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Slide deck for Annual Merit Review event. Describes and presents the entire DirectXFC project, Overview, Relevance, Milestones, Approach, Technical Accomplishments, Future Research, Summary, and Collaborators.
The Hanford Site, Management of the Cesium and Strontium Capsules (MCSC) Project is preparing to place cesium and strontium material into dry storage using stainless steel canisters that are housed inside vertical concrete casks. Part of the site’s aging management program is to use a spare canister system as a leading indicator canister to provide advance warning for signs of chloride induced stress corrosion cracking (CISCC) or any other kind of canister degradation that might take place over the system’s 300-year design life. The Hanford Lead Canister (HLC) will use electric heaters to simulate the decay heat of cesium and strontium to ensure the HLC simulates the environment and conditions the capsule-loaded systems will experience. In addition to being part of the site’s aging management program, the HLC is being made available for research and development that advances the industry regarding canister mitigation and repair (M&R). The HLC system closely resembles current spent nuclear fuel (SNF) dry storage systems, making the HLC useful for demonstrating technologies or performing research that is relevant to SNF canisters . Several organizations are collaborating to prepare the HLC, along with technical strategy, to perform the needed research and development activities, to include the Pacific Northwest National Laboratory (PNNL), Central Plateau Cleanup Company (CPCCo), and the Electric Power Research Institute (EPRI). In one example of this collaborative research, EPRI is planning to use the HLC to demonstrate in-situ M&R technologies under controlled conditions before the HLC is deployed at Hanford. There is a period of several years when the HLC will be available for canister M&R activity before it is deployed. This paper describes the development of the HLC, its role in the Hanford site’s MCSC Project aging management program, and some of the research activities that are planned for the HLC.
We are entering a new era in space exploration. Reduced operating budgets require innovative solutions to leverage existing systems to implement the capabilities of future missions. Custom solutions to fulfill mission objectives are no longer viable. Can NASA adopt international standards to reduce costs and increase interoperability with other space agencies? Can legacy systems be leveraged in a service oriented architecture (SOA) to further reduce operations costs? The Operations Technology Facility (OTF) at the Johnson Space Center (JSC) is collaborating with Deutsches Zentrum fur Luft- und Raumfahrt (DLR) to answer these very questions. The Mission Operations and Information Management Services Area (MOIMS) Spacecraft Monitor and Control (SM&C) Working Group within the Consultative Committee for Space Data Systems (CCSDS) is developing the Mission Operations standards to address this problem space. The set of proposed standards presents a service oriented architecture to increase the level of interoperability among space agencies. The OTF and DLR are developing independent implementations of the standards as part of an interoperability prototype. This prototype will address three key components: validation of the SM&C Mission Operations protocol, exploration of the Object Management Group (OMG) Data Distribution Service (DDS), and the incorporation of legacy systems in a SOA. The OTF will implement the service providers described in the SM&C Mission Operation standards to create a portal for interaction with a spacecraft simulator. DLR will implement the service consumers to perform the monitor and control of the spacecraft. The specifications insulate the applications from the underlying transport layer. We will gain experience with a DDS transport layer as we delegate responsibility to the middleware and explore transport bridges to connect disparate middleware products. A SOA facilitates the reuse of software components. The prototype will leverage the capabilities of existing legacy systems. Various custom applications and middleware solutions will be combined into one system providing the illusion of a set of homogenous services. This paper will document our journey as we implement the interoperability prototype. The team consists of software engineers with experience on the current command, telemetry and messaging systems that support the International Space Station (ISS) and Space Shuttle programs. Emphasis will be on the objectives, results and potential cost saving benefits.
