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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

COVID19 Disease Map, a computational knowledge repository of virus–host interaction mechanisms

We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 molecular mechanisms. The COVID-19 Disease Map (C19DMap) is a graphical, interactive representation of disease-relevant molecular mechanisms linking many knowledge sources. Notably, it is a computational resource for graph-based analyses and disease modelling. To this end, we established a framework of tools, platforms and guidelines necessary for a multifaceted community of biocurators, domain experts, bioinformaticians and computational biologists. The diagrams of the C19DMap, curated from the literature, are integrated with relevant interaction and text mining databases. We demonstrate the application of network analysis and modelling approaches by concrete examples to highlight new testable hypotheses. This framework helps to find signatures of SARS-CoV-2 predisposition, treatment response or prioritisation of drug candidates. Such an approach may help deal with new waves of COVID-19 or similar pandemics in the long-term perspective.

59 BASIC BIOLOGICAL SCIENCES↗

Testing a novel peptide drug towards a goal of reducing mortality in critically ill COVID19 patients

COVID 19 has been devastating the globe over the past year, and although our knowledge of how the disease progresses is constantly evolving, there is a significant amount we now about the mechanisms underlying COVID19. There is growing evidence that a 'cytokine storm' is a significant driver of mortality associated with COVID19, with studies showing high levels of hallmark inflammatory indicators in critically ill COVID19 patients. This essentially consists of the patient's immune system going awry and causing white blood cells to constantly release a large number of small molecules called cytokines. The result of this is further activation of the immune system, which ends up attacking not only infected but also healthy patient tissues, resulting in organ failure.

59 BASIC BIOLOGICAL SCIENCES↗

Tracking 2020 Decreases in Carbon Dioxide Due to the COVID19 Pandemic in NASA’s GEOS Modeling system: Implications for Space-Based Carbon Monitoring

The COVID19 pandemic led to abrupt, worldwide changes in human activity and related emissions of air pollutants and greenhouse gases that are unprecedented in modern times. NASA satellites have demonstrated their ability to observe some of these impacts, particularly in relation to short-lived gases like nitrogen dioxide (NO2), which is emitted primarily from transportation. Bottom-up analyses of carbon dioxide (CO2) emissions suggest that the growth of atmospheric CO2 has also slowed, but differences are much more subtle than for NO2 because of the lifetime of atmospheric CO2 and sectoral differences in emission reductions. Estimates of CO2 from NASA’s Orbiting Carbon Observatory 2 (OCO-2) provide a unique view of COVID19 impacts, but observed changes in the column-average CO2 can be difficult to interpret because of gaps in spatial coverage. Assimilating these data into the Goddard Earth Observing System (GEOS), an integrated Earth system model with an advanced Constituent Data Assimilation System (CoDAS), helped to reveal changes in CO2 that are consistent with separate, bottom-up analyses of emissions reductions. Both indicate that from February-April of 2020, the growth in CO2 over Europe, North America, and Asia was roughly 0.3 ppm less than during the previous four years. Anomalies derived from gap-filled GEOS OCO-2 CoDAS products contribute to a joint effort by the world’s space agencies to track COVID19 impacts on the Earth. However, attribution of these changes is complicated by interannual variability in atmospheric circulation and the influence of climate on ocean and land carbon sinks. We discuss these results from the perspective of space-based carbon monitoring, which has received considerable support over the past decade from NASA. Our results demonstrate the accomplishments of current sensors and data assimilation systems, but also highlight challenges in providing high quality, low latency information to the public. In particular, understanding and attributing CO2 changes during 2020 requires year-specific information about land and ocean fluxes, which is often delayed for months or even years. We discuss current limitations and potential solutions to address these lags, which would support more reliable and timely space-based carbon monitoring.

