Full Factorial Experimental Design Research Articles

Influence of the Processing Parameters on the Microstructure and Mechanical Properties of 316L Stainless Steel Fabricated by Laser Powder Bed Fusion

Complex thermo-kinetic interactions during metal additive manufacturing reduce the homogeneity of the microstructure of the produced samples. Understanding the effect of processing parameters over the resulting mechanical properties is essential for adopting and popularizing this technology. The present work is focused on the effect of laser power, scanning speed, and hatch spacing on the relative density, microhardness, and microstructure of 316L stainless steel processed by laser powder bed fusion. Several characterization techniques were used to study the microstructure and mechanical properties: optical, electron microscopies, and spectrometry. A full-factorial design of experiments was employed for relative density and microhardness evaluation. The results derived from the experimental work were subjected to statistical analysis, including the use of analysis of variance (ANOVA) to determine both the main effects and the interaction between the processing parameters, as well as to observe the contribution of each factor on the mechanical properties. The results show that the scanning speed is the most statistically significant parameter influencing densification and microhardness. Ensuring the amount of volumetric energy density (125 J/mm3) used to melt the powder bed is paramount; maximum densification (99.7%) is achieved with high laser power and low scanning speed, while hatch spacing is not statistically significant.

Development and characterization of colloidal pNIPAM-methylcellulose microgels with potential application for drug delivery in dentoalveolar tissue engineering strategies

Incorporation of growth factors, signaling molecules and drugs can be vital for the success of tissue engineering in complex structures such as the dentoalveolar region. This has led to the development of a variety of drug release systems. This study aimed to develop pNIPAM-methylcellulose microgels with different synthesis parameters based on a 23 full factorial design of experiments for this application. Microgel properties, including volume phase transition temperature (VPTT), hydrodynamic size, drug loading and release, and cytocompatibility were systematically evaluated. The results demonstrated successful copolymerization and development of the microgels, a hydrodynamic size ranging from ∼200 to ∼500 nm, and VPTT in the range of 34–39 °C. Furthermore, loading of genipin, capable of inducing odontoblastic differentiation, and its sustained release over a week was shown in all formulations. Together, this can serve as a solid basis for the development of tunable drug-delivering pNIPAM-methylcellulose microgels for specific tissue engineering applications.

Perceived Barriers to Using Neurostimulation: A National Survey of Psychiatrists, Patients, Caregivers, and the General Public.

Neurostimulation interventions often face heightened barriers limiting patient access. The objective of this study is to examine different stakeholders' perceived barriers to using different neurostimulation interventions for depression. We administered national surveys with an embedded experiment to 4 nationwide samples of psychiatrists (n = 505), people diagnosed with depression (n = 1050), caregivers of people with depression (n = 1026), and members of the general public (n = 1022). We randomly assigned respondents to 1 of 8 conditions using a full factorial experimental design: 4 neurostimulation modalities (electroconvulsive therapy [ECT], repetitive transcranial magnetic stimulation [rTMS], deep brain stimulation [DBS], or adaptive brain implants [ABIs]) by 2 depression severity levels (moderate or severe). We asked participants to rank from a list what they perceived as the top 3 barriers to using their assigned intervention. We analyzed the data with analysis of variance and logistic regression. Nonclinicians most frequently reported "limited evidence of the treatment's effectiveness" and "lack of understanding of intervention" as their top 2 most important practical barriers to using ECT and TMS, respectively. Compared with nonclinicians, psychiatrists were more likely to identify "stigma about treatment" for ECT and "lack of insurance coverage" for TMS as the most important barriers. Overall, psychiatrists' perceptions of the most important barriers to using neurostimulation interventions were significantly different than those of nonclinicians. Perceived barriers were significantly different for implantable DBS and ABI) versus nonimplantable (rTMS and ECT) neurostimulation interventions. Better understanding of how these barriers vary by neurostimulation and stakeholder group could help us address structural and attitudinal barriers to effective use of these interventions.

