Numerical investigation of the structure of a randomly advected Huygens front using a minimal stochastic model
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SEARCH · Engineering Papers
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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In the three funded years of research (and one additional year of no-cost extension), we focused on several areas of interest towards the goal of reducing the content of PGMs in emission control catalysts.
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Condensed version of SAND2024-14972C for 10 minute presentation at APS March Meeting 2025 (aka Global Physics Summit)
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Note that this submission includes a pre-recording of talk to be given at STOC'25. This recording is required of the conference, as per the conference website: https://acm-stoc.org/stoc2025/cfp-stoc2025.html Video link: https://drive.google.com/file/d/1iaYeFooCUTv9h_81hLVvOhTPDjeU01KA/view?usp=sharing
Designing electric lighting systems to meet circadian lighting requirements may raise light levels and consequently energy use compared to existing practices. To reduce energy use, electric lighting can be controlled to be dimmed or turned off when sufficient daylight levels are available in space. This requires input from one or a few critical measurement points. However, it is unclear how critical points can be determined to ensure that all occupants receive the needed light levels while reducing electric lighting energy. This paper discusses three approaches for selecting critical points and utilizes annual daylight simulations modified to account for sky spectra, and coupled with spectral electric lighting simulations. Among the three evaluated approaches, the use of continuous daylight autonomy (modified to use EML measured at eye positions) is helpful for estimating electric lighting energy for dimmable electric lighting systems, and for identifying energy-saving strategies.
Motion primitives allow for application of discrete search algorithms to rapidly produce trajectories in complex continuous space. The maneuver automaton (MA) provides an elegant formulation for creating a primitive library based on trims and maneuvers. However, performance is fundamentally limited by the contents of the primitive library. If the library is too sparse, performance can be poor in terms of path cost, whereas a library that is too large can increase run time. This work outlines new methods for using genetic algorithms to prune a primitive library. The proposed methods balance the path cost and planning time while maintaining the reachability of the MA. The genetic algorithm in this paper evaluates and mutates populations of motion primitive libraries to optimize both objectives. Here, we illustrate the performance of these methods with a simulated study using a nonlinear medium-fidelity F-16 model. We optimize a library with the presented algorithm for obstacle-free navigation and a nap-of-the-Earth navigation task. In the obstacle-free navigation task, we show a tradeoff of a 10.16% higher planning cost for a 96.63% improvement in run time. In the nap-of-the-Earth task, we show a tradeoff of a 9.712% higher planning cost for a 92.06% improvement in run time.
Poplar and other woody feedstocks have the potential to provide up to 200 million tons of biomass per year that could be converted to liquid fuels. Most forestry strategies that aim at increasing biomass productivity per hectare rely on short rotation plantations of fast-growing varieties. The improvement of wood density as a key trait itself has largely been overlooked. We evaluated natural variation in wood density across a population of genetically diversePopulus trichocarpatrees grown in a common garden. Wood density varies greatly within this population but is heritable higher wood density was not systematically associated with reduced growth, challenging assumptions of a trade-off between wood density and biomass accumulation. Furthermore, denser wood led to significant improvements throughout the supply chain, including, lowering biomass production and transportation costs. Higher density not correlate to changes in biomass composition. Density did not impact bioconversion in the two feedstock-to-fuel pipelines tested (pretreatment by ionic liquids or soaking in aqueous ammonia, and fermentation to ethanol) on a representative subset of poplars. These findings highlight wood density as a promising breeding target for accelerating the development of high-yielding, conversion-efficient bioenergy crops and as an avenue for increasing land-use efficiency and reducing biomass transportation cost. This data set contain three datasets.
Ebola virus (EBOV), a member of the Filoviridae family of viruses and a causative agent of Ebola Virus Disease (EVD), is a highly pathogenic virus that has caused over twenty outbreaks in Central and West Africa since its formal discovery in 1976. The only FDA-licensed vaccine against Ebola virus, rVSV-ZEBOV-GP (Ervebo®), is efficacious against infection following just one dose. However, since this vaccine contains a replicating virus, it requires ultra-low temperature storage which imparts considerable logistical challenges for distribution and access. Additional vaccine candidates could provide expanded protection to mitigate current and future outbreaks. Here, we designed and characterized two multimeric protein nanoparticle subunit vaccines displaying 8 or 20 copies of GPΔmucin, a truncated form of the EBOV surface protein GP. Single-dose immunization of mice with GPΔmucin nanoparticles revealed that neutralizing antibody levels were roughly equivalent to those observed in mice immunized with non-multimerized GPΔmucin trimers. These results suggest that some protein subunit antigens do not elicit enhanced antibody responses when displayed on multivalent scaffolds and can inform next-generation design of stable Ebola virus vaccine candidates.
