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All sources NASA NTRS DOE OSTI

NASA NTRS2016

Future Standardization of Space Telecommunications Radio System with Core Flight System

NASA Glenn Research Center (GRC) is integrating the NASA Space Telecommunications Radio System (STRS) Standard with the Core Flight System (cFS), an avionics software operating environment. The STRS standard provides a common, consistent framework to develop, qualify, operate and maintain complex, reconfigurable and reprogrammable radio systems. The cFS is a flexible, open architecture that features a plugand- play software executive called the Core Flight Executive (cFE), a reusable library of software components for flight and space missions and an integrated tool suite. Together, STRS and cFS create a development environment that allows for STRS compliant applications to reference the STRS application programmer interfaces (APIs) that use the cFS infrastructure. These APIs are used to standardize the communication protocols on NASAs space SDRs. The cFS-STRS Operating Environment (OE) is a portable cFS library, which adds the ability to run STRS applications on existing cFS platforms. The purpose of this paper is to discuss the cFS-STRS OE prototype, preliminary experimental results performed using the Advanced Space Radio Platform (ASRP), the GRC S‑ band Ground Station and the SCaN (Space Communication and Navigation) Testbed currently flying onboard the International Space Station (ISS). Additionally, this paper presents a demonstration of the Consultative Committee for Space Data Systems (CCSDS) Spacecraft Onboard Interface Services (SOIS) using electronic data sheets (EDS) inside cFE. This configuration allows for the data sheets to specify binary formats for data exchange between STRS applications. The integration of STRS with cFS leverages mission-proven platform functions and mitigates barriers to integration with future missions. This reduces flight software development time and the costs of software-defined radio (SDR) platforms. Furthermore, the combined benefits of STRS standardization with the flexibility of cFS provide an effective, reliable and modular framework to minimize software development efforts for spaceflight missions.

space communications↗

DOE OSTI2023

Efficient, direct compilation of SU(N) operations into SNAP & Displacement gates

We present a function which connects the parameter of a previously published short sequence of selective number-dependent arbitrary phase (SNAP) and displacement gates acting on a qudit encoded into the Fock states of a superconducting cavity, $V_k(\alpha)=D(\alpha)R_\pi(k)D(-2\alpha)R_\pi(k)D(\alpha)$ to the angle of the Givens rotation $G(\theta)$ on levels $|k\rangle,|k+1\rangle$ that sequence approximates, namely $\alpha=\Phi(\theta) = \frac{\theta}{4\sqrt{k+1}}$. Previous publications left the determination of an appropriate $\alpha$ to numerical optimization at compile time. The map $\Phi$ gives us the ability to compile directly any $d$-dimensional unitary into a sequence of SNAP and displacement gates in $O(d^3)$ complex floating point operations with low constant prefactor, avoiding the need for numerical optimization. Numerical studies demonstrate that the infidelity of the generated gate sequence $V_k$ per Givens rotation $G$ scales as approximately $O(\theta^6)$. We find numerically that the error on compiled circuits can be made arbitrarily small by breaking each rotation into $m$$\theta/m$ rotations, with the full $d\times d$ unitary infidelity scaling as approximately $O(m^{-4})$. This represents a significant reduction in the computational effort to compile qudit unitaries either to SNAP and displacement gates or to generate them via direct low-level pulse optimization via optimal control.

Job, Joshua↗

DOE OSTI2026

Constellation: The autonomous control and data acquisition system for dynamic experimental setups

The operation of instruments and detectors in laboratory or beamline environments presents a complex challenge, requiring stable operation of multiple concurrent devices, often controlled by separate hardware and software solutions. These environments frequently undergo modifications, such as the inclusion of different auxiliary devices depending on the experiment or facility, adding further complexity. The successful management of such dynamic configurations demands a flexible and robust system capable of controlling data acquisition, monitoring experimental setups, enabling seamless reconfiguration, and integrating new devices with limited effort. This paper presents Constellation, a flexible and network-distributed control and data acquisition software framework tailored to laboratory and beamline environments, that addresses the limitations of existing solutions. The framework is designed with a focus on extensibility, providing a streamlined interface for instrument integration. It supports efficient system setup via network discovery mechanisms, promotes stability through autonomous operational features, and provides comprehensive documentation and supporting tools for operators and application developers such as controllers and logging interfaces. At the core of the architectural design is the autonomy of the individual components, called satellites, which can make independent decisions about their operation and communicate these decisions to other components. This paper introduces the design principles and framework architecture of Constellation, presents the available graphical user interfaces, shares insights from initial successful deployments, and provides an outlook on future developments and applications.