Tool life assessment of high strength cast iron alloys in dry face milling operations

The advancement in cast iron alloy properties has led to more efficient materials, especially in the automotive industry. However, this progress has also increased the demand for more durable tools with greater resistance to cutting operations. Conducting an in-depth investigation into the impact of these materials on tool lifespan is crucial, as it directly affects productivity. The main objective of this study was to analyze the lifespan of uncoated cemented carbide tools during milling operations using four high-strength cast iron alloys under various dry cutting conditions. A full factorial Design of Experiment (DoE) (23) was employed. The input variables included cutting speed (vc) of 230 and 350 m/min, tool feed (fz) of 0.1 and 0.2 mm/tooth, and materials, namely cast irons (FC 250, FC 300(Mo), FC300(Mo+RG), and FV 450). Additionally, material tests were conducted on billets without holes to simulate mild cutting conditions and with holes for more severe machining conditions. The established machining operation was face milling without cutting fluid, with the axial depth of cut (ap) and radial depth of cut (ae) maintained constant at 1 mm and 60 mm, respectively. The results showed that FV 450 had the shortest tool life, as expected for the hardest and resistant material, with a maximum lifetime difference of 83 % less when compared to FC 250, the softest one that had the longest tool lifespan. The introduction of holes also significantly reduced the overall tool life by about 57 %. The findings highlight the importance of factors such as cutting speed, feed per tooth, material composition, impact, and workpiece surface quality, which significantly influence tool performance.

Preparation, Optimization, and In-Vitro Evaluation of Brusatol- and Docetaxel-Loaded Nanoparticles for the Treatment of Prostate Cancer.

Challenges to docetaxel use in prostate cancer treatment include several resistance mechanisms as well as toxicity. To overcome these challenges and to improve the therapeutic efficacy in heterogeneous prostate cancer, the use of multiple agents that can destroy different subpopulations of the tumor is required. Brusatol, a multitarget inhibitor, has been shown to exhibit potent anticancer activity and play an important role in drug response and chemoresistance. Thus, the combination of brusatol and docetaxel in a nanoparticle platform for the treatment of prostate cancer is expected to produce synergistic effects. In this study, we reported the development of polymeric nanoparticles for the delivery of brusatol and docetaxel in the treatment of prostate cancer. The one-factor-at-a-time method was used to screen for formulation and process variables that impacted particle size. Subsequently, factors that had modifiable effects on particle size were evaluated using a 24 full factorial statistical experimental design followed by the optimization of drug loading. The optimization of blank nanoparticles gave a formulation with a mean size of 169.1 nm ± 4.8 nm, in agreement with the predicted size of 168.333 nm. Transmission electron microscopy showed smooth spherical nanoparticles. The drug release profile showed that the encapsulated drugs were released over 24 h. Combination index data showed a synergistic interaction between the drugs. Cell cycle analysis and the evaluation of caspase activity showed differences in PC-3 and LNCaP prostate cancer cell responses to the agents. Additionally, immunoblots showed differences in survivin expression in LNCaP cells after treatment with the different agents and formulations for 24 h and 72 h. Therefore, the nanoparticles are potentially suitable for the treatment of advanced prostate cancer.

An investigation into the mechanisms that influence laser sintered polyamide-12 top surfaces

Purpose The purpose of this paper is to elucidate the extent to which the mechanisms of polymer melt viscous flow and finish layer powder particle adhesion influence the top surface topographies of laser sintered polyamide (PA12) components. Design/methodology/approach Laser sintered specimens were manufactured at varying laser parameters in accordance with a full factorial design of experiments. Focus variation microscopy was used to ascertain insight into their top surface heights and peak/valley distributions. Subsequently, regression expressions were generated to model the former with respect to applied laser parameters. Auxiliary experimental analysis was also performed to validate the proposed mechanisms and statistical models. Findings Within the parameter range tested, this work found the root mean square (Sq) and skewness (Ssk) roughness responses of laser sintered PA12 top surfaces to be inversely related to one another, and both also principally influenced by beam spacing. Furthermore, it was demonstrated that using optimised laser parameters (to promote polymer melt dispersion) and building without finish layers (to avert subsequent powder particle adhesion) reduced the mean Sq roughness of resultant topographies by 30.8% and 47.9% relative to standard laser sintered PA12 top surfaces, respectively. Practical implications The scope to which laser sintered PA12 top surfaces can be modified was highlighted. Originality/value This research demonstrated the impact the mechanisms of polymer melt viscous flow and finish layer powder particle adhesion have on laser sintered PA12 top surfaces.

