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At the end of 2019, there were assessments of multiple safety management programs relied on by NCS that had significant issues identified. Discuss outliers with responders. Better definitions of categories. Expand audience. Move from Excel spreadsheet to web-based.
A Java-language computer program has been written to facilitate mining of data in files in the Shuttle Data Center (SDC) archives. This program can be executed on a variety of workstations or via Web-browser programs. This program is partly similar to prior C-language programs used for the same purpose, while differing from those programs in that it exploits the platform-neutrality of Java in implementing several features that are important for analysis of large sets of time-series data. The program supports regular expression queries of SDC archive files, reads the files, interleaves the time-stamped samples according to a chosen output, then transforms the results into that format. A user can choose among a variety of output file formats that are useful for diverse purposes, including plotting, Markov modeling, multivariate density estimation, and wavelet multiresolution analysis, as well as for playback of data in support of simulation and testing.
Romie is a decision support tool based on AI's latest advances in the domain of robust scheduling. Unlike all its predecessors, the tool allows to (i) visually model the operational problem and context entirely (ii) optimize to find near-optimal schedules while taking uncertainty into account and deals with (iii) a combination of various {key performance indicators (KPIs). It comes with a web user interface. Part or all of the modelled activities may be associated to random variables describing their stochastic durations, in order to produce schedules that are robust w.r.t. temporal uncertainty. Hence, depending on the pursued KPIs, the schedules maximize a combination of the following terms: the probability of satisfying the problem constraints, the expected return/efficiency, the expected outcome quality, and even the operators' wellness by minimizing its expected extra-hours. Initially developed for spatial exploration and demonstration in the context of Mars analog missions, this versatile tool is here applied to operations management in both biotechnology manufacturing and robots parametrization in a cave exploration context.
This project report presents the results from the AU31 project that is entitled “Enhancing Risk Analysis of Accidental Release Using CFD Modeling and Machine Learning” performed between FY2021 and FY2022. The technical objective of this project is to enhance risk analysis of accidental release of radioactive materials and provide novel risk forecasting and capabilities for assessing unplanned hazardous chemical releases for the U.S. Department of Energy (DOE). The approach includes a cross-platform finite element analysis of airborne chemical release, machine learning (ML) for simulation and forecasting, and a big data approach to data management, transformation and analysis capable of handling petabyte-scale unstructured and structured data. The outcome of these findings were assembled and accessible as a final output via an intuitive web hosted geospatial-based user interface for demonstration and general dissemination. These new results also provide a mechanism of combining this knowledge in a risk analysis framework tool. The geospatial analysis and output can utilize 5 years of qualified meteorological data to illustrate projected plume footprints that are generated from computational aspects of this study. Specifically, we show the development of a geospatial risk analysis capabilities to respond to and plan for accidental release of radioactive materials and to provide a risk forecasting tool for assessing hazardous chemical releases for the DOE. The focus of this effort is germane to common practices in risk analysis; and it is highly relevant to the timely and transparent release of information related to materials at risk including hazardous materials and chemical vapors and rapid assessment of the potential impacts on the workforce at active sites across the DOE complex.
Design of a successful product requires evaluating many design alternatives in a limited design cycle time. This can be achieved through leveraging design space exploration tools and available computing resources on the network. This paper presents a parallel trade study architecture to integrate trade study clients and computing resources on a network using Web services. The parallel trade study solution is demonstrated to accelerate design of experiments, genetic algorithm optimization, and a cost as an independent variable (CAIV) study for a space system application.
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.
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.
