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Rapid Model Import Tool (RMIT)

Our project is about developing a tool to implement conversion of 3D Computer Aided Design (CAD) models produced with software such as Delmia, 3DS Max, or Maya, into a size and format compatible with the Unity 3D environment. RMIT will be used to aid KSC engineering personnel in the design, development, testing, operations, and training on spacecraft, launch vehicles, facilities, and ground support equipment. For our project, we are using Blender, a free/open-source 3D graphics software, with the goal of developing, testing, and deploying a 3D CAD model converter tool. I worked on using Blender to import 3D CAD models exported from CATIA software into Collada file format. The Collada file format has file extension DAE. Importing the Collada DAE file as is into Blender, generates dots and dashes. In 3DS Max, there is an existing OpenCollada plugin and with that plugin, 3DS Max can import the DAE file successfully. But, Blender does not seem to have an OpenCollada plugin, so I worked on writing a new OpenCollada plugin for Blender. Since 3DS Max was able to display the image, I looked into comparing differences between the original DAE file and the DAE file exported from 3DS Max using the OpenCollada plugin. As Collada documents describing digital assets are XML files with file extension DAE, Collada files contains XML tags, making them easily modifiable. After some research, it appears that Blender does not like primitive 2D tags like tristrips and trifans. Changing those tags to polygons slightly improved the image, but the pieces were exploded. I found after further research comparing differences between the original file and the file exported from 3DS Max that the values inside the translate tags in the original file are scaled down by a factor of 25.4 in the exported file from 3DS Max, representing the millimeters to inches conversion (1 inch = 25.4 millimeters). After scaling down values inside all of the translate tags by 25.4, the exploded pieces stuck back in, but the image needed further improvement. I have been able to create a new plugin in Blender that takes the original DAE file, replaces the primitive 2D tags tristrips and trifans with polygons, scales down the values inside the translate tags by a factor of 25.4, and saves the changes into a temporary DAE file. After the temporary DAE file is imported into Blender, the temp file is then deleted, keeping the original DAE file intact. Starting with a DAE file that is exported using the NASA Enterprise Visualization Application (NEVA), a Collada exporter, from CATIA gives better results. NEVA is a Design Visualization product that is used for exporting 3D models from CATIA. With NEVA, the up axis is defined in the top-level node if navigation gravity is enabled. With that file, just replacing the primitive tags tristrips and trifans with polygons in yields a much improved image in Blender. As we identify more differences between the original DAE file and the DAE file exported from 3DS Max, this plugin can be improved further. Our goal is to have a model that is formatted and sized for import into Unity, and we are trying out different 3D programs to see which will work best.

Ayyangar, Arjun↗

Space Science and the International Traffic in Arms Regulations: Summary of a Workshop

The United States seeks to protect its security and foreign-policy interests, in part, by actively controlling the export of goods, technologies, and services that are or may be useful for military development in other nations. "Export" is defined not simply as the sending abroad of hardware but also as the communication of related technology and know-how to foreigners in the United States and overseas. The U.S. government mechanism for controlling dual-use items--items in commerce that have potential military use is the Export Administration Regulations (EAR) administered by the Department of Commerce; items defined in law as defense articles fall under the jurisdiction of the Department of State and the International Traffic in Arms Regulations (ITAR). Because of the potential military implications of the export of defense articles, the ITAR regime imposes much greater burdens (on both the applicant and the government) than does the EAR regime during the process of applying for, and implementing the provisions of, licenses and technical-assistance agreements. Until the early 1990s export control activity related to all space satellites (commercial and scientific) was handled under ITAR. Between 1992 and 1996 the George H.W. Bush and the Clinton administrations transferred jurisdiction over the licensing of civilian communications satellites to the Commerce Department under EAR. In 1999, however, in response to broad concerns about Chinese attempts to acquire U.S. high technology, the U.S. House of Representatives convened the Select Committee on U.S. National Security and Military/Commercial Concerns with the People s Republic of China, also known as the Cox Committee. One of the many consequences of the Cox Committee's report was Congress's mandate that jurisdiction over export and licensing of satellites and related equipment and services, irrespective of military utility, be transferred from the Department of Commerce to the State Department and that such equipment and services be covered as defense articles under ITAR. Scientific satellites were explicitly included despite their use for decades in peaceful internationally conducted cooperative scientific research. It is widely recognized that the shift in regulatory regime from EAR to ITAR has had major deleterious effects on international scientific research activities that depend on satellites, spaceflight hardware, and other items that are now controlled by ITAR. Furthermore, contravening U.S. interests in attracting foreign students to U.S. universities, the capture of space technology by ITAR has caused serious problems in the teaching of university space science and engineering classes, virtually all of which include non-U.S. students. This report is a summary of a September 2007 workshop in which participants from the space research communities and the export-control administration and policy communities came together to discuss problems, effects, and potential solutions regarding the application of ITAR to space science. The principal themes and ideas that emerged from the discussions are summarized.

