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At least 37 records · Page 2

Software engineering and data management for automated payload experiment tool

The Microgravity Projects Office identified a need to develop a software package that will lead experiment developers through the development planning process, obtain necessary information, establish an electronic data exchange avenue, and allow easier manipulation/reformatting of the collected information. An MS-DOS compatible software package called the Automated Payload Experiment Tool (APET) has been developed and delivered. The objective of this task is to expand on the results of the APET work previously performed by University of Alabama in Huntsville (UAH) and provide versions of the software in a Macintosh and Windows compatible format. Appendix 1 science requirements document (SRD) Users Manual is attached.

Maddux, Gary A.↗

Automated payload experiment tool feasibility study

To achieve an environment less dependent on the flow of paper, automated techniques of data storage and retrieval must be utilized. The prototype under development seeks to demonstrate the ability of a knowledge-based, hypertext computer system. This prototype is concerned with the logical links between two primary NASA support documents, the Science Requirements Document (SRD) and the Engineering Requirements Document (ERD). Once developed, the final system should have the ability to guide a principal investigator through the documentation process in a more timely and efficient manner, while supplying more accurate information to the NASA payload developer.

Maddux, Gary A.↗

Pilot interaction with cockpit automation - Operational experiences with the Flight Management System

Results are presented of two studies on the potential effect of cockpit automation on the pilot's performance, which provide data on pilots' difficulties with understanding and operating one of the core systems of cockpit automation, the Flight Management System (FMS). The results of both studies indicate that, although pilots do become proficient in standard FMS operations through ground training and subsequent flight experience, they still have difficulties tracking the FMS status and behavior in certain flight contexts and show gaps in the understanding of the functional structure of the system. The results suggest that design-related factors such as opaque interfaces contribute to these difficulties, which can affect the pilot's situation awareness.

Sarter, Nadine B.↗

The B737 MAX 8 Accidents as Operational Experiences With Automation Transparency

Automation transparency has come into prominence in the human-machine systems literature, with researchers offering definitions, models, design frameworks, and empirical findings. However, missing from the literature are reflections on the actual operational experiences of human crews interacting with intelligent automation conceived from multiple transparency perspectives. The Boeing 737 MAX 8 accidents present a tragic case of a catastrophic failure of automation transparency. We explore this case with an emphasis on extracting design and regulatory insights for the nuclear power and other safety-critical domains.

99 GENERAL AND MISCELLANEOUS↗

JOINT APPOINTEE: Evolution of ferroelectric properties in SmxBi1-xFeO3 via automated Piezoresponse Force Microscopy across combinatorial spread libraries

Combinatorial spread libraries offer a innovative approach to explore the evolution of material properties over broad concentration, temperature, and growth parameter spaces. However, traditional limitation of this approach is the requirement for the read-out of functional properties across the library. Here we develop automated Piezoresponse Force Microscopy (PFM) for the exploration of combinatorial spread libraries and demonstrate its application in the SmxBi1-xFeO3 system with the ferroelectric-antiferroelectric morphotropic phase boundary. This approach relies on the synergy of the quantitative nature of PFM and the implementation of automated experiments that allow PFM-based sampling over macroscopic samples. The concentration dependence of pertinent ferroelectric parameters has been determined and used to develop the mathematical framework based on Ginzburg-Landau theory describing the evolution of these properties across the concentration space. We pose that a combination of automated scanning probe microscope and combinatorial spread library approach will emerge as an efficient research paradigm to close the characterization gap in the high-throughput materials discovery. We make the data sets open to the community and hope that this will stimulate other efforts to interpret and understand the physics of these systems.

Automated Microscopy, Combinatorial Library, Ferro↗

Automated Testing Experience of the Linear Aerospike SR-71 Experiment (LASRE) Controller

System controllers must be fail-safe, low cost, flexible to software changes, able to output health and status words, and permit rapid retest qualification. The system controller designed and tested for the aerospike engine program was an attempt to meet these requirements. This paper describes (1) the aerospike controller design, (2) the automated simulation testing techniques, and (3) the real time monitoring data visualization structure. Controller cost was minimized by design of a single-string system that used an off-the-shelf 486 central processing unit (CPU). A linked-list architecture, with states (nodes) defined in a user-friendly state table, accomplished software changes to the controller. Proven to be fail-safe, this system reported the abort cause and automatically reverted to a safe condition for any first failure. A real time simulation and test system automated the software checkout and retest requirements. A program requirement to decode all abort causes in real time during all ground and flight tests assured the safety of flight decisions and the proper execution of mission rules. The design also included health and status words, and provided a real time analysis interpretation for all health and status data.

