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From Preface: This document is a compendium of Risk/Requirements Tradeoff Guidelines for Faster, Better, Cheaper missions. It summarizes the reduced-cost approach for the design, verification, and validation of flight equipment for assuring mission success of microspacecraft.
From preface: This document is a compendium of Risk/Requirements Tradeoff Guidelines for Faster, Better, Cheaper Missions. It summarizes the reduced-cost approach for the design, verification, and validation of flight equipment for assuring mission success of microspacecraft.
The focus in solar system exploration has shifted to a faster, better, cheaper approach featuring focused, technically sophisticated, fast track missions.
We investigate small deviation probabilities of the cumulative sum of independent positive random variables, the common distribution of which decreases at zero not faster than exponential function.
The building envelopes contributes significantly to the energy-efficiency of the building. Building performance simulation has made it possible to compare façade technologies regarding energy demand, daylighting, thermal and visual comfort in detail. Planners, such as architects and engineers, need experience to find product data with the right quality and level of detail, and to process the data to fit the calculation and the application. In the available time, planners can compare only a limited number of products, which means that better solutions could go unnoticed. This paper presents a new concept for making product data easily accessible for building façade planning. The concept consists of a network of databases for the efficient exchange and use of optical and calorimetric data of glazing units, shading devices, and combinations of both. The paper presents the research questions, an analysis of the current challenges, six design goals for the product data network and its implementation together with a discussion. Many product data sources can be connected to many planning software applications via the specified application programming interface. When planning software connects to the product data network, the planning of building envelopes can be much faster because planners do not need to spend so much time to search and process product data manually. The planning of building envelopes can also become much easier, especially for planners with limited experience. They do not need to understand all the details about which data fits which calculation if the software company implements this. The planning of building envelopes can become much more reliable when software companies validate their use of the product data network, because the current manual process is prone to errors. The planning of building envelopes can also improve because more products can be compared in the available time, allowing better solutions to be found.
Here, the possibility to save and process information in fundamentally indistinguishable states is the quantum mechanical resource that is not encountered in classical computing. I demonstrate that, if energy constraints are imposed, this resource can be used to accelerate information-processing without relying on entanglement or any other type of quantum correlations. In fact, there are computational problems that can be solved much faster, in comparison to currently used classical schemes, by saving intermediate information in nonorthogonal states of just a single qubit. There are also error correction strategies that protect such computations.
Here, the lithium-excess Li x Ni 2-4x/3 Sb x/3 O 2 (LNSO) materials were previously shown to demonstrate higher capacities and improved cyclability with increasing lithium content. While the performance trend is promising, observed capacities are much lower than theoretical capacities, pointing to a need for further understanding of active redox processes in these materials. In this work, we study the electrochemical behavior of the LNSO materials as a function of lithium content and at slow and fast rates. Surprisingly, Li 1.15 Ni 0.47 Sb 0.38 O 2 (LNSO-15) exhibits higher discharge capacities at faster rates and traverses distinct voltage curves at slow and fast rates. To understand these two peculiarities, we characterize the redox activity of nickel, antimony, and oxygen at different rates. While experiments confirm some nickel redox activity and oxygen loss, these two mechanisms cannot account for all observed capacity. We propose that the balance of the observed capacity may be due reversible oxygen redox and that the rate-dependent voltage curve features may derive from irreversible nickel migration occurring on slow charge. As future high energy density cathodes are likely to contain both lithium excess and high nickel content, both of these findings have important implications for the development of novel high capacity cathode materials.
To date, slow Set operation speed and high Reset operation power remain to be important limitations for substituting dynamic random access memory by phase change memory. Here, we demonstrate phase change memory cell based on Ti0.4Sb2Te3 alloy, showing one order of magnitude faster Set operation speed and as low as one-fifth Reset operation power, compared with Ge2Sb2Te5-based phase change memory cell at the same size. The enhancements may be rooted in the common presence of titanium-centred octahedral motifs in both amorphous and crystalline Ti0.4Sb2Te3 phases. The essentially unchanged local structures around the titanium atoms may be responsible for the significantly improved performance, as these structures could act as nucleation centres to facilitate a swift, low-energy order-disorder transition for the rest of the Sb-centred octahedrons. Our study may provide an alternative to the development of high-speed, low-power dynamic random access memory-like phase change memory technology.
