study the effect of such parameters as the initial component concentrations (C(0,i)) of two solutes (aniline and catechol or aniline and resorcinol) in the solution, temperature (T), adsorbent dosage (m) and contact time (t). The L27 orthogonal array consisting of five parameters each with three levels was used to determine the total amount of solutes adsorbed on GAC (q(tot), mmol/g) and the signal-to-noise ratio. The analysis of variance (ANOVA) was used to determine the optimum conditions. Under these conditions, the ANOVA shows that m is the most important parameter in the adsorption process. The most favourable levels of process parameters were T = 303 K, m = 10 g/l and t = 660 min for both the systems, qtot values in the confirmation experiments carried out at optimum conditions were 0.73 and 0.95 mmol/g for aniline-catechol and aniline-resorcinol systems, respectively.

[Optimization of application parameters of soil seed bank in vegetation recovery via response surface methodology].

PubMed

He, Meng-Xuan; Li, Hong-Yuan; Mo, Xun-Qiang; Meng, Wei-Qing; Yang, Jia-Nan

2014-08-01

The thickness of surface soil, the covering thickness and the number of adding arbor seeds are all important factors to be considered in the application of soil seed bank (SSB) for vegetation recovery. To determine the optimal conditions, the Box-Behnken central composite design with three parameters and three levels was conducted and Design-Expert was used for response surface optimization. Finally, the optimal model and optimal level of each parameter were selected. The quadratic model was more suitable for response surface optimization (P < 0.0001), indicating the model had good statistical significance which could express ideal relations between all the independent variable and dependent variable. For the optimum condition, the thickness of surface soil was 4.3 cm, the covering thickness was 2 cm, and the number of adding arbor seeds was 224 ind x m(-2), under which the number of germinated seedlings could be reached up to 6222 plants x m(-2). During the process of seed germination, significant interactions between the thickness of surface soil and the covering thickness, as well as the thickness of surface soil and the number of adding arbor seeds were found, but the relationship between the covering thickness and the number of adding arbor seeds was relatively unremarkable. Among all the parameters, the thickness of surface soil was the most important one, which had the steepest curve and the largest standardized coefficient.

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

PubMed

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

2016-11-04

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

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

PubMed Central

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

2016-01-01

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

Assessment of optimum threshold and particle shape parameter for the image analysis of aggregate size distribution of concrete sections

NASA Astrophysics Data System (ADS)

Ozen, Murat; Guler, Murat

2014-02-01

Aggregate gradation is one of the key design parameters affecting the workability and strength properties of concrete mixtures. Estimating aggregate gradation from hardened concrete samples can offer valuable insights into the quality of mixtures in terms of the degree of segregation and the amount of deviation from the specified gradation limits. In this study, a methodology is introduced to determine the particle size distribution of aggregates from 2D cross sectional images of concrete samples. The samples used in the study were fabricated from six mix designs by varying the aggregate gradation, aggregate source and maximum aggregate size with five replicates of each design combination. Each sample was cut into three pieces using a diamond saw and then scanned to obtain the cross sectional images using a desktop flatbed scanner. An algorithm is proposed to determine the optimum threshold for the image analysis of the cross sections. A procedure was also suggested to determine a suitable particle shape parameter to be used in the analysis of aggregate size distribution within each cross section. Results of analyses indicated that the optimum threshold hence the pixel distribution functions may be different even for the cross sections of an identical concrete sample. Besides, the maximum ferret diameter is the most suitable shape parameter to estimate the size distribution of aggregates when computed based on the diagonal sieve opening. The outcome of this study can be of practical value for the practitioners to evaluate concrete in terms of the degree of segregation and the bounds of mixture's gradation achieved during manufacturing.

Optimum structural design with static aeroelastic constraints

NASA Technical Reports Server (NTRS)

Bowman, Keith B; Grandhi, Ramana V.; Eastep, F. E.

1989-01-01

The static aeroelastic performance characteristics, divergence velocity, control effectiveness and lift effectiveness are considered in obtaining an optimum weight structure. A typical swept wing structure is used with upper and lower skins, spar and rib thicknesses, and spar cap and vertical post cross-sectional areas as the design parameters. Incompressible aerodynamic strip theory is used to derive the constraint formulations, and aerodynamic load matrices. A Sequential Unconstrained Minimization Technique (SUMT) algorithm is used to optimize the wing structure to meet the desired performance constraints.

On wings and keels (2)

NASA Astrophysics Data System (ADS)

Slooff, J. W.

1985-05-01

The physical mechanisms governing the hydrodynamics of sailing yacht keels and the parameters that, through these mechanisms, determine keel performance are discussed. It is concluded that due to the presence of the free water surface optimum keel shapes differ from optimum shapes for aircraft wings. Utilizing computational fluid dynamics analysis and optimization it is found that the performance of conventional keels can be improved significantly by reducing taper or even applying inverse taper (upside-down keel) and that decisive improvements in performance can be realized through keels with winglets.

Glass microneedles for force measurements: a finite-element analysis model

PubMed Central

Ayittey, Peter N.; Walker, John S.; Rice, Jeremy J.; de Tombe, Pieter P.

2010-01-01

Changes in developed force (0.1–3.0 μN) observed during contraction of single myofibrils in response to rapidly changing calcium concentrations can be measured using glass microneedles. These microneedles are calibrated for stiffness and deflect on response to developed myofibril force. The precision and accuracy of kinetic measurements are highly dependent on the structural and mechanical characteristics of the microneedles, which are generally assumed to have a linear force–deflection relationship. We present a finite-element analysis (FEA) model used to simulate the effects of measurable geometry on stiffness as a function of applied force and validate our model with actual measured needle properties. In addition, we developed a simple heuristic constitutive equation that best describes the stiffness of our range of microneedles used and define limits of geometry parameters within which our predictions hold true. Our model also maps a relation between the geometry parameters and natural frequencies in air, enabling optimum parametric combinations for microneedle fabrication that would reflect more reliable force measurement in fluids and physiological environments. We propose a use for this model to aid in the design of microneedles to improve calibration time, reproducibility, and precision for measuring myofibrillar, cellular, and supramolecular kinetic forces. PMID:19104827

Gene flow from domesticated species to wild relatives: migration load in a model of multivariate selection.

PubMed

Tufto, Jarle

2010-01-01

Domesticated species frequently spread their genes into populations of wild relatives through interbreeding. The domestication process often involves artificial selection for economically desirable traits. This can lead to an indirect response in unknown correlated traits and a reduction in fitness of domesticated individuals in the wild. Previous models for the effect of gene flow from domesticated species to wild relatives have assumed that evolution occurs in one dimension. Here, I develop a quantitative genetic model for the balance between migration and multivariate stabilizing selection. Different forms of correlational selection consistent with a given observed ratio between average fitness of domesticated and wild individuals offsets the phenotypic means at migration-selection balance away from predictions based on simpler one-dimensional models. For almost all parameter values, correlational selection leads to a reduction in the migration load. For ridge selection, this reduction arises because the distance the immigrants deviates from the local optimum in effect is reduced. For realistic parameter values, however, the effect of correlational selection on the load is small, suggesting that simpler one-dimensional models may still be adequate in terms of predicting mean population fitness and viability.

Optimum wall impedance for spinning modes: A correlation with mode cut-off ratio

NASA Technical Reports Server (NTRS)

Rice, E. J.

1978-01-01

A correlating equation relating the optimum acoustic impedance for the wall lining of a circular duct to the acoustic mode cut-off ratio, is presented. The optimum impedance was correlated with cut-off ratio because the cut-off ratio appears to be the fundamental parameter governing the propagation of sound in the duct. Modes with similar cut-off ratios respond in a similar way to the acoustic liner. The correlation is a semi-empirical expression developed from an empirical modification of an equation originally derived from sound propagation theory in a thin boundary layer. This correlating equation represents a part of a simplified liner design method, based upon modal cut-off ratio, for multimodal noise propagation.

Comparative evaluation of distributed-collector solar thermal electric power plants

NASA Technical Reports Server (NTRS)

Fujita, T.; El Gabalawi, N.; Herrera, G. G.; Caputo, R. S.

1978-01-01

Distributed-collector solar thermal-electric power plants are compared by projecting power plant economics of selected systems to the 1990-2000 timeframe. The approach taken is to evaluate the performance of the selected systems under the same weather conditions. Capital and operational costs are estimated for each system. Energy costs are calculated for different plant sizes based on the plant performance and the corresponding capital and maintenance costs. Optimum systems are then determined as the systems with the minimum energy costs for a given load factor. The optimum system is comprised of the best combination of subsystems which give the minimum energy cost for every plant size. Sensitivity analysis is done around the optimum point for various plant parameters.

A reliability-based cost effective fail-safe design procedure

NASA Technical Reports Server (NTRS)

Hanagud, S.; Uppaluri, B.

1976-01-01

The authors have developed a methodology for cost-effective fatigue design of structures subject to random fatigue loading. A stochastic model for fatigue crack propagation under random loading has been discussed. Fracture mechanics is then used to estimate the parameters of the model and the residual strength of structures with cracks. The stochastic model and residual strength variations have been used to develop procedures for estimating the probability of failure and its changes with inspection frequency. This information on reliability is then used to construct an objective function in terms of either a total weight function or cost function. A procedure for selecting the design variables, subject to constraints, by optimizing the objective function has been illustrated by examples. In particular, optimum design of stiffened panel has been discussed.

A quality by design approach to understand formulation and process variability in pharmaceutical melt extrusion processes.

PubMed

Patwardhan, Ketaki; Asgarzadeh, Firouz; Dassinger, Thomas; Albers, Jessica; Repka, Michael A

2015-05-01

In this study, the principles of quality by design (QbD) have been uniquely applied to a pharmaceutical melt extrusion process for an immediate release formulation with a low melting model drug, ibuprofen. Two qualitative risk assessment tools - Fishbone diagram and failure mode effect analysis - were utilized to strategically narrow down the most influential parameters. Selected variables were further assessed using a Plackett-Burman screening study, which was upgraded to a response surface design consisting of the critical factors to study the interactions between the study variables. In process torque, glass transition temperature (Tg ) of the extrudates, assay, dissolution and phase change were measured as responses to evaluate the critical quality attributes (CQAs) of the extrudates. The effect of each study variable on the measured responses was analysed using multiple regression for the screening design and partial least squares for the optimization design. Experimental limits for formulation and process parameters to attain optimum processing have been outlined. A design space plot describing the domain of experimental variables within which the CQAs remained unchanged was developed. A comprehensive approach for melt extrusion product development based on the QbD methodology has been demonstrated. Drug loading concentrations between 40- 48%w/w and extrusion temperature in the range of 90-130°C were found to be the most optimum. © 2015 Royal Pharmaceutical Society.

Finite horizon EOQ model for non-instantaneous deteriorating items with price and advertisement dependent demand and partial backlogging under inflation

NASA Astrophysics Data System (ADS)

Palanivel, M.; Uthayakumar, R.

2015-07-01

This paper deals with an economic order quantity (EOQ) model for non-instantaneous deteriorating items with price and advertisement dependent demand pattern under the effect of inflation and time value of money over a finite planning horizon. In this model, shortages are allowed and partially backlogged. The backlogging rate is dependent on the waiting time for the next replenishment. This paper aids the retailer in minimising the total inventory cost by finding the optimal interval and the optimal order quantity. An algorithm is designed to find the optimum solution of the proposed model. Numerical examples are given to demonstrate the results. Also, the effect of changes in the different parameters on the optimal total cost is graphically presented and the implications are discussed in detail.

Extensions of D-optimal Minimal Designs for Symmetric Mixture Models.

PubMed

Li, Yanyan; Raghavarao, Damaraju; Chervoneva, Inna

2017-01-01

The purpose of mixture experiments is to explore the optimum blends of mixture components, which will provide desirable response characteristics in finished products. D-optimal minimal designs have been considered for a variety of mixture models, including Scheffé's linear, quadratic, and cubic models. Usually, these D-optimal designs are minimally supported since they have just as many design points as the number of parameters. Thus, they lack the degrees of freedom to perform the Lack of Fit tests. Also, the majority of the design points in D-optimal minimal designs are on the boundary: vertices, edges, or faces of the design simplex. Also a new strategy for adding multiple interior points for symmetric mixture models is proposed. We compare the proposed designs with Cornell (1986) two ten-point designs for the Lack of Fit test by simulations.

Dynamics of microbial growth and metabolic activity and their control by aeration.

PubMed

Kalina, V

1993-01-01

The optimization of fermentation processes depends to a large extent on the modelling of microbial activity under complex environmental conditions where aeration is an important limiting and control factor. Simple relationships are used to establish the sensitivity of cultures to oxygen stress. Specific limitation coefficients which can be determined in laboratory reactors allow a projection to industrial operation and the definition of appropriate aeration and agitation profiles. Optimum control can be assured on the basis of directly measurable process parameters. This is shown for the case of ethanol production using S. cerevisiae at high cell dry weight concentrations.

Optimum Multisensor, Multitarget Localization and Tracking.

DTIC Science & Technology

1983-06-07

parameter vector t is given by (see Equation (3.5.1-7)’ the simul- taneous solution of A(e) N B G --1 ae &j’ -4n-in (fk’ ijn k3jn ~ k )kjn kjn - knn =1 k...the coefficient of mutual dependence given by M = 12 -(K-2) 121M12 :(3l 11J12 ) (K-2 and Jij is given by (see Equation (6.4.1-2)) - - (_ I R knN kn K...Transactions on Acoustic, Speech and Signal Processing, Vol ASSP-29, No. 3, June 1981. 17. B. Friedlander, "An ARMA Modeling Approach to Multitarget Tracking

Slot Optimization Design of Induction Motor for Electric Vehicle

NASA Astrophysics Data System (ADS)

Shen, Yiming; Zhu, Changqing; Wang, Xiuhe

2018-01-01

Slot design of induction motor has a great influence on its performance. The RMxprt module based on magnetic circuit method can be used to analyze the influence of rotor slot type on motor characteristics and optimize slot parameters. In this paper, the authors take an induction motor of electric vehicle for a typical example. The first step of the design is to optimize the rotor slot by RMxprt, and then compare the main performance of the motor before and after the optimization through Ansoft Maxwell 2D. After that, the combination of optimum slot type and the optimum parameters are obtained. The results show that the power factor and the starting torque of the optimized motor have been improved significantly. Furthermore, the electric vehicle works at a better running status after the optimization.

