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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Neuromorphic Computing is Turing-Complete

Neuromorphic computing is a non-von Neumann computing paradigm that performs computation by emulating the human brain. Neuromorphic systems are extremely energy-efficient and known to consume thousands of times less power than CPUs and GPUs. They have the potential to drive critical use cases such as autonomous vehicles, edge computing and internet of things in the future. For this reason, they are sought to be an indispensable part of the future computing landscape. Neuromorphic systems are mainly used for spike-based machine learning applications, although there are some non-machine learning applications in graph theory, differential equations, and spike-based simulations. These applications suggest that neuromorphic computing might be capable of general-purpose computing. However, general-purpose computability of neuromorphic computing has not been established yet. In this work, we prove that neuromorphic computing is Turing-complete and therefore capable of general-purpose computing. Specifically, we present a model of neuromorphic computing, with just two neuron parameters (threshold and leak), and two synaptic parameters (weight and delay). We devise neuromorphic circuits for computing all the μ-recursive functions (i.e., constant, successor and projection functions) and all the μ-recursive operators (i.e., composition, primitive recursion and minimization operators). Given that the μ-recursive functions and operators are precisely the ones that can be computed using a Turing machine, this work establishes the Turing-completeness of neuromorphic computing.

Date, Prasanna↗
NASA NTRS2018

The Twisted Configuration of the Martian Magnetotail: MAVEN Observations

Measurements provided by the Mars Atmosphere and Volatile EvolutioN (MAVEN) spacecraft are analyzed to investigate the Martian magnetotail configuration as a function of interplanetary magnetic field (IMF) BY. We find that the magnetotail lobes exhibit a ~45deg twist, either clockwise or counterclockwise from the ecliptic plane, up to a few Mars radii downstream. Moreover, the associated cross-tail current sheet is rotated away from the expected location for a Venus-like induced magnetotail based on nominal IMF draping. Data-model comparisons using magnetohydrodynamic simulations are in good agreement with the observed tail twist. Model field line tracings indicate that a majority of the twisted tail lobes are composed of open field lines, surrounded by draped IMF. We infer that dayside magnetic reconnection between the crustal fields and draped IMF creates these open fields and may be responsible for the twisted tail configuration, similar to what is observed at Earth.

Martian↗
DOE OSTI2025

Applications of Nickelate perovskites for neuromorphic computing from electronic structure and Machine Learning

While the limit of Moore's law is presently being reached with current microelectronic technologies, we need to develop new paradigms that overcome this limitation. In that respect, neuromorphic computing is a concept that emulates the neural behavior and response of the human brain, and it has been recognized as a promising alternative approach. In this research project, we will perform multi-fidelity scale bridging to explore the potential use of materials with metal to insulator transition for neuromorphic applications. In particular, rare earth nickelates are promising for such purposes, as the transition in these materials is quite sensitive to a broad set of different external stimuli. Our multi-fidelity approach will bridge the high-fidelity electronic structure calculations with classical potentials. We will bridge dynamical mean field theory with a classical atomistic representation via a deep learning force field. The neural network is trained with energies, charges, and forces obtained by accurate electronic structure theories based on Dynamical Mean Field Theory. The configurational space is generated from known crystal phases, ab initio molecular dynamics with exchange-correlation functionals corrected with the Hubbard model, disordered phases with different concentrations of oxygen vacancies, and nonsymmetrical positions and induced strain by grain interfaces or contact with a substrate. Strategies to train the model with a reduced number of training examples are obtained from active learning methods, and new structures for improving the learning process are generated by using machine learning autoencoders. This classical potential will be validated through a diversity of electronic structure methods and represents an important step to combine the flexibility and accuracy of first-principles with the speed of classical potentials. The generated multi-fidelity surrogate model will be used to understand the role of strain, oxygen vacancies, proton doping, the variation of the crystal phase, substrate effects, vibrational effects as the octahedral rotation, grain boundaries and defect effects on the response of a Metal to Insulator Transition (MIT) in correlated materials. Long time and large-scale simulations will help understand the role of different stimuli to control the hysteresis of the MIT, as it has been experimentally suggested. Selected configurations will be analyzed with higher-level theories to provide an accurate electronic description and to study how the orbitals and charges are rearranged under different conditions.

