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NASA NTRS2016

Compatibility Assessment Tool

In support of ground system development for the Space Launch System (SLS), engineers are tasked with building immense engineering models of extreme complexity. The various systems require rigorous analysis of pneumatics, hydraulic, cryogenic, and hypergolic systems. There are certain standards that each of these systems must meet, in the form of pressure vessel system (PVS) certification reports. These reports can be hundreds of pages long, and require many hours to compile. Traditionally, each component is analyzed individually, often utilizing hand calculations in the design process. The objective of this opportunity is to perform these analyses in an integrated fashion with the parametric CADCAE environment. This allows for systems to be analyzed on an assembly level in a semi-automated fashion, which greatly improves accuracy and efficiency. To accomplish this, component specific parameters were stored in the Windchill database to individual Creo Parametric models based on spec control drawings. These parameters were then accessed by using the Prime Analysis within Creo Parametric. MathCAD Prime spreadsheets were created that automatically extracted these parameters, performed calculations, and generated reports. The reports described component compatibility based on local conditions such as pressure, temperature, density, and flow rates. The reports also determined component pairing compatibility, such as properly sizing relief valves with regulators. The reports stored the input conditions that were used to determine compatibility to increase traceability of component selection. The desired workflow for using this tool would begin with a Creo Schematics diagram of a PVS system. This schematic would store local conditions and locations of components. The schematic would then populate an assembly within Creo Parametric, using Windchill database parts. These parts would have their attributes already assigned, and the MathCAD spreadsheets could begin running through database parts to determine which components would be suited for specific locations within the assembly. This eliminates a significant amount of time from the design process, and makes initial analysis assessments more accurate. Each component that would be checked for a location within the assembly would generate a report, showing whether the component was compatible. These reports could be used to generate the PVS report without the need to perform the same analysis multiple times. This process also has the potential to be expanded upon to further automate PVS reports. The integration of software codes or macros could be used to automatically check through hundreds of parts for each location on the schematic. If the software could recognize which type of component would be necessary for each location, it is possible that simply starting the macro could completely choose all the components needed for the schematic, and in turn the system. This would save many hours of work initially selecting components, which could end up saving money. Overall, this process helps to automate initial component selections for PVS systems to fit local design specifications. These selections will automatically generate reports showing how the design criteria are met by the specific component that was chosen. These reports will contribute to easier compilation of the PVS certification reports, which currently take a great amount of time and effort to produce.

Egbert, James Allen↗

NASA NTRS2017

Building Better Biosensors for Exploration into Deep-Space, Using Humanized Yeast

1.BioSentinel is 1 of 13 secondary payloads hitching a ride beyond Low Earth Orbit on Exploration Mission 1 (EM-1), set to launch from NASAs Space Launch System in 2019. EM-1 is our first opportunity to investigate the effects of the deep space environment on a eukaryotic biological system, the budding yeast S. cerevisiae. Though separated by a billion years of evolution we share hundreds of genes important for basic cell function, including responses to DNA damage. Thus, yeast is an ideal biosensor for detecting typesextent of damage induced by deep-space radiation.We will fly desiccated cells, then rehydrate to wake them up when the automated payload is ready to initiate the experiment. Rehydration solution contains SC (Synthetic Complete) media and alamarBlue, an indicator for changes in growth and metabolism. Telemetry of LED readings will then allow us to detect how cells respond throughout the mission. The desiccation-rehydration process can be extremely damaging to cells, and can severely diminish our ability to accurately measure and model cellular responses to deep-space radiation. The aim of this study is to develop a better biosensor: yeast strains that are more resistant to desiccation stress. We will over-express known cellular protectants, including hydrophilin Sip18, the protein disaggregase Hsp104, and thioredoxin Trx2, a responder to oxidative stress, then measure cell viability after desiccation to determine which factors improve stress tolerance. Over-expression of SIP18 in wine yeast starter cultures was previously reported to increase viability following desiccation stress by up to 70. Thus, we expect similar improvements in our space-yeast strains. By designing better yeast biosensors we can better prepare for and mitigate the potential dangers of deep-space radiation for future missions.This work is funded by NASAs AES program.

biosensor↗

NASA NTRS2000

Upgrade of the Thermal Vacuum Data System at NASA/GSFC

The Goddard Space Flight Center's new thermal vacuum data acquisition system is a networked client-sever application that enables lab operations crews to monitor all tests from a central location. The GSFC thermal vacuum lab consists of eleven chambers in Building 7 and one chamber in Building 10. The new data system was implemented for several reasons. These included the need for centralized data collection, more flexible and easier to use operator interface, greater data accessibility, a reduction in testing time and cost, and increased payload and personnel safety. Additionally, a new data system was needed for year-2000 compliance. This paper discusses the incorporation of the Thermal Vacuum Data System (TVDS) within the thermal vacuum lab at GSFC, its features and capabilities and lessons learned in its implementation. Additional topics include off-center (Internet) capability for remote monitoring and the role of TVDS in the efforts to automate thermal vacuum chamber operations.

