Nonlinear electro-elastic finite element analysis with neural network constitutive models

A nonlinear finite element analysis (FEA) model is presented for simulating the behaviour of recycled aggregate concrete-filled steel tube (RACFST) beam-columns subjected to constant axial compressive load and cyclically increasing flexural loading. The FEA model was developed based on ABAQUS software package and a displacement-based approach was used. The proposed engineering stress versus engineering strain relationship of core concrete with the effect of recycled coarse aggregate (RCA) replacement ratio was adopted in the FEA model. The predicted results of the FEA model were compared with the experimental results of several RACFST as well as the corresponding concrete-filled steel tube (CFST) beam-columns under cyclic loading reported in the literature. The comparison results indicated that the proposed FEA model was capable of predicting the load versus deformation relationship, lateral bearing capacity and failure pattern of RACFST beam-columns with an acceptable accuracy. A parametric study was further carried out to investigate the effect of typical parameters on the mechanism of RACFST beam-columns subjected to cyclic loading.

This special issue of the Journal of Aerospace Engineering contains a collection of invited papers written by experts working in various areas of composite materials and structures. Some of these papers are based on the presentations delivered in the ‘‘Advanced Composite Materials for Civil/Aerospace Engineering Applications’’ session organized by the ASCE Aerospace Division’s Committee on Advanced Composite Materials at the 2001 SDM Conference. The diversity of topics addressed in this special issue deal not only with composite materials and structure, but other fundamental mechanics applications to aircraft/aerospace analysis and design problems. This reflects the broad interests of the committee’s members. The papers address various rapidly growing areas in aerospace/aircraft applications of composite materials and structures, as well as the development of analytical/numerical techniques in support of test methods. The addressed topics include multiscale modeling of composite materials, material parameter estimation for isotropic and anisotropic materials, use of smart materials in vibration damping, development of analysis techniques and test methodologies for impact testing of aircraft engine components and high speed testing of aircraft/aerospace vehicles, and newly emerging lattice structures, as described in more detail later. Bednarcyk and Arnold present a comprehensive multiscale analysis for the response of metal matrix composites and apply it to a particular material system. The analysis combines micromechanical predictions for the individual ply response within the lamination theory analysis at each loading step. The effects of matrix inelasticity and local damage mechanisms such as fiber breakage/debonding and fatigue-induced matrix damage are taken into account. They developed micromechanics-based methodology which is an important step in utilizing the power of micromechanics to predict failure and fatigue life of metal matrix composites. In the paper by Saleeb et al., the writers present a strategy for estimating material parameters using experimental test data and a chosen constitutive material model. The class of admissible constitutive materials includes some recent viscoplastic and damage models. The procedure which consists of three stages, namely analysis, sensitivity and optimization modules, is implemented through a computer program. The method’s effectiveness is demonstrated through the use of specific experimental data, which reflects different observed material behavior. The use of smart sensors and actuators in active vibration damping of composite beams is the topic of the paper by Song et al. The writers present two approaches for active vibration control of laminated composite beams based on positive and strain rate feedback control algorithms. The experiments that demonstrate the utility of these algorithms are supported by analytical and numerical analyses of the beam response. The paper by Roberts et al. is a conceptoriented contribution in which the writers develop a methodology for evaluating different design concepts for aircraft engine fan cases, taking into account potential failure modes due to impact damage. Experimental impact data are supplemented by numerical analyses of impacted composite panels in order to identify appropriate specimen designs and related failure modes, and offer potential solutions to minimizing impact-induced damage. The results indicate that composite materials are viable candidates for use in aircraft engine fan cases when impact is a limiting design parameter. In the paper by Kocher et al., the writers investigate selected failure modes of a new generation of structural components, known as lattice structures, and how such modes impact the design of these structures. These structures consist of sandwich panels reinforced with truss members in the core. Simple analytical approaches are employed to focus on designs that lead to particular failure modes, and these are further investigated using the finite-element method. Both the topic and the generated results complement the current material/structural development efforts for advanced aircraft/aerospace applications. Finally, Baker et al. develop a model and an analysis technique for a practical problem of rail heating of the Air Force’s high-speed test track facility. This model demonstrates the importance of including temperature fields when analyzing the response of rails subjected to impact loading induced by high-velocity vehicles.

