Constituent Proportions Research Articles

Simultaneous inversion of four physical parameters of hydrate reservoir for high accuracy porosity estimation

AbstractEstimation of the porosity of a hydrate reservoir is essential for its exploration and development. However, the estimation accuracy was usually less certain in most previous studies that simply assumed that there is a linear relationship between the porosity and single‐elastic wave velocities or other rock physical parameters, thus affecting the evaluation of the reserves. In the three‐phase Biot‐type equations that are fundamental to model a hydrate‐bearing reservoir, porosity, alongside hydrate saturation, mineral constituent proportions and hydrate–grain contact factor, is non‐linearly responded by density, compressional and shear wave velocities. To improve porosity estimation, we propose to invert simultaneously four‐parameter (porosity, hydrate saturation, mineral constituent proportions and hydrate–grain contact factor) using an iteratively nonlinear interior‐point optimization algorithm to solve a nonlinear objective function that is a summation of the squared misfits between the well log and three‐phase Biot‐type equation–modelled density, compressional and shear wave velocities. A test in Mount Elbert gas hydrate research well was conducted for the case of a gas hydrate stratigraphic test well where elastic wave velocities, density, porosity and mineral composition analysis data are available. The four‐parameter inversion yielded a lower root mean square error for porosity (0.0245) across the entire well‐logging section compared to previous estimations from the linear relationship, post‐stacked and pre‐stacked seismic traces as well as the pore‐filling effective medium theory model applied to other well cases. Additionally, the other three parameters demonstrated good agreement with well logs. Inversion tests conducted at three additional hydrate sites also produced accurate results. Consequently, the new method surpasses previous approaches in porosity estimation accuracy.

Optimizing compressive strength of quaternary-blended cement concrete through ensemble-instance-based machine learning

Optimizing the composition of concrete, particularly when incorporating ordinary Portland cement (OPC) along with supplementary materials such as ground granulated blast furnace slag (BF), fly ash (FA), and silica fume (SF), poses challenges due to the intricate nonlinearity inherent in concrete properties. Addressing this challenge has urged growing interest in employing Machine Learning (ML) techniques for precise property assessment. In this investigation, various predictive models, encompassing eXtra Gradient Boosting (XGB), random forests (RF), and K-Nearest Neighbor (KNN) algorithms were formulated to predict the compressive strength (CS) of ternary-blended concrete incorporating OPC, BF, FA, and SF. Through comprehensive analysis of an extensive dataset comprising 810 distinct records, the study identifies optimal concrete blends, providing invaluable insights for practical applications. Evaluation of ML models underscores the superior performance of XGB, with a coefficient of multiple determination (R2) values of 0.923 and 0.997 for training and testing datasets, respectively, indicative of exceptional predictive accuracy. Additionally, SHAP values underscore the importance of input age, water–binder ratio, and OPC content. This research enhances understanding of ternary-blended concrete characteristics, offering practical implications for construction practices and laying a foundation for future research endeavors to refine ML models, explore attribute interactions, and optimize concrete constituent proportions for broader civil engineering applications.

Effect of pore water pressure on mechanical performance of recycled aggregate concrete under triaxial compression

The pore water pressure in concrete can significantly increase due to volume compression. Recycled aggregate concrete (RAC) possesses a more complex microstructure compared to natural aggregate concrete (NAC). Understanding the porosity and micromechanical properties of RAC is crucial for analysing its failure mechanism under the influence of coupled confining pressure and pore water pressure. This study compares the constituent proportions and micromechanical properties of interfacial transition zones (ITZs) and the adjacent paste matrix in NAC and RAC. Compressive stress-strain curves were obtained for concrete under coupled confining pressure and pore water pressure. The results indicate that the newly formed ITZ, which bonds to old mortar, outperformed the one bonded to natural aggregate when considering the same water-cement ratio. Compressive strength, ductility, and maximum volumetric strain gradually increased with increasing confining pressure. However, when pore water pressure was removed, compressive strength decreased while elastic modulus improved. Due to the inferior microstructures of RAC compared to NAC, the supportive effect of pore water becomes more pronounced. This is evident in the gradual increase in peak strain with increased pore water pressure for the stress-strain curves of RAC (100 % replacement ratio). Finally, a failure criterion and stress-strain theoretical model considering pore water pressure are proposed, and satisfactory fitting results are obtained.

