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At least 127 records · Page 7

Regional-scale flows in mountainous terrain. Part 1: A numerical and observational comparison

This study uses observed data and a numerical simulation to examine the generation of thermally driven flows across the Colorado mountain barrier on meso-beta to meso-alpha scales. The observations were collected from remote surface observing systems at exposed mountaintop locations throughout the state of Colorado, over the summers of 1984-88, as part of the Rocky Mountain Peaks Experiment (ROMPEX). The data show the development of a recurrent circulation system across the Colorado mountain barrier, operating on a diurnal timescale. From the observations, the basic structure of the flow system appears as a daytime inflow toward the highest terrain, and a nocturnal outflow away from it. However, when examined in detail, the flow system exhibits more unusual behavior, especially west of the barrier crest. Here, winds in the early evening are occasionally observed to onset abruptly from an easterly direction, generally counter to the upper-level winds. Observations from ROMPEX for 26 August 1985 are used to provide comparison data for a numerical simulation with the Regional Atmospheric Modeling System (RAMS). This three-dimensional case study experiment is initialized with data from the National Meteorological Center and incorporates two-way interactive grid nesting. From the observed data and case study simulation, four distinct phases of the regional-scale circulation system have been identified. In the development phase, a deep mountain-plains solenoid is generated through terrain heating along the Front Range. This circulation system transforms in the late afternoon transition phase into a westward-propagating density current (WPDC). The third phase, called the 'density-current propagation phase,' occurs as the WPDC moves westward across the mountains, leaving in its wake strong southeasterly flow at the mountaintop level. This current appears to be the cause of the peculiar easterly component winds found in the ROMPEX mountaintop observations along the western slope. In the final late-night adjustment phase, the WPDC dissipates near the western edge of the Colorado mountains and steady southerly flow evolves over the high mountain terrain. This southerly flow is the steady response to the differential heating that develops between the low-lying plains and the intermountain region.

Bossert, James E.

Navier-Stokes calculations of transonic flows past cavities

Presented in this paper is a computational investigation of subsonic and transonic flows past three-dimensional deep and transitional cavities. Simulations of these self-induced oscillatory flows have been generated through time-accurate solutions of the Reynolds averaged, full Navier-Stokes equations, using the explicit MacCormack scheme. The Reynolds stresses have been included through the Baldwin-Lomax algebraic turbulence model with certain modifications. The computational results include instantaneous and time averaged flow properties. The results of an experimental investigation have been used not only to validate the time-averaged results, but also to investigate the effects of varying the Mach number and the incoming boundary-layer thickness. Time series analyses have been performed for the instantaneous pressure values on the cavity floor and compared with the results obtained by a predictive formula. While most of the comparisons have been favorable, some discrepancies have been observed, particularly on the rear face. The present results help understanding the three-dimensional and unsteady features of the separations, vortices, the shear layer, as well as some of the aeroacoustic phenomena of compressible cavity flows.

Baysal, O.

Origin of high-Ti lunar ultramafic glasses

A series of high pressure melting experiments were performed on a synthetic analog of the Apollo 14 Black Glass. At 15 kb and 1400 C, olivine is the liquidus phase. At 25 kb and 1450 C, orthopyroxene and Cr-spinel crystallize. A multiple saturation point with olivine + orthopyroxene + spinel on the liquidus occurs at 20 kb and 1440 C. It was proposed that the high-Ti ultramafic glass evolved from a low-Ti Green Glass generated deep in the lunar interior that assimilated shallow-level, late stage cumulates of magma ocean differentiation. Heat for assimilation is provided by superheat of the low-Ti magma and melts high-Ca pyroxene and ilmenite cumulates at a depth of 100 km. This model is a variant of that proposed by Hubbard and Minear and rejected by Ringwood and Kesson.

Wagner, T. P.

Variable Stiffness Panel Structural Analyses With Material Nonlinearity and Correlation With Tests

Results from structural analyses of three tow-placed AS4/977-3 composite panels with both geometric and material nonlinearities are presented. Two of the panels have variable stiffness layups where the fiber orientation angle varies as a continuous function of location on the panel planform. One variable stiffness panel has overlapping tow bands of varying thickness, while the other has a theoretically uniform thickness. The third panel has a conventional uniform-thickness [plus or minus 45](sub 5s) layup with straight fibers, providing a baseline for comparing the performance of the variable stiffness panels. Parametric finite element analyses including nonlinear material shear are first compared with material characterization test results for two orthotropic layups. This nonlinear material model is incorporated into structural analysis models of the variable stiffness and baseline panels with applied end shortenings. Measured geometric imperfections and mechanical prestresses, generated by forcing the variable stiffness panels from their cured anticlastic shapes into their flatter test configurations, are also modeled. Results of these structural analyses are then compared to the measured panel structural response. Good correlation is observed between the analysis results and displacement test data throughout deep postbuckling up to global failure, suggesting that nonlinear material behavior is an important component of the actual panel structural response.