Approximately three years ago, the Agency's lead center for the human elements of spaceflight (the Johnson Space Center), along with the National Biomedical Research Institute (NSBRI) (which has the lead role in developing countermeasures) initiated an activity to identify the most critical risks confronting extended human spaceflight. Two salient factors influenced this activity: first, what information is needed to enable a "go/no go" decision to embark on extended human spaceflight missions; and second, what knowledge and capabilities are needed to address known and potential health, safety and performance risks associated with such missions. A unique approach was used to first define and assess those risks, and then to prioritize them. This activity was called the Critical Path Roadmap (CPR) and it represents an opportunity to develop and implement a focused and evolving program of research and technology designed from a "risk reduction" perspective to prevent or minimize the risks to humans exposed to the space environment. The Critical Path Roadmap provides the foundation needed to ensure that human spaceflight, now and in the future, is as safe, productive and healthy as possible (within the constraints imposed on any particular mission) regardless of mission duration or destination. As a tool, the Critical Path Roadmap enables the decisionmaker to select from among the demonstrated or potential risks those that are to be mitigated, and the completeness of that mitigation. The primary audience for the CPR Web Site is the members of the scientific community who are interested in the research and technology efforts required for ensuring safe and productive human spaceflight. They may already be informed about the various space life sciences research programs or they may be newcomers. Providing the CPR content to potential investigators increases the probability of their delivering effective risk mitigations. Others who will use the CPR Web Site and its content include program managers and administrators who track the program and are involved in decisions regarding resource allocation and program evaluation.
Interconnectivity has become a substratum of technology as the benefits of data-driven functionality are being realized in nearly all industries. Increased connectivity of Operational Technology (OT) exacerbates cyber risks because Industrial Control Systems (ICS) are becoming exposed to the Internet. These exposures are often done inadvertently through misconfigurations as additional network devices come online. Attack surface management (ASM) platforms can be used to identify vulnerabilities by performing external network discovery over the Internet using web spiders. These web spiders enable big data analytics of Internet of Things (IoT) devices as identifiable information of Internet-exposed equipment are archived in searchable databases that are made publicly available. There are a multitude of ASM service providers on the market. Here, this study was conducted to evaluate several commonly known tools to determine the aggregate attack surface of control systems. Queries were crafted by targeting commonly known manufacturers and communication protocols found in OT networks. Identified devices were that categorized based on technology types. Each query was replicated between several tools to target identical ICS equipment. Findings in this paper suggested a significant variance in the exposures discovered by each tool, but unique contributions were identified for each tool when a merged attack surface was derived. Therefore, all tools should be used in aggregate.
Approximately three years ago, the Agency's lead center for the human elements of spaceflight (the Johnson Space Center), along with the National Biomedical Research Institute (NSBRI) (which has the lead role in developing countermeasures) initiated an activity to identify the most critical risks confronting extended human spaceflight. Two salient factors influenced this activity: first, what information is needed to enable a "go/no go" decision to embark on extended human spaceflight missions; and second, what knowledge and capabilities are needed to address known and potential health, safety and performance risks associated with such missions. A unique approach was used to first define and assess those risks, and then to prioritize them. This activity was called the Critical Path Roadmap (CPR) and it represents an opportunity to develop and implement a focused and evolving program of research and technology designed from a "risk reduction" perspective to prevent or minimize the risks to humans exposed to the space environment. The Critical Path Roadmap provides the foundation needed to ensure that human spaceflight, now and in the future, is as safe, productive and healthy as possible (within the constraints imposed on any particular mission) regardless of mission duration or destination. As a tool, the Critical Path Roadmap enables the decision maker to select from among the demonstrated or potential risks those that are to be mitigated, and the completeness of that mitigation. The primary audience for the CPR Web Site is the members of the scientific community who are interested in the research and technology efforts required for ensuring safe and productive human spaceflight. They may already be informed about the various space life sciences research programs or they may be newcomers. Providing the CPR content to potential investigators increases the probability of their delivering effective risk mitigations. Others who will use the CPR Web Site and its content include program managers and administrators who track the program and are involved in decisions regarding resource allocation and program evaluation.
