Full Experimental Design Research Articles

Modelo matemático para estimar el coeficiente volumétrico de transferencia de oxígeno en biorreactores usando cálculo conformal

This work proposes a novel mathematical model based on time conformable derivative convective mass transfer equation to calculate the volumetric oxygen transfer coefficient (kLa) in a bioreactor. To validate the novel model, a full mixed-level experimental design was proposed with two factors: agitation speed and dispersed phase. The model employs the conformable derivate order operator (α) and the electrode constant (kp), which changes with electrode use and the operating conditions of the bioreactor. The results show that when the viscosity increases and the agitation decreases, the value α increases, and vice versa. Therefore, α is a parameter that has a physical meaning in the process. The correlation coefficient of the proposed model with the experimental data (R2 > 0.985) is higher than the one obtained with conventional models. The Akaike information criterion determined that the proposed conformal model describes the experimental data by 59%, while the conventional models describe the experimental data by 25% and 15%. There are no reports of similar mathematical models that determine mass transfer coefficients in bioprocesses.

Encouraging bystander helping behaviour in a violent incident: a virtual reality study using reinforcement learning

Virtual reality (VR) affords the study of the behaviour of people in social situations that would be logistically difficult or ethically problematic in reality. The laboratory-controlled setup makes it straightforward to collect multi-modal data and compare the responses across different experimental conditions. However, the scenario is typically fixed and the resulting data are usually analysed only once the VR experience has ended. Here we describe a method that allows adaptation of the environment to the behaviours of participants and where data is collected and processed during the experience. The goal was to examine the extent to which helping behaviour of participants towards the victim of a violent aggression might be encouraged, with the use of reinforcement learning (RL). In the scenario, a virtual human character represented as a supporter of the Arsenal Football Club, was attacked by another with the aggression escalating over time. (In some countries football is referred to as ‘soccer’, but we will use ‘football’ throughout). Each participant, a bystander in the scene, might intervene to help the victim or do nothing. By varying the extent to which some actions of the virtual characters during the scenario were determined by the RL we were able to examine whether the RL resulted in a greater number of helping interventions. Forty five participants took part in the study divided into three groups: with no RL, a medium level of RL, or full operation of the RL. The results show that the greater extent to which the RL operated the greater the number of interventions. We suggest that this methodology could be an alternative to full multi-factorial experimental designs, and more importantly as a way to produce adaptive VR scenarios that encourage participants towards a particular line of action.

Experimental and numerical investigations of the damages induced while drilling flax/epoxy composite

The influence of the drilling parameters and the stacking sequence of flax/epoxy composite laminate on the cutting force and the damage induced were studied experimentally and numerically. Drilling tests were carried out based on full experimental design and the delamination at the entry and exit of the hole were quantified using an optical microscopy. Moreover, the damages at the wall of the hole were analyzed using scanning electron microscopy. Based on the experimental results, it was observed that the drilling forces and the machining quality are influenced on the one side by the spindle speed and feed and on the other side by the stacking sequence composite plate. In fact, the cutting forces recorded when drilling a composite plate with [90/0/90/0]2s is 30% higher to the one recorded when drilling a composite made with quasi-isotropic stacking sequence. A numerical model was developed in ABAQUS/Explicit using Hashin’s failure criteria in order to predict the cutting forces and the defects induced by the interaction of the drill and composite as a function of the machining parameters. The developed model has been validated at the macro-scale (thrust force) and the meso-scale (delamination at the entry and exit of the hole).

Effect of material properties and process parameters on quality of friction stir forming

Friction stir forming is a joining process that can be employed for different types of mechanical connections. The idea is to deform one material and mechanically interlock with a second material exploiting an enhanced ductility at elevated temperature resulting from stir heating. A rigid rotating tool is plunged and, subsequently, moved in a parallel direction to the plane of the upper sheet pushing the material into holes or grooves of the part, placed below, to be joined. Herein, experimental tests were executed by changing the main process variables with the aim of highlighting their effects on the material flow during the studs' extrusion. An aluminum alloy of the same chemical composition, but with two different heat treatments, was processed pointing out the influence of the alloy's mechanical properties on the process dynamics and final stud integrity. An evolution of the microstructure as a result of the process thermo-mechanical conditions is also provided. Furthermore, a full design of experiments was executed to highlight the influences of analyzed input parameters on the stud dimensions. The cross-section area of each extruded stud was measured and analyzed for the joint interlocking mechanism. Finally, the main process input correlations with the obtained results were detected and reported.

