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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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Examines the performance and cost of pairing variable renewable energy (VRE) sources with compressed air energy storage and hydrogen production through PEM electrolysis. Sensitivities were performed on H2 cost, PEM electrolyzer capital cost, and hydrogen cavern capital cost. The analysis shows that the cost of VRE has the most impact on the overall cost results.
This report presents a study of collar compression for the wells at the Bryan Mound site. The study includes a comprehensive review of all available Multi-Arm Caliper (MAC) logs from the site, which has been used to identify specific wells that are experiencing casing restrictions at collar joints. Additional site-wide analysis of Bryan Mound well temperature data, proximity to sulphur wells, pulsed eddy current (PEC) logs, and a general spatial analysis has been included.
We worked out the design of a high repetition rate MeV energy ultrafast electron diffraction instrument based on the existing Cornell photoinjector, which can readily be applied to the presented findings. This example is a blueprint of other similarly arranged UED setups. Using particle tracking simulations in conjunction with multiobjective genetic algorithm optimization, we explored the smallest bunch lengths, emittance, and probe spot sizes achievable. As two limits, we defined stroboscopic conditions (with single electrons per pulse) and operation with 10 5 electrons per bunch which may be suitable for single-shot diffraction images. In the stroboscopic case, the flexibility provided by the many cavity bunching and acceleration allows for longitudinal phase space linearization without a higher harmonic field, providing sub-fs bunch lengths at the sample. Given low emittance photoemission conditions, these small bunch lengths can be maintained with probe transverse sizes at the single micron (1 μm) scale and below. In the case of 10 5 electrons per pulse, we simulated state-of-the-art 5D brightness conditions: rms bunch lengths of 10 fs with 3-nm normalized emittances, while permitting repetition rates as high as 1.3 GHz. We showed that in conjunction with collimating apertures, a novel focusing scheme achieves very high-quality emittance compensation for the central core of the beam composing 40% of particles, for a resulting beam size of 5 μm (rms). Finally, to aid in the design of new SRF-based ultrafast electron diffraction machines, we simulated the trade-off between the number of cavities used and achievable bunch length and emittance. In the longitudinal dimension, we made use of the fact that MeV UED requires much lower energy than the 15-MeV maxi mum energy of Cornell’s CBETA injector, and we may therefore use several of the SRF cavities for bunch length compression. In practice, we used a genetic optimization algorithm to choose the phases and amplitudes of the cavities appropriately for optimal bunching. In the zero space charge case, we found that bunching and acceleration are distributed across the six cavities in a way that produces a linearizing effect. And we showed that the ultimate bunch length can be limited by time-of-flight differences arising from transverse size and transverse momentum spread. The space charge code developed and used for this development is now permanent part of the Bmad accelerator simulation code and has already contributed to other developments, e.g., for the EIC electron cooler design.
Researchers at West Virginia University completed a multi-year project under DE-FE0031865 entitled “Methane Mitigator – Development of a Scalable Vent Mitigation Strategy to Simultaneously Reduce Methane Emissions and Fuel Consumption from the Compression Industry”. An assessment of natural gas production site emission sources was completed to quantify the potential for emissions reductions and reductions in fuel consumption. The main sources of fugitive methane emissions at gas productions sites include condensate tanks, produced water tanks, gas compressor packing vents, pneumatic controller vents, and natural gas engine crankcase vents.
Environmental sampling methods developed by the Savannah River National Laboratory (SRNL) employ collectors with sorbent media tubes set at various locations to collect airborne emissions. Laboratory analyses of these tubes results in one-dimensional signals regarding what chemicals are being released and transported within the atmosphere. The analysis process is time consuming especially when analyzing a full year’s worth of tubes (hourly sample collection results in nearly 9,000 tubes per year). Using a signal processing method such as compressed sensing allows for recreation of the full signal while greatly reducing the number of analyzed samples required. Due to the sparsity of data retrieved from the air tubes, it is possible to use measurements a fraction of the size of the original data to gain much of the same information. This would improve the overall time and cost of analysis when modeling one-dimensional sampling signals.
This project investigated the use of a Centrifugal Particle Separation (CPS) system to improve the durability and operational reliability of outdoor heat exchangers in vapor-compression based heating, ventilation, air conditioning, and refrigeration (HVACR) systems. The developed method introduced a novel dust and fouling mitigation approach by integrating an ambient air pre-cleaner that employs centrifugal forces to remove particulate matter from incoming air before it reaches the heat exchanger. By reducing the accumulation of dust and debris on coil surfaces, the CPS system aims to lower maintenance requirements and extend equipment lifespan. The project specifically involves coupling a centrifugal air pre-cleaner with a single-zone ductless mini-split system and evaluating its effectiveness in maintaining cleaner coil surfaces. Additionally, the study examined the impact of CPS integration on system energy performance. Through controlled experimental testing and performance monitoring, this work seeks to validate CPS-based air pre-cleaning as a practical, efficient solution for mitigating outdoor coil dust accumulation and fouling in both residential and commercial HVACR applications.
