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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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Subsurface formations provide vast resource for energy generation, energy storage, and carbon sequestration. Sustainable energy generation from shale oil/gas and integrity of longterm storage necessitate understanding fluid behavior in nanoporous geomedia (e.g., shale caprock) under dynamic pressure conditions.
The PFvSM cluster at the University of Illinois greatly deepened the science of soft materials and expanded the means for embedding within them unprecedented functionalities. We pioneered a mesoscopic approach to materials design that combined leading competencies in fundamental experimental and theoretical soft matter science and fabrication that powerfully establishes equilibrium and nonequilibrium assembly of novel and complex building blocks as a preeminent contributor to progress in materials chemistry. Our cluster’s vision was an integrated program of work centered on soft matter science with the ultimate goal of impacting important energy technologies. As elementary units we employed function-encoded colloids, nanoparticles, large mesh fibrillar gels, deterministically fabricated networks and hybrid objects. These materials were employed as building blocks for diverse model systems that allowed fundamental soft matter principles of wide relevance to be established. Their assembly into materials with useful functional behavior provided new approaches to challenging problems in basic energy science including energy harvesting, transport and storage. To achieve these goals the cluster brought together a team of recognized world-leaders in materials synthesis and processing, in-situ characterization, theory and modeling, and materials design, integration and fabrication
This dataset provides second-by-second duty cycle data for Class 6 and Class 8 diesel trucks in Texas, including key vehicle metrics, engine-related data, and GPS data (excluding GPS latitude and longitude to ensure confidentiality). The data were collected via tablets installed on the trucks and organized into daily datasets, each associated with a unique vehicle ID and date. There are 12 daily datasets for Class 6 diesel trucks (three unique vehicle IDs) and 43 daily datasets for Class 8 diesel trucks (six unique vehicle IDs). The units associated with each column are included in the name. The engine performance data include columns such as engine speed, engine percent torque, and engine fuel rate. Road grade (%/100) was estimated using the GPS altitude and wheel-based vehicle speed, which is used as an input for FASTSim. Cumulative distance was also calculated using the wheel-based vehicle speed. Additional columns include: - Engine Speed (RPM): Removed inaccurate readings and used to calculate angular velocity (radians/second). - Torque (N·m): Calculated using engine percent torque, nominal friction percent torque, and engine reference torque values (those columns were removed from dataset), then normalized to express as torque (%). - Flywheel Power (%): Calculated using the angular velocity and torque (in kW), then normalized as a percentage of the maximum value. - Engine Fuel Rate (%) and Torque (%): Both metrics were normalized by dividing by their respective maximum values within each dataset to express them as percentages. The datasets were analyzed to assess the energy impact of various driving behaviors, simulate energy efficiency, and recommend optimal routes for diesel trucks using NLR’s tool called RouteE. For driver coaching, factors like speed and acceleration limits were considered, and idle periods were reduced (assuming the engine was off during idling) to adjust each drive cycle. These adjusted drive cycles were then simulated in FASTSim to evaluate their effect on fleet energy consumption and estimate potential energy savings. The original cycles are available for download on this page 
Predicting future CNS risks for astronauts during deep-space missions will rely substantially on ground-based rodent data with space-relevant ions and behaviors. For rats, the accumulated evidence indicates that less densely ionizing radiation, such as 4 He and 12 C ions, induce behavior deficits at lower doses than densely ionizing ions, such as 48 Ti and 56 Fe. However, this observation conflicts with standard somatic radiobiology, in which densely ionizing ions are generally more effective than less densely ionizing ions, and where the DNA/nucleus is the accepted target for radiation-induced tumorigenesis, cytogenetic aberrations, genetic mutations, and reproductive cell death. To gain deeper insight into the subcellular nature of the radiation targets for behavior risks, we compared the effects of dose, fluence, and linear energy transfer (LET) of 4 He and 56 Fe particles using existing datasets for four distinct behavioral outcomes in rats: elevated plus maze (EPM-anxiety), novel object recognition (NOR-memory), operant responding (OR-response to environmental stimuli), and attentional set-shifting (ATSET-cognitive flexibility). We confirmed that less densely ionizing particles (except protons) showed ~100-fold lower threshold doses than densely ionizing particles for behavioral deficits (0.1–1 cGy for 4 He vs. 15–100 cGy for 56 Fe). However, when analyzed by fluence the behavioral responses converged, indicating that 4 He and 56 Fe were equally effective on a per-track basis. When analyzed by LET, there were ~100-fold differences in the LET for maximum effectiveness for behavioral deficits and DNA endpoints (~1 vs ~100 keV/μm, respectively). These unique features of radiation-induced behavioral deficits (high sensitivity to particles in the 1-keV/μm range, insensitivity to protons in the 0.2 keV/μm range, and isofluence dependence for particles with LET>1 keV/μm) provide evidence in support of a new hypothesis of sub-micron sized radiosensitive targets for behavioral effects consistent with the thickness of plasma membranes and/or small subcellular structures, smaller than a whole synapse. Like our behavior findings, mouse immature oocyte killing which is known to have a plasma membrane target was also better explained by fluence, rather than dose. In contrast, fluence analyses for DNA/nuclear endpoints in somatic cells (e.g., tumor induction, chromosome aberrations) showed opposite results, suggesting that behavior targets are not DNA. Our findings raise questions regarding the identity of subcellular targets and the multi-cellular functional unit for behavior risks, low-dose susceptibility, and generalizability from rat to other species and astronauts.