Roll tracking effects of G-vector tilt and various types of motion washout

NASA Technical Reports Server (NTRS)

Jex, H. R.; Magdaleno, R. E.; Junker, A. M.

1978-01-01

In a dogfight scenario, the task was to follow the target's roll angle while suppressing gust disturbances. All subjects adopted the same behavioral strategies in following the target while suppressing the gusts, and the MFP-fitted math model response was generally within one data symbol width. The results include the following: (1) comparisons of full roll motion (both with and without the spurious gravity tilt cue) with the static case. These motion cues help suppress disturbances with little net effect on the visual performance. Tilt cues were clearly used by the pilots but gave only small improvement in tracking errors. (2) The optimum washout (in terms of performance close to real world, similar behavioral parameters, significant motion attenuation (60 percent), and acceptable motion fidelity) was the combined attenuation and first-order washout. (3) Various trends in parameters across the motion conditions were apparent, and are discussed with respect to a comprehensive model for predicting adaptation to various roll motion cues.

Ecological optimality in water-limited natural soil-vegetation systems. I - Theory and hypothesis

NASA Technical Reports Server (NTRS)

Eagleson, P. S.

1982-01-01

The solution space of an approximate statistical-dynamic model of the average annual water balance is explored with respect to the hydrologic parameters of both soil and vegetation. Within the accuracy of this model it is shown that water-limited natural vegetation systems are in stable equilibrium with their climatic and pedologic environments when the canopy density and species act to minimize average water demand stress. Theory shows a climatic limit to this equilibrium above which it is hypothesized that ecological pressure is toward maximization of biomass productivity. It is further hypothesized that natural soil-vegetation systems will develop gradually and synergistically, through vegetation-induced changes in soil structure, toward a set of hydraulic soil properties for which the minimum stress canopy density of a given species is maximum in a given climate. Using these hypotheses, only the soil effective porosity need be known to determine the optimum soil and vegetation parameters in a given climate.

Well-behaved relativistic charged super-dense star models

NASA Astrophysics Data System (ADS)

Faruqi, Shahab; Pant, Neeraj

2012-10-01

A new class of charged super-dense star models is obtained by using an electric intensity, which involves a parameter, K. The metric describing the model shares its metric potential g 44 with that of Durgapal's fourth solution (J. Phys. A, Math. Gen. 15:2637, 1982). The pressure-free surface is kept at the density ρ b =2×1014 g/cm3 and joins smoothly with the Reissner-Nordstrom solution. The charge analogues are well-behaved for a wide range, 0≤ K≤59, with the optimum value of X=0.264 i.e. the pressure, density, pressure-density ratio and velocity of sound are monotonically decreasing and the electric intensity is monotonically increasing in nature for the given range of the parameter K. The maximum mass and the corresponding radius occupied by the neutral solution are 4.22 M Θ and 20 km, respectively for X=0.264. For the charged solution, the maximum mass and radius are defined by the expressions M≈(0.0059 K+4.22) M Θ and r b ≈-0.021464 K+20 km respectively.

TWO-LAYER MODEL FOR PULL-OUT BEHAVIOR OF POST-INSTALLED ANCHOR

NASA Astrophysics Data System (ADS)

Saleem, Muhammad; Tsubaki, Tatsuya

A new two-layer anchor-infill assembly structure for the post-installed anchor is introduced with the analytical model to simulate its pull-out deformational response. The post-installed anchor is such that used in strengthening techniques for reinforced concrete structures. The properties of the infill material used for post-installed anchor are characterized by nonlinear interfaces. Because of the mechanical properties of the infill layer the existing pull-out model of deformed bars is not applicable in this case. Interfacial de-bonding is examined using energy criterion and strength criterion. The effect of the interface properties such as stiffness and strength on the pull-out behavior of a post-installed anchor is investigated. Using sensitivity analysis, the effect of these parameters on load-displacement curve, shear stress distribution, de-bonded length and damage to the surrounding concrete is clarified. Then, the optimum combination of these parameters is presented. It is confirmed that the elastic modulus of infill should be large to reduce the pull-out displacement and the increase of the shear strength of infill makes the pull-out load larger.

Using Central Composite Experimental Design to Optimize the Degradation of Tylosin from Aqueous Solution by Photo-Fenton Reaction

PubMed Central

Sarrai, Abd Elaziz; Hanini, Salah; Merzouk, Nachida Kasbadji; Tassalit, Djilali; Szabó, Tibor; Hernádi, Klára; Nagy, László

2016-01-01

The feasibility of the application of the Photo-Fenton process in the treatment of aqueous solution contaminated by Tylosin antibiotic was evaluated. The Response Surface Methodology (RSM) based on Central Composite Design (CCD) was used to evaluate and optimize the effect of hydrogen peroxide, ferrous ion concentration and initial pH as independent variables on the total organic carbon (TOC) removal as the response function. The interaction effects and optimal parameters were obtained by using MODDE software. The significance of the independent variables and their interactions was tested by means of analysis of variance (ANOVA) with a 95% confidence level. Results show that the concentration of the ferrous ion and pH were the main parameters affecting TOC removal, while peroxide concentration had a slight effect on the reaction. The optimum operating conditions to achieve maximum TOC removal were determined. The model prediction for maximum TOC removal was compared to the experimental result at optimal operating conditions. A good agreement between the model prediction and experimental results confirms the soundness of the developed model. PMID:28773551

Linking density functional and mode coupling models for supercooled liquids

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

Premkumar, Leishangthem; Bidhoodi, Neeta; Das, Shankar P.

2016-03-28

We compare predictions from two familiar models of the metastable supercooled liquid, respectively, constructed with thermodynamic and dynamic approaches. In the so called density functional theory the free energy F[ρ] of the liquid is a functional of the inhomogeneous density ρ(r). The metastable state is identified as a local minimum of F[ρ]. The sharp density profile characterizing ρ(r) is identified as a single particle oscillator, whose frequency is obtained from the parameters of the optimum density function. On the other hand, a dynamic approach to supercooled liquids is taken in the mode coupling theory (MCT) which predict a sharp ergodicity-non-ergodicitymore » transition at a critical density. The single particle dynamics in the non-ergodic state, treated approximately, represents a propagating mode whose characteristic frequency is computed from the corresponding memory function of the MCT. The mass localization parameters in the above two models (treated in their simplest forms) are obtained, respectively, in terms of the corresponding natural frequencies depicted and are shown to have comparable magnitudes.« less

Model analysis and electrical characterization of atmospheric pressure cold plasma jet in pin electrode configuration

NASA Astrophysics Data System (ADS)

Deepak, G. Divya; Joshi, N. K.; Prakash, Ram

2018-05-01

In this study, both model analysis and electrical characterization of a dielectric barrier discharge based argon plasma jet have been carried at atmospheric pressure in a pin electrode configuration. The plasma and fluid dynamics modules of COMSOL multi-physics code have been used for the modeling of the plasma jet. The plasma parameters, such as, electron density, electron temperature and electrical potential have been analyzed with respect to the electrical parameters, i.e., supply voltage and supply frequency with and without the flow of gas. In all the experiments, gas flow rate has been kept constant at 1 liter per minute. This electrode configuration is subjected to a range of supply frequencies (10-25 kHz) and supply voltages (3.5-6.5 kV). The power consumed by the device has been estimated at different applied combinations (supply voltage & frequency) for optimum power consumption at maximum jet length. The maximum power consumed by the device in this configuration for maximum jet length of ˜26 mm is just ˜1 W.

Study of optimum methods of optical communication

NASA Technical Reports Server (NTRS)

Harger, R. O.

1972-01-01

Optimum methods of optical communication accounting for the effects of the turbulent atmosphere and quantum mechanics, both by the semi-classical method and the full-fledged quantum theoretical model are described. A concerted effort to apply the techniques of communication theory to the novel problems of optical communication by a careful study of realistic models and their statistical descriptions, the finding of appropriate optimum structures and the calculation of their performance and, insofar as possible, comparing them to conventional and other suboptimal systems are discussed. In this unified way the bounds on performance and the structure of optimum communication systems for transmission of information, imaging, tracking, and estimation can be determined for optical channels.

Production and characterization of cowpea protein hydrolysate with optimum nitrogen solubility by enzymatic hydrolysis using pepsin.

PubMed

Mune Mune, Martin Alain; Minka, Samuel René

2017-06-01

Cowpea is a source of low-cost and good nutritional quality protein for utilization in food formulations in replacement of animal proteins. Therefore it is necessary that cowpea protein exhibits good functionality, particularly protein solubility which affects the other functional properties. The objective of this study was to produce cowpea protein hydrolysate exhibiting optimum solubility by the adequate combination of hydrolysis parameters, namely time, solid/liquid ratio (SLR) and enzyme/substrate ratio (ESR), and to determine its functional properties and molecular characteristics. A Box-Behnken experimental design was used for the experiments, and a second-order polynomial to model the effects of hydrolysis time, SLR and ESR on the degree of hydrolysis and nitrogen solubility index. The optimum hydrolysis conditions of time 208.61 min, SLR 1/15 (w/w) and ESR 2.25% (w/w) yielded a nitrogen solubility of 75.71%. Protein breakdown and the peptide profile following enzymatic hydrolysis were evaluated by sodium dodecyl sulfate polyacrylamide gel electrophoresis and size exclusion chromatography. Cowpea protein hydrolysate showed higher oil absorption capacity, emulsifying activity and foaming ability compared with the concentrate. The solubility of cowpea protein hydrolysate was adequately optimized by response surface methodology, and the hydrolysate showed adequate functionality for use in food. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

Parameter Estimation as a Problem in Statistical Thermodynamics.

PubMed

Earle, Keith A; Schneider, David J

2011-03-14

In this work, we explore the connections between parameter fitting and statistical thermodynamics using the maxent principle of Jaynes as a starting point. In particular, we show how signal averaging may be described by a suitable one particle partition function, modified for the case of a variable number of particles. These modifications lead to an entropy that is extensive in the number of measurements in the average. Systematic error may be interpreted as a departure from ideal gas behavior. In addition, we show how to combine measurements from different experiments in an unbiased way in order to maximize the entropy of simultaneous parameter fitting. We suggest that fit parameters may be interpreted as generalized coordinates and the forces conjugate to them may be derived from the system partition function. From this perspective, the parameter fitting problem may be interpreted as a process where the system (spectrum) does work against internal stresses (non-optimum model parameters) to achieve a state of minimum free energy/maximum entropy. Finally, we show how the distribution function allows us to define a geometry on parameter space, building on previous work[1, 2]. This geometry has implications for error estimation and we outline a program for incorporating these geometrical insights into an automated parameter fitting algorithm.

Parameter identification studies on the NASA/Ames Research Center Advanced Concepts Flight Simulator. M.S. Thesis

NASA Technical Reports Server (NTRS)

Mckavitt, Thomas P., Jr.

1990-01-01

The results of an aircraft parameters identification study conducted on the National Aeronautics and Space Administration/Ames Research Center Advanced Concepts Flight Simulator (ACFS) in conjunction with the Navy-NASA Joint Institute of Aeronautics are given. The ACFS is a commercial airline simulator with a design based on future technology. The simulator is used as a laboratory for human factors research and engineering as applied to the commercial airline industry. Parametric areas examined were engine pressure ratio (EPR), optimum long range cruise Mach number, flap reference speed, and critical take-off speeds. Results were compared with corresponding parameters of the Boeing 757 and 767 aircraft. This comparison identified two areas where improvements can be made: (1) low maximum lift coefficients (on the order of 20-25 percent less than those of a 757); and (2) low optimum cruise Mach numbers. Recommendations were made to those anticipated with the application of future technologies.

Analysis of light emitting diode array lighting system based on human vision: normal and abnormal uniformity condition.

PubMed

Qin, Zong; Ji, Chuangang; Wang, Kai; Liu, Sheng

2012-10-08

In this paper, condition for uniform lighting generated by light emitting diode (LED) array was systematically studied. To take human vision effect into consideration, contrast sensitivity function (CSF) was novelly adopted as critical criterion for uniform lighting instead of conventionally used Sparrow's Criterion (SC). Through CSF method, design parameters including system thickness, LED pitch, LED's spatial radiation distribution and viewing condition can be analytically combined. In a specific LED array lighting system (LALS) with foursquare LED arrangement, different types of LEDs (Lambertian and Batwing type) and given viewing condition, optimum system thicknesses and LED pitches were calculated and compared with those got through SC method. Results show that CSF method can achieve more appropriate optimum parameters than SC method. Additionally, an abnormal phenomenon that uniformity varies with structural parameters non-monotonically in LALS with non-Lambertian LEDs was found and analyzed. Based on the analysis, a design method of LALS that can bring about better practicability, lower cost and more attractive appearance was summarized.

Application of Differential Evolutionary Optimization Methodology for Parameter Structure Identification in Groundwater Modeling

NASA Astrophysics Data System (ADS)

Chiu, Y.; Nishikawa, T.