Environmental sampling methods developed by the Savannah River National Laboratory (SRNL) employ collectors with sorbent media tubes set at various locations to collect airborne emissions. Laboratory analyses of these tubes results in one-dimensional signals regarding what chemicals are being released and transported within the atmosphere. The analysis process is time consuming especially when analyzing a full year’s worth of tubes (hourly sample collection results in nearly 9,000 tubes per year). Using a signal processing method such as compressed sensing allows for recreation of the full signal while greatly reducing the number of analyzed samples required. Due to the sparsity of data retrieved from the air tubes, it is possible to use measurements a fraction of the size of the original data to gain much of the same information. This would improve the overall time and cost of analysis when modeling one-dimensional sampling signals.
The growing demand for hybrid polymer composites with multifunctional properties has led to the development of various hybridization techniques, such as multi-material compounding and controlled laminate stacking sequence. In this study, a novel hybrid manufacturing approach was used by integrating a multiplexing extrusion system (MExS) based on additive manufacturing with subsequent compression molding process. This technique enabled the co-extrusion of different materials during the additive manufacturing process to fabricate composites with tailored performance. The developed hybrid composite featured a skin layer of glass fiberreinforced polycarbonate (PC/GF) encapsulating a carbon fiber-reinforced acrylonitrile butadiene styrene (CF/ABS) core. The structure was engineered to promote improved thermal and impact resistance at the surface, supported by a stiff core for enhanced overall mechanical integrity. Mechanical, thermal and morphological properties of the hybrid composites were investigated to understand trade-offs in performance compared to a single-material system. The results demonstrate that this approach enables the production of multifunctional composites suitable for applications such as automotive body panels and protective housings, where a balance of weight, mechanical strength, and thermal performance is essential.
We present particle-in-cell simulations with Monte Carlo collisions of fusion burn waves in compressed deuterium–tritium and proton–boron plasmas. We study the energy balance in the one-dimensional expansion of a hot-spot by simulating Coulomb collisions, fusion reactions, and bremsstrahlung emission with a Monte Carlo model and inverse bremsstrahlung absorption using a new PIC model. This allows us to self-consistently capture the alpha particle heating and radiative losses in the expanding hot-spot and surrounding cold fuel. After verifying our model in a code-to-code comparison with both kinetic and fluid codes for the case of a deuterium–tritium hot-spot, we simulate the expansion of a proton–boron hot-spot initialized at 200 keV and 1,000 g/cm 3 . Our model predicts that energy radiated by the hot-spot is recaptured by the surrounding high-density opaque fuel reducing the expansion work done by the propagating burn wave. As a result, we find the net fusion energy produced over the course of $20$~ps is twice the initial hot-spot energy independent of whether radiation physics is included.
Polydimethylsiloxane (PDMS) is known for its exceptional mechanical properties, chemical stability, and flexibility. Recent advancements have focused on developing functional PDMS composites by integrating various functional fillers, including polymers, ceramics, and metals, for advanced applications such as electronics, medical devices, and aerospace. Consequently, there is a growing need to investigate PDMS composites to achieve higher filler loadings offering enhanced mechanical performance. This study addresses this need by utilizing the high molecular weight (MW) PDMS resin we have developed, offering its high elongation capacity of up to >6500%. We incorporated boron (B), hollow glass microballoons (HGMs), and tungsten-coated hollow glass microballoons (WHGMs) into the developed high MW PDMS. The resulting composites demonstrated excellent elastic properties and significant compression resilience (35–80%) and elastic modulus (1.28–10.15 MPa) at high filler loadings (~60 vol.%). Specifically, B/PDMS composites achieved up to 67.6 vol.% of B, HGM/PDMS composites held up to 68.6 vol.% of HGM, and WHGM/PDMS composites incorporated up to 54.0 vol.% of WHGM. These findings highlight the potential of high MW PDMS for developing high-performance PDMS composites suitable for advanced applications such as aerospace, automotive, and medical devices.
Abstract Recent observations by the Parker Solar Probe (PSP) suggest that protons and heavier ions are accelerated to high energies by magnetic reconnection at the heliospheric current sheet (HCS). By solving the energetic particle transport equation in large-scale MHD simulations, we study the compression acceleration of protons and heavier ions in the reconnecting HCS. We find that the acceleration of multispecies ions results in nonthermal power-law distributions with a spectral index consistent with the PSP observations. Our study shows that the high-energy cutoff of protons can reach E max ∼ 0.1 –1 MeV depending on the particle diffusion coefficients. We also study how the high-energy cutoff of different ion species scales with the charge-to-mass ratio E max ∝ ( Q / M ) α . When determining the diffusion coefficients from the quasi-linear theory with a Kolmogorov magnetic power spectrum, we find that α ∼ 0.4, which is somewhat smaller than α ∼ 0.7 observed by PSP.