Larson, Richard R.↗

A Multi-Objective Bayesian Optimized Human Assessed Multi-Target Generated Spectral Recommender System for Rapid Pareto Discoveries of Material Properties

Optimization for different tasks like material characterization, synthesis, and functional properties for desired applications over multi-dimensional control parameter and function spaces need a rapid strategic search through active learning. However, in all cases prior to optimization, the target material properties are assumed known and fixed, which mostly deviates from real-world scenarios in material synthesis. This can be critical for running expensive experiments on new materials, when the experimental results are fuzzy for any scientific outcomes due to improper target setting, ultimately wasting time and cost. The failure rate and cost are even higher over exploring on multi-target space, where we want to learn the pareto among multiple properties, to jointly optimize during material synthesis for desired applications. To address the challenge, here we introduce the human-operator attempt flexibility in the active learning based automated experiment framework, with generating multiple human assessed targets through a voting-based recommender system during real-time microscope measurements over the large material image space, sequentially learn/update multiple desired targets through a weighting system, and adaptively search in multiple material properties functional space for non-dominated pareto discoveries to maximize the custom structural similarity based acquisition function. We term this a multi-objective Bayesian optimized human assessed multi-target generated spectral recommender systems (MOBO-HAM-SRS). The approach has been demonstrated to peizoresponse force spectroscopy of a ferroelectric thin film, exploring with different kernels and acquisition functions. This work shows an advancement towards human-AI collaborated automated experiments, steering optimization trajectories through human overpowering AI at the early stage when uncertainty is high and AI overpowering human at the later stage with rapid exploration towards optimal goal, following human-assessed multiple targets properties.

Biswas, Arpan↗

Space Construction Automated Fabrication Experiment Definition Study (SCAFEDS), part 2

The techniques, processes, and equipment required for automatic fabrication and assembly of structural elements in using Shuttle as a launch vehicle, and construction were defined. Additional construction systems operational techniques, processes, and equipment which can be developed and demonstrated in the same program to provide further risk reduction benefits to future large space systems were identified and examined.

Source record↗

Space Construction Automated Fabrication Experiment Definition Study (SCAFEDS). Volume 1: Executive summary

The techniques, processes, and equipment required for automatic fabrication and assembly of structural elements in space using the space shuttle as a launch vehicle and construction base were investigated. Additional construction/systems/operational techniques, processes, and equipment which can be developed/demonstrated in the same program to provide further risk reduction benefits to future large space systems were included. Results in the areas of structure/materials, fabrication systems (beam builder, assembly jig, and avionics/controls), mission integration, and programmatics are summarized. Conclusions and recommendations are given.

Source record↗

Compact reactor design automation

A conceptual compact reactor design automation experiment was performed using the real-time expert system G2. The purpose of this experiment was to investigate the utility of an expert system in design; in particular, reactor design. The experiment consisted of the automation and integration of two design phases: reactor neutronic design and fuel pin design. The utility of this approach is shown using simple examples of formulating rules to ensure design parameter consistency between the two design phases. The ability of G2 to communicate with external programs even across networks provides the system with the capability of supplementing the knowledge processing features with conventional canned programs with possible applications for realistic iterative design tools.

Nassersharif, Bahram↗

Validation of automated payload experiment tool

The System Management and Production Laboratory, Research Institute, The University of Alabama in Huntsville (UAH), was tasked by the Microgravity Experiment Projects (MEP) Office of the Payload projects Office (PPO) at Marshall Space Flight Center (MSFC) to conduct research in the current methods of written documentation control and retrieval. The goals of this research were to determine the logical interrelationships within selected NASA documentation, and to expand on a previously developed prototype system to deliver a distributable, electronic knowledge-based system. This computer application would then be used to provide a 'paperless' interface between the appropriate parties for the required NASA documentation.

