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NASA NTRS2016

Transitioning Enhanced Land Surface Initialization and Model Verification Capabilities to the Kenya Meteorological Department (KMD)

Flooding, severe weather, and drought are key forecasting challenges for the Kenya Meteorological Department (KMD), based in Nairobi, Kenya. Atmospheric processes leading to convection, excessive precipitation and/or prolonged drought can be strongly influenced by land cover, vegetation, and soil moisture content, especially during anomalous conditions and dry/wet seasonal transitions. It is thus important to represent accurately land surface state variables (green vegetation fraction, soil moisture, and soil temperature) in Numerical Weather Prediction (NWP) models. The NASA SERVIR and the Short-term Prediction Research and Transition (SPoRT) programs in Huntsville, AL have established a working partnership with KMD to enhance its regional modeling capabilities. SPoRT and SERVIR are providing experimental land surface initialization datasets and model verification capabilities for capacity building at KMD. To support its forecasting operations, KMD is running experimental configurations of the Weather Research and Forecasting (WRF; Skamarock et al. 2008) model on a 12-km/4-km nested regional domain over eastern Africa, incorporating the land surface datasets provided by NASA SPoRT and SERVIR. SPoRT, SERVIR, and KMD participated in two training sessions in March 2014 and June 2015 to foster the collaboration and use of unique land surface datasets and model verification capabilities. Enhanced regional modeling capabilities have the potential to improve guidance in support of daily operations and high-impact weather and climate outlooks over Eastern Africa. For enhanced land-surface initialization, the NASA Land Information System (LIS) is run over Eastern Africa at ~3-km resolution, providing real-time land surface initialization data in place of interpolated global model soil moisture and temperature data available at coarser resolutions. Additionally, real-time green vegetation fraction (GVF) composites from the Suomi-NPP VIIRS instrument is being incorporated into the KMD-WRF runs, using the product generated by NOAA/NESDIS. Model verification capabilities are also being transitioned to KMD using NCAR's Model *Corresponding author address: Jonathan Case, ENSCO, Inc., 320 Sparkman Dr., Room 3008, Huntsville, AL, 35805. Email: Jonathan.Case-1@nasa.gov Evaluation Tools (MET; Brown et al. 2009) software in conjunction with a SPoRT-developed scripting package, in order to quantify and compare errors in simulated temperature, moisture and precipitation in the experimental WRF model simulations. This extended abstract and accompanying presentation summarizes the efforts and training done to date to support this unique regional modeling initiative at KMD. To honor the memory of Dr. Peter J. Lamb and his extensive efforts in bolstering weather and climate science and capacity-building in Africa, we offer this contribution to the special Peter J. Lamb symposium. The remainder of this extended abstract is organized as follows. The collaborating international organizations involved in the project are presented in Section 2. Background information on the unique land surface input datasets is presented in Section 3. The hands-on training sessions from March 2014 and June 2015 are described in Section 4. Sample experimental WRF output and verification from the June 2015 training are given in Section 5. A summary is given in Section 6, followed by Acknowledgements and References.

land surface modeling↗

NASA NTRS1980

Analytical simulation of nonlinear satellite links

It is noted that performance predictions for nonlinear digital satellite channels are usually obtained by either purely analytical methods or Monte Carlo simulations. When used with other than very simple channel models, however, they become extremely costly. It is shown that, through analytical modeling of the effect of the nonlinearity on the uplink waveform, it is possible to obtain approximate performance predictions with a minimum of computer time. It is also demonstrated that the results agree quite well with Monte Carlo simulations and that significant trade-offs can be performed with this tool. An analytical simulation based on Blachman's (1968) definition of signal x signal, signal x noise, and noise x noise terms is shown to provide the required flexibility for modeling the effect of signal distortions on the link performance and to produce good results over a wide range of nonlinearities and channel conditions.

