•Natural sources to produce biodegradable films for food packaging are demanded.•Composite films of cellulose, glycerol and polyvinyl alcohol are presented.•Polyvinyl alcohol enhances the toughness ...of cellulose films.•Water adsorption up to 222.09% was obtained.•Films showed higher burst strength (up to 12,014 g) than other biodegradable films.
Nowadays consumers are aware of environmental problems. As an alternative to petrochemical polymers for food packaging, researchers have been focused on biopolymeric materials as raw material. The aim of this study was to evaluate mechanical properties (toughness, burst strength and distance to burst), water adsorption, light-barrier properties and transparency of composite films based on cellulose, glycerol and polyvinyl alcohol. Scanning electron microscopy, spectral analysis (FT-IR and UV–VIS-NIR) and differential scanning calorimetry were performed to explain the morphology, structural and thermal properties of the films. Results showed that polyvinyl alcohol enhances the toughness of films up to 44.30 MJ/m3. However, toughness decreases when glycerol concentration is increased (from 23.41 to 10.55 MJ/m3). Water adsorption increased with increasing polyvinyl alcohol concentration up to 222%. Polyvinyl alcohol increased the film thickness. The films showed higher burst strength (up to 12014 g) than other biodegradable films. The films obtained have optimal values of transparency like those values of synthetic polymers. Glycerol produced a UV protective effect in the films, an important effect for food packaging to prevent lipid oxidative deterioration. Results showed that it is feasible to obtain cellulose-glycerol-polyvinyl alcohol composite films with improved properties.
The excessive use of disposable plastic material in our society demands packaging material which can undergo quick degradation without harming the environment. Agricultural products can serve as one ...of the essential sources for the production of biodegradable packaging material. In the present study, starch was isolated from mung bean and used for the synthesis of nano starch, and it's physicochemical, morphological, and film-forming properties were studied. The average particle size distribution of nano starch was 141.772 nm. Mung bean native starch granules were of oval shape having a smooth surface, free from cracks while mung bean nano starch appeared in an agglomerated form with irregular and rough surface. Nano starch-based composite films with varying concentrations (0.5, 1, 2, 5, and 10%) of nano starch were prepared by the solution casting method. The native starch film properties such as thickness (0.040 ± 0.010 mm), moisture content (8.03 ± 0.26%), water vapor transmission rate (5.982 × 10−3 ± 0.30 g−2 s−1), water solubility (38.49 ± 0.51%) and burst strength (868.49 ± 26.5 g) were observed. With the incorporation of nano starch at concentration of 0.5 to 10.0%, film properties such as thickness (0.043 ± 0.006 to 0.063 ± 0.006 mm), burst strength (943.56 ± 18.1 to 1265 ± 18.9 g), moisture content (6.09 ± 0.28 to 4.80 ± 0.48%), water vapor transmission rate (5.558 × 10−3 ± 0.25 to 3.364 × 10−3 ± 0.35 g−2 s−1) and solubility (37.99 ± 0.47 to 34.11 ± 0.40%) were improved.
•Mung bean nano starch was characterized by dynamic light scattering and field emission- scanning electron microscopy•Nano starch-based composite films were developed by adding 0.5, 1, 2, 5 and 10% nano starch in native starch.•The properties of films were improved due to the addition of nano starch into native starch for development of films.
Accurate assessment of the burst pressure of corroded pipes is pivotal for pipelines integrity management and adequate decision-making and thus, meticulous selection of an appropriate prediction ...model is vital. Several burst strength models have been developed based on analytical, numerical and empirical analyses, often validated by full or small-scale experiments. This paper provides a comprehensive review, calibration and model uncertainty evaluation of a wide range of burst strength models available in the literature relative to a large sample of more than 240 tests of burst pressure covering a variety of steel grades. First, the most appropriate strength model for corrosion free pipes is calibrated by comparing it with extensive test data and the inherent model uncertainty factor is derived. Then, 25 burst strength models for corroded pipelines are categorically analysed in three classes of steel pipe grades, i.e., low (X42 or less to X56), medium (X60 to X70) and high strength (X80 to X120). Statistical parameters such as the mean and absolute mean errors and standard deviation are adopted to analyse and compare the models’ performance against test results. The bust strength models of corroded pipelines in the three categories are then calibrated by model uncertainty factors derived from the experimental data. Then, the top 10 models are comparatively analysed in each category to check their performance and uncertainty. Monte Carlo simulation is used to assess the uncertainties with increasing defect depth. The paper concludes exploring the extent of applicability and best utilization of the models for assessing the burst pressure of corroded pipelines. The present study also provides guidance on the calibrated models, which can be used to assess probabilistically the safety of intact and corroded pipelines against burst failure.
•A calibration and model uncertainty evaluation of many burst strength models is made based on more than 240 tests.•The most appropriate strength model is calibrated and the inherent model uncertainty factor is derived.•Then, 25 burst strength models for corroded pipelines are categorically analysed in three classes of steel pipe grades.•The top 10 models are comparatively analysed in each category to check their performance and uncertainty.•The conclusion recommends the best utilization of the models for assessing the burst pressure of corroded pipelines.
