Selecting the best design for nonstandard toxicology experiments.

PubMed

Webb, Jennifer M; Smucker, Byran J; Bailer, A John

2014-10-01

Although many experiments in environmental toxicology use standard statistical experimental designs, there are situations that arise where no such standard design is natural or applicable because of logistical constraints. For example, the layout of a laboratory may suggest that each shelf serve as a block, with the number of experimental units per shelf either greater than or less than the number of treatments in a way that precludes the use of a typical block design. In such cases, an effective and powerful alternative is to employ optimal experimental design principles, a strategy that produces designs with precise statistical estimates. Here, a D-optimal design was generated for an experiment in environmental toxicology that has 2 factors, 16 treatments, and constraints similar to those described above. After initial consideration of a randomized complete block design and an intuitive cyclic design, it was decided to compare a D-optimal design and a slightly more complicated version of the cyclic design. Simulations were conducted generating random responses under a variety of scenarios that reflect conditions motivated by a similar toxicology study, and the designs were evaluated via D-efficiency as well as by a power analysis. The cyclic design performed well compared to the D-optimal design. © 2014 SETAC.

3D Printed Composites for Topology Transforming Multifunctional Devices

DTIC Science & Technology

2017-01-26

approach to find non -trivial designs. The comparison against experimental measurements motivates future research on improving the accuracy of the...new methodology for the fabrication and the design of new multifunctional composites and devices using 3D printing. The main accomplishments of this...design; 6) developing a finite element framework for the optimum design of PACS by topology optimization; 7) optimizing and experimentally

Experimental Validation of an Integrated Controls-Structures Design Methodology

NASA Technical Reports Server (NTRS)

Maghami, Peiman G.; Gupta, Sandeep; Elliot, Kenny B.; Walz, Joseph E.

1996-01-01

The first experimental validation of an integrated controls-structures design methodology for a class of large order, flexible space structures is described. Integrated redesign of the controls-structures-interaction evolutionary model, a laboratory testbed at NASA Langley, was described earlier. The redesigned structure was fabricated, assembled in the laboratory, and experimentally tested against the original structure. Experimental results indicate that the structure redesigned using the integrated design methodology requires significantly less average control power than the nominal structure with control-optimized designs, while maintaining the required line-of-sight pointing performance. Thus, the superiority of the integrated design methodology over the conventional design approach is experimentally demonstrated. Furthermore, amenability of the integrated design structure to other control strategies is evaluated, both analytically and experimentally. Using Linear-Quadratic-Guassian optimal dissipative controllers, it is observed that the redesigned structure leads to significantly improved performance with alternate controllers as well.

A More Rigorous Quasi-Experimental Alternative to the One-Group Pretest-Posttest Design.

ERIC Educational Resources Information Center

Johnson, Craig W.

1986-01-01

A simple quasi-experimental design is described which may have utility in a variety of applied and laboratory research settings where ordinarily the one-group pretest-posttest pre-experimental design might otherwise be the procedure of choice. The design approaches the internal validity of true experimental designs while optimizing external…

D-Optimal Experimental Design for Contaminant Source Identification

NASA Astrophysics Data System (ADS)

Sai Baba, A. K.; Alexanderian, A.

2016-12-01

Contaminant source identification seeks to estimate the release history of a conservative solute given point concentration measurements at some time after the release. This can be mathematically expressed as an inverse problem, with a linear observation operator or a parameter-to-observation map, which we tackle using a Bayesian approach. Acquisition of experimental data can be laborious and expensive. The goal is to control the experimental parameters - in our case, the sparsity of the sensors, to maximize the information gain subject to some physical or budget constraints. This is known as optimal experimental design (OED). D-optimal experimental design seeks to maximize the expected information gain, and has long been considered the gold standard in the statistics community. Our goal is to develop scalable methods for D-optimal experimental designs involving large-scale PDE constrained problems with high-dimensional parameter fields. A major challenge for the OED, is that a nonlinear optimization algorithm for the D-optimality criterion requires repeated evaluation of objective function and gradient involving the determinant of large and dense matrices - this cost can be prohibitively expensive for applications of interest. We propose novel randomized matrix techniques that bring down the computational costs of the objective function and gradient evaluations by several orders of magnitude compared to the naive approach. The effect of randomized estimators on the accuracy and the convergence of the optimization solver will be discussed. The features and benefits of our new approach will be demonstrated on a challenging model problem from contaminant source identification involving the inference of the initial condition from spatio-temporal observations in a time-dependent advection-diffusion problem.

Optimal experimental design in an epidermal growth factor receptor signalling and down-regulation model.

PubMed

Casey, F P; Baird, D; Feng, Q; Gutenkunst, R N; Waterfall, J J; Myers, C R; Brown, K S; Cerione, R A; Sethna, J P

2007-05-01

We apply the methods of optimal experimental design to a differential equation model for epidermal growth factor receptor signalling, trafficking and down-regulation. The model incorporates the role of a recently discovered protein complex made up of the E3 ubiquitin ligase, Cbl, the guanine exchange factor (GEF), Cool-1 (beta -Pix) and the Rho family G protein Cdc42. The complex has been suggested to be important in disrupting receptor down-regulation. We demonstrate that the model interactions can accurately reproduce the experimental observations, that they can be used to make predictions with accompanying uncertainties, and that we can apply ideas of optimal experimental design to suggest new experiments that reduce the uncertainty on unmeasurable components of the system.

Time-oriented experimental design method to optimize hydrophilic matrix formulations with gelation kinetics and drug release profiles.

PubMed

Shin, Sangmun; Choi, Du Hyung; Truong, Nguyen Khoa Viet; Kim, Nam Ah; Chu, Kyung Rok; Jeong, Seong Hoon

2011-04-04

A new experimental design methodology was developed by integrating the response surface methodology and the time series modeling. The major purposes were to identify significant factors in determining swelling and release rate from matrix tablets and their relative factor levels for optimizing the experimental responses. Properties of tablet swelling and drug release were assessed with ten factors and two default factors, a hydrophilic model drug (terazosin) and magnesium stearate, and compared with target values. The selected input control factors were arranged in a mixture simplex lattice design with 21 experimental runs. The obtained optimal settings for gelation were PEO, LH-11, Syloid, and Pharmacoat with weight ratios of 215.33 (88.50%), 5.68 (2.33%), 19.27 (7.92%), and 3.04 (1.25%), respectively. The optimal settings for drug release were PEO and citric acid with weight ratios of 191.99 (78.91%) and 51.32 (21.09%), respectively. Based on the results of matrix swelling and drug release, the optimal solutions, target values, and validation experiment results over time were similar and showed consistent patterns with very small biases. The experimental design methodology could be a very promising experimental design method to obtain maximum information with limited time and resources. It could also be very useful in formulation studies by providing a systematic and reliable screening method to characterize significant factors in the sustained release matrix tablet. Copyright © 2011 Elsevier B.V. All rights reserved.

OPTIMIZING THE PRECISION OF TOXICITY THRESHOLD ESTIMATION USING A TWO-STAGE EXPERIMENTAL DESIGN

EPA Science Inventory

An important consideration for risk assessment is the existence of a threshold, i.e., the highest toxicant dose where the response is not distinguishable from background. We have developed methodology for finding an experimental design that optimizes the precision of threshold mo...

Bayesian cross-entropy methodology for optimal design of validation experiments

NASA Astrophysics Data System (ADS)

Jiang, X.; Mahadevan, S.

2006-07-01

An important concern in the design of validation experiments is how to incorporate the mathematical model in the design in order to allow conclusive comparisons of model prediction with experimental output in model assessment. The classical experimental design methods are more suitable for phenomena discovery and may result in a subjective, expensive, time-consuming and ineffective design that may adversely impact these comparisons. In this paper, an integrated Bayesian cross-entropy methodology is proposed to perform the optimal design of validation experiments incorporating the computational model. The expected cross entropy, an information-theoretic distance between the distributions of model prediction and experimental observation, is defined as a utility function to measure the similarity of two distributions. A simulated annealing algorithm is used to find optimal values of input variables through minimizing or maximizing the expected cross entropy. The measured data after testing with the optimum input values are used to update the distribution of the experimental output using Bayes theorem. The procedure is repeated to adaptively design the required number of experiments for model assessment, each time ensuring that the experiment provides effective comparison for validation. The methodology is illustrated for the optimal design of validation experiments for a three-leg bolted joint structure and a composite helicopter rotor hub component.

Optimal experimental designs for the estimation of thermal properties of composite materials

NASA Technical Reports Server (NTRS)

Scott, Elaine P.; Moncman, Deborah A.

1994-01-01

Reliable estimation of thermal properties is extremely important in the utilization of new advanced materials, such as composite materials. The accuracy of these estimates can be increased if the experiments are designed carefully. The objectives of this study are to design optimal experiments to be used in the prediction of these thermal properties and to then utilize these designs in the development of an estimation procedure to determine the effective thermal properties (thermal conductivity and volumetric heat capacity). The experiments were optimized by choosing experimental parameters that maximize the temperature derivatives with respect to all of the unknown thermal properties. This procedure has the effect of minimizing the confidence intervals of the resulting thermal property estimates. Both one-dimensional and two-dimensional experimental designs were optimized. A heat flux boundary condition is required in both analyses for the simultaneous estimation of the thermal properties. For the one-dimensional experiment, the parameters optimized were the heating time of the applied heat flux, the temperature sensor location, and the experimental time. In addition to these parameters, the optimal location of the heat flux was also determined for the two-dimensional experiments. Utilizing the optimal one-dimensional experiment, the effective thermal conductivity perpendicular to the fibers and the effective volumetric heat capacity were then estimated for an IM7-Bismaleimide composite material. The estimation procedure used is based on the minimization of a least squares function which incorporates both calculated and measured temperatures and allows for the parameters to be estimated simultaneously.

Optimization of Compressor Mounting Bracket of a Passenger Car

NASA Astrophysics Data System (ADS)

Kalsi, Sachin; Singh, Daljeet; Saini, J. S.

2018-05-01

In the present work, the CAE tools are used for the optimization of the compressor mounting bracket used in an automobile. Both static and dynamic analysis is done for the bracket. With the objective to minimize the mass and increase the stiffness of the bracket, the new design is optimized using shape and topology optimization techniques. The optimized design given by CAE tool is then validated experimentally. The new design results in lower level of vibrations, contribute to lower mass along with lesser cost which is effective in air conditioning system as well as the efficiency of a vehicle. The results given by CAE tool had a very good correlation with the experimental results.

A framework for accelerated phototrophic bioprocess development: integration of parallelized microscale cultivation, laboratory automation and Kriging-assisted experimental design.

PubMed

Morschett, Holger; Freier, Lars; Rohde, Jannis; Wiechert, Wolfgang; von Lieres, Eric; Oldiges, Marco

2017-01-01

Even though microalgae-derived biodiesel has regained interest within the last decade, industrial production is still challenging for economic reasons. Besides reactor design, as well as value chain and strain engineering, laborious and slow early-stage parameter optimization represents a major drawback. The present study introduces a framework for the accelerated development of phototrophic bioprocesses. A state-of-the-art micro-photobioreactor supported by a liquid-handling robot for automated medium preparation and product quantification was used. To take full advantage of the technology's experimental capacity, Kriging-assisted experimental design was integrated to enable highly efficient execution of screening applications. The resulting platform was used for medium optimization of a lipid production process using Chlorella vulgaris toward maximum volumetric productivity. Within only four experimental rounds, lipid production was increased approximately threefold to 212 ± 11 mg L -1  d -1 . Besides nitrogen availability as a key parameter, magnesium, calcium and various trace elements were shown to be of crucial importance. Here, synergistic multi-parameter interactions as revealed by the experimental design introduced significant further optimization potential. The integration of parallelized microscale cultivation, laboratory automation and Kriging-assisted experimental design proved to be a fruitful tool for the accelerated development of phototrophic bioprocesses. By means of the proposed technology, the targeted optimization task was conducted in a very timely and material-efficient manner.

A new experimental design method to optimize formulations focusing on a lubricant for hydrophilic matrix tablets.

PubMed

Choi, Du Hyung; Shin, Sangmun; Khoa Viet Truong, Nguyen; Jeong, Seong Hoon

2012-09-01

A robust experimental design method was developed with the well-established response surface methodology and time series modeling to facilitate the formulation development process with magnesium stearate incorporated into hydrophilic matrix tablets. Two directional analyses and a time-oriented model were utilized to optimize the experimental responses. Evaluations of tablet gelation and drug release were conducted with two factors x₁ and x₂: one was a formulation factor (the amount of magnesium stearate) and the other was a processing factor (mixing time), respectively. Moreover, different batch sizes (100 and 500 tablet batches) were also evaluated to investigate an effect of batch size. The selected input control factors were arranged in a mixture simplex lattice design with 13 experimental runs. The obtained optimal settings of magnesium stearate for gelation were 0.46 g, 2.76 min (mixing time) for a 100 tablet batch and 1.54 g, 6.51 min for a 500 tablet batch. The optimal settings for drug release were 0.33 g, 7.99 min for a 100 tablet batch and 1.54 g, 6.51 min for a 500 tablet batch. The exact ratio and mixing time of magnesium stearate could be formulated according to the resulting hydrophilic matrix tablet properties. The newly designed experimental method provided very useful information for characterizing significant factors and hence to obtain optimum formulations allowing for a systematic and reliable experimental design method.

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.

Identification of vehicle suspension parameters by design optimization

NASA Astrophysics Data System (ADS)

Tey, J. Y.; Ramli, R.; Kheng, C. W.; Chong, S. Y.; Abidin, M. A. Z.

2014-05-01

The design of a vehicle suspension system through simulation requires accurate representation of the design parameters. These parameters are usually difficult to measure or sometimes unavailable. This article proposes an efficient approach to identify the unknown parameters through optimization based on experimental results, where the covariance matrix adaptation-evolutionary strategy (CMA-es) is utilized to improve the simulation and experimental results against the kinematic and compliance tests. This speeds up the design and development cycle by recovering all the unknown data with respect to a set of kinematic measurements through a single optimization process. A case study employing a McPherson strut suspension system is modelled in a multi-body dynamic system. Three kinematic and compliance tests are examined, namely, vertical parallel wheel travel, opposite wheel travel and single wheel travel. The problem is formulated as a multi-objective optimization problem with 40 objectives and 49 design parameters. A hierarchical clustering method based on global sensitivity analysis is used to reduce the number of objectives to 30 by grouping correlated objectives together. Then, a dynamic summation of rank value is used as pseudo-objective functions to reformulate the multi-objective optimization to a single-objective optimization problem. The optimized results show a significant improvement in the correlation between the simulated model and the experimental model. Once accurate representation of the vehicle suspension model is achieved, further analysis, such as ride and handling performances, can be implemented for further optimization.

A new optimal sliding mode controller design using scalar sign function.

PubMed

Singla, Mithun; Shieh, Leang-San; Song, Gangbing; Xie, Linbo; Zhang, Yongpeng

2014-03-01

This paper presents a new optimal sliding mode controller using the scalar sign function method. A smooth, continuous-time scalar sign function is used to replace the discontinuous switching function in the design of a sliding mode controller. The proposed sliding mode controller is designed using an optimal Linear Quadratic Regulator (LQR) approach. The sliding surface of the system is designed using stable eigenvectors and the scalar sign function. Controller simulations are compared with another existing optimal sliding mode controller. To test the effectiveness of the proposed controller, the controller is implemented on an aluminum beam with piezoceramic sensor and actuator for vibration control. This paper includes the control design and stability analysis of the new optimal sliding mode controller, followed by simulation and experimental results. The simulation and experimental results show that the proposed approach is very effective. © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Three-dimensional shape optimization of a cemented hip stem and experimental validations.

PubMed

Higa, Masaru; Tanino, Hiromasa; Nishimura, Ikuya; Mitamura, Yoshinori; Matsuno, Takeo; Ito, Hiroshi

2015-03-01

This study proposes novel optimized stem geometry with low stress values in the cement using a finite element (FE) analysis combined with an optimization procedure and experimental measurements of cement stress in vitro. We first optimized an existing stem geometry using a three-dimensional FE analysis combined with a shape optimization technique. One of the most important factors in the cemented stem design is to reduce stress in the cement. Hence, in the optimization study, we minimized the largest tensile principal stress in the cement mantle under a physiological loading condition by changing the stem geometry. As the next step, the optimized stem and the existing stem were manufactured to validate the usefulness of the numerical models and the results of the optimization in vitro. In the experimental study, strain gauges were embedded in the cement mantle to measure the strain in the cement mantle adjacent to the stems. The overall trend of the experimental study was in good agreement with the results of the numerical study, and we were able to reduce the largest stress by more than 50% in both shape optimization and strain gauge measurements. Thus, we could validate the usefulness of the numerical models and the results of the optimization using the experimental models. The optimization employed in this study is a useful approach for developing new stem designs.

Development and experimental design of a novel controlled-release matrix tablet formulation for indapamide hemihydrate.

PubMed

Antovska, Packa; Ugarkovic, Sonja; Petruševski, Gjorgji; Stefanova, Bosilka; Manchevska, Blagica; Petkovska, Rumenka; Makreski, Petre

2017-11-01

Development, experimental design and in vitro in vivo correlation (IVIVC) of controlled-release matrix formulation. Development of novel oral controlled delivery system for indapamide hemihydrate, optimization of the formulation by experimental design and evaluation regarding IVIVC on a pilot scale batch as a confirmation of a well-established formulation. In vitro dissolution profiles of controlled-release tablets of indapamide hemihydrate from four different matrices had been evaluated in comparison to the originator's product Natrilix (Servier) as a direction for further development and optimization of a hydroxyethylcellulose-based matrix controlled-release formulation. A central composite factorial design had been applied for the optimization of a chosen controlled-release tablet formulation. The controlled-release tablets with appropriate physical and technological properties had been obtained with a matrix: binder concentration variations in the range: 20-40w/w% for the matrix and 1-3w/w% for the binder. The experimental design had defined the design space for the formulation and was prerequisite for extraction of a particular formulation that would be a subject for transfer on pilot scale and IVIV correlation. The release model of the optimized formulation has shown best fit to the zero order kinetics depicted with the Hixson-Crowell erosion-dependent mechanism of release. Level A correlation was obtained.

Optimal design of disc-type magneto-rheological brake for mid-sized motorcycle: experimental evaluation

NASA Astrophysics Data System (ADS)

Sohn, Jung Woo; Jeon, Juncheol; Nguyen, Quoc Hung; Choi, Seung-Bok

2015-08-01

In this paper, a disc-type magneto-rheological (MR) brake is designed for a mid-sized motorcycle and its performance is experimentally evaluated. The proposed MR brake consists of an outer housing, a rotating disc immersed in MR fluid, and a copper wire coiled around a bobbin to generate a magnetic field. The structural configuration of the MR brake is first presented with consideration of the installation space for the conventional hydraulic brake of a mid-sized motorcycle. The design parameters of the proposed MR brake are optimized to satisfy design requirements such as the braking torque, total mass of the MR brake, and cruising temperature caused by the magnetic-field friction of the MR fluid. In the optimization procedure, the braking torque is calculated based on the Herschel-Bulkley rheological model, which predicts MR fluid behavior well at high shear rate. An optimization tool based on finite element analysis is used to obtain the optimized dimensions of the MR brake. After manufacturing the MR brake, mechanical performances regarding the response time, braking torque and cruising temperature are experimentally evaluated.

Optimising reversed-phase liquid chromatographic separation of an acidic mixture on a monolithic stationary phase with the aid of response surface methodology and experimental design.

PubMed

Wang, Y; Harrison, M; Clark, B J

2006-02-10

An optimization strategy for the separation of an acidic mixture by employing a monolithic stationary phase is presented, with the aid of experimental design and response surface methodology (RSM). An orthogonal array design (OAD) OA(16) (2(15)) was used to choose the significant parameters for the optimization. The significant factors were optimized by using a central composite design (CCD) and the quadratic models between the dependent and the independent parameters were built. The mathematical models were tested on a number of simulated data set and had a coefficient of R(2) > 0.97 (n = 16). On applying the optimization strategy, the factor effects were visualized as three-dimensional (3D) response surfaces and contour plots. The optimal condition was achieved in less than 40 min by using the monolithic packing with the mobile phase of methanol/20 mM phosphate buffer pH 2.7 (25.5/74.5, v/v). The method showed good agreement between the experimental data and predictive value throughout the studied parameter space and were suitable for optimization studies on the monolithic stationary phase for acidic compounds.

Experimental validation of an integrated controls-structures design methodology for a class of flexible space structures

NASA Technical Reports Server (NTRS)

Maghami, Peiman G.; Gupta, Sandeep; Elliott, Kenny B.; Joshi, Suresh M.; Walz, Joseph E.

1994-01-01

This paper describes the first experimental validation of an optimization-based integrated controls-structures design methodology for a class of flexible space structures. The Controls-Structures-Interaction (CSI) Evolutionary Model, a laboratory test bed at Langley, is redesigned based on the integrated design methodology with two different dissipative control strategies. The redesigned structure is fabricated, assembled in the laboratory, and experimentally compared with the original test structure. Design guides are proposed and used in the integrated design process to ensure that the resulting structure can be fabricated. Experimental results indicate that the integrated design requires greater than 60 percent less average control power (by thruster actuators) than the conventional control-optimized design while maintaining the required line-of-sight performance, thereby confirming the analytical findings about the superiority of the integrated design methodology. Amenability of the integrated design structure to other control strategies is considered and evaluated analytically and experimentally. This work also demonstrates the capabilities of the Langley-developed design tool CSI DESIGN which provides a unified environment for structural and control design.

A new multiresponse optimization approach in combination with a D-Optimal experimental design for the determination of biogenic amines in fish by HPLC-FLD.

PubMed

Herrero, A; Sanllorente, S; Reguera, C; Ortiz, M C; Sarabia, L A

2016-11-16

A new strategy to approach multiresponse optimization in conjunction to a D-optimal design for simultaneously optimizing a large number of experimental factors is proposed. The procedure is applied to the determination of biogenic amines (histamine, putrescine, cadaverine, tyramine, tryptamine, 2-phenylethylamine, spermine and spermidine) in swordfish by HPLC-FLD after extraction with an acid and subsequent derivatization with dansyl chloride. Firstly, the extraction from a solid matrix and the derivatization of the extract are optimized. Ten experimental factors involved in both stages are studied, seven of them at two levels and the remaining at three levels; the use of a D-optimal design leads to optimize the ten experimental variables, significantly reducing by a factor of 67 the experimental effort needed but guaranteeing the quality of the estimates. A model with 19 coefficients, which includes those corresponding to the main effects and two possible interactions, is fitted to the peak area of each amine. Then, the validated models are used to predict the response (peak area) of the 3456 experiments of the complete factorial design. The variability among peak areas ranges from 13.5 for 2-phenylethylamine to 122.5 for spermine, which shows, to a certain extent, the high and different effect of the pretreatment on the responses. Then the percentiles are calculated from the peak areas of each amine. As the experimental conditions are in conflict, the optimal solution for the multiresponse optimization is chosen from among those which have all the responses greater than a certain percentile for all the amines. The developed procedure reaches decision limits down to 2.5 μg L -1 for cadaverine or 497 μg L -1 for histamine in solvent and 0.07 mg kg -1 and 14.81 mg kg -1 in fish (probability of false positive equal to 0.05), respectively. Copyright © 2016 Elsevier B.V. All rights reserved.

Inverse problems in the design, modeling and testing of engineering systems

NASA Technical Reports Server (NTRS)

Alifanov, Oleg M.

1991-01-01

Formulations, classification, areas of application, and approaches to solving different inverse problems are considered for the design of structures, modeling, and experimental data processing. Problems in the practical implementation of theoretical-experimental methods based on solving inverse problems are analyzed in order to identify mathematical models of physical processes, aid in input data preparation for design parameter optimization, help in design parameter optimization itself, and to model experiments, large-scale tests, and real tests of engineering systems.

Application of mixture experimental design in the formulation and optimization of matrix tablets containing carbomer and hydroxy-propylmethylcellulose.

PubMed

Petrovic, Aleksandra; Cvetkovic, Nebojsa; Ibric, Svetlana; Trajkovic, Svetlana; Djuric, Zorica; Popadic, Dragica; Popovic, Radmila

2009-12-01

Using mixture experimental design, the effect of carbomer (Carbopol((R)) 971P NF) and hydroxypropylmethylcellulose (Methocel((R)) K100M or Methocel((R)) K4M) combination on the release profile and on the mechanism of drug liberation from matrix tablet was investigated. The numerical optimization procedure was also applied to establish and obtain formulation with desired drug release. The amount of TP released, release rate and mechanism varied with carbomer ratio in total matrix and HPMC viscosity. Increasing carbomer fractions led to a decrease in drug release. Anomalous diffusion was found in all matrices containing carbomer, while Case - II transport was predominant for tablet based on HPMC only. The predicted and obtained profiles for optimized formulations showed similarity. Those results indicate that Simplex Lattice Mixture experimental design and numerical optimization procedure can be applied during development to obtain sustained release matrix formulation with desired release profile.

Improving knowledge of garlic paste greening through the design of an experimental strategy.

PubMed

Aguilar, Miguel; Rincón, Francisco

2007-12-12

The furthering of scientific knowledge depends in part upon the reproducibility of experimental results. When experimental conditions are not set with sufficient precision, the resulting background noise often leads to poorly reproduced and even faulty experiments. An example of the catastrophic consequences of this background noise can be found in the design of strategies for the development of solutions aimed at preventing garlic paste greening, where reported results are contradictory. To avoid such consequences, this paper presents a two-step strategy based on the concept of experimental design. In the first step, the critical factors inherent to the problem are identified, using a 2(III)(7-4) Plackett-Burman experimental design, from a list of seven apparent critical factors (ACF); subsequently, the critical factors thus identified are considered as the factors to be optimized (FO), and optimization is performed using a Box and Wilson experimental design to identify the stationary point of the system. Optimal conditions for preventing garlic greening are examined after analysis of the complex process of green-pigment development, which involves both chemical and enzymatic reactions and is strongly influenced by pH, with an overall pH optimum of 4.5. The critical step in the greening process is the synthesis of thiosulfinates (allicin) from cysteine sulfoxides (alliin). Cysteine inhibits the greening process at this critical stage; no greening precursors are formed in the presence of around 1% cysteine. However, the optimal conditions for greening prevention are very sensitive both to the type of garlic and to manufacturing conditions. This suggests that optimal solutions for garlic greening prevention should be sought on a case-by-case basis, using the strategy presented here.

A Tutorial on Adaptive Design Optimization

PubMed Central

Myung, Jay I.; Cavagnaro, Daniel R.; Pitt, Mark A.

2013-01-01

Experimentation is ubiquitous in the field of psychology and fundamental to the advancement of its science, and one of the biggest challenges for researchers is designing experiments that can conclusively discriminate the theoretical hypotheses or models under investigation. The recognition of this challenge has led to the development of sophisticated statistical methods that aid in the design of experiments and that are within the reach of everyday experimental scientists. This tutorial paper introduces the reader to an implementable experimentation methodology, dubbed Adaptive Design Optimization, that can help scientists to conduct “smart” experiments that are maximally informative and highly efficient, which in turn should accelerate scientific discovery in psychology and beyond. PMID:23997275

Experimental Test Rig for Optimal Control of Flexible Space Robotic Arms

DTIC Science & Technology

2016-12-01

was used to refine the test bed design and the experimental workflow. Three concepts incorporated various strategies to design a robust flexible link...used to refine the test bed design and the experimental workflow. Three concepts incorporated various strategies to design a robust flexible link... designed to perform the experimentation . The first and second concepts use traditional elastic springs in varying configurations while a third uses a

Application of iterative robust model-based optimal experimental design for the calibration of biocatalytic models.

PubMed

Van Daele, Timothy; Gernaey, Krist V; Ringborg, Rolf H; Börner, Tim; Heintz, Søren; Van Hauwermeiren, Daan; Grey, Carl; Krühne, Ulrich; Adlercreutz, Patrick; Nopens, Ingmar

2017-09-01

The aim of model calibration is to estimate unique parameter values from available experimental data, here applied to a biocatalytic process. The traditional approach of first gathering data followed by performing a model calibration is inefficient, since the information gathered during experimentation is not actively used to optimize the experimental design. By applying an iterative robust model-based optimal experimental design, the limited amount of data collected is used to design additional informative experiments. The algorithm is used here to calibrate the initial reaction rate of an ω-transaminase catalyzed reaction in a more accurate way. The parameter confidence region estimated from the Fisher Information Matrix is compared with the likelihood confidence region, which is not only more accurate but also a computationally more expensive method. As a result, an important deviation between both approaches is found, confirming that linearization methods should be applied with care for nonlinear models. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 33:1278-1293, 2017. © 2017 American Institute of Chemical Engineers.

Vitamin B12 production from crude glycerol by Propionibacterium freudenreichii ssp. shermanii: optimization of medium composition through statistical experimental designs.

PubMed

Kośmider, Alicja; Białas, Wojciech; Kubiak, Piotr; Drożdżyńska, Agnieszka; Czaczyk, Katarzyna

2012-02-01

A two-step statistical experimental design was employed to optimize the medium for vitamin B(12) production from crude glycerol by Propionibacterium freudenreichii ssp. shermanii. In the first step, using Plackett-Burman design, five of 13 tested medium components (calcium pantothenate, NaH(2)PO(4)·2H(2)O, casein hydrolysate, glycerol and FeSO(4)·7H(2)O) were identified as factors having significant influence on vitamin production. In the second step, a central composite design was used to optimize levels of medium components selected in the first step. Valid statistical models describing the influence of significant factors on vitamin B(12) production were established for each optimization phase. The optimized medium provided a 93% increase in final vitamin concentration compared to the original medium. Copyright © 2011 Elsevier Ltd. All rights reserved.

Chemometric optimization of the robustness of the near infrared spectroscopic method in wheat quality control.

PubMed

Pojić, Milica; Rakić, Dušan; Lazić, Zivorad

2015-01-01

A chemometric approach was applied for the optimization of the robustness of the NIRS method for wheat quality control. Due to the high number of experimental (n=6) and response variables to be studied (n=7) the optimization experiment was divided into two stages: screening stage in order to evaluate which of the considered variables were significant, and optimization stage to optimize the identified factors in the previously selected experimental domain. The significant variables were identified by using fractional factorial experimental design, whilst Box-Wilson rotatable central composite design (CCRD) was run to obtain the optimal values for the significant variables. The measured responses included: moisture, protein and wet gluten content, Zeleny sedimentation value and deformation energy. In order to achieve the minimal variation in responses, the optimal factor settings were found by minimizing the propagation of error (POE). The simultaneous optimization of factors was conducted by desirability function. The highest desirability of 87.63% was accomplished by setting up experimental conditions as follows: 19.9°C for sample temperature, 19.3°C for ambient temperature and 240V for instrument voltage. Copyright © 2014 Elsevier B.V. All rights reserved.

Model-Based Optimal Experimental Design for Complex Physical Systems

DTIC Science & Technology

2015-12-03

for public release. magnitude reduction in estimator error required to make solving the exact optimal design problem tractable. Instead of using a naive...for designing a sequence of experiments uses suboptimal approaches: batch design that has no feedback, or greedy ( myopic ) design that optimally...approved for public release. Equation 1 is difficult to solve directly, but can be expressed in an equivalent form using the principle of dynamic programming

Optimizing an experimental design for an electromagnetic experiment

NASA Astrophysics Data System (ADS)

Roux, Estelle; Garcia, Xavier

2013-04-01

Most of geophysical studies focus on data acquisition and analysis, but another aspect which is gaining importance is the discussion on acquisition of suitable datasets. This can be done through the design of an optimal experiment. Optimizing an experimental design implies a compromise between maximizing the information we get about the target and reducing the cost of the experiment, considering a wide range of constraints (logistical, financial, experimental …). We are currently developing a method to design an optimal controlled-source electromagnetic (CSEM) experiment to detect a potential CO2 reservoir and monitor this reservoir during and after CO2 injection. Our statistical algorithm combines the use of linearized inverse theory (to evaluate the quality of one given design via the objective function) and stochastic optimization methods like genetic algorithm (to examine a wide range of possible surveys). The particularity of our method is that it uses a multi-objective genetic algorithm that searches for designs that fit several objective functions simultaneously. One main advantage of this kind of technique to design an experiment is that it does not require the acquisition of any data and can thus be easily conducted before any geophysical survey. Our new experimental design algorithm has been tested with a realistic one-dimensional resistivity model of the Earth in the region of study (northern Spain CO2 sequestration test site). We show that a small number of well distributed observations have the potential to resolve the target. This simple test also points out the importance of a well chosen objective function. Finally, in the context of CO2 sequestration that motivates this study, we might be interested in maximizing the information we get about the reservoir layer. In that case, we show how the combination of two different objective functions considerably improve its resolution.

Experimental evaluation of HJB optimal controllers for the attitude dynamics of a multirotor aerial vehicle.

PubMed

Prado, Igor Afonso Acampora; Pereira, Mateus de Freitas Virgílio; de Castro, Davi Ferreira; Dos Santos, Davi Antônio; Balthazar, Jose Manoel

2018-06-01

The present paper is concerned with the design and experimental evaluation of optimal control laws for the nonlinear attitude dynamics of a multirotor aerial vehicle. Three design methods based on Hamilton-Jacobi-Bellman equation are taken into account. The first one is a linear control with guarantee of stability for nonlinear systems. The second and third are a nonlinear suboptimal control techniques. These techniques are based on an optimal control design approach that takes into account the nonlinearities present in the vehicle dynamics. The stability Proof of the closed-loop system is presented. The performance of the control system designed is evaluated via simulations and also via an experimental scheme using the Quanser 3-DOF Hover. The experiments show the effectiveness of the linear control method over the nonlinear strategy. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Fatigue design of a cellular phone folder using regression model-based multi-objective optimization

NASA Astrophysics Data System (ADS)

Kim, Young Gyun; Lee, Jongsoo

2016-08-01

In a folding cellular phone, the folding device is repeatedly opened and closed by the user, which eventually results in fatigue damage, particularly to the front of the folder. Hence, it is important to improve the safety and endurance of the folder while also reducing its weight. This article presents an optimal design for the folder front that maximizes its fatigue endurance while minimizing its thickness. Design data for analysis and optimization were obtained experimentally using a test jig. Multi-objective optimization was carried out using a nonlinear regression model. Three regression methods were employed: back-propagation neural networks, logistic regression and support vector machines. The AdaBoost ensemble technique was also used to improve the approximation. Two-objective Pareto-optimal solutions were identified using the non-dominated sorting genetic algorithm (NSGA-II). Finally, a numerically optimized solution was validated against experimental product data, in terms of both fatigue endurance and thickness index.

Structural Model Tuning Capability in an Object-Oriented Multidisciplinary Design, Analysis, and Optimization Tool

NASA Technical Reports Server (NTRS)

Lung, Shun-fat; Pak, Chan-gi

2008-01-01

Updating the finite element model using measured data is a challenging problem in the area of structural dynamics. The model updating process requires not only satisfactory correlations between analytical and experimental results, but also the retention of dynamic properties of structures. Accurate rigid body dynamics are important for flight control system design and aeroelastic trim analysis. Minimizing the difference between analytical and experimental results is a type of optimization problem. In this research, a multidisciplinary design, analysis, and optimization (MDAO) tool is introduced to optimize the objective function and constraints such that the mass properties, the natural frequencies, and the mode shapes are matched to the target data as well as the mass matrix being orthogonalized.

Structural Model Tuning Capability in an Object-Oriented Multidisciplinary Design, Analysis, and Optimization Tool

NASA Technical Reports Server (NTRS)

Lung, Shun-fat; Pak, Chan-gi

2008-01-01

Updating the finite element model using measured data is a challenging problem in the area of structural dynamics. The model updating process requires not only satisfactory correlations between analytical and experimental results, but also the retention of dynamic properties of structures. Accurate rigid body dynamics are important for flight control system design and aeroelastic trim analysis. Minimizing the difference between analytical and experimental results is a type of optimization problem. In this research, a multidisciplinary design, analysis, and optimization [MDAO] tool is introduced to optimize the objective function and constraints such that the mass properties, the natural frequencies, and the mode shapes are matched to the target data as well as the mass matrix being orthogonalized.

[Optimization of vacuum belt drying process of Gardeniae Fructus in Reduning injection by Box-Behnken design-response surface methodology].

PubMed

Huang, Dao-sheng; Shi, Wei; Han, Lei; Sun, Ke; Chen, Guang-bo; Wu Jian-xiong; Xu, Gui-hong; Bi, Yu-an; Wang, Zhen-zhong; Xiao, Wei

2015-06-01

To optimize the belt drying process conditions optimization of Gardeniae Fructus extract from Reduning injection by Box-Behnken design-response surface methodology, on the basis of single factor experiment, a three-factor and three-level Box-Behnken experimental design was employed to optimize the drying technology of Gardeniae Fructus extract from Reduning injection. With drying temperature, drying time, feeding speed as independent variables and the content of geniposide as dependent variable, the experimental data were fitted to a second order polynomial equation, establishing the mathematical relationship between the content of geniposide and respective variables. With the experimental data analyzed by Design-Expert 8. 0. 6, the optimal drying parameter was as follows: the drying temperature was 98.5 degrees C , the drying time was 89 min, the feeding speed was 99.8 r x min(-1). Three verification experiments were taked under this technology and the measured average content of geniposide was 564. 108 mg x g(-1), which was close to the model prediction: 563. 307 mg x g(-1). According to the verification test, the Gardeniae Fructus belt drying process is steady and feasible. So single factor experiments combined with response surface method (RSM) could be used to optimize the drying technology of Reduning injection Gardenia extract.

Experimental Design for Parameter Estimation of Gene Regulatory Networks

PubMed Central

Timmer, Jens

2012-01-01

Systems biology aims for building quantitative models to address unresolved issues in molecular biology. In order to describe the behavior of biological cells adequately, gene regulatory networks (GRNs) are intensively investigated. As the validity of models built for GRNs depends crucially on the kinetic rates, various methods have been developed to estimate these parameters from experimental data. For this purpose, it is favorable to choose the experimental conditions yielding maximal information. However, existing experimental design principles often rely on unfulfilled mathematical assumptions or become computationally demanding with growing model complexity. To solve this problem, we combined advanced methods for parameter and uncertainty estimation with experimental design considerations. As a showcase, we optimized three simulated GRNs in one of the challenges from the Dialogue for Reverse Engineering Assessment and Methods (DREAM). This article presents our approach, which was awarded the best performing procedure at the DREAM6 Estimation of Model Parameters challenge. For fast and reliable parameter estimation, local deterministic optimization of the likelihood was applied. We analyzed identifiability and precision of the estimates by calculating the profile likelihood. Furthermore, the profiles provided a way to uncover a selection of most informative experiments, from which the optimal one was chosen using additional criteria at every step of the design process. In conclusion, we provide a strategy for optimal experimental design and show its successful application on three highly nonlinear dynamic models. Although presented in the context of the GRNs to be inferred for the DREAM6 challenge, the approach is generic and applicable to most types of quantitative models in systems biology and other disciplines. PMID:22815723

Efficient experimental design for uncertainty reduction in gene regulatory networks.

PubMed

Dehghannasiri, Roozbeh; Yoon, Byung-Jun; Dougherty, Edward R

2015-01-01

An accurate understanding of interactions among genes plays a major role in developing therapeutic intervention methods. Gene regulatory networks often contain a significant amount of uncertainty. The process of prioritizing biological experiments to reduce the uncertainty of gene regulatory networks is called experimental design. Under such a strategy, the experiments with high priority are suggested to be conducted first. The authors have already proposed an optimal experimental design method based upon the objective for modeling gene regulatory networks, such as deriving therapeutic interventions. The experimental design method utilizes the concept of mean objective cost of uncertainty (MOCU). MOCU quantifies the expected increase of cost resulting from uncertainty. The optimal experiment to be conducted first is the one which leads to the minimum expected remaining MOCU subsequent to the experiment. In the process, one must find the optimal intervention for every gene regulatory network compatible with the prior knowledge, which can be prohibitively expensive when the size of the network is large. In this paper, we propose a computationally efficient experimental design method. This method incorporates a network reduction scheme by introducing a novel cost function that takes into account the disruption in the ranking of potential experiments. We then estimate the approximate expected remaining MOCU at a lower computational cost using the reduced networks. Simulation results based on synthetic and real gene regulatory networks show that the proposed approximate method has close performance to that of the optimal method but at lower computational cost. The proposed approximate method also outperforms the random selection policy significantly. A MATLAB software implementing the proposed experimental design method is available at http://gsp.tamu.edu/Publications/supplementary/roozbeh15a/.

Efficient experimental design for uncertainty reduction in gene regulatory networks

PubMed Central

2015-01-01

Background An accurate understanding of interactions among genes plays a major role in developing therapeutic intervention methods. Gene regulatory networks often contain a significant amount of uncertainty. The process of prioritizing biological experiments to reduce the uncertainty of gene regulatory networks is called experimental design. Under such a strategy, the experiments with high priority are suggested to be conducted first. Results The authors have already proposed an optimal experimental design method based upon the objective for modeling gene regulatory networks, such as deriving therapeutic interventions. The experimental design method utilizes the concept of mean objective cost of uncertainty (MOCU). MOCU quantifies the expected increase of cost resulting from uncertainty. The optimal experiment to be conducted first is the one which leads to the minimum expected remaining MOCU subsequent to the experiment. In the process, one must find the optimal intervention for every gene regulatory network compatible with the prior knowledge, which can be prohibitively expensive when the size of the network is large. In this paper, we propose a computationally efficient experimental design method. This method incorporates a network reduction scheme by introducing a novel cost function that takes into account the disruption in the ranking of potential experiments. We then estimate the approximate expected remaining MOCU at a lower computational cost using the reduced networks. Conclusions Simulation results based on synthetic and real gene regulatory networks show that the proposed approximate method has close performance to that of the optimal method but at lower computational cost. The proposed approximate method also outperforms the random selection policy significantly. A MATLAB software implementing the proposed experimental design method is available at http://gsp.tamu.edu/Publications/supplementary/roozbeh15a/. PMID:26423515

Simulation Modeling to Compare High-Throughput, Low-Iteration Optimization Strategies for Metabolic Engineering

PubMed Central

Heinsch, Stephen C.; Das, Siba R.; Smanski, Michael J.

2018-01-01

Increasing the final titer of a multi-gene metabolic pathway can be viewed as a multivariate optimization problem. While numerous multivariate optimization algorithms exist, few are specifically designed to accommodate the constraints posed by genetic engineering workflows. We present a strategy for optimizing expression levels across an arbitrary number of genes that requires few design-build-test iterations. We compare the performance of several optimization algorithms on a series of simulated expression landscapes. We show that optimal experimental design parameters depend on the degree of landscape ruggedness. This work provides a theoretical framework for designing and executing numerical optimization on multi-gene systems. PMID:29535690

Optimal active vibration absorber: Design and experimental results

NASA Technical Reports Server (NTRS)

Lee-Glauser, Gina; Juang, Jer-Nan; Sulla, Jeffrey L.

1992-01-01

An optimal active vibration absorber can provide guaranteed closed-loop stability and control for large flexible space structures with collocated sensors/actuators. The active vibration absorber is a second-order dynamic system which is designed to suppress any unwanted structural vibration. This can be designed with minimum knowledge of the controlled system. Two methods for optimizing the active vibration absorber parameters are illustrated: minimum resonant amplitude and frequency matched active controllers. The Controls-Structures Interaction Phase-1 Evolutionary Model at NASA LaRC is used to demonstrate the effectiveness of the active vibration absorber for vibration suppression. Performance is compared numerically and experimentally using acceleration feedback.

Optimal rates for phylogenetic inference and experimental design in the era of genome-scale datasets.

PubMed

Dornburg, Alex; Su, Zhuo; Townsend, Jeffrey P

2018-06-25

With the rise of genome- scale datasets there has been a call for increased data scrutiny and careful selection of loci appropriate for attempting the resolution of a phylogenetic problem. Such loci are desired to maximize phylogenetic information content while minimizing the risk of homoplasy. Theory posits the existence of characters that evolve under such an optimum rate, and efforts to determine optimal rates of inference have been a cornerstone of phylogenetic experimental design for over two decades. However, both theoretical and empirical investigations of optimal rates have varied dramatically in their conclusions: spanning no relationship to a tight relationship between the rate of change and phylogenetic utility. Here we synthesize these apparently contradictory views, demonstrating both empirical and theoretical conditions under which each is correct. We find that optimal rates of characters-not genes-are generally robust to most experimental design decisions. Moreover, consideration of site rate heterogeneity within a given locus is critical to accurate predictions of utility. Factors such as taxon sampling or the targeted number of characters providing support for a topology are additionally critical to the predictions of phylogenetic utility based on the rate of character change. Further, optimality of rates and predictions of phylogenetic utility are not equivalent, demonstrating the need for further development of comprehensive theory of phylogenetic experimental design.

Issues and recent advances in optimal experimental design for site investigation (Invited)

NASA Astrophysics Data System (ADS)

Nowak, W.

2013-12-01

This presentation provides an overview over issues and recent advances in model-based experimental design for site exploration. The addressed issues and advances are (1) how to provide an adequate envelope to prior uncertainty, (2) how to define the information needs in a task-oriented manner, (3) how to measure the expected impact of a data set that it not yet available but only planned to be collected, and (4) how to perform best the optimization of the data collection plan. Among other shortcomings of the state-of-the-art, it is identified that there is a lack of demonstrator studies where exploration schemes based on expert judgment are compared to exploration schemes obtained by optimal experimental design. Such studies will be necessary do address the often voiced concern that experimental design is an academic exercise with little improvement potential over the well- trained gut feeling of field experts. When addressing this concern, a specific focus has to be given to uncertainty in model structure, parameterizations and parameter values, and to related surprises that data often bring about in field studies, but never in synthetic-data based studies. The background of this concern is that, initially, conceptual uncertainty may be so large that surprises are the rule rather than the exception. In such situations, field experts have a large body of experience in handling the surprises, and expert judgment may be good enough compared to meticulous optimization based on a model that is about to be falsified by the incoming data. In order to meet surprises accordingly and adapt to them, there needs to be a sufficient representation of conceptual uncertainty within the models used. Also, it is useless to optimize an entire design under this initial range of uncertainty. Thus, the goal setting of the optimization should include the objective to reduce conceptual uncertainty. A possible way out is to upgrade experimental design theory towards real-time interaction with the ongoing site investigation, such that surprises in the data are immediately accounted for to restrict the conceptual uncertainty and update the optimization of the plan.

Experimental design for estimating unknown groundwater pumping using genetic algorithm and reduced order model

NASA Astrophysics Data System (ADS)

Ushijima, Timothy T.; Yeh, William W.-G.

2013-10-01

An optimal experimental design algorithm is developed to select locations for a network of observation wells that provide maximum information about unknown groundwater pumping in a confined, anisotropic aquifer. The design uses a maximal information criterion that chooses, among competing designs, the design that maximizes the sum of squared sensitivities while conforming to specified design constraints. The formulated optimization problem is non-convex and contains integer variables necessitating a combinatorial search. Given a realistic large-scale model, the size of the combinatorial search required can make the problem difficult, if not impossible, to solve using traditional mathematical programming techniques. Genetic algorithms (GAs) can be used to perform the global search; however, because a GA requires a large number of calls to a groundwater model, the formulated optimization problem still may be infeasible to solve. As a result, proper orthogonal decomposition (POD) is applied to the groundwater model to reduce its dimensionality. Then, the information matrix in the full model space can be searched without solving the full model. Results from a small-scale test case show identical optimal solutions among the GA, integer programming, and exhaustive search methods. This demonstrates the GA's ability to determine the optimal solution. In addition, the results show that a GA with POD model reduction is several orders of magnitude faster in finding the optimal solution than a GA using the full model. The proposed experimental design algorithm is applied to a realistic, two-dimensional, large-scale groundwater problem. The GA converged to a solution for this large-scale problem.

Optimization of the synthesis process of an iron oxide nanocatalyst supported on activated carbon for the inactivation of Ascaris eggs in water using the heterogeneous Fenton-like reaction.

PubMed

Morales-Pérez, Ariadna A; Maravilla, Pablo; Solís-López, Myriam; Schouwenaars, Rafael; Durán-Moreno, Alfonso; Ramírez-Zamora, Rosa-María

2016-01-01

An experimental design methodology was used to optimize the synthesis of an iron-supported nanocatalyst as well as the inactivation process of Ascaris eggs (Ae) using this material. A factor screening design was used for identifying the significant experimental factors for nanocatalyst support (supported %Fe, (w/w), temperature and time of calcination) and for the inactivation process called the heterogeneous Fenton-like reaction (H2O2 dose, mass ratio Fe/H2O2, pH and reaction time). The optimization of the significant factors was carried out using a face-centered central composite design. The optimal operating conditions for both processes were estimated with a statistical model and implemented experimentally with five replicates. The predicted value of the Ae inactivation rate was close to the laboratory results. At the optimal operating conditions of the nanocatalyst production and Ae inactivation process, the Ascaris ova showed genomic damage to the point that no cell reparation was possible showing that this advanced oxidation process was highly efficient for inactivating this pathogen.

Optimal Experiment Design for Thermal Characterization of Functionally Graded Materials

NASA Technical Reports Server (NTRS)

Cole, Kevin D.

2003-01-01

The purpose of the project was to investigate methods to accurately verify that designed , materials meet thermal specifications. The project involved heat transfer calculations and optimization studies, and no laboratory experiments were performed. One part of the research involved study of materials in which conduction heat transfer predominates. Results include techniques to choose among several experimental designs, and protocols for determining the optimum experimental conditions for determination of thermal properties. Metal foam materials were also studied in which both conduction and radiation heat transfer are present. Results of this work include procedures to optimize the design of experiments to accurately measure both conductive and radiative thermal properties. Detailed results in the form of three journal papers have been appended to this report.

CamOptimus: a tool for exploiting complex adaptive evolution to optimize experiments and processes in biotechnology.

PubMed

Cankorur-Cetinkaya, Ayca; Dias, Joao M L; Kludas, Jana; Slater, Nigel K H; Rousu, Juho; Oliver, Stephen G; Dikicioglu, Duygu

2017-06-01

Multiple interacting factors affect the performance of engineered biological systems in synthetic biology projects. The complexity of these biological systems means that experimental design should often be treated as a multiparametric optimization problem. However, the available methodologies are either impractical, due to a combinatorial explosion in the number of experiments to be performed, or are inaccessible to most experimentalists due to the lack of publicly available, user-friendly software. Although evolutionary algorithms may be employed as alternative approaches to optimize experimental design, the lack of simple-to-use software again restricts their use to specialist practitioners. In addition, the lack of subsidiary approaches to further investigate critical factors and their interactions prevents the full analysis and exploitation of the biotechnological system. We have addressed these problems and, here, provide a simple-to-use and freely available graphical user interface to empower a broad range of experimental biologists to employ complex evolutionary algorithms to optimize their experimental designs. Our approach exploits a Genetic Algorithm to discover the subspace containing the optimal combination of parameters, and Symbolic Regression to construct a model to evaluate the sensitivity of the experiment to each parameter under investigation. We demonstrate the utility of this method using an example in which the culture conditions for the microbial production of a bioactive human protein are optimized. CamOptimus is available through: (https://doi.org/10.17863/CAM.10257).

Optimizing Force Deployment and Force Structure for the Rapid Deployment Force

DTIC Science & Technology

1984-03-01

Analysis . . . . .. .. ... ... 97 Experimental Design . . . . . .. .. .. ... 99 IX. Use of a Flexible Response Surface ........ 10.2 Selection of a...setS . ere designe . arun, programming methodology , where the require: s.stem re..r is input and the model optimizes the num=er. :::pe, cargo. an...to obtain new computer outputs" (Ref 38:23). The methodology can be used with any decision model, linear or nonlinear. Experimental Desion Since the

Photonic Jets for Strained-Layer Superlattice Infrared Photodetector Enhancement

DTIC Science & Technology

2014-06-25

top of a 40 µm photodetector fixed into position using a silicone rubber . As illustrated in Fig. 2, the spectral response was characterized before and...midwave-infrared spectral band (3-5 ?m). We optimized the design of these structures and experimentally demonstrated the increased sensitivity compared to...midwave-infrared spectral band (3-5 ?m). We optimized the design of these structures and experimentally demonstrated the increased sensitivity

Application of Taguchi L32 orthogonal array design to optimize copper biosorption by using Spaghnum moss.

PubMed

Ozdemir, Utkan; Ozbay, Bilge; Ozbay, Ismail; Veli, Sevil

2014-09-01

In this work, Taguchi L32 experimental design was applied to optimize biosorption of Cu(2+) ions by an easily available biosorbent, Spaghnum moss. With this aim, batch biosorption tests were performed to achieve targeted experimental design with five factors (concentration, pH, biosorbent dosage, temperature and agitation time) at two different levels. Optimal experimental conditions were determined by calculated signal-to-noise ratios. "Higher is better" approach was followed to calculate signal-to-noise ratios as it was aimed to obtain high metal removal efficiencies. The impact ratios of factors were determined by the model. Within the study, Cu(2+) biosorption efficiencies were also predicted by using Taguchi method. Results of the model showed that experimental and predicted values were close to each other demonstrating the success of Taguchi approach. Furthermore, thermodynamic, isotherm and kinetic studies were performed to explain the biosorption mechanism. Calculated thermodynamic parameters were in good accordance with the results of Taguchi model. Copyright © 2014 Elsevier Inc. All rights reserved.

Optimization of formulation variables of benzocaine liposomes using experimental design.

PubMed

Mura, Paola; Capasso, Gaetano; Maestrelli, Francesca; Furlanetto, Sandra

2008-01-01

This study aimed to optimize, by means of an experimental design multivariate strategy, a liposomal formulation for topical delivery of the local anaesthetic agent benzocaine. The formulation variables for the vesicle lipid phase uses potassium glycyrrhizinate (KG) as an alternative to cholesterol and the addition of a cationic (stearylamine) or anionic (dicethylphosphate) surfactant (qualitative factors); the percents of ethanol and the total volume of the hydration phase (quantitative factors) were the variables for the hydrophilic phase. The combined influence of these factors on the considered responses (encapsulation efficiency (EE%) and percent drug permeated at 180 min (P%)) was evaluated by means of a D-optimal design strategy. Graphic analysis of the effects indicated that maximization of the selected responses requested opposite levels of the considered factors: For example, KG and stearylamine were better for increasing EE%, and cholesterol and dicethylphosphate for increasing P%. In the second step, the Doehlert design, applied for the response-surface study of the quantitative factors, pointed out a negative interaction between percent ethanol and volume of the hydration phase and allowed prediction of the best formulation for maximizing drug permeation rate. Experimental P% data of the optimized formulation were inside the confidence interval (P < 0.05) calculated around the predicted value of the response. This proved the suitability of the proposed approach for optimizing the composition of liposomal formulations and predicting the effects of formulation variables on the considered experimental response. Moreover, the optimized formulation enabled a significant improvement (P < 0.05) of the drug anaesthetic effect with respect to the starting reference liposomal formulation, thus demonstrating its actually better therapeutic effectiveness.

D-OPTIMAL EXPERIMENTAL DESIGNS TO TEST FOR DEPARTURE FROM ADDITIVITY IN A FIXED-RATIO MIXTURE RAY.

EPA Science Inventory

Humans are exposed to mixtures of environmental compounds. A regulatory assumption is that the mixtures of chemicals act in an additive manner. However, this assumption requires experimental validation. Traditional experimental designs (full factorial) require a large number of e...

Optimization of microwave-assisted extraction of analgesic and anti-inflammatory drugs from human plasma and urine using response surface experimental designs.

PubMed

Fernández, Purificación; Fernández, Ana M; Bermejo, Ana M; Lorenzo, Rosa A; Carro, Antonia M

2013-04-01

The performance of microwave-assisted extraction and HPLC with photodiode array detection method for determination of six analgesic and anti-inflammatory drugs from plasma and urine, is described, optimized, and validated. Several parameters affecting the extraction technique were optimized using experimental designs. A four-factor (temperature, phosphate buffer pH 4.0 volume, extraction solvent volume, and time) hybrid experimental design was used for extraction optimization in plasma, and three-factor (temperature, extraction solvent volume, and time) Doehlert design was chosen to extraction optimization in urine. The use of desirability functions revealed the optimal extraction conditions as follows: 67°C, 4 mL phosphate buffer pH 4.0, 12 mL of ethyl acetate and 9 min, for plasma and the same volume of buffer and ethyl acetate, 115°C and 4 min for urine. Limits of detection ranged from 4 to 45 ng/mL in plasma and from 8 to 85 ng/mL in urine. The reproducibility evaluated at two concentration levels was less than 6.5% for both specimens. The recoveries were from 89 to 99% for plasma and from 83 to 99% for urine. The proposed method was successfully applied in plasma and urine samples obtained from analgesic users. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Experimental designs for a Benign Paroxysmal Positional Vertigo model

PubMed Central

2013-01-01

Background The pathology of the Benign Paroxysmal Positional Vertigo (BPPV) is detected by a clinician through maneuvers consisting of a series of consecutive head turns that trigger the symptoms of vertigo in patient. A statistical model based on a new maneuver has been developed in order to calculate the volume of endolymph displaced after the maneuver. Methods A simplification of the Navier‐Stokes problem from the fluids theory has been used to construct the model. In addition, the same cubic splines that are commonly used in kinematic control of robots were used to obtain an appropriate description of the different maneuvers. Then experimental designs were computed to obtain an optimal estimate of the model. Results D‐optimal and c‐optimal designs of experiments have been calculated. These experiments consist of a series of specific head turns of duration Δt and angle α that should be performed by the clinician on the patient. The experimental designs obtained indicate the duration and angle of the maneuver to be performed as well as the corresponding proportion of replicates. Thus, in the D‐optimal design for 100 experiments, the maneuver consisting of a positive 30° pitch from the upright position, followed by a positive 30° roll, both with a duration of one and a half seconds is repeated 47 times. Then the maneuver with 60° /6° pitch/roll during half a second is repeated 16 times and the maneuver 90° /90° pitch/roll during half a second is repeated 37 times. Other designs with significant differences are computed and compared. Conclusions A biomechanical model was derived to provide a quantitative basis for the detection of BPPV. The robustness study for the D‐optimal design, with respect to the choice of the nominal values of the parameters, shows high efficiencies for small variations and provides a guide to the researcher. Furthermore, c‐optimal designs give valuable assistance to check how efficient the D‐optimal design is for the estimation of each of the parameters. The experimental designs provided in this paper allow the physician to validate the model. The authors of the paper have held consultations with an ENT consultant in order to align the outline more closely to practical scenarios. PMID:23509996

Polymeric behavior evaluation of PVP K30-poloxamer binary carrier for solid dispersed nisoldipine by experimental design.

PubMed

Kyaw Oo, May; Mandal, Uttam K; Chatterjee, Bappaditya

2017-02-01

High melting point polymeric carrier without plasticizer is unacceptable for solid dispersion (SD) by melting method. Combined polymer-plasticizer carrier significantly affects drug solubility and tableting property of SD. To evaluate and optimize the combined effect of a binary carrier consisting PVP K30 and poloxamer 188, on nisoldipine solubility and tensile strength of amorphous SD compact (SD compact ) by experimental design. SD of nisoldpine (SD nisol ) was prepared by melt mixing with different PVP K30 and poloxamer amount. A 3 2 factorial design was employed using nisoldipine solubility and tensile strength of SD compact as response variables. Statistical optimization by design expert software, and SD nisol characterization using ATR FTIR, DSC and microscopy were done. PVP K30:poloxamer, at a ratio of 3.73:6.63, was selected as the optimized combination of binary polymeric carrier resulting nisoldipine solubility of 115 μg/mL and tensile strength of 1.19 N/m 2 . PVP K30 had significant positive effect on both responses. Increase in poloxamer concentration after a certain level decreased nisoldipine solubility and tensile strength of SD compact . An optimized PVP K30-poloxamer binary composition for SD carrier was developed. Tensile strength of SD compact can be considered as a response for experimental design to optimize SD.

Simultaneous versus sequential optimal experiment design for the identification of multi-parameter microbial growth kinetics as a function of temperature.

PubMed

Van Derlinden, E; Bernaerts, K; Van Impe, J F

2010-05-21

Optimal experiment design for parameter estimation (OED/PE) has become a popular tool for efficient and accurate estimation of kinetic model parameters. When the kinetic model under study encloses multiple parameters, different optimization strategies can be constructed. The most straightforward approach is to estimate all parameters simultaneously from one optimal experiment (single OED/PE strategy). However, due to the complexity of the optimization problem or the stringent limitations on the system's dynamics, the experimental information can be limited and parameter estimation convergence problems can arise. As an alternative, we propose to reduce the optimization problem to a series of two-parameter estimation problems, i.e., an optimal experiment is designed for a combination of two parameters while presuming the other parameters known. Two different approaches can be followed: (i) all two-parameter optimal experiments are designed based on identical initial parameter estimates and parameters are estimated simultaneously from all resulting experimental data (global OED/PE strategy), and (ii) optimal experiments are calculated and implemented sequentially whereby the parameter values are updated intermediately (sequential OED/PE strategy). This work exploits OED/PE for the identification of the Cardinal Temperature Model with Inflection (CTMI) (Rosso et al., 1993). This kinetic model describes the effect of temperature on the microbial growth rate and encloses four parameters. The three OED/PE strategies are considered and the impact of the OED/PE design strategy on the accuracy of the CTMI parameter estimation is evaluated. Based on a simulation study, it is observed that the parameter values derived from the sequential approach deviate more from the true parameters than the single and global strategy estimates. The single and global OED/PE strategies are further compared based on experimental data obtained from design implementation in a bioreactor. Comparable estimates are obtained, but global OED/PE estimates are, in general, more accurate and reliable. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Structural Optimization of a Force Balance Using a Computational Experiment Design

NASA Technical Reports Server (NTRS)

Parker, P. A.; DeLoach, R.

2002-01-01

This paper proposes a new approach to force balance structural optimization featuring a computational experiment design. Currently, this multi-dimensional design process requires the designer to perform a simplification by executing parameter studies on a small subset of design variables. This one-factor-at-a-time approach varies a single variable while holding all others at a constant level. Consequently, subtle interactions among the design variables, which can be exploited to achieve the design objectives, are undetected. The proposed method combines Modern Design of Experiments techniques to direct the exploration of the multi-dimensional design space, and a finite element analysis code to generate the experimental data. To efficiently search for an optimum combination of design variables and minimize the computational resources, a sequential design strategy was employed. Experimental results from the optimization of a non-traditional force balance measurement section are presented. An approach to overcome the unique problems associated with the simultaneous optimization of multiple response criteria is described. A quantitative single-point design procedure that reflects the designer's subjective impression of the relative importance of various design objectives, and a graphical multi-response optimization procedure that provides further insights into available tradeoffs among competing design objectives are illustrated. The proposed method enhances the intuition and experience of the designer by providing new perspectives on the relationships between the design variables and the competing design objectives providing a systematic foundation for advancements in structural design.

Ultrafiltration membrane reactors for enzymatic resolution of amino acids: design model and optimization.

PubMed

Bódalo, A; Gómez, J L.; Gómez, E; Bastida, J; Máximo, M F.; Montiel, M C.

2001-03-08

In this paper the possibility of continuous resolution of DL-phenylalanine, catalyzed by L-aminoacylase in a ultrafiltration membrane reactor (UFMR) is presented. A simple design model, based on previous kinetic studies, has been demonstrated to be capable of describing the behavior of the experimental system. The model has been used to determine the optimal experimental conditions to carry out the asymmetrical hydrolysis of N-acetyl-DL-phenylalanine.

Optimization of Xylanase Production from Penicillium sp.WX-Z1 by a Two-Step Statistical Strategy: Plackett-Burman and Box-Behnken Experimental Design

PubMed Central

Cui, Fengjie; Zhao, Liming

2012-01-01

The objective of the study was to optimize the nutrition sources in a culture medium for the production of xylanase from Penicillium sp.WX-Z1 using Plackett-Burman design and Box-Behnken design. The Plackett-Burman multifactorial design was first employed to screen the important nutrient sources in the medium for xylanase production by Penicillium sp.WX-Z1 and subsequent use of the response surface methodology (RSM) was further optimized for xylanase production by Box-Behnken design. The important nutrient sources in the culture medium, identified by the initial screening method of Placket-Burman, were wheat bran, yeast extract, NaNO3, MgSO4, and CaCl2. The optimal amounts (in g/L) for maximum production of xylanase were: wheat bran, 32.8; yeast extract, 1.02; NaNO3, 12.71; MgSO4, 0.96; and CaCl2, 1.04. Using this statistical experimental design, the xylanase production under optimal condition reached 46.50 U/mL and an increase in xylanase activity of 1.34-fold was obtained compared with the original medium for fermentation carried out in a 30-L bioreactor. PMID:22949884

Optimization of Xylanase production from Penicillium sp.WX-Z1 by a two-step statistical strategy: Plackett-Burman and Box-Behnken experimental design.