Autonomy↗

NASA NTRS2016

Characterization of Evidence for Human System Risk Assessment

Understanding the kinds of evidence available and using the best evidence to answer a question is critical to evidenced-based decision-making, and it requires synthesis of evidence from a variety of sources. Categorization of human system risks in spaceflight, in particular, focuses on how well the integration and interpretation of all available evidence informs the risk statement that describes the relationship between spaceflight hazards and an outcome of interest. A mature understanding and categorization of these risks requires: 1) sufficient characterization of risk, 2) sufficient knowledge to determine an acceptable level of risk (i.e., a standard), 3) development of mitigations to meet the acceptable level of risk, and 4) identification of factors affecting generalizability of the evidence to different design reference missions. In the medical research community, evidence is often ranked by increasing confidence in findings gleaned from observational and experimental research (e.g., "levels of evidence"). However, an approach based solely on aspects of experimental design is problematic in assessing human system risks for spaceflight. For spaceflight, the unique challenges and opportunities include: (1) The independent variables in most evidence are the hazards of spaceflight, such as space radiation or low gravity, which cannot be entirely duplicated in terrestrial (Earth-based) analogs, (2) Evidence is drawn from multiple sources including medical and mission operations, Lifetime Surveillance of Astronaut Health (LSAH), spaceflight research (LSDA), and relevant environmental & terrestrial databases, (3) Risk metrics based primarily on LSAH data are typically derived from available prevalence or incidence data, which may limit rigorous interpretation, (4) The timeframe for obtaining adequate spaceflight sample size (n) is very long, given the small population, (5) Randomized controlled trials are unattainable in spaceflight, (6) Collection of personal and environmental data on the astronaut population may create opportunities for advanced analytics and human-environment modeling that goes beyond that achieved in isolated experimental designs; and (7) Translation of relevant research to operations is a complex, transdisciplinary enterprise in which the approach must apply across the physical, biological, behavioral, and social sciences. The approach to synthesizing evidence must address both source and fidelity of data, and reflect the most general attributes of quality of evidence in science and engineering: reliability and validity. The authors are developing a two-factor approach which includes the various kinds of evidence required to understand risks and for the integrated interpretation of all evidence that is essential to develop standards and countermeasures. A unified framework for aggregating and assessing different kinds of evidence provides a consistent, traceable, evidence-based decision-making process to translate research to operations in an environment where engineers, scientists, physicians, and managers all engage in analyzing the trade space of vehicle design, standards, requirements and solutions for spaceflight.

Steinberg, S. L.↗

NASA NTRS1990

Operator function modeling: Cognitive task analysis, modeling and intelligent aiding in supervisory control systems

The design, implementation, and empirical evaluation of task-analytic models and intelligent aids for operators in the control of complex dynamic systems, specifically aerospace systems, are studied. Three related activities are included: (1) the models of operator decision making in complex and predominantly automated space systems were used and developed; (2) the Operator Function Model (OFM) was used to represent operator activities; and (3) Operator Function Model Expert System (OFMspert), a stand-alone knowledge-based system was developed, that interacts with a human operator in a manner similar to a human assistant in the control of aerospace systems. OFMspert is an architecture for an operator's assistant that uses the OFM as its system and operator knowledge base and a blackboard paradigm of problem solving to dynamically generate expectations about upcoming operator activities and interpreting actual operator actions. An experiment validated the OFMspert's intent inferencing capability and showed that it inferred the intentions of operators in ways comparable to both a human expert and operators themselves. OFMspert was also augmented with control capabilities. An interface allowed the operator to interact with OFMspert, delegating as much or as little control responsibility as the operator chose. With its design based on the OFM, OFMspert's control capabilities were available at multiple levels of abstraction and allowed the operator a great deal of discretion over the amount and level of delegated control. An experiment showed that overall system performance was comparable for teams consisting of two human operators versus a human operator and OFMspert team.

