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At least 685 records · Page 38

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NASA NTRS1985

Land use mapping using edge density texture measures on Thematic Mapper simulator data

Texture analysis was performed as part of an investigation of the information content of Thematic Mapper (TM) imagery. High altitude aircraft scanner imagery from the Airborne Thematic Mapper (ATM) instrument was acquired over central California and used to simulate TM data. Edge density texture images were constructed by computation of proportions of edge pixels in a 31 x 31 moving window on a near infrared ATM band. A training technique was employed to select computational parameters to maximize the difference between edge density measurements in urban and in rural areas. The results of classification of the texture images showed that urban and rural areas could be distinguished with texture alone, indicating that inclusion of texture in automated classification procedures could significantly improve their accuracy.

Hlavka, C. A.↗

NASA NTRS1991

Cryogenic radiometers and intensity-stabilized lasers for Eos radiometric calibrations

Liquid helium-cooled electrical substitution radiometers (ESRs) provide irradiance standards with demonstrated absolute accuracy at the 0.01 percent level, spectrally flat response between the UV and IR, and sensitivity down to 0.1 nW/sq cm. We describe an automated system developed for NASA - Goddard Space Flight Center, consisting of a cryogenic ESR illuminated by servocontrolled laser beams. This system is designed to provide calibration of single-element and array detectors over the spectral range between 257nm in the UV to 10.6 microns in the IR. We also describe a cryogenic ESR optimized for black body calibrations that has been installed at NIST, and another that is under construction for calibrations of the CERES scanners planned for Eos.

Foukal, P.↗

NASA NTRS2002

REACH: Real-Time Data Awareness in Multi-Spacecraft Missions

Missions have been proposed that will use multiple spacecraft to perform scientific or commercial tasks. Indeed, in the commercial world, some spacecraft constellations already exist. Aside from the technical challenges of constructing and flying these missions, there is also the financial challenge presented by the tradition model of the flight operations team (FOT) when it is applied to a constellation mission. Proposed constellation missions range in size from three spacecraft to more than 50. If the current ratio of three-to-five FOT personnel per spacecraft is maintained, the size of the FOT becomes cost prohibitive. The Advanced Architectures and Automation Branch at the Goddard Space Flight Center (GSFC Code 588) saw the potential to reduce the cost of these missions by creating new user interfaces to the ground system health-and-safety data. The goal is to enable a smaller FOT to remain aware and responsive to the increased amount of ground system information in a multi-spacecraft environment. Rather than abandon the tried and true, these interfaces were developed to run alongside existing ground system software to provide additional support to the FOT. These new user interfaces have been combined in a tool called REACH. REACH-the Real-time Evaluation and Analysis of Consolidated Health-is a software product that uses advanced visualization techniques to make spacecraft anomalies easy to spot, no matter how many spacecraft are in the constellation. REACH reads a real-time stream of data from the ground system and displays it to the FOT such that anomalies are easy to pick out and investigate. Data visualization has been used in ground system operations for many years. To provide a unique visualization tool, we developed a unique source of data to visualize: the REACH Health Model Engine. The Health Model Engine is rule-based software that receives real-time telemetry information and outputs "health" information related to the subsystems and spacecraft that the telemetry belong to. The Health Engine can run out-of-the-box or can be tailored with a scripting language. Out of the box, it uses limit violations to determine the health of subsystems and spacecraft; when tailored, it determines health using equations combining the values and limits of any telemetry in the spacecraft. The REACH visualizations then "roll up" the information from the Health Engine into high level, summary displays. These summary visualizations can be "zoomed" into for increasing levels of detail. Currently REACH is installed in the Small Explorer (SMEX) lab at GSFC, and is monitoring three of their five spacecraft. We are scheduled to install REACH in the Mid-sized Explorer (MIDEX) lab, which will allow us to monitor up to six more spacecraft. The process of installing and using our "research" software in an operational environment has provided many insights into which parts of REACH are a step forward and which of our ideas are missteps. Our paper explores both the new concepts in spacecraft health-and-safety visualization, the difficulties of such systems in the operational environment, and the cost and safety issues of multi-spacecraft missions.

