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At least 1,297 records · Page 72

Assessment of variations in thermal cycle life data of thermal barrier coated rods

An analysis of thermal cycle life data for 22 thermal barrier coated (TBC) specimens was conducted. The Zr02-8Y203/NiCrAlY plasma spray coated Rene 41 rods were tested in a Mach 0.3 Jet A/air burner flame. All specimens were subjected to the same coating and subsequent test procedures in an effort to control three parametric groups; material properties, geometry and heat flux. Statistically, the data sample space had a mean of 1330 cycles with a standard deviation of 520 cycles. The data were described by normal or log-normal distributions, but other models could also apply; the sample size must be increased to clearly delineate a statistical failure model. The statistical methods were also applied to adhesive/cohesive strength data for 20 TBC discs of the same composition, with similar results. The sample space had a mean of 9 MPa with a standard deviation of 4.2 MPa.

Hendricks, R. C.↗

Three-dimensional analysis of magnetometer array data

A technique is developed for mapping magnetic variation fields in three dimensions using data from an array of magnetometers, based on the theory of optimal linear estimation. The technique is applied to data from the Scandinavian Magnetometer Array. Estimates of the spatial power spectra for the internal and external magnetic variations are derived, which in turn provide estimates of the spatial autocorrelation functions of the three magnetic variation components. Statistical errors involved in mapping the external and internal fields are quantified and displayed over the mapping region. Examples of field mapping and of separation into external and internal components are presented. A comparison between the three-dimensional field separation and a two-dimensional separation from a single chain of stations shows that significant differences can arise in the inferred internal component.

Richmond, A. D.↗

Spectral shape variation of interstellar electrons at high energies

The high energy electron spectrum analysis has shown that the electron intensity inside the H2 cloud region, or in a spiral arm, should be much lower than that outside it and the observed electron energy spectrum should flatten again at about 1 TeV. In the framework of the leady box model the recently established rigidity dependence of the escape pathlength of cosmic rays would predict a high energy electron spectrum which is flatter than the observed one. This divergence is explained by assuming that the leaky box model can only apply to cosmic ray heavy nuclei, and light nuclei and electrons in cosmic rays may have different behaviors in the interstellar propagation. Therefore, the measured data on high energy electrons should be analyzed based on the proposed nonuniform galactic disk (NUGD) mode.

Tan, L. C.↗

Correlated variations in the azimuthal and elevation angles of the interplanetary magnetic field

Analysis of data collected during the in-ecliptic phase of the Ulysses mission shows that there are periods during which deviations from the Parker spiral direction in the azimuthal and elevation angles of the interplanetary magnetic field are correlated. There are a number of solar wind structures which might be expected to introduce such a correlation into the data, e.g., CMEs, Stream-stream interfaces or helicity carried by the solar wind. These potential sources fall into two categories: Those produced at or close to the solar wind source region and those produced by extended interactions as the solar wind expands. We will distinguish the contributions of these two source categories and assess the impact on the evolution on the interplanetary magnetic field.

Murphy, N.↗

Coupled Aerodynamic-Thermal-Structural (CATS) Analysis

Coupled Aerodynamic-Thermal-Structural (CATS) Analysis is a focused effort within the Numerical Propulsion System Simulation (NPSS) program to streamline multidisciplinary analysis of aeropropulsion components and assemblies. Multidisciplinary analysis of axial-flow compressor performance has been selected for the initial focus of this project. CATS will permit more accurate compressor system analysis by enabling users to include thermal and mechanical effects as an integral part of the aerodynamic analysis of the compressor primary flowpath. Thus, critical details, such as the variation of blade tip clearances and the deformation of the flowpath geometry, can be more accurately modeled and included in the aerodynamic analyses. The benefits of this coupled analysis capability are (1) performance and stall line predictions are improved by the inclusion of tip clearances and hot geometries, (2) design alternatives can be readily analyzed, and (3) higher fidelity analysis by researchers in various disciplines is possible. The goals for this project are a 10-percent improvement in stall margin predictions and a 2:1 speed-up in multidisciplinary analysis times. Working cooperatively with Pratt & Whitney, the Lewis CATS team defined the engineering processes and identified the software products necessary for streamlining these processes. The basic approach is to integrate the aerodynamic, thermal, and structural computational analyses by using data management and Non-Uniform Rational B-Splines (NURBS) based data mapping. Five software products have been defined for this task: (1) a primary flowpath data mapper, (2) a two-dimensional data mapper, (3) a database interface, (4) a blade structural pre- and post-processor, and (5) a computational fluid dynamics code for aerothermal analysis of the drum rotor. Thus far (1) a cooperative agreement has been established with Pratt & Whitney, (2) a Primary Flowpath Data Mapper has been prototyped and delivered to General Electric Aircraft Engines and Pratt & Whitney for evaluation, (3) a collaborative effort has been initiated with the National Institute of Standards and Testing to develop a Standard Data Access Interface, and (4) a blade tip clearance capability has been implemented into the Structural Airfoil Blade Engineering Routine (SABER) program. We plan to continue to develop the data mappers and data management tools. As progress is made, additional efforts will be made to apply these tools to propulsion system applications.