Wu, K. Chauncey

A first-order estimate of shock heating and vaporization in oceanic impacts

The vaporization of water in oceanic impacts of asteroids or comets of multikilometer dimensions is estimated by a semianalytical modeling of impact heating and shock isobar geometry that is based on computer code calculations. The mass of water vaporized in an infinitely deep ocean by the impact of a 10 km diameter asteroid at 25 km/sec (these values have been proposed for the Cretaceous/Tertiary extinction bolide) is approximately equal to the total mass of water vapor present in the earth's atmosphere, and 3-4 orders of magnitude larger than the mass of water vapor in the stratosphere. For projectiles of this size, however, the finite depth of the ocean becomes significant and may considerably reduce the amount of water vapor initially generated by the impact. Climatological models and extinction scenarios invoking the effects of impact-generated water vapor may critically depend on the a priori ambiguous details of the hypothesized impact.

Croft, S. K.

Preliminary Analysis and Simulations of July 23rd Extended Anvil Case

A key focus of CRYSTAL-FACE (Cirrus Regional Study of Tropical Anvils and cirrus Layers - Florida Area Cirrus Experiment) was the generation and subsequent evolution of cirrus outflow from deep convective cloud systems. A preliminary integrated look at the observations of an extended cirrus anvil cloud system observed on 23 July 2002 will be presented, including lidar and millimeter radar observations from NASA's ER-2 and in- situ observations from NASA's WB-57 and University of North Dakota Citation. The observations will be compared to preliminary results of simulations using 1-D and 2-D high-resolution (100 meter) cloud resolving models. The CRMs explicitly account for cirrus microphysical development by resolving the evolving ice crystal size distribution (bin model) in time and space. Both homogeneous and heterogeneous nucleation are allowed in the model. The CRM simulations are driven using the output of regional simulations using MM5 that produces deep convection similar to what was observed. The MM5 model employs a 2 km inner grid (32 layers) over a 360 km domain, nested within a 6 km grid over a 600 km domain. Initial and boundary conditions for the 36- hour MM5 simulation are taken from NCEP Eta model analysis at 32 km resolution. Key issues to be explored are the settling of the observed anvil versus the model simulations, and comparisons of dynamical properties, such as vertical motions, occurring in the observations and models. The former provides an integrated measure of the validity of the model microphysics (fallspeed) while the latter is the key factor in forcing continued ice generation.

Lin, R.-F.

Thermal Pollution Mathematical Model. Volume 3: User's Manual for One-Dimensional Numerical Model for the Seasonal Thermocline

A user's manual for a one dimensional thermal model to predict the temperature profiles of a deep body of water for any number of annual cycles is presented. The model is essentially a set of partial differential equations which are solved by finite difference methods using a high speed digital computer. The model features the effects of area change with depth, nonlinear interaction of wind generated turbulence and buoyancy, adsorption of radiative heat flux below the surface, thermal discharges, and the effects of vertical convection caused by discharge. The main assumption in the formulation is horizontal homogeneity. The environmental impact of thermal discharges from power plants is emphasized. Although the model is applicable to most lakes, a specific site (Lake Keowee, S.C.) application is described in detail. The programs are written in FORTRAN 5.

Lee, S. S.

Radio interferometric determination of intercontinental baselines and earth orientation utilizing deep space network antennas - 1971 to 1980

Progress has been made toward the realization of the potential of radio interferometry for measuring crustal motions and global rotations of the earth with accuracies at the centimeter level. In this connection, a series of experiments, primarily with NASA's Deep Space Network (DSN) antennas, has been conducted to develop two generations of very long baseline interferometric (VLBI) systems. A description is presented of the employed techniques, an analysis of the experiments, and the results of geophysical significance. Attention is given to the interferometry technique, the geometric delay model, propagation media calibrations, and the observing strategy.

Sovers, O. J.

Deep Space Network Scheduling Using Multi-Objective Optimization with Uncertainty

We have developed a novel technique to incorporate uncertainty modeling within an evolutionary algorithm approach to multi-objective scheduling, with the goal of identifying a Pareto frontier (tradeoff curve) that recognizes the likelihood of events that can impact the schedule outcome. Our approach is particularly applicable to the generation of multiobjective optimized robust schedules, where objectives are assigned a service level, for example that we require an objective value to be greater than or equal to X with Y% confidence. We have demonstrated that such an approach can, for example, minimize scheduling on less reliable resources, based solely on a resource reliability model and not on any ad hoc heuristics. We have also investigated an alternative method of optimizing for robustness, in which we add to the set of objectives a failure risk objective to minimize. We compare the advantages and disadvantages of these two approaches. Future plans for further developing this technology include its application to space-based observatory scheduling problems.

