Statistical Factorial Analysis Research Articles

Anand Model Constants of Sn-Ag-Cu Solders: What Do They Actually Mean?

Abstract Finite element simulations are broadly utilized to calculate the thermally induced mechanical deformations of interconnecting solder materials in electronics. The Anand unified viscoplasticity model is a prevalent choice for simulating the mechanical responses of solder joints, comprising nine parameters whose individual effects are not fully addressed in the literature. For this reason, this study examines the influence of each Anand parameter on the mechanical response of leadless Tin-Silver-Copper solder alloys with varying silver content through comprehensive nonlinear finite element simulations. Anand model coefficients for different SAC alloys, including SAC105, SAC205, SAC305, and SAC405, were sourced from existing literature and used to establish a systematic study matrix for each parameter. These coefficients were then integrated into thermomechanical simulations to induce inelastic deformations in the solder interconnections. The response of the solder interconnects is analyzed using equivalent inelastic strains and inelastic strain energy density. Results indicated that specific Anand parameters could skew the solder joint stress-strain response towards brittle behavior, while other parameters could lead to a more ductile response. Through statistical factorial analysis, the significance of each parameter is found to vary considerably, ranging from negligible to highly significant. The findings of this study are crucial for understanding the behavior of different SAC solder configurations and their expected thermal fatigue performance based on Anand creep constants. Furthermore, this paper provides foundational insights into the interpretation of Anand coefficients and their influence on the mechanical response of solder materials, a topic not yet explored in the existing literature.

Development and characterization of flexible carbon temperature sensors: a study on different inks and sensor designs

Several industries and applications rely on the accurate monitoring of temperature. Consequently, the development and integration of reliable and flexible temperature sensors that are able to conform to different surfaces is desirable. Despite being a known fact that the used materials, chosen technologies, sensor size, and design tend to impact the performance of said sensors, not many studies focus on the analysis of the influence of these factors. As a result, this work intended to explore how the performance of carbon-based screen-printed temperature sensors could be tuned or optimized by changing the ink and the design of the printed sensors. Therefore, two commercial carbon inks and three different designs were used to create the herein-studied temperature sensors. Firstly, to explore potential differences between the used inks, their morphologic, chemical, and electrical properties were evaluated, allowing further insights to be gathered regarding the filler type, composition, and bulk resistivity. After printing the sensors, they were also submitted to electrical impedance spectroscopy, which allowed for a circuit equivalent model to be proposed for each sensor type, unraveling how current flew across the printed materials. Then, a full factorial statistical analysis was outlined and conducted to uncover which combination of factors allowed to optimize the sensors’ performance, i.e. lower initial resistance, higher thermal coefficient of resistance (TCR), and higher correlation coefficient (R2) of the responses. To gather the experimental data, the electrical response of the sensors (resistance variation) to increasing temperature was collected. As a result of these experiments, it was revealed that ink 1 (based upon carbon nanoparticles) allowed to obtain less resistive sensors and, even though ink 2 (based upon carbon nanotubes) presented higher sensitivity, ink 1 resulted in higher linearity of the sensors. Overall, the factor design had less influence on the results than the factor ink. Notwithstanding, design 1 could be used to obtain sensors with lower native resistance and higher linearity. To sum up, using ink 1 combined with design 1 (fewer hoops and thicker line width) allowed to obtain temperature sensors with average resistance at room temperature of 7.8 kΩ, a TCR of 1.13 %.ºC−1, and R2 of 0.99, which means the herein studied sensors present a very promising behavior when compared to the sensors in the preexisting literature. Thus, the proposed optimized sensors presented attractive characteristics as flexible printed temperature sensors.