Water transit times strongly influence water quality, temperature, and seasonal hydrologic response of river systems. How water transit times may shift under future climates remains unconstrained, especially in mountainous regions experiencing rapid snowpack declines. Here, we estimated historical (2006–2013) and future (2086–2093) water transit times in five headwater catchments within the U.S. Pacific Northwest using sequential precipitation input tagging within the Water Tracer enabled version of the Weather Research and Forecasting Hydrologic model. Our results indicate water transit times are 18% (35–64 days) faster on average under the Representative Carbon Pathways (RCP) 8.5 climate scenario due to shifts in rain-snow partitioning, with higher fractions of younger water in the wet season and older water in the dry season. These results suggest shifts in rain-snow partitioning in snowmelt dominated catchments of the Pacific Northwest will shorten water transit times leading to likely impacts on regional water quality, temperature, and hydrologic seasonality.
Here, a model mixed-conducting polymer, blended with an amphiphilic block-copolymer, is shown to yield systems with drastically enhanced electro-chemical doping kinetics, leading to faster electrochemical transistors with a high transduction. Importantly, this approach is robust and reproducible, and should be readily adaptable to other mixed conductors without the need for exhaustive chemical modification.
The use of 1/f noise measurements is explored for the purpose of finding faster techniques for electromigration (EM) characterization in advanced microelectronic interconnects, which also enable a better understanding of its underlying physical mechanisms. Three different applications of 1/f noise for EM characterization are explored. First, whether 1/f noise measurements during EM stress can serve as an early indicator of EM damage. Second, whether the current dependence of the noise power spectral density (PSD) can be used for a qualitative comparison of the defect concentration of different interconnects and consequently also their EM lifetime t50. Third, whether the activation energies obtained from the temperature dependence of the 1/f noise PSD correspond to the activation energies found by means of classic EM tests. In this paper, the 1/f noise technique has been used to assess and compare the EM properties of various advanced integration schemes and different materials, as they are being explored by the industry to enable advanced interconnect scaling. More concrete, different types of copper interconnects and one type of tungsten interconnect are compared. The 1/f noise measurements confirm the excellent electromigration properties of tungsten and demonstrate a dependence of the EM failure mechanism on copper grain size and distribution, where grain boundary diffusion is found to be a dominant failure mechanism.
ABSTRACT We present our 500 pc distance-limited study of stellar flares using the Dark Energy Camera as part of the Deeper, Wider, Faster programme. The data were collected via continuous 20-s cadence g-band imaging and we identify 19 914 sources with precise distances from Gaia DR2 within 12, ∼3 deg2, fields over a range of Galactic latitudes. An average of ∼74 min is spent on each field per visit. All light curves were accessed through a novel unsupervised machine learning techniques designed for anomaly detection. We identify 96 flare events occurring across 80 stars, the majority of which are M dwarfs. Integrated flare energies range from ∼1031–1037 erg, with a proportional relationship existing between increased flare energy with increased distance from the Galactic plane, representative of stellar age leading to declining yet more energetic flare events. In agreement with previous studies we observe an increase in flaring fraction from M0 to M6 spectral types. Furthermore, we find a decrease in the flaring fraction of stars as vertical distance from the galactic plane is increased, with a steep decline present around ∼100 pc. We find that $\sim 70{{\ \rm per\ cent}}$ of identified flares occur on short time-scales of <8 min. Finally, we present our associated flare rates, finding a volumetric rate of 2.9 ± 0.3 × 10−6 flares pc−3 h−1.