COVID-19↗

Remote Support of ISS Payload Operations During the COVID19 Pandemic

As part of the Human Health and Performance Contract (HHPC) with the NASA Johnson Space Center, the Human Research Program’s (HRP) Research Operations and Integration (ROI) element conducts the planning, implementation, and closing of human research operations on-board the International Space Station (ISS). These operations are supported out of the Telescience Support Center (TSC) located in the Mission Control Center at Houston’s Johnson Space Center (MCC-H). HRP ROI has an Emergency Response Plan in place to allow for remote operations to be completed in the case of inclement weather or other natural disaster; however, nominally, the remote support is only expected to last one to two weeks. In response to the COVID-19 global pandemic, HRP ROI was challenged to complete a quick transition to supporting on-orbit operations remotely and distanced for an indefinite amount of time. This shift in ground support required close collaboration with various external groups as well as the implementation or adaptation of various technologies and tools to ensure no loss of science data. Operational adjustments were put into place for ground commanding, telemetry monitoring, personnel staffing and private and public audio and video with the ISS. Adjustments were also put in place for communication and collaboration with MCC-H, the Payload Operation and Integration Center (POIC) at Marshall Space Flight Center (MSFC), as well as between the various HRP ROI console team members spread across Houston, TX. The ability to successfully support a variety of on-orbit operations from any remote location is more in demand as the commercialization of low Earth orbit is expanding.

Operations↗

A modeling framework for designing and evaluating curbside traffic management policies at Dallas-Fort Worth International Airport

Emerging mobility technologies are changing the transportation system landscape. This is especially evident at airports, such as the Dallas-Fort Worth International Airport (DFW). Without careful analysis, these changes could lead to inefficient and costly airport operations. This paper presents a modeling framework that integrates travel mode encoding, demand projection, and microsimulation to enable airports to develop, simulate, and evaluate curbside traffic managements policies and measure their impact. Here, the framework is utilized to analyze several traffic scenarios and policies for DFW: a baseline scenario which represents DFW traffic pattern as observed in 2018 and projected to 2045, a transit network company (TNC) electrification policy, a TNC queuing policy, a policy that increased transit ridership, a bus-only policy which considers the use of only buses inside DFW, an autonomous vehicle (AV) policy which investigates the impact of autonomous vehicle (AV) adoption on airport operations, and an example COVID-19 scenario which models the impact of the COVID19 pandemic. The simulations’ results demonstrate that: increasing the DFW transit ridership postpones the need for airport curbside expansion the most; encouraging shared-mobility with the bus-only policy produces the most savings in curbside congestion delays; automation and electrification for all passenger vehicle trips to/from DFW generates the most saving in fuel consumption and emissions; and uncontrolled AV adoption incurs the highest increase in fuel consumption, delay, and emissions and could require immediate airport capacity extension. Without policy intervention or investment in additional infrastructure capacity, these results predict the current operations would face significant congestion on high demand days starting as early as 2028. While derived in close partnership with DFW, the methodology presented here can be generalized to any airport.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Quantitative methods and modeling to assess COVID–19–interrupted in vivo pharmacokinetic bioequivalence studies with two reference batches

The coronavirus disease 2019 (COVID-19) has presented unprecedented challenges to the generic drug development, including interruptions in bioequivalence (BE) studies. Per guidance published by the US Food and Drug Administration (FDA) during the COVID-19 public health emergency, any protocol changes or alternative statistical analysis plan for COVID-19-interrupted BE study should be accompanied with adequate justifications and not lead to biased equivalence determination. In this study, we used a modeling and simulation approach to assess the potential impact of study outcomes when two different batches of a Reference Standard (RS) were to be used in an in vivo pharmacokinetic BE study due to the RS expiration during the COVID-19 pandemic. Simulations were performed with hypothetical drugs under two scenarios: (1) uninterrupted study using a single batch of an RS, and (2) interrupted study using two batches of an RS. The acceptability of BE outcomes was evaluated by comparing the results obtained from interrupted studies with those from uninterrupted studies. The simulation results demonstrated that using a conventional statistical approach to evaluate BE for COVID-19-interrupted studies may be acceptable based on the pooled data from two batches. An alternative statistical method which includes a “batch” effect to the mixed effects model may be used when a significant “batch” effect was found in interrupted four-way crossover studies. However, such alternative method is not applicable for interrupted two-way crossover studies. Overall, the simulated scenarios are only for demonstration purpose, the acceptability of BE outcomes for the COVID19-interrupted studies could be case-specific.