Mitchell, Christine M.↗

NASA NTRS2010

Complexity Analysis of Traffic in Corridors-in-the-Sky

The corridors-in-the-sky concept imitates the highway system in ground transportation. The benefit expected from a corridor relies on its capability of handling high density traffic with negligible controller workload, the acceptance of extra fuel or distance, and the complexity reduction in underlying sectors. This work evaluates a selected corridor from these perspectives through simulations. To examine traffic inside the corridor, a corridor traffic simulation tool that can resolve conflicts is developed using C language. Prescribed conflict resolution maneuvers mimic corridor users behaviors and conflict resolution counts measure complexity. Different lane options and operational policies are proposed to examine their impacts on complexity. Fuel consumption is calculated and compared for corridor traffic. On the other hand, to investigate the complexity of non-corridor traffic in underlying sectors, the existing Airspace Concept Evaluation System tool is utilized along with the Automated Airspace Concept tool. The number of conflict resolutions is examined and treated as the complexity measurement. The results show heavy traffic can be managed with low complexity for a historical traffic schedule simulated with appropriate operational policies and lane options. For instance, with 608 flights and peak aircraft count of 100, only 84 actions need to be taken in a 24-hour period to resolve the conflicts for an 8-lane corridor. Compared with the fuel consumptions with great circle trajectories, the simulation of corridor traffic shows that the total extra fuel for corridor flights is 26,373 gallons, or 2.76%, which is 0.38% less than flying filed flight plans. Without taking climb and descent portions of corridor traffic, the complexity of underlying sectors is reduced by 17.71%. However the climb and descent portions will eliminate the reduction and the overall complexity of sectors is actually increased by 9.14%.

Xue, Min↗

NASA NTRSDate not supplied

NASA Gateway Refueling Architecture and Concept of Operation

The Lunar Gateway is a deep space orbiting outpost being developed by NASA in partnership with ESA and other domestic and international partners. It is a critical component of NASA’s Artemis program supporting long-term human exploration of the moon and is designed to be refueled, requiring the on-orbit transfer of propellants. The first two modules of Gateway to be launched will be the Power and Propulsion Element (PPE) and the Habitation and Logistics Outpost (HALO). The PPE contains the bipropellant chemical and electrical propulsion systems that will provide attitude control and orbit raising capability for Gateway. The reaction control system (RCS) utilizes monomethylhydrazine (MMH) and mixed oxides of nitrogen-3 (MON-3) as the fuel and oxidizer, respectively. Helium is used as a pressurant. The Advanced Electric Propulsion Systems (AEPS) and Busek hall thrusters that comprise the solar electric propulsion (SEP) system use xenon as the propellent. The ESPRIT Refueling Module, provided by ESA, will supply the propellant refueling function to Gateway’s propulsion systems. On-orbit refueling is a complex, technically challenging operation that is key to enabling sustainable crewed Lunar and Martian exploration. Numerous systems may be involved in the refueling operation. Also numerous systems are required to enable the successful ability for Gateway to refuel such as, SEP, RCS, Structure & Mechanisms (S&M), Guidance, Navigation and Control (GNC), Thermal, Software, Vehicle System Manager (VSM), Flight Ops, Extra Vehicular Robotics (EVR), Communication and Tracking (C&T), Avionics, and more. This paper will detail the design architecture, concept of operations, and challenges associated with the Gateway refueling system. The methodologies used in Gateway will be compared to those implemented in OSAM-1 and the best practices documented by AIAA and CONFERS (Consortium For Execution Of Rendezvous And Servicing Operations).

Brandie L. Rhodes↗

NASA NTRS1991

Objective evaluation of situation awareness for dynamic decision makers in teleoperations

Situation awareness, a current mental mode of the environment, is critical to the ability of operators to perform complex and dynamic tasks. This should be particularly true for teleoperators, who are separated from the situation they need to be aware of. The design of the man-machine interface must be guided by the goal of maintaining and enhancing situation awareness. The objective of this work has been to build a foundation upon which research in the area can proceed. A model of dynamic human decision making which is inclusive of situation awareness will be presented, along with a definition of situation awareness. A method for measuring situation awareness will also be presented as a tool for evaluating design concepts. The Situation Awareness Global Assessment Technique (SAGAT) is an objective measure of situation awareness originally developed for the fighter cockpit environment. The results of SAGAT validation efforts will be presented. Implications of this research for teleoperators and other operators of dynamic systems will be discussed.