Considering occupancy patterns is crucial to simulate buildings' energy use. Current energy models use inputs that simplify the actual diversity in occupancy into static occupancy patterns and are not able to represent the numerous variations in occupancy patterns between buildings and across different locations. Recently, inferring occupancy schedules from metered electricity consumption data was used to model occupancy in commercial buildings. However, the translation from metered data to occupancy schedules requires many assumptions that might not capture the reality, and the process is hindered by the availability of data from advanced metering infrastructure. With the development of information technologies, occupancy modeling should not be limited to traditional approaches. The prevalence of social networks and location services with real-time user feedback provides publicly accessible data via Maps Application Programming Interfaces (APIs) such as Google Maps, SafeGraph, Mapbox, Foursquare, etc. This paper presents an automated framework for modeling parametric occupancy patterns using such APIs to calibrate commercial district buildings' energy models. This process includes three main steps: data extraction and processing, parametric schedules generation, and schedules integration. We demonstrated this framework in districts where we used maps API to generate more accurate behavioral patterns for operations and electric vehicle charging events. We used these patterns to determine differences in energy use across key sociodemographic and spatial parameters. The presented method has the potential for worldwide applications. Users can utilize this framework to extract data for selected locations of interest to create more realistic behavioral patterns for commercial facilities across different districts.
Launch operations engineers at the Kennedy Space Center have identified an Integrated Refrigeration and Storage system as a promising technology to reduce launch costs and enable advanced cryogenic operations. This system uses a close cycle Brayton refrigerator to remove energy from the stored cryogenic propellant. This allows for the potential of a zero loss storage and transfer system, as well and control of the state of the propellant through densification or re-liquefaction. However, the behavior of the fluid in this type of system is different than typical cryogenic behavior, and there will be a learning curve associated with its use. A 400 liter research cryostat has been designed, fabricated and delivered to KSC to test the thermo fluid behavior of liquid oxygen as energy is removed from the cryogen by a simulated DC cycle cryocooler. Results of the initial testing phase focusing on heat exchanger characterization and zero loss storage operations using liquid oxygen are presented in this paper. Future plans for testing of oxygen densification tests and oxygen liquefaction tests will also be discussed. KEYWORDS: Liquid Oxygen, Refrigeration, Storage
Improved high energy capacity designs for lithium ion batteries are described that take advantage of the properties of high specific capacity anode active compositions and high specific capacity cathode active compositions. In particular, specific electrode designs provide for achieving very high energy densities. Furthermore, the complex behavior of the active materials is used advantageously in a radical electrode balancing design that significantly reduced wasted electrode capacity in either electrode when cycling under realistic conditions of moderate to high discharge rates and/or over a reduced depth of discharge.
Effective thermal management systems, designed to handle the impacts of thermal runaway (TR) and to prevent cell-to-cell propagation, are key to safe operation of lithium-ion (Li-ion) battery assemblies. Critical factors for optimizing these systems include the total energy released during a single cell TR event and the fraction of the total energy that is released through the cell casing vs. through the ejecta material. A unique calorimeter was utilized to examine the TR behavior of a statistically significant number of 18650-format Li-ion cells with varying manufacturers, chemistries, and capacities. The calorimeter was designed to contain the TR energy in a format conducive to discerning the fractions of energy released through the cell casing vs. through the ejecta material. Other benefits of this calorimeter included the ability to rapidly test of large quantities of cells and the intentional minimization of secondary combustion effects. High energy (270 Wh/kg) and moderate energy (200 Wh/kg) 18650 cells were tested. Some of the cells had an imbedded short circuit (ISC) device installed to aid in the examination of TR mechanisms under more realistic conditions. Other variations included cells with bottom vent (BV) features and cells with thin casings (0.22 1/4m). After combining the data gathered with the calorimeter, a statistical approach was used to examine the probability of certain TR behavior, and the associated energy distributions, as a function of capacity, venting features, cell casing thickness and temperature.
