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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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DOE OSTI2022

DSO+T: Transactive Energy Coordination Framework (DSO+T Study: Volume 3)

This report describes a transactive energy coordination scheme designed to integrate into existing day-ahead and real-time wholesale energy markets. This scheme was evaluated in the Distribution System Operator with Transactive (DSO+T) study to assess the engineering and economic performance of the transactive energy coordination of a large-scale deployment of distributed energy resources (DER). Transactive agents were developed for a range of DERs (heating, ventilation, and air conditioning units, water heaters, batteries, and electric vehicles) that optimize flexibility over a 48-hour horizon and adjust their strategy in response to changes in real-time prices. A transactive energy coordination scheme, executed by a DSO retail market operator, aggregates these DER bids from participating customers and clears them against a DSO supply curve using a double auction market mechanism. The process of constructing the price-quantity DSO supply curve includes distribution-level transportation constraints (for example, substation congestion limits) and forecast locational marginal price of the DSO’s connected transmission node. The resulting day-ahead and real-time quantities are then bid into a competitive wholesale market operated by an independent system operator. This report also details additional capabilities for proper marketplace simulation such as wholesale price, weather, and load forecasting. The report concludes with a discussion of lessons learned and key design features required to ensure successful operation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1999

Solid Surface Combustion Experiment Yields Significant Observations

The spread of a flame over solid fuel is not only a fundamental textbook combustion phenomenon, but also the central element of destructive fires that cause tragic loss of life and property each year. Throughout history, practical measures to prevent and fight fires have been developed, but these have often been based on lessons learned in a costly fire. Since the 1960 s, scientists and engineers have employed powerful tools of scientific research to understand the details of flame spread and how a material can be rendered nonflammable. High-speed computers have enabled complex flame simulations, whereasand lasers have provided measurements of the chemical composition, temperature, and air velocities inside flames. The microgravity environment has emerged as the third great tool for these studies. Spreading flames are complex combinations of chemical reactions and several physical processes including the transport of oxygen and fuel vapor to the flame and the transfer of heat from the flame to fresh fuel and to the surroundings. Depending on its speed, air motion in the vicinity of the flame can affect the flame in substantially different ways. For example, consider the difference between blowing on a campfire and blowing out a match. On Earth, gravity induces air motion because of buoyancy (the familiar rising hot gases); this process cannot be controlled experimentally. For theoreticians, buoyant air motion complicates the problem modeling of flame spread beyond the capacity of modern computers to simulate. The microgravity environment provides experimental control of air motion near spreading flames, with results that can be compared with detailed theory. The Solid Surface Combustion Experiment (SSCE) was designed to obtain benchmark flame spreading data in quiescent test atmospheres--the limiting case of flames spreading. Professor Robert Altenkirch, Vice President for Research at Mississippi State University, proposed the experiment concept, and the NASA Lewis Research Center designed, built, and tested the SSCE hardware. It was the first microgravity science experiment built by Lewis for the space shuttle and the first combustion science experiment flown in space.

Sacksteder, Kurt R.↗
NASA NTRS2006

NASA Crew and Cargo Launch Vehicle Development Approach Builds on Lessons from Past and Present Missions

The United States (US) Vision for Space Exploration, announced in January 2004, outlines the National Aeronautics and Space Administration's (NASA) strategic goals and objectives, including retiring the Space Shuttle and replacing it with new space transportation systems for missions to the Moon, Mars, and beyond. The Crew Exploration Vehicle (CEV) that the new human-rated Crew Launch Vehicle (CLV) lofts into space early next decade will initially ferry astronauts to the International Space Station (ISS) Toward the end of the next decade, a heavy-lift Cargo Launch Vehicle (CaLV) will deliver the Earth Departure Stage (EDS) carrying the Lunar Surface Access Module (LSAM) to low-Earth orbit (LEO), where it will rendezvous with the CEV launched on the CLV and return astronauts to the Moon for the first time in over 30 years. This paper outlines how NASA is building these new space transportation systems on a foundation of legacy technical and management knowledge, using extensive experience gained from past and ongoing launch vehicle programs to maximize its design and development approach, with the objective of reducing total life cycle costs through operational efficiencies such as hardware commonality. For example, the CLV in-line configuration is composed of a 5-segment Reusable Solid Rocket Booster (RSRB), which is an upgrade of the current Space Shuttle 4- segment RSRB, and a new upper stage powered by the liquid oxygen/liquid hydrogen (LOX/LH2) J-2X engine, which is an evolution of the J-2 engine that powered the Apollo Program s Saturn V second and third stages in the 1960s and 1970s. The CaLV configuration consists of a propulsion system composed of two 5-segment RSRBs and a 33- foot core stage that will provide the LOX/LED needed for five commercially available RS-68 main engines. The J-2X also will power the EDS. The Exploration Launch Projects, managed by the Exploration Launch Office located at NASA's Marshall Space Flight Center, is leading the design, development, testing, and operations planning for these new space transportation systems. Utilizing a foundation of heritage hardware and management lessons learned mitigates both technical and programmatic risk. Project engineers and managers work closely with the Space Shuttle Program to transition hardware, infrastructure, and workforce assets to the new launch systems, leveraging a wealth of knowledge from Shuffle operations. In addition, NASA and its industry partners have tapped into valuable Apollo databases and are applying corporate wisdom conveyed firsthand by Apollo-era veterans of America s original Moon missions. Learning from its successes and failures, NASA employs rigorous systems engineering and systems management processes and principles in a disciplined, integrated fashion to further improve the probability of mission success.

