Nitin Daphalapurkar

Indirect traumatic optic neuropathy

Indirect traumatic optic neuropathy (ITON) refers to optic nerve injury resulting from impact remote to the optic nerve. The mechanism of injury is not understood, and there are no confirmed protocols for prevention, mitigation or treatment. Most data concerning this condition comes from case series of civilian patients suffering blunt injury, such as from sports- or motor vehicle-related concussion, rather than military-related ballistic or blast damage. Research in this field will likely require the development of robust databases to identify patients with ITON and follow related outcomes, in addition to both in-vivo animal and virtual human models to study the mechanisms of damage and potential therapies.

The importance of structural anisotropy in computational models of traumatic brain injury

Understanding the mechanisms of injury might prove useful in assisting the development of methods for the management and mitigation of traumatic brain injury (TBI). Computational head models can provide valuable insight into the multi-length-scale complexity associated with the primary nature of diffuse axonal injury. It involves understanding how the trauma to the head (at the centimeter length scale) translates to the white-matter tissue (at the millimeter length scale), and even further down to the axonal-length scale, where physical injury to axons (e.g., axon separation) may occur. However, to accurately represent the development of TBI, the biofidelity of these computational models is of utmost importance. There has been a focused effort to improve the biofidelity of computational models by including more sophisticated material definitions and implementing physiologically relevant measures of injury. This paper summarizes recent computational studies that have incorporated structural anisotropy in both the material definition of the white matter and the injury criterion as a means to improve the predictive capabilities of computational models for TBI. We discuss the role of structural anisotropy on both the mechanical response of the brain tissue and on the development of injury. We also outline future directions in the computational modeling of TBI.

Data integration for materials research

IntroductionA new data science initiative in materials research has been launched at The Johns Hopkins University within the Materials in Extreme Dynamic Environments (MEDE) Collaborative Research Alliance (CRA). Our first goal is to build a solution that facilitates seamless data sharing among MEDE scientists. We expect to shorten the design and development cycle of new materials by providing integrated storage, database, and analysis services, building on proven components of the SciServer project developed at the Institute for Data Intensive Engineering and Science (IDIES).Case descriptionHere we present our system design and demonstrate the power of our approach through a use-case that enables easy comparison of simulations and measurements. This prototype effort, focusing on boron carbide (BC), brings together multiple materials research elements in the Ceramics group within the MEDE CRA.Discussion and evaluationThe SciServer platform offers single-sign on access to various general purpose data analysis tools familiar to materials scientists in MEDE. During the case study deployment, users appreciated the simple data file upload process, automated database ingestion, and platform applicability to both students of the art and power users.ConclusionsFrom our case study experience in aggregating data from both simulations and physical experiments, we developed a template workflow from which a user may run a common data comparison task outright or customize to another purpose. Next, we turn to acquiring data from more MEDE groups and expanding the user base to the Metals group.

Modeling dynamic fragmentation of concrete under high strain-rate loading

Extreme high-rate loading conditions in structural materials trigger a complex process of fragmentation involving probabilistic, energetic and mechanical aspects. In this work we discuss a one-dimensional model based on [1] that captures the physics of dynamic fracture and fragmentation in concrete at strain rates from 103 to 105 /s, with particular interest in the higher strain rate values. In particular, the model considers a one-dimensional bar under a uniform tensile initial strain rate, with a stochastically varying strength. Initial results for the relationship between average fragment size and strain rate show good agreement with shock tube experiments on concrete panels. However, the predicted distribution of fragment size exhibits a smaller variance than that observed in the experiments. Future work will evaluate this difference in the results, which could be the result of the one-dimensionality of the model, heterogeneity of strain rate in the shock tube tests, experimental measurement errors, or a combination of all of these. Further investigations to extend the present model to other brittle materials like glass and concrete are also currently under development.

Designer materials for a secure future

Materials for armor applications are increasingly being required to be strong and light-weight as a consequence of increasing threat levels. We focus on materials response subjected to impact loads, understanding deformation and failure mechanisms, and developing validated mechanism-based models capable of predicting materials response under high rate loading conditions. As a specific example, we will examine the dynamic behavior of nanocrystalline aluminum using atomistic simulations. The dynamic behavior of this material is discussed in terms of competing deformation mechanisms--slip and twinning. Insights from high strain rate atomistic simulations were used in developing a fundamental mechanism-based analytical model to assist in the microstructural design of advanced materials to tailor their macroscopic properties.