Composite Pressure Vessels Research Articles

Effect of layup sequence on cure deformation and accurate prediction of composite pressure vessels

The application of composite winding pressure vessels is becoming more and more widespread, and the magnitude of deformation during curing can have a significant impact on service performance, but there are fewer studies on the accurate prediction of the numerical and experimental validation of the deformation during the curing process of pressure vessels. To accurately predict the effect of different angles of layup on the curing deformation of high-pressure hydrogen storage vessels made of T700S-12 K/4251A4B2 carbon fiber/epoxy composites in cylindrical and dome sections. In this paper, WCM-ABAQUS segmented pressure vessel accurate modeling method is proposed for the first time, using the method of converting the chemical shrinkage coefficient of epoxy resin into thermal expansion coefficient equivalently, the finite element prediction of the deformation of the pressure vessel during the curing process in different layup sequences was carried out, and the deformation values of the pressure vessel in different layup sequences were analyzed comparatively. Finally, the winding curing experiments were carried out on pressure vessels with different layup sequences, and the curing deformation values of the experimental tests on pressure vessels with different layup sequences were compared with the finite element simulation values, respectively, and the minimum error value 13.07%. It provides a reliable basis for accurately predicting the deformation value of the pressure vessel curing process, and also provides a reference for subsequent experiments to reduce the curing deformation value.

Numerical Investigation on the Capability of Modeling Approaches for Composite Cylinders under Low-Velocity Impact Loading

Composite pressure vessels can be exposed to extreme loadings, for instance, impact loading, during manufacturing, maintenance, or their service lifetime. These kinds of loadings may provoke both visible and invisible levels of damage, e.g., fiber breakage matrix cracks and delamination and eventually may lead to catastrophic failures. Thus, the quantification and evaluation of such damages are of great importance. Considering the cost of relevant full-scale experiments, a numerical model can be a powerful tool for such a kind of study. This paper aims to provide a numerical study to investigate the capability of different modeling methods to predict delamination in composite vessels. In this study, various numerical modeling aspects, such as element types (solid and shell elements) and material parameters (such as interface properties), were considered to investigate delamination in a composite pressure vessel under low-velocity impact loading. Specifically, solid elements were used to model each layer of the composite pressure vessel, while, in another model, shell elements with composite layup were considered. Compared with the available experimental data from low-velocity impact tests described in the literature, the capability of these two models to predict both mechanical responses and failure phenomena is shown.

Failure prediction and optimization for composite pressure vessel combining FEM simulation and machine learning approach

Failure assessment is one of the fundamental tasks for optimization of composite pressure vessels (CPVs). However, the extensive design space of composites usually leads to costly and repetitive work of failure assessment that hinders the design and optimization of CPVs. In this work, a combined FEM simulation and machine learning approach is used to predict the failure factors R of CPVs for further optimization. CPVs with various design parameters are automatically generated and analyzed in ABAQUS to obtain failure factors under various external loadings. Then, an assembled deep neural network (DNN) namely Multi-DNN is trained to map relations between design parameters and R of CPVs. Further, transfer learning (TL) is introduced to improve the extensibility of our approach by fine-tuning the pre-trained Multi-DNN using scarce data of new design space. Such a TL-Multi-DNN model can precisely predict R of CPVs with new design parameters. Additionally, combining the trained models and genetic algorithm, the optimization of CPVs is carried out with high efficiency and low computational cost. As a result, R of CPV with various given and new design parameters can be estimated directly by the trained models and the optimal layer sequence of CPV can be obtained efficiently.

The influence of tow tackiness on tow pull-up during the manufacturing of a composite pressure vessel

Double-curved composite structures that are manufactured via automated fiber placement, such as pressure vessels, can take advantage of tow steering to reduce weight. This design freedom comes with the cost of adding internal normal stresses to the tow, possibly leading to wrinkles or pull up. The present work investigates tow pull up both experimentally and analytically and details a correlation between tow pull up and the minimum critical steering radius, where the material tackiness and the modelled plate’s length are found to be the most influential parameters. The experimental determination of the material tackiness is the next step to improve the predictive capabilities of the proposed model.

