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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
The gravity of approx. 30 coronae have been studied using 2 admittance methods to assess differences in elastic thickness and to see if they correlate with morphology or geologic setting, in addition to attempting to constrain subsurface structure.
Production of highly porous composite materials by traditional materials processing is limited by difficult processing techniques. This work investigates the use of self propagating high temperature (combustion) synthesis (SHS) to create porous tricalcium phosphate (Ca3(PO4)2), TiB-Ti, and NiTi in low and microgravity. Combustion synthesis provides the ability to use set processing parameters to engineer the required porous structure suitable for bone repair or replacement. The processing parameters include green density, particle size, gasifying agents, composition, and gravity. The advantage of the TiB-Ti system is the high level of porosity achieved together with a modulus that can be controlled by both composition (TiB-Ti) and porosity. At the same time, NiTi exhibits shape memory properties. SHS of biomaterials allows the engineering of required porosity coupled with resorbtion properties and specific mechanical properties into the composite materials to allow for a better biomaterial.
This effort is to investigate probabilistic life prediction methodologies for ceramic matrix composites and MicroElectroMechanical Systems (MEMS) and to analyze designs that determine stochastic properties of MEMS. For CMC's this includes a brief literature survey regarding lifing methodologies. Also of interest for MEMS is the design of a proper test for the Weibull size effect in thin film (bulge test) specimens. The Weibull size effect is a consequence of a stochastic strength response predicted from the Weibull distribution. Confirming that MEMS strength is controlled by the Weibull distribution will enable the development of a probabilistic design methodology for MEMS - similar to the GRC developed CARES/Life program for bulk ceramics. A main objective of this effort is to further develop and verify the ability of the Ceramics Analysis and Reliability Evaluation of Structures/Life (CARES/Life) code to predict the time-dependent reliability of MEMS structures subjected to multiple transient loads. A second set of objectives is to determine the applicability/suitability of the CARES/Life methodology for CMC analysis, what changes would be needed to the methodology and software, and if feasible, run a demonstration problem. Also important is an evaluation of CARES/Life coupled to the ANSYS Probabilistic Design System (PDS) and the potential of coupling transient reliability analysis to the ANSYS PDS.
Calculations and test results are given about the feed-power requirement of airplanes with boundary-layer control. Curves and formulas for the rough estimate of pressure-loss and feed-power requirement are set up for the investigated arrangements which differ structurally and aerodynamically. According to these results the feed power for three different designs is calculated at the end of the report.
In this paper, the REE radiation fault model and accompanying tool set are presented. Explained is its derivation, its structure and use, and the work being done to validate it.
The West Antarctic Ice Sheet Divide Core (WDC) provided a high-resolution climate record from near the Ross-Amundsen Divide in Central West Antarctica. In addition, radar-detected internal layers in the vicinity of the WDC site have been dated directly from the ice core to provide spatial variations in the age structure of the region. Using these two data sets together, we first infer a high-resolution Holocene accumulation-rate history from 9.2 thousand years of the ice-core timescale and then confirm that this climate history is consistent with internal layers upstream of the core site. Even though the WDC was drilled only 24 kilometers from the modern ice divide, advection of ice from upstream must be taken into account. We evaluate histories of accumulation rate by using a flowband model to generate internal layers that we compare to observed layers. Results show that the centennially averaged accumulation rate was over 20 percent lower than modern at 9.2 thousand years before present (B.P.), increased by 40 percent from 9.2 to 2.3 thousand years B.P., and decreased by at least 10 percent over the past 2 thousand years B.P. to the modern values; these Holocene accumulation-rate changes in Central West Antarctica are larger than changes inferred from East Antarctic ice-core records. Despite significant changes in accumulation rate, throughout the Holocene the regional accumulation pattern has likely remained similar to today, and the ice-divide position has likely remained on average within 5 kilometers of its modern position. Continent-scale ice-sheet models used for reconstructions of West Antarctic ice volume should incorporate this accumulation history.
The sounding rocket Chromospheric Lyman-Alpha SpectroPolarimeter (CLASP) was launched on September 3rd, 2015, and successfully detected (with a polarization accuracy of 0.1 %) the linear polarization signals (Stokes Q and U) that scattering processes were predicted to produce in the hydrogen Lyman-alpha line (Ly; 121.567 nm). Via the Hanle effect, this unique data set may provide novel information about the magnetic structure and energetics in the upper solar chromosphere. The CLASP instrument was safely recovered without any damage and we have recently proposed to dedicate its second ight to observe the four Stokes profiles in the spectral region of the Mg II h and k lines around 280 nm; in these lines the polarization signals result from scattering processes and the Hanle and Zeeman effects. Here we describe the modifications needed to develop this new instrument called the "Chromospheric LAyer SpectroPolarimeter" (CLASP2).
This study presents a methodology for updating the finite element model of a structure for damage detection purposes using an incomplete set of experimentally obtained modal frequencies and modeshapes.