Palmer, John↗

NASA NTRS2000

Upgrade of The Thermal Vacuum Data System at NASA/GSFC

Palmer, John↗

NASA NTRS1989

Advancing automation and robotics technology for the space station Freedom and for the US economy

In April 1985, as required by Public Law 98-371, the NASA Advanced Technology Advisory Committee (ATAC) reported to Congress the results of its studies on advanced automation and robotics technology for use on the Freedom space station. This material was documented in the initial report (NASA Technical Memorandum 87566). A further requirement of the law was that ATAC follow NASA's progress in this area and report to Congress semiannually. This report is the eighth in a series of progress updates and covers the period between October 1, 1988, and March 31, 1989. NASA has accepted the basic recommendations of ATAC for its Space Station Freedom efforts. ATAC and NASA agree that the thrust of Congress is to build an advanced automation and robotics technology base that will support an evolutionary Space Station Freedom program and serve as a highly visible stimulator, affecting the U.S. long-term economy. The progress report identifies the work of NASA and the Freedom study contractors. It also describes research in progress, and it makes assessments of the advancement of automation and robotics technology on the Freedom space station.

Robotics↗

DOE OSTI2026

Multi-Split Variable Refrigerant Flow (VRF) System Building Energy Simulations Using Performance Maps

Multi-split variable refrigerant flow (VRF) systems are highly energy-efficient HVAC (heating, ventilation and air conditioning) technologies that connect a single outdoor unit to multiple independent indoor terminal units using a common refrigerant circuit and a variable-speed compressor. Building energy simulations that incorporate VRF systems help model their unique operational characteristics and predict energy consumption in specific building designs. Traditionally, EnergyPlus models these systems by employing multiple sets of performance curves to characterize both individual terminal units and the outdoor unit. However, producing these curves is labor intensive and error prone, and they often do not capture all the key input and output variables. This paper introduces a novel approach that uses multi-dimensional performance maps to model VRF systems in building environments for space cooling. In this approach, performance maps are developed at the component level—separately for the outdoor unit and for each indoor terminal. The new modeling method is validated within EnergyPlus via a Python plug-in that contains a simple solver loop to coordinate the component-level, indoor, and outdoor unit maps. Furthermore, because performance maps can span more variables than traditional performance curves, they offer the opportunity to implement advanced controls, such as enhanced dehumidification and compressor modulation. A VRF air conditioner’s hardware system was modeled using the DOE/ORNL Heat Pump Design Model, which was automated to produce extensive performance maps for both the indoor and outdoor units.

Shen, Bo [ORNL] (ORCID:0000000336600393)↗

DOE OSTI2024

Automated path planning for functionally graded materials considering phase stability and solidification behavior: Application to the Mo-Nb-Ta-Ti system

Functionally graded materials have the potential to improve upon monolithic parts by locally tailoring compositions to surrounding environmental conditions. Difficulties arise when designing composition gradients as incompatible materials can result in detrimental phase formation and failure of the gradient joint. As many alloys are multi-component, designing a composition gradient free of detrimental phases is difficult due to the large composition space available to explore. A framework was developed that improves the path planning algorithm and surrogate models with adaptive sampling schemes specific to their problem definition. A cost function was created to minimize a property (such as cracking susceptibility) along a path. This framework was applied to the Mo-Nb-Ta-Ti system as a case study to showcase the efficiency in building the surrogate models and in iterating different optimal compositionally graded paths.

36 MATERIALS SCIENCE↗

NASA NTRS1992

Autonomous Space Processor for Orbital Debris (ASPOD)

A project in the Advanced Design Program at the University of Arizona is described. The project is named the Autonomous Space Processor for Orbital Debris (ASPOD) and is a Universities Space Research Association (USRA) sponsored design project. The development of ASPOD and the students' abilities in designing and building a prototype spacecraft are the ultimate goals of this project. This year's focus entailed the development of a secondary robotic arm and end-effector to work in tandem with an existent arm in the removal of orbital debris. The new arm features the introduction of composite materials and a linear drive system, thus producing a light-weight and more accurate prototype. The main characteristic of the end-effector design is that it incorporates all of the motors and gearing internally, thus not subjecting them to the harsh space environment. Furthermore, the arm and the end-effector are automated by a control system with positional feedback. This system is composed of magnetic and optical encoders connected to a 486 PC via two servo-motor controller cards. Programming a series of basic routines and sub-routines allowed the ASPOD prototype to become more autonomous. The new system is expected to perform specified tasks with a positional accuracy of 0.5 cm.

