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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 325 records · Page 18

AI-Batt (Autonomous Identification of Battery Life Models) [SWR 21-36]

Autonomous Identification of Battery Life Models (AI-Batt) AI-Batt is a MATLAB code base for developing lifetime models for batteries from accelerated aging data. The code base provides many functions for processing, visualizing, and modeling battery aging data, making the data processing, exploration, and modeling workflow substantially faster. These tools are tailored for working with battery aging data sets, which usually consist of many separate time-series for each cell, with many test conditions and possible replicates at each condition, which makes it difficult to simply process or visualize the data set. Complex modeling tasks, such as cross-validation, sensitivity analysis, and uncertainty quantification have been implemented to enable thorough statistical investigation of model predictions. Additionally, several machine-learning algorithms are implemented to autonomously identify suitable models via symbolic regression. Data processing functions automatically cast data from the struct data type, which is commonly used to store experimental data, but is not an acceptable input for most algorithms, to the table data type, which can be easily used as input to any optimization algorithm. Also, the data can be separated into time-invariant and time-variant data tables, which is helpful for exploring the data set as well as developing separate models for time-variant and time-invariant aging mechanisms. For example, in aging tests with constant temperature, temperature is a time-invariant experimental condition. Visualization tools enable plotting of data, model fits, and model simulations possible with single-line function calls, empowering data exploration of complex data sets with both time-varying and time-invariant trends. Plots can be automatically generated for the whole data set, or separated by data group (groups of test replicates) or individual data series. Data points or data series can be automatically colored by the value of a variable with a variety of color maps, and model predictions can also be colored by the value of a fit statistic. Comparisons between data sets and the predictions/simulations of different models on the same data set can be easily plotted as well. Distributions of parameter values from bootstrap resampling can be plotted to visualize the reliability of parameter estimation, or determine any correlations between parameters. Modeling tools handle the complex task of creating and parsing symbolic equations for modeling battery lifetime. Equations are parsed to grab relevant data variables, parameter values, or specified sub-models for input into optimization, evaluation, or simulation functions. Models can be optimized locally (one set of parameters for each data series), bi-level (some parameters shared across the data set), or globally (single set of parameters for all data). Functions implementing symbolic regression algorithms help users to discover effective model equations, even in poorly sampled, high-dimensional data.

Smith, Kandler↗

Echo™ User Manual

Echo™ is a MATLAB-based software package designed for robust and scalable analysis of complex data workflows. An alternative to tedious, error-prone conventional processes, Echo is based on three transformative principles for data analysis: self-describing data, name-based indexing, and dynamic resource allocation. The software takes an object-oriented approach to data analysis, intimately connecting measurement data with associated metadata. Echo operations in an analysis workflow automatically track and merge metadata and computation parameters to provide a complete history of the process used to generate final results, while automated figure and report generation tools eliminate the potential to mislabel those results. History reporting and visualization methods provide straightforward auditability of analysis processes. Furthermore, name-based indexing on metadata greatly improves code readability for analyst collaboration and reduces opportunities for errors to occur. Echo efficiently manages large data sets using a framework that seamlessly allocates resources such that only the necessary computations to produce a given result are executed. Echo provides a versatile and extensible framework, allowing advanced users to add their own tools and data classes tailored to their own specific needs. Applying these transformative principles and powerful features, Echo greatly improves analyst efficiency and quality of results in many application areas.

97 MATHEMATICS AND COMPUTING↗

WEC-Sim Wave Energy Converter Simulator

WEC-Sim (Wave Energy Converter SIMulator) is an open-source wave energy converter (WEC) simulation tool. The code is developed in MATLAB/SIMULINK using the multi-body dynamics solver SimMechanics. WEC-Sim has the ability to model devices that are comprised of rigid bodies, power-take-off systems, and mooring systems. Simulations are performed in the time-domain by solving the governing WEC equations of motion in 6 degrees-of-freedom. The WEC-Sim project is funded by the U.S. Department of Energy's Wind and Water Power Technologies Office and the code development effort is a collaboration between the National Renewable Energy Laboratory (NREL) and Sandia National Laboratories (SNL).