Braun, W. R.↗

NASA NTRS2012

Linking Plasma Conditions in the Magnetosphere with Ionospheric Signatures

Modeling of the full magnetosphere, ring current and ionosphere system has become an indispensable tool in analyzing the series of events that occur during geomagnetic storms. The CCMC has a full model suite available for the magnetosphere, together with visualization tools that allow a user to perform a large variety of analyses. The January, 21, 2005 storm was a moderate-size storm that has been found to feature a large penetration electric field and unusually large polar caps (low-latitude precipitation patterns) that are otherwise found in super storms. Based on simulations runs at CCMC we can outline the likely causes of this behavior. Using visualization tools available to the online user we compare results from different magnetosphere models and present connections found between features in the magnetosphere and the ionosphere that are connected magnetically. The range of magnetic mappings found with different models can be compared with statistical models (Tsyganenko) and the model's fidelity can be verified with observations from low earth orbiting satellites such as DMSP and TIMED.

Rastaetter, Lutz↗

NASA NTRS2010

Performance Analysis of Scientific and Engineering Applications Using MPInside and TAU

In this paper, we present performance analysis of two NASA applications using performance tools like Tuning and Analysis Utilities (TAU) and SGI MPInside. MITgcmUV and OVERFLOW are two production-quality applications used extensively by scientists and engineers at NASA. MITgcmUV is a global ocean simulation model, developed by the Estimating the Circulation and Climate of the Ocean (ECCO) Consortium, for solving the fluid equations of motion using the hydrostatic approximation. OVERFLOW is a general-purpose Navier-Stokes solver for computational fluid dynamics (CFD) problems. Using these tools, we analyze the MPI functions (MPI_Sendrecv, MPI_Bcast, MPI_Reduce, MPI_Allreduce, MPI_Barrier, etc.) with respect to message size of each rank, time consumed by each function, and how ranks communicate. MPI communication is further analyzed by studying the performance of MPI functions used in these two applications as a function of message size and number of cores. Finally, we present the compute time, communication time, and I/O time as a function of the number of cores.

Saini, Subhash↗

NASA NTRSDate not supplied

AIRNOISEUAM: An Urban Air Mobility Noise-Exposure Prediction Tool

A new software tool called AIRNOISEUAM is introduced that models the noise exposure of Urban Air Mobility (UAM) operations. Given relevant UAM aircraft performance models, mission profiles, and Noise-Power-Distance data, AIRNOISEUAM predicts the noise exposure footprint for receptors on the ground. The performance of AIRNOISEUAM using a Robinson R66 helicopter model and a six-passenger quadrotor model, and a diverse set of scenarios from NASA’s UAM human-in-the-loop simulations is compared to that of the industry-standard tool with the same inputs. The predicted noise exposure results from both tools are found to be nearly identical. AIRNOISEUAM offers a fast-time, flexible interface and modular design to facilitate the dynamic requirements of the aviation research community.

Urban air mobility↗

NASA NTRSDate not supplied

AIRNOISEUAM: An Urban Air Mobility Noise-Exposure Prediction Tool

Urban Air Mobility↗

NASA NTRS1990

Neural Network Development Tool (NETS)

Artificial neural networks formed from hundreds or thousands of simulated neurons, connected in manner similar to that in human brain. Such network models learning behavior. Using NETS involves translating problem to be solved into input/output pairs, designing network configuration, and training network. Written in C.

Baffes, Paul T.↗

NASA NTRS1998

Modeling and Project Development

In order to reduce the costs of projects, it is necessary to make full use of today's modern simulation tools.

faster better cheaper (FBC) design build assemble ↗

NASA NTRS2018

Independent Effects of Reynolds and Mach Numbers on the Aerodynamics of an Iced Swept Wing