Optimization of constituent proportions for compressive strength of sustainable geopolymer concrete: A statistical approach

Geopolymer concrete (GPC) is an environmentally friendly and sustainable concrete produced through the geopolymerization process, involving the combination of alumino silicate materials with alkaline solutions. It has unique advantage of being carbon-negative which helps reduce carbon dioxide levels in the atmosphere. One challenge with making GPC is the significant variation in compressive strength that arises from differences in constituent proportions, specimen ages, andcuring conditions. There is a need to optimize the GPC constituents to achieve the desired compressive strength. To address this issue, a comprehensive dataset comprising 1242 data points from existing literature on fly ash-based GPC (FA-based GPC) was compiled for the purpose of optimizing the constituent proportions of GPC using statistical analysis. Nine independent variables were selected to develop the predictive models for compressive strength using linear (LRA), multilinear (MRA), and non-linear (NRA) regression analyses. The models were assessed using scatter plots between experimental and predicted responses and adopting the performance criteria such as the statistical significance of the model unknowns, R2 values, root mean square error (RMSE), mean absolute error (MAE), and scatter index (SI). LRA revealed that the compressive strength of GPC is not dependent on any single independent variable. Therefore regression analysis with multiple independent variables was conducted. From MRA, ±15 % error for training dataset and (15–20) % error for validating dataset was estimated. The R2, RMSE, MAE, and SI values were found to be 0.8086, 6.11, 5.35, and 0.21. NRA predicted the compressive strength more efficiently because it provides the error ±10 % for both training and validating datasets with R2, RMSE, MAE, SI values of 0.8321, 5.46, 4.77, and 0.19. Further, curing temperature, specimen age, Na2SiO3/NaOH ratio, I/b ratio, and aggregate content were found as the most significant independent variables. The time and cost-effective design mix for FA based GPC can be prepared using the regression models presented in the current work.

Investigating the Structural and Lithium Storage Properties of High-Entropy Oxides in the Mg-Co-Ni-Cu-Zn-O System

Recently, a new class of materials known as high-entropy oxides (HEOs) has emerged as an alternative electrode material for the next-generation Li-ion batteries. However, the discovery of these materials brings forth a broad range of compositions remained unexplored. This study aimed to investigate the structural and electrochemical characteristics of the non-equiatomic HEOs. Accordingly, ten different samples were synthesized in the Mg-Co-Ni-Cu-Zn-O system at very high (35 mol. %) and very low (5 mol. %) constituent proportions. Our experimental and theoretical results indicated that the thermodynamic stability of the HEOs was affected significantly by the enthalpic contributions arising from the lattice strain. These findings may provide a more consistent design approach in selection of a suitable component for the synthesis of the single-phase HEOs. Furthermore, the specific capacity, cycling stability and lithiation voltage of the electrodes have also been shown to be influenced by each individual constituent of the electrode.

Clinical and epidemiological characteristics of 369 patients with pelvic fractures in Eastern Zhejiang Province of China: a retrospective study