Multiscale analysis of composite pressure vessel structures wound with different fiber tensile force

The aim of this paper is the multiscale investigation of composite pressure vessel structures wound with varying fibre tension. The paper explores the potential of ”programming” the fibre tension force during the winding process of a high pressure hydrogen storage vessel. Two series of vessels were wound with two different tensions: Two series of vessels wound with forces of 3 N and 80 N respectively were experimentally investigated. Other technological factors, such as the type and weight of carbon fibre used, were kept constant throughout the study. Quasi-static burst tests were used to measure the elastic deformation of the vessel surface. Microscopic studies were also carried out to analyse the structure of the composite at different length scales. The fibre content, the geometric parameters of the voids and the distribution of the three main components of the composite – carbon fibre, technological defects and resin – were also determined. Representative RVE elementary cells were generated for both materials using statistical modelling. The composite was then homogenised and elasticity matrices were obtained for the fibre tensile forces in both materials.

Modal and random vibration responses of composite overwrapped pressure vessels with various geodesic dome trajectories

In the current study, Composite Overwrapped Pressure Vessels (COPVs) with various geodesic dome profiles have been built and their modal and random vibration responses were numerically examined. In this regard, geodesic dome profiles were established for five different polar opening radii of 10, 15, 20, 25, and 30 mm, and thus the impacts of fibre orientations on vibration characteristics depending on the filament winding trajectories were discovered. Furthermore, non-prestressed modal and random vibration responses for COPVs, as well as prestressed vibration behaviours under 50, 100, and 150 Bar internal pressure, were investigated and thus the effects of internal pressure severity on dynamic characteristics were identified. The study found that higher polar opening radius triggered a reduction in the natural frequencies, and these reductions were linked to an increment in the filament winding angle, and a consequent deterioration in the structural stiffness of COPVs. On the other hand, raising the internal pressure severity shifts the natural frequencies to higher frequencies, which are also attributed to ascended structural stiffness. Furthermore, it was established that internal pressure severity and polar opening radius had a coupled effects on the modal and random responses, and that both parameters should be evaluated simultaneously.

On the Multidisciplinary Design of a Hybrid Rocket Launcher with a Composite Overwrapped Pressure Vessel

A multidisciplinary design optimisation (MDO) study of a hybrid rocket launcher is presented, with a focus on quantifying the impact of using composite overwrapped pressure vessels (COPVs) as the oxidiser tank. The rocket hybrid propulsion system (RHPS) consists of a combination of solid fuel (paraffin) and liquid oxidiser (NOx). The oxidiser is conventionally stored in metallic vessels. Alternative design concepts involving composite-based pressure vessels are explored that could lead to significant improvements in the overall performance of the rocket. This design choice may potentially affect parameters such as total weight, thrust curve, and maximum altitude achieved. With this eventual impact in mind, structural considerations such as wall thickness for the COPV are integrated into an in-house MDO framework to conceptually optimise a hybrid rocket launcher.

Burst pressure prediction of carbon/natural fiber and hybrid composite pressure vessels by theoretical and numerical analysis

This study utilized finite element modeling to assess the stress and burst strength of a composite pressure vessel (CPV). The fiber type and its sequences were considered while developing the best CPV. The stress produced inside the CPV may cause damage to the vessel as well as loss of life and property. Therefore, it is critical to guarantee that the CPV's stress output does not surpass the vessel material's maximum allowable stress value. The primary goal of this research is to investigate the stresses induced in composite pressure vessels and then examine the stress using three different solutions: von Mises, Tresca, and ASSY. The theoretical burst strength is first established, and then a numerical solution is developed using ABAQUS. To confirm the correctness of FEA, the outcomes of the theoretical technique and the finite element method are compared. The six-layer carbon fiber-reinforced CPV shows twelve times higher burst strength than four layers but an equal thickness of jute fiber-based CPV. On the other hand, the hybrid combination of CPV (jute and carbon) shows a strength improvement over jute fiber based CPV by almost four times. Other jute fiber-based hybrid CPVs with glass, banana, and aluminum foil show very comparable strength relative to only jute CPV. This study's primary goal is to examine the failure phenomena and burst strength of thin, cylindrical pressure vessels.