13 HYDRO ENERGY↗

Performance Analysis of Apollo Navigational Starter Routine

The focus of this project is to recreate and analyze the effectiveness of the original Apollo Starter Routine (ASR) which was used to generate the state vector of the Apollo spacecraft based on a series of radiometric observations. The original Apollo navigation software is unavailable in a modern programming language and the original coding has not been preserved. This necessitates its recreation using the original software documentation. Space Shuttle navigation software does not typically use the ASR or an algorithm like it since the Shuttle s state vector is easily deduced from GPS information or other sources. However, this tactic will be ineffective when trying to determine the state vector of a craft approaching, departing or in orbit around the Moon since the GPS network faces the surface of the Earth, not outer space. The recreation of the ASR from the original documentation is therefore vital as a simulation baseline for the navigation software under development for the Constellation program. The algorithms that make up the ASR will be extracted from the original documentation and adapted for and then implemented in a modern programming language; the majority of it will be coded in Matlab. The ASR s effectiveness will then be tested using simulated tracking data. The ability of the ASR to handle realistically noisy data and the accuracy with which it generates state vectors were analyzed. The ASR proved to be robust enough to process data with range and angle noise as large as 10,000 meters and 10(exp -6) radians together and 300,000 meters and 5x10(exp -4) radians separately at Lunar distances. The ASR was able to handle marginally more noise at distances closer to the Earth where the angle noise was less significant. The ASR is capable of effectively processing 40-80 data points gathered at a rate of one per 20 seconds at close Earth orbit and up to 28-40 data points gathered at a rate of one per minute at distant Earth orbit and Lunar orbit.

Ivanov, Stoyan I.↗

Tool for Statistical Analysis and Display of Landing Sites

MarsLS is a software tool for analyzing statistical dispersion of spacecraft-landing sites and displaying the results of its analyses. Originally intended for the Mars Explorer Rover (MER) mission, MarsLS is also applicable to landing sites on Earth and non-MER sites on Mars. MarsLS is a collection of interdependent MATLAB scripts that utilize the MATLAB graphical-user-interface software environment to display landing-site data (see figure) on calibrated image-maps of the Martian or other terrain. The landing-site data comprise latitude/longitude pairs generated by Monte Carlo runs of other computer programs that simulate entry, descent, and landing. Using these data, MarsLS can compute a landing-site ellipse a standard means of depicting the area within which the spacecraft can be expected to land with a given probability. MarsLS incorporates several features for the user s convenience, including capabilities for drawing lines and ellipses, overlaying kilometer or latitude/longitude grids, drawing and/or specifying lines and/or points, entering notes, defining and/or displaying polygons to indicate hazards or areas of interest, and evaluating hazardous and/or scientifically interesting areas. As part of such an evaluation, MarsLS can compute the probability of landing in a specified polygonal area.

Wawrzyniak, Geoffrey↗

Goddard Space Flight Center's Structural Dynamics Data Acquisition System

Turnkey Commercial Off The Shelf (COTS) data acquisition systems typically perform well and meet most of the objectives of the manufacturer. The problem is that they seldom meet most of the objectives of the end user. The analysis software, if any, is unlikely to be tailored to the end users specific application; and there is seldom the chance of incorporating preferred algorithms to solve unique problems. Purchasing a customized system allows the end user to get a system tailored to the actual application, but the cost can be prohibitive. Once the system has been accepted, future changes come with a cost and response time that's often not workable. When it came time to replace the primary digital data acquisition system used in the Goddard Space Flight Center's Structural Dynamics Test Section, the decision was made to use a combination of COTS hardware and in-house developed software. The COTS hardware used is the DataMAX II Instrumentation Recorder built by R.C. Electronics Inc. and a desktop Pentium 4 computer system. The in-house software was developed using MATLAB from The MathWorks. This paper will describe the design and development of the new data acquisition and analysis system.