BackgroundData on the epidemiological characteristics and prognostic factors of patients with pelvic fractures are lacking, particularly in China. This study aimed to summarise the clinical and epidemiological characteristics of patients with pelvic fractures in eastern Zhejiang Province, China, and to identify risk factors for poor prognosis.MethodsThe clinical data of 369 patients with pelvic fractures admitted to the Ningbo No. 6 Hospital between September 2020 and September 2021 were retrospectively analysed. Data on the demographic characteristics; fracture classification; injury time, cause, and site; treatment plan; and prognosis were collected using the Picture Archiving and Communication System and the Hospital Information System. Differences in constituent proportions were analysed using the chi-square test. Logistic regression analysis was used to identify factors affecting patient prognosis. Statistical significance was set at p ≤ 0.05.ResultsAmong the 369 patients, there were 206 men and 163 women, at a ratio of 1.26:1, and the average age was 53.64 ± 0.78 years. More than 50% of patients were aged 41–65 years. The average length of hospital stay was 18.88 ± 1.78 days. The three most common causes of pelvic fractures were traffic accidents (51.2%), falls from height (31.44%), and flat-ground falls (14.09%). There were significant differences in the distribution of the three causes of injury depending on age (p < 0.001), sex (p < 0.001), and occupation (p < 0.0001). Most patients were manual workers (48.8%). Furthermore, most patients (n = 262, 71.0%) underwent surgical treatment for pelvic fractures. Postoperative complications occurred in 26 patients (7.05%), and infection was the main complication (73.08%). Age (p = 0.013), occupation (p = 0.034), cause of injury (p = 0.022), treatment options (p = 0.001), and complications (p < 0.0001) were independent factors affecting the prognosis of patients with pelvic fractures. One death (0.027%) occurred, which was due to severe blood loss.ConclusionsAge, occupation, cause of injury, treatment options and complications were factors affecting patient prognosis. In addition, changes in blood flow and prevention of infection warrant attention.

Feasibility analysis for predicting the compressive and tensile strength of concrete using machine learning algorithms

Concrete is the most utilized material (i.e., average production of 2 billion tons per year) for the construction of buildings, bridges, roads, dams, and several other important infrastructures. The strength and durability of these structures largely depend on the compressive strength of the concrete. The compressive strength of concrete depends on the proportionality of the key constituents (i.e., fine aggregate, coarse aggregate, cement, and water). However, the optimization of the constituent proportions (i.e., matrix design) to achieve high-strength concrete is a challenging task. Furthermore, it is essential to reduce the carbon footprint of the cementitious composites through the optimization of the matrix. In this research, machine learning algorithms including regression models, tree regression models, support vector regression (SVR), ensemble regression (ER), and gaussian process regression (GPR) were utilized to predict the compressive and tensile concrete strength. Also, the model performance was characterized based on the number of input variables utilized. The dataset used in this research was compiled from journal publications. The results showed that the exponential GPR had the highest performance and accuracy. The model had an impressive performance during the training phase, with a R2 of 0.98, RMSE of 2.412 MPa, and MAE of 1.6249 MPa when using 8 input variables to predict the compressive strength of concrete. In the testing phase, the model maintained its accuracy with a R2 of 0.99, RMSE of 0.0025134 MPa, and MAE of 0.0016367 MPa. In the training and testing phases, the exponential GPR also demonstrated high accuracy in predicting the tensile strength with an R2, RMSE, and MAE of 0.99, 0.00049247 MPa, and 0.00036929 MPa, respectively. Furthermore, in the prediction of tensile strength the number of variables utilized had an insignificant effect on the performance of the models. However, in predicting the compressive strength, an increase in the number of input variables lead to an enhancement in the performance metrics. The results of this research can allow for the quick and accurate prediction of the strength of a given concrete mixture design.

Effects of Particle Dimension and Constituent Proportions on Internal Bond Strength of Ultra-Low-Density Hemp Hurd Particleboard

The recent legalisation of hemp seeds for human consumption has revitalised the cultivation of hemp in Australia. This provides opportunities for the valorisation of the stem’s residual xylemic core (hemp hurd). This study investigated the effect of particle dimension and constituent proportions on the internal bond strength (IB) of single-layer, ultra-low-density hemp hurd particleboard (ULHPB) with densities between 219 to 304 kg/m3. Particle size distributions (PSD) and granulometry assessments were conducted on three particle size classes (fine (F), medium (M), coarse (C)) based on digital image analysis using ImageJ. Subsequently, four particle size mixes (100% C, 100% M, 50/50% CM, 25/50/25% CMF) were considered for the ULHPB manufacture with bio-epoxy (EPX), phenol resorcinol formaldehyde (PRF) and emulsifiable methylene diphenyl diisocyanate (MDI) adhesives, respectively. The effect of particle loading and adhesive content varied significantly per adhesive type. Internal bond (IB) performance increased in most ULHPB comprising coarse particles and declined with the addition of smaller particle sizes. The granulometry assessment showed the smallest mean elongation amongst particles in the coarse PSD. The IB results confirmed a strong interdependence of particle size and constituent proportions and indicated that various MDI-ULHPB variants can surpass the minimum IB strength requirement of 0.30 MPa stipulated for standard particleboard (&gt;12–22 mm) in AS/NZS 1859.1. Utilising residual hemp biomass as an alternative, renewable lignocellulosic feedstock in the manufacture of engineered lightweight panel products is a key principle of circular economy and an environmentally friendly strategy to address the increasing resource scarcity in the wood-based panel industry.

