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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Injury severity analysis of truck-involved crashes under different weather conditions

This paper investigates truck-involved crashes to determine the statistically significant factors that contribute to injury severity under different weather conditions. The analysis uses crash data from the state of Ohio between 2011 and 2015 available from the Highway Safety Information System. To determine if weather conditions should be considered separately for truck safety analyses, parameter transferability tests are conducted; the results suggest that weather conditions should be modeled separately with a high level of statistical confidence. To this end, three separate mixed logit models are estimated for three different weather conditions: normal, rain and snow. The estimated models identify a variety of statistically significant factors influencing the injury severity. Different weather conditions are found to have different contributing effects on injury severity in truck-involved crashes. Rural, rear-end and sideswipe crash parameters were found to have significantly different levels of impact on injury severity. Based on the findings of this study, several countermeasures are suggested: 1) safety and enforcement programs should focus on female truck drivers, 2) a variable speed limit sign should be used to lower speeds of trucks during rainy condition, and 3) trucks should be restricted or prohibited on non-interstates during rainy and snowy conditions. These countermeasures could reduce the number and severity of truck-involved crashes under different weather conditions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Human fatalities resulting from wild pig attacks worldwide – 2000-2019

Although reported to be rare, human fatalities resulting from wild pig (Sus scrofa) attacks do occur. Toward a better understanding of patterns in fatal wild pig attacks, we synthesized worldwide reports of wild pig attacks on humans between 2000 and 2019. We documented 163 separate reports of fatal wild pig attacks that resulted in 172 human deaths. On average, 8.6 human deaths occurred annually due to wild pig attacks during those 2 decades. The majority of fatal attacks resulted in a single human death; however, there were 6 cases in which an individual fatal attack resulted in 2–4 human deaths. These fatal wild pig attacks occurred in 29 countries, mostly within the wild pig’s native global range. Fatal attacks primarily occurred under non-hunting circumstances and involved seemingly unprovoked wild pigs. Under hunting circumstances, fatal attacks primarily involved provoked or wounded wild pigs. Fatal attacks typically involved a solitary wild pig, with 12% involving multiple pigs. Solitary pigs involved in fatal attacks were typically large boars that in most attacks exhibited defensive behaviors, although we discovered 7 attacks during which the pig’s behaviors appeared to be predatory. Three fatal attacks were initially investigated as homicides. Overall, victims of fatal wild pig attacks were between 3 and 85 years old and were traveling on foot when the attack occurred. The majority of victims of fatal attacks were adult (20–59 years old), male, traveling on foot, and working in isolation. Among all fatal attacks, 50% identified the cause of death, which included exsanguination/hemorrhagic shock, severe injury, heart attack, craniocerebral injury, severe injury/disembowelment/intestinal prolapse, and toxemia/septicemia. Fatal wild pig attacks occurred primarily in rural areas, with fatal attacks 390% more likely to occur in rural areas with large populations and at least 45% forested and agricultural cover. The greater the rural human population size within a country is, the greater the number of fatal wild pig attacks.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

A Bayesian modeling framework for crash severity effects of active traffic management systems

Transportation agencies utilize Active traffic management (ATM) systems to dynamically manage recurrent and non-recurrent congestion based on real-time conditions. While these systems have been shown to have some safety benefits, their impact on injury severity outcomes is currently uncertain. In this paper, we used full Bayesian mixed logit models to quantify the impact that ATM deployment had on crash severities. The estimation results revealed lower severities with ATM deployment. Marginal effects for ATM deployments that featured hard shoulder running (HSR) revealed lower likelihoods for severe and moderate injury crashes of 15.9 % and for minor injury crashes of 10.1 %. The likelihood of severe and moderate injury crashes and minor injury crashes reduced by 12.4 % and 8.33 % with ATM without HSR. The models were observed to be temporally transferable and had forecast error of 0.301 and 0.304 for the two models, revealing better performance with validation data. These results have implications for improving freeway crash risk at critical locations.

