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Certification Concepts for AI/ML Systems

This presentation goes over some of the tools developed at NASA Ames in the Robust Software Engineering group for the assurance and certification of autonomous systems. The research themes presented include improving safety and risk assessment as early as possible in the lifecycle, elicitation and formalization of requirements to facilitate traceability throughout the lifecycle, especially when formal methods are used, algorithms, tools and techniques for the V&V of ML-enabled systems, advanced testing, use of runtime monitoring to ease use of untrusted components, and contribution to draft regulatory standards and assistance in producing and presenting certification evidences.

Autonomy↗

Scaling Building Energy Audits through Machine Learning Methods on Novel Drone Image Data

Building energy audits are time-consuming and labor-intensive. This paper describes a new method using machine learning (ML) techniques on novel data sources (drone images) to improve the identification of building characteristics and retrofit opportunities, and thereby reduce the effort for audits. The new ML method includes: (1) Building footprint extraction using line extraction, polygonization, and polygon-merging, (2) Building envelope extraction using PIX4d modeling software to reconstruct a building 3D model, (3) Visualization tool for viewing images from the 3D model, (4) Window-to-wall ratio (WWR) using state-of-art deep neural network semantic segmentation, (5) Envelope thermal anomaly detection using an unsupervised machine learning clustering algorithm, and (6) Rooftop energy equipment detection based on an object detection algorithm. The testing of this method involved a comparison of additional ML-generated information overlaid on current ‘state-of-practice’ audit and remote assessment baselines using evaluation metrics: labor time and associated cost, marginal benefits of using ML-generated information in workflows for audits and remote assessments, integration potential with existing processes and tools, and replicability/scalability of the method. In two test buildings in California that had comprehensive drawings and meter data available, the ML method effectively generated a building footprint, envelope, rooftop equipment, WWR, and locations of envelope thermal anomalies. Projected target segments of the ML method are sites with minimal drawings and energy data, and underserved sectors such as multistoried housing, disadvantaged communities, and schools for which the ML method can enable identification of building asset characteristics and prioritization of envelope retrofits and decentralized energy equipment retrofits.

Singh, Reshma↗

Composite Design and Manufacturing Development for Human Spacecrafts

The Structural Engineering Division at the NASA Johnson Space Center (JSC) has begun work on lightweight, multi‐functional pressurized composite structures. The first candidate vehicle for technology development is the Multi‐Mission Space Exploration Vehicle (MMSEV) cabin, known as the Gen 2B cabin, which has been built at JSC by the Robotics Division. Of the habitable MMSEV vehicle prototypes designed to date, this is the first one specifically analyzed and tested to hold internal pressure and the only one made out of composite materials. This design uses a laminate base with zoned reinforcement and external stringers, intended to demonstrate certain capabilities, and to prepare for the next cabin design, which will be a composite sandwich panel construction with multi‐functional capabilities. As part of this advanced development process, a number of new technologies were used to assist in the design and manufacturing process. One of the methods, new to JSC, was to build the Gen 2B cabin with Out of Autoclave technology to permit the creation of larger parts with fewer joints. An 8‐ply pre‐preg layup was constructed to form the cabin body. Prior to lay‐up, a design optimization software called FiberSIM was used to create each ply pattern. This software is integrated with Pro/Engineer to allow for customized draping of each fabric ply over the complex tool surface. Slits and darts are made in the software model to create an optimal design that maintains proper fiber placement and orientation. The flat pattern of each ply is then exported and sent to an automated cutting table where the patterns are cut out of graphite material. Additionally, to assist in lay‐up, a laser projection system (LPT) is used to project outlines of each ply directly onto the tool face for accurate fiber placement and ply build‐up. Finally, as part of the OoA process, a large oven was procured to post‐cure each part. After manufacturing complete, the cabin underwent modal and pressure testing (currently in progress at date of writing) and will go on to be outfitted and used for further ops usage.

