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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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We have elicited a reliable Raman spectral signature for glucose in rabbit aqueous humor across mammalian physiological ranges in a rabbit model stressed by recent myocardial infarction.
Objectives were listed for four areas: engineering science, reliability physics, module development, and module performance and failure analysis. The engineering science efforts are to develop module design requirements for large-scale photovoltaic (PV) applications and to develop generic module and array design and construction technology to meet the needed performance, safety, reliability, and system interfaces. The reliability physics effort is to develop the technology for 30-year life modules. The module development efforts are to transfer new technology to PV manufacturers and their products, and to evaluate these advanced modules. The module performance and failure analysis efforts are to determine PV module performance, to identify needed development, and to assess suitability for large-scale use.
Presently there are many opportunities for the application of ceramic materials at elevated temperatures. In the near future ceramic materials are expected to supplant high temperature metal alloys in a number of applications. It thus becomes essential to develop a capability to predict the time-dependent response of these materials. The creep rupture phenomenon is discussed, and a time-dependent reliability model is outlined that integrates continuum damage mechanics principles and Weibull analysis. Several features of the model are presented in a qualitative fashion, including predictions of both reliability and hazard rate. In addition, a comparison of the continuum and the microstructural kinetic equations highlights a strong resemblance in the two approaches.
This paper describes the development of a methodology for sizing Blended-Wing-Body (BWB) transports and how the capabilities of the Flight Optimization System (FLOPS) have been expanded using that methodology. In this approach, BWB transports are sized based on the number of passengers in each class that must fit inside the centerbody or pressurized vessel. Weight estimation equations for this centerbody structure were developed using Finite Element Analysis (FEA). This paper shows how the sizing methodology has been incorporated into FLOPS to enable the design and analysis of BWB transports. Previous versions of FLOPS did not have the ability to accurately represent or analyze BWB configurations in any reliable, logical way. The expanded capabilities allow the design and analysis of a 200 to 450-passenger BWB transport or the analysis of a BWB transport for which the geometry is already known. The modifications to FLOPS resulted in differences of less than 4 percent for the ramp weight of a BWB transport in this range when compared to previous studies performed by NASA and Boeing.
Two problems must be solved if the finite element method is to become a reliable and affordable blackbox engineering tool. Finite element meshes must be generated automatically from computer aided design databases and mesh analysis must be made self-adaptive. The experimental system described solves both problems in 2-D through spatial and analytical substructuring techniques that are now being extended into 3-D.
The next generation of planetary exploration vehicles will rely heavily on robust aero-assist technologies, especially those that include aerocapture. This paper provides an overview of an ongoing development program, led by NASA Langley Research Center (LaRC) and aimed at introducing high-temperature structures, adhesives, and advanced thermal protection system (TPS) materials into the aeroshell design process. The purpose of this work is to demonstrate TPS materials that can withstand the higher heating rates of NASA's next generation planetary missions, and to validate high-temperature structures and adhesives that can reduce required TPS thickness and total aeroshell mass, thus allowing for larger science payloads. The effort described consists of parallel work in several advanced aeroshell technology areas. The areas of work include high-temperature adhesives, high-temperature composite materials, advanced ablator (TPS) materials, sub-scale demonstration test articles, and aeroshell modeling and analysis. The status of screening test results for a broad selection of available higher-temperature adhesives is presented. It appears that at least one (and perhaps a few) adhesives have working temperatures ranging from 315-400 C (600-750 F), and are suitable for TPS-to-structure bondline temperatures that are significantly above the traditional allowable of 250 C (482 F). The status of mechanical testing of advanced high-temperature composite materials is also summarized. To date, these tests indicate the potential for good material performance at temperatures of at least 600 F. Application of these materials and adhesives to aeroshell systems that incorporate advanced TPS materials may reduce aeroshell TPS mass by 15% - 30%. A brief outline is given of work scheduled for completion in 2006 that will include fabrication and testing of large panels and subscale aeroshell test articles at the Solar-Tower Test Facility located at Kirtland AFB and operated by Sandia National Laboratories. These tests are designed to validate aeroshell manufacturability using advanced material systems, and to demonstrate the maintenance of bondline integrity at realistically high temperatures and heating rates. Finally, a status is given of ongoing aeroshell modeling and analysis efforts which will be used to correlate with experimental testing, and to provide a reliable means of extrapolating to performance under actual flight conditions. The modeling and analysis effort includes a parallel series of experimental tests to determine TSP thermal expansion and other mechanical properties which are required for input to the analysis models.