Ramohalli, Kumar↗

NASA NTRS1992

Autonomous space processor for orbital debris advanced design project in support of solar system exploration

This paper is regarding a project in the Advanced Design Program at the University of Arizona. The project is named the Autonomous Space Processor for Orbital Debris (ASPOD) and is a NASA/Universities Space Research Association (USRA) sponsored design project. The development of ASPOD and the students' abilities in designing and building a prototype spacecraft are the ultimate goals of this project. This year's focus entailed the development of a secondary robotic arm and end-effector to work in tandem with an existent arm in the removal of orbital debris. The new arm features the introduction of composite materials and a linear drive system, thus producing a light-weight and more accurate prototype. The main characteristic of the end-effector design is that it incorporates all of the motors and gearing internally, thus not subjecting them to the harsh space environment. Furthermore, the arm and the end-effector are automated by a control system with positional feedback. This system is composed of magnetic and optical encoders connected to a 486 PC via two servo-motor controller cards. Programming a series of basic routines and sub-routines has allowed the ASPOD prototype to become more autonomous. The new system is expected to perform specified tasks with a positional accuracy of 0.5 cm.

Ramohalli, Kumar↗

NASA NTRS1993

Optimization of knowledge-based systems and expert system building tools

The objectives of the NASA-AMES Cooperative Agreement were to investigate, develop, and evaluate, via test cases, the system parameters and processing algorithms that constrain the overall performance of the Information Sciences Division's Artificial Intelligence Research Facility. Written reports covering various aspects of the grant were submitted to the co-investigators for the grant. Research studies concentrated on the field of artificial intelligence knowledge-based systems technology. Activities included the following areas: (1) AI training classes; (2) merging optical and digital processing; (3) science experiment remote coaching; (4) SSF data management system tests; (5) computer integrated documentation project; (6) conservation of design knowledge project; (7) project management calendar and reporting system; (8) automation and robotics technology assessment; (9) advanced computer architectures and operating systems; and (10) honors program.

Yasuda, Phyllis↗

NASA NTRS2005

INDUCTIVE SYSTEM HEALTH MONITORING WITH STATISTICAL METRICS

Model-based reasoning is a powerful method for performing system monitoring and diagnosis. Building models for model-based reasoning is often a difficult and time consuming process. The Inductive Monitoring System (IMS) software was developed to provide a technique to automatically produce health monitoring knowledge bases for systems that are either difficult to model (simulate) with a computer or which require computer models that are too complex to use for real time monitoring. IMS processes nominal data sets collected either directly from the system or from simulations to build a knowledge base that can be used to detect anomalous behavior in the system. Machine learning and data mining techniques are used to characterize typical system behavior by extracting general classes of nominal data from archived data sets. In particular, a clustering algorithm forms groups of nominal values for sets of related parameters. This establishes constraints on those parameter values that should hold during nominal operation. During monitoring, IMS provides a statistically weighted measure of the deviation of current system behavior from the established normal baseline. If the deviation increases beyond the expected level, an anomaly is suspected, prompting further investigation by an operator or automated system. IMS has shown potential to be an effective, low cost technique to produce system monitoring capability for a variety of applications. We describe the training and system health monitoring techniques of IMS. We also present the application of IMS to a data set from the Space Shuttle Columbia STS-107 flight. IMS was able to detect an anomaly in the launch telemetry shortly after a foam impact damaged Columbia's thermal protection system.

Iverson, David L.↗

DOE OSTI2022

Dynamic Decarbonization through Autonomous Physics-Centric Deep Learning and Optimization of Building Operations (Abstract only)

This project directly addresses the primary goal of Area of Interest 2 in the CRADA call: to advance optimization-based integrated energy management systems in commercial and residential buildings. Pacific Northwest National Laboratory (PNNL) and its industry partner PassiveLogic aim to accomplish this by reaching three key objectives. First, to ensure a broad impact in the building controls industry, PNNL will extend its open-source library for predictive control synthesis by augmenting its capabilities with data-driven self-learning of building models and auto-calibration of predictive controllers. The effort will focus on building use cases selected in collaboration with PassiveLogic. The team will specifically address the development of methods for data-driven adaptation of building models, investigation of model architectures that best address specific building types, and automated synthesis of differentiable predictive controllers that optimize diverse objectives. Second, PNNL will collaborate with PassiveLogic to integrate the aforementioned methods with PasiveLogic’s advanced controls platform. The collaborative integration effort will inform the developments under the first objective by providing specific data on the attainable performance of model learning on resource-constrained edge computing platforms. This software integration effort will increase the technical maturity of the developed libraries by exploring the use of software integration tools and methods. Third, PNNL and PassiveLogic will work to improve the technology readiness of the developed predictive controllers by testing their performance in relevant test environments, such as high-fidelity simulation, hardware in the loop, and actual test buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS1980

