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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 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

GPS Space Service Volume: Ensuring Consistent Utility Across GPS Design Builds for Space Users

GPS availability and signal strength originally specified for users on or near surface of Earth with transmitted power levels specified at edge-of-Earth, 14.3 degrees. Prior to the SSV specification, on-orbit performance of GPS varied from block build to block build (IIA, IIRM, IIF) due to antenna gain and beam width variances. Unstable on-orbit performance results in significant risk to space users. Side-lobe signals, although not specified, were expected to significantly boost GPS signal availability for users above the constellation. During GPS III Phase A, NASA noted significant discrepancies in power levels specified in GPS III specification documents, and measured on-orbit performance. To stabilize the signal for high altitude space users, NASA DoD team in 2003-2005 led the creation of new Space Service Volume (SSV) definition and specifications.

Volume↗
NASA NTRSDate not supplied

Lunar Latitude and Terrain Radiator Sensitivity Study

The thermal environment on the moon is highly complex and diverse. The lunar surface near the equator develops extreme hot average temperatures during the lunar day due to solar flux vectors that are nearly orthogonal to the surface. The lunar poles have a cold and uniquely complex thermal environment with low solar elevation angles and permanently shadowed regions located just kilometers from some of the most highly illuminated regions of the moon. Likewise, the topography can range from very flat crater basins to dramatically tall features such as mountains and crater rims. Consequently, when sizing the radiators of a lunar surface vehicle, the specific thermal environment found in the targeted landing or deployment zone must be well understood to build robust appropriately scaled thermal control systems. Here described are parametric studies that characterize the sensitivity of lunar radiator performance to lunar terrain and latitude. Heat rejection is calculated for different radiator tilt angles in a variety of terrain environments. Radiator performance as a function of underside thermal condition is also characterized at lunar latitudes ranging from equatorial to polar. Impacts of latitude and terrain on radiator performance are quantified, and regions are identified where the thermal environment is more or less favorable for specific radiator designs.

Lunar Vehicle Radiator↗
NASA NTRSDate not supplied

Lunar Latitude and Terrain Radiator Sensitivity Study

The thermal environment on the moon is highly complex and diverse. The lunar surface near the equator develops extreme hot average temperatures during the lunar day due to solar flux vectors that are nearly orthogonal to the surface. The lunar poles have a cold and uniquely complex thermal environment with low solar elevation angles and permanently shadowed regions located just kilometers from some of the most highly illuminated regions of the moon. Likewise, the topography can range from very flat crater basins to dramatically tall features such as mountains and crater rims. Consequently, when sizing the radiators of a lunar surface vehicle, the specific thermal environment found in the targeted landing or deployment zone must be well understood to build robust, appropriately scaled thermal control systems. Here described are parametric studies that characterize the sensitivity of lunar radiator performance to lunar terrain and latitude. Heat rejection is calculated for different radiator tilt angles in a variety of terrain environments. Radiator performance as a function of underside thermal condition is also characterized at lunar latitudes ranging from equatorial to polar. Impacts of latitude and terrain on radiator performance are quantified, and regions are identified where the thermal environment is more or less favorable for specific radiator designs.

Lunar Vehicle Radiator↗
NASA NTRSDate not supplied

Lunar Latitude and Terrain Radiator Sensitivity Study

The thermal environment on the moon is highly complex and diverse. The lunar surface near the equator develops extreme hot average temperatures during the lunar day due to solar flux vectors that are nearly orthogonal to the surface. The lunar poles have a cold and uniquely complex thermal environment with low solar elevation angles and permanently shadowed regions located just kilometers from some of the most highly illuminated regions of the moon. Likewise, the topography can range from very flat crater basins to dramatically tall features such as mountains and crater rims. Consequently, when sizing the radiators of a lunar surface vehicle, the specific thermal environment found in the targeted landing or deployment zone must be well understood to build robust, appropriately scaled thermal control systems. Here described are parametric studies that characterize the sensitivity of lunar radiator performance to lunar terrain and latitude. Heat rejection is calculated for different radiator tilt angles in a variety of terrain environments. Radiator performance as a function of underside thermal condition is also characterized at lunar latitudes ranging from equatorial to polar. Impacts of latitude and terrain on radiator performance are quantified, and regions are identified where the thermal environment is more or less favorable for specific radiator designs.

