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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2

Integrated Instrument Simulator Suites for Earth Science

The NASA Earth Observing System Simulators Suite (NEOS3) is a modular framework of forward simulations tools for remote sensing of Earth's Atmosphere from space. It was initiated as the Instrument Simulator Suite for Atmospheric Remote Sensing (ISSARS) under the NASA Advanced Information Systems Technology (AIST) program of the Earth Science Technology Office (ESTO) to enable science users to perform simulations based on advanced atmospheric and simple land surface models, and to rapidly integrate in a broad framework any experimental or innovative tools that they may have developed in this context. The name was changed to NEOS3 when the project was expanded to include more advanced modeling tools for the surface contributions, accounting for scattering and emission properties of layered surface (e.g., soil moisture, vegetation, snow and ice, subsurface layers). NEOS3 relies on a web-based graphic user interface, and a three-stage processing strategy to generate simulated measurements. The user has full control over a wide range of customizations both in terms of a priori assumptions and in terms of specific solvers or models used to calculate the measured signals.This presentation will demonstrate the general architecture, the configuration procedures and illustrate some sample products and the fundamental interface requirements for modules candidate for integration.

radiative transfer↗

NASA's Integrated Instrument Simulator Suite for Atmospheric Remote Sensing from Spaceborne Platforms (ISSARS) and Its Role for the ACE and GPM Missions

Forward simulation is an indispensable tool for evaluation of precipitation retrieval algorithms as well as for studying snow/ice microphysics and their radiative properties. The main challenge of the implementation arises due to the size of the problem domain. To overcome this hurdle, assumptions need to be made to simplify compiles cloud microphysics. It is important that these assumptions are applied consistently throughout the simulation process. ISSARS addresses this issue by providing a computationally efficient and modular framework that can integrate currently existing models and is also capable of expanding for future development. ISSARS is designed to accommodate the simulation needs of the Aerosol/Clouds/Ecosystems (ACE) mission and the Global Precipitation Measurement (GPM) mission: radars, microwave radiometers, and optical instruments such as lidars and polarimeter. ISSARS's computation is performed in three stages: input reconditioning (IRM), electromagnetic properties (scattering/emission/absorption) calculation (SEAM), and instrument simulation (ISM). The computation is implemented as a web service while its configuration can be accessed through a web-based interface.

real-aperture instruments↗

An Approach for Utilizing Power Flow Modeling for Simulations of Hybrid Electric Propulsion Systems

This paper describes an approach to creating simulations of the electric components for a hybrid electric propulsion system. The proposed modeling technique is based on power/load flow modeling and is designed to provide a modular framework that includes buses, lines, and other electrical components that can be connected together to form the electrical distribution system. The purpose of this paper is to detail an electric distribution system modeling technique and to demonstrate how these models may be integrated with turbomachinery simulations. These general modeling techniques were created to be utilized for system and control design studies. Additionally, steady-state and dynamic performance for a proposed model example is compared with data from a hardware in the loop simulation.

Chapman, Jeffryes W.↗

Livermore's Cube Satellite Evolution: Space Program Innovation: One Small Satellite at a Time

Cube satellites, called CubeSats, are a common type of nanosatellite comprising a modular framework of cube-shaped building block units that measure 10 centimeters per side. Their lower cost and ease of construction compared to large, conventional satellites have made them a popular choice for modern space applications. Lawrence Livermore’s first involvement with CubeSats began nearly a decade ago when scientists developed optical imaging payloads for the Space-Based Telescopes for the Actionable Refinement of Ephemeris project to monitor space debris. More recently, as part of a collaboration with NASA Goddard Space Flight Center, the Laboratory has helped develop the MiniCarb CubeSat for measuring atmospheric greenhouse gases. MiniCarb will be the first to use the innovative, Laboratory-developed CubeSat Next Generation Bus platform, ushering in a new era for the institution’s Space Science and Security Program.