Data from SNS bunch compression experiments; presented at NAPAC 2025, IMCC 2025, USMCC 2025.
Contains results on simulations of a Mach 2 expansion compression ramp which mirrors work done in the Tri Sonic Wind tunnel.
In this work we present a comprehensive investigation of state-of-the-art closure models employed to represent interphase momentum, thermal, and work exchange between the gas and particulate phases for Euler–Lagrange (EL) simulations in shock-driven flows. A complete list of closures for the force, torque, heat transfer, and work exchange models is provided. In particular, the present work includes a stochastic closure for the particle-to-particle variation in the quasi-steady force and a deterministic closure for particle-to-particle variation in the added mass force in an EL framework. These variations arise due to the presence of neighboring particles and particle–particle interactions. To investigate the importance of each closure term, we carry out fully three-dimensional simulations for a planar shock propagating over a random bed of inert particles. The primary goal is to evaluate the role of each closure term on the gas dynamic features (such as transmitted and reflected shock locations) and particle curtain features (such as upstream and downstream curtain locations). To this end, thirteen cases are considered, with each case progressively including a closure model with the goal to identify and quantify its contribution to the simulated dynamics. We show that the volume fraction dependence of the mean force models plays an important role in generating wave-like instabilities that lead to concentration bands. In addition, fluctuations in quasi-steady and added mass forces primarily decrease the internal instabilities that tend to enhance local volume fraction variations. Particle rotation is primarily due to inter-particle collisions, is generally weak, and does not play an important role in the translational dynamics for the present configuration. Inter-phase heat transfer has a strong effect on gas phase temperature, slows down the transmitted and reflected shocks, and decreases the width of the curtain. Furthermore, the absence of a work-coupling model fails to conserve the total energy, greatly under-predicts the gas temperature which in turn affects the particle dynamics.
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Secondary high explosives (HEs) exhibit rich microstructure that promotes the formation of hot spots responsible for detonation initiation, but the role of microstructural interfaces remains poorly quantified. To this end, we develop extensions for the generalized crystal-cutting method (GCCM) to prepare molecular dynamics (MD) simulation cells containing grain boundaries (GBs) and other crystal–crystal interfaces with prescribed tilt and twist orientations. Using the GCCM, we perform MD simulations of shock interactions with a GB between the (001) and (100) crystal facets in the secondary HE TATB (1,3,5-triamino-2,4,6-trinitrobenzene). Our MD simulations reveal a strong directional dependence to the formation of a hot spot at the GB interface. In particular, transmission of the shock from the (001) grain to the (100) grain yields a hot spot in the (100) grain at the GB interface, whereas no hot spot is produced when an equivalent shock transits the GB in the opposite direction. We trace the origin of this GB anisotropy to three dominant factors: (1) the intrinsic differences in shock-deformation mechanisms and wave structures for the bulk (100) and (001) grains, which leads to distinct geometries and mechanical impedances upon shock arrival to the GB depending on which grains are donor or acceptor for the transmitted shock; (2) the different time intervals separating the initial shock rise and the formation of steady wave structures in the respective donor–acceptor configurations; and (3) the differences in time scales required to re-establish local thermal equilibrium. Interfacial hot spots form when these factors combine to impede development of a steady two-wave structure and instead induce a localized, pseudosingly shocked region that undergoes a higher rate of work production (resulting in a higher temperature) compared to when the steady two-wave structure develops further from the interface. The extensions to the GCCM approach presented here are anticipated to facilitate a wide range of MD studies that focus on understanding the role of crystal–crystal interfaces in molecular materials.
We present an Atomic Cluster Expansion (ACE) machine learned potential developed for high-fidelity atomistic simulations of hydrocarbons, targeting pressures and temperatures near and above supercritical fluid regimes for molecular fluids. A diverse set of stoichiometries were covered in training, including 1:0 (pure carbon), 1:4 (methane), and 1:1 (benzene), and rich bonding environments sampled at supercritical temperatures, hydrogen rich, reactive mixtures where metastable stoichiometries arise, including 1:2 (ethylene) and 1:3 (ethane). A high-fidelity training database was constructed by performing large-scale quantum molecular dynamic simulations [density functional theory (DFT) MD] of diamond, graphite, methane, and benzene. A novel approach to selecting structures from DFT MD is also presented, which allows for the rapid selection of unique DFT MD frames from complex trajectories. Comparisons to DFT and experimental data demonstrate that the presented ACE potential accurately reproduces isotherms, carbon melting curves, radial distribution functions, and shock Hugoniots for carbon and hydrocarbon systems for pressures up to 100 GPa and temperatures up to 6000 K for hydrocarbon systems and up to 9000 K for pure carbon systems. This work delivers a potential that can be used for accurate, large-scale simulations of shocked hydrocarbons and demonstrates a methodology for fitting and validating machine learning interatomic potentials to complex molecular environments, which can be applied to energetic materials in future works.