A general model for motivational analyses of exchange relationships
Model for motivational analysis of exchange relationships between consumer and supplier
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Model for motivational analysis of exchange relationships between consumer and supplier
In order to explain the results of the testing conducted in Part I and relate the subscale test specimen performance to case performance during prelaunch loading, a comprehensive analysis program was conducted. Finite element models of both full-scale case and subscale test coupons were made. Validated axisymmetric models were used for the case analyses. Modeling of coupons was accomplished using a generalized plane strain finite element model in most cases, although some three-dimensional finite element modeling was used to investigate the importance of three-dimensional effects on the coupon performance. The large number of plies and complexity of the test coupons used limited the finite element grids to a through-the-thickness discretization of one element per ply. Delaminations observed in the helical ply dropoff region were modeled using frictionless sliders. Comparisons of predicted strains and displacements were made with the test data from both cases and coupons to validate the finite element models. Based on observations of the test results and finite element predictions, a failure criterion for both coupons and cases was postulated and then validated by comparing performance predictions to test results. Finally, the validated failure criterion was used to predict the performance of the first two flight cases under prelaunch loads.
AIRS yield and sampling vary with cloud state. Careful utilization of collocated multiple satellite sensors is necessary. Profile differences between AIRS and ECMWF model analyses indicate that AIRS has high sampling and excellent accuracy for certain meteorological conditions. Cloud-dependent sampling biases may have large impact on AIRS L2 and L3 data in climate research. MBL clouds / lower tropospheric stability relationship is one example. AIRS and CloudSat reveal a reasonable climatology in the MBL cloud regime despite limited sampling in stratocumulus. Thermodynamic parameters such as EIS derived from AIRS data map these cloud conditions successfully. We are working on characterizing AIRS scenes with mixed cloud types.
In order to improve operational safety and efficiency, the transportation industry, including aviation, has an urgent need for accurate diagnoses and predictions of clouds and associated weather conditions. Adverse weather accounts for 70% of all air traffic delays within the U.S. National Airspace System. The Federal Aviation Administration has determined that as much as two thirds of weather-related delays are potentially avoidable with better weather information and roughly 20% of all aviation accidents are weather related. Thus, it is recognized that an important factor in meeting the goals of the Next Generation Transportation System (NexGen) vision is the improved integration of weather information. The concept of a 4-D weather cube is being developed to address that need by integrating observed and forecasted weather information into a shared 4-D database, providing an integrated and nationally consistent weather picture for a variety of users and to support operational decision support systems. Weather analyses and forecasts derived using Numerical Weather Prediction (NWP) models are a critical tool that forecasters rely on for guidance and also an important element in current and future decision support systems. For example, the Rapid Update Cycle (RUC) and the recently implemented Rapid Refresh (RR) Weather Research and Forecast (WRF) models provide high frequency forecasts and are key elements of the FAA Aviation Weather Research Program. Because clouds play a crucial role in the dynamics and thermodynamics of the atmosphere, they must be adequately accounted for in NWP models. The RUC, for example, cycles at full resolution five cloud microphysical species (cloud water, cloud ice, rain, snow, and graupel) and has the capability of updating these fields from observations. In order to improve the models initial state and subsequent forecasts, cloud top altitude (or temperature, T(sub c)) derived from operational satellite data, surface observations of cloud base altitude, radar reflectivity, and lightning data are used to help build and remove clouds in the models assimilation system. Despite this advance and the many recent advances made in our understanding of cloud physical processes and radiative effects, many problems remain in adequately representing clouds in models. While the assimilation of cloud top information derived from operational satellite data has merit, other information is available that has not yet been exploited. For example, the vertically integrated cloud water content (CWC) or cloud water path (CWP) and cloud geometric thickness (delta Z) are standard products being derived routinely from operational satellite data. These and other cloud products have been validated under a variety of conditions. Since the uncertainties have generally been found to be less than those found in model analyses and forecasts, the satellite products should be suitable for data assimilation, provided an appropriate strategy can be developed that links the satellite-derived cloud parameters with cloud parameters specified in the model. In this paper, we briefly outline such a strategy and describe a methodology to retrieve cloud water content profiles from operational satellite data. Initial results and future plans are presented. It is expected that the direct assimilation of this new product will provide the most accurate depiction of the vertical distribution of cloud water ever produced at the high spatial and temporal resolution needed for short term weather analyses and forecasts.
A 3-D geometry/mass model of Long Duration Exposure Facility (LDEF) was generated to aid in the interpretation of ionizing radiation experiments relative to the influence of varying shielding distributions around the dosimetry, and to allow more definitive calculations and comparisons with the measured data. This model takes into account the major individual structural members of the LDEF spacecraft, the mass in each experiment tray, and, for selected trays containing ionizing radiation dosimetry, major parts within the tray are modeled. The geometry/mass model, together with a ray tracing algorithms, was programmed for use both as a stand alone code in determining 3-D shielding distributions at dosimetry locations, and as a geometry module that can be interfaced with radiation transport codes.
