Analyzing the 3D Printed Material Tango Plus FLX930 for Using in Self-Folding Structure

Self-folding is the ability of the structure to fold and/or unfold without human intervention or any application of external manipulation. It is known that the structure of folding object consists of two essential parts. These parts are the faces and the creases. In this paper, it is assumed that the faces could be built by using solid materials, and the crease lines can be built using soft material which provides a high bent ability. Furthermore, these two materials should be combined built without using any connections between them. Fortunately, the 3D printer provides this capability. It can print two types of different materials at the same time for the same structure. Therefore, a 3D printer is chosen to fabricate a folding structure using two types of material. These types are the Vero for solid faces and Tango plus FLX930 for the soft creases lines. The soft material at hinge part (creases lines) subjected to the load directly when the structure folds. It should have a clear view of the mechanical properties of this material. Therefore, several mechanical tests for Tango FLX930 material are operated to calculate its mechanical properties and find the force that required to fold it

Advances in the inspection of unpiggable pipelines

The field of in-pipe robotics covers a vast and varied number of approaches to the inspection of pipelines with robots specialising in pipes ranging anywhere from 10 mm to 1200 mm in diameter. Many of these developed systems focus on overcoming in-pipe obstacles such as T-sections and elbows, as a result important aspects of exploration are treated as sub-systems, namely shape adaptability. One of the most prevalent methods of hybridised locomotion today is wall-pressing; generating traction using the encompassing pipe walls. A review of wall-pressing systems has been performed, covering the different approaches taken since their introduction. The advantages and disadvantages of these systems is discussed as well as their effectiveness in the inspection of networks with highly varying pipe diameters. When compared to unconventional in-pipe robotic techniques, traditional full-bore wall-pressing robots were found to be at a disadvantage

Toward High Fidelity Materials Property Prediction from Multiscale Modeling and Simulation

The current approach to materials discovery and design remains dominated by experimental testing, frequently based on little more than trial and error. With the advent of ever more powerful computers, rapid, reliable, and reproducible computer simulations are beginning to represent a feasible alternative. As high performance computing reaches the exascale, exploiting the resources efficiently presents interesting challenges and opportunities. Multiscale modeling and simulation of materials are extremely promising candidates for exploiting these resources based on the assumption of a separation of scales in the architectures of nanomaterials. Examples of hierarchical and concurrent multiscale approaches are presented which benefit from the weak scaling of monolithic applications, thereby efficiently exploiting large scale computational resources. Several multiscale techniques, incorporating the electronic to the continuum scale, which can be applied to the efficient design of a range of nanocomposites, are discussed. Then the work on the development of a software toolkit designed to provide verification, validation, and uncertainty quantification to support actionable prediction from such calculations is discussed

Accelerating Heterogeneous Multiscale Simulations of Advanced Materials Properties with Graph-Based Clustering

Heterogeneous multiscale methods (HMM) capable of simulating asynchronously multiple scales concurrently are now tractable with the advent of exascale supercomputers. However, naive implementations display a large number of redundancies and are very costly. The macroscale model typically requires computations of a large number of very similar microscale simulations. In hierarchical methods, this is barely an issue as phenomenological constitutive models are inexpensive. However, when microscale simulations require, for example, high-dimensional molecular dynamics (MD) or finite element (FE) simulations, redundancy must be avoided. A clustering algorithm suited for HMM workflows is proposed that automatically sorts and eliminates redundant microscale simulations. The algorithm features a combination of splines to render a low-dimension representation of the parameter configurations of microscale simulations and a graph network representation based on their similarity. The algorithm enables the clustering of similar parameter configurations into a single one in order to reduce to a minimum the number of microscale simulations required. An implementation of the algorithm in the context of an HMM application coupling FE and MD to predict the chemically specific mechanical behavior of polymer-graphene nanocomposites. The algorithm furnishes a threefold reduction of the computational effort with limited loss of accuracy

Metamorphic tensegrity structure for pipe inspection

This paper proposes a new concept of metamorphic tensegrity structure for pipe inspection. A new structural deformation technique is developed that can be employed to design a non-complex and lightweight robot or vehicle. This concept is to deform the cross-shaped tensegrity structure by using the cooperation of prismatic actuators (PAs) and passive joints with locking mechanisms called restrictor mechanisms (RMs). Two control levels are designed to control the structural deformation: A high-level controller for motion patterns and low-level controllers to locally control the PA lengths and restrict the cable lengths of four RMs. Experiments show that the proposed deformation technique can deform the shape and size of the tensegrity structures with the aim of creating a new generation of pipe inspection robots

Emergence of structure in mouse embryos: Structural Entropy morphometry applied to digital models of embryonic anatomy