Changing trends in clinical research literature on PubMed database from 1991 to 2020

BackgroundClinical research publications have become the dominant source and basis of clinical evidence-based decision-making. Exploring the type and quantity of clinical research publications in the PubMed database is useful for clarifying the changing trends of clinical research development in recent years. Therefore, a longitudinal analysis of the type and quantity of clinical research publications in the PubMed database over three decades was conducted.MethodsThe PubMed database was searched to retrieve clinical research according to the type and year of publication from January 1, 1991 to December 31, 2020. The research types were classified as primary and secondary literature.ResultsA total of 1,078,404 primary literatures were retrieved and the constituent proportions were ranked from high to low as case report/series (27.54%), randomized clinical trials (RCTs) (23.62%), cohort studies (21.05%), cross-sectional studies (17.49%), case control studies (9.15%), non-RCTs (1.01%), and pragmatic clinical trials (PCTs) (0.15%). Correspondingly, 1,302,173 secondary literatures were retrieved and ranked as narrative review (70.88%), systematic review (15.02%), systematic review and meta-analyses (13.89%), traditional meta-analyses (4.48%), expert consensus (2.31%), guidelines (1.49%), scoping reviews (0.68%), net meta-analyses (0.40%), and umbrella reviews (0.04%). The average annual growth rate for the primary literature was 10.28%, and ranked from high to low as PCTs (83.68%), cohort studies (17.74%), cross-sectional studies (17.61%), non-RCTs (12.11%), case control studies (8.86%), RCTs (7.68%), case report/series (7.51%); while that for the secondary literature was 10.57%, and ranked from high to low as net meta-analyses (48.97%), umbrella reviews (47.09%), scoping reviews (41.92%), systematic reviews and meta-analyses (33.44%), systematic reviews (33.05%), traditional meta-analyses (12.49%), expert consensuses (9.22%), narrative review (8.72%), and guidelines (2.82%). ConclusionBoth the composition and number of clinical studies changed significantly from 1991 to 2020. Based on the trend, the case report/series, case control study, and narrative review are on the decline, while cohort study, cross-sectional study, systematic reviews, and systematic review and meta-analysis literature have increased. To improve the quality of clinical evidence, we recommend RCT and cohort study give priority to access to allocated research resources in future.

Analysis of a Rectangular FML composite subjected to coupled thermo-mechanical multi-axial loading

Glare composites are a new set of materials with a combination of metal- fibre layers where glass fibre/epoxy and aluminium alloy are used as its constituent elements. By varying the constituent proportions and types the behaviour of the material changes. In the present study, Glare 4B combination is considered with specific overall thickness as constant and varying the ply thickness by changing the number of plies in each set as 8, 12, 16, 20, and 24 plies. The effect of number of layers and aspect ratios over the failure mechanical properties when subjected to coupled thermo – mechanical multi – axle loading conditions is under study. As number of layers increases each individual layer thickness goes on reducing and the effect of it over failure loads is presented. As the aspect ratio increases the relative comparable factor value is diminishing. Aspect ratio of 1 is considered to be better choice as S1 & S2 at bottom and top layers are inhibiting the stress limits. When it is required for an alternative value as per design considerations it is good to choose aspect ratio of 1.25.

