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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Testing the Exploration Conops (Excon) Mockup Suit in Lunar Analog Environments in 2022

Understanding how to effectively train for Extravehicular Activities (EVAs) for Artemis missions is critical. Developing high-fidelity simulation environments is important for Artemis mission preparation. Because the actual Lunar exploration environment cannot be fully replicated on Earth, it is paramount to determine where and how to properly train the Artemis team. The overall focus for this test series was developing the capability to perform Artemis simulated EVAs in high-fidelity, full-scale environments. This test series was broken into three distinct tests titled after the EVA & Human Surface Mobility (HSM) Program (EHP) integrated test team: Joint EVA & HSM Test Team (JETT). The test locations are planned to serve as Artemis training sites and were selected because of their relevance to the expected Artemis Lunar terrain. JETT1 was conducted near Kilbourne Hole by El Paso, Texas and focused on hardware development and checkout. JETT2 was conducted in the Icelandic Highlands and began the transition towards EVA concept of operations (con-ops), risks and technology. JETT3 was conducted near SP Crater by Flagstaff, Arizona and focused on simulating the Artemis III mission including a Houston based Flight Control Team (FCT) and a Science Mission Directorate (SMD) science team. All three JETT tests utilized the Exploration Concept of Operations (ExCon) mockup space suit. The ExCon mockup suit is a lightweight, unpressurized Exploration Extravehicular Mobility Unit (xEMU) simulator. While it cannot replicate the feel of working within a pressurized suit, it does introduce similar volume constraints and some of the mobility programing to simulate the user experience in the xEMU. Overall, the JETT testing was able to create a simulated Lunar EVA and have two subjects perform full scale operations in line with Artemis III mission expectations. Future work is planned to continue to improve the simulation quality of Lunar EVA simulations.

spacesuit↗
NASA NTRSDate not supplied

Assessment of Crew Time for Maintenance and Repair Activities for Lunar Surface Missions

NASA is currently evaluating different methods to predict how much time crewmembers will spend conducting repair and maintenance activities on future space missions. As mission scope and spacecraft architectures change, understanding how crew repair and maintenance timelines are impacted by mission operations and technology changes is vital for future mission planning. Past work has been done using historical International Space Station (ISS) data to accurately predict crew habitation and operation timelines, resulting in the development of NASA’s Exploration Crew Time Model (ECTM). However, understanding crew maintenance and repair requirements has posed a unique challenge due to the complexity of available datasets, the probabilistic nature of sub-system failures, and the impacts of reliability growth on failure rates. This paper presents a methodology to collect and condition empirical repair and maintenance time data from available datasets, to extrapolate from that data to estimate projected maintenance and repair times for a lunar Surface Habitat (SH), and to assess how uncertainty in repair time could impact utilization time on the lunar surface. NASA ISS maintenance and crew time data are logged into two central databases: the Maintenance Data Collection (MDC) and the Operations Planning Timeline Integration System (OPTimIS). Separately, each of these two datasets capture only portions of the complete set of data required to generate an accurate assessment of crew time spent on maintenance activities at a sub-system level. To create a more useful crew time estimate for maintenance timelines, the authors developed a methodology to capture relevant data from each set and combine and utilize that data by linking crew time requirements to specific components. The authors compare the failure logs in the MDC to crew activity logs pulled from OPTimIS and then process the data to estimate required repair time for each failure and repair event. The entire maintenance activity dataset is then categorized based on the class of failed component to ensure a significant sample size for each class and accurate crew time estimates for any components lacking relevant data. This resultant component repair time data can be used in the future to generate Mean Time to Repair (MTTR) estimates and confidence intervals for each class of component based on a probabilistic distribution of documented maintenance events. These improved MTTR values can then be applied to candidate element sub-system architectures, along with component Mean Time Between Failure (MTBF) data to generate distributions for potential required system crew repair time estimates for a given mission. The authors applied these modeling methods to a case study of a crewed mission to the planned SH and produced expected corrective maintenance crew time distributions. The results produced an expected corrective maintenance crew time at over 24 hours per mission, and a maintenance crew time distribution that reflects the importance of planning for sufficient maintenance requirements each mission. Repair time distributions can then be used to develop more accurate crew schedules and to assess potential available utilization time.