Complex design and analysis of filament wound composite pressure vessels using data driven evolutionary algorithms

The typical composite pressure vessel manufactured by means of filament winding consists of three elementary construction parts, that is, cylindrical part, end dome and the junction between its cylindrical part and the end dome which are subject of this article. The pressure vessel may fail in each of these three parts. Therefore, all of them must be considered during the design process. This study shows the possible way how to design an optimal pressure vessel related to chosen parameters (which can be mass of the pressure vessel, depth of the end dome, magnitude of internal pressure etc.), so that it does not fail in any construction parts. Any decision, whether the pressure vessel comply or not in studied places, is based on Hoffman's failure index analysis. The finding of an optimal solution requires performing a multi-objective optimization task, which was solved here using data-driven evolutionary algorithms. From the input data, which were generated through analytical approaches, surrogate models were created using the Evolutionary Deep Neural Nets (EvoDN2). These surrogate models were further used as an input to the optimization module which is based upon Constrained Reference Vector Evolutionary Algorithm (cRVEA). The results show that the pressure vessel designed in this way comply in each analyzed location. Moreover, it also finds the most stressed location, which can be useful for the designers.

Distributed fiber optic sensors for structural health monitoring of composite pressure vessels

Abstract In this paper, we present a comprehensive overview of our research in the field of distributed fiber optic sensors for structural health monitoring of hydrogen composite pressure vessels. Specifically, we demonstrate how the integration of fiber optic sensors into composite pressure vessels enhances safety while simultaneously reducing maintenance costs. The small size of optical fibers enables their integration into composite structures during the manufacturing process, allowing continuous monitoring and precise detection and localization of structural damages during service life. We also discuss the potential of state-of-the-art signal processing methods and machine learning for advancing predictive maintenance. Our applications of fiber optic sensors demonstrate their potential to contribute significantly to the energy transition towards renewable sources.

Model-experiment comparison of quasi static loading on a composite overwrap pressure vessel (Part 2)

A methodology to develop a 3D Finite Element (FE) model of a full metal-lined Composite Overwrapped Pressure Vessel (COPV) was developed and is presented in this paper. The model is intended for prediction of the metal-composite delamination and residual dent depth developed in the metal liner as a result of quasi-static indentation loading. Cohesive elements are used to model the composite and the metal-composite interfaces. Experimental and numerical comparisons of force–displacement curves, delamination area and residual dent depth are presented. Numerical results are in good agreement to the experimental data.

Voids in type-IV composite pressure vessels manufactured by a dry filament-winding process

Type-IV high-pressure hydrogen-gas tanks for fuel-cell electric vehicles are made from carbon fiber-reinforced plastic. Their production involves wrapping a carbon-fiber-reinforced thermoset resin towpreg around a plastic liner to form a tank shape, followed by heating in an oven to cure the thermoset resin. The filament-winding process produces many voids in the tank that cause variations in quality and the product lifetime. In this study, the voids in the tank were classified according to their origin. A type-IV high-pressure hydrogen-gas tank with a burst pressure of 70 MPa was fabricated, and the voids produced in the tank were observed. The same filament-winding process was used to fabricate a plate and tank with a simple winding trajectory to identify the voids. The voids produced in the tank by the filament winding were categorized into six groups based on their location, cross-sectional shape, and size, showing the origin of the voids.