Litteken, Douglas↗

Mixed Integer Nonlinear Programming Approaches to Enhance Resiliency and Response Strategies in Critical Infrastructure

Motivation. Critical infrastructures are large, complex engineered systems that must be operated robustly under abnormal conditions resulting from natural hazards or intentional acts. For example, electric power systems must be robust to line faults, water utilities must rapidly mitigate contamination incidents, and computing networks must adapt to adversarial intrusions to protect critical information. Problem. It is difficult for decision-makers within resiliency analysis in critical infrastructure to optimize designs and develop effective response strategies that can account for uncertainties. Facing incomplete information and the sheer scope that a natural hazard or attack vector may incorporate, response can be ineffective without reliable, scalable decision support tools. These problems are intrinsically nonlinear and involve discrete decisions, and unfortunately, existing off-the-shelf mathematical programming methods cannot support optimization-based decision-making of these nonlinear at scale. Method/Approach and Results. This project emphasized development of fundamental optimization strategies that supported real- time mitigation and response for critical infrastructures. In particular, the project developed multi- tree approaches based on piecewise outer-approximations for solution of mixed-integer nonlinear programming (MINLP) problems. These techniques alternate between an MILP or MISOCP relaxation to obtain a lower bound and candidate discrete solutions and an NLP subproblem to obtain upper bounds. Using tailored relaxations based on problem structure, these methods were used to solve several key applications in resilience and response of critical infrastructure. This work resulted in two open-source, copyrighted software packages: CORAMIN (https://github.com/Coramin/Coramin) -- an object-oriented mathematical programming framework that supports tailored multi-tree algorithms for solution of large- scale mixed-integer nonlinear programming; and EGRET (Electrical Grid Research and Engineering Toolkit) (https://github.com/grid- parity-exchange/Egret) -- a declarative mathematical programming framework built upon CORAMIN and Pyomo for formulation and solution of resilience and operations problems in power grid systems. Furthermore, these tools resulted in several important published results, including the following: The first known global optimization approach that could solve the unit-commitment problem with nonlinear power flow constraints on medium-sized test problems; Improved parallel optimization-based bounds tightening and strengthening of relaxations of AC power flow constraints; and, Optimization-based approaches for improved grid resilience and use of demand response to improve grid resilience with reduction in capital requirements. Result Implications. This project developed first-of-a-kind algorithms for decision-making in critical infrastructure resilience operations and planning, as well as a next-generation toolkit for MINLP researchers. These approaches leveraged high-performance computing architectures to solve some of the largest, most challenging nonlinear discrete optimization problems to global optimality, and these successes were captured in open-source software to enable optimization-based decision-making, and efficient solution of MINLP formulations for electric power transmission grids.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Leveraging public AI tools to explore systems biology resources in mathematical modeling

Predictive mathematical modeling is an essential part of systems biology and is interconnected with information management. Systems biology information is often stored in specialized formats to facilitate data storage and analysis. These formats are not designed for easy human readability and thus require specialized software to visualize and interpret results. Therefore, comprehending modeling and underlying networks and pathways is contingent on mastering systems biology tools, which is particularly challenging for users with no or little background in data science or system biology. To address this challenge, we investigated the usage of public Artificial Intelligence (AI) tools in exploring systems biology resources in mathematical modeling. We tested public AI’s understanding of mathematics in models, related systems biology data, and the complexity of model structures. Our approach can enhance the accessibility of systems biology for non-system biologists and help them understand systems biology without a deep learning curve.

59 BASIC BIOLOGICAL SCIENCES↗

Recent evolutions in the LTDP CDF project

In the latest years, CNAF (the national center of the Italian Institute for Nuclear Physics INFN dedicated to Research and Development on Information and Communication Technologies) has been working on the Long Term Data Preservation (LTDP) project for the CDF experiment, active at Fermilab from 1990 to 2011. The main aims of the project are to protect the most relevant part of the CDF RUN-2 data collected between 2001 and 2011 and already stored on tape at CNAF (4 PB), as well as to ensure the availability and the access to the analysis facility to those data over time. Lately, the CDF database, hosting information about CDF datasets such as their structure, file locations and metadata, has been imported from Fermilab to CNAF. Also, the Sequential Access via Metadata (SAM) station data handling tool for CDF data management, that allows to manage data transfers and to retrieve information from the CDF database, has been properly installed and configured at CNAF. This was a fundamental step in the perspective of a complete decommissioning of CDF services on Fermilab side. An access system has been designed and tested to submit CDF analysis jobs, using CDF software distributed via CERN Virtual Machine File System (CVMFS) and requesting delivery of CDF files stored on CNAF tapes, as well as data present only on Fermilab storage archive. Moreover, the availability and the correctness of all CDF data stored on CNAF tapes has been verified. This paper describes all these recent evolutions in detail, presenting the future plans for the LTDP project at CNAF.

