Statistical Design Of Experiments Approach Research Articles

Development of Chemically Defined Media Supporting High-Cell-Density Growth of Lactococci, Enterococci, and Streptococci

Lactococcus lactis IL1403 was used as an experimental strain to develop a chemically defined medium for study of the physiology and metabolic pathways of lactococci. An experimental leave-one-out technique was employed to determine the necessity of each of the 57 chemical components used in medium development. A statistical experimental design approach including three fractional factorial designs and a central composite design was used to optimize the fermentation process with 21 variables composed of 19 nutritional factors grouped from the 57 components and two environmental factors (initial pH and temperature). For L. lactis IL1403, the maximum biomass concentrations obtained with the two optimal chemically defined media developed in this study (ZMB1 and ZMB2) were generally 3.5- to 4-fold higher than the maximum biomass concentrations obtained with the previously described best synthetic media (SA) and 50% to 68% higher than the maximum biomass concentrations obtained with M17, a complex medium commonly used for lactococci. The new chemically defined media support high-cell-density growth of numerous strains of L. lactis, Enterococcus faecalis, and Streptococcus thermophilus.

Optimization of the synthesis of 1-allyloxy-2-hydroxy-propyl-starch through statistical experimental design

The synthesis of 1-allyloxy-2-hydroxy-propyl starches was studied using a statistical experimental design approach. The etherification of two different granular maize starches with allyl glycidyl ether (AGE) in a heterogeneous alkaline suspension was investigated. The optimal reaction conditions were found via experimental design and the obtained response factor, e.g. the degree of substitution (DS) of the starch hydroxyl group, was statistically evaluated. The effects of six process factors on DS, namely the starch concentration, the reaction time, the temperature, and the amount of NaOH, Na 2SO 4 and AGE were investigated. The statistical analysis showed significant impact of the temperature, the amount of NaOH and the amount of AGE on the DS for both starches. Optimum conditions for the highest DS for waxy maize starch were: 0.0166% AGE (based on dry starch (ds)) and 1.0% NaOH (ds) at 34 °C in 4 h; on dent maize starch, these were 0.0099% AGE (ds) and 1.0% NaOH (ds) at 37 °C in 16 h.

Risk Assessment of Oil Fields Using Proxy Models: A Case Study

Abstract Reservoir studies commonly consider many scenarios, cases and realizations. However, reservoir simulation can be expensive. Statistical design has been used in reservoir engineering applications, including performance prediction, uncertainty modelling, sensitivity studies, upscaling, history matching and development optimization. If reservoir simulation studies are conducted with a statistical design, response surface models can estimate how the variation of input factors affects reservoir behaviour with a relatively small number of reservoir simulation models. In petroleum exploration and production, a decision has to consider the risk involved in the process which can be obtained by quantifying the impact of uncertainties on the performance of the petroleum field in question. The process is even more critical because most of the investments are realized during the phase in which the uncertainties are greater. The statistical design is efficient to quantify the impact of the uncertainties of the reservoirs in the production forecast and to reduce the number of simulations to obtain the risk curve. The main objective of this work is the application of the statistical design: Box-Behnken and Central Composite Design using different attributes ranges. To compare the precision of the results, different techniques are used. These are the Derivative Tree Technique by simulation flow, the Monte Carlo Technique and the Response Surface Methodology. Introduction In petroleum exploration and production, a decision has to consider the risk involved in the process(1). Decision and risk analysis can be integrated with a wide variety of engineering and economic applications in the oil and gas industry, including economic evaluation of oil and gas reserves, reservoir modelling and simulation, seismic interpretation, petrophysical analysis and others(2). Decision analysis applied to petroleum field development plans are always strongly related to risk due to the uncertainties present in the process. There are many uncertainties that can influence the success of an E&P project. The most common uncertainties are due to the geological model, the recovery factor and the economic model(3). Quantification of uncertainty in reservoir performance is an important part of proper economic evaluation. The uncertainty in our understanding of a given reservoir performance arises from the uncertainty in the information we have about the attributes that control reservoir performance (permeability, oil water contact, etc.). In a risk methodology, it is possible to combine the geological uncertainties by using the Monte Carlo technique to estimate the range of uncertainty of some objective functions. These values can be obtained through numerical simulation flow or proxy models. The statistical theory, and especially the statistical (experimental) design approach, is well-suited to determine the most uncertain parameters to evaluate the impact of uncertainty on production forecasts, and to help making decisions during the reservoir's development(4). If reservoir simulation studies are conducted with a statistical design, response surface models can estimate how the variation of input attributes affects reservoir behaviour with a relatively small number of reservoir simulation models. Response surface models can test the relative importance of the attributes statistically(5). Because response surfaces are accurate and simple to evaluate, they are efficient proxies for reservoir simulators.