Johnston, Mark D.

Trace gas exchanges and convective transports over the Amazonian rain forest

The NASA Amazon Boundary Layer Experiment (ABLE 2A) based in Manaus, Brazil, in July and August 1985, is used to examine meteorological processes responsible for the vertical and horizontal transport of biogenic and anthropogenic trace gases generated over the Amazon basin. Direct sampling of the surrounding environment of deep convective clouds shows marked changes in the vertical distribution of the lower and midtroposphere concentration of O3 and such surface-derived species as CO, CO2, and NO. Thermodynamic observations, together with two-dimensional cloud model simulations, confirm vertical transports within the convection and provide a basis for an estimation of the magnitude and efficiency of cloud upward and downward exchanges. A distinction is drawn between local changes due to convective updrafts and downdrafts and convective overturning as a net result of the storm processes. Marked variability is seen in trace gas concentrations along horizontal flight paths in the vicinity of the convection. Interpretation of simultaneously measured thermodynamic quantities and trace gas concentrations provide the information to infer the presence and direction of atmospheric transports and/or the presence of anthropogenic influences.

Garstang, Michael

Design of multihundred-watt dynamic isotope power system for robotic space missions

The design of a multihundred-watt dynamic isotope power system (DIPS) based on the US Department of Energy (DOE) general-purpose heat source (GPHS) and small (multihundred-watt) free-piston Stirling engine (FPSE) is described as a potential lower cost alternative to radioisotope thermoelectric generators (RTGs). The design is targeted at the power needs of future unmanned deep space and planetary surface exploration missions. Since the competitive potential of FPSE as an isotope convertor was first identified, work has focused on the feasibility of directly integrating GPHS with the Stirling heater head. Thermal modeling of various radiatively coupled heat source/heater head geometries has been performed using data furnished by the developers of FPSE and GPHS. The analysis indicates that, for the 1050 K heater head configurations considered, GPHS fuel clad temperatures remain safe operating limits under all conditions including shutdown of one engine on a twin engine unit. Based on these results, preliminary characterizations of multihundred-watt units have been established. They indicate that, per electrical watt, the GPHS/small Stirling DIPS will be roughly equivalent to MOD RTG in size and mass but will require about a third the amount of isotope fuel.

Bents, D. J.

MRO DKF Post-Processing Tool

This software tool saves time and reduces risk by automating two labor-intensive and error-prone post-processing steps required for every DKF [DSN (Deep Space Network) Keyword File] that MRO (Mars Reconnaissance Orbiter) produces, and is being extended to post-process the corresponding TSOE (Text Sequence Of Events) as well. The need for this post-processing step stems from limitations in the seq-gen modeling resulting in incorrect DKF generation that is then cleaned up in post-processing.

Ayap, Shanti

Antenna Calibration and Measurement Equipment

A document describes the Antenna Calibration & Measurement Equipment (ACME) system that will provide the Deep Space Network (DSN) with instrumentation enabling a trained RF engineer at each complex to perform antenna calibration measurements and to generate antenna calibration data. This data includes continuous-scan auto-bore-based data acquisition with all-sky data gathering in support of 4th order pointing model generation requirements. Other data includes antenna subreflector focus, system noise temperature and tipping curves, antenna efficiency, reports system linearity, and instrument calibration. The ACME system design is based on the on-the-fly (OTF) mapping technique and architecture. ACME has contributed to the improved RF performance of the DSN by approximately a factor of two. It improved the pointing performances of the DSN antennas and productivity of its personnel and calibration engineers.

Rochblatt, David J.

The Moon's Deep Interior: A Hotbed for Seismicity and the Question of Partial Melt

Terrestrial planets all share a common structural framework (crust, mantle, core) which is developed very shortly after formation and which determines subsequent evolution. The Moon formed under very unique circumstances. Interior properties provide constraints on formation and evolution models, and possible indicators of an early dynamo for magnetic field generation: Layering, Composition, Seismic velocity & density, Presence of partial melt, Core state. Constraints on these properties arise from geophysical observations: Geodetic parameters, Lunar laser ranging, Gravity field, Magnetic induction, Heat flow, Seismology.