PubMed

Cui, Fengjie; Zhao, Liming

2012-01-01

The objective of the study was to optimize the nutrition sources in a culture medium for the production of xylanase from Penicillium sp.WX-Z1 using Plackett-Burman design and Box-Behnken design. The Plackett-Burman multifactorial design was first employed to screen the important nutrient sources in the medium for xylanase production by Penicillium sp.WX-Z1 and subsequent use of the response surface methodology (RSM) was further optimized for xylanase production by Box-Behnken design. The important nutrient sources in the culture medium, identified by the initial screening method of Placket-Burman, were wheat bran, yeast extract, NaNO(3), MgSO(4), and CaCl(2). The optimal amounts (in g/L) for maximum production of xylanase were: wheat bran, 32.8; yeast extract, 1.02; NaNO(3), 12.71; MgSO(4), 0.96; and CaCl(2), 1.04. Using this statistical experimental design, the xylanase production under optimal condition reached 46.50 U/mL and an increase in xylanase activity of 1.34-fold was obtained compared with the original medium for fermentation carried out in a 30-L bioreactor.

Space-filling designs for computer experiments: A review

DOE PAGES

Joseph, V. Roshan

2016-01-29

Improving the quality of a product/process using a computer simulator is a much less expensive option than the real physical testing. However, simulation using computationally intensive computer models can be time consuming and therefore, directly doing the optimization on the computer simulator can be infeasible. Experimental design and statistical modeling techniques can be used for overcoming this problem. This article reviews experimental designs known as space-filling designs that are suitable for computer simulations. In the review, a special emphasis is given for a recently developed space-filling design called maximum projection design. Furthermore, its advantages are illustrated using a simulation conductedmore » for optimizing a milling process.« less

Space-filling designs for computer experiments: A review

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

Joseph, V. Roshan

Improving the quality of a product/process using a computer simulator is a much less expensive option than the real physical testing. However, simulation using computationally intensive computer models can be time consuming and therefore, directly doing the optimization on the computer simulator can be infeasible. Experimental design and statistical modeling techniques can be used for overcoming this problem. This article reviews experimental designs known as space-filling designs that are suitable for computer simulations. In the review, a special emphasis is given for a recently developed space-filling design called maximum projection design. Furthermore, its advantages are illustrated using a simulation conductedmore » for optimizing a milling process.« less

Bioremediation of chlorpyrifos contaminated soil by two phase bioslurry reactor: Processes evaluation and optimization by Taguchi's design of experimental (DOE) methodology.

PubMed

Pant, Apourv; Rai, J P N

2018-04-15

Two phase bioreactor was constructed, designed and developed to evaluate the chlorpyrifos remediation. Six biotic and abiotic factors (substrate-loading rate, slurry phase pH, slurry phase dissolved oxygen (DO), soil water ratio, temperature and soil micro flora load) were evaluated by design of experimental (DOE) methodology employing Taguchi's orthogonal array (OA). The selected six factors were considered at two levels L-8 array (2^7, 15 experiments) in the experimental design. The optimum operating conditions obtained from the methodology showed enhanced chlorpyrifos degradation from 283.86µg/g to 955.364µg/g by overall 70.34% of enhancement. In the present study, with the help of few well defined experimental parameters a mathematical model was constructed to understand the complex bioremediation process and optimize the approximate parameters upto great accuracy. Copyright © 2017 Elsevier Inc. All rights reserved.

D-OPTIMAL EXPERIMENTAL DESIGNS TO TEST FOR DEPARTURE FROM ADDITIVITY IN A FIXED-RATIO MIXTURE RAY.

EPA Science Inventory

Traditional factorial designs for evaluating interactions among chemicals in a mixture are prohibitive when the number of chemicals is large. However, recent advances in statistically-based experimental design have made it easier to evaluate interactions involving many chemicals...

Application of a statistical design to the optimization of parameters and culture medium for alpha-amylase production by Aspergillus oryzae CBS 819.72 grown on gruel (wheat grinding by-product).

PubMed

Kammoun, Radhouane; Naili, Belgacem; Bejar, Samir

2008-09-01

The production optimization of alpha-amylase (E.C.3.2.1.1) from Aspergillus oryzae CBS 819.72 fungus, using a by-product of wheat grinding (gruel) as sole carbon source, was performed with statistical methodology based on three experimental designs. The optimisation of temperature, agitation and inoculum size was attempted using a Box-Behnken design under the response surface methodology. The screening of nineteen nutrients for their influence on alpha-amylase production was achieved using a Plackett-Burman design. KH(2)PO(4), urea, glycerol, (NH(4))(2)SO(4), CoCl(2), casein hydrolysate, soybean meal hydrolysate, MgSO(4) were selected based on their positive influence on enzyme formation. The optimized nutrients concentration was obtained using a Taguchi experimental design and the analysis of the data predicts a theoretical increase in the alpha-amylase expression of 73.2% (from 40.1 to 151.1 U/ml). These conditions were validated experimentally and revealed an enhanced alpha-amylase yield of 72.7%.

Optimisation of the synthesis of vancomycin-selective molecularly imprinted polymer nanoparticles using automatic photoreactor

PubMed Central

2014-01-01

A novel optimized protocol for solid-state synthesis of molecularly imprinted polymer nanoparticles (nanoMIPs) with specificity for antibiotic vancomycin is described. The experimental objective was optimization of the synthesis parameters (factors) affecting the yield of obtained nanoparticles which have been synthesized using the first prototype of an automated solid-phase synthesizer. Applications of experimental design (or design of experiments) in optimization of nanoMIP yield were carried out using MODDE 9.0 software. The factors chosen in the model were the amount of functional monomers in the polymerization mixture, irradiation time, temperature during polymerization, and elution temperature. In general, it could be concluded that the irradiation time is the most important and the temperature was the least important factor which influences the yield of nanoparticles. Overall, the response surface methodology proved to be an effective tool in reducing time required for optimization of complex experimental conditions. PMID:24685151

Optimisation of the synthesis of vancomycin-selective molecularly imprinted polymer nanoparticles using automatic photoreactor.

PubMed

Muzyka, Kateryna; Karim, Khalku; Guerreiro, Antonio; Poma, Alessandro; Piletsky, Sergey

2014-03-31

A novel optimized protocol for solid-state synthesis of molecularly imprinted polymer nanoparticles (nanoMIPs) with specificity for antibiotic vancomycin is described. The experimental objective was optimization of the synthesis parameters (factors) affecting the yield of obtained nanoparticles which have been synthesized using the first prototype of an automated solid-phase synthesizer. Applications of experimental design (or design of experiments) in optimization of nanoMIP yield were carried out using MODDE 9.0 software. The factors chosen in the model were the amount of functional monomers in the polymerization mixture, irradiation time, temperature during polymerization, and elution temperature. In general, it could be concluded that the irradiation time is the most important and the temperature was the least important factor which influences the yield of nanoparticles. Overall, the response surface methodology proved to be an effective tool in reducing time required for optimization of complex experimental conditions.

Optimisation of the synthesis of vancomycin-selective molecularly imprinted polymer nanoparticles using automatic photoreactor

NASA Astrophysics Data System (ADS)

Muzyka, Kateryna; Karim, Khalku; Guerreiro, Antonio; Poma, Alessandro; Piletsky, Sergey

2014-03-01

A novel optimized protocol for solid-state synthesis of molecularly imprinted polymer nanoparticles (nanoMIPs) with specificity for antibiotic vancomycin is described. The experimental objective was optimization of the synthesis parameters (factors) affecting the yield of obtained nanoparticles which have been synthesized using the first prototype of an automated solid-phase synthesizer. Applications of experimental design (or design of experiments) in optimization of nanoMIP yield were carried out using MODDE 9.0 software. The factors chosen in the model were the amount of functional monomers in the polymerization mixture, irradiation time, temperature during polymerization, and elution temperature. In general, it could be concluded that the irradiation time is the most important and the temperature was the least important factor which influences the yield of nanoparticles. Overall, the response surface methodology proved to be an effective tool in reducing time required for optimization of complex experimental conditions.

CamOptimus: a tool for exploiting complex adaptive evolution to optimize experiments and processes in biotechnology

PubMed Central

Cankorur-Cetinkaya, Ayca; Dias, Joao M. L.; Kludas, Jana; Slater, Nigel K. H.; Rousu, Juho; Dikicioglu, Duygu

2017-01-01

Multiple interacting factors affect the performance of engineered biological systems in synthetic biology projects. The complexity of these biological systems means that experimental design should often be treated as a multiparametric optimization problem. However, the available methodologies are either impractical, due to a combinatorial explosion in the number of experiments to be performed, or are inaccessible to most experimentalists due to the lack of publicly available, user-friendly software. Although evolutionary algorithms may be employed as alternative approaches to optimize experimental design, the lack of simple-to-use software again restricts their use to specialist practitioners. In addition, the lack of subsidiary approaches to further investigate critical factors and their interactions prevents the full analysis and exploitation of the biotechnological system. We have addressed these problems and, here, provide a simple‐to‐use and freely available graphical user interface to empower a broad range of experimental biologists to employ complex evolutionary algorithms to optimize their experimental designs. Our approach exploits a Genetic Algorithm to discover the subspace containing the optimal combination of parameters, and Symbolic Regression to construct a model to evaluate the sensitivity of the experiment to each parameter under investigation. We demonstrate the utility of this method using an example in which the culture conditions for the microbial production of a bioactive human protein are optimized. CamOptimus is available through: (https://doi.org/10.17863/CAM.10257). PMID:28635591

Prolonged release matrix tablet of pyridostigmine bromide: formulation and optimization using statistical methods.

PubMed

Bolourchian, Noushin; Rangchian, Maryam; Foroutan, Seyed Mohsen

2012-07-01

The aim of this study was to design and optimize a prolonged release matrix formulation of pyridostigmine bromide, an effective drug in myasthenia gravis and poisoning with nerve gas, using hydrophilic - hydrophobic polymers via D-optimal experimental design. HPMC and carnauba wax as retarding agents as well as tricalcium phosphate were used in matrix formulation and considered as independent variables. Tablets were prepared by wet granulation technique and the percentage of drug released at 1 (Y(1)), 4 (Y(2)) and 8 (Y(3)) hours were considered as dependent variables (responses) in this investigation. These experimental responses were best fitted for the cubic, cubic and linear models, respectively. The optimal formulation obtained in this study, consisted of 12.8 % HPMC, 24.4 % carnauba wax and 26.7 % tricalcium phosphate, had a suitable prolonged release behavior followed by Higuchi model in which observed and predicted values were very close. The study revealed that D-optimal design could facilitate the optimization of prolonged release matrix tablet containing pyridostigmine bromide. Accelerated stability studies confirmed that the optimized formulation remains unchanged after exposing in stability conditions for six months.

IsoDesign: a software for optimizing the design of 13C-metabolic flux analysis experiments.

PubMed

Millard, Pierre; Sokol, Serguei; Letisse, Fabien; Portais, Jean-Charles

2014-01-01

The growing demand for (13) C-metabolic flux analysis ((13) C-MFA) in the field of metabolic engineering and systems biology is driving the need to rationalize expensive and time-consuming (13) C-labeling experiments. Experimental design is a key step in improving both the number of fluxes that can be calculated from a set of isotopic data and the precision of flux values. We present IsoDesign, a software that enables these parameters to be maximized by optimizing the isotopic composition of the label input. It can be applied to (13) C-MFA investigations using a broad panel of analytical tools (MS, MS/MS, (1) H NMR, (13) C NMR, etc.) individually or in combination. It includes a visualization module to intuitively select the optimal label input depending on the biological question to be addressed. Applications of IsoDesign are described, with an example of the entire (13) C-MFA workflow from the experimental design to the flux map including important practical considerations. IsoDesign makes the experimental design of (13) C-MFA experiments more accessible to a wider biological community. IsoDesign is distributed under an open source license at http://metasys.insa-toulouse.fr/software/isodes/ © 2013 Wiley Periodicals, Inc.

Numerical and experimental analysis of a ducted propeller designed by a fully automated optimization process under open water condition

NASA Astrophysics Data System (ADS)

Yu, Long; Druckenbrod, Markus; Greve, Martin; Wang, Ke-qi; Abdel-Maksoud, Moustafa

2015-10-01

A fully automated optimization process is provided for the design of ducted propellers under open water conditions, including 3D geometry modeling, meshing, optimization algorithm and CFD analysis techniques. The developed process allows the direct integration of a RANSE solver in the design stage. A practical ducted propeller design case study is carried out for validation. Numerical simulations and open water tests are fulfilled and proved that the optimum ducted propeller improves hydrodynamic performance as predicted.

Production of footbridge with double curvature made of UHPC

NASA Astrophysics Data System (ADS)

Kolísko, J.; Čítek, D.; Tej, P.; Rydval, M.

2017-09-01

This article present a mix design, preparation and production of thin-walled footbridge made from UHPFRC. In this case an experimental pedestrian bridge was design and prepared. Bridge with span of 10 m and the clear width of 1.50 m designed as single-span bridge. Optimization of UHPFRC matrix and parameters of this material leads to the design of very thin structures. Total thickness of shell structure 30 - 45 mm. Bridge was cast as a prefabricated element in one piece. Self-compacting character of UHPFRC with high flowability allows the production of the final structure. Extensive research was done before production of footbridge. Experimental reached data were compared with extensive numerical analysis and the final design of structure and UHPFRC matrix were optimized in many details. Two versions of large scale mock-ups were casted and tested. According to the complexity of whole experiment a casting technology and production of formwork were tested and optimized many times.

Separation of 20 coumarin derivatives using the capillary electrophoresis method optimized by a series of Doehlert experimental designs.

PubMed

Woźniakiewicz, Michał; Gładysz, Marta; Nowak, Paweł M; Kędzior, Justyna; Kościelniak, Paweł

2017-05-15

The aim of this study was to develop the first CE-based method enabling separation of 20 structurally similar coumarin derivatives. To facilitate method optimization a series of three consequent Doehlert experimental designs with the response surface methodology was employed, using number of peaks and the adjusted time of analysis as the selected responses. Initially, three variables were examined: buffer pH, ionic strength and temperature (No. 1 Doehlert design). The optimal conditions provided only partial separation, on that account, several buffer additives were examined at the next step: organic cosolvents and cyclodextrin (No. 2 Doehlert design). The optimal cyclodextrin type was also selected experimentally. The most promising results were obtained for the buffers fortified with methanol, acetonitrile and heptakis(2,3,6-tri-O-methyl)-β-cyclodextrin. Since these additives may potentially affect acid-base equilibrium and ionization state of analytes, the third Doehlert design (No. 3) was used to reconcile concentration of these additives with optimal pH. Ultimately, the total separation of all 20 compounds was achieved using the borate buffer at basic pH 9.5 in the presence of 10mM cyclodextrin, 9% (v/v) acetonitrile and 36% (v/v) methanol. Identity of all compounds was confirmed using the in-lab build UV-VIS spectra library. The developed method succeeded in identification of coumarin derivatives in three real samples. It demonstrates a huge resolving power of CE assisted by addition of cyclodextrins and organic cosolvents. Our unique optimization approach, based on the three Doehlert designs, seems to be prospective for future applications of this technique. Copyright © 2017 Elsevier B.V. All rights reserved.

Data Science and Optimal Learning for Material Discovery and Design

Science.gov Websites

in computation and experimental techniques generating vast arrays of data, without a clear link to experimental and computational data, designing new materials and impacting computational models. This meeting computational and experimental data (c) Analysis of data from probes such as light sources, as well as other

Probabilistic Finite Element Analysis & Design Optimization for Structural Designs

NASA Astrophysics Data System (ADS)

Deivanayagam, Arumugam

This study focuses on implementing probabilistic nature of material properties (Kevlar® 49) to the existing deterministic finite element analysis (FEA) of fabric based engine containment system through Monte Carlo simulations (MCS) and implementation of probabilistic analysis in engineering designs through Reliability Based Design Optimization (RBDO). First, the emphasis is on experimental data analysis focusing on probabilistic distribution models which characterize the randomness associated with the experimental data. The material properties of Kevlar® 49 are modeled using experimental data analysis and implemented along with an existing spiral modeling scheme (SMS) and user defined constitutive model (UMAT) for fabric based engine containment simulations in LS-DYNA. MCS of the model are performed to observe the failure pattern and exit velocities of the models. Then the solutions are compared with NASA experimental tests and deterministic results. MCS with probabilistic material data give a good prospective on results rather than a single deterministic simulation results. The next part of research is to implement the probabilistic material properties in engineering designs. The main aim of structural design is to obtain optimal solutions. In any case, in a deterministic optimization problem even though the structures are cost effective, it becomes highly unreliable if the uncertainty that may be associated with the system (material properties, loading etc.) is not represented or considered in the solution process. Reliable and optimal solution can be obtained by performing reliability optimization along with the deterministic optimization, which is RBDO. In RBDO problem formulation, in addition to structural performance constraints, reliability constraints are also considered. This part of research starts with introduction to reliability analysis such as first order reliability analysis, second order reliability analysis followed by simulation technique that are performed to obtain probability of failure and reliability of structures. Next, decoupled RBDO procedure is proposed with a new reliability analysis formulation with sensitivity analysis, which is performed to remove the highly reliable constraints in the RBDO, thereby reducing the computational time and function evaluations. Followed by implementation of the reliability analysis concepts and RBDO in finite element 2D truss problems and a planar beam problem are presented and discussed.

Optimization Method of a Low Cost, High Performance Ceramic Proppant by Orthogonal Experimental Design

NASA Astrophysics Data System (ADS)

Zhou, Y.; Tian, Y. M.; Wang, K. Y.; Li, G.; Zou, X. W.; Chai, Y. S.

2017-09-01

This study focused on optimization method of a ceramic proppant material with both low cost and high performance that met the requirements of Chinese Petroleum and Gas Industry Standard (SY/T 5108-2006). The orthogonal experimental design of L9(34) was employed to study the significance sequence of three factors, including weight ratio of white clay to bauxite, dolomite content and sintering temperature. For the crush resistance, both the range analysis and variance analysis reflected the optimally experimental condition was weight ratio of white clay to bauxite=3/7, dolomite content=3 wt.%, temperature=1350°C. For the bulk density, the most important factor was the sintering temperature, followed by the dolomite content, and then the ratio of white clay to bauxite.

Experimental analysis of the performance of optimized fin structures in a latent heat energy storage test rig

NASA Astrophysics Data System (ADS)

Johnson, Maike; Hübner, Stefan; Reichmann, Carsten; Schönberger, Manfred; Fiß, Michael

2017-06-01

Energy storage systems are a key technology for developing a more sustainable energy supply system and lowering overall CO2 emissions. Among the variety of storage technologies, high temperature phase change material (PCM) storage is a promising option with a wide range of applications. PCM storages using an extended finned tube storage concept have been designed and techno-economically optimized for solar thermal power plant operations. These finned tube components were experimentally tested in order to validate the optimized design and simulation models used. Analysis of the charging and discharging characteristics of the storage at the pilot scale gives insight into the heat distribution both axially as well as radially in the storage material, thereby allowing for a realistic validation of the design. The design was optimized for discharging of the storage, as this is the more critical operation mode in power plant applications. The data show good agreement between the model and the experiments for discharging.

Experimental Optimization of a Free-to-Rotate Wing for Small UAS

NASA Technical Reports Server (NTRS)

Logan, Michael J.; DeLoach, Richard; Copeland, Tiwana; Vo, Steven

2014-01-01

This paper discusses an experimental investigation conducted to optimize a free-to-rotate wing for use on a small unmanned aircraft system (UAS). Although free-to-rotate wings have been used for decades on various small UAS and small manned aircraft, little is known about how to optimize these unusual wings for a specific application. The paper discusses some of the design rationale of the basic wing. In addition, three main parameters were selected for "optimization", wing camber, wing pivot location, and wing center of gravity (c.g.) location. A small apparatus was constructed to enable some simple experimental analysis of these parameters. A design-of-experiment series of tests were first conducted to discern which of the main optimization parameters were most likely to have the greatest impact on the outputs of interest, namely, some measure of "stability", some measure of the lift being generated at the neutral position, and how quickly the wing "recovers" from an upset. A second set of tests were conducted to develop a response-surface numerical representation of these outputs as functions of the three primary inputs. The response surface numerical representations are then used to develop an "optimum" within the trade space investigated. The results of the optimization are then tested experimentally to validate the predictions.

A compact microwave patch applicator for hyperthermia treatment of cancer.

PubMed

Chakaravarthi, Geetha; Arunachalam, Kavitha

2014-01-01

Design and development of a compact microstrip C-type patch applicator for hyperthermia treatment of cancer is presented. The patch antenna is optimized for resonance at 434 MHz, return loss (S11) better than -15dB and co-polarized electric field in tissue. Effect of water bolus thickness on power delivery is studied for improved power coupling. Numerical simulations for antenna design optimization carried out using EM simulation software, Ansys HFSS(®), USA were experimentally verified. The effective field coverage for the optimized patch antenna and experimental results indicate that the compact antenna resonates at ISM frequency 434 MHz with better than -15 dB power coupling.

Microspoiler Actuation for Guided Projectiles

DTIC Science & Technology

2016-01-06

and be hardened to gun -launch. Several alternative designs will be explored using various actuation techniques, and downselection to an optimal design...aerodynamic optimization of the microspoiler mechanism, mechanical design/ gun hardening, and parameter estimation from experimental data. These...performed using the aerodynamic parameters in Table 2. Projectile trajectories were simulated without gravity at zero gun elevation. The standard 30mm

Global Design Optimization for Aerodynamics and Rocket Propulsion Components

NASA Technical Reports Server (NTRS)

Shyy, Wei; Papila, Nilay; Vaidyanathan, Rajkumar; Tucker, Kevin; Turner, James E. (Technical Monitor)

2000-01-01

Modern computational and experimental tools for aerodynamics and propulsion applications have matured to a stage where they can provide substantial insight into engineering processes involving fluid flows, and can be fruitfully utilized to help improve the design of practical devices. In particular, rapid and continuous development in aerospace engineering demands that new design concepts be regularly proposed to meet goals for increased performance, robustness and safety while concurrently decreasing cost. To date, the majority of the effort in design optimization of fluid dynamics has relied on gradient-based search algorithms. Global optimization methods can utilize the information collected from various sources and by different tools. These methods offer multi-criterion optimization, handle the existence of multiple design points and trade-offs via insight into the entire design space, can easily perform tasks in parallel, and are often effective in filtering the noise intrinsic to numerical and experimental data. However, a successful application of the global optimization method needs to address issues related to data requirements with an increase in the number of design variables, and methods for predicting the model performance. In this article, we review recent progress made in establishing suitable global optimization techniques employing neural network and polynomial-based response surface methodologies. Issues addressed include techniques for construction of the response surface, design of experiment techniques for supplying information in an economical manner, optimization procedures and multi-level techniques, and assessment of relative performance between polynomials and neural networks. Examples drawn from wing aerodynamics, turbulent diffuser flows, gas-gas injectors, and supersonic turbines are employed to help demonstrate the issues involved in an engineering design context. Both the usefulness of the existing knowledge to aid current design practices and the need for future research are identified.

Near-optimal experimental design for model selection in systems biology.

PubMed

Busetto, Alberto Giovanni; Hauser, Alain; Krummenacher, Gabriel; Sunnåker, Mikael; Dimopoulos, Sotiris; Ong, Cheng Soon; Stelling, Jörg; Buhmann, Joachim M

2013-10-15

Biological systems are understood through iterations of modeling and experimentation. Not all experiments, however, are equally valuable for predictive modeling. This study introduces an efficient method for experimental design aimed at selecting dynamical models from data. Motivated by biological applications, the method enables the design of crucial experiments: it determines a highly informative selection of measurement readouts and time points. We demonstrate formal guarantees of design efficiency on the basis of previous results. By reducing our task to the setting of graphical models, we prove that the method finds a near-optimal design selection with a polynomial number of evaluations. Moreover, the method exhibits the best polynomial-complexity constant approximation factor, unless P = NP. We measure the performance of the method in comparison with established alternatives, such as ensemble non-centrality, on example models of different complexity. Efficient design accelerates the loop between modeling and experimentation: it enables the inference of complex mechanisms, such as those controlling central metabolic operation. Toolbox 'NearOED' available with source code under GPL on the Machine Learning Open Source Software Web site (mloss.org).

Experimental validation of systematically designed acoustic hyperbolic meta material slab exhibiting negative refraction

NASA Astrophysics Data System (ADS)

Christiansen, Rasmus E.; Sigmund, Ole

2016-09-01

This Letter reports on the experimental validation of a two-dimensional acoustic hyperbolic metamaterial slab optimized to exhibit negative refractive behavior. The slab was designed using a topology optimization based systematic design method allowing for tailoring the refractive behavior. The experimental results confirm the predicted refractive capability as well as the predicted transmission at an interface. The study simultaneously provides an estimate of the attenuation inside the slab stemming from the boundary layer effects—insight which can be utilized in the further design of the metamaterial slabs. The capability of tailoring the refractive behavior opens possibilities for different applications. For instance, a slab exhibiting zero refraction across a wide angular range is capable of funneling acoustic energy through it, while a material exhibiting the negative refractive behavior across a wide angular range provides lensing and collimating capabilities.

The system design and performance test of hybrid vertical axis wind turbine

NASA Astrophysics Data System (ADS)

Dwiyantoro, Bambang Arip; Suphandani, Vivien

2017-04-01

Vertical axis wind turbine is a tool that is being developed to generate energy from wind. One cause is still little use of wind energy is the design of wind turbines that are less precise. Therefore in this study will be developed the system design of hybrid vertical axis wind turbine and tested performance with experimental methods. The design of hybrid turbine based on a straight bladed Darrieus turbine along with a double step Savonius turbine. The method used to design wind turbines is by studying literature, analyzing the critical parts of a wind turbine and the structure of the optimal design. Wind turbine prototype of the optimal design characteristic tests in the wind tunnel experimentally by varying the speed of the wind. From the experimental results show that the greater the wind speed, the greater the wind turbine rotation and torque is raised. The hybrid vertical axis wind turbine has much better self-starting and better conversion efficiency.

Microrandomized trials: An experimental design for developing just-in-time adaptive interventions.

PubMed

Klasnja, Predrag; Hekler, Eric B; Shiffman, Saul; Boruvka, Audrey; Almirall, Daniel; Tewari, Ambuj; Murphy, Susan A

2015-12-01

This article presents an experimental design, the microrandomized trial, developed to support optimization of just-in-time adaptive interventions (JITAIs). JITAIs are mHealth technologies that aim to deliver the right intervention components at the right times and locations to optimally support individuals' health behaviors. Microrandomized trials offer a way to optimize such interventions by enabling modeling of causal effects and time-varying effect moderation for individual intervention components within a JITAI. The article describes the microrandomized trial design, enumerates research questions that this experimental design can help answer, and provides an overview of the data analyses that can be used to assess the causal effects of studied intervention components and investigate time-varying moderation of those effects. Microrandomized trials enable causal modeling of proximal effects of the randomized intervention components and assessment of time-varying moderation of those effects. Microrandomized trials can help researchers understand whether their interventions are having intended effects, when and for whom they are effective, and what factors moderate the interventions' effects, enabling creation of more effective JITAIs. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

Micro-Randomized Trials: An Experimental Design for Developing Just-in-Time Adaptive Interventions

PubMed Central

Klasnja, Predrag; Hekler, Eric B.; Shiffman, Saul; Boruvka, Audrey; Almirall, Daniel; Tewari, Ambuj; Murphy, Susan A.

2015-01-01

Objective This paper presents an experimental design, the micro-randomized trial, developed to support optimization of just-in-time adaptive interventions (JITAIs). JITAIs are mHealth technologies that aim to deliver the right intervention components at the right times and locations to optimally support individuals’ health behaviors. Micro-randomized trials offer a way to optimize such interventions by enabling modeling of causal effects and time-varying effect moderation for individual intervention components within a JITAI. Methods The paper describes the micro-randomized trial design, enumerates research questions that this experimental design can help answer, and provides an overview of the data analyses that can be used to assess the causal effects of studied intervention components and investigate time-varying moderation of those effects. Results Micro-randomized trials enable causal modeling of proximal effects of the randomized intervention components and assessment of time-varying moderation of those effects. Conclusions Micro-randomized trials can help researchers understand whether their interventions are having intended effects, when and for whom they are effective, and what factors moderate the interventions’ effects, enabling creation of more effective JITAIs. PMID:26651463

Counteracting moment device for reduction of earthquake-induced excursions of multi-level buildings.

PubMed

Nagaya, K; Fukushima, T; Kosugi, Y

1999-05-01

A vibration-control mechanism for beams and columns was presented in our previous report in which the earthquake force was transformed into a vibration-control force by using a gear train mechanism. In our previous report, however, only the principle of transforming the earthquake force into the control force was presented; the discussion for real structures and the design method were not presented. The present article provides a theoretical analysis of the column which is used in multi-layered buildings. Experimental tests were carried out for a model of multi-layered buildings in the frequency range of a principal earthquake wave. Theoretical results are compared to the experimental data. The optimal design of the control mechanism, which is of importance in the column design, is presented. Numerical calculations are carried out for the optimal design. It is shown that vibrations of the column involving the mechanism are suppressed remarkably. The optimal design method and the analytical results are applicable to the design of the column.

Five-Junction Solar Cell Optimization Using Silvaco Atlas

DTIC Science & Technology

2017-09-01

experimental sources [1], [4], [6]. f. Numerical Method The method selected for solving the non -linear equations that make up the simulation can be...and maximize efficiency. Optimization of solar cell efficiency is carried out via nearly orthogonal balanced design of experiments methodology . Silvaco...Optimization of solar cell efficiency is carried out via nearly orthogonal balanced design of experiments methodology . Silvaco ATLAS is utilized to

Optimization of a miniature Maglev ventricular assist device for pediatric circulatory support.

PubMed

Zhang, Juntao; Koert, Andrew; Gellman, Barry; Gempp, Thomas M; Dasse, Kurt A; Gilbert, Richard J; Griffith, Bartley P; Wu, Zhongjun J

2007-01-01

A miniature Maglev blood pump based on magnetically levitated bearingless technology is being developed and optimized for pediatric patients. We performed impeller optimization by characterizing the hemodynamic and hemocompatibility performances using a combined computational and experimental approach. Both three-dimensional flow features and hemolytic characteristics were analyzed using computational fluid dynamics (CFD) modeling. Hydraulic pump performances and hemolysis levels of three different impeller designs were quantified and compared numerically. Two pump prototypes were constructed from the two impeller designs and experimentally tested. Comparison of CFD predictions with experimental results showed good agreement. The optimized impeller remarkably increased overall pump hydraulic output by more than 50% over the initial design. The CFD simulation demonstrated a clean and streamlined flow field in the main flow path. The numerical results by hemolysis model indicated no significant high shear stress regions. Through the use of CFD analysis and bench-top testing, the small pediatric pump was optimized to achieve a low level of blood damage and improved hydraulic performance and efficiency. The Maglev pediatric blood pump is innovative due to its small size, very low priming volume, excellent hemodynamic and hematologic performance, and elimination of seal-related and bearing-related failures due to adoption of magnetically levitated bearingless motor technology, making it ideal for pediatric applications.

Optimizing Associative Experimental Design for Protein Crystallization Screening

PubMed Central

Dinç, Imren; Pusey, Marc L.; Aygün, Ramazan S.

2016-01-01

The goal of protein crystallization screening is the determination of the main factors of importance to crystallizing the protein under investigation. One of the major issues about determining these factors is that screening is often expanded to many hundreds or thousands of conditions to maximize combinatorial chemical space coverage for maximizing the chances of a successful (crystalline) outcome. In this paper, we propose an experimental design method called “Associative Experimental Design (AED)” and an optimization method includes eliminating prohibited combinations and prioritizing reagents based on AED analysis of results from protein crystallization experiments. AED generates candidate cocktails based on these initial screening results. These results are analyzed to determine those screening factors in chemical space that are most likely to lead to higher scoring outcomes, crystals. We have tested AED on three proteins derived from the hyperthermophile Thermococcus thioreducens, and we applied an optimization method to these proteins. Our AED method generated novel cocktails (count provided in parentheses) leading to crystals for three proteins as follows: Nucleoside diphosphate kinase (4), HAD superfamily hydrolase (2), Nucleoside kinase (1). After getting promising results, we have tested our optimization method on four different proteins. The AED method with optimization yielded 4, 3, and 20 crystalline conditions for holo Human Transferrin, archaeal exosome protein, and Nucleoside diphosphate kinase, respectively. PMID:26955046

Optimal design of high temperature metalized thin-film polymer capacitors: A combined numerical and experimental method

NASA Astrophysics Data System (ADS)

Wang, Zhuo; Li, Qi; Trinh, Wei; Lu, Qianli; Cho, Heejin; Wang, Qing; Chen, Lei

2017-07-01

The objective of this paper is to design and optimize the high temperature metalized thin-film polymer capacitor by a combined computational and experimental method. A finite-element based thermal model is developed to incorporate Joule heating and anisotropic heat conduction arising from anisotropic geometric structures of the capacitor. The anisotropic thermal conductivity and temperature dependent electrical conductivity required by the thermal model are measured from the experiments. The polymer represented by thermally crosslinking benzocyclobutene (BCB) in the presence of boron nitride nanosheets (BNNSs) is selected for high temperature capacitor design based on the results of highest internal temperature (HIT) and the time to achieve thermal equilibrium. The c-BCB/BNNS-based capacitor aiming at the operating temperature of 250 °C is geometrically optimized with respect to its shape and volume. "Safe line" plot is also presented to reveal the influence of the cooling strength on capacitor geometry design.

Framework for the rapid optimization of soluble protein expression in Escherichia coli combining microscale experiments and statistical experimental design.

PubMed

Islam, R S; Tisi, D; Levy, M S; Lye, G J

2007-01-01

A major bottleneck in drug discovery is the production of soluble human recombinant protein in sufficient quantities for analysis. This problem is compounded by the complex relationship between protein yield and the large number of variables which affect it. Here, we describe a generic framework for the rapid identification and optimization of factors affecting soluble protein yield in microwell plate fermentations as a prelude to the predictive and reliable scaleup of optimized culture conditions. Recombinant expression of firefly luciferase in Escherichia coli was used as a model system. Two rounds of statistical design of experiments (DoE) were employed to first screen (D-optimal design) and then optimize (central composite face design) the yield of soluble protein. Biological variables from the initial screening experiments included medium type and growth and induction conditions. To provide insight into the impact of the engineering environment on cell growth and expression, plate geometry, shaking speed, and liquid fill volume were included as factors since these strongly influence oxygen transfer into the wells. Compared to standard reference conditions, both the screening and optimization designs gave up to 3-fold increases in the soluble protein yield, i.e., a 9-fold increase overall. In general the highest protein yields were obtained when cells were induced at a relatively low biomass concentration and then allowed to grow slowly up to a high final biomass concentration, >8 g.L-1. Consideration and analysis of the model results showed 6 of the original 10 variables to be important at the screening stage and 3 after optimization. The latter included the microwell plate shaking speeds pre- and postinduction, indicating the importance of oxygen transfer into the microwells and identifying this as a critical parameter for subsequent scale translation studies. The optimization process, also known as response surface methodology (RSM), predicted there to be a distinct optimum set of conditions for protein expression which could be verified experimentally. This work provides a generic approach to protein expression optimization in which both biological and engineering variables are investigated from the initial screening stage. The application of DoE reduces the total number of experiments needed to be performed, while experimentation at the microwell scale increases experimental throughput and reduces cost.

Experimental design approach to the process parameter optimization for laser welding of martensitic stainless steels in a constrained overlap configuration

NASA Astrophysics Data System (ADS)

Khan, M. M. A.; Romoli, L.; Fiaschi, M.; Dini, G.; Sarri, F.

2011-02-01

This paper presents an experimental design approach to process parameter optimization for the laser welding of martensitic AISI 416 and AISI 440FSe stainless steels in a constrained overlap configuration in which outer shell was 0.55 mm thick. To determine the optimal laser-welding parameters, a set of mathematical models were developed relating welding parameters to each of the weld characteristics. These were validated both statistically and experimentally. The quality criteria set for the weld to determine optimal parameters were the minimization of weld width and the maximization of weld penetration depth, resistance length and shearing force. Laser power and welding speed in the range 855-930 W and 4.50-4.65 m/min, respectively, with a fiber diameter of 300 μm were identified as the optimal set of process parameters. However, the laser power and welding speed can be reduced to 800-840 W and increased to 4.75-5.37 m/min, respectively, to obtain stronger and better welds.

Demonstration of decomposition and optimization in the design of experimental space systems

NASA Technical Reports Server (NTRS)

Padula, Sharon; Sandridge, Chris A.; Haftka, Raphael T.; Walsh, Joanne L.

1989-01-01

Effective design strategies for a class of systems which may be termed Experimental Space Systems (ESS) are needed. These systems, which include large space antenna and observatories, space platforms, earth satellites and deep space explorers, have special characteristics which make them particularly difficult to design. It is argued here that these same characteristics encourage the use of advanced computer-aided optimization and planning techniques. The broad goal of this research is to develop optimization strategies for the design of ESS. These strategics would account for the possibly conflicting requirements of mission life, safety, scientific payoffs, initial system cost, launch limitations and maintenance costs. The strategies must also preserve the coupling between disciplines or between subsystems. Here, the specific purpose is to describe a computer-aided planning and scheduling technique. This technique provides the designer with a way to map the flow of data between multidisciplinary analyses. The technique is important because it enables the designer to decompose the system design problem into a number of smaller subproblems. The planning and scheduling technique is demonstrated by its application to a specific preliminary design problem.

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

PubMed

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

2017-06-15

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

Robust experimental design for optimizing the microbial inhibitor test for penicillin detection in milk.

PubMed

Nagel, O G; Molina, M P; Basílico, J C; Zapata, M L; Althaus, R L

2009-06-01

To use experimental design techniques and a multiple logistic regression model to optimize a microbiological inhibition test with dichotomous response for the detection of Penicillin G in milk. A 2(3) x 2(2) robust experimental design with two replications was used. The effects of three control factors (V: culture medium volume, S: spore concentration of Geobacillus stearothermophilus, I: indicator concentration), two noise factors (Dt: diffusion time, Ip: incubation period) and their interactions were studied. The V, S, Dt, Ip factors and V x S, V x Ip, S x Ip interactions showed significant effects. The use of 100 microl culture medium volume, 2 x 10(5) spores ml(-1), 60 min diffusion time and 3 h incubation period is recommended. In these elaboration conditions, the penicillin detection limit was of 3.9 microg l(-1), similar to the maximum residue limit (MRL). Of the two noise factors studied, the incubation period can be controlled by means of the culture medium volume and spore concentration. We were able to optimize bioassays of dichotomous response using an experimental design and logistic regression model for the detection of residues at the level of MRL, aiding in the avoidance of health problems in the consumer.

Re-designing a mechanism for higher speed: A case history from textile machinery

NASA Astrophysics Data System (ADS)

Douglas, S. S.; Rooney, G. T.

The generation of general mechanism design software which is the formulation of suitable objective functions is discussed. There is a consistent drive towards higher speeds in the development of industrial sewing machines. This led to experimental analyses of dynamic performance and to a search for improved design methods. The experimental work highlighted the need for smoothness of motion at high speed, component inertias, and frame structural stiffness. Smoothness is associated with transmission properties and harmonic analysis. These are added to other design requirements of synchronization, mechanism size, and function. Some of the mechanism trains in overedte sewing machines are shown. All these trains are designed by digital optimization. The design software combines analysis of the sewing machine mechanisms, formulation of objectives innumerical terms, and suitable mathematical optimization ttechniques.

A novel experimental design method to optimize hydrophilic matrix formulations with drug release profiles and mechanical properties.

PubMed

Choi, Du Hyung; Lim, Jun Yeul; Shin, Sangmun; Choi, Won Jun; Jeong, Seong Hoon; Lee, Sangkil

2014-10-01

To investigate the effects of hydrophilic polymers on the matrix system, an experimental design method was developed to integrate response surface methodology and the time series modeling. Moreover, the relationships among polymers on the matrix system were studied with the evaluation of physical properties including water uptake, mass loss, diffusion, and gelling index. A mixture simplex lattice design was proposed while considering eight input control factors: Polyethylene glycol 6000 (x1 ), polyethylene oxide (PEO) N-10 (x2 ), PEO 301 (x3 ), PEO coagulant (x4 ), PEO 303 (x5 ), hydroxypropyl methylcellulose (HPMC) 100SR (x6 ), HPMC 4000SR (x7 ), and HPMC 10(5) SR (x8 ). With the modeling, optimal formulations were obtained depending on the four types of targets. The optimal formulations showed the four significant factors (x1 , x2 , x3 , and x8 ) and other four input factors (x4 , x5 , x6 , and x7 ) were not significant based on drug release profiles. Moreover, the optimization results were analyzed with estimated values, targets values, absolute biases, and relative biases based on observed times for the drug release rates with four different targets. The result showed that optimal solutions and target values had consistent patterns with small biases. On the basis of the physical properties of the optimal solutions, the type and ratio of the hydrophilic polymer and the relationships between polymers significantly influenced the physical properties of the system and drug release. This experimental design method is very useful in formulating a matrix system with optimal drug release. Moreover, it can distinctly confirm the relationships between excipients and the effects on the system with extensive and intensive evaluations. © 2014 Wiley Periodicals, Inc. and the American Pharmacists Association.

Bioresorbable scaffolds for bone tissue engineering: optimal design, fabrication, mechanical testing and scale-size effects analysis.

PubMed

Coelho, Pedro G; Hollister, Scott J; Flanagan, Colleen L; Fernandes, Paulo R

2015-03-01

Bone scaffolds for tissue regeneration require an optimal trade-off between biological and mechanical criteria. Optimal designs may be obtained using topology optimization (homogenization approach) and prototypes produced using additive manufacturing techniques. However, the process from design to manufacture remains a research challenge and will be a requirement of FDA design controls to engineering scaffolds. This work investigates how the design to manufacture chain affects the reproducibility of complex optimized design characteristics in the manufactured product. The design and prototypes are analyzed taking into account the computational assumptions and the final mechanical properties determined through mechanical tests. The scaffold is an assembly of unit-cells, and thus scale size effects on the mechanical response considering finite periodicity are investigated and compared with the predictions from the homogenization method which assumes in the limit infinitely repeated unit cells. Results show that a limited number of unit-cells (3-5 repeated on a side) introduce some scale-effects but the discrepancies are below 10%. Higher discrepancies are found when comparing the experimental data to numerical simulations due to differences between the manufactured and designed scaffold feature shapes and sizes as well as micro-porosities introduced by the manufacturing process. However good regression correlations (R(2) > 0.85) were found between numerical and experimental values, with slopes close to 1 for 2 out of 3 designs. Copyright © 2015 IPEM. Published by Elsevier Ltd. All rights reserved.

Optomechanical study and optimization of cantilever plate dynamics

NASA Astrophysics Data System (ADS)

Furlong, Cosme; Pryputniewicz, Ryszard J.

1995-06-01

Optimum dynamic characteristics of an aluminum cantilever plate containing holes of different sizes and located at arbitrary positions on the plate are studied computationally and experimentally. The objective function of this optimization is the minimization/maximization of the natural frequencies of the plate in terms of such design variable s as the sizes and locations of the holes. The optimization process is performed using the finite element method and mathematical programming techniques in order to obtain the natural frequencies and the optimum conditions of the plate, respectively. The modal behavior of the resultant optimal plate layout is studied experimentally through the use of holographic interferometry techniques. Comparisons of the computational and experimental results show that good agreement between theory and test is obtained. The comparisons also show that the combined, or hybrid use of experimental and computational techniques complement each other and prove to be a very efficient tool for performing optimization studies of mechanical components.

Fast Bayesian experimental design: Laplace-based importance sampling for the expected information gain

NASA Astrophysics Data System (ADS)

Beck, Joakim; Dia, Ben Mansour; Espath, Luis F. R.; Long, Quan; Tempone, Raúl

2018-06-01

In calculating expected information gain in optimal Bayesian experimental design, the computation of the inner loop in the classical double-loop Monte Carlo requires a large number of samples and suffers from underflow if the number of samples is small. These drawbacks can be avoided by using an importance sampling approach. We present a computationally efficient method for optimal Bayesian experimental design that introduces importance sampling based on the Laplace method to the inner loop. We derive the optimal values for the method parameters in which the average computational cost is minimized according to the desired error tolerance. We use three numerical examples to demonstrate the computational efficiency of our method compared with the classical double-loop Monte Carlo, and a more recent single-loop Monte Carlo method that uses the Laplace method as an approximation of the return value of the inner loop. The first example is a scalar problem that is linear in the uncertain parameter. The second example is a nonlinear scalar problem. The third example deals with the optimal sensor placement for an electrical impedance tomography experiment to recover the fiber orientation in laminate composites.

Optimal experimental design for assessment of enzyme kinetics in a drug discovery screening environment.

PubMed

Sjögren, Erik; Nyberg, Joakim; Magnusson, Mats O; Lennernäs, Hans; Hooker, Andrew; Bredberg, Ulf

2011-05-01

A penalized expectation of determinant (ED)-optimal design with a discrete parameter distribution was used to find an optimal experimental design for assessment of enzyme kinetics in a screening environment. A data set for enzyme kinetic data (V(max) and K(m)) was collected from previously reported studies, and every V(max)/K(m) pair (n = 76) was taken to represent a unique drug compound. The design was restricted to 15 samples, an incubation time of up to 40 min, and starting concentrations (C(0)) for the incubation between 0.01 and 100 μM. The optimization was performed by finding the sample times and C(0) returning the lowest uncertainty (S.E.) of the model parameter estimates. Individual optimal designs, one general optimal design and one, for laboratory practice suitable, pragmatic optimal design (OD) were obtained. In addition, a standard design (STD-D), representing a commonly applied approach for metabolic stability investigations, was constructed. Simulations were performed for OD and STD-D by using the Michaelis-Menten (MM) equation, and enzyme kinetic parameters were estimated with both MM and a monoexponential decay. OD generated a better result (relative standard error) for 99% of the compounds and an equal or better result [(root mean square error (RMSE)] for 78% of the compounds in estimation of metabolic intrinsic clearance. Furthermore, high-quality estimates (RMSE < 30%) of both V(max) and K(m) could be obtained for a considerable number (26%) of the investigated compounds by using the suggested OD. The results presented in this study demonstrate that the output could generally be improved compared with that obtained from the standard approaches used today.

Optimal design of stimulus experiments for robust discrimination of biochemical reaction networks.

PubMed

Flassig, R J; Sundmacher, K

2012-12-01

Biochemical reaction networks in the form of coupled ordinary differential equations (ODEs) provide a powerful modeling tool for understanding the dynamics of biochemical processes. During the early phase of modeling, scientists have to deal with a large pool of competing nonlinear models. At this point, discrimination experiments can be designed and conducted to obtain optimal data for selecting the most plausible model. Since biological ODE models have widely distributed parameters due to, e.g. biologic variability or experimental variations, model responses become distributed. Therefore, a robust optimal experimental design (OED) for model discrimination can be used to discriminate models based on their response probability distribution functions (PDFs). In this work, we present an optimal control-based methodology for designing optimal stimulus experiments aimed at robust model discrimination. For estimating the time-varying model response PDF, which results from the nonlinear propagation of the parameter PDF under the ODE dynamics, we suggest using the sigma-point approach. Using the model overlap (expected likelihood) as a robust discrimination criterion to measure dissimilarities between expected model response PDFs, we benchmark the proposed nonlinear design approach against linearization with respect to prediction accuracy and design quality for two nonlinear biological reaction networks. As shown, the sigma-point outperforms the linearization approach in the case of widely distributed parameter sets and/or existing multiple steady states. Since the sigma-point approach scales linearly with the number of model parameter, it can be applied to large systems for robust experimental planning. An implementation of the method in MATLAB/AMPL is available at http://www.uni-magdeburg.de/ivt/svt/person/rf/roed.html. flassig@mpi-magdeburg.mpg.de Supplementary data are are available at Bioinformatics online.

Application of Plackett-Burman and Doehlert designs for optimization of selenium analysis in plasma with electrothermal atomic absorption spectrometry.

PubMed

El Ati-Hellal, Myriam; Hellal, Fayçal; Hedhili, Abderrazek

2014-10-01

The aim of this study was the optimization of selenium determination in plasma samples with electrothermal atomic absorption spectrometry using experimental design methodology. 11 variables being able to influence selenium analysis in human blood plasma by electrothermal atomic absorption spectrometry (ETAAS) were evaluated with Plackett-Burman experimental design. These factors were selected from sample preparation, furnace program and chemical modification steps. Both absorbance and background signals were chosen as responses in the screening approach. Doehlert design was used for method optimization. Results showed that only ashing temperature has a statistically significant effect on the selected responses. Optimization with Doehlert design allowed the development of a reliable method for selenium analysis with ETAAS. Samples were diluted 1/10 with 0.05% (v/v) TritonX-100+2.5% (v/v) HNO3 solution. Optimized ashing and atomization temperatures for nickel modifier were 1070°C and 2270°C, respectively. A detection limit of 2.1μgL(-1) Se was obtained. Accuracy of the method was checked by the analysis of selenium in Seronorm™ Trace element quality control serum level 1. The developed procedure was applied for the analysis of total selenium in fifteen plasma samples with standard addition method. Concentrations ranged between 24.4 and 64.6μgL(-1), with a mean of 42.6±4.9μgL(-1). The use of experimental designs allowed the development of a cheap and accurate method for selenium analysis in plasma that could be applied routinely in clinical laboratories. Copyright © 2014 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

An Umeclidinium membrane sensor; Two-step optimization strategy for improved responses.

PubMed

Yehia, Ali M; Monir, Hany H

2017-09-01

In the scientific context of membrane sensors and improved experimentation, we devised an experimentally designed protocol for sensor optimization. Two-step strategy was implemented for Umeclidinium bromide (UMEC) analysis which is a novel quinuclidine-based muscarinic antagonist used for maintenance treatment of symptoms accompanied with chronic obstructive pulmonary disease. In the first place, membrane components were screened for ideal ion exchanger, ionophore and plasticizer using three categorical factors at three levels in Taguchi design. Secondly, experimentally designed optimization was followed in order to tune the sensor up for finest responses. Twelve experiments were randomly carried out in a continuous factor design. Nernstian response, detection limit and selectivity were assigned as responses in these designs. The optimized membrane sensor contained tetrakis-[3,5-bis(trifluoro- methyl)phenyl] borate (0.44wt%) and calix[6]arene (0.43wt%) in 50.00% PVC plasticized with 49.13wt% 2-ni-tro-phenyl octylether. This sensor, along with an optimum concentration of inner filling solution (2×10 -4 molL -1 UMEC) and 2h of soaking time, attained the design objectives. Nernstian response approached 59.7mV/decade and detection limit decreased by about two order of magnitude (8×10 -8 mol L -1 ) through this optimization protocol. The proposed sensor was validated for UMEC determination in its linear range (3.16×10 -7 -1×10 -3 mol L -1 ) and challenged for selective discrimination of other congeners and inorganic cations. Results of INCRUSE ELLIPTA ® inhalation powder analyses obtained from the proposed sensor and manufacturer's UPLC were statistically compared. Moreover the proposed sensor was successfully used for the determination of UMEC in plasma samples. Copyright © 2017 Elsevier B.V. All rights reserved.

Experimental validation of 3D printed material behaviors and their influence on the structural topology design

NASA Astrophysics Data System (ADS)

Yang, Kai Ke; Zhu, Ji Hong; Wang, Chuang; Jia, Dong Sheng; Song, Long Long; Zhang, Wei Hong

2018-05-01

The purpose of this paper is to investigate the structures achieved by topology optimization and their fabrications by 3D printing considering the particular features of material microstructures and macro mechanical performances. Combining Digital Image Correlation and Optical Microscope, this paper experimentally explored the anisotropies of stiffness and strength existing in the 3D printed polymer material using Stereolithography (SLA) and titanium material using Selective Laser Melting (SLM). The standard specimens and typical structures obtained by topology optimization were fabricated along different building directions. On the one hand, the experimental results of these SLA produced structures showed stable properties and obviously anisotropic rules in stiffness, ultimate strengths and places of fractures. Further structural designs were performed using topology optimization when the particular mechanical behaviors of SLA printed materials were considered, which resulted in better structural performances compared to the optimized designs using `ideal' isotropic material model. On the other hand, this paper tested the mechanical behaviors of SLM printed multiscale lattice structures which were fabricated using the same metal powder and the same machine. The structural stiffness values are generally similar while the strength behaviors show a difference, which are mainly due to the irregular surface quality of the tiny structural branches of the lattice. The above evidences clearly show that the consideration of the particular behaviors of 3D printed materials is therefore indispensable for structural design and optimization in order to improve the structural performance and strengthen their practical significance.

Experimental validation of 3D printed material behaviors and their influence on the structural topology design

NASA Astrophysics Data System (ADS)

Yang, Kai Ke; Zhu, Ji Hong; Wang, Chuang; Jia, Dong Sheng; Song, Long Long; Zhang, Wei Hong

2018-02-01

The purpose of this paper is to investigate the structures achieved by topology optimization and their fabrications by 3D printing considering the particular features of material microstructures and macro mechanical performances. Combining Digital Image Correlation and Optical Microscope, this paper experimentally explored the anisotropies of stiffness and strength existing in the 3D printed polymer material using Stereolithography (SLA) and titanium material using Selective Laser Melting (SLM). The standard specimens and typical structures obtained by topology optimization were fabricated along different building directions. On the one hand, the experimental results of these SLA produced structures showed stable properties and obviously anisotropic rules in stiffness, ultimate strengths and places of fractures. Further structural designs were performed using topology optimization when the particular mechanical behaviors of SLA printed materials were considered, which resulted in better structural performances compared to the optimized designs using `ideal' isotropic material model. On the other hand, this paper tested the mechanical behaviors of SLM printed multiscale lattice structures which were fabricated using the same metal powder and the same machine. The structural stiffness values are generally similar while the strength behaviors show a difference, which are mainly due to the irregular surface quality of the tiny structural branches of the lattice. The above evidences clearly show that the consideration of the particular behaviors of 3D printed materials is therefore indispensable for structural design and optimization in order to improve the structural performance and strengthen their practical significance.

Optimization of turning process through the analytic flank wear modelling

NASA Astrophysics Data System (ADS)

Del Prete, A.; Franchi, R.; De Lorenzis, D.

2018-05-01

In the present work, the approach used for the optimization of the process capabilities for Oil&Gas components machining will be described. These components are machined by turning of stainless steel castings workpieces. For this purpose, a proper Design Of Experiments (DOE) plan has been designed and executed: as output of the experimentation, data about tool wear have been collected. The DOE has been designed starting from the cutting speed and feed values recommended by the tools manufacturer; the depth of cut parameter has been maintained as a constant. Wear data has been obtained by means the observation of the tool flank wear under an optical microscope: the data acquisition has been carried out at regular intervals of working times. Through a statistical data and regression analysis, analytical models of the flank wear and the tool life have been obtained. The optimization approach used is a multi-objective optimization, which minimizes the production time and the number of cutting tools used, under the constraint on a defined flank wear level. The technique used to solve the optimization problem is a Multi Objective Particle Swarm Optimization (MOPS). The optimization results, validated by the execution of a further experimental campaign, highlighted the reliability of the work and confirmed the usability of the optimized process parameters and the potential benefit for the company.

Experimental design methods for bioengineering applications.

PubMed

Keskin Gündoğdu, Tuğba; Deniz, İrem; Çalışkan, Gülizar; Şahin, Erdem Sefa; Azbar, Nuri

2016-01-01

Experimental design is a form of process analysis in which certain factors are selected to obtain the desired responses of interest. It may also be used for the determination of the effects of various independent factors on a dependent factor. The bioengineering discipline includes many different areas of scientific interest, and each study area is affected and governed by many different factors. Briefly analyzing the important factors and selecting an experimental design for optimization are very effective tools for the design of any bioprocess under question. This review summarizes experimental design methods that can be used to investigate various factors relating to bioengineering processes. The experimental methods generally used in bioengineering are as follows: full factorial design, fractional factorial design, Plackett-Burman design, Taguchi design, Box-Behnken design and central composite design. These design methods are briefly introduced, and then the application of these design methods to study different bioengineering processes is analyzed.

Computational wing optimization and comparisons with experiment for a semi-span wing model

NASA Technical Reports Server (NTRS)

Waggoner, E. G.; Haney, H. P.; Ballhaus, W. F.

1978-01-01

A computational wing optimization procedure was developed and verified by an experimental investigation of a semi-span variable camber wing model in the NASA Ames Research Center 14 foot transonic wind tunnel. The Bailey-Ballhaus transonic potential flow analysis and Woodward-Carmichael linear theory codes were linked to Vanderplaats constrained minimization routine to optimize model configurations at several subsonic and transonic design points. The 35 deg swept wing is characterized by multi-segmented leading and trailing edge flaps whose hinge lines are swept relative to the leading and trailing edges of the wing. By varying deflection angles of the flap segments, camber and twist distribution can be optimized for different design conditions. Results indicate that numerical optimization can be both an effective and efficient design tool. The optimized configurations had as good or better lift to drag ratios at the design points as the best designs previously tested during an extensive parametric study.

Reliability-based design optimization using a generalized subset simulation method and posterior approximation

NASA Astrophysics Data System (ADS)

Ma, Yuan-Zhuo; Li, Hong-Shuang; Yao, Wei-Xing

2018-05-01

The evaluation of the probabilistic constraints in reliability-based design optimization (RBDO) problems has always been significant and challenging work, which strongly affects the performance of RBDO methods. This article deals with RBDO problems using a recently developed generalized subset simulation (GSS) method and a posterior approximation approach. The posterior approximation approach is used to transform all the probabilistic constraints into ordinary constraints as in deterministic optimization. The assessment of multiple failure probabilities required by the posterior approximation approach is achieved by GSS in a single run at all supporting points, which are selected by a proper experimental design scheme combining Sobol' sequences and Bucher's design. Sequentially, the transformed deterministic design optimization problem can be solved by optimization algorithms, for example, the sequential quadratic programming method. Three optimization problems are used to demonstrate the efficiency and accuracy of the proposed method.

Determining a Robust D-Optimal Design for Testing for Departure from Additivity in a Mixture of Four Perfluoroalkyl Acids.

EPA Science Inventory

Our objective is to determine an optimal experimental design for a mixture of perfluoroalkyl acids (PFAAs) that is robust to the assumption of additivity. PFAAs are widely used in consumer products and industrial applications. The presence and persistence of PFAAs, especially in ...

Data-driven design optimization for composite material characterization

Treesearch

John G. Michopoulos; John C. Hermanson; Athanasios Iliopoulos; Samuel G. Lambrakos; Tomonari Furukawa

2011-06-01

The main goal of the present paper is to demonstrate the value of design optimization beyond its use for structural shape determination in the realm of the constitutive characterization of anisotropic material systems such as polymer matrix composites with or without damage. The approaches discussed are based on the availability of massive experimental data...

DETERMINING A ROBUST D-OPTIMAL DESIGN FOR TESTING FOR DEPARTURE FROM ADDITIVITY IN A MIXTURE OF FOUR PFAAS

EPA Science Inventory

Our objective was to determine an optimal experimental design for a mixture of perfluoroalkyl acids (PFAAs) that is robust to the assumption of additivity. Of particular focus to this research project is whether an environmentally relevant mixture of four PFAAs with long half-liv...

Optimization of β-carotene loaded solid lipid nanoparticles preparation using a high shear homogenization technique

NASA Astrophysics Data System (ADS)

Triplett, Michael D.; Rathman, James F.

2009-04-01

Using statistical experimental design methodologies, the solid lipid nanoparticle design space was found to be more robust than previously shown in literature. Formulation and high shear homogenization process effects on solid lipid nanoparticle size distribution, stability, drug loading, and drug release have been investigated. Experimentation indicated stearic acid as the optimal lipid, sodium taurocholate as the optimal cosurfactant, an optimum lecithin to sodium taurocholate ratio of 3:1, and an inverse relationship between mixing time and speed and nanoparticle size and polydispersity. Having defined the base solid lipid nanoparticle system, β-carotene was incorporated into stearic acid nanoparticles to investigate the effects of introducing a drug into the base solid lipid nanoparticle system. The presence of β-carotene produced a significant effect on the optimal formulation and process conditions, but the design space was found to be robust enough to accommodate the drug. β-Carotene entrapment efficiency averaged 40%. β-Carotene was retained in the nanoparticles for 1 month. As demonstrated herein, solid lipid nanoparticle technology can be sufficiently robust from a design standpoint to become commercially viable.

Optimal Experimental Design for Model Discrimination

ERIC Educational Resources Information Center

Myung, Jay I.; Pitt, Mark A.

2009-01-01

Models of a psychological process can be difficult to discriminate experimentally because it is not easy to determine the values of the critical design variables (e.g., presentation schedule, stimulus structure) that will be most informative in differentiating them. Recent developments in sampling-based search methods in statistics make it…

Applications of Chemiluminescence in the Teaching of Experimental Design

ERIC Educational Resources Information Center

Krawczyk, Tomasz; Slupska, Roksana; Baj, Stefan

2015-01-01

This work describes a single-session laboratory experiment devoted to teaching the principles of factorial experimental design. Students undertook the rational optimization of a luminol oxidation reaction, using a two-level experiment that aimed to create a long-lasting bright emission. During the session students used only simple glassware and…

Optimal design of isotope labeling experiments.

PubMed

Yang, Hong; Mandy, Dominic E; Libourel, Igor G L

2014-01-01

Stable isotope labeling experiments (ILE) constitute a powerful methodology for estimating metabolic fluxes. An optimal label design for such an experiment is necessary to maximize the precision with which fluxes can be determined. But often, precision gained in the determination of one flux comes at the expense of the precision of other fluxes, and an appropriate label design therefore foremost depends on the question the investigator wants to address. One could liken ILE to shadows that metabolism casts on products. Optimal label design is the placement of the lamp; creating clear shadows for some parts of metabolism and obscuring others.An optimal isotope label design is influenced by: (1) the network structure; (2) the true flux values; (3) the available label measurements; and, (4) commercially available substrates. The first two aspects are dictated by nature and constrain any optimal design. The second two aspects are suitable design parameters. To create an optimal label design, an explicit optimization criterion needs to be formulated. This usually is a property of the flux covariance matrix, which can be augmented by weighting label substrate cost. An optimal design is found by using such a criterion as an objective function for an optimizer. This chapter uses a simple elementary metabolite units (EMU) representation of the TCA cycle to illustrate the process of experimental design of isotope labeled substrates.

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

NASA Astrophysics Data System (ADS)

Yang, Huanhuan; Gunzburger, Max

2017-06-01

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

Optimal Design of an Automotive Exhaust Thermoelectric Generator

NASA Astrophysics Data System (ADS)

Fagehi, Hassan; Attar, Alaa; Lee, Hosung

2018-07-01

The consumption of energy continues to increase at an exponential rate, especially in terms of conventional automobiles. Approximately 40% of the applied fuel into a vehicle is lost as waste exhausted to the environment. The desire for improved fuel efficiency by recovering the exhaust waste heat in automobiles has become an important subject. A thermoelectric generator (TEG) has the potential to convert exhaust waste heat into electricity as long as it is improving fuel economy. The remarkable amount of research being conducted on TEGs indicates that this technology will have a bright future in terms of power generation. The current study discusses the optimal design of the automotive exhaust TEG. An experimental study has been conducted to verify the model that used the ideal (standard) equations along with effective material properties. The model is reasonably verified by experimental work, mainly due to the utilization of the effective material properties. Hence, the thermoelectric module that was used in the experiment was optimized by using a developed optimal design theory (dimensionless analysis technique).

Optimization of deep eutectic solvent-based ultrasound-assisted extraction of polysaccharides from Dioscorea opposita Thunb.

PubMed

Zhang, Lijin; Wang, Maoshan

2017-02-01

In this study, deep eutectic solvents were proposed for the ultrasound-assisted extraction of polysaccharides from Dioscorea opposita Thunb. Several deep eutectic solvents were prepared for the extraction of polysaccharides, among which the deep eutectic solvent composed of choline chloride and 1,4-butanediol was proved to be suitable for the extraction. Based on the screening of single-factor experiment design and orthogonal experiment design, three experimental factors were optimized for the Box-Behnken experimental design combined with response surface methodology, which gave the optimal extraction conditions: water content of 32.89%(v/v), extraction temperature of 94.00°C, and the extraction time of 44.74min. The optimal extraction conditions could supply higher extraction yield than those of hot water extraction and water-based ultrasound-assisted extraction. Therefore, deep eutectic solvents were an excellent extraction solvent alternative to the extraction of polysaccharides from sample matrices. Copyright © 2016 Elsevier B.V. All rights reserved.