Finarelli, Margaret G.↗

Arctic Ocean Freshwater: How Robust are Model Simulations

The Arctic freshwater (FW) has been the focus of many modeling studies, due to the potential impact of Arctic FW on the deep water formation in the North Atlantic. A comparison of the hindcasts from ten ocean-sea ice models shows that the simulation of the Arctic FW budget is quite different in the investigated models. While they agree on the general sink and source terms of the Arctic FW budget, the long-term means as well as the variability of the FW export vary among models. The best model-to-model agreement is found for the interannual and seasonal variability of the solid FW export and the solid FW storage, which also agree well with observations. For the interannual and seasonal variability of the liquid FW export, the agreement among models is better for the Canadian Arctic Archipelago (CAA) than for Fram Strait. The reason for this is that models are more consistent in simulating volume flux anomalies than salinity anomalies and volume-flux anomalies dominate the liquid FW export variability in the CAA but not in Fram Strait. The seasonal cycle of the liquid FW export generally shows a better agreement among models than the interannual variability, and compared to observations the models capture the seasonality of the liquid FW export rather well. In order to improve future simulations of the Arctic FW budget, the simulation of the salinity field needs to be improved, so that model results on the variability of the liquid FW export and storage become more robust.

Jahn, A.↗

Chemical Data Assimilation Estimates of Continental US Ozone and Nitrogen Budgets during INTEX-A

Global ozone analyses, based on assimilation of stratospheric profile and ozone column measurements, and NOy predictions from the Real-time Air Quality Modeling System (RAQMS) are used to estimate the ozone and NOy budget over the Continental US during the July-August 2004 Intercontinental Chemical Transport Experiment-North America (INTEX-A). Comparison with aircraft, satellite, surface, and ozonesonde measurements collected during the INTEX-A show that RAQMS captures the main features of the global and Continental US distribution of tropospheric ozone, carbon monoxide, and NOy with reasonable fidelity. Assimilation of stratospheric profile and column ozone measurements is shown to have a positive impact on the RAQMS upper tropospheric/lower stratosphere ozone analyses, particularly during the period when SAGE III limb scattering measurements were available. Eulerian ozone and NOy budgets during INTEX-A show that the majority of the Continental US export occurs in the upper troposphere/lower stratosphere poleward of the tropopause break, a consequence of convergence of tropospheric and stratospheric air in this region. Continental US photochemically produced ozone was found to be a minor component of the total ozone export, which was dominated by stratospheric ozone during INTEX-A. The unusually low photochemical ozone export is attributed to anomalously cold surface temperatures during the latter half of the INTEX-A mission, which resulted in net ozone loss during the first 2 weeks of August. Eulerian NOy budgets are shown to be very consistent with previously published estimates. The NOy export efficiency was estimated to be 24 percent, with NOx+PAN accounting for 54 percent of the total NOy export during INTEX-A.

Pierce, Robert B.↗

Component Level Regression Testing in a Hierarchical Architecture

The Goddard Earth Observing System (GEOS) is an Earth system model consisting of a large suite of individual model components that can be coupled in a flexible manner to investigate a variety of Earth science issues. Specific GEOS model configurations are composed as a hierarchical collection of components based on the Earth System Modeling Framework (ESMF). Regression testing of GEOS is currently limited to (1) full system tests that are poor at isolating specific defects and (2) a suite of unit tests which have very limited coverage. As part of our approach to improve upon the current testing situation, we have prototyped the capability to perform regression tests on individual GEOS components by leveraging and extending existing checkpoint/restart capabilities. In our implementation, each ESMF component has 3 states: Import (what it needs to run), Export (which it needs to provide to other components), and Internal (the component state proper). By capturing, Import, Export and Internal states for a given component during a ull run of GEOS, a generic driver can then rerun the component offline and compare expected exports with those that have been saved. The hierarchical structure of GEOS introduces an interesting wrinkle when trying to test components that in turn drive interacting child components. To fully isolate a parent component, we use the approach of software mocks, in which the exports of children are also saved during the initial capture run of GEOS. Then when testing the parent component, the children components are replaced by a generic mock component that produces exports from the previously saved data and ensures that that all interdependencies among children components are satisfied.

