Institute of Fundamental Technological Research

The macroscopic behaviors of materials are determined by interactions that occur at multiple lengths and time scales. Depending on the application, describing, predicting, and understanding these behaviors may require models that rely on insights from atomic and electronic scales. In such cases, classical simplified approximations at those scales are insufficient, and quantum-based modeling is required. In this paper, we study how quantum effects can modify the mechanical properties of systems relevant to materials engineering. We base our study on a high-fidelity modeling framework that combines two computationally efficient models rooted in quantum first principles: Density Functional Tight Binding (DFTB) and many-body dispersion (MBD). The MBD model is applied to accurately describe non-covalent van der Waals interactions. Through various benchmark applications, we demonstrate the capabilities of this framework and the limitations of simplified modeling. We provide an open-source repository containing all codes, datasets, and examples presented in this work. This repository serves as a practical toolkit that we hope will support the development of future research in effective large-scale and multiscale modeling with quantum-mechanical fidelity.

DFT, DFTB, Energy range separation, Many-body dispersion, van der Waals interaction, Carbon nanotube, UHMWPE

In many cutting-edge applications, high-fidelity computational models prove to be too slow for practical use and are therefore replaced by much faster surrogate models. Recently, deep learning techniques have increasingly been utilized to accelerate such predictions. To enable learning on large-dimensional and complex data, specific neural network architectures have been developed, including convolutional and graph neural networks. In this work, we present a novel encoder–decoder geometric deep learning framework called MAgNET, which extends the well-known convolutional neural networks to accommodate arbitrary graph-structured data. MAgNET consists of innovative Multichannel Aggregation (MAg) layers and graph pooling/unpooling layers, forming a graph U-Net architecture that is analogous to convolutional U-Nets. We demonstrate the predictive capabilities of MAgNET in surrogate modeling for non-linear finite element simulations in the mechanics of solids.

Geometric deep learning, Mesh based simulations, Finite element method, Graph U-Net, Surrogate modeling

We provide an optimization framework that is capable of identifying the material parameters and contact traction field from two measured deformed geometries of a soft body in contact. The novelty of the framework is the idea of parametrizing the missing contact traction field and incorporating it into the inverse+forward hyper-elasticity formulation. We provide the continuum- and finite element formulation of the framework, as well as the direct differentiation method of sensitivity analysis to efficiently obtain necessary gradients for the BFGS optimizer. The correctness of the formulation and the excellent performance of the framework are confirmed by a series of benchmark numerical examples.

Hyper-elasticity, Inverse form, Large strains, Contact, Calibration, Soft bodies

Deep learning surrogate models are being increasingly used in accelerating scientific simulations as a replacement for costly conventional numerical techniques. However, their use remains a significant challenge when dealing with real-world complex examples. In this work, we demonstrate three types of neural network architectures for efficient learning of highly non-linear deformations of solid bodies. The first two architectures are based on the recently proposed CNN U-NET and MAgNET (graph U-NET) frameworks which have shown promising performance for learning on mesh-based data. The third architecture is Perceiver IO, a very recent architecture that belongs to the family of attention-based neural networks–a class that has revolutionised diverse engineering fields and is still unexplored in computational mechanics. We study and compare the performance of all three networks on two benchmark examples, and show their capabilities to accurately predict the non-linear mechanical responses of soft bodies.

surrogate modeling, deep learning-artificial neural network, CNN U-NET, graph U-net, perceiver IO, finite element method

For many novel applications, such as patient-specific computer-aided surgery, conventional solution techniques of the underlying nonlinear problems are usually computationally too expensive and are lacking information about how certain can we be about their predictions. In the present work, we propose a highly efficient deep-learning surrogate framework that is able to accurately predict the response of bodies undergoing large deformations in real-time. The surrogate model has a convolutional neural network architecture, called U-Net, which is trained with force–displacement data obtained with the finite element method. We propose deterministic and probabilistic versions of the framework. The probabilistic framework utilizes the Variational Bayes Inference approach and is able to capture all the uncertainties present in the data as well as in the deep-learning model. Based on several benchmark examples, we show the predictive capabilities of the framework and discuss its possible limitations.

