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NASA NTRSDate not supplied

Artificial Intelligence (AI) Methods for Automating the Impact Tool Evidence Library

INTRODUCTION: The development of the Evidence Library for use with the IMPACT (Informing Mission Planning via Analysis of Complex Tradespaces) probability risk assessment tool involved a multilayered, time intensive process of data collection and analysis by subject matter experts from the Exploration Medical Capability (ExMC) Element Clinical and Science Team to produce clinical findings forms (CliFFs) for 120 medical conditions. Artificial Intelligence Large Language Models (LLMs) can be leveraged to facilitate this process, thus reducing labor and time. TOPIC: CliFFs contain information about medical conditions as they pertain to spaceflight. This includes condition definitions, incidence data, crew task impairment estimates caused by conditions, treatment protocols and references to literature used for gathering condition evidence. Guided by the Evidence Library Methods document and the CliFF development instructions, a team has leveraged Microsoft Azure AI services and open-source documentation to construct an AI-assisted automated pipeline for CliFF development. This process is designed to search, retrieve, and evaluate the applicable data, and ultimately generate a completed CliFF. The LLM evaluates the relevance of each of the source materials to spaceflight, either as direct evidence or as an analog. The model extracts keywords and generates brief summaries to enhance search and retrieval in later stages of CliFF development. For instance, it can calculate epidemiological statistical data, such as incidence rates and the likelihood of best or worst-case scenarios. APPLICATION: Large Language Models (LLMs) can efficiently summarize large amounts of text. Leveraging this technology will automate data retrieval and evidence gathering for medical databases, like the IMPACT tool, by aiding in the labor-intensive process of analyzing large bodies of literature and organizing it into a formatted document like a CliFF. This added efficiency will enable expeditious expansion of the Evidence Library with additional medical conditions and update previous CLiFFs as new technology becomes available.

Ali Al↗

NASA NTRS2006

Deductive Glue Code Synthesis for Embedded Software Systems Based on Code Patterns

Automated code synthesis is a constructive process that can be used to generate programs from specifications. It can, thus, greatly reduce the software development cost and time. The use of formal code synthesis approach for software generation further increases the dependability of the system. Though code synthesis has many potential benefits, the synthesis techniques are still limited. Meanwhile, components are widely used in embedded system development. Applying code synthesis to component based software development (CBSD) process can greatly enhance the capability of code synthesis while reducing the component composition efforts. In this paper, we discuss the issues and techniques for applying deductive code synthesis techniques to CBSD. For deductive synthesis in CBSD, a rule base is the key for inferring appropriate component composition. We use the code patterns to guide the development of rules. Code patterns have been proposed to capture the typical usages of the components. Several general composition operations have been identified to facilitate systematic composition. We present the technique for rule development and automated generation of new patterns from existing code patterns. A case study of using this method in building a real-time control system is also presented.

automated code synthesis↗

NASA NTRS1976

An Automated System for Chromosome Analysis

The design, construction, and testing of a complete system to produce karyotypes and chromosome measurement data from human blood samples, and to provide a basis for statistical analysis of quantitative chromosome measurement data are described.

Castleman, K. R.↗

NASA NTRS1993

Architectural constructs of Ampex DST

The DST 800 automated library is a high performance, automated tape storage system, developed by AMPEX, providing mass storage to host systems. Physical Volume Manager (PVM) is a volume server which supports either a DST 800, DST 600 stand alone tape drive, or a combination of DST 800 and DST 600 subsystems. The objective of the PVM is to provide the foundation support to allow automated and operator assisted access to the DST cartridges with continuous operation. A second objective is to create a data base about the media, its location, and its usage so that the quality and utilization of the media on which specific data is recorded and the performance of the storage system may be managed. The DST tape drive architecture and media provides several unique functions that enhance the ability to achieve high media space utilization and fast access. Access times are enhanced through the implementation of multiple areas (called system zones) on the media where the media may be unloaded. This reduces positioning time in loading and unloading the cartridge. Access times are also reduced through high speed positioning in excess of 800 megabytes per second. A DST cartridge can be partitioned into fixed size units which can be reclaimed for rewriting without invalidating other recorded data on the tape cartridge. Most tape management systems achieve space reclamation by deleting an entire tape volume, then allowing users to request a 'scratch tape' or 'nonspecific' volume when they wish to record data to tape. Physical cartridge sizes of 25, 75, or 165 gigabytes will make this existing process inefficient or unusable. The DST cartridge partitioning capability provides an efficient mechanism for addressing the tape space utilization problem.