Endsley, Mica R.↗

DOE OSTI2019

Processing of Alnico Magnets by Additive Manufacturing

Permanent magnets without rare earth (RE) elements, such as alnico, will improve supply stability and potentially decrease permanent magnet cost, especially for traction drive motors and other increased temperature applications. Commercial alnico magnets with the highest energy product are produced by directional solidification (DS) to achieve a < 001 > columnar grain orientation followed by significant final machining, adding to the high cost. Additive manufacturing (AM) is an effective method to process near net-shape parts with minimal final machining of complex geometries. AM also, has potential for texture/grain orientation control and compositionally graded structures. This report describes fabrication of alnico magnets by AM using both laser engineered net shaping (LENS)/directed energy deposition (DED) and electron beam melting powder bed fusion (EBM/PBF). High pressure gas atomized (HPGA) pre-alloyed alnico powders, with high purity and sphericity, were built into cylindrical and rectangular samples, followed by magnetic annealing (MA) and a full heat treatment (FHT). The magnetic properties of these AM processed specimens were different from their cast and sintered counterparts of the same composition and show a great sensitivity to heat treatment. The AM process parameters used in this developmental study did not yet result in any preferred texture within the alnico AM builds. These findings demonstrate feasibility for near net-shape processing of alnico permanent magnets for use in next generation traction drive motors and other applications requiring increased operating temperatures and/or complex engineered part geometries, especially with further AM process development for texture control.

36 MATERIALS SCIENCE↗

NASA NTRSDate not supplied

Initial Development of A Digital Twin Model for an Electrified Aircraft Propulsion Emulation Rig

In support of aviation fuel burn and emission reduction goals, NASA is pursing high-payoff research investments that promise to transform aviation. This includes investments in Electrified Aircraft Propulsion (EAP), which relies on the generation, storage, transmission, and use of electrical power for producing thrust and optimizing propulsion system efficiency. Multiple technology challenges must be addressed to unlock the full potential of EAP. This includes advances in propulsion controls, which will be vital for ensuring coordinated efficient operation of the complex integrated subsystems that comprise EAP architectures. To support EAP controls research, the NASA Glenn Research Center has developed the Hybrid Propulsion Emulation Rig (HyPER). The HyPER laboratory hardware includes shaft-mounted electric machines, power converters, power supplies, power distribution cables, and an energy storage device that can be reconfigured to represent a variety of EAP architectures. It also includes an integrated real-time computer system that hosts developed EAP control software and turbomachinery simulations. This enables the electrical system and rotating shafts of EAP designs to be implemented in actual hardware and integrated with turbomachinery simulations and system-level EAP control logic implemented in software. In this form, the HyPER laboratory provides a partially simulated, partially hardware-in-the-loop test environment enabling the initial development and evaluation of EAP control technology. A prerequisite for the development of EAP control designs is the availability of a system model that accurately reflects the operation of the electrical system hardware. To support this need, a digital twin model of the HyPER electrical system hardware is under development. This model is being coded in the MATLAB Simulink environment and uses the NASA-developed Electrical Modeling and Thermal Analysis Toolbox (EMTAT) to construct a digital twin framework. EMTAT contains generic electrical component building blocks that are simulated at turbomachinery timescales. Associated inputs and outputs allow the blocks to be combined to model complete electrical systems. The EMTAT blocks also contain adjustable internal maps and parameters that can be set to reflect the operation of a specific electrical component. For the HyPER digital twin, the settings of these EMTAT block internal maps and parameters is determined through machine learning approaches applied to characterization run data collected from the laboratory. During characterization runs the laboratory electrical system hardware is subjected to a full range of torque, speed, and power settings. Acquired data is then used to estimate EMTAT block parameters using a variety of machine learning techniques. The resulting digital twin model is found to match the operation of actual HyPER hardware with an accuracy suitable for control development purposes. It also holds promise for other applications including modeling the performance of HyPER laboratory reconfigurations and model-based anomaly detection. Planned follow-on work to automate post-processing of acquired laboratory data to update the HyPER digital twin model will also be presented and discussed.

