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At least 703 records · Page 39

Earth system modeling: can we stay ahead of what's actually happening?

Over the last forty years, Earth System Models have become more and more comprehensive and detailed. They have assimilated previously independent modeling efforts in ocean circulation, atmospheric composition, the stratosphere, land surface, and the cryosphere, and are today demonstrably more skillful than earlier efforts. Yet the structural uncertainty in the latest model projections is actually increasing. Meanwhile, impacts of climate change on, for instance, wildfires, tropical cyclones and sea level, appear to be increasing faster than we have been able to predict. I will address some of the current issues at the bleeding edges of model development and the continuing importance of model evaluation.

Gavin A Schmidt↗

Modeling the TPF interferometer

The Terrestrial Planet Finder interferometer design concepts are large and complex systems that must operate in environments that are impractical to reproduce in preflight testing. The structurally-connected design is 36 meters long - longer than all but one thermal vacuum chamber in existence. The formation flying design will be comprised of up to five separate spacecraft, each with a sunshield over 15 meters on a side, and is designed to operate with formation sizes spanning over 100 meters to very close formations. System-level verification of the performance of the designs will need to rely on analytical modeling. The effort to model the many physical aspects of the designs under study is under way*. This paper describes the program of modeling for the TPF-I concepts. The program includes a number of types of models, such as the standard stand-alone optics, thermal, and structural models, as well as an end-to-end performance model of the project system called the Observatory Simulation. Aspects of each model are discussed including the purpose, methods of implementation (software applications), and approaches to validation. Program-level considerations (such as model-to-model integration and configuration management) are also discussed. Given that there are at least seven different organizations contributing to model developments and more than twenty separate models, these are special challenges.

Henry, Curt↗

Environmental Testing of the HERMeS TDU-2 Hall Thruster

The Hall Effect Rocket with Magnetic Shielding (HERMeS) is a 12.5 kW magnetically shielded Hall thruster presently under development for deep-space missions. A development model HERMeS thruster, TDU-2, with borosilicate channel walls, has successfully undergone proto-qualification testing including random vibration and thermal-vacuum, demonstrating the thruster can survive critical launch and operational environmental requirements. The three-axis random vibrational tests were performed with the thruster body mounted directly to the shaker table using a modified loading schedule to compensate for the vibration isolation dampers under design for the flight thruster. Initial random vibration testing revealed issues with fragmentation of magnetic coil potting material and thruster spool mount fabrication weaknesses that were addressed with an alternate potting material and fabrication revisions that were then successfully retested with an additional round of random vibration tests. Thermal-vacuum testing involved three cycles of full-power 600 V 12.5 kW thruster operation from -121°C to +373°C which included eight hours at peak temperature as well as a hot restart. A thermal model of the test configuration was developed and validated with the experiment results within an average difference of 5°C. Before and after the random vibrational and thermal-vacuum tests, the thruster performance, plasma plume, thrust vector angle, discharge characteristics, and magnetic field profile were measured. The thruster performance, magnetic field, and most other parameters remained invariant throughout the environmental testing campaign. During the thermal testing, an increase in the discharge oscillation amplitude of 11% was observed as well as subtle thrust vector changes of ±0.2° as the thruster warmed from -121°C to +373°C.

Sorenson, Ryan↗

Simulating Ordinary Chondrite (Tamdakht) Ablation at the Hypersonic Materials Environmental Test System (HyMETS) Facility.

