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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Radiation Damage Analysis of FNSF Components Using McCad and MCNP

The Fusion Energy System Studies Fusion Nuclear Science Facility (FESS-FNSF) concept represents a transitional step between ITER and a commercial fusion power plant. The FNSF is a conceptualized D-T fueled tokamak with 518 MW of fusion power that has been extensively used to explore and optimize design features. The energetic 14.1-MeV neutrons can produce significant localized heating and activations, and can cause damage to plasma-facing components, which can determine maintenance/outage scheduling needs and also impact the lifetime of the device as a whole. This study illustrates a neutronics analysis that was conducted on a 22.5-degree symmetric sector of the FNSF with the goal of understanding the neutron heating and radiation damage that can be characterized by quantifying the displacements per atom (dpa). Concurrently, this study also focused on the development of analysis capabilities by converting a three-dimensional computer-aided design model of the FNSF into MCNP6.2 input using the McCad code. Accordingly, some confirmatory results on tritium production and the tritium breeding ratio (TBR) are provided to support model validation. The results produced by MCNP6.2 simulations showed that the highest heating and damage occurred in the outboard region, which concentrated approximately 290 MW of the total nuclear heating, in contrast to 97 MW within the inboard region. These results are consistent with previous studies that employed earlier versions of the FNSF concept and different modeling approaches. Furthermore, this study also provides additional details on neutron wall loading, as well as total heating from neutrons and gammas, results which show the total heating of the device (16 sectors) is approximately 477.83 ± 0.80% MW, indicating a neutron energy multiplication factor of 1.15. Additionally, the capability to calculate hydrogen and helium production, as well as dpa, is illustrated. Finally, the neutronics effects of using alternative materials to tungsten carbide were evaluated for the vacuum vessel, low-temperature shield, and structural ring components, which showed that compounds like YH 2 , Mg(BH 4 ) 2 , and ZrH 2 could reduce the total heating on the magnet and also reduce the TBR.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

EJFAT: Towards Intelligent Compute Destination Load Balancing

To handle increased data flow, Jefferson Lab (JLab) is partnering with ESnet for development of an AI/ML directed compute work Load Balancer (LB) of UDP streamed data. The LB is FPGA based featuring dynamically configurable, low latency and high throughput destination address switching. The LB provides integration of edge and core computing to support JLab experimental programs, the Electron-Ion Collider, as well as data centers of the future. In the ESnet/JLab FPGA Accelerated Transport (EJFAT) initiative, the function of the LB Data Plane (DP) is to redirect data streams to selectable (but unknown to sender) destination hosts based on current worload and within that host to destination ports as a function of sub- stream id. This effects hierarchical scaling, first across compute machines for processing over a series of events and second, across ports so different data source sub-streams may be assigned to different processors for further parallelization. The LB Control Plane (CP) programs the DP using compute farm telemetry to direct and balance workloads across a compute cluster as the operating conditions require. While Proportional/Integrative/Derivative (PID) controllers are often seen in similar applications, here we investigate the feasibility of a Reinforcement Learning (RL) based schedule manager running in the CP to provide dynamic updates to the DP scheduling policy.

Lawrence, David↗
DOE OSTI2023

Deployment of Dynamic Neural Network Optimization to Minimize Heat Rate During Ramping for Coal Power Plants (Final Technical Report)

Much success was achieved throughout the course of this project. A successful implementation of Dynamic Neural Network Optimization (D-NNO) was coupled with Adaptive Predictive Controls (APC) and a novel hardware installation comprised of an advanced sensor network (ASN) measuring mass-weighted averages of flue gas constituents above the horizontal superheater of a coal-fired utility boiler. From 2019 through 2023 (including an extension due to COVID delays), the team was able to prototype, evaluate, deploy, iterate, and ultimately finalize an advanced closed-loop control D-NNO system which demonstrated the ability to: •improve unit efficiency ~2.0% relative to unoptimized operation (represented as total fuel fired per MWh generated) •improve unit NOx emission rates 10%+ beyond static optimization baselines •improve unit temperature stability as much as 58% and on average 12% •improve operating load stability as much as 35% The culmination of this project has generated an advanced methodology of deploying specially designed recurrent neural networks (long short-term memory, gated recurrent unit, encoder-decoder networks, transformers, etc.), customized trajectory planning and closed-loop optimization modules capable of adapting to live electric grid responses and demands, self-tuning and adaptive expert controls constantly adjusting prediction parameters to real-time unit behavior, and a hardware/software package able to reliably calculate net unit heat rate (NUHR) in real-time using flue gas constituents, machine learning, and known combustion relationships. Through this real-time NUHR value, immediate feedback on system adjustments relative to operating efficiency was available, allowing for rapid improvements to system performance. In addition to development and deployment of the advanced D-NNO system, the approach methodology has been readily commercialized through the project platform Griffin Open Systems, LLC, the D-NNO software platform host. Similar methodologies to those developed by this project have already been deployed at 5 other units across the United States, with another 6 implementations scheduled, and more expected. Over the course of the project, multiple academic papers were submitted and accepted for publication within esteemed academic journals, and PhD students were trained and graduated, as well as undergraduate students becoming involved and participating to project objectives.