McLeod, Christopher↗

Time Delay of Wide Area Damping Control in Urban Power Grid: Model-Based Analysis and Data-Driven Compensation

Due to the rapid development of economies, large urban cities consume an increasing amount of energy and have a higher requirement for power quality. Voltage source converter based high voltage direct current (VSC-HVDC) is a promising device to transmit clean power from remote regions to urban power systems, while also providing wide area damping control (WADC) for frequency stabilization. However, the time-delay naturally existing in the VSC-HVDC system may degrade the performance of WADC and even result in instability. To address this issue, this paper develops a time-delay correction control strategy for VSC-HVDC damping control in urban power grids. First, a small signal model of WADC is built to analyze the negative impacts of time delay. Then, a data-driven approach is proposed to compensate for the inherent time delay in VSC-HVDC damping control. The extensive training data will be generated under various disturbances. After offline training, the long short-term memory network (LSTM) can be implemented online to predict the actual frequency deviation based on real-time measurements. Finally, the proposed method is validated through MATLAB-Simulink in a two-area four-machine system. The results indicate that the data-driven compensation has a strong generalization ability for random delay time constants and can improve the performance of WADC significantly.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Transition Marshall Space Flight Center Wind Profiler Splicing Algorithm to Launch Services Program Upper Winds Tool

NASAs LSP customers and the future SLS program rely on observations of upper-level winds for steering, loads, and trajectory calculations for the launch vehicles flight. On the day of launch, the 45th Weather Squadron (45 WS) Launch Weather Officers (LWOs) monitor the upper-level winds and provide forecasts to the launch team via the AMU-developed LSP Upper Winds tool for launches at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station. This tool displays wind speed and direction profiles from rawinsondes released during launch operations, the 45th Space Wing 915-MHz Doppler Radar Wind Profilers (DRWPs) and KSC 50-MHz DRWP, and output from numerical weather prediction models.The goal of this task was to splice the wind speed and direction profiles from the 45th Space Wing (45 SW) 915-MHz Doppler radar Wind Profilers (DRWPs) and KSC 50-MHz DRWP at altitudes where the wind profiles overlap to create a smooth profile. In the first version of the LSP Upper Winds tool, the top of the 915-MHz DRWP wind profile and the bottom of the 50-MHz DRWP were not spliced, sometimes creating a discontinuity in the profile. The Marshall Space Flight Center (MSFC) Natural Environments Branch (NE) created algorithms to splice the wind profiles from the two sensors to generate an archive of vertically complete wind profiles for the SLS program. The AMU worked with MSFC NE personnel to implement these algorithms in the LSP Upper Winds tool to provide a continuous spliced wind profile.The AMU transitioned the MSFC NE algorithms to interpolate and fill data gaps in the data, implement a Gaussian weighting function to produce 50-m altitude intervals in each sensor, and splice the data together from both DRWPs. They did so by porting the MSFC NE code written with MATLAB software into Microsoft Excel Visual Basic for Applications (VBA). After testing the new algorithms in stand-alone VBA modules, the AMU replaced the existing VBA code in the LSP Upper Winds tool with the new algorithms. They then tested the code in the LSP Upper Winds tool with archived data. The tool will be delivered to the 45 WS after the 50-MHz DRWP upgrade is complete and the tool is tested with real-time data. The 50-MHz DRWP upgrade is expected to be finished in October 2014.

Space launch↗

A New Model for Simulating the Imbibition of a Wetting-Phase Fluid in a Matrix-Fracture Dual Connectivity System

The imbibition experiment is an effective approach for measuring petrophysical properties of porous media, with many such experiments performed over the past decade. Quite some empirical, analytical, and numerical models have been developed to simulate spontaneous imbibition of the wetting phase fluid into porous media, but limitations still exist. In previous studies, the imbibition process has been considered to give a piston-like displacement or the porous medium modeled as multiply-sized pores linked with bonds; both approaches fail to yield comprehensive results due to their neglect of the presence of irregular fractures or nonuniform flow paths through the matrix. By building a numerical model for simulating laboratory-scale experimental data, we performed imbibition tests on several fractured Barnett Shale samples having fractures either parallel ( P ) or transverse ( T ) to the bedding plane and used MATLAB to build a new numerical model by combining the imbibition process in fractures and the matrix using concepts from percolation theory. The experimental data show that the rocks with P -direction fractures have a more steady increase of imbibition rates than the case of T -direction one. As the shale matrix with low pore connectivity hampers the upward water movement, the imbibition rate of shales with T -direction fractures will decrease suddenly after the bottom layer in contact with water is saturated during the initial period. This wetting phase movement (WPM) model can simulate 3D porous media with 2D fractures. The rate of imbibition by fractured porous media is associated with physical parameters such as porosity and fracture distribution (e.g., the number and angle of fractures). Using Monte Carlo methods, we examined fracture parameters and predicted elapsed time and cumulative water imbibition, for the Barnett Shale samples. The results show that the rate of imbibed water mass is sensitive to the number of fractures directly connected to water source, and the connectivity between two neighboring grid cells is a key parameter for the wetting-front progression. The findings of this study can help to better understand the imbibition process with multiple influencing processes and factors in fractured-matrix rocks. Although the experiments, data simulation, and prediction results are based only on Barnett Shale samples, the model is readily applicable to imbibition tests of other fractured rocks to show the spatial and temporal behavior during a dynamic imbibition process that are not easily captured experimentally.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