Optimal Design of an Automotive Exhaust Thermoelectric Generator

NASA Astrophysics Data System (ADS)

Fagehi, Hassan; Attar, Alaa; Lee, Hosung

2018-04-01

The consumption of energy continues to increase at an exponential rate, especially in terms of conventional automobiles. Approximately 40% of the applied fuel into a vehicle is lost as waste exhausted to the environment. The desire for improved fuel efficiency by recovering the exhaust waste heat in automobiles has become an important subject. A thermoelectric generator (TEG) has the potential to convert exhaust waste heat into electricity as long as it is improving fuel economy. The remarkable amount of research being conducted on TEGs indicates that this technology will have a bright future in terms of power generation. The current study discusses the optimal design of the automotive exhaust TEG. An experimental study has been conducted to verify the model that used the ideal (standard) equations along with effective material properties. The model is reasonably verified by experimental work, mainly due to the utilization of the effective material properties. Hence, the thermoelectric module that was used in the experiment was optimized by using a developed optimal design theory (dimensionless analysis technique).

Active SAmpling Protocol (ASAP) to Optimize Individual Neurocognitive Hypothesis Testing: A BCI-Inspired Dynamic Experimental Design.

PubMed

Sanchez, Gaëtan; Lecaignard, Françoise; Otman, Anatole; Maby, Emmanuel; Mattout, Jérémie

2016-01-01

The relatively young field of Brain-Computer Interfaces has promoted the use of electrophysiology and neuroimaging in real-time. In the meantime, cognitive neuroscience studies, which make extensive use of functional exploration techniques, have evolved toward model-based experiments and fine hypothesis testing protocols. Although these two developments are mostly unrelated, we argue that, brought together, they may trigger an important shift in the way experimental paradigms are being designed, which should prove fruitful to both endeavors. This change simply consists in using real-time neuroimaging in order to optimize advanced neurocognitive hypothesis testing. We refer to this new approach as the instantiation of an Active SAmpling Protocol (ASAP). As opposed to classical (static) experimental protocols, ASAP implements online model comparison, enabling the optimization of design parameters (e.g., stimuli) during the course of data acquisition. This follows the well-known principle of sequential hypothesis testing. What is radically new, however, is our ability to perform online processing of the huge amount of complex data that brain imaging techniques provide. This is all the more relevant at a time when physiological and psychological processes are beginning to be approached using more realistic, generative models which may be difficult to tease apart empirically. Based upon Bayesian inference, ASAP proposes a generic and principled way to optimize experimental design adaptively. In this perspective paper, we summarize the main steps in ASAP. Using synthetic data we illustrate its superiority in selecting the right perceptual model compared to a classical design. Finally, we briefly discuss its future potential for basic and clinical neuroscience as well as some remaining challenges.

Robust Bayesian Experimental Design for Conceptual Model Discrimination

NASA Astrophysics Data System (ADS)

Pham, H. V.; Tsai, F. T. C.

2015-12-01

A robust Bayesian optimal experimental design under uncertainty is presented to provide firm information for model discrimination, given the least number of pumping wells and observation wells. Firm information is the maximum information of a system can be guaranteed from an experimental design. The design is based on the Box-Hill expected entropy decrease (EED) before and after the experiment design and the Bayesian model averaging (BMA) framework. A max-min programming is introduced to choose the robust design that maximizes the minimal Box-Hill EED subject to that the highest expected posterior model probability satisfies a desired probability threshold. The EED is calculated by the Gauss-Hermite quadrature. The BMA method is used to predict future observations and to quantify future observation uncertainty arising from conceptual and parametric uncertainties in calculating EED. Monte Carlo approach is adopted to quantify the uncertainty in the posterior model probabilities. The optimal experimental design is tested by a synthetic 5-layer anisotropic confined aquifer. Nine conceptual groundwater models are constructed due to uncertain geological architecture and boundary condition. High-performance computing is used to enumerate all possible design solutions in order to identify the most plausible groundwater model. Results highlight the impacts of scedasticity in future observation data as well as uncertainty sources on potential pumping and observation locations.

Analysis and optimization of hybrid excitation permanent magnet synchronous generator for stand-alone power system

NASA Astrophysics Data System (ADS)

Wang, Huijun; Qu, Zheng; Tang, Shaofei; Pang, Mingqi; Zhang, Mingju

2017-08-01

In this paper, electromagnetic design and permanent magnet shape optimization for permanent magnet synchronous generator with hybrid excitation are investigated. Based on generator structure and principle, design outline is presented for obtaining high efficiency and low voltage fluctuation. In order to realize rapid design, equivalent magnetic circuits for permanent magnet and iron poles are developed. At the same time, finite element analysis is employed. Furthermore, by means of design of experiment (DOE) method, permanent magnet is optimized to reduce voltage waveform distortion. Finally, the validity of proposed design methods is validated by the analytical and experimental results.

designGG: an R-package and web tool for the optimal design of genetical genomics experiments.

PubMed

Li, Yang; Swertz, Morris A; Vera, Gonzalo; Fu, Jingyuan; Breitling, Rainer; Jansen, Ritsert C

2009-06-18

High-dimensional biomolecular profiling of genetically different individuals in one or more environmental conditions is an increasingly popular strategy for exploring the functioning of complex biological systems. The optimal design of such genetical genomics experiments in a cost-efficient and effective way is not trivial. This paper presents designGG, an R package for designing optimal genetical genomics experiments. A web implementation for designGG is available at http://gbic.biol.rug.nl/designGG. All software, including source code and documentation, is freely available. DesignGG allows users to intelligently select and allocate individuals to experimental units and conditions such as drug treatment. The user can maximize the power and resolution of detecting genetic, environmental and interaction effects in a genome-wide or local mode by giving more weight to genome regions of special interest, such as previously detected phenotypic quantitative trait loci. This will help to achieve high power and more accurate estimates of the effects of interesting factors, and thus yield a more reliable biological interpretation of data. DesignGG is applicable to linkage analysis of experimental crosses, e.g. recombinant inbred lines, as well as to association analysis of natural populations.

Optimal design and experimental analyses of a new micro-vibration control payload-platform

NASA Astrophysics Data System (ADS)

Sun, Xiaoqing; Yang, Bintang; Zhao, Long; Sun, Xiaofen

2016-07-01

This paper presents a new payload-platform, for precision devices, which possesses the capability of isolating the complex space micro-vibration in low frequency range below 5 Hz. The novel payload-platform equipped with smart material actuators is investigated and designed through optimization strategy based on the minimum energy loss rate, for the aim of achieving high drive efficiency and reducing the effect of the magnetic circuit nonlinearity. Then, the dynamic model of the driving element is established by using the Lagrange method and the performance of the designed payload-platform is further discussed through the combination of the controlled auto regressive moving average (CARMA) model with modified generalized prediction control (MGPC) algorithm. Finally, an experimental prototype is developed and tested. The experimental results demonstrate that the payload-platform has an impressive potential of micro-vibration isolation.

Optimal experimental designs for fMRI when the model matrix is uncertain.

PubMed

Kao, Ming-Hung; Zhou, Lin

2017-07-15

This study concerns optimal designs for functional magnetic resonance imaging (fMRI) experiments when the model matrix of the statistical model depends on both the selected stimulus sequence (fMRI design), and the subject's uncertain feedback (e.g. answer) to each mental stimulus (e.g. question) presented to her/him. While practically important, this design issue is challenging. This mainly is because that the information matrix cannot be fully determined at the design stage, making it difficult to evaluate the quality of the selected designs. To tackle this challenging issue, we propose an easy-to-use optimality criterion for evaluating the quality of designs, and an efficient approach for obtaining designs optimizing this criterion. Compared with a previously proposed method, our approach requires a much less computing time to achieve designs with high statistical efficiencies. Copyright © 2017 Elsevier Inc. All rights reserved.

Multi-objective experimental design for (13)C-based metabolic flux analysis.

PubMed

Bouvin, Jeroen; Cajot, Simon; D'Huys, Pieter-Jan; Ampofo-Asiama, Jerry; Anné, Jozef; Van Impe, Jan; Geeraerd, Annemie; Bernaerts, Kristel

2015-10-01

(13)C-based metabolic flux analysis is an excellent technique to resolve fluxes in the central carbon metabolism but costs can be significant when using specialized tracers. This work presents a framework for cost-effective design of (13)C-tracer experiments, illustrated on two different networks. Linear and non-linear optimal input mixtures are computed for networks for Streptomyces lividans and a carcinoma cell line. If only glucose tracers are considered as labeled substrate for a carcinoma cell line or S. lividans, the best parameter estimation accuracy is obtained by mixtures containing high amounts of 1,2-(13)C2 glucose combined with uniformly labeled glucose. Experimental designs are evaluated based on a linear (D-criterion) and non-linear approach (S-criterion). Both approaches generate almost the same input mixture, however, the linear approach is favored due to its low computational effort. The high amount of 1,2-(13)C2 glucose in the optimal designs coincides with a high experimental cost, which is further enhanced when labeling is introduced in glutamine and aspartate tracers. Multi-objective optimization gives the possibility to assess experimental quality and cost at the same time and can reveal excellent compromise experiments. For example, the combination of 100% 1,2-(13)C2 glucose with 100% position one labeled glutamine and the combination of 100% 1,2-(13)C2 glucose with 100% uniformly labeled glutamine perform equally well for the carcinoma cell line, but the first mixture offers a decrease in cost of $ 120 per ml-scale cell culture experiment. We demonstrated the validity of a multi-objective linear approach to perform optimal experimental designs for the non-linear problem of (13)C-metabolic flux analysis. Tools and a workflow are provided to perform multi-objective design. The effortless calculation of the D-criterion can be exploited to perform high-throughput screening of possible (13)C-tracers, while the illustrated benefit of multi-objective design should stimulate its application within the field of (13)C-based metabolic flux analysis. Copyright © 2015 Elsevier Inc. All rights reserved.

Global Design Optimization for Fluid Machinery Applications

NASA Technical Reports Server (NTRS)

Shyy, Wei; Papila, Nilay; Tucker, Kevin; Vaidyanathan, Raj; Griffin, Lisa

2000-01-01

Recent experiences in utilizing the global optimization methodology, based on polynomial and neural network techniques for fluid machinery design are summarized. Global optimization methods can utilize the information collected from various sources and by different tools. These methods offer multi-criterion optimization, handle the existence of multiple design points and trade-offs via insight into the entire design space can easily perform tasks in parallel, and are often effective in filtering the noise intrinsic to numerical and experimental data. Another advantage is that these methods do not need to calculate the sensitivity of each design variable locally. However, a successful application of the global optimization method needs to address issues related to data requirements with an increase in the number of design variables and methods for predicting the model performance. Examples of applications selected from rocket propulsion components including a supersonic turbine and an injector element and a turbulent flow diffuser are used to illustrate the usefulness of the global optimization method.

Fast Synthesis of Gibbsite Nanoplates and Process Optimization using Box-Behnken Experimental Design

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

Zhang, Xin; Zhang, Xianwen; Graham, Trent R.

Developing the ability to synthesize compositionally and morphologically well-defined gibbsite particles at the nanoscale with high yield is an ongoing need that has not yet achieved the level of rational design. Here we report optimization of a clean inorganic synthesis route based on statistical experimental design examining the influence of Al(OH)3 gel precursor concentration, pH, and aging time at temperature. At 80 oC, the optimum synthesis conditions of gel concentration at 0.5 M, pH at 9.2, and time at 72 h maximized the reaction yield up to ~87%. The resulting gibbsite product is composed of highly uniform euhedral hexagonal nanoplatesmore » within a basal plane diameter range of 200-400 nm. The independent roles of key system variables in the growth mechanism are considered. On the basis of these optimized experimental conditions, the synthesis procedure, which is both cost-effective and environmentally friendly, has the potential for mass production scale-up of high quality gibbsite material for various fundamental research and industrial applications.« less

Prediction uncertainty and optimal experimental design for learning dynamical systems.

PubMed

Letham, Benjamin; Letham, Portia A; Rudin, Cynthia; Browne, Edward P

2016-06-01

Dynamical systems are frequently used to model biological systems. When these models are fit to data, it is necessary to ascertain the uncertainty in the model fit. Here, we present prediction deviation, a metric of uncertainty that determines the extent to which observed data have constrained the model's predictions. This is accomplished by solving an optimization problem that searches for a pair of models that each provides a good fit for the observed data, yet has maximally different predictions. We develop a method for estimating a priori the impact that additional experiments would have on the prediction deviation, allowing the experimenter to design a set of experiments that would most reduce uncertainty. We use prediction deviation to assess uncertainty in a model of interferon-alpha inhibition of viral infection, and to select a sequence of experiments that reduces this uncertainty. Finally, we prove a theoretical result which shows that prediction deviation provides bounds on the trajectories of the underlying true model. These results show that prediction deviation is a meaningful metric of uncertainty that can be used for optimal experimental design.

Application of a neural network to simulate analysis in an optimization process

NASA Technical Reports Server (NTRS)

Rogers, James L.; Lamarsh, William J., II

1992-01-01

A new experimental software package called NETS/PROSSS aimed at reducing the computing time required to solve a complex design problem is described. The software combines a neural network for simulating the analysis program with an optimization program. The neural network is applied to approximate results of a finite element analysis program to quickly obtain a near-optimal solution. Results of the NETS/PROSSS optimization process can also be used as an initial design in a normal optimization process and make it possible to converge to an optimum solution with significantly fewer iterations.

Optimal experimental design for parameter estimation of a cell signaling model.

PubMed

Bandara, Samuel; Schlöder, Johannes P; Eils, Roland; Bock, Hans Georg; Meyer, Tobias

2009-11-01

Differential equation models that describe the dynamic changes of biochemical signaling states are important tools to understand cellular behavior. An essential task in building such representations is to infer the affinities, rate constants, and other parameters of a model from actual measurement data. However, intuitive measurement protocols often fail to generate data that restrict the range of possible parameter values. Here we utilized a numerical method to iteratively design optimal live-cell fluorescence microscopy experiments in order to reveal pharmacological and kinetic parameters of a phosphatidylinositol 3,4,5-trisphosphate (PIP(3)) second messenger signaling process that is deregulated in many tumors. The experimental approach included the activation of endogenous phosphoinositide 3-kinase (PI3K) by chemically induced recruitment of a regulatory peptide, reversible inhibition of PI3K using a kinase inhibitor, and monitoring of the PI3K-mediated production of PIP(3) lipids using the pleckstrin homology (PH) domain of Akt. We found that an intuitively planned and established experimental protocol did not yield data from which relevant parameters could be inferred. Starting from a set of poorly defined model parameters derived from the intuitively planned experiment, we calculated concentration-time profiles for both the inducing and the inhibitory compound that would minimize the predicted uncertainty of parameter estimates. Two cycles of optimization and experimentation were sufficient to narrowly confine the model parameters, with the mean variance of estimates dropping more than sixty-fold. Thus, optimal experimental design proved to be a powerful strategy to minimize the number of experiments needed to infer biological parameters from a cell signaling assay.

Optimizing Experimental Designs Relative to Costs and Effect Sizes.

ERIC Educational Resources Information Center

Headrick, Todd C.; Zumbo, Bruno D.

A general model is derived for the purpose of efficiently allocating integral numbers of units in multi-level designs given prespecified power levels. The derivation of the model is based on a constrained optimization problem that maximizes a general form of a ratio of expected mean squares subject to a budget constraint. This model provides more…

On the Constitutive Response Characterization for Composite Materials Via Data-Driven Design Optimization

Treesearch

John G. Michopoulos; John G. Hermanson; Athanasios lliopoulos; Samuel Lambrakos; Tomonari Furukawa

2011-01-01

In the present paper we focus on demonstrating the use of design optimization for the constitutive characterization of anisotropic material systems such as polymer matrix composites, with or without damage. All approaches are based on the availability of experimental data originating from mechatronic material testing systems that can expose specimens to...

Convergence in parameters and predictions using computational experimental design.

PubMed

Hagen, David R; White, Jacob K; Tidor, Bruce

2013-08-06

Typically, biological models fitted to experimental data suffer from significant parameter uncertainty, which can lead to inaccurate or uncertain predictions. One school of thought holds that accurate estimation of the true parameters of a biological system is inherently problematic. Recent work, however, suggests that optimal experimental design techniques can select sets of experiments whose members probe complementary aspects of a biochemical network that together can account for its full behaviour. Here, we implemented an experimental design approach for selecting sets of experiments that constrain parameter uncertainty. We demonstrated with a model of the epidermal growth factor-nerve growth factor pathway that, after synthetically performing a handful of optimal experiments, the uncertainty in all 48 parameters converged below 10 per cent. Furthermore, the fitted parameters converged to their true values with a small error consistent with the residual uncertainty. When untested experimental conditions were simulated with the fitted models, the predicted species concentrations converged to their true values with errors that were consistent with the residual uncertainty. This paper suggests that accurate parameter estimation is achievable with complementary experiments specifically designed for the task, and that the resulting parametrized models are capable of accurate predictions.

Application of Statistical Design for the Production of Cellulase by Trichoderma reesei Using Mango Peel.

PubMed

Saravanan, P; Muthuvelayudham, R; Viruthagiri, T

2012-01-01

Optimization of the culture medium for cellulase production using Trichoderma reesei was carried out. The optimization of cellulase production using mango peel as substrate was performed with statistical methodology based on experimental designs. The screening of nine nutrients for their influence on cellulase production is achieved using Plackett-Burman design. Avicel, soybean cake flour, KH(2)PO(4), and CoCl(2)·6H(2)O were selected based on their positive influence on cellulase production. The composition of the selected components was optimized using Response Surface Methodology (RSM). The optimum conditions are as follows: Avicel: 25.30 g/L, Soybean cake flour: 23.53 g/L, KH(2)PO(4): 4.90 g/L, and CoCl(2)·6H(2)O: 0.95 g/L. These conditions are validated experimentally which revealed an enhanced Cellulase activity of 7.8 IU/mL.

Rationally reduced libraries for combinatorial pathway optimization minimizing experimental effort.

PubMed

Jeschek, Markus; Gerngross, Daniel; Panke, Sven

2016-03-31

Rational flux design in metabolic engineering approaches remains difficult since important pathway information is frequently not available. Therefore empirical methods are applied that randomly change absolute and relative pathway enzyme levels and subsequently screen for variants with improved performance. However, screening is often limited on the analytical side, generating a strong incentive to construct small but smart libraries. Here we introduce RedLibs (Reduced Libraries), an algorithm that allows for the rational design of smart combinatorial libraries for pathway optimization thereby minimizing the use of experimental resources. We demonstrate the utility of RedLibs for the design of ribosome-binding site libraries by in silico and in vivo screening with fluorescent proteins and perform a simple two-step optimization of the product selectivity in the branched multistep pathway for violacein biosynthesis, indicating a general applicability for the algorithm and the proposed heuristics. We expect that RedLibs will substantially simplify the refactoring of synthetic metabolic pathways.

Experimental design data for the biosynthesis of citric acid using Central Composite Design method.

PubMed

Kola, Anand Kishore; Mekala, Mallaiah; Goli, Venkat Reddy

2017-06-01

In the present investigation, we report that statistical design and optimization of significant variables for the microbial production of citric acid from sucrose in presence of filamentous fungi A. niger NCIM 705. Various combinations of experiments were designed with Central Composite Design (CCD) of Response Surface Methodology (RSM) for the production of citric acid as a function of six variables. The variables are; initial sucrose concentration, initial pH of medium, fermentation temperature, incubation time, stirrer rotational speed, and oxygen flow rate. From experimental data, a statistical model for this process has been developed. The optimum conditions reported in the present article are initial concentration of sucrose of 163.6 g/L, initial pH of medium 5.26, stirrer rotational speed of 247.78 rpm, incubation time of 8.18 days, fermentation temperature of 30.06 °C and flow rate of oxygen of 1.35 lpm. Under optimum conditions the predicted maximum citric acid is 86.42 g/L. The experimental validation carried out under the optimal values and reported citric acid to be 82.0 g/L. The model is able to represent the experimental data and the agreement between the model and experimental data is good.

Factorial experimental design intended for the optimization of the alumina purification conditions

NASA Astrophysics Data System (ADS)

Brahmi, Mounaouer; Ba, Mohamedou; Hidri, Yassine; Hassen, Abdennaceur

2018-04-01

The objective of this study was to determine the optimal conditions by using the experimental design methodology for the removal of some impurities associated with the alumina. So, three alumina qualities of different origins were investigated under the same conditions. The application of full-factorial designs on the samples of different qualities of alumina has followed the removal rates of the sodium oxide. However, a factorial experimental design was developed to describe the elimination of sodium oxide associated with the alumina. The experimental results showed that chemical analyze followed by XRF prior treatment of the samples, provided a primary idea concerning these prevailing impurities. Therefore, it appeared that the sodium oxide constituted the largest amount among all impurities. After the application of experimental design, analysis of the effectors different factors and their interactions showed that to have a better result, we should reduce the alumina quantity investigated and by against increase the stirring time for the first two samples, whereas, it was necessary to increase the alumina quantity in the case of the third sample. To expand and improve this research, we should take into account all existing impurities, since we found during this investigation that the levels of partial impurities increased after the treatment.

Optimization of headspace solid-phase microextraction by means of an experimental design for the determination of methyl tert.-butyl ether in water by gas chromatography-flame ionization detection.

PubMed

Dron, Julien; Garcia, Rosa; Millán, Esmeralda

2002-07-19

A procedure for determination of methyl tert.-butyl ether (MTBE) in water by headspace solid-phase microextraction (HS-SPME) has been developed. The analysis was carried out by gas chromatography with flame ionization detection. The extraction procedure, using a 65-microm poly(dimethylsiloxane)-divinylbenzene SPME fiber, was optimized following experimental design. A fractional factorial design for screening and a central composite design for optimizing the significant variables were applied. Extraction temperature and sodium chloride concentration were significant variables, and 20 degrees C and 300 g/l were, respectively chosen for the best extraction response. With these conditions, an extraction time of 5 min was sufficient to extract MTBE. The calibration linear range for MTBE was 5-500 microg/l and the detection limit 0.45 microg/l. The relative standard deviation, for seven replicates of 250 microg/l MTBE in water, was 6.3%.

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

Optimal Design of Passive Flow Control for a Boundary-Layer-Ingesting Offset Inlet Using Design-of-Experiments

NASA Technical Reports Server (NTRS)

Allan, Brian G.; Owens, Lewis R.; Lin, John C.

2006-01-01

This research will investigate the use of Design-of-Experiments (DOE) in the development of an optimal passive flow control vane design for a boundary-layer-ingesting (BLI) offset inlet in transonic flow. This inlet flow control is designed to minimize the engine fan-face distortion levels and first five Fourier harmonic half amplitudes while maximizing the inlet pressure recovery. Numerical simulations of the BLI inlet are computed using the Reynolds-averaged Navier-Stokes (RANS) flow solver, OVERFLOW, developed at NASA. These simulations are used to generate the numerical experiments for the DOE response surface model. In this investigation, two DOE optimizations were performed using a D-Optimal Response Surface model. The first DOE optimization was performed using four design factors which were vane height and angles-of-attack for two groups of vanes. One group of vanes was placed at the bottom of the inlet and a second group symmetrically on the sides. The DOE design was performed for a BLI inlet with a free-stream Mach number of 0.85 and a Reynolds number of 2 million, based on the length of the fan-face diameter, matching an experimental wind tunnel BLI inlet test. The first DOE optimization required a fifth order model having 173 numerical simulation experiments and was able to reduce the DC60 baseline distortion from 64% down to 4.4%, while holding the pressure recovery constant. A second DOE optimization was performed holding the vanes heights at a constant value from the first DOE optimization with the two vane angles-of-attack as design factors. This DOE only required a second order model fit with 15 numerical simulation experiments and reduced DC60 to 3.5% with small decreases in the fourth and fifth harmonic amplitudes. The second optimal vane design was tested at the NASA Langley 0.3- Meter Transonic Cryogenic Tunnel in a BLI inlet experiment. The experimental results showed a 80% reduction of DPCP(sub avg), the circumferential distortion level at the engine fan-face.

Optimal Design of Passive Flow Control for a Boundary-Layer-Ingesting Offset Inlet Using Design-of-Experiments

NASA Technical Reports Server (NTRS)

Allan, Brian G.; Owens, Lewis R., Jr.; Lin, John C.

2006-01-01

This research will investigate the use of Design-of-Experiments (DOE) in the development of an optimal passive flow control vane design for a boundary-layer-ingesting (BLI) offset inlet in transonic flow. This inlet flow control is designed to minimize the engine fan face distortion levels and first five Fourier harmonic half amplitudes while maximizing the inlet pressure recovery. Numerical simulations of the BLI inlet are computed using the Reynolds-averaged Navier-Stokes (RANS) flow solver, OVERFLOW, developed at NASA. These simulations are used to generate the numerical experiments for the DOE response surface model. In this investigation, two DOE optimizations were performed using a D-Optimal Response Surface model. The first DOE optimization was performed using four design factors which were vane height and angles-of-attack for two groups of vanes. One group of vanes was placed at the bottom of the inlet and a second group symmetrically on the sides. The DOE design was performed for a BLI inlet with a free-stream Mach number of 0.85 and a Reynolds number of 2 million, based on the length of the fan face diameter, matching an experimental wind tunnel BLI inlet test. The first DOE optimization required a fifth order model having 173 numerical simulation experiments and was able to reduce the DC60 baseline distortion from 64% down to 4.4%, while holding the pressure recovery constant. A second DOE optimization was performed holding the vanes heights at a constant value from the first DOE optimization with the two vane angles-of-attack as design factors. This DOE only required a second order model fit with 15 numerical simulation experiments and reduced DC60 to 3.5% with small decreases in the fourth and fifth harmonic amplitudes. The second optimal vane design was tested at the NASA Langley 0.3-Meter Transonic Cryogenic Tunnel in a BLI inlet experiment. The experimental results showed a 80% reduction of DPCPavg, the circumferential distortion level at the engine fan face.

Solar-Diesel Hybrid Power System Optimization and Experimental Validation

NASA Astrophysics Data System (ADS)

Jacobus, Headley Stewart

As of 2008 1.46 billion people, or 22 percent of the World's population, were without electricity. Many of these people live in remote areas where decentralized generation is the only method of electrification. Most mini-grids are powered by diesel generators, but new hybrid power systems are becoming a reliable method to incorporate renewable energy while also reducing total system cost. This thesis quantifies the measurable Operational Costs for an experimental hybrid power system in Sierra Leone. Two software programs, Hybrid2 and HOMER, are used during the system design and subsequent analysis. Experimental data from the installed system is used to validate the two programs and to quantify the savings created by each component within the hybrid system. This thesis bridges the gap between design optimization studies that frequently lack subsequent validation and experimental hybrid system performance studies.

Optimization of Simplex Atomizer Inlet Port Configuration through Computational Fluid Dynamics and Experimental Study for Aero-Gas Turbine Applications

NASA Astrophysics Data System (ADS)

Marudhappan, Raja; Chandrasekhar, Udayagiri; Hemachandra Reddy, Koni

2017-10-01

The design of plain orifice simplex atomizer for use in the annular combustion system of 1100 kW turbo shaft engine is optimized. The discrete flow field of jet fuel inside the swirl chamber of the atomizer and up to 1.0 mm downstream of the atomizer exit are simulated using commercial Computational Fluid Dynamics (CFD) software. The Euler-Euler multiphase model is used to solve two sets of momentum equations for liquid and gaseous phases and the volume fraction of each phase is tracked throughout the computational domain. The atomizer design is optimized after performing several 2D axis symmetric analyses with swirl and the optimized inlet port design parameters are used for 3D simulation. The Volume Of Fluid (VOF) multiphase model is used in the simulation. The orifice exit diameter is 0.6 mm. The atomizer is fabricated with the optimized geometric parameters. The performance of the atomizer is tested in the laboratory. The experimental observations are compared with the results obtained from 2D and 3D CFD simulations. The simulated velocity components, pressure field, streamlines and air core dynamics along the atomizer axis are compared to previous research works and found satisfactory. The work has led to a novel approach in the design of pressure swirl atomizer.

Modeling and multi-response optimization of pervaporation of organic aqueous solutions using desirability function approach.

PubMed

Cojocaru, C; Khayet, M; Zakrzewska-Trznadel, G; Jaworska, A

2009-08-15

The factorial design of experiments and desirability function approach has been applied for multi-response optimization in pervaporation separation process. Two organic aqueous solutions were considered as model mixtures, water/acetonitrile and water/ethanol mixtures. Two responses have been employed in multi-response optimization of pervaporation, total permeate flux and organic selectivity. The effects of three experimental factors (feed temperature, initial concentration of organic compound in feed solution, and downstream pressure) on the pervaporation responses have been investigated. The experiments were performed according to a 2(3) full factorial experimental design. The factorial models have been obtained from experimental design and validated statistically by analysis of variance (ANOVA). The spatial representations of the response functions were drawn together with the corresponding contour line plots. Factorial models have been used to develop the overall desirability function. In addition, the overlap contour plots were presented to identify the desirability zone and to determine the optimum point. The optimal operating conditions were found to be, in the case of water/acetonitrile mixture, a feed temperature of 55 degrees C, an initial concentration of 6.58% and a downstream pressure of 13.99 kPa, while for water/ethanol mixture a feed temperature of 55 degrees C, an initial concentration of 4.53% and a downstream pressure of 9.57 kPa. Under such optimum conditions it was observed experimentally an improvement of both the total permeate flux and selectivity.

Optimization of Pressurized Liquid Extraction of Three Major Acetophenones from Cynanchum bungei Using a Box-Behnken Design

PubMed Central

Li, Wei; Zhao, Li-Chun; Sun, Yin-Shi; Lei, Feng-Jie; Wang, Zi; Gui, Xiong-Bin; Wang, Hui

2012-01-01

In this work, pressurized liquid extraction (PLE) of three acetophenones (4-hydroxyacetophenone, baishouwubenzophenone, and 2,4-dihydroxyacetophenone) from Cynanchum bungei (ACB) were investigated. The optimal conditions for extraction of ACB were obtained using a Box-Behnken design, consisting of 17 experimental points, as follows: Ethanol (100%) as the extraction solvent at a temperature of 120 °C and an extraction pressure of 1500 psi, using one extraction cycle with a static extraction time of 17 min. The extracted samples were analyzed by high-performance liquid chromatography using an UV detector. Under this optimal condition, the experimental values agreed with the predicted values by analysis of variance. The ACB extraction yield with optimal PLE was higher than that obtained by soxhlet extraction and heat-reflux extraction methods. The results suggest that the PLE method provides a good alternative for acetophenone extraction. PMID:23203079

Recent advances in stellarator optimization

DOE PAGES

Gates, D. A.; Boozer, A. H.; Brown, T.; ...

2017-10-27

Computational optimization has revolutionized the field of stellarator design. To date, optimizations have focused primarily on optimization of neoclassical confinement and ideal MHD stability, although limited optimization of other parameters has also been performed. Here, we outline a select set of new concepts for stellarator optimization that, when taken as a group, present a significant step forward in the stellarator concept. One of the criticisms that has been leveled at existing methods of design is the complexity of the resultant field coils. Recently, a new coil optimization code—COILOPT++, which uses a spline instead of a Fourier representation of the coils,—wasmore » written and included in the STELLOPT suite of codes. The advantage of this method is that it allows the addition of real space constraints on the locations of the coils. The code has been tested by generating coil designs for optimized quasi-axisymmetric stellarator plasma configurations of different aspect ratios. As an initial exercise, a constraint that the windings be vertical was placed on large major radius half of the non-planar coils. Further constraints were also imposed that guaranteed that sector blanket modules could be removed from between the coils, enabling a sector maintenance scheme. Results of this exercise will be presented. New ideas on methods for the optimization of turbulent transport have garnered much attention since these methods have led to design concepts that are calculated to have reduced turbulent heat loss. We have explored possibilities for generating an experimental database to test whether the reduction in transport that is predicted is consistent with experimental observations. Thus, a series of equilibria that can be made in the now latent QUASAR experiment have been identified that will test the predicted transport scalings. Fast particle confinement studies aimed at developing a generalized optimization algorithm are also discussed. A new algorithm developed for the design of the scraper element on W7-X is presented along with ideas for automating the optimization approach.« less

Recent advances in stellarator optimization

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

Gates, D. A.; Boozer, A. H.; Brown, T.

Computational optimization has revolutionized the field of stellarator design. To date, optimizations have focused primarily on optimization of neoclassical confinement and ideal MHD stability, although limited optimization of other parameters has also been performed. Here, we outline a select set of new concepts for stellarator optimization that, when taken as a group, present a significant step forward in the stellarator concept. One of the criticisms that has been leveled at existing methods of design is the complexity of the resultant field coils. Recently, a new coil optimization code—COILOPT++, which uses a spline instead of a Fourier representation of the coils,—wasmore » written and included in the STELLOPT suite of codes. The advantage of this method is that it allows the addition of real space constraints on the locations of the coils. The code has been tested by generating coil designs for optimized quasi-axisymmetric stellarator plasma configurations of different aspect ratios. As an initial exercise, a constraint that the windings be vertical was placed on large major radius half of the non-planar coils. Further constraints were also imposed that guaranteed that sector blanket modules could be removed from between the coils, enabling a sector maintenance scheme. Results of this exercise will be presented. New ideas on methods for the optimization of turbulent transport have garnered much attention since these methods have led to design concepts that are calculated to have reduced turbulent heat loss. We have explored possibilities for generating an experimental database to test whether the reduction in transport that is predicted is consistent with experimental observations. Thus, a series of equilibria that can be made in the now latent QUASAR experiment have been identified that will test the predicted transport scalings. Fast particle confinement studies aimed at developing a generalized optimization algorithm are also discussed. A new algorithm developed for the design of the scraper element on W7-X is presented along with ideas for automating the optimization approach.« less

Actinobacteria consortium as an efficient biotechnological tool for mixed polluted soil reclamation: Experimental factorial design for bioremediation process optimization.

PubMed

Aparicio, Juan Daniel; Raimondo, Enzo Emanuel; Gil, Raúl Andrés; Benimeli, Claudia Susana; Polti, Marta Alejandra

2018-01-15

The objective of the present work was to establish optimal biological and physicochemical parameters in order to remove simultaneously lindane and Cr(VI) at high and/or low pollutants concentrations from the soil by an actinobacteria consortium formed by Streptomyces sp. M7, MC1, A5, and Amycolatopsis tucumanensis AB0. Also, the final aim was to treat real soils contaminated with Cr(VI) and/or lindane from the Northwest of Argentina employing the optimal biological and physicochemical conditions. In this sense, after determining the optimal inoculum concentration (2gkg -1 ), an experimental design model with four factors (temperature, moisture, initial concentration of Cr(VI) and lindane) was employed for predicting the system behavior during bioremediation process. According to response optimizer, the optimal moisture level was 30% for all bioremediation processes. However, the optimal temperature was different for each situation: for low initial concentrations of both pollutants, the optimal temperature was 25°C; for low initial concentrations of Cr(VI) and high initial concentrations of lindane, the optimal temperature was 30°C; and for high initial concentrations of Cr(VI), the optimal temperature was 35°C. In order to confirm the model adequacy and the validity of the optimization procedure, experiments were performed in six real contaminated soils samples. The defined actinobacteria consortium reduced the contaminants concentrations in five of the six samples, by working at laboratory scale and employing the optimal conditions obtained through the factorial design. Copyright © 2017 Elsevier B.V. All rights reserved.

Quantum computing gates via optimal control

NASA Astrophysics Data System (ADS)

Atia, Yosi; Elias, Yuval; Mor, Tal; Weinstein, Yossi

2014-10-01

We demonstrate the use of optimal control to design two entropy-manipulating quantum gates which are more complex than the corresponding, commonly used, gates, such as CNOT and Toffoli (CCNOT): A two-qubit gate called polarization exchange (PE) and a three-qubit gate called polarization compression (COMP) were designed using GRAPE, an optimal control algorithm. Both gates were designed for a three-spin system. Our design provided efficient and robust nuclear magnetic resonance (NMR) radio frequency (RF) pulses for 13C2-trichloroethylene (TCE), our chosen three-spin system. We then experimentally applied these two quantum gates onto TCE at the NMR lab. Such design of these gates and others could be relevant for near-future applications of quantum computing devices.

A Model for Designing Adaptive Laboratory Evolution Experiments.

PubMed

LaCroix, Ryan A; Palsson, Bernhard O; Feist, Adam M

2017-04-15

The occurrence of mutations is a cornerstone of the evolutionary theory of adaptation, capitalizing on the rare chance that a mutation confers a fitness benefit. Natural selection is increasingly being leveraged in laboratory settings for industrial and basic science applications. Despite increasing deployment, there are no standardized procedures available for designing and performing adaptive laboratory evolution (ALE) experiments. Thus, there is a need to optimize the experimental design, specifically for determining when to consider an experiment complete and for balancing outcomes with available resources (i.e., laboratory supplies, personnel, and time). To design and to better understand ALE experiments, a simulator, ALEsim, was developed, validated, and applied to the optimization of ALE experiments. The effects of various passage sizes were experimentally determined and subsequently evaluated with ALEsim, to explain differences in experimental outcomes. Furthermore, a beneficial mutation rate of 10 -6.9 to 10 -8.4 mutations per cell division was derived. A retrospective analysis of ALE experiments revealed that passage sizes typically employed in serial passage batch culture ALE experiments led to inefficient production and fixation of beneficial mutations. ALEsim and the results described here will aid in the design of ALE experiments to fit the exact needs of a project while taking into account the resources required and will lower the barriers to entry for this experimental technique. IMPORTANCE ALE is a widely used scientific technique to increase scientific understanding, as well as to create industrially relevant organisms. The manner in which ALE experiments are conducted is highly manual and uniform, with little optimization for efficiency. Such inefficiencies result in suboptimal experiments that can take multiple months to complete. With the availability of automation and computer simulations, we can now perform these experiments in an optimized fashion and can design experiments to generate greater fitness in an accelerated time frame, thereby pushing the limits of what adaptive laboratory evolution can achieve. Copyright © 2017 American Society for Microbiology.

Comparison of optimal design methods in inverse problems

NASA Astrophysics Data System (ADS)

Banks, H. T.; Holm, K.; Kappel, F.

2011-07-01

Typical optimal design methods for inverse or parameter estimation problems are designed to choose optimal sampling distributions through minimization of a specific cost function related to the resulting error in parameter estimates. It is hoped that the inverse problem will produce parameter estimates with increased accuracy using data collected according to the optimal sampling distribution. Here we formulate the classical optimal design problem in the context of general optimization problems over distributions of sampling times. We present a new Prohorov metric-based theoretical framework that permits one to treat succinctly and rigorously any optimal design criteria based on the Fisher information matrix. A fundamental approximation theory is also included in this framework. A new optimal design, SE-optimal design (standard error optimal design), is then introduced in the context of this framework. We compare this new design criterion with the more traditional D-optimal and E-optimal designs. The optimal sampling distributions from each design are used to compute and compare standard errors; the standard errors for parameters are computed using asymptotic theory or bootstrapping and the optimal mesh. We use three examples to illustrate ideas: the Verhulst-Pearl logistic population model (Banks H T and Tran H T 2009 Mathematical and Experimental Modeling of Physical and Biological Processes (Boca Raton, FL: Chapman and Hall/CRC)), the standard harmonic oscillator model (Banks H T and Tran H T 2009) and a popular glucose regulation model (Bergman R N, Ider Y Z, Bowden C R and Cobelli C 1979 Am. J. Physiol. 236 E667-77 De Gaetano A and Arino O 2000 J. Math. Biol. 40 136-68 Toffolo G, Bergman R N, Finegood D T, Bowden C R and Cobelli C 1980 Diabetes 29 979-90).

Optimizing methods and dodging pitfalls in microbiome research.

PubMed

Kim, Dorothy; Hofstaedter, Casey E; Zhao, Chunyu; Mattei, Lisa; Tanes, Ceylan; Clarke, Erik; Lauder, Abigail; Sherrill-Mix, Scott; Chehoud, Christel; Kelsen, Judith; Conrad, Máire; Collman, Ronald G; Baldassano, Robert; Bushman, Frederic D; Bittinger, Kyle

2017-05-05

Research on the human microbiome has yielded numerous insights into health and disease, but also has resulted in a wealth of experimental artifacts. Here, we present suggestions for optimizing experimental design and avoiding known pitfalls, organized in the typical order in which studies are carried out. We first review best practices in experimental design and introduce common confounders such as age, diet, antibiotic use, pet ownership, longitudinal instability, and microbial sharing during cohousing in animal studies. Typically, samples will need to be stored, so we provide data on best practices for several sample types. We then discuss design and analysis of positive and negative controls, which should always be run with experimental samples. We introduce a convenient set of non-biological DNA sequences that can be useful as positive controls for high-volume analysis. Careful analysis of negative and positive controls is particularly important in studies of samples with low microbial biomass, where contamination can comprise most or all of a sample. Lastly, we summarize approaches to enhancing experimental robustness by careful control of multiple comparisons and to comparing discovery and validation cohorts. We hope the experimental tactics summarized here will help researchers in this exciting field advance their studies efficiently while avoiding errors.

Review: Optimization methods for groundwater modeling and management

NASA Astrophysics Data System (ADS)

Yeh, William W.-G.

2015-09-01

Optimization methods have been used in groundwater modeling as well as for the planning and management of groundwater systems. This paper reviews and evaluates the various optimization methods that have been used for solving the inverse problem of parameter identification (estimation), experimental design, and groundwater planning and management. Various model selection criteria are discussed, as well as criteria used for model discrimination. The inverse problem of parameter identification concerns the optimal determination of model parameters using water-level observations. In general, the optimal experimental design seeks to find sampling strategies for the purpose of estimating the unknown model parameters. A typical objective of optimal conjunctive-use planning of surface water and groundwater is to minimize the operational costs of meeting water demand. The optimization methods include mathematical programming techniques such as linear programming, quadratic programming, dynamic programming, stochastic programming, nonlinear programming, and the global search algorithms such as genetic algorithms, simulated annealing, and tabu search. Emphasis is placed on groundwater flow problems as opposed to contaminant transport problems. A typical two-dimensional groundwater flow problem is used to explain the basic formulations and algorithms that have been used to solve the formulated optimization problems.

Design of clinical trials involving multiple hypothesis tests with a common control.

PubMed

Schou, I Manjula; Marschner, Ian C

2017-07-01

Randomized clinical trials comparing several treatments to a common control are often reported in the medical literature. For example, multiple experimental treatments may be compared with placebo, or in combination therapy trials, a combination therapy may be compared with each of its constituent monotherapies. Such trials are typically designed using a balanced approach in which equal numbers of individuals are randomized to each arm, however, this can result in an inefficient use of resources. We provide a unified framework and new theoretical results for optimal design of such single-control multiple-comparator studies. We consider variance optimal designs based on D-, A-, and E-optimality criteria, using a general model that allows for heteroscedasticity and a range of effect measures that include both continuous and binary outcomes. We demonstrate the sensitivity of these designs to the type of optimality criterion by showing that the optimal allocation ratios are systematically ordered according to the optimality criterion. Given this sensitivity to the optimality criterion, we argue that power optimality is a more suitable approach when designing clinical trials where testing is the objective. Weighted variance optimal designs are also discussed, which, like power optimal designs, allow the treatment difference to play a major role in determining allocation ratios. We illustrate our methods using two real clinical trial examples taken from the medical literature. Some recommendations on the use of optimal designs in single-control multiple-comparator trials are also provided. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Optimization of Biosorptive Removal of Dye from Aqueous System by Cone Shell of Calabrian Pine

PubMed Central

Deniz, Fatih

2014-01-01

The biosorption performance of raw cone shell of Calabrian pine for C.I. Basic Red 46 as a model azo dye from aqueous system was optimized using Taguchi experimental design methodology. L9 (33) orthogonal array was used to optimize the dye biosorption by the pine cone shell. The selected factors and their levels were biosorbent particle size, dye concentration, and contact time. The predicted dye biosorption capacity for the pine cone shell from Taguchi design was obtained as 71.770 mg g−1 under optimized biosorption conditions. This experimental design provided reasonable predictive performance of dye biosorption by the biosorbent (R 2: 0.9961). Langmuir model fitted better to the biosorption equilibrium data than Freundlich model. This displayed the monolayer coverage of dye molecules on the biosorbent surface. Dubinin-Radushkevich model and the standard Gibbs free energy change proposed physical biosorption for predominant mechanism. The logistic function presented the best fit to the data of biosorption kinetics. The kinetic parameters reflecting biosorption performance were also evaluated. The optimization study revealed that the pine cone shell can be an effective and economically feasible biosorbent for the removal of dye. PMID:25405213

Optimal designs for copula models

PubMed Central

Perrone, E.; Müller, W.G.

2016-01-01

Copula modelling has in the past decade become a standard tool in many areas of applied statistics. However, a largely neglected aspect concerns the design of related experiments. Particularly the issue of whether the estimation of copula parameters can be enhanced by optimizing experimental conditions and how robust all the parameter estimates for the model are with respect to the type of copula employed. In this paper an equivalence theorem for (bivariate) copula models is provided that allows formulation of efficient design algorithms and quick checks of whether designs are optimal or at least efficient. Some examples illustrate that in practical situations considerable gains in design efficiency can be achieved. A natural comparison between different copula models with respect to design efficiency is provided as well. PMID:27453616

Experimental design in chemistry: A tutorial.

PubMed

Leardi, Riccardo

2009-10-12

In this tutorial the main concepts and applications of experimental design in chemistry will be explained. Unfortunately, nowadays experimental design is not as known and applied as it should be, and many papers can be found in which the "optimization" of a procedure is performed one variable at a time. Goal of this paper is to show the real advantages in terms of reduced experimental effort and of increased quality of information that can be obtained if this approach is followed. To do that, three real examples will be shown. Rather than on the mathematical aspects, this paper will focus on the mental attitude required by experimental design. The readers being interested to deepen their knowledge of the mathematical and algorithmical part can find very good books and tutorials in the references [G.E.P. Box, W.G. Hunter, J.S. Hunter, Statistics for Experimenters: An Introduction to Design, Data Analysis, and Model Building, John Wiley & Sons, New York, 1978; R. Brereton, Chemometrics: Data Analysis for the Laboratory and Chemical Plant, John Wiley & Sons, New York, 1978; R. Carlson, J.E. Carlson, Design and Optimization in Organic Synthesis: Second Revised and Enlarged Edition, in: Data Handling in Science and Technology, vol. 24, Elsevier, Amsterdam, 2005; J.A. Cornell, Experiments with Mixtures: Designs, Models and the Analysis of Mixture Data, in: Series in Probability and Statistics, John Wiley & Sons, New York, 1991; R.E. Bruns, I.S. Scarminio, B. de Barros Neto, Statistical Design-Chemometrics, in: Data Handling in Science and Technology, vol. 25, Elsevier, Amsterdam, 2006; D.C. Montgomery, Design and Analysis of Experiments, 7th edition, John Wiley & Sons, Inc., 2009; T. Lundstedt, E. Seifert, L. Abramo, B. Thelin, A. Nyström, J. Pettersen, R. Bergman, Chemolab 42 (1998) 3; Y. Vander Heyden, LC-GC Europe 19 (9) (2006) 469].

Computational Optimization of a Natural Laminar Flow Experimental Wing Glove

NASA Technical Reports Server (NTRS)

Hartshom, Fletcher

2012-01-01

Computational optimization of a natural laminar flow experimental wing glove that is mounted on a business jet is presented and discussed. The process of designing a laminar flow wing glove starts with creating a two-dimensional optimized airfoil and then lofting it into a three-dimensional wing glove section. The airfoil design process does not consider the three dimensional flow effects such as cross flow due wing sweep as well as engine and body interference. Therefore, once an initial glove geometry is created from the airfoil, the three dimensional wing glove has to be optimized to ensure that the desired extent of laminar flow is maintained over the entire glove. TRANAIR, a non-linear full potential solver with a coupled boundary layer code was used as the main tool in the design and optimization process of the three-dimensional glove shape. The optimization process uses the Class-Shape-Transformation method to perturb the geometry with geometric constraints that allow for a 2-in clearance from the main wing. The three-dimensional glove shape was optimized with the objective of having a spanwise uniform pressure distribution that matches the optimized two-dimensional pressure distribution as closely as possible. Results show that with the appropriate inputs, the optimizer is able to match the two dimensional pressure distributions practically across the entire span of the wing glove. This allows for the experiment to have a much higher probability of having a large extent of natural laminar flow in flight.

A new efficient mixture screening design for optimization of media.

PubMed

Rispoli, Fred; Shah, Vishal

2009-01-01

Screening ingredients for the optimization of media is an important first step to reduce the many potential ingredients down to the vital few components. In this study, we propose a new method of screening for mixture experiments called the centroid screening design. Comparison of the proposed design with Plackett-Burman, fractional factorial, simplex lattice design, and modified mixture design shows that the centroid screening design is the most efficient of all the designs in terms of the small number of experimental runs needed and for detecting high-order interaction among ingredients. (c) 2009 American Institute of Chemical Engineers Biotechnol. Prog., 2009.

Optimization of composite coagulant made from polyferric chloride and tapioca starch in landfill leachate treatment

NASA Astrophysics Data System (ADS)

Shaylinda, M. Z. N.; Hamidi, A. A.; Mohd, N. A.; Ariffin, A.; Irvan, D.; Hazreek, Z. A. M.; Nizam, Z. M.

2018-04-01

In this research, the performance of polyferric chloride and tapioca flour as composite coagulants for partially stabilized leachate was investigated. Response surface methodology (RSM) was used to optimize the coagulation and flocculation process of partially stabilized leachate. Central composite design a standard design tool in RSM was applied to evaluate the interactions and effects of dose and pH. Dose 0.2 g/L Fe and pH 4.71 were the optimum value suggested by RSM. Experimental test based on the optimum condition, resulted in 95.9%, 94.6% and 50.4% of SS, color and COD removals, respectively. The percentage difference recorded between experimental and model responses was <5%. Therefore, it can be concluded that RSM was an appropriate optimization tool for coagulation and flocculation process.

Optimization of Nd: YAG Laser Marking of Alumina Ceramic Using RSM And ANN

NASA Astrophysics Data System (ADS)

Peter, Josephine; Doloi, B.; Bhattacharyya, B.

2011-01-01

The present research papers deals with the artificial neural network (ANN) and the response surface methodology (RSM) based mathematical modeling and also an optimization analysis on marking characteristics on alumina ceramic. The experiments have been planned and carried out based on Design of Experiment (DOE). It also analyses the influence of the major laser marking process parameters and the optimal combination of laser marking process parametric setting has been obtained. The output of the RSM optimal data is validated through experimentation and ANN predictive model. A good agreement is observed between the results based on ANN predictive model and actual experimental observations.

Experimental Investigation of a Point Design Optimized Arrow Wing HSCT Configuration

NASA Technical Reports Server (NTRS)

Narducci, Robert P.; Sundaram, P.; Agrawal, Shreekant; Cheung, S.; Arslan, A. E.; Martin, G. L.

1999-01-01

The M2.4-7A Arrow Wing HSCT configuration was optimized for straight and level cruise at a Mach number of 2.4 and a lift coefficient of 0.10. A quasi-Newton optimization scheme maximized the lift-to-drag ratio (by minimizing drag-to-lift) using Euler solutions from FL067 to estimate the lift and drag forces. A 1.675% wind-tunnel model of the Opt5 HSCT configuration was built to validate the design methodology. Experimental data gathered at the NASA Langley Unitary Plan Wind Tunnel (UPWT) section #2 facility verified CFL3D Euler and Navier-Stokes predictions of the Opt5 performance at the design point. In turn, CFL3D confirmed the improvement in the lift-to-drag ratio obtained during the optimization, thus validating the design procedure. A data base at off-design conditions was obtained during three wind-tunnel tests. The entry into NASA Langley UPWT section #2 obtained data at a free stream Mach number, M(sub infinity), of 2.55 as well as the design Mach number, M(sub infinity)=2.4. Data from a Mach number range of 1.8 to 2.4 was taken at UPWT section #1. Transonic and low supersonic Mach numbers, M(sub infinity)=0.6 to 1.2, was gathered at the NASA Langley 16 ft. Transonic Wind Tunnel (TWT). In addition to good agreement between CFD and experimental data, highlights from the wind-tunnel tests include a trip dot study suggesting a linear relationship between trip dot drag and Mach number, an aeroelastic study that measured the outboard wing deflection and twist, and a flap scheduling study that identifies the possibility of only one leading-edge and trailing-edge flap setting for transonic cruise and another for low supersonic acceleration.

Application of an experimental design for the optimization and validation of a new HPLC method for the determination of vancomycin in an extemporaneous ophthalmic solution.

PubMed

Enrique, Montse; García-Montoya, Encarna; Miñarro, Montserrat; Orriols, Anna; Ticó, Joseph Ramon; Suñé-Negre, Joseph Maria; Pérez-Lozano, Pilar

2008-10-01

An experimental design has been used to develop and optimize a new high-performance liquid chromatographic (HPLC) method for the determination of Vancomycin in an extemporaneous ophthalmic solution. After the preliminary studies and literature review, the optimized method was carried out on a second generation of a C18 reverse-phase column (Luna 150 x 4.6 mm i.d., 5 microm particle size) and using methanol as organic phase, a less toxic solvent than acetonitrile, described in the extended literature. The experimental design consisted of a Placket-Burman design where six different variables were studied (flow rate, mL/min; temperature, degrees C; pH mobile phase; % buffer solution; wavelength; and injection volume) to obtain the best suitability parameters (Capacity factor-K', tailing factor, resolution, and theoretical plates). After the optimization of the chromatographic conditions and statistical treatment of the obtained results, the final method uses a mixture of a buffer solution of water-phosphoric acid (85%) (99.83:0.17, v/v) adjusted to pH 3.0 using triethylamine and mixed with methanol (87:13, v/v). The separation is achieved using a flow rate of 1.0 mL/min at 35 degrees C. The UV detector was operated at 280 nm. The validation study carried out, demonstrates the viability of the method, obtaining a good selectivity, linearity, precision, accuracy, and sensitivity.

Experimental design and optimization of leaching process for recovery of valuable chemical elements (U, La, V, Mo, Yb and Th) from low-grade uranium ore.

PubMed

Zakrzewska-Koltuniewicz, Grażyna; Herdzik-Koniecko, Irena; Cojocaru, Corneliu; Chajduk, Ewelina

2014-06-30

The paper deals with experimental design and optimization of leaching process of uranium and associated metals from low-grade, Polish ores. The chemical elements of interest for extraction from the ore were U, La, V, Mo, Yb and Th. Sulphuric acid has been used as leaching reagent. Based on the design of experiments the second-order regression models have been constructed to approximate the leaching efficiency of elements. The graphical illustrations using 3-D surface plots have been employed in order to identify the main, quadratic and interaction effects of the factors. The multi-objective optimization method based on desirability approach has been applied in this study. The optimum condition have been determined as P=5 bar, T=120 °C and t=90 min. Under these optimal conditions, the overall extraction performance is 81.43% (for U), 64.24% (for La), 98.38% (for V), 43.69% (for Yb) and 76.89% (for Mo) and 97.00% (for Th). Copyright © 2014 Elsevier B.V. All rights reserved.

Selecting optimal structure of burners for tubular cylindrical furnaces by the mathematical experiment planning method

NASA Astrophysics Data System (ADS)

Katin, Viktor; Kosygin, Vladimir; Akhtiamov, Midkhat

2017-10-01

This paper substantiates the method of mathematical planning for experimental research in the process of selecting the most efficient types of burning devices for tubular refinery furnaces of vertical-cylindrical design. This paper provides detailed consideration of an experimental plan of a 4×4 Latin square type when studying the impact of three factors with four levels of variance. On the basis of the experimental research we have developed practical recommendations on the employment of optimal burners for two-step fuel combustion.

Optimal cooperative control synthesis of active displays

NASA Technical Reports Server (NTRS)

Garg, S.; Schmidt, D. K.

1985-01-01

A technique is developed that is intended to provide a systematic approach to synthesizing display augmentation for optimal manual control in complex, closed-loop tasks. A cooperative control synthesis technique, previously developed to design pilot-optimal control augmentation for the plant, is extended to incorporate the simultaneous design of performance enhancing displays. The technique utilizes an optimal control model of the man in the loop. It is applied to the design of a quickening control law for a display and a simple K/s(2) plant, and then to an F-15 type aircraft in a multi-channel task. Utilizing the closed loop modeling and analysis procedures, the results from the display design algorithm are evaluated and an analytical validation is performed. Experimental validation is recommended for future efforts.

Topology Optimization of Lightweight Lattice Structural Composites Inspired by Cuttlefish Bone

NASA Astrophysics Data System (ADS)

Hu, Zhong; Gadipudi, Varun Kumar; Salem, David R.

2018-03-01

Lattice structural composites are of great interest to various industries where lightweight multifunctionality is important, especially aerospace. However, strong coupling among the composition, microstructure, porous topology, and fabrication of such materials impedes conventional trial-and-error experimental development. In this work, a discontinuous carbon fiber reinforced polymer matrix composite was adopted for structural design. A reliable and robust design approach for developing lightweight multifunctional lattice structural composites was proposed, inspired by biomimetics and based on topology optimization. Three-dimensional periodic lattice blocks were initially designed, inspired by the cuttlefish bone microstructure. The topologies of the three-dimensional periodic blocks were further optimized by computer modeling, and the mechanical properties of the topology optimized lightweight lattice structures were characterized by computer modeling. The lattice structures with optimal performance were identified.

Optimization of photocatalytic degradation of methyl blue using silver ion doped titanium dioxide by combination of experimental design and response surface approach.

PubMed

Sahoo, C; Gupta, A K

2012-05-15

Photocatalytic degradation of methyl blue (MYB) was studied using Ag(+) doped TiO(2) under UV irradiation in a batch reactor. Catalytic dose, initial concentration of dye and pH of the reaction mixture were found to influence the degradation process most. The degradation was found to be effective in the range catalytic dose (0.5-1.5g/L), initial dye concentration (25-100ppm) and pH of reaction mixture (5-9). Using the three factors three levels Box-Behnken design of experiment technique 15 sets of experiments were designed considering the effective ranges of the influential parameters. The results of the experiments were fitted to two quadratic polynomial models developed using response surface methodology (RSM), representing functional relationship between the decolorization and mineralization of MYB and the experimental parameters. Design Expert software version 8.0.6.1 was used to optimize the effects of the experimental parameters on the responses. The optimum values of the parameters were dose of Ag(+) doped TiO(2) 0.99g/L, initial concentration of MYB 57.68ppm and pH of reaction mixture 7.76. Under the optimal condition the predicted decolorization and mineralization rate of MYB were 95.97% and 80.33%, respectively. Regression analysis with R(2) values >0.99 showed goodness of fit of the experimental results with predicted values. Copyright © 2012 Elsevier B.V. All rights reserved.

Optimization and Development of a Human Scent Collection Method

DTIC Science & Technology

2007-06-04

19. Schoon, G. A. A., Scent Identification Lineups by Dogs (Canis familiaris): Experimental Design and Forensic Application. Applied Animal...Parker, Lloyd R., Morgan, Stephen L., Deming, Stanley N., Sequential Simplex Optimization. Chemometrics Series, ed. S.D. Brown. 1991, Boca Raton

Optimizing adaptive design for Phase 2 dose-finding trials incorporating long-term success and financial considerations: A case study for neuropathic pain.

PubMed

Gao, Jingjing; Nangia, Narinder; Jia, Jia; Bolognese, James; Bhattacharyya, Jaydeep; Patel, Nitin

2017-06-01

In this paper, we propose an adaptive randomization design for Phase 2 dose-finding trials to optimize Net Present Value (NPV) for an experimental drug. We replace the traditional fixed sample size design (Patel, et al., 2012) by this new design to see if NPV from the original paper can be improved. Comparison of the proposed design to the previous design is made via simulations using a hypothetical example based on a Diabetic Neuropathic Pain Study. Copyright © 2017 Elsevier Inc. All rights reserved.

Quality by design: optimization of a freeze-drying cycle via design space in case of heterogeneous drying behavior and influence of the freezing protocol.

PubMed

Pisano, Roberto; Fissore, Davide; Barresi, Antonello A; Brayard, Philippe; Chouvenc, Pierre; Woinet, Bertrand

2013-02-01

This paper shows how to optimize the primary drying phase, for both product quality and drying time, of a parenteral formulation via design space. A non-steady state model, parameterized with experimentally determined heat and mass transfer coefficients, is used to define the design space when the heat transfer coefficient varies with the position of the vial in the array. The calculations recognize both equipment and product constraints, and also take into account model parameter uncertainty. Examples are given of cycles designed for the same formulation, but varying the freezing conditions and the freeze-dryer scale. These are then compared in terms of drying time. Furthermore, the impact of inter-vial variability on design space, and therefore on the optimized cycle, is addressed. With this regard, a simplified method is presented for the cycle design, which reduces the experimental effort required for the system qualification. The use of mathematical modeling is demonstrated to be very effective not only for cycle development, but also for solving problem of process transfer. This study showed that inter-vial variability remains significant when vials are loaded on plastic trays, and how inter-vial variability can be taken into account during process design.

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.

Development of a semidefined growth medium for Pedobacter cryoconitis BG5 using statistical experimental design.

PubMed

Ong, Magdalena; Ongkudon, Clarence M; Wong, Clemente Michael Vui Ling

2016-10-02

Pedobacter cryoconitis BG5 are psychrophiles isolated from the cold environment and capable of proliferating and growing well at low temperature regime. Their cellular products have found a broad spectrum of applications, including in food, medicine, and bioremediation. Therefore, it is imperative to develop a high-cell density cultivation strategy coupled with optimized growth medium for P. cryoconitis BG5. To date, there has been no published report on the design and optimization of growth medium for P. cryoconitis, hence the objective of this research project. A preliminary screening of four commercially available media, namely tryptic soy broth, R2A, Luria Bertani broth, and nutrient broth, was conducted to formulate the basal medium. Based on the preliminary screening, tryptone, glucose, NaCl, and K2HPO4 along with three additional nutrients (yeast extract, MgSO4, and NH4Cl) were identified to form the basal medium which was further analyzed by Plackett-Burman experimental design. Central composite experimental design using response surface methodology was adopted to optimize tryptone, yeast extract, and NH4Cl concentrations in the formulated growth medium. Statistical data analysis showed a high regression factor of 0.84 with a predicted optimum optical (600 nm) cell density of 7.5 using 23.7 g/L of tryptone, 8.8 g/L of yeast extract, and 0.7 g/L of NH4Cl. The optimized medium for P. cryoconitis BG5 was tested, and the observed optical density was 7.8. The cost-effectiveness of the optimized medium was determined as 6.25 unit prices per gram of cell produced in a 250-ml Erlenmeyer flask.

Theoretical and experimental investigations on the optimal match between compressor and cold finger of the Stirling-type pulse tube cryocooler

NASA Astrophysics Data System (ADS)

Dang, Haizheng; Tan, Jun; Zhang, Lei

2016-06-01

The match between the pulse tube cold finger (PTCF) and the linear compressor of the Stirling-type pulse tube cryocooler plays a vital role in optimizing the compressor efficiency and in improving the PTCF cooling performance as well. In this paper, the interaction of them has been analyzed in a detailed way to reveal the match mechanism, and systematic investigations on the two-way matching have been conducted. The design method of the PTCF to achieve the optimal matching for the given compressor and the counterpart design method of the compressor to achieve the optimal matching for the given PTCF are put forward. Specific experiments are then carried out to verify the conducted theoretical analyses and modeling. For a given linear compressor, a new in-line PTCF which seeks to achieve the optimal match is simulated, designed and tested. And for a given coaxial PTCF, a new dual-opposed moving-coil linear compressor is also developed to match with it. The simulated and experimental results are compared, and fairly good agreements are found between them in both cases. The matched in-line cooler with the newly-designed PTCF has capacities of 4-11.84 W at 80 K with higher than 17% of Carnot efficiency and the mean motor efficiency of 81.5%, and the matched coaxial cooler with the new-designed compressor can provide 2-5.5 W at 60 K with higher than 9.6% of Carnot efficiency and the mean motor efficiency of 83%, which verify the validity of the theoretical investigations on the optimal match and the proposed design methods.

Optimized design and performance of a shared pump single clad 2 μm TDFA

NASA Astrophysics Data System (ADS)

Tench, Robert E.; Romano, Clément; Delavaux, Jean-Marc

2018-05-01

We report the design, experimental performance, and simulation of a single stage, co- and counter-pumped Tm-doped fiber amplifier (TDFA) in the 2 μm signal wavelength band with an optimized 1567 nm shared pump source. We investigate the dependence of output power, gain, and efficiency on pump coupling ratio and signal wavelength. Small signal gains of >50 dB, an output power of 2 W, and small signal noise figures of <3.5 dB are demonstrated. Simulations of TDFA performance agree well with the experimental data. We also discuss performance tradeoffs with respect to amplifier topology for this simple and efficient TDFA.

Experimental Investigation of a 2D Supercritical Circulation-Control Airfoil Using Particle Image Velocimetry

NASA Technical Reports Server (NTRS)

Jones, Gregory S.; Yao, Chung-Sheng; Allan, Brian G.

2006-01-01

Recent efforts in extreme short takeoff and landing aircraft configurations have renewed the interest in circulation control wing design and optimization. The key to accurately designing and optimizing these configurations rests in the modeling of the complex physics of these flows. This paper will highlight the physics of the stagnation and separation regions on two typical circulation control airfoil sections.