convolutional neural network, Bayesian inference, Bayesian deep learning, large deformations, finite element method, real-time simulations

Being able to reposition tumors from prone imaging to supine surgery stances is key for bypassing current invasive marking used for conservative breast surgery. This study aims to demonstrate the feasibility of using Digital Volume Correlation (DVC) to measure the deformation of a female quarter thorax between two different body positioning when subjected to gravity. A segmented multipart mesh (bones, cartilage and tissue) was constructed and a three-step FE-based DVC procedure with heterogeneous elastic regularization was implemented. With the proposed framework, the large displacement field of a hard/soft breast sample was recovered with low registration residuals and small error between the measured and manually determined deformations of phase interfaces. The present study showed the capacity of FE-based DVC to faithfully capture large deformations of hard/soft tissues.

Digital Volume Correlation, Elastic regularization, Hard/soft tissues, Large displacements, Kinematic fields, X-ray tomography

This contribution presents the extensions of beam‐to‐beam and beam‐inside‐beam contact schemes of the same authors towards frictional interactions. Since the schemes are based on the beams' true surfaces (instead of surfaces implicitly deduced from the beams' centroid lines), the presented enhancements are not only able to account for frictional sliding in the beams' axial directions, but also in the circumferential directions. Both the frictional beam‐to‐beam approach as well as the frictional beam‐inside‐beam approach are applicable to shear‐deformable and shear‐undeformable beams, as well as to beams with both circular and elliptical cross‐sections (although the cross‐sections must be rigid). A penalty formulation is used to treat unilateral and frictional contact constraints. FE implementation details are discussed, where automatic differentiation techniques are used to derive the implementations. Simulations involving large sliding displacements and large deformations are presented for both beam‐to‐beam and beam‐inside‐beam schemes. All simulation results are compared to those of the frictionless schemes.

beam contact, beam-to-beam contact, beam-inside-beam contact, friction, Coulomb's law

We present a distributed framework for predicting whether a planned reconfiguration step of a modular robot will mechanically overload the structure, causing it to break or lose stability under its own weight. The algorithm is executed by the modular robot itself and based on a distributed iterative solution of mechanical equilibrium equations derived from a simplified model of the robot. The model treats intermodular connections as beams and assumes no-sliding contact between the modules and the ground. We also provide a procedure for simplified instability detection. The algorithm is verified in the Programmable Matter simulator VisibleSim, and in real-life experiments on the modular robotic system Blinky Blocks.

distributed algorithms, modular robots, mechanical constraints, programmable matter, self-reconfiguration

Solid contacts involving soft materials are important in mechanical engineering or biomechanics. Experimentally, such contacts have been shown to shrink significantly under shear, an effect which is usually explained using adhesion models. Here we show that quantitative agreement with recent high-load experiments can be obtained, with no adjustable parameter, using a non-adhesive model, provided that finite deformations are taken into account. Analysis of the model uncovers the basic mechanisms underlying anisotropic shear-induced area reduction, local contact lifting being the dominant one. We confirm experimentally the relevance of all those mechanisms, by tracking the shear-induced evolution of tracers inserted close to the surface of a smooth elastomer sphere in contact with a smooth glass plate. Our results suggest that finite deformations are an alternative to adhesion, when interpreting a variety of sheared contact experiments involving soft materials.

contact mechanics, friction, contact area, elastomer, full-field measurement

The key novelty of this contribution is a dedicated technique to efficiently determine the distance (gap) function between parallel or almost parallel beams with circular and elliptical cross-sections. The technique consists of parametrizing the surfaces of the two beams in contact, fixing a point on the centroid line of one of the beams and searching for a constrained minimum distance between the surfaces (two variants are investigated). The resulting unilateral (frictionless) contact condition is then enforced with the Penalty method, which introduces compliance to the, otherwise rigid, beams' cross-sections. Two contact integration schemes are considered: the conventional slave-master approach (which is biased as the contact virtual work is only integrated over the slave surface) and the so-called two-half-pass approach (which is unbiased as the contact virtual work is integrated over the two contacting surfaces). Details of the finite element formulation, which is suitably implemented using Automatic Differentiation techniques, are presented. A set of numerical experiments shows the overall performance of the framework and allows a quantitative comparison of the investigated variants.

