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Producing Evaluation-quality 239 Pu Average Prompt Fission Neutron Multiplicities using a Correlated Fission Model

An evaluation of the average prompt fission neutron multiplicity, $\bar{ν}_p$, of 239 Pu(n,f) is shown. This evaluation includes (a) the correlated fission model CGMF, and (b) a detailed analysis of past and recently published experimental data. Using CGMF-calculated $\bar{ν}_p$ as prior enables to link, through the use of evaluated model input parameters, $\bar{ν}_p$ to other fission observables such as the prompt fission neutron spectrum (PFNS), preneutron emission fission yields as a function of mass, and the average total kinetic energy of the fragments. These evaluated parameters produce realistic predictions of many fission observables, while the evaluated $\bar{ν}_p$ agrees well (χ 2 ≈ 1) with data. Moreover, with the new evaluated $\bar{ν}_p$, the effective neutron multiplication factor of fast Pu ICSBEP critical assemblies are predicted with a mean bias of 58 pcm compared to 18 pcm with ENDF/B-VIII.0, when paired with a new 239 Pu PFNS and fission cross section. Due to these encouraging validation results, the evaluated $\bar{ν}_p$ is currently part of a release candidate for the 239 Pu ENDF/B-VIII.1 file. Hence, a correlated fission model was used for the first time for evaluating $\bar{ν}_p$ that is of evaluation quality. This is an important step towards consistent evaluations of prompt fission observables.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE JGI Metagenome Workflow

The DOE Joint Genome Institute (JGI) Metagenome Workflow performs metagenome data processing, including assembly; structural, functional, and taxonomic annotation; and binning of metagenomic data sets that are subsequently included into the Integrated Microbial Genomes and Microbiomes (IMG/M) (I.-M. A. Chen, K. Chu, K. Palaniappan, A. Ratner, et al., Nucleic Acids Res, 49:D751–D763, 2021, https://doi.org/10.1093/nar/gkaa939) comparative analysis system and provided for download via the JGI data portal (https://genome.jgi.doe.gov/portal/). This workflow scales to run on thousands of metagenome samples per year, which can vary by the complexity of microbial communities and sequencing depth. Here, we describe the different tools, databases, and parameters used at different steps of the workflow to help with the interpretation of metagenome data available in IMG and to enable researchers to apply this workflow to their own data. We use 20 publicly available sediment metagenomes to illustrate the computing requirements for the different steps and highlight the typical results of data processing. The workflow modules for read filtering and metagenome assembly are available as a workflow description language (WDL) file (https://code.jgi.doe.gov/BFoster/jgi_meta_wdl). The workflow modules for annotation and binning are provided as a service to the user community at https://img.jgi.doe.gov/submit and require filling out the project and associated metadata descriptions in the Genomes OnLine Database (GOLD) (S. Mukherjee, D. Stamatis, J. Bertsch, G. Ovchinnikova, et al., Nucleic Acids Res, 49:D723–D733, 2021, https://doi.org/10.1093/nar/gkaa983).