NASA’s Science Mission Directorate (SMD) created the Asteroid Threat Assessment Project (ATAP) to inform decision-makers of risks associated with Potentially Hazardous Objects (PHOs), which may pose an existential threat to human civilization. ATAP assesses risk, in part, by developing analytical physics-based damage models which draw upon data collected during material property characterization efforts, entry simulations, hazard simulations, and ground-based arc-jet testing. Therefore, a pathfinder test campaign was con-ducted at the Hypersonic Materials Environmental Test System (HyMETS) at the NASA Langley Re-search Center to investigate the ablation mechanisms of an ordinary chondrite (Tamdakht H5) and a terrestrial analog (basalt). The HyMETS facility is a 400 kW constricted arc heater used to screen material performance under simulated aerothermal conditions of hypersonic flow.1 Facility conditions were chosen to simulate Earth entry conditions be-tween the upper-mesosphere and the lower thermo-sphere. The ablation mechanisms of Tamdakht and bas-alt are illustrated with still images collected from high-speed video cameras (fig. 1, Tamdakht). Tamdakht produces a relatively stable melt flow, as evidenced by the perpetual growth of a flange at the sidewall and the exiguous detachment of molten material into the flow. Furthermore, an inspection of high-speed video and chemical analysis of the post-test melt layer suggests that the dominant mode of mass loss for Tamdakht, at these test conditions, is expressed through the vaporization of volatiles (e.g., iron, potassium, sodium, phosphorus, and sulfur). The vaporization rates of Tamdakht are greater than basalt under the most extreme test conditions, which leads to an enhanced blowing layer, in-creased thermal shielding, and reduced recession. The ablation mechanisms of basalt are markedly different from Tamdakht and are attributed to the presence of hydrated minerals dispersed at irregular intervals throughout the silicate matrix. Rapid de-composition of secondary minerals and the subsequent formation of water lead to the ejection of the subsurface and overlying melt layer. Furthermore, the presence of water is suspected of lowering the viscosity of the melt layer resulting in increased mass loss near the edge of the test article where drag forces overcome rheological properties (fig. 1, bas-alt). Finally, the results will be discussed in the broader context of meteorite-based material response model development and the potential impact on the Asteroid Threat Assessment Project (ATAP).

Brody K. Bessire↗

Computational models for the analysis/design of hypersonic scramjet components. I - Combustor and nozzle models

An overview of computational models developed for the complete, design-oriented analysis of a scramjet propulsion system is provided. The modular approach taken involves the use of different PNS models to analyze the individual propulsion system components. The external compression and internal inlet flowfields are analyzed by the SCRAMP and SCRINT components discussed in Part II of this paper. The combustor is analyzed by the SCORCH code which is based upon SPLITP PNS pressure-split methodology formulated by Dash and Sinha. The nozzle is analyzed by the SCHNOZ code which is based upon SCIPVIS PNS shock-capturing methodology formulated by Dash and Wolf. The current status of these models, previous developments leading to this status, and, progress towards future hybrid and 3D versions are discussed in this paper.

Dash, S. M.↗

An Integrated High Resolution Hydrometeorological Modeling Testbed using LIS and WRF

Scientists have made great strides in modeling physical processes that represent various weather and climate phenomena. Many modeling systems that represent the major earth system components (the atmosphere, land surface, and ocean) have been developed over the years. However, developing advanced Earth system applications that integrates these independently developed modeling systems have remained a daunting task due to limitations in computer hardware and software. Recently, efforts such as the Earth System Modeling Ramework (ESMF) and Assistance for Land Modeling Activities (ALMA) have focused on developing standards, guidelines, and computational support for coupling earth system model components. In this article, the development of a coupled land-atmosphere hydrometeorological modeling system that adopts these community interoperability standards, is described. The land component is represented by the Land Information System (LIS), developed by scientists at the NASA Goddard Space Flight Center. The Weather Research and Forecasting (WRF) model, a mesoscale numerical weather prediction system, is used as the atmospheric component. LIS includes several community land surface models that can be executed at spatial scales as fine as 1km. The data management capabilities in LIS enable the direct use of high resolution satellite and observation data for modeling. Similarly, WRF includes several parameterizations and schemes for modeling radiation, microphysics, PBL and other processes. Thus the integrated LIS-WRF system facilitates several multi-model studies of land-atmosphere coupling that can be used to advance earth system studies.