2013-12-01

With the increasing complexity of parameter-structure identification (PSI) in groundwater modeling, there is a need for robust, fast, and accurate optimizers in the groundwater-hydrology field. For this work, PSI is defined as identifying parameter dimension, structure, and value. In this study, Voronoi tessellation and differential evolution (DE) are used to solve the optimal PSI problem. Voronoi tessellation is used for automatic parameterization, whereby stepwise regression and the error covariance matrix are used to determine the optimal parameter dimension. DE is a novel global optimizer that can be used to solve nonlinear, nondifferentiable, and multimodal optimization problems. It can be viewed as an improved version of genetic algorithms and employs a simple cycle of mutation, crossover, and selection operations. DE is used to estimate the optimal parameter structure and its associated values. A synthetic numerical experiment of continuous hydraulic conductivity distribution was conducted to demonstrate the proposed methodology. The results indicate that DE can identify the global optimum effectively and efficiently. A sensitivity analysis of the control parameters (i.e., the population size, mutation scaling factor, crossover rate, and mutation schemes) was performed to examine their influence on the objective function. The proposed DE was then applied to solve a complex parameter-estimation problem for a small desert groundwater basin in Southern California. Hydraulic conductivity, specific yield, specific storage, fault conductance, and recharge components were estimated simultaneously. Comparison of DE and a traditional gradient-based approach (PEST) shows DE to be more robust and efficient. The results of this work not only provide an alternative for PSI in groundwater models, but also extend DE applications towards solving complex, regional-scale water management optimization problems.

Fault Slip Distribution and Optimum Sea Surface Displacement of the 2017 Tehuantepec Earthquake in Mexico (Mw 8.2) Estimated from Tsunami Waveforms

NASA Astrophysics Data System (ADS)

Gusman, A. R.; Satake, K.; Mulia, I. E.

2017-12-01

An intraplate normal fault earthquake (Mw 8.2) occurred on 8 September 2017 in the Tehuantepec seismic gap of the Middle America Trench. The submarine earthquake generated a tsunami which was recorded by coastal tide gauges and offshore DART buoys. We used the tsunami waveforms recorded at 16 stations to estimate the fault slip distribution and an optimum sea surface displacement of the earthquake. A steep fault dipping to the northeast with strike of 315°, dip of 73°and rake of -96° based on the USGS W-phase moment tensor solution was assumed for the slip inversion. To independently estimate the sea surface displacement without assuming earthquake fault parameters, we used the B-spline function for the unit sources. The distribution of the unit sources was optimized by a Genetic Algorithm - Pattern Search (GA-PS) method. Tsunami waveform inversion resolves a spatially compact region of large slip (4-10 m) with a dimension of 100 km along the strike and 80 km along the dip in the depth range between 40 km and 110 km. The seismic moment calculated from the fault slip distribution with assumed rigidity of 6 × 1010 Nm-2 is 2.46 × 1021 Nm (Mw 8.2). The optimum displacement model suggests that the sea surface was uplifted up to 0.5 m and subsided down to -0.8 m. The deep location of large fault slip may be the cause of such small sea surface displacements. The simulated tsunami waveforms from the optimum sea surface displacement can reproduce the observations better than those from fault slip distribution; the normalized root mean square misfit for the sea surface displacement is 0.89, while that for the fault slip distribution is 1.04. We simulated the tsunami propagation using the optimum sea surface displacement model. Large tsunami amplitudes up to 2.5 m were predicted to occur inside and around a lagoon located between Salina Cruz and Puerto Chiapas. Figure 1. a) Sea surface displacement for the 2017 Tehuantepec earthquake estimated by tsunami waveforms. b) Map of simulated maximum tsunami amplitude and comparison between observed (blue circles) and simulated (red circles) tsunami maximum amplitude along the coast.

Melt-Pool Temperature and Size Measurement During Direct Laser Sintering

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

List, III, Frederick Alyious; Dinwiddie, Ralph Barton; Carver, Keith

2017-08-01

Additive manufacturing has demonstrated the ability to fabricate complex geometries and components not possible with conventional casting and machining. In many cases, industry has demonstrated the ability to fabricate complex geometries with improved efficiency and performance. However, qualification and certification of processes is challenging, leaving companies to focus on certification of material though design allowable based approaches. This significantly reduces the business case for additive manufacturing. Therefore, real time monitoring of the melt pool can be used to detect the development of flaws, such as porosity or un-sintered powder and aid in the certification process. Characteristics of the melt poolmore » in the Direct Laser Sintering (DLS) process is also of great interest to modelers who are developing simulation models needed to improve and perfect the DLS process. Such models could provide a means to rapidly develop the optimum processing parameters for new alloy powders and optimize processing parameters for specific part geometries. Stratonics’ ThermaViz system will be integrated with the Renishaw DLS system in order to demonstrate its ability to measure melt pool size, shape and temperature. These results will be compared with data from an existing IR camera to determine the best approach for the determination of these critical parameters.« less

Liquid Phase adsorption kinetics and equilibrium of toluene by novel modified-diatomite.

PubMed

Sheshdeh, Reza Khalighi; Abbasizadeh, Saeed; Nikou, Mohammad Reza Khosravi; Badii, Khashayar; Sharafi, Mohammad Sadegh

2014-01-01

The adsorption equilibria of toluene from aqueous solutions on natural and modified diatomite were examined at different operation parameters such as pH, contact time, initial toluene concentration was evaluated and optimum experimental conditions were identified. The surface area and morphology of the nanoparticles were characterized by SEM, BET, XRD, FTIR and EDX analysis. It was found that in order to obtain the highest possible removal of toluene, the experiments can be carried out at pH 6, temperature 25°C, an agitation speed of 200 rpm, an initial toluene concentration of 150 mg/L, a centrifugal rate of 4000 rpm, adsorbent dosage = 0.1 g and a process time of 90 min. The results of this work show that the maximum percentage removal of toluene from aqueous solution in the optimum conditions for NONMD was 96.91% (145.36 mg/g). Furthermore, under same conditions, the maximum adsorption of natural diatomite was 71.45% (107.18 mg/g). Both adsorption kinetic and isotherm experiments were carried out. The experimental data showed that the adsorption follows the Langmuir model and Freundlich model on natural and modified diatomite respectively. The kinetics results were found to conform well to pseudo-second order kinetics model with good correlation. Thus, this study demonstrated that the modified diatomite could be used as potential adsorbent for removal of toluene from aqueous solution.

Modeling and Multiresponse Optimization for Anaerobic Codigestion of Oil Refinery Wastewater and Chicken Manure by Using Artificial Neural Network and the Taguchi Method

PubMed Central

Hemmat, Abbas; Kafashan, Jalal; Huang, Hongying

2017-01-01

To study the optimum process conditions for pretreatments and anaerobic codigestion of oil refinery wastewater (ORWW) with chicken manure, L9 (34) Taguchi's orthogonal array was applied. The biogas production (BGP), biomethane content (BMP), and chemical oxygen demand solubilization (CODS) in stabilization rate were evaluated as the process outputs. The optimum conditions were obtained by using Design Expert software (Version 7.0.0). The results indicated that the optimum conditions could be achieved with 44% ORWW, 36°C temperature, 30 min sonication, and 6% TS in the digester. The optimum BGP, BMP, and CODS removal rates by using the optimum conditions were 294.76 mL/gVS, 151.95 mL/gVS, and 70.22%, respectively, as concluded by the experimental results. In addition, the artificial neural network (ANN) technique was implemented to develop an ANN model for predicting BGP yield and BMP content. The Levenberg-Marquardt algorithm was utilized to train ANN, and the architecture of 9-19-2 for the ANN model was obtained. PMID:29441352

Using texture analysis to improve per-pixel classification of very high resolution images for mapping plastic greenhouses

NASA Astrophysics Data System (ADS)

Agüera, Francisco; Aguilar, Fernando J.; Aguilar, Manuel A.

The area occupied by plastic-covered greenhouses has undergone rapid growth in recent years, currently exceeding 500,000 ha worldwide. Due to the vast amount of input (water, fertilisers, fuel, etc.) required, and output of different agricultural wastes (vegetable, plastic, chemical, etc.), the environmental impact of this type of production system can be serious if not accompanied by sound and sustainable territorial planning. For this, the new generation of satellites which provide very high resolution imagery, such as QuickBird and IKONOS can be useful. In this study, one QuickBird and one IKONOS satellite image have been used to cover the same area under similar circumstances. The aim of this work was an exhaustive comparison of QuickBird vs. IKONOS images in land-cover detection. In terms of plastic greenhouse mapping, comparative tests were designed and implemented, each with separate objectives. Firstly, the Maximum Likelihood Classification (MLC) was applied using five different approaches combining R, G, B, NIR, and panchromatic bands. The combinations of the bands used, significantly influenced some of the indexes used to classify quality in this work. Furthermore, the quality classification of the QuickBird image was higher in all cases than that of the IKONOS image. Secondly, texture features derived from the panchromatic images at different window sizes and with different grey levels were added as a fifth band to the R, G, B, NIR images to carry out the MLC. The inclusion of texture information in the classification did not improve the classification quality. For classifications with texture information, the best accuracies were found in both images for mean and angular second moment texture parameters. The optimum window size in these texture parameters was 3×3 for IK images, while for QB images it depended on the quality index studied, but the optimum window size was around 15×15. With regard to the grey level, the optimum was 128. Thus, the optimum texture parameter depended on the main objective of the image classification. If the main classification goal is to minimize the number of pixels wrongly classified, the mean texture parameter should be used, whereas if the main classification goal is to minimize the unclassified pixels the angular second moment texture parameter should be used. On the whole, both QuickBird and IKONOS images offered promising results in classifying plastic greenhouses.

Method and Apparatus to Access Optimum Strength During Processing of Precipitation Strengthened Alloys

NASA Technical Reports Server (NTRS)

Cantrell, John H. (Inventor); Yost, William T. (Inventor)

2001-01-01

A method and apparatus are provided which enable the nondestructive testing of strength of a heat treated alloy. An alloy is insonified with an ultrasonic signal. The resulting convoluted signal is detected and the acoustic nonlinearity parameter is determined. The acoustic nonlinearity parameter shows a peak corresponding to a peak in material strength.

The application of the pilot points in groundwater numerical inversion model

NASA Astrophysics Data System (ADS)

Hu, Bin; Teng, Yanguo; Cheng, Lirong

2015-04-01

Numerical inversion simulation of groundwater has been widely applied in groundwater. Compared to traditional forward modeling, inversion model has more space to study. Zones and inversing modeling cell by cell are conventional methods. Pilot points is a method between them. The traditional inverse modeling method often uses software dividing the model into several zones with a few parameters needed to be inversed. However, distribution is usually too simple for modeler and result of simulation deviation. Inverse cell by cell will get the most actual parameter distribution in theory, but it need computational complexity greatly and quantity of survey data for geological statistical simulation areas. Compared to those methods, pilot points distribute a set of points throughout the different model domains for parameter estimation. Property values are assigned to model cells by Kriging to ensure geological units within the parameters of heterogeneity. It will reduce requirements of simulation area geological statistics and offset the gap between above methods. Pilot points can not only save calculation time, increase fitting degree, but also reduce instability of numerical model caused by numbers of parameters and other advantages. In this paper, we use pilot point in a field which structure formation heterogeneity and hydraulics parameter was unknown. We compare inversion modeling results of zones and pilot point methods. With the method of comparative analysis, we explore the characteristic of pilot point in groundwater inversion model. First, modeler generates an initial spatially correlated field given a geostatistical model by the description of the case site with the software named Groundwater Vistas 6. Defining Kriging to obtain the value of the field functions over the model domain on the basis of their values at measurement and pilot point locations (hydraulic conductivity), then we assign pilot points to the interpolated field which have been divided into 4 zones. And add range of disturbance values to inversion targets to calculate the value of hydraulic conductivity. Third, after inversion calculation (PEST), the interpolated field will minimize an objective function measuring the misfit between calculated and measured data. It's an optimization problem to find the optimum value of parameters. After the inversion modeling, the following major conclusion can be found out: (1) In a field structure formation is heterogeneity, the results of pilot point method is more real: better fitting result of parameters, more stable calculation of numerical simulation (stable residual distribution). Compared to zones, it is better of reflecting the heterogeneity of study field. (2) Pilot point method ensures that each parameter is sensitive and not entirely dependent on other parameters. Thus it guarantees the relative independence and authenticity of parameters evaluation results. However, it costs more time to calculate than zones. Key words: groundwater; pilot point; inverse model; heterogeneity; hydraulic conductivity

Markov Chain Monte Carlo Used in Parameter Inference of Magnetic Resonance Spectra

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

Hock, Kiel; Earle, Keith

2016-02-06

In this paper, we use Boltzmann statistics and the maximum likelihood distribution derived from Bayes’ Theorem to infer parameter values for a Pake Doublet Spectrum, a lineshape of historical significance and contemporary relevance for determining distances between interacting magnetic dipoles. A Metropolis Hastings Markov Chain Monte Carlo algorithm is implemented and designed to find the optimum parameter set and to estimate parameter uncertainties. In conclusion, the posterior distribution allows us to define a metric on parameter space that induces a geometry with negative curvature that affects the parameter uncertainty estimates, particularly for spectra with low signal to noise.

Studies on plasma profiles and its effect on dust charging in hydrogen plasma

NASA Astrophysics Data System (ADS)

Kakati, B.; Kausik, S. S.; Saikia, B. K.; Bandyopadhay, M.

2010-02-01

Plasma profiles and its influence on dust charging are studied in hydrogen plasma. The plasma is produced in a high vacuum device by a hot cathode discharge method and is confined by a cusped magnetic field cage. A cylindrical Espion advanced Langmuir probe having 0.15 mm diameter and 10.0 mm length is used to study the plasma parameters for various discharge conditions. Optimum operational discharge parameters in terms of charging of the dust grains are studied. The charge on the surface of the dust particle is calculated from the capacitance model and the current by the dust grains is measured by the combination of a Faraday cup and an electrometer. Unlike our previous experiments in which dust grains were produced in-situ, here a dust dropper is used to drop the dust particles into the plasma.