Improved balance between compressive strength and thermal conductivity of insulating and structural lightweight concretes for low rise construction

In order to save energy consumption in concrete buildings, there is a demand for structural cement-based materials with low thermal conductivity and sufficient compressive strength. This paper evaluates the effect of various proportion combinations of three concrete constituents namely, coarse expanded clay (CEC), fine expanded clay (FEC) and fly ash (FA), on the thermal conductivity and compressive strength of concrete at equilibrium density. The use of FEC produced a greater reduction in thermal conductivity and a lower reduction in compressive strength than using CEC. This is due to the finer pore size distribution, smaller maximum pore size and better spatial distribution within the mixture of the FEC. FA alone presents the least significant effect on both thermal and mechanical properties, but the combination of the three constituents shows capabilities to reduce the thermal conductivity, as well as the compressive strength within acceptable limits. The study shows the constituent proportions, which can be used in concrete mixtures towards an improved balance between compressive strength and thermal conductivity for low-energy concrete building applications.

Arctic freshwater fluxes: sources, tracer budgets and inconsistencies

Abstract. The net rate of freshwater input to the Arctic Ocean has been calculated in the past by two methods: directly, as the sum of precipitation, evaporation and runoff, an approach hindered by sparsity of measurements, and by the ice and ocean budget method, where the net surface freshwater flux within a defined boundary is calculated from the rate of dilution of salinity, comparing ocean inflows with ice and ocean outflows. Here a third method is introduced, the geochemical method, as a modification of the budget method. A standard approach uses geochemical tracers (salinity, oxygen isotopes, inorganic nutrients) to compute “source fractions” that quantify a water parcel's constituent proportions of seawater, freshwater of meteoric origin, and either sea ice melt or brine (from the freezing-out of sea ice). The geochemical method combines the source fractions with the boundary velocity field of the budget method to quantify the net flux derived from each source. Here it is shown that the geochemical method generates an Arctic Ocean surface freshwater flux, which is also the meteoric source flux, of 200±44 mSv (1 Sv=106 m3 s−1), statistically indistinguishable from the budget method's 187±44 mSv, so that two different approaches to surface freshwater flux calculation are reconciled. The freshwater export rate of sea ice (40±14 mSv) is similar to the brine export flux, due to the “freshwater deficit” left by the freezing-out of sea ice (60±50 mSv). Inorganic nutrients are used to define Atlantic and Pacific seawater categories, and the results show significant non-conservation, whereby Atlantic seawater is effectively “converted” into Pacific seawater. This is hypothesized to be a consequence of denitrification within the Arctic Ocean, a process likely becoming more important with seasonal sea ice retreat. While inorganic nutrients may now be delivering ambiguous results on seawater origins, they may prove useful to quantify the Arctic Ocean's net denitrification rate. End point degeneracy is also discussed: multiple property definitions that lie along the same “mixing line” generate confused results.

NMR-based approach reveals seasonal metabolic changes in mate (Ilex paraguariensis A. St.-Hil.).

Ilex paraguariensis (mate) is a species native to South America and is widely consumed in countries such Argentina, Uruguay, Paraguay, and Brazil. Mate consumption is associated with several phytotherapeutic functions, in addition to its cultural and regional importance. However, the harvest period can affect the properties of the mate, due to variations in the constituent proportions, as a consequence of seasonal changes. In this work, we employed nuclear magnetic resonance and chemometrics to evaluate the chemical variations in leaf extracts of I.paraguariensis over the four seasons of the year. We found significant changes in the levels of glucose, myo-inositol, caffeine, theobromine, and fatty acids. These changes can be related to resource allocation for the flowering period, or to responses to environmental stresses, such as temperature.