Crew Time↗
DOE OSTI2021

Operando video microscopy of Li plating and re-intercalation on graphite anodes during fast charging

Despite the demand for fast-charging lithium (Li)-ion batteries, high-energy-density batteries with thick graphite anodes are limited by Li plating when charging at >4C rates. In this work, plan-view operando video microscopy is applied on >3 mA h cm –2 calendared graphite electrodes to study the dynamic evolution of local state-of-charge (SoC) and Li plating during fast charging. This technique allows for visualization of the spatial heterogeneity in SoC across the electrode, nucleation and growth of Li filaments, Li re-intercalation into graphite, “dead Li” formation, and SoC equilibration. The operando microscopy analysis is complemented by ex situ imaging of through-plane gradients in SoC to gain a three-dimensional visualization of spatial heterogeneity. We demonstrate that (1) Li plating preferentially nucleates on the graphite particles that lithiate fastest during fast charging; (2) the onset of Li plating correlates with the local minimum of the graphite electrode potential; (3) galvanic corrosion currents are responsible for Li re-intercalation, dead Li formation, and SoC re-equilibration after fast charging; and (4) electrochemical signatures during OCV rest or discharge are associated with Li re-intercalation into graphite. Furthermore, this work provides insight into the Li–graphite interactions at the composite electrode level and can be used to inform strategies to diagnose and mitigate Li plating during fast charging.

25 ENERGY STORAGE↗
NASA NTRSDate not supplied

Simulated X-59 on- and off-Design Sonic Boom Levels in Realistic Atmospheres for Noise Dose Range Estimation

NASA is planning several community noise surveys across the USA using the X-59 low-boom aircraft. These surveys require a range of noise levels to resolve a dose-response relationship. The X-59 was designed to produce a shaped sonic boom with a Stevens’ Perceived Level (PL) of 75 dB or less across the boom carpet in a standard atmosphere. However, the X-59’s flight condition can be adjusted to produce levels other than 75 PLdB to obtain a range of doses during community testing. Simulated nearfield pressure waveforms of the X-59 C612A in its on-design condition (Mach 1.4 at 53,200 ft) and an off-design condition at a lower altitude (Mach 1.4 at 46,000 ft) were propagated using PCBoom through realistic atmospheres over the span of one year at several locations across the country. The predicted on-design and off-design boom levels and carpet widths are presented, resulting in a preliminary estimate of the dose range that the X-59 may produce. Future work is planned with additional off-design conditions to assess the true capable dose range of the X-59.

X-59↗
DOE OSTI2021

City of Largo Clear Sky Assessment Process: Prioritizing Solar + Storage for Resilient Facilities & Communities

The Clear Sky Tampa Bay project was a 15-month collaborative research effort to support solar + storage deployment for community resilience in Florida. The Clear Sky Decision Support Toolkit is a collection of resources designed to support users in conducting solar + storage prioritization and feasibility screening assessments at critical facilities. The Tampa Bay Regional Planning Council worked with four local governments in the region to test and apply the Toolkit. This case study series describes how each partner government used the Toolkit and highlights key insights and lessons learned that other users could follow to replicate the process. The City of Largo used the Clear Sky Decision Support Toolkit to advance community solar + storage resilience goals by collaborating with staff across departments and disciplines and engaging with utility stakeholders. The City of Largo conducted an analysis of its Wastewater Treatment Facility (WWTF), which processes an average of 43 million gallons of wastewater daily. Water treatment operations are both critical and energy intensive, requiring sustained energy throughout the day.

