Effective Stiffness of Fused Deposition Modeling Infill Lattice Patterns Made of PLA-Wood Material

Fused deposition modeling (FDM) uses lattice arrangements, known as infill, within the fabricated part. The mechanical properties of parts fabricated via FDM are dependent on these infill patterns, which make their study of great relevance. One of the advantages of FDM is the wide range of materials that can be employed using this technology. Among these, polylactic acid (PLA)-wood has been recently gaining attention as it has become commercially available. In this work, the stiffness of two different lattice structures fabricated from PLA-wood material using FDM are studied: hexagonal and star. Rectangular samples with four different infill densities made of PLA-wood material were fabricated via FDM. Samples were subjected to 3-point bending to characterize the effective stiffness and their sensitivity to shear deformation. Lattice beams proved to be more sensitive to shear deformations, as including the contribution of shear in the apparent stiffness of these arrangements leads to more accurate results. This was evaluated by comparing the effective Young’s modulus characterized from 3-point bending using equations with and without shear inclusion. A longer separation between supports yielded closer results between both models (~41% for the longest separation tested). The effective stiffness as a function of the infill density of both topologies showed similar trends. However, the maximum difference obtained at low densities was the hexagonal topology that was ~60% stiffer, while the lowest difference was obtained at higher densities (star topology being stiffer by ~20%). Results for stiffness of PLA-wood samples were scattered. This was attributed to the defects at the lattice element level inherent to the material employed in this study, confirmed via micro-characterization.

An X-Band CMOS Digital Phased Array Radar from Hardware to Software

Phased array technology features rapid and directional scanning and has become a promising approach for remote sensing and wireless communication. In addition, element-level digitization has increased the feasibility of complicated signal processing and simultaneous multi-beamforming processes. However, the high cost and bulky characteristics of beam-steering systems have prevented their extensive application. In this paper, an X-band element-level digital phased array radar utilizing fully integrated complementary metal-oxide-semiconductor (CMOS) transceivers is proposed for achieving a low-cost and compact-size digital beamforming system. An 8–10 GHz transceiver system-on-chip (SoC) fabricated in 65 nm CMOS technology offers baseband filtering, frequency translation, and global clock synchronization through the proposed periodic pulse injection technique. A 16-element subarray module with an SoC integration, antenna-in-package, and tile array configuration achieves digital beamforming, back-end computing, and dc–dc conversion with a size of 317 ×149 × 74.6 mm3. A radar demonstrator with scalable subarray modules simultaneously realizes range sensing and azimuth recognition for pulsed radar configurations. Captured by the suggested software-defined pulsed radar, a complete range–azimuth figure with a 1 km maximum observation range can be displayed within 150 ms under the current implementation.

General Consistency of Strong Discontinuity Kinematics in Embedded Finite Element Method (E-FEM) Formulations

This paper performs an in-depth study of the theoretical basis behind the strong discontinuity methods to improve local fracture simulations using the Embedded Finite Element Method (E-FEM). The process starts from a review of the elemental enhancement functions found in current E-FEM literature, providing the reader a solid context of E-FEM fundamentals. A set of theoretical pathologies is then discussed, which prevent current frameworks from attaining full kinematic consistency and introduce unintended mesh dependencies. Based on this analysis, a new proposal of strong discontinuity enhancement functions is presented considering generalised fracture kinematics in a full tridimensional setting and a more robust definition of internal auxiliary functions. Element-level simulations are performed to compare the outputs within a group of selected E-FEM approaches, including the novel proposal. Simulations show that the new element formulation grants a wider level of basic kinematic coherence between the local fracture outputs and element kinematics, demonstrating an increase in robustness that might drive the usefulness of E-FEM techniques for fracture simulations to a higher level.

Two-field formulations for isogeometric Reissner–Mindlin plates and shells with global and local condensation

In this paper, mixed formulations are presented in the framework of isogeometric Reissner–Mindlin plates and shells with the aim of alleviating membrane and shear locking. The formulations are based on the Hellinger-Reissner functional and use the stress resultants as additional unknowns, which have to be interpolated in appropriate approximation spaces. The additional unknowns can be eliminated by static condensation. In the framework of isogeometric analysis static condensation is performed globally on the patch level, which leads to a high computational cost. Thus, two additional local approaches to the existing continuous method are presented, an approach with discontinuous stress resultant fields at the element boundaries and a reconstructed approach which is blending the local control variables by using weights in order to compute the global ones. Both approaches allow for a static condensation on the element level instead of the patch level. Various numerical examples are investigated in order to verify the accuracy and effectiveness of the different approaches and a comparison to existing elements that include mechanisms against locking is carried out.

Element-Level Optimization Module for Bridge Planning and Programming

The overall objective of this research is to support state departments of transportation with their decision-making processes and transitions to performance management and performance-based planning and programming mandated by the Moving Ahead for Progress in the 21st Century Act. Accomplishing this objective requires a systematic multiobjective optimization methodology. This research proposes such a methodology, referred to as an “element-based multiobjective optimization” (EB-MOO) methodology, which produces optimal or near-optimal sets of short- and long-term intervention strategies detailed at the bridge element level for planning and programming. The methodology currently focuses on the bridge asset class and consists of five modules: (1) data processing, (2) improvement, (3) element-level optimization (ELO), (4) bridge-level optimization (BLO), and (5) network-level optimization (NLO) modules. This paper details the ELO module, specifically: the basic framework of underlying processes and concepts, the alternative feasibility screening process, optimization problem types and mathematical formulations, and the heuristic algorithm used to solve the ELO problems. The paper also includes an illustrative example using a prototyping tool developed to implement EB-MOO methodology. The example presents several ELO problems under unconstrained scenarios. The implementation demonstrated the module’s capability in producing optimal or near-optimal ELO solutions, recommending element intervention actions, predicting performance, and determining funding requirements for the specified improvement type and program year. The broader EB-MOO methodology uses the ELO results as inputs for the BLO and NLO modules.

Bridge-Level Optimization Module for Planning and Programming

The paper briefly introduces an element-based multi-objective optimization (EB-MOO) methodology to support state departments of transportation with their decision-making process, asset management, and performance-based transportation planning and programming. The methodology focuses on the bridge asset class and consists of five modules: (i) data processing, (ii) improvement, (iii) element-level optimization (ELO), (iv) bridge-level optimization (BLO), and (v) network-level optimization (NLO) modules. These five modules jointly produce short- and long-term intervention strategies detailed at the bridge element level for planning and programming. The paper focuses on the BLO module, specifically: the basic framework of underlying processes and concepts, the optimization problem types and mathematical formulations, and the heuristic algorithm to solve the BLO problems. A prototyping tool is developed to implement these five modules of the EB-MOO methodology, test concepts, prove effectiveness, and demonstrate potential benefits. The paper also includes an illustrative example using the prototyping tool. The example consists of the BLO problems under different budget and/or performance scenarios. The implementation proves the module’s capability in producing a diverse set of Pareto optimal or near-optimal solutions, recommending set of element intervention actions and timings, predicting performance, and determining budget requirements for the entire program period. The BLO results associated with the recommended solutions serve as the fundamental inputs for the NLO module. Nevertheless, the BLO module can be used independently, providing a systematic process for the development of bridge improvement/preservation programs detailed at the element level.