Vertical Graphene Growth on AlCu4Mg Alloy by PECVD Technique

Vertical graphene, which belongs to nanomaterials, is a very promising tool for improving the useful properties of long-used and proven materials. Since the growth of vertical graphene is different on each base material and has specific deposition setting parameters, it is necessary to examine each base material separately. For this reason, a full factor design of experiment was performed with 26 = 64 rounds, which contained additional 5 central points, i.e., a total of 69 rounds of individual experiments, which was to examine the effect of input factors Temperature, Pressure, Flow, CH4, Plasma Power, and Annealing in H2 on the growth of vertical graphene on aluminum alloy AlCu4Mg. The deposition was performed using plasma-enhanced chemical vapor deposition (PECVD) technology. Mainly, the occurrence of graphene was analyzed, which was confirmed by Raman spectroscopy, as well as its thickness. The characterization was performed using electron and transmission microscopy, including an atomic force microscope. It was found that the growth of graphene occurred in 7 cases and its thickness is affected only by the interaction flow (sccm) × pretreatment H2 (sccm).

Positive genetic covariance and limited thermal tolerance constrain tropical insect responses to global warming.

Tropical ectotherms are particularly vulnerable to global warming because their physiologies are assumed to be adapted to narrow temperature ranges. This study explores three mechanisms potentially constraining thermal adaptation to global warming in tropical insects: (a) Trade-offs in genotypic performance at different temperatures (the jack-of-all-trades hypothesis), (b) positive genetic covariance in performance, with some genotypes performing better than others at viable temperatures (the 'winner' and 'loser' genotypes hypothesis), or (c) limited genetic variation as the potential result of relaxed selection and the loss of genes associated with responses to extreme temperatures (the gene decay hypothesis). We estimated changes in growth and survival rates at multiple temperatures for three tropical rain forest insect herbivores (Cephaloleia rolled-leaf beetles, Chrysomelidae). We reared 2,746 individuals in a full sibling experimental design, at temperatures known to be experienced by this genus of beetles in nature (i.e. 10-35°C). Significant genetic covariance was positive for 16 traits, supporting the 'winner' and 'loser' genotypes hypothesis. Only two traits displayed negative cross-temperature performance correlations. We detected a substantial contribution of genetic variance in traits associated with size and mass (0%-44%), but low heritability in plastic traits such as development time (0%-6%) or survival (0%-4%). Lowland insect populations will most likely decline if current temperatures increase between 2 and 5°C. It is concerning that local adaption is already lagging behind current temperatures. The consequences of maintaining the current global warming trajectory would be devastating for tropical insects. However, if humans can limit or slow warming, many tropical ectotherms might persist in their current locations and potentially adapt to warmer temperatures.

Development and Optimization for a New Planar Spring Using Finite Element Method, Deep Feedforward Neural Networks, and Water Cycle Algorithm

The gravity balance mechanism plays a vital role in maintaining the equilibrium for robots and assistive devices. The purpose of this paper was to optimize the geometry of a planar spring, which is an essential element of the gravity balance mechanism. To implement the optimization process, a hybrid method is proposed by combining the finite element method, the deep feedforward neural network, and the water cycle algorithm. Firstly, datasets are collected using the finite element method with a full experiment design. Secondly, the output datasets are normalized to eliminate the effects of the difference of units. Thirdly, the deep feedforward neural network is then employed to build the approximate models for the strain energy, deformation, and stress of the planar spring. Finally, the water cycle algorithm is used to optimize the dimensions of the planar spring. The results found that the optimal geometries of the spring include the length of 45 mm, the thickness of 1.029 mm, the width of 9 mm, and the radius of 0.3 mm. Besides, the predicted results determined that the strain energy, the deformation, and the stress are 0.01123 mJ, 33.666 mm, and 79.050 MPa, respectively. The errors between the predicted result and the verifying results for the strain energy, the deformation, and the stress are about 1.87%, 1.69%, and 3.06%, respectively.

Corrosion Inhibition of Brass by Biochemical Process in Circulating Cooling Water System

Controlling the corrosion rate of metal materials is one of the key issues in circulating cooling water treatment. In recent years, the treatment of circulating cooling water by microorganisms has become a research hotspot. Compared with the traditional chemical treatment, microbial treatment is an environmentally friendly technology. In this paper, the effects of ammonia nitrogen concentration, microbial dosage and aeration intensity on copper corrosion rate were studied. In order to analyze the experimental data more comprehensively, a full factor experimental design was used to investigate the effects of ammonia nitrogen concentration, microbial dosage and aeration intensity on copper corrosion. The corrosion rate of copper was less than the national standard (< 0.005 mm / a), in which ammonia nitrogen concentration and aeration intensity were significant factors (P < 0.05), and the interaction between ammonia nitrogen concentration and aeration intensity was also significant (P < 0.05), After optimization, the regression rate of the model increased from 85.02% to 92.41%.