Lunar Thermal Analysis↗
NASA NTRSDate not supplied

Lunar Latitude and Terrain Radiator Sensitivity Study

The thermal environment on the moon is highly complex and diverse. The lunar surface near the equator develops extreme hot average temperatures during the lunar day due to solar flux vectors that are nearly orthogonal to the surface. The lunar poles have a cold and uniquely complex thermal environment with low solar elevation angles and permanently shadowed regions located just kilometers from some of the most highly illuminated regions of the moon. Likewise, the topography can range from very flat crater basins to dramatically tall features such as mountains and crater rims. Consequently, when sizing the radiators of a lunar surface vehicle, the specific thermal environment found in the targeted landing or deployment zone must be well understood to build robust appropriately scaled thermal control systems. Here described are parametric studies that characterize the sensitivity of lunar radiator performance to lunar terrain and latitude. Heat rejection is calculated for different radiator tilt angles in a variety of terrain environments. Radiator performance as a function of underside thermal condition is also characterized at lunar latitudes ranging from equatorial to polar. Impacts of latitude and terrain on radiator performance are quantified, and regions are identified where the thermal environment is more or less favorable for specific radiator designs.

Lunar Vehicle Radiator↗
DOE OSTI2022

Modularity-at-scale for advanced reactors presentation

Modularity options have been limited for traditional nuclear energy deployment due to the conventional light water reactor (LWR) safety requirements, such as high pressure retaining heavy and robust containment structures. However, a relatively new regulatory approach called ‘Functional Containment’ has potential to allow less expensive and more flexible designs for non-LWRs. Functional containment provides flexibility in design and deployment based on risk-informed and performance-based criteria, so that reactors are not over-designed. Non-nuclear industry has successfully used modular design approaches in automotive, aerospace, chemical processing, building construction, and ship building. These industries have shown that modular construction reduces construction time by around 30% - 50% compared to the conventional stick-built approach. The nuclear industry can use similar approaches to reduce construction time and costs, balanced with safety requirements, using the functional containment approach. This paper discussing the background of modularity in nuclear energy, examples of less learned, modularity approaches in non-nuclear industries and the potential of cost and schedule savings through the emerging regulatory design flexibilities potentially enabling combination of modular deployment at different scales.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Building Durable Multimetallic Electrocatalysts from Intermetallic Seeds

When combined with earth-abundant metals, Pt-based alloy nanoparticles (NPs) can be cost-effective electrocatalysts. However, these NPs can experience leaching of non-noble-metal components under harsh electrocatalytic conditions. In this work, the Skrabalak group has demonstrated a novel NP construct in which Pt-based random alloy surfaces are stabilized against non-noble-metal leaching by their deposition onto intermetallic seeds. These core@shell NPs are highly durable electrocatalysts, with the ability to tune catalytic performance by the core@shell architecture, surface alloy composition, and NP shape. This versatility was demonstrated in a model system in which random alloy (ra-) PtM surfaces were deposited onto ordered intermetallic (i-) PdCu seeds using seed-mediated co-reduction (SMCR). In the initial demonstration, ra-PtCu shells were deposited on i-PdCu seeds, with these core@shell NPs exhibiting higher specific and mass activities for the oxygen reduction reaction (ORR) when compared to similarly sized ra-PtCu NPs. These NPs also showed outstanding durability, maintaining ~85% in specific activity after 5000 cycles. Characterization of the NPs after use revealed minimal loss of Cu. The activity enhancement was attributed to the strained surface that arises from the lattice mismatch between the intermetallic core and random alloy surface. The outstanding durability was attributed to the ordered structure of the intermetallic core. The origin of this durability enhancement was investigated by classical molecular dynamics simulations, where Pt atoms were found to have a lower potential energy when deposited on an intermetallic core than when deposited on a random alloy core. Also, ordering of Cu atoms at the core@shell interface appears to enhance the overall binding between the core and the shell materials. Inspired by this initial demonstration, SMCR has been used to achieve shells of different random alloy compositions, PtM (M = Ni, Co, Cu, or Fe). This advance is significant because ligand effects vary as a function of PtM identity and Pt/M ratio. These features also influence the degree of surface strain imparted from the lattice mismatch between the core and shell materials. Like the initial demonstration, standout features of these core@shell NPs were high durability and resistance to non-noble metal leaching. Moving forward, efforts have been directed toward integrating shape-control to this core@shell NP construct. This integration is motivated by the shape-dependent catalytic performance of NPs derived from the selective expression of specific facets. Considering the initial i-PdCu@ra-PtCu system, NPs with a cubic shape have been achieved by judicious selection of capping ligands during SMCR. Evaluation of these NPs as catalysts for the electrooxidation of formic acid found that the nanocubic shape enhances catalytic performance compared to similar core@shell NPs with a spherical morphology. We envision that SMCR can be applied to other NP systems to achieve highly durable catalysts as the syntheses of monodisperse and shape-controlled intermetallic seeds are advanced. This Account highlights the role of intermetallic cores in providing more durable electrocatalysts. More broadly, the versatility of SMCR is highlighted as a route to integrate architecture, alloy surfaces, and shape within one NP system, and how this achievement is inspiring new high-performance and robust catalysts is discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Production of Astatine-211 for Translational Science in Radiotherapy (Research Performance Progress Report)