Electrified Aircraft Propulsion↗

NASA NTRS2014

Film Cooled Recession of SiC/SiC Ceramic Matrix Composites: Test Development, CFD Modeling and Experimental Observations

SiCSiC ceramic matrix composites (CMCs) systems will play a crucial role in next generation turbine engines for hot-section component applications because of their ability to significantly increase engine operating temperatures, reduce engine weight and cooling requirements. However, the environmental stability of Si-based ceramics in high pressure, high velocity turbine engine combustion environment is of major concern. The water vapor containing combustion gas leads to accelerated oxidation and corrosion of the SiC based ceramics due to the water vapor reactions with silica (SiO2) scales forming non-protective volatile hydroxide species, resulting in recession of the ceramic components. Although environmental barrier coatings are being developed to help protect the CMC components, there is a need to better understand the fundamental recession behavior of in more realistic cooled engine component environments.In this paper, we describe a comprehensive film cooled high pressure burner rig based testing approach, by using standardized film cooled SiCSiC disc test specimen configurations. The SiCSiC specimens were designed for implementing the burner rig testing in turbine engine relevant combustion environments, obtaining generic film cooled recession rate data under the combustion water vapor conditions, and helping developing the Computational Fluid Dynamics (CFD) film cooled models and performing model validation. Factors affecting the film cooled recession such as temperature, water vapor concentration, combustion gas velocity, and pressure are particularly investigated and modeled, and compared with impingement cooling only recession data in similar combustion flow environments. The experimental and modeling work will help predict the SiCSiC CMC recession behavior, and developing durable CMC systems in complex turbine engine operating conditions.

Recession↗

NASA NTRS2024

Autonomy to Enable NASA Missions from Aeronautics to Space

2024 ASCEND Call for Sessions Session Format: Panel Session Topic: Space Exploration and Infrastructure: Exploring, Living, and Working in Space (The panel must map to one of six Session Topics - https://www.ascend.events/presenters/call-for-sessions/#sessiontopics) Title: Autonomy to Enable NASA Missions from Aeronautics to Space Short Session Description: In this panel discussion the National Aeronautics and Space Administration (NASA) will discuss the role that autonomy and Artificial Intelligence (AI) will play as humanity moves off-world. Recent advances in general autonomy tools are changing the way NASA and its partners leverage autonomy for its air and space initiatives, including Advanced Air Mobility (AAM) concepts and potential lunar and Martian operations. The panelists will consist of autonomy subject matter experts familiar with the current state of the art for autonomy across both aeronautical and space domains. They will discuss how those technologies could evolve as operations become more complex and which autonomy technologies can be used in both the space and aeronautical domains. For example, perhaps autonomy work originally developed for terrestrial applications, like Advanced Air Mobility (AAM), could be applied to off-world lunar and Martian applications and vice versa. Additionally, the panel will address common misconceptions of these technologies, obstacles to implementation, and possible solutions for overcoming those obstacles. Join NASA in exploring how research activities can align to streamline autonomy development efforts, advancing NASA's goals to expand humanity's reach beyond Earth for the benefit of all. Contact Information: • Dr. Adam Yingling • Office of Technology, Policy, and Strategy (OTPS) • Adam.j.yingling@nasa.gov, 703-416-9129 Session Length: 1.25 hours, 75 minutes Extended Description: Moderator: Dr. Adam Yingling, NASA, Office of Technology, Policy, and Strategy Panel Speakers: • Autonomy Forum Principals o Dr. Charles Norton, Deputy Chief Technologist, Jet Propulsion Laboratory (JPL) o Dr. Carolyn Mercer, Chief Technologist, Space Mission Directorate (SMD) o Dr. Parimal Kopardekar (PK), Advanced Air Mobility (AAM) Integration Manager o Danette Alan, NASA, Senior Leader for Autonomous Systems, Space Technology Mission Directorate (STMD) o Duane Armstrong, Intelligent Systems Lead, Autonomous Systems Laboratory (ASL) Panel Format: • Introduction (10 min): The panel moderator will provide a 10-minute session introduction that will include an overview NASA’s Moon to Mars architecture, AAM autonomy research, and an introduction of the principals as panel speakers. • Moderated Session Part 1 (30 min): There will be a 30-minute moderated session among the moderator and the five autonomy principals to discuss the current state of art for autonomy and how work developed in one domain may be applicable to other domains; including the merits and challenges for implementing those technologies. • Moderated Session Part 2 (25 min): The moderator will then ask the principals to consider how technologies developed across all the domains might be able to address the most salient challenges identified in the previous session. • Q&A (10 min): The session will conclude with 10-minutes of audience Q&A. Session Goals and Outcomes: The session goals are 1) to communicate the importance of autonomy for both aeronautical and space mission, 2) Investigate potential synergies across autonomy research efforts that will enable scalable operations, and 3) to receive community feedback as NASA leverages autonomy to evolve aviation on Earth and enable humanity to live and work off-world.