Effects of experimental design on calibration curve precision in routine analysis

PubMed Central

Pimentel, Maria Fernanda; Neto, Benício de Barros; Saldanha, Teresa Cristina B.

1998-01-01

A computational program which compares the effciencies of different experimental designs with those of maximum precision (D-optimized designs) is described. The program produces confidence interval plots for a calibration curve and provides information about the number of standard solutions, concentration levels and suitable concentration ranges to achieve an optimum calibration. Some examples of the application of this novel computational program are given, using both simulated and real data. PMID:18924816

Interface design for CMOS-integrated Electrochemical Impedance Spectroscopy (EIS) biosensors.

PubMed

Manickam, Arun; Johnson, Christopher Andrew; Kavusi, Sam; Hassibi, Arjang

2012-10-29

Electrochemical Impedance Spectroscopy (EIS) is a powerful electrochemical technique to detect biomolecules. EIS has the potential of carrying out label-free and real-time detection, and in addition, can be easily implemented using electronic integrated circuits (ICs) that are built through standard semiconductor fabrication processes. This paper focuses on the various design and optimization aspects of EIS ICs, particularly the bio-to-semiconductor interface design. We discuss, in detail, considerations such as the choice of the electrode surface in view of IC manufacturing, surface linkers, and development of optimal bio-molecular detection protocols. We also report experimental results, using both macro- and micro-electrodes to demonstrate the design trade-offs and ultimately validate our optimization procedures.

Experimental Design for Estimating Unknown Hydraulic Conductivity in a Confined Aquifer using a Genetic Algorithm and a Reduced Order Model

NASA Astrophysics Data System (ADS)

Ushijima, T.; Yeh, W.

2013-12-01

An optimal experimental design algorithm is developed to select locations for a network of observation wells that provides the maximum information about unknown hydraulic conductivity in a confined, anisotropic aquifer. The design employs a maximal information criterion that chooses, among competing designs, the design that maximizes the sum of squared sensitivities while conforming to specified design constraints. Because that the formulated problem is non-convex and contains integer variables (necessitating a combinatorial search), for a realistically-scaled model, the problem may be difficult, if not impossible, to solve through traditional mathematical programming techniques. Genetic Algorithms (GAs) are designed to search out the global optimum; however because a GA requires a large number of calls to a groundwater model, the formulated optimization problem may still be infeasible to solve. To overcome this, Proper Orthogonal Decomposition (POD) is applied to the groundwater model to reduce its dimension. The information matrix in the full model space can then be searched without solving the full model.

Application of optimal control theory to the design of broadband excitation pulses for high-resolution NMR.

PubMed

Skinner, Thomas E; Reiss, Timo O; Luy, Burkhard; Khaneja, Navin; Glaser, Steffen J

2003-07-01

Optimal control theory is considered as a methodology for pulse sequence design in NMR. It provides the flexibility for systematically imposing desirable constraints on spin system evolution and therefore has a wealth of applications. We have chosen an elementary example to illustrate the capabilities of the optimal control formalism: broadband, constant phase excitation which tolerates miscalibration of RF power and variations in RF homogeneity relevant for standard high-resolution probes. The chosen design criteria were transformation of I(z)-->I(x) over resonance offsets of +/- 20 kHz and RF variability of +/-5%, with a pulse length of 2 ms. Simulations of the resulting pulse transform I(z)-->0.995I(x) over the target ranges in resonance offset and RF variability. Acceptably uniform excitation is obtained over a much larger range of RF variability (approximately 45%) than the strict design limits. The pulse performs well in simulations that include homonuclear and heteronuclear J-couplings. Experimental spectra obtained from 100% 13C-labeled lysine show only minimal coupling effects, in excellent agreement with the simulations. By increasing pulse power and reducing pulse length, we demonstrate experimental excitation of 1H over +/-32 kHz, with phase variations in the spectra <8 degrees and peak amplitudes >93% of maximum. Further improvements in broadband excitation by optimized pulses (BEBOP) may be possible by applying more sophisticated implementations of the optimal control formalism.

Heuristic optimization of a continuous flow point-of-use UV-LED disinfection reactor using computational fluid dynamics.

PubMed

Jenny, Richard M; Jasper, Micah N; Simmons, Otto D; Shatalov, Max; Ducoste, Joel J

2015-10-15

Alternative disinfection sources such as ultraviolet light (UV) are being pursued to inactivate pathogenic microorganisms such as Cryptosporidium and Giardia, while simultaneously reducing the risk of exposure to carcinogenic disinfection by-products (DBPs) in drinking water. UV-LEDs offer a UV disinfecting source that do not contain mercury, have the potential for long lifetimes, are robust, and have a high degree of design flexibility. However, the increased flexibility in design options will add a substantial level of complexity when developing a UV-LED reactor, particularly with regards to reactor shape, size, spatial orientation of light, and germicidal emission wavelength. Anticipating that LEDs are the future of UV disinfection, new methods are needed for designing such reactors. In this research study, the evaluation of a new design paradigm using a point-of-use UV-LED disinfection reactor has been performed. ModeFrontier, a numerical optimization platform, was coupled with COMSOL Multi-physics, a computational fluid dynamics (CFD) software package, to generate an optimized UV-LED continuous flow reactor. Three optimality conditions were considered: 1) single objective analysis minimizing input supply power while achieving at least (2.0) log10 inactivation of Escherichia coli ATCC 11229; and 2) two multi-objective analyses (one of which maximized the log10 inactivation of E. coli ATCC 11229 and minimized the supply power). All tests were completed at a flow rate of 109 mL/min and 92% UVT (measured at 254 nm). The numerical solution for the first objective was validated experimentally using biodosimetry. The optimal design predictions displayed good agreement with the experimental data and contained several non-intuitive features, particularly with the UV-LED spatial arrangement, where the lights were unevenly populated throughout the reactor. The optimal designs may not have been developed from experienced designers due to the increased degrees of freedom offered by using UV-LEDs. The results of this study revealed that the coupled optimization routine with CFD was effective at significantly decreasing the engineer's design decision space and finding a potentially near-optimal UV-LED reactor solution. Published by Elsevier Ltd.

Experimental design and response surface modelling for optimization of vat dye from water by nano zero valent iron (NZVI).

PubMed

Arabi, Simin; Sohrabi, Mahmoud Reza

2013-01-01

In this study, NZVI particles was prepared and studied for the removal of vat green 1 dye from aqueous solution. A four-factor central composite design (CCD) combined with response surface modeling (RSM) to evaluate the combined effects of variables as well as optimization was employed for maximizing the dye removal by prepared NZVI based on 30 different experimental data obtained in a batch study. Four independent variables, viz. NZVI dose (0.1-0.9 g/L), pH (1.5-9.5), contact time (20-100 s), and initial dye concentration (10-50 mg/L) were transform to coded values and quadratic model was built to predict the responses. The significant of independent variables and their interactions were tested by the analysis of variance (ANOVA). Adequacy of the model was tested by the correlation between experimental and predicted values of the response and enumeration of prediction errors. The ANOVA results indicated that the proposed model can be used to navigate the design space. Optimization of the variables for maximum adsorption of dye by NZVI particles was performed using quadratic model. The predicted maximum adsorption efficiency (96.97%) under the optimum conditions of the process variables (NZVI dose 0.5 g/L, pH 4, contact time 60 s, and initial dye concentration 30 mg/L) was very close to the experimental value (96.16%) determined in batch experiment. In the optimization, R2 and R2adj correlation coefficients for the model were evaluated as 0.95 and 0.90, respectively.

Weight optimization of an aerobrake structural concept for a lunar transfer vehicle

NASA Technical Reports Server (NTRS)

Bush, Lance B.; Unal, Resit; Rowell, Lawrence F.; Rehder, John J.

1992-01-01

An aerobrake structural concept for a lunar transfer vehicle was weight optimized through the use of the Taguchi design method, finite element analyses, and element sizing routines. Six design parameters were chosen to represent the aerobrake structural configuration. The design parameters included honeycomb core thickness, diameter-depth ratio, shape, material, number of concentric ring frames, and number of radial frames. Each parameter was assigned three levels. The aerobrake structural configuration with the minimum weight was 44 percent less than the average weight of all the remaining satisfactory experimental configurations. In addition, the results of this study have served to bolster the advocacy of the Taguchi method for aerospace vehicle design. Both reduced analysis time and an optimized design demonstrated the applicability of the Taguchi method to aerospace vehicle design.

Optimization design of multiphase pump impeller based on combined genetic algorithm and boundary vortex flux diagnosis

NASA Astrophysics Data System (ADS)

Zhang, Jin-ya; Cai, Shu-jie; Li, Yong-jiang; Li, Yong-jiang; Zhang, Yong-xue

2017-12-01

A novel optimization design method for the multiphase pump impeller is proposed through combining the quasi-3D hydraulic design (Q3DHD), the boundary vortex flux (BVF) diagnosis, and the genetic algorithm (GA). The BVF diagnosis based on the Q3DHD is used to evaluate the objection function. Numerical simulations and hydraulic performance tests are carried out to compare the impeller designed only by the Q3DHD method and that optimized by the presented method. The comparisons of both the flow fields simulated under the same condition show that (1) the pressure distribution in the optimized impeller is more reasonable and the gas-liquid separation is more efficiently inhibited, (2) the scales of the gas pocket and the vortex decrease remarkably for the optimized impeller, (3) the unevenness of the BVF distributions near the shroud of the original impeller is effectively eliminated in the optimized impeller. The experimental results show that the differential pressure and the maximum efficiency of the optimized impeller are increased by 4% and 2.5%, respectively. Overall, the study indicates that the optimization design method proposed in this paper is feasible.

A statistical approach to optimizing concrete mixture design.

PubMed

Ahmad, Shamsad; Alghamdi, Saeid A

2014-01-01

A step-by-step statistical approach is proposed to obtain optimum proportioning of concrete mixtures using the data obtained through a statistically planned experimental program. The utility of the proposed approach for optimizing the design of concrete mixture is illustrated considering a typical case in which trial mixtures were considered according to a full factorial experiment design involving three factors and their three levels (3(3)). A total of 27 concrete mixtures with three replicates (81 specimens) were considered by varying the levels of key factors affecting compressive strength of concrete, namely, water/cementitious materials ratio (0.38, 0.43, and 0.48), cementitious materials content (350, 375, and 400 kg/m(3)), and fine/total aggregate ratio (0.35, 0.40, and 0.45). The experimental data were utilized to carry out analysis of variance (ANOVA) and to develop a polynomial regression model for compressive strength in terms of the three design factors considered in this study. The developed statistical model was used to show how optimization of concrete mixtures can be carried out with different possible options.

A Statistical Approach to Optimizing Concrete Mixture Design

PubMed Central

Alghamdi, Saeid A.

2014-01-01

A step-by-step statistical approach is proposed to obtain optimum proportioning of concrete mixtures using the data obtained through a statistically planned experimental program. The utility of the proposed approach for optimizing the design of concrete mixture is illustrated considering a typical case in which trial mixtures were considered according to a full factorial experiment design involving three factors and their three levels (33). A total of 27 concrete mixtures with three replicates (81 specimens) were considered by varying the levels of key factors affecting compressive strength of concrete, namely, water/cementitious materials ratio (0.38, 0.43, and 0.48), cementitious materials content (350, 375, and 400 kg/m3), and fine/total aggregate ratio (0.35, 0.40, and 0.45). The experimental data were utilized to carry out analysis of variance (ANOVA) and to develop a polynomial regression model for compressive strength in terms of the three design factors considered in this study. The developed statistical model was used to show how optimization of concrete mixtures can be carried out with different possible options. PMID:24688405

Optimization of Contrast Detection Power with Probabilistic Behavioral Information

PubMed Central

Cordes, Dietmar; Herzmann, Grit; Nandy, Rajesh; Curran, Tim

2012-01-01

Recent progress in the experimental design for event-related fMRI experiments made it possible to find the optimal stimulus sequence for maximum contrast detection power using a genetic algorithm. In this study, a novel algorithm is proposed for optimization of contrast detection power by including probabilistic behavioral information, based on pilot data, in the genetic algorithm. As a particular application, a recognition memory task is studied and the design matrix optimized for contrasts involving the familiarity of individual items (pictures of objects) and the recollection of qualitative information associated with the items (left/right orientation). Optimization of contrast efficiency is a complicated issue whenever subjects’ responses are not deterministic but probabilistic. Contrast efficiencies are not predictable unless behavioral responses are included in the design optimization. However, available software for design optimization does not include options for probabilistic behavioral constraints. If the anticipated behavioral responses are included in the optimization algorithm, the design is optimal for the assumed behavioral responses, and the resulting contrast efficiency is greater than what either a block design or a random design can achieve. Furthermore, improvements of contrast detection power depend strongly on the behavioral probabilities, the perceived randomness, and the contrast of interest. The present genetic algorithm can be applied to any case in which fMRI contrasts are dependent on probabilistic responses that can be estimated from pilot data. PMID:22326984

Optimization of the combined ultrasonic assisted/adsorption method for the removal of malachite green by gold nanoparticles loaded on activated carbon: Experimental design

NASA Astrophysics Data System (ADS)

Roosta, M.; Ghaedi, M.; Shokri, N.; Daneshfar, A.; Sahraei, R.; Asghari, A.

2014-01-01

The present study was aimed to experimental design optimization applied to removal of malachite green (MG) from aqueous solution by ultrasound-assisted removal onto the gold nanoparticles loaded on activated carbon (Au-NP-AC). This nanomaterial was characterized using different techniques such as FESEM, TEM, BET, and UV-vis measurements. The effects of variables such as pH, initial dye concentration, adsorbent dosage (g), temperature and sonication time on MG removal were studied using central composite design (CCD) and the optimum experimental conditions were found with desirability function (DF) combined response surface methodology (RSM). Fitting the experimental equilibrium data to various isotherm models such as Langmuir, Freundlich, Tempkin and Dubinin-Radushkevich models show the suitability and applicability of the Langmuir model. Kinetic models such as pseudo -first order, pseudo-second order, Elovich and intraparticle diffusion models applicability was tested for experimental data and the second-order equation and intraparticle diffusion models control the kinetic of the adsorption process. The small amount of proposed adsorbent (0.015 g) is applicable for successful removal of MG (RE > 99%) in short time (4.4 min) with high adsorption capacity (140-172 mg g-1).

Development of a chromatographic method with multi-criteria decision making design for simultaneous determination of nifedipine and atenolol in content uniformity testing.

PubMed

Ahmed, Sameh; Alqurshi, Abdulmalik; Mohamed, Abdel-Maaboud Ismail

2018-07-01

A new robust and reliable high-performance liquid chromatography (HPLC) method with multi-criteria decision making (MCDM) approach was developed to allow simultaneous quantification of atenolol (ATN) and nifedipine (NFD) in content uniformity testing. Felodipine (FLD) was used as an internal standard (I.S.) in this study. A novel marriage between a new interactive response optimizer and a HPLC method was suggested for multiple response optimizations of target responses. An interactive response optimizer was used as a decision and prediction tool for the optimal settings of target responses, according to specified criteria, based on Derringer's desirability. Four independent variables were considered in this study: Acetonitrile%, buffer pH and concentration along with column temperature. Eight responses were optimized: retention times of ATN, NFD, and FLD, resolutions between ATN/NFD and NFD/FLD, and plate numbers for ATN, NFD, and FLD. Multiple regression analysis was applied in order to scan the influences of the most significant variables for the regression models. The experimental design was set to give minimum retention times, maximum resolution and plate numbers. The interactive response optimizer allowed prediction of optimum conditions according to these criteria with a good composite desirability value of 0.98156. The developed method was validated according to the International Conference on Harmonization (ICH) guidelines with the aid of the experimental design. The developed MCDM-HPLC method showed superior robustness and resolution in short analysis time allowing successful simultaneous content uniformity testing of ATN and NFD in marketed capsules. The current work presents an interactive response optimizer as an efficient platform to optimize, predict responses, and validate HPLC methodology with tolerable design space for assay in quality control laboratories. Copyright © 2018 Elsevier B.V. All rights reserved.

Application of Statistical Design for the Production of Cellulase by Trichoderma reesei Using Mango Peel

PubMed Central

Saravanan, P.; Muthuvelayudham, R.; Viruthagiri, T.

2012-01-01

Optimization of the culture medium for cellulase production using Trichoderma reesei was carried out. The optimization of cellulase production using mango peel as substrate was performed with statistical methodology based on experimental designs. The screening of nine nutrients for their influence on cellulase production is achieved using Plackett-Burman design. Avicel, soybean cake flour, KH2PO4, and CoCl2 ·6H2O were selected based on their positive influence on cellulase production. The composition of the selected components was optimized using Response Surface Methodology (RSM). The optimum conditions are as follows: Avicel: 25.30 g/L, Soybean cake flour: 23.53 g/L, KH2PO4: 4.90 g/L, and CoCl2 ·6H2O: 0.95 g/L. These conditions are validated experimentally which revealed an enhanced Cellulase activity of 7.8 IU/mL. PMID:23304453

Design and synthesis of a novel multifunctional stabilizer for highly stable uc(dl)-tetrahydropalmatine nanosuspensions and in vitro study

NASA Astrophysics Data System (ADS)

Yan, Beibei; Wang, Yancai; Wang, Lulu; Zhou, Yuqi; Shang, Xueyun; Zhao, Juan; Liu, Yangyang; Du, Juan

2018-05-01

The present study aimed to prepare stable uc(dl)-tetrahydropalmatine (uc(dl)-THP) nanosuspensions of optimized formulation with PEGylated chitosan as a multifunctional stabilizer using the antisolvent precipitation method. A central composite design project of three factors and five-level full factorial (53) was applied to design the experimental program, and response surface methodology analysis was used to optimize the experimental conditions. The effects of critical influencing factors such as PEGylated chitosan concentration, operational temperature, and ultrasonic energy on particle size and zeta potential were investigated. Under the optimization nanosuspension formulation, the particle size was 269 nm and zeta potential was at 37.4 mV. Also, the uc(dl)-THP nanosuspensions maintained good physical stability after 2 months, indicating the potential ability of the multifunctional stabilizer for stable nanosuspension formulation. Hence, the present findings indicated that PEGylated chitosan could be used as the ideal stabilizer to form a physically stable nanosuspension formulation.

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

Delcamp, E.; Lagarde, B.; Polack, F.

Though optimization softwares are commonly used in visible optical design, none seems to exist for soft X-ray optics. It is shown here that optimization techniques can be applied with some advantages to X-UV monochromator design. A merit function, suitable for minimizing the aberrations is proposed, and the general method of computation is described. Samples of the software inputs and outputs are presented, and compared to reference data. As an example of application to soft X-ray monochromator design, the optimization of the soft X-ray monochromator of the ESRF microscopy beamline is presented. Good agreement between the predicted resolution of a modifiedmore » PGM monochromator and experimental measurements is reported.« less

A multiple-alignment based primer design algorithm for genetically highly variable DNA targets

PubMed Central

2013-01-01

Background Primer design for highly variable DNA sequences is difficult, and experimental success requires attention to many interacting constraints. The advent of next-generation sequencing methods allows the investigation of rare variants otherwise hidden deep in large populations, but requires attention to population diversity and primer localization in relatively conserved regions, in addition to recognized constraints typically considered in primer design. Results Design constraints include degenerate sites to maximize population coverage, matching of melting temperatures, optimizing de novo sequence length, finding optimal bio-barcodes to allow efficient downstream analyses, and minimizing risk of dimerization. To facilitate primer design addressing these and other constraints, we created a novel computer program (PrimerDesign) that automates this complex procedure. We show its powers and limitations and give examples of successful designs for the analysis of HIV-1 populations. Conclusions PrimerDesign is useful for researchers who want to design DNA primers and probes for analyzing highly variable DNA populations. It can be used to design primers for PCR, RT-PCR, Sanger sequencing, next-generation sequencing, and other experimental protocols targeting highly variable DNA samples. PMID:23965160

Optimizing experimental procedures for quantitative evaluation of crop plant performance in high throughput phenotyping systems

PubMed Central

Junker, Astrid; Muraya, Moses M.; Weigelt-Fischer, Kathleen; Arana-Ceballos, Fernando; Klukas, Christian; Melchinger, Albrecht E.; Meyer, Rhonda C.; Riewe, David; Altmann, Thomas

2015-01-01

Detailed and standardized protocols for plant cultivation in environmentally controlled conditions are an essential prerequisite to conduct reproducible experiments with precisely defined treatments. Setting up appropriate and well defined experimental procedures is thus crucial for the generation of solid evidence and indispensable for successful plant research. Non-invasive and high throughput (HT) phenotyping technologies offer the opportunity to monitor and quantify performance dynamics of several hundreds of plants at a time. Compared to small scale plant cultivations, HT systems have much higher demands, from a conceptual and a logistic point of view, on experimental design, as well as the actual plant cultivation conditions, and the image analysis and statistical methods for data evaluation. Furthermore, cultivation conditions need to be designed that elicit plant performance characteristics corresponding to those under natural conditions. This manuscript describes critical steps in the optimization of procedures for HT plant phenotyping systems. Starting with the model plant Arabidopsis, HT-compatible methods were tested, and optimized with regard to growth substrate, soil coverage, watering regime, experimental design (considering environmental inhomogeneities) in automated plant cultivation and imaging systems. As revealed by metabolite profiling, plant movement did not affect the plants' physiological status. Based on these results, procedures for maize HT cultivation and monitoring were established. Variation of maize vegetative growth in the HT phenotyping system did match well with that observed in the field. The presented results outline important issues to be considered in the design of HT phenotyping experiments for model and crop plants. It thereby provides guidelines for the setup of HT experimental procedures, which are required for the generation of reliable and reproducible data of phenotypic variation for a broad range of applications. PMID:25653655

Optimization of Nd: YAG Laser Marking of Alumina Ceramic Using RSM And ANN

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

Peter, Josephine; Doloi, B.; Bhattacharyya, B.

The present research papers deals with the artificial neural network (ANN) and the response surface methodology (RSM) based mathematical modeling and also an optimization analysis on marking characteristics on alumina ceramic. The experiments have been planned and carried out based on Design of Experiment (DOE). It also analyses the influence of the major laser marking process parameters and the optimal combination of laser marking process parametric setting has been obtained. The output of the RSM optimal data is validated through experimentation and ANN predictive model. A good agreement is observed between the results based on ANN predictive model and actualmore » experimental observations.« less

Optimal color design of psychological counseling room by design of experiments and response surface methodology.

PubMed

Liu, Wenjuan; Ji, Jianlin; Chen, Hua; Ye, Chenyu

2014-01-01

Color is one of the most powerful aspects of a psychological counseling environment. Little scientific research has been conducted on color design and much of the existing literature is based on observational studies. Using design of experiments and response surface methodology, this paper proposes an optimal color design approach for transforming patients' perception into color elements. Six indices, pleasant-unpleasant, interesting-uninteresting, exciting-boring, relaxing-distressing, safe-fearful, and active-inactive, were used to assess patients' impression. A total of 75 patients participated, including 42 for Experiment 1 and 33 for Experiment 2. 27 representative color samples were designed in Experiment 1, and the color sample (L = 75, a = 0, b = -60) was the most preferred one. In Experiment 2, this color sample was set as the 'central point', and three color attributes were optimized to maximize the patients' satisfaction. The experimental results show that the proposed method can get the optimal solution for color design of a counseling room.

Optimal Color Design of Psychological Counseling Room by Design of Experiments and Response Surface Methodology

PubMed Central

Chen, Hua; Ye, Chenyu

2014-01-01

Color is one of the most powerful aspects of a psychological counseling environment. Little scientific research has been conducted on color design and much of the existing literature is based on observational studies. Using design of experiments and response surface methodology, this paper proposes an optimal color design approach for transforming patients’ perception into color elements. Six indices, pleasant-unpleasant, interesting-uninteresting, exciting-boring, relaxing-distressing, safe-fearful, and active-inactive, were used to assess patients’ impression. A total of 75 patients participated, including 42 for Experiment 1 and 33 for Experiment 2. 27 representative color samples were designed in Experiment 1, and the color sample (L = 75, a = 0, b = -60) was the most preferred one. In Experiment 2, this color sample was set as the ‘central point’, and three color attributes were optimized to maximize the patients’ satisfaction. The experimental results show that the proposed method can get the optimal solution for color design of a counseling room. PMID:24594683

Efficient experimental design of high-fidelity three-qubit quantum gates via genetic programming

NASA Astrophysics Data System (ADS)

Devra, Amit; Prabhu, Prithviraj; Singh, Harpreet; Arvind; Dorai, Kavita

2018-03-01

We have designed efficient quantum circuits for the three-qubit Toffoli (controlled-controlled-NOT) and the Fredkin (controlled-SWAP) gate, optimized via genetic programming methods. The gates thus obtained were experimentally implemented on a three-qubit NMR quantum information processor, with a high fidelity. Toffoli and Fredkin gates in conjunction with the single-qubit Hadamard gates form a universal gate set for quantum computing and are an essential component of several quantum algorithms. Genetic algorithms are stochastic search algorithms based on the logic of natural selection and biological genetics and have been widely used for quantum information processing applications. We devised a new selection mechanism within the genetic algorithm framework to select individuals from a population. We call this mechanism the "Luck-Choose" mechanism and were able to achieve faster convergence to a solution using this mechanism, as compared to existing selection mechanisms. The optimization was performed under the constraint that the experimentally implemented pulses are of short duration and can be implemented with high fidelity. We demonstrate the advantage of our pulse sequences by comparing our results with existing experimental schemes and other numerical optimization methods.

Improving Health-care Delivery for Post-Traumatic Stress Disorder: An Interrelated Approach Leveraging Systems Engineering and Optimization

DTIC Science & Technology

2011-09-01

AND EXPERIMENTAL DESIGN ..........................................................................................................31   1...PRIMARY RESERCH QUESTION ............................................................41   C.   OBJECTIVE ACHIEVEMENT...Based Outpatient Clinic CPT Cognitive Processing Therapy DISE Distributed Information Systems Experimentation EBT Evidence-Based Treatment GMC

Optimization and characterization of liposome formulation by mixture design.

PubMed

Maherani, Behnoush; Arab-tehrany, Elmira; Kheirolomoom, Azadeh; Reshetov, Vadzim; Stebe, Marie José; Linder, Michel

2012-02-07

This study presents the application of the mixture design technique to develop an optimal liposome formulation by using the different lipids in type and percentage (DOPC, POPC and DPPC) in liposome composition. Ten lipid mixtures were generated by the simplex-centroid design technique and liposomes were prepared by the extrusion method. Liposomes were characterized with respect to size, phase transition temperature, ζ-potential, lamellarity, fluidity and efficiency in loading calcein. The results were then applied to estimate the coefficients of mixture design model and to find the optimal lipid composition with improved entrapment efficiency, size, transition temperature, fluidity and ζ-potential of liposomes. The response optimization of experiments was the liposome formulation with DOPC: 46%, POPC: 12% and DPPC: 42%. The optimal liposome formulation had an average diameter of 127.5 nm, a phase-transition temperature of 11.43 °C, a ζ-potential of -7.24 mV, fluidity (1/P)(TMA-DPH)((¬)) value of 2.87 and an encapsulation efficiency of 20.24%. The experimental results of characterization of optimal liposome formulation were in good agreement with those predicted by the mixture design technique.

Design and construction of a spectrometer facility and experiment for intermediate energy proton scattering on helium. [Wave functions, preliminary experimental techniques

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

Rolfe, R.M.

1976-12-01

The goal of the research was to investigate proton scattering on nuclei at intermediate energies and in particular to investigate proton scattering on helium. A theoretical investigation of the helium nucleus and the nature of the intermediate energy interaction, design and optimization of an energy-loss spectrometer facility for proton-nucleus scattering, and the unique superfluid helium target and experimental design are discussed.

Synthesis and acid digestion of biomorphic ceramics: determination of alkaline and alkaline earth ions.

PubMed

Bosch Ojeda, Catalina; Sánchez Rojas, Fuensanta; Cano Pavón, José Manuel

2007-09-01

Ceramic and glass are some of the more recent engineering materials and those that are most resistant to environmental conditions. They belong to advanced materials in that they are being developed for the aerospace and electronics industries. In the last decade, a new class of ceramic materials has been the focus of particular attention. The materials were produced with natural, renewable resources (wood or wood-based products). In this work, we have synthesised a new biomorphic ceramic material from oak wood and Si infiltration. After the material characterization, we have optimized the dissolution of the sample by acid attack in an oven under microwave irradiation. Experimental designs were used as a multivariate strategy for the evaluation of the effects of varying several variables at the same time. The optimization was performed in two steps using factorial design for preliminary evaluation and a Draper-Lin design for determination of the critical experimental conditions. Five variables (time, power, volume of HNO3, volume H2SO4 and volume of HF) were considered as factors and as a response the concentration of different metal ions in the optimization process. Interactions between analytical factors and their optimal levels were investigated using a Draper-Lin design.

Enhanced α-amylase production by a marine protist, Ulkenia sp. using response surface methodology and genetic algorithm.

PubMed

Shirodkar, Priyanka V; Muraleedharan, Usha Devi

2017-11-26

Amylases are a group of enzymes with a wide variety of industrial applications. Enhancement of α-amylase production from the marine protists, thraustochytrids has been attempted for the first time by applying statistical-based experimental designs using response surface methodology (RSM) and genetic algorithm (GA) for optimization of the most influencing process variables. A full factorial central composite experimental design was used to study the cumulative interactive effect of nutritional components viz., glucose, corn starch, and yeast extract. RSM was performed on two objectives, that is, growth of Ulkenia sp. AH-2 (ATCC® PRA-296) and α-amylase activity. When GA was conducted for maximization of the enzyme activity, the optimal α-amylase activity was found to be 71.20 U/mL which was close to that obtained by RSM (71.93 U/mL), both of which were in agreement with the predicted value of 72.37 U/mL. Optimal growth at the optimized process variables was found to be 1.89A 660nm . The optimized medium increased α-amylase production by 1.2-fold.

An External Archive-Guided Multiobjective Particle Swarm Optimization Algorithm.

PubMed

Zhu, Qingling; Lin, Qiuzhen; Chen, Weineng; Wong, Ka-Chun; Coello Coello, Carlos A; Li, Jianqiang; Chen, Jianyong; Zhang, Jun

2017-09-01

The selection of swarm leaders (i.e., the personal best and global best), is important in the design of a multiobjective particle swarm optimization (MOPSO) algorithm. Such leaders are expected to effectively guide the swarm to approach the true Pareto optimal front. In this paper, we present a novel external archive-guided MOPSO algorithm (AgMOPSO), where the leaders for velocity update are all selected from the external archive. In our algorithm, multiobjective optimization problems (MOPs) are transformed into a set of subproblems using a decomposition approach, and then each particle is assigned accordingly to optimize each subproblem. A novel archive-guided velocity update method is designed to guide the swarm for exploration, and the external archive is also evolved using an immune-based evolutionary strategy. These proposed approaches speed up the convergence of AgMOPSO. The experimental results fully demonstrate the superiority of our proposed AgMOPSO in solving most of the test problems adopted, in terms of two commonly used performance measures. Moreover, the effectiveness of our proposed archive-guided velocity update method and immune-based evolutionary strategy is also experimentally validated on more than 30 test MOPs.

Optimization of the fabrication of novel stealth PLA-based nanoparticles by dispersion polymerization using D-optimal mixture design

PubMed Central

Adesina, Simeon K.; Wight, Scott A.; Akala, Emmanuel O.

2015-01-01

Purpose Nanoparticle size is important in drug delivery. Clearance of nanoparticles by cells of the reticuloendothelial system has been reported to increase with increase in particle size. Further, nanoparticles should be small enough to avoid lung or spleen filtering effects. Endocytosis and accumulation in tumor tissue by the enhanced permeability and retention effect are also processes that are influenced by particle size. We present the results of studies designed to optimize crosslinked biodegradable stealth polymeric nanoparticles fabricated by dispersion polymerization. Methods Nanoparticles were fabricated using different amounts of macromonomer, initiators, crosslinking agent and stabilizer in a dioxane/DMSO/water solvent system. Confirmation of nanoparticle formation was by scanning electron microscopy (SEM). Particle size was measured by dynamic light scattering (DLS). D-optimal mixture statistical experimental design was used for the experimental runs, followed by model generation (Scheffe polynomial) and optimization with the aid of a computer software. Model verification was done by comparing particle size data of some suggested solutions to the predicted particle sizes. Results and Conclusion Data showed that average particle sizes follow the same trend as predicted by the model. Negative terms in the model corresponding to the crosslinking agent and stabilizer indicate the important factors for minimizing particle size. PMID:24059281

Optimization of the fabrication of novel stealth PLA-based nanoparticles by dispersion polymerization using D-optimal mixture design.

PubMed

Adesina, Simeon K; Wight, Scott A; Akala, Emmanuel O

2014-11-01

Nanoparticle size is important in drug delivery. Clearance of nanoparticles by cells of the reticuloendothelial system has been reported to increase with increase in particle size. Further, nanoparticles should be small enough to avoid lung or spleen filtering effects. Endocytosis and accumulation in tumor tissue by the enhanced permeability and retention effect are also processes that are influenced by particle size. We present the results of studies designed to optimize cross-linked biodegradable stealth polymeric nanoparticles fabricated by dispersion polymerization. Nanoparticles were fabricated using different amounts of macromonomer, initiators, crosslinking agent and stabilizer in a dioxane/DMSO/water solvent system. Confirmation of nanoparticle formation was by scanning electron microscopy (SEM). Particle size was measured by dynamic light scattering (DLS). D-optimal mixture statistical experimental design was used for the experimental runs, followed by model generation (Scheffe polynomial) and optimization with the aid of a computer software. Model verification was done by comparing particle size data of some suggested solutions to the predicted particle sizes. Data showed that average particle sizes follow the same trend as predicted by the model. Negative terms in the model corresponding to the cross-linking agent and stabilizer indicate the important factors for minimizing particle size.

Box-Behnken statistical design to optimize thermal performance of energy storage systems

NASA Astrophysics Data System (ADS)

Jalalian, Iman Joz; Mohammadiun, Mohammad; Moqadam, Hamid Hashemi; Mohammadiun, Hamid

2018-05-01

Latent heat thermal storage (LHTS) is a technology that can help to reduce energy consumption for cooling applications, where the cold is stored in phase change materials (PCMs). In the present study a comprehensive theoretical and experimental investigation is performed on a LHTES system containing RT25 as phase change material (PCM). Process optimization of the experimental conditions (inlet air temperature and velocity and number of slabs) was carried out by means of Box-Behnken design (BBD) of Response surface methodology (RSM). Two parameters (cooling time and COP value) were chosen to be the responses. Both of the responses were significantly influenced by combined effect of inlet air temperature with velocity and number of slabs. Simultaneous optimization was performed on the basis of the desirability function to determine the optimal conditions for the cooling time and COP value. Maximum cooling time (186 min) and COP value (6.04) were found at optimum process conditions i.e. inlet temperature of (32.5), air velocity of (1.98) and slab number of (7).

Decolorization and mineralization of Diarylide Yellow 12 (PY12) by photo-Fenton process: the Response Surface Methodology as the optimization tool.

PubMed

GilPavas, Edison; Dobrosz-Gómez, Izabela; Gómez-García, Miguel Ángel

2012-01-01

The Response Surface Methodology (RSM) was applied as a tool for the optimization of the operational conditions of the photo-degradation of highly concentrated PY12 wastewater, resulting from a textile industry located in the suburbs of Medellin (Colombia). The Box-Behnken experimental Design (BBD) was chosen for the purpose of response optimization. The photo-Fenton process was carried out in a laboratory-scale batch photo-reactor. A multifactorial experimental design was proposed, including the following variables: the initial dyestuff concentration, the H(2)O(2) and the Fe(+2) concentrations, as well as the UV wavelength radiation. The photo-Fenton process performed at the optimized conditions resulted in ca. 100% of dyestuff decolorization, 92% of COD and 82% of TOC degradation. A kinetic study was accomplished, including the identification of some intermediate compounds generated during the oxidation process. The water biodegradability reached a final DBO(5)/DQO = 0.86 value.

Optimization of glibenclamide tablet composition through the combined use of differential scanning calorimetry and D-optimal mixture experimental design.

PubMed

Mura, P; Furlanetto, S; Cirri, M; Maestrelli, F; Marras, A M; Pinzauti, S

2005-02-07

A systematic analysis of the influence of different proportions of excipients on the stability of a solid dosage form was carried out. In particular, a d-optimal mixture experimental design was applied for the evaluation of glibenclamide compatibility in tablet formulations, consisting of four classic excipients (natrosol as binding agent, stearic acid as lubricant, sorbitol as diluent and cross-linked polyvinylpyrrolidone as disintegrant). The goal was to find the mixture component proportions which correspond to the optimal drug melting parameters, i.e. its maximum stability, using differential scanning calorimetry (DSC) to quickly obtain information about possible interactions among the formulation components. The absolute value of the difference between the melting peak temperature of pure drug endotherm and that in each analysed mixture and the absolute value of the difference between the enthalpy of the pure glibenclamide melting peak and that of its melting peak in the different analyzed mixtures, were chosen as indexes of the drug-excipient interaction degree.

Scramjet Fuel Injection Array Optimization Utilizing Mixed Variable Pattern Search With Kriging Surrogates

DTIC Science & Technology

2008-03-01

injector con- figurations for Scramjet applications.” International Journal of Heat and Mass Transfer 49: 3634–3644 (2006). 8. Anderson, C.D...Experimental Attainment of Optimal Conditions,” Journal of the Royal Statistical Society, B(13): 1–38, 1951. 19. Brewer, K.M. Exergy Methods for the Mission...second applies mvps to a new scramjet design in support of the Hypersonic International Flight Re- search Experimentation (hifire). The results

Design of 9.271-pressure-ratio 5-stage core compressor and overall performance for first 3 stages

NASA Technical Reports Server (NTRS)

Steinke, Ronald J.

1986-01-01

Overall aerodynamic design information is given for all five stages of an axial flow core compressor (74A) having a 9.271 pressure ratio and 29.710 kg/sec flow. For the inlet stage group (first three stages), detailed blade element design information and experimental overall performance are given. At rotor 1 inlet tip speed was 430.291 m/sec, and hub to tip radius ratio was 0.488. A low number of blades per row was achieved by the use of low-aspect-ratio blading of moderate solidity. The high reaction stages have about equal energy addition. Radial energy varied to give constant total pressure at the rotor exit. The blade element profile and shock losses and the incidence and deviation angles were based on relevant experimental data. Blade shapes are mostly double circular arc. Analysis by a three-dimensional Euler code verified the experimentally measured high flow at design speed and IGV-stator setting angles. An optimization code gave an optimal IGV-stator reset schedule for higher measured efficiency at all speeds.

Electrochemical production and use of free chlorine for pollutant removal: an experimental design approach.

PubMed

Antonelli, Raissa; de Araújo, Karla Santos; Pires, Ricardo Francisco; Fornazari, Ana Luiza de Toledo; Granato, Ana Claudia; Malpass, Geoffroy Roger Pointer

2017-10-28

The present paper presents the study of (1) the optimization of electrochemical-free chlorine production using an experimental design approach, and (2) the application of the optimum conditions obtained for the application in photo-assisted electrochemical degradation of simulated textile effluent. In the experimental design the influence of inter-electrode gap, pH, NaCl concentration and current was considered. It was observed that the four variables studied are significant for the process, with NaCl concentration and current being the most significant variables for free chlorine production. The maximum free chlorine production was obtained at a current of 2.33 A and NaCl concentrations in 0.96 mol dm -3 . The application of the optimized conditions with simultaneous UV irradiation resulted in up to 83.1% Total Organic Carbon removal and 100% of colour removal over 180 min of electrolysis. The results indicate that a systematic (statistical) approach to the electrochemical treatment of pollutants can save time and reagents.

Development of a fast, lean and agile direct pelletization process using experimental design techniques.

PubMed

Politis, Stavros N; Rekkas, Dimitrios M

2017-04-01

A novel hot melt direct pelletization method was developed, characterized and optimized, using statistical thinking and experimental design tools. Mixtures of carnauba wax (CW) and HPMC K100M were spheronized using melted gelucire 50-13 as a binding material (BM). Experimentation was performed sequentially; a fractional factorial design was set up initially to screen the factors affecting the process, namely spray rate, quantity of BM, rotor speed, type of rotor disk, lubricant-glidant presence, additional spheronization time, powder feeding rate and quantity. From the eight factors assessed, three were further studied during process optimization (spray rate, quantity of BM and powder feeding rate), at different ratios of the solid mixture of CW and HPMC K100M. The study demonstrated that the novel hot melt process is fast, efficient, reproducible and predictable. Therefore, it can be adopted in a lean and agile manufacturing setting for the production of flexible pellet dosage forms with various release rates easily customized between immediate and modified delivery.

Integrating uniform design and response surface methodology to optimize thiacloprid suspension

PubMed Central

Li, Bei-xing; Wang, Wei-chang; Zhang, Xian-peng; Zhang, Da-xia; Mu, Wei; Liu, Feng

2017-01-01

A model 25% suspension concentrate (SC) of thiacloprid was adopted to evaluate an integrative approach of uniform design and response surface methodology. Tersperse2700, PE1601, xanthan gum and veegum were the four experimental factors, and the aqueous separation ratio and viscosity were the two dependent variables. Linear and quadratic polynomial models of stepwise regression and partial least squares were adopted to test the fit of the experimental data. Verification tests revealed satisfactory agreement between the experimental and predicted data. The measured values for the aqueous separation ratio and viscosity were 3.45% and 278.8 mPa·s, respectively, and the relative errors of the predicted values were 9.57% and 2.65%, respectively (prepared under the proposed conditions). Comprehensive benefits could also be obtained by appropriately adjusting the amount of certain adjuvants based on practical requirements. Integrating uniform design and response surface methodology is an effective strategy for optimizing SC formulas. PMID:28383036

Receding horizon online optimization for torque control of gasoline engines.

PubMed

Kang, Mingxin; Shen, Tielong

2016-11-01

This paper proposes a model-based nonlinear receding horizon optimal control scheme for the engine torque tracking problem. The controller design directly employs the nonlinear model exploited based on mean-value modeling principle of engine systems without any linearizing reformation, and the online optimization is achieved by applying the Continuation/GMRES (generalized minimum residual) approach. Several receding horizon control schemes are designed to investigate the effects of the integral action and integral gain selection. Simulation analyses and experimental validations are implemented to demonstrate the real-time optimization performance and control effects of the proposed torque tracking controllers. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Optimal bioprocess design through a gene regulatory network - growth kinetic hybrid model: Towards Replacing Monod kinetics.

PubMed

Tsipa, Argyro; Koutinas, Michalis; Usaku, Chonlatep; Mantalaris, Athanasios

2018-05-02

Currently, design and optimisation of biotechnological bioprocesses is performed either through exhaustive experimentation and/or with the use of empirical, unstructured growth kinetics models. Whereas, elaborate systems biology approaches have been recently explored, mixed-substrate utilisation is predominantly ignored despite its significance in enhancing bioprocess performance. Herein, bioprocess optimisation for an industrially-relevant bioremediation process involving a mixture of highly toxic substrates, m-xylene and toluene, was achieved through application of a novel experimental-modelling gene regulatory network - growth kinetic (GRN-GK) hybrid framework. The GRN model described the TOL and ortho-cleavage pathways in Pseudomonas putida mt-2 and captured the transcriptional kinetics expression patterns of the promoters. The GRN model informed the formulation of the growth kinetics model replacing the empirical and unstructured Monod kinetics. The GRN-GK framework's predictive capability and potential as a systematic optimal bioprocess design tool, was demonstrated by effectively predicting bioprocess performance, which was in agreement with experimental values, when compared to four commonly used models that deviated significantly from the experimental values. Significantly, a fed-batch biodegradation process was designed and optimised through the model-based control of TOL Pr promoter expression resulting in 61% and 60% enhanced pollutant removal and biomass formation, respectively, compared to the batch process. This provides strong evidence of model-based bioprocess optimisation at the gene level, rendering the GRN-GK framework as a novel and applicable approach to optimal bioprocess design. Finally, model analysis using global sensitivity analysis (GSA) suggests an alternative, systematic approach for model-driven strain modification for synthetic biology and metabolic engineering applications. Copyright © 2018. Published by Elsevier Inc.

Risk assessment and experimental design in the development of a prolonged release drug delivery system with paliperidone.

PubMed

Iurian, Sonia; Turdean, Luana; Tomuta, Ioan

2017-01-01

This study focuses on the development of a drug product based on a risk assessment-based approach, within the quality by design paradigm. A prolonged release system was proposed for paliperidone (Pal) delivery, containing Kollidon ® SR as an insoluble matrix agent and hydroxypropyl cellulose, hydroxypropyl methylcellulose (HPMC), or sodium carboxymethyl cellulose as a hydrophilic polymer. The experimental part was preceded by the identification of potential sources of variability through Ishikawa diagrams, and failure mode and effects analysis was used to deliver the critical process parameters that were further optimized by design of experiments. A D-optimal design was used to investigate the effects of Kollidon SR ratio ( X 1 ), the type of hydrophilic polymer ( X 2 ), and the percentage of hydrophilic polymer ( X 3 ) on the percentages of dissolved Pal over 24 h ( Y 1 - Y 9 ). Effects expressed as regression coefficients and response surfaces were generated, along with a design space for the preparation of a target formulation in an experimental area with low error risk. The optimal formulation contained 27.62% Kollidon SR and 8.73% HPMC and achieved the prolonged release of Pal, with low burst effect, at ratios that were very close to the ones predicted by the model. Thus, the parameters with the highest impact on the final product quality were studied, and safe ranges were established for their variations. Finally, a risk mitigation and control strategy was proposed to assure the quality of the system, by constant process monitoring.

Cr(VI) transport via a supported ionic liquid membrane containing CYPHOS IL101 as carrier: system analysis and optimization through experimental design strategies.

PubMed

Rodríguez de San Miguel, Eduardo; Vital, Xóchitl; de Gyves, Josefina

2014-05-30

Chromium(VI) transport through a supported liquid membrane (SLM) system containing the commercial ionic liquid CYPHOS IL101 as carrier was studied. A reducing stripping phase was used as a mean to increase recovery and to simultaneously transform Cr(VI) into a less toxic residue for disposal or reuse. General functions which describe the time-depending evolution of the metal fractions in the cell compartments were defined and used in data evaluation. An experimental design strategy, using factorial and central-composite design matrices, was applied to assess the influence of the extractant, NaOH and citrate concentrations in the different phases, while a desirability function scheme allowed the synchronized optimization of depletion and recovery of the analyte. The mechanism for chromium permeation was analyzed and discussed to contribute to the understanding of the transfer process. The influence of metal concentration was evaluated as well. The presence of different interfering ions (Ca(2+), Al(3+), NO3(-), SO4(2-), and Cl(-)) at several Cr(VI): interfering ion ratios was studied through the use of a Plackett and Burman experimental design matrix. Under optimized conditions 90% of recovery was obtained from a feed solution containing 7mgL(-1) of Cr(VI) in 0.01moldm(-3) HCl medium after 5h of pertraction. Copyright © 2014 Elsevier B.V. All rights reserved.

Evaluation of thermal conductivity of MgO-MWCNTs/EG hybrid nanofluids based on experimental data by selecting optimal artificial neural networks

NASA Astrophysics Data System (ADS)

Vafaei, Masoud; Afrand, Masoud; Sina, Nima; Kalbasi, Rasool; Sourani, Forough; Teimouri, Hamid

2017-01-01

In this paper, the thermal conductivity ratio of MgO-MWCNTs/EG hybrid nanofluids has been predicted by an optimal artificial neural network at solid volume fractions of 0.05%, 0.1%, 0.15%, 0.2%, 0.4% and 0.6% in the temperature range of 25-50 °C. In this way, at the first, thirty six experimental data was presented to determine the thermal conductivity ratio of the hybrid nanofluid. Then, four optimal artificial neural networks with 6, 8, 10 and 12 neurons in hidden layer were designed to predict the thermal conductivity ratio of the nanofluid. The comparison between four optimal ANN results and experimental showed that the ANN with 12 neurons in hidden layer was the best model. Moreover, the results obtained from the best ANN indicated the maximum deviation margin of 0.8%.

Optimization of Maghemite (γ-Fe2O3) Nano-Powder Mixed micro-EDM of CoCrMo with Multiple Responses Using Gray Relational Analysis (GRA)

NASA Astrophysics Data System (ADS)

Mejid Elsiti, Nagwa; Noordin, M. Y.; Idris, Ani; Saed Majeed, Faraj

2017-10-01

This paper presents an optimization of process parameters of Micro-Electrical Discharge Machining (EDM) process with (γ-Fe2O3) nano-powder mixed dielectric using multi-response optimization Grey Relational Analysis (GRA) method instead of single response optimization. These parameters were optimized based on 2-Level factorial design combined with Grey Relational Analysis. The machining parameters such as peak current, gap voltage, and pulse on time were chosen for experimentation. The performance characteristics chosen for this study are material removal rate (MRR), tool wear rate (TWR), Taper and Overcut. Experiments were conducted using electrolyte copper as the tool and CoCrMo as the workpiece. Experimental results have been improved through this approach.

Central Composite Design Optimization of Zinc Removal from Contaminated Soil, Using Citric Acid as Biodegradable Chelant.

PubMed

Asadzadeh, Farrokh; Maleki-Kaklar, Mahdi; Soiltanalinejad, Nooshin; Shabani, Farzin

2018-02-08

Citric acid (CA) was evaluated in terms of its efficiency as a biodegradable chelating agent, in removing zinc (Zn) from heavily contaminated soil, using a soil washing process. To determine preliminary ranges of variables in the washing process, single factor experiments were carried out with different CA concentrations, pH levels and washing times. Optimization of batch washing conditions followed using a response surface methodology (RSM) based central composite design (CCD) approach. CCD predicted values and experimental results showed strong agreement, with an R 2 value of 0.966. Maximum removal of 92.8% occurred with a CA concentration of 167.6 mM, pH of 4.43, and washing time of 30 min as optimal variable values. A leaching column experiment followed, to examine the efficiency of the optimum conditions established by the CCD model. A comparison of two soil washing techniques indicated that the removal efficiency rate of the column experiment (85.8%) closely matching that of the batch experiment (92.8%). The methodology supporting the research experimentation for optimizing Zn removal may be useful in the design of protocols for practical engineering soil decontamination applications.

Optimization Techniques for Design Problems in Selected Areas in WSNs: A Tutorial

PubMed Central

Ibrahim, Ahmed; Alfa, Attahiru

2017-01-01

This paper is intended to serve as an overview of, and mostly a tutorial to illustrate, the optimization techniques used in several different key design aspects that have been considered in the literature of wireless sensor networks (WSNs). It targets the researchers who are new to the mathematical optimization tool, and wish to apply it to WSN design problems. We hence divide the paper into two main parts. One part is dedicated to introduce optimization theory and an overview on some of its techniques that could be helpful in design problem in WSNs. In the second part, we present a number of design aspects that we came across in the WSN literature in which mathematical optimization methods have been used in the design. For each design aspect, a key paper is selected, and for each we explain the formulation techniques and the solution methods implemented. We also provide in-depth analyses and assessments of the problem formulations, the corresponding solution techniques and experimental procedures in some of these papers. The analyses and assessments, which are provided in the form of comments, are meant to reflect the points that we believe should be taken into account when using optimization as a tool for design purposes. PMID:28763039

Optimization Techniques for Design Problems in Selected Areas in WSNs: A Tutorial.

PubMed

Ibrahim, Ahmed; Alfa, Attahiru

2017-08-01

This paper is intended to serve as an overview of, and mostly a tutorial to illustrate, the optimization techniques used in several different key design aspects that have been considered in the literature of wireless sensor networks (WSNs). It targets the researchers who are new to the mathematical optimization tool, and wish to apply it to WSN design problems. We hence divide the paper into two main parts. One part is dedicated to introduce optimization theory and an overview on some of its techniques that could be helpful in design problem in WSNs. In the second part, we present a number of design aspects that we came across in the WSN literature in which mathematical optimization methods have been used in the design. For each design aspect, a key paper is selected, and for each we explain the formulation techniques and the solution methods implemented. We also provide in-depth analyses and assessments of the problem formulations, the corresponding solution techniques and experimental procedures in some of these papers. The analyses and assessments, which are provided in the form of comments, are meant to reflect the points that we believe should be taken into account when using optimization as a tool for design purposes.

A FRAMEWORK TO DESIGN AND OPTIMIZE CHEMICAL FLOODING PROCESSES

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

Mojdeh Delshad; Gary A. Pope; Kamy Sepehrnoori

2005-07-01

The goal of this proposed research is to provide an efficient and user friendly simulation framework for screening and optimizing chemical/microbial enhanced oil recovery processes. The framework will include (1) a user friendly interface to identify the variables that have the most impact on oil recovery using the concept of experimental design and response surface maps, (2) UTCHEM reservoir simulator to perform the numerical simulations, and (3) an economic model that automatically imports the simulation production data to evaluate the profitability of a particular design. Such a reservoir simulation framework is not currently available to the oil industry. The objectivesmore » of Task 1 are to develop three primary modules representing reservoir, chemical, and well data. The modules will be interfaced with an already available experimental design model. The objective of the Task 2 is to incorporate UTCHEM reservoir simulator and the modules with the strategic variables and developing the response surface maps to identify the significant variables from each module. The objective of the Task 3 is to develop the economic model designed specifically for the chemical processes targeted in this proposal and interface the economic model with UTCHEM production output. Task 4 is on the validation of the framework and performing simulations of oil reservoirs to screen, design and optimize the chemical processes.« less

A Framework to Design and Optimize Chemical Flooding Processes

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

Mojdeh Delshad; Gary A. Pope; Kamy Sepehrnoori

2006-08-31

The goal of this proposed research is to provide an efficient and user friendly simulation framework for screening and optimizing chemical/microbial enhanced oil recovery processes. The framework will include (1) a user friendly interface to identify the variables that have the most impact on oil recovery using the concept of experimental design and response surface maps, (2) UTCHEM reservoir simulator to perform the numerical simulations, and (3) an economic model that automatically imports the simulation production data to evaluate the profitability of a particular design. Such a reservoir simulation framework is not currently available to the oil industry. The objectivesmore » of Task 1 are to develop three primary modules representing reservoir, chemical, and well data. The modules will be interfaced with an already available experimental design model. The objective of the Task 2 is to incorporate UTCHEM reservoir simulator and the modules with the strategic variables and developing the response surface maps to identify the significant variables from each module. The objective of the Task 3 is to develop the economic model designed specifically for the chemical processes targeted in this proposal and interface the economic model with UTCHEM production output. Task 4 is on the validation of the framework and performing simulations of oil reservoirs to screen, design and optimize the chemical processes.« less

A FRAMEWORK TO DESIGN AND OPTIMIZE CHEMICAL FLOODING PROCESSES

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

Mojdeh Delshad; Gary A. Pope; Kamy Sepehrnoori

2004-11-01

The goal of this proposed research is to provide an efficient and user friendly simulation framework for screening and optimizing chemical/microbial enhanced oil recovery processes. The framework will include (1) a user friendly interface to identify the variables that have the most impact on oil recovery using the concept of experimental design and response surface maps, (2) UTCHEM reservoir simulator to perform the numerical simulations, and (3) an economic model that automatically imports the simulation production data to evaluate the profitability of a particular design. Such a reservoir simulation framework is not currently available to the oil industry. The objectivesmore » of Task 1 are to develop three primary modules representing reservoir, chemical, and well data. The modules will be interfaced with an already available experimental design model. The objective of the Task 2 is to incorporate UTCHEM reservoir simulator and the modules with the strategic variables and developing the response surface maps to identify the significant variables from each module. The objective of the Task 3 is to develop the economic model designed specifically for the chemical processes targeted in this proposal and interface the economic model with UTCHEM production output. Task 4 is on the validation of the framework and performing simulations of oil reservoirs to screen, design and optimize the chemical processes.« less

Development, optimization, and in vitro characterization of dasatinib-loaded PEG functionalized chitosan capped gold nanoparticles using Box-Behnken experimental design.

PubMed

Adena, Sandeep Kumar Reddy; Upadhyay, Mansi; Vardhan, Harsh; Mishra, Brahmeshwar

2018-03-01

The purpose of this research study was to develop, optimize, and characterize dasatinib loaded polyethylene glycol (PEG) stabilized chitosan capped gold nanoparticles (DSB-PEG-Ch-GNPs). Gold (III) chloride hydrate was reduced with chitosan and the resulting nanoparticles were coated with thiol-terminated PEG and loaded with dasatinib (DSB). Plackett-Burman design (PBD) followed by Box-Behnken experimental design (BBD) were employed to optimize the process parameters. Polynomial equations, contour, and 3D response surface plots were generated to relate the factors and responses. The optimized DSB-PEG-Ch-GNPs were characterized by FTIR, XRD, HR-SEM, EDX, TEM, SAED, AFM, DLS, and ZP. The results of the optimized DSB-PEG-Ch-GNPs showed particle size (PS) of 24.39 ± 1.82 nm, apparent drug content (ADC) of 72.06 ± 0.86%, and zeta potential (ZP) of -13.91 ± 1.21 mV. The responses observed and the predicted values of the optimized process were found to be close. The shape and surface morphology studies showed that the resulting DSB-PEG-Ch-GNPs were spherical and smooth. The stability and in vitro drug release studies confirmed that the optimized formulation was stable at different conditions of storage and exhibited a sustained drug release of the drug of up to 76% in 48 h and followed Korsmeyer-Peppas release kinetic model. A process for preparing gold nanoparticles using chitosan, anchoring PEG to the particle surface, and entrapping dasatinib in the chitosan-PEG surface corona was optimized.

Optimization of flask culture medium and conditions for hyaluronic acid production by a Streptococcus equisimilis mutant nc2168.

PubMed

Chen, Yong-Hao; Li, Jun; Liu, Li; Liu, Hong-Zhi; Wang, Qiang

2012-10-01

A mutant designated NC2168, which was selected from wild-type Streptococcus equisimilis CVCC55116 by ultraviolet ray combined with(60)Co-γ ray treatment and does not produce streptolysin, was employed to produce hyaluronic acid (HA). In order to increase the output of HA in a flask, the culture medium and conditions for NC2168 were optimized in this study. The influence of culture medium ingredients including carbon sources, nitrogen sources and metal ions on HA production was evaluated using factional factorial design. The mathematical model, which represented the effect of each medium component and their interaction on the yield of HA, was established by the quadratic rotary combination design and response surface method. The model estimated that, a maximal yield of HA could be obtained when the concentrations of yeast extract, peptone, glucose, and MgSO4 were set at 3 g/100 mL, 2 g/100 mL, 0.5 g/100 mL and 0.15 g/100 mL, respectively. Compared with the values obtained by other runs in the experimental design, the optimized medium resulted in a remarkable increase in the output of HA and the maximum of the predicted HA production was 174.76 mg/L. The model developed was accurate and reliable for predicting the production of HA by NC2168.Cultivation conditions were optimized by an orthogonal experimental design and the optimal conditions were as follows: temperature 33°C, pH 7.8, agitation speed 200 rpm, medium volume 20 mL.

Modeling and optimization of joint quality for laser transmission joint of thermoplastic using an artificial neural network and a genetic algorithm

NASA Astrophysics Data System (ADS)

Wang, Xiao; Zhang, Cheng; Li, Pin; Wang, Kai; Hu, Yang; Zhang, Peng; Liu, Huixia

2012-11-01

A central composite rotatable experimental design(CCRD) is conducted to design experiments for laser transmission joining of thermoplastic-Polycarbonate (PC). The artificial neural network was used to establish the relationships between laser transmission joining process parameters (the laser power, velocity, clamp pressure, scanning number) and joint strength and joint seam width. The developed mathematical models are tested by analysis of variance (ANOVA) method to check their adequacy and the effects of process parameters on the responses and the interaction effects of key process parameters on the quality are analyzed and discussed. Finally, the desirability function coupled with genetic algorithm is used to carry out the optimization of the joint strength and joint width. The results show that the predicted results of the optimization are in good agreement with the experimental results, so this study provides an effective method to enhance the joint quality.

Experimental design

NASA Technical Reports Server (NTRS)

Lim, H. S.

1983-01-01

The design of long life, low weight nickel cadmium cells is studied. The status of a program to optimize nickel electrodes for the best performance is discussed. The pore size of the plaque, the mechanical strength and active material loading are considered in depth.

A Bayesian multi-stage cost-effectiveness design for animal studies in stroke research

PubMed Central

Cai, Chunyan; Ning, Jing; Huang, Xuelin

2017-01-01

Much progress has been made in the area of adaptive designs for clinical trials. However, little has been done regarding adaptive designs to identify optimal treatment strategies in animal studies. Motivated by an animal study of a novel strategy for treating strokes, we propose a Bayesian multi-stage cost-effectiveness design to simultaneously identify the optimal dose and determine the therapeutic treatment window for administrating the experimental agent. We consider a non-monotonic pattern for the dose-schedule-efficacy relationship and develop an adaptive shrinkage algorithm to assign more cohorts to admissible strategies. We conduct simulation studies to evaluate the performance of the proposed design by comparing it with two standard designs. These simulation studies show that the proposed design yields a significantly higher probability of selecting the optimal strategy, while it is generally more efficient and practical in terms of resource usage. PMID:27405325

Experimental design for evaluating WWTP data by linear mass balances.

PubMed

Le, Quan H; Verheijen, Peter J T; van Loosdrecht, Mark C M; Volcke, Eveline I P

2018-05-15

A stepwise experimental design procedure to obtain reliable data from wastewater treatment plants (WWTPs) was developed. The proposed procedure aims at determining sets of additional measurements (besides available ones) that guarantee the identifiability of key process variables, which means that their value can be calculated from other, measured variables, based on available constraints in the form of linear mass balances. Among all solutions, i.e. all possible sets of additional measurements allowing the identifiability of all key process variables, the optimal solutions were found taking into account two objectives, namely the accuracy of the identified key variables and the cost of additional measurements. The results of this multi-objective optimization problem were represented in a Pareto-optimal front. The presented procedure was applied to a full-scale WWTP. Detailed analysis of the relation between measurements allowed the determination of groups of overlapping mass balances. Adding measured variables could only serve in identifying key variables that appear in the same group of mass balances. Besides, the application of the experimental design procedure to these individual groups significantly reduced the computational effort in evaluating available measurements and planning additional monitoring campaigns. The proposed procedure is straightforward and can be applied to other WWTPs with or without prior data collection. Copyright © 2018 Elsevier Ltd. All rights reserved.

Optimization of an angle-beam ultrasonic approach for characterization of impact damage in composites

NASA Astrophysics Data System (ADS)

Henry, Christine; Kramb, Victoria; Welter, John T.; Wertz, John N.; Lindgren, Eric A.; Aldrin, John C.; Zainey, David

2018-04-01

Advances in NDE method development are greatly improved through model-guided experimentation. In the case of ultrasonic inspections, models which provide insight into complex mode conversion processes and sound propagation paths are essential for understanding the experimental data and inverting the experimental data into relevant information. However, models must also be verified using experimental data obtained under well-documented and understood conditions. Ideally, researchers would utilize the model simulations and experimental approach to efficiently converge on the optimal solution. However, variability in experimental parameters introduce extraneous signals that are difficult to differentiate from the anticipated response. This paper discusses the results of an ultrasonic experiment designed to evaluate the effect of controllable variables on the anticipated signal, and the effect of unaccounted for experimental variables on the uncertainty in those results. Controlled experimental parameters include the transducer frequency, incidence beam angle and focal depth.

Dual-mode ultraflow access networks: a hybrid solution for the access bottleneck

NASA Astrophysics Data System (ADS)

Kazovsky, Leonid G.; Shen, Thomas Shunrong; Dhaini, Ahmad R.; Yin, Shuang; De Leenheer, Marc; Detwiler, Benjamin A.

2013-12-01

Optical Flow Switching (OFS) is a promising solution for large Internet data transfers. In this paper, we introduce UltraFlow Access, a novel optical access network architecture that offers dual-mode service to its end-users: IP and OFS. With UltraFlow Access, we design and implement a new dual-mode control plane and a new dual-mode network stack to ensure efficient connection setup and reliable and optimal data transmission. We study the impact of the UltraFlow system's design on the network throughput. Our experimental results show that with an optimized system design, near optimal (around 10 Gb/s) OFS data throughput can be attained when the line rate is 10Gb/s.

Teaching-learning-based Optimization Algorithm for Parameter Identification in the Design of IIR Filters

NASA Astrophysics Data System (ADS)

Singh, R.; Verma, H. K.

2013-12-01

This paper presents a teaching-learning-based optimization (TLBO) algorithm to solve parameter identification problems in the designing of digital infinite impulse response (IIR) filter. TLBO based filter modelling is applied to calculate the parameters of unknown plant in simulations. Unlike other heuristic search algorithms, TLBO algorithm is an algorithm-specific parameter-less algorithm. In this paper big bang-big crunch (BB-BC) optimization and PSO algorithms are also applied to filter design for comparison. Unknown filter parameters are considered as a vector to be optimized by these algorithms. MATLAB programming is used for implementation of proposed algorithms. Experimental results show that the TLBO is more accurate to estimate the filter parameters than the BB-BC optimization algorithm and has faster convergence rate when compared to PSO algorithm. TLBO is used where accuracy is more essential than the convergence speed.