Investigation of Hydrogen Transport Properties through the Liner Material of 70 MPa Type IV Composite Overwrapped Pressure Vessels

In zero-emission solutions for the hydrogen supply chain, high-pressure hydrogen storage in Type IV composite overwrapped pressure vessels (COPVs) is crucial for being safe and secure for a variety of stationary and transport applications. These COPVs consist of a polymeric liner material that works as a barrier for the stored hydrogen, while the carbon fiber-based composite provides the strength to hold the high-pressure hydrogen (of nominal working pressure more than 70 MPa to achieve the competitive driving range). Several experimental studies and simulation work have been performed on the viability of various polymers as low-permeability materials under low-pressure conditions. However, because of their proprietary nature and commercialized research, the characteristics of hydrogen permeation through polymers and their behavior at high pressure are still readily available in the literature. It is a major concern and the most crucial component of Type IV COPVs that these polymeric liners hold high pressure and maintain the necessary density of hydrogen (state of charge) toward operational requirements and safety concerns related to the cause of failures due to permeation (such as blistering, buckling, cracking, and so on). This paper investigates the role of polymeric liners on hydrogen permeation behavior using finite element modeling. For this, a UMATHT subroutine is developed within the Abaqus software to implement a new hydrogen permeation transport model with extended governing equations. Through the simulations and material modeling, the role of hydrogen transport properties (permeability, diffusivity, and solubility), structural characteristics (crystallinity, free volume, thickness) of plastic liners, and the role of operational parameters (concentration, pressure) are combined to validate the model from the experimental data in the literature to estimate the effective thickness required to maintain the permeation limit of the polymeric liner of 70 MPa Type IV COPVs.

Weight Minimization of Type 2 Composite Pressure Vessel for Fuel Cell Electric Vehicles Considering Mechanical Safety with Kriging Metamodel

In recent years, increased sales of fuel cell electric vehicles (FCEVs) have required composite overwrapped pressure vessel (COPV) designs to be lightweight and allow safe high-pressure hydrogen storage. In this study, we propose the weight minimization of Type 2 COPVs for FCEVs considering mechanical safety. Steel liner thickness, ply thickness, ply orientation, and the number of plies were set as design variables, and weight minimization was performed. For the constraints of optimization, the Tsai–Wu failure index of the composite layer and von Mises stress of the steel liner are considered. The design of experiments (DoE) was conducted to generate kriging model and perform sensitivity analysis. The optimized design of Type 2 COPVs was determined by satisfying all constraints, with significant weight reduction and preserved mechanical safety of the structure.

An Efficient Optimization Method for Stacking Sequence of Composite Pressure Vessels Based on Artificial Neural Network and Genetic Algorithm

An Efficient Optimization Method for Stacking Sequence of Composite Pressure Vessels Based on Artificial Neural Network and Genetic Algorithm

Design of Type-IV Composite Pressure Vessel Based on Comparative Analysis of Numerical Methods for Modeling Type-III Vessels

Compressed gas storage of hydrogen has emerged as the preferred choice for fuel cell vehicle manufacturers, as well as for various applications, like road transport and aviation. However, designers face increasing challenges in designing safe and efficient composite overwrapped pressure vessels (COPVs) for hydrogen storage. One challenge lies in the development of precise software programs that consider a multitude of factors associated with the filament winding process. These factors include layer thickness, stacking sequence, and the development of particularly robust models for the dome region. Another challenge is the formulation of predictive behavior and failure models to ensure that COPVs have optimal structural integrity. The present study offers an exploration of numerical methods used in modeling COPVs, aiming to enhance our understanding of their performance characteristics. The methods examined include finite element analysis in Abaqus, involving conventional shell element, continuum shell element, three-dimensional solid element, and homogenization techniques for multilayered composite pressure vessels. Through rigorous comparisons with type-III pressure vessels from the literature, the research highlights the most suitable choice for simulating COPVs and their practicality. Finally, we propose a new design for type-IV hydrogen composite pressure vessels using one explored method, paving the way for future developments in this critical field.

Development of machine learning based classifier for the pressure test result prediction of type IV composite overwrapped pressure vessels

The stringent safety regulations of type IV composite overwrapped pressure vessels (COPVs) for commercial vehicles mandate a certification process involving pressurization up to 1050 bar, with the critical requirement of withstanding burst pressures of 1570 bar. Analyzing proof test data is crucial to enhance and ensure tank safety regarding burst pressure. In this study, we developed various machine learning classifiers for structure health monitoring and damage prediction of COPVs. The classifiers were trained using a substantial amount of acoustic emission data collected during burst and pressure cycling tests. The test results were employed as label inputs during the training process. Statistical features were extracted per time unit and trained using Naive Bayes, Logistic Regression, Decision Tree, XGBoost, and TabNet models. Upon training the data collected from the burst pressure test, TabNet, Decision Tree, and XGBoost achieved classification accuracies above 0.94. Notably, TabNet demonstrated also the best performance for the pressure cycling test with an accuracy of 0.98. Furthermore, TabNet provided visualizations of feature sensitivity in relation to classification results. This study marks the first development of a machine learning classifier for predicting the damage state of COPV tanks in commercial applications pertaining to required safety tests.