Experimental investigation of the effect of slenderness ratio and retention time on the separation performance of a two-phase horizontal separator

This study investigates the effect of the slenderness ratio (L/D) on the performance of a three-phase separator for constant retention times in the oil phase. The research combines experimental measurements with statistical analysis. To determine the controlling parameters of separation efficiency. The experiments varied 4 independent variables: slenderness ratios (2:1, 4:1, and 5:1); total mass flow rates (2, 3, 4, 5, and 6 GPM); oil layer thickness (9 18 27 and 36 mm) and composition. In addition, the oil flow rate, as part of the total flow, was varied to allow the oil retention time to be held constant. Taguchi and full factorial statistical analysis methods were used to analyse the results. The performance was seen to increase with increasing slenderness ratio for constant retention time. This implies that the slenderness ratio has a positive effect on separation. However, this is not a simple relationship. The main independent variables that affect separation were identified as total flow and aspect ratio, but the interaction of flow rate and slenderness ratio can cancel each other out. The interaction of the oil layer and slenderness ratio is normally insignificant but becomes controlling when the aspect ratio and flow effect cancel each other out. The performance decreases as the oil layer thickness increases and the aspect ratio decreases. This indicates that separators with shorter and wider configurations are less efficient than those with longer and slimmer designs.

Reducing damage with higher precision in drilling bones

Bone drilling poses intricate challenges due to its high hardness, strength, and anisotropic composite structure. In the dynamic field of orthopedics, advancing surgical drilling techniques is imperative for optimizing precision and implant stability. As drilling methods have progressed from conventional to robot-assisted machining, some new possibilities are now appearing. While orbital drilling has been pivotal in aerospace for reduced forces and superior hole quality, its application in bone drilling remains unexplored. This study pioneers the introduction of orbital drilling for bone machining, aiming to unveil its potential to improve processing quality. Experimental investigations were conducted on cortical femur bone to evaluate its mechanical behavior and the geometry of the holes, encompassing parameters such as hole aperture, roundness, cylindricity and delamination. Employing full factorial statistical analysis, the study systematically elucidates the influence of cutting speed and feed rate on hole quality. Results reveal the potential of orbital drilling in mitigating its defaults and could significantly contribute to improving surgical outcomes in orthopedic procedures.

Electrolytic galvanizing technology on internal surfaces of machined parts using computer numerical control (CNC)

In the present investigation, the study of the Zinc electrolytic galvanizing process on the interior surfaces for high-pressure pipe couplings is detailed, this through a statistical factorial analysis 23 that allowed to relate the 3 factors of the experimentation layout of parts, electrolyte agitation and immersion time; in this way, 8 types of possible iterations were determined in order to analyze the correlation and the incidence in the quality of the anticorrosive protection under the ISO 10289:2001 standard. The adequate levels of the electrolyte were determined using a Hull cell, and optimal working parameters were established at a temperature of 20 °C, a current density of 2.7 A/dm2 and a voltage of 5 V. After experimentation it was determined that the arrangement of the parts is the most determining factor for the coating to provide good anti-corrosion protection in combination with acid baths. The methodology used could serve as a basis for the collection of new results and possible comparisons.

Effects of Heating Rate and Temperature on the Thermal Pyrolysis of Expanded Polystyrene Post-Industrial Waste.

The use of plastic as material in various applications has been essential in the evolution of the technology industry and human society since 1950. Therefore, their production and waste generation are high due to population growth. Pyrolysis is an effective recycling method for treating plastic waste because it can recover valuable products for the chemical and petrochemical industry. This work addresses the thermal pyrolysis of expanded polystyrene (EPS) post-industrial waste in a semi-batch reactor. The influence of reaction temperature (350-500 °C) and heating rate (4-40 °C min-1) on the liquid conversion yields and physicochemical properties was studied based on a multilevel factorial statistical analysis. In addition, the analysis of the obtaining of mono-aromatics such as styrene, toluene, benzene, ethylbenzene, and α-methyl styrene was performed. Hydrocarbon liquid yields of 76.5-93% were achieved at reaction temperatures between 350 and 450 °C, respectively. Styrene yields reached up to 72% at 450 °C and a heating rate of 25 °C min-1. Finally, the potential application of the products obtained is discussed by proposing the minimization of EPS waste via pyrolysis.