MASK4 Test Campaign for Sandia WaveBot Device

This data and report details the findings from a wave tank test focused on production of useful work of a wave energy converter (WEC) device. The experimental system and test were specifically designed to validate models for power transmission throughout the WEC system. Additionally, the validity of co-design informed changes to the power take-off (PTO) were assessed and shown to provide the expected improvements in system performance. These data describe the "MASK4" wave tank test of the Sandia WaveBot device. The WaveBot device has been tested a number of times in different permutations at the US Navy's Maneuvering and Sea Keeping (MASK) basin. Each test in this series is referred to as MASK1, MASK2, etc. The WaveBot device was first tested in one degree of freedom (heave) in 2016. This MASK1 test focused primarily on system identification and modeling. After MASK1, major modifications were performed to improve the overall real-time control and measurement system, improve the heave drive train, and add surge and pitch degrees of freedom. The second set of testing, which was broken up in to two stages: MASK2A and MASK2B, focused on bench testing and closed-loop control performance as well as nonlinear modeling. MASK3 then focused on multi-input, multi-output modeling and control for maximization of electrical power. The attached report presents the results from MASK4, which focuses on detailed modeling of the power conversion chain and validation co-design principles by way of the introduction of a magnetic spring. The test log, report, and data from the MASK4 test of the WaveBot augmented with a tunable magnetic spring. Processing codes can be found at the Github link below.

16 TIDAL AND WAVE POWER↗

TEAMER: Biofouling Analysis for Wave Energy Piston Design - Load Cell Data

Biofouling and corrosion are a major concern for all ocean-deployed components, especially when mechanical motion is involved. Triton has developed the concept of a biofouling mitigation seal as part of the piston sealing assembly for the Triton Wave Energy Converter (TSI-WEC). This mitigation seal has the purpose of preventing the formation of a biofilm on the inside of the piston cylinder. It is hypothesized that the prevention of a biofilm will reduce the amount of macro-biofouling that can occur in the piston assembly. The mitigation seal can also reduce the wear on the main dynamic seal, helping to maintain smooth operation and water-tightness. The cylinder is made from a thermoset composite epoxy, which is resistant to corrosion. However, no studies have researched the material's performance with biofouling. Triton placed two prototype Power Take-Off (PTO) assemblies in a PNNL biofouling tank, one with a biofouling mitigation seal and one without, allowing for an evaluation of seal effectiveness at the prevention of biofouling. In actual WEC operation, wave action would react against the piston, which would drive the linear actuator and electric generator, providing electrical power. In the test setup, this was reversed; a linear actuator was powered to drive the piston in a consistent motion within the cylinder. There are two assemblies: one has a biofouling mitigation seal, the other (control) does not. The following data encompasses a 4 month test period, with load cells being used to monitor piston friction force. Results from this testing will be used to improve seal design and material selection, mitigating risk of premature failure during open water testing and evaluation. This project is part of the TEAMER RFTS 3 (request for technical support) program.

16 TIDAL AND WAVE POWER↗

NEON AOP Survey of Upper East River CO Watersheds: Waveform LiDAR Binary Data

The waveform Light Detection and Ranging (LiDAR) data in this package were generated through a National Ecological Observatory Network Airborne Observation Platform (NEON AOP) acquisition over watersheds of interest surrounding Crested Butte, Colorado. The remote sensing imagery acquired by the NEON AOP supports an interdisciplinary project on hydrology, biogeochemistry, and ecosystem functioning in a snow-dominated headwater environment. These waveform LiDAR data enable spatially continuous estimation of vegetation structure parameters to facilitate analyses of the major environmental drivers of structural and compositional variability. The package contains 97 compressed file archives in 7-zip (.7z) format, each corresponding to one acquisition flightpath. Within each .7z archive is a set of constituent files describing properties of the LiDAR waveforms, such as return intensity, geolocation, outgoing pulse and other behavior of the sensor and signals. Once downloaded, the files must first be unzipped using the widely distributed command-line software utility 7z, using the command '7z x \[filename\].7z \[target_directory\]'. All files within the .7z archives can be opened in IDL, MatLab, or the open-source R statistical computing environment. Further details about the data package are in the attached user guide (neon_aop_crbu_waveformlidar_userguide.pdf). This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