01 COAL, LIGNITE, AND PEAT↗
NASA NTRSDate not supplied

BRAINSTACK – A Platform for Artificial Intelligence & Machine Learning Collaborative Experiments on a Nano-Satellite

As space missions continue to become more ambitious, complex, and distant to Earth, the need for advanced on-board intelligent decision making to guide everything from mission operations to fault detection and recovery has become a major front of space research. While the prevalence of research on such Artificial Intelligence / Machine Learning (AI/ML) modules has exploded, the capacity to experimentally validate such modules in space in a rapid and inexpensive format has not. To this end, the Nano Orbital Workshop (NOW) group at NASA Ames Research Center has been at the forefront of performing initial flight evaluation tests of ‘commercially’ available AI/ML computational platforms via the TechEdSat (TES-n) flight series as part of what is programmatically referred to as the BRAINSTACK. BRAINSTACK will provide an orbital AI/ML evaluation laboratory where computational experiments are pre-loaded into memory prior to launch, and then executed as desired during the mission, with results reported back and program tweaks or new data sets uploaded as needed. Processors selected as part of the BRAINSTACK are of ideal size, packaging, and power consumption for easy integration into a cube satellite structure. These experiments have included the evaluation of small, high-performance GPUs and more recently, neuromorphic processors in LEO operations. Neuromorphic processors are of particular interest due to their superior computational power efficiency over GPUs. The first TES-n flight test of an Intel first-generation Loihi neuromorphic processor launched on January 13, 2022 and continues to operate in orbit despite almost no space environment modifications. The Intel Loihi Gen-1 is characterized by a 14nm 128-core Spiking Neural Network (SNN) able to support on-chip training. This experiment utilized a Loihi packaged in the ‘Kapoho Bay’ USB module, providing a relatively straight-forward interface to the bus avionics system. The Kapoho Bay was in turn managed by a host Intel Pentium single-board computer to handle scheduling of the AI/ML application payloads, and communications with the satellite vehicle manager. The recently released Intel Loihi Gen-2, able to support integer-valued spike payloads and produced using 7nm process, will form part of the basis of the evolving BRAINSTACK in the upcoming three TES-n/NOW flights. Additionally, it is planned to measure the radiation environment these processors experience to understand any degradation or computational artifacts caused by long term space radiation exposure on these novel architectures. This evolving flexible and collaborative environment involving various research teams across NASA and other organizations is intended to be a convenient orbital test platform from which many anticipated future space AI/ML applications may be initially tested.

Artificial Intelligence↗
NASA NTRSDate not supplied

BRAINSTACK – A Platform for Artificial Intelligence & Machine Learning Collaborative Experiments on a Nano-Satellite

