The design of structural and functional materials for specialized applications is experiencing significant growth fueled by rapid advancements in materials synthesis, characterization, and manufacturing, as well as by sophisticated computational materials modeling frameworks that span a wide spectrum of length and time scales in the mesoscale between atomistic and homogenized continuum approaches. This is leading towards a systems-based design methodology that will replace traditional empirical approaches, embracing the principles of the Materials Genome Initiative. However, there are several gaps in this framework as it relates to advanced structural materials development: (1) limited availability and access to high-fidelity experimental and computational datasets, (2) lack of co-design of experiments and simulation aimed at computational model validation, (3) lack of on-demand access to verified and validated codes for simulation and for experimental analyses, and (4) limited opportunities for workforce training and educational outreach. These shortcomings stifle major innovations in structural materials design. This paper describes plans for a community-driven research initiative that addresses current gaps based on best-practice recommendations of leaders in mesoscale modeling, experimentation, and cyberinfrastructure obtained at an NSF-sponsored workshop dedicated to this topic and subsequent discussions. The proposal is to create a hub for "Mesoscale Experimentation and Simulation co-Operation (h-MESO)---that will (I) provide curation and sharing of models, data, and codes, (II) foster co-design of experiments for model validation with systematic uncertainty quantification, and (III) provide a platform for education and workforce development. h-MESO will engage experimental and computational experts in mesoscale mechanics and plasticity, along with mathematicians and computer scientists with expertise in algorithms, data science, machine learning, and large-scale cyberinfrastructure initiatives. 
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                            Multiscale Modeling in Neuroethology: The Significance of the Mesoscale
                        
                    
    
            Recent accounts of multiscale modeling investigate ontic and epistemic constraints imposed by relations between component models at varying relative scales (macro, meso, micro). These accounts often focus especially on the role of the meso, or intermediate, relative scale in a multiscale model. We aid this effort by highlighting a novel role for mesoscale models: functioning as a focal point, and explanation, for disagreement between researchers who otherwise share theoretical commitments. We present a case study in multiscale modeling of insect behavior to illustrate, arguing that the cognitive map debate in neuroethology research is best understood as a mesoscale disagreement. 
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                            - Award ID(s):
- 2132038
- PAR ID:
- 10514610
- Publisher / Repository:
- Cambridge University Press
- Date Published:
- Journal Name:
- Philosophy of Science
- Volume:
- 90
- Issue:
- 5
- ISSN:
- 0031-8248
- Page Range / eLocation ID:
- 1374 to 1384
- Subject(s) / Keyword(s):
- Philosophy of Science Multiscale Modeling Neuroethology Mesoscale
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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