Aerospace↗

DOE OSTI2018

Machine Learning Algorithms for Matching Theories, Simulations, and Observations in Cosmology (Final Project)

The search for simple and elegant equations to explain and predict observable natural phenomena has been a driving force in scientific theory for several centuries. The great successes of Newton's laws, Maxwell's equations, the Schrodinger equation, and the theory of General Relativity have encouraged this perspective, and perhaps a beautiful equation comprising a “theory of everything” remains to be discovered. But now scientists are grappling with systems of ever-increasing complexity, fraught with nonlinearity, and with the quantities of interest often only indirectly observed. Nature may resist a simple description, and the most important discoveries of the next century may be complex theories with countless variables and parameters. The era of big data opens up a promising new approach to scientific discovery in this setting. The predictions of modern theories, even if complex or nonlinear, can be examined through detailed and computationally-intensive simulations that take days or weeks to run and fill petabytes of disk space. The upcoming generation of scientific instruments will provide petabytes of observations at unprecedented resolution and depth. The challenge is to compare data to simulations so as to test theories and identify those that best match the observations. The data are numerous and rich but are subject to noise and various systematic biases. The simulations are large and detailed but are so costly that the effective sample size is small. Moreover, the mapping from data to simulation to the parameters of interest is typically complicated and ill-conditioned. Although these challenges, and the solutions we propose, apply across the sciences, we will ground our efforts by focusing on cosmology. Here, we are truly entering the era of big data in several senses. Ever larger experiments survey larger and larger cosmological volumes, resulting in enormous amounts of pixel data to process and extract the information of cosmological interest. These include large imaging surveys, which collect all the light in broad wavelength ranges over significant fractions of the sky, and spectroscopic surveys, which measure the light as a function of wavelength to map out 3D distances. These experiments are designed to shed light on the big unanswered questions in cosmology. Distilling the petabytes of data into observed quantities for comparison with theory is a daunting task. But these large experiments do not only result in large amounts of data to analyze: if we wish to compare to theories of physics, then we need increasingly extensive predictions for the observed quantities as well, which requires ever-larger cosmological simulations that take substantial -- and at times prohibitive -- computational resources to produce. Our goal is to develop statistical and machine learning methods for using observed and simulated data to advance machine learning with applications cosmology. In particular, we focus our research efforts on the following tasks: The challenge for automated science is that it is computationally impossible and statistically dangerous to consider every possible model in order to find the best one. We will develop Bayesian Optimization based active-learning methods that accelerate both the execution of the simulations and the search for best-fitting parameters. The key idea is to make the simulations adaptive -- across resolutions, time, and parameters -- using the data to search as the simulation runs; Most ML methods operate on simple finite dimensional feature vectors. However, many cosmology and other science applications require ML methods that can operate on more complex objects as inputs or outputs such as functions, distributions, or sets and point clouds. Our goal is to develop efficient ML methods for this problem and demonstrate their applicability in Cosmology, Astrophysics, and other science problems.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1997

Operational Issues: What Science in Available?