As space missions continue to become more ambitious, complex, and distant to Earth, the need for advanced on-board intelligent decision making to guide everything from mission operations to fault detection and recovery has become a major front of space research. While the prevalence of research on such Artificial Intelligence / Machine Learning (AI/ML) modules has exploded, the capacity to experimentally validate such modules in space in a rapid and inexpensive format has not. To this end, the Nano Orbital Workshop (NOW) group at NASA Ames Research Center has been at the forefront of performing initial flight evaluation tests of ‘commercially’ available AI/ML computational platforms via the TechEdSat (TES-n) flight series as part of what is programmatically referred to as the BRAINSTACK. BRAINSTACK will provide an orbital AI/ML evaluation laboratory where computational experiments are pre-loaded into memory prior to launch, and then executed as desired during the mission, with results reported back and program tweaks or new data sets uploaded as needed. Processors selected as part of the BRAINSTACK are of ideal size, packaging, and power consumption for easy integration into a cube satellite structure. These experiments have included the evaluation of small, high-performance GPUs and more recently, neuromorphic processors in LEO operations. Neuromorphic processors are of particular interest due to their superior computational power efficiency over GPUs. The first TES-n flight test of an Intel first-generation Loihi neuromorphic processor launched on January 13, 2022 and continues to operate in orbit despite almost no space environment modifications. The Intel Loihi Gen-1 is characterized by a 14nm 128-core Spiking Neural Network (SNN) able to support on-chip training. This experiment utilized a Loihi packaged in the ‘Kapoho Bay’ USB module, providing a relatively straight-forward interface to the bus avionics system. The Kapoho Bay was in turn managed by a host Intel Pentium single-board computer to handle scheduling of the AI/ML application payloads, and communications with the satellite vehicle manager. The recently released Intel Loihi Gen-2, able to support integer-valued spike payloads and produced using 7nm process, will form part of the basis of the evolving BRAINSTACK in the upcoming three TES-n/NOW flights. Additionally, it is planned to measure the radiation environment these processors experience to understand any degradation or computational artifacts caused by long term space radiation exposure on these novel architectures. This evolving flexible and collaborative environment involving various research teams across NASA and other organizations is intended to be a convenient orbital test platform from which many anticipated future space AI/ML applications may be initially tested.

Artificial Intelligence↗
NASA NTRS2012

James Webb Space Telescope Integrated Science Instrument Module Calibration and Verification of High-Accuracy Instrumentation to Measure Heat Flow in Cryogenic Testing

The James Webb Space Telescope (JWST) is an upcoming flagship observatory mission scheduled to be launched in 2018. Three of the four science instruments are passively cooled to their operational temperature range of 36K to 40K, and the fourth instrument is actively cooled to its operational temperature of approximately 6K. The requirement for multiple thermal zoned results in the instruments being thermally connected to five external radiators via individual high purity aluminum heat straps. Thermal-vacuum and thermal balance testing of the flight instruments at the Integrated Science Instrument Module (ISIM) element level will take place within a newly constructed shroud cooled by gaseous helium inside Goddard Space Flight Center's (GSFC) Space environment Simulator (SES). The flight external radiators are not available during ISIM-level thermal vacuum/thermal testing, so they will be replaced in test with stable and adjustable thermal boundaries with identical physical interfaces to the flight radiators. Those boundaries are provided by specially designed test hardware which also measures the heat flow within each of the five heat straps to an accuracy of less than 2 mW, which is less than 5% of the minimum predicted heat flow values. Measurement of the heat loads to this accuracy is essential to ISIM thermal model correlation, since thermal models are more accurately correlated when temperature data is supplemented by accurate knowledge of heat flows. It also provides direct verification by test of several high-level thermal requirements. Devices that measure heat flow in this manner have historically been referred to a "Q-meters". Perhaps the most important feature of the design of the JWST Q-meters is that it does not depend on the absolute accuracy of its temperature sensors, but rather on knowledge of precise heater power required to maintain a constant temperature difference between sensors on two stages, for which a table is empirically developed during a calibration campaign in a small chamber at GSFC. This paper provides a brief review of Q-meter design, and discusses the Q-meter calibration procedure including calibration chamber modifications and accommodations, handling of differing conditions between calibration and usage, the calibration process itself, and the results of the tests used to determine if the calibration is successful.