We apply an information-theoretic measure to anatomical models of the Edinburgh Mouse Atlas Project. Our goal is to quantify the anatomical complexity of the embryo and to understand how this quantity changes as the organism develops through time. Our measure, Structural Entropy, takes into account the geometrical character of the intermingling of tissue types in the embryo. It does this by a mathematical process that effectively imagines a point-like explorer that starts at an arbitrary place in the 3D structure of the embryo and takes a random path through the embryo, recording the sequence of tissues through which it passes. Consideration of a large number of such paths yields a probability distribution of paths making connections between specific tissue types, and Structural Entropy is calculated from this (mathematical details are given in the main text). We find that Structural Entropy generally decreases (order increases) almost linearly throughout developmental time (4–18 days). There is one `blip’ of increased Structural Entropy across days 7–8: this corresponds to gastrulation. Our results highlight the potential for mathematical techniques to provide insight into the development of anatomical structure, and also the need for further sources of accurate 3D anatomical data to support analyses of this kind

The Role of Graphene in Enhancing the Material Properties of Thermosetting Polymers

Graphene continues to attract considerable attention from the materials science community through its potential for improving the mechanical properties of polymer thermosets, yet there remains considerable uncertainty over the underlying mechanisms. The effect of introducing graphene sheets to a typical thermosetting polymer network on mechanical behaviour is explored here through concurrently coupling molecular dynamics with a finite element solver. In this multiscale approach, Graphene is observed to act in two ways: as passive microscopic defects, dispersing crack propagation (high deformation); and as active geometric constraints, impeding polymer conformational changes (low deformation). By contrast, single‐scale atomistic simulations alone predict little measurable difference in the properties of the graphene‐enhanced epoxy resins as compared with the pure polymer case. The multiscale model predicts that epoxy resins reinforced with graphene nanoparticles exhibit enhanced overall elastoplastic properties, reducing strain energy dissipation by up to 70%. Importantly, this is only observed when taking into account the complex boundary conditions, mainly involving shear, arising from coupling physics on length scales separated by five orders of magnitude. The approach herein clearly highlights a novel role of graphene nanoparticles in actively constraining the surrounding polymer matrix, impeding local dissipative mechanisms, and resisting shear deformation

Miniature Magnetic Robots For In-Pipe Locomotion

Inspection of both small and large diameter bore pipelines for pipe integrity and defect identification with a single system has previously been impractical; especially using wall-press locomotion methods with low adaptive range. A miniature magnetic wallclimbing robot has been developed as a robotic solution for the inspection of 50mm bore diameter pipelines which can scale in-pipe geometry obstacles to access larger connected pipelines. Using magnetic arrays directed through steel flux plates within the wheels, the robot uses magnetic forces to adhere to the pipe. The system is 3D printed and includes soft printed material rubber wheels. The robot prototype is wirelessly driven, controlled remotely through serial Bluetooth communication radio at 2.4 GHz rated up to 100m. The robot’s unique compact geometry and magnetic design allows it to scale concave rightangle wall cases in just a 50mm diameter bore. By entering pipe networks through these small existing access points the robot removes the need for expensive drilling procedures required to fit launch vessels

Fragments of the earliest land plants

The earliest fossil evidence for land plants comes from microscopic dispersed spores. These microfossils are abundant and widely distributed in sediments, and the earliest generally accepted reports are from rocks of mid-Ordovician age (Llanvirn, 475 million years ago). Although distribution, morphology and ultrastructure of the spores indicate that they are derived from terrestrial plants, possibly early relatives of the bryophytes, this interpretation remains controversial as there is little in the way of direct evidence for the parent plants. An additional complicating factor is that there is a significant hiatus between the appearance of the first dispersed spores and fossils of relatively complete land plants (megafossils): spores predate the earliest megafossils (Late Silurian, 425 million year ago) by some 50 million years. Here we report the description of spore-containing plant fragments from Ordovician rocks of Oman. These fossils provide direct evidence for the nature of the spore-producing plants. They confirm that the earliest spores developed in large numbers within sporangia, providing strong evidence that they are the fossilized remains of bona fide land plants. Furthermore, analysis of spore wall ultrastructure supports liverwort affinities

A powerful method for detecting differentially expressed genes from GeneChip arrays that does not require replicates

BACKGROUND: Studies of differential expression that use Affymetrix GeneChip arrays are often carried out with a limited number of replicates. Reasons for this include financial considerations and limits on the available amount of RNA for sample preparation. In addition, failed hybridizations are not uncommon leading to a further reduction in the number of replicates available for analysis. Most existing methods for studying differential expression rely on the availability of replicates and the demand for alternative methods that require few or no replicates is high. RESULTS: We describe a statistical procedure for performing differential expression analysis without replicates. The procedure relies on a Bayesian integrated approach (BGX) to the analysis of Affymetrix GeneChips. The BGX method estimates a posterior distribution of expression for each gene and condition, from a simultaneous consideration of the available probe intensities representing the gene in a condition. Importantly, posterior distributions of expression are obtained regardless of the number of replicates available. We exploit these posterior distributions to create ranked gene lists that take into account the estimated expression difference as well as its associated uncertainty. We estimate the proportion of non-differentially expressed genes empirically, allowing an informed choice of cut-off for the ranked gene list, adapting an approach proposed by Efron. We assess the performance of the method, and compare it to those of other methods, on publicly available spike-in data sets, as well as in a proper biological setting. CONCLUSION: The method presented is a powerful tool for extracting information on differential expression from GeneChip expression studies with limited or no replicates