beams, contact, circular and elliptical cross-sections, rigid cross-sections, single-pass algorithm, two-half-pass algorithm

This contribution presents a rapid computational framework to mechanically simulate the insertion of a slender medical instrument in a tubular structure such as an artery, the cochlea or another slender instrument.

surgical simulation, contact mechanics, beam-inside-beam, artery, cochlea

We propose a methodology of planning effective shape shifting and locomotion of large-ensemble modular robots based on a cubic lattice. The modules are divided into two groups: fixed ones, that build a rigid porous frame, and mobile ones, that flow through the frame. Mobile modules which flow out of the structure attach to the frame, advancing its boundary. Conversely, a deficiency of mobile modules in other parts of the boundary is corrected by decomposition of the frame. Inside the structure, appropriate module flow is arranged to transport the modules in a desired direction, which is planned by a special distributed version of a maximum flow search algorithm. The method engages a volume of modules during reconfiguration, which is more efficient than common surface-flow approaches. Also, the proposed interpretation as a flow in porous media with moving boundaries seems particularly suitable for further development of more advanced global reconfiguration scenarios. The theoretical efficiency of the method is assessed, and then partially verified by a series of simulations. The method can be possibly also applied to a wider class of modular robots, not necessarily cubic-lattice-based.

modular robots, self-reconfiguration, maximum flow search, programmable matter, distributed algorithms

This review summarizes recent advances in the area of tribology based on the outcome of a Lorentz Center workshop surveying various physical, chemical and mechanical phenomena across scales. Among the main themes discussed were those of rough surface representations, the breakdown of continuum theories at the nano- and microscales, as well as multiscale and multiphysics aspects for analytical and computational models relevant to applications spanning a variety of sectors, from automotive to biotribology and nanotechnology. Significant effort is still required to account for complementary nonlinear effects of plasticity, adhesion, friction, wear, lubrication and surface chemistry in tribological models. For each topic, we propose some research directions.

Tribology, Multiscale modeling, Multiphysics modeling, Roughness, Contact, Friction, Adhesion, Wear, Lubrication, Tribochemistry

The role of contact pressure on skin friction has been documented in multiple experimental studies. Skin friction significantly raises in the low-pressure regime as load increases while, after a critical pressure value is reached, the coefficient of friction of skin against an external surface becomes mostly insensitive to contact pressure. However, up to now, no study has elucidated the qualitative and quantitative nature of the interplay between contact pressure, the material and microstructural properties of the skin, the size of an indenting slider and the resulting measured macroscopic coefficient of friction. A mechanistic understanding of these aspects is essential for guiding the rational design of products intended to interact with the skin through optimally-tuned surface and/or microstructural properties. Here, an anatomically-realistic 2D multi-layer finite element model of the skin was embedded within a computational contact homogenisation procedure. The main objective was to investigate the sensitivity of macroscopic skin friction to the parameters discussed above, in addition to the local (i.e. microscopic) coefficient of friction defined at skin asperity level. This was accomplished via the design of a large-scale computational experiment featuring 312 analyses. Results confirmed the potentially major role of finite deformations of skin asperities on the resulting macroscopic friction. This effect was shown to be modulated by the level of contact pressure and relative size of skin surface asperities compared to those of a rigid slider. The numerical study also corroborated experimental observations concerning the existence of two contact pressure regimes where macroscopic friction steeply and non-linearly increases up to a critical value, and then remains approximately constant as pressure increases further. The proposed computational modelling platform offers attractive features which are beyond the reach of current analytical models of skin friction, namely, the ability to accommodate arbitrary kinematics, non-linear constitutive properties and the complex skin microstructure.