Optimizing milling parameters based on full factorial experiment and backpropagation artificial neural network of lamina milling temperature prediction model.

Milling operations of laminae in spinal surgery generate high temperatures, which can lead to thermal injury and osteonecrosis and affect the biomechanical effects of implants, ultimately leading to surgical failure. In this paper, a backpropagation artificial neural network (Bp-ANN) temperature prediction model was developed based on full factorial experimental data of laminae milling to optimize the milling motion parameters and to improve the safety of robot-assisted spine surgery. A full factorial experiment design were used to analyze the parameters affecting the milling temperature of laminae. The experimental matrixes were established by collecting the corresponding cutter temperature Tc and bone surface temperature Tb for the milling depth, feed speed and different bone densities. The Bp-ANN lamina milling temperature prediction model was constructed from experiment data. Increasing milling depth increases bone surface and cutter temperature. Increasing feed speed had little effect on cutter temperature, but decreased bone surface temperature. Increasing bone density of laminae increased cutter temperature. The Bp-ANN temperature prediction model had best training results in the 10th epoch, and there is no overfitting (training set R= 0.99661, validation set R= 0.85003, testing set R= 0.90421, all temperature data set R= 0.93807). The goodness of fit R of Bp-ANN was close to 1, indicating that the predicted temperature was in good agreement with the experiment measurements. This study can help spinal surgery-assisted robot to select appropriate motion parameters at different density bones to improve lamina milling safety.

Recombinant T7 RNA polymerase production using ClearColi BL21(DE3) and animal-free media for in vitro transcription.

In vitro transcription (IVT) using T7 RNA polymerase (RNAP) is integral to RNA research, yet producing this enzyme in E. coli presents challenges regarding endotoxins and animal-sourced toxins. This study demonstrates the viable production and characterization of T7 RNAP using ClearColi BL21(DE3) (an endotoxin-free E. coli strain) and animal-free media. Compared to BL21(DE3) with animal-free medium, soluble T7 RNAP expression is ~50% lower in ClearColi BL21(DE3). Optimal soluble T7 RNAP expression in flask fermentation is achieved through the design of experiments (DoE). Specification and functional testing showed that the endotoxin-free T7 RNAP has comparable activity to conventional T7 RNAP. After Ni-NTA purification, endotoxin levels were approximately 109-fold lower than T7 RNAP from BL21(DE3) with animal-free medium. Furthermore, a full factorial DoE created an optimal IVT system that maximized mRNA yield from the endotoxin-free and animal-free T7 RNAP. This work addresses critical challenges in recombinant T7 RNAP production through innovative host and medium combinations, avoided endotoxin risks and animal-derived toxins. Together with an optimized IVT reaction system, this study represents a significant advance for safe and reliable reagent manufacturing and RNA therapeutics. KEY POINTS: • Optimized IVT system maximizes mRNA yields, enabling the synthesis of long RNAs. • Novel production method yields endotoxin-free and animal-free T7 RNAP. • The T7 RNAP has equivalent specifications and function to conventional T7 RNAP.

A decision support system for the selection of FDM process parameters using MOORA

Additive Manufacturing (AM) is an automated process of fabricating three-dimensional (3D) physical objects from a 3D-CAD data by adding layers of materials one upon another through a print head or nozzle without using any tooling components or machining environments. Due to freedom in design, any complex shape can be produced using this process. Fused Deposition Modeling (FDM) is one such AM technology that is commonly used for its simplicity, environment friendliness and low requirement for process monitoring. However, this technology is limited only to small-scale production due to high cost and high build time. The present work focuses on the development of a framework for parametric optimization of the FDM process using multi-objective optimization based on ratio analysis (MOORA). A CAD model of the cam follower mechanism has been prepared in the Solidworks platform and used in this experiment for optimization of build time and cost which have been considered as response variables of the experiment. The experiment has been conducted following the full factorial design of experiment (DoE) method.