Aerodynamic assessment of icing effects on swept wings is an important component of a larger effort to improve three-dimensional icing simulation capabilities. An understanding of ice-shape geometric fidelity and Reynolds and Mach number effects on the iced-wing aerodynamics is needed to guide the development and validation of ice-accretion simulation tools. To this end, wind-tunnel testing was carried out for a 13.3%-scale semispan wing based upon the Common Research Model airplane configuration. The wind-tunnel testing was conducted at the ONERA F1 pressurized wind tunnel with Reynolds numbers of 1.6×10(exp 6) to 11.9×10(exp 6) and Mach numbers of 0.09 to 0.34. Five different configurations were investigated using fully 3D, high-fidelity artificial ice shapes that maintain nearly all of the 3D ice accretion features documented in prior icing-wind tunnel tests. These large, leadingedge ice shapes were nominally based upon airplane holding in icing conditions scenarios. For three of these configurations, lower-fidelity simulations were also built and tested. The results presented in this paper show that while Reynolds and Mach number effects are important for quantifying the clean-wing performance, there is very little to no effect for an iced-wing with 3D, high-fidelity artificial ice shapes or 3D smooth ice shapes with grit roughness. These conclusions are consistent with the large volume of past research on icedairfoils. However, some differences were also noted for the associated stalling angle of the iced swept wing and for various lower-fidelity versions of the leading-edge ice accretion. More research is planned to further investigate the key features of ice accretion geometry that must be simulated in lower-fidelity versions in order to capture the essential aerodynamics.

Broeren, Andy P.↗

NASA NTRSDate not supplied

Modeling Space-Radiation Induced Chromosome Aberrations

Exposure to ionizing radiation is identified as one of the main hazards of space flight. Galactic cosmic rays (GCRs) are composed of energetic protons (87%), helium nuclei (12%) and high-charge and energy (HZE) ions. At the cellular scale, HZE ions have a pattern of energy deposition that depends on the ion linear energy transfer (LET), with high LET ions favoring the formation of complex DNA damages that induce chromosome aberrations (CAs). Understanding how physical (e.g., ion type and energy) and biological (e.g., cell type) parameters impact CA formation is required to assess space radiation risks such as carcinogenesis. The Monte Carlo tool RITCARD/RITRACKS [1,2] developed by NASA allows simulation of the transport of HZE ions and subsequent energy deposition at the cellular scale and models the creation of DNA double strand breaks (DSBs), DNA repair and formation of CAs. We used this radiation transport code to further understand how radiation quality and cell size affects CA formation.

Floriane Poignant↗

NASA NTRS1997

Aviation Simulators for the Desktop: Panel and Demonstrations

Panel Members are: Christine M. Mitchell (Georgia Tech), Michael T. Palmer (NASA Langley), Greg Pisani (NASA Ames), and Amy R. Pritchett (MIT). The Panel members are affiliated with aviation human factors groups from NASA Ames, NASA Langley, MITCHELL Department of Aerospace and Aeronautical Engineering, and Georgia Technics Center for Human-Machine Systems Research. Panelists will describe the simulator(s) used in their respective institutions including a description of the FMS aircraft models, software, hardware, and displays. Panelists will summarize previous, on-going, and planned empirical studies conducted with the simulators. Greg Pisanich will describe two NASA Ames simulation systems: the Stone Soup Simulator (SSS), and the Airspace Operations Human Factors Simulation Laboratory. The the Stone Soup Simulator is a desktop-based, research flight simulator that includes mode control, flight management, and datalink functionality. It has been developed as a non-proprietary simulator that can be easily distributed to academic and industry researchers who are collaborating on NASA research projects. It will be used and extended by research groups represented by at least two panelists (Mitchell and Palmer). The Airspace Operations Simulator supports the study of air traffic control in conjunction with the flight deck. This simulator will be used provide an environment in which many AATT and free flight concepts can be demonstrated and evaluated. Mike Palmer will describe two NASA Langley efforts: The Langley Simulator and MD-11 extensions to the NASA Amesbury simulator. The first simulator is publicly available and combines a B-737 model with a high fidelity flight management system. The second simulator enhances the S3 simulator with MD-11 electronic flight displays together with modifications to the flight and FMS models to emulate MD-11 dynamics and operations. Chris Mitchell will describe GT-EFIRT (Georgia Tech-Electronic Flight Instrument Research Tool) and B-757 enhancements to the NASA Ames S3. GT-EFIRT is a medium fidelity simulator used to conduct preliminary studies of the CATS (crew activity tracking system). Like the Langley efforts with S3, the Georgia Tech enhancements will allow it to emulate the dynamics and operations of a widely used glass cockpit. Amy Pritchett will describe the MIT simulator(s) that have been used in a range of research investigating cockpit displays, warning devices, and flight deck-ATC interaction.

