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15 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Micromovements and discomfort associated with flight mission with helmet operation tasks with different levels of cognitive workload

When performing stationary tasks under elevated cognitive workload, individuals must perform continual muscle contractions to maintain stability of the body, resulting in fatigue of the postural muscles. When the muscles perform these contractions in a prolonged manner, the body potentially responds through small changes in body movements—micromovements that may lead to discomfort. The study purpose was to evaluate impact of cognitive load on micromovements. The micromovements were measured during three different cognitive workloads; low, medium, and high. The NASA-TLX score was used to evaluate the perceived mental workload and discomfort was assessed by visual analog scale. In total, 60 subjects (30 males and 30 females) were recruited and performed cognitive tasks that simulated flight operations such as changing the radio frequency based on air traffic control messages, balancing the fuel levels in simulated fuel tanks, and aiming a reticle in a designated moving target using the cyclic control. Cognitive load was defined by the frequency of events. Micromovements were defined by changes in the center of pressure (COP) of the seat pan and COP standard deviation. It was found that the high cognitive workloads had the highest NASA-TLX scores including mental demands, temporal demands, and effort. The neck area had the highest overall levels of discomfort followed by upper back. The highest standard deviation for COP shift and number of micromovements occurred for medium cognitive workloads. In conclusion, while there were some interesting trends, few trends reached a statistical significance due to high variability among subjects for the outcome variables.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Exploring the Interaction Between Head-Supported Mass, Posture, and Visual Stress on Neck Muscle Activation

Objective Assess neck muscle activity for varying interactions between helmet, posture, and visual stress in a simulated “helo-hunch” posture. Background Military aviators frequently report neck pain (NP). Risk factors for NP include head-supported mass, awkward postures, and mental workload. Interactions between these factors could induce constant low-level muscle activation during helicopter flight and better explain instances of NP. Method Interactions between physical loading (helmet doffed/donned), posture (symmetric/asymmetric), and visual stress (low/high contrast) were studied through neck muscle electromyography (EMG), head kinematics, subjective discomfort, perceived workload, and task performance. Subjects ( n = 16) performed eight 30-min test conditions (varied physical loading, posture, and visual stress) while performing a simple task in a simulated “helo-hunch” seating environment. Results Conditions with a helmet donned had fewer EMG median frequency cycles (which infer motor unit rotation for rest/recovery, where more cycles are better) in the left cervical extensor and left sternocleidomastoid. Asymmetric posture (to the right) resulted in higher normalized EMG activity in the right cervical extensor and left sternocleidomastoid and resulted in less lateral bending compared with neutral across all conditions. Conditions with high visual stress also resulted in fewer EMG cycles in the right cervical extensor. Conclusion A complex interaction exists between the physical load of the helmet, postural stress from awkward postures, and visual stress within a simulated “helo-hunch” seating environment. Application These results provide insight into how visual factors influence biomechanical loading. Such insights may assist future studies in designing short-term administrative controls and long-term engineering controls.

Behavioral Sciences↗
DOE OSTI2020

Blunt Impact Brain Injury using Cellular Injury Criterion

The Advanced Combat Helmet (\ACH") military specification (\mil-spec") requires a helmeted magnesium (\Mg") Department of Transportation (\DOT") headform be dropped vertically, with an impact speed of 3.1 m/s (10 ft/s), onto a steel hemispherical target. The pass/fail criteria are based on translational acceleration (150 G) alone, absent of any rotational component. Without a rotational component, the specification's injury risk application is limited to skull fracture and peripheral hematomas (subdural, subarachnoid), since this translational acceleration injury risk assessment is based on the Wayne State Tolerance Curve (\WSTC"). To provide a more comprehensive view of injury for the entire brain, an alternative approach is needed. To meet this need, we worked with a larger group called PANTHER, a collaboration between national laboratories, industry, and academia. Collaborations specific to research and results presented here come from efforts led by Mr. Ron Szalkowski and Mr. Sushant Malave, Ms. Alice Fawzi, and Dr. Christian Franck. We have developed a prototypical injury risk criterion based on the neuronal response to abrupt changes in general motion (translation, rotation, or both). The cellular-based mild traumatic brain injury (\cbmTBI") criterion utilizes both the strain and strain rate of brain tissue to account for the stretch and rate of stretch that occurs throughout the brain as a result of blunt impact to the head. We conducted physical experiments of an ACH-fitted magnesium headform, which produced repeatable headform peak accelerations. Then, we developed a simulation of the experiment, and validated the simulation output with the experimental data. We then substituted the magnesium headform with a human headform, consisting of skin, muscle, bone, gray matter, white matter, cerebral-spinal fluid, membranes, vasculature, intravertebral discs, airway and sinus. We quantified brain injury risk using the cbmTBI criterion, using the current mil-spec test and a modified test. The modified mil-spec test used an inclined anvil target that was located posterior to the crown of the helmet in the axial plane. While the current mil-spec test produced brain deformation from head translation alone, the modified test produced brain deformation from head translation and rotation, which is closer to most real world and combat theater impacts (e.g., such as occur in tertiary blast exposure). Compared to the current mil-spec test, the modified test produced elevated strains in the human digital twin. These data, mapped to the cbmTBI criterion, suggest increased injury risk for blunt impacts that cause rotation and translation, rather than just translation alone. Moreover, these data may lead to a rotational performance metric, which is rooted in the biology and pathology of the brain's response to impact and blast, and which should be used to improve next-generation helmet designs.