Influence of surface texture of electric discharge machined Ti6Al4V on the surface wettability

This study examines the effects of crucial ISO 25178 parameters, including height, functional, spatial, functional (stratified), hybrid, and functional (volume), on surface wettability and the influence of key electric discharge texturing process parameters, including current and pulse ON time, on surface roughness (Sa) and water droplet contact angle. To examine the level of significance of each parameter and to determine the level of correlation, a three-level full factorial experimental design, and ANOVA analysis are used. The findings showed that over pulse ON time, the important factor influencing surface roughness (Sa) and contact angle is current. The surface roughness (Sa) is observed to vary between 4.2 and 12.7, whereas the water droplet contact angle varies between 90.7° and 120.4°. In order to find out the correlation between the surface texture parameters based on the ISO 251718, Pearson Correlation analysis were adopted and it is observed that Sa, Sq, Str, Smrk1, Sdr, Vm, and Vmp are having a substantial correlation with the contact angle. Among the ISO25178 parameters examined, Smrk1, however, has demonstrated a highest impact on the contact angle with a highest pearson correlation coefficient of −0.757.

Taking Advantage of the Operating Heterogeneities in PEMFC: Numerical Study with a Pseudo-3D Model

A Proton Exchange Membrane Fuel Cell (PEMFC) is an open system. Its operation is therefore inherently heterogeneous. Indeed, in a cell, electrochemical reactions do not take place homogeneously on the active surface area. It has already been pointed out that operating heterogeneities over a large cell active area can cause a decrease of performance and durability. In fact, studies to date have focused on the relation between operating heterogeneities and local degradation on the active surface area for a small selection of operating conditions.The objective of our study is to find a way to control the current, temperature and water distributions by adjusting the operating conditions to, hopefully, optimize performance and improve durability. In order to define those control strategies, a better understanding of the heterogeneities for a wide range of operating conditions is necessary. To that end, a first numerical approach seems to be the most appropriate.This numerical study is based on a pseudo-3D multi-physics and single-phase model of a large cell, developed on COMSOL Multiphysics®. One novelty of our study, from a methodological point of view, is the calibration of the model. Instead of calibrating the model with the electrochemical response of a large cell for some chosen operating conditions as per usual, it has been calibrated with the electrochemical response of a small cell (1.8 cm²), called differential cell, emulating local operating conditions on a larger cell. Three areas of the large cell were emulated for different operating conditions: inlet, middle and outlet. Once calibrated, the pseudo-3D model was used to calculate the distributions for 108 operating conditions, which were chosen from a full factorial design of experiment defined according to the automobile application of PEMFC. The statistical analysis of these simulation results will give the influence of operating conditions (gases pressure, the magnitude and orientation of the thermal gradient of the cooling fluid, gases temperature and relative humidity) on the current density, temperature and water distributions on the active surface area. These results will later be useful for the design of strategies for controlling heterogeneities, which will be finally tested on PEM stack. Figure 1

The effect of the vibratory surface finishing process on surface integrity and dimensional deviation of selective laser melted parts

Selective laser melting (SLM) is an additive manufacturing method used in aerospace and biomedical industries due to its ability to fabricate complex geometries with excellent mechanical properties. However, achieving the desired surface quality can be challenging. Vibratory surface finishing (VSF) is a widely used post-processing technique in engineering industries to improve surface quality. In this study, SLM-produced stainless steel 316L samples with different geometries, including samples with flat surfaces (SFS), samples with bulged surfaces (SBS), and samples with concave surfaces (SCS), were processed using triangular, spherical, and cylindrical media shapes for different processing times. The research aimed to analyze the surface integrity and dimensional deviation of each sample type after VSF. Our study employed a full factorial design of experiments (DoE) to assess the influences on the surface integrity, dimensional deviations, surface morphology, and surface hardness of 316L stainless steel parts produced via SLM. After VSF, the average Ra value was reduced by 75% after 9 h of operation, achieving the lowest Ra value (1.68 μm) using spherical media. Spherical media also reduced Ra values on concave surfaces by approximately 71%, with a reduction from 14.55 to 4.15 μm. The study found that VSF helps improve surface roughness while affecting the components’ average dimensional deviation and subsurface microhardness. The microhardness measurement showed a value of 220 HV, which was approximately 6.4% higher than the bulk hardness.