Pisanich, Greg↗

NASA NTRSDate not supplied

An Optimization Approach to Support Science Decision Making for Lunar Surface Exploration

Introduction: Scientific exploration is one of the three pillars of NASA’s Moon2Mars architecture, with crew surface extra vehicular activities (EVA) serving a critical enabling function. Development of surface EVA operational planning and execution, specifically integrating science and flight control teams (FCT), is currently being explored through analog scenarios. This integration, exercised, for example, through the Joint EVA and Hu-man Surface Mobility Test Team (JETT), allows for science input on EVA activities in near real-time through a Science Evaluation Room (SER), or Arte-mis science backroom, which integrates with the broader FCT through the Science Officer. The SER works within the FCT to support dynamic EVA planning in response to changes in operational constraints as well as science opportunities and re-prioritization, increasing the mission science return and accelerating the accomplishment of the Moon2Mars science objectives. The SER works within the FCT to provide recommendations to traverse execution in near real-time. One challenge is the requirement to deliver SER inputs to the FCT on operationally relevant timelines. Failure to do so may result in suboptimal execution of science exploration EVAs or even loss of key science objectives. To close this gap, we present a network optimization tool to allow the SER to provide rapid input to the FCT in response to changes in operational constraints or science opportunities. Inputs are predicated on approved science objectives, and clear rationale must be provided to the FCT for any requested change. Accordingly, this tool incorporates the Science Traceability Matrix (STM), SER prioritization scheme, and station characterization and action planning with operational constraints such as duration, traverse speed, and distance to maximize science objectives based on SER priorities, consistent with FCT operational requirements. Method: As a proof of concept, we used an existing linear programing software package used to simulate optimal routes through cellular metabolism. We built a Demonstrative Model with three STM objectives and four stations on a region of the Moon. The objectives were given an arbitrary prioritization and mapped to the stations through four possible crew actions. (Figs. 1 and 2). This station to STM mapping is consistent with the method used by the JETT5 Science Team to develop analog surface EVA science planning. We used a grid system with the landing site at the origin and the four stations placed across the positive x,y quadrant. Actions were assigned to each station and the accomplishment of those actions resulted in a numerical “reward” based on the ability of that action to achieve science objectives. The aggregate reward from each individual STM objective contributes to a global score (Science Yield), weighted by its priority. Operational constraints included a requirement to start and end at the landing site, 5 minutes each for initial station characterization and “clean up,” and variable total EVA time, traverse rate (fixed to 0.5 meters per second in our example), and time to perform each action (10, 5, 7, and 15 min for actions 1, 2, 3, and 4, respectively). Additional constraints and variables will be added in the future (e.g., sample mass, number of stations, traverse route constraints, illumination). Optimization. We converted the connections (arcs) between these stations (nodes) into a mixed integer linear programming optimization problem (arcs = constraints, nodes = variables) with the objective to maximize Science Yield. For any action, the Science Yield is equal to the relevance of that action to an STM objective [3, 2, and 1 point(s) for High, Med., and Low relevance, respectively], multiplied by the STM Objective Priority [3, 2, and 1 point(s) for High, Med., and Low priority, respectively]. This resulted in a model that computes the optimal station and action combination to maximize the Science Yield. These weightings can be adjusted by the SER as desired. Results: We explored three test cases for the Demonstrative Model. First, we set the maximum EVA duration to 120 minutes and computed the optimal route (Fig. 3A). The model suggested per-forming Actions 1 and 2 at Station P01, followed by Actions 1 and 2 at Station P02, and finally Actions 1 and 3 at Station P04 before returning to the Landing Site. Second, we adjusted the STM Objective Priori-ty order and computed the new optimal route (Fig. 3B). Under this situation, the model suggested per-forming all Actions at Station P02 followed by all Actions at Station P03. The previous test cases were relevant to SER planning activities. Next, we explored providing mid-EVA replanning input to the FCT. Scenario: While executing the Route in Fig. 3A the crew finishes at Station P01 and FCT decides that the EVA needs to finish in 45 minutes back at the Landing Site. FCT asks SER to recommend changes to the plan to accommodate this operation-al change. Using the model and incorporating these new constraints (start at Station P01, max. time of 45 min), the model suggested performing Actions 2 and 4 at Station P03 (Fig. 4), requiring 41 minutes to complete and return to the Landing Site. Interestingly, Station 3 was not part of the original route. Using the model, we determined the EVA would need 66 minutes, instead of 45, in order for the original Station P04 to yield a larger Science Yield than Station P03. The parametrization and simulation was per-formed in less than a minute, demonstrating the operational relevance of the approach. Future Efforts: The results from the Demonstrative Model suggest this tool can accelerate SER decision making on operationally relevant timelines. Use in analog activities, such as JETT5 or follow-ons, which have over a dozen stations for a crew to explore and over a dozen actions per station, will provide needed validation of the utility of this tool for planning EVAs, replanning mid-EVA, or planning follow-on EVAs based on previous results. Further integration with FCT execution monitoring tools may provide additional efficiency gains, al-lowing rapid and iterative exploration of operation-al and science decision space by the FCT and SER.