BACKGROUND: Communication delays are an inherent challenge of space missions to the Moon and beyond. Past research studies showed that 50+ second delays adversely affected individual well-being, team cohesion, and overall task performance (Kintz et al., 2016; Larson et al., 2019). However, there is a dearth of research on the effects of shorter delays (on the order of 4-12 seconds one-way) that may present a more immediate challenge during the upcoming Artemis missions. Even these shorter delays could make it difficult or infeasible for ground control to provide real-time support to Artemis astronauts, especially in complex and time-critical tasks such as extra-vehicular activities (EVAs). Results from studies on longer or Mars-like delays cannot be directly applied to Artemis-like delays, due to the large differences in delay magnitude and task types between these mission categories. For example, real-time oversight and guidance from ground control is impossible under Mars-like delays but may be performed under Artemis-like delays, albeit with potentially high workload and communication difficulty. Thus, a better understanding of the effects of Artemis-like communication delays on collaborative task performance is needed. Additionally, there is a need to develop reliable task paradigms that can be used in future studies on communication delays. METHODS: This project will study the effects of Artemis-like communication delays on collaborative task performance in a simulated space-to-ground team task via a lunar Gateway-like interface prototype. Teams of two astronaut-like participants - one serving as “crewmember” and one as “flight controller” - will perform a spaceflight-relevant task under six delay conditions (i.e., 0, 4, 6, 8, 10, and 12 seconds). Audio, video, texting, and file transfer will be delayed between the participants to mimic lunar-like communication delays. Measures related to workload, situation awareness, system usability, task performance, team cohesion, well-being, and communication strategies will be collected. These measures will be compared across delay levels, participant roles, and off-nominal and nominal tasks. Participants will be given the choice to use any combination of video and text communication in order to study preferences in interaction modality. RESEARCH AIMS: One aim is to identify a delay level or range of levels at which there may be significant decrements in individual and team-based measures. Identifying such ranges may help design novel workload management or communication countermeasures for future space missions. Also, the spaceflight-relevant research tasks and corresponding communication delay technology developed as part of this effort may be used for future studies on communication delays. Results from this work are also expected to inform study scenarios in the Human Exploration Research Analog (HERA) Campaign.
Abstract The high-luminosity upgrade of the Large Hadron Collider, scheduled to become operational in 2029, requires the replacement of the ATLAS Inner Detector with a new all-silicon Inner Tracker. Radiation hard n + -in-p micro-strip silicon sensors were developed by the ATLAS Inner Tracker strip collaboration and are produced by Hamamatsu Photonics K.K. Production of the total amount of 22000 strip sensors has started in 2020 and will continue until 2025. The ATLAS strip sensor collaboration has the responsibility to monitor the quality of the fabricated devices by performing detailed measurements of individual sensor characteristics and by comparing the obtained results with the tests done by the manufacturer. Dedicated Quality Control procedures were developed to check whether the delivered large-format sensors adhere to the ATLAS specifications. The institutes performing the Quality Control testing of the pre-production and production ATLAS ITk strip sensors had to initially be qualified for multiple high-throughput tests by successfully completing the Site Qualification process. The Quality Control procedures and the qualification process are described in this paper.
NASA’s GeneLab, part of the NASA Open Science Data Repository, is a space-related database that hosts a diverse range of transcriptomics, proteomics, epigenomics and genomics data. The NASA GeneLab Sample Processing Laboratory (SPL) generates omics data from biological experiments conducted aboard the International Space Station, Space Shuttle and space related ground experiments, this omics data then hosted on the GeneLab repository. Samples generated such experiments pose numerous technical challenges such as small experimental sample size, variance in dissection times, limited tissue preservation methods, prolonged storage time, and more. GeneLab SPL team had developed specialized expertise in nucleic acid extraction, library preparation and sequencing of such biological samples via extensive training and years of experience. In order to ensure data accuracy and consistency across experiments, SPL has developed standardized protocols for each species and tissue type. These protocols in conjunction with quality control metrics and data standards are crucial in generating of high-quality data. SPL protocols and standards have been developed in collaboration with the scientific community and had been made publicly available on the GeneLab portal, guaranteeing comparability of datasets across spaceflight experiments. To ensure reliability of data generation, SPL leverages cutting-edge innovations in laboratory automation for sample processing. By leveraging these state-of-the-art platforms, SPL achieves high levels of data reproducibility while significantly minimizing sources of bias and variability, especially across experiments with large numbers of samples. Over the past few years, the space biology investigator community has accessed SPL-generated data from the Open Science Data Repository for a myriad of data re-analysis and re-use studies. We observe a trend that in-house SPL-generated data consistently outperforms outsourced sequencing data in terms of technical standards, quality control metrics, timeliness of data delivery, and sequencing and reagent efficiency. Superior data generation has and will continue to enable discoveries in disease, diagnostic tools, and the biological effects of long duration spaceflight.