Analysis and Design of Rotors at Ultra-Low Reynolds Numbers

NASA Technical Reports Server (NTRS)

Kunz, Peter J.; Strawn, Roger C.

2003-01-01

Design tools have been developed for ultra-low Reynolds number rotors, combining enhanced actuator-ring / blade-element theory with airfoil section data based on two-dimensional Navier-Stokes calculations. This performance prediction method is coupled with an optimizer for both design and analysis applications. Performance predictions from these tools have been compared with three-dimensional Navier Stokes analyses and experimental data for a 2.5 cm diameter rotor with chord Reynolds numbers below 10,000. Comparisons among the analyses and experimental data show reasonable agreement both in the global thrust and power required, but the spanwise distributions of these quantities exhibit significant deviations. The study also reveals that three-dimensional and rotational effects significantly change local airfoil section performance. The magnitude of this issue, unique to this operating regime, may limit the applicability of blade-element type methods for detailed rotor design at ultra-low Reynolds numbers, but these methods are still useful for evaluating concept feasibility and rapidly generating initial designs for further analysis and optimization using more advanced tools.

Intracavity adaptive optics. 1: Astigmatism correction performance.

PubMed

Spinhirne, J M; Anafi, D; Freeman, R H; Garcia, H R

1981-03-15

A detailed experimental study has been conducted on adaptive optical control methodologies inside a laser resonator. A comparison is presented of several optimization techniques using a multidither zonal coherent optical adaptive technique system within a laser resonator for the correction of astigmatism. A dramatic performance difference is observed when optimizing on beam quality compared with optimizing on power-in-the-bucket. Experimental data are also presented on proper selection criteria for dither frequencies when controlling phase front errors. The effects of hardware limitations and design considerations on the performance of the system are presented, and general conclusions and physical interpretations on the results are made when possible.

A divide-and-conquer approach to determine the Pareto frontier for optimization of protein engineering experiments.

PubMed

He, Lu; Friedman, Alan M; Bailey-Kellogg, Chris

2012-03-01

In developing improved protein variants by site-directed mutagenesis or recombination, there are often competing objectives that must be considered in designing an experiment (selecting mutations or breakpoints): stability versus novelty, affinity versus specificity, activity versus immunogenicity, and so forth. Pareto optimal experimental designs make the best trade-offs between competing objectives. Such designs are not "dominated"; that is, no other design is better than a Pareto optimal design for one objective without being worse for another objective. Our goal is to produce all the Pareto optimal designs (the Pareto frontier), to characterize the trade-offs and suggest designs most worth considering, but to avoid explicitly considering the large number of dominated designs. To do so, we develop a divide-and-conquer algorithm, Protein Engineering Pareto FRontier (PEPFR), that hierarchically subdivides the objective space, using appropriate dynamic programming or integer programming methods to optimize designs in different regions. This divide-and-conquer approach is efficient in that the number of divisions (and thus calls to the optimizer) is directly proportional to the number of Pareto optimal designs. We demonstrate PEPFR with three protein engineering case studies: site-directed recombination for stability and diversity via dynamic programming, site-directed mutagenesis of interacting proteins for affinity and specificity via integer programming, and site-directed mutagenesis of a therapeutic protein for activity and immunogenicity via integer programming. We show that PEPFR is able to effectively produce all the Pareto optimal designs, discovering many more designs than previous methods. The characterization of the Pareto frontier provides additional insights into the local stability of design choices as well as global trends leading to trade-offs between competing criteria. Copyright © 2011 Wiley Periodicals, Inc.

A computer simulator for development of engineering system design methodologies

NASA Technical Reports Server (NTRS)

Padula, S. L.; Sobieszczanski-Sobieski, J.

1987-01-01

A computer program designed to simulate and improve engineering system design methodology is described. The simulator mimics the qualitative behavior and data couplings occurring among the subsystems of a complex engineering system. It eliminates the engineering analyses in the subsystems by replacing them with judiciously chosen analytical functions. With the cost of analysis eliminated, the simulator is used for experimentation with a large variety of candidate algorithms for multilevel design optimization to choose the best ones for the actual application. Thus, the simulator serves as a development tool for multilevel design optimization strategy. The simulator concept, implementation, and status are described and illustrated with examples.

RARtool: A MATLAB Software Package for Designing Response-Adaptive Randomized Clinical Trials with Time-to-Event Outcomes.

PubMed

Ryeznik, Yevgen; Sverdlov, Oleksandr; Wong, Weng Kee

2015-08-01

Response-adaptive randomization designs are becoming increasingly popular in clinical trial practice. In this paper, we present RARtool , a user interface software developed in MATLAB for designing response-adaptive randomized comparative clinical trials with censored time-to-event outcomes. The RARtool software can compute different types of optimal treatment allocation designs, and it can simulate response-adaptive randomization procedures targeting selected optimal allocations. Through simulations, an investigator can assess design characteristics under a variety of experimental scenarios and select the best procedure for practical implementation. We illustrate the utility of our RARtool software by redesigning a survival trial from the literature.

Biologically Inspired, Anisoptropic Flexible Wing for Optimal Flapping Flight

DTIC Science & Technology

2013-01-31

Anisotropic Flexible Wing for Optimal Flapping Flight FA9550-07-1-0547 Sb. GRANT NUMBER Sc. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Sd. PROJECT NUMBER...anisotropic structural flexibility ; c) Conducted coordinated experimental and computational modeling to determine the roles of aerodynamic loading, wing inertia...and structural flexibility and elasticity; and d) Developed surrogate tools for flapping wing MA V design and optimization. Detailed research

Taguchi experimental design to determine the taste quality characteristic of candied carrot

NASA Astrophysics Data System (ADS)

Ekawati, Y.; Hapsari, A. A.

2018-03-01

Robust parameter design is used to design product that is robust to noise factors so the product’s performance fits the target and delivers a better quality. In the process of designing and developing the innovative product of candied carrot, robust parameter design is carried out using Taguchi Method. The method is used to determine an optimal quality design. The optimal quality design is based on the process and the composition of product ingredients that are in accordance with consumer needs and requirements. According to the identification of consumer needs from the previous research, quality dimensions that need to be assessed are the taste and texture of the product. The quality dimension assessed in this research is limited to the taste dimension. Organoleptic testing is used for this assessment, specifically hedonic testing that makes assessment based on consumer preferences. The data processing uses mean and signal to noise ratio calculation and optimal level setting to determine the optimal process/composition of product ingredients. The optimal value is analyzed using confirmation experiments to prove that proposed product match consumer needs and requirements. The result of this research is identification of factors that affect the product taste and the optimal quality of product according to Taguchi Method.

Experimental Investigation of the Application of Microramp Flow Control to an Oblique Shock Interaction

NASA Technical Reports Server (NTRS)

Hirt, Stefanie M.; Anderson, Bernhard H.

2009-01-01

The effectiveness of microramp flow control devices in controlling an oblique shock interaction was tested in the 15- by 15-Centimeter Supersonic Wind Tunnel at NASA Glenn Research Center. Fifteen microramp geometries were tested varying the height, chord length, and spacing between ramps. Measurements of the boundary layer properties downstream of the shock reflection were analyzed using design of experiments methods. Results from main effects, D-optimal, full factorial, and central composite designs were compared. The designs provided consistent results for a single variable optimization.

Optimization of the combined ultrasonic assisted/adsorption method for the removal of malachite green by gold nanoparticles loaded on activated carbon: experimental design.

PubMed

Roosta, M; Ghaedi, M; Shokri, N; Daneshfar, A; Sahraei, R; Asghari, A

2014-01-24

The present study was aimed to experimental design optimization applied to removal of malachite green (MG) from aqueous solution by ultrasound-assisted removal onto the gold nanoparticles loaded on activated carbon (Au-NP-AC). This nanomaterial was characterized using different techniques such as FESEM, TEM, BET, and UV-vis measurements. The effects of variables such as pH, initial dye concentration, adsorbent dosage (g), temperature and sonication time on MG removal were studied using central composite design (CCD) and the optimum experimental conditions were found with desirability function (DF) combined response surface methodology (RSM). Fitting the experimental equilibrium data to various isotherm models such as Langmuir, Freundlich, Tempkin and Dubinin-Radushkevich models show the suitability and applicability of the Langmuir model. Kinetic models such as pseudo -first order, pseudo-second order, Elovich and intraparticle diffusion models applicability was tested for experimental data and the second-order equation and intraparticle diffusion models control the kinetic of the adsorption process. The small amount of proposed adsorbent (0.015 g) is applicable for successful removal of MG (RE>99%) in short time (4.4 min) with high adsorption capacity (140-172 mg g(-1)). Copyright © 2013. Published by Elsevier B.V.

Optimality models in the age of experimental evolution and genomics.

PubMed

Bull, J J; Wang, I-N

2010-09-01

Optimality models have been used to predict evolution of many properties of organisms. They typically neglect genetic details, whether by necessity or design. This omission is a common source of criticism, and although this limitation of optimality is widely acknowledged, it has mostly been defended rather than evaluated for its impact. Experimental adaptation of model organisms provides a new arena for testing optimality models and for simultaneously integrating genetics. First, an experimental context with a well-researched organism allows dissection of the evolutionary process to identify causes of model failure--whether the model is wrong about genetics or selection. Second, optimality models provide a meaningful context for the process and mechanics of evolution, and thus may be used to elicit realistic genetic bases of adaptation--an especially useful augmentation to well-researched genetic systems. A few studies of microbes have begun to pioneer this new direction. Incompatibility between the assumed and actual genetics has been demonstrated to be the cause of model failure in some cases. More interestingly, evolution at the phenotypic level has sometimes matched prediction even though the adaptive mutations defy mechanisms established by decades of classic genetic studies. Integration of experimental evolutionary tests with genetics heralds a new wave for optimality models and their extensions that does not merely emphasize the forces driving evolution.

Characterization and Optimization Design of the Polymer-Based Capacitive Micro-Arrayed Ultrasonic Transducer

NASA Astrophysics Data System (ADS)

Chiou, De-Yi; Chen, Mu-Yueh; Chang, Ming-Wei; Deng, Hsu-Cheng

2007-11-01

This study constructs an electromechanical finite element model of the polymer-based capacitive micro-arrayed ultrasonic transducer (P-CMUT). The electrostatic-structural coupled-field simulations are performed to investigate the operational characteristics, such as collapse voltage and resonant frequency. The numerical results are found to be in good agreement with experimental observations. The study of influence of each defined parameter on the collapse voltage and resonant frequency are also presented. To solve some conflict problems in diversely physical fields, an integrated design method is developed to optimize the geometric parameters of the P-CMUT. The optimization search routine conducted using the genetic algorithm (GA) is connected with the commercial FEM software ANSYS to obtain the best design variable using multi-objective functions. The results show that the optimal parameter values satisfy the conflicting objectives, namely to minimize the collapse voltage while simultaneously maintaining a customized frequency. Overall, the present result indicates that the combined FEM/GA optimization scheme provides an efficient and versatile approach of optimization design of the P-CMUT.

Enzymatic catalysis treatment method of meat industry wastewater using lacasse.

PubMed

Thirugnanasambandham, K; Sivakumar, V

2015-01-01

The process of meat industry produces in a large amount of wastewater that contains high levels of colour and chemical oxygen demand (COD). So they must be pretreated before their discharge into the ecological system. In this paper, enzymatic catalysis (EC) was adopted to treat the meat wastewater. Box-Behnken design (BBD), an experimental design for response surface methodology (RSM), was used to create a set of 29 experimental runs needed for optimizing of the operating conditions. Quadratic regression models with estimated coefficients were developed to describe the colour and COD removals. The experimental results show that EC could effectively reduce colour (95 %) and COD (86 %) at the optimum conditions of enzyme dose of 110 U/L, incubation time of 100 min, pH of 7 and temperature of 40 °C. RSM could be effectively adopted to optimize the operating multifactors in complex EC process.

Optimization and evaluation of clarithromycin floating tablets using experimental mixture design.

PubMed

Uğurlu, Timucin; Karaçiçek, Uğur; Rayaman, Erkan

2014-01-01

The purpose of the study was to prepare and evaluate clarithromycin (CLA) floating tablets using experimental mixture design for treatment of Helicobacter pylori provided by prolonged gastric residence time and controlled plasma level. Ten different formulations were generated based on different molecular weight of hypromellose (HPMC K100, K4M, K15M) by using simplex lattice design (a sub-class of mixture design) with Minitab 16 software. Sodium bicarbonate and anhydrous citric acid were used as gas generating agents. Tablets were prepared by wet granulation technique. All of the process variables were fixed. Results of cumulative drug release at 8th h (CDR 8th) were statistically analyzed to get optimized formulation (OF). Optimized formulation, which gave floating lag time lower than 15 s and total floating time more than 10 h, was analyzed and compared with target for CDR 8th (80%). A good agreement was shown between predicted and actual values of CDR 8th with a variation lower than 1%. The activity of clarithromycin contained optimizedformula against H. pylori were quantified using well diffusion agar assay. Diameters of inhibition zones vs. log10 clarithromycin concentrations were plotted in order to obtain a standard curve and clarithromycin activity.

The Design and Implementation of Adsorptive Removal of Cu(II) from Leachate Using ANFIS

PubMed Central

Turan, Nurdan Gamze; Ozgonenel, Okan

2013-01-01

Clinoptilolite was investigated for the removal of Cu(II) ions from industrial leachate. Adaptive neural fuzzy interface system (ANFIS) was used for modeling the batch experimental system and predicting the optimal input values, that is, initial pH, adsorbent dosage, and contact time. Experiments were studied under laboratory batch and fixed bed conditions. The outcomes of suggested ANFIS modeling were then compared to a full factorial experimental design (23), which was utilized to assess the effect of three factors on the adsorption of Cu(II) ions in aqueous leachate of industrial waste. It was observed that the optimized parameters are almost close to each other. The highest removal efficiency was found as about 93.65% at pH 6, adsorbent dosage 11.4 g/L, and contact time 33 min for batch conditions of 23 experimental design and about 90.43% at pH 5, adsorbent dosage 15 g/L and contact time 35 min for batch conditions of ANFIS. The results show that clinoptilolite is an efficient sorbent and ANFIS, which is easy to implement and is able to model the batch experimental system. PMID:23844405

Optimization of the intravenous glucose tolerance test in T2DM patients using optimal experimental design.

PubMed

Silber, Hanna E; Nyberg, Joakim; Hooker, Andrew C; Karlsson, Mats O

2009-06-01

Intravenous glucose tolerance test (IVGTT) provocations are informative, but complex and laborious, for studying the glucose-insulin system. The objective of this study was to evaluate, through optimal design methodology, the possibilities of more informative and/or less laborious study design of the insulin modified IVGTT in type 2 diabetic patients. A previously developed model for glucose and insulin regulation was implemented in the optimal design software PopED 2.0. The following aspects of the study design of the insulin modified IVGTT were evaluated; (1) glucose dose, (2) insulin infusion, (3) combination of (1) and (2), (4) sampling times, (5) exclusion of labeled glucose. Constraints were incorporated to avoid prolonged hyper- and/or hypoglycemia and a reduced design was used to decrease run times. Design efficiency was calculated as a measure of the improvement with an optimal design compared to the basic design. The results showed that the design of the insulin modified IVGTT could be substantially improved by the use of an optimized design compared to the standard design and that it was possible to use a reduced number of samples. Optimization of sample times gave the largest improvement followed by insulin dose. The results further showed that it was possible to reduce the total sample time with only a minor loss in efficiency. Simulations confirmed the predictions from PopED. The predicted uncertainty of parameter estimates (CV) was low in all tested cases, despite the reduction in the number of samples/subject. The best design had a predicted average CV of parameter estimates of 19.5%. We conclude that improvement can be made to the design of the insulin modified IVGTT and that the most important design factor was the placement of sample times followed by the use of an optimal insulin dose. This paper illustrates how complex provocation experiments can be improved by sequential modeling and optimal design.

Optimization of Bioactive Ingredient Extraction from Chinese Herbal Medicine Glycyrrhiza glabra: A Comparative Study of Three Optimization Models

PubMed Central

Li, Xiaohong; Zhang, Yuyan

2018-01-01

The ultraviolet spectrophotometric method is often used for determining the content of glycyrrhizic acid from Chinese herbal medicine Glycyrrhiza glabra. Based on the traditional single variable approach, four extraction parameters of ammonia concentration, ethanol concentration, circumfluence time, and liquid-solid ratio are adopted as the independent extraction variables. In the present work, central composite design of four factors and five levels is applied to design the extraction experiments. Subsequently, the prediction models of response surface methodology, artificial neural networks, and genetic algorithm-artificial neural networks are developed to analyze the obtained experimental data, while the genetic algorithm is utilized to find the optimal extraction parameters for the above well-established models. It is found that the optimization of extraction technology is presented as ammonia concentration 0.595%, ethanol concentration 58.45%, return time 2.5 h, and liquid-solid ratio 11.065 : 1. Under these conditions, the model predictive value is 381.24 mg, the experimental average value is 376.46 mg, and the expectation discrepancy is 4.78 mg. For the first time, a comparative study of these three approaches is conducted for the evaluation and optimization of the effects of the extraction independent variables. Furthermore, it is demonstrated that the combinational method of genetic algorithm and artificial neural networks provides a more reliable and more accurate strategy for design and optimization of glycyrrhizic acid extraction from Glycyrrhiza glabra. PMID:29887907

Optimization of Bioactive Ingredient Extraction from Chinese Herbal Medicine Glycyrrhiza glabra: A Comparative Study of Three Optimization Models.

PubMed

Yu, Li; Jin, Weifeng; Li, Xiaohong; Zhang, Yuyan

2018-01-01

The ultraviolet spectrophotometric method is often used for determining the content of glycyrrhizic acid from Chinese herbal medicine Glycyrrhiza glabra . Based on the traditional single variable approach, four extraction parameters of ammonia concentration, ethanol concentration, circumfluence time, and liquid-solid ratio are adopted as the independent extraction variables. In the present work, central composite design of four factors and five levels is applied to design the extraction experiments. Subsequently, the prediction models of response surface methodology, artificial neural networks, and genetic algorithm-artificial neural networks are developed to analyze the obtained experimental data, while the genetic algorithm is utilized to find the optimal extraction parameters for the above well-established models. It is found that the optimization of extraction technology is presented as ammonia concentration 0.595%, ethanol concentration 58.45%, return time 2.5 h, and liquid-solid ratio 11.065 : 1. Under these conditions, the model predictive value is 381.24 mg, the experimental average value is 376.46 mg, and the expectation discrepancy is 4.78 mg. For the first time, a comparative study of these three approaches is conducted for the evaluation and optimization of the effects of the extraction independent variables. Furthermore, it is demonstrated that the combinational method of genetic algorithm and artificial neural networks provides a more reliable and more accurate strategy for design and optimization of glycyrrhizic acid extraction from Glycyrrhiza glabra .

Stochastic modeling and control system designs of the NASA/MSFC Ground Facility for large space structures: The maximum entropy/optimal projection approach

NASA Technical Reports Server (NTRS)

Hsia, Wei-Shen

1986-01-01

In the Control Systems Division of the Systems Dynamics Laboratory of the NASA/MSFC, a Ground Facility (GF), in which the dynamics and control system concepts being considered for Large Space Structures (LSS) applications can be verified, was designed and built. One of the important aspects of the GF is to design an analytical model which will be as close to experimental data as possible so that a feasible control law can be generated. Using Hyland's Maximum Entropy/Optimal Projection Approach, a procedure was developed in which the maximum entropy principle is used for stochastic modeling and the optimal projection technique is used for a reduced-order dynamic compensator design for a high-order plant.

Investigation of a 7-pole/6-slot Halbach-magnetized permanent-magnet linear alternator used for free-piston stirling engines

NASA Astrophysics Data System (ADS)

Zheng, Ping; Tong, Chengde; Zhao, Jing; Yu, Bin; Li, Lin; Bai, Jingang; Zhang, Lu

2012-04-01

This paper investigates a 7-pole/6-slot Halbach-magnetized permanent-magnet linear alternator used for free piston Stirling engines (FPSEs). Taking the advantages of Halbach array, a 1 kW prototype alternator is designed. Considering the rms value of electromotive force (EMF) and harmonic distortion, the optimal length ratio of the axial- and radial-magnetized permanent magnets and thicknesses of the permanent magnets are optimized by 2D finite element method. The alternator detent force, which is an important factor for smooth operation of FPSEs, is studied by optimizing slot tip and end tooth. The load and thermal performances of the final design are simulated. A prototype alternator was designed, built and tested. Experimental data indicated satisfactory design.

Optimum Tolerance Design Using Component-Amount and Mixture-Amount Experiments

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

Piepel, Gregory F.; Ozler, Cenk; Sehirlioglu, Ali Kemal

2013-08-01

One type of tolerance design problem involves optimizing component and assembly tolerances to minimize the total cost (sum of manufacturing cost and quality loss). Previous literature recommended using traditional response surface (RS) designs and models to solve this type of tolerance design problem. In this article, component-amount (CA) and mixture-amount (MA) approaches are proposed as more appropriate for solving this type of tolerance design problem. The advantages of the CA and MA approaches over the RS approach are discussed. Reasons for choosing between the CA and MA approaches are also discussed. The CA and MA approaches (experimental design, response modeling,more » and optimization) are illustrated using real examples.« less

A Novel Latin Hypercube Algorithm via Translational Propagation

PubMed Central

Pan, Guang; Ye, Pengcheng

2014-01-01

Metamodels have been widely used in engineering design to facilitate analysis and optimization of complex systems that involve computationally expensive simulation programs. The accuracy of metamodels is directly related to the experimental designs used. Optimal Latin hypercube designs are frequently used and have been shown to have good space-filling and projective properties. However, the high cost in constructing them limits their use. In this paper, a methodology for creating novel Latin hypercube designs via translational propagation and successive local enumeration algorithm (TPSLE) is developed without using formal optimization. TPSLE algorithm is based on the inspiration that a near optimal Latin Hypercube design can be constructed by a simple initial block with a few points generated by algorithm SLE as a building block. In fact, TPSLE algorithm offers a balanced trade-off between the efficiency and sampling performance. The proposed algorithm is compared to two existing algorithms and is found to be much more efficient in terms of the computation time and has acceptable space-filling and projective properties. PMID:25276844

Wrinkle-free design of thin membrane structures using stress-based topology optimization

NASA Astrophysics Data System (ADS)

Luo, Yangjun; Xing, Jian; Niu, Yanzhuang; Li, Ming; Kang, Zhan

2017-05-01

Thin membrane structures would experience wrinkling due to local buckling deformation when compressive stresses are induced in some regions. Using the stress criterion for membranes in wrinkled and taut states, this paper proposed a new stress-based topology optimization methodology to seek the optimal wrinkle-free design of macro-scale thin membrane structures under stretching. Based on the continuum model and linearly elastic assumption in the taut state, the optimization problem is defined as to maximize the structural stiffness under membrane area and principal stress constraints. In order to make the problem computationally tractable, the stress constraints are reformulated into equivalent ones and relaxed by a cosine-type relaxation scheme. The reformulated optimization problem is solved by a standard gradient-based algorithm with the adjoint-variable sensitivity analysis. Several examples with post-bulking simulations and experimental tests are given to demonstrate the effectiveness of the proposed optimization model for eliminating stress-related wrinkles in the novel design of thin membrane structures.

Broadband angle-independent antireflection coatings on nanostructured light trapping solar cells

NASA Astrophysics Data System (ADS)

Vázquez-Guardado, Abraham; Boroumand, Javaneh; Franklin, Daniel; Chanda, Debashis

2018-03-01

Backscattering from nanostructured surfaces greatly diminishes the efficacy of light trapping solar cells. While the analytical design of broadband, angle-independent antireflection coatings on nanostructured surfaces proved inefficient, numerical optimization proves a viable alternative. Here, we numerically design and experimentally verify the performance of single and bilayer antireflection coatings on a 2D hexagonal diffractive light trapping pattern on crystalline silicon substrates. Three well-known antireflection coatings, aluminum oxide, silicon nitride, and silicon oxide, which also double as high-quality surface passivation materials, are studied in the 400-1000 nm band. By varying thickness and conformity, the optimal parameters that minimize the broadband total reflectance (specular and scattering) from the nanostructured surface are obtained. The design results in a single-layer antireflection coating with normal-angle wavelength-integrated reflectance below 4% and a bilayer antireflection coating demonstrating reflection down to 1.5%. We show experimentally an angle-averaged reflectance of ˜5.2 % up to 60° incident angle from the optimized bilayer antireflection-coated nanostructured surface, paving the path toward practical implementation of the light trapping solar cells.

Photonic crystal enhanced silicon cell based thermophotovoltaic systems

DOE PAGES

Yeng, Yi Xiang; Chan, Walker R.; Rinnerbauer, Veronika; ...

2015-01-30

We report the design, optimization, and experimental results of large area commercial silicon solar cell based thermophotovoltaic (TPV) energy conversion systems. Using global non-linear optimization tools, we demonstrate theoretically a maximum radiative heat-to-electricity efficiency of 6.4% and a corresponding output electrical power density of 0.39 W cm⁻² at temperature T = 1660 K when implementing both the optimized two-dimensional (2D) tantalum photonic crystal (PhC) selective emitter, and the optimized 1D tantalum pentoxide – silicon dioxide PhC cold-side selective filter. In addition, we have developed an experimental large area TPV test setup that enables accurate measurement of radiative heat-to-electricity efficiency formore » any emitter-filter-TPV cell combination of interest. In fact, the experimental results match extremely well with predictions of our numerical models. Our experimental setup achieved a maximum output electrical power density of 0.10W cm⁻² and radiative heat-to-electricity efficiency of 1.18% at T = 1380 K using commercial wafer size back-contacted silicon solar cells.« less

Ultrasound-assisted magnetic dispersive solid-phase microextraction: A novel approach for the rapid and efficient microextraction of naproxen and ibuprofen employing experimental design with high-performance liquid chromatography.

PubMed

Ghorbani, Mahdi; Chamsaz, Mahmoud; Rounaghi, Gholam Hossein

2016-03-01

A simple, rapid, and sensitive method for the determination of naproxen and ibuprofen in complex biological and water matrices (cow milk, human urine, river, and well water samples) has been developed using ultrasound-assisted magnetic dispersive solid-phase microextraction. Magnetic ethylendiamine-functionalized graphene oxide nanocomposite was synthesized and used as a novel adsorbent for the microextraction process and showed great adsorptive ability toward these analytes. Different parameters affecting the microextraction were optimized with the aid of the experimental design approach. A Plackett-Burman screening design was used to study the main variables affecting the microextraction process, and the Box-Behnken optimization design was used to optimize the previously selected variables for extraction of naproxen and ibuprofen. The optimized technique provides good repeatability (relative standard deviations of the intraday precision 3.1 and 3.3, interday precision of 5.6 and 6.1%), linearity (0.1-500 and 0.3-650 ng/mL), low limits of detection (0.03 and 0.1 ng/mL), and a high enrichment factor (168 and 146) for naproxen and ibuprofen, respectively. The proposed method can be successfully applied in routine analysis for determination of naproxen and ibuprofen in cow milk, human urine, and real water samples. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Optimization and modeling of laccase production by Trametes versicolor in a bioreactor using statistical experimental design.

PubMed

Tavares, A P M; Coelho, M A Z; Agapito, M S M; Coutinho, J A P; Xavier, A M R B

2006-09-01

Experimental design and response surface methodologies were applied to optimize laccase production by Trametes versicolor in a bioreactor. The effects of three factors, initial glucose concentration (0 and 9 g/L), agitation (100 and 180 rpm), and pH (3.0 and 5.0), were evaluated to identify the significant effects and its interactions in the laccase production. The pH of the medium was found to be the most important factor, followed by initial glucose concentration and the interaction of both factors. Agitation did not seem to play an important role in laccase production, nor did the interaction agitation x medium pH and agitation x initial glucose concentration. Response surface analysis showed that an initial glucose concentration of 11 g/L and pH controlled at 5.2 were the optimal conditions for laccase production by T. versicolor. Under these conditions, the predicted value for laccase activity was >10,000 U/L, which is in good agreement with the laccase activity obtained experimentally (11,403 U/L). In addition, a mathematical model for the bioprocess was developed. It is shown that it provides a good description of the experimental profile observed, and that it is capable of predicting biomass growth based on secondary process variables.

Experimental design, modeling and optimization of polyplex formation between DNA oligonucleotides and branched polyethylenimine.

PubMed

Clima, Lilia; Ursu, Elena L; Cojocaru, Corneliu; Rotaru, Alexandru; Barboiu, Mihail; Pinteala, Mariana

2015-09-28

The complexes formed by DNA and polycations have received great attention owing to their potential application in gene therapy. In this study, the binding efficiency between double-stranded oligonucleotides (dsDNA) and branched polyethylenimine (B-PEI) has been quantified by processing of the images captured from the gel electrophoresis assays. The central composite experimental design has been employed to investigate the effects of controllable factors on the binding efficiency. On the basis of experimental data and the response surface methodology, a multivariate regression model has been constructed and statistically validated. The model has enabled us to predict the binding efficiency depending on experimental factors, such as concentrations of dsDNA and B-PEI as well as the initial pH of solution. The optimization of the binding process has been performed using simplex and gradient methods. The optimal conditions determined for polyplex formation have yielded a maximal binding efficiency close to 100%. In order to reveal the mechanism of complex formation at the atomic-scale, a molecular dynamic simulation has been carried out. According to the computation results, B-PEI amine hydrogen atoms have interacted with oxygen atoms from dsDNA phosphate groups. These interactions have led to the formation of hydrogen bonds between macromolecules, stabilizing the polyplex structure.

Optimization of permeability for quality improvement by using factorial design

NASA Astrophysics Data System (ADS)

Said, Rahaini Mohd; Miswan, Nor Hamizah; Juan, Ng Shu; Hussin, Nor Hafizah; Ahmad, Aminah; Kamal, Mohamad Ridzuan Mohamad

2017-05-01

Sand castings are used worldwide by the manufacturing process in Metal Casting Industry, whereby the green sand are the commonly used sand mould type in the industry of sand casting. The defects on the surface of casting product is one of the problems in the industry of sand casting. The problems that relates to the defect composition of green sand are such as blowholes, pinholes shrinkage and porosity. Our objective is to optimize the best composition of green sand in order to minimize the occurrence of defects. Sand specimen of difference parameters (Bentonite, Green Sand, Cold dust and water) were design and prepared to undergo permeability test. The 24 factorial design experiment with four factors at difference composition were runs, and the total of 16 runs experiment were conducted. The developed models based on the experimental design necessary models were obtained. The model with a high coefficient of determination (R2=0.9841) and model for predicted and actual fitted well with the experimental data. Using the Analysis of Design Expert software, we identified that bentonite and water are the main interaction effect in the experiments. The optimal settings for green sand composition are 100g silica sand, 21g bentonite, 6.5 g water and 6g coal dust. This composition gives an effect of permeability number 598.3GP.

Computer-aided design and experimental investigation of a hydrodynamic device: the microwire electrode

PubMed

Fulian; Gooch; Fisher; Stevens; Compton

2000-08-01

The development and application of a new electrochemical device using a computer-aided design strategy is reported. This novel design is based on the flow of electrolyte solution past a microwire electrode situated centrally within a large duct. In the design stage, finite element simulations were employed to evaluate feasible working geometries and mass transport rates. The computer-optimized designs were then exploited to construct experimental devices. Steady-state voltammetric measurements were performed for a reversible one-electron-transfer reaction to establish the experimental relationship between electrolysis current and solution velocity. The experimental results are compared to those predicted numerically, and good agreement is found. The numerical studies are also used to establish an empirical relationship between the mass transport limited current and the volume flow rate, providing a simple and quantitative alternative for workers who would prefer to exploit this device without the need to develop the numerical aspects.

Application of experimental design for the optimization of artificial neural network-based water quality model: a case study of dissolved oxygen prediction.

PubMed

Šiljić Tomić, Aleksandra; Antanasijević, Davor; Ristić, Mirjana; Perić-Grujić, Aleksandra; Pocajt, Viktor

2018-04-01

This paper presents an application of experimental design for the optimization of artificial neural network (ANN) for the prediction of dissolved oxygen (DO) content in the Danube River. The aim of this research was to obtain a more reliable ANN model that uses fewer monitoring records, by simultaneous optimization of the following model parameters: number of monitoring sites, number of historical monitoring data (expressed in years), and number of input water quality parameters used. Box-Behnken three-factor at three levels experimental design was applied for simultaneous spatial, temporal, and input variables optimization of the ANN model. The prediction of DO was performed using a feed-forward back-propagation neural network (BPNN), while the selection of most important inputs was done off-model using multi-filter approach that combines a chi-square ranking in the first step with a correlation-based elimination in the second step. The contour plots of absolute and relative error response surfaces were utilized to determine the optimal values of design factors. From the contour plots, two BPNN models that cover entire Danube flow through Serbia are proposed: an upstream model (BPNN-UP) that covers 8 monitoring sites prior to Belgrade and uses 12 inputs measured in the 7-year period and a downstream model (BPNN-DOWN) which covers 9 monitoring sites and uses 11 input parameters measured in the 6-year period. The main difference between the two models is that BPNN-UP utilizes inputs such as BOD, P, and PO 4 3- , which is in accordance with the fact that this model covers northern part of Serbia (Vojvodina Autonomous Province) which is well-known for agricultural production and extensive use of fertilizers. Both models have shown very good agreement between measured and predicted DO (with R 2  ≥ 0.86) and demonstrated that they can effectively forecast DO content in the Danube River.

Fast and Accurate Circuit Design Automation through Hierarchical Model Switching.

PubMed

Huynh, Linh; Tagkopoulos, Ilias

2015-08-21

In computer-aided biological design, the trifecta of characterized part libraries, accurate models and optimal design parameters is crucial for producing reliable designs. As the number of parts and model complexity increase, however, it becomes exponentially more difficult for any optimization method to search the solution space, hence creating a trade-off that hampers efficient design. To address this issue, we present a hierarchical computer-aided design architecture that uses a two-step approach for biological design. First, a simple model of low computational complexity is used to predict circuit behavior and assess candidate circuit branches through branch-and-bound methods. Then, a complex, nonlinear circuit model is used for a fine-grained search of the reduced solution space, thus achieving more accurate results. Evaluation with a benchmark of 11 circuits and a library of 102 experimental designs with known characterization parameters demonstrates a speed-up of 3 orders of magnitude when compared to other design methods that provide optimality guarantees.

Plant Disease Severity Assessment-How Rater Bias, Assessment Method, and Experimental Design Affect Hypothesis Testing and Resource Use Efficiency.

PubMed

Chiang, Kuo-Szu; Bock, Clive H; Lee, I-Hsuan; El Jarroudi, Moussa; Delfosse, Philippe

2016-12-01

The effect of rater bias and assessment method on hypothesis testing was studied for representative experimental designs for plant disease assessment using balanced and unbalanced data sets. Data sets with the same number of replicate estimates for each of two treatments are termed "balanced" and those with unequal numbers of replicate estimates are termed "unbalanced". The three assessment methods considered were nearest percent estimates (NPEs), an amended 10% incremental scale, and the Horsfall-Barratt (H-B) scale. Estimates of severity of Septoria leaf blotch on leaves of winter wheat were used to develop distributions for a simulation model. The experimental designs are presented here in the context of simulation experiments which consider the optimal design for the number of specimens (individual units sampled) and the number of replicate estimates per specimen for a fixed total number of observations (total sample size for the treatments being compared). The criterion used to gauge each method was the power of the hypothesis test. As expected, at a given fixed number of observations, the balanced experimental designs invariably resulted in a higher power compared with the unbalanced designs at different disease severity means, mean differences, and variances. Based on these results, with unbiased estimates using NPE, the recommended number of replicate estimates taken per specimen is 2 (from a sample of specimens of at least 30), because this conserves resources. Furthermore, for biased estimates, an apparent difference in the power of the hypothesis test was observed between assessment methods and between experimental designs. Results indicated that, regardless of experimental design or rater bias, an amended 10% incremental scale has slightly less power compared with NPEs, and that the H-B scale is more likely than the others to cause a type II error. These results suggest that choice of assessment method, optimizing sample number and number of replicate estimates, and using a balanced experimental design are important criteria to consider to maximize the power of hypothesis tests for comparing treatments using disease severity estimates.

Design optimization of the sensor spatial arrangement in a direct magnetic field-based localization system for medical applications.

PubMed

Marechal, Luc; Shaohui Foong; Zhenglong Sun; Wood, Kristin L

2015-08-01

Motivated by the need for developing a neuronavigation system to improve efficacy of intracranial surgical procedures, a localization system using passive magnetic fields for real-time monitoring of the insertion process of an external ventricular drain (EVD) catheter is conceived and developed. This system operates on the principle of measuring the static magnetic field of a magnetic marker using an array of magnetic sensors. An artificial neural network (ANN) is directly used for solving the inverse problem of magnetic dipole localization for improved efficiency and precision. As the accuracy of localization system is highly dependent on the sensor spatial location, an optimization framework, based on understanding and classification of experimental sensor characteristics as well as prior knowledge of the general trajectory of the localization pathway, for design of such sensing assemblies is described and investigated in this paper. Both optimized and non-optimized sensor configurations were experimentally evaluated and results show superior performance from the optimized configuration. While the approach presented here utilizes ventriculostomy as an illustrative platform, it can be extended to other medical applications that require localization inside the body.

Risk assessment and experimental design in the development of a prolonged release drug delivery system with paliperidone

PubMed Central

Iurian, Sonia; Turdean, Luana; Tomuta, Ioan

2017-01-01

This study focuses on the development of a drug product based on a risk assessment-based approach, within the quality by design paradigm. A prolonged release system was proposed for paliperidone (Pal) delivery, containing Kollidon® SR as an insoluble matrix agent and hydroxypropyl cellulose, hydroxypropyl methylcellulose (HPMC), or sodium carboxymethyl cellulose as a hydrophilic polymer. The experimental part was preceded by the identification of potential sources of variability through Ishikawa diagrams, and failure mode and effects analysis was used to deliver the critical process parameters that were further optimized by design of experiments. A D-optimal design was used to investigate the effects of Kollidon SR ratio (X1), the type of hydrophilic polymer (X2), and the percentage of hydrophilic polymer (X3) on the percentages of dissolved Pal over 24 h (Y1–Y9). Effects expressed as regression coefficients and response surfaces were generated, along with a design space for the preparation of a target formulation in an experimental area with low error risk. The optimal formulation contained 27.62% Kollidon SR and 8.73% HPMC and achieved the prolonged release of Pal, with low burst effect, at ratios that were very close to the ones predicted by the model. Thus, the parameters with the highest impact on the final product quality were studied, and safe ranges were established for their variations. Finally, a risk mitigation and control strategy was proposed to assure the quality of the system, by constant process monitoring. PMID:28331293

Aerodynamic design optimization using sensitivity analysis and computational fluid dynamics

NASA Technical Reports Server (NTRS)

Baysal, Oktay; Eleshaky, Mohamed E.

1991-01-01

A new and efficient method is presented for aerodynamic design optimization, which is based on a computational fluid dynamics (CFD)-sensitivity analysis algorithm. The method is applied to design a scramjet-afterbody configuration for an optimized axial thrust. The Euler equations are solved for the inviscid analysis of the flow, which in turn provides the objective function and the constraints. The CFD analysis is then coupled with the optimization procedure that uses a constrained minimization method. The sensitivity coefficients, i.e. gradients of the objective function and the constraints, needed for the optimization are obtained using a quasi-analytical method rather than the traditional brute force method of finite difference approximations. During the one-dimensional search of the optimization procedure, an approximate flow analysis (predicted flow) based on a first-order Taylor series expansion is used to reduce the computational cost. Finally, the sensitivity of the optimum objective function to various design parameters, which are kept constant during the optimization, is computed to predict new optimum solutions. The flow analysis of the demonstrative example are compared with the experimental data. It is shown that the method is more efficient than the traditional methods.

Optimal control design of turbo spin‐echo sequences with applications to parallel‐transmit systems

PubMed Central

Hoogduin, Hans; Hajnal, Joseph V.; van den Berg, Cornelis A. T.; Luijten, Peter R.; Malik, Shaihan J.

2016-01-01

Purpose The design of turbo spin‐echo sequences is modeled as a dynamic optimization problem which includes the case of inhomogeneous transmit radiofrequency fields. This problem is efficiently solved by optimal control techniques making it possible to design patient‐specific sequences online. Theory and Methods The extended phase graph formalism is employed to model the signal evolution. The design problem is cast as an optimal control problem and an efficient numerical procedure for its solution is given. The numerical and experimental tests address standard multiecho sequences and pTx configurations. Results Standard, analytically derived flip angle trains are recovered by the numerical optimal control approach. New sequences are designed where constraints on radiofrequency total and peak power are included. In the case of parallel transmit application, the method is able to calculate the optimal echo train for two‐dimensional and three‐dimensional turbo spin echo sequences in the order of 10 s with a single central processing unit (CPU) implementation. The image contrast is maintained through the whole field of view despite inhomogeneities of the radiofrequency fields. Conclusion The optimal control design sheds new light on the sequence design process and makes it possible to design sequences in an online, patient‐specific fashion. Magn Reson Med 77:361–373, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine PMID:26800383

Optimal experimental designs for estimating Henry's law constants via the method of phase ratio variation.

PubMed

Kapelner, Adam; Krieger, Abba; Blanford, William J

2016-10-14

When measuring Henry's law constants (k H ) using the phase ratio variation (PRV) method via headspace gas chromatography (G C ), the value of k H of the compound under investigation is calculated from the ratio of the slope to the intercept of a linear regression of the inverse G C response versus the ratio of gas to liquid volumes of a series of vials drawn from the same parent solution. Thus, an experimenter collects measurements consisting of the independent variable (the gas/liquid volume ratio) and dependent variable (the G C -1 peak area). A review of the literature found that the common design is a simple uniform spacing of liquid volumes. We present an optimal experimental design which estimates k H with minimum error and provides multiple means for building confidence intervals for such estimates. We illustrate performance improvements of our design with an example measuring the k H for Naphthalene in aqueous solution as well as simulations on previous studies. Our designs are most applicable after a trial run defines the linear G C response and the linear phase ratio to the G C -1 region (where the PRV method is suitable) after which a practitioner can collect measurements in bulk. The designs can be easily computed using our open source software optDesignSlopeInt, an R package on CRAN. Copyright © 2016 Elsevier B.V. All rights reserved.

Optimization of the capillary zone electrophoresis method for Huperzine A determination using experimental design and artificial neural networks.

PubMed

Hameda, A Ben; Elosta, S; Havel, J

2005-08-19

Huperzine A, natural product from Huperzia serrata, is quite an important compound used to treat the Alzheimer's disease as a food supplement and also proposed as a prospective and prophylactic antidote against organophosphate poisoning. In this work, simple and fast capillary electrophoresis (CE) procedure with UV detection (at 230 nm) for determination of Huperzine A was developed and optimized. Capillary electrophoresis determination of Huperzine A was optimized using a combination of the experimental design (ED) and the artificial neural networks (ANN). In the first stage of optimization, the experiments were done according to the appropriate ED. Data evaluated by ANN allowed finding the optimal values of several analytical parameters (peak area, peak height, and analysis time). Optimal conditions found were 50 mM acetate buffer, pH 4.6, separation voltage 10 kV, hydrodynamic injection time 10 s and temperature 25 degrees C. The developed method shows good repeatability as relative standard division (R.S.D. = 0.9%) and it has been applied for determination of Huperzine A in various pharmaceutical products and in biological liquids. The limit of detection (LOD) in aqueous media was 0.226 ng/ml and 0.233 ng/ml for determination in the serum.

Preconcentration and determination of ceftazidime in real samples using dispersive liquid-liquid microextraction and high-performance liquid chromatography with the aid of experimental design.

PubMed

Razmi, Rasoul; Shahpari, Behrouz; Pourbasheer, Eslam; Boustanifar, Mohammad Hasan; Azari, Zhila; Ebadi, Amin

2016-11-01

A rapid and simple method for the extraction and preconcentration of ceftazidime in aqueous samples has been developed using dispersive liquid-liquid microextraction followed by high-performance liquid chromatography analysis. The extraction parameters, such as the volume of extraction solvent and disperser solvent, salt effect, sample volume, centrifuge rate, centrifuge time, extraction time, and temperature in the dispersive liquid-liquid microextraction process, were studied and optimized with the experimental design methods. Firstly, for the preliminary screening of the parameters the taguchi design was used and then, the fractional factorial design was used for significant factors optimization. At the optimum conditions, the calibration curves for ceftazidime indicated good linearity over the range of 0.001-10 μg/mL with correlation coefficients higher than the 0.98, and the limits of detection were 0.13 and 0.17 ng/mL, for water and urine samples, respectively. The proposed method successfully employed to determine ceftazidime in water and urine samples and good agreement between the experimental data and predictive values has been achieved. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Optimization of large animal MI models; a systematic analysis of control groups from preclinical studies.

PubMed

Zwetsloot, P P; Kouwenberg, L H J A; Sena, E S; Eding, J E; den Ruijter, H M; Sluijter, J P G; Pasterkamp, G; Doevendans, P A; Hoefer, I E; Chamuleau, S A J; van Hout, G P J; Jansen Of Lorkeers, S J

2017-10-27

Large animal models are essential for the development of novel therapeutics for myocardial infarction. To optimize translation, we need to assess the effect of experimental design on disease outcome and model experimental design to resemble the clinical course of MI. The aim of this study is therefore to systematically investigate how experimental decisions affect outcome measurements in large animal MI models. We used control animal-data from two independent meta-analyses of large animal MI models. All variables of interest were pre-defined. We performed univariable and multivariable meta-regression to analyze whether these variables influenced infarct size and ejection fraction. Our analyses incorporated 246 relevant studies. Multivariable meta-regression revealed that infarct size and cardiac function were influenced independently by choice of species, sex, co-medication, occlusion type, occluded vessel, quantification method, ischemia duration and follow-up duration. We provide strong systematic evidence that commonly used endpoints significantly depend on study design and biological variation. This makes direct comparison of different study-results difficult and calls for standardized models. Researchers should take this into account when designing large animal studies to most closely mimic the clinical course of MI and enable translational success.

Mechanical design optimization of a single-axis MOEMS accelerometer based on a grating interferometry cavity for ultrahigh sensitivity

NASA Astrophysics Data System (ADS)

Lu, Qianbo; Bai, Jian; Wang, Kaiwei; Lou, Shuqi; Jiao, Xufen; Han, Dandan; Yang, Guoguang

2016-08-01

The ultrahigh static displacement-acceleration sensitivity of a mechanical sensing chip is essential primarily for an ultrasensitive accelerometer. In this paper, an optimal design to implement to a single-axis MOEMS accelerometer consisting of a grating interferometry cavity and a micromachined sensing chip is presented. The micromachined sensing chip is composed of a proof mass along with its mechanical cantilever suspension and substrate. The dimensional parameters of the sensing chip, including the length, width, thickness and position of the cantilevers are evaluated and optimized both analytically and by finite-element-method (FEM) simulation to yield an unprecedented acceleration-displacement sensitivity. Compared with one of the most sensitive single-axis MOEMS accelerometers reported in the literature, the optimal mechanical design can yield a profound sensitivity improvement with an equal footprint area, specifically, 200% improvement in displacement-acceleration sensitivity with moderate resonant frequency and dynamic range. The modified design was microfabricated, packaged with the grating interferometry cavity and tested. The experimental results demonstrate that the MOEMS accelerometer with modified design can achieve the acceleration-displacement sensitivity of about 150μm/g and acceleration sensitivity of greater than 1500V/g, which validates the effectiveness of the optimal design.

Visible light activity of Ag-loaded and guanidine nitrate-doped nano-TiO2: Degradation of dichlorophenol and antibacterial properties

EPA Science Inventory

To utilize visible light, co-doped nano-TiO2 was prepared via “one pot” synthesis using mild reaction conditions and benign precursors. Synthesis was optimized using an appropriate experimental design taking into account silver content and calcination temperature. The optimized ...

Optimizing Classroom Instruction through Self-Paced Learning Prototype

ERIC Educational Resources Information Center

Bautista, Romiro G.

2015-01-01

This study investigated the learning impact of self-paced learning prototype in optimizing classroom instruction towards students' learning in Chemistry. Two sections of 64 Laboratory High School students in Chemistry were used as subjects of the study. The Quasi-Experimental and Correlation Research Design was used in the study: a pre-test was…

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

Mueller, Juliane

MISO is an optimization framework for solving computationally expensive mixed-integer, black-box, global optimization problems. MISO uses surrogate models to approximate the computationally expensive objective function. Hence, derivative information, which is generally unavailable for black-box simulation objective functions, is not needed. MISO allows the user to choose the initial experimental design strategy, the type of surrogate model, and the sampling strategy.

MDTri: robust and efficient global mixed integer search of spaces of multiple ternary alloys: A DIRECT-inspired optimization algorithm for experimentally accessible computational material design

DOE PAGES

Graf, Peter A.; Billups, Stephen

2017-07-24

Computational materials design has suffered from a lack of algorithms formulated in terms of experimentally accessible variables. Here we formulate the problem of (ternary) alloy optimization at the level of choice of atoms and their composition that is normal for synthesists. Mathematically, this is a mixed integer problem where a candidate solution consists of a choice of three elements, and how much of each of them to use. This space has the natural structure of a set of equilateral triangles. We solve this problem by introducing a novel version of the DIRECT algorithm that (1) operates on equilateral triangles insteadmore » of rectangles and (2) works across multiple triangles. We demonstrate on a test case that the algorithm is both robust and efficient. Lastly, we offer an explanation of the efficacy of DIRECT -- specifically, its balance of global and local search -- by showing that 'potentially optimal rectangles' of the original algorithm are akin to the Pareto front of the 'multi-component optimization' of global and local search.« less

Design optimization of beta- and photovoltaic conversion devices

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

Wichner, R.; Blum, A.; Fischer-Colbrie, E.

1976-01-08

This report presents the theoretical and experimental results of an LLL Electronics Engineering research program aimed at optimizing the design and electronic-material parameters of beta- and photovoltaic p-n junction conversion devices. To meet this objective, a comprehensive computer code has been developed that can handle a broad range of practical conditions. The physical model upon which the code is based is described first. Then, an example is given of a set of optimization calculations along with the resulting optimized efficiencies for silicon (Si) and gallium-arsenide (GaAs) devices. The model we have developed, however, is not limited to these materials. Itmore » can handle any appropriate material--single or polycrystalline-- provided energy absorption and electron-transport data are available. To check code validity, the performance of experimental silicon p-n junction devices (produced in-house) were measured under various light intensities and spectra as well as under tritium beta irradiation. The results of these tests were then compared with predicted results based on the known or best estimated device parameters. The comparison showed very good agreement between the calculated and the measured results.« less

Spectrophotometric determination of triclosan based on diazotization reaction: response surface optimization using Box-Behnken design.

PubMed

Kaur, Inderpreet; Gaba, Sonal; Kaur, Sukhraj; Kumar, Rajeev; Chawla, Jyoti

2018-05-01

A spectrophotometric method based on diazotization of aniline with triclosan has been developed for the determination of triclosan in water samples. The diazotization process involves two steps: (1) reaction of aniline with sodium nitrite in an acidic medium to form diazonium ion and (2) reaction of diazonium ion with triclosan to form a yellowish-orange azo compound in an alkaline medium. The resulting yellowish-orange product has a maximum absorption at 352 nm which allows the determination of triclosan in aqueous solution in the linear concentration range of 0.1-3.0 μM with R 2 = 0.998. The concentration of hydrochloric acid, sodium nitrite, and aniline was optimized for diazotization reaction to achieve good spectrophotometric determination of triclosan. The optimization of experimental conditions for spectrophotometric determination of triclosan in terms of concentration of sodium nitrite, hydrogen chloride and aniline was also carried out by using Box-Behnken design of response surface methodology and results obtained were in agreement with the experimentally optimized values. The proposed method was then successfully applied for analyses of triclosan content in water samples.

MDTri: robust and efficient global mixed integer search of spaces of multiple ternary alloys: A DIRECT-inspired optimization algorithm for experimentally accessible computational material design

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

Graf, Peter A.; Billups, Stephen

Computational materials design has suffered from a lack of algorithms formulated in terms of experimentally accessible variables. Here we formulate the problem of (ternary) alloy optimization at the level of choice of atoms and their composition that is normal for synthesists. Mathematically, this is a mixed integer problem where a candidate solution consists of a choice of three elements, and how much of each of them to use. This space has the natural structure of a set of equilateral triangles. We solve this problem by introducing a novel version of the DIRECT algorithm that (1) operates on equilateral triangles insteadmore » of rectangles and (2) works across multiple triangles. We demonstrate on a test case that the algorithm is both robust and efficient. Lastly, we offer an explanation of the efficacy of DIRECT -- specifically, its balance of global and local search -- by showing that 'potentially optimal rectangles' of the original algorithm are akin to the Pareto front of the 'multi-component optimization' of global and local search.« less

Optimization of poorly compactable drug tablets manufactured by direct compression using the mixture experimental design.

PubMed

Martinello, Tiago; Kaneko, Telma Mary; Velasco, Maria Valéria Robles; Taqueda, Maria Elena Santos; Consiglieri, Vladi O

2006-09-28

The poor flowability and bad compressibility characteristics of paracetamol are well known. As a result, the production of paracetamol tablets is almost exclusively by wet granulation, a disadvantageous method when compared to direct compression. The development of a new tablet formulation is still based on a large number of experiments and often relies merely on the experience of the analyst. The purpose of this study was to apply experimental design methodology (DOE) to the development and optimization of tablet formulations containing high amounts of paracetamol (more than 70%) and manufactured by direct compression. Nineteen formulations, screened by DOE methodology, were produced with different proportions of Microcel 102, Kollydon VA 64, Flowlac, Kollydon CL 30, PEG 4000, Aerosil, and magnesium stearate. Tablet properties, except friability, were in accordance with the USP 28th ed. requirements. These results were used to generate plots for optimization, mainly for friability. The physical-chemical data found from the optimized formulation were very close to those from the regression analysis, demonstrating that the mixture project is a great tool for the research and development of new formulations.

Application of optimal design methodologies in clinical pharmacology experiments.

PubMed

Ogungbenro, Kayode; Dokoumetzidis, Aristides; Aarons, Leon

2009-01-01

Pharmacokinetics and pharmacodynamics data are often analysed by mixed-effects modelling techniques (also known as population analysis), which has become a standard tool in the pharmaceutical industries for drug development. The last 10 years has witnessed considerable interest in the application of experimental design theories to population pharmacokinetic and pharmacodynamic experiments. Design of population pharmacokinetic experiments involves selection and a careful balance of a number of design factors. Optimal design theory uses prior information about the model and parameter estimates to optimize a function of the Fisher information matrix to obtain the best combination of the design factors. This paper provides a review of the different approaches that have been described in the literature for optimal design of population pharmacokinetic and pharmacodynamic experiments. It describes options that are available and highlights some of the issues that could be of concern as regards practical application. It also discusses areas of application of optimal design theories in clinical pharmacology experiments. It is expected that as the awareness about the benefits of this approach increases, more people will embrace it and ultimately will lead to more efficient population pharmacokinetic and pharmacodynamic experiments and can also help to reduce both cost and time during drug development. Copyright (c) 2008 John Wiley & Sons, Ltd.

Experimental research of radio-frequency ion thruster

NASA Astrophysics Data System (ADS)

Antropov, N. N.; Akhmetzhanov, R. V.; Bogatyy, A. V.; Grishin, R. A.; Kozhevnikov, V. V.; Plokhikh, A. P.; Popov, G. A.; Khartov, S. A.

2016-12-01

The article is devoted to the research of low-power (300 W) radio-frequency ion thruster designed at the Moscow Aviation Institute. The main results of experimental research of the thruster using the testfacility power supplies and the power processing unit of their own design are presented. The dependence of the working fluid ionization cost on its mass flow rate at the constant ion beam current was investigated experimentally. The influence of the shape and material of the discharge chamber on the integral characteristics of the thruster was studied. The recommendations on the optimization of the thruster primary performance were developed based on the results of experimental studies.

Applications of Elpasolites as a Multimode Radiation Sensor

NASA Astrophysics Data System (ADS)

Guckes, Amber

This study consists of both computational and experimental investigations. The computational results enabled detector design selections and confirmed experimental results. The experimental results determined that the CLYC scintillation detector can be applied as a functional and field-deployable multimode radiation sensor. The computational study utilized MCNP6 code to investigate the response of CLYC to various incident radiations and to determine the feasibility of its application as a handheld multimode sensor and as a single-scintillator collimated directional detection system. These simulations include: • Characterization of the response of the CLYC scintillator to gamma-rays and neutrons; • Study of the isotopic enrichment of 7Li versus 6Li in the CLYC for optimal detection of both thermal neutrons and fast neutrons; • Analysis of collimator designs to determine the optimal collimator for the single CLYC sensor directional detection system to assay gamma rays and neutrons; Simulations of a handheld CLYC multimode sensor and a single CLYC scintillator collimated directional detection system with the optimized collimator to determine the feasibility of detecting nuclear materials that could be encountered during field operations. These nuclear materials include depleted uranium, natural uranium, low-enriched uranium, highly-enriched uranium, reactor-grade plutonium, and weapons-grade plutonium. The experimental study includes the design, construction, and testing of both a handheld CLYC multimode sensor and a single CLYC scintillator collimated directional detection system. Both were designed in the Inventor CAD software and based on results of the computational study to optimize its performance. The handheld CLYC multimode sensor is modular, scalable, low?power, and optimized for high count rates. Commercial?off?the?shelf components were used where possible in order to optimize size, increase robustness, and minimize cost. The handheld CLYC multimode sensor was successfully tested to confirm its ability for gamma-ray and neutron detection, and gamma?ray and neutron spectroscopy. The sensor utilizes wireless data transfer for possible radiation mapping and network?centric deployment. The handheld multimode sensor was tested by performing laboratory measurements with various gamma-ray sources and neutron sources. The single CLYC scintillator collimated directional detection system is portable, robust, and capable of source localization and identification. The collimator was designed based on the results of the computational study and is constructed with high density polyethylene (HDPE) and lead (Pb). The collimator design and construction allows for the directional detection of gamma rays and fast neutrons utilizing only one scintillator which is interchangeable. For this study, a CLYC-7 scintillator was used. The collimated directional detection system was tested by performing laboratory directional measurements with various gamma-ray sources, 252Cf and a 239PuBe source.

Efficient Optimization of Stimuli for Model-Based Design of Experiments to Resolve Dynamical Uncertainty.

PubMed

Mdluli, Thembi; Buzzard, Gregery T; Rundell, Ann E

2015-09-01

This model-based design of experiments (MBDOE) method determines the input magnitudes of an experimental stimuli to apply and the associated measurements that should be taken to optimally constrain the uncertain dynamics of a biological system under study. The ideal global solution for this experiment design problem is generally computationally intractable because of parametric uncertainties in the mathematical model of the biological system. Others have addressed this issue by limiting the solution to a local estimate of the model parameters. Here we present an approach that is independent of the local parameter constraint. This approach is made computationally efficient and tractable by the use of: (1) sparse grid interpolation that approximates the biological system dynamics, (2) representative parameters that uniformly represent the data-consistent dynamical space, and (3) probability weights of the represented experimentally distinguishable dynamics. Our approach identifies data-consistent representative parameters using sparse grid interpolants, constructs the optimal input sequence from a greedy search, and defines the associated optimal measurements using a scenario tree. We explore the optimality of this MBDOE algorithm using a 3-dimensional Hes1 model and a 19-dimensional T-cell receptor model. The 19-dimensional T-cell model also demonstrates the MBDOE algorithm's scalability to higher dimensions. In both cases, the dynamical uncertainty region that bounds the trajectories of the target system states were reduced by as much as 86% and 99% respectively after completing the designed experiments in silico. Our results suggest that for resolving dynamical uncertainty, the ability to design an input sequence paired with its associated measurements is particularly important when limited by the number of measurements.

Efficient Optimization of Stimuli for Model-Based Design of Experiments to Resolve Dynamical Uncertainty

PubMed Central

Mdluli, Thembi; Buzzard, Gregery T.; Rundell, Ann E.

2015-01-01

This model-based design of experiments (MBDOE) method determines the input magnitudes of an experimental stimuli to apply and the associated measurements that should be taken to optimally constrain the uncertain dynamics of a biological system under study. The ideal global solution for this experiment design problem is generally computationally intractable because of parametric uncertainties in the mathematical model of the biological system. Others have addressed this issue by limiting the solution to a local estimate of the model parameters. Here we present an approach that is independent of the local parameter constraint. This approach is made computationally efficient and tractable by the use of: (1) sparse grid interpolation that approximates the biological system dynamics, (2) representative parameters that uniformly represent the data-consistent dynamical space, and (3) probability weights of the represented experimentally distinguishable dynamics. Our approach identifies data-consistent representative parameters using sparse grid interpolants, constructs the optimal input sequence from a greedy search, and defines the associated optimal measurements using a scenario tree. We explore the optimality of this MBDOE algorithm using a 3-dimensional Hes1 model and a 19-dimensional T-cell receptor model. The 19-dimensional T-cell model also demonstrates the MBDOE algorithm’s scalability to higher dimensions. In both cases, the dynamical uncertainty region that bounds the trajectories of the target system states were reduced by as much as 86% and 99% respectively after completing the designed experiments in silico. Our results suggest that for resolving dynamical uncertainty, the ability to design an input sequence paired with its associated measurements is particularly important when limited by the number of measurements. PMID:26379275

Using constraints and their value for optimization of large ODE systems

PubMed Central

Domijan, Mirela; Rand, David A.

2015-01-01

We provide analytical tools to facilitate a rigorous assessment of the quality and value of the fit of a complex model to data. We use this to provide approaches to model fitting, parameter estimation, the design of optimization functions and experimental optimization. This is in the context where multiple constraints are used to select or optimize a large model defined by differential equations. We illustrate the approach using models of circadian clocks and the NF-κB signalling system. PMID:25673300

Efficiency of operation of wind turbine rotors optimized by the Glauert and Betz methods

NASA Astrophysics Data System (ADS)

Okulov, V. L.; Mikkelsen, R.; Litvinov, I. V.; Naumov, I. V.

2015-11-01

The models of two types of rotors with blades constructed using different optimization methods are compared experimentally. In the first case, the Glauert optimization by the pulsed method is used, which is applied independently for each individual blade cross section. This method remains the main approach in designing rotors of various duties. The construction of the other rotor is based on the Betz idea about optimization of rotors by determining a special distribution of circulation over the blade, which ensures the helical structure of the wake behind the rotor. It is established for the first time as a result of direct experimental comparison that the rotor constructed using the Betz method makes it possible to extract more kinetic energy from the homogeneous incoming flow.

Topology-optimized silicon photonic wire mode (de)multiplexer

NASA Astrophysics Data System (ADS)

Frellsen, Louise F.; Frandsen, Lars H.; Ding, Yunhong; Elesin, Yuriy; Sigmund, Ole; Yvind, Kresten

2015-02-01

We have designed and for the first time experimentally verified a topology optimized mode (de)multiplexer, which demultiplexes the fundamental and the first order mode of a double mode photonic wire to two separate single mode waveguides (and multiplexes vice versa). The device has a footprint of ~4.4 μm x ~2.8 μm and was fabricated for different design resolutions and design threshold values to verify the robustness of the structure to fabrication tolerances. The multiplexing functionality was confirmed by recording mode profiles using an infrared camera and vertical grating couplers. All structures were experimentally found to maintain functionality throughout a 100 nm wavelength range limited by available laser sources and insertion losses were generally lower than 1.3 dB. The cross talk was around -12 dB and the extinction ratio was measured to be better than 8 dB.

Designing biomedical proteomics experiments: state-of-the-art and future perspectives.

PubMed

Maes, Evelyne; Kelchtermans, Pieter; Bittremieux, Wout; De Grave, Kurt; Degroeve, Sven; Hooyberghs, Jef; Mertens, Inge; Baggerman, Geert; Ramon, Jan; Laukens, Kris; Martens, Lennart; Valkenborg, Dirk

2016-05-01

With the current expanded technical capabilities to perform mass spectrometry-based biomedical proteomics experiments, an improved focus on the design of experiments is crucial. As it is clear that ignoring the importance of a good design leads to an unprecedented rate of false discoveries which would poison our results, more and more tools are developed to help researchers designing proteomic experiments. In this review, we apply statistical thinking to go through the entire proteomics workflow for biomarker discovery and validation and relate the considerations that should be made at the level of hypothesis building, technology selection, experimental design and the optimization of the experimental parameters.