Nanosatellite↗

TPSAS-NF1676L-14964-DND

Radiation models and methods (software) have been developed by researchers for 35+ years. Few had access to the software and it was very difficult to combine, maintain, and update. OLTARIS – On-Line Tool for the Assessment of Radiation in Space: - Web portal created to supply the “best practices” in radiation shielding models, methods, and algorithms to the community - Rigorously developed in a modular framework that is easily maintained and updated - Easily accessible by NASA’s customers and collaborators

Chris A Sandridge↗

Fast Linearized Coronagraph Optimizer (FALCO) I: A Software Toolbox for Rapid Coronagraphic Design and Wavefront Correction

The Fast Linearized Coronagraph Optimizer (FALCO) is an open-source toolbox of routines for coronagraphic focal plane wavefront correction. The goal of FALCO is to provide a free, modular framework for the simulation or testbed operation of several common types of coronagraphs. FALCO includes routines for pair-wise probing estimation of the complex electric field and Electric Field Conjugation (EFC) control, and we ask the community to contribute other wavefront correction algorithms. FALCO utilizes and builds upon PROPER, an established optical propagation library. The key innovation in FALCO is the rapid computation of the linearized response matrix for each deformable mirror (DM), which facilitates re-linearization after each control step for faster DM-integrated coronagraph design and wavefront correction experiments. FALCO is freely available as source code in MATLAB at github.com/ajeldorado/falco-matlab and will be available later this year in Python 3 at github.com/ajeldorado/falco-python.

Shaklan, Stuart B.↗

Modular Spectral Inference Framework Applied to Young Stars and Brown Dwarfs

In practice, synthetic spectral models are imperfect, causing inaccurate estimates of stellar parameters. Using forward modeling and statistical inference, we derive accurate stellar parameters for a given observed spectrum by emulating a grid of precomputed spectra to track uncertainties. Spectral inference as applied to brown dwarfs re: Synthetic spectral models (Marley et al 1996 and 2014) via the newest grid spans a massive multi-dimensional grid applied to IGRINS spectra, improving atmospheric models for JWST. When applied to young stars(10Myr) with large starpots, they can be measured spectroscopically, especially in the near-IR with IGRINS.

Modular Autonomous Systems Technology Framework: A Distributed Solution for System Monitoring and Control

The Modular Autonomous Systems Technology (MAST) framework is a tool for building distributed, hierarchical autonomous systems. Originally intended for the autonomous monitoring and control of spacecraft, this framework concept provides support for variable autonomy, assume-guarantee contracts, and efficient communication between subsystems and a centralized systems manager. MAST was developed at NASA's Johnson Space Center (JSC) and has been applied to an integrated spacecraft example scenario.

Badger, Julia M.↗

An Integrated Snow Radiance and Snow Physics Modeling Framework for Cold Land Surface Modeling

Recent developments in forward radiative transfer modeling and physical land surface modeling are converging to allow the assembly of an integrated snow/cold lands modeling framework for land surface modeling and data assimilation applications. The key elements of this framework include: a forward radiative transfer model (FRTM) for snow, a snowpack physical model, a land surface water/energy cycle model, and a data assimilation scheme. Together these form a flexible framework for self-consistent remote sensing and water/energy cycle studies. In this paper we will describe the elements and the integration plan. Each element of this framework is modular so the choice of element can be tailored to match the emphasis of a particular study. For example, within our framework, four choices of a FRTM are available to simulate the brightness temperature of snow: Two models are available to model the physical evolution of the snowpack and underlying soil, and two models are available to handle the water/energy balance at the land surface. Since the framework is modular, other models-physical or statistical--can be accommodated, too. All modules will operate within the framework of the Land Information System (LIS), a land surface modeling framework with data assimilation capabilities running on a parallel-node computing cluster at the NASA Goddard Space Flight Center. The advantages of such an integrated modular framework built on the LIS will be described through examples-e.g., studies to analyze snow field experiment observations, and simulations of future satellite missions for snow and cold land processes.