Johnson, Clay↗

NASA NTRS1993

Automatic specification of reliability models for fault-tolerant computers

The calculation of reliability measures using Markov models is required for life-critical processor-memory-switch structures that have standby redundancy or that are subject to transient or intermittent faults or repair. The task of specifying these models is tedious and prone to human error because of the large number of states and transitions required in any reasonable system. Therefore, model specification is a major analysis bottleneck, and model verification is a major validation problem. The general unfamiliarity of computer architects with Markov modeling techniques further increases the necessity of automating the model specification. Automation requires a general system description language (SDL). For practicality, this SDL should also provide a high level of abstraction and be easy to learn and use. The first attempt to define and implement an SDL with those characteristics is presented. A program named Automated Reliability Modeling (ARM) was constructed as a research vehicle. The ARM program uses a graphical interface as its SDL, and it outputs a Markov reliability model specification formulated for direct use by programs that generate and evaluate the model.

Liceaga, Carlos A.↗

NASA NTRS1994

CORSS: Cylinder Optimization of Rings, Skin, and Stringers

Launch vehicle designs typically make extensive use of cylindrical skin stringer construction. Structural analysis methods are well developed for preliminary design of this type of construction. This report describes an automated, iterative method to obtain a minimum weight preliminary design. Structural optimization has been researched extensively, and various programs have been written for this purpose. Their complexity and ease of use depends on their generality, the failure modes considered, the methodology used, and the rigor of the analysis performed. This computer program employs closed-form solutions from a variety of well-known structural analysis references and joins them with a commercially available numerical optimizer called the 'Design Optimization Tool' (DOT). Any ring and stringer stiffened shell structure of isotropic materials that has beam type loading can be analyzed. Plasticity effects are not included. It performs a more limited analysis than programs such as PANDA, but it provides an easy and useful preliminary design tool for a large class of structures. This report briefly describes the optimization theory, outlines the development and use of the program, and describes the analysis techniques that are used. Examples of program input and output, as well as the listing of the analysis routines, are included.

Finckenor, J.↗

NASA NTRS2005

Tools of the Future: How Decision Tree Analysis Will Impact Mission Planning

The universe is infinitely complex; however, the human mind has a finite capacity. The multitude of possible variables, metrics, and procedures in mission planning are far too many to address exhaustively. This is unfortunate because, in general, considering more possibilities leads to more accurate and more powerful results. To compensate, we can get more insightful results by employing our greatest tool, the computer. The power of the computer will be utilized through a technology that considers every possibility, decision tree analysis. Although decision trees have been used in many other fields, this is innovative for space mission planning. Because this is a new strategy, no existing software is able to completely accommodate all of the requirements. This was determined through extensive research and testing of current technologies. It was necessary to create original software, for which a short-term model was finished this summer. The model was built into Microsoft Excel to take advantage of the familiar graphical interface for user input, computation, and viewing output. Macros were written to automate the process of tree construction, optimization, and presentation. The results are useful and promising. If this tool is successfully implemented in mission planning, our reliance on old-fashioned heuristics, an error-prone shortcut for handling complexity, will be reduced. The computer algorithms involved in decision trees will revolutionize mission planning. The planning will be faster and smarter, leading to optimized missions with the potential for more valuable data.

Otterstatter, Matthew R.↗

NASA NTRS2016

Controlled Contamination of Epoxy Composites with PDMS and Removal by Laser Ablation

Surface preparation is critical to the performance of adhesively bonded composites. During manufacturing, minute quantities of mold release compounds are inevitably deposited on faying surfaces and may compromise bond performance. To ensure safety, mechanical fasteners and other crack arrest features must be installed in the bondlines of primary structures, which negates some advantages of adhesively bonded construction. Laser ablation is an automated, repeatable, and scalable process with high potential for the surface preparation of metals and composites in critical applications such as primary airframe structures. In this study, laser ablation is evaluated on composite surfaces for the removal of polydimethylsiloxane (PDMS), a common mold release material. Composite panels were contaminated uniformly with PDMS film thicknesses as low as 6.0 nm as measured by variable angle spectroscopic ellipsometry. Bond performance was assessed by mechanical testing using a 250 F cure, epoxy adhesive and compared with pre-bond surface inspection results. Water contact angle, optically stimulated electron emission, and laser induced breakdown spectroscopy were used to characterize contaminated and laser ablated surfaces. The failure mode obtained from double cantilever beam tests correlated well with surface characterization data. The test results indicated that even low levels of PDMS were not completely removed by laser ablation.