Design of a transverse-flux permanent-magnet linear generator and controller for use with a free-piston stirling engine

NASA Astrophysics Data System (ADS)

Zheng, Jigui; Huang, Yuping; Wu, Hongxing; Zheng, Ping

2016-07-01

Transverse-flux with high efficiency has been applied in Stirling engine and permanent magnet synchronous linear generator system, however it is restricted for large application because of low and complex process. A novel type of cylindrical, non-overlapping, transverse-flux, and permanent-magnet linear motor(TFPLM) is investigated, furthermore, a high power factor and less process complexity structure research is developed. The impact of magnetic leakage factor on power factor is discussed, by using the Finite Element Analysis(FEA) model of stirling engine and TFPLM, an optimization method for electro-magnetic design of TFPLM is proposed based on magnetic leakage factor. The relation between power factor and structure parameter is investigated, and a structure parameter optimization method is proposed taking power factor maximum as a goal. At last, the test bench is founded, starting experimental and generating experimental are performed, and a good agreement of simulation and experimental is achieved. The power factor is improved and the process complexity is decreased. This research provides the instruction to design high-power factor permanent-magnet linear generator.

Optimal Objective-Based Experimental Design for Uncertain Dynamical Gene Networks with Experimental Error.

PubMed

Mohsenizadeh, Daniel N; Dehghannasiri, Roozbeh; Dougherty, Edward R

2018-01-01

In systems biology, network models are often used to study interactions among cellular components, a salient aim being to develop drugs and therapeutic mechanisms to change the dynamical behavior of the network to avoid undesirable phenotypes. Owing to limited knowledge, model uncertainty is commonplace and network dynamics can be updated in different ways, thereby giving multiple dynamic trajectories, that is, dynamics uncertainty. In this manuscript, we propose an experimental design method that can effectively reduce the dynamics uncertainty and improve performance in an interaction-based network. Both dynamics uncertainty and experimental error are quantified with respect to the modeling objective, herein, therapeutic intervention. The aim of experimental design is to select among a set of candidate experiments the experiment whose outcome, when applied to the network model, maximally reduces the dynamics uncertainty pertinent to the intervention objective.

Optimization of a Small Scale Linear Reluctance Accelerator

NASA Astrophysics Data System (ADS)

Barrera, Thor; Beard, Robby

2011-11-01

Reluctance accelerators are extremely promising future methods of transportation. Several problems still plague these devices, most prominently low efficiency. Variables to overcoming efficiency problems are many and difficult to correlate how they affect our accelerator. The study examined several differing variables that present potential challenges in optimizing the efficiency of reluctance accelerators. These include coil and projectile design, power supplies, switching, and the elusive gradient inductance problem. Extensive research in these areas has been performed from computational and theoretical to experimental. Findings show that these parameters share significant similarity to transformer design elements, thus general findings show current optimized parameters the research suggests as a baseline for further research and design. Demonstration of these current findings will be offered at the time of presentation.

MEMS resonant load cells for micro-mechanical test frames: feasibility study and optimal design

NASA Astrophysics Data System (ADS)

Torrents, A.; Azgin, K.; Godfrey, S. W.; Topalli, E. S.; Akin, T.; Valdevit, L.

2010-12-01

This paper presents the design, optimization and manufacturing of a novel micro-fabricated load cell based on a double-ended tuning fork. The device geometry and operating voltages are optimized for maximum force resolution and range, subject to a number of manufacturing and electromechanical constraints. All optimizations are enabled by analytical modeling (verified by selected finite elements analyses) coupled with an efficient C++ code based on the particle swarm optimization algorithm. This assessment indicates that force resolutions of ~0.5-10 nN are feasible in vacuum (~1-50 mTorr), with force ranges as large as 1 N. Importantly, the optimal design for vacuum operation is independent of the desired range, ensuring versatility. Experimental verifications on a sub-optimal device fabricated using silicon-on-glass technology demonstrate a resolution of ~23 nN at a vacuum level of ~50 mTorr. The device demonstrated in this article will be integrated in a hybrid micro-mechanical test frame for unprecedented combinations of force resolution and range, displacement resolution and range, optical (or SEM) access to the sample, versatility and cost.

Application of D-optimal experimental design method to optimize the formulation of O/W cosmetic emulsions.

PubMed

Djuris, J; Vasiljevic, D; Jokic, S; Ibric, S

2014-02-01

This study investigates the application of D-optimal mixture experimental design in optimization of O/W cosmetic emulsions. Cetearyl glucoside was used as a natural, biodegradable non-ionic emulsifier in the relatively low concentration (1%), and the mixture of co-emulsifiers (stearic acid, cetyl alcohol, stearyl alcohol and glyceryl stearate) was used to stabilize the formulations. To determine the optimal composition of co-emulsifiers mixture, D-optimal mixture experimental design was used. Prepared emulsions were characterized with rheological measurements, centrifugation test, specific conductivity and pH value measurements. All prepared samples appeared as white and homogenous creams, except for one homogenous and viscous lotion co-stabilized by stearic acid alone. Centrifugation testing revealed some phase separation only in the case of sample co-stabilized using glyceryl stearate alone. The obtained pH values indicated that all samples expressed mild acid value acceptable for cosmetic preparations. Specific conductivity values are attributed to the multiple phases O/W emulsions with high percentages of fixed water. Results of the rheological measurements have shown that the investigated samples exhibited non-Newtonian thixotropic behaviour. To determine the influence of each of the co-emulsifiers on emulsions properties, the obtained results were evaluated by the means of statistical analysis (ANOVA test). On the basis of comparison of statistical parameters for each of the studied responses, mixture reduced quadratic model was selected over the linear model implying that interactions between co-emulsifiers play the significant role in overall influence of co-emulsifiers on emulsions properties. Glyceryl stearate was found to be the dominant co-emulsifier affecting emulsions properties. Interactions between the glyceryl stearate and other co-emulsifiers were also found to significantly influence emulsions properties. These findings are especially important as they can be used for development of the product that meets users' requirements, as represented in the study. © 2013 Society of Cosmetic Scientists and the Société Française de Cosmétologie.

Quality by design approach for developing chitosan-Ca-alginate microspheres for colon delivery of celecoxib-hydroxypropyl-β-cyclodextrin-PVP complex.

PubMed

Mennini, N; Furlanetto, S; Cirri, M; Mura, P

2012-01-01

The aim of the present work was to develop a new multiparticulate system, designed for colon-specific delivery of celecoxib for both systemic (in chronotherapic treatment of arthritis) and local (in prophylaxis of colon carcinogenesis) therapy. The system simultaneously benefits from ternary complexation with hydroxypropyl-β-cyclodextrin and PVP (polyvinylpyrrolidone), to increase drug solubility, and vectorization in chitosan-Ca-alginate microspheres, to exploit the colon-specific carrier properties of these polymers. Statistical experimental design was employed to investigate the combined effect of four formulation variables, i.e., % of alginate, CaCl₂, and chitosan and time of cross-linking on microsphere entrapment efficiency (EE%) and drug amount released after 4h in colonic medium, considered as the responses to be optimized. Design of experiment was used in the context of Quality by Design, which requires a multivariate approach for understanding the multifactorial relationships among formulation parameters. Doehlert design allowed for defining a design space, which revealed that variations of the considered factors had in most cases an opposite influence on the responses. Desirability function was used to attain simultaneous optimization of both responses. The desired goals were achieved for both systemic and local use of celecoxib. Experimental values obtained from the optimized formulations were in both cases very close to the predicted values, thus confirming the validity of the generated mathematical model. These results demonstrated the effectiveness of the proposed jointed use of drug cyclodextrin complexation and chitosan-Ca-alginate microsphere vectorization, as well as the usefulness of the multivariate approach for the preparation of colon-targeted celecoxib microspheres with optimized properties. Copyright © 2011 Elsevier B.V. All rights reserved.

Inverse problems and optimal experiment design in unsteady heat transfer processes identification

NASA Technical Reports Server (NTRS)

Artyukhin, Eugene A.

1991-01-01

Experimental-computational methods for estimating characteristics of unsteady heat transfer processes are analyzed. The methods are based on the principles of distributed parameter system identification. The theoretical basis of such methods is the numerical solution of nonlinear ill-posed inverse heat transfer problems and optimal experiment design problems. Numerical techniques for solving problems are briefly reviewed. The results of the practical application of identification methods are demonstrated when estimating effective thermophysical characteristics of composite materials and thermal contact resistance in two-layer systems.

Research design.

PubMed

Toledo-Pereyra, Luis H

2012-10-01

The development of a good research design permits us to obtain the best research data possible. From the experimental question to the research hypothesis and data collection variables, we can begin to consider the optimal research design. Details pertaining to the selection of the research design are considered within and very much in relation with the knowledge of the researcher and the support of his research group.

Application of the experimental design of experiments (DoE) for the determination of organotin compounds in water samples using HS-SPME and GC-MS/MS.

PubMed

Coscollà, Clara; Navarro-Olivares, Santiago; Martí, Pedro; Yusà, Vicent

2014-02-01

When attempting to discover the important factors and then optimise a response by tuning these factors, experimental design (design of experiments, DoE) gives a powerful suite of statistical methodology. DoE identify significant factors and then optimise a response with respect to them in method development. In this work, a headspace-solid-phase micro-extraction (HS-SPME) combined with gas chromatography tandem mass spectrometry (GC-MS/MS) methodology for the simultaneous determination of six important organotin compounds namely monobutyltin (MBT), dibutyltin (DBT), tributyltin (TBT), monophenyltin (MPhT), diphenyltin (DPhT), triphenyltin (TPhT) has been optimized using a statistical design of experiments (DOE). The analytical method is based on the ethylation with NaBEt4 and simultaneous headspace-solid-phase micro-extraction of the derivative compounds followed by GC-MS/MS analysis. The main experimental parameters influencing the extraction efficiency selected for optimization were pre-incubation time, incubation temperature, agitator speed, extraction time, desorption temperature, buffer (pH, concentration and volume), headspace volume, sample salinity, preparation of standards, ultrasonic time and desorption time in the injector. The main factors (excitation voltage, excitation time, ion source temperature, isolation time and electron energy) affecting the GC-IT-MS/MS response were also optimized using the same statistical design of experiments. The proposed method presented good linearity (coefficient of determination R(2)>0.99) and repeatibilty (1-25%) for all the compounds under study. The accuracy of the method measured as the average percentage recovery of the compounds in spiked surface and marine waters was higher than 70% for all compounds studied. Finally, the optimized methodology was applied to real aqueous samples enabled the simultaneous determination of all compounds under study in surface and marine water samples obtained from Valencia region (Spain). © 2013 Elsevier B.V. All rights reserved.

Doehlert experimental design applied to optimization of light emitting textile structures

NASA Astrophysics Data System (ADS)

Oguz, Yesim; Cochrane, Cedric; Koncar, Vladan; Mordon, Serge R.

2016-07-01

A light emitting fabric (LEF) has been developed for photodynamic therapy (PDT) for the treatment of dermatologic diseases such as Actinic Keratosis (AK). A successful PDT requires homogenous and reproducible light with controlled power and wavelength on the treated skin area. Due to the shape of the human body, traditional PDT with external light sources is unable to deliver homogenous light everywhere on the skin (head vertex, hand, etc.). For better light delivery homogeneity, plastic optical fibers (POFs) have been woven in textile in order to emit laterally the injected light. The previous studies confirmed that the light power could be locally controlled by modifying the radius of POF macro-bendings within the textile structure. The objective of this study is to optimize the distribution of macro-bendings over the LEF surface in order to increase the light intensity (mW/cm2), and to guarantee the best possible light deliver homogeneity over the LEF which are often contradictory. Fifteen experiments have been carried out with Doehlert experimental design involving Response Surface Methodology (RSM). The proposed models are fitted to the experimental data to enable the optimal set up of the warp yarns tensions.

Optimal design of a piezoelectric transducer for exciting guided wave ultrasound in rails

NASA Astrophysics Data System (ADS)

Ramatlo, Dineo A.; Wilke, Daniel N.; Loveday, Philip W.

2017-02-01

An existing Ultrasonic Broken Rail Detection System installed in South Africa on a heavy duty railway line is currently being upgraded to include defect detection and location. To accomplish this, an ultrasonic piezoelectric transducer to strongly excite a guided wave mode with energy concentrated in the web (web mode) of a rail is required. A previous study demonstrated that the recently developed SAFE-3D (Semi-Analytical Finite Element - 3 Dimensional) method can effectively predict the guided waves excited by a resonant piezoelectric transducer. In this study, the SAFE-3D model is used in the design optimization of a rail web transducer. A bound-constrained optimization problem was formulated to maximize the energy transmitted by the transducer in the web mode when driven by a pre-defined excitation signal. Dimensions of the transducer components were selected as the three design variables. A Latin hypercube sampled design of experiments that required a total of 500 SAFE-3D analyses in the design space was employed in a response surface-based optimization approach. The Nelder-Mead optimization algorithm was then used to find an optimal transducer design on the constructed response surface. The radial basis function response surface was first verified by comparing a number of predicted responses against the computed SAFE-3D responses. The performance of the optimal transducer predicted by the optimization algorithm on the response surface was also verified to be sufficiently accurate using SAFE-3D. The computational advantages of SAFE-3D in optimal transducer design are noteworthy as more than 500 analyses were performed. The optimal design was then manufactured and experimental measurements were used to validate the predicted performance. The adopted design method has demonstrated the capability to automate the design of transducers for a particular rail cross-section and frequency range.

Novel chemometric strategy based on the application of artificial neural networks to crossed mixture design for the improvement of recombinant protein production in continuous culture.

PubMed

Didier, Caroline; Forno, Guillermina; Etcheverrigaray, Marina; Kratje, Ricardo; Goicoechea, Héctor

2009-09-21

The optimal blends of six compounds that should be present in culture media used in recombinant protein production were determined by means of artificial neural networks (ANN) coupled with crossed mixture experimental design. This combination constitutes a novel approach to develop a medium for cultivating genetically engineered mammalian cells. The compounds were collected in two mixtures of three elements each, and the experimental space was determined by a crossed mixture design. Empirical data from 51 experimental units were used in a multiresponse analysis to train artificial neural networks which satisfy different requirements, in order to define two new culture media (Medium 1 and Medium 2) to be used in a continuous biopharmaceutical production process. These media were tested in a bioreactor to produce a recombinant protein in CHO cells. Remarkably, for both predicted media all responses satisfied the predefined goals pursued during the analysis, except in the case of the specific growth rate (mu) observed for Medium 1. ANN analysis proved to be a suitable methodology to be used when dealing with complex experimental designs, as frequently occurs in the optimization of production processes in the biotechnology area. The present work is a new example of the use of ANN for the resolution of a complex, real life system, successfully employed in the context of a biopharmaceutical production process.

Response surface methodology for the optimization of sludge solubilization by ultrasonic pre-treatment

NASA Astrophysics Data System (ADS)

Zheng, Mingyue; Zhang, Xiaohui; Lu, Peng; Cao, Qiguang; Yuan, Yuan; Yue, Mingxing; Fu, Yiwei; Wu, Libin

2018-02-01

The present study examines the optimization of the ultrasonic pre-treatment conditions with response surface experimental design in terms of sludge disintegration efficiency (solubilisation of organic components). Ultrasonic pre-treatment for the maximum solubilization with residual sludge enhanced the SCOD release. Optimization of the ultrasonic pre-treatment was conducted through a Box-Behnken design (three variables, a total of 17 experiments) to determine the effects of three independent variables (power, residence time and TS) on COD solubilization of sludge. The optimal COD was obtained at 17349.4mg/L, when the power was 534.67W, the time was 10.77, and TS was 2%, while the SE of this condition was 28792J/kg TS.

Studies on the Parametric Effects of Plasma Arc Welding of 2205 Duplex Stainless Steel

NASA Astrophysics Data System (ADS)

Selva Bharathi, R.; Siva Shanmugam, N.; Murali Kannan, R.; Arungalai Vendan, S.

2018-03-01

This research study attempts to create an optimized parametric window by employing Taguchi algorithm for Plasma Arc Welding (PAW) of 2 mm thick 2205 duplex stainless steel. The parameters considered for experimentation and optimization are the welding current, welding speed and pilot arc length respectively. The experimentation involves the parameters variation and subsequently recording the depth of penetration and bead width. Welding current of 60-70 A, welding speed of 250-300 mm/min and pilot arc length of 1-2 mm are the range between which the parameters are varied. Design of experiments is used for the experimental trials. Back propagation neural network, Genetic algorithm and Taguchi techniques are used for predicting the bead width, depth of penetration and validated with experimentally achieved results which were in good agreement. Additionally, micro-structural characterizations are carried out to examine the weld quality. The extrapolation of these optimized parametric values yield enhanced weld strength with cost and time reduction.

Genetically Engineered Microelectronic Infrared Filters

NASA Technical Reports Server (NTRS)

Cwik, Tom; Klimeck, Gerhard

1998-01-01

A genetic algorithm is used for design of infrared filters and in the understanding of the material structure of a resonant tunneling diode. These two components are examples of microdevices and nanodevices that can be numerically simulated using fundamental mathematical and physical models. Because the number of parameters that can be used in the design of one of these devices is large, and because experimental exploration of the design space is unfeasible, reliable software models integrated with global optimization methods are examined The genetic algorithm and engineering design codes have been implemented on massively parallel computers to exploit their high performance. Design results are presented for the infrared filter showing new and optimized device design. Results for nanodevices are presented in a companion paper at this workshop.

Optimization of the NIF ignition point design hohlraum

NASA Astrophysics Data System (ADS)

Callahan, D. A.; Hinkel, D. E.; Berger, R. L.; Divol, L.; Dixit, S. N.; Edwards, M. J.; Haan, S. W.; Jones, O. S.; Lindl, J. D.; Meezan, N. B.; Michel, P. A.; Pollaine, S. M.; Suter, L. J.; Town, R. P. J.; Bradley, P. A.

2008-05-01

In preparation for the start of NIF ignition experiments, we have designed a porfolio of targets that span the temperature range that is consistent with initial NIF operations: 300 eV, 285 eV, and 270 eV. Because these targets are quite complicated, we have developed a plan for choosing the optimum hohlraum for the first ignition attempt that is based on this portfolio of designs coupled with early NIF experiements using 96 beams. These early experiments will measure the laser plasma instabilities of the candidate designs and will demonstrate our ability to tune symmetry in these designs. These experimental results, coupled with the theory and simulations that went into the designs, will allow us to choose the optimal hohlraum for the first NIF ignition attempt.

Influence of architecture and material properties on vanadium redox flow battery performance

NASA Astrophysics Data System (ADS)

Houser, Jacob; Clement, Jason; Pezeshki, Alan; Mench, Matthew M.

2016-01-01

This publication reports a design optimization study of all-vanadium redox flow batteries (VRBs), including performance testing, distributed current measurements, and flow visualization. Additionally, a computational flow simulation is used to support the conclusions made from the experimental results. This study demonstrates that optimal flow field design is not simply related to the best architecture, but is instead a more complex interplay between architecture, electrode properties, electrolyte properties, and operating conditions which combine to affect electrode convective transport. For example, an interdigitated design outperforms a serpentine design at low flow rates and with a thin electrode, accessing up to an additional 30% of discharge capacity; but a serpentine design can match the available discharge capacity of the interdigitated design by increasing the flow rate or the electrode thickness due to differing responses between the two flow fields. The results of this study should be useful to design engineers seeking to optimize VRB systems through enhanced performance and reduced pressure drop.

Comparison of optimization algorithms for the slow shot phase in HPDC

NASA Astrophysics Data System (ADS)

Frings, Markus; Berkels, Benjamin; Behr, Marek; Elgeti, Stefanie

2018-05-01

High-pressure die casting (HPDC) is a popular manufacturing process for aluminum processing. The slow shot phase in HPDC is the first phase of this process. During this phase, the molten metal is pushed towards the cavity under moderate plunger movement. The so-called shot curve describes this plunger movement. A good design of the shot curve is important to produce high-quality cast parts. Three partially competing process goals characterize the slow shot phase: (1) reducing air entrapment, (2) avoiding temperature loss, and (3) minimizing oxide caused by the air-aluminum contact. Due to the rough process conditions with high pressure and temperature, it is hard to design the shot curve experimentally. There exist a few design rules that are based on theoretical considerations. Nevertheless, the quality of the shot curve design still depends on the experience of the machine operator. To improve the shot curve it seems to be natural to use numerical optimization. This work compares different optimization strategies for the slow shot phase optimization. The aim is to find the best optimization approach on a simple test problem.

Optimal design of a shear magnetorheological damper for turning vibration suppression

NASA Astrophysics Data System (ADS)

Zhou, Y.; Zhang, Y. L.

2013-09-01

The intelligent material, so-called magnetorheological (MR) fluid, is utilized to control turning vibration. According to the structure of a common lathe CA6140, a shear MR damper is conceived by designing its structure and magnetic circuit. The vibration suppression effect of the damper is proved with dynamic analysis and simulation. Further, the magnetic circuit of the damper is optimized with the ANSYS parametric design language (APDL). In the optimization course, the area of the magnetic circuit and the damping force are considered. After optimization, the damper’s structure and its efficiency of electrical energy consumption are improved. Additionally, a comparative study on damping forces acquired from the initial and optimal design is conducted. A prototype of the developed MR damper is fabricated and magnetic tests are performed to measure the magnetic flux intensities and the residual magnetism in four damping gaps. Then, the testing results are compared with the simulated results. Finally, the suppressing vibration experimental system is set up and cylindrical turning experiments are performed to investigate the working performance of the MR damper.

Superscattering of light optimized by a genetic algorithm

NASA Astrophysics Data System (ADS)

Mirzaei, Ali; Miroshnichenko, Andrey E.; Shadrivov, Ilya V.; Kivshar, Yuri S.

2014-07-01

We analyse scattering of light from multi-layer plasmonic nanowires and employ a genetic algorithm for optimizing the scattering cross section. We apply the mode-expansion method using experimental data for material parameters to demonstrate that our genetic algorithm allows designing realistic core-shell nanostructures with the superscattering effect achieved at any desired wavelength. This approach can be employed for optimizing both superscattering and cloaking at different wavelengths in the visible spectral range.

Implementation of "Quality by Design (QbD)" Approach for the Development of 5-Fluorouracil Loaded Thermosensitive Hydrogel.

PubMed

Dalwadi, Chintan; Patel, Gayatri

2016-01-01

The purpose of this study was to investigate Quality by Design (QbD) principle for the preparation of hydrogel products to prove both practicability and utility of executing QbD concept to hydrogel based controlled release systems. Product and process understanding will help in decreasing the variability of critical material and process parameters, which give quality product output and reduce the risk. This study includes the identification of the Quality Target Product Profiles (QTPPs) and Critical Quality Attributes (CQAs) from literature or preliminary studies. To identify and control the variability in process and material attributes, two tools of QbD was utilized, Quality Risk Management (QRM) and Experimental Design. Further, it helps to identify the effect of these attributes on CQAs. Potential risk factors were identified from fishbone diagram and screened by risk assessment and optimized by 3-level 2- factor experimental design with center points in triplicate, to analyze the precision of the target process. This optimized formulation was further characterized by gelling time, gelling temperature, rheological parameters, in-vitro biodegradation and in-vitro drug release. Design space was created using experimental design tool that gives the control space and working within this controlled space reduces all the failure modes below the risk level. In conclusion, QbD approach with QRM tool provides potent and effectual pyramid to enhance the quality into the hydrogel.

Designing Experiments to Discriminate Families of Logic Models.

PubMed

Videla, Santiago; Konokotina, Irina; Alexopoulos, Leonidas G; Saez-Rodriguez, Julio; Schaub, Torsten; Siegel, Anne; Guziolowski, Carito

2015-01-01

Logic models of signaling pathways are a promising way of building effective in silico functional models of a cell, in particular of signaling pathways. The automated learning of Boolean logic models describing signaling pathways can be achieved by training to phosphoproteomics data, which is particularly useful if it is measured upon different combinations of perturbations in a high-throughput fashion. However, in practice, the number and type of allowed perturbations are not exhaustive. Moreover, experimental data are unavoidably subjected to noise. As a result, the learning process results in a family of feasible logical networks rather than in a single model. This family is composed of logic models implementing different internal wirings for the system and therefore the predictions of experiments from this family may present a significant level of variability, and hence uncertainty. In this paper, we introduce a method based on Answer Set Programming to propose an optimal experimental design that aims to narrow down the variability (in terms of input-output behaviors) within families of logical models learned from experimental data. We study how the fitness with respect to the data can be improved after an optimal selection of signaling perturbations and how we learn optimal logic models with minimal number of experiments. The methods are applied on signaling pathways in human liver cells and phosphoproteomics experimental data. Using 25% of the experiments, we obtained logical models with fitness scores (mean square error) 15% close to the ones obtained using all experiments, illustrating the impact that our approach can have on the design of experiments for efficient model calibration.

Optimal Design of Multitype Groundwater Monitoring Networks Using Easily Accessible Tools.

PubMed

Wöhling, Thomas; Geiges, Andreas; Nowak, Wolfgang

2016-11-01

Monitoring networks are expensive to establish and to maintain. In this paper, we extend an existing data-worth estimation method from the suite of PEST utilities with a global optimization method for optimal sensor placement (called optimal design) in groundwater monitoring networks. Design optimization can include multiple simultaneous sensor locations and multiple sensor types. Both location and sensor type are treated simultaneously as decision variables. Our method combines linear uncertainty quantification and a modified genetic algorithm for discrete multilocation, multitype search. The efficiency of the global optimization is enhanced by an archive of past samples and parallel computing. We demonstrate our methodology for a groundwater monitoring network at the Steinlach experimental site, south-western Germany, which has been established to monitor river-groundwater exchange processes. The target of optimization is the best possible exploration for minimum variance in predicting the mean travel time of the hyporheic exchange. Our results demonstrate that the information gain of monitoring network designs can be explored efficiently and with easily accessible tools prior to taking new field measurements or installing additional measurement points. The proposed methods proved to be efficient and can be applied for model-based optimal design of any type of monitoring network in approximately linear systems. Our key contributions are (1) the use of easy-to-implement tools for an otherwise complex task and (2) yet to consider data-worth interdependencies in simultaneous optimization of multiple sensor locations and sensor types. © 2016, National Ground Water Association.

Molecular identification of potential denitrifying bacteria and use of D-optimal mixture experimental design for the optimization of denitrification process.

PubMed

Ben Taheur, Fadia; Fdhila, Kais; Elabed, Hamouda; Bouguerra, Amel; Kouidhi, Bochra; Bakhrouf, Amina; Chaieb, Kamel

2016-04-01

Three bacterial strains (TE1, TD3 and FB2) were isolated from date palm (degla), pistachio and barley. The presence of nitrate reductase (narG) and nitrite reductase (nirS and nirK) genes in the selected strains was detected by PCR technique. Molecular identification based on 16S rDNA sequencing method was applied to identify positive strains. In addition, the D-optimal mixture experimental design was used to optimize the optimal formulation of probiotic bacteria for denitrification process. Strains harboring denitrification genes were identified as: TE1, Agrococcus sp LN828197; TD3, Cronobacter sakazakii LN828198 and FB2, Pedicoccus pentosaceus LN828199. PCR results revealed that all strains carried the nirS gene. However only C. sakazakii LN828198 and Agrococcus sp LN828197 harbored the nirK and the narG genes respectively. Moreover, the studied bacteria were able to form biofilm on abiotic surfaces with different degree. Process optimization showed that the most significant reduction of nitrate was 100% with 14.98% of COD consumption and 5.57 mg/l nitrite accumulation. Meanwhile, the response values were optimized and showed that the most optimal combination was 78.79% of C. sakazakii LN828198 (curve value), 21.21% of P. pentosaceus LN828199 (curve value) and absence (0%) of Agrococcus sp LN828197 (curve value). Copyright © 2016 Elsevier Ltd. All rights reserved.

D-OPTIMAL EXPERIMENTAL DESIGNS TO TEST FOR DEPARTURE FROM ADDITIVITY IN A FIXED-RATIO RAY MIXTURE.

EPA Science Inventory

Risk assessors are becoming increasingly aware of the importance of assessing interactions between chemicals in a mixture. Most traditional designs for evaluating interactions are prohibitive when the number of chemicals in the mixture is large. However, evaluation of interacti...

Statistical optimization of lovastatin production by Omphalotus olearius (DC.) singer in submerged fermentation.

PubMed

Atlı, Burcu; Yamaç, Mustafa; Yıldız, Zeki; Isikhuemhen, Omoanghe S

2016-01-01

In this study, culture conditions were optimized to improve lovastatin production by Omphalotus olearius, isolate OBCC 2002, using statistical experimental designs. The Plackett-Burman design was used to select important variables affecting lovastatin production. Accordingly, glucose, peptone, and agitation speed were determined as the variables that have influence on lovastatin production. In a further experiment, these variables were optimized with a Box-Behnken design and applied in a submerged process; this resulted in 12.51 mg/L lovastatin production on a medium containing glucose (10 g/L), peptone (5 g/L), thiamine (1 mg/L), and NaCl (0.4 g/L) under static conditions. This level of lovastatin production is eight times higher than that produced under unoptimized media and growth conditions by Omphalotus olearius. To the best of our knowledge, this is the first attempt to optimize submerged fermentation process for lovastatin production by Omphalotus olearius.

Modeling and optimization of trihalomethanes formation potential of surface water (a drinking water source) using Box-Behnken design.

PubMed

Singh, Kunwar P; Rai, Premanjali; Pandey, Priyanka; Sinha, Sarita

2012-01-01

The present research aims to investigate the individual and interactive effects of chlorine dose/dissolved organic carbon ratio, pH, temperature, bromide concentration, and reaction time on trihalomethanes (THMs) formation in surface water (a drinking water source) during disinfection by chlorination in a prototype laboratory-scale simulation and to develop a model for the prediction and optimization of THMs levels in chlorinated water for their effective control. A five-factor Box-Behnken experimental design combined with response surface and optimization modeling was used for predicting the THMs levels in chlorinated water. The adequacy of the selected model and statistical significance of the regression coefficients, independent variables, and their interactions were tested by the analysis of variance and t test statistics. The THMs levels predicted by the model were very close to the experimental values (R(2) = 0.95). Optimization modeling predicted maximum (192 μg/l) TMHs formation (highest risk) level in water during chlorination was very close to the experimental value (186.8 ± 1.72 μg/l) determined in laboratory experiments. The pH of water followed by reaction time and temperature were the most significant factors that affect the THMs formation during chlorination. The developed model can be used to determine the optimum characteristics of raw water and chlorination conditions for maintaining the THMs levels within the safe limit.

Design optimization of an ironless inductive position sensor for the LHC collimators

NASA Astrophysics Data System (ADS)

Danisi, A.; Masi, A.; Losito, R.; Perriard, Y.

2013-09-01

The Ironless Inductive Position Sensor (I2PS) is an air-cored displacement sensor which has been conceived to be totally immune to external DC/slowly-varying magnetic fields. It can thus be used as a valid alternative to Linear Variable Differential Transformers (LVDTs), which can show a position error in magnetic environments. In addition, since it retains the excellent properties of LVDTs, the I2PS can be used in harsh environments, such as nuclear plants, plasma control and particle accelerators. This paper focuses on the design optimization of the sensor, considering the CERN LHC Collimators as application. In particular, the optimization comes after a complete review of the electromagnetic and thermal modeling of the sensor, as well as the proper choice of the reading technique. The design optimization stage is firmly based on these preliminary steps. Therefore, the paper summarises the sensor's complete development, from its modeling to its actual implementation. A set of experimental measurements demonstrates the sensor's performances to be those expected in the design phase.

Dynamic Data Driven Experiment Control Coordinated with Anisotropic Elastic Material Characterization

Treesearch

John G. Michopoulos; Tomonari Furukawa; John C. Hermanson; Samuel G. Lambrakos

2011-01-01

The goal of this paper is to propose and demonstrate a multi level design optimization approach for the coordinated determination of a material constitutive model synchronously to the design of the experimental procedure needed to acquire the necessary data. The methodology achieves both online (real-time) and offline design of optimum experiments required for...

Application of response surface methodology for optimization of polygalacturonase production by Aspergillus niger.

PubMed

Yadav, Kaushlesh K; Garg, Neelima; Kumar, Devendra; Kumar, Sanjay; Singh, Achal; Muthukumar, M

2015-01-01

Polygalacturonase (PG) degrades pectin into D-galacturonic acid monomers and is used widely in food industry especially for juice clarification. In the present study,. fermentation conditions for polygalacturonase production by Asgergillus niger NAIMCCF-02958, using mango peel as substrate, were optimized using the 2(3) factorial design with central composite rotatable experimental design (CCRD) of response surface methodology (RSM). The maximum PG activity 723.66 U g(-1) was achieved under pH 4.0, temperature 30 degrees C and 2% inoculum by response surface curve. The experimental value of PG activity wkas higher 607.65 U g(-1) than the predicted value 511.75 U g(-1). Under the proposed optimized conditions, the determination coefficient (R2) was equal to 0.66 indicating that the model could explain 66% of the total variation as well as establish the relationship between the variables and the responses. ANOVA analysis and the three dimensional plots also confirmed interactions among the parameters.

Optimization by response surface methodology of lutein recovery from paprika leaves using accelerated solvent extraction.

PubMed

Kang, Jae-Hyun; Kim, Suna; Moon, BoKyung

2016-08-15

In this study, we used response surface methodology (RSM) to optimize the extraction conditions for recovering lutein from paprika leaves using accelerated solvent extraction (ASE). The lutein content was quantitatively analyzed using a UPLC equipped with a BEH C18 column. A central composite design (CCD) was employed for experimental design to obtain the optimized combination of extraction temperature (°C), static time (min), and solvent (EtOH, %). The experimental data obtained from a twenty sample set were fitted to a second-order polynomial equation using multiple regression analysis. The adjusted coefficient of determination (R(2)) for the lutein extraction model was 0.9518, and the probability value (p=0.0000) demonstrated a high significance for the regression model. The optimum extraction conditions for lutein were temperature: 93.26°C, static time: 5 min, and solvent: 79.63% EtOH. Under these conditions, the predicted extraction yield of lutein was 232.60 μg/g. Copyright © 2016 Elsevier Ltd. All rights reserved.

Solution blow spinning: parameters optimization and effects on the properties of nanofibers from poly(lactic) acid/dimethyl carbonate solutions

USDA-ARS?s Scientific Manuscript database

Solution blow spinning (SBS) is a process to produce non-woven fiber sheets with high porosity and an extremely large amount of surface area. In this study, a Box-Behnken experimental design (BBD) was used to optimize the processing parameters for the production of nanofibers from polymer solutions ...

Research of vibration control based on current mode piezoelectric shunt damping circuit

NASA Astrophysics Data System (ADS)

Liu, Weiwei; Mao, Qibo

2017-12-01

The piezoelectric shunt damping circuit using current mode approach is imposed to control the vibration of a cantilever beam. Firstly, the simulated inductance with large values are designed for the corresponding RL series shunt circuits. Moreover, with an example of cantilever beam, the second natural frequency of the beam is targeted to control for experiment. By adjusting the values of the equivalent inductance and equivalent resistance of the shunt circuit, the optimal damping of the shunt circuit is obtained. Meanwhile, the designed piezoelectric shunt damping circuit stability is experimental verified. Experimental results show that the proposed piezoelectric shunt damping circuit based on current mode circuit has good vibration control performance. However, the control performance will be reduced if equivalent inductance and equivalent resistance values deviate from optimal values.

Teaching Experimental Design Using a GC MS Analysis of Cocaine on Money: A Cross-Disciplinary Laboratory 1254 Christopher A. Heimbuck and Nathan W. Bower Quantitative Determination of Nicotine and Cotinine in Urine and Sputum Using a Combined SPME-GC/MS Method

NASA Astrophysics Data System (ADS)

Witter, A. E.; Klinger, D. M.; Fan, X.; Lam, M.; Mathers, D. T.; Mabury, S. A.

2002-10-01

The forensic analysis of cocaine on currencies was optimized using a fractional, two-level experimental design that compared methanol and HCl extraction, SPE versus heptane pre-concentration, and extracted versus total ion chromatography. Subsequent student-initiated questions about levels of cocaine on U.S. and world currencies helped make connections to societal issues while teaching method optimization and chromatography. A significant correlation was found between the levels of cocaine and the age of the bills. Levels of cocaine on various world currencies followed expected drug-trafficking patterns with the highest levels found in the most developed countries.

A numerical identifiability test for state-space models--application to optimal experimental design.

PubMed

Hidalgo, M E; Ayesa, E

2001-01-01

This paper describes a mathematical tool for identifiability analysis, easily applicable to high order non-linear systems modelled in state-space and implementable in simulators with a time-discrete approach. This procedure also permits a rigorous analysis of the expected estimation errors (average and maximum) in calibration experiments. The methodology is based on the recursive numerical evaluation of the information matrix during the simulation of a calibration experiment and in the setting-up of a group of information parameters based on geometric interpretations of this matrix. As an example of the utility of the proposed test, the paper presents its application to an optimal experimental design of ASM Model No. 1 calibration, in order to estimate the maximum specific growth rate microH and the concentration of heterotrophic biomass XBH.

Optimization of marine waste based-growth media for microbial lipase production using mixture design methodology.

PubMed

Sellami, Mohamed; Kedachi, Samiha; Frikha, Fakher; Miled, Nabil; Ben Rebah, Faouzi

2013-01-01

Lipase production by Staphylococcus xylosus and Rhizopus oryzae was investigated using a culture medium based on a mixture of synthetic medium and supernatants generated from tuna by-products and Ulva rigida biomass. The proportion of the three medium components was optimized using the simplex-centroid mixture design method (SCMD). Results indicated that the experimental data were in good agreement with predicted values, indicating that SCMD was a reliable method for determining the optimum mixture proportion of the growth medium. Maximal lipase activities of 12.5 and 23.5 IU/mL were obtained with a 50:50 (v:v) mixture of synthetic medium and tuna by-product supernatant for Staphylococcus xylosus and Rhizopus oryzae, respectively. The predicted responses from these mixture proportions were also validated experimentally.

Modified optimal control pilot model for computer-aided design and analysis

NASA Technical Reports Server (NTRS)

Davidson, John B.; Schmidt, David K.

1992-01-01

This paper presents the theoretical development of a modified optimal control pilot model based upon the optimal control model (OCM) of the human operator developed by Kleinman, Baron, and Levison. This model is input compatible with the OCM and retains other key aspects of the OCM, such as a linear quadratic solution for the pilot gains with inclusion of control rate in the cost function, a Kalman estimator, and the ability to account for attention allocation and perception threshold effects. An algorithm designed for each implementation in current dynamic systems analysis and design software is presented. Example results based upon the analysis of a tracking task using three basic dynamic systems are compared with measured results and with similar analyses performed with the OCM and two previously proposed simplified optimal pilot models. The pilot frequency responses and error statistics obtained with this modified optimal control model are shown to compare more favorably to the measured experimental results than the other previously proposed simplified models evaluated.

Optimal design of composite upper covers of lateral wings with the effect of rib attachment to stiffener webs

NASA Astrophysics Data System (ADS)

Barkanov, E.; Eglītis, E.; Almeida, F.; Bowering, M. C.; Watson, G.

2013-07-01

The present investigation is devoted to the development of new optimal design concepts that exploit the full potential of advanced composite materials in the upper covers of aircraft lateral wings. A finite-element simulation of three-rib-bay laminated composite panels with T-stiffeners and a stiffener pitch of 200 mm is carried out using ANSYS to investigate the effect of rib attachment to stiffener webs on the performance of stiffened panels in terms of their buckling behavior and in relation to skin and stiffener lay-ups, stiffener height, and root width. Due to the large dimension of numerical problems to be solved, an optimization methodology is developed employing the method of experimental design and the response surface technique. Minimal-weight optimization problems were solved for four load levels with account of manufacturing, repairability, and damage tolerance requirements. The optimal results were verified successfully by using the ANSYS and ABAQUS shared-node models.

Design optimization for 25 Gbit/s DML InGaAlAs/InGaAsP/InP SL-MQW laser diode incorporating temperature effect

NASA Astrophysics Data System (ADS)

Ke, Cheng; Li, Xun; Xi, Yanping; Yu, Yang

2017-11-01

In this paper, a detailed carrier dynamics model for quantum well lasers is used to study the modulation bandwidth of the directly modulated strained-layer multiple quantum well (SL-MQW) laser. The active region of the directly modulated laser (DML) is optimized in terms of the number of QWs and barrier height. To compromise the device dynamic performance at different operating temperatures, we present an overall optimized design for a 25 Gbps DML under an ambient temperature ranging from 25 to 85°C. To further enhance the modulation bandwidth, we have also proposed a mixed QWs design that increases the 3 dB bandwidth by almost 44% compared to the one without undergoing optimization. The experimental results show that the 3 dB bandwidth of the optimized DML can reach 19 GHz. A clear eye diagram with a bit rate of 25 Gbps was observed at 25°C.

Principles of Experimental Design for Big Data Analysis.

PubMed

Drovandi, Christopher C; Holmes, Christopher; McGree, James M; Mengersen, Kerrie; Richardson, Sylvia; Ryan, Elizabeth G

2017-08-01

Big Datasets are endemic, but are often notoriously difficult to analyse because of their size, heterogeneity and quality. The purpose of this paper is to open a discourse on the potential for modern decision theoretic optimal experimental design methods, which by their very nature have traditionally been applied prospectively, to improve the analysis of Big Data through retrospective designed sampling in order to answer particular questions of interest. By appealing to a range of examples, it is suggested that this perspective on Big Data modelling and analysis has the potential for wide generality and advantageous inferential and computational properties. We highlight current hurdles and open research questions surrounding efficient computational optimisation in using retrospective designs, and in part this paper is a call to the optimisation and experimental design communities to work together in the field of Big Data analysis.

Principles of Experimental Design for Big Data Analysis

PubMed Central

Drovandi, Christopher C; Holmes, Christopher; McGree, James M; Mengersen, Kerrie; Richardson, Sylvia; Ryan, Elizabeth G

2016-01-01

Big Datasets are endemic, but are often notoriously difficult to analyse because of their size, heterogeneity and quality. The purpose of this paper is to open a discourse on the potential for modern decision theoretic optimal experimental design methods, which by their very nature have traditionally been applied prospectively, to improve the analysis of Big Data through retrospective designed sampling in order to answer particular questions of interest. By appealing to a range of examples, it is suggested that this perspective on Big Data modelling and analysis has the potential for wide generality and advantageous inferential and computational properties. We highlight current hurdles and open research questions surrounding efficient computational optimisation in using retrospective designs, and in part this paper is a call to the optimisation and experimental design communities to work together in the field of Big Data analysis. PMID:28883686

Automatic design of synthetic gene circuits through mixed integer non-linear programming.

PubMed

Huynh, Linh; Kececioglu, John; Köppe, Matthias; Tagkopoulos, Ilias

2012-01-01

Automatic design of synthetic gene circuits poses a significant challenge to synthetic biology, primarily due to the complexity of biological systems, and the lack of rigorous optimization methods that can cope with the combinatorial explosion as the number of biological parts increases. Current optimization methods for synthetic gene design rely on heuristic algorithms that are usually not deterministic, deliver sub-optimal solutions, and provide no guaranties on convergence or error bounds. Here, we introduce an optimization framework for the problem of part selection in synthetic gene circuits that is based on mixed integer non-linear programming (MINLP), which is a deterministic method that finds the globally optimal solution and guarantees convergence in finite time. Given a synthetic gene circuit, a library of characterized parts, and user-defined constraints, our method can find the optimal selection of parts that satisfy the constraints and best approximates the objective function given by the user. We evaluated the proposed method in the design of three synthetic circuits (a toggle switch, a transcriptional cascade, and a band detector), with both experimentally constructed and synthetic promoter libraries. Scalability and robustness analysis shows that the proposed framework scales well with the library size and the solution space. The work described here is a step towards a unifying, realistic framework for the automated design of biological circuits.

A new chaotic multi-verse optimization algorithm for solving engineering optimization problems

NASA Astrophysics Data System (ADS)

Sayed, Gehad Ismail; Darwish, Ashraf; Hassanien, Aboul Ella

2018-03-01

Multi-verse optimization algorithm (MVO) is one of the recent meta-heuristic optimization algorithms. The main inspiration of this algorithm came from multi-verse theory in physics. However, MVO like most optimization algorithms suffers from low convergence rate and entrapment in local optima. In this paper, a new chaotic multi-verse optimization algorithm (CMVO) is proposed to overcome these problems. The proposed CMVO is applied on 13 benchmark functions and 7 well-known design problems in the engineering and mechanical field; namely, three-bar trust, speed reduce design, pressure vessel problem, spring design, welded beam, rolling element-bearing and multiple disc clutch brake. In the current study, a modified feasible-based mechanism is employed to handle constraints. In this mechanism, four rules were used to handle the specific constraint problem through maintaining a balance between feasible and infeasible solutions. Moreover, 10 well-known chaotic maps are used to improve the performance of MVO. The experimental results showed that CMVO outperforms other meta-heuristic optimization algorithms on most of the optimization problems. Also, the results reveal that sine chaotic map is the most appropriate map to significantly boost MVO's performance.

Optimization of Nanocomposite Modified Asphalt Mixtures Fatigue Life using Response Surface Methodology

NASA Astrophysics Data System (ADS)

Bala, N.; Napiah, M.; Kamaruddin, I.; Danlami, N.

2018-04-01

In this study, modelling and optimization of materials polyethylene, polypropylene and nanosilica for nanocomposite modified asphalt mixtures has been examined to obtain optimum quantities for higher fatique life. Response Surface Methodology (RSM) was applied for the optimization based on Box Behnken design (BBD). Interaction effects of independent variables polymers and nanosilica on fatique life were evaluated. The result indicates that the individual effects of polymers and nanosilica content are both important. However, the content of nanosilica used has more significant effect on fatique life resistance. Also, the mean error obtained from optimization results is less than 5% for all the responses, this indicates that predicted values are in agreement with experimental results. Furthermore, it was concluded that asphalt mixture design with high performance properties, optimization using RSM is a very effective approach.

Optimization of ultrasound-assisted extraction of phenolic compounds from grapefruit (Citrus paradisi Macf.) leaves via D-optimal design and artificial neural network design with categorical and quantitative variables.

PubMed

Ciğeroğlu, Zeynep; Aras, Ömür; Pinto, Carlos A; Bayramoglu, Mahmut; Kırbaşlar, Ş İsmail; Lorenzo, José M; Barba, Francisco J; Saraiva, Jorge A; Şahin, Selin

2018-03-06

The extraction of phenolic compounds from grapefruit leaves assisted by ultrasound-assisted extraction (UAE) was optimized using response surface methodology (RSM) by means of D-optimal experimental design and artificial neural network (ANN). For this purpose, five numerical factors were selected: ethanol concentration (0-50%), extraction time (15-60 min), extraction temperature (25-50 °C), solid:liquid ratio (50-100 g L -1 ) and calorimetric energy density of ultrasound (0.25-0.50 kW L -1 ), whereas ultrasound probe horn diameter (13 or 19 mm) was chosen as categorical factor. The optimized experimental conditions yielded by RSM were: 10.80% for ethanol concentration; 58.52 min for extraction time; 30.37 °C for extraction temperature; 52.33 g L -1 for solid:liquid ratio; 0.457 kW L -1 for ultrasonic power density, with thick probe type. Under these conditions total phenolics content was found to be 19.04 mg gallic acid equivalents g -1 dried leaf. The same dataset was used to train multilayer feed-forward networks using different approaches via MATLAB, with ANN exhibiting superior performance to RSM (differences included categorical factor in one model and higher regression coefficients), while close values were obtained for the extraction variables under study, except for ethanol concentration and extraction time. © 2018 Society of Chemical Industry. © 2018 Society of Chemical Industry.

Analysis and design of a capsule landing system and surface vehicle control system for Mars exploration

NASA Technical Reports Server (NTRS)

Frederick, D. K.; Lashmet, P. K.; Sandor, G. N.; Shen, C. N.; Smith, E. V.; Yerazunis, S. W.

1973-01-01

Problems related to the design and control of a mobile planetary vehicle to implement a systematic plan for the exploration of Mars are reported. Problem areas include: vehicle configuration, control, dynamics, systems and propulsion; systems analysis, terrain modeling and path selection; and chemical analysis of specimens. These tasks are summarized: vehicle model design, mathematical model of vehicle dynamics, experimental vehicle dynamics, obstacle negotiation, electrochemical controls, remote control, collapsibility and deployment, construction of a wheel tester, wheel analysis, payload design, system design optimization, effect of design assumptions, accessory optimal design, on-board computer subsystem, laser range measurement, discrete obstacle detection, obstacle detection systems, terrain modeling, path selection system simulation and evaluation, gas chromatograph/mass spectrometer system concepts, and chromatograph model evaluation and improvement.

Performance metric comparison study for non-magnetic bi-stable energy harvesters

NASA Astrophysics Data System (ADS)

Udani, Janav P.; Wrigley, Cailin; Arrieta, Andres F.

2017-04-01

Energy harvesting employing non-linear systems offers considerable advantages over linear systems given the broadband resonant response which is favorable for applications involving diverse input vibrations. In this respect, the rich dynamics of bi-stable systems present a promising means for harvesting vibrational energy from ambient sources. Harvesters deriving their bi-stability from thermally induced stresses as opposed to magnetic forces are receiving significant attention as it reduces the need for ancillary components and allows for bio- compatible constructions. However, the design of these bi-stable harvesters still requires further optimization to completely exploit the dynamic behavior of these systems. This study presents a comparison of the harvesting capabilities of non-magnetic, bi-stable composite laminates under variations in the design parameters as evaluated utilizing established power metrics. Energy output characteristics of two bi-stable composite laminate plates with a piezoelectric patch bonded on the top surface are experimentally investigated for variations in the thickness ratio and inertial mass positions for multiple load conditions. A particular design configuration is found to perform better over the entire range of testing conditions which include single and multiple frequency excitation, thus indicating that design optimization over the geometry of the harvester yields robust performance. The experimental analysis further highlights the need for appropriate design guidelines for optimization and holistic performance metrics to account for the range of operational conditions.

Effect of leading-edge load constraints on the design and performance of supersonic wings

NASA Technical Reports Server (NTRS)

Darden, C. M.

1985-01-01

A theoretical and experimental investigation was conducted to assess the effect of leading-edge load constraints on supersonic wing design and performance. In the effort to delay flow separation and the formation of leading-edge vortices, two constrained, linear-theory optimization approaches were used to limit the loadings on the leading edge of a variable-sweep planform design. Experimental force and moment tests were made on two constrained camber wings, a flat uncambered wing, and an optimum design with no constraints. Results indicate that vortex strength and separation regions were mildest on the severely and moderately constrained wings.

Optimal Design for Regression Discontinuity Studies with Clustering

ERIC Educational Resources Information Center

Rhoads, Christopher; Dye, Charles

2014-01-01

Recent years have seen an increased interest in quantitative educational research studies that use random assignment (RA) to evaluate the causal impacts of educational interventions (Angrist, 2004). The multi-level structure of the public education system in the United States often leads to experimental designs where naturally occurring clusters…

[Optimization of ultrasonic-assisted extraction of total flavonoids from leaves of the Artocarpus heterophyllus by response surface methodology].

PubMed

Wang, Hong-wu; Liu, Yan-qing; Wang, Yuan-hong

2011-07-01

To investigate the ultrasonic-assisted extract on of total flavonoids from leaves of the Artocarpus heterophyllus. Investigated the effects of ethanol concentration, extraction time, and liquid-solid ratio on flavonoids yield. A 17-run response surface design involving three factors at three levels was generated by the Design-Expert software and experimental data obtained were subjected to quadratic regression analysis to create a mathematical model describing flavonoids extraction. The optimum ultrasonic assisted extraction conditions were: ethanol volume fraction 69.4% and liquid-solid ratio of 22.6:1 for 32 min. Under these optimized conditions, the yield of flavonoids was 7.55 mg/g. The Box-Behnken design and response surface analysis can well optimize the ultrasonic-assisted extraction of total flavonoids from Artocarpus heterophyllus.

Solar-cell interconnect design for terrestrial photovoltaic modules

NASA Technical Reports Server (NTRS)

Mon, G. R.; Moore, D. M.; Ross, R. G., Jr.

1984-01-01

Useful solar cell interconnect reliability design and life prediction algorithms are presented, together with experimental data indicating that the classical strain cycle (fatigue) curve for the interconnect material does not account for the statistical scatter that is required in reliability predictions. This shortcoming is presently addressed by fitting a functional form to experimental cumulative interconnect failure rate data, which thereby yields statistical fatigue curves enabling not only the prediction of cumulative interconnect failures during the design life of an array field, but also the quantitative interpretation of data from accelerated thermal cycling tests. Optimal interconnect cost reliability design algorithms are also derived which may allow the minimization of energy cost over the design life of the array field.

Solar-cell interconnect design for terrestrial photovoltaic modules

NASA Astrophysics Data System (ADS)

Mon, G. R.; Moore, D. M.; Ross, R. G., Jr.

1984-11-01

Useful solar cell interconnect reliability design and life prediction algorithms are presented, together with experimental data indicating that the classical strain cycle (fatigue) curve for the interconnect material does not account for the statistical scatter that is required in reliability predictions. This shortcoming is presently addressed by fitting a functional form to experimental cumulative interconnect failure rate data, which thereby yields statistical fatigue curves enabling not only the prediction of cumulative interconnect failures during the design life of an array field, but also the quantitative interpretation of data from accelerated thermal cycling tests. Optimal interconnect cost reliability design algorithms are also derived which may allow the minimization of energy cost over the design life of the array field.

Design variables for mechanical properties of bone tissue scaffolds.

PubMed

Howk, Daniel; Chu, Tien-Min G

2006-01-01

The reconstruction of segmental defect in long bone is a clinical challenge. Multiple surgeries are typically required to restore the structure and function of the affected defect site. In order to overcome this defect a biodegradable bone tissue engineering scaffold is used. This scaffold acts as a carrier of proteins and growth factors, while also supporting the load that the bone would normally sustain, until the natural bone can regenerate in its place. Work was done to optimize an existing solid free-form scaffold design. The goal of the optimization was to increase the porosity of the scaffold while maintaining the strength of a previously-tested prototype design. With this in mind, eight new designs were created. These designs were drawn using CAD software and then through the use of finite element analysis the theoretical ultimate compressive strength of each design was obtained. Each scaffold design was constructed by casting a thermal-curable poly(propylene fumarate)/tricalcium phosphate (PPF/TCP) suspension into wax molds fabricated on inkjet printing rapid prototyping machine. The constructs were then experimentally tested by applying a uniaxial compressive load. The theoretical and experimental values of ultimate compressive strength and specific strength of each design were compared. Theoretically, the best scaffold design produced from this work improved upon the current design by increasing the porosity by 46% and also increasing the ultimate compressive strength by 27%. The experimental data was found to match the theoretical strength in four designs, but deviate from the theoretical strength in five designs. The reasons for the deviations and their relation to the rapid prototyping manufacturing technique were discussed. The results of this work show that it is possible to increase the porosity and strength of a bone tissue engineering scaffold through simple iterations in architectural design.

Real-time PCR probe optimization using design of experiments approach.

PubMed

Wadle, S; Lehnert, M; Rubenwolf, S; Zengerle, R; von Stetten, F

2016-03-01

Primer and probe sequence designs are among the most critical input factors in real-time polymerase chain reaction (PCR) assay optimization. In this study, we present the use of statistical design of experiments (DOE) approach as a general guideline for probe optimization and more specifically focus on design optimization of label-free hydrolysis probes that are designated as mediator probes (MPs), which are used in reverse transcription MP PCR (RT-MP PCR). The effect of three input factors on assay performance was investigated: distance between primer and mediator probe cleavage site; dimer stability of MP and target sequence (influenza B virus); and dimer stability of the mediator and universal reporter (UR). The results indicated that the latter dimer stability had the greatest influence on assay performance, with RT-MP PCR efficiency increased by up to 10% with changes to this input factor. With an optimal design configuration, a detection limit of 3-14 target copies/10 μl reaction could be achieved. This improved detection limit was confirmed for another UR design and for a second target sequence, human metapneumovirus, with 7-11 copies/10 μl reaction detected in an optimum case. The DOE approach for improving oligonucleotide designs for real-time PCR not only produces excellent results but may also reduce the number of experiments that need to be performed, thus reducing costs and experimental times.

Design and experimental realization of an optimal scheme for teleportation of an n-qubit quantum state

NASA Astrophysics Data System (ADS)

Sisodia, Mitali; Shukla, Abhishek; Thapliyal, Kishore; Pathak, Anirban

2017-12-01

An explicit scheme (quantum circuit) is designed for the teleportation of an n-qubit quantum state. It is established that the proposed scheme requires an optimal amount of quantum resources, whereas larger amount of quantum resources have been used in a large number of recently reported teleportation schemes for the quantum states which can be viewed as special cases of the general n-qubit state considered here. A trade-off between our knowledge about the quantum state to be teleported and the amount of quantum resources required for the same is observed. A proof-of-principle experimental realization of the proposed scheme (for a 2-qubit state) is also performed using 5-qubit superconductivity-based IBM quantum computer. The experimental results show that the state has been teleported with high fidelity. Relevance of the proposed teleportation scheme has also been discussed in the context of controlled, bidirectional, and bidirectional controlled state teleportation.

Application of Box-Behnken experimental design to optimize the extraction of insecticidal Cry1Ac from soil.

PubMed

Li, Yan-Liang; Fang, Zhi-Xiang; You, Jing

2013-02-20

A validated method for analyzing Cry proteins is a premise to study the fate and ecological effects of contaminants associated with genetically engineered Bacillus thuringiensis crops. The current study has optimized the extraction method to analyze Cry1Ac protein in soil using a response surface methodology with a three-level-three-factor Box-Behnken experimental design (BBD). The optimum extraction conditions were at 21 °C and 630 rpm for 2 h. Regression analysis showed a good fit of the experimental data to the second-order polynomial model with a coefficient of determination of 0.96. The method was sensitive and precise with a method detection limit of 0.8 ng/g dry weight and relative standard deviations at 7.3%. Finally, the established method was applied for analyzing Cry1Ac protein residues in field-collected soil samples. Trace amounts of Cry1Ac protein were detected in the soils where transgenic crops have been planted for 8 and 12 years.

Design principles and operating principles: the yin and yang of optimal functioning.

PubMed

Voit, Eberhard O

2003-03-01

Metabolic engineering has as a goal the improvement of yield of desired products from microorganisms and cell lines. This goal has traditionally been approached with experimental biotechnological methods, but it is becoming increasingly popular to precede the experimental phase by a mathematical modeling step that allows objective pre-screening of possible improvement strategies. The models are either linear and represent the stoichiometry and flux distribution in pathways or they are non-linear and account for the full kinetic behavior of the pathway, which is often significantly effected by regulatory signals. Linear flux analysis is simpler and requires less input information than a full kinetic analysis, and the question arises whether the consideration of non-linearities is really necessary for devising optimal strategies for yield improvements. The article analyzes this question with a generic, representative pathway. It shows that flux split ratios, which are the key criterion for linear flux analysis, are essentially sufficient for unregulated, but not for regulated branch points. The interrelationships between regulatory design on one hand and optimal patterns of operation on the other suggest the investigation of operating principles that complement design principles, like a user's manual complements the hardwiring of electronic equipment.

Manganese ore tailing: optimization of acid leaching conditions and recovery of soluble manganese.

PubMed

Santos, Olívia de Souza Heleno; Carvalho, Cornélio de Freitas; Silva, Gilmare Antônia da; Santos, Cláudio Gouvêa Dos

2015-01-01

Manganese recovery from industrial ore processing waste by means of leaching with sulfuric acid was the objective of this study. Experimental conditions were optimized by multivariate experimental design approaches. In order to study the factors affecting leaching, a screening step was used involving a full factorial design with central point for three variables in two levels (2(3)). The three variables studied were leaching time, concentration of sulfuric acid and sample amount. The three factors screened were shown to be relevant and therefore a Doehlert design was applied to determine the best working conditions for leaching and to build the response surface. By applying the best leaching conditions, the concentrations of 12.80 and 13.64 %w/w of manganese for the global sample and for the fraction -44 + 37 μm, respectively, were found. Microbeads of chitosan were tested for removal of leachate acidity and recovering of soluble manganese. Manganese recovery from the leachate was 95.4%. Upon drying the leachate, a solid containing mostly manganese sulfate was obtained, showing that the proposed optimized method is efficient for manganese recovery from ore tailings. Copyright © 2014 Elsevier Ltd. All rights reserved.

Method optimization for drug impurity profiling in supercritical fluid chromatography: Application to a pharmaceutical mixture.

PubMed

Muscat Galea, Charlene; Didion, David; Clicq, David; Mangelings, Debby; Vander Heyden, Yvan

2017-12-01

A supercritical chromatographic method for the separation of a drug and its impurities has been developed and optimized applying an experimental design approach and chromatogram simulations. Stationary phase screening was followed by optimization of the modifier and injection solvent composition. A design-of-experiment (DoE) approach was then used to optimize column temperature, back-pressure and the gradient slope simultaneously. Regression models for the retention times and peak widths of all mixture components were built. The factor levels for different grid points were then used to predict the retention times and peak widths of the mixture components using the regression models and the best separation for the worst separated peak pair in the experimental domain was identified. A plot of the minimal resolutions was used to help identifying the factor levels leading to the highest resolution between consecutive peaks. The effects of the DoE factors were visualized in a way that is familiar to the analytical chemist, i.e. by simulating the resulting chromatogram. The mixture of an active ingredient and seven impurities was separated in less than eight minutes. The approach discussed in this paper demonstrates how SFC methods can be developed and optimized efficiently using simple concepts and tools. Copyright © 2017 Elsevier B.V. All rights reserved.

Optimization of the isolation and quantitation of kahweol and cafestol in green coffee oil.

PubMed

Chartier, Agnes; Beaumesnil, Mathieu; de Oliveira, Alessandra Lopes; Elfakir, Claire; Bostyn, Stephane

2013-12-15

Kahweol and cafestol are two diterpenes that exist mainly as esters of fatty acids in green coffee oil. To recover them under their free form they have to be either saponified or trans-esterified. These two compounds are well known to be sensitive to heat, and reagents, therefore experimental conditions used in the transesterification reaction are critical. In this paper, a Doehlert experimental design plan is used to optimize the transesterification conditions using some key variables such as the temperature of the reaction, the reagent base concentration and the duration of the reaction. Therefore, the optimal parameters determined from the Doehlert design are equal to 70 °C, temperature of the reaction; 1.25 mol L(-1) concentration of the reagent base; and 60 min reaction time. The contour plots show that the extracted quantity of kahweol and cafestol can depend greatly from the experimental conditions. After transesterification, the free form of the diterpernes is extracted from the lipid fraction using liquid-liquid extraction and analyzed using GC-FID without prior derivatization. The amount of kahweol and cafestol obtained from green coffee oil obtained by cold mechanical press of Catuai coffee bean is equal to 33.2±2.2 and 24.3±2.4 g kg(-1)oil, respectively. In an attempt to streamline the process, the transesterification reaction is performed in an in-flow chemistry reactor using the optimal conditions obtained with the Doehlert experimental design. The amount of kahweol and cafestol obtained from the same green coffee oil is equal to 43.5 and 30.072 g kg(-1)oil, respectively. Results are slightly higher compared to the ones obtained with the batch procedure. This can be explained by a better mixing of the coffee oil with the reagents and a faster transesterification reaction. © 2013 Elsevier B.V. All rights reserved.

Application of Box-Behnken design for ultrasonic-assisted extraction of polysaccharides from Paeonia emodi.

PubMed

Ahmad, Ajaz; Alkharfy, Khalid M; Wani, Tanveer A; Raish, Mohammad

2015-01-01

The objective of the present work was to study the ultrasonic assisted extraction and optimization of polysaccharides from Paeonia emodi and evaluation of its anti-inflammatory response. Specifically, the optimization of polysaccharides was carried out using Box-Behnken statistical experimental design. Response surface methodology (RSM) of three factors (extraction temperature, extraction time and liquid solid ratio) was employed to optimize the percentage yield of the polysaccharides. The experimental data were fitted to quadratic response surface models using multiple regression analysis with high coefficient of determination value (R) of 0.9906. The highest polysaccharide yield (8.69%) as per the Derringer's desirability prediction tool was obtained under the optimal extraction condition (extraction temperature 47.03 °C, extraction time 15.68 min, and liquid solid ratio 1.29 ml/g) with a desirability value of 0.98. These optimized values of tested parameters were validated under similar conditions (n = 6), an average of 8.13 ± 2.08% of polysaccharide yield was obtained in an optimized extraction conditions with 93.55% validity. The anti-inflammatory effect of polysaccharides of P. emodi were studied on carrageenan induced paw edema. In vivo results showed that the P. emodi 200mg/kg of polysaccharide extract exhibited strong potential against inflammatory response induced by 1% suspension of carrageenean in normal saline. Copyright © 2014 Elsevier B.V. All rights reserved.

Optimization of process parameters in CNC turning of aluminium alloy using hybrid RSM cum TLBO approach

NASA Astrophysics Data System (ADS)

Rudrapati, R.; Sahoo, P.; Bandyopadhyay, A.