Performance characterization of III–V power devices

The power performance of GaAs/AlGaAs pseudomorphic high electron mobility transistors (PHEMTs) has been modeled by using the statistical Design of Experiment approach. Empirical models for the small signal gain, output power and power added efficiency have been developed. The “walk-out/in” phenomenon has been observed in the devices as a result of power measurements. The evolution of surface photovoltage spectra after RF power stress indicates accumulation of positive electrical charge in the buffer and the surface layer of the devices.

A statistical experiment design approach for advanced oxidation of Direct Red azo-dye by photo-Fenton treatment

Advanced oxidation of an azo-dye, Direct Red 28 (DR 28) by photo-Fenton treatment was investigated in batch experiments using Box–Behnken statistical experiment design and the response surface analysis. Dyestuff (DR 28), H 2O 2 and Fe(II) concentrations were selected as independent variables in Box–Behnken design while color and total organic carbon (TOC) removal (mineralization) were considered as the response functions. Color removal increased with increasing H 2O 2 and Fe(II) concentrations up to a certain level. High concentrations of H 2O 2 and Fe(II) adversely affected the color and TOC removals due to hydroxyl radical scavenging effects of high oxidant and catalyst concentrations. Both H 2O 2 and Fe(II) concentration had profound effects on decolorization. Percent color removal was higher than TOC removal indicating formation of colorless organic intermediates. Complete color removal was achieved within 5 min while complete mineralization took nearly 15 min. The optimal reagent doses varied depending on the initial dyestuff dose. For the highest dyestuff concentration tested, the optimal H 2O 2/Fe(II)/dyestuff ratio resulting in the maximum color removal (100%) was predicted to be 715/71/250 (mg L −1), while this ratio was 1550/96.5/250 for maximum mineralization (97.5%).

An orthogonal design of experiment/exploratory data analysis for plutonium contamination

This paper describes a statistical-experimental design approach for identifying sources of Pu contamination in the radioactivity material analysis of dried shellfish at the National Institute of Standards and Technology (NIST). Identification and elimination of sources of contamination were required for certifications of the radioactivity concentration of actinides in the proposed reference material. Sources of contamination included the fume hood, glassware, and reagents. The experimental design employed reduced number of required experiments by a factor of 100. The result is an orthogonal design of experiment (ODEX) and subsequent data was analyzed using Exploratory Date Analysis (EDA), which narrowed the 200+ experiments to a manageable 16. This design made it possible to identify the sources and interactions of sources of contamination in a timely and cost effective manner.

Biohydrogen production by dark fermentation of wheat powder solution: Effects of C/N and C/P ratio on hydrogen yield and formation rate

The effects of C/N and C/P ratio on hydrogen yield and specific production rate were investigated in dark fermentation of wheat powder solution (WPS) by external addition of N and P since the wheat powder was N and P deficient. A Box–Wilson statistical experiment design approach was used. C/N ratio was varied between 20 and 200 while C/P ratio was between 50 and 1000. A quadratic response function was used to correlate the objective functions with the independent variables and the response function coefficients were determined by regression analysis. Hydrogen yield increased with increasing C/N and C/P ratios. Low nitrogen concentrations required low phosphorous contents for high hydrogen yields. A C/N ratio of 200 and C/P ratio of 1000 yielded the highest H 2 yield of 281 ml H 2 g - 1 starch at STP. SHPR also increased with increasing C/N and C/P ratios. Again the highest SHPR ( 98 ml H 2 g - 1 biomass h - 1 at STP) was obtained at C/N and C/P ratios of 200 and 1000, respectively. The C/N/P ratio maximizing the yield and formation rate of hydrogen was 100/0.5/0.1 ( w w - 1 w - 1 ) .