Study on the method of improving the flashover voltage of 110kV suspension porcelain insulators based on neural network genetic algorithm

NASA Astrophysics Data System (ADS)

Zhang, Ruiqi; Cai, Li; Chen, Junwu; Wang, Luo; Tan, Xuefeng

2018-04-01

This paper presents a new method to improve 110kV porcelain insulator flashover voltage by adding a metal ring on the insulator cap, which can not only effectively reduce the field strength of the steel cap, but also reduce the tangential field intensity of the umbrella group and inhibit the development of the discharge process, thus the flashover voltage can be increased. The surface strength calculation model of 110kV porcelain insulator is established by the finite element method (FEM), and the parameters of the metal ring are designed by neural network genetic algorithm (BP-GA). Then the experiments were carried out to verify the results, and the results show that the metal ring plate under the optimum parameters can greatly improve the flashover voltage.

Beam parameter optimization at CLIC using the process e+e- → HZ → Hq q bar at 380 GeV

NASA Astrophysics Data System (ADS)

Andrianala, F.; Raboanary, R.; Roloff, P.; Schulte, D.

2017-01-01

At CLIC and the ILC beam-beam forces lead to the emission of beamstrahlung photons and a reduction of the effective center-of-mass energy. This degradation is controlled by the choice of the horizontal beam size. A reduction of this parameter would increase the luminosity but also the beamstrahlung. In this paper the optimum choice for the horizontal beam size is investigated for one of the most important physics processes. The Higgsstrahlung process e+e- → HZ is identified in a model-independent manner by observing the Z boson and determining the mass against which it is recoiling. The physics analysis for this process is performed for constant running times, assuming different beam size and taking into account the resulting levels of integrated luminosity and the associated luminosity spectra.

Modelling the Cast Component Weight in Hot Chamber Die Casting using Combined Taguchi and Buckingham's π Approach

NASA Astrophysics Data System (ADS)

Singh, Rupinder

2018-02-01

Hot chamber (HC) die casting process is one of the most widely used commercial processes for the casting of low temperature metals and alloys. This process gives near-net shape product with high dimensional accuracy. However in actual field environment the best settings of input parameters is often conflicting as the shape and size of the casting changes and one have to trade off among various output parameters like hardness, dimensional accuracy, casting defects, microstructure etc. So for online inspection of the cast components properties (without affecting the production line) the weight measurement has been established as one of the cost effective method (as the difference in weight of sound and unsound casting reflects the possible casting defects) in field environment. In the present work at first stage the effect of three input process parameters (namely: pressure at 2nd phase in HC die casting; metal pouring temperature and die opening time) has been studied for optimizing the cast component weight `W' as output parameter in form of macro model based upon Taguchi L9 OA. After this Buckingham's π approach has been applied on Taguchi based macro model for the development of micro model. This study highlights the Taguchi-Buckingham based combined approach as a case study (for conversion of macro model into micro model) by identification of optimum levels of input parameters (based on Taguchi approach) and development of mathematical model (based on Buckingham's π approach). Finally developed mathematical model can be used for predicting W in HC die casting process with more flexibility. The results of study highlights second degree polynomial equation for predicting cast component weight in HC die casting and suggest that pressure at 2nd stage is one of the most contributing factors for controlling the casting defect/weight of casting.

An annealed chaotic maximum neural network for bipartite subgraph problem.

PubMed

Wang, Jiahai; Tang, Zheng; Wang, Ronglong

2004-04-01

In this paper, based on maximum neural network, we propose a new parallel algorithm that can help the maximum neural network escape from local minima by including a transient chaotic neurodynamics for bipartite subgraph problem. The goal of the bipartite subgraph problem, which is an NP- complete problem, is to remove the minimum number of edges in a given graph such that the remaining graph is a bipartite graph. Lee et al. presented a parallel algorithm using the maximum neural model (winner-take-all neuron model) for this NP- complete problem. The maximum neural model always guarantees a valid solution and greatly reduces the search space without a burden on the parameter-tuning. However, the model has a tendency to converge to a local minimum easily because it is based on the steepest descent method. By adding a negative self-feedback to the maximum neural network, we proposed a new parallel algorithm that introduces richer and more flexible chaotic dynamics and can prevent the network from getting stuck at local minima. After the chaotic dynamics vanishes, the proposed algorithm is then fundamentally reined by the gradient descent dynamics and usually converges to a stable equilibrium point. The proposed algorithm has the advantages of both the maximum neural network and the chaotic neurodynamics. A large number of instances have been simulated to verify the proposed algorithm. The simulation results show that our algorithm finds the optimum or near-optimum solution for the bipartite subgraph problem superior to that of the best existing parallel algorithms.

Optimisation of warpage on plastic injection moulding part using response surface methodology (RSM)

NASA Astrophysics Data System (ADS)

Miza, A. T. N. A.; Shayfull, Z.; Nasir, S. M.; Fathullah, M.; Rashidi, M. M.

2017-09-01

The warpage is often encountered which occur during injection moulding process of thin shell part depending the process condition. The statistical design of experiment method which are Integrating Finite Element (FE) Analysis, moldflow analysis and response surface methodology (RSM) are the stage of few ways in minimize the warpage values of x,y and z on thin shell plastic parts that were investigated. A battery cover of a remote controller is one of the thin shell plastic part that produced by using injection moulding process. The optimum process condition parameter were determined as to achieve the minimum warpage from being occur. Packing pressure, Cooling time, Melt temperature and Mould temperature are 4 parameters that considered in this study. A two full factorial experimental design was conducted in Design Expert of RSM analysis as to combine all these parameters study. FE analysis result gain from analysis of variance (ANOVA) method was the one of the important process parameters influenced warpage. By using RSM, a predictive response surface model for warpage data will be shown.

Multi Objective Optimization of Multi Wall Carbon Nanotube Based Nanogrinding Wheel Using Grey Relational and Regression Analysis

NASA Astrophysics Data System (ADS)

Sethuramalingam, Prabhu; Vinayagam, Babu Kupusamy

2016-07-01

Carbon nanotube mixed grinding wheel is used in the grinding process to analyze the surface characteristics of AISI D2 tool steel material. Till now no work has been carried out using carbon nanotube based grinding wheel. Carbon nanotube based grinding wheel has excellent thermal conductivity and good mechanical properties which are used to improve the surface finish of the workpiece. In the present study, the multi response optimization of process parameters like surface roughness and metal removal rate of grinding process of single wall carbon nanotube (CNT) in mixed cutting fluids is undertaken using orthogonal array with grey relational analysis. Experiments are performed with designated grinding conditions obtained using the L9 orthogonal array. Based on the results of the grey relational analysis, a set of optimum grinding parameters is obtained. Using the analysis of variance approach the significant machining parameters are found. Empirical model for the prediction of output parameters has been developed using regression analysis and the results are compared empirically, for conditions of with and without CNT grinding wheel in grinding process.

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

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

Effect of input signal and filter parameters on patterning effect in a semiconductor optical amplifier

NASA Astrophysics Data System (ADS)

Hussain, Kamal; Pratap Singh, Satya; Kumar Datta, Prasanta

2013-11-01

A numerical investigation is presented to show the dependence of patterning effect (PE) of an amplified signal in a bulk semiconductor optical amplifier (SOA) and an optical bandpass filter based amplifier on various input signal and filter parameters considering both the cases of including and excluding intraband effects in the SOA model. The simulation shows that the variation of PE with input energy has a characteristic nature which is similar for both the cases. However the variation of PE with pulse width is quite different for the two cases, PE being independent of the pulse width when intraband effects are neglected in the model. We find a simple relationship between the PE and the signal pulse width. Using a simple treatment we study the effect of the amplified spontaneous emission (ASE) on PE and find that the ASE has almost no effect on the PE in the range of energy considered here. The optimum filter parameters are determined to obtain an acceptable extinction ratio greater than 10 dB and a PE less than 1 dB for the amplified signal over a wide range of input signal energy and bit-rate.

Optimization and Performance parameters for adsorption of Cr6+ by microwave assisted carbon from Sterculia foetida shells

NASA Astrophysics Data System (ADS)

Gnanasundaram, N.; Loganathan, M.; Singh, A.

2017-06-01

Modeling of adsorption of Cr6+ on to activated carbon prepared from Sterculia foetida dried seed shells under different drying techniques namely sun, oven, and microwave drying (450W, 600W, 900W power). Optimization of process parameters such as pH, adsorbent dosage (g/ml), temperature (°C), contact time (min) were evaluated using Central Composite Rotatable Design (CCRD) of Response Surface Methodology (RSM). For batch adsorption studies at pH 3, adsorbent dosage of 1.5 g/ml, temperature 35°C and contact time 90 min were found to be optimum for the system under consideration and Microwave Activated Carbonized Sterculia foetida (MACSF) at 450W was found to be best suited for the adsorption of Cr+6 ions. The system was found to follow Langmuir type monolayer adsorption for the given operational parameters. SEM analysis was used to study the surface morphology of the carbon samples and the effect of pretreatment on carbonization.

Parameter identifiability and regional calibration for reservoir inflow prediction

NASA Astrophysics Data System (ADS)

Kolberg, Sjur; Engeland, Kolbjørn; Tøfte, Lena S.; Bruland, Oddbjørn

2013-04-01

The large hydropower producer Statkraft is currently testing regional, distributed models for operational reservoir inflow prediction. The need for simultaneous forecasts and consistent updating in a large number of catchments supports the shift from catchment-oriented to regional models. Low-quality naturalized inflow series in the reservoir catchments further encourages the use of donor catchments and regional simulation for calibration purposes. MCMC based parameter estimation (the Dream algorithm; Vrugt et al, 2009) is adapted to regional parameter estimation, and implemented within the open source ENKI framework. The likelihood is based on the concept of effectively independent number of observations, spatially as well as in time. Marginal and conditional (around an optimum) parameter distributions for each catchment may be extracted, even though the MCMC algorithm itself is guided only by the regional likelihood surface. Early results indicate that the average performance loss associated with regional calibration (difference in Nash-Sutcliffe R2 between regionally and locally optimal parameters) is in the range of 0.06. The importance of the seasonal snow storage and melt in Norwegian mountain catchments probably contributes to the high degree of similarity among catchments. The evaluation continues for several regions, focusing on posterior parameter uncertainty and identifiability. Vrugt, J. A., C. J. F. ter Braak, C. G. H. Diks, B. A. Robinson, J. M. Hyman and D. Higdon: Accelerating Markov Chain Monte Carlo Simulation by Differential Evolution with Self-Adaptive Randomized Subspace Sampling. Int. J. of nonlinear sciences and numerical simulation 10, 3, 273-290, 2009.

Using the Standard Deviation of a Region of Interest in an Image to Estimate Camera to Emitter Distance

PubMed Central

Cano-García, Angel E.; Lazaro, José Luis; Infante, Arturo; Fernández, Pedro; Pompa-Chacón, Yamilet; Espinoza, Felipe

2012-01-01

In this study, a camera to infrared diode (IRED) distance estimation problem was analyzed. The main objective was to define an alternative to measures depth only using the information extracted from pixel grey levels of the IRED image to estimate the distance between the camera and the IRED. In this paper, the standard deviation of the pixel grey level in the region of interest containing the IRED image is proposed as an empirical parameter to define a model for estimating camera to emitter distance. This model includes the camera exposure time, IRED radiant intensity and the distance between the camera and the IRED. An expression for the standard deviation model related to these magnitudes was also derived and calibrated using different images taken under different conditions. From this analysis, we determined the optimum parameters to ensure the best accuracy provided by this alternative. Once the model calibration had been carried out, a differential method to estimate the distance between the camera and the IRED was defined and applied, considering that the camera was aligned with the IRED. The results indicate that this method represents a useful alternative for determining the depth information. PMID:22778608

Using the standard deviation of a region of interest in an image to estimate camera to emitter distance.

PubMed

Cano-García, Angel E; Lazaro, José Luis; Infante, Arturo; Fernández, Pedro; Pompa-Chacón, Yamilet; Espinoza, Felipe

2012-01-01

In this study, a camera to infrared diode (IRED) distance estimation problem was analyzed. The main objective was to define an alternative to measures depth only using the information extracted from pixel grey levels of the IRED image to estimate the distance between the camera and the IRED. In this paper, the standard deviation of the pixel grey level in the region of interest containing the IRED image is proposed as an empirical parameter to define a model for estimating camera to emitter distance. This model includes the camera exposure time, IRED radiant intensity and the distance between the camera and the IRED. An expression for the standard deviation model related to these magnitudes was also derived and calibrated using different images taken under different conditions. From this analysis, we determined the optimum parameters to ensure the best accuracy provided by this alternative. Once the model calibration had been carried out, a differential method to estimate the distance between the camera and the IRED was defined and applied, considering that the camera was aligned with the IRED. The results indicate that this method represents a useful alternative for determining the depth information.

A Decolorization Technique with Spent “Greek Coffee” Grounds as Zero-Cost Adsorbents for Industrial Textile Wastewaters

PubMed Central

Kyzas, George Z.

2012-01-01

In this study, the decolorization of industrial textile wastewaters was studied in batch mode using spent “Greek coffee” grounds (COF) as low-cost adsorbents. In this attempt, there is a cost-saving potential given that there was no further modification of COF (just washed with distilled water to remove dirt and color, then dried in an oven). Furthermore, tests were realized both in synthetic and real textile wastewaters for comparative reasons. The optimum pH of adsorption was acidic (pH = 2) for synthetic effluents, while experiments in free pH (non-adjusted) were carried out for real effluents. Equilibrium data were fitted to the Langmuir, Freundlich and Langmuir-Freundlich (L-F) models. The calculated maximum adsorption capacities (Qmax) for total dye (reactive) removal at 25 °C was 241 mg/g (pH = 2) and 179 mg/g (pH = 10). Thermodynamic parameters were also calculated (ΔH0, ΔG0, ΔS0). Kinetic data were fitted to the pseudo-first, -second and -third order model. The optimum pH for desorption was determined, in line with desorption and reuse analysis. Experiments dealing the increase of mass of adsorbent showed a strong increase in total dye removal.

PSC algorithm description

NASA Technical Reports Server (NTRS)

Nobbs, Steven G.