2016-09-01

The main aim of the present work is to analyse the significance of turning parameters on surface roughness in computer numerically controlled (CNC) turning operation while machining of aluminium alloy material. Spindle speed, feed rate and depth of cut have been considered as machining parameters. Experimental runs have been conducted as per Box-Behnken design method. After experimentation, surface roughness is measured by using stylus profile meter. Factor effects have been studied through analysis of variance. Mathematical modelling has been done by response surface methodology, to made relationships between the input parameters and output response. Finally, process optimization has been made by teaching learning based optimization (TLBO) algorithm. Predicted turning condition has been validated through confirmatory experiment.

[Experimental orthopedic surgery: the practical aspects and management].

PubMed

Di Denia, P; Caligiuri, G; Guzzardella, G A; Fini, M; Giardino, R

1996-01-01

The funds to grant for a scientific research project are more and more interesting public and private administrations. A quantitative analysis of experimental research prices in all its phases is mandatory for an optimization process. The aim of this paper is to define practical and economical aspects of the experimental 'in vivo' models designed for the validation of biomaterials, with particular respect to the managerial bookkeeping of consumer goods, based on the experience of our Institute. Some tables were realized in order to quantify the resources needed to perform experimental 'in vivo' models. These tables represent a reliable tool for a continuous monitoring of managerial costs for the current year and for an accurate budget planning for the future years considering the experimental projects in progress and the planned researches. A business organization of public research facilities may lead to an optimization of costs and an easier national and international funds achievement increasing, also, the partnership with private appointers.

Above-knee prosthesis design based on fatigue life using finite element method and design of experiment.

PubMed

Phanphet, Suwattanarwong; Dechjarern, Surangsee; Jomjanyong, Sermkiat

2017-05-01

The main objective of this work is to improve the standard of the existing design of knee prosthesis developed by Thailand's Prostheses Foundation of Her Royal Highness The Princess Mother. The experimental structural tests, based on the ISO 10328, of the existing design showed that a few components failed due to fatigue under normal cyclic loading below the required number of cycles. The finite element (FE) simulations of structural tests on the knee prosthesis were carried out. Fatigue life predictions of knee component materials were modeled based on the Morrow's approach. The fatigue life prediction based on the FE model result was validated with the corresponding structural test and the results agreed well. The new designs of the failed components were studied using the design of experimental approach and finite element analysis of the ISO 10328 structural test of knee prostheses under two separated loading cases. Under ultimate loading, knee prosthesis peak von Mises stress must be less than the yield strength of knee component's material and the total knee deflection must be lower than 2.5mm. The fatigue life prediction of all knee components must be higher than 3,000,000 cycles under normal cyclic loading. The design parameters are the thickness of joint bars, the diameter of lower connector and the thickness of absorber-stopper. The optimized knee prosthesis design meeting all the requirements was recommended. Experimental ISO 10328 structural test of the fabricated knee prosthesis based on the optimized design confirmed the finite element prediction. Copyright © 2017 IPEM. Published by Elsevier Ltd. All rights reserved.

Experimental designs for detecting synergy and antagonism between two drugs in a pre-clinical study.

PubMed

Sperrin, Matthew; Thygesen, Helene; Su, Ting-Li; Harbron, Chris; Whitehead, Anne

2015-01-01

The identification of synergistic interactions between combinations of drugs is an important area within drug discovery and development. Pre-clinically, large numbers of screening studies to identify synergistic pairs of compounds can often be ran, necessitating efficient and robust experimental designs. We consider experimental designs for detecting interaction between two drugs in a pre-clinical in vitro assay in the presence of uncertainty of the monotherapy response. The monotherapies are assumed to follow the Hill equation with common lower and upper asymptotes, and a common variance. The optimality criterion used is the variance of the interaction parameter. We focus on ray designs and investigate two algorithms for selecting the optimum set of dose combinations. The first is a forward algorithm in which design points are added sequentially. This is found to give useful solutions in simple cases but can lack robustness when knowledge about the monotherapy parameters is insufficient. The second algorithm is a more pragmatic approach where the design points are constrained to be distributed log-normally along the rays and monotherapy doses. We find that the pragmatic algorithm is more stable than the forward algorithm, and even when the forward algorithm has converged, the pragmatic algorithm can still out-perform it. Practically, we find that good designs for detecting an interaction have equal numbers of points on monotherapies and combination therapies, with those points typically placed in positions where a 50% response is expected. More uncertainty in monotherapy parameters leads to an optimal design with design points that are more spread out. Copyright © 2015 John Wiley & Sons, Ltd.

[Optimization of one-step pelletization technology of Biqiu granules by Plackett-Burman design and Box-Behnken response surface methodology].

PubMed

Zhang, Yan-jun; Liu, Li-li; Hu, Jun-hua; Wu, Yun; Chao, En-xiang; Xiao, Wei

2015-11-01

First with the qualified rate of granules as the evaluation index, significant influencing factors were firstly screened by Plackett-Burman design. Then, with the qualified rate and moisture content as the evaluation indexes, significant factors that affect one-step pelletization technology were further optimized by Box-Behnken design; experimental data were imitated by multiple regression and second-order polynomial equation; and response surface method was used for predictive analysis of optimal technology. The best conditions were as follows: inlet air temperature of 85 degrees C, sample introduction speed of 33 r x min(-1), density of concrete 1. 10. One-step pelletization technology of Biqiu granules by Plackett-Burman design and Box-Behnken response surface methodology was stable and feasible with good predictability, which provided reliable basis for the industrialized production of Biqiu granules.

Enriching peptide libraries for binding affinity and specificity through computationally directed library design

PubMed Central

Foight, Glenna Wink; Chen, T. Scott; Richman, Daniel; Keating, Amy E.

2017-01-01

Peptide reagents with high affinity or specificity for their target protein interaction partner are of utility for many important applications. Optimization of peptide binding by screening large libraries is a proven and powerful approach. Libraries designed to be enriched in peptide sequences that are predicted to have desired affinity or specificity characteristics are more likely to yield success than random mutagenesis. We present a library optimization method in which the choice of amino acids to encode at each peptide position can be guided by available experimental data or structure-based predictions. We discuss how to use analysis of predicted library performance to inform rounds of library design. Finally, we include protocols for more complex library design procedures that consider the chemical diversity of the amino acids at each peptide position and optimize a library score based on a user-specified input model. PMID:28236241

Enriching Peptide Libraries for Binding Affinity and Specificity Through Computationally Directed Library Design.

PubMed

Foight, Glenna Wink; Chen, T Scott; Richman, Daniel; Keating, Amy E

2017-01-01

Peptide reagents with high affinity or specificity for their target protein interaction partner are of utility for many important applications. Optimization of peptide binding by screening large libraries is a proven and powerful approach. Libraries designed to be enriched in peptide sequences that are predicted to have desired affinity or specificity characteristics are more likely to yield success than random mutagenesis. We present a library optimization method in which the choice of amino acids to encode at each peptide position can be guided by available experimental data or structure-based predictions. We discuss how to use analysis of predicted library performance to inform rounds of library design. Finally, we include protocols for more complex library design procedures that consider the chemical diversity of the amino acids at each peptide position and optimize a library score based on a user-specified input model.

Wet scrubbing of biomass producer gas tars using vegetable oil

NASA Astrophysics Data System (ADS)

Bhoi, Prakashbhai Ramabhai

The overall aims of this research study were to generate novel design data and to develop an equilibrium stage-based thermodynamic model of a vegetable oil based wet scrubbing system for the removal of model tar compounds (benzene, toluene and ethylbenzene) found in biomass producer gas. The specific objectives were to design, fabricate and evaluate a vegetable oil based wet scrubbing system and to optimize the design and operating variables; i.e., packed bed height, vegetable oil type, solvent temperature, and solvent flow rate. The experimental wet packed bed scrubbing system includes a liquid distributor specifically designed to distribute a high viscous vegetable oil uniformly and a mixing section, which was designed to generate a desired concentration of tar compounds in a simulated air stream. A method and calibration protocol of gas chromatography/mass spectroscopy was developed to quantify tar compounds. Experimental data were analyzed statistically using analysis of variance (ANOVA) procedure. Statistical analysis showed that both soybean and canola oils are potential solvents, providing comparable removal efficiency of tar compounds. The experimental height equivalent to a theoretical plate (HETP) was determined as 0.11 m for vegetable oil based scrubbing system. Packed bed height and solvent temperature had highly significant effect (p0.05) effect on the removal of model tar compounds. The packing specific constants, Ch and CP,0, for the Billet and Schultes pressure drop correlation were determined as 2.52 and 2.93, respectively. The equilibrium stage based thermodynamic model predicted the removal efficiency of model tar compounds in the range of 1-6%, 1-4% and 1-2% of experimental data for benzene, toluene and ethylbenzene, respectively, for the solvent temperature of 30° C. The NRTL-PR property model and UNIFAC for estimating binary interaction parameters are recommended for modeling absorption of tar compounds in vegetable oils. Bench scale experimental data from the wet scrubbing system would be useful in the design and operation of a pilot scale vegetable oil based system. The process model, validated using experimental data, would be a key design tool for the design and optimization of a pilot scale vegetable oil based system.

Design of a magnetic shielding system for the time of flight enhanced diagnostics neutron spectrometer at Experimental Advanced Superconducting Tokamak

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

Cui, Z. Q.; Chen, Z. J.; Xie, X. F.

2014-11-15

The novel neutron spectrometer TOFED (Time of Flight Enhanced Diagnostics), comprising 90 individual photomultiplier tubes coupled with 85 plastic scintillation detectors through light guides, has been constructed and installed at Experimental Advanced Superconducting Tokamak. A dedicated magnetic shielding system has been constructed for TOFED, and is designed to guarantee the normal operation of photomultiplier tubes in the stray magnetic field leaking from the tokamak device. Experimental measurements and numerical simulations carried out employing the finite element method are combined to optimize the design of the magnetic shielding system. The system allows detectors to work properly in an external magnetic fieldmore » of 200 G.« less

Optimal design of an electro-hydraulic valve for heavy-duty vehicle clutch actuator with certain constraints

NASA Astrophysics Data System (ADS)

Meng, Fei; Shi, Peng; Karimi, Hamid Reza; Zhang, Hui

2016-02-01

The main objective of this paper is to investigate the sensitivity analysis and optimal design of a proportional solenoid valve (PSV) operated pressure reducing valve (PRV) for heavy-duty automatic transmission clutch actuators. The nonlinear electro-hydraulic valve model is developed based on fluid dynamics. In order to implement the sensitivity analysis and optimization for the PRV, the PSV model is validated by comparing the results with data obtained from a real test-bench. The sensitivity of the PSV pressure response with regard to the structural parameters is investigated by using Sobol's method. Finally, simulations and experimental investigations are performed on the optimized prototype and the results reveal that the dynamical characteristics of the valve have been improved in comparison with the original valve.

Identification and statistical optimization of fermentation conditions for a newly isolated extracellular cholesterol oxidase-producing Streptomyces cavourensis strain NEAE-42.

PubMed

El-Naggar, Noura El-Ahmady; El-Shweihy, Nancy M; El-Ewasy, Sara M

2016-09-20

Due to broad range of clinical and industrial applications of cholesterol oxidase, isolation and screening of bacterial strains producing extracellular form of cholesterol oxidase is of great importance. One hundred and thirty actinomycete isolates were screened for their cholesterol oxidase activity. Among them, a potential culture, strain NEAE-42 is displayed the highest extracellular cholesterol oxidase activity. It was selected and identified as Streptomyces cavourensis strain NEAE-42. The optimization of different process parameters for cholesterol oxidase production by Streptomyces cavourensis strain NEAE-42 using Plackett-Burman experimental design and response surface methodology was carried out. Fifteen variables were screened using Plackett-Burman experimental design. Cholesterol, initial pH and (NH4)2SO4 were the most significant positive independent variables affecting cholesterol oxidase production. Central composite design was chosen to elucidate the optimal concentrations of the selected process variables on cholesterol oxidase production. It was found that, cholesterol oxidase production by Streptomyces cavourensis strain NEAE-42 after optimization process was 20.521U/mL which is higher than result obtained from the basal medium before screening process using Plackett-Burman (3.31 U/mL) with a fold of increase 6.19. The cholesterol oxidase level production obtained in this study (20.521U/mL) by the statistical method is higher than many of the reported values.

Demonstration of differential phase-shift keying demodulation at 10 Gbit/s optimal fiber Bragg grating filters.

PubMed

Gatti, Davide; Galzerano, Gianluca; Laporta, Paolo; Longhi, Stefano; Janner, Davide; Guglierame, Andrea; Belmonte, Michele

2008-07-01

Optimal demodulation of differential phase-shift keying signals at 10 Gbit/s is experimentally demonstrated using a specially designed structured fiber Bragg grating composed by Fabry-Perot coupled cavities. Bit-error-rate measurements show that, as compared with a conventional Gaussian-shaped filter, our demodulator gives approximately 2.8 dB performance improvement.

On the suitability of different representations of solid catalysts for combinatorial library design by genetic algorithms.

PubMed

Gobin, Oliver C; Schüth, Ferdi

2008-01-01

Genetic algorithms are widely used to solve and optimize combinatorial problems and are more often applied for library design in combinatorial chemistry. Because of their flexibility, however, their implementation can be challenging. In this study, the influence of the representation of solid catalysts on the performance of genetic algorithms was systematically investigated on the basis of a new, constrained, multiobjective, combinatorial test problem with properties common to problems in combinatorial materials science. Constraints were satisfied by penalty functions, repair algorithms, or special representations. The tests were performed using three state-of-the-art evolutionary multiobjective algorithms by performing 100 optimization runs for each algorithm and test case. Experimental data obtained during the optimization of a noble metal-free solid catalyst system active in the selective catalytic reduction of nitric oxide with propene was used to build up a predictive model to validate the results of the theoretical test problem. A significant influence of the representation on the optimization performance was observed. Binary encodings were found to be the preferred encoding in most of the cases, and depending on the experimental test unit, repair algorithms or penalty functions performed best.

Optimization of the preparation conditions of ceramic products using drinking water treatment sludges.

PubMed

Zamora, R M Ramirez; Ayala, F Espesel; Garcia, L Chavez; Moreno, A Duran; Schouwenaars, R

2008-11-01

The aim of this work is to optimize, via Response Surface Methodology, the values of the main process parameters for the production of ceramic products using sludges obtained from drinking water treatment in order to valorise them. In the first experimental stage, sludges were collected from a drinking water treatment plant for characterization. In the second stage, trials were carried out to elaborate thin cross-section specimens and fired bricks following an orthogonal central composite design of experiments with three factors (sludge composition, grain size and firing temperature) and five levels. The optimization parameters (Y(1)=shrinking by firing (%), Y(2)=water absorption (%), Y(3)=density (g/cm(3)) and Y(4)=compressive strength (kg/cm(2))) were determined according to standardized analytical methods. Two distinct physicochemical processes were active during firing at different conditions in the experimental design, preventing the determination of a full response surface, which would allow direct optimization of production parameters. Nevertheless, the temperature range for the production of classical red brick was closely delimitated by the results; above this temperature, a lightweight ceramic with surprisingly high strength was produced, opening possibilities for the valorisation of a product with considerably higher added value than what was originally envisioned.

Optimal Wonderful Life Utility Functions in Multi-Agent Systems

NASA Technical Reports Server (NTRS)

Wolpert, David H.; Tumer, Kagan; Swanson, Keith (Technical Monitor)

2000-01-01

The mathematics of Collective Intelligence (COINs) is concerned with the design of multi-agent systems so as to optimize an overall global utility function when those systems lack centralized communication and control. Typically in COINs each agent runs a distinct Reinforcement Learning (RL) algorithm, so that much of the design problem reduces to how best to initialize/update each agent's private utility function, as far as the ensuing value of the global utility is concerned. Traditional team game solutions to this problem assign to each agent the global utility as its private utility function. In previous work we used the COIN framework to derive the alternative Wonderful Life Utility (WLU), and experimentally established that having the agents use it induces global utility performance up to orders of magnitude superior to that induced by use of the team game utility. The WLU has a free parameter (the clamping parameter) which we simply set to zero in that previous work. Here we derive the optimal value of the clamping parameter, and demonstrate experimentally that using that optimal value can result in significantly improved performance over that of clamping to zero, over and above the improvement beyond traditional approaches.

A review on experimental design for pollutants removal in water treatment with the aid of artificial intelligence.

PubMed

Fan, Mingyi; Hu, Jiwei; Cao, Rensheng; Ruan, Wenqian; Wei, Xionghui

2018-06-01

Water pollution occurs mainly due to inorganic and organic pollutants, such as nutrients, heavy metals and persistent organic pollutants. For the modeling and optimization of pollutants removal, artificial intelligence (AI) has been used as a major tool in the experimental design that can generate the optimal operational variables, since AI has recently gained a tremendous advance. The present review describes the fundamentals, advantages and limitations of AI tools. Artificial neural networks (ANNs) are the AI tools frequently adopted to predict the pollutants removal processes because of their capabilities of self-learning and self-adapting, while genetic algorithm (GA) and particle swarm optimization (PSO) are also useful AI methodologies in efficient search for the global optima. This article summarizes the modeling and optimization of pollutants removal processes in water treatment by using multilayer perception, fuzzy neural, radial basis function and self-organizing map networks. Furthermore, the results conclude that the hybrid models of ANNs with GA and PSO can be successfully applied in water treatment with satisfactory accuracies. Finally, the limitations of current AI tools and their new developments are also highlighted for prospective applications in the environmental protection. Copyright © 2018 Elsevier Ltd. All rights reserved.

Is the linear modeling technique good enough for optimal form design? A comparison of quantitative analysis models.

PubMed

Lin, Yang-Cheng; Yeh, Chung-Hsing; Wang, Chen-Cheng; Wei, Chun-Chun

2012-01-01

How to design highly reputable and hot-selling products is an essential issue in product design. Whether consumers choose a product depends largely on their perception of the product image. A consumer-oriented design approach presented in this paper helps product designers incorporate consumers' perceptions of product forms in the design process. The consumer-oriented design approach uses quantification theory type I, grey prediction (the linear modeling technique), and neural networks (the nonlinear modeling technique) to determine the optimal form combination of product design for matching a given product image. An experimental study based on the concept of Kansei Engineering is conducted to collect numerical data for examining the relationship between consumers' perception of product image and product form elements of personal digital assistants (PDAs). The result of performance comparison shows that the QTTI model is good enough to help product designers determine the optimal form combination of product design. Although the PDA form design is used as a case study, the approach is applicable to other consumer products with various design elements and product images. The approach provides an effective mechanism for facilitating the consumer-oriented product design process.

Is the Linear Modeling Technique Good Enough for Optimal Form Design? A Comparison of Quantitative Analysis Models

PubMed Central

Lin, Yang-Cheng; Yeh, Chung-Hsing; Wang, Chen-Cheng; Wei, Chun-Chun

2012-01-01

How to design highly reputable and hot-selling products is an essential issue in product design. Whether consumers choose a product depends largely on their perception of the product image. A consumer-oriented design approach presented in this paper helps product designers incorporate consumers' perceptions of product forms in the design process. The consumer-oriented design approach uses quantification theory type I, grey prediction (the linear modeling technique), and neural networks (the nonlinear modeling technique) to determine the optimal form combination of product design for matching a given product image. An experimental study based on the concept of Kansei Engineering is conducted to collect numerical data for examining the relationship between consumers' perception of product image and product form elements of personal digital assistants (PDAs). The result of performance comparison shows that the QTTI model is good enough to help product designers determine the optimal form combination of product design. Although the PDA form design is used as a case study, the approach is applicable to other consumer products with various design elements and product images. The approach provides an effective mechanism for facilitating the consumer-oriented product design process. PMID:23258961

Simulation in production of open rotor propellers: from optimal surface geometry to automated control of mechanical treatment

NASA Astrophysics Data System (ADS)

Grinyok, A.; Boychuk, I.; Perelygin, D.; Dantsevich, I.

2018-03-01

A complex method of the simulation and production design of open rotor propellers was studied. An end-to-end diagram was proposed for the evaluating, designing and experimental testing the optimal geometry of the propeller surface, for the machine control path generation as well as for simulating the cutting zone force condition and its relationship with the treatment accuracy which was defined by the propeller elastic deformation. The simulation data provided the realization of the combined automated path control of the cutting tool.

Initial state-specific photodissociation dynamics of pyrrole via 1 π σ ∗/ S 0 conical intersection initiated with optimally controlled UV-laser pulses

NASA Astrophysics Data System (ADS)

Nandipati, K. R.; Kanakati, Arun Kumar; Singh, H.; Lan, Z.; Mahapatra, S.

2017-09-01

Optimal initiation of quantum dynamics of N-H photodissociation of pyrrole on the S0-1πσ∗(1A2) coupled electronic states by UV-laser pulses in an effort to guide the subsequent dynamics to dissociation limits is studied theoretically. Specifically, the task of designing optimal laser pulses that act on initial vibrational states of the system for an effective UV-photodissociation is considered by employing optimal control theory. The associated control mechanism(s) for the initial state dependent photodissociation dynamics of pyrrole in the presence of control pulses is examined and discussed in detail. The initial conditions determine implicitly the variation in the dissociation probabilities for the two channels, upon interaction with the field. The optimal pulse corresponds to the objective fixed as maximization of overall reactive flux subject to constraints of reasonable fluence and quantum dynamics. The simple optimal pulses obtained by the use of genetic algorithm based optimization are worth an experimental implementation given the experimental relevance of πσ∗-photochemistry in recent times.

Two-dimensional designed fabrication of subwavelength grating HCG mirror on silicon-on-insulator

NASA Astrophysics Data System (ADS)

Huang, Shen-Che; Hong, Kuo-Bin; Lu, Tien-Chang; He, Sailing

2016-03-01

We designed and fabricated a two dimensional high contrast subwavelength grating (HCG) mirrors. The computer-aided software was employed to verify the structural parameters including grating periods and filling factors. From the optimized simulation results, the designed HCG structure has a wide reflection stopband (reflectivity (R) >90%) of over 200 nm, which centered at telecommunication wavelength. The optimized HCG mirrors were fabricated by electron beam lithography and inductively coupled plasma process technique. The experimental result was almost consistent with calculated data. This achievement should have an impact on numerous photonic devices helpful attribution to the integrated HCG VCSELs in the future.

On the physical operation and optimization of the p-GaN gate in normally-off GaN HEMT devices

NASA Astrophysics Data System (ADS)

Efthymiou, L.; Longobardi, G.; Camuso, G.; Chien, T.; Chen, M.; Udrea, F.

2017-03-01

In this study, an investigation is undertaken to determine the effect of gate design parameters on the on-state characteristics (threshold voltage and gate turn-on voltage) of pGaN/AlGaN/GaN high electron mobility transistors (HEMTs). Design parameters considered are pGaN doping and gate metal work function. The analysis considers the effects of variations on these parameters using a TCAD model matched with experimental results. A better understanding of the underlying physics governing the operation of these devices is achieved with a view to enable better optimization of such gate designs.

Design, Kinematic Optimization, and Evaluation of a Teleoperated System for Middle Ear Microsurgery

PubMed Central

Miroir, Mathieu; Nguyen, Yann; Szewczyk, Jérôme; Sterkers, Olivier; Bozorg Grayeli, Alexis

2012-01-01

Middle ear surgery involves the smallest and the most fragile bones of the human body. Since microsurgical gestures and a submillimetric precision are required in these procedures, the outcome can be potentially improved by robotic assistance. Today, there is no commercially available device in this field. Here, we describe a method to design a teleoperated assistance robotic system dedicated to the middle ear surgery. Determination of design specifications, the kinematic structure, and its optimization are detailed. The robot-surgeon interface and the command modes are provided. Finally, the system is evaluated by realistic tasks in experimental dedicated settings and in human temporal bone specimens. PMID:22927789

Shape optimization techniques for musical instrument design

NASA Astrophysics Data System (ADS)

Henrique, Luis; Antunes, Jose; Carvalho, Joao S.

2002-11-01

The design of musical instruments is still mostly based on empirical knowledge and costly experimentation. One interesting improvement is the shape optimization of resonating components, given a number of constraints (allowed parameter ranges, shape smoothness, etc.), so that vibrations occur at specified modal frequencies. Each admissible geometrical configuration generates an error between computed eigenfrequencies and the target set. Typically, error surfaces present many local minima, corresponding to suboptimal designs. This difficulty can be overcome using global optimization techniques, such as simulated annealing. However these methods are greedy, concerning the number of function evaluations required. Thus, the computational effort can be unacceptable if complex problems, such as bell optimization, are tackled. Those issues are addressed in this paper, and a method for improving optimization procedures is proposed. Instead of using the local geometric parameters as searched variables, the system geometry is modeled in terms of truncated series of orthogonal space-funcitons, and optimization is performed on their amplitude coefficients. Fourier series and orthogonal polynomials are typical such functions. This technique reduces considerably the number of searched variables, and has a potential for significant computational savings in complex problems. It is illustrated by optimizing the shapes of both current and uncommon marimba bars.

Optimization of prosthetic foot stiffness to reduce metabolic cost and intact knee loading during below-knee amputee walking: a theoretical study.

PubMed

Fey, Nicholas P; Klute, Glenn K; Neptune, Richard R

2012-11-01

Unilateral below-knee amputees develop abnormal gait characteristics that include bilateral asymmetries and an elevated metabolic cost relative to non-amputees. In addition, long-term prosthesis use has been linked to an increased prevalence of joint pain and osteoarthritis in the intact leg knee. To improve amputee mobility, prosthetic feet that utilize elastic energy storage and return (ESAR) have been designed, which perform important biomechanical functions such as providing body support and forward propulsion. However, the prescription of appropriate design characteristics (e.g., stiffness) is not well-defined since its influence on foot function and important in vivo biomechanical quantities such as metabolic cost and joint loading remain unclear. The design of feet that improve these quantities could provide considerable advancements in amputee care. Therefore, the purpose of this study was to couple design optimization with dynamic simulations of amputee walking to identify the optimal foot stiffness that minimizes metabolic cost and intact knee joint loading. A musculoskeletal model and distributed stiffness ESAR prosthetic foot model were developed to generate muscle-actuated forward dynamics simulations of amputee walking. Dynamic optimization was used to solve for the optimal muscle excitation patterns and foot stiffness profile that produced simulations that tracked experimental amputee walking data while minimizing metabolic cost and intact leg internal knee contact forces. Muscle and foot function were evaluated by calculating their contributions to the important walking subtasks of body support, forward propulsion and leg swing. The analyses showed that altering a nominal prosthetic foot stiffness distribution by stiffening the toe and mid-foot while making the ankle and heel less stiff improved ESAR foot performance by offloading the intact knee during early to mid-stance of the intact leg and reducing metabolic cost. The optimal design also provided moderate braking and body support during the first half of residual leg stance, while increasing the prosthesis contributions to forward propulsion and body support during the second half of residual leg stance. Future work will be directed at experimentally validating these results, which have important implications for future designs of prosthetic feet that could significantly improve amputee care.

Design and implementation of fuzzy-PD controller based on relation models: A cross-entropy optimization approach

NASA Astrophysics Data System (ADS)

Anisimov, D. N.; Dang, Thai Son; Banerjee, Santo; Mai, The Anh

2017-07-01

In this paper, an intelligent system use fuzzy-PD controller based on relation models is developed for a two-wheeled self-balancing robot. Scaling factors of the fuzzy-PD controller are optimized by a Cross-Entropy optimization method. A linear Quadratic Regulator is designed to bring a comparison with the fuzzy-PD controller by control quality parameters. The controllers are ported and run on STM32F4 Discovery Kit based on the real-time operating system. The experimental results indicate that the proposed fuzzy-PD controller runs exactly on embedded system and has desired performance in term of fast response, good balance and stabilize.

A minimalistic and optimized conveyor belt for neutral atoms.

PubMed

Roy, Ritayan; Condylis, Paul C; Prakash, Vindhiya; Sahagun, Daniel; Hessmo, Björn

2017-10-20

Here we report of a design and the performance of an optimized micro-fabricated conveyor belt for precise and adiabatic transportation of cold atoms. A theoretical model is presented to determine optimal currents in conductors used for the transportation. We experimentally demonstrate a fast adiabatic transportation of Rubidium ( 87 Rb) cold atoms with minimal loss and heating with as few as three conveyor belt conductors. This novel design of a multilayered conveyor belt structure is fabricated in aluminium nitride (AlN) because of its outstanding thermal and electrical properties. This demonstration would pave a way for a compact and portable quantum device required for quantum information processing and sensors, where precise positioning of cold atoms is desirable.

Illumination system development using design and analysis of computer experiments

NASA Astrophysics Data System (ADS)

Keresztes, Janos C.; De Ketelaere, Bart; Audenaert, Jan; Koshel, R. J.; Saeys, Wouter

2015-09-01

Computer assisted optimal illumination design is crucial when developing cost-effective machine vision systems. Standard local optimization methods, such as downhill simplex optimization (DHSO), often result in an optimal solution that is influenced by the starting point by converging to a local minimum, especially when dealing with high dimensional illumination designs or nonlinear merit spaces. This work presents a novel nonlinear optimization approach, based on design and analysis of computer experiments (DACE). The methodology is first illustrated with a 2D case study of four light sources symmetrically positioned along a fixed arc in order to obtain optimal irradiance uniformity on a flat Lambertian reflecting target at the arc center. The first step consists of choosing angular positions with no overlap between sources using a fast, flexible space filling design. Ray-tracing simulations are then performed at the design points and a merit function is used for each configuration to quantify the homogeneity of the irradiance at the target. The obtained homogeneities at the design points are further used as input to a Gaussian Process (GP), which develops a preliminary distribution for the expected merit space. Global optimization is then performed on the GP more likely providing optimal parameters. Next, the light positioning case study is further investigated by varying the radius of the arc, and by adding two spots symmetrically positioned along an arc diametrically opposed to the first one. The added value of using DACE with regard to the performance in convergence is 6 times faster than the standard simplex method for equal uniformity of 97%. The obtained results were successfully validated experimentally using a short-wavelength infrared (SWIR) hyperspectral imager monitoring a Spectralon panel illuminated by tungsten halogen sources with 10% of relative error.

Increasing Optimism Protects Against Pain-Induced Impairment in Task-Shifting Performance.

PubMed

Boselie, Jantine J L M; Vancleef, Linda M G; Peters, Madelon L

2017-04-01

Persistent pain can lead to difficulties in executive task performance. Three core executive functions that are often postulated are inhibition, updating, and shifting. Optimism, the tendency to expect that good things happen in the future, has been shown to protect against pain-induced performance deterioration in executive function updating. This study tested whether this protective effect of a temporary optimistic state by means of a writing and visualization exercise extended to executive function shifting. A 2 (optimism: optimism vs no optimism) × 2 (pain: pain vs no pain) mixed factorial design was conducted. Participants (N = 61) completed a shifting task once with and once without concurrent painful heat stimulation after an optimism or neutral manipulation. Results showed that shifting performance was impaired when experimental heat pain was applied during task execution, and that optimism counteracted pain-induced deterioration in task-shifting performance. Experimentally-induced heat pain impairs shifting task performance and manipulated optimism or induced optimism counteracted this pain-induced performance deterioration. Identifying psychological factors that may diminish the negative effect of persistent pain on the ability to function in daily life is imperative. Copyright © 2016 American Pain Society. Published by Elsevier Inc. All rights reserved.

Southern Regional Center for Lightweight Innovative Design

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

Wang, Paul T.

The Southern Regional Center for Lightweight Innovative Design (SRCLID) has developed an experimentally validated cradle-to-grave modeling and simulation effort to optimize automotive components in order to decrease weight and cost, yet increase performance and safety in crash scenarios. In summary, the three major objectives of this project are accomplished: To develop experimentally validated cradle-to-grave modeling and simulation tools to optimize automotive and truck components for lightweighting materials (aluminum, steel, and Mg alloys and polymer-based composites) with consideration of uncertainty to decrease weight and cost, yet increase the performance and safety in impact scenarios; To develop multiscale computational models that quantifymore » microstructure-property relations by evaluating various length scales, from the atomic through component levels, for each step of the manufacturing process for vehicles; and To develop an integrated K-12 educational program to educate students on lightweighting designs and impact scenarios. In this final report, we divided the content into two parts: the first part contains the development of building blocks for the project, including materials and process models, process-structure-property (PSP) relationship, and experimental validation capabilities; the second part presents the demonstration task for Mg front-end work associated with USAMP projects.« less

Designing electronic properties of two-dimensional crystals through optimization of deformations

NASA Astrophysics Data System (ADS)

Jones, Gareth W.; Pereira, Vitor M.

2014-09-01

One of the enticing features common to most of the two-dimensional (2D) electronic systems that, in the wake of (and in parallel with) graphene, are currently at the forefront of materials science research is the ability to easily introduce a combination of planar deformations and bending in the system. Since the electronic properties are ultimately determined by the details of atomic orbital overlap, such mechanical manipulations translate into modified (or, at least, perturbed) electronic properties. Here, we present a general-purpose optimization framework for tailoring physical properties of 2D electronic systems by manipulating the state of local strain, allowing a one-step route from their design to experimental implementation. A definite example, chosen for its relevance in light of current experiments in graphene nanostructures, is the optimization of the experimental parameters that generate a prescribed spatial profile of pseudomagnetic fields (PMFs) in graphene. But the method is general enough to accommodate a multitude of possible experimental parameters and conditions whereby deformations can be imparted to the graphene lattice, and complies, by design, with graphene's elastic equilibrium and elastic compatibility constraints. As a result, it efficiently answers the inverse problem of determining the optimal values of a set of external or control parameters (such as substrate topography, sample shape, load distribution, etc) that result in a graphene deformation whose associated PMF profile best matches a prescribed target. The ability to address this inverse problem in an expedited way is one key step for practical implementations of the concept of 2D systems with electronic properties strain-engineered to order. The general-purpose nature of this calculation strategy means that it can be easily applied to the optimization of other relevant physical quantities which directly depend on the local strain field, not just in graphene but in other 2D electronic membranes.

Design, analysis, and testing of a flexure-based vibration-assisted polishing device

NASA Astrophysics Data System (ADS)

Gu, Yan; Zhou, Yan; Lin, Jieqiong; Lu, Mingming; Zhang, Chenglong; Chen, Xiuyuan

2018-05-01

A vibration-assisted polishing device (VAPD) composed of leaf-spring and right-circular flexure hinges is proposed with the aim of realizing vibration-assisted machining along elliptical trajectories. To design the structure, energy methods and the finite-element method are used to calculate the performance of the proposed VAPD. An improved bacterial foraging optimization algorithm is used to optimize the structural parameters. In addition, the performance of the VAPD is tested experimentally. The experimental results indicate that the maximum strokes of the two directional mechanisms operating along the Z1 and Z2 directions are 29.5 μm and 29.3 μm, respectively, and the maximum motion resolutions are 10.05 nm and 10.01 nm, respectively. The maximum working bandwidth is 1,879 Hz, and the device has a good step response.

Thermophotovoltaic space power system, phase 3

NASA Technical Reports Server (NTRS)

Horne, W. E.; Lancaster, C.

1987-01-01

Work performed on a research and development program to establish the feasibility of a solar thermophotovoltaic space power generation concept was summarized. The program was multiphased. The earlier work is summarized and the work on the current phase is detailed as it pertains to and extends the earlier work. Much of the experimental hardware and materials development was performed on the internal program. Experimental measurements and data evaluation were performed on the contracted effort. The objectives of the most recent phase were: to examine the thermal control design in order to optimize it for lightweight and low cost; to examine the concentrator optics in an attempt to relieve pointing accuracy requirements to + or - 2 degrees about the optical axis; and to use the results of the thermal and optical studies to synthesize a solar thermophotovoltaic (STPV) module design that is optimized for space application.

Online optimal experimental re-design in robotic parallel fed-batch cultivation facilities.

PubMed

Cruz Bournazou, M N; Barz, T; Nickel, D B; Lopez Cárdenas, D C; Glauche, F; Knepper, A; Neubauer, P

2017-03-01

We present an integrated framework for the online optimal experimental re-design applied to parallel nonlinear dynamic processes that aims to precisely estimate the parameter set of macro kinetic growth models with minimal experimental effort. This provides a systematic solution for rapid validation of a specific model to new strains, mutants, or products. In biosciences, this is especially important as model identification is a long and laborious process which is continuing to limit the use of mathematical modeling in this field. The strength of this approach is demonstrated by fitting a macro-kinetic differential equation model for Escherichia coli fed-batch processes after 6 h of cultivation. The system includes two fully-automated liquid handling robots; one containing eight mini-bioreactors and another used for automated at-line analyses, which allows for the immediate use of the available data in the modeling environment. As a result, the experiment can be continually re-designed while the cultivations are running using the information generated by periodical parameter estimations. The advantages of an online re-computation of the optimal experiment are proven by a 50-fold lower average coefficient of variation on the parameter estimates compared to the sequential method (4.83% instead of 235.86%). The success obtained in such a complex system is a further step towards a more efficient computer aided bioprocess development. Biotechnol. Bioeng. 2017;114: 610-619. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Fragment informatics and computational fragment-based drug design: an overview and update.

PubMed

Sheng, Chunquan; Zhang, Wannian

2013-05-01

Fragment-based drug design (FBDD) is a promising approach for the discovery and optimization of lead compounds. Despite its successes, FBDD also faces some internal limitations and challenges. FBDD requires a high quality of target protein and good solubility of fragments. Biophysical techniques for fragment screening necessitate expensive detection equipment and the strategies for evolving fragment hits to leads remain to be improved. Regardless, FBDD is necessary for investigating larger chemical space and can be applied to challenging biological targets. In this scenario, cheminformatics and computational chemistry can be used as alternative approaches that can significantly improve the efficiency and success rate of lead discovery and optimization. Cheminformatics and computational tools assist FBDD in a very flexible manner. Computational FBDD can be used independently or in parallel with experimental FBDD for efficiently generating and optimizing leads. Computational FBDD can also be integrated into each step of experimental FBDD and help to play a synergistic role by maximizing its performance. This review will provide critical analysis of the complementarity between computational and experimental FBDD and highlight recent advances in new algorithms and successful examples of their applications. In particular, fragment-based cheminformatics tools, high-throughput fragment docking, and fragment-based de novo drug design will provide the focus of this review. We will also discuss the advantages and limitations of different methods and the trends in new developments that should inspire future research. © 2012 Wiley Periodicals, Inc.

Optimization of scaffold design for bone tissue engineering: A computational and experimental study.

PubMed

Dias, Marta R; Guedes, José M; Flanagan, Colleen L; Hollister, Scott J; Fernandes, Paulo R

2014-04-01

In bone tissue engineering, the scaffold has not only to allow the diffusion of cells, nutrients and oxygen but also provide adequate mechanical support. One way to ensure the scaffold has the right properties is to use computational tools to design such a scaffold coupled with additive manufacturing to build the scaffolds to the resulting optimized design specifications. In this study a topology optimization algorithm is proposed as a technique to design scaffolds that meet specific requirements for mass transport and mechanical load bearing. Several micro-structures obtained computationally are presented. Designed scaffolds were then built using selective laser sintering and the actual features of the fabricated scaffolds were measured and compared to the designed values. It was possible to obtain scaffolds with an internal geometry that reasonably matched the computational design (within 14% of porosity target, 40% for strut size and 55% for throat size in the building direction and 15% for strut size and 17% for throat size perpendicular to the building direction). These results support the use of these kind of computational algorithms to design optimized scaffolds with specific target properties and confirm the value of these techniques for bone tissue engineering. Copyright © 2014 IPEM. Published by Elsevier Ltd. All rights reserved.

An equivalent method for optimization of particle tuned mass damper based on experimental parametric study

NASA Astrophysics Data System (ADS)

Lu, Zheng; Chen, Xiaoyi; Zhou, Ying

2018-04-01

A particle tuned mass damper (PTMD) is a creative combination of a widely used tuned mass damper (TMD) and an efficient particle damper (PD) in the vibration control area. The performance of a one-storey steel frame attached with a PTMD is investigated through free vibration and shaking table tests. The influence of some key parameters (filling ratio of particles, auxiliary mass ratio, and particle density) on the vibration control effects is investigated, and it is shown that the attenuation level significantly depends on the filling ratio of particles. According to the experimental parametric study, some guidelines for optimization of the PTMD that mainly consider the filling ratio are proposed. Furthermore, an approximate analytical solution based on the concept of an equivalent single-particle damper is proposed, and it shows satisfied agreement between the simulation and experimental results. This simplified method is then used for the preliminary optimal design of a PTMD system, and a case study of a PTMD system attached to a five-storey steel structure following this optimization process is presented.

Tree crickets optimize the acoustics of baffles to exaggerate their mate-attraction signal.

PubMed

Mhatre, Natasha; Malkin, Robert; Deb, Rittik; Balakrishnan, Rohini; Robert, Daniel

2017-12-11

Object manufacture in insects is typically inherited, and believed to be highly stereotyped. Optimization, the ability to select the functionally best material and modify it appropriately for a specific function, implies flexibility and is usually thought to be incompatible with inherited behaviour. Here, we show that tree-crickets optimize acoustic baffles, objects that are used to increase the effective loudness of mate-attraction calls. We quantified the acoustic efficiency of all baffles within the naturally feasible design space using finite-element modelling and found that design affects efficiency significantly. We tested the baffle-making behaviour of tree crickets in a series of experimental contexts. We found that given the opportunity, tree crickets optimised baffle acoustics; they selected the best sized object and modified it appropriately to make a near optimal baffle. Surprisingly, optimization could be achieved in a single attempt, and is likely to be achieved through an inherited yet highly accurate behavioural heuristic.

Therapeutic Vascular Targeting and Irradiation: Correlation of MRI Tissue Changes at Cellular and Molecular Levels to Optimizing Outcome

DTIC Science & Technology

2008-06-01

cascade of tumor cell death in experimental tumors (4-6). However, survived tissues in a thin viable rim of tumor usually re-grow in spite of...changes monitored by MRI, optimum scheme of the combined radiation and CA4P will be designed and experimental treatment will be performed on the...CD31 Overlap Figure 4 CD 10 Task 2. Experimental tumor therapy

Limit of detection of 15{sub N} by gas-chromatography atomic emission detection: Optimization using an experimental design

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

Deruaz, D.; Bannier, A.; Pionchon, C.

1995-08-01

This paper deals with the optimal conditions for the detection of {sup 15}N determined using a four-factor experimental design from [2{sup 13}C,-1,3 {sup 15}N] caffeine measured with an atomic emission detector (AED) coupled to gas chromatography (GC). Owing to the capability of a photodiodes array, AED can simultaneously detect several elements using their specific emission lines within a wavelength range of 50 nm. So, the emissions of {sup 15}N and {sup 14}N are simultaneously detected at 420.17 nm and 421.46 nm respectively. Four independent experimental factors were tested (1) helium flow rate (plasma gas); (2) methane pressure (reactant gas); (3)more » oxygen pressure; (4) hydrogen pressure. It has been shown that these four gases had a significant influence on the analytical response of {sup 15}N. The linearity of the detection was determined using {sup 15}N amounts ranging from 1.52 pg to 19 ng under the optimal conditions obtained from the experimental design. The limit of detection was studied using different methods. The limits of detection of {sup 15}N was 1.9 pg/s according to the IUPAC method (International-Union of Pure and Applied Chemistry). The method proposed by Quimby and Sullivan gave a value of 2.3 pg/s and that of Oppenheimer gave a limit of 29 pg/s. For each determination, and internal standard: 1-isobutyl-3.7 dimethylxanthine was used. The results clearly demonstrate that GC AED is sensitive and selective enough to detect and measure {sup 15}N-labelled molecules after gas chromatographic separation.« less

Flow range enhancement by secondary flow effect in low solidity circular cascade diffusers

NASA Astrophysics Data System (ADS)

Sakaguchi, Daisaku; Tun, Min Thaw; Mizokoshi, Kanata; Kishikawa, Daiki

2014-08-01

High-pressure ratio and wide operating range are highly required for compressors and blowers. The technical issue of the design is achievement of suppression of flow separation at small flow rate without deteriorating the efficiency at design flow rate. A numerical simulation is very effective in design procedure, however, cost of the numerical simulation is generally high during the practical design process, and it is difficult to confirm the optimal design which is combined with many parameters. A multi-objective optimization technique is the idea that has been proposed for solving the problem in practical design process. In this study, a Low Solidity circular cascade Diffuser (LSD) in a centrifugal blower is successfully designed by means of multi-objective optimization technique. An optimization code with a meta-model assisted evolutionary algorithm is used with a commercial CFD code ANSYS-CFX. The optimization is aiming at improving the static pressure coefficient at design point and at low flow rate condition while constraining the slope of the lift coefficient curve. Moreover, a small tip clearance of the LSD blade was applied in order to activate and to stabilize the secondary flow effect at small flow rate condition. The optimized LSD blade has an extended operating range of 114 % towards smaller flow rate as compared to the baseline design without deteriorating the diffuser pressure recovery at design point. The diffuser pressure rise and operating flow range of the optimized LSD blade are experimentally verified by overall performance test. The detailed flow in the diffuser is also confirmed by means of a Particle Image Velocimeter. Secondary flow is clearly captured by PIV and it spreads to the whole area of LSD blade pitch. It is found that the optimized LSD blade shows good improvement of the blade loading in the whole operating range, while at small flow rate the flow separation on the LSD blade has been successfully suppressed by the secondary flow effect.

Optimization of MLS receivers for multipath environments

NASA Technical Reports Server (NTRS)

Mcalpine, G. A.; Highfill, J. H., III

1979-01-01

The angle tracking problems in microwave landing system receivers along with a receiver design capable of optimal performance in the multipath environments found in air terminal areas were studied. Included were various theoretical and evaluative studies like: (1) signal model development; (2) derivation of optimal receiver structures; and (3) development and use of computer simulations for receiver algorithm evaluation. The development of an experimental receiver for flight testing is presented. An overview of the work and summary of principal results and conclusions are reported.

Analysis and design of a capsule landing system and surface vehicle control system for Mars exporation

NASA Technical Reports Server (NTRS)

Frederick, D. K.; Lashmet, P. K.; Sandor, G. N.; Shen, C. N.; Smith, E. J.; Yerazunis, S. W.

1972-01-01

The problems related to the design and control of a mobile planetary vehicle to implement a systematic plan for the exploration of Mars were investigated. Problem areas receiving attention include: vehicle configuration, control, dynamics, systems and propulsion; systems analysis; navigation, terrain modeling and path selection; and chemical analysis of specimens. The following specific tasks were studied: vehicle model design, mathematical modeling of dynamic vehicle, experimental vehicle dynamics, obstacle negotiation, electromechanical controls, collapsibility and deployment, construction of a wheel tester, wheel analysis, payload design, system design optimization, effect of design assumptions, accessory optimal design, on-board computer subsystem, laser range measurement, discrete obstacle detection, obstacle detection systems, terrain modeling, path selection system simulation and evaluation, gas chromatograph/mass spectrometer system concepts, chromatograph model evaluation and improvement and transport parameter evaluation.

Analysis and design of a capsule landing system and surface vehicle control system for Mars exploration

NASA Technical Reports Server (NTRS)

Frederick, D. K.; Lashmet, P. K.; Sandor, G. N.; Shen, C. N.; Smith, E. J.; Yerazunis, S. W.

1972-01-01

Investigation of problems related to the design and control of a mobile planetary vehicle to implement a systematic plan for the exploration of Mars has been undertaken. Problem areas receiving attention include: vehicle configuration, control, dynamics, systems and propulsion; systems analysis; terrain modeling and path selection; and chemical analysis of specimens. The following specific tasks have been under study: vehicle model design, mathematical modeling of a dynamic vehicle, experimental vehicle dynamics, obstacle negotiation, electromechanical controls, collapsibility and deployment, construction of a wheel tester, wheel analysis, payload design, system design optimization, effect of design assumptions, accessory optimal design, on-board computer sybsystem, laser range measurement, discrete obstacle detection, obstacle detection systems, terrain modeling, path selection system simulation and evaluation, gas chromatograph/mass spectrometer system concepts, chromatograph model evaluation and improvement.

From laptop to benchtop to bedside: Structure-based Drug Design on Protein Targets

PubMed Central

Chen, Lu; Morrow, John K.; Tran, Hoang T.; Phatak, Sharangdhar S.; Du-Cuny, Lei; Zhang, Shuxing

2013-01-01

As an important aspect of computer-aided drug design, structure-based drug design brought a new horizon to pharmaceutical development. This in silico method permeates all aspects of drug discovery today, including lead identification, lead optimization, ADMET prediction and drug repurposing. Structure-based drug design has resulted in fruitful successes drug discovery targeting protein-ligand and protein-protein interactions. Meanwhile, challenges, noted by low accuracy and combinatoric issues, may also cause failures. In this review, state-of-the-art techniques for protein modeling (e.g. structure prediction, modeling protein flexibility, etc.), hit identification/optimization (e.g. molecular docking, focused library design, fragment-based design, molecular dynamic, etc.), and polypharmacology design will be discussed. We will explore how structure-based techniques can facilitate the drug discovery process and interplay with other experimental approaches. PMID:22316152

Design, Optimization and Evaluation of Integrally Stiffened Al 7050 Panel with Curved Stiffeners

NASA Technical Reports Server (NTRS)

Slemp, Wesley C. H.; Bird, R. Keith; Kapania, Rakesh K.; Havens, David; Norris, Ashley; Olliffe, Robert

2011-01-01

A curvilinear stiffened panel was designed, manufactured, and tested in the Combined Load Test Fixture at NASA Langley Research Center. The panel was optimized for minimum mass subjected to constraints on buckling load, yielding, and crippling or local stiffener failure using a new analysis tool named EBF3PanelOpt. The panel was designed for a combined compression-shear loading configuration that is a realistic load case for a typical aircraft wing panel. The panel was loaded beyond buckling and strains and out-of-plane displacements were measured. The experimental data were compared with the strains and out-of-plane deflections from a high fidelity nonlinear finite element analysis and linear elastic finite element analysis of the panel/test-fixture assembly. The numerical results indicated that the panel buckled at the linearly elastic buckling eigenvalue predicted for the panel/test-fixture assembly. The experimental strains prior to buckling compared well with both the linear and nonlinear finite element model.

A data driven control method for structure vibration suppression

NASA Astrophysics Data System (ADS)

Xie, Yangmin; Wang, Chao; Shi, Hang; Shi, Junwei

2018-02-01

High radio-frequency space applications have motivated continuous research on vibration suppression of large space structures both in academia and industry. This paper introduces a novel data driven control method to suppress vibrations of flexible structures and experimentally validates the suppression performance. Unlike model-based control approaches, the data driven control method designs a controller directly from the input-output test data of the structure, without requiring parametric dynamics and hence free of system modeling. It utilizes the discrete frequency response via spectral analysis technique and formulates a non-convex optimization problem to obtain optimized controller parameters with a predefined controller structure. Such approach is then experimentally applied on an end-driving flexible beam-mass structure. The experiment results show that the presented method can achieve competitive disturbance rejections compared to a model-based mixed sensitivity controller under the same design criterion but with much less orders and design efforts, demonstrating the proposed data driven control is an effective approach for vibration suppression of flexible structures.

Optimization of the Alkaline Pretreatment of Rice Straw for Enhanced Methane Yield

PubMed Central

Song, Zilin; Yang, Gaihe; Han, Xinhui; Feng, Yongzhong; Ren, Guangxin

2013-01-01

The lime pretreatment process for rice straw was optimized to enhance the biodegradation performance and increase biogas yield. The optimization was implemented using response surface methodology (RSM) and Box-Behnken experimental design. The effects of biodegradation, as well as the interactive effects of Ca(OH)2 concentration, pretreatment time, and inoculum amount on biogas improvement, were investigated. Rice straw compounds, such as lignin, cellulose, and hemicellulose, were significantly degraded with increasing Ca(OH)2 concentration. The optimal conditions for the use of pretreated rice straw in anaerobic digestion were 9.81% Ca(OH)2 (w/w TS), 5.89 d treatment time, and 45.12% inoculum content, which resulted in a methane yield of 225.3 mL/g VS. A determination coefficient (R 2) of 96% was obtained, indicating that the model used to predict the anabolic digestion process shows a favorable fit with the experimental parameters. PMID:23509824

Investigation on gas medium parameters for an ArF excimer laser through orthogonal experimental design

NASA Astrophysics Data System (ADS)

Song, Xingliang; Sha, Pengfei; Fan, Yuanyuan; Jiang, R.; Zhao, Jiangshan; Zhou, Yi; Yang, Junhong; Xiong, Guangliang; Wang, Yu

2018-02-01

Due to complex kinetics of formation and loss mechanisms, such as ion-ion recombination reaction, neutral species harpoon reaction, excited state quenching and photon absorption, as well as their interactions, the performance behavior of different laser gas medium parameters for excimer laser varies greatly. Therefore, the effects of gas composition and total gas pressure on excimer laser performance attract continual research studies. In this work, orthogonal experimental design (OED) is used to investigate quantitative and qualitative correlations between output laser energy characteristics and gas medium parameters for an ArF excimer laser with plano-plano optical resonator operation. Optimized output laser energy with good pulse to pulse stability can be obtained effectively by proper selection of the gas medium parameters, which makes the most of the ArF excimer laser device. Simple and efficient method for gas medium optimization is proposed and demonstrated experimentally, which provides a global and systematic solution. By detailed statistical analysis, the significance sequence of relevant parameter factors and the optimized composition for gas medium parameters are obtained. Compared with conventional route of varying single gas parameter factor sequentially, this paper presents a more comprehensive way of considering multivariables simultaneously, which seems promising in striking an appropriate balance among various complicated parameters for power scaling study of an excimer laser.

Genetic algorithm optimization of a film cooling array on a modern turbine inlet vane

NASA Astrophysics Data System (ADS)

Johnson, Jamie J.

In response to the need for more advanced gas turbine cooling design methods that factor in the 3-D flowfield and heat transfer characteristics, this study involves the computational optimization of a pressure side film cooling array on a modern turbine inlet vane. Latin hypersquare sampling, genetic algorithm reproduction, and Reynolds-Averaged Navier Stokes (RANS) computational fluid dynamics (CFD) as an evaluation step are used to assess a total of 1,800 film cooling designs over 13 generations. The process was efficient due to the Leo CFD code's ability to estimate cooling mass flux at surface grid cells using a transpiration boundary condition, eliminating the need for remeshing between designs. The optimization resulted in a unique cooling design relative to the baseline with new injection angles, compound angles, cooling row patterns, hole sizes, a redistribution of cooling holes away from the over-cooled midspan to hot areas near the shroud, and a lower maximum surface temperature. To experimentally confirm relative design trends between the optimized and baseline designs, flat plate infrared thermography assessments were carried out at design flow conditions. Use of flat plate experiments to model vane pressure side cooling was justified through a conjugate heat transfer CFD comparison of the 3-D vane and flat plate which showed similar cooling performance trends at multiple span locations. The optimized flat plate model exhibited lower minimum surface temperatures at multiple span locations compared to the baseline. Overall, this work shows promise of optimizing film cooling to reduce design cycle time and save cooling mass flow in a gas turbine.

Response surface methodology to optimize partition and purification of two recombinant oxidoreductase enzymes, glucose dehydrogenase and d-galactose dehydrogenase in aqueous two-phase systems.

PubMed

Shahbaz Mohammadi, Hamid; Mostafavi, Seyede Samaneh; Soleimani, Saeideh; Bozorgian, Sajad; Pooraskari, Maryam; Kianmehr, Anvarsadat

2015-04-01

Oxidoreductases are an important family of enzymes that are used in many biotechnological processes. An experimental design was applied to optimize partition and purification of two recombinant oxidoreductases, glucose dehydrogenase (GDH) from Bacillus subtilis and d-galactose dehydrogenase (GalDH) from Pseudomonas fluorescens AK92 in aqueous two-phase systems (ATPS). Response surface methodology (RSM) with a central composite rotatable design (CCRD) was performed to optimize critical factors like polyethylene glycol (PEG) concentration, concentration of salt and pH value. The best partitioning conditions was achieved in an ATPS composed of 12% PEG-6000, 15% K2HPO4 with pH 7.5 at 25°C, which ensured partition coefficient (KE) of 66.6 and 45.7 for GDH and GalDH, respectively. Under these experimental conditions, the activity of GDH and GalDH was 569.5U/ml and 673.7U/ml, respectively. It was found that these enzymes preferentially partitioned into the top PEG-rich phase and appeared as single bands on SDS-PAGE gel. Meanwhile the validity of the response model was confirmed by a good agreement between predicted and experimental results. Collectively, according to the obtained data it can be inferred that the ATPS optimization using RSM approach can be applied for recovery and purification of any enzyme from oxidoreductase family. Copyright © 2015 Elsevier Inc. All rights reserved.

Formulation and optimization by experimental design of eco-friendly emulsions based on d-limonene.

PubMed

Pérez-Mosqueda, Luis M; Trujillo-Cayado, Luis A; Carrillo, Francisco; Ramírez, Pablo; Muñoz, José

2015-04-01

d-Limonene is a natural occurring solvent that can replace more pollutant chemicals in agrochemical formulations. In the present work, a comprehensive study of the influence of dispersed phase mass fraction, ϕ, and of the surfactant/oil ratio, R, on the emulsion stability and droplet size distribution of d-limonene-in-water emulsions stabilized by a non-ionic triblock copolymer surfactant has been carried out. An experimental full factorial design 3(2) was conducted in order to optimize the emulsion formulation. The independent variables, ϕ and R were studied in the range 10-50 wt% and 0.02-0.1, respectively. The emulsions studied were mainly destabilized by both creaming and Ostwald ripening. Therefore, initial droplet size and an overall destabilization parameter, the so-called turbiscan stability index, were used as dependent variables. The optimal formulation, comprising minimum droplet size and maximum stability was achieved at ϕ=50 wt%; R=0.062. Furthermore, the surface response methodology allowed us to obtain the formulation yielding sub-micron emulsions by using a single step rotor/stator homogenizer process instead of most commonly used two-step emulsification methods. In addition, the optimal formulation was further improved against Ostwald ripening by adding silicone oil to the dispersed phase. The combination of these experimental findings allowed us to gain a deeper insight into the stability of these emulsions, which can be applied to the rational development of new formulations with potential application in agrochemical formulations. Copyright © 2015 Elsevier B.V. All rights reserved.

Automatic Design of Synthetic Gene Circuits through Mixed Integer Non-linear Programming

PubMed Central

Huynh, Linh; Kececioglu, John; Köppe, Matthias; Tagkopoulos, Ilias

2012-01-01

Automatic design of synthetic gene circuits poses a significant challenge to synthetic biology, primarily due to the complexity of biological systems, and the lack of rigorous optimization methods that can cope with the combinatorial explosion as the number of biological parts increases. Current optimization methods for synthetic gene design rely on heuristic algorithms that are usually not deterministic, deliver sub-optimal solutions, and provide no guaranties on convergence or error bounds. Here, we introduce an optimization framework for the problem of part selection in synthetic gene circuits that is based on mixed integer non-linear programming (MINLP), which is a deterministic method that finds the globally optimal solution and guarantees convergence in finite time. Given a synthetic gene circuit, a library of characterized parts, and user-defined constraints, our method can find the optimal selection of parts that satisfy the constraints and best approximates the objective function given by the user. We evaluated the proposed method in the design of three synthetic circuits (a toggle switch, a transcriptional cascade, and a band detector), with both experimentally constructed and synthetic promoter libraries. Scalability and robustness analysis shows that the proposed framework scales well with the library size and the solution space. The work described here is a step towards a unifying, realistic framework for the automated design of biological circuits. PMID:22536398

Object-Oriented MDAO Tool with Aeroservoelastic Model Tuning Capability

NASA Technical Reports Server (NTRS)

Pak, Chan-gi; Li, Wesley; Lung, Shun-fat

2008-01-01

An object-oriented multi-disciplinary analysis and optimization (MDAO) tool has been developed at the NASA Dryden Flight Research Center to automate the design and analysis process and leverage existing commercial as well as in-house codes to enable true multidisciplinary optimization in the preliminary design stage of subsonic, transonic, supersonic and hypersonic aircraft. Once the structural analysis discipline is finalized and integrated completely into the MDAO process, other disciplines such as aerodynamics and flight controls will be integrated as well. Simple and efficient model tuning capabilities based on optimization problem are successfully integrated with the MDAO tool. More synchronized all phases of experimental testing (ground and flight), analytical model updating, high-fidelity simulations for model validation, and integrated design may result in reduction of uncertainties in the aeroservoelastic model and increase the flight safety.

Numerical model of tapered fiber Bragg gratings for comprehensive analysis and optimization of their sensing and strain-induced tunable dispersion properties.

PubMed

Osuch, Tomasz; Markowski, Konrad; Jędrzejewski, Kazimierz

2015-06-10

A versatile numerical model for spectral transmission/reflection, group delay characteristic analysis, and design of tapered fiber Bragg gratings (TFBGs) is presented. This approach ensures flexibility with defining both distribution of refractive index change of the gratings (including apodization) and shape of the taper profile. Additionally, sensing and tunable dispersion properties of the TFBGs were fully examined, considering strain-induced effects. The presented numerical approach, together with Pareto optimization, were also used to design the best tanh apodization profiles of the TFBG in terms of maximizing its spectral width with simultaneous minimization of the group delay oscillations. Experimental verification of the model confirms its correctness. The combination of model versatility and possibility to define the other objective functions of Pareto optimization creates a universal tool for TFBG analysis and design.

Research on theoretical optimization and experimental verification of minimum resistance hull form based on Rankine source method

NASA Astrophysics Data System (ADS)

Zhang, Bao-Ji; Zhang, Zhu-Xin

2015-09-01

To obtain low resistance and high efficiency energy-saving ship, minimum total resistance hull form design method is studied based on potential flow theory of wave-making resistance and considering the effects of tail viscous separation. With the sum of wave resistance and viscous resistance as objective functions and the parameters of B-Spline function as design variables, mathematical models are built using Nonlinear Programming Method (NLP) ensuring the basic limit of displacement and considering rear viscous separation. We develop ship lines optimization procedures with intellectual property rights. Series60 is used as parent ship in optimization design to obtain improved ship (Series60-1) theoretically. Then drag tests for the improved ship (Series60-1) is made to get the actual minimum total resistance hull form.

Experimental optimization of the number of blocks by means of algorithms parameterized by confidence interval in popcorn breeding.

PubMed

Paula, T O M; Marinho, C D; Amaral Júnior, A T; Peternelli, L A; Gonçalves, L S A

2013-06-27

The objective of this study was to determine the optimal number of repetitions to be used in competition trials of popcorn traits related to production and quality, including grain yield and expansion capacity. The experiments were conducted in 3 environments representative of the north and northwest regions of the State of Rio de Janeiro with 10 Brazilian genotypes of popcorn, consisting by 4 commercial hybrids (IAC 112, IAC 125, Zélia, and Jade), 4 improved varieties (BRS Ângela, UFVM-2 Barão de Viçosa, Beija-flor, and Viçosa) and 2 experimental populations (UNB2U-C3 and UNB2U-C4). The experimental design utilized was a randomized complete block design with 7 repetitions. The Bootstrap method was employed to obtain samples of all of the possible combinations within the 7 blocks. Subsequently, the confidence intervals of the parameters of interest were calculated for all simulated data sets. The optimal number of repetition for all of the traits was considered when all of the estimates of the parameters in question were encountered within the confidence interval. The estimates of the number of repetitions varied according to the parameter estimated, variable evaluated, and environment cultivated, ranging from 2 to 7. It is believed that only the expansion capacity traits in the Colégio Agrícola environment (for residual variance and coefficient of variation), and number of ears per plot, in the Itaocara environment (for coefficient of variation) needed 7 repetitions to fall within the confidence interval. Thus, for the 3 studies conducted, we can conclude that 6 repetitions are optimal for obtaining high experimental precision.

Application of Box-Behnken design to prepare gentamicin-loaded calcium carbonate nanoparticles.

PubMed

Maleki Dizaj, Solmaz; Lotfipour, Farzaneh; Barzegar-Jalali, Mohammad; Zarrintan, Mohammad-Hossein; Adibkia, Khosro

2016-09-01

The aim of this research was to prepare and optimize calcium carbonate (CaCO3) nanoparticles as carriers for gentamicin sulfate. A chemical precipitation method was used to prepare the gentamicin sulfate-loaded CaCO3 nanoparticles. A 3-factor, 3-level Box-Behnken design was used for the optimization procedure, with the molar ratio of CaCl2: Na2CO3 (X1), the concentration of drug (X2), and the speed of homogenization (X3) as the independent variables. The particle size and entrapment efficiency were considered as response variables. Mathematical equations and response surface plots were used, along with the counter plots, to relate the dependent and independent variables. The results indicated that the speed of homogenization was the main variable contributing to particle size and entrapment efficiency. The combined effect of all three independent variables was also evaluated. Using the response optimization design, the optimized Xl-X3 levels were predicted. An optimized formulation was then prepared according to these levels, resulting in a particle size of 80.23 nm and an entrapment efficiency of 30.80%. It was concluded that the chemical precipitation technique, together with the Box-Behnken experimental design methodology, could be successfully used to optimize the formulation of drug-incorporated calcium carbonate nanoparticles.