Transform coding of monochrome images with a statistical design of experiments approach to separate noise

A new transform coding technique based on a set of orthogonal polynomials has been proposed in this paper. In the transformed domain, statistical design of experiments approach is used to separate the spatial variation due to discriminable low level features (signals) from the spatial variation due to an unexplained source called noise. The proposed polynomial transform has a low computational complexity because it is configured as an integer transform. The proposed transform also has very good compression ability or separationability. The degree of this separationability can be controlled by specifying the level of the signal-to-noise ratio.

Examination of a Grit-Blasting Process for Thermal Spraying Using Statistical Methods

An experimental study was conducted to develop an understanding of how the grit blasting process, prior to plasma spray coating, affects various properties of the substrate and coatings. A statistical design of experiment approach was used and the results were analyzed using both the linear regression method and average response of factors calculations. The following process variables were studied: grit size (20, 36, 54), blasting pressure (20, 35, 50 psi), blasting duration (4, 6, 8 passes), blasting distance (4, 6 in.), and blasting angle (45°, 90°). Properties such as bond strength, grit contamination, surface roughness, and substrate distortion were evaluated and correlated to the process variables. Based on multiple linear regression results, it was shown that the bond strength can be improved by increasing all of the parameters within the range studied here. No relationship between the surface roughness and bond strength was observed. Grit contamination is mostly influenced by grit size, blasting pressure, and number of blasting passes. The average response method provided indications to the direction of modifying the required properties as a function of process variables. While the average response method agreed mostly with the linear regression predication, some differences are further discussed in the study.

Diels−Alder Trapping of Photochemically Generated o-Quinodimethane Intermediates: An Alternative Route to Photocured Polymer Film Development

Photolysis of o-methylphenyl ketones generates bis-o-quinodimethane intermediates that can be trapped in situ by dienophiles through Diels-Alder cycloadditions. This well-known photochemical process is applied to a series of six new photoreactive monomers containing bis-(o-methylphenyl ketone) functionalities combined with diacrylate and triacrylate ester monomers for the development of acrylic ester copolymer blends. Irradiation of cyclohexanone solutions of the bis-(o-methylphenyl ketone)s and acrylate esters produce thin polymer films. Solid state 13C NMR data indicated 47- 100% reaction of the bis-(o-methylphenyl ketone)s, depending on experimental conditions, to yield the desired products. DSC and TGA analyses were performed to determine the glass transition temperature, T,, and onset of decomposition, Td, of the resulting polymer films. A statistical Design of Experiments approach was used to obtain a systematic understanding of the effects of experimental variables on the extent of polymerization and the final polymer properties.

Errors associated with swelling in the analysis of polymer–solvent diffusion measurements

Sorption curves are generated from a mathematical model which includes the influence of the polymer swelling for unsteady-state sorption of a vapor or liquid by a polymer. To investigate the simultaneous effects of the specific volumes of the polymer–penetrant pair and the difference between the final and initial equilibrium concentrations on the sorption curves, statistical experimental design approach is used. Simulation results obtained from the numerical solution of model equations are utilized to estimate the error that would occur if one simply evaluates the diffusion coefficient using the traditional formulas derived from the analytical solution of the sorption equation. An empirical expression is developed that describes the effects of the difference between the final and initial equilibrium concentrations and the specific volumes of the polymer and the penetrant on the magnitude of error in diffusivity associated with the use of one of these traditional formulas so called the initial slope method. The predictive ability of the regression model is tested by performing additional simulations not used in the regression analysis.

Statistical experimental design of protein crystallization screening revisited.