Characteristics of global organic matrix in normal and pimpled chicken eggshells

The organic matrix from normal and pimpled calcified chicken eggshells were dissociated into acid-insoluble, water-insoluble, and facultative-soluble (both acid- and water-soluble) components, to understand the influence of shell matrix on eggshell qualities. A linear correlation was shown among these 3 matrix components in normal eggshells but was not observed in pimpled eggshells. In pimpled eggshells, the percentage contents of all 4 groups of matrix (the total matrix, acid-insoluble matrix, water-insoluble matrix, and facultative-soluble matrix) were significantly higher than that in normal eggshells. The amounts of both total matrix and acid-insoluble matrix in individual pimpled calcified shells were high, even though their weight was much lower than a normal eggshell. In both normal and pimpled eggshells, the calcified eggshell weight and shell thickness significantly and positively correlated with the amounts of all 4 groups of matrix in an individual calcified shell. In normal eggshells, the calcified shell thickness and shell breaking strength showed no significant correlations with the percentage contents of all 4 groups of matrix. In normal eggshells, only the shell membrane weight significantly correlated with the constituent ratios of both acid-insoluble matrix and facultative-soluble matrix in the whole matrix. In pimpled eggshells, 3 variables (calcified shell weight, shell thickness, and breaking strength) were significantly correlated with the constituent proportions of both acid-insoluble matrix and facultative-matrix. This study suggests that mechanical properties of normal eggshells may not linearly depend on the organic matrix content in the calcified eggshells and that pimpled eggshells might result by the disequilibrium enrichment of some proteins with negative effects.

Chemical composition of essential oil extracted from leaves of Campomanesia adamantium subjected to different hydrodistillation times

ABSTRACT: Campomanesia adamantium is a native fruit species of the Cerrado and is used in food and medicines and as bee pasture. The chemical composition of essential oils obtained from plants of the same species have varying constituent proportions due to the influence of extractive factors, environmental, genetic and ontogenetic. This study aimed to identify the influence of hydrodistillation time on the content and chemical composition of essential oil extracted from the leaves of C. adamantium . Treatments consisted of five extraction times (1, 2, 3, 4, and 5h) using Clevenger with five replications in a completely randomized design. It was observed that after two hours of hydrodistillation, the essential oil content remains constant. Regarding the chemical constituents of essential oil, variation of the proportions of the compounds tested occurred at all hydrodistillation times. The compounds spathulenol oxygenated sesquiterpenes and caryophyllene oxide were the majority in the five hydrodistillation times.

State-of-the-art and practice review and recommended testing protocol: self-consolidating concrete for prestressed bridge girders

Self-consolidating concrete (SCC) is a highly flowable, non-segregating concrete. Relevant technology and applications have steadily grown in various construction fields in the United States. Several State Departments of Transportation (DOTs) have performed significant research on SCC for prestressed bridge girders, resulting in their own guidelines. The objective of this study is to summarise the current state-of-the art and practice of technical documentation and specifications related to material properties for prestressed SCC bridge girders. To seek more practical information, a cursory survey among SCC experts at each DOT was performed and summarised herein. Key findings indicate that testing for the examination of fresh and hardened SCC properties are necessary for prestressed bridge girder applications. It is important to determine constituent proportions of the mixture and need of admixtures, as well as to require higher early compressive strengths required for prestressed SCC bridge girders. Based on the literature review and survey, a material property testing protocol to efficiently investigate SCC mix performance for prestressed bridge girders is recommended.

Development and Assessment of Polyester Reinforced with Sansevieria Cylindrica/Zawa Flour Composites

This paper zero in on preparation of hybrid composites in which Polyester matrix filled with Sanseveria cylindrica fiber(SCF) and Zawa flour. SCF fiber was taken 10% volume constantly in all the samples. Camera ready samples were prepared using hand layup technique in which filler constituent proportions were taken by using rule of hybrid mixture (RoHM). The mail aim of the composites is to increase the tensile flexural, and impact strengths, TGA, DSC results by incorporating the filler. It was observed that, tensile strength was linearly increased up to 4wt.% zawa after that sudden falling was observed. On other hand, tensile modulus was increased linearly up to 5wt.% was the clear indication of addition of zawa imparts more stiffness to the composites. Flexural strength was increased up 3wt.% zawa flour after than it starts depreciating suddenly. Flexural modulus was increased linearly up to 3wt.% zawa four composites after that decreases. Impact strength was optimised at 4wt.% zawa flour after that it starts going down. In DSC analysis, for 3wt.% zawa flour composite registered good performance than the 2wt.%,whereas in TGA analysis 3wt.% composite was having good performance than 2wt.% zawa flour composites. Reasons attributed for increased glass transition temperature was due to the less moisture content or due to the deprived of void due to the good bonding strength