Maks, Lori↗

NASA NTRS2010

Decision Engines for Software Analysis Using Satisfiability Modulo Theories Solvers

The area of software analysis, testing and verification is now undergoing a revolution thanks to the use of automated and scalable support for logical methods. A well-recognized premise is that at the core of software analysis engines is invariably a component using logical formulas for describing states and transformations between system states. The process of using this information for discovering and checking program properties (including such important properties as safety and security) amounts to automatic theorem proving. In particular, theorem provers that directly support common software constructs offer a compelling basis. Such provers are commonly called satisfiability modulo theories (SMT) solvers. Z3 is a state-of-the-art SMT solver. It is developed at Microsoft Research. It can be used to check the satisfiability of logical formulas over one or more theories such as arithmetic, bit-vectors, lists, records and arrays. The talk describes some of the technology behind modern SMT solvers, including the solver Z3. Z3 is currently mainly targeted at solving problems that arise in software analysis and verification. It has been applied to various contexts, such as systems for dynamic symbolic simulation (Pex, SAGE, Vigilante), for program verification and extended static checking (Spec#/Boggie, VCC, HAVOC), for software model checking (Yogi, SLAM), model-based design (FORMULA), security protocol code (F7), program run-time analysis and invariant generation (VS3). We will describe how it integrates support for a variety of theories that arise naturally in the context of the applications. There are several new promising avenues and the talk will touch on some of these and the challenges related to SMT solvers. Proceedings

Bjorner, Nikolaj↗

NASA NTRS2017

Reconfigurable Model Execution in the OpenMDAO Framework

NASA's OpenMDAO framework facilitates constructing complex models and computing their derivatives for multidisciplinary design optimization. Decomposing a model into components that follow a prescribed interface enables OpenMDAO to assemble multidisciplinary derivatives from the component derivatives using what amounts to the adjoint method, direct method, chain rule, global sensitivity equations, or any combination thereof, using the MAUD architecture. OpenMDAO also handles the distribution of processors among the disciplines by hierarchically grouping the components, and it automates the data transfer between components that are on different processors. These features have made OpenMDAO useful for applications in aircraft design, satellite design, wind turbine design, and aircraft engine design, among others. This paper presents new algorithms for OpenMDAO that enable reconfigurable model execution. This concept refers to dynamically changing, during execution, one or more of: the variable sizes, solution algorithm, parallel load balancing, or set of variables-i.e., adding and removing components, perhaps to switch to a higher-fidelity sub-model. Any component can reconfigure at any point, even when running in parallel with other components, and the reconfiguration algorithm presented here performs the synchronized updates to all other components that are affected. A reconfigurable software framework for multidisciplinary design optimization enables new adaptive solvers, adaptive parallelization, and new applications such as gradient-based optimization with overset flow solvers and adaptive mesh refinement. Benchmarking results demonstrate the time savings for reconfiguration compared to setting up the model again from scratch, which can be significant in large-scale problems. Additionally, the new reconfigurability feature is applied to a mission profile optimization problem for commercial aircraft where both the parametrization of the mission profile and the time discretization are adaptively refined, resulting in computational savings of roughly 10% and the elimination of oscillations in the optimized altitude profile.

Hwang, John T.↗

DOE OSTI2026

Enhancing Operational Safety via Agentic Dialogue Hazard Identification Analysis

Operational safety in high-stakes domains such as industrial process control, autonomous, and safety-critical systems demand reliable hazard identification. While large language models (LLMs) have shown promise in automating safety analysis tasks, single-turn, monolithic inference is brittle: it lacks the self-correction, deliberation, and contextual refinement that safety engineers apply iteratively. In this paper, we introduce HAZDIAL, a framework that investigates whether structured agentic dialogue (multi-agent, multi-turn interactions) improves the quality of NLP-based hazard identification over single-pass baselines. We systematically compare two dialogue modalities: adversarial debate and constructive discussion, and propose an genetic algorithm-based agentic interaction optimization. We evaluate all configurations against a curated golden dataset using standard classification metrics (accuracy, precision, recall, F1) and a novel dialogue metrics. This work advances the intersection of dialogue systems, multi-agent reasoning, and AI safety, providing empirical evidence for dialogue-driven hazard analysis.

Das, Sanjay [ORNL] (ORCID:0009000542591915)↗

DOE OSTI2025

Deep Point Cloud Building Envelope Segmentation (DeeP-CuBES) using Deep Learning

Building Information Modeling (BIM) plays an important role in building design and construction, particularly for achieving energy-efficient retrofits. Building envelope retrofits using panelized prefabricated system, such as those popularized by the Energiesprong program, need accurate as-built dimensions of facade features (windows, doors, etc.) to achieve the desired thermal and air tightness. Traditionally, building surveying is done manually, resulting in a time-consuming and labor-intensive process. Recently, 3D point clouds from terrestrial LiDAR have been used to automate the generation of as-built dimensions of existing buildings. However, automated BIM using LiDAR relies on solving the point cloud semantic segmentation (PCSS) problem. In this work, we propose a robust pipeline for solving the PCSS problem using deep neural networks, focusing on overcoming challenges posed by imbalanced datasets and complex architectural features. We introduce the first high-density, labeled, and validated building envelope point cloud dataset derived from multiple building scans, specifically curated to tackle challenges in facade-level segmentation. Results from the trained neural networks show that advanced attention-based architectures and incorporating radiometry (light intensity and RGB) features significantly boost segmentation accuracy for windows and doors.