42 ENGINEERING↗
DOE OSTI2020

A Phenomenological Model for Cavitation

A phenomenological model of cavitation is presented, based on observations that both large relative negative pressures and large negative time derivatives of pressure are required for cavitation onset. We simulated two cavitation experiments to generate cavitation scaling parameters for relative pressure drop and rate of pressure drop. Our results show the model, while simple, is effective at reproducing results from laboratory experiments of cavitation. The parameters were then used in conjunction with a human surrogate computational model to predict, at any position within the head, the probability of intracranial cavitation caused by exposure to a blast event. The results suggest that the magnitude of blast overpressure observed in field data is sufficient to cause intracranial cavitation. Our analysis indicates that the helmeted head, when compared to the unhelmeted head configuration, results in a decrease but not elimination of cavitation exposure. When density functions of cavitation probability versus cumulative brain volume are combined with an injury severity model, the results show helmet efficacy at low and moderate risk levels. However, the convergence of unhelmeted and helmeted probability density functions at high-to-excessive risk thresholds indicates the helmet offers diminishing protection at elevated exposure levels, relative to the unhelmeted baseline. Future investigation and collaboration with neuroscience subject matter experts are needed to contextualize the current computational results. While the present work contributes specific and quantified predictions of intracranial cavitation location and severity, more research is required to apply our results to clinical settings with population-based brain injury subjects and controls. The relationship between our intracranial cavitation predictions with their anticipated clinical sequelae remains a topic in need of exploration.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

A materials data framework and dataset for elastomeric foam impact mitigating materials

The availability of materials data for impact-mitigating materials has lagged behind applications-based data. For example, data describing on-field helmeted impacts are available, whereas material behaviors for the constituent impact-mitigating materials used in helmet designs lack open datasets. Here, we describe a new FAIR (findable, accessible, interoperable, reusable) data framework with structural and mechanical response data for one example elastic impact protection foam. The continuum-scale behavior of foams emerges from the interplay of polymer properties, internal gas, and geometric structure. This behavior is rate and temperature sensitive, therefore, describing structure-property characteristics requires data collected across several types of instruments. Data included are from structure imaging via micro-computed tomography, finite deformation mechanical measurements from universal test systems with full-field displacement and strain, and visco-thermo-elastic properties from dynamic mechanical analysis. These data facilitate modeling and design efforts in foam mechanics, e.g., homogenization, direct numerical simulation, or phenomenological fitting. The data framework is implemented using data services and software from the Materials Data Facility of the Center for Hierarchical Materials Design.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Nonlinear viscoelastic response of silicone additively manufactured direct ink write (DIW) foams under repetitive compression

To investigate dynamic fatigue behavior of foam in military protective applications, such as helmets, additively manufactured (AM) foams were compressively strained into the plateau region using a reduced design of experiments. A simple power law was found to govern the decline in dynamic stiffness (complex modulus) as the foams underwent the purchase order requirement of 10,000 cycles of small deformation in the plateau region. This rate of decline was newly found to correlate with the degree of nonlinearity in the material’s deformation, quantified using total harmonic distortion. Materials with low nonlinearity exhibited relatively stable stiffness across cycles, while those with high nonlinearity experienced greater losses. The observed nonlinearity depended on both applied stress and strain rate. A strong linear correlation (R 2 = 0.78) was identified between second-order nonlinearity and the time-dependent stiffness response. Two lattice structures were examined: face-centered tetragonal (FCT) and simple cubic (SC). The SC material exhibited higher total harmonic distortion (5%) and lower stiffness retention than the FCT (2%). In conclusion, these results suggest that for cyclic compression applications in a wide variety of industries such as packaging, personal protective equipment, or aerospace, selecting materials with lower stress and greater structural uniformity can enhance the stability of dynamic performance.