Comber, Brian↗
NASA NTRS2015

Tropospheric Emissions: Monitoring of Pollution Overview

TEMPO is now well into its implementation phase, having passed both its Key Decision Point C and the Critical Design Review (CDR) for the instrument. The CDR for the ground systems will occur in March 2016 and the CDR for the Mission component at a later date, after the host spacecraft has been selected. TEMPO is on schedule to measure atmospheric pollution for greater North America from space using ultraviolet and visible spectroscopy. TEMPO measures from Mexico City to the Canadian oil sands, and from the Atlantic to the Pacific, hourly and at high spatial resolution. TEMPO provides a tropospheric measurement suite that includes the key elements of tropospheric air pollution chemistry. Measurements are from geostationary (GEO) orbit, to capture the inherent high variability in the diurnal cycle of emissions and chemistry. The small product spatial footprint resolves pollution sources at sub-urban scale. Together, this temporal and spatial resolution improves emission inventories, monitors population exposure, and enables effective emission-control strategies. TEMPO takes advantage of a GEO host spacecraft to provide a modest cost mission that measures the spectra required to retrieve O3, NO2, SO2, H2CO, C2H2O2, H2O, aerosols, cloud parameters, and UVB radiation. TEMPO thus measures the major elements, directly or by proxy, in the tropospheric O3 chemistry cycle. Multi-spectral observations provide sensitivity to O3 in the lowermost troposphere, substantially reducing uncertainty in air quality predictions by 50 percent. TEMPO quantifies and tracks the evolution of aerosol loading. It provides near-real-time air quality products that will be made widely, publicly available. TEMPO provides much of the atmospheric measurement capability recommended for GEO-CAPE in the 2007 National Research Council Decadal Survey, Earth Science and Applications from Space: National Imperatives for the Next Decade and Beyond. Instruments from Europe (Sentinel 4) and Asia (GEMS) will form parts of a global GEO constellation for pollution monitoring later this decade, with a major focus on intercontinental pollution transport. TEMPO will launch at a prime time to be a component of this constellation.

Chance, Kelly↗
NASA NTRS2004

Preliminary Interpretation of Ambient Pickup Ions at Titan Observed by the Cassini Plasma Spectrometer

The Cassini Plasma Spectrometer (CAPS) instrument is scheduled to observe the plasma environment at Titan October 26,2004 from the Cassini Orbiter. Preliminary CAPS ion measurements from this encounter will be compared with measurements made by the Voyager I Plasma Science Instrument (PSI). The comparison will be used to evaluate previous interpretations and predictions of the Titan plasma environment that have been made using PSI measurements. The comparisons will focus on the composition and nature of the ambient plasma and pickup ions. Using the CAPS ion measurements, some of the questions to be addressed, as stimulated by the previous interpretations and predictions made evaluating PSI data, are the following: A) Are H+ and N+ the major ion components of Saturn's rotating magnetosphere in the vicinity of Titan? B) Are other ambient ions present? C) Are finite gyroradius effects apparent in ambient N+ as the result of its interaction with Titans atmosphere? D) Are the principal pickup ions composed of H+, H2+, N+, N2+ and CH4+? E) Is the dominant pickup ion closest to Titan's ionopause N2+? F) Is there evidence of slowing down of the ambient plasma due to pickup ion mass loading? F) If so, does the ambient plasma slow down rapidly, as the ionopause is approached and heavier pickup ions like N2+ are added? During the Voyager I flyby, Titan was in Saturn's magnetosphere. If Titan is in Saturn's magnetosheath or the solar wind at the encounter, questions similar to the above will be addressed as appropriate.

Hartle, R. E.↗
DOE OSTI2026

From Cell to System: Accelerated hpc Simulations of BESS Aging under Frequency Regulation and Arbitrage use cases

Lithium-ion battery energy storage systems (BESS) packs have emerged as a leading solution for grid-scale energy storage, enhancing resiliency and balancing load fluctuations. Yet, experimental characterization of large-format LIB packs-particularly to assess performance and degradation over hundreds of cycles - demands substantial hardware investment and multi-year testing campaigns. In this work, we couple a hierarchical, physics-based modeling framework agnostic to electrode chemistries with high-performance computing to accelerate systems level evaluation by upto two orders of magnitude. Building on the open-source liionpack platform, we implement cell, module, and pack-scale electrochemical models enriched with mechanistic aging mechanisms and deploy them on an HPC cluster to simulate 150−200kWh systems over 500 - 1,000 cycles with in days. We subject these virtual B ESS to both constant-current cycling and realistic grid service profiles spanning frequency regulation, ramp-rate support, and energy arbitrage-and quantify the resulting degradation patterns. Our results reveal that localized cell aging can induce substantial nonuniformity at module and pack levels, with service-specific cycling protocols driving distinct aging modes. This rapid, multiscale modeling approach provides a powerful design-space exploration tool for optimizing electrical architecture, control strategies, and operational schedules to prolong pack lifetime and lower total cost of ownership.