skin friction, contact mechanics, pressure, microstructure, finite element, homogenisation, material properties

In this paper, we present a novel approach to modeling and analysis of Vacuum Packed Particle dampers (VPP dampers) with the use of Discrete Element Method (DEM). VPP dampers are composed of loose granular medium encapsulated in a hermetic envelope, with controlled pressure inside the envelope. By changing the level of underpressure inside the envelope, one can control mechanical properties of the system. The main novelty of the DEM model proposed in this paper is the method to treat special (pressure) boundary conditions at the envelope. The model has been implemented within the open-source Yade DEM software. Preliminary results are presented and discussed in the paper. The qualitative agreement with experimental results has been achieved.

VPP, discrete element method, Yade DEM, modelling, smart structures, smart materials

Due to its multifactorial nature, skin friction remains a multiphysics and multiscale phenomenon poorly understood despite its relevance for many biomedical and engineering applications (from superficial pressure ulcers, through shaving and cosmetics, to automotive safety and sports equipment). For example, it is unclear whether, and in which measure, the skin microscopic surface topography, internal microstructure and associated nonlinear mechanics can condition and modulate skin friction. This study addressed this question through the development of a parametric finite element contact homogenisation procedure which was used to study and quantify the effect of the skin microstructure on the macroscopic skin frictional response. An anatomically realistic two-dimensional image-based multilayer finite element model of human skin was used to simulate the sliding of rigid indenters of various sizes over the skin surface. A corresponding structurally idealised multilayer skin model was also built for comparison purposes. Microscopic friction specified at skin asperity or microrelief level was an input to the finite element computations. From the contact reaction force measured at the sliding indenter, a homogenised (or apparent) macroscopic friction was calculated. Results demonstrated that the naturally complex geometry of the skin microstructure and surface topography alone can play as significant role in modulating the deformation component of macroscopic friction and can significantly increase it. This effect is further amplified as the ground-state Young's modulus of the stratum corneum is increased (for example, as a result of a dryer environment). In these conditions, the skin microstructure is a dominant factor in the deformation component of macroscopic friction, regardless of indenter size or specified local friction properties. When the skin is assumed to be an assembly of nominally flat layers, the resulting global coefficient of friction is reduced with respect to the local one. This seemingly counter-intuitive effect had already been demonstrated in a recent computational study found in the literature. Results also suggest that care should be taken when assigning a coefficient of friction in computer simulations, as it might not reflect the conditions of microscopic and macroscopic friction one intends to represent. The modelling methodology and simulation tools developed in this study go beyond what current analytical models of skin friction can offer: the ability to accommodate arbitrary kinematics (i.e. finite deformations), nonlinear constitutive properties and the complex geometry of the skin microstructural constituents. It was demonstrated how this approach offered a new level of mechanistic insight into plausible friction mechanisms associated with purely structural effects operating at the microscopic scale; the methodology should be viewed as complementary to physical experimental protocols characterising skin friction as it may facilitate the interpretation of observations and measurements and/or could also assist in the design of new experimental quantitative assays.

skin, friction mechanisms, contact mechanics, microstructure, finite element, image-based modelling, material properties

We propose a new class of modular-robotic structures, intended to produce forces which scale with the number of modules. We adopt the concept of a spherical catom and extend it by a new connection type which is relatively strong but static. We examine analytically and numerically the mechanical properties of two collective-actuator designs. The simulations are based on the discrete element method (DEM), with friction and elastic deformations taken into account. One of the actuators is shown to generate forces proportional to its volume. This property seems necessary for building modular structures of useful strength and dimensions.

modular robots, self-reconfiguration, programmable matter, actuators, mechanical strength