Kim, Edward J.↗

The Future of Electronic Device Design: Device and Process Simulation Find Intelligence on the World Wide Web

We are on the path to meet the major challenges ahead for TCAD (technology computer aided design). The emerging computational grid will ultimately solve the challenge of limited computational power. The Modular TCAD Framework will solve the TCAD software challenge once TCAD software developers realize that there is no other way to meet industry's needs. The modular TCAD framework (MTF) also provides the ideal platform for solving the TCAD model challenge by rapid implementation of models in a partial differential solver.

Biegel, Bryan A.↗

Improving Flight Software Module Validation Efforts : a Modular, Extendable Testbed Software Framework

Ever since Explorer-1, the United States' first Earth satellite, was developed and launched in 1958, JPL has developed many more spacecraft, including landers and orbiters. While these spacecraft vary greatly in their missions, capabilities,and destination, they all have something in common. All of the components of these spacecraft had to be comprehensively tested. While thorough testing is important to mitigate risk, it is also a very expensive and time consuming process. Thankfully,since virtually all of the software testing procedures for SMAP are computer controlled, these procedures can be automated. Most people testing SMAP flight software (FSW) would only need to write tests that exercise specific requirements and then check the filtered results to verify everything occurred as planned. This gives developers the ability to automatically launch tests on the testbed, distill the resulting logs into only the important information, generate validation documentation, and then deliver the documentation to management. With many of the steps in FSW testing automated, developers can use their limited time more effectively and can validate SMAP FSW modules quicker and test them more rigorously. As a result of the various benefits of automating much of the testing process, management is considering this automated tools use in future FSW validation efforts.

flight software testing↗

A Modular Conjugate Heat Transfer Optimization Framework for Thermal Management of Electric Aircraft

Conjugate heat transfer (CHT) analysis and optimization is a powerful method for improving thermal management, as it simultaneously resolves the temperature distribution in both fluid and solid domains. This paper presents a modular, discrete adjoint-based CHT optimization capability integrated within the OpenMDAO/MPhys framework. A unique feature of the proposed framework is its flexibility to extend to multidisciplinary optimization, including aero-structural-thermal applications. The fluid domain is modeled using a finite-volume Computational Fluid Dynamics (CFD) solver, and the solid domain with a conduction heat transfer solver. A mixed Neumann-Dirichlet boundary condition is developed to enable full submersion of the solid geometry within the fluid domain, while ensuring consistent temperature and heat flux coupling at the CHT interface. Gradient-based optimization is performed; the gradients are efficiently computed using the discrete adjoint solvers implemented in DAFoam. To demonstrate the method, this paper considers two cases related to electric aircraft thermal management: a U-bend heat exchanger and an actively cooled battery pack. The U-bend case aims to minimize pressure loss while maximizing heat flux by changing the pipe geometry. The optimized design reduces pressure loss by 52.7% and increases total heat flux by 2.3%. In the battery pack case, a 3-by-3 cell configuration is cooled by ambient airflow, with constant heat generation prescribed in the cells. The battery casing shape serves as the design variable, and the objective function is a weighted sum of pressure loss and pack weight, subject to a maximum temperature constraint. The optimized design achieves a 44.6% reduction in pressure loss and a 1.5% reduction in weight, while satisfying the thermal constraint. To ensure the reliability of the optimized designs, this study validates coarse-mesh, steady-state predictions against fine-mesh unsteady simulations, demonstrating consistency within acceptable errors. This work demonstrates the potential of the developed framework to enable rapid, high-fidelity design of thermal management systems for electric aircraft.

heat transfer↗

The K9 On-Board Rover Architecture

This paper describes the software architecture of NASA Ames Research Center s K9 rover. The goal of the onboard software architecture team was to develop a modular, flexible framework that would allow both high- and low-level control of the K9 hardware. Examples of low-level control are the simple drive or pan/tilt commands which are handled by the resource managers, and examples of high-level control are the command sequences which are handled by the conditional executive. In between these two control levels are complex behavioral commands which are handled by the pilot, such as drive to goal with obstacle avoidance or visually servo to a target. This paper presents the design of the architecture as of Fall 2000. We describe the state of the architecture implementation as well as its current evolution. An early version of the architecture was used for K9 operations during a dual-rover field experiment conducted by NASA Ames Research Center (ARC) and the Jet Propulsion Laboratory (JPL) from May 14 to May 16, 2000.