1995-01-01

An overview of the performance seeking control (PSC) algorithm and details of the important components of the algorithm are given. The onboard propulsion system models, the linear programming optimization, and engine control interface are described. The PSC algorithm receives input from various computers on the aircraft including the digital flight computer, digital engine control, and electronic inlet control. The PSC algorithm contains compact models of the propulsion system including the inlet, engine, and nozzle. The models compute propulsion system parameters, such as inlet drag and fan stall margin, which are not directly measurable in flight. The compact models also compute sensitivities of the propulsion system parameters to change in control variables. The engine model consists of a linear steady state variable model (SSVM) and a nonlinear model. The SSVM is updated with efficiency factors calculated in the engine model update logic, or Kalman filter. The efficiency factors are used to adjust the SSVM to match the actual engine. The propulsion system models are mathematically integrated to form an overall propulsion system model. The propulsion system model is then optimized using a linear programming optimization scheme. The goal of the optimization is determined from the selected PSC mode of operation. The resulting trims are used to compute a new operating point about which the optimization process is repeated. This process is continued until an overall (global) optimum is reached before applying the trims to the controllers.

Effects of machining parameters on tool life and its optimization in turning mild steel with brazed carbide cutting tool

NASA Astrophysics Data System (ADS)

Dasgupta, S.; Mukherjee, S.

2016-09-01

One of the most significant factors in metal cutting is tool life. In this research work, the effects of machining parameters on tool under wet machining environment were studied. Tool life characteristics of brazed carbide cutting tool machined against mild steel and optimization of machining parameters based on Taguchi design of experiments were examined. The experiments were conducted using three factors, spindle speed, feed rate and depth of cut each having three levels. Nine experiments were performed on a high speed semi-automatic precision central lathe. ANOVA was used to determine the level of importance of the machining parameters on tool life. The optimum machining parameter combination was obtained by the analysis of S/N ratio. A mathematical model based on multiple regression analysis was developed to predict the tool life. Taguchi's orthogonal array analysis revealed the optimal combination of parameters at lower levels of spindle speed, feed rate and depth of cut which are 550 rpm, 0.2 mm/rev and 0.5mm respectively. The Main Effects plot reiterated the same. The variation of tool life with different process parameters has been plotted. Feed rate has the most significant effect on tool life followed by spindle speed and depth of cut.

Optimizing solar-cell grid geometry

NASA Technical Reports Server (NTRS)

Crossley, A. P.

1969-01-01

Trade-off analysis and mathematical expressions calculate optimum grid geometry in terms of various cell parameters. Determination of the grid geometry provides proper balance between grid resistance and cell output to optimize the energy conversion process.

Evaluation of SIR-A space radar for geologic interpretation: United States, Panama, Colombia, and New Guinea

NASA Technical Reports Server (NTRS)

Macdonald, H.; Waite, W. P.; Kaupp, V. H.; Bridges, L. C.; Storm, M.

1983-01-01

Comparisons between LANDSAT MSS imagery, and aircraft and space radar imagery from different geologic environments in the United States, Panama, Colombia, and New Guinea demonstrate the interdependence of radar system geometry and terrain configuration for optimum retrieval of geologic information. Illustrations suggest that in the case of space radars (SIR-A in particular), the ability to acquire multiple look-angle/look-direction radar images of a given area is more valuable for landform mapping than further improvements in spatial resolution. Radar look-angle is concluded to be one of the most important system parameters of a space radar designed to be used for geologic reconnaissance mapping. The optimum set of system parameters must be determined for imaging different classes of landform features and tailoring the look-angle to local topography.

Improved importance sampling technique for efficient simulation of digital communication systems

NASA Technical Reports Server (NTRS)

Lu, Dingqing; Yao, Kung

1988-01-01

A new, improved importance sampling (IIS) approach to simulation is considered. Some basic concepts of IS are introduced, and detailed evolutions of simulation estimation variances for Monte Carlo (MC) and IS simulations are given. The general results obtained from these evolutions are applied to the specific previously known conventional importance sampling (CIS) technique and the new IIS technique. The derivation for a linear system with no signal random memory is considered in some detail. For the CIS technique, the optimum input scaling parameter is found, while for the IIS technique, the optimum translation parameter is found. The results are generalized to a linear system with memory and signals. Specific numerical and simulation results are given which show the advantages of CIS over MC and IIS over CIS for simulations of digital communications systems.

Determination of betulinic acid, oleanolic acid and ursolic acid from Achyranthes aspera L. using RP-UFLC-DAD analysis and evaluation of various parameters for their optimum yield.

PubMed

Pai, Sandeep R; Upadhya, Vinayak; Hegde, Harsha V; Joshi, Rajesh K; Kholkute, Sanjiva D

2016-03-01

Achyranthes aspera L. is a well known herb commonly used in traditional system of Indian medicine to treat various disorders, such as cough, dysentery, gonorrhea, piles, kidney stone, pneumonia, renal dropsy, skin eruptions, snake bite, etc. Here, we used RP-UFLC-DAD method for determining triterpenoids betulinic acid (BA), oleanolic acid (OA) and ursolic acid (UA) from A. aspera. Optimum yield of these compounds were studied and evaluated using parameters viz., method of extraction, time of extraction, age of plant and plant parts (leaves, stem and roots). Linear relationships in RP-UFLC-DAD analysis were obtained in the range 0.05-100 µg/mL with 0.035, 0.042 and 0.033 µg/mL LOD for BA, OA and UA, respectively. Of the variables tested, extraction method and parts used significantly affected content yield. Continuous shaking extraction (CSE) at ambient temperature gave better extraction efficiency than exposure to ultra sonic extraction (USE) or microwave assisted extraction (MAE) methods. The highest content of BA, OA and UA were determined individually in leaf, stem and root extracts with CSE. Collective yield of these triterpenoids were higher in leaf part exposed to 15 min USE method. To best of our knowledge, the study newly reports UA from A. aspera and the same was confirmed using ATR-FT-IR studies. This study explains the distribution pattern of these major triterpenoids and optimum extraction parameters in detail.

Theoretical and Field Experimental Investigation of an Arrayed Solar Thermoelectric Flat-Plate Generator

NASA Astrophysics Data System (ADS)

Rehman, Naveed ur; Siddiqui, Mubashir Ali

2018-05-01

This work theoretically and experimentally investigated the performance of an arrayed solar flat-plate thermoelectric generator (ASFTEG). An analytical model, based on energy balances, was established for determining load voltage, power output and overall efficiency of ASFTEGs. An array consists of TEG devices (or modules) connected electrically in series and operating in closed-circuit mode with a load. The model takes into account the distinct temperature difference across each module, which is a major feature of this model. Parasitic losses have also been included in the model for realistic results. With the given set of simulation parameters, an ASFTEG consisting of four commercially available Bi2Te3 modules had a predicted load voltage of 200 mV and generated 3546 μW of electric power output. Predictions from the model were in good agreement with field experimental outcomes from a prototype ASFTEG, which was developed for validation purposes. Later, the model was simulated to maximize the performance of the ASFTEG by adjusting the thermal and electrical design of the system. Optimum values of design parameters were evaluated and discussed in detail. Beyond the current limitations associated with improvements in thermoelectric materials, this study will eventually lead to the successful development of portable roof-top renewable TEGs.

Numerical simulation of heat transfer and phase change during freezing of potatoes with different shapes at the presence or absence of ultrasound irradiation

NASA Astrophysics Data System (ADS)

Kiani, Hossein; Sun, Da-Wen

2018-03-01

As novel processes such as ultrasound assisted heat transfer are emerged, new models and simulations are needed to describe these processes. In this paper, a numerical model was developed to study the freezing process of potatoes. Different thermal conductivity models were investigated, and the effect of sonication was evaluated on the convective heat transfer in a fluid to the particle heat transfer system. Potato spheres and sticks were the geometries researched, and the effect of different processing parameters on the results were studied. The numerical model successfully predicted the ultrasound assisted freezing of various shapes in comparison with experimental data of the process. The model was sensitive to processing parameters variation (sound intensity, duty cycle, shape, etc.) and could accurately simulate the freezing process. Among the thermal conductivity correlations studied, de Vries and Maxwell models gave closer estimations. The maximum temperature difference was obtained for the series equation that underestimated the thermal conductivity. Both numerical and experimental data confirmed that an optimum condition of intensity and duty cycle is needed for reducing the freezing time, as increasing the intensity, increased the heat transfer rate and sonically heating rate, simultaneously, that acted against each other.

Design of high productivity antibody capture by protein A chromatography using an integrated experimental and modeling approach.

PubMed

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.

Solid-substrate bioprocessing of cow dung for the production of carboxymethyl cellulase by Bacillus halodurans IND18.

PubMed

Vijayaraghavan, P; Prakash Vincent, S G; Dhillon, G S

2016-02-01

The production of carboxymethyl cellulase (CMCase) by Bacillus halodurans IND18 under solid substrate fermentation (SSF) using cow dung was optimized through two level full factorial design and second order response surface methodology (RSM). The central composite design (CCD) was employed to optimize the vital fermentation parameters, such as pH of the substrate, concentration of nitrogen source (peptone) and ion (sodium dihydrogen phosphate) sources in medium for achieving higher enzyme production. The optimum medium composition was found to be 1.46% (w/w) peptone, 0.095% (w/w) sodium dihydrogen phosphate and pH 8.0. The model prediction of 4210IU/g enzyme activity at optimum conditions was verified experimentally as 4140IU/g. The enzyme was active over a broad temperature range (40-60±1°C) and pH (7.0-9.0) with maximal activity at 60±1°C and pH 8.0. This study demonstrated the potential of cow dung as novel substrate for CMCase production. Copyright © 2015 Elsevier Ltd. All rights reserved.

Color removal from distillery spent wash through coagulation using Moringa oleifera seeds: use of optimum response surface methodology.

PubMed

Prasad, R Krishna

2009-06-15

The effects of dosage, pH and concentration of salts were investigated for an optimized condition of color removal from the distillery spent wash. The optimization process was analyzed using custom response surface methodology (RSM). The design was employed to derive a statistical model for the effect of parameters studied on removal of color using Moringa oleifera coagulant (MOC). The dosage (20 and 60 ml), pH (7 and 8.5) and concentration of 0.25 M had been found to be the optimum conditions for maximum 56% and 67% color removal using sodium chloride (NaCl) and potassium chloride (KCl) salts respectively. The actual color removal at optimal conditions was found to be 53% and 64% respectively for NaCl and KCl salts which confirms close to RSM results. The effects of storage duration and temperature on MOC studied reveal that coagulation efficiency of MOC kept at room temperature was effective for 3 days and at 4 degrees C it performed coagulation up to 5 days.

Intelligent inversion method for pre-stack seismic big data based on MapReduce

NASA Astrophysics Data System (ADS)

Yan, Xuesong; Zhu, Zhixin; Wu, Qinghua

2018-01-01

Seismic exploration is a method of oil exploration that uses seismic information; that is, according to the inversion of seismic information, the useful information of the reservoir parameters can be obtained to carry out exploration effectively. Pre-stack data are characterised by a large amount of data, abundant information, and so on, and according to its inversion, the abundant information of the reservoir parameters can be obtained. Owing to the large amount of pre-stack seismic data, existing single-machine environments have not been able to meet the computational needs of the huge amount of data; thus, the development of a method with a high efficiency and the speed to solve the inversion problem of pre-stack seismic data is urgently needed. The optimisation of the elastic parameters by using a genetic algorithm easily falls into a local optimum, which results in a non-obvious inversion effect, especially for the optimisation effect of the density. Therefore, an intelligent optimisation algorithm is proposed in this paper and used for the elastic parameter inversion of pre-stack seismic data. This algorithm improves the population initialisation strategy by using the Gardner formula and the genetic operation of the algorithm, and the improved algorithm obtains better inversion results when carrying out a model test with logging data. All of the elastic parameters obtained by inversion and the logging curve of theoretical model are fitted well, which effectively improves the inversion precision of the density. This algorithm was implemented with a MapReduce model to solve the seismic big data inversion problem. The experimental results show that the parallel model can effectively reduce the running time of the algorithm.

Study of interface correlation in W/C multilayer structure by specular and non-specular grazing incidence X-ray reflectivity measurements

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

Biswas, A., E-mail: arupb@barc.gov.in; Bhattacharyya, D.; Sahoo, N. K.

2015-10-28

W/C/W tri-layer thin film samples have been deposited on c-Si substrates in a home-built Ion Beam Sputtering system at 1.5 × 10{sup −3} Torr Ar working pressure and 10 mA grid current. The tri-layer samples have been deposited at different Ar{sup +} ion energies between 0.6 and 1.2 keV for W layer deposition and the samples have been characterized by specular and non-specular grazing incidence X-ray reflectivity (GIXR) measurements. By analyzing the GIXR spectra, various interface parameters have been obtained for both W-on-C and C-on-W interfaces and optimum Ar{sup +} ion energy for obtaining interfaces with low imperfections has been found. Subsequently, multilayermore » W/C samples with 5-layer, 7-layer, 9-layer, and 13-layer have been deposited at this optimum Ar{sup +} ion energy. By fitting the specular and diffused GIXR data of the multilayer samples with the parameters of each interface as fitting variables, different interface parameters, viz., interface width, in-plane correlation length, interface roughness, and interface diffusion have been estimated for each interface and their variation across the depth of the multilayers have been obtained. The information would be useful in realizing W/C multilayers for soft X-ray mirror application in the <100 Å wavelength regime. The applicability of the “restart of the growth at the interface” model in the case of these ion beam sputter deposited W/C multilayers has also been investigated in the course of this study.« less

Effect of fermentation parameters on bio-alcohols production from glycerol using immobilized Clostridium pasteurianum: an optimization study.