42 ENGINEERING↗
DOE OSTI2021

The 3D printing and modeling of functionally graded Kelvin foams for controlling crushing performance

Mechanical impact protection is an important consideration in many applications, ranging from product transportation to sports. Cellular materials are typically used due to their desirable energy absorption properties and light weight. However, their large deformation and rate dependent responses (especially of polymer foams) are challenging to consider in design. Additionally, the use of foams with uniform properties, such as uniform density and uniform stiffness, often restricts the designed foams to only be suitable for a narrow range of mechanical impact conditions whereas real applications commonly face unpredictable situations. 3D printing offers fabrication flexibility and thus opens the door to create foams with tailored properties. In this work, we investigate the feasibility of using 3D printing for functionally graded foams (FGFs) that are optimal over a broad range of mechanical environments. The foams are fabricated by the recently developed grayscale digital light processing (g-DLP) method which can print parts with locally designed properties. These foams are tested under drop test conditions and with slower displacement control. We also model the large deformation behavior of FGFs using finite element analysis in which we account for the different viscoelastic behaviors of the distinct grayscale regions. We then use the model to examine the impact mitigation capabilities of FGFs in different loading scenarios. Finally, we show how FGFs can be used to satisfy real-world design goals using the case study of a motorcycle helmet. In contrast to prior work, we investigate continuous, functionally graded foams of a single density that differ in their viscoelastic responses. This work provides further insight into the benefits of viscoelastic properties and modulus graded foams and presents a manufacturing approach that can be used to produce the next generation of flexible lattice foams as mechanical absorbers.

3D printing↗
DOE OSTI2021

Laminar and turbulent plasmoid ejection in a laboratory Parker Spiral current sheet

Quasi-periodic plasmoid formation at the tip of magnetic streamer structures is observed to occur in experiments on the Big Red Ball as well as in simulations of these experiments performed with the extended magnetohydrodynamics code, NIMROD. This plasmoid formation is found to occur on a characteristic time scale dependent on pressure gradients and magnetic curvature in both experiment and simulation. Single mode, or laminar, plasmoids exist when the pressure gradient is modest, but give way to turbulent plasmoid ejection when the system drive is higher, which produces plasmoids of many sizes. However, a critical pressure gradient is also observed, below which plasmoids are never formed. A simple heuristic model of this plasmoid formation process is presented and suggested to be a consequence of a dynamic loss of equilibrium in the high- $\beta$ region of the helmet streamer. This model is capable of explaining the periodicity of plasmoids observed in the experiment and simulations, and produces plasmoid periods of 90 minutes when applied to two-dimensional models of solar streamers with a height of $3R_\odot$ . This is consistent with the location and frequency at which periodic plasma blobs have been observed to form by Large Angle and Spectrometric Coronograph and Sun Earth Connection Coronal and Heliospheric Investigation instruments.

Physics↗
DOE OSTI2023

Single-trial classification of evoked responses to auditory tones using OPM- and SQUID-MEG

Abstract Objective. Optically pumped magnetometers (OPMs) are emerging as a near-room-temperature alternative to superconducting quantum interference devices (SQUIDs) for magnetoencephalography (MEG). In contrast to SQUIDs, OPMs can be placed in a close proximity to subject’s scalp potentially increasing the signal-to-noise ratio and spatial resolution of MEG. However, experimental demonstrations of these suggested benefits are still scarce. Here, to compare a 24-channel OPM-MEG system to a commercial whole-head SQUID system in a data-driven way, we quantified their performance in classifying single-trial evoked responses. Approach. We measured evoked responses to three auditory tones in six participants using both OPM- and SQUID-MEG systems. We performed pairwise temporal classification of the single-trial responses with linear discriminant analysis as well as multiclass classification with both EEGNet convolutional neural network and xDAWN decoding. Main results. OPMs provided higher classification accuracies than SQUIDs having a similar coverage of the left hemisphere of the participant. However, the SQUID sensors covering the whole helmet had classification scores larger than those of OPMs for two of the tone pairs, demonstrating the benefits of a whole-head measurement. Significance. The results demonstrate that the current OPM-MEG system provides high-quality data about the brain with room for improvement for high bandwidth non-invasive brain–computer interfacing.

