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The appropriate and efficient design of structural components made with ultra-high-performance concrete (UHPC) requires the establishment of key design properties and material models that engage UHPC's distinct mechanical properties, as compared to conventional concrete. This paper presents the results of an extensive program of compression and tension property assessment executed according to existing testing methods to assess the mechanical characteristics of several commercially available UHPC products. The experimental results are then used to propose suitable mechanical models and design parameters that are foundational for the structural-level application of UHPC. The models rely on a set of experimentally identified mechanical performance properties that distinguish UHPC from conventional concrete and establish the basis of the material qualification for use in structural design. As such, this work constitutes a fundamental step in ongoing efforts to develop UHPC structural design guidance in the United States. Keywords: compression properties; mechanical models; structural design parameters; tension properties; ultra-high-performance concrete (UHPC).

Soundness of additively manufactured parts depends on a lot of process and geometrical parameters. A wrong process design leads to defects such as lack of fusion or keyhole porosity that have a detrimental effect on the mechanical properties of the printed parts. Process parameter optimization is thus a formidable challenge that requires in general a huge amount of experimental data. Among the others, heat source power and scan speed are the most defects-affecting parameters to be optimized. The energy density is used in literature to quantify their combination. Unfortunately, in different works it was demonstrated that it fails if used as design parameter mainly because it does not take into account the material properties and the interaction between heat source and the powder bed. In this contribution, a modified volumetric energy density equation that takes into account the powder-heat source interaction to optimize the combination of power-scan speed values for porosity assessment in powder bed fusion process design is proposed and verified on both AlSi10Mg alloy and Maraging steel 300.

Selective laser melting (SLM) additive manufacturing of pure tungsten encounters nearly all intractable difficulties of SLM metals fields due to its intrinsic properties. The key factors, including powder characteristics, layer thickness, and laser parameters of SLM high density tungsten are elucidated and discussed in detail. The main parameters were designed from theoretical calculations prior to the SLM process and experimentally optimized. Pure tungsten products with a density of 19.01 g/cm 3 (98.50% theoretical density) were produced using SLM with the optimized processing parameters. A high density microstructure is formed without significant balling or macrocracks. The formation mechanisms for pores and the densification behaviors are systematically elucidated. Electron backscattered diffraction analysis confirms that the columnar grains stretch across several layers and parallel to the maximum temperature gradient, which can ensure good bonding between the layers. The mechanical properties of the SLM-produced tungsten are comparable to that produced by the conventional fabrication methods, with hardness values exceeding 460 HV 0.05 and an ultimate compressive strength of about 1 GPa. This finding offers new potential applications of refractory metals in additive manufacturing.

This paper presents a literature survey documenting the evolution of continuum robots over the past two decades (1999–present). Attention is paid to bioinspired soft robots with respect to the following three design parameters: structure, materials, and actuation. Using this three-faced prism, we identify the uniqueness and novelty of robots that have hitherto not been publicly disclosed. The motivation for this study comes from the fact that continuum soft robots can make inroads in industrial manufacturing, and their adoption will be accelerated if their key advantages over counterparts with rigid links are clear. Four different taxonomies of continuum robots are included in this study, enabling researchers to quickly identify robots of relevance to their studies. The kinematics and dynamics of these robots are not covered, nor is their application in surgical manipulation.

NASA's Global Ecosystem Dynamics Investigation (GEDI) mission will collect waveform lidar data at a dense sample of ∼25 m footprints along ground tracks paralleling the orbit of the International Space Station (ISS). GEDI's primary science deliverable will be a 1 km grid of estimated mean aboveground biomass density (Mg ha−1), covering the latitudes overflown by ISS (51.6 °S to 51.6 °N). One option for using the sample of waveforms contained within an individual grid cell to produce an estimate for that cell is hybrid inference, which explicitly incorporates both sampling design and model parameter covariance into estimates of variance around the population mean. We explored statistical properties of hybrid estimators applied in the context of GEDI, using simulations calibrated with lidar and field data from six diverse sites across the United States. We found hybrid estimators of mean biomass to be unbiased and the corresponding estimators of variance appeared to be asymptotically unbiased, with under-estimation of variance by approximately 20% when data from only two clusters (footprint tracks) were available. In our study areas, sampling error contributed more to overall estimates of variance than variability due to the model, and it was the design-based component of the variance that was the source of the variance estimator bias at small sample sizes. These results highlight the importance of maximizing GEDI's sample size in making precise biomass estimates. Given a set of assumptions discussed here, hybrid inference provides a viable framework for estimating biomass at the scale of a 1 km grid cell while formally accounting for both variability due to the model and sampling error.