Source record↗

Seasonal Variations in Atmospheric Composition as Measured in Gale Crater, Mars

The Sample Analysis at Mars (SAM) instrument onboard the Mars Science Laboratory Curiosity rover measures the chemical composition of major atmospheric species (CO2, N2, 40Ar,O2, and CO) through a dedicated atmospheric inlet. We report here measurements of volume mixing ratios in Gale Crater using the SAM quadrupole mass spectrometer, obtained over a period of nearly 5 years (3 Mars years) from landing. The observation period spans the northern summer of MY31 and solar longitude (L(sub S)) of 175° through spring of MY 34, L(sub S) = 12°. This work expands upon prior reports of the mixing ratios measured by SAM QMS in the first 105 sols of the mission. The SAM QMS atmospheric measurements were taken periodically, with a cumulative coverage of four or five experiments per season on Mars. Major observations include the seasonal cycle of CO2, N2, and Ar, which lags approximately 20–40° of L(sub S) behind the pressure cycle driven by CO2 condensation and sublimation from the winter poles. This seasonal cycle indicates that transport occurs on faster timescales than mixing. The mixing ratio of O2 shows significant seasonal and interannual variability, suggesting an unknown atmospheric or surface process at work. The O2 measurements are compared to several parameters, including dust optical depth and trace CH4 measurements by Curiosity. We derive annual mean volume mixing ratios for the atmosphere in Gale Crater: CO2 = 0.951 (±0.003), N2 = 0.0259 (±0.0006), 40Ar = 0.0194 (±0.0004), O2 = 1.61 (±0.09) x 10(exp ‐3), and CO = 5.8 (±0.8) x 10(exp ‐4).

Gale Crater↗

Understanding the hydrological response of a headwater-dominated catchment by analysis of distributed surface–subsurface interactions

Abstract We computationally explore the relationship between surface–subsurface exchange and hydrological response in a headwater-dominated high elevation, mountainous catchment in East River Watershed, Colorado, USA. In order to isolate the effect of surface–subsurface exchange on the hydrological response, we compare three model variations that differ only in soil permeability. Traditional methods of hydrograph analysis that have been developed for headwater catchments may fail to properly characterize catchments, where catchment response is tightly coupled to headwater inflow. Analyzing the spatially distributed hydrological response of such catchments gives additional information on the catchment functioning. Thus, we compute hydrographs, hydrological indices, and spatio-temporal distributions of hydrological variables. The indices and distributions are then linked to the hydrograph at the outlet of the catchment. Our results show that changes in the surface–subsurface exchange fluxes trigger different flow regimes, connectivity dynamics, and runoff generation mechanisms inside the catchment, and hence, affect the distributed hydrological response. Further, changes in surface–subsurface exchange rates lead to a nonlinear change in the degree of connectivity—quantified through the number of disconnected clusters of ponding water—in the catchment. Although the runoff formation in the catchment changes significantly, these changes do not significantly alter the aggregated streamflow hydrograph. This hints at a crucial gap in our ability to infer catchment function from aggregated signatures. We show that while these changes in distributed hydrological response may not always be observable through aggregated hydrological signatures, they can be quantified through the use of indices of connectivity.

54 ENVIRONMENTAL SCIENCES↗

Uncertainty Analysis of Stiffened Composite Panels

A study is made of the variability in the nonlinear response of three stiffened composite panels associated with variations in their geometric and material parameters. The three panels have a cylindrical skin with either four or five T-shaped stiffeners. Two of the panels have a notch and the third panel has a circular cutout. Hierarchical sensitivity analysis is used to identify the major parameters at the micro-mechanical, layer, laminate and sub-component levels. The major parameters are then taken to be fuzzy parameters, and a fuzzy set analysis is used to determine the range of variation of the response associated with pre-selected variations in the major parameters.