In this proposal we outline the methods to improve the isotope production of astatine-211 at the University of Pennsylvania Cyclotron Facility. Astatine-211 is an isotope that emits alpha- radiation and has high potential for treating otherwise untreatable cancers. The goal of this proposal is two fold, 1) Optimize current production of astatine-211 and maintain routine production and 2) develop new isotope production target systems and chemical isolation systems. By completing this proposal we will ensure that the University of Pennsylvania Cyclotron Facility continues to build it’s isotope program in an effort that unites under DOE isotope network supply initiatives with the overall goal of increasing the national supply of isotopes. The University of Pennsylvania is uniquely located in the northeast corridor of the United States of America and has access to dozens of institutions that could use astatine-211 in their research. With the support of the DOE we have the opportunity to provide additional momentum to this growing field of research and will be able to provide the foundation for economical development of astatine-211 research and application in medicine.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
NASA NTRS2010

Mission Reliability Estimation for Repairable Robot Teams

A mission reliability estimation method has been designed to translate mission requirements into choices of robot modules in order to configure a multi-robot team to have high reliability at minimal cost. In order to build cost-effective robot teams for long-term missions, one must be able to compare alternative design paradigms in a principled way by comparing the reliability of different robot models and robot team configurations. Core modules have been created including: a probabilistic module with reliability-cost characteristics, a method for combining the characteristics of multiple modules to determine an overall reliability-cost characteristic, and a method for the generation of legitimate module combinations based on mission specifications and the selection of the best of the resulting combinations from a cost-reliability standpoint. The developed methodology can be used to predict the probability of a mission being completed, given information about the components used to build the robots, as well as information about the mission tasks. In the research for this innovation, sample robot missions were examined and compared to the performance of robot teams with different numbers of robots and different numbers of spare components. Data that a mission designer would need was factored in, such as whether it would be better to have a spare robot versus an equivalent number of spare parts, or if mission cost can be reduced while maintaining reliability using spares. This analytical model was applied to an example robot mission, examining the cost-reliability tradeoffs among different team configurations. Particularly scrutinized were teams using either redundancy (spare robots) or repairability (spare components). Using conservative estimates of the cost-reliability relationship, results show that it is possible to significantly reduce the cost of a robotic mission by using cheaper, lower-reliability components and providing spares. This suggests that the current design paradigm of building a minimal number of highly robust robots may not be the best way to design robots for extended missions.

Trebi-Ollennu, Ashitey↗
DOE OSTI2021

A machine learning approach to galaxy properties: joint redshift–stellar mass probability distributions with Random Forest

We demonstrate that highly accurate joint redshift–stellar mass probability distribution functions (PDFs) can be obtained using the Random Forest (RF) machine learning (ML) algorithm, even with few photometric bands available. As an example, we use the Dark Energy Survey (DES), combined with the COSMOS2015 catalogue for redshifts and stellar masses. We build two ML models: one containing deep photometry in the griz bands, and the second reflecting the photometric scatter present in the main DES survey, with carefully constructed representative training data in each case. We validate our joint PDFs for 10 699 test galaxies by utilizing the copula probability integral transform and the Kendall distribution function, and their univariate counterparts to validate the marginals. Benchmarked against a basic set-up of the template-fitting code bagpipes, our ML-based method outperforms template fitting on all of our predefined performance metrics. In addition to accuracy, the RF is extremely fast, able to compute joint PDFs for a million galaxies in just under 6 min with consumer computer hardware. Such speed enables PDFs to be derived in real time within analysis codes, solving potential storage issues. As part of this work we have developed galpro 1, a highly intuitive and efficient python package to rapidly generate multivariate PDFs on-the-fly. galpro is documented and available for researchers to use in their cosmology and galaxy evolution studies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Powering Data Centers with Clean Energy: A Techno-Economic Case Study of Nuclear and Renewable Energy Dependability

