Residual strength prediction for unidirectional CFRP using a nonlinear viscoelastic constitutive equation considering entropy damage

Sato, Mio; Hasegawa, Kodai; Koyanagi, Jun; Higuchi, Ryo; Ishida, Yuichi

doi:10.1016/j.compositesa.2020.106178

Cited by 32 publications

(22 citation statements)

References 50 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Moreover, damage to composites is prone to increase, and will reduce structural bearing capacity and strength. If no damage is discovered and addressed appropriately in the initiation state, it can facilitate severe damage or even structural failure [4]. Hence, it is crucial to continuously monitor the damage status of composite structures to enhance structural safety [5].…”

Section: Introductionmentioning

confidence: 99%

Lamb Wave-Based Damage Localization and Quantification in Composites Using Probabilistic Imaging Algorithm and Statistical Method

Guo

Zeng

Liu

et al. 2022

Sensors

View full text Add to dashboard Cite

Quantitatively and accurately monitoring the damage to composites is critical for estimating the remaining life of structures and determining whether maintenance is essential. This paper proposed an active sensing method for damage localization and quantification in composite plates. The probabilistic imaging algorithm and the statistical method were introduced to reduce the impact of composite anisotropy on the accuracy of damage detection. The matching pursuit decomposition (MPD) algorithm was utilized to extract the precise TOF for damage detection. The damage localization was realized by comprehensively evaluating the damage probability evaluation results of all sensing paths in the monitoring area. Meanwhile, the scattering source was recognized on the elliptical trajectory obtained through the TOF of each sensing path to estimate the damage size. Damage size was characterized by the Gaussian kernel probability density distribution of scattering sources. The algorithm was validated by through-thickness hole damages of various locations and sizes in composite plates. The experimental results demonstrated that the localization and quantification absolute error are within 11 mm and 2.2 mm, respectively, with a sensor spacing of 100 mm. The algorithm proposed in this paper can accurately locate and quantify damage in composite plate-like structures.

show abstract

Section: Introductionmentioning

confidence: 99%

Lamb Wave-Based Damage Localization and Quantification in Composites Using Probabilistic Imaging Algorithm and Statistical Method

Guo

Zeng

Liu

et al. 2022

Sensors

View full text Add to dashboard Cite

show abstract

“…Stress relaxation is a common phenomenon in polymer composite materials and the rate of relaxation can be affected by time, temperature, initial strain, environment, and so on [1][2][3][4]. In the course of long-term service, a pre-stressed part in a structure may lose its prescribed initial stress due to stress relaxation, and structural failure may occur when the retained stressed is less than the threshold value [5][6][7].…”

Section: Introductionmentioning

confidence: 99%

An Engineering Prediction Model for Stress Relaxation of Polymer Composites at Multiple Temperatures

et al. 2022

View full text Add to dashboard Cite

This study develops an engineering prediction model for stress relaxation of polymer composites, allowing the prediction of stress relaxation behaviour under a constant strain, over a range of temperatures. The model is based on the basic assumption that in the stress relaxation process the reversible strain is transformed to irreversible strain continuously. A strain-hardening model is proposed to incorporate nonlinear elastic behaviour, and a creep rate model is used to describe the irreversible deformation in the process. By using stress relaxation data at different temperatures, under different strains, the dependence on temperature and initial strain of the model parameters can be established. The effectiveness of the proposed model is verified and validated using three polymer composite materials. The performance of the model is compared with three commonly used stress relaxation models such as the parallel Maxwell and Prony series models. To ease the use of the proposed model in realistic structural problems, a user subroutine is developed, and the stress relaxation of a plate structure example is demonstrated.

show abstract

“…Naderi et al revealed that failure occurs when entropy generation inside materials reaches a threshold value [9]. Sato et al reported that the fracture entropy generation of TriA-X polyimide was ~15.5 kJ/m 3 K [11]. Entropy-based damage evaluation has been experimentally confirmed for metallic [12][13][14], polymeric [9], and composite materials [15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

A Possibility for Quantitative Detection of Mechanically-Induced Invisible Damage by Thermal Property Measurement via Entropy Generation for a Polymer Material

et al. 2022

Self Cite

View full text Add to dashboard Cite

Entropy generation from a mechanical and thermal perspective are quantitatively compared via molecular dynamic (MD) simulations and mechanical and thermal experiments. The entropy generation values regarding mechanical tensile loading—which causes invisible damage—of the Polyamide 6 (PA6) material are discussed in this study. The entropy values measured mechanically and thermally in the MD simulation were similar. To verify this consistency, mechanical and thermal experiments for measuring entropy generation were conducted. The experimentally obtained mechanical entropy was slightly less than that calculated by MD simulation. The thermal capacity is estimated based on the specific heat capacity measured by differential scanning calorimetry (DSC), applying the assumed extrapolation methods. The estimated entropy generation was higher than the aforementioned values. There is a possibility that the entropy-estimating method used in this study was inappropriate, resulting in overestimations. In any case, it is verified that entropy increases with mechanical loading and material invisible damage can be qualitatively detected via thermal property measurements.

show abstract

Residual strength prediction for unidirectional CFRP using a nonlinear viscoelastic constitutive equation considering entropy damage

Cited by 32 publications

References 50 publications

Lamb Wave-Based Damage Localization and Quantification in Composites Using Probabilistic Imaging Algorithm and Statistical Method

Lamb Wave-Based Damage Localization and Quantification in Composites Using Probabilistic Imaging Algorithm and Statistical Method

An Engineering Prediction Model for Stress Relaxation of Polymer Composites at Multiple Temperatures

A Possibility for Quantitative Detection of Mechanically-Induced Invisible Damage by Thermal Property Measurement via Entropy Generation for a Polymer Material

Contact Info

Product

Resources

About