36 MATERIALS SCIENCE↗
NASA NTRS2018

The Twisted Configuration of the Martian Magnetotail: MAVEN Observations

Measurements provided by the Mars Atmosphere and Volatile EvolutioN (MAVEN) spacecraft are analyzed to investigate the Martian magnetotail configuration as a function of interplanetary magnetic field (IMF) BY. We find that the magnetotail lobes exhibit a ~45° twist, either clockwise or counterclockwise from the ecliptic plane, up to a few Mars radii downstream. Moreover, the associated cross‐tail current sheet is rotated away from the expected location for a Venus‐like induced magnetotail based on nominal IMF draping. Data‐model comparisons using magnetohydrodynamic simulations are in good agreement with the observed tail twist. Model field line tracings indicate that a majority of the twisted tail lobes are composed of open field lines, surrounded by draped IMF. We infer that dayside magnetic reconnection between the crustal fields and draped IMF creates these open fields and may be responsible for the twisted tail configuration, similar to what is observed at Earth.

Gina A. DiBraccio↗
NASA NTRS2002

Bioinspired engineering of exploration systems for NASA and DoD

A new approach called bioinspired engineering of exploration systems (BEES) and its value for solving pressing NASA and DoD needs are described. Insects (for example honeybees and dragonflies) cope remarkably well with their world, despite possessing a brain containing less than 0.01% as many neurons as the human brain. Although most insects have immobile eyes with fixed focus optics and lack stereo vision, they use a number of ingenious, computationally simple strategies for perceiving their world in three dimensions and navigating successfully within it. We are distilling selected insect-inspired strategies to obtain novel solutions for navigation, hazard avoidance, altitude hold, stable flight, terrain following, and gentle deployment of payload. Such functionality provides potential solutions for future autonomous robotic space and planetary explorers. A BEES approach to developing lightweight low-power autonomous flight systems should be useful for flight control of such biomorphic flyers for both NASA and DoD needs. Recent biological studies of mammalian retinas confirm that representations of multiple features of the visual world are systematically parsed and processed in parallel. Features are mapped to a stack of cellular strata within the retina. Each of these representations can be efficiently modeled in semiconductor cellular nonlinear network (CNN) chips. We describe recent breakthroughs in exploring the feasibility of the unique blending of insect strategies of navigation with mammalian visual search, pattern recognition, and image understanding into hybrid biomorphic flyers for future planetary and terrestrial applications. We describe a few future mission scenarios for Mars exploration, uniquely enabled by these newly developed biomorphic flyers.

Space Flight↗
DOE OSTI2022

High-Density, Actively Multiplexed µECoG Array on Reinforced Silicone Substrate

Simultaneous interrogation of electrical signals from wide areas of the brain is vital for neuroscience research and can aid in understanding the mechanisms of brain function and treatments for neurological disorders. There emerges a demand for development of devices with highly conformal interfaces that can span large cortical regions, have sufficient spatial resolution, and chronic recording capability while keeping a small implantation footprint. In this work, we have designed 61 channel and 48 channel high-density, cortical, micro-electrocorticographic electrode arrays with 400 µm pitch on an ultra-soft but durable substrate. We have also developed a custom multiplexing integrated circuit (IC), methods for packaging the IC in a water-tight liquid crystal polymer casing, and a micro-bonding method for attaching the electronics package to the electrode array. With the integrated multiplexer, the number of external wire connections can be reduced to 16 wires, thereby diminishing the invasive footprint of the device. Both the electrode array and IC were tested in vivo in a rat model to demonstrate the ability to sense finely-localized electrophysiological signals.

Rachinskiy, Iakov↗
NASA NTRS1998

Of mice and genes: evolution of vertebrate brain development

In this review the current understanding of genetic and molecular evolution of development, in particular the formation of the major axis of bilateral animals, is critically evaluated, and the early pattern formation in the hindbrain is related as much as possible to these processes. On the genetic level it is proposed that the exuberant multiplication of regulatory genes compared to that of structural genes relates to the increased flexibility of early vertebrate development. In comparisons to fruit flies, many conserved genes are found to be expressed very differently, while many others seem to reflect a comparable pattern and thus suggest a conservation of function. Even genes with a largely conserved pattern of expression may change the level at which they are expressed and the mechanisms by which they are regulated in their expression. Evolution and development of hindbrain motoneurons is reviewed, and it is concluded that both comparative data as well as more recent experimental data suggest a limited importance for the rhombomeres. Clearly, many cell fate-specifying processes work below the level of rhombomeres or in the absence of rhombomeres. It is suggested that more comparative developmental data are needed to establish firmly the relationship between homeobox genes and rhombomere specification in vertebrates other than a few model species.