Science Operations↗

NASA NTRS2022

Observational Signatures of Coronal Heating in Magnetohydrodynamic Simulations without Radiation or a Lower Atmosphere

It is extremely difficult to simulate the details of coronal heating and also make meaningful predictions of the emitted radiation. Thus, testing realistic models with observations is a major challenge. Observational signatures of coronal heating depend crucially on radiation, thermal conduction, and the exchange of mass and energy with the transition region and chromosphere below. Many magnetohydrodynamic simulation studies do not include these effects, opting instead to devote computational resources to the magnetic aspects of the problem. We have developed a simple method of accounting approximately for the missing effects. It is applied to the simulation output ex post facto and therefore may be a valuable tool for many studies. We have used it to predict the emission from a model corona that is driven by vortical boundary motions meant to represent photospheric convection. We find that individual magnetic strands experience short-term brightenings, both scattered throughout the computational volume and in localized clusters. The former may explain the diffuse component of the observed corona, while the latter may explain bright coronal loops. Several observed properties of loops are reproduced reasonably well: width, lifetime, and quasi-circular cross section (aspect ratio not high). Our results lend support to the idea that loops are multistranded structures heated by "storms" of nanoflares.

James A. Klimchuk↗

NASA NTRS2012

An Overview of Atmospheric Composition OSSE Activities at NASA's Global Modeling and Assimilation Office

A model-based Observing System Simulation Experiment (OSSE) is a framework for numerical experimentation in which observables are simulated from fields generated by an earth system model, including a parameterized description of observational error characteristics. Simulated observations can be used for sampling studies, quantifying errors in analysis or retrieval algorithms, and ultimately being a planning tool for designing new observing missions. While this framework has traditionally been used to assess the impact of observations on numerical weather prediction, it has a much broader applicability, in particular to aerosols and chemical constituents. In this talk we will give a general overview of Observing System Simulation Experiments (OSSE) activities at NASA's Global Modeling and Assimilation Office, with focus on its emerging atmospheric composition component.

daSilva, Arlinda↗

NASA NTRS1991

Macromolecular recognition: Structural aspects of the origin of the genetic system