Fornari, Federico↗

A continuous symmetry breaking measure for finite clusters using Jensen-Shannon divergence

A quantitative measure of symmetry breaking is introduced that allows the quantification of which symmetries are most strongly broken due to the introduction of some kind of defect in a perfect structure. The method uses a statistical approach based on the Jensen-Shannon divergence. The measure is calculated by comparing the transformed atomic density function with its original. Software code is presented that carries the calculations out numerically using Monte Carlo methods. The behavior of this symmetry breaking measure is tested for various cases including finite size crystallites (where the surfaces break the crystallographic symmetry), atomic displacements from high symmetry positions, and collective motions of atoms due to rotations of rigid octahedra. Finally, the approach provides a powerful tool for assessing local symmetry breaking and offers new insights that can help researchers understand how different structural distortions affect different symmetry operations.

atomic & molecular structure↗

Continuous Security and Configuration Monitoring of HPC Clusters

Continuous security and configuration monitoring of information systems has been a time consuming and laborious task for system administrators at the High Performance Computing (HPC) center. Prior to this project, system administrators had to manually check the settings of thousands of nodes, which required a significant number of hours rendering the old process ineffective and inefficient. This paper explains the application of Splunk Enterprise, a software agent, and a reporting tool in the development of a user application interface to track and report on critical system updates and security compliance status of HPC Clusters. In conjunction with other configuration management systems, the reporting tool is to provide continuous situational awareness to system administrators of the compliance state of information systems. Our approach consisted of the development, testing, and deployment of an agent to collect any arbitrary information across a massively distributed computing center, and organize that information into a human-readable format. Using Splunk Enterprise, this raw data was then gathered into a central repository and indexed for search, analysis, and correlation. Following acquisition and accumulation, the reporting tool generated and presented actionable information by filtering the data according to command line parameters passed at run time. Preliminary data showed results for over six thousand nodes. Further research and expansion of this tool could lead to the development of a series of agents to gather and report critical system parameters. However, in order to make use of the flexibility and resourcefulness of the reporting tool the agent must conform to specifications set forth in this paper. This project has simplified the way system administrators gather, analyze, and report on the configuration and security state of HPC clusters, maintaining ongoing situational awareness. Rather than querying each cluster independently, compliance checking can be managed from one central location.

97 MATHEMATICS AND COMPUTING↗

Image understanding and the man-machine interface II; Proceedings of the Meeting, Los Angeles, CA, Jan. 17, 18, 1989

Image understanding concepts and models, image understanding systems and applications, advanced digital processors and software tools, and advanced man-machine interfaces are among the topics discussed. Particular papers are presented on such topics as neural networks for computer vision, object-based segmentation and color recognition in multispectral images, the application of image algebra to image measurement and feature extraction, and the integration of modeling and graphics to create an infrared signal processing test bed.

Barrett, Eamon B.↗

Small scale sequence automation pays big dividends

Galileo sequence design and integration are supported by a suite of formal software tools. Sequence review, however, is largely a manual process with reviewers scanning hundreds of pages of cryptic computer printouts to verify sequence correctness. Beginning in 1990, a series of small, PC based sequence review tools evolved. Each tool performs a specific task but all have a common 'look and feel'. The narrow focus of each tool means simpler operation, and easier creation, testing, and maintenance. Benefits from these tools are (1) decreased review time by factors of 5 to 20 or more with a concomitant reduction in staffing, (2) increased review accuracy, and (3) excellent returns on time invested.

Nelson, Bill↗

Application of CFD in aeronautics at NASA Ames Research Center

The role of Computational Fluid Dynamics (CFD) at Ames Research Center has expanded to address a broad range of aeronautical problems, including wind tunnel support, flight test support, design, and analysis. Balancing the requirements of each new problem against the available resources - software, hardware, time, and expertise - is critical to the effective use of CFD. Several case studies of recent applications highlight the depth of CFD capability at Ames, the tradeoffs involved in various approaches, and lessons learned in the use of CFD as an engineering tool.