14 SOLAR ENERGY↗
DOE OSTI2024

Pinellas County Clear Sky Assessment Process: Prioritizing Solar + Storage for Resilient Facilities & Communities

The Clear Sky Tampa Bay project was a 15-month collaborative research effort to support solar + storage deployment for community resilience in Florida. The Clear Sky Decision Support Toolkit is a collection of resources designed to support users in conducting solar + storage prioritization and feasibility screening assessments at critical facilities. The Tampa Bay Regional Planning Council worked with four local governments in the region to test and apply the Toolkit. This case study series describes how each partner government used the Toolkit and highlights key insights and lessons learned that other users could follow to replicate the process. Pinellas County applied the Clear Sky Decision Support Toolkit to improve interagency coordination and gather data to analyze solar + storage projects for its critical facilities. This case study examines energy resilience strategies for the Pinellas County Solid Waste-to-Energy Plant. The Toolkit's modular assessment process developed institutional capacity and knowledge within the county and will assist in the research and application of future solar energy projects.

14 SOLAR ENERGY↗
DOE OSTI2021

Manatee County Clear Sky Assessment Process: Prioritizing Solar + Storage for Resilient Facilities & Communities

The Clear Sky Tampa Bay project was a 15-month collaborative research effort to support solar + storage deployment for community resilience in Florida. The Clear Sky Decision Support Toolkit is a collection of resources designed to support users in conducting solar + storage prioritization and feasibility screening assessments at critical facilities. The Tampa Bay Regional Planning Council worked with four local governments in the region to test and apply the Toolkit. This case study series describes how each partner government used the Toolkit and highlights key insights and lessons learned that other users could follow to replicate the process. Manatee County applied the Clear Sky Decision Support Toolkit to two of the county's critical facilities: Nolan Middle School, which serves as a special needs emergency shelter, and its Public Safety Complex (PSC), which houses critical services including emergency management, communications, and medical services, traffic control, and more. The PSC serves as the Emergency Operations Center during activation events. The Clear Sky assessment process improved interagency communication and coordination and informed siting decisions for a potential solar + storage system for the Manatee County PSC.

14 SOLAR ENERGY↗
NASA NTRSDate not supplied

Forging the Forge

As part of the NASA Johnson Space Center’s (JSC) effort to revitalize and recommit to our “Dare Unite Explore” vision for the future, the Center is exploring a new strategy to spread the innovation mindset and increase collaboration across the workforce. In order to maintain JSC’s leadership in human spaceflight, there is a need for working at the speed of commercial industry, breaking down silos between organizations, improving innovation and increasing workforce flexibility. Through brainstorming concepts and benchmarking other facilities, the leadership team evaluated several ideas, assessed constraints and derived that an “Innovation Team” was relatively easy to adopt. Modeled after productive teams like the Jet Propulsion Laboratory’s Innovation Foundry and Glenn Research Center's Compass team, JSC is laying the foundation of a new innovation team called the Forge. This team is as much about getting employees tempered in the ways of innovative thinking as it is about refining design studies and hammering out proposals. By the dictionary definition of the verb, forge can mean either to move ahead slowly and steadily or to move with a sudden increase of speed and power. Driving cultural change in a large government organization like NASA often involves slow perseverance with small injections of momentum to forge ahead. Leveraging lessons learned from the Innovation Foundry and Compass, this paper describes how the collaborative, concurrent engineering framework was tailored to JSC’s needs, as well as the aspects that were considered given JSC’s operation-focused, Program-driven landscape. Our process to drive cultural change, the steps taken, and challenges encountered are discussed. The first two pilots of the teaming framework are described with initial results presented in terms of employee engagement and fostering innovation. We also describe the planned future work and next steps to continue to push the initiative forward. Long has the Center been resting on its operations heritage, now we are forging a new path to Dare to expand frontiers, Unite with our partners and Explore space to benefit humanity.

Culture Change↗
DOE OSTI2021

Small Animal IMRT Using 3D-Printed Compensators

Preclinical radiation replicating clinical intensity modulated radiation therapy (IMRT) techniques can provide data translatable to clinical practice. For this work, treatment plans were created for oxygen-guided dose-painting in small animals using inverse-planned IMRT. Spatially varying beam intensities were achieved using 3-dimensional (3D)-printed compensators.