59 BASIC BIOLOGICAL SCIENCES↗

ORNL_AISD_NiPt

This dataset describes the nickel-platinum (NiPt) solid solution binary alloy, where the two constituent elements nickel (Ni) and platinum (Pt) are randomly placed on the face centered cubic (FCC) crystal structure, with the lattice constant of 3.840 angstroms. The dataset comprises data for three different sizes of the crystal structure: 256 atoms, 864 atoms, and 2,048 atoms, each of which contains 1900 configurations. For each size of the crystal structure, the data set was generated for concentrations ranging from 0at% of Pt to 100at% of Pt in the NiPt binary system, with increasing the concentration of Pt in the system every 5at%. For each one of the chemical compositions, 100 random configurations were generated, each with a different random seed. Each of the output files contains the mass, type, atomic coordinates, energy per atom, and forces in x, y, and z directions respectively. For each atomic configuration, the output was collected every 150 steps during the minimization stage and every 1000 steps during the replica exchange stage. Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) [1], which is a molecular dynamics code, was used to generate data for NiPt alloy. The simulation used the interatomic potential for NiPt binary system MEAM_LAMMPS_KimSeolJi_2017_PtNi__MO_020840179467_001 [3] from the OpenKIM library (Open Knowledgebase of Interatomic Models) [2]. This potential was developed based on the second nearest-neighbor modified embedded-atom method (2NN MEAM). The simulation process begins with the generation of the random NiPt structure and follows with the short minimization and replica exchange simulation. The minimization procedure adjusts atomic coordinates and performs energy minimization, which typically leads to a local potential energy minimum. The method used for the minimization was the conjugate gradient algorithm. A short replica exchange (parallel tempering) simulation involves four replicas (ensembles) of a system and follows the minimization stage. Multiple snapshots of the configuration were collected during the minimization and replica exchange stages. NiPt alloy is interesting due to its magnetic and charge transfer properties [4]. The data is provided in three compressed zipped folders: atoms256.zip, atoms864.zip, atoms2048.zip Each zipped folder contains the data that describes crystals of size 256 atoms, 864 atoms, and 2,048 atoms respectively. Each one of the three zipped folders contains the data structured in the following way: -Ni_ground_state.cfg --> atomic configuration for the pure nickel -Pt_ground_state.cfg --> atomic configuration for the pure platinum -Pt#_filtered --> folders containing atomic configurations for #at% concentration of platinum. The folder contains 100 atomic configurations, each saved in a subfolder. Each subfolder named config* is associated with a specific atomic configuration. Each of these subfolders contains files with .cfg format, corresponding to outputs for each atomic configuration The total number of atomic configurations contained in atoms256.zip is 65,046. The total number of atomic configurations contained in atoms864.zip is 63,936. The total number of atomic configurations contained in atoms2048.zip is 61,997. The total number of atomic configurations spanned by the entire dataset is 190,979. References [1] https://www.lammps.org/ [2] https://openkim.org/ [3] https://openkim.org/id/MEAM_LAMMPS_KimSeolJi_2017_PtNi__MO_020840179467_001 [4] El-Gendy, Ahmed A. and Hampel, Silke and Büccchner, Bernd and Klingeler, Rüdiger, Tuneable magnetic properties of carbon-shielded NiPt-nanoalloys, RSC Adv., volume 6, issue 57, pages 52427-52433, 2016, The Royal Society of Chemistry, doi:10.1039/C6RA05910D

36 MATERIALS SCIENCE↗

py4DSTEM: A Software Package for Four-Dimensional Scanning Transmission Electron Microscopy Data Analysis

Scanning transmission electron microscopy (STEM) allows for imaging, diffraction, and spectroscopy of materials on length scales ranging from microns to atoms. By using a high-speed, direct electron detector, it is now possible to record a full two-dimensional (2D) image of the diffracted electron beam at each probe position, typically a 2D grid of probe positions. These 4D-STEM datasets are rich in information, including signatures of the local structure, orientation, deformation, electromagnetic fields, and other sample-dependent properties. However, extracting this information requires complex analysis pipelines that include data wrangling, calibration, analysis, and visualization, all while maintaining robustness against imaging distortions and artifacts. In this paper, we present py4DSTEM, an analysis toolkit for measuring material properties from 4D-STEM datasets, written in the Python language and released with an open-source license. We describe the algorithmic steps for dataset calibration and various 4D-STEM property measurements in detail and present results from several experimental datasets. We also implement a simple and universal file format appropriate for electron microscopy data in py4DSTEM, which uses the open-source HDF5 standard. We hope this tool will benefit the research community and help improve the standards for data and computational methods in electron microscopy, and we invite the community to contribute to this ongoing project.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Revision of Fission Yields Uncertainties in ENDF/B-VIII.0

The spontaneous and neutron-induced fission yield sublibraries in the Evaluated Nuclear Data Files (ENDF/B) contain cumulative and independent fission yield values for dozens of fissioning systems, and hundreds of fission products. In this work, we report on a correction step that was undertaken after observing anomalously large uncertainties for several end-of-chain fission products. A total of 17 cumulative fission yield uncertainties and the value of 2 independent yields were corrected as a result of this revision.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Analysis of data from spacecraft (stratospheric warmings)

Investigations involved a search through existing literature and data to obtain case histories for the six or more stratospheric warmings that occurred in April - May 1969, June - July 1969, August 1969, December 1969 - January 1970, December 1970 - January 1971, and January 1973 - February 1973. For each of these warmings the following steps have been taken in preparation for analysis: (1) defining the nature of the problem; (2) literature search of stratwarmings and solar-terrestrial phenomens; and (3) file of data sources, especially stratospheric temperatures (radiances) and geophysical indices.