Selvakumar, Balaji [ORNL]↗

NASA NTRS2023

Anisotropic Mach Cone Aligned Mesh Adaptation for Low Boom Simulations

An automated off-body Mach cone aligned structured curvilinear grid generation procedure is presented for near-field computational fluid dynamics simulations. This procedure combines output-based indicators and mesh redistribution to perform anisotropic mesh adaptation while maintaining Mach cone alignment. Automation is achieved through a novel direction-based adaptation indicator formulation. The adaptation procedure is demonstrated on the JAXA Wing Body geometry and X-59 C608 demonstrator model from the Second and Third AIAA Sonic Boom Prediction Workshops, respectively. It is demonstrated that anisotropic mesh adaptation may result in a greater than fifty percent reduction in resource usage required to achieve the same level of accuracy as uniform and user constructed Mach cone aligned grids for near-field pressure signatures, ground-level overpressure signatures, and loudness metrics.

CST↗

NASA NTRS2023

Anisotropic Mach Cone Aligned Mesh Adaptation for Low Boom Simulations

CST↗

DOE OSTI2023

Optimizing Cell-based Antimicrobials through Pooled Genomic Libraries

DNA synthesis and assembly technologies ushered in through synthetic biology have great promise for biomanufacturing, bioremediation, and the development of living therapeutics. Unfortunately, predicting sequence to function relationships, including for biosynthetic pathways expressed in a new host organism, is difficult and often requires many iterative cycles of design, construction, and testing. We are working to develop data-driven approaches to identify the genetic determinants of growth defects and productivity for the expression of a cell-based antimicrobial. We assayed the growth, pigment production, and antimicrobial activity of a collection of over 10,000 genetic mutants of the violacein biosynthetic pathway and sequenced the genetic variation of these mutants. Through this project, we have developed an innovative codebase to automate the determination of pigmentation and antimicrobial clearing diameter for tens of thousands of genetic mutants cultivated on agar dishes. Further, we have written DNA sequence analysis code to demultiplex & provide consensus sequences from high-throughput PacBio long-read circular consensus sequencing (CCS) datasets. From this foundation, we plan to map DNA sequence to function to predict an optimal genetic design to maximize antimicrobial activity while minimizing deleterious growth effects. The workflows and algorithms developed through this project can be broadly applied to other engineered functions in microbes, uncovering sequence to function relationships for complex phenotypes where function impacts fitness.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1984

SAGA: A project to automate the management of software production systems

The project to automate the management of software production systems is described. The SAGA system is a software environment that is designed to support most of the software development activities that occur in a software lifecycle. The system can be configured to support specific software development applications using given programming languages, tools, and methodologies. Meta-tools are provided to ease configuration. Several major components of the SAGA system are completed to prototype form. The construction methods are described.