3D PRINTING↗
DOE OSTI2025

Developing and Implementing Risk-Based Research Safety at Argonne National Laboratory

Facilities operated by the US Department of Energy (DOE) are required to have extensive worker safety and health programs by regulation. Here we describe how Argonne National Laboratory (ANL) has implemented the DOE requirements to bring the Laboratory’s multidisciplinary research risk to an acceptable level to safely execute ANL’s mission to perform cutting-edge research.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Developing an Undergraduate Research Laboratory for Experimental Physical Chemistry [Book Chapter]

Embarking on a faculty career in physical chemistry at a primarily undergraduate institution (PUI) is exciting, but also overwhelming. Becoming both an effective teacher and a productive researcher requires a good plan, hard work and support from others who understand what it takes to be successful. The phrase, “building a laboratory,” calls to mind the physical construction of a research instrument, but beginning a career at a PUI involves much more than assembling equipment. Funding for the lab must be secured, students must be recruited and mentored, and the lab must be overseen to keep things running on a daily basis. While many of these tasks would also be part of starting a career at a doctoral level institution, there are many special considerations that must be taken into account when working with undergraduate students because their laboratory experience and chemical knowledge are still within those beautiful but nascent stages. Here, this unique aspect makes building a research program challenging, but also very rewarding. Exposing young minds to the wonders of physical chemistry and building personal relationships through the mentoring process can be immensely gratifying. This chapter is a compilation of holistic advice for building an experimental physical chemistry research laboratory for undergraduates, reflecting a typical experience found in the United States.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Global Barotropic Tide Modeling Using Inline Self‐Attraction and Loading in MPAS‐Ocean

Abstract We examine ocean tides in the barotropic version of the Model for Prediction Across Scales (MPAS‐Ocean), the ocean component of the Department of Energy Earth system model. We focus on four factors that affect tidal accuracy: self‐attraction and loading (SAL), model resolution, details of the underlying bathymetry, and parameterized topographic wave drag. The SAL term accounts for the tidal loading of Earth's crust and the self‐gravitation of the ocean and the load‐deformed Earth. A common method for calculating SAL is to decompose mass anomalies into their spherical harmonic constituents. Here, we compare a scalar SAL approximation versus an inline SAL using a fast spherical harmonic transform package. Wave drag accounts for energy lost by breaking internal tides that are produced by barotropic tidal flow over topographic features. We compare a series of successively finer quasi‐uniform resolution meshes (62.9, 31.5, 15.7, and 7.87 km) to a variable resolution (45 to 5 km) configuration. We ran MPAS‐Ocean in a single‐layer barotropic mode forced by five tidal constituents. The 45 to 5 km variable resolution mesh obtained the best total root‐mean‐square error (5.4 cm) for the deep ocean ( 1,000 m) tide compared to TPXO8 and ran twice as fast as the quasi‐uniform 8 km mesh, which had an error of 5.8 cm. This error is comparable to those found in other forward (non‐assimilative) ocean tide models. In future work, we plan to use MPAS‐Ocean to study tidal interactions with other Earth system components, and the tidal response to climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Employing Technology to Enable Remote Research Charrettes as a Method for Engaging Industry and Uncovering Best Practices: A Novel Approach for a Post-COVID-19 World