Statistical Approach to Design Zn Particle Size, Shape, and Crystallinity for Alkaline Batteries

The modern alkaline primary battery is composed of a highly alkaline, gelled electrolyte-zinc powder anode dispersion (slurry), a cellulose-based separator, and an electrolytic manganese dioxide (EMD) cathode pellet – typically arranged in a cylindrical cell geometry. This battery system has its origins in the 1950s and thus has had decades to be researched and matured and it is known that the limiting performance of this battery system is concentrated at the slurried zinc anode. This had led many researchers to focus on the anode for improvement with most previous engineering efforts targeting enhanced performance, capacity, and stability of this material. Due to the various material fabrication processes involved with manufacturing industrial zinc powder, there exists an array of unique zinc particle size, shape, and crystallinity combinations that distinguish industrial zinc powders from one another. These industrial zinc powders are typically produced through trial-and-error processes using existing “rules of thumb”. Consequentially, it is possible that something has been missed and a data-driven approach could elucidate the optimum combination of zinc particle properties.In this study, we investigate the effect of Zn particle size, shape, and degree of crystallinity on the achievable capacity and corrosion current. Various types of zinc powders were sieved into size fraction ranges and chemically and thermo-chemically treated to control their crystallinity. The procedure for producing zinc powders of various sizes, shapes, and crystallinities led to a 64-powder Zn matrix that was then electrochemically analyzed by linear sweep voltammetry to determine the corrosion current and galvanostatically discharged to determine the achievable capacity. These experiments were done in a newly-designed, custom-built electroanalytical cell that will be described in the talk. Following the data collection, a 4k factorial statistical analysis was performed. This analysis identified which of the controlling variables have a statistically significant influence on the achievable capacity and corrosion. The statistical model was also able to provide guidance regarding the preferred particle shape. This information can be used to develop actionable procedures for battery manufacturers to create cells that are more stable, longer lasting, and have higher energy densities.

Analysis of the Most Relevant Factors for Routing in Internet of Space Things Networks

The “Internet of Space Things” (IoST) is an emerging paradigm to provide Internet and data services around the globe. IoST networks can potentially support the deployment of services in underserved areas, such as monitoring inaccessible areas for early warning applications, open ocean and sea ice monitoring, and surveillance of remote ecosystems such as forests and jungles, among others. To enable the IoST paradigm, designing and developing appropriate routing protocols is crucial. This work presents a methodology based on 2k factorial statistical analysis and an in-house developed space simulator (available upon request) to identify the critical factors affecting the performance of routing protocols in “Internet of Space Things” scenarios. The analyzed factors consider reactive and proactive routing approaches, connectivity, and the freshness of routing information. The results provide essential lessons for the research community to design protocols that could adapt under different IoST scenarios. The 2k factorial analysis applied in the study of the routing protocols’ performance can be an effective tool for developing specialized routing protocols.

Spatially Controlled Generation and Probing of Random Telegraph Noise in Metal Nanocrystal Embedded HfO2 Using Defect Nanospectroscopy

Random telegraph noise (RTN) is often considered a nuisance or, more critically, a key reliability challenge for miniaturized semiconductor devices. However, this picture is gradually changing as recent works have shown emerging applications based on the inherent randomness of the RTN signals in state-of-the-art technologies, including true random number generator and IoT hardware security. Suitable material platforms and device architectures are now actively explored to bring these technologies from an embryonic stage to practical application. A key challenge is to devise material systems, which can be reliably used for the deterministic creation of localized defects to be used for RTN generation. Toward this goal, we have investigated RTN in Au nanocrystal (Au-NC) embedded HfO2 stacks at the nanoscale by combining conduction atomic force microscopy defect spectroscopy and a statistical factorial hidden Markov model analysis. With a voltage applied across the stack, there is an enhanced asymmetric electric field surrounding the Au-NC. This in turn leads to the preferential generation of atomic defects in the HfO2 near the Au-NC when voltage is applied to the stack to induce dielectric breakdown. Since RTN arises from various electrostatic interactions between closely spaced atomic defects, the Au-NC HfO2 material system exhibits an intrinsic ability to generate RTN signals. Our results also highlight that the spatial confinement of multiple defects and the resulting electrostatic interactions between the defects provides a dynamic environment leading to many complex RTN patterns in addition to the presence of the standard two-level RTN signals. The insights obtained at the nanoscale are useful to optimize metal nanocrystal embedded high-κ stacks and circuits for on-demand generation of RTN for emerging random number applications.

