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Design optimization of metamaterials and other complex systems often relies on the use of computationally expensive models. This makes it challenging to use global multi-objective optimization approaches that require many function evaluations. Engineers often have heuristics or rules of thumb with potential to drastically reduce the number of function evaluations needed to achieve good convergence. Recent research has demonstrated that these design heuristics can be used explicitly in design optimization, indeed leading to accelerated convergence. However, these approaches have only been demonstrated on specific problems, the performance of different methods was diverse, and despite all heuristics being “correct”, some heuristics were found to perform much better than others for various problems. In this paper, we describe a case study in design heuristics for a simple class of 2D constrained multiobjective optimization problems involving lattice-based metamaterial design. Design heuristics are strategically incorporated into the design search and the heuristics-enabled optimization framework is compared with the standard optimization framework not using the heuristics. Results indicate that leveraging design heuristics for design optimization can help in reaching the optimal designs faster. We also identify some guidelines to help designers choose design heuristics and methods to incorporate them for a given problem at hand.

Lattice-based mechanical metamaterials can be tailored for a wide variety of applications by modifying the underlying mesostructure. However, most existing lattice patterns take symmetry as a starting point. We show that asymmetric lattice patterns can be more likely to have certain mechanical properties than symmetric lattice patterns. To directly compare the effects of asymmetric versus symmetric lattice arrangements, a constrained design space is defined. A generative design process is used to generate both symmetric and asymmetric lattice patterns within the design space. Asymmetric lattice patterns are shown to have distinct metamaterial property spaces from symmetric lattice patterns. Key design features are identified that are present predominantly in asymmetric lattice patterns. We show that asymmetric lattice patterns with two of these features (arrows and spider nodes) are more likely to induce a broader range of Poisson's ratios and larger shear stiffness values, respectively, compared to lattice patterns without these features. In addition, we show that symmetry can play a role in hampering the impact of multiple features when present. This work provides insights into the benefits of using asymmetric lattice patterns in select metamaterial design applications.

Recent work concerned with passive vibration suppression in structural systems has focused on the development of metastructures. Metastructures (also called architected materials) are a type of mechanical metamaterial: an object arranged or constructed in such a manner that it has traits unachievable by its constituent material. Metastructures often consist of embedded spring mass systems made from small beams with a tip mass or chiral lattice structures with mass inserts. The goal of a metastructures design is to reduce vibrations of the host structure. It does this using the absorber action of the embedded spring mass systems. The embedded tuned mass dampers (TMDs) then become prone to sustaining failure by fatigue. While many recent papers discuss various geometric and material designs, very few if any address the issues of fatigue of the embedded absorbers. This paper makes an initial investigation into the relationship between the TMDs’ geometric parameters and their fatigue performance with the goal of improving the design and implementation metastructures. A sensitivity analysis was performed to identify the geometric TMD parameter with the largest impact on natural frequency and stress concentration. Analytical models for natural frequency and maximum stress were developed for the TMDs and compared to finite element models. The analytical models were substantiated by the FEA models for some of the perturbed parameters, indicating that further work would be needed to confirm that, for a given parameter, a certain trend in natural frequency indicates an anticipatable trend in stress.

Cancer cells have been increasingly grown in pharmaceutical research to understand tumorigenesis and develop new therapeutic drugs. Currently, cells are typically grown using two-dimensional (2-D) cell culture approaches, where the native tumor microenvironment is difficult to recapitulate. Thus, one of the main obstacles in oncology is the lack of proper infection models that recount main features present in tumors. In recent years, microtechnology-based platforms have been employed to generate three-dimensional (3-D) models that better mimic the native microenvironment in cell culture. Here, we present an innovative approach to culture Kaposi’s sarcoma-associated herpesvirus (KSHV) infected human B cells in 3-D using a microwell array system. The results demonstrate that the KSHV-infected B cells can be grown up to 15 days in a 3-D culture. Compared with 2-D, cells grown in 3-D had increased numbers of KSHV latency-associated nuclear antigen (LANA) dots, as detected by immunofluorescence microscopy, indicating a higher viral genome copy number. Cells in 3-D also demonstrated a higher rate of lytic reactivation. The 3-D microwell array system has the potential to improve 3-D cell oncology models and allow for better-controlled studies for drug discovery.