A study on the transient heat generation rate of lithium-ion battery based on full matrix orthogonal experimental design with mixed levels

Determination of the heat generation rate of the lithium-ion battery is crucial in both the design of battery thermal management system (BTMS) and prediction of the transient temperature rise during dynamic operation. In this work, the commercial cylindrical 18,650 lithium-ion battery with Ni-Co-Mn ternary positive materials was exemplified by the full matrix orthogonal experimental design to obtain the heat generation rate. The experiment with 176 over-potential tests and 66 entropy coefficient tests was conducted by taking into account the influencing parameters including the depth of discharge (DOD), discharge rate (DR) and ambient temperature. It was found that the heat generation rate exhibited minor variation for DOD=0~0.8 with slight decrease in the segment of DOD=0.3~0.6, and increased rapidly near the end of discharge (DOD=0.8~1). The average heat generation rate showed the approximate quadratic nonlinear correlation with discharge rate. In addition, the third-order transient heat generation rate model of the lithium-ion battery was correlated with all the influencing parameters by the response surface methodology (RSM). This work provides a detailed method for determining the heat generation rate of the lithium-ion battery, which lays foundation for predicting the temperature field of the battery and designing battery thermal management system.

Study on microbial corrosion inhibition of carbon steel in circulating cooling water system

Although the industrial circulating cooling water system can save a lot of water resources, there will be serious scaling and corrosion during operation. Based on the environmental friendliness of microbial corrosion inhibition technology, this work evaluated the influence of microbial environmental indicators on the corrosion rate of carbon steel in circulating cooling water system by full factor experimental design. The results showed that under 10-50 mg/L ammonia nitrogen, 1-3 L/min aeration fluxes, the corrosion rate getting lower with the increase of ammonia nitrogen concentration and the decrease of aeration rate, while the microbial content had little effect on the corrosion rate.

Supercritical Fluid Chromatography development of a predictive analytical tool to selectively extract bioactive compounds by supercritical fluid extraction and pressurised liquid extraction

Selective extraction is a great concern in the field of natural products. The interest is to apply specific conditions favouring the solubility of targeted secondary metabolites and avoiding the simultaneous extraction of unwanted ones. Different ways exist to reach selective extractions with suited conditions. These conditions can be determined from experimental studies through experimental design, but a full experimental design takes time, energy, and uses plant samples. Prediction from varied solubility models can also be applied allowing a better understanding of the final selected conditions and eventually less experiments.The aim of this work was to develop and use a chromatographic model to determine optimal extraction conditions without the need for numerous extraction experiments. This model would be applied on the selective extraction of the desired antioxidant compounds in rosemary leaves (rosmarinic and carnosic acids) vs chlorophyll pigments to limit the green colour in extracts. This model was achieved with Supercritical Fluid Chromatography (SFC) and then applied to Supercritical Fluid Extraction (SFE) and Pressurised Liquid Extraction (PLE) assays.SFC models predicted low solubility of chlorophylls for low (5%) and high (100%) percentage of solvent in carbon dioxide. Also, low solubility was predicted with acetonitrile solvent compared to methanol or ethanol. This was confirmed with different extractions performed using SFE with different percentages of solvent (5, 30, and 70%) and with the three solvents used in the SFC models (acetonitrile, methanol and ethanol). Also extractions using PLE were carried out using the same neat solvents in order to confirm the SFC models obtained for 100% of solvent. Globally, extractions validated the SFC models. Only some differences were observed between ethanol and methanol showing the complexity of plant extraction due to matrix effect. For all these extracts, the content of carnosic acid and rosmarinic acid was also monitored and selective extraction conditions of bioactive compounds could be determined.

Caffeine removal using Elaeis guineensis activated carbon: adsorption and RSM studies.