Campbell, R. H.↗

NASA NTRS2015

Attitude Design for the LADEE Mission

The Lunar Atmosphere and Dust Environment Explorer (LADEE) satellite successfully completed its 148-day science investigation in a low-altitude, near-equatorial lunar orbit on April 18, 2014. The LADEE spacecraft was built, managed and operated by NASA's Ames Research Center (ARC). The Mission Operations Center (MOC) was located at Ames and was responsible for activity planning, command sequencing, trajectory and attitude design, orbit determination, and spacecraft operations. The Science Operations Center (SOC) was located at Goddard Space Flight Center and was responsible for science planning, data archiving and distribution. This paper details attitude design and operations support for the LADEE mission. LADEE's attitude design was shaped by a wide range of instrument pointing requirements that necessitated regular excursions from the baseline one revolution per orbit "Ram" attitude. Such attitude excursions were constrained by a number of flight rules levied to protect instruments from the Sun, avoid geometries that would result in simultaneous occlusion of LADEE's two star tracker heads, and maintain the spacecraft within its thermal and power operating limits. To satisfy LADEE's many attitude requirements and constraints, a set of rules and conventions was adopted to manage the complexity of this design challenge and facilitate the automation of ground software that generated pointing commands spanning multiple days of operations at a time. The resulting LADEE Flight Dynamics System (FDS) that was developed used Visual Basic scripts that generated instructions to AGI's Satellite Tool Kit (STK) in order to derive quaternion commands at regular intervals that satisfied LADEE's pointing requirements. These scripts relied heavily on the powerful "align and constrain" capability of STK's attitude module to construct LADEE's attitude profiles and the slews to get there. A description of the scripts and the attitude modeling they embodied is provided. One particular challenge analysts faced was in the design of LADEE maneuver attitudes. A flight rule requiring pre-maneuver verification of in-flight maneuver conditions by ground operators prior to burn execution resulted in the need to accommodate long periods in the maneuver attitude. This in turn complicated efforts to satisfy star tracker interference and communication constraints in lunar orbit. In response to this challenge, a graphical method was developed and used to survey candidate rotation angles about the thrust vector. This survey method is described and an example of its use on a particular LADEE maneuver is discussed. Finally, the software and methodology used to satisfy LADEE's attitude requirements are also discussed in the context of LADEE's overall activity planning effort. In particular, the way in which strategic schedules of instrument and engineering activities were translated into actual attitude profiles at the tactical level, then converted into precise quaternion commands to achieve those pointing goals is explained. In order to reduce the risk of time-consuming re-planning efforts, this process included the generation of long-term projections of constraint violation predictions for individual attitude profiles that could be used to establish keep-out time-frames for particular attitude profiles. The challenges experienced and overall efficacy of both the overall LADEE ground system and the attitude components of the Flight Dynamics System in meeting LADEE's varied pointing requirements are discussed.

LADEE↗

NASA NTRS1995

Shielded, Automated Umbilical Mechanism

Umbilical mechanism automatically connects and disconnects various fluid couplings and/or electrical contacts while shielding mating parts from debris. Reacts mating and demating loads internally, without additional supporting structures. All functions - extension of plug, mating, and movement of debris shields - actuated by single motor. If mechanism jams or fails at any point in sequence, override feature in drive train allows manual operation. Designed for service in outer space, where its shields protect against micrometeoroids, debris, ultraviolet radiation, and atomic oxygen. Used on Earth to connect or disconnect fluid or electrical utilities in harsh environments like those of nuclear powerplants or undersea construction sites, or in presence of radioactive, chemical, or biological hazards, for example.

Barron, Daniel R.↗

NASA NTRS2003

Traceability Through Automatic Program Generation

Program synthesis is a technique for automatically deriving programs from specifications of their behavior. One of the arguments made in favour of program synthesis is that it allows one to trace from the specification to the program. One way in which traceability information can be derived is to augment the program synthesis system so that manipulations and calculations it carries out during the synthesis process are annotated with information on what the manipulations and calculations were and why they were made. This information is then accumulated throughout the synthesis process, at the end of which, every artifact produced by the synthesis is annotated with a complete history relating it to every other artifact (including the source specification) which influenced its construction. This approach requires modification of the entire synthesis system - which is labor-intensive and hard to do without influencing its behavior. In this paper, we introduce a novel, lightweight technique for deriving traceability from a program specification to the corresponding synthesized code. Once a program has been successfully synthesized from a specification, small changes are systematically made to the specification and the effects on the synthesized program observed. We have partially automated the technique and applied it in an experiment to one of our program synthesis systems, AUTOFILTER, and to the GNU C compiler, GCC. The results are promising: 1. Manual inspection of the results indicates that most of the connections derived from the source (a specification in the case of AUTOFILTER, C source code in the case of GCC) to its generated target (C source code in the case of AUTOFILTER, assembly language code in the case of GCC) are correct. 2. Around half of the lines in the target can be traced to at least one line of the source. 3. Small changes in the source often induce only small changes in the target.

Richardson, Julian↗

DOE OSTI2024

Explainable AI classification for parton density theory

Quantitatively connecting properties of parton distribution functions (PDFs, or parton densities) to the theoretical assumptions made within the QCD analyses which produce them has been a longstanding problem in HEP phenomenology. To confront this challenge, we introduce an ML-based explainability framework, XAI4PDF, to classify PDFs by parton flavor or underlying theoretical model using ResNet-like neural networks (NNs). By leveraging the differentiable nature of ResNet models, this approach deploys guided backpropagation to dissect relevant features of fitted PDFs, identifying x-dependent signatures of PDFs important to the ML model classifications. By applying our framework, we are able to sort PDFs according to the analysis which produced them while constructing quantitative, human-readable maps locating the x regions most affected by the internal theory assumptions going into each analysis. This technique expands the toolkit available to PDF analysis and adjacent particle phenomenology while pointing to promising generalizations.

