The mechanics of $\textit{Less In More Out}$: modeling fabric-based soft robotic hearts

TL;DR

This work develops a finite-element model of a fabric-based, fluid-actuated soft total artificial heart (the LIMO device) and validates it against quasi-static experiments. Using a symmetric, heat-sealed fabric geometry and a St. Venant–Kirchhoff–type fabric model, the framework reproduces nonlinear deformation, pressure–volume behavior, buckling events, and fatigue indicators, enabling design optimization across pouch counts and loading conditions. Key findings include that lower pouch counts yield larger stroke volumes, peak stresses concentrate at seams and buckle zones, and fatigue risk maps align with observed failure sites, all while the device remains efficient across afterload scenarios. The framework links macroscopic pumping performance to local stresses and strains, supporting targeted reinforcement, material optimization, and geometry adjustments, with potential extension to fully coupled fluid–structure and circulation models for patient-specific design optimization.

Abstract

Fabric-based soft robots combine high load-carrying capacity, efficiency, and low weight with the ability to bend, twist, contract, or extend with ease, making them promising candidates for biomedical applications such as soft total artificial hearts. While recent experiments have demonstrated their potential, predictive numerical models are urgently needed to study their complex mechanics, guide design optimization and improve their reliability. We develop a computational model of the Less In More Out device, a fluidically actuated soft total artificial heart constructed from heat-sealed layers of woven fabric. Our model reproduces the nonlinear deformation, strain fields, and pressure-volume relationships measured in quasi-static experiments. Devices with fewer pouches deliver higher stroke volumes but exhibit up to 50% higher peak von Mises stresses. Fatigue analysis using a strain-life approach identifies heat-sealed seams and buckling regions as durability-limiting features. Our framework enables detailed evaluation of stress concentrations, buckling, and fatigue life, providing mechanistic insights that are difficult to obtain experimentally. It also offers a foundation for the optimization of artificial hearts and other fluid actuated fabric-based soft robotic systems.

Figures (18)

• Figure 1: Computational domain of the soft ventricle and deformation during quasi-static inflation. Isometric view of the computational domain $\Omega_0=\Omega_{\text{endo},0} \cup \Omega_{\text{epi},0} \cup \Omega_{\text{pouch},0}$ with the valve boundary $\Gamma_{\text{valve},0}$ at different time during the quasi-static inflation. (left) Reference configuration of the device before being fitted to the valve support. (center) Initial configuration of the device after the fitting step. (right) Current configuration at the end of a quasi-static inflation with a static pressure $P_v=13.8$ kPa.
• Figure 1: Schematic of the domain and boundary conditions and mesh for the square airbag validation case. Symmetric boundary conditions are imposed in the symmetry planes ($x=0$ and $y=0$) while the vertical displacement of the outer-edge is fixed ($w=0$). Since we have three symmetry planes, we model only 1/8$^\text{th}$ of the geometry, here represented by a quadrilateral mesh with $N=41$, instead of the total upper surface of the pillow (grey area).
• Figure 1: Time evolution of the device deformation for $N_p=4$ under various afterloads $P_\text{aft}$. Deformed geometry, colored with deformation magnitude, normalised by device length. Top, middle, and bottom rows correspond to afterload pressures of 0, 10, and 20 kPa, respectively. The different snapshots are equally spaced during static inflation, starting from the reference configuration, where the pressure in the ventricle is maximal and the actuation pressure is zero ($t=1$), until the maximal actuation pressure is reached ($t=2$).
• Figure 1: Fatigue life estimate for $N_p \in \{4,6,8,10\}$ under various afterloads $P_\text{aft}$. Isocontourf of the expected number of cycles of a pure TPU device using the maximal principal strain in the membrane as a reference strain for the fatigue assessment see Section \ref{['ssec:res_stress_fatigue']} and Figure \ref{['fig:fatigue_life']} for a detail description of the method used. Note that we assume that the weakest points are near the seams on the TPU-TPU bonds, and thus we use a strain-cycle curve for pure TPU type only. The expected number of cycles is only valid in the seams region. Top, middle, and bottom rows correspond to afterload pressures of 0, 10, and 20 kPa, respectively.
• Figure 2: Time evolution of the deformation for the different devices under an afterload $P_\text{aft}=0$ kPa. Rows correspond to different pouch numbers $N_p\in\{4,6,8,10\}$ and the different columns are at different time during the quasi-static inflation. $t=1$ corresponds to the initial configuration and $t=2$ to the final state at the maximum actuation pressure.