The palm (Elaeis guineensis), known as dendê, is an important oleaginous Brazilian plant with a high performance of oil production. In this work, a 23 full experimental design was performed and the response surface method (RSM) was used to indicate the optimum parameter of caffeine adsorption on Elaeis guineensis endocarp activated carbon, since the endocarp is the main by-product from dendê oil production. It was set the adsorbent point of zero charge (pHpzc), and the material was characterized by Fourier transform infrared spectroscopy (FT-IR), thermogravimetric analysis (TGA), and scanning electron microscopy (SEM). The RSM results indicate removal efficiency (%) at the optimal conditions, 0.20 g of adsorbent, and caffeine initial concentration of 20 mg/L, and acidic medium was about 95%. Based on ANOVA and F test (Fcalculated > Fstandard), the mathematical/statistical model obtained fits well to the experimental data. The overall kinetic studies showed time was achieved after 5 h and caffeine adsorption followed the pseudo-second-order model suggesting chemisorption is a predominant mechanism. Redlich-Peterson and Sips models best represented the experimental data (0.967 < R2 < 0.993). Thermodynamic revealed that caffeine adsorption was spontaneous at all temperatures studied, exothermic, and probably with changes in the adsorbate-adsorbent complex during the process. The tests conducted in different water matrixes corroborate the suitability of this adsorbent to be used in caffeine removal even in a complex solution.

Effect of powder reuse on mechanical properties of Ti-6Al-4V produced through selective laser melting

Metallic powder reuse presents attractive economic and environmental advantages for direct metal laser sintering (DMLS). However, continuous recycling of powder raises concerns of powder quality and sintered part performance, and complicates process validation. Efforts to examine the mechanical response of parts built with reused feedstocks are increasingly common in the technical literature, but none have optimized process parameters in DMLS to control for changes in material properties. In this paper, titanium powder reuse was investigated with the objective of optimizing the additive manufacturing (AM) process for reuse. Virgin Ti-6Al-4V powder was cycled a total of eight times through conditions representative of industrial DMLS machines. A full 23-factorial design of experiments (DOE) approach was employed to identify how parameter settings affect mechanical behavior, and include reuse as a process variable. The independent factors (laser power, laser speed, and hatch distance) did not significantly affect mechanical properties; however, measurements of ductility were found to be influenced by some interaction between the factors. These results were attributed to the narrow operating envelope which was required for successfully sintered specimens. Density and chemistry measurements further demonstrated no significant change with respect to reuse. The findings suggest that titanium powder can be reused up to eight times without any noticeable loss in strength or ductility.

Prediction of the main cutting force in longitudinal turning of AISI D6 tool steel bars by applying full and fractional experimental design

This investigation concerns the cutting force magnitude during turning of AISI D6 tool steel using both Taguchi Experimental Design (TED) and full factorial design (FFD). Three main cutting parameters namely spindle speed, feed rate and depth of cut were considered as the cutting parameters, each one having three levels, while the cutting force (Fc) was selected as the machinability process output. The full factorial design of the 27 (33) experiments was splitted in three sub-arrays, each one having 9 experiments. These three sub-arrays were orthogonal and were treated as Taguchi L9 orthogonal arrays. The performance of the FFD and each TED was analysed using stem-and-leaf plots, box plots, as well as analysis of means (ANOM) and analysis of variance (ANOVA). The results obtained indicate the suitability of all proposed experimental designs for machinability studies.

Optimal Response Formats for Online Surveys: Branch, Grid, or Single Item?

Abstract This article reports the results of an experiment comparing branch, grid, and single-item question formats in an internet survey with a nationally representative probability sample. We compare the three formats in terms of administration time, item nonresponse, survey breakoff rates, response distribution, and criterion validity. On average, the grid format obtained the fastest answers, the single-item format was intermediate, and the branch format took the longest. Item nonresponse rates were lowest for the single-item format, intermediate for the grid, and highest for branching, but these results were not statistically significant when modeling the full experimental design. Survey breakoff rates among the formats are not statistically distinguishable. Criterion validity was weakest in the branching format, and there was no significant difference between the grid and single-item formats. This evidence indicates that the branching format is not well suited to internet data collection and that both single-item and short, well-constructed grids are better question formats.

Development of Artificial Neural Network Model for Estimation of Salt Fields Productivity

In recent years, Indonesia needs import million tons of salt to satisfy domestic industries demand. The production of salt in Indonesia is highly dependent on the weather. Therefore, this article aims to develop a prediction model by examining rainfall, humidity and wind speed data to estimate salt production. In this research, Artificial Neural Network (ANN) method is used to develop a model based on data collected from Kaliumenet Sumenep Madura. The model analysis uses the full experimental factorial design to determine the effect of the ANN parameter differences. Then, the selected model performance compared with the estimate predictor of Holt-Winters. The results present that ANN-based models are more accurate and efficient for predicting salt field productivity.