Rising data demands from artificial intelligence (AI) and large language models (LLMs) generating images, videos, and text have prompted increased need for larger and more robust data centers in the United States. Major companies interested in these larger data centers face the choice of linking them to existing regional grids, building stand-alone power supplies onsite, or a combination of both. The request, review, and approval process for new transmission lines to grids in the United States, however, has grown in recent years to times spans rivaling those of new construction for nuclear power plants. Building an islanded power supply for each data center is therefore becoming a prominent option. In this case study, several technologies are modeled in techno-economic simulations for long-term system costs subject to fixed electricity demand from a singular data center. A 250 MWe data center is assumed with additional 50 MWe for resiliency. Techno-economic simulations are conducted using the Holistic Energy Resource Optimization Network (HERON) software, which is a part of the Framework for Optimization of Resources and Economics (FORCE) tool suite. Technologies considered include solar, wind, lithium-ion batteries, and several types of nuclear reactors: large-scale reactors, small modular reactors, and microreactors. A low- and high-cost estimate for each technology is assumed to develop a range of expected economic performance. Low-cost estimates included several clean energy production tax credits. Different combinations of renewable energy generators with nuclear reactors are considered, ranging from a fully renewable-powered data center to a fully nuclear-powered data center. Historic time series of wind and solar availability from the Texas grid are used to train a reduced order model; this model then generates unique time series with similar characteristics of the training dataset. Multiple scenarios of weather and subsequent operations are simulated for each renewable-nuclear combination to determine total costs throughout the project lifetime. Fully renewable-powered configurations required large amounts of installed capacity (GW scale) in the simulations to meet the fixed demand of the data center. This is due to some scenarios in the historical dataset which captured low-wind and low-solar days, requiring over-building of these technologies as well as batteries to compensate for the low amounts of electricity generation. Fully nuclear-powered configurations outperformed the fully renewable and mixed renewable-nuclear configurations in terms of cost, with ranges between $1B and $10B in 2023 USDs compared to $40B+ for fully renewable configurations. Of the nuclear technologies, small modular reactors performed better economically than large-scale nuclear models due to lower projected capital costs, and both performed better than the microreactor models. These results demonstrate the applicability of firm, dispatchable electricity resources from baseload generators like nuclear power plants for operating facilities that run at constant power without daily variability.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

SAXS Assistant: Automated SAXS analysis for structural discovery in biologics and polymeric nanoparticles

Small-angle x-ray scattering (SAXS) is a powerful technique for assessing macromolecular structure. High-throughput SAXS is limited by the time-consuming and, at times, subjective nature of SAXS data interpretation. Here, we present SAXS Assistant, a Python-based script that streamlines SAXS data analysis to extract features for machine learning (ML) and key structural parameters, including the Guinier radius of gyration (R g ), pair distance distribution function (PDDF)-derived R g , maximum particle dimension (D max ), and Kratky plots. The script builds upon BioXTAS RAW and validates reliability via Guinier/PDDF R g agreement, an important indicator of well-measured data sets. For assistance in D max estimation, a multilayer perceptron regressor was trained with 1940 data files from the Small Angle Scattering Biological Data Bank. The model achieved a test set performance R 2 = 0.90 and mean absolute error = 11.7 Å. Training exclusively with experimental data translates analyses from researchers, including experts in the field, to the ML model, which helps assess D max estimations from PDDF. Gaussian mixture model clustering was implemented to classify profiles into structural classes based on entries in the Small Angle Scattering Biological Data Bank. Users may therefore assess the similarity between experimental samples and known biomolecular shapes within the mapped repository entries. This probabilistic clustering aids in quantifying information from Kratky and generating shape-descriptive features. SAXS Assistant accelerates SAXS data analysis through enforced quality control, ML-ready outputs, and flags for low-confidence results. In addition to providing the ability to analyze large data sets at high throughput, this tool is versatile and may serve researchers in both biological and synthetic polymer research fields.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Laser Beam Welding for in-Space Joining Demonstrated Under Vacuum on the Ground and By Parabolic Flight Experiments