Bresina, John L.↗

Simulating Operation of a Planetary Rover

Simulating Operation of a Planetary Rover Rover Analysis, Modeling, and Simulations (ROAMS) is a computer program that simulates the operation of a robotic vehicle (rover) engaged in exploration of a remote planet. ROAMS is a roverspecific extension of the DARTS and Dshell programs, described in prior NASA Tech Briefs articles, which afford capabilities for mathematical modeling of the dynamics of a spacecraft as a whole and of its instruments, actuators, and other subsystems. ROAMS incorporates mathematical models of kinematics and dynamics of rover mechanical subsystems, sensors, interactions with terrain, solar panels and batteries, and onboard navigation and locomotion-control software. ROAMS provides a modular simulation framework that can be used for analysis, design, development, testing, and operation of rovers. ROAMS can be used alone for system performance and trade studies. Alternatively, ROAMS can be used in an operator-in-the-loop or flight-software closed-loop environment. ROAMS can also be embedded within other software for use in analysis and development of algorithms, or for Monte Carlo studies, using a variety of terrain models, to generate performance statistics. Moreover, taking advantage of realtime features of the underlying DARTS/Dshell simulation software, ROAMS can also be used for real-time simulations.

Jain, Abhinandan↗

The InSAR Scientific Computing Environment

We have developed a flexible and extensible Interferometric SAR (InSAR) Scientific Computing Environment (ISCE) for geodetic image processing. ISCE was designed from the ground up as a geophysics community tool for generating stacks of interferograms that lend themselves to various forms of time-series analysis, with attention paid to accuracy, extensibility, and modularity. The framework is python-based, with code elements rigorously componentized by separating input/output operations from the processing engines. This allows greater flexibility and extensibility in the data models, and creates algorithmic code that is less susceptible to unnecessary modification when new data types and sensors are available. In addition, the components support provenance and checkpointing to facilitate reprocessing and algorithm exploration. The algorithms, based on legacy processing codes, have been adapted to assume a common reference track approach for all images acquired from nearby orbits, simplifying and systematizing the geometry for time-series analysis. The framework is designed to easily allow user contributions, and is distributed for free use by researchers. ISCE can process data from the ALOS, ERS, EnviSAT, Cosmo-SkyMed, RadarSAT-1, RadarSAT-2, and TerraSAR-X platforms, starting from Level-0 or Level 1 as provided from the data source, and going as far as Level 3 geocoded deformation products. With its flexible design, it can be extended with raw/meta data parsers to enable it to work with radar data from other platforms

geodetic imaging↗

Unified Simulation and Analysis Framework for Deep Space Navigation Design

As the technology that enables advanced deep space autonomous navigation continues to develop and the requirements for such capability continues to grow, there is a clear need for a modular expandable simulation framework. This tool's purpose is to address multiple measurement and information sources in order to capture system capability. This is needed to analyze the capability of competing navigation systems as well as to develop system requirements, in order to determine its effect on the sizing of the integrated vehicle. The development for such a framework is built upon Model-Based Systems Engineering techniques to capture the architecture of the navigation system and possible state measurements and observations to feed into the simulation implementation structure. These models also allow a common environment for the capture of an increasingly complex operational architecture, involving multiple spacecraft, ground stations, and communication networks. In order to address these architectural developments, a framework of agent-based modules is implemented to capture the independent operations of individual spacecraft as well as the network interactions amongst spacecraft. This paper describes the development of this framework, and the modeling processes used to capture a deep space navigation system. Additionally, a sample implementation describing a concept of network-based navigation utilizing digitally transmitted data packets is described in detail. This developed package shows the capability of the modeling framework, including its modularity, analysis capabilities, and its unification back to the overall system requirements and definition.

Anzalone, Evan↗