Kumar, Sujay V.↗

Evaluation of Aeroservoelastic Effects on Flutter

The HSCT Flight Controls Group is developing a longitudinal control law, known as Gamma-dot / V, for the NASA HSR program. Currently, this control law is based on a quasi-steady aeroelastic (QSAE) model of the vehicle. This control law was implemented into the p-k flutter analysis process for closed loop aeroservoelastic analysis. The available flexible models, developed for the TCA aeroelastic analysis, were used to assess the effect of control laws on flutter at several different Mach numbers and mass conditions. Significant structures and flight control system interaction was observed during the initial assessment. Figures 1 and 2 present a summary of the effect of total closed loop gain and phase on flutter mechanisms, based on ideal sensors and real sensors, for Mach 0.95 and mass M02 condition. Control laws based on ideal sensors gave rise to increased coupling between the rigid body short period mode and the first symmetric elastic mode. This reduced the stability margins for the first elastic mode and does not meet the required 6 dB gain margin requirement. The effect of "real" sensors significantly increased the structures and control system interactions. This caused the elastic,modes to be highly unstable throughout most of the flight envelope. State-space models were developed for several conditions and then MATLAB program was used for the aeroservoelastic stability analysis. These results provided an independent verification of the p-k flutter analysis findings. Good overall agreement was observed between the p-k flutter analysis and state-space model results for both damping and frequency comparisons. These results are also included in this document.

Nagaraja, K. S.↗

Model Based Engineering for Software Assurance

NASA's successful development of next generation space vehicles, habitats, and robotic systems will require reliable hardware and software systems. The aim of this initiative is to develop modeling methodology and tools to support Model-Based Systems Engineering (MBSE) for software assurance and reliability analysis. This effort expands the Unified Modeling Language (UML) software design models to include fault data for the extraction of Failure Modes and Effects Criticality Analysis (FMECA) and Fault Tree Analysis (FTA) for software. We explored different modeling approaches to integrate the UML software design models with the Systems Modeling Language (SysML) system models to generate an integrated model and reliability tools that take into account software and hardware interfaces.The benefits of this concept directly affect the safety community with quick turnarounds to produce software assurance and reliability analysis artifacts and the ability to visualize failure effects, both hardware and software. The result is enhanced system design integrity and early identification of system risks. This initiative will enable software assurance activities early in the system design lifecycle, facilitating the discovery of design weaknesses and enhancing the capability to produce safe, hazard-free systems

Wang, Lui↗

Design, fabrication and test of a trace contaminant control system

A trace contaminant control system was designed, fabricated, and evaluated to determine suitability of the system concept to future manned spacecraft. Two different models were considered. The load model initially required by the contract was based on the Space Station Prototype (SSP) general specifications SVSK HS4655, reflecting a change from a 9 man crew to a 6 man crew of the model developed in previous phases of this effort. Trade studies and a system preliminary design were accomplished based on this contaminant load, including computer analyses to define the optimum system configuration in terms of component arrangements, flow rates and component sizing. At the completion of the preliminary design effort a revised contaminant load model was developed for the SSP. Additional analyses were then conducted to define the impact of this new contaminant load model on the system configuration. A full scale foam-core mock-up with the appropriate SSP system interfaces was also fabricated.

Source record↗

Program test objectives milestone 3

The following conclusions have been developed relative to propulsion system technology adequacy for efficient development and operation of recoverable and expendable launch vehicles (RLV and ELV) and the benefits which the integrated propulsion technology demonstrator will provide for enhancing technology: (1) Technology improvements relative to propulsion system design and operation can reduce program cost. Many features or improvement needs to enhance operability, reduce cost, and improve payload are identified. (2) The Integrated Propulsion Technology Demonstrator (IPTD) Program provides a means of resolving the majority of issues associated with improvement needs. (3) The IPTD will evaluate complex integration of vehicle and facility functions in fluid management and propulsion control systems, and provides an environment for validating improved mechanical and electrical components. (4) The IPTD provides a mechanism for investigating operational issues focusing on reducing manpower and time to perform various functions at the launch site. These efforts include model development, collection of data to validate subject models, and ultimate development of complex time line models. (5) The IPTD provides an engine test bed for tri/bi-propellant engine development firings which is representative of the actual vehicle environment. (6) The IPTD provides for only a limited multiengine configuration integration environment for RLV. Multiengine efforts may be simulated for a number of subsystems and a number of subsystems are relatively independent of the multiengine influences.