Ayalasomayajula, Surya [ORNL] (ORCID:0009000860788↗
DOE OSTI2024

MICROREACTOR APPLICATIONS, RESEARCH, VALIDATION, AND EVALUATION (MARVEL) REACTOR ? STATUS, CONSTRUCTION, AND TESTING

The paper presents the current status of the Microreactor Applications, Research, Validation, and Evaluation (MARVEL) microreactor design, qualification testing, fabrication, and high-level construction schedule. An overview of initial criticality, low power physics testing, and start-up testing is included, as well as an overview of the envisioned processes in which end-users can engage the project for access to operational data or specific demonstrations. Designed by the Idaho National Laboratory (INL) under the auspices of the US Department of Energy’s Microreactor Program for construction and operation at the INL, MARVEL is a small, fully functional advanced reactor with UZrH fuel and thermal output of 85 kW. It offers a unique opportunity for scaled demonstrations that can dramatically accelerate the design, licensing, and deployment of commercial microreactors for power production or process heat applications. MARVEL’s objective is to build a small liquid-metal thermal reactor at the INL to demonstrate design and operating processes for microreactors, microgrid integration, and process heat applications. MARVEL finished 90%-final-design in September 2023 and completed an independent project assessment in early 2024. Fabrication of long-lead components and fuel, safety analysis review, and procurement for construction are underway. MARVEL assembly and construction will start in 2025 and fuel loading is expected in mid- 2027. Initial criticality will be performed in a dry condition in late 2027, followed by loading of NaK coolant and start-up testing. Approximately six months later, release for unrestricted operations will enable subsequent testing of microreactor characteristics, microgrid integration and select heat extraction applications.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1994

Martian environmental simulation for a deployable lattice mast

The Mars Pathfinder mission (formerly Mars Environmental Survey or MESUR) is scheduled for launch in December 1996 and is designed to place a small lander on the surface of Mars. After impact, the lander unfolds to expose its solar panels and release a miniature rover. Also on board is the Imager for Mars Pathfinder (IMP) binocular camera which is elevated by a deployable mast to obtain a panoramic view of the landing area. The design of this deployable mast is based on similar designs which have a long and successful flight history. In the past when this type of self-deployable mast has been used, a rate limiter has been incorporated to control the speed of deployment. In this application, to reduce weight and complexity, it was proposed to eliminate the rate limiter so that the mast would deploy without restraint. Preliminary tests showed that this type of deployment was possible especially if the deployed length was relatively short, as in this application. Compounding the problem, however, was the requirement to deploy the mast at an angle of up to 30 degrees from vertical. The deployment process was difficult to completely analyze due to the effects of gravitational and inertial loads on the mast and camera during rapid extension. Testing in a realistic manner was imperative to verify the system performance. A deployment test was therefore performed to determine the maximum tilt angle at which the mast could reliably extend and support the camera on Mars. The testing of the deployable mast requires partial gravity compensation to simulate the smaller force of Martian gravity. During the test, mass properties were maintained while weight properties were reduced. This paper describes the testing of a deployable mast in a simulated Martian environment as well as the results of the tests.

Warden, Robert M.↗
NASA NTRS2003

Dual-Spool Turbine Facility Design Overview

The next generation of aircraft engines, both commercial and military, will attempt to capitalize on the benefits of close-coupled, vaneless, counter-rotating turbine systems. Experience has shown that significant risks and challenges are present with close-coupled systems in terms of efficiency and durability. The UEET program needs to demonstrate aerodynamic loading and efficiency goals for close-coupled, reduced-stage HP/LP turbine systems as a Level 1 Milestone for FY05. No research facility exists in the U.S. to provide risk reduction for successful development of close-coupled, high and low pressure turbine systems for the next generations of engines. To meet these objectives, the design, construction, and integrated systems testing of a Dual-Spool Turbine Facility (DSTF) facility has been initiated at the NASA Glenn Research Center. The facility will be a warm (-IOOO'F), continuous flow facility for overall aerodynamic performance and detailed flow field measurement acquisition. The facility will have state-of-the-art instrumentation to capture flow physics details. Accurate and reliable speed control will be achieved by utilizing the existing Variable Frequency Drive System. Utilization of this and other existing GRC centralized utilities will reduce the overall construction costs. The design allows for future installation of a turbine inlet combustor profile simulator. This presentation details the objectives of the facility and the concepts used in specifying its capabilities. Some preliminary design results will be presented along with a discussion of plans and schedules.