Noor, Ahmed K.↗

Citizen science coupled with machine learning to quantify green-blue infrastructure cooling potential in Maricopa County, Arizona

Here, this study investigates the spatiotemporal cooling performance of green and blue infrastructure (GBI) in the Dobson Ranch urban neighborhood in Phoenix, Arizona. We leveraged citizen science near-surface (2 m) air temperature (Tair) measurements to train a highly accurate Tair predicting LightGBM machine learning model (R 2 : 0.986, MAE: 0.251 °C, RMSE: 0.585 °C). On June 16, 2024, the park area exhibited approximately 1 °C cooling effect (relative to the neighborhood mean) during both day and night. In contrast, the nearby artificial lake exhibited a stronger cooling effect of 2.4 °C during the day but a slight warming of 0.3 °C at night. At 00:00, locations 50 m downwind of the park were 0.3 °C warmer than the park, while locations 50 m upwind were 0.8 °C warmer. At 11:00, we observed that the downwind area is 0.8 °C cooler and the upwind area is 0.6 °C warmer—at the same 50 m distances relative to the park. We also observed 1 °C cooler and warmer effects respectively at the same 50 m downwind and upwind locations at 19:00 on June 17, 2024. Our data-driven analysis highlights potential limitations of car-traverse measurements, showing that failure to account for temporal variations during the traverse can lead to overestimation of Tair at night and underestimation during the day. Our analysis also showed only a weak correlation (coefficient: 0.48) between Landsat-derived land surface temperature (LST) and model predicted Tair at the time of the local Landsat overpass (∼11.00). This highlights the potential error of relying solely on LST for human thermal exposure analysis—particularly within the heterogenous built-environment.

54 ENVIRONMENTAL SCIENCES↗

Scaling studies of solar pumped lasers

A progress report of scaling studies of solar pumped lasers is presented. Conversion of blackbody radiation into laser light has been demonstrated in this study. Parametric studies of the variation of laser mixture composition and laser gas temperature were carried out for CO2 and N2O gases. Theoretical analysis and modeling of the system have been performed. Reasonable agreement between predictions in the parameter variation and the experimental results have been obtained. Almost 200 mW of laser output at 10.6 micron was achieved by placing a small sapphire laser tube inside an oven at 1500 K the tube was filled with CO2 laser gas mixture and cooled by longitudinal nitrogen gas flow.

Christiansen, W. H.↗

Microgravity-Induced Physiological Fluid Redistribution: Computational Analysis to Assess Influence of Physiological Parameters

Space flight impacts human physiology in many ways, the most immediate being the marked cephalad (headward) shift of fluid upon introduction into the microgravity environment. This physiological response to microgravity points to the redistribution of blood and interstitial fluid as a major factor in the loss of venous tone and reduction in heart muscle efficiency which impact astronaut performance. In addition, researchers have hypothesized that a reduction in astronaut visual acuity, part of the Visual Impairment and Intracranial Pressure (VIIP) syndrome, is associated with this redistribution of fluid. VIIP arises within several months of beginning space flight and includes a variety of ophthalmic changes including posterior globe flattening, distension of the optic nerve sheath, and kinking of the optic nerve. We utilize a suite of lumped parameter models to simulate microgravity-induced fluid redistribution in the cardiovascular, central nervous and ocular systems to provide initial and boundary data to a 3D finite element simulation of ocular biomechanics in VIIP. Specifically, the lumped parameter cardiovascular model acts as the primary means of establishing how microgravity, and the associated lack of hydrostatic gradient, impacts fluid redistribution. The cardiovascular model consists of 16 compartments, including three cerebrospinal fluid (CSF) compartments, three cranial blood compartments, and 10 thoracic and lower limb blood compartments. To assess the models capability to address variations in physiological parameters, we completed a formal uncertainty and sensitivity analysis that evaluated the relative importance of 42 input parameters required in the model on relative compartment flows and compartment pressures. Utilizing the model in a pulsatile flow configuration, the sensitivity analysis identified the ten parameters that most influenced each compartment pressure. Generally, each compartment responded appropriately to parameter variations associated with itself and adjacent compartments. However, several unexpected interactions between components, such as between the choroid plexus and the lower capillaries, were found, and are due to simplifications in the formulation of the model. The analysis illustrates that highly influential parameters and those that have unique influences within the model formulation must be tightly controlled for successful model application.

gravitational physiology↗

A Monte-Carlo Method for Evaluating the Economic Performance of Plastics Recycling Systems Using Historical Pricing