The Build System - Integration and management of large software avionic systems

The Build System comprises the software tools and procedures creating the flight memory load for the Space Shuttle Backup Flight System. The system has six functions: (1) configuration management, which insures that the memory load contains the proper modules, all clearly marked; (2) source translation, which translates the source code into a relocatable machine code; (3) module integration, which combines and assigns memory locations to all the object modules produced in source translation; (4) static code analysis, which verifies the integration process; (5) deliverables generation, which yields release documentation and deliverable items; and (6) release maintenance, which controls all system patches subsequent to release. Further developments will include more automation in the producing of patches from source-code updates and system requirements for tracking.

Mayer, J. T. B.↗

NASA NTRS2020

Planetary Defence Activities Beyond NASA and ESA

The collision of a significant asteroid or comet with Earth represents a singular natural disaster for a myriad of reasons, including: its extraterrestrial origin; the fact that it is perhaps the only natural disaster that is preventable in many cases, given sufficient preparation and warning; its scope, which ranges from damaging a city to an extinction-level event; and the duality of asteroids and comets themselves---they are grave potential threats, but are also tantalising scientific clues to our ancient past and resources with which we may one day build a prosperous spacefaring future. Accordingly, the problems of developing the means to interact with asteroids and comets for purposes of defence, scientific study, exploration, and resource utilisation have grown in importance over the past several decades. Since the 1980s, more and more asteroids and comets (especially the former) have been discovered, radically changing our picture of the solar system. At the beginning of the year 1980, approximately 9,000 asteroids were known to exist. By the beginning of 2001, that number had risen to approximately 125,000 thanks to the Earth-based telescopic survey efforts of the era, particularly the emergence of modern automated telescopic search systems, pioneered by the Massachusetts Institute of Technology’s (MIT’s) LINEAR system in the mid-to-late 1990s. Today, in late 2019, about 840,000 asteroids have been discovered, with more and more being found every week, month, and year. Of those, approximately 21,400 are categorised as near-Earth asteroids (NEAs), 2,000 of which are categorised as Potentially Hazardous Asteroids (PHAs) and 2,749 of which are categorised as potentially accessible. The hazards posed to us by asteroids affect people everywhere around the world. As well, the opportunities presented by asteroids may benefit our entire species. Thus, with such a large number of currently known asteroids and so many yet to be discovered, it is not surprising that individuals, organisations, institutions, and governments all around the world have become interested in the study of asteroids. Indeed, a variety of government space agencies, private organisations, and individuals have worked on developing the means by which to observe, study, and even interact with asteroids and comets for purposes including science, exploration, pioneering, commerce, and planetary defence. This includes significant individual contributions by amateur asteroid astronomers all over the world. International cooperation in planetary defence within the contexts of the United Nations and the International Asteroid Warning Network (IAWN) are discussed in Chapter 2, and the activities undertaken by the world’s larger space agencies, ESA and NASA, are discussed in Chapters 3 and 4. But, what of the other agencies and institutions around the world who are also working on the problem of defence against hazardous asteroids and comets, or related topics? In this chapter we provide an overview, in alphabetical order, of some of the planetary defence related efforts that have been undertaken around the world beyond the activities at the United Nations, NASA, and ESA.

Barbee, Brent W.↗

NASA NTRS2005

Faults Discovery By Using Mined Data

Fault discovery in the complex systems consist of model based reasoning, fault tree analysis, rule based inference methods, and other approaches. Model based reasoning builds models for the systems either by mathematic formulations or by experiment model. Fault Tree Analysis shows the possible causes of a system malfunction by enumerating the suspect components and their respective failure modes that may have induced the problem. The rule based inference build the model based on the expert knowledge. Those models and methods have one thing in common; they have presumed some prior-conditions. Complex systems often use fault trees to analyze the faults. Fault diagnosis, when error occurs, is performed by engineers and analysts performing extensive examination of all data gathered during the mission. International Space Station (ISS) control center operates on the data feedback from the system and decisions are made based on threshold values by using fault trees. Since those decision-making tasks are safety critical and must be done promptly, the engineers who manually analyze the data are facing time challenge. To automate this process, this paper present an approach that uses decision trees to discover fault from data in real-time and capture the contents of fault trees as the initial state of the trees.