Source record↗

XTCE (XML Telemetric and Command Exchange) Standard Making It Work at NASA. Can It Work For You?

The XML Telemetric and Command Exchange (XTCE) standard is intended as a way to describe telemetry and command databases to be exchanged across centers and space agencies. XTCE usage has the potential to lead to consolidation of the Mission Operations Center (MOC) Monitor and Control displays for mission cross-support, reducing equipment and configuration costs, as well as a decrease in the turnaround time for telemetry and command modifications during all the mission phases. The adoption of XTCE will reduce software maintenance costs by reducing the variation between our existing mission dictionaries. The main objective of this poster is to show how powerful XTCE is in terms of interoperability across centers and missions. We will provide results for a use case where two centers can use their local tools to process and display the same mission telemetry in their MOC independently of one another. In our use case we have first quantified the ability for XTCE to capture the telemetry definitions of the mission by use of our suite of support tools (Conversion, Validation, and Compliance measurement). The next step was to show processing and monitoring of the same telemetry in two mission centers. Once the database was converted to XTCE using our tool, the XTCE file became our primary database and was shared among the various tool chains through their XTCE importers and ultimately configured to ingest the telemetry stream and display or capture the telemetered information in similar ways.Summary results include the ability to take a real mission database and real mission telemetry and display them on various tools from two centers, as well as using commercially free COTS.

CCSDS↗

Characterization of Soil and Rock Magnetic Properties along Multiple Hillslope Transects at Teller Road Site, Seward Peninsula, Alaska, 2018 and 2023

The magnetometer data was collected in multiple directions across the watershed hillslope at the NGEE Arctic Teller Road site at mile marker 27 (TL_MM27) on the Seward Peninsula, Alaska over multiple years in March 2018 and April 2023. The magnetic data were collected using a Geometrics Inc. G-858 gradiometer and G-857 base station in 2018 and the G-864 gradiometer and G857 base station in 2023. The data was collected (in all instances) by towing the gradiometer behind a snow machine around the watershed with the two sensors in a vertical profile with constant spacing during the continuous survey in that specific year. Magnetic total field measurements were collected by gradiometer and base station, and the data processing was performed in Geometrics MagMap2000 software. The processing steps were limited to removal of data spikes (despiking), reading dropouts, and correction/removal of bad GPS points. All offsets between sensors and GPS are stated within the data files and metadata, alongwith the processed and raw data. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).In this data submission there are two sets of raw magnetic data (.bin and .stn for 2018 and base for 2023; raw rover mag for 2023 is in .csv) inside two .zip files that identify the year the mag data was collected. The data are proprietary format to Geometrics and can be opened and processed with MagMap2000 which can be downloaded for free at Geometrics website. There are also two processed data files *.csv for each year and two metadata files *.csv.

54 ENVIRONMENTAL SCIENCES↗

The 1.2 micron CMOS technology

A set of test structures was designed using the Jet Propulsion Laboratory (JPL) test chip assembler and was used to evaluate the first CMOS-bulk foundry runs with feature sizes of 1.2 microns. In addition to the problems associated with the physical scaling of the structures, this geometry provided an additional set of problems, since the design files had to be generated in such a way as to be capable of being processed through p-well, n-well, and twin-well processing lines. This requirement meant that the files containing the geometric design rules as well as the structure design files had to produce process-insensitive designs, a requirement that does not apply to the more mature 3.0-micron CMOS feature size technology. Because of the photolithographic steps required with this feature size, the maximum allowable chip size was 10 x 10 mm, and this chip was divided into 24 project areas, with each area being 1.6 x 1.6 mm in size. The JPL-designed structures occupied 13 out of the 21 allowable project sizes and provided the only test information obtained from these three preliminary runs. The structures were used to successfully evaluate three different manufacturing runs through two separate foundries.

