Research on human skin anatomy reveals its complex multi-scale, multi-phase nature, with up to 70% of its composition being bounded and free water. Fluid movement plays a key role in the skin's mechanical and biological responses, influencing its time-dependent behavior and nutrient transport. Poroelastic modeling is a promising approach for studying skin dynamics across scales by integrating multi-physics processes. This paper introduces a hierarchical two-compartment model capturing fluid distribution in the interstitium and micro-circulation. A theoretical framework is developed with a biphasic interstitium -- distinguishing interstitial fluid and non-structural cells -- and analyzed through a one-dimensional consolidation test of a column. This biphasic approach allows separate modeling of cell and fluid motion, considering their differing characteristic times. An appendix discusses extending the model to include biological exchanges like oxygen transport. Preliminary results indicate that cell viscosity introduces a second characteristic time, and at high viscosity and short time scales, cells behave similarly to solids. A simplified model was used to replicate an experimental campaign on short time scales. Local pressure (up to 31 kPa) was applied to dorsal finger skin using a laser Doppler probe PF801 (Perimed Sweden), following a setup described in Fromy Brain Res (1998). The model qualitatively captured ischemia and post-occlusive reactive hyperemia, aligning with experimental data. All numerical simulations used the open-source software FEniCSx v0.9.0. To ensure transparency and reproducibility, anonymized experimental data and finite element codes are publicly available on GitHub.


翻译:暂无翻译

0
下载
关闭预览

相关内容

ACM/IEEE第23届模型驱动工程语言和系统国际会议,是模型驱动软件和系统工程的首要会议系列,由ACM-SIGSOFT和IEEE-TCSE支持组织。自1998年以来,模型涵盖了建模的各个方面,从语言和方法到工具和应用程序。模特的参加者来自不同的背景,包括研究人员、学者、工程师和工业专业人士。MODELS 2019是一个论坛,参与者可以围绕建模和模型驱动的软件和系统交流前沿研究成果和创新实践经验。今年的版本将为建模社区提供进一步推进建模基础的机会,并在网络物理系统、嵌入式系统、社会技术系统、云计算、大数据、机器学习、安全、开源等新兴领域提出建模的创新应用以及可持续性。 官网链接:http://www.modelsconference.org/
Keras François Chollet 《Deep Learning with Python 》, 386页pdf
专知会员服务
163+阅读 · 2019年10月12日
【SIGGRAPH2019】TensorFlow 2.0深度学习计算机图形学应用
专知会员服务
41+阅读 · 2019年10月9日
灾难性遗忘问题新视角:迁移-干扰平衡
CreateAMind
17+阅读 · 2019年7月6日
meta learning 17年:MAML SNAIL
CreateAMind
11+阅读 · 2019年1月2日
disentangled-representation-papers
CreateAMind
26+阅读 · 2018年9月12日
国家自然科学基金
0+阅读 · 2014年12月31日
VIP会员
相关资讯
灾难性遗忘问题新视角:迁移-干扰平衡
CreateAMind
17+阅读 · 2019年7月6日
meta learning 17年:MAML SNAIL
CreateAMind
11+阅读 · 2019年1月2日
disentangled-representation-papers
CreateAMind
26+阅读 · 2018年9月12日
相关基金
Top
微信扫码咨询专知VIP会员