Gaynor, T. L.↗

Developing Deep Learning Models for System Remaining Useful Life Predictions: Application to Aircraft Engines

Prognostics and health management (PHM) is an important part of ensuring reliable operations of complex safety- critical systems. System-level remaining useful life (RUL) estimation is a much more complex problem than making estimations at the component level, and system-level RUL methodologies remain sparse in the literature. Model-based approaches have traditionally worked in the past for components such as capacitors, MOSFETs, batteries, or hard-drives (to name a few examples), but developing high fidelity dynamics models of cyber physical systems that can be used to study the effects of multiple degrading components in the system remains a challenging task. Some initial work on model-based System RUL predictions was demonstrated in Khorasgani, et al [1], but, to generalize the system-level prognostics problem, we have to resort to pure data driven and hybrid approaches. In this work, we propose an end-to-end data- driven framework for developing deep learning models to predict remaining useful life of cyber physical systems operating under unknown faulty conditions. The raw data is organized with a data schema that improves the model development process and down stream data analysis tasks. Due to the unknown faulty conditions, the raw sensor data is transformed into signals that expose the underlying degradation processes, which are then used for model development. Bayesian Optimization is used to tune the model parameters prior to training and validation. We show that this approach results in accurate predictions within 3 cycles to end of life (EOL). We demonstrate the effectiveness of our approach by applying it to the N-CMAPSS turbofan engine dataset recently released by NASA, which includes high fidelity degradation modeling, real world operating conditions, and a large set of fault operating modes.

Prognostics↗

Prediction of Lunar Reconnaissance Orbiter Reaction Wheel Assembly Angular Momentum Using Regression Analysis

This study determines the feasibility of creating a tool that can accurately predict Lunar Reconnaissance Orbiter (LRO) reaction wheel assembly (RWA) angular momentum, weeks or even months into the future. LRO is a three-axis stabilized spacecraft that was launched on June 18, 2009. While typically nadir-pointing, LRO conducts many types of slews to enable novel science collection. Momentum unloads have historically been performed approximately once every two weeks with the goal of maintaining system total angular momentum below 70 Nms; however flight experience shows the models developed before launch are overly conservative, with many momentum unloads being performed before system angular momentum surpasses 50 Nms. A more accurate model of RWA angular momentum growth would improve momentum unload scheduling and decrease the frequency of these unloads. Since some LRO instruments must be deactivated during momentum unloads and in the case of one instrument, decontaminated for 24 hours there after a decrease in the frequency of unloads increases science collection. This study develops a new model to predict LRO RWA angular momentum. Regression analysis of data from October 2014 to October 2015 was used to develop relationships between solar beta angle, slew specifications, and RWA angular momentum growth. The resulting model predicts RWA angular momentum using input solar beta angle and mission schedule data. This model was used to predict RWA angular momentum from October 2013 to October 2014. Predictions agree well with telemetry; of the 23 momentum unloads performed from October 2013 to October 2014, the mean and median magnitude of the RWA total angular momentum prediction error at the time of the momentum unloads were 3.7 and 2.7 Nms, respectively. The magnitude of the largest RWA total angular momentum prediction error was 10.6 Nms. Development of a tool that uses the models presented herein is currently underway.