Giel, Paul↗
NASA NTRS2007

Optomechanical Design and Analysis Considerations on the Lunar Orbiter Laser Altimeter

This paper presents the mechanical design and analysis work completed on the Lunar Orbiter Laser Altimeter (LOLA). LOLA is one of six instruments on the Lunar Reconnaissance Orbiter (LRO), scheduled to launch in 2008. LOLA's main objective is to produce a high-resolution global lunar topographic model to aid in safe landings and enhance surface mobility in future exploration missions. LOLA will also look for evidence of ice water in the permanently shadowed regions around the lunar poles. Beryllium was chosen as the primary material for the LOLA Optical Transmitter Assembly to take advantage of the material's low mass density for light weight optical instrument design and for CTE matching of the refractive optical components. In addition, the thermal conductivity and specific heat of beryllium minimizes thermal gradients and thermal excursions. Special consideration must be made for the planning and preparation to fabricate beryllium components, as well as the preparation and cleaning of the components for gold plating. Assembly challenges include handling, precision cleaning and integration and testing. Structural analysis considerations include following General Environmental Verification Specification (GEVS) guidelines for GSFC payloads. The GEVS random environment for LOLA has an acceptance level of 10.0 Grms, which was analyzed for higher frequency transients. The low frequency transients were analyzed using a Mass Acceleration Curve to obtain an equivalent static loading. In addition, Structural-Thermal-Optical analysis, commonly referred to as STOP analysis, was completed to predict optical performance under the instrument's operational thermal environment. This included stress and distortion analysis on the receiver telescope lens.

Schmidt. Stephen↗
NASA NTRS2023

BRAINSTACK – A Platform for Artificial Intelligence & Machine Learning Collaborative Experiments on a Nano-Satellite

As the space economy continues to expand through increasingly easy access to advanced and inexpensive technology, space missions themselves have become more ambitious with exploration targets growing ever distant while simultaneously requiring larger guidance and communication budgets. These conflicting desires of distance and control drive the need for advanced on-board intelligent decision making to reduce communication and control limitations by automating as many mission functions as possible in-situ. While the amount of research on such Artificial Intelligence and Machine Learning (AI/ML) software modules has grown exponentially, the capacity to experimentally validate such software modules in space in a rapid and inexpensive format has not. To this end, the Nano Orbital Workshop (NOW) group at NASA Ames Research Center has been at the forefront of performing initial flight evaluation tests of ‘commercially’ available bleeding-edge computational platforms via what is programmatically referred to as the BrainStack on the TechEdSat (TES-n) flight series. This on-orbit computational platform provides an evaluation laboratory where advanced software experiments are pre-loaded into memory prior to launch, then executed as payloads during mission operations with results reported back and program tweaks or new training sets uploaded as needed. Processors selected as part of the BrainStack are of ideal size, packaging, and power consumption for easy integration into a cube satellite structure. These experiments have included the evaluation of small, high-performance GPUs and, more recently, neuromorphic processors, in LEO operations. Neuromorphic processors are of particular interest due to their superior power efficiency over GPUs in intelligent automation applications. The first TES-n flight test of an Intel first-generation Loihi neuromorphic processor launched on TES-13, January 13, 2022, and continues to operate in orbit despite no significant modifications to harden the processor against the space environment. The Intel Loihi Gen-1 on TES-13 is characterized by a 14nm 128-core Spiking Neural Network (SNN) able to support on-chip training. The processor is packaged in the Kapoho Bay USB module, providing a relatively straight-forward interface to the bus avionics system. The Kapoho Bay was in turn managed by an Intel Pentium single-board computer to handle scheduling of the software application payloads and communications with the satellite’s primary computer. The recently released Intel Loihi Gen-2, able to support integer-valued spike payloads and produced using 7nm process, will form part of the continually evolving BrainStack in the upcoming three TES-n/NOW flights. The Kapoho Point unit will incorporate eight Loihi-2 processors, enabling neural networks of up to one million neurons and one billion synapsis. Additionally, it is planned to measure the radiation environment these processors experience to understand any degradation or computational artifacts caused by long term space radiation exposure on these novel architectures. This evolving flexible and collaborative environment involving various research teams across NASA and other organizations is intended to be a convenient orbital test platform from which many anticipated future space automation applications may be initially tested.