The management of plastic waste is a considerable emerging global concern. Conventional plastics recycling rates range from 5–10% in the US, which results in considerable material being sent to landfill. New sorting technologies using artificial intelligence have the potential to dramatically increase the ability of waste management companies to sort out valuable fractions of plastic waste and create high-purity streams for secondary markets. However, several fractions of the plastics recycling stream, i.e., low-density polyethylene, polypropylene, and polystyrene, do not have well-developed markets. These materials may be sent to pyrolysis facilities for thermal recycling, but the economics of the pyrolysis industry are currently uncertain. This work aims to identify the breakeven price of the plastic fractions that would be sent to pyrolysis in order to determine the economic viability of the sorting facility. The work will use Monte Carlo analysis to evaluate several scenarios and understand how compositional variation, price variability, and facility attributes affect the breakeven price. Here, the presorting conditions in Materials Recovery Facilities strongly affects the profitability of the sorting facility. High residual high density polyethylene (HDPE) and polyethylene terephthalate (PET) content in presorted bales are important revenue drivers for the facility, even in presorted 3-7 bales. Key variables that lead to profitability include a high sale price of polyethylene terephthalate, a high sale price of high-density polyethylene, and if polypropylene can be sold to recycling markets (as opposed to pyrolysis facilities).

Plastics↗

Long-Term Climatic Variations in the Almati Oblast in Central Asian Kazakhstan: Correlations between National Centers for Environmental Prediction (NCEP) Reanalysis II Results and Oblast Meteorological Station Data from 1949 to the Present

As part of a larger analysis of country systems described elsewhere, named a Crop Country Inventory, CCI, large variations in annual crop yield for selected climate sensitive agricultural regions or sub-regions within a country have been studied over extended periods in decades. These climate sensitive regions, principally responsible for large annual variations in an entire country s crop production, generally are characterized by distinctive patterns of atmospheric circulation and synoptic processes that result in large seasonal fluctuations in temperature, precipitation and soil moisture as well as other climate properties. The immediate region of interest is drought prone Kazakhstan in Central Asia, part of the Former Soviet Union, FSU. As a partial validation test in a dry southern region of Kazakhstan, the Almati Oblast was chosen. The Almati Oblast, a sub-region of Kazakhstan located in its southeast corner, is one of 14 oblasts within the Republic of Kazahstan. The climate data set used to characterize this region was taken from the results of the current maturely developed Global Climate Model, GCM. In this paper, the GCM results have been compared to the meteorological station data at the station locations, over various periods. If the empirical correlation of the data sets from both the GCM and station data is sufficiently significant, this would validate the use of the superior GCM profile mapping and integration for the climatic characterization of a sub-region. Precipitation values interpolated from NCEP Reanalysis II data, a global climate database spanning over 5 decades since 1949, have been statistically correlated with monthly-averaged station data from 1949 through 1993, and with daily station data from April through August, 1990 for the Almati Oblast in Kazakhstan. The resultant correlation is significant, which implies that the methodology may be extended to different regions globally for Crop Country Inventory studies.

Welker, Jean E.↗

Seasonal Seismicity in the Lake Biwa Region of Central Japan Moderately Modulated by Lake Water Storage Changes

Seasonal seismicity in Japan has been observed and attributed to variations induced by hydrological loading, as well as atmospheric and pore-fluid pressure. We examine the seasonal variations of crustal (<15 km depth) and low magnitude (M < 4.5) earthquakes in central Japan near the Biwako-Seigan Fault Zone (BSFZ), and analyze their correlation with the annual hydrological cycle of nearby Lake Biwa, the largest freshwater lake in Japan. The 2002–2018 lake water storage is estimated using water-level gauge and satellite altimetry data. Regional surface mass loading from soil moisture and snow predicted by the Global Land Data Assimilation System is used to augment the lake mass variation. We compute the stress and stressing-rate changes induced by the surface mass loading from lake storage, snow, and soil moisture at seismogenic depth (10 km) along the BSFZ using a finite element model incorporating a 3D Earth structure. The results show that seasonal surface mass loading generates 1–5 kPa peak-to-peak Coulomb stress change and 2.5–15 kPa/year stressing-rate variations on the fault segments along the BSFZ. Two of the four fault segments present significant correlation between local seismicity rate and loading-derived stress and/or stressing rate changes. Among the hydrological load components, lake water, snow, and soil moisture exhibit different annual phases, and the lake water storage dominates the total annual stress changes. Our analysis indicates that seasonal surface hydrological loads, especially lake water variations, modulate the seismicity rate along the BSFZ in central Japan.