NASA Discipline Developmental Biology↗
NASA NTRS2013

Correlations Between Variations in Solar EUV and Soft X-Ray Irradiance and Photoelectron Energy Spectra Observed on Mars and Earth

Solar extreme ultraviolet (EUV; 10-120 nm) and soft X-ray (XUV; 0-10 nm) radiation are major heat sources for the Mars thermosphere as well as the primary source of ionization that creates the ionosphere. In investigations of Mars thermospheric chemistry and dynamics, solar irradiance models are used to account for variations in this radiation. Because of limited proxies, irradiance models do a poor job of tracking the significant variations in irradiance intensity in the EUV and XUV ranges over solar rotation time scales when the Mars-Sun-Earth angle is large. Recent results from Earth observations show that variations in photoelectron energy spectra are useful monitors of EUV and XUV irradiance variability. Here we investigate photoelectron energy spectra observed by the Mars Global Surveyor (MGS) Electron Reflectometer (ER) and the FAST satellite during the interval in 2005 when Earth, Mars, and the Sun were aligned. The Earth photoelectron data in selected bands correlate well with calculations based on 1 nm resolution observations above 27 nm supplemented by broadband observations and a solar model in the 0-27 nm range. At Mars, we find that instrumental and orbital limitations to the identifications of photoelectron energy spectra in MGS/ER data preclude their use as a monitor of solar EUV and XUV variability. However, observations with higher temporal and energy resolution obtained at lower altitudes on Mars might allow the separation of the solar wind and ionospheric components of electron energy spectra so that they could be used as reliable monitors of variations in solar EUV and XUV irradiance than the time shifted, Earth-based, F(10.7) index currently used.

EUV↗
DOE OSTI2021

A domain wall-magnetic tunnel junction artificial synapse with notched geometry for accurate and efficient training of deep neural networks

Inspired by the parallelism and efficiency of the brain, several candidates for artificial synapse devices have been developed for neuromorphic computing, yet a nonlinear and asymmetric synaptic response curve precludes their use for backpropagation, the foundation of modern supervised learning. Spintronic devices—which benefit from high endurance, low power consumption, low latency, and CMOS compatibility—are a promising technology for memory, and domain-wall magnetic tunnel junction (DW-MTJ) devices have been shown to implement synaptic functions such as long-term potentiation and spike-timing dependent plasticity. In this work, we propose a notched DW-MTJ synapse as a candidate for supervised learning. Using micromagnetic simulations at room temperature, we show that notched synapses ensure the non-volatility of the synaptic weight and allow for highly linear, symmetric, and reproducible weight updates using either spin transfer torque (STT) or spin–orbit torque (SOT) mechanisms of DW propagation. We use lookup tables constructed from micromagnetics simulations to model the training of neural networks built with DW-MTJ synapses on both the MNIST and Fashion-MNIST image classification tasks. Accounting for thermal noise and realistic process variations, the DW-MTJ devices achieve classification accuracy close to ideal floating-point updates using both STT and SOT devices at room temperature and at 400 K. Our work establishes the basis for a magnetic artificial synapse that can eventually lead to hardware neural networks with fully spintronic matrix operations implementing machine learning.

42 ENGINEERING↗
NASA NTRS2018

The Three-Dimensional Bow Shock of Mars as Observed by MAVEN

The Martian magnetosphere is a product of the interaction of Mars with the interplanetary magnetic field and the supersonic solar wind. The location of the bow shock has been previously modeled as conic sections using data from spacecraft such as Phobos 2, Mars Global Surveyor, and Mars Express. The Mars Atmosphere and Volatile EvolutioN (MAVEN) mission spacecraft arrived in orbit about Mars in November 2014 resulting in thousands of crossings to date. We identify over 1,000 bow shock crossings. We model the bow shock as a three-dimensional surface accommodating asymmetry caused by crustal magnetic fields. By separating MAVEN's bow shock encounters based on solar condition, we also investigate the variability of the surface. We find that the shock surface varies in shape and location in response to changes in the solar radiation, the solar wind Mach number, dynamic pressure of the solar wind, and the relative local time location of the strong crustal magnetic fields (i.e., whether they are on the dayside or on the nightside).