The Deeper, Wider, Faster (DWF) program coordinates observations with telescopes across the electromagnetic spectrum, searching for transients on time-scales of milliseconds to days. The tenth DWF observing run was carried out in near real-time during September 2021, and consisted of six consecutive days of observations of the NGC 6744 galaxy group and a field containing the repeating fast radio burst FRB 190711 with the Australian Square Kilometre Array Pathfinder, the Dark Energy Camera, the Hard X-ray Modulation Telescope, and the Parkes 64-m ‘Murriyang’ radio telescope. Here, in this work, we present the results of an image-domain search for transient, variable, and circularly polarized sources carried out with ASKAP, using data from the observing run along with test observations prior to the run and follow-up observations carried out during and after the run. We identified eight variable radio sources, consisting of one pulsar, six stellar systems (five of which exhibit circularly polarized emission), and one previously uncatalogued source. Of particular interest is the detection of pulses from the ultra-cool dwarf SCR J1845–6357 with a period of 14.2 ± 0.3 h in good agreement with the known optical rotation period, making this the slowest rotating radio-loud ultra-cool dwarf discovered.
Observations in Earth’s turbulent magnetosheath downstream of a quasiparallel bow shock reveal a prevalence of electron-scale current sheets favorable for electron-only reconnection where ions are not coupled to the reconnecting magnetic fields. In small-scale turbulence, magnetic structures associated with intense current sheets are limited in all dimensions. And since the coupling of ions are constrained by a minimum length scale, the dynamics of electron reconnection is likely to be 3D. Here, both 2D and 3D kinetic particle-in-cell simulations are used to investigate electron-only reconnection, focusing on the reconnection rate and associated electron flows. A new form of 3D electron-only reconnection spontaneously develops where the magnetic X-line is localized in the out-of-plane (z) direction. The consequence is an enhancement of the reconnection rate compared with two dimensions, which results from differential mass flux out of the diffusion region along z, enabling a faster inflow velocity and thus a larger reconnection rate. This outflow along z is due to the magnetic tension force in z just as the conventional exhaust tension force, allowing particles to leave the diffusion region efficiently along z unlike the 2D configuration.
Physics-of-Failure (PoF) based reliability assessment for photovoltaic (PV) inverters requires long-duration electrical and electrothermal stress histories, yet generating such stress histories with high-fidelity switching models over year long mission profiles is computationally prohibitive. Conventional methods either sacrifice modeling fidelity for speed or require runtimes that are impractical for design iteration and uncertainty studies. To address this bottleneck, this paper presents a High-Performance Computing (HPC) based simulation frame work for faster-than-real-time reliability-oriented simulation. The proposed framework integrates the Average-to-Switching (A2S) method with parallel computing techniques to accelerate switching-level waveform reconstruction. We further introduce optimization strategies, including cluster merging and sensitivity based mission profile screening, to reduce the computational burden. Evaluated using real-world mission profile inputs and a MATLAB/Simulink switching-model reference, the framework reduces the simulation time for a one-year mission from an intractable multi-year duration to approximately 7.3 minutes while maintaining low waveform error. This acceleration provides a practical reliability-oriented simulation engine that can be coupled with component-specific aging models for subsequent PV inverter PoF assessment.
Abstract Increases in atmospheric carbon dioxide (CO 2 ) concentrations are expected to lead to increases in the rate of tree biomass accumulation, at least temporarily. On the one hand, trees may simply grow faster under higher CO 2 concentrations, preserving the allometric relations that prevailed under lower CO 2 concentrations. Alternatively, the allometric relations themselves may change. In this study, the effects of elevated CO 2 (eCO 2 ) on tree biomass and allometric relations were jointly assessed. Over 100 trees, grown at Duke Forest, NC, USA, were harvested from eight plots. Half of the plots had been subjected to CO 2 enrichment from 1996 to 2010. Several subplots had also been subjected to nitrogen fertilization from 2005 to 2010. Allometric equations were developed to predict tree height, stem volume, and aboveground biomass components for loblolly pine ( Pinus taeda L.), the dominant tree species, and broad‐leaved species. Using the same diameter‐based allometric equations for biomass, it was estimated that plots with eCO 2 contained 21% more aboveground biomass, consistent with previous studies. However, eCO 2 significantly affected allometry, and these changes had an additional effect on biomass. In particular, P. taeda trees at a given diameter were observed to be taller under eCO 2 than under ambient CO 2 due to changes in both the allometric scaling exponent and intercept. Accounting for allometric change increased the treatment effect of eCO 2 on aboveground biomass from a 21% to a 27% increase. No allometric changes for the nondominant broad‐leaved species were identified, nor were allometric changes associated with nitrogen fertilization. For P. taeda , it is concluded that eCO 2 affects allometries, and that knowledge of allometry changes is necessary to accurately compute biomass under eCO 2 . Further observations are needed to determine whether this assessment holds for other taxa.