Pina, C. A.↗

Application of Data Cubes for Improving Detection of Water Cycle Extreme Events

As part of an ongoing NASA-funded project to remove a longstanding barrier to accessing NASA data (i.e., accessing archived time-step array data as point-time series), for the hydrology and other point-time series-oriented communities, "data cubes" are created from which time series files (aka "data rods") are generated on-the-fly and made available as Web services from the Goddard Earth Sciences Data and Information Services Center (GES DISC). Data cubes are data as archived rearranged into spatio-temporal matrices, which allow for easy access to the data, both spatially and temporally. A data cube is a specific case of the general optimal strategy of reorganizing data to match the desired means of access. The gain from such reorganization is greater the larger the data set. As a use case of our project, we are leveraging existing software to explore the application of the data cubes concept to machine learning, for the purpose of detecting water cycle extreme events, a specific case of anomaly detection, requiring time series data. We investigate the use of support vector machines (SVM) for anomaly classification. We show an example of detection of water cycle extreme events, using data from the Tropical Rainfall Measuring Mission (TRMM).

water cycle extreme events↗

Feasibility of Earthbound Motion in Lunar Gravity

BACKGROUND: Marginal stability of astronaut movement while performing lunar surface tasks has been well documented, and is clearly demonstrated in videos of falls, and near falls, during Apollo Lunar Extravehicular Activities. Referencing mission reports from Apollo 15 and 16 [1, 2], suspected causes for falls include: surface conditions, visibility, and gravitational effects (hypogravity). In this preliminary test, we employ the open-source biomechanical tool OpenSim [3, 4] to analyze the impact of lunar gravity (Lg) on two object-pickup motions performed by a single shirt-sleeved subject. Specifically, we attempt to answer the following questions based on an estimation of the Center of Mass Projection (CoMP) and ground reaction force Center of Pressure (COP) as it relates to the astronaut Base of Support (BOS) for 1g and Lg conditions: 1. Is the task motion, as performed in 1g, dynamically feasible in 1g and Lg? 2. Can we make the motion dynamically feasible in Lg by slowing it down? 3. Is the Lg COP equal to the 1g COP at a theoretically predicted reduction in motion speed? METHODS AND RESULTS: To answer the first question, the gravitational acceleration in the OpenSim model is modified from a nominal 9.81 m/s2 to 1.64 m/s2, and the 1g joint trajectory is input to an OpenSim based method [5] for estimating ground reaction forces and moments. From this method, the position of the CoMP and COP can be estimated and checked to see if they remain within a simulated BOS formed from the footprint of the OpenSim model to determine whether the motion is dynamically feasible. As expected, both of the motions were estimated to be feasible in a 1g environment, however, both motions had periods of infeasibility in Lg. It is well known that crew members make adjustments to motion trajectories in altered gravity fields to maintain balance. As a first step, we considered the simple adjustment of slowing the motion in Lg by a constant factor. This was accomplished by scaling the time stamps in the motion trajectory file by that factor. For the two motions considered, it was found that scale factors of 1.3 and 1.4 kept the COP just within the subject BOS. The CoMP is unchanged by the gravity field. Simple analysis of an inverted pendulum in the Lg environment, which generalizes to a general multibody system, leads to a theoretical prediction that a reduction in speed factor of √1g/Lg, or 2.445, will make the COP trajectory in Lg equivalent to that in 1g. When the above procedure was performed with a factor of 2.445, the estimated COP in Lg, was observed to be very close to that in 1g. In summary, we have developed a method for estimating the CoMP and COP in Lg, for subject motion collected in 1g. We believe this method can prove to be a valuable check and balance for simulated Lg training and testing by exposing potential simulator-induced artifacts that make the simulated task motion seem possible, when in fact, it would violate the above criteria. We also note that a reduction in task speed should tend the task motion towards stability, with a theoretical slowdown factor of √1g/Lg making the motion stability equal to that in 1g according to the CoMP and COP criteria.