Recent evaluations of counter-based periodic testing strategies for fault detection in Microprocessor (μP) have shown that only a small set of counters is needed to provide complete coverage of severe faults. Severe faults are defined as faults that leak sensitive information, e.g., an encryption key on the output of a serial port. Alternatively, fault detection can be accomplished by executing instructions that periodically test the control and functional units of the μP. In this paper, we propose a fault detection method that utilizes an ’engineered’ executable program combined with a small set of strategically placed counters in pursuit of a hardware Periodic Built-In-Self-Test (PBIST). We analyze two distinct methods for generating such a binary; the first uses an Automatic Test Generation Pattern (ATPG)-based methodology, and the second uses a process whereby existing counter-based node-monitoring infrastructure is utilized. We show that complete fault coverage of all leakage faults is possible using relatively small binaries with low latency to fault detection and by utilizing only a few strategically placed counters in the μP.
To further the development of low-enriched uranium fuels, precedence has been placed on delivering the same amount of power while lowering the fuel temperature and radial temperature gradient. To address this, modeling efforts have resulted in a novel design featuring conductive fins of varying thermal conductivities and geometries inserted into the fuel matrix. These conductive inserts were not allowed to exceed 6% of the original fuel volume. This constraint was imposed due to other designs displacing 10% of fuel volume. A parametric study was performed that consisted of 2.56 million BISON simulations involving varying fin characteristics (i.e., fin thermal conductivity, number, and geometry) to determine the optimal geometric configuration for a desired amount of fuel volume displaced. The results from this study show that the thickness and length of each fin affect the fuel temperature and temperature gradient more than varying the number and thermal conductivity of the fins. The parametric study resulted in the development of an optimized combination to produce the lowest peak fuel temperature, lowest radial temperature gradient, and highest temperature reduction for the amount of original fuel volume displaced. The simulations presented in this work will eventually be compared with irradiation experiments of similar fuel designs at Idaho National Laboratory’s Advanced Test Reactor.
We report on experimental investigation of thermal contact resistance, RC, of the noncuring graphene thermal interface materials with the surfaces characterized by different degree of roughness, Sq. It is found that the thermal contact resistance depends on the graphene loading, ξ, non-monotonically, achieving its minimum at the loading fraction of ξ ~15 wt%. Decreasing the surface roughness by Sq~1 μm results in approximately the factor of ×2 decrease in the thermal contact resistance for this graphene loading. The obtained dependences of the thermal conductivity, KTIM, thermal contact resistance, RC, and the total thermal resistance of the thermal interface material layer on ξ and Sq can be utilized for optimization of the loading fraction of graphene for specific materials and roughness of the connecting surfaces. Our results are important for the thermal management of high-power-density electronics implemented with diamond and other wide-band-gap semiconductors.
The process of phosphate desorption from soils is difficult to measure using stirred batch techniques because of the accumulation of desorbed ions in a bathing solution. To accurately measure the apparent rate coefficient of phosphate desorption from soils, it is necessary to remove the desorbed ions. In this study, a novel hybrid (i.e., iron oxide coated) anion exchange resin was used as a sink to study long-term (seven days) P desorption kinetics in intensively managed agricultural soils in the Midwestern U.S. (total phosphorus (TP): 196–419 mg/kg). The phosphate desorption kinetics in the hybrid anion exchange resin method were compared with those in the other conventional batch desorption method with pure anion exchange resins or without any sink. The extent of P desorption in the hybrid resin methods was >50% of total desorbed phosphate in the other methods. The initial kinetic rate estimated in the pseudo-second-order kinetic model was also highest (3.03–31.35 mg/(g·hr)) in the hybrid resin method when the same soil system was compared. This is because adsorbed P in the hybrid resins was nearly irreversible. The hybrid anion exchange resin might be a new and ideal sink in measuring the P desorption process in soils and sediments
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Incorporating battery electric buses into bus fleets faces three primary challenges: a BEB’s extended refuel time, the cost of charging, both by the consumer and the power provider, and large compute demands for planning methods. When BEBs charge, the additional demands on the grid may exceed hardware limitations, so power providers divide a consumer’s energy needs into separate meters even though doing so is expensive for both power providers and consumers. Prior work has developed a number of strategies for computing charge schedules for bus fleets; however, prior work has not worked to reduce costs by aggregating meters. Additionally, because many works use mixed integer linear programs, their compute needs make planning for commercial-sized bus fleets intractable. This work presents a multi-program approach to computing charge plans for electric bus fleets. The proposed method solves a series of subproblems where the solution to the charge problem becomes more refined with each problem, moving closer to the optimal schedule. The results demonstrate how runtimes are reduced by using intermediate subproblems to refine the bus charge solution so that the proposed method can be applied to large bus fleets of 100+ buses. Not only will we demonstrate that runtimes scale linearly with the number of buses but we will also show how the proposed method scales to large bus fleets of over 100 buses while managing the monthly cost of energy.
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