In support of the Space Shuttle Orbiter post-flight inspection, structure temperatures are recorded at selected positions on the windward, leeward, starboard and port surfaces. Statistical analysis of this flight data and a non-dimensional load interference (NDLI) method are used to estimate the thermal reliability at positions were reusable surface insulation (RSI) is installed. In this analysis, structure temperatures that exceed the design limit define the critical failure mode. At thirty-three positions the RSI thermal reliability is greater than 0.999999 for the missions studied. This is not the overall system level reliability of the thermal protection system installed on an Orbiter. The results from two Orbiters, OV-102 and OV-105, are in good agreement. The original RSI designs on the OV-102 Orbital Maneuvering System pods, which had low reliability, were significantly improved on OV-105. The NDLI method was also used to estimate thermal reliability from an assessment of TPS uncertainties that was completed shortly before the first Orbiter flight. Results fiom the flight data analysis and the pre-flight assessment agree at several positions near each other. The NDLI method is also effective for optimizing RSI designs to provide uniform thermal reliability on the acreage surface of reusable launch vehicles.
Abstract Water and ligand binding play critical roles in the structure and function of proteins, yet their binding sites and significance are difficult to predict a priori. Multiple solvent crystal structures (MSCS) is a method where several X‐ray crystal structures are solved, each in a unique solvent environment, with organic molecules that serve as probes of the protein surface for sites evolved to bind ligands, while the first hydration shell is essentially maintained. When superimposed, these structures contain a vast amount of information regarding hot spots of protein‐protein or protein‐ligand interactions, as well as conserved water‐binding sites retained with the change in solvent properties. Optimized mining of this information requires reliable structural data and a consistent, objective analysis tool. Detection of related solvent positions (DRoP) was developed to automatically organize and rank the water or small organic molecule binding sites within a given set of structures. It is a flexible tool that can also be used in conserved water analysis given multiple structures of any protein independent of the MSCS method. The DRoP output is an HTML format list of the solvent sites ordered by conservation rank in its population within the set of structures, along with renumbered and recolored PDB files for visualization and facile analysis. Here, we present a previously unpublished set of MSCS structures of bovine pancreatic ribonuclease A (RNase A) and use it together with published structures to illustrate the capabilities of DRoP.
Interfacial stability is one of the critical challenges in all-solid-state Li metal batteries. Multiple processes such as solid electrolyte (SE) decomposition and lithium dendrite growth take place at the solid interfaces during cycling, leading to the overall cell failure. To deconvolute these complex processes, in situ characterization is of paramount importance to elucidate the interfacial evolution on the SE upon Li plating/stripping. Herein, an all-solid-state asymmetric in situ cell is developed that allows the direct visualization of the highly localized Li plating/stripping processes under the optical microscope. Moreover, this cell configuration enables reliable post-mortem chemical and morphological analysis of the intact SE/Li interface. Using combined scanning electron microscopy and energy-dispersive X-ray spectroscopy, the study reveals that the evolution of the Li argyrodite interface is strongly influenced by the current density, particularly in terms of chemical distribution and Li plating morphology. More specifically, the solid interface is LiCl-rich with the formation of Li cubes at low current densities, while high currents result in more uniform elemental distribution and filament morphology. These findings elucidate the dynamic evolution mechanism at solid interfaces and offer valuable guidance for developing stable solid interfaces in all-solid-state Li metal batteries.