97 MATHEMATICS AND COMPUTING↗
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 OSTI2022

Mass Spectrometry-Based Approaches for Clinical Biomarker Discovery in Traumatic Brain Injury

Purpose of Review: Precision treatments to address the multifaceted pathophysiology of traumatic brain injury (TBI) are desperately needed, which has led to the intense study of fluid-based protein biomarkers in TBI. Mass Spectrometry (MS) is increasingly being applied to biomarker discovery and quantification in neurological disease to explore the proteome, allowing for more flexibility in biomarker discovery than commonly encountered antibody-based assays. In this narrative review, we will provide specific examples of how MS technology has advanced translational research in traumatic brain injury (TBI) focusing on clinical studies, and looking ahead to promising emerging applications of MS to the field of Neurocritical Care. Recent Findings: Proteomic biomarker discovery using MS technology in human subjects has included the full range of injury severity in TBI, though critically ill patients can offer more options to biofluids given the need for invasive monitoring. Blood, urine, cerebrospinal fluid, brain specimens, and cerebral extracellular fluid have all been sources for analysis. Emerging evidence suggests there are distinct proteomic profiles in radiographic TBI subtypes, and that biomarkers may be used to distinguish patients sustaining TBI from healthy controls. Metabolomics may offer a window into the perturbations of ongoing cerebral insults in critically ill patients after severe TBI. Summary: Emerging MS technologies may offer biomarker discovery and validation opportunities not afforded by conventional means due to its ability to handle the complexities associated with the proteome. In conclusion, while MS techniques are relatively early in development in the neurosciences space, the potential applications to TBI and neurocritical care are likely to accelerate in the coming decade.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Impact of cyberattacks on safety and stability of connected and automated vehicle platoons under lane changes

Connected and automated vehicles (CAVs) offer a huge potential to improve the operations and safety of transportation systems. However, the use of smart devices and communications in CAVs introduce new risks. CAVs would leverage vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) communication, thus providing additional system access points compared to traditional systems. Automation makes these systems more vulnerable and increases the consequences of cyberattacks. This study utilizes an infrastructure-based communication platform consisting of cooperative adaptive cruise control and lane control advisories developed by the authors to perform cyber risk assessment of CAVs. The study emulates three types of cyberattacks (message falsification, dedicated denial of service, and spoofing attacks) in a representative traffic environment consisting of multiple CAV platoons and lane change events to analyze the safety and stability impacts of the cyberattacks. Simulation experiments using VISSIM reveals that traffic stream and CAV string is unstable under all three types of cyberattacks. The worst case is represented by the message falsification attack. Increases in volatility are observed over a no attack case, with variations increasing by an average of 43%–51% along with an increase of over 3000 crash conflicts. Similarly, lane change crash conflicts are observed to be more severe compared to rear end crash conflicts, showing a higher probability of severe injuries. Further, the case of slight cyberattack on a single CAV also creates significant disruption in the traffic stream. Analysis of variance (ANOVA) reveals the statistical significance of the results. Furthermore, these results pave the way for future design of secure systems from a monitoring perspective.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Connected Traffic Signal Coordination Optimization Framework through Network-Wide Adaptive Linear Quadratic Regulator–Based Control Strategy

Traffic congestion in metropolitan areas causes several significant challenges, such as longer travel times, decreased productivity, increased fuel consumption and vehicle emissions, and even severe injuries during crashes. Traffic signal control is a management approach to reduce traffic congestion and allocate the appropriate right of way for safety and mobility efficiency, both in temporal and spatial domains. Here, this study proposes a network-wide adaptive signal control coordination optimization framework based on the linear quadratic regulator algorithm. The traffic flow conditions driven by signal control inputs are formulated based on their network-wide state-space representation. After modeling traffic control regulation constraints, an adaptive linear quadratic regulator algorithm is designed to maximize the network-wide total throughput under the current conditions. Optimal signal control split time durations for multiple intersections in the network are derived by solving the algebraic Riccati equation. Furthermore, the recursive least square parameter estimation method is employed to quantify dynamic traffic condition changes. To verify the effectiveness of this proposed signal control framework, both simulation and real-world experimental tests are conducted for multiple intersections in downtown Chattanooga, Tennessee, United States. In preparation for real-world experimental tests, pipelines for real-time data processing implementation and historical traffic flow data analysis are conducted. The test results demonstrate that the proposed control framework achieves a decrease in travel time by up to 19.4%, total time spent (TTS) by up to 11.9%, and relative queue balance (RQB) by up to 15.6%. The research findings indicate that the proposed signal control framework can be generalized to handle large scale signal control optimization network-wide.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