High energy density electron beam welding enabled the first and, to date, only American weld performed in space during the M551 experiment on Skylab in 1973. Though welding is critical to 90% of durable goods manufacturing in America, there is not yet regular and reliable application of welding processes to the In-space Servicing, Assembly, and Manufacturing (ISAM) sector. Fundamental studies are needed to develop basic capabilities and to enhance fundamental process knowledge, which will support follow-on efforts to mature in-space welding for use in commercial, defense, and other aerospace applications. The current work seeks to build on past flights and improve understanding and quantification of materials joining in space conditions using laser beam welding (LBW). LBW offers several advantages over the electron beam welding of Skylab, amongst others: reduced electromagnetic interference, less exposure of operators to ionizing radiation, and flexible delivery through optical fibers supporting unique workpieces and joints. Since there is no orbital laboratory to mature laser beam welding for space, the current effort addresses maturation of laser beam welding through parabolic flights augmented with data collection to enable numerical modeling efforts that capture the physical effects of the space environment. This team has retrofitted an LBW experimental apparatus that can simulate the vacuum and, during a parabolic flight, the reduced gravity & microgravity conditions of in-space welding. A team of Capstone students modified the setup, originally developed by NASA Langley Research Center for electron beam free-form fabrication, to replace its electron gun with a 1 kW, 1070 nm Yb fiber laser. The apparatus was further instrumented with temperature sensing and high-speed welding cameras to monitor and record changes in the thermal state of the workpiece, the melt pool, the laser penetration level, and the development and orientation of spatter & plumes. The system will operate autonomously, demonstrating its utility to uncrewed missions. During upcoming parabolic flight campaigns expected summer 2024, this LBW equipment will weld common aerospace alloys of aluminum, stainless steel, and titanium under conditions representative of the space environment. This data will guide future computational modeling efforts of laser welding in space and help to qualify in-space welding as a viable ISAM technique.

laser beam welding↗
DOE OSTI2022

Electron Cloud Simulations for the Electron-Ion Collider in Brookhaven National Laboratory

For high-intensity circular accelerators and storage rings, if the secondary electron emission yield (SEY) of the vacuum chamber surfaces is high, an EC (Electron Cloud) could build up with the passage of the circulating beam. The presence of EC can strongly affect the beam quality, such as transverse instabilities, transverse emittance growth, and beam loss. Furthermore, the heat load from EC can exceed the available cryogenic capability. For the RHIC superconducting (SC) arc magnets, to be used for the hadron storage ring of the Electron-Ion Collider (EIC), the dynamic heat load budget is 0.5 W/m to the 4.5 K stainless steel beam pipe. This can limit the maximum beam bunches or intensity of the EIC, hence diminishing the luminosity provided by the EIC. The EC has affected the beam instability and significantly contributed to cryogenic heat load in the Large Hadron Collider (LHC). Positron storage rings for which ECs have been a critical factor in the design and performance include KEKB in Japan and EC buildup remains one of the concerns for future high-intensity accelerators design. EC considerations have driven the SuperKEKB collider design and the positron damping ring for the proposed International Linear Collider (ILC). The LHC luminosity upgrade is contingent on reducing the bunch spacing to 25 ns; at this bunch spacing, severe EC buildup has been observed. The success of the upgrade is likely contingent on limiting EC buildup. To study the EC heat load, we did some EC simulations with PyECLOUD code for the dipole, quadrupole, sextupole magnets, and the warm (drift) section of the EIC hadron storage ring. PyECLOUD is an EC simulation code developed by CERN. The code has been validated and used to study EC in the LHC, SPS, and PS. To eliminate EC buildup, the sources of electrons must be minimized. First, we will reduce the production of electrons due to residual gas ionization by specifying the maximum gas density, which requires a vacuum chamber with low electron-stimulated desorption (ESD) yields and a sufficient (preferably distributed) pumping speed. Second, we should reduce the secondary electrons with a lower secondary electron yield (SEY) material.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Dual Phase Soft Magnetic Laminates for Low-cost, Non/Reduced-Rare-Earth Containing Electrical Machines