Iivanainen, Joonas (ORCID:0000000160344604)↗
DOE OSTI2021

Human Readiness Levels Explained

The Human Readiness Level scale complements and supplements the existing technology readiness level scale to support comprehensive and systematic evaluation of human system aspects throughout a system’s life cycle. The objective is to ensure humans can use a fielded technology or system as intended to support mission operations safely and effectively. This article defines the nine human readiness levels in the scale, explains their meaning, and illustrates their application using a helmet-mounted display example.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

2022 Bull E-Bike Pilot Program Study

In 2022, the City of Durham conducted an e-bike pilot program study to learn more about how electric bikes (e-bikes) could improve the transportation experience in the "Bull City" (a.k.a., Durham, North Carolina). The study used pedal-assist e-bikes, which feature an electric motor and battery to help power the bike. The motor amplifies the power behind each pedal stroke, augmenting the energy you put into the bike. #### Data Collection Agency The City of Durham's Transportation Department conducted the study. #### Survey Methodology Program participants used electric-assist e-bikes for at least 4 weeks between August and November 2022 in exchange for sharing information about their experiences, including tracking their travel via a smartphone app. In addition to the e-bike, participants received maintenance support along with a helmet, bike lock, and other accessories. Data collection was enabled by the [NLR OpenPATH platform](https://www.nlr.gov/transportation/openpath.html). #### Survey Records and Data Survey records include a total of 76 participants. The dataset contains 3 months of partially automated travel diaries, combining sensed and surveyed travel behavior data—patterns of multimodal, end-to-end, individual human mobility—as well as demographic and socioeconomic information from participants. The number of total trips was 6,488, the number of e-bike trips was 2,183, and the number of e-bike miles traveled was 5,450.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Biofidelic Digital Head Model Software

Researchers at Los Alamos have extensive capabilities in biofidelic modeling, simulation and software development for predicting traumatic brain injury (TBI). Since injury-causing experiments cannot be performed on live humans, and head dummies are incapable of predicting brain deformations/strain, our approach uses magnetic resonance imaging (MRI) data for the brain combined with advanced computational methods and substructure constitutive properties to identify harmful accelerations that may develop diffused axonal injury in the brain. The goal is to develop this capability to analyze the effectiveness of personal protective equipment (PPE) such as, helmets and the advanced energy-absorbing materials used in PPE to mitigate brain injury. Los Alamos is seeking a collaborative partner (through a cooperative research and development agreement) to develop this capability toward a potential technology that will have commercial viability.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Diagnosis of Alzheimer’s disease using plasma biomarkers adjusted to clinical probability

Abstract Recently approved anti-amyloid immunotherapies for Alzheimer’s disease (AD) require evidence of amyloid-β pathology from positron emission tomography (PET) or cerebrospinal fluid (CSF) before initiating treatment. Blood-based biomarkers promise to reduce the need for PET or CSF testing; however, their interpretation at the individual level and the circumstances requiring confirmatory testing are poorly understood. Individual-level interpretation of diagnostic test results requires knowledge of disease prevalence in relation to clinical presentation (clinical pretest probability). Here, in a study of 6,896 individuals evaluated from 11 cohort studies from six countries, we determined the positive and negative predictive value of five plasma biomarkers for amyloid-β pathology in cognitively impaired individuals in relation to clinical pretest probability. We observed that p-tau217 could rule in amyloid-β pathology in individuals with probable AD dementia (positive predictive value above 95%). In mild cognitive impairment, p-tau217 interpretation depended on patient age. Negative p-tau217 results could rule out amyloid-β pathology in individuals with non-AD dementia syndromes (negative predictive value between 90% and 99%). Our findings provide a framework for the individual-level interpretation of plasma biomarkers, suggesting that p-tau217 combined with clinical phenotyping can identify patients where amyloid-β pathology can be ruled in or out without the need for PET or CSF confirmatory testing.

Cell Biology↗