PNNL CRADA No. 488, Amendment 2 with Natel Energy, Inc.: The Center Sender

Under the Cooperative Research and Development Agreement (CRADA) No. 488, awarded to Natel Energy, Inc. (Natel) for third place in the Fish Protection Prize 2020 initiative, research was conducted on the Center Sender concept, a simple physical or combined physical and electrical device intended to guide fish to the safest path through a hydropower intake or water diversion. Applying this to a hydropower turbine, the Center Sender can be designed to divert fish to the center of the turbine, where blade velocities are slower and the risk of severe injuries due blade strike, pinching, and grinding are reduced.

13 HYDRO ENERGY↗
DOE OSTI2023

An Explainable Machine-Learning Model for Compensatory Reserve Measurement: Methods for Feature Selection and the Effects of Subject Variability

Tracking vital signs accurately is critical for triaging a patient and ensuring timely therapeutic intervention. The patient’s status is often clouded by compensatory mechanisms that can mask injury severity. The compensatory reserve measurement (CRM) is a triaging tool derived from an arterial waveform that has been shown to allow for earlier detection of hemorrhagic shock. However, the deep-learning artificial neural networks developed for its estimation do not explain how specific arterial waveform elements lead to predicting CRM due to the large number of parameters needed to tune these models. Alternatively, we investigate how classical machine-learning models driven by specific features extracted from the arterial waveform can be used to estimate CRM. More than 50 features were extracted from human arterial blood pressure data sets collected during simulated hypovolemic shock resulting from exposure to progressive levels of lower body negative pressure. A bagged decision tree design using the ten most significant features was selected as optimal for CRM estimation. This resulted in an average root mean squared error in all test data of 0.171, similar to the error for a deep-learning CRM algorithm at 0.159. By separating the dataset into sub-groups based on the severity of simulated hypovolemic shock withstood, large subject variability was observed, and the key features identified for these sub-groups differed. This methodology could allow for the identification of unique features and machine-learning models to differentiate individuals with good compensatory mechanisms against hypovolemia from those that might be poor compensators, leading to improved triage of trauma patients and ultimately enhancing military and emergency medicine.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Antibiotic Treatment Prior to Injury Improves Post-Traumatic Osteoarthritis Outcomes in Mice

Osteoarthritis (OA) is a painful and debilitating disease characterized by the chronic and progressive degradation of articular cartilage. Post-traumatic OA (PTOA) is a secondary form of OA that develops in ~50% of cases of severe articular injury. Inflammation and re-occurring injury have been implicated as contributing to the progression of PTOA after the initial injury. However, there is very little known about external factors prior to injury that could affect the risk of PTOA development. To examine how the gut microbiome affects PTOA development we used a chronic antibiotic treatment regimen starting at weaning for six weeks prior to ACL rupture, in mice. A six-weeks post-injury histological examination showed more robust cartilage staining on the antibiotic (AB)-treated mice than the untreated controls (VEH), suggesting slower disease progression in AB cohorts. Injured joints also showed an increase in the presence of anti-inflammatory M2 macrophages in the AB group. Molecularly, the phenotype correlated with a significantly lower expression of inflammatory genes Tlr5, Ccl8, Cxcl13, and Foxo6 in the injured joints of AB-treated animals. Our results indicate that a reduced state of inflammation at the time of injury and a lower expression of Wnt signaling modulatory protein, Rspo1, caused by AB treatment can slow down or improve PTOA outcomes.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Antibiotic Treatment Prior to Injury Abrogates the Detrimental Effects of LPS in STR/ort Mice Susceptible to Osteoarthritis Development