LRO↗

Development of an Uncertainty Model for the National Transonic Facility

This paper introduces an uncertainty model being developed for the National Transonic Facility (NTF). The model uses a Monte Carlo technique to propagate standard uncertainties of measured values through the NTF data reduction equations to calculate the combined uncertainties of the key aerodynamic force and moment coefficients and freestream properties. The uncertainty propagation approach to assessing data variability is compared with ongoing data quality assessment activities at the NTF, notably check standard testing using statistical process control (SPC) techniques. It is shown that the two approaches are complementary and both are necessary tools for data quality assessment and improvement activities. The SPC approach is the final arbiter of variability in a facility. Its result encompasses variation due to people, processes, test equipment, and test article. The uncertainty propagation approach is limited mainly to the data reduction process. However, it is useful because it helps to assess the causes of variability seen in the data and consequently provides a basis for improvement. For example, it is shown that Mach number random uncertainty is dominated by static pressure variation over most of the dynamic pressure range tested. However, the random uncertainty in the drag coefficient is generally dominated by axial and normal force uncertainty with much less contribution from freestream conditions.

Walter, Joel A.↗

International Space Station Bipropellant Plume Contamination Model Update for Short Thruster Pulse Widths

The International Space Station (ISS) Bipropellant Plume Contamination Model has been a vital tool for characterizing the thruster plume-induced contamination environment at the ISS but was not intended to be used for very short thruster pulse widths. This paper presents an updated model that ensures full start-up and shut-down phases are modeled for each thruster firing, when the majority of liquid phase contaminant mass is released. The updated ISS Bipropellant Plume Contamination Model prevents potential under-prediction of thruster plume-induced contamination due to visiting vehicle proximity operations and provides a way to take advantage of thruster start-up and shut-down data performance data gathered during thruster test programs, if available. The International Space Station (ISS) Bipropellant Plume Contamination Model developed by Boeing Space Environments is a semi-empirical model anchored in flight experiment data and has been a vital tool for characterizing the thruster plume-induced contamination environment at the ISS.[1] The current model utilizes flight experiment data from the Plume Impingement Contamination (PIC) and Shuttle Plume Impingement Flight Experiment (SPIFEX) studies, which include Orbiter 3870 N Primary Reaction Control System (PRCS) and Russian 130 N thrusters operating in pulse mode with 80-100 ms.[2] As the next generation of crew and cargo visiting vehicles are developed and arrive at ISS, minimum pulse widths of vehicle thrusters used for ISS proximity operations have decreased significantly below 80 ms. An update to the ISS Bipropellant Contamination Model is needed to prevent potential under-prediction of thruster plume-induced contamination for these very short pulse widths. Contamination due to thruster plumes occurs in the liquid phase (i.e., unburned or partially burned propellant in the plume). Liquid phase releases primarily occur during thruster start-up and shut-down phases, with the steady state phase contributing a small amount to the total contaminant mass released. The current ISS Bipropellant Plume Contamination Model includes functional dependencies on thruster parameters (thrust, mass flow rate, specific impulse (Isp)), distance to receiver surface, and angle off plume centerline. For modeling purposes, contaminant mass released scales linearly with pulse width. This is a conservative approach for pulse widths greater than 80 ms but could under-predict contamination for very short pulse widths (i.e., with little or no steady state phase). This paper presents a model update to add a functional dependency on commanded pulse width to ensure the portion of the pulse spent in start-up and shut-down phases is appropriately modeled, when the majority of liquid phase contaminant mass is released. The updated model prevents potential under-prediction of thruster plume-induced contamination due to visiting vehicle proximity operations while providing a way to take advantage of thruster start-up and shut-down data gathered during test programs, if available. Developing the plume model for a specific thruster using the ISS Bipropellant Plume Contamination Model must be done in consideration of all available thruster performance data. Example thruster data will be used to illustrate this point and options for implementing the model update with existing ISS Bipropellant Plume Contamination Model code will be discussed.

plume contamination↗

Clover development during spaceflight: A model system

The development of legume root nodules was studied as a model system for the examination of gravitational effects on plant root development. In order to examine whether rhizobial association with clover roots can be achieved in microgravity, experiments were performed aboard the KC-135 parabolic aircraft and aboard the sounding rocket mission Consort 3. Binding of rhizobia to roots and the initial stages of root nodule development successfully occurred in microgravity. Seedling germination experiments were performed in the sliding block device, the Materials Dispersion Apparatus, aboard STS-37. When significant hydration of the seeds was achieved, normal rates of germination and seedling development were observed.

