The development of the best properties of corn husk fibre (CHF) as a reinforcing material from coconut shell powder–polyester composite is an extremely interesting subject. This research focuses on ...characterising the mechanical properties and morphology of polyester/coconut shell powder composites filled with CHF. The variations of coconut shell powder (CSP) contents are 5% and 10%, and the corn husk fibre contents are 10%, 15%, 20% and 30% (vol%). The mixture is blended and poured into a composite mould using the hot press technique. The tensile and flexural strengths of the mixture were investigated, and the fracture surface of the composite was also analysed by scanning electron microscopy (SEM). The tensile strength of polyester/5 vol % CSP decreased dramatically from 22.459 MPa to 16.955 MPa. However, flexural strength increased from 24.233 MPa to 45.844 MPa when the corn husk fibre (CHF) content increased. Further, all polyester–10% of CSP composites have higher flexural strength values than the polyester–5% of CSP counterparts. Conversely, the tensile strength properties decrease at 10%–15% CHF content and then increase at 20%–30% CHF contents. This outcome is due to the tighter and stronger interfacial bonding between CHF–CSP–polyester and the decreasing number of fibres–pull-outs. Fractured morphology with SEM shows poor interfacial bonding between CHF–CSP–polyester and fibre pullout on composites.
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•The characterisation of a novel CSP/CHF polyester composite is investigated.•Tensile and flexural strength are investigated.•The fracture surface of the composite was analysed by SEM.•10% of CSP-filled CHF/polyester composite will be economical and satisfactory in terms of flexural strength.
There exist challenges in balancing structural lightweight and strength of the suspension mechanism for a wave-adaptive unmanned quadramaran (WUQ). In this paper, the mechanical properties of key ...components pertaining to the suspension mechanism are comprehensively analyzed by finite element method. By employing structural safety factor, the strength safety of each component is quantitatively assured, thereby enhancing the overall strength of the suspension mechanism under various navigation conditions. Building upon this foundation, a variable-density topological optimization model with load constraints is established so as to optimize relative densities of various elements that support the overall structural rigidity, thereby structurally lightening the suspension mechanism without compromising mechanical performance. Simulation results show that the strength and fatigue life of suspension mechanism with lightweight optimization can be sufficiently maintained, while the masses of upper and lower swing arms can be lightened by 27.5% and 20%, respectively.
•Mechanical properties of the suspension mechanism are comprehensively analyzed under various navigation conditions by finite element method.•Each component is quantitatively assured by employing structural safety factor, thereby enhancing the overall strength of the suspension mechanism.•A variable-density topological optimization model with load constraints is established to structurally lighten the suspension mechanism.
•Mechanical behaviour magnetic fluid dynamic seal shell structure under thermal/mechanical load is estimated.•Fuzzy fatigue reliability function is obtained based on Latin hypercube sampling and the ...second-order response surface method.•Collaborative optimization design of fatigue reliability and lightweight is performed.
In order to study the reliability of Magnetic fluid dynamic seal shell structure under thermal/mechanical load, the improving cooling structure, calculating fuzzy fatigue reliability, and collaborative optimization design of fatigue reliability and lightweight are studied in this paper. The temperature model of the shell structure under four temperature conditions is established to analyze the influence of the thermal deformation caused by excessive local temperature. The cooling structure is improved, and the maximum temperature under the maximum temperature condition is reduced by 40.154 °C. For the sake of calculating the reliability of the new shell structure, a strength analysis model under thermal/mechanical load is built, and the fuzzy fatigue reliability function is obtained based on Latin hypercube sampling and the second-order response surface method. Four kinds of reliability are acquired by coding the functional functions and four kinds of membership functions with MATLAB, but all of them are lower than 90 % of the industrial requirements. To improve the reliability of the new shell structure and carry out the anti-fatigue lightweight design at the same time, an approximate model was constructed based on the interval analysis method and second-order response surface method for analysis. The accuracy of the approximate model was verified by re-sampling and finite element analysis. Based on the non-dominated sorting genetic algorithm, the optimal solution is determined. The optimization results show that the stress target value is reduced by 19.3 %, the weight target value is reduced by 3 %, and the fuzzy fatigue reliability reaches 94.65 %, 94.58 %, 93.89 %, and 96.31 % respectively. A new cooling structure of the Magnetic fluid dynamic seal is obtained and the maximum temperature is reduced. Moreover, the reliability of the new shell structure under thermal/mechanical load coupling is improved.
The aim of this study is to analyze the number of deaths due to COVID-19 for Europe and China. For this purpose, we proposed a novel three parametric model named as Exponentiatedtransformation of ...Gumbel Type-II (ETGT-II) for modeling the two data sets of death cases due to COVID-19. Specific statistical attributes are derived and analyzed along with moments and associated measures, moments generating functions, uncertainty measures, complete/incomplete moments, survival function, quantile function and hazard function, etc. Additionally, model parameters are estimated by utilizing maximum likelihood method and Bayesian paradigm. To examine efficiency of the ETGT-II model a simulation analysis is performed. Finally, using the data sets of death cases of COVID-19 of Europe and China to show adaptability of suggested model. The results reveal that it may fit better than other well-known models.
•Meso-model can simulate the behavior of composites from a preparation view.•Kernel density estimation describes the distribution of parameters more accurately.•The effect of the stitching process in ...the split type of tip shroud is enormous.•The joints of tip shroud structure are prone to crack initiation.