R K Huffman↗

Visual PEF Reader - VIPER

This software graphically displays all pertinent information from a Predicted Events File (PEF) using the Java Swing framework, which allows for multi-platform support. The PEF is hard to weed through when looking for specific information and it is a desire for the MRO (Mars Reconn aissance Orbiter) Mission Planning & Sequencing Team (MPST) to have a different way to visualize the data. This tool will provide the team with a visual way of reviewing and error-checking the sequence product. The front end of the tool contains much of the aesthetically appealing material for viewing. The time stamp is displayed in the top left corner, and highlighted details are displayed in the bottom left corner. The time bar stretches along the top of the window, and the rest of the space is allotted for blocks and step functions. A preferences window is used to control the layout of the sections along with the ability to choose color and size of the blocks. Double-clicking on a block will show information contained within the block. Zooming into a certain level will graphically display that information as an overlay on the block itself. Other functions include using hotkeys to navigate, an option to jump to a specific time, enabling a vertical line, and double-clicking to zoom in/out. The back end involves a configuration file that allows a more experienced user to pre-define the structure of a block, a single event, or a step function. The individual will have to determine what information is important within each block and what actually defines the beginning and end of a block. This gives the user much more flexibility in terms of what the tool is searching for. In addition to the configurability, all the settings in the preferences window are saved in the configuration file as well

Luo, Victor↗

Coupling Subsurface and Above-Surface Models for Optimizing the Design of Borefields and District Heating and Cooling Systems

Accurate dynamic energy simulation is important for the design and sizing of district heating and cooling systems with geothermal heat exchange for seasonal energy storage. Current modeling approaches in building and district energy simulation tools typically consider heat conduction through the ground between boreholes without flowing groundwater. While detailed simulation tools for subsurface heat and mass transfer exist, these fall short in simulating above-surface energy systems. To support the design and operation of such systems, the study developed a coupled model including a software package for building and district energy simulation, and software for detailed heat and mass transfer in the subsurface. For the first, it uses the open-source Modelica Buildings Library, which includes dynamic simulation models for building and district energy and control systems. For the heat and mass transfer in the soil, it uses the TOUGH simulator. The TOUGH family of codes can model heat and multi-phase, multi-component mass transport for a variety of fluid systems, as well as chemical reactions, in fractured porous media. The study validated the coupled modeling approach by comparing the simulation results with one from the g-function based ground response model. It then looked into effects when the water table and the regional groundwater flow are considered in the ground, from the perspective of heat exchange between borehole and ground, and the electrical consumption of the district heating and cooling systems. To access the simulation models, please find the links in the submission: -- For coupled approach validation: see model Buildings.Fluid.Geothermal.Borefields.Examples.BorefieldsWithTough and Buildings.Examples.DistrictReservoirNetworks.Examples.Reservoir3Variable_TOUGH from the "Modelica Building Library" resource, branch issue1495_tough_interface, commit a2667c0. -- For the study of the effect of water table: see model Buildings.Examples.DistrictReservoirNetworks.Examples.Reservoir3Variable_TOUGH from he "Modelica Building Library" resource, branch issue1495_tough_interface_moreIO, commit 760de49. -- For the study of the effect of regional groundwater flow: see Buildings.Examples.DistrictReservoirNetworks.Examples.Reservoir3Variable_TOUGH from he "Modelica Building Library" resource, branch issue1495_tough_interface_moreIO_3D, commit c2a2d2a. The coupling interface script "GrounResponse.py" can be found from the above links in the folder Buildings/Resources/Python-Sources. Also, the needed files for TOUGH simulation are in the folder Buildings/Resources/Python-Sources/ToughFiles that can be accessed through the above links. A brief description of these files is given below; detailed specifications for the first three files may be found in the TOUGH3 Users Guide (Jung et al., 2018) https://tough.lbl.gov/documentation/tough-manuals/. (1) INCON - initial conditions for each grid block (2) INFILE - main input file with material properties and control parameters (3) MESH - description of the computational grid (4) readsave - Modelica/TOUGH interface program: read the final output of TOUGH simulation after TOUGH time step and prepare for transfer to Modelica for next Modelica time step (5) readsave.inp - input parameters for program readsave (6) writeincon - Modelica/TOUGH interface program: write the output of Modelica after Modelica time step and prepare for transfer to TOUGH as initial conditions for the next TOUGH step (7) writeincon.inp - input parameters for program writeincon