2018 NEON and 2025 CHESS Campaigns↗

Prediction of Adverse Events in Time Series Data Using ACCEPT (Adverse Condition and Critical Event Prediction Toolbox)

Abstract:An open-source toolbox called ACCEPT (Adverse Condition and Critical Event Prediction Toolbox) that operates from within the Matlab programming environment is introduced. The toolbox provides an open source, special-purpose functionality that can be used specifically for the prediction or forecasting of adverse events in time series data. It also provides a single, unifying framework in which to compare a variety of combinations of algorithmic approaches addressing this problem. The architectural framework also offers the flexibility for expansion to accommodate the newest, latest popular regression and detection methods for this particular problem, enabling the development of an infrastructure that can act as a proving ground platform for comparing new techniques to the state of the art. As such, its intention is to act as a catalyst in advancing the state of the art in technologies related to this problem. There are a variety of other toolboxes that offer similar capabilities and features, however they are either more suitable as general purpose machine learning toolboxes or are only available commercially or through agreements. ACCEPT fills that niche by offering visibility into a specific approach for addressing the adverse event prediction problem.

programming environments↗

UNH TDP - Concurrent Measurements of Inflow, Power Performance, and Loads for a Grid-Synchronized Vertical Axis Cross-Flow Turbine Operating in a Tidal Estuary

This data was collected between October 12 and December 15 of 2021 at the University of New Hampshire (UNH) and Atlantic Marine Energy Center (AMEC) turbine deployment platform (TDP). This data set includes over 29 days of grid connected turbine operation during this 65 day time frame. The priority for this measurement campaign was to collect data while the turbine was electrically connected to the grid by means of a rectifier and inverter. The Fall_2021_UNH_Measurement_Timeline.png highlights when each instrument was functioning and the Fall_2021_UNH_Test_Log.jpg indicates the four main regions for analysis available from this measurement campaign. The TDP is a floating structure moored on the Portsmouth facing side of Memorial Bridge pier #2, which spans the Piscataqua River between Portsmouth, NH and Kittery, ME. The Piscataqua River connects the Great Bay Estuary to the Gulf of Maine and the river currents are dominated by tidal forcing with water velocities exceeding 2.5 m/s during spring ebb tides at this site which were previously characterized by Kaelin Chancey (Assessment Of The Localized Flow And Tidal Energy Conversion System At An Estuarine Bridge - UNH MS Thesis 2019). The turbine under test was a modified New Energy Corporation (Calgary, CA) model EVG-025 4-blade H-Darrius type vertical axis cross flow turbine that rotates in the clockwise direction with a rotor diameter of 3.2m and blade length of 1.7m. The hydro-foil profile was a NACA 0021 with a 10 inch chord length and a blade preset pitch angle of +4deg with a positive angle corresponding with the toe in direction. The standard EVG-025 has a rotor diameter of 3.4m and its rated power output is 25kW at 3 m/s. The rotor diameter was reduced to accommodate the size of the existing TDP moon-pool. This project was pursued to quantify device performance for cross flow turbines operating in a marine environment. Accurate physical models, to characterize cross flow turbine performance, require real operational data sets due to the complexity of blade fluid interactions. This data can help support model development which will help predict turbine performance when analyzing perspective project locations in the future. Instrumentation was deployed to measure; water speed/direction, electrical power output, turbine shaft speed, turbine thrust force, and platform motion. Concurrent measurements of these parameters allow for correlations (cause and affect) to be inferred, allowing for characterization of device performance over a range of operating conditions. Water currents were measured using Acoustic Doppler Current Profilers (ADCP's) and Acoustic Doppler Velocimeters (ADV's) directly upstream and downstream of the turbine for inflow, wake and turbulence measurements. Electrical power output was measured using the Voltsys rectifier and the Shark power meter. Shaft speed was calculated based on the Voltsys measurements of the permanent magnet three phase generator AC generation frequency, coupled directly to the cross flow turbine under test (i.e., no gear box). Platform motions were captured using a Yost IMU (inertial measurement unit). Turbine thrust loading was measured using a reaction arm about the turbine deployment platform spanning beam, where two bi-directional load cells were connected to the system via a pinned connection. This submission includes zipped folders for each instrument containing quality controlled (QC'd) data in daily .csv files for the relevant duration specific to each instrument, along with separate .csv file that contains the units for each variable. Some instrument daily files are quite large and can pose a challenge for a visual spreadsheet editor to open. A processing software like MATLAB or Python is recommended. Note the degree of QC varied between each instrument due to time constraints. Particular time and attention was given to perform quality control tests on the acoustic based instruments that are particularly suscep...