60 APPLIED LIFE SCIENCES↗

Solar Ready Vets: Recruiting and Retaining Military Talent in the Solar Workforce

The solar industry stands to benefit from a more diverse, robust and resilient workforce as we continue to emerge from COVID19 disruptions and expand our industry’s role as a mainstream part of the American energy sector. Veterans and transitioning service members have strong leadership experience and critical thinking skills that make them outstanding candidates for solar careers in today’s fast-changing world. This session will inform solar companies about how they can engage with the U.S. Department of Energy funded Solar Ready Vets Network and the Solar Ready Vets Corporate Fellowship Program, which are expanding and strengthening a nationwide pipeline of transitioning military service members and veterans into technical and leadership roles in the American solar workforce.

14 SOLAR ENERGY↗

Bioscience COVID Rapid Response Report

The COVID-19 disease outbreak and its impact on global health and economies have highlighted the national security threat posed by pathogens with pandemic potential and the need for rapid development of effective diagnostics and medical countermeasures. The Bioscience IA selected for funding rapid COVID LDRD project proposals that addressed critical R&D gaps in pandemic response that could be accomplished in 1-3 months with the requested funding. In total, the Bioscience IA funded nine rapid projects that addressed 1) rapid and accurate methods for SARS-CoV-2 RNA detection, 2) modeling tools to help prioritize populations for diagnostic testing, 3) bioinformatic tools to track SARS-CoV-2 genomic sequence changes over time, 4) molecular inhibitors of SARS-CoV-2 cellular infection, and 5) method for rapid staging of COVID19 disease to enable administration of more effective treatments. In addition, LDRD funded one larger project to be completed in FY21 that leverages Sandia capabilities to address the need for platform diagnostics and therapeutics that can be rapidly tailored against emerging pathogen targets.

59 BASIC BIOLOGICAL SCIENCES↗

Adaptive Recovery Model: Designing Systems for Testing Tracing and Vaccination to Support COVID-19 Recovery Planning.

This report documents a new approach to designing disease control policies that allocate scarce testing, contact tracing, and vaccination resources to better control community transmission of COVID19 or similar diseases. The Adaptive Recovery Model (ARM) combines a deterministic compartmental disease model with a stochastic network disease propagation model to enable us to simulate COVID-19 community spread through the lens of two complementary modeling motifs. ARM contact networks are derived from cell-phone location data that have been anonymized and interpreted as individual arrivals to specic public locations. Modeling disease spread over these networks allows us to identify locations within communities conducive to rapid disease spread. ARM applies this model- and data-derived abstractions of community transmission to evaluate the effectiveness of disease control measures including targeted social distancing, contact tracing, testing and vaccination. The architecture of ARM provides a unique capacity to help decision makers understand how best to deploy scarce testing, tracing and vaccination resources to minimize disease-spread potential in a community. This document details the novel mathematical formulations underlying ARM, presents a dynamical stability analysis of the deterministic model components, a sensitivity analysis of control parameters and network structure, and summarizes a process for deriving contact networks from cell-phone location data. An example use case steps through applying ARM to evaluate three targeted social distancing policies using Bernalillo County, New Mexico as an exemplar test locale. This step-by-step analysis demonstrates how ARM can be used to measure the relative performance of competing public health policies. Initial scenario tests of ARM shows that ARMs design focus on resource utilization rather than simple incidence prediction can provide decision makers with additional quantitative guidance for managing ongoing public health emergencies and planning future responses.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Quantitative form and fit of N95 filtering facepiece respirators are retained after dry and humid heat treatments for coronavirus deactivation