Design of continuous transition line pattern between layers of composite pressure vessel

To realize efficient and stable continuous transition between different winding process layers of composite pressure vessels. This article uses the non-geodesic winding equation to propose a transition layer design method for composite pressure vessel shells with circular cross-section core molds and ellipsoidal heads. Firstly, the fourth-order Runge–Kutta method is used to solve the non-geodesic stabilized winding pattern and then analyze different regions’ transition ability. Established a calculation model to determine the corresponding transition winding trajectory according to the known core mold shape and fiber position and carried out computer image simulation of different modes of transition layer patterns, and finally carried out experimental verification of 35 MPa composite pressure vessel based on the simulation. The results show that different regions of the core mold have different abilities to change different starting winding angles, and the design of the transition process layer based on this law can save the area needed for transition. This method realizes the smooth transition of different process layers; the fiber of the transition layer does not slip in the actual winding process, and the actual pattern of the winding is consistent with the simulation results, which saves 20.8% of the winding time, and effectively improves the automation of the composite pressure vessel winding process.

Advanced methods for the detection of measurement outliers in fibre optic strain measurements for non-destructive monitoring of the structural health of composite over-wrapped pressure vessels of type-IV

To analyse the applicability of fibre optic measurements as a measurement method for structural health monitoring, fibre-optic sensors are placed on the vessel surface. The influence of the surface profile of the vessel on the measurement result is analysed by correlating the 3D scanned surface and measurement results. One outcome is that the measurement is substantially influenced by the surface topography. The surface height can be directly correlated to the strain magnitude, which is also verified by analytical calculations. Outliers and invalid values can be traced back to surface-related influences on the sensor fibre. For the outlier detection, a novel method is presented, which is based on quantitative evaluation criteria and inductive reasoning and enables transient cycle- by-cycle outlier detection adapted to the load case. Based on the results an estimate for the expanded measurement uncertainty is given for of the measurement chain consisting of vessel, adhesive and sensor fibre.

Design method of variable slippage coefficient non‐geodesic filament‐wound composite pressure vessels

AbstractPrevious studies on the design methods of filament winding paths for composite pressure vessels have mainly focused on geodesic and constant slippage coefficient non‐geodesic patterns, neglecting the design of variable slippage coefficients along the fiber path. In this paper, a design method of variable slippage coefficient non‐geodesic filament wound composite pressure vessels is proposed. The study begins by establishing a meridian rotation mapping model and deriving fiber path equations on the shell surface. Subsequently, the fiber paths, curvature characteristics, slippage coefficients, and shell stress responses of the shell under variable geometrical parameters are simulated and analyzed. Next, the winding parameters are optimized while considering bandwidth and stable winding constraints. The optimal winding parameters are determined, and filament winding simulations are conducted on composite pressure vessels. Results demonstrate the feasibility of the proposed method for variable slippage coefficient fiber path winding mode, providing a new and effective filament winding path design approach for composite pressure vessels.Highlights Establishment of meridian rotation mapping model and simulation of shell fiber paths under variable geometric parameters. The fiber paths, curvature characteristics, slippage coefficients, and winding angles of the shell under variable geometrical parameters are simulated and analyzed. Stress response analysis of shells based on Tsai‐Wu failure criterion and classical lamination theory stress field dimensionless modeling. Construction of winding parameter optimization strategies and bandwidth error evaluation based on stable winding and fiber bandwidth constraints. Simulation of variable slippage coefficient non‐geodesic filament winding for composite pressure vessels with different parameters.