Understanding load transfer mechanisms from the surface of the skin to its deeper layers is crucial in gaining a fundamental insight into damage phenomena related to skin tears, blisters and superficial/deep tissue ulcers. It is unknown how shear stresses in the viable epidermis are conditioned by the skin surface topography and internal microstructure and to which extent their propagation is conditioned by the size of a contacting asperities. In this computational study, these questions were addressed by conducting a series of contact finite element analyses simulating normal indentation of an anatomically-based two-dimensional multi-layer model of the skin by rigid indenters of various sizes and sliding of these indenters over the skin surface. Indentation depths, local (i.e. microscopic) coefficients of friction and Young's modulus of the stratum corneum were also varied. For comparison purpose and for isolating effects arising purely from the skin microstructure, a geometrically-idealised equivalent multi-layer model of the skin was also considered. The multi-asperity contact induced by the skin topographic features in combination with a non-idealised geometry of the skin layers lead to levels of shear stresses much higher than those produced in the geometrically-idealised case. These effects are also modulated by other system parameters (e.g. local coefficient of friction, indenter radius). These findings have major implications for the design and analyses of finite element studies aiming at modelling the tribology of skin, particularly if the focus is on how surface shear stress leads to damage initiation which is a process known to occur across several length scales.

Skin, Microstructure, Contact mechanics, Indentation, Sliding contact, Finite element, Image-based modelling, Material properties

Soft elastohydrodynamic lubrication regime is typical for many elastomeric and biological contacts. As one or both contacting bodies are then highly compliant, relatively low contact pressures may lead to large deformations which are neglected in the classical EHL theory. In the paper, the related finite-deformation effects are studied for two representative soft-EHL problems. To this end, a fully-coupled nonlinear formulation has been developed which combines finite-strain elasticity for the solid and the Reynolds equation for the fluid, both treated using the finite element method with full account of all elastohydrodynamic couplings. Results of friction measurements are also reported and compared to theoretical predictions for lubricated contact of a rubber ball sliding against a steel disc under high loads.

Soft-EHL problem, Finite deformation, Finite element method, Monolithic scheme

Computational contact homogenization approach is applied to study friction anisotropy resulting from asperity interaction in elastic contacts. Contact of rough surfaces with anisotropic roughness is considered with asperity contact at the micro scale being governed by the isotropic Coulomb friction model. Application of a micro-to-macro scale transition scheme yields a macroscopic friction model with orientation- and pressure-dependent macroscopic friction coefficient. The macroscopic slip rule is found to exhibit a weak non-associativity in the tangential plane, although the slip rule at the microscale is associated in the tangential plane. Counterintuitive effects are observed for compressible materials, in particular, for auxetic materials.

Contact, Friction, Anisotropy, Roughness, Micromechanics

A mixed formulation of the mass-conserving cavitation model is developed. The cavitation problem is formulated in terms of the hydrodynamic pressure and a complementary variable representing the void fraction in the cavitation zone. Weak form of the mass-balance equation is consistently derived, and it exhibits subtle differences with respect to the available formulations. Finite element treatment preserves the two-field formulation, and a semi-smooth Newton method is applied to solve the resulting discretized equations. A monolithic Newton-based scheme is also applied to solve the fully coupled elastohydrodynamic lubrication problem in the soft-EHL regime. Numerical examples illustrate the performance of the computational scheme.

Lubrication, Cavitation, Reynolds equation, Soft-EHL problem

A computationally efficient model of evolution of contact and wear is developed for a general periodic pin-on-flat problem with the focus on the pin-on-disc configuration and Archard wear model. The evolving contact state is assumed to be fully controlled by the wear process except during a short initial transient period controlled by both wear and elasticity. The contact pressure distribution is thus obtained by considering only the local wear model and the geometry of the conforming contact, without referring to the underlying elasticity problem. Evolution of the contact state is then obtained by time integration of the resulting rate-problem, and two computational schemes are developed for that purpose employing either the forward- or the backward-Euler method. The model is successfully verified against a three-dimensional finite element model. A dimensionless wear-mode index specifying the relative magnitude of wear coefficients of the contact pair is introduced, and model predictions are presented as a function of this parameter.