Simultaneous Determination of Steroids and NSAIDs, Using DLLME-SFO Extraction and HPLC Analysis, in Milk and Eggs Collected from Rural Roma Communities in Transylvania, Romania.

This research aims to determine five steroids and four non-steroidal anti-inflammatory drugs in milk and egg samples collected from rural Roma communities in Transylvania, Romania. Target compounds were extracted from selected matrices by protein precipitation, followed by extract purification by dispersive liquid-liquid microextraction based on solidification of floating organic droplets. The extraction procedure was optimized using a 24 full factorial experimental design. Good enrichment factors (87.64-122.07 milk; 26.97-38.72 eggs), extraction recovery (74.49-103.76% milk; 75.64-108.60% eggs), and clean-up of the sample were obtained. The method detection limits were 0.74-1.77 µg/L for milk and 2.39-6.02 µg/kg for eggs, while the method quantification limits were 2.29-5.46 µg/L for milk and 7.38-18.65 µg/kg for eggs. The steroid concentration in milk samples was <MDL up to 4.30 µg/L, decreasing from 17α-ethinyl estradiol, 17β-estradiol, and estrone to estriol. The NSAID concentration was <MDL up to 3.41 µg/L, decreasing from ibuprofen, diclofenac, and ketoprofen to naproxen. The steroid concentration in the egg samples was <MDL to 2.79 µg/kg, with all steroids detected, while the concentration of NSAIDs was <MDL to 2.28 µg/kg, with only ibuprofen, ketoprofen, and naproxen detected. The developed protocol was successfully applied to the analysis of target compounds in real milk and egg samples.

Analytical optimization of open hole effects on the tensile properties of SS400 sheet specimens using an integrated FFD-CRITIC-DFA method

Structural components are generally composed of material discontinuities, including open holes, which are considered stress concentrators in engineering components. In view of this, assessing the influence of open holes on the tensile properties is crucial to determine the sensitivity and tensile strength of a particular material. Nevertheless, investigation of the impact of open holes on the tensile properties of SS400 steel sheets is very limited and yet to be explored. Therefore, this study was performed to optimize the effects of open holes on the tensile properties of SS400 sheet specimens based on a Full Factorial Design (FFD) experiment. Four input parameters that represent various hole configurations, which include the hole diameter, location of the hole, number of holes, and hole shape, were considered in this study to develop the experimental-based prediction models to optimize the output performance, namely yield strength, ultimate tensile strength, and ultimate elongation, commonly denoted as YS, UTS, and UE respectively. A total of 10 additional experimental trials were then utilized to verify the constructed models. In addition, the weight fractions for YS, UTS, and UE were identified using the Criteria Importance Through Inter-Criteria Correlation (CRITIC) method. Subsequently, the Desirability Function Analysis (DFA) is utilized to pinpoint the optimal parameter conditions for maximizing the tensile properties. Based on the results, all four parameters showed significant effects on the response variables, except the number of holes for UTS and hole location for UE. The diameter also recorded the highest contribution toward UTS and UE, followed by the hole shape. Regarding YS, hole diameter takes precedence, with the number of holes as the second most influential factor. Furthermore, the average absolute percent deviation for the prediction responses of 10 experimental cases were 1.06 %, 0.90 %, and 0.85 % for YS, UTS, and UE, respectively, confirming the validity of the constructed models. Meanwhile, the CRITIC method estimated the weight fractions for YS, UTS and UE from the experimental data, which were 0.3825, 0.2559, and 0.3616, respectively. The DFA-derived composite desirability, rated at 0.9820, suggests optimal conditions: a 1 mm hole diameter, centered hole location, three holes, and a hexagonal shape. The minimal deviations between predicted and experimental values affirm the robustness of the models. Overall, this investigation yields important insights for optimizing open holes and elevating the tensile performance of SS400 sheet specimens.

