Evolutionary Inverse Material Identification: Bespoke Characterization of Soft Materials Using a Metaheuristic Algorithm

The growing interest in soft robotics has resulted in an increased demand for accurate and reliable material modelling. As soft robots experience high deformations, highly nonlinear behavior is possible. Several analytical models that are able to capture this nonlinear behavior have been proposed, however, accurately calibrating them for specific materials and applications can be challenging. Multiple experimental testbeds may be required for material characterization which can be expensive and cumbersome. In this work, we propose an alternative framework for parameter fitting established hyperelastic material models, with the aim of improving their utility in the modelling of soft continuum robots. We define a minimization problem to reduce fitting errors between a soft continuum robot deformed experimentally and its equivalent finite element simulation. The soft material is characterized using four commonly employed hyperelastic material models (Neo Hookean; Mooney–Rivlin; Yeoh; and Ogden). To meet the complexity of the defined problem, we use an evolutionary algorithm to navigate the search space and determine optimal parameters for a selected material model and a specific actuation method, naming this approach as Evolutionary Inverse Material Identification (EIMI). We test the proposed approach with a magnetically actuated soft robot by characterizing two polymers often employed in the field: Dragon Skin™ 10 MEDIUM and Ecoflex™ 00-50. To determine the goodness of the FEM simulation for a specific set of model parameters, we define a function that measures the distance between the mesh of the FEM simulation and the experimental data. Our characterization framework showed an improvement greater than 6% compared to conventional model fitting approaches at different strain ranges based on the benchmark defined. Furthermore, the low variability across the different models obtained using our approach demonstrates reduced dependence on model and strain-range selection, making it well suited to application-specific soft robot modelling.

Mapping Blue and Red Color-Coated Steel Sheet Roof Buildings over China Using Sentinel-2A/B MSIL2A Images

Accurate and efficiently updated information on color-coated steel sheet (CCSS) roof materials in urban areas is of great significance for understanding the potential impact, challenges, and issues of these materials on urban sustainable development, human health, and the environment. Thanks to the development of Earth observation technologies, remote sensing (RS) provides abundant data to identify and map CCSS materials with different colors in urban areas. However, existing studies are still quite challenging with regards to the data collection and processing costs, particularly in wide geographical areas. Combining free access high-resolution RS data and a cloud computing platform, i.e., Sentinel-2A/B data sets and Google Earth Engine (GEE), this study aims at CCSS material identification and mapping. Specifically, six novel spectral indexes that use Sentinel-2A/B MSIL2A data are proposed for blue and red CCSS material identification, namely the normalized difference blue building index (NDBBI), the normalized difference red building index NDRBI, the enhanced blue building index (EBBI), the enhanced red building index (ERBI), the logical blue building index (LBBI) and the logical red building index (LRBI). These indexes are qualitatively and quantitatively evaluated on a very large number of urban sites all over the P.R. China and compared with the state-of-the-art redness and blueness indexes (RI and BI, respectively). The results demonstrate that the proposed indexes, specifically the LRBI and LBBI, are highly effective in visual evaluation, clearly detecting and discriminating blue and red CCSS covers from other urban materials. Results show that urban areas from the northern parts of P.R. China have larger proportions of blue and red CCSS materials, and areas of blue and red CCSS material buildings are positively correlated with population and urban size at the provincial level across China.

A review of the genus Scrobipalpa Janse, 1951 (Lepidoptera, Gelechiidae) in the Afrotropical region

The genus Scrobipalpa in the Afrotropical region is revised. Thirty-six species are recognized as valid, 20 of which are described as new: S. ochroxantha sp. nov. (South Africa), S. wieseri sp. nov. (Namibia, South Africa), S. turiensis sp. nov. (Kenya), S. wolframi sp. nov. (Namibia), S. natalensis sp. nov. (South Africa), S. varivansoni sp. nov. (South Africa), S. typica sp. nov. (South Africa), S. staudei sp. nov. (South Africa), S. afromontana sp. nov. (Kenya), S. erexita sp. nov. (South Africa), S. admirabilis sp. nov. (Namibia), S. griseata sp. nov. (South Africa), S. nigristriana sp. nov. (Kenya), S. munita sp. nov. (Malawi), S. ochracea sp. nov. (South Africa), S. asantesana sp. nov. (South Africa), S. selectoides sp. nov. (Namibia, RSA), S. etoshensis sp. nov. (Namibia), S. ethiopica sp. nov. (Ethiopia), and S. agassizi sp. nov. (Kenya). Six new synonyms are established: Phthorimaea blapsigona Meyrick, 1916 and Scrobipalpa asiri Povolný, 1980 syn. nov. of Scrobipalpa concreta (Meyrick, 1914); Scrobipalpa xylochroa Janse, 1963 and S. obsoletella hospes Povolný, 1964 syn. nov. of S. obsoletella (Fischer von Röslerstamm, 1841); S. vicaria (Meyrick, 1921) syn. nov. of S. geomicta (Meyrick, 1918); and Gelechia chersophila Meyrick, 1918 syn. nov. of S. portosanctana (Stainton, 1859). The following new combinations for five species previously placed in Scrobipalpa are proposed: Ephysteris cretigena (Meyrick, 1914) comb. nov., Microlechia colasta (Meyrick, 1921) comb. nov., Schizovalva costimacula (Janse, 1951) comb. nov., Gelechia trychnophylla (Janse, 1960) comb. nov. and Trychnopalpa phalacrodes (Meyrick, 1913) comb. nov. Two species, Phthorimaea pendens Meyrick, 1918 comb. rev. and Homaloxestis ocyphanes Meyrick, 1937 comb. rev., are excluded from Scrobipalpa but no current genus is available. The male genitalia of Scrobipalpa nomias (Meyrick, 1921) are described for the first time. All species are diagnosed, some of them are redescribed based on additional material. Identification keys and photographs of adults and genitalia are provided. New or additional host plants are recorded for Scrobipalpa incola (Meyrick, 1912), S. concreta, S. portosanctana, and S. ergasima (Meyrick, 1916). Scrobipalpa incola is recorded for the first time from Namibia, Tanzania, and Kenya; S. concreta is new for Ethiopia, Sudan, Tanzania, Kenya, Mozambique, Benin and Mauritius; S. subroseata for Tanzania and Kenya; S. aptatella (Walker, 1864) and S. biljurshi Povolný, 1980 for Ethiopia; S. obsoletella and S. traganella (Chrétien, 1915) for Namibia; S. geomicta for India and Ethiopia; and S. ergasima for Benin, Zimbabwe, Tanzania, Ethiopia, and Yemen.

Analysis of Inverse Methods in Empirical Structural Mechanics

The application of inverse methods in empirical structural mechanics is the subject of this study. After a broad introduction to Inverse Problems (IPs), which includes a discussion of the many domains of application in general structural mechanics, the focus is limited to the critical area of material identification, with a special focus on the use of complete surveys. In this example, a more detailed explanation of the IPs to solve is provided, as well as the primary approaches to solving it. Lastly, there are several illustrations of exploratory uses of such techniques.