Supersonic↗
DOE OSTI2021

cAMP binding to closed pacemaker ion channels is non-cooperative

Electrical activity in the brain and heart depends on rhythmic generation of action potentials by pacemaker ion channels (HCN) whose activity is regulated by cAMP binding. Previous work has uncovered evidence for both positive and negative cooperativity in cAMP binding, but such bulk measurements suffer from limited parameter resolution. Efforts to eliminate this ambiguity using single-molecule techniques have been hampered by the inability to directly monitor binding of individual ligand molecules to membrane receptors at physiological concentrations. Here we overcome these challenges using nanophotonic zero-mode waveguides4 to directly resolve binding dynamics of individual ligands to multimeric HCN1 and HCN2 ion channels. We show that cAMP binds independently to all four subunits when the pore is closed, despite a subsequent conformational isomerization to a flip state at each site. The different dynamics in binding and isomerization are likely to underlie physiologically distinct responses of each isoform to cAMP and provide direct validation of the ligand-induced flip-state model. Furthermore, this approach for observing stepwise binding in multimeric proteins at physiologically relevant concentrations can directly probe binding allostery at single-molecule resolution in other intact membrane proteins and receptors.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

De novo designed protein inhibitors of amyloid aggregation and seeding

Neurodegenerative diseases are characterized by the pathologic accumulation of aggregated proteins. Known as amyloid, these fibrillar aggregates include proteins such as tau and amyloid-β (Aβ) in Alzheimer’s disease (AD) and alpha-synuclein (αSyn) in Parkinson’s disease (PD). The development and spread of amyloid fibrils within the brain correlates with disease onset and progression, and inhibiting amyloid formation is a possible route toward therapeutic development. Recent advances have enabled the determination of amyloid fibril structures to atomic-level resolution, improving the possibility of structure-based inhibitor design. In this work, we use these amyloid structures to design inhibitors that bind to the ends of fibrils, “capping” them so as to prevent further growth. Using de novo protein design, we develop a library of miniprotein inhibitors of 35 to 48 residues that target the amyloid structures of tau, Aβ, and αSyn. Biophysical characterization of top in silico designed inhibitors shows they form stable folds, have no sequence similarity to naturally occurring proteins, and specifically prevent the aggregation of their targeted amyloid-prone proteins in vitro. The inhibitors also prevent the seeded aggregation and toxicity of fibrils in cells. In vivo evaluation reveals their ability to reduce aggregation and rescue motor deficits in Caenorhabditis elegans models of PD and AD.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Lithium-Ion Batteries with Safer Current Collectors

The US Department of Energy’s Oak Ridge National Laboratory and Soteria Battery Innovation Group collaborated to develop a metallized polymer film as a current collector for lithium-ion batteries and design slit patterns for electrodes to improve battery safety. The metallized polymer film serves as a fuse that will break under high temperature resulting from a short circuit. Consequently, the short circuit will be broken and the heat generated from the short circuit will be alleviated to avoid thermal runaway. The electrodes with slit patterns are expected to be broken into small segments upon mechanical impact, which can isolate the damaged electrodes from the rest. Thus, the heat generation associated with the mechanical impact will be reduced, along with the likelihood of thermal runaway. This effort aimed to improve lithium-ion battery safety by replacing traditional metal foils with metallized polymer films as current collector and introducing slit patterns to battery electrodes. The metallized polymer films were polyethylene terephthalate with a thin metal (aluminum for cathodes and copper for anodes) coating on both sides. Slit patterns with various geometries and dimensions were designed via simulation. Temperature distribution on cells with electrodes with and without slit patterns was also simulated via nemerical modeling. Electrodes on traditional metal foils and metallized polymer films were coated via a pilot-scale slot-die coater at the US Department of Energy Battery Manufacturing Facility at Oak Ridge National Laboratory. The electrodes were calendered to 35% porosity and punched out with and without slit patterns. Pouch cells were assembed with the electrodes inside a dry room for electrochemical and safety testing. Electrodes coated on metallized polymer films exhibited comparable electrochemical performance to their counterparts coated on traditional metal foils. They also showed improved safety in nail penetration and indentation tests.