This paper considers the impact of the random distribution of yarn properties on the mechanical and failure behavior of ceramic matrix composites (CMCs) structures and proposes an integrated analysis method based on preform-structure. Tensile tests of CMCs tip shroud specimens were carried out, and the digital image correlation technique was used to record the deformation of the specimens in real-time during loading. Based on the actual structure, a preform model of the CMCs tip shroud was established, and the kernel density estimation method was used to obtain the distribution of the yarn cross-sectional area. The random distribution of the cross-sectional area is equivalent to material properties, simulating the dispersion of the performance of CMCs. The progressive damage method simulates the failure mode during the specimen's loading process. The peak load error is 1.5 %, and the failure modes such as transverse shear damage, stitching yarn fracture, and interlaminar separation were successfully predicted.
•Comparison of four IVS methods to predict flow in two distinct watersheds using ANNs.•Two IVS methods are model-free and two are model-based, improvements are proposed for the model-based ...methods.•Performance comparison between models with and without IVS, the termination criteria used, and predefined number of inputs.•Input usefulness is not binary; the correct number of selected inputs is dependent on the desired model complexity.
Artificial neural networks (ANNs) are increasingly used for flood forecasting. The performance of these models relies on the selection of appropriate inputs. However, Input Variable Selection (IVS) is typically performed using expert knowledge or simple linear methods. This research compares and evaluates four IVS methods including two model-free methods: partial correlation (PC), partial mutual information (PMI), and two novel model-based methods: an improved input omission (IO), and improved combined neural pathway strength (CNPS). A comprehensive comparison of performance efficacy for multiple IVS methods has not been published in literature before. Each method is used for daily and hourly lead times in the Bow and Don Rivers (both in Canada), respectively. These watersheds represent different hydrological systems and were selected to highlight the performance of the IVS methods under differing conditions. This research determines that the proposed CNPS produces the strongest performing ANNs based on the robustness of the inputs selected, comparison to other IVS methods, and models developed without IVS. Additionally, this research demonstrates that standard termination criteria do not reliably identify the optimum number of inputs for the ANNs and using a model-based optimization of inputs is recommended. As a result, it is recommended that the number of inputs be determined using a systematic approach, where each input selection is informed by an IVS-based input ranking, rather than a predefined termination criterion. Lastly, this research demonstrates that input usefulness is not binary concept; the correct number of selected inputs is dependant on the desired model complexity, instead of an arbitrarily selected IVS termination criteria.
•Post-pandemic era requires supply chains to be technologically driven.•Recognized the crucial drivers for the adoption 77of IoT in supply chain management.•Identified causal links of crucial drivers ...using rough strength relation analysis.•Implications for sustainable development goals are presented.
As the post-COVID-19 pandemic era begins, the supply chain operating environment has transformed and faced disruptions. The Internet of Things (IoT) has emerged as one of the expedient technologies in the information technology domain, which solves the issues of traditional supply chain management (SCM) by providing resiliency, flexibility, and traceability. Despite the perceived advantages of IoT, it remains unknown what drivers are essential to adopt IoT in SCM. To achieve this aim, an integrated approach combining rough set theory and decision-making trial and evaluation laboratory (DEMATEL), that is rough strength relation analysis (RSRA) method, has been used to identify and investigate drivers of IoT adoption in SCM where drivers were analyzed according to their comparative importance based on expert opinions from industrial and academic backgrounds. A total of 14 drivers have been identified from the extensive literature review on previous IoT and SCM associated works, which were further analyzed to determine the most important drivers. The results show that “Efficient logistics systems”, “Business knowledge acumen”, and “Information safety assurance” are among the three most predominant driving factors. The findings may help practitioners implement IoT in supply chains to deal with disruptions, risks and vulnerabilities in the post-pandemic era.
The subject of the study are short sandwich beams with special structure of the core (honeycomb). The beam is made using additive manufacturing technology. The values of elastic modules vary along ...beam. The linear shear deformation theory – the “zig-zag” hypothesis is assumed for plane cross section. The analytical model of beam is based on this hypothesis. The deflection of beam is analytically calculated. Moreover, the deflection of beam is experimentally determined on a test stand. The results of these two methods are compared.
•The impact of the preceding layer stacking on rear filament winding is considered.•An improved cubic spline function approach and a novel parabola method were proposed.•The strength analysis of gas ...cylinders based on the parabola method was carried out.•The parabola method adapts well to cylinders with varied sizes and ply schemes.
Due to the characteristics of changing angle and thickness, predicting the outer contour of the vessel dome has been a challenging task in composite pressure vessel design. The impact of preceding layer fiber stacking on subsequent filament winding has never been considered in existing methods of dome thickness calculation. So we developed an improved cubic spline function approach and a novel parabola method that takes preceding layer fiber stacking into account. The example findings show that the improved cubic spline function approach has a weakness in that the selection of several critical parameters is not clearly described and heavily reliant on actual engineering knowledge. The parabola approach described in our study is not only simple in design, but also adapts well to dome contour of gas cylinders with varied sizes and ply schemes. Moreover, the strength analysis of composite gas cylinders was carried out by finite element method. The results show high consistency with hydraulic burst test results, which clearly demonstrates that the parabola method we proposed can effectively realize the precise modeling of composite pressure vessels and will be very beneficial in the design of composite pressure vessels.
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