Composite pressure vessels have been widely used for high-pressure hydrogen storage. This paper aims to study the residual burst strength of composite pressure vessels after low velocity impact. An ...explicit-implicit combined model using strain-based three-dimensional failure theory is employed for numerical analysis, which is implemented by ABAQUS user-defined subroutines VUAMT, UMAT and ABAQUS-Python scripting language. Impacted-induced damage including the intralaminar fiber and matrix damage, and interface delamination is directly imported to the residual strength analysis to explore the whole-process damage mechanisms by using current model. For composite pressure vessels, the mechanical responses and damage behaviors of intralaminar damage and interface delamination at six impact energy are explored. After impact, the damage evolution under internal pressure for vessels is discussed. By comparison, the numerical results are basically consistent with experimental results. Besides, the effects of impact direction of strip impactor and liner type on the low velocity impact responses and residual burst strength are explored. By studying the influence of impact energy, liner type and impact direction systematically, it shows that fiber damage on the hoop layers caused by impact load can reduce the residual burst strength for current composite pressure vessels.
•Residual burst strength for the vessels after low velocity impact are explored.•An explicit-implicit combined model is introduced for whole-process analysis.•Damage behaviors for the vessels at six impact energy are explored.•Damage evolution under internal pressure for vessels is discussed.•Effects of impact direction of strip impactor and liner type are studied.
This paper assesses the uncertainties in the structural reliability levels of thick high strength pipelines with active corrosion defects subjected to internal pressure. A general burst strength ...model and other applicable to thick high strength pipes are adopted and their predictions uncertainty over a wide range of corrosion defect depths is assessed by Monte Carlo simulation. A 3-parameter lognormal probability model is adopted to describe the uncertainty in the burst pressure. Global and corrosion defect depth dependent model uncertainty factors are derived by comparing the predictions of the burst strength models with burst test data of corroded pipes. Burst failure limit states are formulated in terms of the burst strength models and corresponding model uncertainty factors. Linear and nonlinear corrosion models are adopted to describe the growth of corrosion defects. The uncertainty on the safety levels of pipelines due to the uncertainty on the corrosion defect, corrosion growth model and reliability algorithm is assessed. The results presented for the two strength models provide insights on the adequacy of a thick high strength burst model for probabilistic applications in comparison with a general burst strength model.
•The uncertainties of thick high strength pipelines with active corrosion defects subjected to internal pressure are assessed.•A general burst strength model and other applicable to thick high strength pipes are adopted.•Global and corrosion defect depth dependent model uncertainty factors are derived.•Burst failure limit states are formulated in terms of the burst strength and corresponding model uncertainty factors.•The results provide insights on the adequacy of a thick high strength burst model for probabilistic applications.
To accurately predict the burst strength of both thin and thick-walled pressure vessels (PVs), a parametric study of PV burst strength was performed for a wide range of vessel geometries and ...materials using elastic-plastic finite element analysis (FEA). A valid FEA model was established through a detailed study of 2D versus 3D FEA models, the critical stress failure criterion versus the limit load criteria, and the thick-wall effect on the FEA simulations. The results show that the stresses and strains at the mean diameter, rather than outside diameter, determines a more accurate burst strength for both thin and thick-walled PVs. On this basis, a parametrized FEA script using the ABAQUS Python application programming interface (API) was used to create a large database of PV burst strengths for a variety of vessel geometries and materials, demonstrating that Python scripting is a powerful technique for performing parametric studies or generating large databases. From the FEA results, using the regression method, a new burst pressure model was developed as a function of the vessel geometry (D/t ratio) and material properties (UTS and n). As validated by a large number of full-scale burst test data, the proposed burst model can very accurately predict the burst strength for both thin and thick-walled PVs.
•A probabilistic framework is used to calibrate burst strength models of pipelines based on the hierarchical Bayesian method.•The approach uses burst test data of intact and corroded pipelines of ...different steel grades.•The most appropriate burst strength models for corrosion-free and corroded pipelines are adopted.•Using the hierarchical Bayesian approach model uncertainty factors are derived to calibrate the burst strength models.•The differences in uncertainty resulting from the use of the proposed approach are compared to the conventional method.