NASA’s GeneLab, part of the NASA Open Science Data Repository, is a space-related database that hosts a diverse range of transcriptomics, proteomics, epigenomics and genomics data. The NASA GeneLab Sample Processing Laboratory (SPL) generates omics data from biological experiments conducted aboard the International Space Station, Space Shuttle and space related ground experiments, this omics data then hosted on the GeneLab repository. Samples generated such experiments pose numerous technical challenges such as small experimental sample size, variance in dissection times, limited tissue preservation methods, prolonged storage time, and more. GeneLab SPL team had developed specialized expertise in nucleic acid extraction, library preparation and sequencing of such biological samples via extensive training and years of experience. In order to ensure data accuracy and consistency across experiments, SPL has developed standardized protocols for each species and tissue type. These protocols in conjunction with quality control metrics and data standards are crucial in generating of high-quality data. SPL protocols and standards have been developed in collaboration with the scientific community and had been made publicly available on the GeneLab portal, guaranteeing comparability of datasets across spaceflight experiments. To ensure reliability of data generation, SPL leverages cutting-edge innovations in laboratory automation for sample processing. By leveraging these state-of-the-art platforms, SPL achieves high levels of data reproducibility while significantly minimizing sources of bias and variability, especially across experiments with large numbers of samples. Over the past few years, the space biology investigator community has accessed SPL-generated data from the Open Science Data Repository for a myriad of data re-analysis and re-use studies. We observe a trend that in-house SPL-generated data consistently outperforms outsourced sequencing data in terms of technical standards, quality control metrics, timeliness of data delivery, and sequencing and reagent efficiency. Superior data generation has and will continue to enable discoveries in disease, diagnostic tools, and the biological effects of long duration spaceflight.
This project builds upon knowledge gained from previous projects on Additive Manufacturing (AM) operation, process control and monitoring, repeatability, and process improvement. This project will exclusively focus on metal powder bed additive manufacturing (PBAM). Objective 1: Advance metal powder bed AM R&D capabilities. Perform enhanced R&D on increased build volumes and throughput, safety and handling controls, process monitoring, and diagnostics with a focus on production end-states. Objective 2: Build upon knowledge gained from previous PDRD projects to develop deeper understanding of process controls, essential for transitioning metal AM processes for future applications. Objective 3: Maintain business development and research advantages through collaborations with external industry and university partners.
Superconducting qubits, originally developed for quantum computing, are emerging as a potentially powerful tool for detecting low-energy particle interactions, such as dark matter and neutrinos. These devices can register energy deposits as small as a few meV, dramatically lowering the detection threshold compared to conventional sensors. However, their deployment in rare-event searches is hampered by a critical and unresolved background: Two-Level Systems (TLSes). TLSes are material defects that can scramble qubit frequencies and coherence times in a way that resembles particle energy deposits. Such false signals can critically limit the sensitivity and extend experimental runtimes for qubit-based sensors by years. This talk introduces a novel method to eliminate TLSes as a background source in superconducting qubit-based detectors. By harnessing the Quantum Zeno Effect (QZE), a well-established quantum phenomenon where frequent observation inhibits system evolution, I will discuss the possibility of “freezing” these TLS defects in place. This effectively suppresses their interference, stabilizes qubit behavior, and opens the door to using TLSes themselves as auxiliary sensors. I have already identified target TLSes and observed early signs of QZE-like dynamics in Fermilab-fabricated devices. The method builds on my existing collaborations at Fermilab’s Quantum Information Testbed (QUIET), with access to low muon flux cryogenic facilities 100 meters underground, control electronics, and expert mentors across multiple institutions. By removing a key bottleneck to superconducting sensor deployment, this research targets advancing the development of a general-purpose technique to enhance sensitivity, reduce false positives, and accelerate discovery in searches for dark matter, neutrinos, and other rare phenomena.
The Environmental Health Unit, located on-site at the the Goddard Space Flight Center (GSFC), is responsible for the implementation of the Center's Employee Environmental and Occupational Health Program. The Health Unit, Health Physics (HP), and Industrial Hygiene (IH) staffs collaborate to provide quality service to the employees at GSFC. The Health Unit staff identifies, evaluates, and ensures the control of occupational hazards on the Center. In the past, components of the Industrial Hygiene Program have included the Industrial Hygiene Health Hazard Identification Program (IHHIP), the Hearing Conservation Program (HCP), the Hazard Communication Program, and the bi-annual fume hood survey. More recently, the Environmental Health Unit has expanded its services by adding the Ergonomics Program. Various aspects of the Ergonomics Program are discussed.