Methods to collect data in construction engineering and management (CEM) research are evolving, informed by recent technological advancements. One such method is research charrettes that allow effective interactions and knowledge sharing between expert industry practitioners and academic researchers, all colocated in a single venue, enabling rich data collection and live communication. A pivot point in technological evolution occurred with the COVID-19 pandemic, forcing a global shift to remote work. Hence, planned in-person research charrettes had to shift to remote sessions, relying on virtual conferencing platforms and online data collection mechanisms. Technology-enabled charrettes have allowed the authors to collect significantly richer data sets and ensure a more diverse representation of participants, while saving tremendous amounts of time. With the continuing emergence of technological applications, the world might not go back to functioning fully in person. The authors believe remote research charrettes (RRCs) will still be used in a post-COVID-19 world because of their superior performance. This paper builds on a previous publication that described traditional research charrettes as a method to enhance CEM research a decade ago; it offers a significantly updated and improved RRC method based on the knowledge gained from transitioning a dozen in-person charrettes into RRCs. It also presents performance comparisons between RRCs and traditional charrettes by quantifying metrics indicating how RRCs are more time-efficient and cost-saving, harness more participants from more diverse locations, and enable the collection of richer data sets and four times more industry comments and expert feedback. This paper also provides guidance on the integration of technology with traditional research charrettes, hence contributing to the CEM body of knowledge.

42 ENGINEERING↗
DOE OSTI2024

Empirical correlations between the function of entropy ( Z S ) and net artificial viscous work in a shock physics hydrocode

Entropy is a state variable that may be obtained from any thermodynamically complete equation of state (EOS). However, hydrocode calculations that output the entropy often contain numerical errors; this is not because of the EOS, but rather the solution techniques that are used in hydrocodes (especially Eulerian) such as convection, remapping, and artificial viscosity. Here, in this work, empirical correlations are investigated to reduce the errors in entropy without altering the solution techniques for the conservation of mass, momentum, and energy. Specifically, these correlations are developed for the function of entropy Z S , and they depend upon the net artificial viscous work, as determined via Sandia National Laboratories’ shock physics hydrocode CTH. These results are a continuation of a prior effort to implement the entropy-based CREST reactive burn model in CTH, and they are presented here to stimulate further interest from the shock physics community. Future work is planned to study higher-dimensional shock waves, shock wave interactions, and possible ties between the empirical correlations and a physical law.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Continuum shock mixture models for Ni+Al multilayers: Individual layers and bulk equations of state

Continuum shock mixture models are reviewed and applied to determine the equations of state for five different compositions of Ni x Al y ⁠, as well as bulk Ni+Al reactive multilayers, by combining the fundamental property data for elemental nickel and aluminum. From the literature, we down-select and evaluate two analytical models for the mixture Hugoniot, i.e., the well-known method of kinetic energy averaging (KEA) and a recent model proposed by Jordan and Baer [J. Appl. Phys. 111, 083516 (2012)]. Fundamentally, the former method assumes pressure equilibrium, whereas the latter assumes a common particle velocity and mixture sound speed from compressible two-phase cavitating flows. Additionally, we construct thermodynamically complete equations of state by fitting Einstein oscillator series models for the specific heat at constant volume. Finally, the solid solution approximation is invoked for intermetallic compositions, which are not strictly physical mixtures. Overall, the KEA model provides a better fit to the available Ni x Al y and Ni+Al multilayer shock compression data; however, there are combinations of material properties where the performance of these two models is thought to be reversed. Moreover, the results of this work include the first analytical solution of Jordan–Baer that does not require numerical root finding, as well as proposed modifications to the Einstein oscillator series to incorporate some effects of local pressure–temperature equilibrium and reaction–diffusion. Future work is planned that will use these equations of state in mesoscale simulations to study shock-induced reaction in Ni+Al multilayers, and the intended application is illustrated with a brief 2D hydrocode example.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Simulation of the NuScale SMR and Investigation of the Effect of Load-Following on Component Lifetimes