16 TIDAL AND WAVE POWER↗

Developing a Fundamental Model for an Integrated GPS/INS State Estimation System with Kalman Filtering

This work will demonstrate the integration of sensor and system dynamic data and their appropriate models using an optimal filter to create a robust, adaptable, easily reconfigurable state (motion) estimation system. This state estimation system will clearly show the application of fundamental modeling and filtering techniques. These techniques are presented at a general, first principles level, that can easily be adapted to specific applications. An example of such an application is demonstrated through the development of an integrated GPS/INS navigation system. This system acquires both global position data and inertial body data, to provide optimal estimates of current position and attitude states. The optimal states are estimated using a Kalman filter. The state estimation system will include appropriate error models for the measurement hardware. The results of this work will lead to the development of a "black-box" state estimation system that supplies current motion information (position and attitude states) that can be used to carry out guidance and control strategies. This black-box state estimation system is developed independent of the vehicle dynamics and therefore is directly applicable to a variety of vehicles. Issues in system modeling and application of Kalman filtering techniques are investigated and presented. These issues include linearized models of equations of state, models of the measurement sensors, and appropriate application and parameter setting (tuning) of the Kalman filter. The general model and subsequent algorithm is developed in Matlab for numerical testing. The results of this system are demonstrated through application to data from the X-33 Michael's 9A8 mission and are presented in plots and simple animations.

Canfield, Stephen↗

4BCO2 Model Validation and Comparisons Between Simulation and Ground and ISS Telemetry Data

The 4-bed CO2Scrubber (4BCO2), used to remove carbon dioxide from the atmosphere of the International Space Station(ISS), was built to improve upon its predecessors to meet the air revitalization needs of future missions. During this internship session, a Matlab wrapper of COMSOL models used to simulate the operation of the 4BCO2 unit was improved upon and validated against both ground test data and flight test data from the currently operating 4BCO2 unit. This presentation details the results of the activities and exercises performed during this internship session, such as the discussion on the plots generated from least squares minimization of the simulation linear driving force and sorbent bed dispersion correction factor multiplier. Plots derived from the collection and processing of telemetry data from the 4BCO2 unit aboard the ISS are discussed in relation to the work processing work performed, and comparisons between real-time CO2 removal rates and simulation removal rates are also discussed.

Larissa Lagria↗

Solar-System Ephemeris Toolbox

NASA s Jet Propulsion Laboratory (JPL) generates planetary and lunar ephemeris data and FORTRAN routines that allow users to obtain state data for the Sun, the moon, and the planets. The JPL Solar System Ephemeris Toolbox, developed at Kennedy Space Center, is a set of functions that provides the same functionality in the MATLAB computing environment along with some additional capabilities. The toolbox can be used interactively via a graphical user interface (GUI), or individual functions can be called from the MATLAB command prompt or other MATLAB scripts and functions. The toolbox also includes utility functions to define and perform coordinate transformation (e.g., mean-of-date, true-of-date, J2000) that are common in the use of these ephemerides. An attached README file guides the user through the process of constructing binary ephemeris files, verifying correct installation, and using functions to extract state data. This process also can be performed using the GUI. Help from each toolbox function is available through MATLAB s "help" function. Many of the functions in the toolbox are MATLAB equivalents of the JPL-written FORTRAN programs and subroutines used for the same purposes. A novice can use the GUI to extract state data, while a more experienced user can use the functions directly, as needed, in his/her applications. The toolbox has been tested using MATLAB Releases 13 an

Walker, Charles F.↗