One of the most critical functions of the systems engineering requirements process for a large multi-instrument science-driven space mission is to successfully communicate customer expectations into a comprehensive and traceable science requirements flowdown. These requirements are essential to communicating the constraints on the scope of the science investigations and clarifying how multiple instruments contribute to a given science goal. They also provide insight into how the science goals of the whole mission are affected by design choices. There is little specific guidance available on best practices for developing this science-driven flowdown. A unified Science Traceability Matrix (USTM) contains a significant amount of information that can be leveraged for that purpose, but the USTM was not designed to directly produce a complete science requirements flowdown. Thus, starting with the principles codified in a USTM, the authors propose a framework that directly maps into the requirements flowdown and supports broader systems engineering processes while retaining its meaning to the science team. This Science Traceability and Alignment Framework, or STAF, defines a set of common definitions and valid relationships to structure communication across the project. In addition, STAF populates a network of information that can be useful to support complex mission analysis activities such as fault protection. This work discusses the highest-level implementation of the STAF, the project-domain or P-STAF, which describes an approach to decomposing customer requirements into science requirements. The planned Europa Mission is used as a case study for the implementation of this framework and its potential benefits to a project.
Due to the complexity of modeling the radiative transfer inside the accretion columns of neutron star binaries, their X-ray spectra are still commonly described with phenomenological models, e.g., a cut off power law. While the behavior of these models is well understood and they allow for a comparison of different sources and studying source behavior, the extent to which the underlying physics can be derived from the model parameters is very limited. During recent years, several physically motivated spectral models have been developed to overcome these limitations. Their application, however, is generally computationally much more expensive and they require a high number of parameters which are difficult to constrain. In particular, Becker & Wolff(2007) presented an analytical solution to the radiative transfer equation inside the accretion column assuming a velocity profile that is linear in the optical depth. An implementation of this model that is both fast and accurate enough to be fitted to observed spectra is available in XSPEC. The main difficulty of this implementation is that some solutions violate energy conservation and therefore have to be rejected by the user. We propose a novel fitting strategy that ensures energy conservation during theχ2-minimization which simplifies the application of the model considerably. We demonstrate this approach as well as a study of possible parameter degeneracies with a comprehensive Markov-Chain Monte Carlo analysis of the complete parameter space for a combined NuSTAR and Swift/XRT data-set of Cen X-3.The derived accretion-flow structure features a small column radius of∼63 m and a spectrum dominated by bulk-Comptonization of bremsstrahlung seed photons, in agreement with previous studies
Space weather, a natural hazard, can adversely impact human technological assets. High-voltage electric power transmission grids constitute one of the most critical technological systems vulnerable to space weather driven geomagnetically induced currents (GICs). One of the major challenges pertaining to the study of GICs over the continental United States has been the availability of GIC measurements, which are critical for validation of geoelectric field and power flow models, for example. In this study, we analyze GIC measurements collected at 17 Electrical Power Research Institute (EPRI) SUNBURST transformer locations across the United States for which a GIC value of 10 A or greater was recorded. This data set includes 52 individual geomagnetic storms with Kp index 6 and above during the period from 2010 to 2021. The analysis confirms that there is a good correlation between the number of geomagnetic storms per year and the number of recorded GIC events. Our results also show that about 76% of the top 17 GIC events are associated with the storm main phase, while only 24% are attributed to storm sudden commencements. In addition, it is shown, for the first time, that mid-latitude positive bays can cause large GICs over the continental United States. Finally, this study shows that the largest measured GIC event in the data set was associated with a localized intense dB/dt structure, which could be attributed to substorm activity.
Modeling uncertainty is defined in terms of the difference between predicted and measured eigenvalues and eigenvectors. Data compiled from 22 sets of analysis/test results was used to create statistical databases for large truss-type space structures and both pretest and posttest models of conventional satellite-type space structures. Modeling uncertainty is propagated through the model to produce intervals of uncertainty on frequency response functions, both amplitude and phase. This methodology was used successfully to evaluate the predictive accuracy of several structures, including the NASA CSI Evolutionary Structure tested at Langley Research Center. Test measurements for this structure were within + one-sigma intervals of predicted accuracy for the most part, demonstrating the validity of the methodology and computer code.
Effective micro-structure properties of two-dimensional large repetitive frame-like structures are derived using straightforward combinations of energy methods of linear transformations. Once the actual structure is identified symmetry considerations are used in order to identify its independent property constants. The actual values of these constants are constructed according to a building block format which is carried out in the three consecutive steps: (1) all basic planar lattices are identified, (2) effective continuum properties are derived for each of these planar basic grids using energy methods, and (3) orthogonal transformations are finally used to determine the contribution of each basic set to the overall effective continuum properties of the structure.