25 ENERGY STORAGE↗
DOE OSTI2025

Genetic algorithm optimization of nuclear criticality experiment for reduction of intermediate-energy 239 Pu nuclear data uncertainties

Nuclear criticality experiments are conducted to investigate specific nuclear data important for safe handling and storage of fissile materials, reactor design and operation, and the validation of radiation transport codes. Incorrect or uncertain nuclear data can prohibitively impact operational safety limits, reactor licensing, and predictive simulation capability; therefore, integral measurements from criticality experiments are necessary and should be performed frequently. To maximize the impact of the integral measurements, it is important to consider experiment geometry, material selection, and component dimensions. When taking these considerations into account, the experiment design process becomes iterative and very time intensive. This work utilizes a genetic algorithm to efficiently explore potential nuclear criticality experiment designs for the Laboratory Directed Research & Development project PARADIGM (PARallel Approach of Differential and InteGral Measurements) at Los Alamos National Laboratory. In this paper, the building blocks of the genetic algorithm are discussed in detail, the genetic algorithm methodology is verified, and the genetic algorithm is used to produce three candidate experiment models for the final PARADIGM design. The three candidate models produced by the genetic algorithm consist of copper-reflected assemblies containing 14 repeating units of alumina, graphite, boron, and plutonium plates. Furthermore, in addition to the optimization results, final design considerations are also discussed for designs with a height and/or weight very close to or slightly above assembly machine operational limits.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Impact of Higher Fidelity Design Iterations on Critical System Criteria

Nuclear criticality experiments are effective at informing the performance of nuclear data libraries across many applications. This work explores the implications of refining critical experiment MCNP models from their low fidelity optimization phase to penultimate neutronic models. Specifically, this work is focused on two series of plutonium fueled experiments funded through internal programs at Los Alamos National Laboratory building off previous efforts under the EUCLID (Experiments Underpinned by Computational Learning for Improvements in Nuclear Data) collaboration. Thales, the first of the two collaborations, is a fast spectrum Ta-reflected plutonium experiment to support operations at PF-4. The second experiment are twin configurations designed to target the intermediate energy cross sections in 239 Pu. Motivation for this experiment stems from the PARallel Approach of Differential and InteGral Measurements (PARADIGM) collaboration which hopes to achieve a significant reduction in 239 Pu cross section uncertainties in the intermediate region.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

CRCNS22 Learning Rules in the Hippocampus and their Mapping to Neuromorphic Systems (Final Technical Report)

Large scale biologically-realistic computational models are key to investigating the interplay between structure and function in nervous systems, thus paving the way to new clinical methods and neuro-inspired computing solutions. This project focuses on the hippocampus, in particular the CA3-CA1 regions, due to their role in associative learning and memory, pattern separation and completion, and spatial navigation. Investigations into the neuronal organization and learning rule(s) of this circuit can shed light into how declarative memories are formed, stored, recalled and forgotten and inform computational, experimental and clinical neuroscience work. Our project aims at developing a novel data-driven methodology supported by a broad heterogeneous base of neuroscience experimental knowledge and inspired from advances in computer science and engineering. Specifically, this work will benchmark existing and new learning rules within a full-scale spiking neural network simulation of the CA3-CA1 region. The model will be based on an open-source repository, called the Hippocampome, which contains neuronal morphologies, firing patterns, synapse probabilities, and most other required parameters for all known neuron types in the rodent hippocampal formation. The model will be first trained in a supervised fashion for associative memory tasks using backpropagation through time traditionally used in computer science, enhanced with a new technique called the surrogate gradient method. This optimization method will be used to obtain a global loss minimization, but it is not biologically inspired as it assumes the use of data not locally available to the synapses. However, we propose its use as a benchmarking tool, to compare the training performance of local biologically plausible and hardware-mappable learning rules at scale. New rules or combinations will be proposed and tested as needed, based on the obtained results. Progress in this area will also drive the development of novel hardware-mappable algorithms for continual lifelong learning and categorization of new events from few presented examples. This project goes beyond the existing state-of-the-art by looking at large scale realistic neuronal circuits as networks trainable via global optimization methods such as surrogate gradient descent. The objective function of the brain that supports learning is largely unknown, but it is likely that it operates through local learning rules. Studying network trajectories around local minima as proposed in this work represents a useful strategy for understanding whether a network is training by using a specific (set of) learning rule(s). Starting from a completely untrained network is a challenging test since it is difficult to determine how the learning rule affects the trajectory of the network. This interdisciplinary project will help understand what rule governs learning in these regions or if multiple learning rules are involved. The work will develop a robust methodology to measure if the network is converging to the target solution, oscillating around it, or diverging away.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Improvements of Nuclear Data Evaluations for Lead Isotopes in Support of Next Generation Lead-Cooled Fast Systems