Maddux, Gary A.↗

Autonomous Molecular Structure Imaging with High-Resolution Atomic Force Microscopy for Molecular Mixture Discovery

Due to its single-molecule sensitivity, high-resolution atomic force microscopy (HR-AFM) has proved to be a valuable and uniquely advantageous tool to study complex molecular mixtures, which hold promise for developing clean energy and achieving environmental sustainability. However, significant challenges remain to achieve the full potential of the sophisticated and time-consuming experiments. Automation combined with machine learning (ML) and artificial intelligence (AI) is key to overcoming these challenges. Here we present Auto-HR-AFM, an AI tool to automatically collect HR-AFM images of petroleum-based mixtures. In this study, we trained an instance segmentation model to teach Auto-HR-AFM how to recognize features in HR-AFM images. Auto-HR-AFM then uses that information to optimize the imaging by adjusting the probe-molecule distance for each molecule in the run. Auto-HR-AFM is the initial tool that will lead to fully automated scanning probe microscopy (SPM) experiments, from start to finish. This automation will allow SPM to become a mainstream characterization technique for complex mixtures, an otherwise unattainable target.

36 MATERIALS SCIENCE↗

A Heritage BioSensor for Lunar Biology Experiments

Introduction: Automated biological experiments on small spacecraft missions have gained prominence over the past decade due to their simplicity, accessibility, and small mass, volume, and power needs. Most recently, the BioSensor microfluidic CubeSat payload aboard BioSentinel used an automated microfluidic cell culture system to study the effects of environmental stressors like deep space radiation and microgravity on yeast growth and metabolism. BioSentinel’s successor, the Lunar Explorer Instrument for space biology Applications (LEIA), will study the effects of lunar gravity and radiation using an improved version of the BioSensor microfluidic platform. The BioSensor payload has great adaptability to host a diverse range of biological experiments with single- and multi-celled organisms in both crewed and uncrewed missions, making it a compelling candidate for future space biology studies in a lunar surface environment. BioSensor Instrumentation on BioSentinel: The first spaceflight mission with the BioSensor, BioSentinel’s biology experiments occurred at three locations -- deep space, ISS and ground. The payload contained 18 microfluidic cards, each featuring 16 growth wells (a total of 288 growth wells). Each well was loaded before launch with desiccated yeast. In space, liquid culture medium (nutrients) was automatically introduced to batches of wells at a time to initiate a series of biology experiments. Temperature was maintained by thin film heaters on both sides of each card. Each well was equipped with three LEDs emitting at 570 nm, 630 nm, and 850 nm, paired with photodetectors to measure cell concentration and the alamarBlue (metabolic indicator dye) color transition from blue to pink. Phenotypic parameters like cell viability, metabolic rate, and generation time can be derived from these measurements. The sequence and timing of fluid fills, optical measurements, and thermal control were stored onboard, but could be updated asynchronously via ground communication. LEIA: LEIA is slated for launch no earlier than 2026 on a CLPS lander. BioSentinel’s BioSensor has been modified for use in LEIA. These improvements include: (a) storage for multiple culture medium types, (b) additional LED color (465 nm) for a new biological assay for antioxidant (carotenoid) production, (c) housing modifications for later biology load before launch, (d) improved isolation between electronic and fluidic components, and (e) improved humidity control for prolonged organism viability in case of post-load launch delay. Future Prospects: The consistent and successful demonstration of complex fluidics platforms alongside reliable instrument operations in a space environment is poised to create strong momentum for BioSensor-based biological experiment payloads. Planned future developments with the BioSensor include extending compatibility to a broader range of organisms and assays. Preliminary work has already demonstrated successful growth of Arabidopsis seedlings in fluidic cards. With a few modifications to the optical assembly, the setup could easily measure photosynthetic traits in plants and cyanobacteria. The addition of fluorescence measurements and generation of novel luminescent assays will elevate BioSensor’s functionality further. Beyond the BioSensor’s potential uses on free-flyer missions, ISS and Gateway, and CLPS landers, deploying the BioSensor to the lunar surface or in an artificial habitat on crewed missions could enable pioneering research on both how life responds to lunar conditions and future bioproduction capabilities making the BioSensor an indispensable tool for future space biology research.

Chinmayee Govinda Raj↗