PubMed

Khanna, Swati; Goyal, Arun; Moholkar, Vijayanand S

2013-01-01

This article addresses the issue of effect of fermentation parameters for conversion of glycerol (in both pure and crude form) into three value-added products, namely, ethanol, butanol, and 1,3-propanediol (1,3-PDO), by immobilized Clostridium pasteurianum and thereby addresses the statistical optimization of this process. The analysis of effect of different process parameters such as agitation rate, fermentation temperature, medium pH, and initial glycerol concentration indicated that medium pH was the most critical factor for total alcohols production in case of pure glycerol as fermentation substrate. On the other hand, initial glycerol concentration was the most significant factor for fermentation with crude glycerol. An interesting observation was that the optimized set of fermentation parameters was found to be independent of the type of glycerol (either pure or crude) used. At optimum conditions of agitation rate (200 rpm), initial glycerol concentration (25 g/L), fermentation temperature (30°C), and medium pH (7.0), the total alcohols production was almost equal in anaerobic shake flasks and 2-L bioreactor. This essentially means that at optimum process parameters, the scale of operation does not affect the output of the process. The immobilized cells could be reused for multiple cycles for both pure and crude glycerol fermentation.

Parametric study of waste chicken fat catalytic chemical vapour deposition for controlled synthesis of vertically aligned carbon nanotubes

NASA Astrophysics Data System (ADS)

Suriani, A. B.; Dalila, A. R.; Mohamed, A.; Rosmi, M. S.; Mamat, M. H.; Malek, M. F.; Ahmad, M. K.; Hashim, N.; Isa, I. M.; Soga, T.; Tanemura, M.

2016-12-01

High-quality vertically aligned carbon nanotubes (VACNTs) were synthesised using ferrocene-chicken oil mixture utilising a thermal chemical vapour deposition (TCVD) method. Reaction parameters including vaporisation temperature, catalyst concentration and synthesis time were examined for the first time to investigate their influence on the growth of VACNTs. Analysis via field emission scanning electron microscopy and micro-Raman spectroscopy revealed that the growth rate, diameter and crystallinity of VACNTs depend on the varied synthesis parameters. Vaporisation temperature of 570°C, catalyst concentration of 5.33 wt% and synthesis time of 60 min were considered as optimum parameters for the production of VACNTs from waste chicken fat. These parameters are able to produce VACNTs with small diameters in the range of 15-30 nm and good quality (ID/IG 0.39 and purity 76%) which were comparable to those synthesised using conventional carbon precursor. The low turn on and threshold fields of VACNTs synthesised using optimum parameters indicated that the VACNTs synthesised using waste chicken fat are good candidate for field electron emitter. The result of this study therefore can be used to optimise the growth and production of VACNTs from waste chicken fat in a large scale for field emission application.

Optimum Design of Forging Process Parameters and Preform Shape under Uncertainties

NASA Astrophysics Data System (ADS)

Repalle, Jalaja; Grandhi, Ramana V.

2004-06-01

Forging is a highly complex non-linear process that is vulnerable to various uncertainties, such as variations in billet geometry, die temperature, material properties, workpiece and forging equipment positional errors and process parameters. A combination of these uncertainties could induce heavy manufacturing losses through premature die failure, final part geometric distortion and production risk. Identifying the sources of uncertainties, quantifying and controlling them will reduce risk in the manufacturing environment, which will minimize the overall cost of production. In this paper, various uncertainties that affect forging tool life and preform design are identified, and their cumulative effect on the forging process is evaluated. Since the forging process simulation is computationally intensive, the response surface approach is used to reduce time by establishing a relationship between the system performance and the critical process design parameters. Variability in system performance due to randomness in the parameters is computed by applying Monte Carlo Simulations (MCS) on generated Response Surface Models (RSM). Finally, a Robust Methodology is developed to optimize forging process parameters and preform shape. The developed method is demonstrated by applying it to an axisymmetric H-cross section disk forging to improve the product quality and robustness.

Optimization study for the experimental configuration of CMB-S4

NASA Astrophysics Data System (ADS)

Barron, Darcy; Chinone, Yuji; Kusaka, Akito; Borril, Julian; Errard, Josquin; Feeney, Stephen; Ferraro, Simone; Keskitalo, Reijo; Lee, Adrian T.; Roe, Natalie A.; Sherwin, Blake D.; Suzuki, Aritoki

2018-02-01

The CMB Stage 4 (CMB-S4) experiment is a next-generation, ground-based experiment that will measure the cosmic microwave background (CMB) polarization to unprecedented accuracy, probing the signature of inflation, the nature of cosmic neutrinos, relativistic thermal relics in the early universe, and the evolution of the universe. CMB-S4 will consist of O(500,000) photon-noise-limited detectors that cover a wide range of angular scales in order to probe the cosmological signatures from both the early and late universe. It will measure a wide range of microwave frequencies to cleanly separate the CMB signals from galactic and extra-galactic foregrounds. To advance the progress towards designing the instrument for CMB-S4, we have established a framework to optimize the instrumental configuration to maximize its scientific output. The framework combines cost and instrumental models with a cosmology forecasting tool, and evaluates the scientific sensitivity as a function of various instrumental parameters. The cost model also allows us to perform the analysis under a fixed-cost constraint, optimizing for the scientific output of the experiment given finite resources. In this paper, we report our first results from this framework, using simplified instrumental and cost models. We have primarily studied two classes of instrumental configurations: arrays of large-aperture telescopes with diameters ranging from 2–10 m, and hybrid arrays that combine small-aperture telescopes (0.5-m diameter) with large-aperture telescopes. We explore performance as a function of telescope aperture size, distribution of the detectors into different microwave frequencies, survey strategy and survey area, low-frequency noise performance, and balance between small and large aperture telescopes for hybrid configurations. Both types of configurations must cover both large (~ degree) and small (~ arcmin) angular scales, and the performance depends on assumptions for performance vs. angular scale. The configurations with large-aperture telescopes have a shallow optimum around 4–6 m in aperture diameter, assuming that large telescopes can achieve good performance for low-frequency noise. We explore some of the uncertainties of the instrumental model and cost parameters, and we find that the optimum has a weak dependence on these parameters. The hybrid configuration shows an even broader optimum, spanning a range of 4–10 m in aperture for the large telescopes. We also present two strawperson configurations as an outcome of this optimization study, and we discuss some ideas for improving our simple cost and instrumental models used here. There are several areas of this analysis that deserve further improvement. In our forecasting framework, we adopt a simple two-component foreground model with spatially varying power-law spectral indices. We estimate de-lensing performance statistically and ignore non-idealities such as anisotropic mode coverage, boundary effect, and possible foreground residual. Instrumental systematics, which is not accounted for in our analyses, may also influence the conceptual design. Further study of the instrumental and cost models will be one of the main areas of study by the entire CMB-S4 community. We hope that our framework will be useful for estimating the influence of these improvements in the future, and we will incorporate them in order to further improve the optimization.

Germination response of Hylocereus setaceus (Salm-Dyck ex DC: ) Ralf Bauer (Cactaceae) seeds to temperature and reduced water potentials.

PubMed

Simão, E; Takaki, M; Cardoso, V J M

2010-02-01

The germination response of Hylocereus setaceus seeds to isothermic incubation at different water potentials was analysed by using the thermal time and hydrotime models, aiming to describe some germination parameters of the population and to test the validity of the models to describe the response of the seeds to temperature and water potential. Hylocereus setaceus seeds germinated relatively well in a wide range of temperatures and the germination was rate limited from 11 to 20 degrees C interval and beyond 30 degrees C until 40 degrees C, in which the germination rate respectively shifts positively and negatively with temperature. The minimum or base temperature (T(b)) for the germination of H. setaceus was 7 degrees C, and the ceiling temperature varied nearly from 43.5 to 59 degrees C depending on the percent fraction, with median set on 49.8 degrees C. The number of degrees day necessary for 50% of the seeds to germinate in the infra-optimum temperature range was 39.3 degrees C day, whereas at the supra-optimum interval the value of theta = 77 was assumed to be constant throughout. Germination was sensitive to decreasing values of psi in the medium, and both the germinability and the germination rate shift negatively with the reduction of psi, but the rate of reduction changed with temperature. The values of base water potential (psi(b)) shift to zero with increasing temperatures and such variation reflects in the relatively greater effect of low psi on germination in supra optimum range of T. In general, the model described better the germination time courses at lower than at higher water potentials. The analysis also suggest that Tb may not be independent of psi and that psi(b(g)) may change as a function of temperature at the infra-otimum temperature range.

Parameter sensitivity analysis of a lumped-parameter model of a chain of lymphangions in series.

PubMed

Jamalian, Samira; Bertram, Christopher D; Richardson, William J; Moore, James E

2013-12-01

Any disruption of the lymphatic system due to trauma or injury can lead to edema. There is no effective cure for lymphedema, partly because predictive knowledge of lymphatic system reactions to interventions is lacking. A well-developed model of the system could greatly improve our understanding of its function. Lymphangions, defined as the vessel segment between two valves, are the individual pumping units. Based on our previous lumped-parameter model of a chain of lymphangions, this study aimed to identify the parameters that affect the system output the most using a sensitivity analysis. The system was highly sensitive to minimum valve resistance, such that variations in this parameter caused an order-of-magnitude change in time-average flow rate for certain values of imposed pressure difference. Average flow rate doubled when contraction frequency was increased within its physiological range. Optimum lymphangion length was found to be some 13-14.5 diameters. A peak of time-average flow rate occurred when transmural pressure was such that the pressure-diameter loop for active contractions was centered near maximum passive vessel compliance. Increasing the number of lymphangions in the chain improved the pumping in the presence of larger adverse pressure differences. For a given pressure difference, the optimal number of lymphangions increased with the total vessel length. These results indicate that further experiments to estimate valve resistance more accurately are necessary. The existence of an optimal value of transmural pressure may provide additional guidelines for increasing pumping in areas affected by edema.

A mathematical model for the iron/chromium redox battery

NASA Technical Reports Server (NTRS)

Fedkiw, P. S.; Watts, R. W.

1984-01-01

A mathematical model has been developed to describe the isothermal operation of a single anode-separator-cathode unit cell in a redox-flow battery and has been applied to the NASA iron/chromium system. The model, based on porous electrode theory, incorporates redox kinetics, mass transfer, and ohmic effects as well as the parasitic hydrogen reaction which occurs in the chromium electrode. A numerical parameter study was carried out to predict cell performance to aid in the rational design, scale-up, and operation of the flow battery. The calculations demonstrate: (1) an optimum electrode thickness and electrolyte flow rate exist; (2) the amount of hydrogen evolved and, hence, cycle faradaic efficiency, can be affected by cell geometry, flow rate, and charging procedure; (3) countercurrent flow results in enhanced cell performance over cocurrent flow; and (4) elevated temperature operation enhances cell performance.

Mathematical modeling and hydrodynamics of Electrochemical deburring process

NASA Astrophysics Data System (ADS)

Prabhu, Satisha; Abhishek Kumar, K., Dr

2018-04-01

The electrochemical deburring (ECD) is a variation of electrochemical machining is considered as one of the efficient methods for deburring of intersecting features and internal parts. Since manual deburring costs are comparatively high one can potentially use this method in both batch production and flow production. The other advantage of this process is that time of deburring as is on the order of seconds as compared to other methods. In this paper, the mathematical modeling of Electrochemical deburring is analysed from its deburring time and base metal removal point of view. Simultaneously material removal rate is affected by electrolyte temperature and bubble formation. The mathematical model and hydrodynamics of the process throw limelight upon optimum velocity calculations which can be theoretically determined. The analysis can be the powerful tool for prediction of the above-mentioned parameters by experimentation.

Subsite mapping of enzymes. Depolymerase computer modelling.

PubMed Central

Allen, J D; Thoma, J A

1976-01-01

We have developed a depolymerase computer model that uses a minimization routine. The model is designed so that, given experimental bond-cleavage frequencies for oligomeric substrates and experimental Michaelis parameters as a function of substrate chain length, the optimum subsite map is generated. The minimized sum of the weighted-squared residuals of the experimental and calculated data is used as a criterion of the goodness-of-fit for the optimized subsite map. The application of the minimization procedure to subsite mapping is explored through the use of simulated data. A procedure is developed whereby the minimization model can be used to determine the number of subsites in the enzymic binding region and to locate the position of the catalytic amino acids among these subsites. The degree of propagation of experimental variance into the subsite-binding energies is estimated. The question of whether hydrolytic rate coefficients are constant or a function of the number of filled subsites is examined. PMID:999629

Feed-Forward Neural Network Soft-Sensor Modeling of Flotation Process Based on Particle Swarm Optimization and Gravitational Search Algorithm

PubMed Central

Wang, Jie-Sheng; Han, Shuang

2015-01-01

For predicting the key technology indicators (concentrate grade and tailings recovery rate) of flotation process, a feed-forward neural network (FNN) based soft-sensor model optimized by the hybrid algorithm combining particle swarm optimization (PSO) algorithm and gravitational search algorithm (GSA) is proposed. Although GSA has better optimization capability, it has slow convergence velocity and is easy to fall into local optimum. So in this paper, the velocity vector and position vector of GSA are adjusted by PSO algorithm in order to improve its convergence speed and prediction accuracy. Finally, the proposed hybrid algorithm is adopted to optimize the parameters of FNN soft-sensor model. Simulation results show that the model has better generalization and prediction accuracy for the concentrate grade and tailings recovery rate to meet the online soft-sensor requirements of the real-time control in the flotation process. PMID:26583034

Key Factors Influencing the Energy Absorption of Dual-Phase Steels: Multiscale Material Model Approach and Microstructural Optimization

NASA Astrophysics Data System (ADS)

Belgasam, Tarek M.; Zbib, Hussein M.