Dumbacher, Daniel L.↗
NASA NTRS2016

MarCO: Interplanetary Mission Development on a CubeSat Scale

Shortly after JPL’s Interior Exploration using Seismic Investigations, Geodesy and Heat Transport (InSight) mission launches, separates, and commences its cruise phase, two CubeSats will deploy from the launch vehicle’s upper stage and begin independent flight to Mars (Fig. 1). During InSight’s entry, descent, and landing (EDL) sequence, these twin Mars Cube One (MarCO) spacecraft will fly 3,500 km above the Martian surface, recording and relaying InSight UHF radio data to the Deep Space Network (DSN) on Earth1. MarCO is a twin CubeSat mission developed by the NASA Jet Propulsion Laboratory (JPL) to accompany the InSight (Interior Exploration using Seismic Investigations, Geodesy and Heat Transport) Mars mission lander. MarCO's primary mission objective is to launch with InSight and independently fly to Mars to serve as a communications relay during InSight's entry, descent, and landing (EDL) phase. MarCO represents a new type of deep space mission: CubeSats at Mars. Building on the development of JPL's first interplanetary CubeSat project, the Interplanetary Nano-Spacecraft Pathfinder in Relevant Environment (INSPIRE), MarCO further refined the approach to hardware, software, and ground architecture development to solve the challenges of quickly building low-budget spacecraft to fly to Mars. The greatest constraint, beyond others typical of CubeSat missions, was time. The duration between MarCO's conception to completion of spacecraft assembly was less than two years - an unprecedented schedule for any planetary mission to date. Through necessity, MarCO has built on previous experience, procedures, systems, and development methodologies, defining a new niche for supporting larger primary missions. The MarCO spacecraft are poised to write a new chapter in deep space exploration. Originally slated to launch and reach Mars in 2016, the InSight mission schedule subsequently slipped to 2018. During the original landing of InSight, Earth would not be in view, and no orbiter around Mars would have been in position to both receive UHF EDL data and simultaneously relay it back to Earth. It was from this obstacle that MarCO was conceived. Regardless of any changes to InSight’s 2018 EDL configuration geometry, MarCO is still expected to fly and serve in the same capacity as originally designed: the first CubeSat mission to Mars. CubeSats have historically been firmly in the domain of universities and small companies. As first conceived, they served as a platform upon which to teach all aspects of the space mission lifecycle. JPL took on this mission type with Interplanetary Nano-Spacecraft Pathfinder in Relevant Environment2 (INSPIRE), moving the concept into a new domain: deep space. Building from the INSPIRE platform and lessons learned, MarCO addressed new challenges in the domain of planetary missions: independent interplanetary flight and navigation, integration with a large-scale mission, long-distance and long-delay communication, short development time, and a small development team. Of these, the greatest constraint was schedule: only 18 months passed from conception of mission concept until delivery of fully assembled and tested flight hardware. Careful selection of mission team, along with extensive use of off-the-shelf equipment, and streamlining automated processes, was essential. This achievement represents the next step in the evolution of CubeSats beyond low-Earth orbit.

Werne, Thomas↗
NASA NTRS2022

Europa Clipper Payload Verification and Validation: Avionics-Instrument Interface Test Campaign

NASA's Europa Clipper mission will investigate Jupiter's icy moon Europa using a payload suite consisting of nine instruments to address a range of scientific objectives concerning Europa's habitability. As the project proceeds past its Critical Design Review, confidence is being built in the system's ability to achieve mission objectives through the implementation of a rigorous payload verification and validation (V&V) program. As part of this payload V&V program, instrument box-level testing was performed by the payload team to verify select instrument-avionics interface requirements. This testing was performed at JPL using the avionics testbed's Bulk Data Storage Emulator (BDSEM) with visiting instrument Test Models. This paper summarizes the Data Link test campaign involving roughly four days of functional testing per instrument, including planning, testing methods, types of issues found, and the requirement closure process. Detail is also provided on the development, deployment, and validation of a standardized analysis tool used in data reviews. This testing verified requirements related to commanding rates, loss of link, packet format, clock counters, loopback test capability, and SpaceWire jitter and skew margins. Additional risk reduction testing of basic commanding, counter behavior, science data collection and transfer, and interface swapping was also performed. Because the BDSEM venue was not originally designed to be a run for record venue, the process of characterizing venue fidelity and establishing suitability for requirement closure using data collected in this venue will also be addressed.In order to close requirements, an extensible tool was developed to post-process instrument command and telemetry data from their original binary to a human-readable format and give visibility to errors detected within the data, such as packets with Cyclic Redundancy Check errors. This tool, called payload-packet-parser, is a Python 3.9 command line tool built using a variety of open-source Python libraries. Payload-packet-parser was designed to support parsing command and telemetry packets for all Europa Clipper instruments and additional analysis tools were developed for verification of specific information interface requirements. This test campaign, including post-processing using a single parsing and verification toolset, allowed for early interface testing, alleviating testing burdens on instrument teams and buying down risk on the instrument-avionics interface by finding hardware and software issues and idiosyncrasies prior to integration with system test venues. Over twenty issues were discovered across the payload, resulting in software updates and instrument rework well in advance of any system impacts. This paper concludes with an assessment of benefits and costs of this type of testing and lessons learned.