Thomas Clune↗

Component Level Testing in a Hierarchical Architecture

The Goddard Earth Observing System (GEOS) is an Earth system model consisting of a large suite of individual model components that can be coupled in a flexible manner to investigate a variety of Earth science issues. Specific GEOS model configurations are composed as a hierarchical collection of components based on the Earth System Modeling Framework (ESMF). Regression testing of GEOS is currently limited to (1) full system tests that are poor at isolating specific defects and (2) a suite of unit tests which have very limited coverage. As part of our approach to improve upon the current testing situation, we have prototyped the capability to perform regression tests on individual GEOS components by leveraging and extending existing checkpoint/restart capabilities. In our implementation, each ESMF component has 3 states: Import (what it needs to run), Export (which it needs to provide to other components), and Internal (the component state proper). By capturing, Import, Export and Internal states for a given component during a ull run of GEOS, a generic driver can then rerun the component offline and compare expected exports with those that have been saved. The hierarchical structure of GEOS introduces an interesting wrinkle when trying to test components that in turn drive interacting child components. To fully isolate a parent component, we use the approach of software mocks, in which the exports of children are also saved during the initial capture run of GEOS. Then when testing the parent component, the children components are replaced by a generic mock component that produces exports from the previously saved data and ensures that that all interdependencies among children components are satisfied.

Tom Clune↗

Estuarine Dissolved Organic Carbon Flux From Space: With Application to Chesapeake and Delaware Bays

This study uses a neural network model trained with in situ data, combined with satellite data and hydrodynamic model products, to compute the daily estuarine export of dissolved organic carbon (DOC) at the mouths of Chesapeake Bay (CB) and Delaware Bay (DB) from 2007 to 2011. Both bays show large flux variability with highest fluxes in spring and lowest in fall as well as interannual flux variability (0.18 and 0.27 Tg C/year in 2008 and 2010 for CB; 0.04 and 0.09 Tg C/year in 2008 and 2011 for DB). Based on previous estimates of total organic carbon (TOCexp) exported by all Mid-Atlantic Bight estuaries (1.2 Tg C/year), the DOC export (CB + DB) of 0.3 Tg C/year estimated here corresponds to 25% of the TOCexp. Spatial and temporal covariations of velocity and DOC concentration provide contributions to the flux, with larger spatial influence. Differences in the discharge of fresh water into the bays (74 billion cu. m/year for CB and 21 billion cu. m/year for DB) and their geomorphologies are major drivers of the differences in DOC fluxes for these two systems. Terrestrial DOC inputs are similar to the export of DOC at the bay mouths at annual and longer time scales but diverge significantly at shorter time scales (days to months). Future efforts will expand to the Mid-Atlantic Bight and Gulf of Maine, and its major rivers and estuaries, in combination with coupled terrestrial-estuarine-ocean biogeochemical models that include effects of climate change, such as warming and CO2 increase.