Backbone networks are typically overprovisioned in order to support peak loads. Research and education networks (RENs), for example, are often designed to operate at 20–30% of capacity. Thus, Internet2 upgrades its backbone interconnects when the weekly 95th-percentile load is reliably above 30% of link capacity, and analysis of ESnet traffic between major laboratories shows a substantial gap between peak and average utilization. As science data volumes increase exponentially, it is unclear whether this overprovisioning trend can continue into the future. Even if overprovisioning is possible, it may not be the most cost-effective (and desirable) approach going forward. Under the current mode of free access to RENs, traffic at peak load may include both flows that need to be transferred in near-real time–for example, for computation and instrument monitoring and steering–and flows that are less time-critical, for example, archival and storage replication operations. Thus, peak load does not necessarily indicate the capacity that is absolutely required at that moment. We thus examine how data transfers are impacted when the average network load is increased while the network capacity is kept at the current levels. We also classify data transfers into on-demand (time-critical) and best-effort (less time-critical) and study the impact on both classes for different proportions of both the number of on-demand transfers and amount of bandwidth allocated for on-demand transfers. For our study, we use real transfer logs from production GridFTP servers to do simulation-based experiments as well as real experiments on a testbed. We find that when the transfer load is doubled and the network capacity is fixed at the current level, the gap between peak and average throughput decreases by an average of 18% in the simulation experiments and 16% in the testbed experiments, and the average slowdown experienced by the data transfers is under 1.5×. Moreover, when transfers are classified as on-demand or best-effort, on-demand transfers experience almost no slowdown and the mean slowdown experienced by best-effort transfers is under 2× in the simulation experiments and under 1.2× in the testbed experiments.
Machine learning (ML) applications in hydrological forecasting are increasingly prevalent and show great potential. However, many previous studies have only evaluated performance through reanalysis or retrospective simulations compared to simplified baselines. This study provides the first assessment of ML performance against actual operational forecasting systems operated by the California Nevada River Forecast Center (CNRFC), which combines the Community Hydrologic Prediction System (CHPS) with forecasters-in-the-loop. Results demonstrate that forecasters-in-the-loop systems consistently outperform ML models in both general forecasts and flood alerting across lead times up to 96 hr, even when ML models use observed forcings, while CNRFC operational process relies on biased weather forecasts. Our analysis reveals that forecaster expertise maintains forecast reliability despite inaccurate precipitation inputs, with human-guided systems showing superior performance degradation characteristics at extended lead times. These findings highlight the irreplaceable value of human expertise in operational forecasting and caution against overstating current ML capabilities in real-world applications.
A silicon-graphite blended anode is paired with a high capacity LiFePO 4 reference/counter electrode to track irreversibility and lithium inventory. The LiFePO 4 electrode provides a reliable, flat potential for dQ dV -1 analysis of Li x Si and Li x C electrochemical reactions. We can relate this electrochemistry to the morphological and physical changes taking place.
In this study, a Bayesian based non-stationary Gaussian Process (GP) method for the inference of soft X-ray emissivity distribution along with its associated uncertainties has been developed. For the investigation of equilibrium condition and fast magnetohydrodynamic behaviors in nuclear fusion plasmas, it is of importance to infer, especially in the plasma center, spatially resolved soft X-ray profiles from a limited number of noisy line integral measurements. For this ill-posed inversion problem, Bayesian probability theory can provide a posterior probability distribution over all possible solutions under given model assumptions. Specifically, the use of a non-stationary GP to model the emission allows the model to adapt to the varying length scales of the underlying diffusion process. In contrast to other conventional methods, the prior regularization is realized in a probability form which enhances the capability of uncertainty analysis, in consequence, scientists who concern the reliability of their results will benefit from it. Under the assumption of normally distributed noise, the posterior distribution evaluated at a discrete number of points becomes a multivariate normal distribution whose mean and covariance are analytically available, making inversions and calculation of uncertainty fast. Additionally, the hyper-parameters embedded in the model assumption can be optimized through a Bayesian Occam's Razor formalism and thereby automatically adjust the model complexity. This method is shown to produce convincing reconstructions and good agreements with independently calculated results from the Maximum Entropy and Equilibrium-Based Iterative Tomography Algorithm methods.