Artificial Intelligence↗

NASA NTRS1990

Situational awareness in the commercial aircraft cockpit - A cognitive perspective

A cognitive theory is presented that has relevance for the definition and assessment of situational awareness in the cockpit. The theory asserts that maintenance of situation awareness is a constructive process that demands mental resources in competition with ongoing task performance. Implications of this perspective for assessing and improving situational awareness are discussed. It is concluded that the goal of inserting advanced technology into any system is that it results in an increase in the effectiveness, timeliness, and safety with which the system's activities can be accomplished. The inherent difficulties of the multitask situation are very often compounded by the introduction of automation. To maximize situational awareness, the dynamics and capabilities of such technologies must be designed with thorough respect for the dynamics and capabilities of human information-processing.

Adams, Marilyn J.↗

NASA NTRS1997

Biogeochemistry of DMS in Surface Waters

Dimethylsulfide (DMS) is important in influencing the formation of aerosols in the troposphere over large areas of the world's oceans. Understanding the dynamics of aerosols is important to understanding the earth's radiation balance. In evaluating the factors controlling DMS in the troposphere it is vital to understand the dynamics of DMS in the surface ocean. The biogeochemical processes controlling DMS concentration in seawater are myriad; modeling and theoretical estimation are problematic. At the beginning of this project we believed that we were on the verge of simplifying the ship-track measurement of DMS, and we proposed to deploy such a system to develop a database relating high frequency DMS measurements to biological and physicochemical and optical properties of surface water that can be quantified by remote sensing techniques. We designed a system to measure DMS concomitantly with other basic chemical and biological data in a flow-through system. The project was collaborative between Woods Hole Oceanographic Institution (WHOI) and Bermuda Biological Station for Research (BBSR). The project on which we are reporting was budgeted for only one year with a one year no-cost extension. At WHOI our effort was directed towards designing traps which would be used to concentrate DMS from seawater and allow storage for subsequent analysis. At that time, GC systems were too large for easy long-term deployment on a research vessel like R/V Weatherbird, so we focused on simplifying the shipboard sampling procedure. Initial studies of sample recovery with high levels of DMS suggested that Carboxen 1000, a relatively new carbon molecular sieve, could be used as a stable storage medium. The affinity of Carboxen for DMS is several orders of magnitude higher than gold wool (another adsorbent used for DMS collection) on a weight or volume basis. Furthermore, Carboxen's affinity for DMS is also far less susceptible to humidity than gold wool. Unfortunately, further experiments with low level DMS indicated that recovery of DMS after storage was not quantitative. The material has proven to be completely acceptable for short term storage and has been incorporated into a micro-GC system. Since working on this project, we have collaborated with RVM Scientific in Santa Barbara in the design and construction of small portable micro-GC's that will make feasible at-sea measurement in moving ships, making rapid gas analysis and quantification feasible in a ship-track mode. Throughout this period at both WHOI and BBSR, we continued to analyze field data to understand that patterns of time and space variability in DMS and the processes that govern it. These insights will be crucial to determining the specifications for our automated sampling program. The data from this, the longest continuous sampling program for ocean DMS, provided insights into year to year and short-term variability.

Dacey, J. W. H.↗

NASA NTRS2003

Development of a Dynamically Configurable, Object-Oriented Framework for Distributed, Multi-modal Computational Aerospace Systems Simulation: Second Year Progress Report

Mesh generation has long been recognized as a bottleneck in the CFD process. While much research on automating the volume mesh generation process have been relatively successful,these methods rely on appropriate initial surface triangulation to work properly. Surface discretization has been one of the least automated steps in computational simulation due to its dependence on implicitly defined CAD surfaces and curves. Differences in CAD peometry engines manifest themselves in discrepancies in their interpretation of the same entities. This lack of "good" geometry causes significant problems for mesh generators, requiring users to "repair" the CAD geometry before mesh generation. The problem is exacerbated when CAD geometry is translated to other forms (e.g., IGES )which do not include important topological and construction information in addition to entity geometry. One technique to avoid these problems is to access the CAD geometry directly from the mesh generating software, rather than through files. By accessing the geometry model (not a discretized version) in its native environment, t h s a proach avoids translation to a format which can deplete the model of topological information. Our approach to enable models developed in the Denali software environment to directly access CAD geometry and functions is through an Application Programming Interface (API) known as CAPRI. CAPRI provides a layer of indirection through which CAD-specific data may be accessed by an application program using CAD-system neutral C and FORTRAN language function calls. CAPRI supports a general set of CAD operations such as truth testing, geometry construction and entity queries.

Afjeh, Abdollah A.↗