Tool for Interactive Plotting, Sonification, and 3D Orbit Display (TIPSOD) is a computer program for generating interactive, animated, four-dimensional (space and time) displays of spacecraft orbits. TIPSOD utilizes the programming interface of the Satellite Situation Center Web (SSCWeb) services to communicate with the SSC logic and database by use of the open protocols of the Internet. TIPSOD is implemented in Java 3D and effects an extension of the preexisting SSCWeb two-dimensional static graphical displays of orbits. Orbits can be displayed in any or all of the following seven reference systems: true-of-date (an inertial system), J2000 (another inertial system), geographic, geomagnetic, geocentric solar ecliptic, geocentric solar magnetospheric, and solar magnetic. In addition to orbits, TIPSOD computes and displays Sibeck's magnetopause and Fairfield's bow-shock surfaces. TIPSOD can be used by the scientific community as a means of projection or interpretation. It also has potential as an educational tool.
This report documents the code AMR1D, which is currently posted on the World Wide Web (http://sdcd.gsfc.nasa.gov/ESS/exchange/contrib/de-fainchtein/adaptive _mesh_refinement.html). AMR1D is a one-dimensional finite element fluid-dynamics solver, capable of adaptive mesh refinement (AMR). It was written as an instructional tool for AMR on unstructured mesh codes. It is meant to illustrate the minimum requirements for AMR on more than one dimension. For that purpose, it uses the same type of data structure that would be necessary on a two-dimensional AMR code (loosely following the algorithm described by Lohner).
NASA’s Prediction of Worldwide Energy Resource (POWER) project facilitates the use of NASA Earth Science data holdings within the energy, agricultural, and building heating/cooling design industries. POWER packages solar and meteorological data at various temporal levels from several NASA projects in a user friendly GIS-enabled web services system (https://power.larc.nasa.gov). Data users can access these data either through an intuitive data viewer, image services fully integrable with GIS analysis, connections in the cloud through an Amazon Web Services S3 Bucket, or fully customizable access through an API. Data provided by POWER has been used to remotely monitor solar array fields and integrated in a sizing tool for off-grid solar and storage systems. POWER data has also been coupled with key building decision tools to support design and retrofitting of building energy systems for energy efficiency and reduction of greenhouse gases. POWER is now developing capabilities to provide time series of the projected future evolution of surface quantities important to future energy production and use, such as heating/cooling degree days, temperature, wind speed, and downwelling solar flux. We present here a range of possible future changes in these quantities at locations throughout the continental United States. We show how both average and extreme values of the quantities will evolve from present-day to future climate conditions. We plan to provide these projections for users in the energy and sustainable energy communities.
Running realistic simulations and developing algorithms for decision support tools usually require weather data access. This document describes the weather data service capability implemented in the Air Traffic Management (ATM) TestBed. The capability provides ways for querying weather data from the weather products provided by the National Aeronautics and Space Administration’s (NASA) Sherlock ATM Data Warehouse. Depending on use cases, weather data can be queried using a Java application programming interface, web data access, and map tile image access. Map tile images are generated using triangular meshes obtained using the Matching Squares contour algorithm. An analysis determines a grid size that will produce both high image quality and fast image rendering. In addition, the visualization of weather data as map tiles on a TestBed visualization tool called Traffic Viewer is presented.