A statistical experimental design approach was used to prepare a set of solutions for the screening of protein crystallization conditions. This approach is shown to be amenable to quantitative evaluation and therefore to the rational optimization of the screening results. All solutions contain a cryoprotectant, thus eliminating the need for subsequent optimization of crystal freezing conditions.

Statistical experimental design of Al–Cu–Mg–Si P/M alloys

The principle that alloys are designed to accommodate the manufacture of goods made from them as much as the properties required of them in service has not been widely applied to pressed and sintered P/M aluminium alloys. Most commercial alloys made from mixed elemental blends are identical to standard wrought alloys. Here we use a statistical design of experiment approach to re-evaluate the composition spectrum of the 2xxx alloys. Copper has the major influence on the tensile properties. Magnesium and silicon do effect some properties, but to a lesser extent. The major value of magnesium is breaking up the surface oxide layer. Conversely, an extensive secondary pore network develops from excess magnesium and this severely limits the ductility. Hard intermetallic particles, which are a residue of the sintering liquid, also reduce the tensile ductility. The tensile strength is limited by the low ductility, which is related to the equilibrium liquid volume at the sintering temperature, as well as the sintered density.

Limitations of Statistical Design of Experiments Approaches in Engineering Testing

A hypothetical experiment and Monte Carlo simulations were used to examine the effectiveness of statistical design of experiments methods in identifying from the experimental data the correct terms in postulated regression models for a variety of experimental conditions. Two analysis of variance techniques (components of variance and pooled mean square error) combined with F-test statistics were investigated with first-order and second-order regression models. It was concluded that there are experimental conditions for which one or the other of the procedures results in model identification with high confidence, but there are also other conditions in which neither procedure is successful. The ability of the statistical approaches to identify the correct models varies so drastically, depending on experimental conditions, that it seems unlikely that arbitrarily choosing a method and applying it will lead to identification of the effects that are significant with a reasonable degree of confidence. It is concluded that before designing and conducting an experiment, one should use simulations of the proposed experiment with postulated truths in order to determine which statistical design of experiments approach, if any, will identify the correct model from the experimental data with an acceptable degree of confidence. In addition, no significant change in the effectiveness of the methods in identifying the correct model was observed when systematic uncertainties of up to 10 percent in the independent variables and in the response were introduced into the simulations. An explanation is that the systematic errors in the simulation data caused a shift of the whole response surface up or down from the true value, without a significant change in shape. [S0098-2202(00)03102-3]

Low-temperature aqueous synthesis (LTAS) of BaTiO 3: a statistical design of experiment approach

The effect of a selected number of parameters of the Low-Temperature Aqueous Synthesis (LTAS) on BaTiO 3 particle size was investigated by the statistical design of experiment approach. Different syntheses were carried out changing the value of six physico-chemical parameters involved in the process, following the scheme of a 2 6-2 fractional factorial design. The characterisation of the submicron powders produced shows variations of the average size in the range 30–55 nm, deduced from specific surface area measurements. The statistical analysis of experimental results, performed by the ANOVA method, allows to ascribe such variations to the effect of solutions concentration, stirring energy and precursors mixing conditions. The significance of such parameters, together with the apparent ineffectiveness of the ageing time, is discussed. Also the XRD measurement of barium carbonate amount is presented and its dependence on experimental conditions is discussed.

Application of factorial designs for optimization of cyclodextrin glycosyltransferase production fromKlebsiella pneumoniae pneumoniae AS-22

Production of cyclodextrin glycosyltransferase (CGTase) from Klebsiella pneumoniae pneumoniae AS-22 was optimized in shake flasks using a statistical experimental design approach. Effect of various components in the basal medium, like carbon, nitrogen, phosphorus, and mineral sources as well as initial pH and temperature, were tested on enzyme production. The optimum concentrations of the selected media components were determined using statistical experimental designs. Two level fractional factorial designs in five variables, namely, dextrin, peptone, yeast extract, ammonium dihydrogen orthophosphate, and magnesium sulphate concentrations were constructed. The optimum medium composition thus found consisted of 49.3 g/L dextrin, 20.6 g/L peptone, 18.3 g/L yeast extract, 6.7 g/L ammonium dihydrogen orthophosphate, and 0.5 g/L magnesium sulphate. The maximum CGTase activity obtained was 21.4 U/mL in 28 h of incubation. The cell growth and CGTase production profiles were studied with the optimized medium in shake flasks and in 1-L fermenters. It was observed that the enzyme production was growth associated both in shake flask and in fermenter, although it was slower in shake flask. The maximum CGTase activity obtained in the fermenter was 32.5 U/mL in 16 h. The optimized medium resulted in about 9-fold increase in the enzyme activity as compared to that obtained in the basal medium in shake flask as well as in fermenter.