58 GEOSCIENCES↗

Unveiling mesoscopic structures in distorted lamellar phases through deep learning-based small angle neutron scattering analysis

Hypothesis: The formation of distorted lamellar phases, distinguished by their arrangement of crumpled, stacked layers, is frequently accompanied by the disruption of long-range order, leading to the formation of interconnected network structures commonly observed in the sponge phase. Nevertheless, traditional scattering functions grounded in deterministic modeling fall short of fully representing these intricate structural characteristics. Our hypothesis posits that a deep learning method, in conjunction with the generalized leveled wave approach used for describing structural features of distorted lamellar phases, can quantitatively unveil the inherent spatial correlations within these phases. Experiments and Simulations: This report outlines a novel strategy that integrates convolutional neural networks and variational autoencoders, supported by stochastically generated density fluctuations, into a regression analysis framework for extracting structural features of distorted lamellar phases from small angle neutron scattering data. To evaluate the efficacy of our proposed approach, we conducted computational accuracy assessments and applied it to the analysis of experimentally measured small angle neutron scattering spectra of AOT surfactant solutions, a frequently studied lamellar system. Findings: The findings unambiguously demonstrate that deep learning provides a dependable and quantitative approach for investigating the morphology of wide variations of distorted lamellar phases. It is adaptable for deciphering structures from the lamellar to sponge phase including intermediate structures exhibiting fused topological features. In conclusion, this research highlights the effectiveness of deep learning methods in tackling complex issues in the field of soft matter structural analysis and beyond.

36 MATERIALS SCIENCE↗

A Performance Analysis of Folding Conformal Propeller Blade Designs

NASA’s X-57 Maxwell flight demonstrator has a high-lift system that includes 12 fixed- pitch high-lift propellers located upstream of the wing leading edge for lift augmentation at low speeds. These high-lift propellers are only required at low speeds, and to reduce drag, the propeller blades are folded conformally along the nacelles at other operating conditions. The method of designing the high-lift blades permits several variations of blade cross-section placement along the nacelle surface and a comparative performance analysis was needed to determine if any particular design showed significant benefits. We analyzed the performance of three conformal high-lift propeller designs and compared them to that of a non-conformal baseline propeller to establish both the benefit of stowable blades and the value of each variation. In this study, we first performed a drag analysis of each design in the stowed configuration at the X-57 cruise speed and altitude to determine the drag benefits of each conforming method. Then, among blade designs we compared the thrust, power, and lift for a given input shaft speed to establish any performance losses from the baseline. This analysis shows that the conformal blade designs do not have any appreciable performance losses compared to the baseline blades. Moreover, although the drag in the cruise condition is significantly less than for the non-folding baseline, the drag benefits of each conforming blade approach are similar and the value of each approach largely depends on the ease of integration into the nacelle. This paper presents the results of these studies and discusses the benefits and drawbacks of implementing the conformal blade designs. Specifically, we demonstrate that folding, conformal propeller blades contribute significantly less to cruise drag when compared to windmilling, with an increase relative to a. We also show a less than 1% difference in performance formal, folding propellers and the non-conforming baseline propeller.

Litherland, Brandon L.↗

Optical and radio variability in blazars

An analysis is presented of the optical (0.44 micron) and radio flux density variations (4.8, 8.0, and 14.5 GHz) of the five best observed variable AGN, of which three are BL Lac objects and two are optically violent variable (OVV) quasars. For each object the nature of the variability at individual wavelengths is determined by using a structure function analysis and the autocorrelation function as calculated from the discrete correlation technique. Both techniques yield similar results, showing that the optical variations are similar for all objects and are a combination of flicker and shot noise. The radio variability is distinct, being described by shot noise (less variation at short times), with the two OVVs exhibiting the most extreme behavior. The time lag between the variations at the three radio frequencies and the optical flux is studied with the discrete cross-correlation function and the mean variance methods. It is concluded that the optical and radio emitting regions are physically related, exist on distinct time scales, and excite their synchrotron emitting plasmas differently.

Hufnagel, Beth R.↗

Uncertainty Quantification of Bifacial Performance Modeling

Analysis on uncertainty in the annual energy of PV systems that can be attributed to parameters of particular importance to bifacial PV modules is presented. Monte Carlo simulations are used to evaluate the effect of uncertain module bifaciality factors, module transmission fractions, albedo values, and ground clearance. The analyses cover a wide spectrum of potential PV array archetypes through variation of installation parameters. The results of the Monte Carlo analysis reveal that the uncertainty is largely dependent on albedo uncertainty, but more simulations are needed to identify trends across system archetypes. The simulations are aimed at attributing an annual energy uncertainty factor for bifacial considerations that can be applied in post-processing of project probability of exceedance analysis.

energy modeling↗