Heat recuperation in an ISRU reactor system involves the recovery of heat from a reacted regolith batch by transferring this energy into a batch of fresh regolith. One concept for a hydrogen reduction reactor is a concentric chamber design where heat is transferred from the inner, reaction chamber into fresh regolith in the outer, recuperation chamber. This concept was tested and analyzed to define the overall benefit compared to a more traditional single chamber batch reactor. Data was gathered for heat-up and recuperation in the inner chamber alone, simulating a single chamber design, as well as recuperation into the outer chamber, simulating a dual chamber design. Experimental data was also used to improve two analytical models, with good agreement for temperature behavior during recuperation, calculated mass of the reactor concepts, and energy required during heat-up. The five tests, performed using JSC-1A regolith simulant, also explored the effectiveness of helium gas fluidization, hydrogen gas fluidization, and vibrational fluidization. Results indicate that higher hydrogen volumetric flow rates are required compared to helium for complete fluidization and mixing, and that vibrational fluidization may provide equivalent mixing while eliminating the need to flow large amounts of excess hydrogen. Analysis of the total energy required for heat-up and steady-state operations for a variety of conditions and assumptions shows that the dual-chamber concept requires the same or more energy than the single chamber concept. With no clear energy savings, the added mass and complexity of the dual-chamber makes it unlikely that this design concept will provide any added benefit to the overall ISRU oxygen production system.
The lifecycle assessment (LCA) framework is widely applied to comprehensively evaluate and improve the environmental performance of a circular economy (CE). The advances and application of LCA has been primarily restricted to evaluate the environmental performance of the CE at a micro-level, wherein the CE is implemented for a single product system. However, the CE can be operationalized at two broader levels: the meso–level (for eco-industrial parks) and the macro-level (for a city, state, or nation). Six methodological challenges emerge when applying LCA to a meso- or macro-level CE and remain unaddressed in the existing literature. This includes: selecting a relevant system boundary and functional unit, addressing data paucity and uncertainty, accounting for stakeholder behavior, assessing the trade-offs from renewable energy (RE) use, accounting for manufacturing and technology evolution, and quantifying displacement and rebound. This article proposes potential solutions and research priorities to address the above challenges.
Avalanching nanoparticles (ANPs) are a new class of lanthanide-based upconverting material demonstrating steep optical nonlinearities with the potential to advance applications ranging from subwavelength bioimaging to neuromorphic computing, nanothermometry, and pressure transduction. Here, we use single-nanocrystal imaging to uncover design-dependent heterogeneity in ANP threshold intensity (I th ). Quantitative comparisons between distributions of I th and ANP shell properties reveal correlations between mean I th values, histogram widths, and nanocrystal shell thickness. Evaluating avalanching behaviors using an established model of shell-dependent surface energy transfer shows that variations in shell thickness-and the resultant energy transfer through the shell to the surface and environment-are likely the primary contributor to ANP-to-ANP I th heterogeneity. Further, nanocrystals with an ~6 nm average shell thickness show I th heterogeneity beyond the extent expected from statistical measurements of shell size and variability using transmission electron microscopy (TEM). Here these results provide a principal guide for the design and application of ANPs to environmental sensing.
This project advances the development and application of the TEMPO transportation energy systems model to support DOE analysis of evolving mobility futures. Recent work has focused on improving model transparency, performance, and fidelity through a redesigned software architecture and updated technology adoption scenarios aligned with the latest data and assumptions. Ongoing efforts aim to expand TEMPO's ability to assess transportation affordability and consumer decision-making, including vehicle ownership dynamics and distributional impacts across households. These enhancements position TEMPO to better inform policy and R&D decisions by providing more behaviorally realistic and policy-relevant insights into transportation energy use, technology adoption, and system-level outcomes.
Accelerated temperature tests, calculating temperature behavior of hazard rates and activation energy from failure data using computer simulation
A biaxial tester was used to obtain precise biaxial stress responses of highly filled, high strain capability elastomers. Stress-relaxation experiments show that the time-dependent part of the relaxation response can be reasonably approximated by a function which is strain and biaxiality independent. Thus, isochronal data from the stress-relaxation curves can be used to determine the stored energy density function. The complex behavior of the elastomers under biaxial deformation may be caused by dewetting.