Offshore pipeline on-bottom roughness analysis is generally performed to understand pipe stress and areas of free spanning. In this paper, the predicted pipeline profiles, by finite element analysis (FEA) modeling, are compared with survey data. Several case studies are presented and parametric effects are assessed. The FEA modeling procedures are presented in this paper along with several project experiences. The pipeline on-bottom roughness analysis is conducted to determine the pipe stress and the associated fatigue damage due to internal pressure and temperature fluctuation and vortex-induced vibration (VIV) of free span sections due to seabed unevenness. The analysis presented in this paper can aid the design of pipeline free spans and mitigation, if required. The parametric effects of higher and lower bound soil stiffness, friction resistance, pipeline bottom tension, external / internal pressure, and content density are considered. The predicted pipeline profiles by FEA modeling are compared with surveyed profiles under several loading conditions. A strong correlation between survey data and finite element analysis (FEA) is achieved. This paper shows that the FEA stress prediction is adequate, and the FEA modeling is suitable as an advanced design tool for pipeline on-bottom roughness assessment and free span behavior analysis. A commonly used mitigation method for VIV fatigue is to install VIV suppression strakes. For overstresses due to pipeline bending effect, the common mitigation methods are to install mechanical supports, use heavy wall pipe and correct the seabed unevenness among others. It is important to reliably predict the pipeline profiles in order to precisely assess the pipeline free span response and to provide guidance to determine a proper free span mitigation strategy. The FEA method can be utilized to realistically simulate the pipeline on-bottom roughness behavior affected by the pipe properties, pipe-soil interaction including penetration and soil friction resistance, the internal and external pressure, product content, temperature profile, and the bottom tension from pipe-lay. An accurately built FEA model can provide a reliable prediction for the pipeline profile, free spanning length and gap under all conditions, which are crucial for the stress and fatigue assessment as well as for the design of free span mitigation.

Behavior of flat grouted connections subjected to lateral pressure and vertical load

The application of composite materials in bogies for high‐speed electric multiple units (EMUs) has been regarded as a technical breakthrough. The application of composite materials in rail vehicles began late in China. Currently, most composite materials are used in non‐load‐bearing components on the track, and applications in bogies, tie beams, and other load‐bearing components are not mature. In this paper, we innovatively apply a design strategy using thin‐ply on the composite bolster of a bogie for a multiple unit to optimize the static strength of the composite structure under very complex loading. We applied nine unconventional loads and 11 major operating loads in total to evaluate a potential positive influence of using thin‐ply on the static strength of the composite bolster of a bogie. The numerical results showed that for all the complex loading scenarios, the application of thin‐ply could effectively improve the static strength of the composite structure, which is more effective at the location of the bolts and holes. The research results break through the traditional design ideas of composite structures and provide an effective ply design and optimization strategy for composite structure design engineering of high‐speed EMU.

Integration of the modified Cam-Clay model in non-linear finite element analysis

Wireline tools are designed in such a way that they can be lowered into a wellbore on the end of the wireline cable. They can be used for helping evaluate the reservoir and rock properties and formation pressures, locate casing collars, identify the properties of liquid present in the reservoir, and so on. Wireline tools can be subjected to harsh conditions such as those found in many modern oil, gas, and geothermal wells. For instance, pressures in gas wells can exceed 15,000 psi, while temperatures can reach 400 deg Fahrenheit in some geothermal wells. The tools can also experience bending loads when measurement is performed in the curved section of a well, and tension when the tool is pulled out. Housings are critical tubular-like structures that are intentionally designed to withstand such combined loads acting on the tool and protect the measurement components in the tool from damage during operation. Collapse of the housings has been one of the major failure modes and concerns for structural integrity of the wireline tools. Moreover, with continuous operation over time, these housings can get worn out, which could result in reduced collapse resistance. Collapse failures, particularly for those nuclear tools with radiation sources and nuclear detectors, can cause not only loss of the expensive assets, but also harm to the environment. Therefore, there is a strong demand to develop a fast-loop model that can be used for efficiently predicting the collapse resistance of the housings under combined service loads. Placement of the tool in a pressure vessel for physical testing could take several weeks’ effort, and is only affordable on a few limited sample configurations and pressure-only conditions. Conventionally, pressure rating of the housing was evaluated with empirical equations and an imposed safety factor, and its accuracy was limited to a ballpark estimation. When a housing needs to be qualified for high pressure applications, a high fidelity FEA (finite element analysis) model needs to be used. However, nonlinear FEA of a pressure housing could take hours due to its high-fidelity nature, which prevents it from being used as a computing engine for real-time applications. It is demonstrated in this paper that such challenges can be overcome with a newly developed computational framework by combining state-of-the art machine learning and nonlinear FEA for efficient and accurate collapse pressure predictions. First, a nonlinear FEA model that captures dimensions of both new and worn housings, elasto-plastic material properties, and environmental loads such as pressure, bending, tension, and temperature was developed, parametrized, and automated for parametric studies. Second, a carefully selected synthesized dataset containing simulation-based solutions, which had been pre-produced with automated FEA of the housings, was used to train a fast-loop predictive model. Third, feature engineering was performed to discover the compressed feature space representation of the data. Finally, modern supervised machine learning (ML) algorithms with hyperparameter tuning techniques were then evaluated to select a best performing model that can map the underlying pattern between the features and the collapse pressure of the housings. The resulting collapse pressure predictions for the housings were found to agree favorably well with the holdout dataset, which contains the experimental measurements from pressure vessel testing. This newly developed surrogate model has been deployed to a cloud-based platform for enabling prompt model-based job planning and asset utilization optimization without consuming expensive commercial FEA software licenses. The implemented model takes 1–2 minutes to calculate the pressure rating of a housing with satisfactory calculation accuracy.