Influence of cell history on the subsequent inactivation of Campylobacter jejuni during cold storage under modified atmosphere

Worldwide, Campylobacter infections are the main cause of human bacterial enteritis and broiler meat is considered as the most important source of human campylobacteriosis. Some mitigation strategies have been focused on reduction of Campylobacter at the slaughtering steps. This study aimed to determine the influence of consecutive stresses inspired by slaughtering steps on the subsequent inactivation of Campylobacter jejuni during cold storage under different modified atmospheres. Using a full experimental design, three strains of C. jejuni of poultry origin were submitted to consecutive heat (46°, 50° or 54 °C for 4 min) and cold (−4° or 3 °C for 2 h) stresses by plunging cultures into baths at appropriate temperatures. Cultures were then stored at 6 °C during seven days under modified atmospheres (70% O2/30% CO2 or 50% CO2/50% N2). Inactivation of C. jejuni induced by cold storage was shown to depend significantly (P < 0.0001) upon the heat stress previously applied. It was shown to be the highest under the atmosphere enriched in oxygen, after application of 54 °C. Strain inactivation variability was also quantified. These results show that consecutive stresses influence further inactivation of C. jejuni during storage and consequently the contamination level at consumer's plate.

Polyculture of curimata pacu (Prochilodus argenteus) and canela shrimp (Macrobrachium acanthurus) feed with dehydrated cassava leaf meal

Polyculture systems are integrated cultivation systems where two or more aquatic species are maintained at the same place using locally available ecological resources. The purpose of this study was to analyze the zootechnical performance of curimata-pacu ( Prochilodus argenteus ) when polyculture with canela shrimps ( Macrobrachium acanthurus ) and with dehydrated cassava leaf bran comparatively with monoculture. 96 curimata-pacu fishes ( P. argenteus ) and 72 canela shrimps ( M. acanthurus ) were cultivated. At the beginning of the experiment, their average body masses were 10.77 ± 1.29 and 3.68 ± 0.74 g, respectively, randomly distributed in a factorial scheme with a full random experimental design in 24 polyethylene water tanks (70 L) in water recirculation system, comprising two simultaneous factors: curimata pacu monoculture (4 fishes: 0 shrimps per tank) and curimata pacu and canela shrimp polyculture (4 fishes: 6 shrimps per tank), was added dehydrated cassava leaf meal (DCLM) to the monocultures and polycultures in different percentages: 0% (treatment 1, T1), 10% (T2) and 20% (T3), with four replicas each. The results indicated that presence of shrimps and the higher concentration of DCLM (20%) had a negative impact on the fish development regarding final total biomass (BF), absolute growth rate (AGR), and feed conversion rate (FCR). However, the diet with the addition of up to 10% DCLM in P. argenteus in monoculture systems, obtained a zootechnical performance similar to control, thereby reducing the feed costs for this species.

Repeated batches as a feasible industrial process for hemicellulosic ethanol production from sugarcane bagasse by using immobilized yeast cells

Currently, sugarcane bagasse (SB) is the most abundant agricultural residue generated in Brazil. Given that hemicelluloses can reach up to 30% of SB, bioconversion of this fraction into second generation ethanol (2G) is essential for the success of biorefinery based operations. For 2G ethanol production, techniques such as immobilization process could be an interesting strategy to improve process productivity and must receive special investigation. Cell immobilization of the native Brazilian pentose wild converting yeast, Scheffersomyces shehatae UFMG-HM 52.2, was proposed for the production of 2G ethanol from SB hemicellulosic hydrolysate. A 23 full experimental design was constructed with varying concentrations of sodium alginate (1.0, 1.5 and 2.0% w/v), and calcium chloride (0.1 M, 0.15 M and 0.2 M) and conditioning time (12, 18 and 24 h). Through statistical analysis, it was determined that highest ethanol yield (YP/S of 0.32 g/g) and productivity (QP of 0.146 g/L.h) were obtained with immobilization conditions of 1% sodium alginate, 0.2 M calcium chloride and 12 h of conditioning time. Repeated batches were conducted employing these defined conditions, showing the feasibility to use the system for 5 consecutive cycles. Results highlighted the use of proposed approach for ethanol production, promoting its inclusion in biorefinery operation portfolios. Hemicellulosic hydrolysate from sugarcane bagasse: a large available carbon source; S. shehatae UFMG-HM 52.2 is a Brazilian wild native pentose fermenting yeast; Immobilization conditions for this yeast were defined for ethanol production; Stability in ethanol production was demonstrated in 5 repeated consecutive batches; Our approach was demonstrated feasible for industrial 2G ethanol process development.

Study on bubble detachment in a narrow rectangular channel with natural circulation based on full factor experiment design

Study on bubble detachment in a narrow rectangular channel with natural circulation based on full factor experiment design