2018-06-01

The increase in use of dual-phase (DP) steel grades by vehicle manufacturers to enhance crash resistance and reduce body car weight requires the development of a clear understanding of the effect of various microstructural parameters on the energy absorption in these materials. Accordingly, DP steelmakers are interested in predicting the effect of various microscopic factors as well as optimizing microstructural properties for application in crash-relevant components of vehicle bodies. This study presents a microstructure-based approach using a multiscale material and structure model. In this approach, Digimat and LS-DYNA software were coupled and employed to provide a full micro-macro multiscale material model, which is then used to simulate tensile tests. Microstructures with varied ferrite grain sizes, martensite volume fractions, and carbon content in DP steels were studied. The impact of these microstructural features at different strain rates on energy absorption characteristics of DP steels is investigated numerically using an elasto-viscoplastic constitutive model. The model is implemented in a multiscale finite-element framework. A comprehensive statistical parametric study using response surface methodology is performed to determine the optimum microstructural features for a required tensile toughness at different strain rates. The simulation results are validated using experimental data found in the literature. The developed methodology proved to be effective for investigating the influence and interaction of key microscopic properties on the energy absorption characteristics of DP steels. Furthermore, it is shown that this method can be used to identify optimum microstructural conditions at different strain-rate conditions.

Kinetic and isotherm modeling of Cd (II) adsorption by L-cysteine functionalized multi-walled carbon nanotubes as adsorbent.

PubMed

Taghavi, Mahmoud; Zazouli, Mohammad Ali; Yousefi, Zabihollah; Akbari-adergani, Behrouz

2015-11-01

In this study, multi-walled carbon nanotubes were functionalized by L-cysteine to show the kinetic and isotherm modeling of Cd (II) ions onto L-cysteine functionalized multi-walled carbon nanotubes. The adsorption behavior of Cd (II) ion was studied by varying parameters including dose of L-MWCNTs, contact time, and cadmium concentration. Equilibrium adsorption isotherms and kinetics were also investigated based on Cd (II) adsorption tests. The results showed that an increase in contact time and adsorbent dosage resulted in increase of the adsorption rate. The optimum condition of the Cd (II) removal process was found at pH=7.0, 15 mg/L L-MWCNTs dosage, 6 mg/L cadmium concentration, and contact time of 60 min. The removal percent was equal to 89.56 at optimum condition. Langmuir and Freundlich models were employed to analyze the experimental data. The data showed well fitting with the Langmuir model (R2=0.994) with q max of 43.47 mg/g. Analyzing the kinetic data by the pseudo-first-order and pseudo-second-order equations revealed that the adsorption of cadmium using L-MWSNTs following the pseudo-second-order kinetic model with correlation coefficients (R2) equals to 0.998, 0.992, and 0.998 for 3, 6, and 9 mg/L Cd (II) concentrations, respectively. The experimental data fitted very well with the pseudo-second-order. Overall, treatment of polluted solution to Cd (II) by adsorption process using L-MWCNT can be considered as an effective technology.

Key Factors Influencing the Energy Absorption of Dual-Phase Steels: Multiscale Material Model Approach and Microstructural Optimization

NASA Astrophysics Data System (ADS)

Belgasam, Tarek M.; Zbib, Hussein M.

2018-03-01

The increase in use of dual-phase (DP) steel grades by vehicle manufacturers to enhance crash resistance and reduce body car weight requires the development of a clear understanding of the effect of various microstructural parameters on the energy absorption in these materials. Accordingly, DP steelmakers are interested in predicting the effect of various microscopic factors as well as optimizing microstructural properties for application in crash-relevant components of vehicle bodies. This study presents a microstructure-based approach using a multiscale material and structure model. In this approach, Digimat and LS-DYNA software were coupled and employed to provide a full micro-macro multiscale material model, which is then used to simulate tensile tests. Microstructures with varied ferrite grain sizes, martensite volume fractions, and carbon content in DP steels were studied. The impact of these microstructural features at different strain rates on energy absorption characteristics of DP steels is investigated numerically using an elasto-viscoplastic constitutive model. The model is implemented in a multiscale finite-element framework. A comprehensive statistical parametric study using response surface methodology is performed to determine the optimum microstructural features for a required tensile toughness at different strain rates. The simulation results are validated using experimental data found in the literature. The developed methodology proved to be effective for investigating the influence and interaction of key microscopic properties on the energy absorption characteristics of DP steels. Furthermore, it is shown that this method can be used to identify optimum microstructural conditions at different strain-rate conditions.

Testing optimum viewing conditions for mammographic image displays.

PubMed

Waynant, R W; Chakrabarti, K; Kaczmarek, R A; Dagenais, I

1999-05-01

The viewbox luminance and viewing room light level are important parameters in a medical film display, but these parameters have not had much attention. Spatial variations and too much room illumination can mask real signal or create the false perception of a signal. This presentation looks at how scotopic light sources and dark-adapted radiologists may identify more real diseases.

Optimum shape of a blunt forebody in hypersonic flow

NASA Technical Reports Server (NTRS)

Maestrello, L.; Ting, L.

1989-01-01

The optimum shape of a blunt forebody attached to a symmetric wedge or cone is determined. The length of the forebody, its semi-thickness or base radius, the nose radius and the radius of the fillet joining the forebody to the wedge or cone are specified. The optimum shape is composed of simple curves. Thus experimental models can be built readily to investigate the utilization of aerodynamic heating for boundary layer control. The optimum shape based on the modified Newtonian theory can also serve as the preliminary shape for the numerical solution of the optimum shape using the governing equations for a compressible inviscid or viscous flow.

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

PubMed

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

2012-03-01

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

Optimum structural sizing of conventional cantilever and joined wing configurations using equivalent beam models

NASA Technical Reports Server (NTRS)

Hajela, P.; Chen, J. L.

1986-01-01

The present paper describes an approach for the optimum sizing of single and joined wing structures that is based on representing the built-up finite element model of the structure by an equivalent beam model. The low order beam model is computationally more efficient in an environment that requires repetitive analysis of several trial designs. The design procedure is implemented in a computer program that requires geometry and loading data typically available from an aerodynamic synthesis program, to create the finite element model of the lifting surface and an equivalent beam model. A fully stressed design procedure is used to obtain rapid estimates of the optimum structural weight for the beam model for a given geometry, and a qualitative description of the material distribution over the wing structure. The synthesis procedure is demonstrated for representative single wing and joined wing structures.

On the Optimum Architecture of the Biologically Inspired Hierarchical Temporal Memory Model Applied to the Hand-Written Digit Recognition

NASA Astrophysics Data System (ADS)

Štolc, Svorad; Bajla, Ivan

2010-01-01

In the paper we describe basic functions of the Hierarchical Temporal Memory (HTM) network based on a novel biologically inspired model of the large-scale structure of the mammalian neocortex. The focus of this paper is in a systematic exploration of possibilities how to optimize important controlling parameters of the HTM model applied to the classification of hand-written digits from the USPS database. The statistical properties of this database are analyzed using the permutation test which employs a randomization distribution of the training and testing data. Based on a notion of the homogeneous usage of input image pixels, a methodology of the HTM parameter optimization is proposed. In order to study effects of two substantial parameters of the architecture: the patch size and the overlap in more details, we have restricted ourselves to the single-level HTM networks. A novel method for construction of the training sequences by ordering series of the static images is developed. A novel method for estimation of the parameter maxDist based on the box counting method is proposed. The parameter sigma of the inference Gaussian is optimized on the basis of the maximization of the belief distribution entropy. Both optimization algorithms can be equally applied to the multi-level HTM networks as well. The influences of the parameters transitionMemory and requestedGroupCount on the HTM network performance have been explored. Altogether, we have investigated 2736 different HTM network configurations. The obtained classification accuracy results have been benchmarked with the published results of several conventional classifiers.

Studying flow close to an interface by total internal reflection fluorescence cross-correlation spectroscopy: Quantitative data analysis

NASA Astrophysics Data System (ADS)

Schmitz, R.; Yordanov, S.; Butt, H. J.; Koynov, K.; Dünweg, B.

2011-12-01

Total internal reflection fluorescence cross-correlation spectroscopy (TIR-FCCS) has recently [S. Yordanov , Optics ExpressOPEXFF1094-408710.1364/OE.17.021149 17, 21149 (2009)] been established as an experimental method to probe hydrodynamic flows near surfaces, on length scales of tens of nanometers. Its main advantage is that fluorescence occurs only for tracer particles close to the surface, thus resulting in high sensitivity. However, the measured correlation functions provide only rather indirect information about the flow parameters of interest, such as the shear rate and the slip length. In the present paper, we show how to combine detailed and fairly realistic theoretical modeling of the phenomena by Brownian dynamics simulations with accurate measurements of the correlation functions, in order to establish a quantitative method to retrieve the flow properties from the experiments. First, Brownian dynamics is used to sample highly accurate correlation functions for a fixed set of model parameters. Second, these parameters are varied systematically by means of an importance-sampling Monte Carlo procedure in order to fit the experiments. This provides the optimum parameter values together with their statistical error bars. The approach is well suited for massively parallel computers, which allows us to do the data analysis within moderate computing times. The method is applied to flow near a hydrophilic surface, where the slip length is observed to be smaller than 10nm, and, within the limitations of the experiments and the model, indistinguishable from zero.

A feasibility investigation for modeling and optimization of temperature in bone drilling using fuzzy logic and Taguchi optimization methodology.

PubMed

Pandey, Rupesh Kumar; Panda, Sudhansu Sekhar

2014-11-01

Drilling of bone is a common procedure in orthopedic surgery to produce hole for screw insertion to fixate the fracture devices and implants. The increase in temperature during such a procedure increases the chances of thermal invasion of bone which can cause thermal osteonecrosis resulting in the increase of healing time or reduction in the stability and strength of the fixation. Therefore, drilling of bone with minimum temperature is a major challenge for orthopedic fracture treatment. This investigation discusses the use of fuzzy logic and Taguchi methodology for predicting and minimizing the temperature produced during bone drilling. The drilling experiments have been conducted on bovine bone using Taguchi's L25 experimental design. A fuzzy model is developed for predicting the temperature during orthopedic drilling as a function of the drilling process parameters (point angle, helix angle, feed rate and cutting speed). Optimum bone drilling process parameters for minimizing the temperature are determined using Taguchi method. The effect of individual cutting parameters on the temperature produced is evaluated using analysis of variance. The fuzzy model using triangular and trapezoidal membership predicts the temperature within a maximum error of ±7%. Taguchi analysis of the obtained results determined the optimal drilling conditions for minimizing the temperature as A3B5C1.The developed system will simplify the tedious task of modeling and determination of the optimal process parameters to minimize the bone drilling temperature. It will reduce the risk of thermal osteonecrosis and can be very effective for the online condition monitoring of the process. © IMechE 2014.

Tool life and cutting speed for the maximum productivity at the drilling of the stainless steel X22CrMoV12-1

NASA Astrophysics Data System (ADS)

Vlase, A.; Blăjină, O.; Iacob, M.; Darie, V.

2015-11-01

Two addressed issues in the research regarding the cutting machinability, establishing of the optimum cutting processing conditions and the optimum cutting regime, do not yet have sufficient data for solving. For this reason, in the paper it is proposed the optimization of the tool life and the cutting speed at the drilling of a certain stainless steel in terms of the maximum productivity. For this purpose, a nonlinear programming mathematical model to maximize the productivity at the drilling of the steel is developed in the paper. The optimum cutting tool life and the associated cutting tool speed are obtained by solving the numerical mathematical model. Using this proposed model allows increasing the accuracy in the prediction of the productivity for the drilling of a certain stainless steel and getting the optimum tool life and the optimum cutting speed for the maximum productivity. The results presented in this paper can be used in the production activity, in order to increase the productivity of the stainless steels machining. Also new research directions for the specialists in this interested field may come off from this paper.

Retention of ductility in high-strength steels

NASA Technical Reports Server (NTRS)

Parker, E. R.; Zackay, V. F.

1969-01-01

To produce high strength alloy steel with retention of ductility, include tempering, cooling and subsequent tempering. Five parameters for optimum results are pretempering temperature, amount of strain, strain rate, temperature during strain, and retempering temperature.

Analysis and Experimental Investigation of Optimum Design of Thermoelectric Cooling/Heating System for Car Seat Climate Control (CSCC)

NASA Astrophysics Data System (ADS)

Elarusi, Abdulmunaem; Attar, Alaa; Lee, HoSung

2018-02-01

The optimum design of a thermoelectric system for application in car seat climate control has been modeled and its performance evaluated experimentally. The optimum design of the thermoelectric device combining two heat exchangers was obtained by using a newly developed optimization method based on the dimensional technique. Based on the analytical optimum design results, commercial thermoelectric cooler and heat sinks were selected to design and construct the climate control heat pump. This work focuses on testing the system performance in both cooling and heating modes to ensure accurate analytical modeling. Although the analytical performance was calculated using the simple ideal thermoelectric equations with effective thermoelectric material properties, it showed very good agreement with experiment for most operating conditions.

Parameter extraction with neural networks

NASA Astrophysics Data System (ADS)

Cazzanti, Luca; Khan, Mumit; Cerrina, Franco

1998-06-01

In semiconductor processing, the modeling of the process is becoming more and more important. While the ultimate goal is that of developing a set of tools for designing a complete process (Technology CAD), it is also necessary to have modules to simulate the various technologies and, in particular, to optimize specific steps. This need is particularly acute in lithography, where the continuous decrease in CD forces the technologies to operate near their limits. In the development of a 'model' for a physical process, we face several levels of challenges. First, it is necessary to develop a 'physical model,' i.e. a rational description of the process itself on the basis of know physical laws. Second, we need an 'algorithmic model' to represent in a virtual environment the behavior of the 'physical model.' After a 'complete' model has been developed and verified, it becomes possible to do performance analysis. In many cases the input parameters are poorly known or not accessible directly to experiment. It would be extremely useful to obtain the values of these 'hidden' parameters from experimental results by comparing model to data. This is particularly severe, because the complexity and costs associated with semiconductor processing make a simple 'trial-and-error' approach infeasible and cost- inefficient. Even when computer models of the process already exists, obtaining data through simulations may be time consuming. Neural networks (NN) are powerful computational tools to predict the behavior of a system from an existing data set. They are able to adaptively 'learn' input/output mappings and to act as universal function approximators. In this paper we use artificial neural networks to build a mapping from the input parameters of the process to output parameters which are indicative of the performance of the process. Once the NN has been 'trained,' it is also possible to observe the process 'in reverse,' and to extract the values of the inputs which yield outputs with desired characteristics. Using this method, we can extract optimum values for the parameters and determine the process latitude very quickly.