Retrofit Measures Evaluation Considering Thermal Comfort and Energy Efficiency in School Buildings Using Design of Experiments

An evaluation of retrofitting public school buildings for energy-efficiency without sacrificing thermal comfort was investigated using the design of experiments. A current school building was used as a case study for this research. Three building codes were applied to improve energy efficiency in school buildings in Jordan. These codes are the Jordan building code, The Pearl Rating System for Estidama ‘’Emirate of Abu Dhabi’’ and Jordan Green Building Council booklet. By using the three codes, six-building construction cases were derived by changing the U- values to enhance the thermal insulation for buildings, such as changing the material used in external walls and roof or Window to Wall Ratio ‘’WWR’’. A statistical factorial analysis was performed to understand the main effect of each variable on the heating and the cooling load and if there is any interaction between these variables. The seven parameters used in the statistical analysis were; U-roof (0.18-1.963 W/m2. K), U-wall (0.24-0.682 W/m2.K), U-glass (3.63-6.11 W/m2.K), WWR for north, south, east and west (33.5%-50%). After keeping the U-wall constant (UW= 0.682 W/m2.K ) based on the payback period results, a second statistical analysis was performed on other parameters such as external shading (no shade or 1.6m shade from building surface) and U-roof ( 0.18-1.963 W/m2.K), U-glass(3.63-6.11 W/m2.K), WWR for north, south, east and west (33.5%-50%). An optimization technique was finally utilized to summarize all the relations between variables and the cost of materials by using Lagrange multipliers; an equation was written and solved by EES software.

Microwave Dewatering of Gibbsite-Type Bauxite Ores: Permittivities, Heating Behavior and Strength Indices

Microwave radiation is a relatively new energy source that is being considered for several applications in mineral processing and extractive metallurgy. In the present research, various gibbsite-type bauxite ores were subjected to microwave radiation. The main objective was to assess the effect of microwave dewatering on the compressive strength indices of the ores and to compare the results obtained to those for conventional heating. Firstly, the fundamental interactions of the microwaves with the ores were evaluated by determining both the real and the imaginary permittivities as a function of temperature, and these were related to the water content. Secondly, the microwave heating behavior was modeled using a 24 factorial statistical analysis. Thirdly, the effect of dewatering by microwave heating on the compressive strength indices of roughly spherical bauxite ore pisoids was studied, and these results were compared to those obtained using conventional heating. Fourthly, the effect of particle size on the compressive strengths of irregular-shaped single particles of bauxite ore was investigated using both heating techniques. Finally, the energy requirements for dewatering of the ores, and hence reducing their compressive strengths, were compared for both processes. On the laboratory scale, the results showed that in comparison to conventional dewatering, microwave dewatering resulted in lower strength indices at both lower moisture removals and energy inputs.