Estuarine DOC export↗

Cyote-attack Chain Estimator

Attack Chain Estimator (ACE) Application Overview The Attack Chain Estimator (ACE) Application is a sophisticated tool designed for the ingestion, classification, sequencing, and enrichment of cybersecurity threat reports. This application leverages advanced machine learning models and extensive historical data to provide comprehensive insights into cyber threats, specifically targeting Industrial Control Systems (ICS). Purpose The primary functions of the ACE Application include: Ingestion of Cybersecurity Threat Reporting: Capable of ingesting text-based threat reports in markdown or text file format. Supports ingestion of structured data from other sources in STIX/JSON format. Classification of Report’s Text-Based Events: Utilizes a DeBERTa classifier, specifically trained on cybersecurity data, to map the events to MITRE ATT&CK for ICS Tactics and Techniques. Classification is performed using multiple Jupyter notebooks and machine learning workflows hosted as FastAPI microservices: regex_data deberta_base_35_train_hft_classifier_mlflow.ipynb hft_regex_classifier_mlflow.ipynb param_train_hft_classifier_mlflow.ipynb regex_tactic_tech.ipynb Ordering of Tactics, Techniques, and Observable Events: Sequences the identified tactics, techniques, and events to form a coherent attack chain. Enrichment with Historical Attack Chain Details: Enhances the attack chain with details from historical attacks using a Markov model developed from CyOTE Precursor Analysis Report data. The Markov model is available as a FastAPI endpoint for seamless integration. Enrichment with Adversary Emulation Capabilities Data: Integrates adversary emulation capabilities data using MITRE Caldera for OT adversary abilities UUIDs. Export of Output Files: Provides options to export the enriched attack chain in JSON or CSV formats. Routing of Output to Other Applications: Facilitates routing of output to various platforms and applications, including: Threat Intelligence Platforms COREII Scout for Threat Intelligence Analysis COREII Modeling and Simulation for Adversary Emulation Technical Description The ACE Application is an advanced cybersecurity tool designed to provide detailed threat analysis and sequence generation. It is built on a robust architecture that integrates natural language processing, machine learning, and historical data modeling. Key Components: Data Ingestion Module: Handles the input of threat reports and data from various formats, ensuring flexibility in data sources. Classification Engine: Employs DeBERTa-based classifiers hosted as FastAPI microservices to analyze and classify threat report events in accordance with the MITRE ATT&CK framework for ICS. Sequence Generator: Orders the classified events into a logical attack chain, providing clear insight into the sequence of tactics and techniques used in the threat. Enrichment Engine: Integrates historical data and adversary emulation capabilities to enhance the attack chain with valuable context and additional details. The historical data enrichment is powered by a Markov model, which is available as a FastAPI endpoint. Export and Routing Module: Facilitates the export of the enriched attack chain in multiple formats and routes the output to designated applications for further analysis or emulation.

Paul, Tony [Idaho National Laboratory (INL), Idaho↗

A simulation analysis of the fate of phytoplankton within the mid-Atlantic bight

A time-dependent, three-dimensional simulation model of wind-induced changes of the circulation field, of light and nutrient regulation of photosynthesis, of vertical mixing as well as algal sinking, and of herbivore grazing stress, is used to analyze the seasonal production, consumption, and transport of the spring bloom within the mid-Atlantic Bight. The particular case (c) of a 58-day period in February-April 1979, simulated primary production, based on both nitrate and recycled nitrogen, with a mean of 0.62 g C sq m/day over the whole model domain, and an export at the shelf-break off Long Island of 2.60 g ch1 sq m/day within the lower third of the water column. About 57% of the carbon fixation was removed by herbivores, with 21% lost as export, either downshelf or offshore to slope waters, after the first 58 days of the spring bloom. Extension of the model for another 22 days of case (c) increased the mean export to 27%, while variation of the model's parameters in 8 other cases led to a range in export from 8% to 38% of the average primary production. Spatial and temporal variations of the simulated albal biomass, left behind in the shelf water column, reproduced chlorophyll fields sensed by satellite, shipboard, and in situ instruments.

Walsh, J. J.↗

An Arctic source for the Great Salinity Anomaly - A simulation of the Arctic ice-ocean system for 1955-1975

The paper employs a fully prognostic Arctic ice-ocean model to study the interannual variability of sea ice during the period 1955-1975 and to explain the large variability of the ice extent in the Greenland and Iceland seas during the late 1960s. The model is used to test the contention of Aagaard and Carmack (1989) that the Great Salinity Anomaly (GSA) was a consequence of the anomalously large ice export in 1968. The high-latitude ice-ocean circulation changes due to wind field changes are explored. The ice export event of 1968 was the largest in the simulation, being about twice as large as the average and corresponding to 1600 cu km of excess fresh water. The simulations suggest that, besides the above average ice export to the Greenland Sea, there was also fresh water export to support the larger than average ice cover. The model results show the origin of the GSA to be in the Arctic, and support the view that the Arctic may play an active role in climate change.

Hakkinen, Sirpa↗