Post traumatic osteoarthritis (PTOA) is a form of secondary osteoarthritis (OA) that develops in ~50% of cases of severe articular joint injuries and leads to chronic and progressive degradation of articular cartilage and other joint tissues. PTOA progression can be exacerbated by repeated injury and systemic inflammation. Few studies have examined approaches for blunting or slowing down PTOA progression with emphasis on systemic inflammation; most arthritis studies focused on the immune system have been in the context of rheumatoid arthritis. To examine how the gut microbiome affects systemic inflammation during PTOA development, we used a chronic antibiotic treatment regimen starting at weaning for 6 weeks before anterior cruciate ligament (ACL) rupture in STR/ort mice combined with lipopolysaccharide (LPS)-induced systemic inflammation. STR/ort mice develop spontaneous OA as well as a more severe PTOA phenotype than C57Bl/6J mice. By 6 weeks post injury, histological examination showed a more robust cartilage staining in the antibiotic-treated (AB) STR/ort mice than in the untreated STR/ort controls. Furthermore, we also examined the effects of AB treatment on systemic inflammation and found that the effects of LPS administration before injury are also blunted by AB treatment in STR/ort mice. The AB- or AB+LPS-treated STR/ort injured joints more closely resembled the C57Bl/6J VEH OA phenotypes than the vehicle- or LPS-treated STR/ort, suggesting that antibiotic treatment has the potential to slow disease progression and should be further explored therapeutically as prophylactic post injury.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Early Unloading After ACL Rupture and Prior to Surgical Restabilization in Mice Slows Post-Traumatic Osteoarthritis Progression

Purpose: People who sustain joint injuries such as anterior cruciate ligament (ACL) rupture often go on to develop post-traumatic osteoarthritis (PTOA). ACL injuries are often treated with ACL reconstruction, but there is typically a gap of several weeks between injury and surgery. However, it is unclear how loading or unloading of the injured joint during the early postinjury period affects the progression of PTOA. The goal of this study was to determine how unloading between noninvasive ACL injury and surgical restabilization of the injured joint affects PTOA progression in mice. Findings: Mice were subjected to noninvasive ACL injury or no injury followed by 1 week of hindlimb unloading (HLU) or normal cage activity. After 1 week of HLU or cage activity, mice underwent restabilization surgery or no surgery. ACL injury resulted in considerable epiphyseal trabecular bone loss regardless of HLU or cage activity. HLU groups exhibited significantly reduced chondrophyte/osteophyte formation, OA scoring, and synovitis at day 42. Single-cell RNA sequencing revealed that 1 week of HLU resulted in more neutrophils and less monocytes-macrophages in the injured joint. Conclusions: This study establishes that 1 week of HLU after ACL injury effectively slowed PTOA progression, suggesting that the early inflammatory response and joint instability play a key role in PTOA initiation and progression, and neutrophils and monocytes-macrophages play roles in the modulation. However, subsequent joint restabilization surgery caused greater inflammatory protease activity in the joint and exacerbated the loss of epiphyseal trabecular bone but did not significantly diminish OA score or synovitis.

ACL injury↗
DOE OSTI2021

Bioactive scaffolds with enhanced supramolecular motion promote recovery from spinal cord injury

The signaling of cells by scaffolds of synthetic molecules that mimic proteins is known to be effective in the regeneration of tissues. Here, we describe peptide amphiphile supramolecular polymers containing two distinct signals and test them in a mouse model of severe spinal cord injury. One signal activates the transmembrane receptor β1-integrin and a second one activates the basic fibroblast growth factor 2 receptor. By mutating the peptide sequence of the amphiphilic monomers in nonbioactive domains, we intensified the motions of molecules within scaffold fibrils. This resulted in notable differences in vascular growth, axonal regeneration, myelination, survival of motor neurons, reduced gliosis, and functional recovery. Here, we hypothesize that the signaling of cells by ensembles of molecules could be optimized by tuning their internal motions.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Characterization of recent wild pig-vehicle collisions in Georgia, USA