Development and Assessment of Polyester Reinforced with Sansevieria Cylindrica/Zawa Flour Composites

This paper zero in on preparation of hybrid composites in which Polyester matrix filled with Sanseveria cylindrica fiber(SCF) and Zawa flour. SCF fiber was taken 10% volume constantly in all the samples. Camera ready samples were prepared using hand layup technique in which filler constituent proportions were taken by using rule of hybrid mixture (RoHM). The mail aim of the composites is to increase the tensile flexural, and impact strengths, TGA, DSC results by incorporating the filler. It was observed that, tensile strength was linearly increased up to 4wt.% zawa after that sudden falling was observed. On other hand, tensile modulus was increased linearly up to 5wt.% was the clear indication of addition of zawa imparts more stiffness to the composites. Flexural strength was increased up 3wt.% zawa flour after than it starts depreciating suddenly. Flexural modulus was increased linearly up to 3wt.% zawa four composites after that decreases. Impact strength was optimised at 4wt.% zawa flour after that it starts going down. In DSC analysis, for 3wt.% zawa flour composite registered good performance than the 2wt.%,whereas in TGA analysis 3wt.% composite was having good performance than 2wt.% zawa flour composites. Reasons attributed for increased glass transition temperature was due to the less moisture content or due to the deprived of void due to the good bonding strength

Parametric and non-parametric probabilistic approaches in the mechanics of thin-walled composite curved beams

In this paper we perform a quantification of the uncertainty propagation of the dynamics of slender initially curved structures constructed with fiber reinforced composite materials. Depending on the manufacturing process, composite materials may have deviations with respect to the expected response, often called nominal response in a deterministic sense. The manufacturing aspects lead to uncertainty in the structural response associated with constituent proportions, material and/or geometric parameters among others. Another aspect of uncertainty that can be sensitive in composite structures is the mathematical model that represents the mechanics of the structural member, that is: the assumptions and type of hypotheses invoked reflect the most relevant aspects of the physics of a structure, however in some circumstances these hypotheses are not enough, and cannot represent properly the mechanics of the structure. Uncertainties should be considered in a structural system in order to improve the predictability of a given modeling scheme. There are two approaches to evaluate the propagation of uncertainties in structural models: the parametric probabilistic approach and the non-parametric probabilistic approach. In the parametric, one quantifies the uncertainty of given parameters (such as variation of the angles of fiber reinforcement and material constituents) by associating random variables to them. In the non-parametric, the propagation of uncertainty is quantified by considering uncertain the matrices of the whole system. In this study a shear deformable model of composite curved thin-walled beams is employed as the mean or expected model. The probabilistic model is constructed by adopting random variables for the uncertain entities (parameters or matrices) of the model. The probability density functions of the random entities are derived appealing to the maximum entropy principle under given constraints. Once the probabilistic model is discretized in the context of the finite element method, the Monte Carlo method is employed to perform the simulations. Then the statistics of the simulations is evaluated and the parametric and non-parametric approaches are compared.

Preparation of Virgin Coconut Oil Nanoemulsions by Phase Inversion Temperature Method

Presently, the low energy emulsification method; phase inversion temperature (PIT) method offers a convenient mean of nanoemulsion formation for the incorporation of fragile substances. The aim of the current study was to prepare coconut oil nanoemulsions using cremophor RH 40 as nonionic surfactant in the light of PIT method. The suitable composition of coconut oil, cremophor RH40 and water was investigated by construction of ternary phase diagram. The PIT of system can be adjusted to 75 °C by adding NaCl at the concentration of 6%(w/w). Stable translucent nanoemulsions with particle size in range of 20-100 nm and PDI&lt;0.2 can be formed at the constituent proportions of 5%-30%(w/w), coconut oil, 10%-80%(w/w) cremophor RH40 and 5%-85%(w/w) NaCl solution of 6%(w/w). All formulations were stable for up to 2 months when stored at 4, 30 and 40 °C and protected from light.