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

PubMed

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

2016-07-15

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

Optimization of Passive Voltage Multipliers for Fast Start-up and Multi-voltage Power Supplies in Electromagnetic Energy Harvesting Systems

NASA Astrophysics Data System (ADS)

Yang, G.; Stark, B. H.; Burrow, S. G.; Hollis, S. J.

2014-11-01

This paper demonstrates the use of passive voltage multipliers for rapid start-up of sub-milliwatt electromagnetic energy harvesting systems. The work describes circuit optimization to make as short as possible the transition from completely depleted energy storage to the first powering-up of an actively controlled switched-mode converter. The dependency of the start-up time on component parameters and topologies is derived by simulation and experimentation. The resulting optimized multiplier design reduces the start-up time from several minutes to 1 second. An additional improvement uses the inherent cascade structure of the voltage multiplier to power sub-systems at different voltages. This multi-rail start-up is shown to reduce the circuit losses of the active converter by 72% with respect to the optimized single-rail system. The experimental results provide insight into the multiplier's transient behaviour, including circuit interactions, in a complete harvesting system, and offer important information to optimize voltage multipliers for rapid start-up.

Optimization of Polyplex Formation between DNA Oligonucleotide and Poly(ʟ-Lysine): Experimental Study and Modeling Approach.

PubMed

Vasiliu, Tudor; Cojocaru, Corneliu; Rotaru, Alexandru; Pricope, Gabriela; Pinteala, Mariana; Clima, Lilia

2017-06-17

The polyplexes formed by nucleic acids and polycations have received a great attention owing to their potential application in gene therapy. In our study, we report experimental results and modeling outcomes regarding the optimization of polyplex formation between the double-stranded DNA (dsDNA) and poly(ʟ-Lysine) (PLL). The quantification of the binding efficiency during polyplex formation was performed by processing of the images captured from the gel electrophoresis assays. The design of experiments (DoE) and response surface methodology (RSM) were employed to investigate the coupling effect of key factors (pH and N/P ratio) affecting the binding efficiency. According to the experimental observations and response surface analysis, the N/P ratio showed a major influence on binding efficiency compared to pH. Model-based optimization calculations along with the experimental confirmation runs unveiled the maximal binding efficiency (99.4%) achieved at pH 5.4 and N/P ratio 125. To support the experimental data and reveal insights of molecular mechanism responsible for the polyplex formation between dsDNA and PLL, molecular dynamics simulations were performed at pH 5.4 and 7.4.

Optimization of Polyplex Formation between DNA Oligonucleotide and Poly(l-Lysine): Experimental Study and Modeling Approach

PubMed Central

Vasiliu, Tudor; Cojocaru, Corneliu; Rotaru, Alexandru; Pricope, Gabriela; Pinteala, Mariana; Clima, Lilia

2017-01-01

The polyplexes formed by nucleic acids and polycations have received a great attention owing to their potential application in gene therapy. In our study, we report experimental results and modeling outcomes regarding the optimization of polyplex formation between the double-stranded DNA (dsDNA) and poly(l-Lysine) (PLL). The quantification of the binding efficiency during polyplex formation was performed by processing of the images captured from the gel electrophoresis assays. The design of experiments (DoE) and response surface methodology (RSM) were employed to investigate the coupling effect of key factors (pH and N/P ratio) affecting the binding efficiency. According to the experimental observations and response surface analysis, the N/P ratio showed a major influence on binding efficiency compared to pH. Model-based optimization calculations along with the experimental confirmation runs unveiled the maximal binding efficiency (99.4%) achieved at pH 5.4 and N/P ratio 125. To support the experimental data and reveal insights of molecular mechanism responsible for the polyplex formation between dsDNA and PLL, molecular dynamics simulations were performed at pH 5.4 and 7.4. PMID:28629130

Bayesian Dose-Response Modeling in Sparse Data

NASA Astrophysics Data System (ADS)

Kim, Steven B.

This book discusses Bayesian dose-response modeling in small samples applied to two different settings. The first setting is early phase clinical trials, and the second setting is toxicology studies in cancer risk assessment. In early phase clinical trials, experimental units are humans who are actual patients. Prior to a clinical trial, opinions from multiple subject area experts are generally more informative than the opinion of a single expert, but we may face a dilemma when they have disagreeing prior opinions. In this regard, we consider compromising the disagreement and compare two different approaches for making a decision. In addition to combining multiple opinions, we also address balancing two levels of ethics in early phase clinical trials. The first level is individual-level ethics which reflects the perspective of trial participants. The second level is population-level ethics which reflects the perspective of future patients. We extensively compare two existing statistical methods which focus on each perspective and propose a new method which balances the two conflicting perspectives. In toxicology studies, experimental units are living animals. Here we focus on a potential non-monotonic dose-response relationship which is known as hormesis. Briefly, hormesis is a phenomenon which can be characterized by a beneficial effect at low doses and a harmful effect at high doses. In cancer risk assessments, the estimation of a parameter, which is known as a benchmark dose, can be highly sensitive to a class of assumptions, monotonicity or hormesis. In this regard, we propose a robust approach which considers both monotonicity and hormesis as a possibility. In addition, We discuss statistical hypothesis testing for hormesis and consider various experimental designs for detecting hormesis based on Bayesian decision theory. Past experiments have not been optimally designed for testing for hormesis, and some Bayesian optimal designs may not be optimal under a wrong parametric assumption. In this regard, we consider a robust experimental design which does not require any parametric assumption.

Optimal Experimental Design of Borehole Locations for Bayesian Inference of Past Ice Sheet Surface Temperatures

NASA Astrophysics Data System (ADS)

Davis, A. D.; Huan, X.; Heimbach, P.; Marzouk, Y.

2017-12-01

Borehole data are essential for calibrating ice sheet models. However, field expeditions for acquiring borehole data are often time-consuming, expensive, and dangerous. It is thus essential to plan the best sampling locations that maximize the value of data while minimizing costs and risks. We present an uncertainty quantification (UQ) workflow based on rigorous probability framework to achieve these objectives. First, we employ an optimal experimental design (OED) procedure to compute borehole locations that yield the highest expected information gain. We take into account practical considerations of location accessibility (e.g., proximity to research sites, terrain, and ice velocity may affect feasibility of drilling) and robustness (e.g., real-time constraints such as weather may force researchers to drill at sub-optimal locations near those originally planned), by incorporating a penalty reflecting accessibility as well as sensitivity to deviations from the optimal locations. Next, we extract vertical temperature profiles from these boreholes and formulate a Bayesian inverse problem to reconstruct past surface temperatures. Using a model of temperature advection/diffusion, the top boundary condition (corresponding to surface temperatures) is calibrated via efficient Markov chain Monte Carlo (MCMC). The overall procedure can then be iterated to choose new optimal borehole locations for the next expeditions.Through this work, we demonstrate powerful UQ methods for designing experiments, calibrating models, making predictions, and assessing sensitivity--all performed under an uncertain environment. We develop a theoretical framework as well as practical software within an intuitive workflow, and illustrate their usefulness for combining data and models for environmental and climate research.

Optimization of Extraction Conditions for Phenolic Acids from the Leaves of Melissa officinalis L. Using Response Surface Methodology

PubMed Central

Yoo, Guijae; Lee, Il Kyun; Park, Seonju; Kim, Nanyoung; Park, Jun Hyung; Kim, Seung Hyun

2018-01-01

Background: Melissa officinalis L. is a well-known medicinal plant from the family Lamiaceae, which is distributed throughout Eastern Mediterranean region and Western Asia. Objective: In this study, response surface methodology (RSM) was utilized to optimize the extraction conditions for bioactive compounds from the leaves of M. officinalis L. Materials and Methods: A Box–Behnken design (BBD) was utilized to evaluate the effects of three independent variables, namely extraction temperature (°C), methanol concentration (%), and solvent-to-material ratio (mL/g) on the responses of the contents of caffeic acid and rosmarinic acid. Results: Regression analysis showed a good fit of the experimental data. The optimal condition was obtained at extraction temperature 80.53°C, methanol concentration 29.89%, and solvent-to-material ratio 30 mL/g. Conclusion: These results indicate the suitability of the model employed and the successful application of RSM in optimizing the extraction conditions. This study may be useful for standardizing production quality, including improving the efficiency of large-scale extraction systems. SUMMARY The optimum conditions for the extraction of major phenolic acids from the leaves of Melissa officinalis L. were determined using response surface methodologyBox–Behnken design was utilized to evaluate the effects of three independent variablesQuadratic polynomial model provided a satisfactory description of the experimental dataThe optimized condition for simultaneous maximum contents of caffeic acid and rosmarinic acid was determined. Abbreviations used: RSM: Response surface methodology, BBD: Box–Behnken design, CA: Caffeic acid, RA: Rosmarinic acid, HPLC: High-performance liquid chromatography. PMID:29720824

Development of Optimal Stressor Scenarios for New Operational Energy Systems

DTIC Science & Technology

2017-12-01

Analyzing the previous model using a design of experiments (DOE) and regression analysis provides critical information about the associated operational...from experimentation. The resulting system requirements can be used to revisit the design requirements and develop a more robust system. This process...stressor scenarios for acceptance testing. Analyzing the previous model using a design of experiments (DOE) and regression analysis provides critical

Robust parameter design for automatically controlled systems and nanostructure synthesis

NASA Astrophysics Data System (ADS)

Dasgupta, Tirthankar

2007-12-01

This research focuses on developing comprehensive frameworks for developing robust parameter design methodology for dynamic systems with automatic control and for synthesis of nanostructures. In many automatically controlled dynamic processes, the optimal feedback control law depends on the parameter design solution and vice versa and therefore an integrated approach is necessary. A parameter design methodology in the presence of feedback control is developed for processes of long duration under the assumption that experimental noise factors are uncorrelated over time. Systems that follow a pure-gain dynamic model are considered and the best proportional-integral and minimum mean squared error control strategies are developed by using robust parameter design. The proposed method is illustrated using a simulated example and a case study in a urea packing plant. This idea is also extended to cases with on-line noise factors. The possibility of integrating feedforward control with a minimum mean squared error feedback control scheme is explored. To meet the needs of large scale synthesis of nanostructures, it is critical to systematically find experimental conditions under which the desired nanostructures are synthesized reproducibly, at large quantity and with controlled morphology. The first part of the research in this area focuses on modeling and optimization of existing experimental data. Through a rigorous statistical analysis of experimental data, models linking the probabilities of obtaining specific morphologies to the process variables are developed. A new iterative algorithm for fitting a Multinomial GLM is proposed and used. The optimum process conditions, which maximize the above probabilities and make the synthesis process less sensitive to variations of process variables around set values, are derived from the fitted models using Monte-Carlo simulations. The second part of the research deals with development of an experimental design methodology, tailor-made to address the unique phenomena associated with nanostructure synthesis. A sequential space filling design called Sequential Minimum Energy Design (SMED) for exploring best process conditions for synthesis of nanowires. The SMED is a novel approach to generate sequential designs that are model independent, can quickly "carve out" regions with no observable nanostructure morphology, and allow for the exploration of complex response surfaces.

Angular rate optimal design for the rotary strapdown inertial navigation system.

PubMed

Yu, Fei; Sun, Qian

2014-04-22

Due to the characteristics of high precision for a long duration, the rotary strapdown inertial navigation system (RSINS) has been widely used in submarines and surface ships. Nowadays, the core technology, the rotating scheme, has been studied by numerous researchers. It is well known that as one of the key technologies, the rotating angular rate seriously influences the effectiveness of the error modulating. In order to design the optimal rotating angular rate of the RSINS, the relationship between the rotating angular rate and the velocity error of the RSINS was analyzed in detail based on the Laplace transform and the inverse Laplace transform in this paper. The analysis results showed that the velocity error of the RSINS depends on not only the sensor error, but also the rotating angular rate. In order to minimize the velocity error, the rotating angular rate of the RSINS should match the sensor error. One optimal design method for the rotating rate of the RSINS was also proposed in this paper. Simulation and experimental results verified the validity and superiority of this optimal design method for the rotating rate of the RSINS.

Flow optimization study of a batch microfluidics PET tracer synthesizing device

PubMed Central

Elizarov, Arkadij M.; Meinhart, Carl; van Dam, R. Michael; Huang, Jiang; Daridon, Antoine; Heath, James R.; Kolb, Hartmuth C.

2010-01-01

We present numerical modeling and experimental studies of flow optimization inside a batch microfluidic micro-reactor used for synthesis of human-scale doses of Positron Emission Tomography (PET) tracers. Novel techniques are used for mixing within, and eluting liquid out of, the coin-shaped reaction chamber. Numerical solutions of the general incompressible Navier Stokes equations along with time-dependent elution scalar field equation for the three dimensional coin-shaped geometry were obtained and validated using fluorescence imaging analysis techniques. Utilizing the approach presented in this work, we were able to identify optimized geometrical and operational conditions for the micro-reactor in the absence of radioactive material commonly used in PET related tracer production platforms as well as evaluate the designed and fabricated micro-reactor using numerical and experimental validations. PMID:21072595

Optimal Decision Stimuli for Risky Choice Experiments: An Adaptive Approach.

PubMed

Cavagnaro, Daniel R; Gonzalez, Richard; Myung, Jay I; Pitt, Mark A

2013-02-01

Collecting data to discriminate between models of risky choice requires careful selection of decision stimuli. Models of decision making aim to predict decisions across a wide range of possible stimuli, but practical limitations force experimenters to select only a handful of them for actual testing. Some stimuli are more diagnostic between models than others, so the choice of stimuli is critical. This paper provides the theoretical background and a methodological framework for adaptive selection of optimal stimuli for discriminating among models of risky choice. The approach, called Adaptive Design Optimization (ADO), adapts the stimulus in each experimental trial based on the results of the preceding trials. We demonstrate the validity of the approach with simulation studies aiming to discriminate Expected Utility, Weighted Expected Utility, Original Prospect Theory, and Cumulative Prospect Theory models.

Sequential-Optimization-Based Framework for Robust Modeling and Design of Heterogeneous Catalytic Systems

DOE PAGES

Rangarajan, Srinivas; Maravelias, Christos T.; Mavrikakis, Manos

2017-11-09

Here, we present a general optimization-based framework for (i) ab initio and experimental data driven mechanistic modeling and (ii) optimal catalyst design of heterogeneous catalytic systems. Both cases are formulated as a nonlinear optimization problem that is subject to a mean-field microkinetic model and thermodynamic consistency requirements as constraints, for which we seek sparse solutions through a ridge (L 2 regularization) penalty. The solution procedure involves an iterative sequence of forward simulation of the differential algebraic equations pertaining to the microkinetic model using a numerical tool capable of handling stiff systems, sensitivity calculations using linear algebra, and gradient-based nonlinear optimization.more » A multistart approach is used to explore the solution space, and a hierarchical clustering procedure is implemented for statistically classifying potentially competing solutions. An example of methanol synthesis through hydrogenation of CO and CO 2 on a Cu-based catalyst is used to illustrate the framework. The framework is fast, is robust, and can be used to comprehensively explore the model solution and design space of any heterogeneous catalytic system.« less

Sequential-Optimization-Based Framework for Robust Modeling and Design of Heterogeneous Catalytic Systems

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

Rangarajan, Srinivas; Maravelias, Christos T.; Mavrikakis, Manos

Here, we present a general optimization-based framework for (i) ab initio and experimental data driven mechanistic modeling and (ii) optimal catalyst design of heterogeneous catalytic systems. Both cases are formulated as a nonlinear optimization problem that is subject to a mean-field microkinetic model and thermodynamic consistency requirements as constraints, for which we seek sparse solutions through a ridge (L 2 regularization) penalty. The solution procedure involves an iterative sequence of forward simulation of the differential algebraic equations pertaining to the microkinetic model using a numerical tool capable of handling stiff systems, sensitivity calculations using linear algebra, and gradient-based nonlinear optimization.more » A multistart approach is used to explore the solution space, and a hierarchical clustering procedure is implemented for statistically classifying potentially competing solutions. An example of methanol synthesis through hydrogenation of CO and CO 2 on a Cu-based catalyst is used to illustrate the framework. The framework is fast, is robust, and can be used to comprehensively explore the model solution and design space of any heterogeneous catalytic system.« less

Strategic Mobility 21: Baseline Joint Experimentation Campaign Plan

DTIC Science & Technology

2008-06-19

including energy. The Value Stream Analysis Future State then designed Kaizens (process optimizations) for an improved Future State to help drive waste...Recommended Improvements and Experimentation Opportunities Initial recommended Kaizens (improvement opportunities) for waste reduction, constraint...Trucking, Service Craft Logistics, BNSF, and Madison Warehouse, Inc. • Kaizen 1 (Figure 17): Full upload electronically of the Dole ANS files • Kaizen

Taguchi method of experimental design in materials education

NASA Technical Reports Server (NTRS)

Weiser, Martin W.

1993-01-01

Some of the advantages and disadvantages of the Taguchi Method of experimental design as applied to Materials Science will be discussed. This is a fractional factorial method that employs the minimum number of experimental trials for the information obtained. The analysis is also very simple to use and teach, which is quite advantageous in the classroom. In addition, the Taguchi loss function can be easily incorporated to emphasize that improvements in reproducibility are often at least as important as optimization of the response. The disadvantages of the Taguchi Method include the fact that factor interactions are normally not accounted for, there are zero degrees of freedom if all of the possible factors are used, and randomization is normally not used to prevent environmental biasing. In spite of these disadvantages it is felt that the Taguchi Method is extremely useful for both teaching experimental design and as a research tool, as will be shown with a number of brief examples.

A Survey on Optimal Signal Processing Techniques Applied to Improve the Performance of Mechanical Sensors in Automotive Applications

PubMed Central

Hernandez, Wilmar

2007-01-01

In this paper a survey on recent applications of optimal signal processing techniques to improve the performance of mechanical sensors is made. Here, a comparison between classical filters and optimal filters for automotive sensors is made, and the current state of the art of the application of robust and optimal control and signal processing techniques to the design of the intelligent (or smart) sensors that today's cars need is presented through several experimental results that show that the fusion of intelligent sensors and optimal signal processing techniques is the clear way to go. However, the switch between the traditional methods of designing automotive sensors and the new ones cannot be done overnight because there are some open research issues that have to be solved. This paper draws attention to one of the open research issues and tries to arouse researcher's interest in the fusion of intelligent sensors and optimal signal processing techniques.

The usefulness of systematic reviews of animal experiments for the design of preclinical and clinical studies.

PubMed

de Vries, Rob B M; Wever, Kimberley E; Avey, Marc T; Stephens, Martin L; Sena, Emily S; Leenaars, Marlies

2014-01-01

The question of how animal studies should be designed, conducted, and analyzed remains underexposed in societal debates on animal experimentation. This is not only a scientific but also a moral question. After all, if animal experiments are not appropriately designed, conducted, and analyzed, the results produced are unlikely to be reliable and the animals have in effect been wasted. In this article, we focus on one particular method to address this moral question, namely systematic reviews of previously performed animal experiments. We discuss how the design, conduct, and analysis of future (animal and human) experiments may be optimized through such systematic reviews. In particular, we illustrate how these reviews can help improve the methodological quality of animal experiments, make the choice of an animal model and the translation of animal data to the clinic more evidence-based, and implement the 3Rs. Moreover, we discuss which measures are being taken and which need to be taken in the future to ensure that systematic reviews will actually contribute to optimizing experimental design and thereby to meeting a necessary condition for making the use of animals in these experiments justified. © The Author 2014. Published by Oxford University Press.

The Usefulness of Systematic Reviews of Animal Experiments for the Design of Preclinical and Clinical Studies

PubMed Central

de Vries, Rob B. M.; Wever, Kimberley E.; Avey, Marc T.; Stephens, Martin L.; Sena, Emily S.; Leenaars, Marlies

2014-01-01

The question of how animal studies should be designed, conducted, and analyzed remains underexposed in societal debates on animal experimentation. This is not only a scientific but also a moral question. After all, if animal experiments are not appropriately designed, conducted, and analyzed, the results produced are unlikely to be reliable and the animals have in effect been wasted. In this article, we focus on one particular method to address this moral question, namely systematic reviews of previously performed animal experiments. We discuss how the design, conduct, and analysis of future (animal and human) experiments may be optimized through such systematic reviews. In particular, we illustrate how these reviews can help improve the methodological quality of animal experiments, make the choice of an animal model and the translation of animal data to the clinic more evidence-based, and implement the 3Rs. Moreover, we discuss which measures are being taken and which need to be taken in the future to ensure that systematic reviews will actually contribute to optimizing experimental design and thereby to meeting a necessary condition for making the use of animals in these experiments justified. PMID:25541545

Inverse problems in complex material design: Applications to non-crystalline solids

NASA Astrophysics Data System (ADS)

Biswas, Parthapratim; Drabold, David; Elliott, Stephen

The design of complex amorphous materials is one of the fundamental problems in disordered condensed-matter science. While impressive developments of ab-initio simulation methods during the past several decades have brought tremendous success in understanding materials property from micro- to mesoscopic length scales, a major drawback is that they fail to incorporate existing knowledge of the materials in simulation methodologies. Since an essential feature of materials design is the synergy between experiment and theory, a properly developed approach to design materials should be able to exploit all available knowledge of the materials from measured experimental data. In this talk, we will address the design of complex disordered materials as an inverse problem involving experimental data and available empirical information. We show that the problem can be posed as a multi-objective non-convex optimization program, which can be addressed using a number of recently-developed bio-inspired global optimization techniques. In particular, we will discuss how a population-based stochastic search procedure can be used to determine the structure of non-crystalline solids (e.g. a-SiH, a-SiO2, amorphous graphene, and Fe and Ni clusters). The work is partially supported by NSF under Grant Nos. DMR 1507166 and 1507670.

Production optimization of invertase by Lactobacillus brevis Mm-6 and its immobilization on alginate beads.

PubMed

Awad, Ghada E A; Amer, Hassan; El-Gammal, Eman W; Helmy, Wafaa A; Esawy, Mona A; Elnashar, Magdy M M

2013-04-02

A sequential optimization strategy, based on statistical experimental designs, was employed to enhance the production of invertase by Lactobacillus brevis Mm-6 isolated from breast milk. First, a 2-level Plackett-Burman design was applied to screen the bioprocess parameters that significantly influence the invertase production. The second optimization step was performed using fractional factorial design in order to optimize the amounts of variables have the highest positive significant effect on the invertase production. A maximal enzyme activity of 1399U/ml was more than five folds the activity obtained using the basal medium. Invertase was immobilized onto grafted alginate beads to improve the enzyme's stability. Immobilization process increased the operational temperature from 30 to 60°C compared to the free enzyme. The reusability test proved the durability of the grafted alginate beads for 15 cycles with retention of 100% of the immobilized enzyme activity to be more convenient for industrial uses. Copyright © 2013 Elsevier Ltd. All rights reserved.

Improvement of halophilic cellulase production from locally isolated fungal strain.

PubMed

Gunny, Ahmad Anas Nagoor; Arbain, Dachyar; Jamal, Parveen; Gumba, Rizo Edwin

2015-07-01

Halophilic cellulases from the newly isolated fungus, Aspergillus terreus UniMAP AA-6 were found to be useful for in situ saccharification of ionic liquids treated lignocelluloses. Efforts have been taken to improve the enzyme production through statistical optimization approach namely Plackett-Burman design and the Face Centered Central Composite Design (FCCCD). Plackett-Burman experimental design was used to screen the medium components and process conditions. It was found that carboxymethylcellulose (CMC), FeSO4·7H2O, NaCl, MgSO4·7H2O, peptone, agitation speed and inoculum size significantly influence the production of halophilic cellulase. On the other hand, KH2PO4, KOH, yeast extract and temperature had a negative effect on enzyme production. Further optimization through FCCCD revealed that the optimization approach improved halophilic cellulase production from 0.029 U/ml to 0.0625 U/ml, which was approximately 2.2-times greater than before optimization.

Improvement of halophilic cellulase production from locally isolated fungal strain

PubMed Central

Gunny, Ahmad Anas Nagoor; Arbain, Dachyar; Jamal, Parveen; Gumba, Rizo Edwin

2014-01-01

Halophilic cellulases from the newly isolated fungus, Aspergillus terreus UniMAP AA-6 were found to be useful for in situ saccharification of ionic liquids treated lignocelluloses. Efforts have been taken to improve the enzyme production through statistical optimization approach namely Plackett–Burman design and the Face Centered Central Composite Design (FCCCD). Plackett–Burman experimental design was used to screen the medium components and process conditions. It was found that carboxymethylcellulose (CMC), FeSO4·7H2O, NaCl, MgSO4·7H2O, peptone, agitation speed and inoculum size significantly influence the production of halophilic cellulase. On the other hand, KH2PO4, KOH, yeast extract and temperature had a negative effect on enzyme production. Further optimization through FCCCD revealed that the optimization approach improved halophilic cellulase production from 0.029 U/ml to 0.0625 U/ml, which was approximately 2.2-times greater than before optimization. PMID:26150755

Active control of the spatial MRI phase distribution with optimal control theory

NASA Astrophysics Data System (ADS)

Lefebvre, Pauline M.; Van Reeth, Eric; Ratiney, Hélène; Beuf, Olivier; Brusseau, Elisabeth; Lambert, Simon A.; Glaser, Steffen J.; Sugny, Dominique; Grenier, Denis; Tse Ve Koon, Kevin

2017-08-01

This paper investigates the use of Optimal Control (OC) theory to design Radio-Frequency (RF) pulses that actively control the spatial distribution of the MRI magnetization phase. The RF pulses are generated through the application of the Pontryagin Maximum Principle and optimized so that the resulting transverse magnetization reproduces various non-trivial and spatial phase patterns. Two different phase patterns are defined and the resulting optimal pulses are tested both numerically with the ODIN MRI simulator and experimentally with an agar gel phantom on a 4.7 T small-animal MR scanner. Phase images obtained in simulations and experiments are both consistent with the defined phase patterns. A practical application of phase control with OC-designed pulses is also presented, with the generation of RF pulses adapted for a Magnetic Resonance Elastography experiment. This study demonstrates the possibility to use OC-designed RF pulses to encode information in the magnetization phase and could have applications in MRI sequences using phase images.

Optimization of Physical Conditions for the Aqueous Extraction of Antioxidant Compounds from Ginger (Zingiber officinale) Applying a Box-Behnken Design.

PubMed

Ramírez-Godínez, Juan; Jaimez-Ordaz, Judith; Castañeda-Ovando, Araceli; Añorve-Morga, Javier; Salazar-Pereda, Verónica; González-Olivares, Luis Guillermo; Contreras-López, Elizabeth

2017-03-01

Since ancient times, ginger (Zingiber officinale) has been widely used for culinary and medicinal purposes. This rhizome possesses several chemical constituents; most of them present antioxidant capacity due mainly to the presence of phenolic compounds. Thus, the physical conditions for the optimal extraction of antioxidant components of ginger were investigated by applying a Box-Behnken experimental design. Extracts of ginger were prepared using water as solvent in a conventional solid-liquid extraction. The analyzed variables were time (5, 15 and 25 min), temperature (20, 55 and 90 °C) and sample concentration (2, 6 and 10 %). The antioxidant activity was measured using the 2,2-diphenyl-1-picrylhydrazyl method and a modified ferric reducing antioxidant power assay while total phenolics were measured by Folin & Ciocalteu's method. The suggested experimental design allowed the acquisition of aqueous extracts of ginger with diverse antioxidant activity (100-555 mg Trolox/100 g, 147-1237 mg Fe 2+ /100 g and 50-332 mg gallic acid/100 g). Temperature was the determining factor in the extraction of components with antioxidant activity, regardless of time and sample quantity. The optimal physical conditions that allowed the highest antioxidant activity were: 90 °C, 15 min and 2 % of the sample. The correlation value between the antioxidant activity by ferric reducing antioxidant power assay and the content of total phenolics was R 2  = 0.83. The experimental design applied allowed the determination of the physical conditions under which ginger aqueous extracts liberate compounds with antioxidant activity. Most of them are of the phenolic type as it was demonstrated through the correlation established between different methods used to measure antioxidant capacity.

Unbalanced and Minimal Point Equivalent Estimation Second-Order Split-Plot Designs

NASA Technical Reports Server (NTRS)

Parker, Peter A.; Kowalski, Scott M.; Vining, G. Geoffrey

2007-01-01

Restricting the randomization of hard-to-change factors in industrial experiments is often performed by employing a split-plot design structure. From an economic perspective, these designs minimize the experimental cost by reducing the number of resets of the hard-to- change factors. In this paper, unbalanced designs are considered for cases where the subplots are relatively expensive and the experimental apparatus accommodates an unequal number of runs per whole-plot. We provide construction methods for unbalanced second-order split- plot designs that possess the equivalence estimation optimality property, providing best linear unbiased estimates of the parameters; independent of the variance components. Unbalanced versions of the central composite and Box-Behnken designs are developed. For cases where the subplot cost approaches the whole-plot cost, minimal point designs are proposed and illustrated with a split-plot Notz design.

Sequential experimental design based generalised ANOVA

NASA Astrophysics Data System (ADS)

Chakraborty, Souvik; Chowdhury, Rajib

2016-07-01

Over the last decade, surrogate modelling technique has gained wide popularity in the field of uncertainty quantification, optimization, model exploration and sensitivity analysis. This approach relies on experimental design to generate training points and regression/interpolation for generating the surrogate. In this work, it is argued that conventional experimental design may render a surrogate model inefficient. In order to address this issue, this paper presents a novel distribution adaptive sequential experimental design (DA-SED). The proposed DA-SED has been coupled with a variant of generalised analysis of variance (G-ANOVA), developed by representing the component function using the generalised polynomial chaos expansion. Moreover, generalised analytical expressions for calculating the first two statistical moments of the response, which are utilized in predicting the probability of failure, have also been developed. The proposed approach has been utilized in predicting probability of failure of three structural mechanics problems. It is observed that the proposed approach yields accurate and computationally efficient estimate of the failure probability.

Sequential experimental design based generalised ANOVA

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

Chakraborty, Souvik, E-mail: csouvik41@gmail.com; Chowdhury, Rajib, E-mail: rajibfce@iitr.ac.in

Over the last decade, surrogate modelling technique has gained wide popularity in the field of uncertainty quantification, optimization, model exploration and sensitivity analysis. This approach relies on experimental design to generate training points and regression/interpolation for generating the surrogate. In this work, it is argued that conventional experimental design may render a surrogate model inefficient. In order to address this issue, this paper presents a novel distribution adaptive sequential experimental design (DA-SED). The proposed DA-SED has been coupled with a variant of generalised analysis of variance (G-ANOVA), developed by representing the component function using the generalised polynomial chaos expansion. Moreover,more » generalised analytical expressions for calculating the first two statistical moments of the response, which are utilized in predicting the probability of failure, have also been developed. The proposed approach has been utilized in predicting probability of failure of three structural mechanics problems. It is observed that the proposed approach yields accurate and computationally efficient estimate of the failure probability.« less

Design and Experimental Results for the S407 Airfoil

DTIC Science & Technology

2010-08-01

reduced to the inverse problem of transforming the pressure distributions into an airfoil shape. The Eppler Airfoil Design and Analysis Code (refs. 3 and...Circuit Wind Tunnel. M. S. Thesis, Pennsylvania State Univ., 1993. 3. Eppler , Richard: Airfoil Design and Data. Springer-Verlag (Berlin), 1990. 4. Eppler ...Richard: Airfoil Program System “PROFIL07.” User’s Guide. Richard Eppler , c.2007. 5. Drela, M.: Design and Optimization Method for Multi-Element

Quantum Parameter Estimation: From Experimental Design to Constructive Algorithm

NASA Astrophysics Data System (ADS)

Yang, Le; Chen, Xi; Zhang, Ming; Dai, Hong-Yi

2017-11-01

In this paper we design the following two-step scheme to estimate the model parameter ω 0 of the quantum system: first we utilize the Fisher information with respect to an intermediate variable v=\\cos ({ω }0t) to determine an optimal initial state and to seek optimal parameters of the POVM measurement operators; second we explore how to estimate ω 0 from v by choosing t when a priori information knowledge of ω 0 is available. Our optimal initial state can achieve the maximum quantum Fisher information. The formulation of the optimal time t is obtained and the complete algorithm for parameter estimation is presented. We further explore how the lower bound of the estimation deviation depends on the a priori information of the model. Supported by the National Natural Science Foundation of China under Grant Nos. 61273202, 61673389, and 61134008

Medium Optimization for the Production of Fibrinolytic Enzyme by Paenibacillus sp. IND8 Using Response Surface Methodology

PubMed Central

Prakash Vincent, Samuel Gnana

2014-01-01

Production of fibrinolytic enzyme by a newly isolated Paenibacillus sp. IND8 was optimized using wheat bran in solid state fermentation. A 25 full factorial design (first-order model) was applied to elucidate the key factors as moisture, pH, sucrose, yeast extract, and sodium dihydrogen phosphate. Statistical analysis of the results has shown that moisture, sucrose, and sodium dihydrogen phosphate have the most significant effects on fibrinolytic enzymes production (P < 0.05). Central composite design (CCD) was used to determine the optimal concentrations of these three components and the experimental results were fitted with a second-order polynomial model at 95% level (P < 0.05). Overall, 4.5-fold increase in fibrinolytic enzyme production was achieved in the optimized medium as compared with the unoptimized medium. PMID:24523635

Optimized extraction of polysaccharides from corn silk by pulsed electric field and response surface quadratic design.

PubMed

Zhao, Wenzhu; Yu, Zhipeng; Liu, Jingbo; Yu, Yiding; Yin, Yongguang; Lin, Songyi; Chen, Feng

2011-09-01

Corn silk is a traditional Chinese herbal medicine, which has been widely used for treatment of some diseases. In this study the effects of pulsed electric field on the extraction of polysaccharides from corn silk were investigated. Polysaccharides in corn silk were extracted by pulsed electric field and optimized by response surface methodology (RSM), based on a Box-Behnken design (BBD). Three independent variables, including electric field intensity (kV cm(-1) ), ratio of liquid to raw material and pulse duration (µs), were investigated. The experimental data were fitted to a second-order polynomial equation and also profiled into the corresponding 3-D contour plots. Optimal extraction conditions were as follows: electric field intensity 30 kV cm(-1) , ratio of liquid to raw material 50, and pulse duration 6 µs. Under these condition, the experimental yield of extracted polysaccharides was 7.31% ± 0.15%, matching well with the predicted value. The results showed that a pulsed electric field could be applied to extract value-added products from foods and/or agricultural matrix. Copyright © 2011 Society of Chemical Industry.

Design, Optimization, and Evaluation of Integrally-Stiffened Al-2139 Panel with Curved Stiffeners

NASA Technical Reports Server (NTRS)

Havens, David; Shiyekar, Sandeep; Norris, Ashley; Bird, R. Keith; Kapania, Rakesh K.; Olliffe, Robert

2011-01-01

A curvilinear stiffened panel was designed, manufactured, and tested in the Combined Load Test Fixture at NASA Langley Research Center. The panel is representative of a large wing engine pylon rib and was optimized for minimum mass subjected to three combined load cases. The optimization included constraints on web buckling, material yielding, crippling or local stiffener failure, and damage tolerance using a new analysis tool named EBF3PanelOpt. Testing was performed for the critical combined compression-shear loading configuration. The panel was loaded beyond initial buckling, and strains and out-of-plane displacements were extracted from a total of 20 strain gages and 6 linear variable displacement transducers. The VIC-3D system was utilized to obtain full field displacements/strains in the stiffened side of the panel. The experimental data were compared with the strains and out-of-plane deflections from a high fidelity nonlinear finite element analysis. The experimental data were also compared with linear elastic finite element results of the panel/test-fixture assembly. Overall, the panel buckled very near to the predicted load in the web regions.

Evaluation and simultaneous optimization of bio-hydrogen production using 3 2 factorial design and the desirability function

NASA Astrophysics Data System (ADS)

Cuetos, M. J.; Gómez, X.; Escapa, A.; Morán, A.

Various mixtures incorporating a simulated organic fraction of municipal solid wastes and blood from a poultry slaughterhouse were used as substrate in a dark fermentation process for the production of hydrogen. The individual and interactive effects of hydraulic retention time (HRT), solid content in the feed (%TS) and proportion of residues (%Blood) on bio-hydrogen production were studied in this work. A central composite design and response surface methodology were employed to determine the optimum conditions for the hydrogen production process. Experimental results were approximated to a second-order model with the principal effects of the three factors considered being statistically significant (P < 0.05). The production of hydrogen obtained from the experimental point at conditions close to best operability was 0.97 L Lr -1 day -1. Moreover, a desirability function was employed in order to optimize the process when a second, methanogenic, phase is coupled with it. In this last case, the optimum conditions lead to a reduction in the production of hydrogen when the optimization process involves the maximization of intermediary products.

Central composite design optimization of pilot plant fluidized-bed heterogeneous Fenton process for degradation of an azo dye.

PubMed

Aghdasinia, Hassan; Bagheri, Rasoul; Vahid, Behrouz; Khataee, Alireza

2016-11-01

Optimization of Acid Yellow 36 (AY36) degradation by heterogeneous Fenton process in a recirculated fluidized-bed reactor was studied using central composite design (CCD). Natural pyrite was applied as the catalyst characterized by X-ray diffraction and scanning electron microscopy. The CCD model was developed for the estimation of degradation efficiency as a function of independent operational parameters including hydrogen peroxide concentration (0.5-2.5 mmol/L), initial AY36 concentration (5-25 mg/L), pH (3-9) and catalyst dosage (0.4-1.2 mg/L). The obtained data from the model are in good agreement with the experimental data (R(2 )= 0.964). Moreover, this model is applicable not only to determine the optimized experimental conditions for maximum AY36 degradation, but also to find individual and interactive effects of the mentioned parameters. Finally, gas chromatography-mass spectroscopy (GC-MS) was utilized for the identification of some degradation intermediates and a plausible degradation pathway was proposed.

Media milling process optimization for manufacture of drug nanoparticles using design of experiments (DOE).

PubMed

Nekkanti, Vijaykumar; Marwah, Ashwani; Pillai, Raviraj

2015-01-01

Design of experiments (DOE), a component of Quality by Design (QbD), is systematic and simultaneous evaluation of process variables to develop a product with predetermined quality attributes. This article presents a case study to understand the effects of process variables in a bead milling process used for manufacture of drug nanoparticles. Experiments were designed and results were computed according to a 3-factor, 3-level face-centered central composite design (CCD). The factors investigated were motor speed, pump speed and bead volume. Responses analyzed for evaluating these effects and interactions were milling time, particle size and process yield. Process validation batches were executed using the optimum process conditions obtained from software Design-Expert® to evaluate both the repeatability and reproducibility of bead milling technique. Milling time was optimized to <5 h to obtain the desired particle size (d90 < 400 nm). The desirability function used to optimize the response variables and observed responses were in agreement with experimental values. These results demonstrated the reliability of selected model for manufacture of drug nanoparticles with predictable quality attributes. The optimization of bead milling process variables by applying DOE resulted in considerable decrease in milling time to achieve the desired particle size. The study indicates the applicability of DOE approach to optimize critical process parameters in the manufacture of drug nanoparticles.

Simplex optimization of headspace factors for headspace gas chromatography determination of residual solvents in pharmaceutical products.

PubMed

Grodowska, Katarzyna; Parczewski, Andrzej

2013-01-01

The purpose of the present work was to find optimum conditions of headspace gas chromatography (HS-GC) determination of residual solvents which usually appear in pharmaceutical products. Two groups of solvents were taken into account in the present examination. Group I consisted of isopropanol, n-propanol, isobutanol, n-butanol and 1,4-dioxane and group II included cyclohexane, n-hexane and n-heptane. The members of the groups were selected in previous investigations in which experimental design and chemometric methods were applied. Four factors were taken into consideration in optimization which describe HS conditions: sample volume, equilibration time, equilibrium temperature and NaCl concentration in a sample. The relative GC peak area served as an optimization criterion which was considered separately for each analyte. Sequential variable size simplex optimization strategy was used and the progress of optimization was traced and visualized in various ways simultaneously. The optimum HS conditions appeared different for the groups of solvents tested, which proves that influence of experimental conditions (factors) depends on analyte properties. The optimization resulted in significant signal increase (from seven to fifteen times).

Desynchronization of stochastically synchronized chemical oscillators

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

Snari, Razan; Tinsley, Mark R., E-mail: mark.tinsley@mail.wvu.edu, E-mail: kshowalt@wvu.edu; Faramarzi, Sadegh

Experimental and theoretical studies are presented on the design of perturbations that enhance desynchronization in populations of oscillators that are synchronized by periodic entrainment. A phase reduction approach is used to determine optimal perturbation timing based upon experimentally measured phase response curves. The effectiveness of the perturbation waveforms is tested experimentally in populations of periodically and stochastically synchronized chemical oscillators. The relevance of the approach to therapeutic methods for disrupting phase coherence in groups of stochastically synchronized neuronal oscillators is discussed.

Prediction of sonic boom from experimental near-field overpressure data. Volume 1: Method and results

NASA Technical Reports Server (NTRS)

Glatt, C. R.; Hague, D. S.; Reiners, S. J.

1975-01-01

A computerized procedure for predicting sonic boom from experimental near-field overpressure data has been developed. The procedure extrapolates near-field pressure signatures for a specified flight condition to the ground by the Thomas method. Near-field pressure signatures are interpolated from a data base of experimental pressure signatures. The program is an independently operated ODIN (Optimal Design Integration) program which obtains flight path information from other ODIN programs or from input.

Design Optimization of Irregular Cellular Structure for Additive Manufacturing

NASA Astrophysics Data System (ADS)

Song, Guo-Hua; Jing, Shi-Kai; Zhao, Fang-Lei; Wang, Ye-Dong; Xing, Hao; Zhou, Jing-Tao

2017-09-01

Irregularcellular structurehas great potential to be considered in light-weight design field. However, the research on optimizing irregular cellular structures has not yet been reporteddue to the difficulties in their modeling technology. Based on the variable density topology optimization theory, an efficient method for optimizing the topology of irregular cellular structures fabricated through additive manufacturing processes is proposed. The proposed method utilizes tangent circles to automatically generate the main outline of irregular cellular structure. The topological layoutof each cellstructure is optimized using the relative density informationobtained from the proposed modified SIMP method. A mapping relationship between cell structure and relative densityelement is builtto determine the diameter of each cell structure. The results show that the irregular cellular structure can be optimized with the proposed method. The results of simulation and experimental test are similar for irregular cellular structure, which indicate that the maximum deformation value obtained using the modified Solid Isotropic Microstructures with Penalization (SIMP) approach is lower 5.4×10-5 mm than that using the SIMP approach under the same under the same external load. The proposed research provides the instruction to design the other irregular cellular structure.

LED light design method for high contrast and uniform illumination imaging in machine vision.

PubMed

Wu, Xiaojun; Gao, Guangming

2018-03-01

In machine vision, illumination is very critical to determine the complexity of the inspection algorithms. Proper lights can obtain clear and sharp images with the highest contrast and low noise between the interested object and the background, which is conducive to the target being located, measured, or inspected. Contrary to the empirically based trial-and-error convention to select the off-the-shelf LED light in machine vision, an optimization algorithm for LED light design is proposed in this paper. It is composed of the contrast optimization modeling and the uniform illumination technology for non-normal incidence (UINI). The contrast optimization model is built based on the surface reflection characteristics, e.g., the roughness, the reflective index, and light direction, etc., to maximize the contrast between the features of interest and the background. The UINI can keep the uniformity of the optimized lighting by the contrast optimization model. The simulation and experimental results demonstrate that the optimization algorithm is effective and suitable to produce images with the highest contrast and uniformity, which is very inspirational to the design of LED illumination systems in machine vision.

Optimization of lipids production by Cryptococcus laurentii 11 using cheese whey with molasses.

PubMed

Castanha, Rodrigo Fernandes; Mariano, Adriano Pinto; de Morais, Lilia Aparecida Salgado; Scramin, Shirlei; Monteiro, Regina Teresa Rosim

2014-01-01

This study aimed the optimization of culture condition and composition for production of Cryptococcus laurentii 11 biomass and lipids in cheese whey medium supplemented with sugarcane molasses. The optimization of pH, fermentation time, and molasses concentration according to a full factorial statistical experimental design was followed by a Plackett-Burman experimental design, which was used to determine whether the supplementation of the culture medium by yeast extract and inorganic salts could provide a further enhancement of lipids production. The following conditions and composition of the culture medium were found to optimize biomass and lipids production: 360 h fermentation, 6.5 pH and supplementation of (g L(-1)): 50 molasses, 0.5 yeast extract, 4 KH2PO4, 1 Na2HPO4, 0.75 MgSO4 · 7H2O and 0.002 ZnSO4 · H2O. Additional supplementation with inorganic salts and yeast extract was essential to optimize the production, in terms of product concentration and productivity, of neutral lipids by C. laurentii 11. Under this optimized condition, the production of total lipids increased by 133% in relation to control experiment (from 1.27 to 2.96 g L(-1)). The total lipids indicated a predominant (86%) presence of neutral lipids with high content of 16- and 18-carbon-chain saturated and monosaturated fatty acids. This class of lipids is considered especially suitable for the production of biodiesel.

[Simultaneous desulfurization and denitrification by TiO2/ACF under different irradiation].

PubMed

Han, Jing; Zhao, Yi

2009-04-15

The supported TiO2 photocatalysts were prepared in laboratory, and the experiments of simultaneous desulfurization and denitrification were carried out by self-designed photocatalysis reactor. The optimal experimental conditions were achieved, and the efficiencies of simultaneous desulfurization and denitrification under two different light sources were compared. The results show that the oxygen content of flue gas, reaction temperature, flue gas humidity and irradiation intensity are most essential factors to photocatalysis. For TiO2/ACF, the removal efficiencies of 99.7% for SO2 and 64.3% for NO are obtained respectively at optimal experimental conditions under UV irradiation. For TiO2/ACF, the removal efficiencies of 97.5% for SO2 and 49.6% for NO are achieved respectively at optimal experimental conditions under the visible light irradiation. The results of five times parallel experiments indicate standard deviation S of parallel data is little. The mechanism of removal for SO2 and NO is proposed under two light sources by ion chromatography analysis of the absorption liquid.

A general framework for multicharacter segmentation and its application in recognizing multilingual Asian documents

NASA Astrophysics Data System (ADS)

Wen, Di; Ding, Xiaoqing

2003-12-01

In this paper we propose a general framework for character segmentation in complex multilingual documents, which is an endeavor to combine the traditionally separated segmentation and recognition processes into a cooperative system. The framework contains three basic steps: Dissection, Local Optimization and Global Optimization, which are designed to fuse various properties of the segmentation hypotheses hierarchically into a composite evaluation to decide the final recognition results. Experimental results show that this framework is general enough to be applied in variety of documents. A sample system based on this framework to recognize Chinese, Japanese and Korean documents and experimental performance is reported finally.

Optimization of chiral structures for microscale propulsion.

PubMed

Keaveny, Eric E; Walker, Shawn W; Shelley, Michael J

2013-02-13

Recent advances in micro- and nanoscale fabrication techniques allow for the construction of rigid, helically shaped microswimmers that can be actuated using applied magnetic fields. These swimmers represent the first steps toward the development of microrobots for targeted drug delivery and minimally invasive surgical procedures. To assess the performance of these devices and improve on their design, we perform shape optimization computations to determine swimmer geometries that maximize speed in the direction of a given applied magnetic torque. We directly assess aspects of swimmer shapes that have been developed in previous experimental studies, including helical propellers with elongated cross sections and attached payloads. From these optimizations, we identify key improvements to existing designs that result in swimming speeds that are 70-470% of their original values.

Optimizing laboratory animal stress paradigms: The H-H* experimental design.

PubMed

McCarty, Richard

2017-01-01

Major advances in behavioral neuroscience have been facilitated by the development of consistent and highly reproducible experimental paradigms that have been widely adopted. In contrast, many different experimental approaches have been employed to expose laboratory mice and rats to acute versus chronic intermittent stress. An argument is advanced in this review that more consistent approaches to the design of chronic intermittent stress experiments would provide greater reproducibility of results across laboratories and greater reliability relating to various neural, endocrine, immune, genetic, and behavioral adaptations. As an example, the H-H* experimental design incorporates control, homotypic (H), and heterotypic (H*) groups and allows for comparisons across groups, where each animal is exposed to the same stressor, but that stressor has vastly different biological and behavioral effects depending upon each animal's prior stress history. Implementation of the H-H* experimental paradigm makes possible a delineation of transcriptional changes and neural, endocrine, and immune pathways that are activated in precisely defined stressor contexts. Copyright © 2016 Elsevier Ltd. All rights reserved.

A simplified design of the staggered herringbone micromixer for practical applications

PubMed Central

Du, Yan; Zhang, Zhiyi; Yim, ChaeHo; Lin, Min; Cao, Xudong

2010-01-01

We demonstrated a simple method for the device design of a staggered herringbone micromixer (SHM) using numerical simulation. By correlating the simulated concentrations with channel length, we obtained a series of concentration versus channel length profiles, and used mixing completion length Lm as the only parameter to evaluate the performance of device structure on mixing. Fluorescence quenching experiments were subsequently conducted to verify the optimized SHM structure for a specific application. Good agreement was found between the optimization and the experimental data. Since Lm is straightforward, easily defined and calculated parameter for characterization of mixing performance, this method for designing micromixers is simple and effective for practical applications. PMID:20697584

A simplified design of the staggered herringbone micromixer for practical applications.

PubMed

Du, Yan; Zhang, Zhiyi; Yim, Chaeho; Lin, Min; Cao, Xudong

2010-05-07

We demonstrated a simple method for the device design of a staggered herringbone micromixer (SHM) using numerical simulation. By correlating the simulated concentrations with channel length, we obtained a series of concentration versus channel length profiles, and used mixing completion length L(m) as the only parameter to evaluate the performance of device structure on mixing. Fluorescence quenching experiments were subsequently conducted to verify the optimized SHM structure for a specific application. Good agreement was found between the optimization and the experimental data. Since L(m) is straightforward, easily defined and calculated parameter for characterization of mixing performance, this method for designing micromixers is simple and effective for practical applications.

Optimized structural designs for stretchable silicon integrated circuits.

PubMed

Kim, Dae-Hyeong; Liu, Zhuangjian; Kim, Yun-Soung; Wu, Jian; Song, Jizhou; Kim, Hoon-Sik; Huang, Yonggang; Hwang, Keh-Chih; Zhang, Yongwei; Rogers, John A

2009-12-01

Materials and design strategies for stretchable silicon integrated circuits that use non-coplanar mesh layouts and elastomeric substrates are presented. Detailed experimental and theoretical studies reveal many of the key underlying aspects of these systems. The results shpw, as an example, optimized mechanics and materials for circuits that exhibit maximum principal strains less than 0.2% even for applied strains of up to approximately 90%. Simple circuits, including complementary metal-oxide-semiconductor inverters and n-type metal-oxide-semiconductor differential amplifiers, validate these designs. The results suggest practical routes to high-performance electronics with linear elastic responses to large strain deformations, suitable for diverse applications that are not readily addressed with conventional wafer-based technologies.

Optimization of Culture Conditions for Production of the Anti-Leukemic Glutaminase Free L-Asparaginase by Newly Isolated Streptomyces olivaceus NEAE-119 Using Response Surface Methodology.

PubMed

El-Naggar, Noura El-Ahmady; Moawad, Hassan; El-Shweihy, Nancy M; El-Ewasy, Sara M

2015-01-01

Among the antitumor drugs, bacterial enzyme L-asparaginase has been employed as the most effective chemotherapeutic agent in pediatric oncotherapy especially for acute lymphoblastic leukemia. Glutaminase free L-asparaginase producing actinomycetes were isolated from soil samples collected from Egypt. Among them, a potential culture, strain NEAE-119, was selected and identified on the basis of morphological, cultural, physiological, and biochemical properties together with 16S rRNA sequence as Streptomyces olivaceus NEAE-119 and sequencing product (1509 bp) was deposited in the GenBank database under accession number KJ200342. The optimization of different process parameters for L-asparaginase production by Streptomyces olivaceus NEAE-119 using Plackett-Burman experimental design and response surface methodology was carried out. Fifteen variables (temperature, pH, incubation time, inoculum size, inoculum age, agitation speed, dextrose, starch, L-asparagine, KNO3, yeast extract, K2HPO4, MgSO4·7H2O, NaCl, and FeSO4·7H2O) were screened using Plackett-Burman experimental design. The most positive significant independent variables affecting enzyme production (temperature, inoculum age, and agitation speed) were further optimized by the face-centered central composite design-response surface methodology.

Optimization of Culture Conditions for Production of the Anti-Leukemic Glutaminase Free L-Asparaginase by Newly Isolated Streptomyces olivaceus NEAE-119 Using Response Surface Methodology

PubMed Central

El-Naggar, Noura El-Ahmady; Moawad, Hassan; El-Shweihy, Nancy M.; El-Ewasy, Sara M.

2015-01-01

Among the antitumor drugs, bacterial enzyme L-asparaginase has been employed as the most effective chemotherapeutic agent in pediatric oncotherapy especially for acute lymphoblastic leukemia. Glutaminase free L-asparaginase producing actinomycetes were isolated from soil samples collected from Egypt. Among them, a potential culture, strain NEAE-119, was selected and identified on the basis of morphological, cultural, physiological, and biochemical properties together with 16S rRNA sequence as Streptomyces olivaceus NEAE-119 and sequencing product (1509 bp) was deposited in the GenBank database under accession number KJ200342. The optimization of different process parameters for L-asparaginase production by Streptomyces olivaceus NEAE-119 using Plackett-Burman experimental design and response surface methodology was carried out. Fifteen variables (temperature, pH, incubation time, inoculum size, inoculum age, agitation speed, dextrose, starch, L-asparagine, KNO3, yeast extract, K2HPO4, MgSO4·7H2O, NaCl, and FeSO4·7H2O) were screened using Plackett-Burman experimental design. The most positive significant independent variables affecting enzyme production (temperature, inoculum age, and agitation speed) were further optimized by the face-centered central composite design-response surface methodology. PMID:26180806

Use of response surface methodology in a fed-batch process for optimization of tricarboxylic acid cycle intermediates to achieve high levels of canthaxanthin from Dietzia natronolimnaea HS-1.

PubMed

Nasri Nasrabadi, Mohammad Reza; Razavi, Seyed Hadi

2010-04-01

In this work, we applied statistical experimental design to a fed-batch process for optimization of tricarboxylic acid cycle (TCA) intermediates in order to achieve high-level production of canthaxanthin from Dietzia natronolimnaea HS-1 cultured in beet molasses. A fractional factorial design (screening test) was first conducted on five TCA cycle intermediates. Out of the five TCA cycle intermediates investigated via screening tests, alfaketoglutarate, oxaloacetate and succinate were selected based on their statistically significant (P<0.05) and positive effects on canthaxanthin production. These significant factors were optimized by means of response surface methodology (RSM) in order to achieve high-level production of canthaxanthin. The experimental results of the RSM were fitted with a second-order polynomial equation by means of a multiple regression technique to identify the relationship between canthaxanthin production and the three TCA cycle intermediates. By means of this statistical design under a fed-batch process, the optimum conditions required to achieve the highest level of canthaxanthin (13172 + or - 25 microg l(-1)) were determined as follows: alfaketoglutarate, 9.69 mM; oxaloacetate, 8.68 mM; succinate, 8.51 mM. Copyright 2009 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

The Challenge of Reproducibility and Accuracy in Nutrition Research: Resources and Pitfalls1234

PubMed Central

Kuszak, Adam J; Williamson, John S; Hopp, D Craig; Betz, Joseph M

2016-01-01

Inconsistent and contradictory results from nutrition studies conducted by different investigators continue to emerge, in part because of the inherent variability of natural products, as well as the unknown and therefore uncontrolled variables in study populations and experimental designs. Given these challenges inherent in nutrition research, it is critical for the progress of the field that researchers strive to minimize variability within studies and enhance comparability between studies by optimizing the characterization, control, and reporting of products, reagents, and model systems used, as well as the rigor and reporting of experimental designs, protocols, and data analysis. Here we describe some recent developments relevant to research on plant-derived products used in nutrition research, highlight some resources for optimizing the characterization and reporting of research using these products, and describe some of the pitfalls that may be avoided by adherence to these recommendations. PMID:26980822

Effect and interaction study of acetamiprid photodegradation using experimental design.

PubMed

Tassalit, Djilali; Chekir, Nadia; Benhabiles, Ouassila; Mouzaoui, Oussama; Mahidine, Sarah; Merzouk, Nachida Kasbadji; Bentahar, Fatiha; Khalil, Abbas

2016-10-01

The methodology of experimental research was carried out using the MODDE 6.0 software to study the acetamiprid photodegradation depending on the operating parameters, such as the initial concentration of acetamiprid, concentration and type of the used catalyst and the initial pH of the medium. The results showed the importance of the pollutant concentration effect on the acetamiprid degradation rate. On the other hand, the amount and type of the used catalyst have a considerable influence on the elimination kinetics of this pollutant. The degradation of acetamiprid as an environmental pesticide pollutant via UV irradiation in the presence of titanium dioxide was assessed and optimized using response surface methodology with a D-optimal design. The acetamiprid degradation ratio was found to be sensitive to the different studied factors. The maximum value of discoloration under the optimum operating conditions was determined to be 99% after 300 min of UV irradiation.

Gaussian process surrogates for failure detection: A Bayesian experimental design approach

NASA Astrophysics Data System (ADS)

Wang, Hongqiao; Lin, Guang; Li, Jinglai

2016-05-01

An important task of uncertainty quantification is to identify the probability of undesired events, in particular, system failures, caused by various sources of uncertainties. In this work we consider the construction of Gaussian process surrogates for failure detection and failure probability estimation. In particular, we consider the situation that the underlying computer models are extremely expensive, and in this setting, determining the sampling points in the state space is of essential importance. We formulate the problem as an optimal experimental design for Bayesian inferences of the limit state (i.e., the failure boundary) and propose an efficient numerical scheme to solve the resulting optimization problem. In particular, the proposed limit-state inference method is capable of determining multiple sampling points at a time, and thus it is well suited for problems where multiple computer simulations can be performed in parallel. The accuracy and performance of the proposed method is demonstrated by both academic and practical examples.

Selective Acidic Leaching of Spent Zinc-Carbon Batteries Followed by Zinc Electrowinning

NASA Astrophysics Data System (ADS)

Shalchian, Hossein; Rafsanjani-Abbasi, Ali; Vahdati-Khaki, Jalil; Babakhani, Abolfazl

2015-02-01

In this work, a selective acidic leaching procedure was employed for recycling zinc from spent zinc-carbon batteries. Leaching experiments were carried out in order to maximize zinc recovery and minimize manganese recovery in diluted sulfuric acid media. Response surface methodology and analysis of variance were employed for experimental design, data analysis, and leaching optimization. The experimental design has 28 experiments that include 24 main runs and four replicate in center point. The optimal conditions obtained from the selective acidic leaching experiments, were sulfuric acid concentration of 1 pct v/v, leaching temperature of 343 K (70 °C), pulp density of 8 pct w/v, and stirring speed of 300 rpm. The results show that the zinc and manganese recoveries after staged selective leaching are about 92 and 15 pct, respectively. Finally, metallic zinc with purity of 99.9 pct and electrolytic manganese dioxide were obtained by electrowinning.

Note: Ultrasonic gas flowmeter based on optimized time-of-flight algorithms

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

Wang, X. F.; Tang, Z. A.

2011-04-15

A new digital signal processor based single path ultrasonic gas flowmeter is designed, constructed, and experimentally tested. To achieve high accuracy measurements, an optimized ultrasound driven method of incorporation of the amplitude modulation and the phase modulation of the transmit-receive technique is used to stimulate the transmitter. Based on the regularities among the received envelope zero-crossings, different received signal's signal-to-noise ratio situations are discriminated and optional time-of-flight algorithms are applied to take flow rate calculations. Experimental results from the dry calibration indicate that the designed flowmeter prototype can meet the zero-flow verification test requirements of the American Gas Association Reportmore » No. 9. Furthermore, the results derived from the flow calibration prove that the proposed flowmeter prototype can measure flow rate accurately in the practical experiments, and the nominal accuracies after FWME adjustment are lower than 0.8% throughout the calibration range.« less

Model Selection in Systems Biology Depends on Experimental Design

PubMed Central

Silk, Daniel; Kirk, Paul D. W.; Barnes, Chris P.; Toni, Tina; Stumpf, Michael P. H.

2014-01-01

Experimental design attempts to maximise the information available for modelling tasks. An optimal experiment allows the inferred models or parameters to be chosen with the highest expected degree of confidence. If the true system is faithfully reproduced by one of the models, the merit of this approach is clear - we simply wish to identify it and the true parameters with the most certainty. However, in the more realistic situation where all models are incorrect or incomplete, the interpretation of model selection outcomes and the role of experimental design needs to be examined more carefully. Using a novel experimental design and model selection framework for stochastic state-space models, we perform high-throughput in-silico analyses on families of gene regulatory cascade models, to show that the selected model can depend on the experiment performed. We observe that experimental design thus makes confidence a criterion for model choice, but that this does not necessarily correlate with a model's predictive power or correctness. Finally, in the special case of linear ordinary differential equation (ODE) models, we explore how wrong a model has to be before it influences the conclusions of a model selection analysis. PMID:24922483

Model selection in systems biology depends on experimental design.

PubMed

Silk, Daniel; Kirk, Paul D W; Barnes, Chris P; Toni, Tina; Stumpf, Michael P H

2014-06-01

Experimental design attempts to maximise the information available for modelling tasks. An optimal experiment allows the inferred models or parameters to be chosen with the highest expected degree of confidence. If the true system is faithfully reproduced by one of the models, the merit of this approach is clear - we simply wish to identify it and the true parameters with the most certainty. However, in the more realistic situation where all models are incorrect or incomplete, the interpretation of model selection outcomes and the role of experimental design needs to be examined more carefully. Using a novel experimental design and model selection framework for stochastic state-space models, we perform high-throughput in-silico analyses on families of gene regulatory cascade models, to show that the selected model can depend on the experiment performed. We observe that experimental design thus makes confidence a criterion for model choice, but that this does not necessarily correlate with a model's predictive power or correctness. Finally, in the special case of linear ordinary differential equation (ODE) models, we explore how wrong a model has to be before it influences the conclusions of a model selection analysis.

Finite Element Analysis and Optimization of Flexure Bearing for Linear Motor Compressor

NASA Astrophysics Data System (ADS)

Khot, Maruti; Gawali, Bajirao

Nowadays linear motor compressors are commonly used in miniature cryocoolers instead of rotary compressors because rotary compressors apply large radial forces to the piston, which provide no useful work, cause large amount of wear and usually require lubrication. Recent trends favour flexure supported configurations for long life. The present work aims at designing and geometrical optimization of flexure bearings using finite element analysis and the development of design charts for selection purposes. The work also covers the manufacturing of flexures using different materials and the validation of the experimental finite element analysis results.

Chronic behavior evaluation of a micro-machined neural implant with optimized design based on an experimentally derived model.

PubMed

Andrei, Alexandru; Welkenhuysen, Marleen; Ameye, Lieveke; Nuttin, Bart; Eberle, Wolfgang

2011-01-01

Understanding the mechanical interactions between implants and the surrounding tissue is known to have an important role for improving the bio-compatibility of such devices. Using a recently developed model, a particular micro-machined neural implant design aiming the reduction of insertion forces dependence on the insertion speed was optimized. Implantations with 10 and 100 μm/s insertion speeds showed excellent agreement with the predicted behavior. Lesion size, gliosis (GFAP), inflammation (ED1) and neuronal cells density (NeuN) was evaluated after 6 week of chronic implantation showing no insertion speed dependence.

Integrated optical design for highly dynamic laser beam shaping with membrane deformable mirrors

NASA Astrophysics Data System (ADS)

Pütsch, Oliver; Stollenwerk, Jochen; Loosen, Peter

2017-02-01

The utilization of membrane deformable mirrors has raised its importance in laser materials processing since they enable the generation of highly spatial and temporal dynamic intensity distributions for a wide field of applications. To take full advantage of these devices for beam shaping, the huge amount of degrees of freedom has to be considered and optimized already within the early stage of the optical design. Since the functionality of commercial available ray-tracing software has been mainly specialized on geometric dependencies and their optimization within constraints, the complex system characteristics of deformable mirrors cannot be sufficiently taken into account yet. The main reasons are the electromechanical interdependencies of electrostatic membrane deformable mirrors, namely saturation and mechanical clamping, that result in non-linear deformation. This motivates the development of an integrative design methodology. The functionality of the ray-tracing program ZEMAX is extended with a model of an electrostatic membrane mirror. This model is based on experimentally determined influence functions. Furthermore, software routines are derived and integrated that allow for the compilation of optimization criteria for the most relevant analytically describable beam shaping problems. In this way, internal optimization routines can be applied for computing the appropriate membrane deflection of the deformable mirror as well as for the parametrization of static optical components. The experimental verification of simulated intensity distributions demonstrates that the beam shaping properties can be predicted with a high degree of reliability and precision.