Optimization Studies of Elemental Composition of Composite Polymer for Neutron Shielding Using Factorial Design Analysis

The present study is envisaged with an aim to highlight a novel approach of applying the statistical factorial design analysis (FDA) technique in radiation shielding design. In FDA, the estimated total dose rate (TDR) and concentration of elements in shielding material are termed as “Response” and “Factors.” The impact on the response due to the change in the level of factors is defined as “Effects.” Monte Carlo simulation (MCS) is performed using the MCNP4A code to compute the surface TDRs due to the coupled neutron-gamma field arising from the 740-GBq 241Am-Be source housed inside a shielding container made of composite polymer (CP). The composition of CP is hydrogen, carbon, and oxygen with lead and natural boron as fillers. In the present work, the weight percent of hydrogen, carbon, and lead is optimized in the CP by minimizing the surface TDR at the exit of the shield, and a proposed CP (PCP) is obtained. For the first time, a detailed regression analysis is performed to develop a model linking TDR and the three factors, namely, hydrogen weight percent, carbon weight percent, and lead weight percent. Three levels of each factor are considered, and the impact due to the linear, quadratic, and interaction effects of the factors that influences the TDR is investigated using Student’s t-test analysis. The results from the statistical analysis indicate that the weight percent of hydrogen and lead have a greater influence on TDR. The interaction effects arising out of the combination of hydrogen, carbon, and lead are observed to be negligible. Hence, the regression model is modified by dropping the statistically insignificant terms from the equation, and the new model has shown excellent correlation within ±1% of the estimated TDRs using MCS. The R2 and R2 Adj values are found to be 0.99970 and 0.99966, which explains the computation power of the model. The model can be applied to compute the TDRs for any combinations of factors within the range of variability as studied in the present work. The shielding container made of PCP obtained from the present study provides a minimum of 20% reduction in volume and mass compared to the conventional high-density polyethylene and other polymer-based materials.

Exploring uncertainty in thermodynamic modeling of the lead carbonate aqueous system

Abstract Thermodynamic models of the lead carbonate aqueous system have been used in prior studies to evaluate the effect of water chemistry on lead solubility and corrosion scale composition in water distribution systems. A common challenge in these studies is uncertainty arising from the thermodynamic equilibrium constants (logK values) used to parameterize the models. The objective of this study is to evaluate the way in which uncertainty in logK values propagates through thermodynamic models of the lead carbonate system and provide guidance for future modeling efforts. This was done by conducting a full factorial statistical analysis implemented using a custom Python (v3) code coupled with a PHREEQC (v1.4.2) geochemical model, along with batch lead solubility experiments. Two lead carbonate solid phases (cerussite and hydrocerussite) and nine aqueous lead complexes are considered in the geochemical model with conditions simulated ranging from pH 4 to 11 and dissolved inorganic carbon (DIC) ranging from 0 to 250 mg C/L. Main effect analysis indicates that model uncertainty is predominately associated with logK values for five species (in order of decreasing effect): hydrocerussite, , cerussite, PbOH+, and PbCO3o, with model uncertainty varying depending on the specific pH and DIC conditions simulated. Interaction effects show that logK values cannot be selected independently, as their influence on lead solubility is connected. Finally, by considering uncertainty in logK values it was possible for the thermodynamic model to match batch hydrocerussite solubility experimental data over a range of pH and DIC conditions. Six combinations of logK values that provided a good match between the simulated and experimental data were determined with the average difference between the simulated and experimental lead concentrations calculated to be 0.031 mg/L when the recommended logK value combination was used.

Modeling and statistical analysis of complexity in manufacturing systems under flow shop and hybrid environments

In manufacturing systems, there are environments where the elaboration of a product requires a series of sequential operations, involving the configuration of machines by stages, intermediate buffer capacities, definition of assembly lines, and routing of parts. The objective of this research is to develop a modeling and statistical analysis of complexity in manufacturing systems under flow shop and hybrid environments. The methodological approach starts with the structural modeling, then the measurement of the complexity in the systems is developed, the hypotheses are proposed, and finally an experimental and factorial statistical analysis is developed. The results obtained corroborate the hypotheses proposed, where statistically the structural design factors and the variation of production time per stage have a significant influence on the response variable associated to the total complexity. Similarly, there is evidence of correlation between the performance indicators and the variable studied, in which the incidence with production costs stands out.