Maksymiuk, Catherine M.↗

Evaluating the Usability of Pinchigator, a system for Navigating Virtual Worlds using Pinch Gloves

Appropriate design of two dimensional user interfaces (2D U/I) utilizing the well known WIMP (Window, Icon, Menu, Pointing device) environment for computer software is well studied and guidance can be found in several standards. Three-dimensional U/I design is not nearly so mature as 2D U/I, and standards bodies have not reached consensus on what makes a usable interface. This is especially true when the tools for interacting with the virtual environment may include stereo viewing, real time trackers and pinch gloves instead of just a mouse & keyboard. Over the last several years the authors have created a 3D U/I system dubbed Pinchigator for navigating virtual worlds based on the dVise dV/Mockup visualization software, Fakespace Pinch Gloves and Pohlemus trackers. The current work is to test the usability of the system on several virtual worlds, suggest improvements to increase Pinchigator s usability, and then to generalize about what was learned and how those lessons might be applied to improve other 3D U/I systems.

Hamilton, George S.↗

Verifying Correct Functionality of Avionics Subsystems

This project focuses on the testing of the telecommunications interface subsystem of the Multi-Mission System Architecture Platform to ensure proper functionality. The Multi-Mission System Architecture Platform is a set of basic tools designed to be used in future spacecraft. The responsibilities of the telecommunications interface include communication between the spacecraft and ground teams as well as acting as the bus controller for the system. The tests completed include bit wise read\write tests to each register, testing of status bits, and verifying various bus controller activities. Testing is accomplished through the use of software-based simulations run on an electronic design of the system. The tests are written in Verilog Hardware Definition Language and they simulate specific states and conditions in telecommunication interfaces. Upon successful completion, the output is examined to verify that the system responded appropriately.

Meuer, Ben t.↗

Shoulder Postures in EVA Training in Reduced Gravity Analogues

Shoulder Postures in EVA Training in Reduced Gravity Analogues K. Guhl1, L. Vu2, H. Kim3, S. Rajulu4 1KBR Inc., Houston, TX, 2Aegis Aerospace Inc., Houston, TX, 3Leidos Innovations, Houston, TX, 4NASA Johnson Space Center, Houston, TX. During extravehicular activities (EVAs) and EVA training in both the Neutral Buoyancy Laboratory (NBL) and at the Active Response Gravity Offload System (ARGOS), crewmembers perform a variety of hand-intensive tasks with frequent arm/shoulder repositioning while wearing a pressurized spacesuit. As a result, crewmembers may experience ergonomic stressors such as awkward shoulder postures. The ergonomic shoulder risk is also compounded by limited or restricted shoulder mobility of the spacesuit, extreme work positions such as overhead tasks, and tasks with heavy tools and repetitive motions. Prolonged or frequent shoulder elevation and overhead work, in particular, can lead to excessive stresses and musculoskeletal injuries of the shoulder joints. Future EVA missions, specifically lunar surface EVAs, will also be longer in duration and thus increase the exposure to awkward shoulder postures. In this study, we aimed to assess the ergonomic risk of awkward shoulder postures in simulated lunar surface EVAs by quantifying when and how long the arms are raised above the chest level. We assessed video recordings of pilot lunar EVA simulations (3 lunar trials each in the NBL and at ARGOS and 2 microgravity EVA trials in the NBL). These runs consisted of both training and engineering test objectives. Actual demands for shoulder use varied for different EVA types and analogues, but many EVA runs have common tasks and require similar motion components. A video observation and event logging software was used to document the duration and occurrence of the subject’s arms being raised throughout the video recordings of each EVA run. An arm raised instance was classified as the arm being at 90 degrees or above with relation to gravity for lunar EVA training events and with relation to the body for microgravity EVA training events. Such events included EVA hardware maintenance or heavy geology sampling tool operations. Events where the arm load was partially supported by external objects, like climbing a ladder or leaning against a surface were separately identified and excluded. Statistical analysis was performed to summarize the timing, frequency, and durations of the arm raise events and compared across the different EVA tasks and analogue types. Preliminary observations indicated that the total duration and number of arm raised instances were surprisingly smaller for lunar surface EVA training as compared to microgravity EVA training. The observed difference may be attributed to differing task demands and unique environmental characteristics found in lunar EVAs in comparison to microgravity EVAs. A detailed statistical analysis will be performed between lunar surface EVA training events and microgravity EVA training events in the final submission. Overall, this analysis is expected to provide insight into how ergonomic recommendations can be refined for lunar EVA training with pressurized suits. It may also inform task design and influence suit padding design to better protect crewmembers during future lunar training.