Palmieri, Frank↗

NASA NTRSDate not supplied

Artificial Intelligence (AI) Methods for Augmenting the IMPACT Tool Evidence Library

Development of the Evidence Library for use with the IMPACT probability risk assessment tool took several years and involved a staggering amount of effort from a multi-disciplinary team. A very significant amount of the labor effort to collect, assess and finalize the Clinical Finding Form (CliFF) for each of the 119 medical conditions was provided by physician subject matter experts from the Exploration Medical Capability (ExMC) Element Clinical and Science Team. Many AI tools such as ChatGPT are excellent at summarizing large amounts of information and the current project was initiated to determine how such tools might streamline laborious processes, e.g., review and summarization of many scientific research publications, to execute key steps more efficiently in the process of developing CliFFs. The process for collecting the evidence which is found in the CliFFs is well documented in the Evidence Library Methods document (ELM; HRP-48036*). Using ELM and the CliFF development instructions as a guideline, a team of developers is leveraging Microsoft Azure AI tools and services along with open-source frameworks, to construct an AI-assisted automated pipeline. This pipeline is designed to search, retrieve, and process the necessary data sources, and ultimately help generate the final version of a CliFF. Currently, the large language model evaluates the relevance of each source material to spaceflights, either as direct evidence or as an analog. Additionally, the model assists in extracting keywords and generating brief summaries to enhance augmented retrieval and search processes in later stages of CliFF development. Once the data is ready, the model can perform semantic search and retrieval, generating and extracting valuable information for the CliFF. For instance, it can handle epidemiological statistical data, such as incidence rates and the likelihood of best or worst-case scenarios. The steps that required reading and summarizing articles were viewed as providing the greatest return on investment since large language models are very efficient and accurate in summarizing large amounts of text. Since labor effort to complete the original CliFF was not recorded with sufficient granularity, comparisons with an AI tool-generated CliFF will provide merely an approximation of time saved. Upon completion of the process, the CliFF for the medical condition “appendicitis” generated with the support of AI-based methods will serve as a proof-of-concept and will be compared to the original appendicitis CliFF to determine if use of the tools resulted in content and conclusory similarity. Based upon the results from face validation of the two CliFFs, modifications to the process will be made if necessary and additional condition CliFFs will be evaluated. Ultimately, CliFFs for the entire set of medical conditions will be created with the assistance of AI tools. Depending on the cost savings realized, CliFFs for additional medical conditions can be created to expand the Evidence Library. Future direction includes specifying the characteristics of the reviewer (prompting the AI tools to generate output assuming the reviewer is a sub-specialist physician, or nurse or EMT/medic) to determine if the effects on AI-generated output are different based on knowledge, skills and abilities. *Exploration Medical Capability Evidence Library Methods, HRP-48036 Rev A, July 2022.

Ali Al↗

NASA NTRS1993

Air Force construction automation/robotics

The Air Force has several missions which generate unique requirements that are being met through the development of construction robotic technology. One especially important mission will be the conduct of Department of Defense (DOD) space activities. Space operations and other missions place construction/repair equipment operators in dangerous environments and potentially harmful situations. Additionally, force reductions require that human resources be leveraged to the maximum extent possible, and more stringent construction repair requirements push for increased automation. To solve these problems, the U.S. Air Force is undertaking a research and development effort at Tyndall AFB, FL, to develop robotic construction/repair equipment. This development effort involves the following technologies: teleoperation, telerobotics, construction operations (excavation, grading, leveling, tool change), robotic vehicle communications, vehicle navigation, mission/vehicle task control architecture, and associated computing environment. The ultimate goal is the fielding of a robotic repair capability operating at the level of supervised autonomy. This paper will discuss current and planned efforts in space construction/repair, explosive ordnance disposal, hazardous waste cleanup, and fire fighting.