Re-use of filtering facepiece respirators (FFRs, commonly referred to as N95s) normally meant for single use only is becoming common in healthcare facilities due to shortages caused by the COVID19 pandemic. Here we report that mouse hepatitis virus (MHV) initially seeded on FFR filter material is inactivated (6 log reduction as measured by 50% tissue culture infective dose (TCID50)) after dry heating at 75 °C for 30 minutes. We also find that the quantitative fit of FFRs after heat treatment at this temperature, under dry conditions or at 90% relative humidity, is not affected by single or ten heating cycles. Previous studies have reported that the filtration efficiency of FFR filters is not negatively impacted by these heating conditions. These results suggest that thermal inactivation of coronaviruses is a potentially rapid and widely deployable method to re-use N95 FFRs in emergency situations where reusing FFRs is a necessity and broad-spectrum sterilization is unavailable. However, we also found that a heat source that emits radiation (e.g., an exposed heating element) results in rapid qualitative degradation of the FFR. Finally, we discuss differences in the results reported here and other recent studies investing heat as a means to recycle FFRs and suggest that overall wear time and donning/doffing cycles are important factors that need to be considered.

36 MATERIALS SCIENCE↗

Collaborative VR/AR Data Visualization Tool

This is the final report on Phase II SBIR for the development of a collaborative VR data visualization tool. In the 15 months of the Phase II, we have met and exceeded most objectives that we outlined for ourselves in the proposal. COVID19 has caused us to do some thing differently, but in fact the outcome is better for the development - we were meant to have traveled to institutions in the UK and EU to show the capabilities in April, but instead we have got into an iterative cycle in-house of weekly testing of the new features and functions. This is working well, so we will soon have the ability to share the application with collaborators in remote locations, without the need to travel. We are also making short videos of the features to share with those afar, again mitigating the need to travel and demonstrate in-person our new capabilities. That said, we are behind on getting input from the Beta testers, but when we do get their input it will be to test features and functions that are working, and not failing due to some glitch, which in turn will more likely lead to the acceptance of the product. One of our goals is to have a near-term commercial product, and we are tantalizingly close to it with commercial interest from LANL, Survice and other entities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Metal (Cu,Al)/CNT Composite Wires for Energy Efficient Motors

This report summarizes the main results of research project on Metal/CNT nanocomposites conducted at University of Central Florida (UCF). It should be noted that the project was budgeted for three years, but the budget period 3 was unfortunately not funded and conducted in COVID19 pandemic years due to many reasons. The demonstration plan on the small motors was also removed according to the discussion with the DOE program manager. All research activities were focused on the (Cu,Al)/CNT material development and wire extrusion. Existing methods to fabricate Metal/CNTs were usually suffering from agglomeration of CNTs due to their density and stiffness differences. A new method is studied by the UCF research team, where CNTs are surface treated firstly, then coated with pure metals (i.e., Al, Cu, and Nickle). The metal encapsulation on CNT is expected to significantly improve the interfacial bonding between CNTs and the intimated metal matrices. The coated CNT powders were used to make sample materials through sintering, then a customized wire extrusion process was employed to fabricate wires. Measurement of material property improvements in mechanical strength, thermal conductivity, and electrical conductivity were conducted on both cylinder samples and extruded wires. In addition to the sintering process, casting on metal coated CNT powder was also investigated. The best results we achieved are summarized as follows. (1) The measured thermal conductivity of Al/CNT composite made with Ni-encapsulated CNTs and pure Al powders is about 85% better than that of pure aluminum fabricated. The measured electrical conductivity of fabricated Al/CNT is about 14-20% better than that of pure aluminum. (2) The measured electrical conductivity of Cu/CNT is about 14.5% better than that of pure copper fabricated. (3) The mechanical strengths of both Cu/CNT and Al/CNT (with about 1% wt. CNTs) are 70% better than pure metals although losing some material ductility. (4) Two-stage wire extrusion at high temperatures were designed and successfully conducted to fabricate wires of Metal/CNTs.

36 MATERIALS SCIENCE↗