Vehicle collisions with wild pigs (Sus scrofa) are reported almost everywhere this species is found. However, this is one of the least studied and characterized forms of damage that these invasive animals cause in the United States (U.S.). Here, we analyzed 518 wild pig-vehicle collisions (WPVCs) that took place statewide in Georgia between 2015 and 2021. From that dataset, we analyzed several parameters in order to better understand and characterize these accidents on a scale that had previously not been done in the U.S. Wild pig-vehicle collisions were reported from 105 out of the 159 counties in Georgia, increasing in number annually over the seven-year period. WPVCs were most likely to occur in the fall (37%). A duration weighted time of day analysis showed that WPVCs were most frequent at dusk. Most (97%) reported accidents were caused by live wild pigs, with the remainder being due to collisions with already dead or road-killed pigs. Most (86%) collisions involved a single wild pig while the remainder occurred with two or more pigs. Collisions occurred mostly with passenger cars on dry, straight, and level two-lane blacktop roads under dark, unlighted conditions. Nine percent of the vehicle accidents involving wild pigs resulted in injuries to the drivers and passengers. Some of the most severe injuries reported were caused by swerving to avoid striking wild pigs. No human fatalities were recorded due to these accidents. Wild pig-vehicle collisions are costly and dangerous and should be closely monitored and mitigated by the agencies responsible for motorist safety, transportation infrastructure, and wildlife management.

Georgia↗
DOE OSTI2020

Tracking elemental changes in an ischemic stroke model with X-ray fluorescence imaging

Stroke is a leading cause of long-term disability in adults and a leading cause of death in developed nations. The cascade of cellular events and signalling that occur after cerebral ischemia are complex, however, analyzing global element markers of metabolic state affords the means to monitor stroke severity, status of injury, and recovery. These markers provide a multi-parameter method for assessing changes through the post-stroke time course. We employ synchrotron-based elemental mapping to follow elemental changes in the brain at 1 h, 1-, 2-, and 3-days, and at 1-, 2-, 3-, and 4-weeks post-stroke in a photothrombotic stroke model in mice. Our analysis reveals a highly consistent metabolic penumbra that can be readily identified based on the level of dysregulated potassium and other key elements. Maps of elemental distributions are also useful to demarcate events in the cellular response to the inflammatory cascade, including ion dysregulation, recruitment of cells to the lesion, and glial scar formation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Progress Toward a Multiomic Understanding of Traumatic Brain Injury: A Review

Traumatic brain injury (TBI) is not a single disease state but describes an array of conditions associated with insult or injury to the brain. While some individuals with TBI recover within a few days or months, others present with persistent symptoms that can cause disability, neuropsychological trauma, and even death. Understanding, diagnosing, and treating TBI is extremely complex for many reasons, including the variable biomechanics of head impact, differences in severity and location of injury, and individual patient characteristics. Because of these confounding factors, the development of reliable diagnostics and targeted treatments for brain injury remains elusive. We argue that the development of effective diagnostic and therapeutic strategies for TBI requires a deep understanding of human neurophysiology at the molecular level and that the framework of multiomics may provide some effective solutions for the diagnosis and treatment of this challenging condition. To this end, we present here a comprehensive review of TBI biomarker candidates from across the multiomic disciplines and compare them with known signatures associated with other neuropsychological conditions, including Alzheimer’s disease and Parkinson’s disease. We believe that this integrated view will facilitate a deeper understanding of the pathophysiology of TBI and its potential links to other neurological diseases.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

A Novel Design of Guiding Stress Wave Propagation

Impact loads can induce a series of undesirable physical phenomena including vibration, acoustical shock, perforation, fracture and fragmentation, etc. The energy associated with the impact loads can lead to severe structure damage and human injuries. A design approach which effectively reduces these negative impacts through shock/stress wave diversion is highly needed. In this paper, a computational model which predicts stress wave propagation by considering different beam geometries and configurations is developed. Additionally, a novel concept of wave guide design which modifies the stress wave propagation path without disturbance is also presented. Furthermore, this design approach is not only useful for material property characterization particularly at intermediate or high strain rates, but also allows stress wave propagation in a desired direction as the shock/impact energy can be redistributed in controllable paths. The numerical results are experimentally verified through a Drop-Hopkinson bar apparatus at Sandia National Laboratories.

36 MATERIALS SCIENCE↗