Flight/duty/rest considerations involve two highly complex factors: the diverse demands of aviation operations and human physiology (especially sleep and circadian rhythms). Several core operational issues related to fatigue have been identified, such as minimum rest requirements, duty length, flight time considerations, crossing multiple time zones, and night flying. Operations also can involve on-call reserve status and callout, delays due to unforeseen circumstances (e.g., weather, mechanical), and on-demand flights. Over 40 years of scientific research is now available to apply to these complex issues of flight/duty/rest requirements. This research involves controlled 'laboratory studies, simulations, and data collected during regular flight operations. When flight/duty/rest requirements are determined they are typically based on a variety of considerations, such as operational demand, safety, economic, etc. Rarely has the available, state-of-the-art science been a consideration along with these other factors when determining flight/duty/rest requirements. While the complexity of the operational demand and human physiology precludes an absolute solution, there is an opportunity to take full advantage of the current scientific data. Incorporating these data in a rational operational manner into flight/duty/rest requirements can improve flight crew performance, alertness, and ultimately, aviation safety.

Rosekind, Mark R.↗

NASA NTRS2000

Iterative Repair Planning for Spacecraft Operations Using the Aspen System

This paper describes the Automated Scheduling and Planning Environment (ASPEN). ASPEN encodes complex spacecraft knowledge of operability constraints, flight rules, spacecraft hardware, science experiments and operations procedures to allow for automated generation of low level spacecraft sequences. Using a technique called iterative repair, ASPEN classifies constraint violations (i.e., conflicts) and attempts to repair each by performing a planning or scheduling operation. It must reason about which conflict to resolve first and what repair method to try for the given conflict. ASPEN is currently being utilized in the development of automated planner/scheduler systems for several spacecraft, including the UFO-1 naval communications satellite and the Citizen Explorer (CX1) satellite, as well as for planetary rover operations and antenna ground systems automation. This paper focuses on the algorithm and search strategies employed by ASPEN to resolve spacecraft operations constraints, as well as the data structures for representing these constraints.

Rabideau, G.↗

NASA NTRS1999

Iterative Repair Planning for Spacecraft Operations Using the Aspen System

planning↗

DOE OSTI2019

A Click‐Chemistry‐Based Enrichable Crosslinker for Structural and Protein Interaction Analysis by Mass Spectrometry

Abstract Mass spectrometry is the method of choice for the characterisation of proteomes. Most proteins operate in protein complexes, in which their close association modulates their function. However, with standard MS analysis, information on protein–protein interactions is lost and no structural information is retained. To gain structural and interactome data, new crosslinking reagents are needed that freeze inter‐ and intramolecular interactions. Herein, the development of a new reagent, which has several features that enable highly sensitive crosslinking MS, is reported. The reagent enables enrichment of crosslinked peptides from the majority of background peptides to facilitate efficient detection of low‐abundant crosslinked peptides. Due to the special cleavable properties, the reagent can be used for MS 2 and potentially for MS 3 experiments. Thus, the new crosslinking reagent, in combination with high‐end MS, should enable sensitive analysis of interactomes, which will help researchers to obtain important insights into cellular states in health and diseases.

Biochemistry & Molecular Biology↗

DOE OSTI2019

Microstructural Modeling of the α + β Phase in Ti-6Al-4V: A Diffusion-Based Approach

Complex heat treatment operations and advanced manufacturing processes such as laser or electron-beam welding will see the metallic workpiece experience a considerable range of temperatures and heating/cooling rates. These intrinsic conditions will have a significant bearing upon the microstructure of the material, and in turn upon the thermo-mechanical properties. In this work, a diffusion-based approach to model the growth and shrinkage of precipitates in the alpha + beta field of the common titanium alloy Ti-6Al-4V is established. Further, the numerical model is extended using a JMA-type approach to explore the dependency of the beta-transus temperature on extremely high heating rates, whereby dissolution alone is too slow to accurately describe the alpha to beta-phase transformation. Experimental heat treatments at rates of 5, 50, and 500 °C/s were performed, and metallographic analysis of the samples was used to validate the numerical modeling framework predictions for lamellar shrinkage, while data from the literature has been used to evaluate the numerical modeling framework for the growth of equiaxed microstructures. The agreement between measurements and numerical predictions was found to be good.

36 MATERIALS SCIENCE↗