对形状记忆合金的热机械行为进行建模：同时考虑损伤与断裂现象。应用于根管治疗器械的研究。

该博士项目通过开发一种预测性数值工具，旨在解决在牙科根管治疗器械中使用镍钛形状记忆合金所面临的挑战。申请者将构建一种本构模型以模拟热机械行为，进行实验测试，并根据实验数据对模型进行验证，从而提升器械设计水平与临床效果。

Job description: Project description: Modern endodontics relies heavily on files made of nickel–titanium (NiTi) shape memory alloys (SMAs), whose superelasticity-induced flexibility enables the effective treatment of complex root canals. However, the service life of these instruments remains limited by functional and structural fatigue phenomena, as well as by an increased risk of instrument fracture, as reported by dental practitioners [1]. To address this public health and safety challenge, the ANR ENDOPTISHAPE project aims to develop a comprehensive predictive numerical tool to support both instrument design and clinical practice. This PhD project will be conducted within the LEM3-MMSV research team, based at the Polytech Nancy campus, and builds upon the team's previous work [2,3,4]. The doctoral candidate will develop an advanced thermomechanical constitutive model for shape memory alloys (SMAs), incorporating the coupled effects of plasticity, material damage, and fracture [5]. The numerical integration techniques used to solve the constitutive equations will be revisited to reduce computational time and improve the reliability and robustness of the simulations. The resulting formulation will be implemented as a user-defined material subroutine (UMAT) in the Abaqus finite element analysis software. In parallel, the doctoral candidate will actively contribute to experimental characterization using the laboratory's dedicated testing facilities (SMART platform). This work will involve improving the reference penetration–withdrawal test, notably by integrating an environmental chamber to reproduce the intraoral temperature of 35 °C and by using a multiaxial force sensor. Similar investigations will also be conducted to characterize instrument performance under combined bending and torsional loading. Finally, a key component of the research will involve systematically comparing experimental data with numerical predictions to validate the developed model. Accordingly, four closely interconnected research areas will be addressed to successfully carry out this PhD project. - Literature Review and Theoretical Formulation : Conduct an in-depth review of the state of the art in the thermomechanical behavior of shape memory alloys (SMAs), as well as damage and fracture mechanisms relevant to endodontic instruments. - Numerical Model Development and Implementation : Extend the proposed free-energy formulation describing the thermomechanical behavior of SMAs to account for the coupling between martensitic transformation, plasticity, and damage, followed by coding and implementation in Abaqus. This stage will build upon an initial phase dedicated to improving the performance of the numerical tools. - Advanced Experimental Characterization : Conduct optimized penetration–withdrawal tests on artificial root canals and extracted natural teeth at the intraoral temperature of 35 °C, with high-resolution acquisition of the components of the mechanical action wrench. A similar approach will be adopted for bending–torsion tests. - Model Validation and Coupling : Perform a rigorous comparative analysis of experimentally measured responses and numerical results obtained using the developed model, directly contributing to the enhancement of the project's comprehensive predictive tool.

所需个人简历与技能要求： 具备扎实的结构与材料力学以及数值方法基础至关重要。熟悉使用Fortran、Python和C++进行编程的经验将更具优势。 书面及口语均具备良好的英语能力非常重要，而掌握法语则是一种优势。 理想的申请者应为充满热情的研究人员，具有强烈的学习与探索欲望；喜欢在国际团队中工作，并对实验研究与理论研究均抱有浓厚兴趣。 要求的法语水平：熟练/流畅：您能够自如地使用语言，并在讨论复杂主题时表现出足够的能力。 所需英语水平：高级中级：您能够有效使用语言，并能准确表达观点。