Contact mechanics, Wear, Simulation, Quasi-steady-state process, Rigid-wear model, Pin-on-disc

A finite deformation contact problem with friction and wear is studied in which the shape changes due to wear are finite. Accordingly, in addition to the initial configuration and the current configuration, an intermediate time-dependent configuration is introduced that corresponds to the undeformed body of the shape changed due to wear. Two time scales are also introduced in order to distinguish the fast time of the actual deformation (contact) problem from the slow time of the wear process (shape evolution problem). Separation of these time scales allows us to partially decouple the deformation problem and the shape evolution problem. Shape parameterization is introduced and the corresponding shape update scheme is formulated as a minimization problem. In particular, a second-order scheme is developed which exploits shape sensitivities of the deformation problem. Numerical examples are provided to illustrate the performance and accuracy of the proposed numerical schemes.

Frictional contact, Wear, Sensitivity analysis

The aim of this paper is to present a general method for automation of finite element formulations of large deformation contact problems. A new automatic-differentiation-based notation is introduced that represents a bridge between the classical mathematical notation of contact mechanics and the actual computer implementation of contact finite elements. Automation of derivation of the required formulas (e.g. element residual and tangent matrix) combined with automatic code generation makes the finite element implementation possible at a moderate effort. Accordingly, several 3D contact formulations have been implemented in this work, including penalty and augmented Lagrangian treatments of contact constraints, and several contact smoothing techniques. A typical benchmark problem could thus be executed in an objective way leading to a comprehensive study of the efficiency and the accuracy of various formulations of 3D contact finite elements.

automatic differentiation, symbolic methods, automation, frictional contact, contact smoothing, augmented Lagrangian method

The purpose of this report was to construct some alternative methods to estimate the effectiveness of investments in scientific research and development of advanced technologies, especially their long-term effects. Study Group decided to focus on the sub-problem of finding the relation between the spending on science and the quality of science itself. As a result, we have developed two independent methodologies. The most promising one is based on the theory of time-delay systems, which allows capturing effects of the time-lag between the use of funds and the results related to scientific work. Moreover, the methodology gives an opportunity to see kthe optimal spending scenario that would fulfill some prescribed constraints (e.g. it would minimize costs and at the same time remain above a desired level of quality of science). The second methodology is premised on Stochastic Frontier Analysis and it can be applied to determine the form of relation between the amount of financing and the results of scientific work. It offers considerable advantages for analyses of several forms of relation at once (production functions) and for a suitable choice of the best one. Both methods are promising, however, additional work is necessary to apply them successfully to some real-life problems

Direct differentiation method of sensitivity analysis is developed for frictional contact problems. As a result of the augmented Lagrangian treatment of contact constraints, the direct problem is solved simultaneously for the displacements and Lagrange multipliers using the Newton method. The main purpose of the paper is to show that this formulation of the augmented Lagrangian method is particularly suitable for sensitivity analysis because the direct differentiation method leads to a non-iterative exact sensitivity problem to be solved at each time increment. The approach is applied to a general class of three-dimensional frictional contact problems, and numerical examples are provided involving large deformations, multibody contact interactions, and contact smoothing techniques.

Sensitivity analysis, Direct differentiation method, Frictional contact, Augmented Lagrangian method

Large-scale 3D autonomous self-reconfigurable modular robots are made of numerous interconnected robotic modules that operate in a close packing. The modules are assumed to have their own CPU and memory, and are only able to communicate with their direct neighbors. As such, the robots embody a special computing architecture: a distributed memory and distributed CPU system with a local messagepassing interface. The modules can move and rearrange themselves changing the robot's connection topology. This may potentially cause mechanical failures (e.g., overloading of some inter-modular connections), which are irreversible and need to be detected in advance. In the present contribution, we further develop the idea of performing model-based detection of mechanical failures, posed in the form of balance equations solved by the modular robot itself in a distributed manner. A special implementation of the Conjugate Gradient iterative solution method is proposed and shown to greatly reduce the required number of iterations compared with the weighted Jacobi method used previously. The algorithm is verified in a virtual test bed—the VisibleSim emulator of the modular robot. The assessments of time-, CPU-, communication- and memory complexities of the proposed scheme are provided.

