Life test of 50 AH NiH2 battery
Life cycle testing on a battery is reported. The cells were built in 1975, put into battery in 1976, and flown in 1977 in low Earth orbit.
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Life cycle testing on a battery is reported. The cells were built in 1975, put into battery in 1976, and flown in 1977 in low Earth orbit.
This report focuses on second-order digital phase-locked loops (DPLLs) with uniformly sampled input, an amplitude-insenstive phase extractor and a conventional loop filter.
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Immersion freezing, initiated by ice-nucleating particles (INPs) in supercooled aqueous droplets, plays an important role in the formation of ice crystals within clouds. The efficiency of immersion freezing depends strongly on INP composition and, crucially, on the mixing state – how chemical species are distributed across the particle population. Here, we quantify the impact of aerosol mixing state on immersion freezing using a combined theoretical and particle-resolved modeling approach. We derive analytical expressions for the frozen fraction of internally and externally mixed INP populations based on classical nucleation theory, showing that the frozen fraction is sensitive to whether ice-active species are present in all particles or only in a subset of the population. We introduce a multi-species immersion freezing scheme into the particle-resolved model PartMC, using the water activity-based immersion freezing model (ABIFM) to compute freezing probabilities for mixed-composition particles. To improve computational efficiency, we implement a Binned Tau-Leaping algorithm and demonstrate an order-of-magnitude speedup with minimal accuracy loss. Simulations reproduce the analytical trends in limiting cases and extend the analysis to more general aerosol populations, where mixing state continues to exert a substantial control on frozen fraction. Sensitivity analyses across particle size, species type, and cooling condition reveal that the mixing state effect is most pronounced when small amounts of highly efficient INPs are mixed with less efficient materials. These findings underscore the need to represent aerosol mixing state explicitly in models of heterogeneous ice nucleation to reduce uncertainty in cloud-phase partitioning.
Raman spectra of glasses and glass-ceramics in the Y2O3-Al2O3-B2O3 system are reported. Glasses with B2O3 contents ranging from 40 to 60 mole percent were prepared by melting 20 g of the appropriate oxide or carbonate powders in alumina crucibles at 1400 C for 45 minutes. Subsequent heat treatments of the glasses at temperatures ranging from 600 to 800 C were performed in order to induce nucleation and crystallization. It was found that Na2CO3 added to the melt served as a nucleating agent and resulted in uniform bulk crystallization. The Raman spectra of the glasses are interpreted primarily in terms of vibrations of boron - oxygen structural groups. Comparison of the Raman spectra of the glass-ceramic samples with spectra of aluminate and borate crystalline materials reveal that these glasses crystallize primarily as yttrium aluminum borate, YAl3(BO3)4.
This paper addresses the problem of building trust in online predictions of the remaining available flying time for two different electric Unmanned Aerial Vehicles (eUAVs) powered by lithium-ion-polymer batteries. Flight tests for various automation research missions for the two vehicles were monitored using two on-board battery health management applications to make predictions of the remaining flying time (RFT) for each eUAV and to predict the state of the battery. Playback of the voltage, current and temperature profiles of the battery discharge were used to assess the accuracy of the estimation of the voltage and the charge states of the models as well as the estimate of the RFT. The reference ground truth values were the observed landing time and the measured battery pack resting pack voltage 20 minutes after the flight. The predicted RFT, state of charge (SoC), and state of energy (SoE) were compared with the observed results. Noise values of one standard deviation from the mean values of the internal charge states of the battery model during a reference run were used to vary the states during simulation. One application used an equivalent circuit model of the electrical dynamics of the battery pack, and the other application used a reduced-order electrochemistry model. The variation of the model state components was compared to the variation in the estimate of the RFT and the variation in the SoE to estimate a confidence factor. Variation in the estimates caused by factors affecting the off-line laboratory parameter identification experiments is considered. Variation in the estimates due to environmental factors are discussed.
Indoor radon accounts for 37% of population-level exposure to ionizing radiation in the United States. However, radon metrics are typically reported at coarse spatial scales, potentially obscuring meaningful local variation. We developed a high-resolution modeling framework to estimate indoor radon concentrations across Utah while explicitly quantifying predictive uncertainty. A total of 19,497 residential radon measurements collected between 2006 and 2017 were combined with environmental and housing characteristics and analyzed using a geospatial neural network that accommodates spatial dependence and nonlinear associations. Predictions were generated on a uniform hexagonal grid at 0.73 km2 resolution (H3 level 8). Out-of-sample predictions aggregated to the H3 level 8 grid showed good agreement with observed concentrations (Pearson r=0.64), while household-level predictions exhibited more moderate agreement (r=0.45). The model produced well-calibrated uncertainty estimates, with 24.1% of held-out observations exceeding the predicted 75th-percentile threshold. Maps of predicted radon concentrations and the probability of exceeding the U.S. EPA action level of 148 Bq/m3 (4 pCi/L) revealed substantial fine-scale spatial heterogeneity that was not apparent in conventional coarse-resolution summaries, with greater local variability observed in densely monitored urban counties than in sparsely sampled regions. High-resolution radon models that explicitly quantify uncertainty provide a useful framework for characterizing the spatial distribution of indoor radon and identifying areas of elevated exceedance risk. These findings highlight the value of fine-scale monitoring data and uncertainty-aware modeling approaches for radon exposure assessment, environmental risk characterization, and radon-related health research.
A series of tests were performed to characterize battery performance relating to certain operating parameters which include charge current, discharge current, temperature, and pressure. The parameters were varied to confirm battery design concepts and to determine optimal operating conditions.
As the Space Community endeavors to reach new heights of human exploration, materials for extreme environments are at the forefront of research. One class of materials of particular focus are polymer aerogels; lightweight solids with nanoscale pore size, high internal surface area, and extremely high porosities. These interesting properties allow aerogels to act as superior thermal insulators, IR scattering filters, sensor platforms, and vibro-acoustic mitigating materials. Polymer aerogels also have the potential to combat issues found in lunar environments such as dust and radiation mitigation. Herein, past and present research, synthesis, and applications of polymer aerogels will be discussed.
High temperature battery development - zeolites, anode and cathode couples, and molten salts
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This work demonstrates a series of functionalization methods to enhance the utility of thermoplastic-elastomer derived ordered mesoporous carbons, including chemical activation, heteroatom doping, and the introduction of nanoparticles.