War-gaming application for future space systems acquisition part 2: acquisition and bidding war-gaming modeling and simulation approaches for FFP and FPIF

NASA Astrophysics Data System (ADS)

Nguyen, Tien M.; Guillen, Andy T.

2017-05-01

This paper describes cooperative and non-cooperative static Bayesian game models with complete and incomplete information for the development of optimum acquisition strategies associated with the Program and Technical Baseline (PTB) solutions obtained from Part 1 of this paper [1]. The optimum acquisition strategies discussed focus on achieving "Affordability" by incorporating contractors' bidding strategies into the government acquisition strategies for acquiring future space systems. The paper discusses System Engineering (SE) frameworks, analytical and simulation approaches and modeling for developing the optimum acquisition strategies from both the government and contractor perspectives for Firm Fixed Price (FFP) and Fixed Price Incentive Firm (FPIF) contract types.

Developing an Optimum Protocol for Thermoluminescence Dosimetry with GR-200 Chips using Taguchi Method.

PubMed

Sadeghi, Maryam; Faghihi, Reza; Sina, Sedigheh

2017-06-15

Thermoluminescence dosimetry (TLD) is a powerful technique with wide applications in personal, environmental and clinical dosimetry. The optimum annealing, storage and reading protocols are very effective in accuracy of TLD response. The purpose of this study is to obtain an optimum protocol for GR-200; LiF: Mg, Cu, P, by optimizing the effective parameters, to increase the reliability of the TLD response using Taguchi method. Taguchi method has been used in this study for optimization of annealing, storage and reading protocols of the TLDs. A number of 108 GR-200 chips were divided into 27 groups, each containing four chips. The TLDs were exposed to three different doses, and stored, annealed and read out by different procedures as suggested by Taguchi Method. By comparing the signal-to-noise ratios the optimum dosimetry procedure was obtained. According to the results, the optimum values for annealing temperature (°C), Annealing Time (s), Annealing to Exposure time (d), Exposure to Readout time (d), Pre-heat Temperature (°C), Pre-heat Time (s), Heating Rate (°C/s), Maximum Temperature of Readout (°C), readout time (s) and Storage Temperature (°C) are 240, 90, 1, 2, 50, 0, 15, 240, 13 and -20, respectively. Using the optimum protocol, an efficient glow curve with low residual signals can be achieved. Using optimum protocol obtained by Taguchi method, the dosimetry can be effectively performed with great accuracy. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Superinsulating Polyisocyanate Based Aerogels: A Targeted Search for the Optimum Solvent System.

PubMed

Zhu, Zhiyuan; Snellings, Geert M B F; Koebel, Matthias M; Malfait, Wim J

2017-05-31

Polyisocyanate based aerogels combine ultralow thermal conductivities with better mechanical properties than silica aerogel, but these properties critically depend on the nature of the gelation solvent, perhaps more so than on any other parameter. Here, we present a systematic study of the relationship between the polyurethane-polyisocyanurate (PUR-PIR) aerogel microstructure, surface area, thermal conductivity, and density and the gelation solvent's Hansen solubility parameters for an industrially relevant PUR-PIR rigid foam formulation. We first investigated aerogels prepared in acetone-dimethyl sulfoxide (DMSO) blends and observed a minimum in thermal conductivity (λ) and maximum in specific surface area for an acetone:DMSO ratio of 85:15 v/v. We then prepared PUR-PIR aerogels in 32 different solvent blends, divided into three series with δ Dispersion , δ Polarity , and δ H-bonding fixed at 15.94, 11.30, and 7.48 MPa 1/2 , respectively, corresponding to the optimum parameters for the acetone:DMSO series. The aerogel properties display distinct dependencies on the various solubility parameters: aerogels with low thermal conductivity can be synthesized in solvents with a high δ H-bonding parameter (above 7.2) and δ Dispersion around 16.3 MPa 1/2 . In contrast, the δ Polarity parameter is of lesser importance. Our study highlights the importance of the gelation solvent, clarifies the influence of the different solvent properties, and provides a methodology for a targeted search across the solvent chemical space based on the Hansen solubility parameters.

Optimum Design Rules for CMOS Hall Sensors

PubMed Central

Crescentini, Marco; Biondi, Michele; Romani, Aldo; Tartagni, Marco; Sangiorgi, Enrico

2017-01-01

This manuscript analyzes the effects of design parameters, such as aspect ratio, doping concentration and bias, on the performance of a general CMOS Hall sensor, with insight on current-related sensitivity, power consumption, and bandwidth. The article focuses on rectangular-shaped Hall probes since this is the most general geometry leading to shape-independent results. The devices are analyzed by means of 3D-TCAD simulations embedding galvanomagnetic transport model, which takes into account the Lorentz force acting on carriers due to a magnetic field. Simulation results define a set of trade-offs and design rules that can be used by electronic designers to conceive their own Hall probes. PMID:28375191

Optimum Design Rules for CMOS Hall Sensors.

PubMed

Crescentini, Marco; Biondi, Michele; Romani, Aldo; Tartagni, Marco; Sangiorgi, Enrico

2017-04-04

This manuscript analyzes the effects of design parameters, such as aspect ratio, doping concentration and bias, on the performance of a general CMOS Hall sensor, with insight on current-related sensitivity, power consumption, and bandwidth. The article focuses on rectangular-shaped Hall probes since this is the most general geometry leading to shape-independent results. The devices are analyzed by means of 3D-TCAD simulations embedding galvanomagnetic transport model, which takes into account the Lorentz force acting on carriers due to a magnetic field. Simulation results define a set of trade-offs and design rules that can be used by electronic designers to conceive their own Hall probes.

Hyperbola-parabola primary mirror in Cassegrain optical antenna to improve transmission efficiency.

PubMed

Zhang, Li; Chen, Lu; Yang, HuaJun; Jiang, Ping; Mao, Shengqian; Caiyang, Weinan

2015-08-20

An optical model with a hyperbola-parabola primary mirror added in the Cassegrain optical antenna, which can effectively improve the transmission efficiency, is proposed in this paper. The optimum parameters of a hyperbola-parabola primary mirror and a secondary mirror for the optical antenna system have been designed and analyzed in detail. The parabola-hyperbola primary structure optical antenna is obtained to improve the transmission efficiency of 10.60% in theory, and the simulation efficiency changed 9.359%. For different deflection angles to the receiving antenna with the emit antenna, the coupling efficiency curve of the optical antenna has been obtained.

Solid-State Thermionic Power Generators: An Analytical Analysis in the Nonlinear Regime

NASA Astrophysics Data System (ADS)

Zebarjadi, M.

2017-07-01

Solid-state thermionic power generators are an alternative to thermoelectric modules. In this paper, we develop an analytical model to investigate the performance of these generators in the nonlinear regime. We identify dimensionless parameters determining their performance and provide measures to estimate an acceptable range of thermal and electrical resistances of thermionic generators. We find the relation between the optimum load resistance and the internal resistance and suggest guidelines for the design of thermionic power generators. Finally, we show that in the nonlinear regime, thermionic power generators can have efficiency values higher than the state-of-the-art thermoelectric modules.

Modeling the Hot Tensile Flow Behaviors at Ultra-High-Strength Steel and Construction of Three-Dimensional Continuous Interaction Space for Forming Parameters

NASA Astrophysics Data System (ADS)

Quan, Guo-zheng; Zhan, Zong-yang; Wang, Tong; Xia, Yu-feng

2017-01-01

The response of true stress to strain rate, temperature and strain is a complex three-dimensional (3D) issue, and the accurate description of such constitutive relationships significantly contributes to the optimum process design. To obtain the true stress-strain data of ultra-high-strength steel, BR1500HS, a series of isothermal hot tensile tests were conducted in a wide temperature range of 973-1,123 K and a strain rate range of 0.01-10 s-1 on a Gleeble 3800 testing machine. Then the constitutive relationships were modeled by an optimally constructed and well-trained backpropagation artificial neural network (BP-ANN). The evaluation of BP-ANN model revealed that it has admirable performance in characterizing and predicting the flow behaviors of BR1500HS. A comparison on improved Arrhenius-type constitutive equation and BP-ANN model shows that the latter has higher accuracy. Consequently, the developed BP-ANN model was used to predict abundant stress-strain data beyond the limited experimental conditions. Then a 3D continuous interaction space for temperature, strain rate, strain and stress was constructed based on these predicted data. The developed 3D continuous interaction space for hot working parameters contributes to fully revealing the intrinsic relationships of BR1500HS steel.

QSAR models for removal rates of organic pollutants adsorbed by in situ formed manganese dioxide under acid condition.

PubMed

Su, Pingru; Zhu, Huicen; Shen, Zhemin

2016-02-01

Manganese dioxide formed in oxidation process by potassium permanganate exhibits promising adsorptive capacity which can be utilized to remove organic pollutants in wastewater. However, the structure variances of organic molecules lead to wide difference of adsorption efficiency. Therefore, it is of great significance to find a general relationship between removal rate of organic compounds and their quantum parameters. This study focused on building up quantitative structure activity relationship (QSAR) models based on experimental removal rate (r(exp)) of 25 organic compounds and 17 quantum parameters of each organic compounds computed by Gaussian 09 and Material Studio 6.1. The recommended model is rpre = -0.502-7.742 f(+)x + 0.107 E HOMO + 0.959 q(H(+)) + 1.388 BOx. Both internal and external validations of the recommended model are satisfied, suggesting optimum stability and predictive ability. The definition of applicability domain and the Y-randomization test indicate all the prediction is reliable and no possibility of chance correlation. The recommended model contains four variables, which are closely related to adsorption mechanism. f(+)x reveals the degree of affinity for nucleophilic attack. E HOMO represents the difficulty of electron loss. q(H(+)) reflect the distribution of partial charge between carbon and hydrogen atom. BO x shows the stability of a molecule.

Microstructure Optimization of Dual-Phase Steels Using a Representative Volume Element and a Response Surface Method: Parametric Study

NASA Astrophysics Data System (ADS)

Belgasam, Tarek M.; Zbib, Hussein M.

2017-12-01

Dual-phase (DP) steels have received widespread attention for their low density and high strength. This low density is of value to the automotive industry for the weight reduction it offers and the attendant fuel savings and emission reductions. Recent studies on developing DP steels showed that the combination of strength/ductility could be significantly improved when changing the volume fraction and grain size of phases in the microstructure depending on microstructure properties. Consequently, DP steel manufacturers are interested in predicting microstructure properties and in optimizing microstructure design. In this work, a microstructure-based approach using representative volume elements (RVEs) was developed. The approach examined the flow behavior of DP steels using virtual tension tests with an RVE to identify specific mechanical properties. Microstructures with varied martensite and ferrite grain sizes, martensite volume fractions, carbon content, and morphologies were studied in 3D RVE approaches. The effect of these microstructure parameters on a combination of strength/ductility of DP steels was examined numerically using the finite element method by implementing a dislocation density-based elastic-plastic constitutive model, and a Response surface methodology to determine the optimum conditions for a required combination of strength/ductility. The results from the numerical simulations are compared with experimental results found in the literature. The developed methodology proves to be a powerful tool for studying the effect and interaction of key microstructural parameters on strength and ductility and thus can be used to identify optimum microstructural conditions.

Biosorption of Congo Red from aqueous solution onto burned root of Eichhornia crassipes biomass

NASA Astrophysics Data System (ADS)

Roy, Tapas Kumar; Mondal, Naba Kumar

2017-07-01

Biosorption is becoming a promising alternative to replace or supplement the present dye removal processes from dye containing waste water. In this work, adsorption of Congo Red (CR) from aqueous solution on burned root of Eichhornia crassipes ( BREC) biomass was investigated. A series of batch experiments were performed utilizing BREC biomass to remove CR dye from aqueous systems. Under optimized batch conditions, the BREC could remove up to 94.35 % of CR from waste water. The effects of operating parameters such as initial concentration, pH, adsorbent dose and contact time on the adsorption of CR were analyzed using response surface methodology. The proposed quadratic model for central composite design fitted very well to the experimental data. Response surface plots were used to determine the interaction effects of main factors and optimum conditions of the process. The optimum adsorption conditions were found to be initial CR concentration = 5 mg/L-1, pH = 7, adsorbent dose = 0.125 g and contact time = 45 min. The experimental isotherms data were analyzed using Langmuir, Freundlich, Temkin and Dubinin-Radushkevich (D-R) isotherm equations and the results indicated that the Freundlich isotherm showed a better fit for CR adsorption. Thermodynamic parameters were calculated from Van't Hoff plot, confirming that the adsorption process was spontaneous and exothermic. The high CR adsorptive removal ability and regeneration efficiency of this adsorbent suggest its applicability in industrial/household systems and data generated would help in further upscaling of the adsorption process.

Generation Process of Large-Amplitude Upper-Band Chorus Emissions Observed by Van Allen Probes

DOE PAGES

Kubota, Yuko; Omura, Yoshiharu; Kletzing, Craig; ...

2018-04-19

In this paper, we analyze large-amplitude upper-band chorus emissions measured near the magnetic equator by the Electric and Magnetic Field Instrument Suite and Integrated Science instrument package on board the Van Allen Probes. In setting up the parameters of source electrons exciting the emissions based on theoretical analyses and observational results measured by the Helium Oxygen Proton Electron instrument, we calculate threshold and optimum amplitudes with the nonlinear wave growth theory. We find that the optimum amplitude is larger than the threshold amplitude obtained in the frequency range of the chorus emissions and that the wave amplitudes grow between themore » threshold and optimum amplitudes. Finally, in the frame of the wave growth process, the nonlinear growth rates are much greater than the linear growth rates.« less