Dyeing and colour fastness in cotton and wool, using natural extracts of sunflower petals, onion peel and cocoa shell

ABSTRACT At the present time, the sustainable use of natural products in textiles is sought, in this work the dyeing of cotton and wool was carried out, with the extracts of sunflower petals, purple onion peel and cocoa shell. Applying concentrations of 50, 75 and 100% on the weight of the fiber to be dyed (cotton and wool), with three replicas. The color in each dyed fiber was measured, performing an ANOVA analysis and 5 color fastness tests were performed, with three replicates each. The ΔE value was obtained and a factorial statistical analysis was performed. As a result of dyeing, lighter colors were obtained in cotton than in wool. Regarding the color fastness, it was observed that they depended on the coloring extract applied. In the case of sunflower petals, the strength tests that most affected both fibers were washing at high temperatures and basic pH. For the purple onion peel a greater change in the wool fiber was observed. For the cocoa shell it was observed that the tests where there was more change for both fibers were those of domestic washing and at high temperatures.

Cambios en alimentación en pacientes con recurrencia de cáncer

Introducción: Hasta 30% de las causas del cáncer se atribuyen a la alimentación. Los sobrevivientes de esta enfermedad, como parte del autocuidado, deben adquirir una alimentación saludable. Este estudio pretendió describir los cambios alimentarios realizados entre el primero y segundo diagnóstico de cáncer y conocer algunas de sus causas. Materiales y Métodos: Se utilizó una muestra aleatoria de proporciones con 195 pacientes, a quienes se les aplicó una encuesta en el año 2019, relacionada con el objeto de estudio. Para el análisis de los datos, se usó el método estadístico factorial de correspondencia múltiple, análisis de clúster y distribución de frecuencias. Resultados: La salud fue lo que más motivó al cambio de hábitos alimentarios, seguido por factores asociados al tratamiento. Las personas disminuyeron el consumo de carnes con grasa, fritos, alcohol, snacks, embutidos y lácteos, aumentando la ingesta de frutas y verduras. Discusión: Luego de un segundo diagnóstico de cáncer, los participantes presentaron cambios favorables para la salud, acordes a las recomendaciones de los entes internacionales. El estado de salud y el tratamiento para el cáncer, fueron las condiciones que más influyeron para que las personas sobrevivientes de cáncer realizaran cambios en su alimentación ante un nuevo diagnóstico o una recidiva. Conclusión: Los sobrevivientes de cáncer con recidiva, modifican su alimentación hacia una vida más saludable. Se debe promover una alimentación adecuada en la población en general, y más aún en sobrevivientes de cáncer.

Compact shielding design for 740 GBq 241Am-Be neutron source transport container

For transport and storage of neutron sources, shielding materials like polymers and multi layer shields are used. A compact shielding design for 740 GBq portable 241Am-Be neutron source transport container using Monte Carlo technique is presented. In the design, a polymer host material with lead and natural boron (NB) as fillers is chosen as the shielding medium. Monte Carlo simulation (MCS) is performed for optimizing the quantity of fillers in the polymer. The total dose rate (TDR) on the surface of the container due to neutrons and gamma rays emanating from source as well as polymer shield, is considered as the optimization criterion. MCS studies indicate that a polymer material with 5% of lead and 1% of NB as fillers is observed to give optimized composition of polymer (OCP). Statistical factorial design analysis (FDA) technique is employed for the first time in the shielding design to investigate the impact of fillers in the polymer. FDA studies reveal that the quantity of lead has more significant impact compared to NB in the polymer. MCS results are validated by carrying out shielding experiments with high density polyethylene (HDPE) and composite polymer (CP) based containers. The computed and experimental dose rates are observed to be within ±12%. A shielding container made of OCP for the transport of 740 GBq 241Am-Be source provides 25% reduction in the volume as compared to HDPE and CP. The mass of the OCP container is lower by 18% and 26% compared to the containers made of HDPE and CP respectively. The surface dose rate of the OCP container adheres to the IAEA transport regulations.