Nease, A. D.↗

NASA NTRS1997

Automated Reuse of Scientific Subroutine Libraries through Deductive Synthesis

Systematic software construction offers the potential of elevating software engineering from an art-form to an engineering discipline. The desired result is more predictable software development leading to better quality and more maintainable software. However, the overhead costs associated with the formalisms, mathematics, and methods of systematic software construction have largely precluded their adoption in real-world software development. In fact, many mainstream software development organizations, such as Microsoft, still maintain a predominantly oral culture for software development projects; which is far removed from a formalism-based culture for software development. An exception is the limited domain of safety-critical software, where the high-assuiance inherent in systematic software construction justifies the additional cost. We believe that systematic software construction will only be adopted by mainstream software development organization when the overhead costs have been greatly reduced. Two approaches to cost mitigation are reuse (amortizing costs over many applications) and automation. For the last four years, NASA Ames has funded the Amphion project, whose objective is to automate software reuse through techniques from systematic software construction. In particular, deductive program synthesis (i.e., program extraction from proofs) is used to derive a composition of software components (e.g., subroutines) that correctly implements a specification. The construction of reuse libraries of software components is the standard software engineering solution for improving software development productivity and quality.

Lowry, Michael R.↗

NASA NTRS1992

A Boon for the Architect Engineer

Langley Research Center's need for an improved construction specification system led to an automated system called SPECSINTACT. A catalog of specifications, the system enables designers to retrieve relevant sections from computer storage and modify them as needed. SPECSINTACT has also been adopted by government agencies. The system is an integral part of the Construction Criteria Base (CCB), a single disc containing design and construction information for 10 government agencies including the American Institute of Architects' MASTERSPEC. CCB employs CD- ROM technologies and is available from the National Institute of Building Sciences. Users report substantial savings in time and productivity.

Source record↗

NASA NTRS2020

Designing and Training for Appropriate Trust in Increasingly Autonomous Advanced Air Mobility Operations: A Mental Model Approach: Version 1

To enable effective human-autonomy teaming (HAT) in Advanced Air Mobility (AAM) operations, the current paper presents a theoretical framework to design and train for appropriate trust in automation. The novel contribution of this work resides in connecting the construct of trust to mental models and showing how this method could be used to enable emerging HAT concepts such as Adaptive Trust Calibration. To contextualize this framework, in section 2 we discuss simplified vehicle operations (SVO) and remote vehicle operations (RVO), which are leading operational concepts within AAM. In section 3 we describe our perspective on automation and increasingly autonomous systems and present a brief discussion on human-automation interaction and human-autonomy teaming. In section 4 we provide a detailed discussion on the construct of trust in automation. In section 5 we present a framework that associates mental models with trust through principles of transparent design. Finally, in section 6 we present three descriptive models for designing and training for appropriate trust in increasingly autonomous systems.

Human-Autonomy Teaming↗

NASA NTRS1994

Air Force construction automation/robotics

The Air Force has several unique requirements that are being met through the development of construction robotic technology. The missions associated with these requirements place construction/repair equipment operators in potentially harmful situations. Additionally, force reductions require that human resources be leveraged to the maximum extent possible and that more stringent construction repair requirements push for increased automation. To solve these problems, the U.S. Air Force is undertaking a research and development effort at Tyndall AFB, FL to develop robotic teleoperation, telerobotics, robotic vehicle communications, automated damage assessment, vehicle navigation, mission/vehicle task control architecture, and associated computing environment. The ultimate goal is the fielding of robotic repair capability operating at the level of supervised autonomy. The authors of this paper will discuss current and planned efforts in construction/repair, explosive ordnance disposal, hazardous waste cleanup, fire fighting, and space construction.