15 GEOTHERMAL ENERGY↗

HERO WEC V1.0 2024 - WEC-Sim Detailed Simulation Runs and Summary Data

This dataset includes results from simulations of NREL's hydraulic and electric reverse osmosis wave energy converter (HEREO WEC). Simulation runs include 135 wave cases that were based on the updated WEC-Sim model, which is linked below. The data represented in this repository is based on an updated WEC-Sim model using laboratory data to tune and refine the original WEC-Sim model for the V1.0 HERO WEC. The 135 wave cases represent waves with the following wave height and wave period ranges: - Significant Wave Height: 0.25 - 3.75m in 0.25m increments - Wave Period: 5 - 13 sec in 1 sec increments Each run was simulated using a Pierson-Moskowitz irregular wave spectrum with a 100 second ramp time, a total simulation time of 3,100 seconds, and a simulation time-step of 0.005s. A reference table has been included to map each multi condition run (MCR) case with each wave condition. Summary data set includes a spreadsheet and image files with matrices that are associated with data from simulation runs. All matrices cover the same significant wave height and wave periods from the simulation runs, in the same increments. The following matrices are included: - Power Abs: The average absorbed power from the WEC (calculated from anchor reaction force and heave velocity) - Power Hyd: The average hydraulic power output at pump (calculated from pump output flow and pressure) - Power - Hyd ROi: The average hydraulic power measured at the RO system inlet (calculated from RO system pressure and flow (pre-accumulator)) - Flow - Pump out: The average flowrate measured at the pump outlet - Flow - Perm: The average permeate (clean water) production - Flow - RO (pre): The average flowrate measured at the inlet of the RO system before the accumulators - Flow - RO (post): The average flowrate measured after the accumulator bank in the RO system - Pressure - RO: The average pressure measured at the inlet of the RO system This data set has been developed by the National Renewable Energy Laboratory, operated by the Alliance for Sustainable Energy, LLC, for the U.S. Department of Energy (DOE) under Contract No. DE-AC36-08GO28308. Funding provided by the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Water Power Technologies Office.

16 TIDAL AND WAVE POWER↗

Flight Dynamic Model Exchange using XML

The AIAA Modeling and Simulation Technical Committee has worked for several years to develop a standard by which the information needed to develop physics-based models of aircraft can be specified. The purpose of this standard is to provide a well-defined set of information, definitions, data tables and axis systems so that cooperating organizations can transfer a model from one simulation facility to another with maximum efficiency. This paper proposes using an application of the eXtensible Markup Language (XML) to implement the AIAA simulation standard. The motivation and justification for using a standard such as XML is discussed. Necessary data elements to be supported are outlined. An example of an aerodynamic model as an XML file is given. This example includes definition of independent and dependent variables for function tables, definition of key variables used to define the model, and axis systems used. The final steps necessary for implementation of the standard are presented. Software to take an XML-defined model and import/export it to/from a given simulation facility is discussed, but not demonstrated. That would be the next step in final implementation of standards for physics-based aircraft dynamic models.