Solar Lyman alpha irradiance is estimated from various solar indices using linear regression analyses. Models developed with multiple linear regression analysis, including daily values and 81-day running means of solar indices, predict reasonably well both the short- and long-term variations observed in Lyman alpha. It is shown that the full disk equivalent width of the He line at 1083 nm offers the best proxy for Lyman alpha, and that the total irradiance corrected for sunspot effect also has a high correlation with Lyman alpha.
We present updated evaluation of stratospheric ozone profile trends in the 60° S–60°N latitude range using long-term ground-based and satellite climate data records, as well as simulations by chemistry-climate models. The trends are evaluated using the LOTUS (Long-term Ozone Trends and Uncertainties in the Stratosphere) regression model. Analyses of satellite data confirm the statistically significant positive ozone trends in the period 2000–2024 in the upper stratosphere of ~1–3% per decade, with larger trends at mid-latitudes compared to the tropics. The trends are slightly positive or close to zero in the middle stratosphere, and mostly negative, -1 to -2% per decade, in the lower stratosphere, but they are not statistically significant. The morphology and magnitude of ozone trends are similar to previous analyses (2000–2020 trends). Ozone trends in 2000–2024 predicted by chemistry-climate model simulations are in good agreement with combined satellite trends. In the upper stratosphere, models predict a slightly stronger ozone recovery than observations. In the lower stratosphere, both models and satellite observations report negative trends in the tropics, while modelled ozone trends are slightly positive at mid-latitudes. Ozone profile trends over several stations estimated from ground-based records capture the same overall vertical pattern of ozone trends as merged gridded satellite datasets. Analyses of regional ozone profile trends in 2003–2024 using merged satellite datasets confirmed the previous observations of a longitudinal structure in ozone trends in the NH mid-latitude stratosphere, with positive trends over Scandinavia and negative trends over Siberia. However, the magnitude of this dipole-like structure is reduced compared to previous analyses.
High-frequency TMI and AMSR-E radiances, which are sensitive to precipitation over land, are assimilated into the Goddard Weather Research and Forecasting Model- Ensemble Data Assimilation System (WRF-EDAS) for a few heavy rain events over the continental US. Independent observations from surface rainfall, satellite IR brightness temperatures, as well as ground-radar reflectivity profiles are used to evaluate the impact of assimilating rain-sensitive radiances on cloud and precipitation within WRF-EDAS. The evaluations go beyond comparisons of forecast skills and domain-mean statistics, and focus on studying the cloud and precipitation features in the jointed rainradiance and rain-cloud space, with particular attentions on vertical distributions of height-dependent cloud types and collective effect of cloud hydrometers. Such a methodology is very helpful to understand limitations and sources of errors in rainaffected radiance assimilations. It is found that the assimilation of rain-sensitive radiances can reduce the mismatch between model analyses and observations by reasonably enhancing/reducing convective intensity over areas where the observation indicates precipitation, and suppressing convection over areas where the model forecast indicates rain but the observation does not. It is also noted that instead of generating sufficient low-level warmrain clouds as in observations, the model analysis tends to produce many spurious upperlevel clouds containing small amount of ice water content. This discrepancy is associated with insufficient information in ice-water-sensitive radiances to address the vertical distribution of clouds with small amount of ice water content. Such a problem will likely be mitigated when multi-channel multi-frequency radiances/reflectivity are assimilated over land along with sufficiently accurate surface emissivity information to better constrain the vertical distribution of cloud hydrometers.
Sounding rocket Experiment 74-18 was designed to demonstrate the effects of the Black Brandt rocket acceleration levels (during the low-g coast phase of its flight) on the motion of a liquid metal system to assist in preflight design. Some post flight analyses were also conducted. Preflight studies consisted of heat transfer analysis and convection sensitivity and convection modeling analyses which aided in the: (1) final selection of fluid materials (indium-lead melts rather than paraffins); (2) design and timing of heater and quench system; and (3) preflight predictions of the degree of lead penetration into the pure indium segment of the fluid. Postflight studies involved: (1) updating the convection sensitivity calculations by utilizing actual flight gravity levels; and (2) modeling the mixing in the flight samples.
We present a statistical representation of the aggregate effects of deep convection on the chemistry and dynamics of the Upper Troposphere (UT) based on direct aircraft observations of the chemical composition of the UT over the Eastern United States and Canada during summer. These measurements provide new and unique observational constraints on the chemistry occurring downwind of convection and the rate at which air in the UT is recycled, previously only the province of model analyses. These results provide quantitative measures that can be used to evaluate global climate and chemistry models.