The High performance Antiproton Trap (HiPAT) research project was initiated by the Marshall Space Flight Center's propulsion Research Center to examining the fundamental behavior of low energy antiprotons. Stored antiproton would ultimately be used for experimental demonstration of basic propulsive concepts. Matter-antimatter annihilation produces approximately 10(exp 8) MJ/g nearly 10 orders of magnitude more energy per unit mass than chemical based combustion, hence NASA's interest. To achieve containment, HiPAT utilizes a type of electromagnetic bottle know as a Penning trap positioned within an ultrahigh vacuum test section. Recently, the HiPAT hardware configuration has been enhanced to facilitate the capture of multiple normal matter ion burst. This endeavor is often referred to as "stacking" and used to increasing the number of captured particles. A prior normal matter experimental effort, successfully demonstrated the effectiveness of single burst capture. The stacking process is accomplished by manipulating the electric field generated by the confinement electrodes i.e. adjusting the well potential depth. These potential well values are initially configured to maximize the quantity of captured ions per burst; shallow wells with a depth of 100 volt or less (referenced to the incoming ion beam energy) are typically selected. Once captured, a cooling interval is required to reduce the energy of trapped particles below the lower extent of the "trap door" (or leading electrode) ion emitting potential. This is necessary such that a new burst of hot ions can be introduced while preventing those already inside from escaping. The cooling time is driven by a combination of mechanisms such as synchrotron radiation, background gas scattering, and resistive damping in a time scale on the order of minutes. A potential for reducing this hold period is to actively manipulate the electric field shape, using the power supply control system, to produce a deeper potential well. The trapped ions ride down the morphing well to a lower potential energy, leaving margin to once again cycle the "trap door" capturing a new burst while limiting the number of escaping ions. By adjusting the magnitude and timing of the potential well shaping, subsequent shots from the ion beam can be captured on a time scale shorter then that dictated by the standard inject, capture and cool technique. Currently, experimental tests are under way examining the functionally of this system for stacking multiple ions bursts within the HiPAT system.
Two gold-base active metal brazes (gold-ABA and gold-ABA-V) were evaluated for oxidation resistance to 850 C, and used to join yttria-stabilized zirconia (YSZ) to a corrosion-resistant ferritic stainless steel for possible use in solid oxide fuel cells. Thermogravimetric analysis and optical microscopy and scanning electron microscopy coupled with energy-dispersive spectroscopy were used to evaluate the braze oxidation behavior, and microstructure and composition of the YSZ/braze/steel joints. Both gold-ABA and gold-ABA-V exhibited nearly linear oxidation kinetics at 850 C, with gold-ABA-V showing faster oxidation than gold-ABA. Both brazes produced metallurgically sound YSZ/steel joints due to chemical interactions of Ti and V with the YSZ and steel substrates.
A lighter, more robust airframe design is required to withstand the loading inherent to next generation non cylindrical commercial airliners. The Pultruded Rod Stitched Efficient Unitized Structure concept, a highly integrated composite design involving a stitched and co-cured substructure, has been developed to meet such requirements. While this structure has been shown to meet the demanding out-of-plane loading requirements of the flat-sided pressurized cabin design, there are concerns that the stiff co-cured details will result in relatively high acoustic radiation efficiencies at frequencies well below the thin skin acoustic coincidence frequency. To address this concern and establish a set of baseline vibroacoustic characteristics, a representative test panel was fabricated and a suite of tests were conducted that involved measurements of panel vibration and radiated sound power during point force and diffuse acoustic field excitations. Experimental results are shown and compared with Finite Element and Statistical Energy Analysis model predictions through the use of modal and energy correlation techniques among others. The behavior of the structure subject to turbulent boundary layer excitation is also numerically examined.
Time-varying dark energy is often modeled in observational analyses through generic parameterizations of its equation of state w(z), which typically use two free parameters {w 0 , w a } to span a broad range of behaviors as a function of redshift. However, this broad range of behaviors can only approximately capture the dynamics of any given microphysical theory of dark energy. A complementary approach is to use targeted parameterizations designed to model specific classes of dynamical dark energy with greater precision. Focusing on the class of thawing dark energy, we quantify and compare the precision with which nineteen generic and targeted parameterizations can capture the dynamics of physically motivated thawing quintessence theories. We find that a targeted parameterization derived from a Padé expansion of w is the most reliable of these, producing accurate reconstructions of w(z), the expansion history H(z), and cosmological parameters such as H 0 and Ω m for a broad range of microphysical theories.