The combination of thin-walled steel structure with concrete infill can be used as the alternative material properties in the building in Indonesia. This composite material is suitable for seismic-resistant building because it has more ductility than conventional material. In the tsunami event, some tsunami debris strikes the building and induced partial or full collapse of the building. The loading tip shape of tsunami debris which contacts to a tubular surface affects the local deformation or buckling mode of the thin-walled structures. In order to investigate the effects, we conducted three-dimensional nonlinear finite element analyses of concrete filled square steel tubular members subjected to concentrated lateral loads by using the finite element analysis (FEM) program MSC Marc/Mentat. The fiber element analysis is also performed to reduce the analysis time of FEM and simplify the analysis. The accuracy of the FEM and fiber element analysis is verified by the experiment. Being based on the parametric numerical study, it discusses the effect of axial load on the load-deflection relations. It shows that the higher the axial load, the more degradation the ductility of the structure.

A finite element analysis (FEA) model is established to investigate the concrete-encased concrete-filled steel tubular (CFST) column to reinforced concrete (RC) beam joints under cyclic loading. The feasibility of the FEA model is verified by a set of test results, consisting of the failure modes, the exposed view of connections, the crack distributions and development, and the hysteretic relationships. The full-range analysis is conducted to investigate the stress and strain development process in the composite joint by using this FEA model. The internal force distributions of different components, as well as the deformation distributions, are analyzed under different failure modes. The proposed connections are investigated under dimensional and material parameters, and the proper constructional details of the connections are recommended. Parameters of the beam-column joints, including material strength, confinement factor, reinforcement ratio, diameter of steel tube to sectional width ratio, beam to column linear bending stiffness ratio and beam shear span ratio are evaluated. Furthermore, the key parameters affecting the failure modes and the corresponding parameters ranges are proposed in this paper.

Intelligent finite element method: An evolutionary approach to constitutive modeling

Carbon fiber (CF) ankle-foot orthoses (AFOs) can improve gait by increasing ankle plantar-flexor power and improving plantar-flexor ankle joint moment and energy efficiency compared with posterior leaf spring AFOs made of thermoplastic. However, fabricating a CF AFO to optimize the performance of the individual user may require multiple AFOs and expensive fabrication costs. Finite element analysis (FEA) models were developed to predict the mechanical behavior of AFOs in this study. Three AFOs, two made of CF composite material and one made of thermoplastic material, were fabricated and then mechanically tested to produce force-displacement data. The FEA models were validated by comparing model predictions with mechanical testing data performed under the same loading and boundary conditions. The actual mechanical testing demonstrated that CF performs better than thermoplastic. The simulation results showed that FEA models produced accurate predictions for both types of orthoses. The relative error of the energy return ratio predicted by the CF AFO FEA model developed in this study is less than 3%. We conclude that highly accurate FEA models will allow orthotists to improve CF AFO fabrication without wasting resources (time and money) on trial and error fabrications that are expensive and do not consistently improve AFO and user performance.

ABSTRACTCycloaliphatic epoxies (CEs) are commonly used for structural applications requiring improved resistance to elevated temperatures, UV radiation, and moisture relative to other epoxy materials. Accurate and efficient computational models can greatly facilitate the development of CE‐based composite materials for applications such as Aluminum Conductor Composite Core high‐voltage power lines. In this study, a new multiscale modeling method is developed for CE resins and composite materials to efficiently predict thermal properties (glass‐transition temperature, thermal expansion coefficient, and thermal conductivity). The predictions are compared to experimental data, and the results indicate that the multiscale modeling method can accurately predict thermal properties for CE‐based materials. For 85% crosslink densities, the predicted glass‐transition temperature, thermal expansion coefficient, and thermal conductivity are 279 °C, 109 ppm °C−1, 0.24 W m−1 K−1, respectively. Thus, this multiscale modeling method can be used for the future development of improved CE composite materials for thermal applications. © 2018 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2018, 135, 46371.