Study on the roughness parameters describing surface functionality in bore honing

In the examination of the finishing procedures, it is also necessary to examine the parameters characterizing the functionality in addition to the numerical values of the surface roughness. This allows us to get a more complex picture of the behaviour of the machined surface during the working conditions. In this paper, the parameters of average roughness, surface skewness, and surface kurtosis are examined for holes machined with honing. During the experiments, the full factorial experimental design is used. Thus, the cutting experiments were performed with a total of 8 settings for 2 values of three selected parameters (average grain size, pressure, feed rate). The effect of the investigated technological parameters on the analysed roughness parameters was given in the study.

Exploring symbiotic supply chains dynamics

Symbiotic Supply Chains – where the inputs of some members belonging to one supply chain are obtained using the waste generated by other companies in a different supply chain – represent a great opportunity for companies to move towards the Circular Economy paradigm. However, the dynamic behavior of Symbiotic Supply Chains (i.e., how detrimental time-varying phenomena of supply chains, such as the bullwhip effect, impact the performance) remains largely unknown. In this work we aim to contribute to this quite unexplored research field by analyzing the dynamics of two supply chains that implement, at the manufacturer level, a symbiotic exchange of waste. We derive closed analytical equations to estimate several indicators of the bullwhip effect under different information sharing scenarios and evaluate them for different coefficients of circularity (i.e. the average proportion of the output of one supply chain that is obtained using the waste of the other supply chain). Furthermore, we extend our analysis by carrying out a simulation study, when some underlying assumptions are removed, and a full-factorial Design of Experiments to emulate and explore the behavior of Symbiotic Supply Chains under further real-life scenarios. By doing so, we identify different properties of Symbiotic Supply Chains and provide some managerial implications. Among those, we observe how the bullwhip effect of one supply chain propagates to the other, which is also greatly influenced by the variability of the demand in both supply chains. Also, we note that high coefficient of circularity does not necessary improve the dynamic performance of Symbiotic Supply Chains. Results point out to the need to carefully design symbiotic exchange in supply chains to avoid undesirable effects that may hinder the advocated advantages of Circular Economy practices.

Design of Experiments to Compare the Mechanical Properties of Polylactic Acid Using Material Extrusion Three-Dimensional-Printing Thermal Parameters Based on a Cyber-Physical Production System.

The material extrusion 3D printing process known as fused deposition modeling (FDM) has recently gained relevance in the additive manufacturing industry for large-scale part production. However, improving the real-time monitoring of the process in terms of its mechanical properties remains important to extend the lifespan of numerous critical applications. To enhance the monitoring of mechanical properties during printing, it is necessary to understand the relationship between temperature profiles and ultimate tensile strength (UTS). This study uses a cyber-physical production system (CPPS) to analyze the impact of four key thermal parameters on the tensile properties of polylactic acid (PLA). Layer thickness, printing speed, and extrusion temperature are the most influential factors, while bed temperature has less impact. The Taguchi L-9 array and the full factorial design of experiments were implemented along with the deposited line's local fused temperature profile analysis. Furthermore, correlations between temperature profiles with the bonding strength during layer adhesion and part solidification can be stated. The results showed that layer thickness is the most important factor, followed by printing speed and extrusion temperature, with very close influence between each other. The lowest impact is attributed to bed temperature. In the experiments, the UTS values varied from 46.38 MPa to 56.19 MPa. This represents an increase in the UTS of around 17% from the same material and printing design conditions but different temperature profiles. Additionally, it was possible to observe that the influence of the parameter variations was not linear in terms of the UTS value or temperature profiles. For example, the increase in the UTS at the 0.6 mm layer thickness was around four times greater than the increase at 0.4 mm. Finally, even when it was found that an increase in the layer temperature led to an increase in the value of the UTS, for some of the parameters, it could be observed that it was not the main factor that caused the UTS to increase. From the monitoring conditions analyzed, it was concluded that the material requires an optimal thermal transition between deposition, adhesion, and layer solidification in order to result in part components with good mechanical properties. A tracking or monitoring system, such as the one designed, can serve as a potential tool for reducing the anisotropy in part production in 3D printing systems.