Artificial Intelligence↗
NASA NTRS2004

Reconditioning of Batteries on the International Space Station

Primary source of electric power for the International Space Station (ISS) is the photovoltaic module (PVM). At assembly complete stage, the ISS will be served by 4 PVMs. Each PVM contains two independent power channels such that one failure will result in loss of only one power channel. During early stages of assembly, the ISS is served by only one PVM designated as P6. Solar arrays are used to convert solar flux into electrical power. Nickel hydrogen batteries are used to store electrical power for use during periods when the solar input is not adequate to support channel loads. Batteries are operated per established procedures that ensure that they are maintained within specified temperature limits, charge current is controlled to conform to a specified charge profile, and battery voltages are maintained within specified limits. Both power channels on the PVM P6 have been operating flawlessly since December 2000 with 100 percent power availability. All components, including batteries, are monitored regularly to ensure that they are operating within specified limits and to trend their wear out and age effects. The paper briefly describes the battery trend data. Batteries have started to show some effects of aging and a battery reconditioning procedure is being evaluated at this time. Reconditioning is expected to reduce cell voltage divergence and provide data that can be used to update the state of charge (SOC) computation in the software to account for battery age. During reconditioning, each battery, one at a time, will be discharged per a specified procedure and then returned to a full state of charge. The paper describes the reconditioning procedure and the expected benefits. The reconditioning procedures have been thoroughly coordinated by all affected technical teams and approved by all required boards. The reconditioning is tentatively scheduled for September 2004.

Hajela, Gyan↗
NASA NTRS1984

Ion thruster system (8-cm) cyclic endurance test

This report describes the qualification test of an Engineering-Model 5-mN-thrust 8-cm-diameter mercury ion thruster which is representative of the Ion Auxiliary Propulsion System (IAPS) thrusters. Two of these thrusters are scheduled for future flight test. The cyclic endurance test described herein was a ground-based test performed in a vacuum facility with a liquid-nitrogen-cooled cryo-surface and a frozen mercury target. The Power Electronics Unit, Beam Shield, Gimal, and Propellant Tank that were used with the thruster in the endurance test are also similar to those of the IAPS. The IAPS thruster that will undergo the longest beam-on-time during the actual space test will be subjected to 7,055 hours of beam-on-time and 2,557 cycles during the flight test. The endurance test was successfully concluded when the mercury in the IAPS Propellant Tank was consumed. At that time, 8,471 hours of beam-on-time and 599 cycles had been accumulated. Subsequent post-test-evaluation operations were performed (without breaking vacuum) which extended the test values to 652 cycles and 9,489 hours of beam-on-time. The Power Electronic Unit (PEU) and thruster were in the same vacuum chamber throughout the test. The PEU accumulated 10,268 hr of test time with high voltage applied to the operating thruster or dummy load.

Dulgeroff, C. R.↗
DOE OSTI2023

Front-End Engineering and Design: Project Tundra Carbon Capture System (Final Report)

As the next phase of Project Tundra, Minnkota Power Cooperative (MPC) completed a front-end engineering and design (FEED) study to install a post-combustion CO 2 capture system (CCS) at the MPC operated (Square Butte Electric Cooperative-owned) Milton R. Young Station (MRYS) Unit 2 (MRY2), a 477-MW power plant fueled by North Dakota lignite. The project team completed the FEED with Fluor’s Econamine FG Plus℠ (EFG+) technology and is taking the next steps leading up to start of construction. Team members included FEED technical lead Fluor Enterprises (Fluor); owner’s engineer and balance of plant (BOP) engineer Burns & McDonnell (BMcD); leading carbon capture consultants (David Greeson Consulting, Hunt International Energy Services); environmental consultants (AECOM, Agora Environmental), other BOP engineering consultants (Golder Associates, Nels); cost-share funding agency, the North Dakota Industrial Commission (NDIC); and the Energy & Environmental Research Center (EERC). Project Tundra’s goal is to implement carbon capture, utilization, and storage (CCUS) in North Dakota, while preserving the use of lignite. Future options could lead to revitalizing legacy oil fields and creating a new CO 2 enhanced oil recovery (EOR) industry. The topic of this report is the FEED study for the carbon dioxide capture portion of Project Tundra. Building on the findings of a pre-FEED study for MRY2, the key deliverables contained in this FEED study are: a) design, costing, and performance data needed to commence project financing activities; b) engineering and material balances required to file for all project permits; and c) a final project schedule. Based on the results of the previous pre-FEED study, MPC and its team evaluated two options to provide the large amount of steam needed to operate the CCS: 1) installation of new natural gas package boilers and a new pipeline to supply natural gas to the facility and 2) extraction of steam from the existing MRYS steam turbine generator. The FEED study was performed using the package boilers option, as it was deemed to have the lowest technical risk, overall cost, and cost uncertainty. A key feature of the design, however, was the mixing the natural gas boilers’ flue gas with the MRY2 flue gas. This increased the size of the CCS system. This design also enabled the tie-in of Unit 1 flue gas for times when Unit 2 is offline. The CCS was designed to capture a combined 12,978 short tons per day (STPD) of CO 2 from the flue gases produced by the existing MRY Unit 2 along with flue gas produced by the new boiler package within the CCS. The 12,978 STPD CO 2 capture is achieved by normally processing 100% of the total available MRY Unit 2 flue gas (considering full load operation) and 100% of the boiler package flue gas, then removing 90% of the CO 2 available from the processed flue gas streams.