A new boundary condition is presented.for simulating the flow over passively porous surfaces. The model builds on the prior work of R.H. Bush to eliminate the need for constructing grid within an underlying plenum, thereby simplifying the numerical modeling of passively porous flow control systems and reducing computation cost. Code experts.for two structured-grid.flow solvers, TLNS3D and CFL3D. and one unstructured solver, USM3Dns, collaborated with an experimental porosity expert to develop the model and implement it into their respective codes. Results presented,for the three codes on a slender forebody with circumferential porosity and a wing with leading-edge porosity demonstrate a good agreement with experimental data and a remarkable ability to predict the aggregate aerodynamic effects of surface porosity with a simple boundary condition.
The NASA Swift mission is an innovative new multiwavelength observatory designed to determine the origin of gamma-ray bursts and use them to probe the early Universe. Swift is now in orbit since November 20, 2004 and all hardware is performing well. A new-technology wide-field gamma-ray camera is detecting a hundred bursts per year. Sensitive narrow-field X-ray and UV/optical telescopes, built in collaboration with UK and Italian partners, are pointed at the burst location in 50-100 sec by an autonomously controlled "swift" spacecraft. For each burst, arcsec positions are determined and optical/UV/X-ray/gamma-ray spectrophotometry performed. Information is also rapidly sent to the ground to a team of more than 50 observers at telescopes around the world. The first year and a half of findings from the mission will be presented. There has been a break-through in the long-standing mystery of short GRBs; they appear to be caused by merging neutron stars. High redshift bursts have been detected leading to a better understanding of star formation rates and distant galaxy environments. A fascinating nearby burst triggered Swift and enabled the best early-time observations of an emerging coincident Type lb/c supernova. GRBs have been found with giant X-ray flares occurring in their afterglow.
Gamma-ray bursts are among the most fascinating occurrences in the cosmos. They are thought to be the birth cries of black holes throughout the universe. The NASA swift mission is an innovative new multiwavelength observatory designed to determine the origin of bursts and use them to probe the early Universe. Swift is now in orbit since November 20, 2004 and all hardware is performing well. A new-technology wide-field gamma-ray camera is detecting a hundred bursts per year. sensitive narrow-field X-ray and uv/optical telescopes, built in collaboration with UK and Italian partners, are pointed at the burst location in 50-100 sec by an autonomously controlled "swift" spacecraft. For each burst, arcsec positions are determined and optical/UV/X-ray/gamma-ray spectrophotometry performed. Information is also rapidly sent to the ground to a team of more than 50 observers at telescopes around the world. The first year of findings from the mission will be presented. There has been a break-through in the longstanding mystery of short GRBs; they appear to be caused by merging neutron stars. High redshift bursts have been detected leading to a better understanding of star formation rates and distant galaxy environments. GRBs have been found with giant X-ray flares occurring in their afterglow.
Mission Statement: Concrete wall characterization for structural integrity evaluation of H-Canyon exhaust tunnel using a remote controlled robotic arm with a NDT Concrete Instrument. Challenges: Rough and Curved Surfaces, Remote location. The UR5 is a collaborative robotic arm capable of: Payload: 11 lbs (5 kg), Reach: 33.5 in (850 mm), Footprint: 5.87 in (149 mm) diameter, Weight: 45.4 Ibs (20.6 kg). The force torque sensor reacts to a set value inputted by the user that can be utilized for sensitive products. This allows the UR5 to react to surfaces using the built-in function to search for a wall and orient itself normal to that plane. The Proceq Pundit 250 array is a nondestructive device that the user applies against a concrete wall and scans using ultrasonic transducers. The back wall and other defects can be show through the touchscreen. A fixture to hold the Proceq Pundit 250 array onto the UR5 robotic arm was designed and 3D printed. It includes openings for easy access to the buttons from the Pundit array as well as a reinforced structural design. The scan from the Pundit array can show the back-wall, rebars, and other defects to assist in determining the structural integrity. In order to scan, a program was made to search for the wall first. 1. The UR5 robotic arm will go to the desired location away from the wall. 2. It will then search for the wall by moving towards it slowly. 3. After contact, the force applied will slowly but steadily increase to a preset value inputted by the user. 4. The force torque sensor will use those values and communicate with the UR5 by adjusting the arm to become normal to the wall. 5. The arm will then apply force to push back the transducers on the Pundit array to avoid gaps. 6. It will then prompt the user to collect data and wait until finished. The UR5 teach pendant allows the user to program the robot to perform automated and repeatable tasks. It includes a free drive mode which allows the user to move the arm to a desired position by hand. The user can also apply restricted planes which include either stopped or slower motion to ensure safety. The concrete sample being tested includes rebars and different grades of surface roughness to understand the readings from the Proceq Pundit 250 array. Desired concrete samples are currently being fabricated that will simulate the terrain being tested.