The threat for aircraft icing in clouds is a significant hazard that routinely impacts aviation operations. Accurate diagnoses and forecasts of aircraft icing conditions requires identifying the location and vertical distribution of clouds with super-cooled liquid water (SLW) droplets, as well as the characteristics of the droplet size distribution. Traditional forecasting methods rely on guidance from numerical models and conventional observations, neither of which currently resolve cloud properties adequately on the optimal scales needed for aviation. Satellite imagers provide measurements over large areas with high spatial resolution that can be interpreted to identify the locations and characteristics of clouds, including features associated with adverse weather and storms. This paper describes new techniques for interpreting cloud products derived from satellite data to infer the flight icing threat to aircraft. For unobscured low clouds, the icing threat is determined using empirical relationships developed from correlations between satellite imager retrievals of liquid water path and droplet size with icing conditions reported by pilots (PIREPS). For deep ice over water cloud systems, ice and liquid water content (IWC and LWC) profiles are derived by using the imager cloud properties to constrain climatological information on cloud vertical structure and water phase obtained apriori from radar and lidar observations, and from cloud model analyses. Retrievals of the SLW content embedded within overlapping clouds are mapped to the icing threat using guidance from an airfoil modeling study. Compared to PIREPS and ground-based icing remote sensing datasets, the satellite icing detection and intensity accuracies are approximately 90% and 70%, respectively, and found to be similar for both low level and deep ice over water cloud systems. The satellite-derived icing boundaries capture the reported altitudes over 90% of the time. Satellite analyses corresponding to the time and location of several recent aviation accidents and with icing PIREPS are also presented that reveal skill in identifying severe icing conditions. These results demonstrate the utility of satellite cloud retrievals for quantitatively diagnosing the potential for icing conditions on temporal and spatial scales that should be useful to the aviation community. Plans are being developed to deliver these new satellite products to the GOES-R Proving Ground in the near future so that they can be evaluated in operational applications.
The dynamic fidelity of an operational blade-element simulation model of the UH-60A helicopter is assessed for the hovering and low-speed flight regimes. Nonparametric frequency-response identification techniques and time-history comparisons are used to determine the validity of vehicle responses. Frequency-domain methods are applied to the model to isolate deficiencies and verify refinements and corrections. A dedicated flight-test program was conducted to provide data used in the analyses. Model deficiencies are also identified by using side-by-side pilot assessments of a motion-based simulation and of a test aircraft. Model refinements are found to improve fidelity significantly in the frequency range of interest to handling-qualities research. The applicability of the model to high-bandwidth flight-control research is also discussed.
Simulations of Antarctic ozone photochemistry performed using a photochemical model integrated along air parcel trajectories are described. This type of model has a major advantage at high latitudes of being able to simulate correctly the complex interaction between photolysis and temperature fields, which, because of the polar night cannot be represented accurately in a zonally averaged framework. Isentropic air parcel trajectories were computed using Meteorological Office global model analyses and forecast fields from positions along the ER-2 flight paths during the Airborne Antarctic Ozone Experiment in Austral Spring 1987. A photochemical model is integrated along these trajectories using the aircraft observations to initialize constituent concentrations. The model includes additional reactions of the ClO dimer and also bromine reactions, which are thought to play a significant role in Antarctica. The model also includes heterogeneous reactions which are invoked when the air parcel passes through a polar stratospheric cloud (PSC). The existence of a PSC is determined throughout the course of the model integration from the parcel temperature and the saturated vapour pressure of water over an assumed H2O/HNO3 mixture. The air parcel temperature is used to determine the saturated vapor pressure of HNO3 over the same mixture. Mixing ratios which exceed saturation result in condensation of the excess in the model and hence lead to a reduction of the amount of gas phase NO2 available for chemical reaction.
For a Ni-5.2 Al-14.2 Cr at.% alloy with moderate solute supersaturations, the compositional pathways, as measured with atom-probe tomography, during early to later stage y'(LI2)-precipitation (R = 0.45-10 nm), aged at 873 K, are discussed in light of a multi-component coarsening model. Employing nondilute thermodynamics, detailed model analyses during quasistationary coarsening of the experimental data establish that the y/y' interfacial free-energy is 22- 23+/-7 mJ/sq m. Additionally, solute diffusivities are significantly slower than model estimates. Strong quantitative evidence indicates that an observed y'-supersaturation of Al results from the Gibbs-Thomson effect, providing the first experimental verification of this phenomenon. The Gibbs-Thomson relationship, for a ternary system, as well as differences in measured phase equilibria with CALPHAD assessments, are considered in great detail.