01 COAL, LIGNITE, AND PEAT↗
NASA NTRS2024

Evaluating Liftoff Debris for NASA’s Space Launch System (SLS) Prior to the Artemis I Launch

The SLS Artemis I launch vehicle is the first of several planned Artemis launch vehicles, with a number of design differences from earlier NASA missions that incur liftoff debris risk to the mission. As a test vehicle, the Artemis I hardware also endured environments and tests not planned for future missions, which led to several additional factors contributing to an evolving liftoff debris risk to the SLS vehicle. This paper will summarize these risk factors and address the processes used to evaluate and communicate the risks to support a successful Artemis I launch. It will discuss how the evolving risks that were quantified and evaluated by a Cross-Program team of debris Subject Matter Experts to mitigate liftoff debris hazards and communicate updated risk to the SLS vehicle. This process was performed through the inaugural use of an SLS debris day-of-launch (DOL) standard operating procedure that will be used for subsequent Artemis missions. This paper addresses the risk of liftoff debris, debris released by the vehicle or from the launch pad during liftoff through vehicle tower clear. Expected liftoff debris is well understood from previous NASA programs’ experience and from tests of materials, processes and functions that are known to release liftoff debris. These expected sources were assessed and cleared well ahead of launch day. However, given the ever-changing schedules and environments, processes were in place to evaluate any additional potential liftoff debris risks identified during launch countdown. Although many of the Artemis vehicle hardware components are similar to those on the NASA Shuttle Program, there are important differences in the architecture of the Artemis I vehicle which require new assessments of liftoff debris risk for the Artemis missions. The more favorable Artemis crew module location and surfaces are far less vulnerable to debris impacts; however, the longer vehicle can result in higher liftoff debris impact energies to those components on the aft end of the vehicle. Additionally, the positional change of the RS-25 liquid engines to nearer the Booster nozzle exit plane along with the change in Booster throat plug design is a disadvantage to the overall liftoff debris risk which resulted in additional test and analysis efforts for evaluating the integrated vehicle debris risk. In spite of the comprehensive tests and analyses of Artemis I expected liftoff debris, a number of additional tests/processes were completed prior to the Artemis I mission that were required to support a complete understanding of a new launch vehicle, but increased the risk of releasing liftoff debris. The hardware endured several additional cryogenic loading cycles, including the Green Run tests at Stennis Space Center, Wet Dress Rehearsals at Kennedy Space Center, and multiple launch attempts. Each of these cycles induced stresses in the thermal protection system (TPS) materials, increasing the risk of damage to and release of the TPS. Additionally, induced and weather environmental factors that could increase the likelihood of debris release were significant. Vibrations and stresses in the TPS were induced by a required roll-back to the Vehicle Assembly Building before Hurricane Ian to protect the vehicle from damage by high winds. Wind damage and potential internal stresses to several outer mold line materials on the integrated SLS vehicle and mobile launcher were caused by weathering Hurricane Nicole at Pad 39B the week before launch. A thorough imagery scan of the vehicle was performed after each event and the damage observed was repaired, removed, or assessed and the risk to the mission evaluated. Mitigation of debris risk can occur by tests and analyses to show debris impacted components as damage tolerant, by new/improved processes for prevention of debris availability, or redesign. Risk mitigation processes for Artemis I-specific liftoff debris events and the development and use of the SLS debris day of launch (DOL) procedures that will be used for subsequent Artemis missions will be described.

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