The NuScale SMR has been modelled using the Virtual Environment for Reactor Applications (VERA) multiphysics environment and the results compared with the publicly reported data in the Design Certification Application (DCA). The results show an excellent agreement for the compared axial and radial power distributions, temperature coefficients of reactivity, boron and control rod worths, and fast neutron flux. This NuScale model is then used to investigate the effect of different operational modes on reactor components to determine how flexible load-following operation may affect control rod and reactor pressure vessel (RPV) lifetimes. The control rod degradation is confirmed to primarily affect the silver-indium-cadmium (AIC) rod tip. The degradation rate is observed to follow a non-linear function of core power level where the increase in degradation decreases with insertion depth. For the variation in core power levels expected with current load-following schemes, the total control rod degradation is found to be mild, at 5-10% of usable life per cycle for a reactor operating at <80% power. Nonetheless, this enables load following strategies to be confirmed and/or modified to ensure that control rods do not need to be replaced during the 60+ year life of the reactor. The RPV degradation was found to be almost directly proportional to the core power level and was not overly sensitive to flux shape perturbations. Future work is planned using these damage functions to optimize operation over multiple NuScale SMR units and develop strategies for prognostics and health management.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Global centroid moment tensor solutions in a heterogeneous earth: the CMT3D catalogue

SUMMARY For over 40 yr, the global centroid-moment tensor (GCMT) project has determined location and source parameters for globally recorded earthquakes larger than magnitude 5.0. The GCMT database remains a trusted staple for the geophysical community. Its point-source moment-tensor solutions are the result of inversions that model long-period observed seismic waveforms via normal-mode summation for a 1-D reference earth model, augmented by path corrections to capture 3-D variations in surface wave phase speeds, and to account for crustal structure. While this methodology remains essentially unchanged for the ongoing GCMT catalogue, source inversions based on waveform modelling in low-resolution 3-D earth models have revealed small but persistent biases in the standard modelling approach. Keeping pace with the increased capacity and demands of global tomography requires a revised catalogue of centroid-moment tensors (CMT), automatically and reproducibly computed using Green's functions from a state-of-the-art 3-D earth model. In this paper, we modify the current procedure for the full-waveform inversion of seismic traces for the six moment-tensor parameters, centroid latitude, longitude, depth and centroid time of global earthquakes. We take the GCMT solutions as a point of departure but update them to account for the effects of a heterogeneous earth, using the global 3-D wave speed model GLAD-M25. We generate synthetic seismograms from Green's functions computed by the spectral-element method in the 3-D model, select observed seismic data and remove their instrument response, process synthetic and observed data, select segments of observed and synthetic data based on similarity, and invert for new model parameters of the earthquake’s centroid location, time and moment tensor. The events in our new, preliminary database containing 9382 global event solutions, called CMT3D for ‘3-D centroid-moment tensors’, are on average 4 km shallower, about 1 s earlier, about 5 per cent larger in scalar moment, and more double-couple in nature than in the GCMT catalogue. We discuss in detail the geographical and statistical distributions of the updated solutions, and place them in the context of earlier work. We plan to disseminate our CMT3D solutions via the online ShakeMovie platform.

58 GEOSCIENCES↗
DOE OSTI2024

Machine learning surrogate for charged particle beam dynamics with space charge based on a recurrent neural network with aleatoric uncertainty

In this work, we develop a machine learning (ML) model with aleatoric uncertainty for the low energy beam transport (LEBT) region of the LANSCE linear accelerator in which we model the transport of a space-charge-dominated 750 keV proton beam through a lattice of 22 quadrupole magnets. Our ML model is developed based on data generated by a Kapchinsky–Vladimirsky (KV) envelope model of beam transport. We show that a recurrent neural network can be used as a dynamical surrogate model for fast prediction of the LEBT beam envelope. Furthermore, we endow the model with the prediction of aleatoric uncertainty and compare three different approaches. We demonstrate that the ML-based uncertainty quantification models are well calibrated and produce good estimates of the regions where the model is less certain about its predictions. This ML framework is a necessary step in the development of a real-time virtual diagnostic tool with uncertainty quantification that can be integrated into more complex downstream tasks (e.g., adaptive control or learning flexible control policies via reinforcement learning) for improved efficiency in beam operations. In future work, we plan to expand on this preliminary study by considering more realistic envelope models that include longitudinal momentum spread and dispersive effects in bending magnets, as well as particle tracking codes with 3D space charge (such as and ). Published by the American Physical Society 2024

43 PARTICLE ACCELERATORS↗