Many scientific disciplines rely on computational methods for data analysis, model generation, and prediction. Implementing these methods is often accomplished by researchers with domain expertise but without formal training in software engineering or computer science. This arrangement has led to underappreciation of sustainability and maintainability of scientific software tools developed in academic environments. Some software tools have avoided this fate, including the scientific library Rosetta. We use this software and its community as a case study to show how modern software development can be accomplished successfully, irrespective of subject area. Rosetta is one of the largest software suites for macromolecular modeling, with 3.1 million lines of code and many state-of-the-art applications. Since the mid 1990s, the software has been developed collaboratively by the RosettaCommons, a community of academics from over 60 institutions worldwide with diverse backgrounds including chemistry, biology, physiology, physics, engineering, mathematics, and computer science. Developing this software suite has provided us with more than two decades of experience in how to effectively develop advanced scientific software in a global community with hundreds of contributors. Here we illustrate the functioning of this development community by addressing technical aspects (like version control, testing, and maintenance), community-building strategies, diversity efforts, software dissemination, and user support. We demonstrate how modern computational research can thrive in a distributed collaborative community. The practices described here are independent of subject area and can be readily adopted by other software development communities
The Integrated Health Management (IHM) for the future aerospace systems requires to interface models of multiple subsystems in an efficient and accurate information environment at the earlier stages of system design. The complexity of modern aeronautic and aircraft systems (including e.g. the power distribution, flight control, solid and liquid motors) dictates employment of hybrid models and high-level reasoners for analysing mixed continuous and discrete information flow involving multiple modes of operation in uncertain environments, unknown state variables, heterogeneous software and hardware components. To provide the information link between key design/performance parameters and high-level reasoners we rely on development of multi-physics performance models, distributed sensors networks, and fault diagnostic and prognostic (FD&P) technologies in close collaboration with system designers. The main challenges of our research are related to the in-flight assessment of the structural stability, engine performance, and trajectory control. The main goal is to develop an intelligent IHM that not only enhances components and system reliability, but also provides a post-flight feedback helping to optimize design of the next generation of aerospace systems. Our efforts are concentrated on several directions of the research. One of the key components of our strategy is an innovative approach to the diagnostics/prognostics based on the real time dynamical inference (DI) technologies extended to encompass hybrid systems with hidden state trajectories. The major investments are into the multiphysics performance modelling that provides an access of the FD&P technologies to the main performance parameters of e.g. solid and liquid rocket motors and composite materials of the nozzle and case. Some of the recent results of our research are discussed in this chapter. We begin by introducing the problem of dynamical inference of stochastic nonlinear models and reviewing earlier results. Next, we present our analytical approach to the solution of this problem based on the path integral formulation. The resulting algorithm does not require an extensive global search for the model parameters, provides optimal compensation for the effects of dynamical noise, and is robust for a broad range of dynamical models. In the following Section the strengths of the algorithm are illustrated illustrated by inferring the parameters of the stochastic Lorenz system and comparing the results with those of earlier research. Next, we discuss a number of recent results in application to the development of the IHM for aerospace system. Firstly, we apply dynamical inference approach to a solution of classical three tank problems with mixed unknown continuous and binary parameters. The problem is considered in the context of ground support system for filling fuel tanks of liquid rocket motors. It is shown that the DI algorithm is well suited for successful solution of a hybrid version of this benchmark problem even in the presence of additional periodic and stochastic perturbation of unknown strength. Secondly, we illustrate our approach by its application to an analysis of the nozzle fault in a solid rocket motor (SRM). The internal ballistics of the SRM is modelled as a