Theoretical simulation of prebiotic chemical processes is an invaluable tool for probing the phenomenon of the evolution of life. Using computational and modeling techniques and guided by analogies from present day systems, we seek to understand the emergence of the genetic apparatus, enzymatic catalysis and protein synthesis under prebiotic conditions. Modeling of the ancestral aminoacyl-tRNA-synthetases (aRS) may provide important clues to the emergence of the genetic code and the protein synthetic machinery. The minimal structural requirements for the catalysis of tRNA aminoacylation are being explored. A formation of an aminoacyl adenylate was studied in the framework of ab initio molecular orbital theory. The role of individual residues in the vicinity of the TyrRS active site was examined, and the effect of all possible amino acids substitutions near the active site was examined. A formation of aminoacyl tRNA was studied by the molecular modeling system SYBYL with the high resolution crystallographic structures of the present day tRNA, aRS's complexes. The ultimate goal is to propose a simple RNA segment that is small enough to be build in the primordial chemical environment but maintains the specificity and catalytic activity of the contemporary RNA enzyme. To understand the mechanism of ribozyme catalyzed reactions, ab initio and semi-empirical (ZINDO) programs were used to investigate the reaction path of transphosphorylation. A special emphasis was placed on the possible catalytic and structural roles played by the coordinated magnesium cation. Both the inline and adjacent mechanisms of transphosphorylation were studied. The structural characteristics of the target helices, particularly a possible role for the G-T pair, is also studied by a molecular dynamics (MD) simulation technique.

Rein, Robert↗

NASA NTRS2017

Validation Testing of a Peridynamic Impact Damage Model Using NASA's Micro-Particle Gun

Through a collaborative effort between the Virginia Commonwealth University and Raytheon, a peridynamic model for sand impact damage has been developed1-3. Model development has focused on simulating impacts of sand particles on ZnS traveling at velocities consistent with aircraft take-off and landing speeds. The model reproduces common features of impact damage including pit and radial cracks, and, under some conditions, lateral cracks. This study focuses on a preliminary validation exercise in which simulation results from the peridynamic model are compared to a limited experimental data set generated by NASA's recently developed micro-particle gun (MPG). The MPG facility measures the dimensions and incoming and rebound velocities of the impact particles. It also links each particle to a specific impact site and its associated damage. In this validation exercise parameters of the peridynamic model are adjusted to fit the experimentally observed pit diameter, average length of radial cracks and rebound velocities for 4 impacts of 300 μm glass beads on ZnS. Results indicate that a reasonable fit of these impact characteristics can be obtained by suitable adjustment of the peridynamic input parameters, demonstrating that the MPG can be used effectively as a validation tool for impact modeling and that the peridynamic sand impact model described herein possesses not only a qualitative but also a quantitative ability to simulate sand impact events.

Baber, Forrest E.↗

NASA NTRS1992

MAGIK robotics simulation - A window on Space Station Freedom

The MAGIK program is the primary kinematic analysis tool used by the Robotic Systems group at MDSSC. It allows users to conduct man-in-the-loop analyses to evaluate space robotic operations, including reach, clearance, and accessibility. MAGIK can be used to model, specify, simulate, analyze, and modify n-jointed type manipulators and their respective control algorithms. The MAGIK simulation currently implements kinematic models of all robotic devices currently baselined on Space Station Freedom (SSF).

Read, David A.↗

NASA NTRS2022

Implementation and Evaluation of Irrigation Techniques in the Community Land Model

Several previous studies have highlighted the irrigation-induced impacts on the global and regional water cycle, energy budget, and near-surface climate. While land models are widely used to address this question, the implementations of irrigation in these models vary in complexity. Here, we expand the representation of irrigation in Community Land Model to enable six different irrigation methods. We find that using a combination of irrigation methods, including default, sprinkler, flood and paddy techniques performs best as determined by evaluating the simulated irrigation water withdrawals against observations, and therefore select this combination as the new irrigation scheme. Then, the impact of the new irrigation scheme on surface fluxes is evaluated and detected using single-point simulations. Finally, the global and regional irrigation-induced impacts on surface energy and water fluxes are compared using both the original and the new irrigation scheme. The new irrigation scheme substantially reduces the bias and root-mean-square error of simulated irrigation water withdrawal in the USA and other countries, but considerably overestimates withdrawals in Central China. Results of single-point experiments show that different irrigation methods have different effects on surface fluxes, while the magnitudes are small. At the global scale, the new scheme enlarges the irrigation-induced impacts on water and energy variables relative to the original scheme, with varying magnitudes across regions. Overall, our results suggest that this newly developed scheme is a better tool for simulating irrigation-induced impacts on climate, and highlight the added value of incorporating human water management in Earth system models.

Community land models↗