Nease, AL↗

NASA NTRS2006

Using Apex To Construct CPM-GOMS Models

process for automatically generating computational models of human/computer interactions as well as graphical and textual representations of the models has been built on the conceptual foundation of a method known in the art as CPM-GOMS. This method is so named because it combines (1) the task decomposition of analysis according to an underlying method known in the art as the goals, operators, methods, and selection (GOMS) method with (2) a model of human resource usage at the level of cognitive, perceptual, and motor (CPM) operations. CPM-GOMS models have made accurate predictions about behaviors of skilled computer users in routine tasks, but heretofore, such models have been generated in a tedious, error-prone manual process. In the present process, CPM-GOMS models are generated automatically from a hierarchical task decomposition expressed by use of a computer program, known as Apex, designed previously to be used to model human behavior in complex, dynamic tasks. An inherent capability of Apex for scheduling of resources automates the difficult task of interleaving the cognitive, perceptual, and motor resources that underlie common task operators (e.g., move and click mouse). The user interface of Apex automatically generates Program Evaluation Review Technique (PERT) charts, which enable modelers to visualize the complex parallel behavior represented by a model. Because interleaving and the generation of displays to aid visualization are automated, it is now feasible to construct arbitrarily long sequences of behaviors. The process was tested by using Apex to create a CPM-GOMS model of a relatively simple human/computer-interaction task and comparing the time predictions of the model and measurements of the times taken by human users in performing the various steps of the task. The task was to withdraw $80 in cash from an automated teller machine (ATM). For the test, a Visual Basic mockup of an ATM was created, with a provision for input from (and measurement of the performance of) the user via a mouse. The times predicted by the automatically generated model turned out to approximate the measured times fairly well (see figure). While these results are promising, there is need for further development of the process. Moreover, it will also be necessary to test other, more complex models: The actions required of the user in the ATM task are too sequential to involve substantial parallelism and interleaving and, hence, do not serve as an adequate test of the unique strength of CPM-GOMS models to accommodate parallelism and interleaving.

John, Bonnie↗

NASA NTRS1988

Bipolar-Battery Construction

Bipolar batteries fabricated in continuous quasi-automated process. Components of battery configured so processing steps run sequentially. Key components of battery, bipolar plate and bipolar separator, fabricated separately and later joined together.

Rippel, Wally E.↗

NASA NTRS1993

SimTool - An object based approach to simulation construction

The creation and maintenance of large complex simulations can be a difficult and error prone task. A number of interactive and automated tools have been developed to aid in simulation construction and maintenance. Many of these tools are based upon object oriented analysis and design concepts. One such tool, SimTool, is an object based integrated tool set for the development, maintenance, and operation of large, complex and long lived simulations. This paper discusses SimTool's object based approach to simulation design, construction and execution. It also discusses the services provided to various levels of SimTool users to assist them in a wide range of simulation tasks. Also, with the aid of an implemented and working simulation example, this paper discusses SimTool's key design and operational features. Finally, this paper presents a condensed discussion of SimTool's Entity-Relationship-Attribute (ERA) modeling approach.

Crues, Edwin Z.↗

NASA NTRS1994

EVA-SCRAM operations

This paper wrestles with the on-orbit operational challenges introduced by the proposed Space Construction, Repair, and Maintenance (SCRAM) tool kit for Extra-Vehicular Activity (EVA). SCRAM undertakes a new challenging series of on-orbit tasks in support of the near-term Hubble Space Telescope, Extended Duration Orbiter, Long Duration Orbiter, Space Station Freedom, other orbital platforms, and even the future manned Lunar/Mars missions. These new EVA tasks involve welding, brazing, cutting, coating, heat-treating, and cleaning operations. Anticipated near-term EVA-SCRAM applications include construction of fluid lines and structural members, repair of punctures by orbital debris, refurbishment of surfaces eroded by atomic oxygen, and cleaning of optical, solar panel, and high emissivity radiator surfaces which have been degraded by contaminants. Future EVA-SCRAM applications are also examined, involving mass production tasks automated with robotics and artificial intelligence, for construction of large truss, aerobrake, and reactor shadow shield structures. Realistically achieving EVA-SCRAM is examined by addressing manual, teleoperated, semi-automated, and fully-automated operation modes. The operational challenges posed by EVA-SCRAM tasks are reviewed with respect to capabilities of existing and upcoming EVA systems, such as the Extravehicular Mobility Unit, the Shuttle Remote Manipulating System, the Dexterous End Effector, and the Servicing Aid Tool.

Flanigan, Lee A.↗