Revealing the contributions of genes to plant phenotype is frequently challenging because loss-of-function effects may be subtle or masked by varying degrees of genetic redundancy. Such effects can potentially be detected by measuring plant fitness, which reflects the cumulative effects of genetic changes over the lifetime of a plant. However, fitness is challenging to measure accurately, particularly in species with high fecundity and relatively small propagule sizes such as Arabidopsis thaliana. An image segmentation-based method using the software ImageJ and an object detection-based method using the Faster Region-based Convolutional Neural Network (R-CNN) algorithm were used for measuring two Arabidopsis fitness traits: seed and fruit counts. The segmentation-based method was error-prone (correlation between true and predicted seed counts, r 2 = 0.849) because seeds touching each other were undercounted. By contrast, the object detection-based algorithm yielded near perfect seed counts (r 2 = 0.9996) and highly accurate fruit counts (r 2 = 0.980). Comparing seed counts for wild-type and 12 mutant lines revealed fitness effects for three genes; fruit counts revealed the same effects for two genes. Our study provides analysis pipelines and models to facilitate the investigation of Arabidopsis fitness traits and demonstrates the importance of examining fitness traits when studying gene functions.
This data package contains the data and code to use and run the Water Tracer enabled version of the Weather Research and Forecasting Hydrologic model (WT-WRF-Hydro) with the Sequential Precipitation Input Tagging (SPIT) framework. It is associated with the publication “Shifts in Rain-Snow Partitioning Drive Faster Water Transit Times in the US Pacific Northwest” published in Scientific Reports (Butler et al., 2026; https://doi.org/10.1038/s41598-026-46539-1). We use the Continental U.S. (CONUSII; Rasmussen et al., 2021) dataset to force the model with an historical climate (2006–2013) and a future climate (2086–2093) with a representative carbon pathway (RCP) 8.5 scenario. We use the model to calculate water transit times in five headwater catchments within the U.S. Pacific Northwest. We also show key hydrologic and environmental variables that affect water transit times and changes in the future. Finally, we use observed data to validate the model such as stream water isotopes, snowpack characteristics, and stream discharge. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. The data package consists of 11 folders: (1) "Figures" contains the exported figures used in the manuscript; (2) "Model_Isotope_Date" contains the WT-WRF-Hydro isotope date used in model validation; (3) “Model_Outputs_Future” contains the WT-WRF-Hydro future climate outputs; (4) “Model_Outputs_Historical” contains the WT-WRF-Hydro historical climate outputs; (5) “Model_Outputs_Weights_Areas” contains the WT-WRF-Hydro weights per catchment used to calculate water transit times and isotopes in stream water; (6) “MODIS_data_scripts” contains data used to validate snow conditions in the study area; (7) “Observed_Flow_Data” contains the observed streamflow data used in model validation; (8) “Observed_Isotope_Data” contains the observed stream water isotope data used in model validation; (9) “Scripts” contains the Python scripts used to general results and the figures; (10) “Statistic_Outputs” contains the water transit time statistical outputs reported in this manuscript; (11) “Validation_SNOTEL” contains the SNOTEL data used in model validation. The files in this data package have the following file extensions: .tif, .txt, .csv, .pdf, .py, .jpg, and .png.