This paper proposes a probabilistic framework to calibrate burst strength models of intact and corroded pipelines based on the hierarchical Bayesian method. The approach uses burst test data of intact and corroded pipelines of different steel grades compiled from the literature and accounts for the variations among the data sources. First, the most appropriate burst strength models for corrosion-free and corroded pipelines are adopted. The burst pressure prediction models are categorised under low, medium and high-grade steel classes. Using the hierarchical Bayesian approach model uncertainty factors are derived to calibrate the burst strength models. The mean values and uncertainty of posterior probabilities of the model uncertainty factors are estimated for intact and corroded pipelines in three material categories. This study further investigates the uncertainty propagated by calibrated and non-calibrated models and draws important observations regarding the uncertainty associated with the calibration. The prediction uncertainties follow a non-linear increasing trend as corrosion defect increases. This study's importance is demonstrated with a case study that shows the differences in the uncertainty resulting from the use of the proposed approach compared to the conventional method. Additionally, for corroded pipes, model uncertainty factors are described as a function of defect depth with regression parameters estimated from hierarchical Bayesian-based regression analysis. Finally, a comparison between calibrated and non-calibrated models indicates that the calibrated models provide non-conservative predictions.
The aim of this research was to study the residual burst strength, dynamic structural response, and failure mechanism of composite overwrapped pressure vessel (COPV) subjected to low velocity impact ...by numerically and experimentally. A three-dimensional composite pressure vessel model was developed using Wound composite module (WCM) plugin of Abaqus. The impact response of composite pressure vessels was calculated based on the Hashin progressive damage criteria. The residual burst strength was predicted using maximum strain failure criteria. The COPV was impact tested and the residual burst strength was calculated. The predicted and testing results were compared, and a good correlation was found.
•Residual burst strength and dynamic structural responses of composite overwrapped pressure vessels (COPV) was determined. Low velocity impact was investigated by numerically and experimentally.•Impact response of composite pressure vessels was calculated based on the Hashin progressive damage criteria.•Residual burst strength was predicted using maximum strain failure criteria.•COPV was impact tested and the residual burst strength was calculated.•The predicted and testing results were compared, and a good correlation was found.
Background: The field of critical care-related artificial intelligence (AI) research is rapidly gaining interest. However, there is still a lack of comprehensive bibliometric studies that measure and ...analyze scientific publications on a global scale. Network charts have traditionally been used to highlight author collaborations and coword phenomena (ACCP). It is necessary to determine whether chord network charts (CNCs) can provide a better understanding of ACCP, thus requiring clarification. This study aimed to achieve 2 objectives: evaluate global research trends in AI in intensive care medicine on publication outputs, coauthorships between nations, citations, and co-occurrences of keywords; and demonstrate the use of CNCs for ACCP in bibliometric analysis. Methods: The web of science database was searched for a total of 1992 documents published between 2013 and 2022. The document type was limited to articles and article reviews, and titles and abstracts were screened for eligibility. The characteristics of the publications, including preferred journals, leading research countries, international collaborations, top institutions, and major keywords, were analyzed using the category-journal rank-authorship-L-index score and trend analysis. The 100 most highly cited articles are also listed in detail. Results: Between 2018 and 2022, there was a sharp increase in publications, which accounted for 92.8% (1849/1992) of all papers included in the study. The United States and China were responsible for nearly 50% (936/1992) of the total publications. The leading countries, institutes, departments, authors, and journals in terms of publications were the US, Massachusetts Gen Hosp (US), Medical School, Zhongheng Zhang (China), and Science Reports. The top 3 primary keywords denoting research hotspots for AI in critically ill patients were mortality, model, and intensive care unit, with mortality having the highest burst strength (4.49). The keywords risk and system showed the highest growth trend (0.98) in counts over the past 4 years. Conclusions: This study provides valuable insights into the potential for ACCP and future research opportunities. For AI-based clinical research to become widely accepted in critical care practice, collaborative research efforts are necessary to strengthen the maturity and robustness of AI-driven models using CNCs for display.
The appearance of a topic in a document stream is signaled by a burst of activity, with certain features rising sharply in frequency as the topic emerges. Although temporal bar graph (TBG) is ...frequently applied to present the burst spot in the bibliographical study, none of the research has combined the inflection point (IP) to interpret the burst spot feature. The aims of this study are to improve the traditional TBG and apply the TBG to understand better the evolution of a topic (e.g., publications and citations for a given author).
The EISTL model, including entity, indicator, selection of a few vital ones (named attributes) with higher values in quantity (e.g., the citation data of the top 10 entities), TBG and line-chart plots to verify the trend of interest, was proposed to demonstrate the TBG as a whole. The IP locations compared to the median point in data along with the heap map and line-chart trend were identified. The burst strength was computed. A dashboard on Google Maps was designed and launched for bibliometric analysis. Four authors in MDPI (Multidisciplinary Digital Publishing Institute) journals named to be Citation Laureates 2021 were recruited to compare their research achievements shown on the TBG, particularly displaying the burst spots and the recent developments and stages (e.g., increasing, ready to increase, slowdown, or decreasing).
We observed that the highest burst strengths in publication and citations are earned by Barry Halliwell (8.99) and Jean-Pierre Changeux (18.01). The breakthrough of TBG using the EISTL model to display the influence of authors in academics was made with 2 parts of the primary IP point and the trend feature in the data.
The dashboard-type TBG shown on Google Maps is unique and innovative and able to provide deeper insights to readers, not merely limited to the publications and citations for a given author as we did in this study.