To accelerate the mass market adoption of electric drive vehicles, the key technology barriers in electric motors are (1) magnet cost and rare-earth element price volatility; (2) non-rare-earth electric motor performance; and (3) materials property optimization. The goal of this project was to address these barriers by advancing a unique and innovative dual phase soft magnetic material technology and demonstrating the material in a 30-kW synchronous reluctance motor without using any permanent magnet for electric vehicles. Dual phase magnetic materials offer the electric motor designer the ability to locally control the magnetic saturation level in a motor laminate, while at the same time enhancing the mechanical strength of the laminate material, resulting in an enhancement in motor performance and efficiency. Scalable dual phase soft magnetic laminates manufacturing technologies were developed in collaboration with multiple US manufacturers. 1000 lbs of alloy sheet with a thickness of 0.25mm and width of 280 mm was manufactured within the specifications. Batch sizes of up to 240 laminates per run were produced from the alloy sheet. Two prototype motors with dual phase soft magnetic laminates were designed, built, and tested. The major goal of building the subscale prototype as a pathway to develop scalable manufacturing technologies for the dual phase soft magnetic laminates was met. The additional goal of building and testing the subscale prototype in order to validate the calculated performance with the tested motor performance was also met. For the full-scale 30kW continuous power synchronous reluctance motor prototype, the tested performance met the targets in terms of continuous power at the operating speeds up to 8000 rpm. Post-test studies were conducted and the root causes for the discrepancy between the predicted and tested peak power, continuous power at high speed range, and efficiency were identified. Further modeling study showed that the dual phase rotor machine has a 27% higher torque to active weight ratio than an equivalent performance silicon steel rotor machine. Application space and multiple discussions with traction motor and electric vehicle manufacturers for commercialization of the dual phase soft magnetic material technology were identified and conducted. An initial cost model was established based on the developed manufacturing technologies with the US manufacturers. Future paths for further cost reduction were identified, including increasing the market volume by broadening the applications of the dual phase soft magnetic laminate technology for electric machines in other energy sections such as oil & gas, heating, ventilation, and air conditioning (HVAC), and power generation.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

High-Efficiency Modular SiC-based Power-Converter for Flexible-CHP Systems with Stability-Enhanced Grid-Support Functions

This project seeks to develop a modular, scalable MV power converter featuring stability-enhanced grid-support functions for future grid-interface applications in flexible combined heat and power (F-CHP) cogeneration plants, being fully compliant with the IEEE Standard 1547, category B—for operation in local areas with high aggregated distributed energy resource (DER) penetration, and also with the IEEE standard for the specification of microgrid controllers, namely IEEE Std 2030.7, with the goal to enable F-CHP systems for both microgrid and standalone applications. Further, the proposed converter will use a modular circuit topology, the MMC, which is scalable both in voltage and current by interconnecting power-cell building blocks, thus flexibly suiting the needs of F-CHP systems in the 1–20 MWe range. Furthermore, the use of 10 kV SiC MOSFET devices will minimize the number of power-cells needed to operate in 2–13.8 kV MV distribution systems, but more importantly, they will render feasible a power conversion efficiency > 98 %, and a power density > 10 kW/l. This is highly relevant given that these are two key performance metrics that will further increase the value of F-CHP systems by shortening the time required to recover their investment costs.

14 SOLAR ENERGY↗
DOE OSTI2025

Enabling Partnership between South Carolina and NREL for Advancing Opportunities in Plastics Recycling Research (EPSCOR for Plastics Recycling)

Proposal Objectives: 1. Utilize depolymerization/fractionation techniques to recover highly processable and reactive feedstocks for polymer synthesis from lignin. 2. Synthesize lignin‐derived non‐isocyanate polyurethane, epoxy, and polyamide using non‐ toxic, biobased route designed for chemical recycling. Characterize resulting materials. 3. Design a high‐yielding chemical recycling process for as‐synthesized materials yielding usable building blocks for many generations of polymer synthesis. 4. Optimize chemical recycling of PET waste for the synthesis of lignin‐based polymers. Compare properties to commercial materials. 5. Optimize reaction conditions and recycling steps to facilitate enhanced sustainability of the synthetic steps and final properties of materials. 6. Complete a lifecycle assessment of lignin utilization and chemical recycling to compare their environmental performance to that of materials produced from virgin material. Identify hot spots and benefits using the chemical recycling process.

36 MATERIALS SCIENCE↗
NASA NTRS1984

Component specific modeling

Modern jet engine design imposes extremely high loadings and temperatures on hot section components. A series of interdisciplinary modeling and analysis techniques which were specialized to address three specific components (combustor burner linings, hollow air-cooled turbine blades, and air-cooled turbine vanes) were developed and verified. These techniques will incorporate data as well as theoretical methods from many diverse areas, including cycle and performance analysis, heat transfer analysis, linear and nonlinear stress analysis, and mission analysis. Building on the proven techniques already available in these fields, the new methods developed will be integrated to predict temperature, deformation, stress, and strain histories throughout a complete flight mission.

Roberts, M. L.↗