Lee, Charles↗

DOE OSTI2025

A self-supervised robotic system for autonomous contact-based spatial mapping of semiconductor properties

Integrating robotically driven contact-based material characterization techniques into self-driving laboratories can enhance measurement quality, reliability, and throughput. While deep learning models support robust autonomy, current methods lack reliable pixel-precision positioning and require extensive labeled data. To overcome these challenges, we propose an approach for building self-supervised autonomy into contact-based robotic systems that teach the robot to follow domain expert measurement principles at high throughputs. We demonstrate the performance of this approach by autonomously driving a 4-DOF robotic probe for 24 hours to characterize semiconductor photoconductivity at 3025 uniquely predicted poses across a gradient of drop-casted perovskite film compositions, achieving throughputs of more than 125 measurements per hour. Spatially mapping photoconductivity onto each drop-casted film reveals compositional trends and regions of inhomogeneity, valuable for identifying manufacturing defects. With this self-supervised neural network–driven robotic system, we enable high-precision and reliable automation of contact-based characterization techniques at high throughputs, thereby allowing measurement of previously inaccessible yet important semiconductor properties for self-driving laboratories.

Science & Technology - Other Topics↗

NASA NTRS1993

Matera Laser Ranging Observatory (MLRO): An overview

The Agenzia Spaziale Italiana (ASI) is currently under negotiation with the Bendix Field Engineering Corporation (BFEC) of the Allied Signal Aerospace Company (ASAC) to build a state-of-the-art laser ranging observatory for the Centro di Geodesia Spaziale, in Matera, Italy. The contract calls for the delivery of a system based on a 1.5 meter afocal Cassegrain astronomical quality telescope with multiple ports to support a variety of experiments for the future, with primary emphasis on laser ranging. Three focal planes, viz. Cassegrain, Coude, and Nasmyth will be available for these experiments. The open telescope system will be protected from dust and turbulence using a specialized dome which will be part of the building facilities to be provided by ASI. The fixed observatory facility will be partitioned into four areas for locating the following: laser, transmit/receive optics, telescope/dome enclosure, and the operations console. The optical tables and mount rest on a common concrete pad for added mechanical stability. Provisions will be in place for minimizing the effects of EMI, for obtaining maximum cleanliness for high power laser and transmit optics, and for providing an ergonomic environment fitting to a state-of-the-art multipurpose laboratory. The system is currently designed to be highly modular and adaptable for scaling or changes in technology. It is conceived to be a highly automated system with superior performance specifications to any currently operational system. Provisions are also made to adapt and accommodate changes that are of significance during the course of design and integration.

Varghese, Thomas K.↗

NASA NTRS1994

An operations and command systems for the extreme ultraviolet explorer

About 40% of the budget of a scientific spacecraft mission is usually consumed by Mission Operations & Data Analysis (MO&DA) with MO driving these costs. In the current practice, MO is separated from spacecraft design and comes in focus relatively late in the mission life cycle. As a result, spacecraft may be designed that are very difficult to operate. NASA centers have extensive MO expertise but often lessons learned in one mission are not exploited for other parallel or future missions. A significant reduction of MO costs is essential to ensure a continuing and growing access to space for the scientific community. We are addressing some of these issues with a highly automated payload operations and command system for an existing mission, the Extreme Ultraviolet Explorer (EUVE). EUVE is currently operated jointly by the Goddard Space Flight Center (GSFC), responsible for spacecraft operations, and the Center for Extreme Ultraviolet Astrophysics (CEA) of the University of California, Berkeley, which controls the telescopes and scientific instruments aboard the satellite. The new automated system is being developed by a team including personnel from the NASA Ames Research Center (ARC), the Jet Propulsion Laboratory (JPL) and the Center for EUV Astrophysics (CEA). An important goal of the project is to provide AI-based technology that can be easily operated by nonspecialists in AI. Another important goal is the reusability of the techniques for other missions. Models of the EUVE spacecraft need to be built both for planning/scheduling and for monitoring. In both cases, our modeling tools allow the assembly of a spacecraft model from separate sub-models of the various spacecraft subsystems. These sub-models are reusable; therefore, building mission operations systems for another small satellite mission will require choosing pre-existing modules, reparametrizing them with respect to the actual satellite telemetry information, and reassembling them in a new model. We briefly describe the EUVE mission and indicate why it is particularly suitable for the task. Then we briefly outline our current work in mission planning/scheduling and spacecraft and instrument health monitoring.

Muscettola, Nicola↗