Guikema, James A.↗

Deriving Severe Hail Likelihood from Satellite Observations and Model Reanalysis Parameters using a Deep Neural Network

Geostationary satellite imagers, such as those of the Geostationary Operational Environmental Satellite (GOES) series, have been observing severe convection at 15–60-minute intervals for over 40 years. When properly assessed, such a data record can be valuable in efforts of estimating severe storm risk throughout the diurnal cycle based on automated detection of patterns consistently found atop severe storms. Furthermore, environmental conditions favorable for severe weather are well-known and are thought to be represented well by modern reanalysis products. Promoting resilience against such hazards on local and global scales is a chief goal the NASA Disasters program, which seeks to encourage use of satellite observations to mitigate risk. For instance, hail is the costliest severe weather hazard across the globe in terms of insured loss, but reporting inconsistencies for hail events globally make it difficult to develop models that can quantify the risk. Satellite observation and model reanalysis taken together have the potential to, with reasonable skill and specificity, characterize environmental conditions that are favorable for hazardous weather, and thereby enable creation of hazard climatologie. Such climatologies are particularly useful over regions without extensive radar networks or storm reporting. By mapping the multivariate combination of observed cloud features and reanalysis environmental parameters/indices to United States Next Generation Weather Radar (NEXRAD) radar-estimated Maximum Expected Size of Hail (MESH) by way of a deep neural network (DNN), estimates of likelihood for potentially severe hail can be produced. Such estimates are of greater complexity and efficiency than could be performed with previous multivariate or logistic regression analyses for observed points within convective systems. Statistical distributions of convective parameters from satellite and reanalysis are shown to highlight non-severe/severe class separation for well-known hailstorm predictors, e.g., overshooting cloud top characteristics, deep-layer wind shear, mid-level stability, helicity, and convective inhibition. These complex, multivariate predictor relationships are exploited within a DNN, which can efficiently produce a quantitative hail risk metric with better than 70% detection rate and under 30% false alarms. These hail classifications can then be aggregated across the satellite record to yield a hazard climatology for hail frequency and severity – knowledge of which is of particular interest to those who manage risk (e.g., insurers) and are seeking opportunities to identify hail-prone regions, particularly in developing nations. This NASA study uses satellite observations and model parameters in a DNN to perform climatological hailstorm analysis in support of catastrophe model development, with the hope of promoting risk resilience particularly in regions without adequate weather radar coverage.

Passive Remote Sensing↗

Computational Ion Optics Design Evaluations

Ion optics computational models are invaluable tools in the design of ion optics systems. In this study a new computational model developed by an outside vendor for use at the NASA Glenn Research Center (GRC) is presented. This computational model is a gun code that has been modified to model the plasma sheaths both upstream and downstream of the ion optics. The model handles multiple species (e.g. singly and doubly-charged ions) and includes a charge-exchange model to support erosion estimations. The model uses commercially developed solid design and meshing software to allow high flexibility in ion optics geometric configurations. The results from this computational model are applied to the NEXT project to investigate the effects of crossover impingement erosion seen during the 2000-hour wear test.

Malone, Shane P.↗

Report of the panel on geopotential fields: Gravity field, section 8

The objective of the Geopotential Panel was to develop a program of data acquisition and model development for the Earth's gravity and magnetic fields that meet the basic science requirements of the solid Earth and ocean studies. Presented here are the requirements for gravity information and models through the end of the century, the present status of our knowledge, data acquisition techniques, and an outline of a program to meet the requirements.

Anderson, Allen Joel↗