Most wellbore strengthening (WBS) techniques require an understanding of the width on an induced fracture to design the size and concentration of appropriate mud additives to mitigate the fracture growth. Current methods to estimate fracture width primarily consider stress and rock properties but neglect the effect of the thermal contrast between the drilling fluid and the formation. This paper reports the results of the modeling of the thermal effect on fracture width and proposes a practical method to integrate the thermal effect into current WBS design workflows. The proposed process uses both analytical and numerical methods to investigate the thermal effect. A finite element analysis (FEA) model simulates the coupled stress and temperature field around the borehole, which allows the width of the fracture to be derived at any point along the length. The Abaqus FEA model uses 2-D plane strain elements to allow either steady-state or transient thermal-mechanical analysis. The results of FEA modeling are compared to the semi-analytical solution which only addresses the mechanical effect. Both models use field data to verify and validate results. An equivalent tensile stress is used to derive an analytical solution for fracture width for the case of ‘long-term’ cooling. The results provide a good match to the steady-state thermal elastic FEA results. In the case of transient heat transfer, an approximate analytical solution is derived to describe temperature distribution around the borehole as function of time. Then the analytical solution for thermal stresses is derived based on intact circular borehole. The analytical results are compared and verified with the FEA. Currently, the fracture width in response to a transient thermal event can only be calculated using the FEA model. The change in fracture width due to the temperature disturbance can be superimposed over the elastic fracture width to provide a more accurate estimate of width due to both mechanical and thermal influences for planning WBS formulations. The model demonstrates that the cooling of the borehole with drilling mud results in a wider fracture than that which is predicted by the purely elastic models. If drilling mud temperature is not considered or managed effectively, the failure of the WBS application could result, leading to a lost circulation event. A field case where wellbore cooling occurs and leads to lost circulation is presented.

Advanced composite materials have been commonly used in aerospace engineering, because of their good mechanical properties and attractive potential for creating lightweight structures. Susceptibility to delamination is one of the most important issues in the applications of these materials. This disadvantage can prohibit the application of composite materials in primary aerospace structures and limit their lightweight potential. Therefore, characterizing fatigue delamination growth behavior in composite laminates is important for the applications of these materials in aerospace, as it provides the necessary information for the damage tolerance design philosophy. Fibre bridging is an important shielding mechanism during delamination growth in composite laminates. It can increase the fracture toughness by restraining the crack opening and inhibit delamination growth. However, there is no reliable method to take into account of its contribution to fatigue delamination growth. Thus, investigation of this phenomenon and development of a prediction method is required. The objective of this investigation is to study mode I fatigue delamination growth with fibre bridging in composite laminates and provide physics-based interpretations of fatigue delamination growth. Two approaches are applied to interpret the fatigue delamination growth behavior according to different perspectives. In the engineering perspective, the Paris relation is applied. However, in the physics-based perspective, energy principles are used. The bridging effect on fatigue delamination growth is first investigated by a series of fatigue tests. The Paris relation is used to interpret the fatigue data. It demonstrates that fibre bridging can significantly decrease the fatigue crack growth rate, making it invalid to use a single fatigue resistance curve to determine fatigue delamination with bridging. A new method, still based on the Paris relation, is developed to predict fatigue delamination growth with fibre bridging, by correlating the curve fitting parameters with the amount of bridging fibres. Fatigue delamination growth is physically explained according to the energy conservation law. It is found that bridging fibres periodically store and release strain energy upon loading and unloading cycles. However, they have no contribution to the real strain energy release, unless the bridging fibre pullout or fails. This can lead to the invalidity of using the strain energy release rate (SERR) determined by the fixed grip assumption for quasi-static crack growth to interpret fatigue crack growth. Therefore, the SERR commonly used is not a suitable similitude parameter to determine fatigue delamination growth. Energy principles are subsequently used to interpret the stress ratio effect in fatigue delamination growth. A concept of fatigue fracture toughness is proposed to describe the steady fatigue delamination growth, in which little or no bridging fibre pullout or failure occurs. Therefore, all energy dissipation in the steady delamination growth is concentrated on the new crack generation. The fatigue fracture toughness is observed to be interface configuration independent but significantly stress ratio dependent. The mechanisms related to this are interpreted by fractographic observation. Using the concept of fatigue fracture toughness, the stress ratio effect on fatigue delamination growth can be explained with a clear physical background.

The paper briefly summarizes the application of composite materials on various sports equipments, especially the specific application on table tennis bats and tables. The paper explains the good properties of composite materials shown in the table tennis bat in detail through a data analysis. It has an important significance on the improvement of table tennis. Through table tennis, the paper shows the wide and profound application of composite materials in the field of sports equipments.