Weber, Renee

The Porous Microstructure Analysis (PuMA) software

The open-source Porous Microstructure Analysis (PuMA) software was implemented to offer an efficient framework for determining material characteristics from 3D microstructures. Its development was inspired by progress in X-ray microtomography, an imaging technology that captures the internal structure of materials in 3D, and even in a 4D temporal context. Over recent years, this method has transformed the domain of materials science due to its capability to non-destructively examine material microstructures while presenting digital data about their geometrical details. It has provided insights into materials relevant to several NASA missions, including heatshields, parachute fabrics, meteorites, and other advanced composites. PuMA, in its current version 3, delivers an array of features, spanning from basic geometric insights of a microstructure to intricate anisotropic thermo-elastic and chemical behavior. Specifically, the software evaluates morphological attributes (specific surface area, volume fractions, mean intercept lengths, orientation) and physical characteristics (conductivity, elasticity, permeability, and tortuosity). Additionally, it can model material degradation processes, such as oxidation and surface chemistry interactions. The software can generate synthetic microstructures, from straightforward geometrical designs to intricate woven and non-woven geometries. Coupling material generation and characterization enable parametric studies and sensitivity analysis to optimize the microstructural performance and inform design decisions and reliability assessment based on uncertainty quantification. A recent addition to PuMA includes the TomoSAM plugin, devised to incorporate the cutting-edge Segment Anything Model (SAM). SAM is a promptable deep learning model that can identify objects and create image masks in a zero-shot manner, based only on a few user clicks. The synergy between these tools aids in the segmentation of complex 3D datasets from tomography or other imaging techniques, which would otherwise require a laborious manual segmentation process.

Tomography

CRYSTAL-FACE Analysis and Simulations of the July 23rd Extended Anvil Case

A key focus of CRYSTAL-FACE (Cirrus Regional Study of Tropical Anvils and cirrus Layers - Florida Area Cirrus Experiment) was the generation and subsequent evolution of cirrus outflow from deep convective cloud systems. Present theoretical background and motivations will be discussed. An integrated look at the observations of an extended cirrus anvil cloud system observed on 23 July 2002 will be presented, including lidar and millimeter radar observation; from NASA s ER-2 and in-situ observations from NASA s WB-57 and University of North Dakota Citation. The observations will be compared to results of simulations using 1-D and 2-D high-resolution (100 meter) cloud resolving models. The CRMs explicitly account for cirrus microphysical development by resolving the evolving ice crystal size distribution (bin model) in time and space. Both homogeneous and heterogeneous nucleation are allowed in the model. The CRM simulations are driven using the output of regional simulations using MM5 that produces deep convection similar to what was observed. The MM5 model employs a 2 km inner grid (32 layers) over a 360 km domain, nested within a 6-km grid over a 600-km domain. Initial and boundary conditions for the 36-hour MM5 simulation are taken from NCEP Eta model analysis at 32 km resolution. Key issues to be explored are the settling of the observed anvil versus the model simulations, and comparisons of dynamical properties, such as vertical motions, occurring in the observations and models. The former provides an integrated measure of the validity of the model microphysics (fallspeed) while the latter is the key factor in forcing continued ice generation.

Starr, David

Physics-Guided Deep Learning for Complex System Health Management and Decision Making

The landscape of complex engineered systems is rapidly evolving, from smart manufacturing facilities to next-generation transportation vehicles. As these systems become increasingly sophisticated and interconnected, the need for advanced health management systems grows ever more critical. These systems must go beyond simple monitoring, actively predicting potential failures before they occur. This paradigm shift from fixed maintenance schedules to condition-based predictions is key to optimizing system performance, enhancing safety, and paving the way for autonomous decision-making across various industries. Whether in industrial processes, energy systems, or advanced transportation, the ability to anticipate and prevent failures is becoming a cornerstone of operational excellence. To accurately predict the future health of any complex system, knowledge of its current health state and future operational conditions is essential. Recent advancements in data-driven algorithms have generated growing interest in artificial intelligence for industrial applications. However, the limitations of pure data-driven methods, particularly in industries where data acquisition is costly and limited, have become apparent. This has led to a focus on blending physics with data-driven algorithms, mitigating the drawbacks of both approaches while emphasizing their respective advantages. This research proposes a novel framework for integrating physics-based performance models with deep learning algorithms for the prognostics of complex safety-critical systems. In this approach, physics-based models serve as a blueprint, capturing fundamental system behaviors, while deep learning algorithms, leveraging real-world sensor data, fill in gaps and identify subtle patterns indicative of potential problems. This hybrid methodology, utilizing techniques such as Physics-Informed Neural Networks (PINNs), offers a powerful solution for predicting system health. By fusing domain knowledge with data-driven insights, this approach promises more accurate, adaptable, and reliable models for health prediction. The resulting framework is versatile, applicable across various sectors including aerospace, manufacturing, and energy systems, ultimately contributing to safer, more efficient operations in our increasingly complex technological landscape.

Diagnostics