Jackson, E. Bruce↗

A user-friendly, menu-driven, language-free laser characteristics curves graphing program for desk-top IBM PC compatible computers

A facility was established that uses collected data and feeds it into mathematical models that generate improved data arrays by correcting for various losses, base line drift, and conversion to unity scaling. These developed data arrays have headers and other identifying information affixed and are subsequently stored in a Laser Materials and Characteristics data base which is accessible to various users. The two part data base: absorption - emission spectra and tabulated data, is developed around twelve laser models. The tabulated section of the data base is divided into several parts: crystalline, optical, mechanical, and thermal properties; aborption and emission spectra information; chemical name and formulas; and miscellaneous. A menu-driven, language-free graphing program will reduce and/or remove the requirement that users become competent FORTRAN programmers and the concomitant requirement that they also spend several days to a few weeks becoming conversant with the GEOGRAF library and sequence of calls and the continual refreshers of both. The work included becoming thoroughly conversant with or at least very familiar with GEOGRAF by GEOCOMP Corp. The development of the graphing program involved trial runs of the various callable library routines on dummy data in order to become familiar with actual implementation and sequencing. This was followed by trial runs with actual data base files and some additional data from current research that was not in the data base but currently needed graphs. After successful runs, with dummy and real data, using actual FORTRAN instructions steps were undertaken to develop the menu-driven language-free implementation of a program which would require the user only know how to use microcomputers. The user would simply be responding to items displayed on the video screen. To assist the user in arriving at the optimum values needed for a specific graph, a paper, and pencil check list was made available to use on the trial runs.

Klutz, Glenn↗

Work Package 5: Contingency Management. Mission Planning Requirements Document: Preliminary Version. Revision A

The purpose of this document is to identify the general flight/mission planning requirements for same-day file-and-fly access to the NAS for both civil and military High-Altitude Long Endurance (HALE) Unmanned Aircraft System (UAS). Currently the scope of this document is limited to Step 1, operations above flight level 43,000 feet (FL430). This document describes the current applicable mission planning requirements and procedures for both manned and unmanned aircraft and addresses HALE UAS flight planning considerations in the future National Airspace System (NAS). It also discusses the unique performance and operational capabilities of HALE UAS associated with the Access 5 Project, presents some of the projected performance characteristics and conceptual missions for future systems, and provides detailed analysis of the recommended mission planning elements for operating HALE UAS in the NAS.

Source record↗

WORM (Write One, Read Many)

WORM (Write One, Run Many) is an easy to use, cross platform, embedded and extensible, functional programming language designed to facilitate the creation of input-decks for computer codes that use standard ASCII text files for input. WORM makes it easy to create generic (yet, complex and powerful) reusable models. Additionally its nature allows for complex calculations and routines to be coded once and easily reused, further simplifying the creation of input decks. WORM (Write One, Run Many) is a powerful and versatile tool designed to improve the efficiency of today’s criticality safety analyst by allowing: + input decks for parametric studies to be created quickly and easily, + calculations and variables to be imbedded into any input deck, thus allowing for meaningful parameter specifications, + problems to be specified using any combination of units, and + complex mathematically defined models to be created. A very simple syntax is employed, and therefore the WORM is easy to learn. A WORM model is essentially a standard input deck with some of its numerical values replaced by WORM code. WORM code may include and evaluate the following mathematical operators and functions: addition, subtraction, multiplication, division, exponentiation, modulus, sine, cosine, tangent, arcsine, arccosine, arctangent, the natural logarithm, logarithm base 10, integer truncation, absolute value, and random number. Several common constants, e.g., pi, e, and Avogadros’s Number (both as 6.022e23 and 0.6022), are predefined in WORM. Additionally, many unit conversion factors are also predefined: millimeters, meters, inches, feet, yards, and mils to centimeters; kilograms, pounds, and ounces to grams; liters, milliliters, gallons, and fluid ounces to cubic centimeters; and angular degrees to radians. For parametric studies, WORM supports various shorthand list specifications: the explicit step size, linear interpolation, and logarithmic interpolation. The list notation sequentially assigns multiple values to a name. WORM creates an input deck for each value of the name. If multiple lists are used, WORM steps through each list individually, i.e., WORM creates input decks corresponding to each and every permutation of the list values. Additionally, a library of standard material definitions and Perl subroutines are included. Any one of these files can be incorporated into the subject model with a simple WORM read command. WORM is completely written in Perl, the Practical Extraction and Reporting Language. Perl is one of the most portable programming languages available today. As such, the WORM works on practically any computer platform.

Sartor, Raymond↗