In navigating spacecraft throughout the solar system, the space navigator relies on three academic disciplines - optimization, estimation, and control - that work on mathematical models of the real world. Thus, the navigator determines the flight path that will consume propellant and other resources in an efficient manner, determines where the craft is and predicts where it will go, and transfers it onto the optimal trajectory that meets operational and mission constraints. Mission requirements, for example, demand that observational measurements be made with sufficient precision that relativity must be modeled in collecting and fitting (the estimation process) the data, and propagating the trajectory. Thousands of parameters are now determined in near real-time to model the gravitational forces acting on a spacecraft in the vicinity of an irregularly shaped body. Completing these tasks requires mathematical models, analyses, and processing techniques. Newton, Gauss, Lambert, Legendre, and others are justly famous for their contributions to the mathematics of these tasks. More recently, graduate students participated in research to update the gravity model of the Saturnian system, including higher order gravity harmonics, tidal effects, and the influence of the rings. This investigation was conducted for the Cassini project to incorporate new trajectory modeling features in the navigation software. The resulting trajectory model will be used in navigating the 4-year tour of the Saturnian satellites. Also, undergraduate students are determining the ephemerides (locations versus time) of asteroids that will be used as reference objects in navigating the New Millennium's Deep Space 1 spacecraft autonomously.
The problems in applying standard electric utility models, analyses, and algorithms to the study of the stability of spacecraft power conditioning and distribution systems are discussed. Both single-phase and three-phase systems are considered. Of particular concern are the load and generator models that are used in terrestrial power system studies, as well as the standard assumptions of load and topological balance that lead to the use of the positive sequence network. The standard assumptions regarding relative speeds of subsystem dynamic responses that are made in the classical transient stability algorithm, which forms the backbone of utility-based studies, are examined. The applicability of these assumptions to a spacecraft power system stability study is discussed in detail. In addition to the classical indirect method, the applicability of Liapunov's direct methods to the stability determination of spacecraft power systems is discussed. It is pointed out that while the proposed method uses a solution process similar to the classical algorithm, the models used for the sources, loads, and networks are, in general, more accurate. Some preliminary results are given for a linear-graph, state-variable-based modeling approach to the study of the stability of space-based power distribution networks.
Techniques for orbital refueling of space based vehicles were developed and experimental programs to verify these techniques were identified. Orbital refueling operations were developed for two cryogenic orbital transfer vehicles (OTV's) and an Earth storable low thrust liquid propellant vehicle. Refueling operations were performed assuming an orbiter tanker for near term missions and an orbital depot. Analyses were conducted using liquid hydrogen and N2O4. The influence of a pressurization system and acquisition device on operations was also considered. Analyses showed that vehicle refill operations will be more difficult with a cryogen than with an earth storable. The major elements of a successful refill with cryogens include tank prechill and fill. Propellant quantities expended for tank prechill appear to to insignificant. Techniques were identified to avoid loss of liquid or excessive tank pressures during refill. It was determined that refill operations will be similar whether or not an orbiter tanker or orbital depot is available. Modeling analyses were performed for prechill and fill tests to be conducted assuming the Spacelab as a test bed, and a 1/10 scale model OTV (with LN2 as a test fluid) as an experimental package.
There is a natural partitioning of scientific interest amongst three specialties of aerosol research: modeling, in situ measurements, and remote sensing. The community sees enhanced measurement capabilities when these groups interact, and this strengthens the overall scientific impact on climate and air quality. The Models, In situ, and Remote sensing of Aerosols (MIRA) working group connects members of the different aerosol communities through collaborative projects. What is MIRA? MIRA is a forum that fosters international collaborations amongst the aerosol specialties. MIRA is also a collection of interdisciplinary projects with clear goals that are pursued by small working groups. Finally, MIRA projects are generally characterized by requests for additional scientific data (both observational and modeled). Why? The purpose of MIRA is to contextualize both observations and model results through the encouragement of holistic projects and collaborations. How does MIRA differ from other projects? MIRA focuses on interdisciplinarity to improve measurements and their utility, so MIRA complements the activities of other groups. For example, ensemble model runs of AeroCom could be used in a MIRA project with greater robustness than a similar effort that uses single-model analyses. We present a description of MIRA and brief descriptions of some of the current MIRA topics, which include Satellite-Assisted Particulate Matter (SAPM), Mapping of Aerosol lidar ratios for CALIPSO (MAC), Tables of Aerosol Optics (TAO), and the Harmonization of aerosol Assimilation Models and Retrievals (HAMR). Finally, we discuss the immediate science goals and organization of MIRA. See https://science.larc.nasa.gov/mira-wg/ for more information.