Kaitlyn Lea Guhl↗

A User Guide for Smoothing Air Traffic Radar Data

Matlab software was written to provide smoothing of radar tracking data to simulate ADS-B (Automatic Dependent Surveillance-Broadcast) data in order to test a tactical conflict probe. The probe, called TSAFE (Tactical Separation-Assured Flight Environment), is designed to handle air-traffic conflicts left undetected or unresolved when loss-of-separation is predicted to occur within approximately two minutes. The data stream that is down-linked from an aircraft equipped with an ADS-B system would include accurate GPS-derived position and velocity information at sample rates of 1 Hz. Nation-wide ADS-B equipage (mandated by 2020) should improve surveillance accuracy and TSAFE performance. Currently, position data are provided by Center radar (nominal 12-sec samples) and Terminal radar (nominal 4.8-sec samples). Aircraft ground speed and ground track are estimated using real-time filtering, causing lags up to 60 sec, compromising performance of a tactical resolution tool. Offline smoothing of radar data reduces wild-point errors, provides a sample rate as high as 1 Hz, and yields more accurate and lag-free estimates of ground speed, ground track, and climb rate. Until full ADS-B implementation is available, smoothed radar data should provide reasonable track estimates for testing TSAFE in an ADS-B-like environment. An example illustrates the smoothing of radar data and shows a comparison of smoothed-radar and ADS-B tracking. This document is intended to serve as a guide for using the smoothing software.

Center/Tracon Radar↗

Annex C. Data Libraries for IAEA Nuclear Security Assessment Methodologies (NUSAM)

Data Libraries are a collection of experimental data for PP elements based on specific defeat mechanisms. The data can de related to probability of detection, assessment, or barrier delay times. The data libraries can be a manually tabulated list or an electronic menu values enbedded in a stand-alone database or in an assessment software program such as SAVI or EASI. Data library values are usually based on years of historical testing data for many forms of common and sometimes unique PPS systems. Most useful testing libraries include data from the most basic alarm sensors, doors, walls, and barriers to very sophisticated PP elements. Each PP element is tested using increasing levels of defeat techniques from hand tools, power tools, breaching tools, explosives, and vehicles, as applicable.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Research pressure instrumentation for NASA Space Shuttle main engine, modification no. 5

The objective of the research project described is to define and demonstrate methods to advance the state of the art of pressure sensors for the space shuttle main engine (SSME). Silicon piezoresistive technology was utilized in completing tasks: generation and testing of three transducer design concepts for solid state applications; silicon resistor characterization at cryogenic temperatures; experimental chip mounting characterization; frequency response optimization and prototype design and fabrication. Excellent silicon sensor performance was demonstrated at liquid nitrogen temperature. A silicon resistor ion implant dose was customized for SSME temperature requirements. A basic acoustic modeling software program was developed as a design tool to evaluate frequency response characteristics.

Anderson, P. J.↗

Spacecraft On-Board Information Extraction Computer (SOBIEC)

The Jet Propulsion Laboratory is the Technical Monitor on an SBIR Program issued for Irvine Sensors Corporation to develop a highly compact, dual use massively parallel processing node known as SOBIEC. SOBIEC couples 3D memory stacking technology provided by nCUBE. The node contains sufficient network Input/Output to implement up to an order-13 binary hypercube. The benefit of this network, is that it scales linearly as more processors are added, and it is a superset of other commonly used interconnect topologies such as: meshes, rings, toroids, and trees. In this manner, a distributed processing network can be easily devised and supported. The SOBIEC node has sufficient memory for most multi-computer applications, and also supports external memory expansion and DMA interfaces. The SOBIEC node is supported by a mature set of software development tools from nCUBE. The nCUBE operating system (OS) provides configuration and operational support for up to 8000 SOBIEC processors in an order-13 binary hypercube or any subset or partition(s) thereof. The OS is UNIX (USL SVR4) compatible, with C, C++, and FORTRAN compilers readily available. A stand-alone development system is also available to support SOBIEC test and integration.

Eisenman, David↗