set of one-dimensional partial differential equations coupled to the dynamics of the propellant regression. In this example we are specifically focussed on the inference of discrete and continuous parameters of the nozzle blocking fault and on the possibility of an application of the DI algorithm to reducing the probability of "misses" of an on-board FD&P for SRM. In the next section re-contact problem caused by first stage/upper stage separation failure is discussed. The reaction forces imposed on the nozzle of the upper stage during the re-contact and their connection to the nozzle damage and to the thrust vector control (TVC) signal are obtained. It is shown that transient impact induced torquean be modelled as a response of an effective damped oscillator. A possible application of the DI algorithm to the inference of damage parameters and predicting fault dynamics ahead of time using the actuator signal is discussed. Finally, we formulate Bayesian inferential framework for development of the IHM system for in-flight structural health monitoring (SHM) of composite materials. We consider the signal generated by piezoelectric actuator mounted on composite structure generating elastic waves in it. The signal received by the sensor is than compared with the baseline signal. The possibility of damage inference is discussed in the context of development of the SHM.
The US and UK share the vision for fusion as a vital part of the clean energy future. This vision is reflected in the respective national plans in the form of the Bold Decadal Vision for Commercial Fusion (BDV) in the US and the Spherical Tokamak for Energy Production (STEP) program in the UK. Digital tools such as simulation and control frameworks, design tools, AI/ML, high performance computing (HPC), and virtual reality (VR) will play an important role in developing, diagnosing, operating, and further improving burning-plasma-class fusion power plants. Therefore, a collaborative approach, involving both the public and private sectors, to developing these digital tools can accelerate the path to fusion energy commercialization. In this report we discuss previous and ongoing collaborations and opportunities to expand these collaborations into new areas. We conclude this report with near term actions and a vision of the collaboration to the Joint Coordinating Committee.
Spatial mapping of 1D, 2D, and particularly 3D thermal boundary condition data is essential for accurate thermal simulation of spacecraft and launch vehicles. This information typically is available in simple ASCII file format but can be problematic to use for thermal simulations. Difficulties that can be encountered include the ability to directly use the available file format, transformation of the data into the desired reference coordinate system in 3D space, and accurate interpolation of the data onto the thermal calculation domain. This paper presents a streamlined approach to spatial mapping of complex unsymmetrical 3D cold wall heat flux data using the fields’ capability in Simcenter3D. A recent example of 3D thermal plume simulation at MSFC will be employed to illustrate the use of text, csv, and Excel files, specifying coordinate systems for transformation of data in 3D space, and use of the various interpolation schemes available for spatial mapping. Spatial boundary condition verification is also very important, and the spacecraft thermal analyst needs effective visualization tools to develop confidence in the boundary condition definitions. Visualization of the spacecraft plume raw field data, the calculated field data, and the interpolated field data onto the thermal calculation domain will be discussed, with a particular focus on real-time viewing of the interpolated data for available interpolation schemes. The objective of this paper is to outline the modeling techniques used with the integrated thermal analysis of a terrestrial lunar lander demonstrator. Specifically, the techniques outlined herein focus on spatial mapping of convective and radiative exhaust plume results from a computational fluid dynamics (CFD) analysis. Two cases were investigated, however, the modeling techniques that were utilized translate to both cases seamlessly. Those two cases were as follows: • Lunar lander demonstrator firing on-pad (worst case). • Lunar lander demonstrator hovering at an elevated position above the launch pad. For the purposes of information control, this paper will focus on the modeling techniques only, using altered or dimensionless data where necessary. BACKGROUND The thermal model examined in this paper is of the lunar lander demonstrator known as XL-1T (terrestrial), born from a collaborative effort between Masten Space Systems (MSS) and NASA, under NASA’s Lunar CATALYST (also known as Lunar Cargo Transportation and Landing by Soft Touchdown) initiative. The lander is a reusable vertical takeoff/vertical landing (VTVL) test bed which is controlled by four throttleable main engines utilizing green hypergolic propellants.