This study explores the controls of temperature, pressure, and silicate melt composition on S solubility in silicate liquids. The solubility of S in FeO-containing silicate melts in equilibrium with metal sulfide increases significantly with increasing temperature but decreases with increasing pressure. The silicate melt structure also exercises a control on S solubility. Increasing the degree of polymerization of the silicate melt structure lowers the S solubility in the silicate liquid. The new set of experimental data is used to expand the model of Mavrogenes and O'Neill(1999) for S solubility in silicate liquids by incorporating the influence of the silicate melt structure. The expected S solubility in the ascending magma is calculated using the expanded model. Because the negative pressure dependence of S solubility is more influential than the positive temperature dependence, decompression and adiabatic ascent of a formerly S-saturated silicate magma will lead to S undersaturation. A primitive magma that is S-saturated in its source region will, therefore, become S-undersaturated as it ascends to shallower depth. In order to precipitate magmatic sulfides, the magma must first cool and undergo fractional crystallization to reach S saturation. The S content in a metallic liquid that is in equilibrium with a magma ocean that contains approx. 200 ppm S (i.e., Earth's bulk mantle S content) ranges from 5.5 to 12 wt% S. This range of S values encompasses the amount of S (9 to 12 wt%) that would be present in the outer core if S is the light element. Thus, the Earth's proto-mantle could be in equilibrium (in terms of the preserved S abundance) with a core-forming metallic phase.
An alternative structure for control systems is proposed. The structure is represented by a three-element block diagram and three functional definitions. It is argued that the three functional elements form a canonical set. The set includes the functions description, estimation and control. General overlay of the structure on parallel state and nested-state control systems is discussed. Breakdown of two real nested-state control systems into the proposed functional format is displayed. Application of the process to the mapping of complex control systems R and D efforts is explained with the Mars Rover Sample and Return mission as an example. A previous application of this basic functional structure to Space Station performance requirements organization is discussed.
Kinases are a family of proteins that function as molecular switches, regulating several essential cellular activities such as cell proliferation. Dysfunctional kinases are implicated in several types of cancers and hence they are actively pursued as drug targets. Given the vast number of complex kinase structures that are available in the protein data bank (PDB), there is a necessity to develop methodologies that can identify structurally important moieties of the kinases in an automated fashion, for such techniques can be instrumental in identifying novel drug targets. In this work, we develop a graph neural network (GNN) based deep learning framework for classifying the functionally active and inactive states of a large set of eukaryotic protein kinases, making use of their 3D structure from the PDB. We show that GNN based machine learning models can classify protein states with an accuracy greater than 97%. We further use the GNN models to automatically identify regions of the kinases that are important for its function. For this purpose, Gradient-weighted Class Activation Mapping (Grad-CAM) was implemented on the protein graphs. Remarkably, Grad-CAM consistently identifies the highly conserved DFG motif as the most important part of the protein across the entire kinome, without any prior input. Other regions of the hydrophobic core such as the HRD motif were also identified by the interpretable GNN framework, consistent with the literature. We discuss the significance of each of these regions in detail.
Clouds is an operating system in a novel class of distributed operating systems providing the integration, reliability, and structure that makes a distributed system usable. Clouds is designed to run on a set of general purpose computers that are connected via a medium-of-high speed local area network. The system structuring paradigm chosen for the Clouds operating system, after substantial research, is an object/thread model. All instances of services, programs and data in Clouds are encapsulated in objects. The concept of persistent objects does away with the need for file systems, and replaces it with a more powerful concept, namely the object system. The facilities in Clouds include integration of resources through location transparency; support for various types of atomic operations, including conventional transactions; advanced support for achieving fault tolerance; and provisions for dynamic reconfiguration.
The Evolvable Neural Software System (ENSS) is composed of sets of Neural Basis Functions (NBFs), which can be totally autonomously created and removed according to the changing needs and requirements of the software system. The resulting structure is both hierarchical and self-similar in that a given set of NBFs may have a ruler NBF, which in turn communicates with other sets of NBFs. These sets of NBFs may function as nodes to a ruler node, which are also NBF constructs. In this manner, the synthetic neural system can exhibit the complexity, three-dimensional connectivity, and adaptability of biological neural systems. An added advantage of ENSS over a natural neural system is its ability to modify its core genetic code in response to environmental changes as reflected in needs and requirements. The neural system is fully adaptive and evolvable and is trainable before release. It continues to rewire itself while on the job. The NBF is a unique, bilevel intelligence neural system composed of a higher-level heuristic neural system (HNS) and a lower-level, autonomic neural system (ANS). Taken together, the HNS and the ANS give each NBF the complete capabilities of a biological neural system to match sensory inputs to actions. Another feature of the NBF is the Evolvable Neural Interface (ENI), which links the HNS and ANS. The ENI solves the interface problem between these two systems by actively adapting and evolving from a primitive initial state (a Neural Thread) to a complicated, operational ENI and successfully adapting to a training sequence of sensory input. This simulates the adaptation of a biological neural system in a developmental phase. Within the greater multi-NBF and multi-node ENSS, self-similar ENI s provide the basis for inter-NBF and inter-node connectivity.