The purpose of this paper is to explore an innovative approach to culture change at NASA that goes beyond reorganizations, management training, and a renewed emphasis on safety. Over the last five years, a technological social revolution has been emerging from the internet. Blogs (aka web logs) are transforming traditional communication and information sharing outlets away from established information sources such as the media. The Blogosphere has grown from zero blogs in 1999 to approximately 4.5 million as of November 2004 and is expected to double in 2005. Blogs have demonstrated incredible effectiveness and efficiency with regards to affecting major military and political events. Consequently, NASA should embrace the new information paradigm presented by blogging. NASA can derive exceptional benefits from the new technology as follows: 1) Personal blogs can overcome the silent safety culture by giving voice to concerns or questions that are not well understood or seemingly inconsequential to the NASA community at-large without the pressure of formally raising a potential false alarm. Since blogs can be open to Agency-wide participation, an incredible amount of resources from an extensive pool of experience can focus on a single issue, concern, or problem and quickly vetted, discussed and assessed for feasibility, significance, and criticality. The speed for which this could be obtained cannot be matched through any other process or procedure currently in use. 2) Through official NASA established blogs, lessons learned can be a real-time two way process that is formed and implemented from the ground level. Data mining of official NASA blogs and personal blogs of NASA personnel can identify hot button issues and concerns to senior management. 3) NASA blogs could function as a natural ombudsman for the NASA community. Through the recognition of issues being voiced by the community and taking a proactive stance on those issues, credibility within NASA Management can be restored. For NASA to harness the capabilities of blogs, NASA must develop an Agency-wide policy on blogging to encourage use and provide guidance. This policy should describe basic rules of conduct and content as well as a policy of non-retribution and/or anonymity. The Agency must provide sever space within their firewalls, provide appropriate software tools, and promote blogs in newsletters and official websites. By embracing the use of blogs, a potential pool of 19,000 experts could be available to address each posted safety issue, concern, problem, or question. Blogs could result in real NASA culture change.
A polyglot is a file that is valid in two or more formats. Polyglot files pose a problem for file-upload and generative AI web interfaces that rely on format identification to determine how to securely handle incoming files. In this work we found that existing file-format and embedded-file detection tools, even those developed specifically for polyglot files, fail to reliably detect polyglot files used in the wild. To address this issue, we studied the use of polyglot files by malicious actors in the wild, finding 30 polyglot samples and 15 attack chains that leveraged polyglot files. Using knowledge from our survey of polyglot usage in the wild---the first of its kind---we created a novel data set based on adversary techniques. We then trained a machine learning detection solution, PolyConv, using this data set. PolyConv achieves a precision-recall area-under-curve score of 0.999 with an F1 score of 99.20% for polyglot detection and 99.47% for file-format identification, significantly outperforming all other tools tested. We developed a content disarmament and reconstruction tool, ImSan, that successfully sanitized 100% of the tested image-based polyglots, which were the most common type found via the survey. Our work provides concrete tools and suggestions to enable defenders to better defend themselves against polyglot files, as well as directions for future work to create more robust file specifications and methods of disarmament.
Brick (https://brickschema.org/) is a unified metadata schema to address the problem of building data standardization. Creating Brick models for building datasets means that the contents of the datasets are semantically described using the standard terms defined in the Brick ontology, and it will enable the benefits of data standardization, without having to recollect or reorganize the data. The challenge is that building brick models for building datasets leads to repeated manual trial and error processes, which can be time-consuming. VizBrick is a tool with a graphic/Web-based user interface that can assist users to create Brick models visually and interactively without having to understand the Resource Description Framework (RDF) syntax. VizBrick contains a web server that renders VizBrick web interface pages for browsers. The web server utilizes software components that (1) provide Brick ontology entity mapping to data column suggestions to users so that they can efficiently create their model; (2) provide keyword/Metadata-based search capability for easy find of relevant brick concepts and relations to their data columns
We are developing simulation and analysis tools in order to develop a solid Earth science framework for understanding and studying active tectonic and earthquake processes. The goal of QuakeSim and its extension, the Solid Earth Research Virtual Observatory (SERVO), is to study the physics of earthquakes using state-of-the-art modeling, data manipulation, and pattern recognition technologies. We are developing clearly defined accessible data formats and code protocols as inputs to simulations, which are adapted to high-performance computers. The solid Earth system is extremely complex and nonlinear resulting in computationally intensive problems with millions of unknowns. With these tools it will be possible to construct the more complex models and simulations necessary to develop hazard assessment systems critical for reducing future losses from major earthquakes. We are using Web (Grid) service technology to demonstrate the assimilation of multiple distributed data sources (a typical data grid problem) into a major parallel high-performance computing earthquake forecasting code. Such a linkage of Geoinformatics with Geocomplexity demonstrates the value of the Solid Earth Research Virtual Observatory (SERVO) Grid concept, and advances Grid technology by building the first real-time large-scale data assimilation grid.