This paper presents a risk-aware path planning strategy for Unmanned Aerial Vehicles in urban environments. The aim is to compute an effective path that minimizes the risk to the population, thus enforcing safety of flight operations over inhabited areas. To quantify the risk, the proposed approach uses a risk-map that associates discretized locations of the space with a suitable risk-cost. Path planning is performed in two phases: first, a tentative path is computed off-line on the basis on the information related to static risk factors; then, using a dynamic risk-map, an on-line path planning adjusts and adapts the off-line path to dynamically arising conditions. Off-line path planning is performed using riskA*, an ad-hoc variant of the A* algorithm, which aims at minimizing the risk. While off-line path planning has no stringent time constraints for its execution, this is not the case for the on-line phase, where a fast response constitutes a critical design parameter. We propose a novel algorithm called Borderland , which uses the check and repair approach to rapidly identify and adjust only the portion of path involved by the inception of relevant dynamical changes in the risk factor. After the path planning, a smoothing process is performed using Dubins curves. Simulation results confirm the suitability of the proposed approach.

Multiple free water surface flow constructed wetlands (multi-FWS CWs) are a variety of conventional water treatment plants for the interception of pollutants. This review encapsulated the characteristics and applications in the field of ecological non-point source water pollution control technology. The roles of in-series design and operation parameters (hydraulic residence time, hydraulic load rate, water depth and aspect ratio, composition of influent, and plant species) for performance intensification were also analyzed, which were crucial to achieve sustainable and effective contaminants removal, especially the retention of nutrient. The mechanism study of design and operation parameters for the removal of nitrogen and phosphorus was also highlighted. Conducive perspectives for further research on optimizing its design/operation parameters and advanced technologies of ecological restoration were illustrated to possibly interpret the functions of multi-FWS CWs.

Cartilage tissue equivalents formed from hydrogels containing chondrocytes could provide a solution for replacing damaged cartilage. Previous approaches have often utilized elastic hydrogels. However, elastic stresses may restrict cartilage matrix formation and alter the chondrocyte phenotype. Here we investigated the use of viscoelastic hydrogels, in which stresses are relaxed over time and which exhibit creep, for three-dimensional (3D) culture of chondrocytes. We found that faster relaxation promoted a striking increase in the volume of interconnected cartilage matrix formed by chondrocytes. In slower relaxing gels, restriction of cell volume expansion by elastic stresses led to increased secretion of IL-1β, which in turn drove strong up-regulation of genes associated with cartilage degradation and cell death. As no cell-adhesion ligands are presented by the hydrogels, these results reveal cell sensing of cell volume confinement as an adhesion-independent mechanism of mechanotransduction in 3D culture, and highlight stress relaxation as a key design parameter for cartilage tissue engineering. The mechanical properties of biomaterials affect cell growth through mechanotransduction signals. Here, hydrogels with fast stress relaxation were developed and showed increased cartilage matrix formation by cartilage cells compared to slow relaxation hydrogels.

3D printing is widely used for various applications as it offers many benefits. The mechanical property of the part manufactured by using 3D printing is very critical. For that reason, it is important to understand how different values of 3D printing process parameters impact the mechanical properties of the part. As Polylactic Acid (PLA) is most widely used as 3D printing material, it is chosen as the material discussed in this research. The purpose of this research is to provide information related to the influence of various parameters of 3D printing to the mechanical properties of the PLA part. A literature review was performed based on the current research that investigates the 3D printing process of PLA. Based on the literature review, the infill design parameters are considered as important parameters and discussed in this research. The infill design parameters referred in this research are layer thickness, infill pattern, infill density, infill width, and infill deposition speed. The mechanical properties discussed in this research are tensile strength and yield strength, ductility, elasticity or young modulus, compression strength, flexural strength, and stiffness.

A key advantage of additive manufacturing (AM) is that it allows the fabrication of lattice structures for customized biomedical implants with high performance. This paper presents the use of statistical approaches in design optimization of additively manufactured titanium lattice structures for biomedical implants. Design of experiments using response surface and analysis of variance was carried out to study the effect design parameters on the properties of the AM lattice structures such as ultimate compression strength, specific compressive strength, elastic modulus, and porosity. In addition, the lattice dimensions were optimized to fabricate a diamond cellular structure with properties that match human bones. The study found that the length of a diamond-shaped unit cell strut is the most significant design parameter. In particular, the porosity of the unit cell increases as the strut length increases, while it had a significant reverse effect on the specific compressive strength, elastic modulus, and ultimate compression strength. On the other hand, increasing the orientation angle was found to reduce both the specific compressive strength and modulus of elasticity of the lattice structure. An optimized lattice structure with strut diameter of 0.84 mm, length of 3.29 mm, and orientation angle of 47° was shown to have specific compressive strength, elastic modulus, ultimate compression strength, and porosity of 37.8 kN m/kg, 1 GPa, 49.5 MPa, and 85.7%, respectively. A cellular structure with the obtained properties could be effectively applied for trabecular bone replacement surgeries.