The Froggatt-Nielsen (FN) mechanism is an elegant solution to the flavor problem. In its minimal application to the quark sector, the different quark types and generations have different charges under a 𝑈(1)𝑋 flavor symmetry. The SM Yukawa couplings are generated below the flavor breaking scale with hierarchies dictated by the quark charge assignments. Only a handful of charge assignments are generally considered in the literature. We analyze the complete space of possible charge assignments with |𝑋 𝑞𝑖 | ≤ 4 and perform both a set of Bayesian-inspired numerical scans and an analytical spurion analysis to identify those charge assignments that reliably generate SM-like quark mass and mixing hierarchies. The resulting set of top-20 flavor charge assignments significantly enlarges the viable space of FN models but is still compact enough to enable focused phenomenological study. We then apply our numerical methodology to demonstrate that these distinct charge assignments result in the generation of correlated flavor-violating four-quark operators characterized by significantly varied strengths, potentially differing substantially from the possibilities previously explored in the literature. Future precision measurement of Δ𝐹 = 2 observables, along with increasingly accurate SM predictions, may therefore enable us to distinguish among otherwise equally plausible FN charges, thus shedding light on the UV structure of the flavor sector.
Survivability of silicon-carbide (SiC) mosfet modules during short circuit (SC) is essential for modern power electronics systems due to large economic implications. SiC mosfet modules exhibit narrow SC withstand times and generally much lower SC robustness than silicon (Si) insulated-gate bipolar transistors (IGBTs). This puts a critical concern on their utilization, further stressing the importance of reliable protection. This article presents a comprehensive analysis and discussion on the SiC mosfet module SC protection and performance comparison between conventional desaturation detection, previously used for Si IGBT protection, and Rogowski switch-current sensor (RSCS) detection. In addition, this article presents the experimental design for soft turn-off as a reaction to the SC detection to avoid excessive overshoots during the abrupt turn-off of the SC current. To perform different types of SC with various fault inductances on different temperatures, and for the sake of fair comparison under the same conditions, a gate-driver unit for 1.2 kV SiC mosfet half-bridge modules is developed containing both detection methods. The results demonstrate that both methods are successful in protecting the module in all SC types, with superiority of the RSCS detection and concerns for desaturation detection in high-inductance and high dc-bus voltage SC events.
The performance, safety, and reliability of Li-ion batteries are determined by a complex set of multiphysics, multiscale phenomena that must be holistically studied and optimized. This paper provides a summary of the state of the art in a variety of research fields related to Li-ion battery materials, processes, and systems. The material presented here is based on a series of discussions at a recently concluded bilateral workshop in which researchers and students from India and the U.S. participated. It is expected that this summary will help understand the complex nature of Li-ion batteries and help highlight the critical directions for future research.
Titanium thin films of different thicknesses were prepared by direct current magnetron sputtering to study modulated infrared (IR) radiometry as a tool for analyzing film thickness. Thickness was varied by regularly increasing the deposition time, keeping all the other deposition parameters constant. The influence of film thickness on morphological, structural, and electrical properties of the titanium coatings also was investigated. The experimental results revealed a systematic grain growth with increasing film thickness, along with enhanced film crystallinity, which led to increased electrical conductivity. Using the results obtained by modulated IR radiometry, the thickness of each thin film was calculated. These thickness values were then compared with the coating thickness measurements obtained by scanning electron microscopy. The values confirmed the reliability of modulated IR radiometry as an analysis tool for thin films and coatings, and for determining thicknesses in the micrometer range, in particular.