We discuss selected mechanical aspects of self-reconfiguration of densely-packed modular robots. The change of connection topology and transport of modules are fundamental mechanisms for these systems, which determine their desired emergent behavior, e.g., movement, shape change or interaction with their surroundings. At the same time, reconfiguration affects the forces between modules. We present a distributed procedure by which a robot can predict if the next planned reconfiguration step will overstress intermodular connections. We use a Finite Element model of a modular robot, with one-node-per-module discretization and beam elements representing intermodular connections. The analysis is restricted to static loads and linear elasticity. We present a distributed procedure of aggregation of the stiffness matrix and iterative solution of the resulting equations of elasticity. The procedure is illustrated with numerical examples and analyzed in terms of its efficiency. © 2017 IEEE.

Finite element method, Modular robots, Stiffness matrix, Distributed computations, Iterative solutions, Reconfiguration planning

Module localization is an important aspect of the operation of self-reconfigurable robots. The knowledge of spatial positions of modules, or at least of the overall shape which the modules form, is the usual prerequisite for reconfiguration planning. We present a general, decentralized algorithm for determining the positions of modules placed on a cubic grid from local sensor information. The connection topology of the robot is arbitrary. We assume that a module can sense the presence of its immediate neighbors on the grid and determine their positions in its own local coordinate system, but cannot sense the orientations of the coordinate systems of its neighbors. Since orientation cannot be directly communicated between modules, the modules can only exchange information about the relative positions of their neighbors. The algorithm aggregates this information over the entire network of modules and narrows down the set of valid positions for each module as far as possible. If there exists a unique locally-consistent assignment of coordinates to all modules then it is found.

A collective actuator is a self-reconfigurable modular-robotic structure which produces useful mechanical work through simultaneous reconfiguration of its constituent units. An actuator is additionally called scalable if its force-to-weight ratio does not depend on the number of its member modules. In this work, we consider scalable collective actuators built from spherical catoms with two connection types: strong but fixed and weak but mobile. We investigate how to construct these actuators in such a way, as to maximize their force-to-weight ratio. We present a number of designs of high strength, whose force capacities significantly exceed those of similar actuators reported previously.

The term Programmable Matter (PM) describes the class of future meta-materials of programmable and controllable properties and behavior, e.g., able to autonomously transform into an arbitrary shape. The robotic approaches towards PM are based on the concept of cooperation of millions of micro-robots (modules), acting at a very fine length-scale and collectively imitating deformation of a macroscopically continuous material. Recent ideas about reconfiguration of a collective of modules to obtain a desired overall mechanical response are promising. However, they are limited by the strength of individual connections between modules. In the present work, we propose a way of arranging spherical modules into microstructures, in which some connections are fixed and mechanically stronger, and the rest are active (reconfigurable) but weaker. If the fixed connections are sufficiently strong, the proposed microstructures perform the function of collective actuation by exerting forces proportional to their volumes. Two variants of a linear-actuator microstructure are presented and studied in more detail. A rotary-actuator microstructure is also introduced.

Summary We present a computational scheme for predicting whether addition of new modules to an existing modular robotic structure will mechanically overload the system, causing it to break or lose stability. The algorithm is executed by the modular robot itself in a distributed way, and relies on the iterative solution of mechanical equilibrium equations derived from a simple Finite Element model of the robot. In the model, inter-modular connections are represented as beams and the contact between modules and external supports is accounted for by a predictor-corrector scheme. The algorithm is verified through simulations in the Programmable Matter simulator VisibleSim and real-life experiments on the modular robotic system Blinky Blocks.

We examine, analytically and numerically, forces produced by collective actuators–possible future building blocks of Programmable Matter. The actuators are composed of tiny spherical robotic modules which can strongly attach to their neighbors, and move by rolling over one another using electric or magnetic local propulsion mechanisms. An actuator works through collective reconfiguration–a coordinated motion of its constituent modules–which results in a global deformation of the structure. The simulations are performed using specially adapted discrete element method software, and account for friction and elastic deformations of modules.

programmable matter, active materials, actuators, mechanical strength, modular robots