A parametric study of acetabular cup design variables using finite element analysis and statistical design of experiments.

To isolate the primary variables influencing acetabular cup and interface stresses, we performed an evaluation of cup loading and cup support variables, using a Statistical Design of Experiments (SDOE) approach. We developed three-dimensional finite element (FEM) models of the pelvis and adjacent bone. Cup support variables included fixation mechanism (cemented or noncemented), amount of bone support, and presence of metal backing. Cup loading variables included head size and cup thickness, cup/head friction, and conformity between the cup and head. Interaction between and among variables was determined using SDOE techniques. Of the variables tested, conformity, head size, and backing emerged as significant influences on stresses. Since initially nonconforming surfaces would be expected to wear into conforming surfaces, conformity is not expected to be a clinically significant variable. This indicates that head size should be tightly toleranced during manufacturing, and that small changes in head size can have a disproportionate influence on the stress environment. In addition, attention should be paid to the use of nonmetal backed cups, in limiting cup/bone interface stresses. No combination of secondary variables could compensate for, or override the effect of, the primary variables. Based on the results using the SDOE approach, adaptive FEM models simulating the wear process may be able to limit their parameters to head size and cup backing.

Optimization of cyclomaltodextrin glucanotransferase production from Bacillus firmus

Production of cyclomaltodextrin glucanotransferase (CGTase) from Bacilus firmus was optimized in shake flasks using a statistical experimental design approach. Two level complete factorial designs in three variables were used for media optimization. The maximum CGTase activity obtained was 7.05 U ml −1 with 21 g l −1 corn starch, 22.6 g l −1 yeast extract, 21.9 g l −1 Pharmamedia, and an initial pH of 9.8. The optimized medium resulted in about a 20-fold increase in the enzyme activity as compared to that obtained in the basal medium.

Design of ignition and fuel systems for two-stroke engines: A statistical experimental design approach

Abstract Two problems in the production of two-stroke outboard marine engines, namely the low speed problem at wide open throttle and the pickup stall problem, are solved using a statistical experimental design approach. Because theoretical relationships between the controllable variables and the performance of the engine are difficult to establish, it is unrealistic to solve these problems analytically from a thermodynamic approach. Experimental design has been proved to be an effective and efficient methodology for solving the problems in this situation. In this project, four experiments were conducted sequentially, and more than 200 readings were taken. It is required to optimize the setting of the different parameters so that the engine can reach a sufficiently high speed at wide open throttle and the vibration is reduced to an acceptably low level. Analysis of the experimental results suggests optimal choices of spark plug, advance firing angle, pressure relief hole size, spark plug gap, fuel flow rate, and rate of change of fuel flow rate.

Technical note: Design of ignition and fuel systems for two-stroke engines: A statistical experimental design approach

This paper describes a PC-based Diesel Engine Cycle and cooling system SIMulation (DECSIM) program that was developed at the Australian Maritime College. DECSIM has been validated against a variety of marine engines and can be used to predict the steady state performance characteristics of two- and four-stroke diesel engines. The program may be used to obtain pressure-crank angle, pressure-volume, and heat release diagrams. Applications of DECSIM are discussed that show how the program can be used to assist marine engineers in fault diagnosis and designers to predict the thermal behaviour of combustion chamber components. The program may also be used to model cooling system behaviour, and so can be used by design engineers to optimize the dimensions of components such as heat exchangers and pumps with acceptable system pressure drop characteristics.