Socio‐spatial inequalities and dynamics of rich and poor enclaves in three French cities: A policy of social mixing under test

AbstractThis paper analyses and compares the dynamics of sociospatial inequalities in districts of three cities located in the Northeast of France for the period 1990–1999–2006. The idea is to measure and track the dynamics of these inequalities that reveal significant urban fractures. Sociospatial disparities between districts and changes in them are measured using a multidate factorial statistical analysis. To do this, this paper collates 17 indicators from population censuses referring to characteristics of households and housing so as to compare not just the level of segregation but also the trajectory of neighbourhoods towards greater gentrification, pauperisation, or mixing. By analysing the selective processes of population distribution and urban change and monitoring them over time, this paper shows that inequalities have intensified in the three studied cities and that rich and poor segregated enclaves have become accentuated despite the objectives of social mixing of French urban policies. Other explanatory factors are therefore highlighted, such as the urban functions of the cities, residents' behaviours, and the “hidden” ethnic dimension, that all question the effectiveness of governmental actions, particularly on social mixing and diversity.

EAD: O Perfil Desejável do Professor Tutor e o Uso dos Recursos Tecnológicos

O objetivo deste estudo foi verificar a percepção dos alunos a respeito dos atributos de um bom professor tutor e o uso dos recursos tecnológicos na sala de aula em uma Instituição de Ensino Superior, na modalidade de educação a distância. Os dados foram coletados mediante aplicação de questionários para alunos EAD, totalizando uma amostra de 175 alunos. O estudo caracteriza-se como quantitativo. A análise de resultados ocorreu por meio da técnica estatística descritiva e análise fatorial exploratório. Os principais atributos para um bom professor tutor na percepção dos alunos EAD foram a postura, o relacionamento e a didática, por outro lado, a capacidade profissional e a motivação foram os atributos com menor relevância. Os recursos tecnólogos mais utilizados em sala de aula e destacados pelos alunos foram o Projetor Multimídia e o Power Point, enquanto o Tablet e o Socrative resultaram em menor uso. Estes achados indicam que, embora seja possível ampliar o uso destes recursos para o processo de ensino e aprendizagem de forma produtiva, os professores tutores ainda utilizam recursos tecnológicos tradicionais. Os resultados contribuem ainda para expandir a literatura sobre o professor tutor na EAD, comprovando seu papel de mediador.

Factorial analysis and experimental study of water-based cooling system effect on the performance of photovoltaic module

A study of the performance of a photovoltaic system with water cooling was carried out experimentally. Three main parameters, namely the water flow rate, the setpoint temperature of the photovoltaic panel, and the maximum allowable temperature difference of the photovoltaic panel, were investigated. In addition, the effect of dust accumulation, in terms of the cleanness factor, ambient temperature, and relative humidity, was studied. An experimental setup was constructed to investigate the cooling effect of water flowing over the panel surface on the performance of a photovoltaic module built at the campus of Jordan University of Science and Technology. Cooling of the photovoltaic module was performed for the period from June to September 2015. The photovoltaic module temperature was controlled to be between 30 and 50 °C, with different levels of water flow rate: high, medium, and low, i.e., 0.9, 0.6, and 0.3 m3/h, respectively. In addition, a statistical factorial analysis of the three-level full factorial design for the experimental data was conducted. It was found that the photovoltaic system performance was higher under water-cooling conditions. The optimum photovoltaic panels cooling temperature was shown to be 37 °C. The designed cooling system achieved an acceptable percentage of excess energy production, i.e., 15.28–17.75%, with minimum water losses. Furthermore, it was found from the statistical analysis that the setpoint temperature of the photovoltaic module had the largest effect on the percentage of excess energy production from photovoltaic, while the effect of maximum allowable temperature difference was negligible.