The differential effects of psychiatrists' and patients’ prior experiences on views about psychiatric electroceutical interventions

The aim of this study is to examine ways in which prior experiences and familiarity with psychiatric electroceutical interventions (PEI) shape psychiatrists' and patients’ views about these interventions. We administered a national survey, with an embedded experiment, to psychiatrists (n = 505) and adults diagnosed with depression (n = 1050). We randomly assigned respondents to one of 8 conditions using a full factorial experimental design: 4 PEI modalities [ECT, rTMS, DBS, or adaptive brain implants (ABIs)] by 2 depression severity levels [moderate or severe]. We analyzed the survey data with ANOVA and OLS linear regression models. Patients having experience with any PEI reported more positive affect toward, but also greater perceived risk from, their assigned PEI than did patients with no such experience. Psychiatrists who referred or administered any PEI reported more positive affect toward and greater perceived influence on self and perceived benefit from their assigned PEI than did psychiatrists with no such familiarity. Limitations of our study include that our participants were randomly assigned to a PEI, not necessarily to the one they had experience with. Moreover, our study did not directly ask about the kind of experiences participants had with a given PEI.Overall, our survey data shows that greater experience with PEIs elicits more positive affect in both stakeholder groups. Beyond this, prior PEI experience shapes attitudes towards these interventions in complex ways. Further research linking different types of experience with a given PEI would help better understand factors shaping attitudes about specific PEIs.

Horizontal-axis propeller hydrokinetic turbine optimization by using the response surface methodology: Performance effect of rake and skew angles

The design of a horizontal-axis propeller hydrokinetic turbine (HPHT) depends on several geometric parameters affecting its hydrodynamic efficiency which is measured through the power coefficient (CP). In this study, a 1 kW turbine with 1.6 m of rotor diameter (D) was used as the prototype to know the relationship between the CP and the turbine design parameters, such as the skew (ϕ) and rake (γ) angles. A full-factorial design of experiments, as a response surface methodology technique, and computational fluid dynamics simulation were used to determine the significance of the factors considered and their interaction in the maximization of the response variable (CP). A 3D computational domain in ANSYS Fluent software and the k-ω SST turbulence model were utilized, for the unsteady flow simulations. Under optimal design conditions, i.e., when ϕ and γ were equal to 13.30° and -18.06°, respectively, the highest CP was 0.4571. For these optimal values, a scaled model with 0.24 m of diameter was numerical and experimentally studied and the findings were compared. A good agreement was found between the numerical results regarding the lab-scale turbine and the experimental data for the CP values obtained as a function of the tip speed ratio.

Effect of Shot Peening Parameters on PLA Parts Manufactured with Fused Deposition Modeling

Fused deposition modeling (FDM) is a technology with potential benefits such as material versatility, user-friendliness, and cost-effectiveness. However, the mechanical properties of FDM-printed specimens are relatively low. To address this issue, post-processing techniques such as shot peening can be employed. Shot peening is utilized as a post-treatment for metal-based and ABS materials, but its application to PLA material has not been explored yet. This study aimed to evaluate the effect of shot peening on the mechanical properties of FDM-printed PLA samples. A full factorial experimental design was employed with shot peening speed, duration, and number of outer shells as parameters. The tensile strength of 72 samples after the shot peening process was measured and evaluated. Analysis of variance (ANOVA) revealed that all parameters had a significant influence on tensile strength. Additionally, the interaction of speed*time and speed*number of shells also had a significant influence. Meanwhile, the interaction of time*number of shells and speed*time*number of shells had no significant influence. The findings of this study demonstrate the potential of post-processing techniques to enhance the mechanical strength of FDM components, particularly those composed of PLA material.