The neutron evaluation of the isotopes that comprise natural lead were undertaken as a part of DOE-NEUP Project #19-16739. The goal of the project was to update the neutron cross sections to account for new differential measurements and incorporate the most up-to-date physics. Shortcomings in the lead cross sections was made known by several independent reports. The work performed here repeated the simulation of all the “benchmark” validation systems and concluded that the major issue is the scattering cross sections in the major lead isotopes above 100 keV. Re-evaluation of 206,207,208 Pb included both the resolved resonance region and fast region evaluations of the cross sections. Combined these regions cover energies from thermal to 20 MeV. The most drastic improvement is the resolved resonance region evaluation of 208 Pb which is now extended from 1.0 to 1.5 MeV. Parameterization of these resonances in the R-matrix provides a superior reconstruction of not only the experimental cross section but also the scattering distributions via the Blatt-Biedenharn formalism. Fast region evaluations of the three major isotopes were done to include new inelastic experimental data from the neutron Time-of-Flight facility at CERN. The culmination of all the changes to the cross section is a drastic improvement in the scattering kernel as shown in Rensselaer Polytechnic Institute (RPI) Quasi-Differential scattering measurements and improved prediction of keff for fast integral experiments. Alongside the new cross sections, new nuclear data covariance (uncertainties) have been computed and are included in the evaluation. Little is changed in the magnitude of the uncertainties but the correlations within the covariance display non-trivial changes. The new evaluations of 206,207,208 Pb have been submitted to the National Nuclear Data Center to be included in the ENDF/B-VIII.1 library. While the cross sections have been updated extensively, knowledge and modeling of the cross sections between 1.0 and 3.0 MeV for the isotopes remain a challenge. Most notably is the double differential elastic cross section for 208 Pb and 206 Pb. New quasi-differential measurements for pure samples of these two nuclei would go a long way in reducing compensating errors in the evaluations. Qualitatively, the project has produced a prosperous collaboration between the nuclear data group at RPI with staff scientists at Brookhaven National Laboratory, Naval Nuclear Laboratory, Oak Ridge National Laboratory, Los Alamos National Laboratory, Lawrence Livermore National Laboratory, and Sandia National Laboratories. Quantitatively this is reflected in seven conference presentations, at least one journal submission, and one doctoral thesis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

The Biomechanics of Indirect Traumatic Optic Neuropathy Using a Computational Head Model With a Biofidelic Orbit

Indirect traumatic optic neuropathy (ITON) is an injury to the optic nerve due to head trauma and usually results in partial or complete loss of vision. In order to advance a mechanistic understanding of the injury to the optic nerve, we developed a head model with a biofidelic orbit. Head impacts were simulated under controlled conditions of impactor velocity. The locations of impact were varied to include frontal, lateral, and posterior parts of the head. Impact studies were conducted using two types of impactors that differed in their rigidity relative to the skull. The simulated results from both the impactors suggest that forehead impacts are those to which the optic nerve is most vulnerable. The mode and location of optic nerve injury is significantly different between the impacting conditions. Simulated results using a relatively rigid impactor (metal cylinder) suggest optic nerve injury initiates at the location of the intracranial end of the optic canal and spreads to the regions of the optic nerve in the vicinity of the optic canal. In this case, the deformation of the skull at the optic canal, resulting in deformation of the optic nerve, was the primary mode of injury. On the other hand, simulated results using a relatively compliant impactor (soccer ball) suggest that primary mode of injury comes from the brain tugging upon the optic nerve (from where it is affixed to the intracranial end of the optic canal) during coup countercoup motion of the brain. This study represents the first published effort to employ a biofidelic simulation of the full length of the optic nerve in which the orbit is integrated within the whole head.

59 BASIC BIOLOGICAL SCIENCES↗