Montanez, Leticia↗
NASA NTRS2024

Flight Mechanics Modeling and Simulation of the Earth Entry System

Introduction: The Mars Sample Return (MSR) Campaign being planned by NASA and ESA has the ambitious goal to return Mars samples back to Earth. This international collaboration had developed a concept of operations that included a ESA-designed Earth Return Orbiter (ERO) and NASA-designed Capture, Containment, and Return System (CCRS). The Earth Entry System (EES), consisting of a protective aeroshell that houses the samples as well as sample containment vessels, would conduct entry, descent, and landing (EDL) on a direct Earth trajectory. The EES would enter on a spin-stabilized ballistic trajectory with the goal to passively achieve aerodynamic stability throughout all regions of flight. The EDL sequence would end with the EES impacting the soft playa soil of the Utah Test and Training Range (UTTR). As of the submission of this abstract, the MSR campaign is undergoing a re-architecture leading to a pause in EES development. However, the novel approaches developed in flight mechanics modeling and simulation can significantly benefit the greater IPPW community in the development of Earth return vehicles. This paper will present the latest state of EES flight mechanics modeling and simulation. The paper will highlight the simulation architecture developed and key lessons learned from understanding of EDL trajectory sensitivities. Modeling and Simulation: Figure 1 provides a high-level concept of operations for the approach, entry, descent, and landing (AEDL) phase of the CCRS-portion of MSR. The objective of EES flight mechanics is to model and simulate the EES trajectory from ERO separation to ground impact at UTTR. A variety of flight mechanics simulation models were utilized to model both exo-atmopsheric and atmospheric portions of flight. 42, a 6-DOF simulation developed at Goddard Space Flight Center, is utilized for propagating the attitude of EES during exo-atmospheric flight. 42 allows for a variety of spin eject mechanism scenarios to be simulated for analysis. 10 minutes prior to entry, the 42 states are handed off to the EDL sims. The prime EDL sim utilized by EES is the Program to Optimize Simulated Trajectories II (POST2), a 6-DOF sim developed at Langley Research Center, and the independent verification and validation EDL sim utilized is DSENDS, a 6-DOF sim developed at Jet Propulsion Laboratory. Figure 2 provides a visualization of the flight mechanics simulation model flow through various points in the AEDL phase. Due to the existence of a variety of sim models, the EES flight mechanics team developed processes for data hand-off. These processes included the development of a centralized coordinate frame document, utilization of a single, centralized simulation input document for all sims to reference, and hand-off files containing both the technical data to be ingested by other flight mechanics sims as well as annotations of modeling assumptions utilized to generate the data. Figure~\ref{fig:post2simarchitecture} provides an overview of the POST2 sim architecture wherein POST2 ingests numerous subsystem models and input files. The dispersed state file generated by MONTE provides the position/velocity state of the trajectory while the 42 Handoff file provides the attitude. The aerodynamics database, delivered by the EES aeroscience team, is utilized to simulate the aerodynamic forces and moments experienced during EDL. A custom atmosphere model, developed by EES atmosphere team, is utilized to simulate the anticipated atmosphere environment around the region of Earth through which the EES trajectory flys. These inputs and subsystem models can be varied depending on the AEDL flight mechanics scenario being simulated. Monte Carlo simulations are utilized to generate statistical AEDL performance metrics in the form of scorecards and violin plots. Furthermore, outputs from the POST2 simulation are utilized for follow-on analyses including aerothermal and landing performance. \section{Flight Mechanics Lessons Learned} Though the EES flight mechanics team uncovered a variety of lessons learned through the analysis conducted to support CCRS through preliminary design review, this paper will highlight the most important lessons. A key AEDL performance goal is to ensure the landing footprint of EES remains on the UTTR south range. A common modeling strategy used in EDL analysis is One-Variable-At-a-Time (OVAT). OVAT analysis provides insight into the key drivers that affect AEDL performance metrics. Figure 3 shows the landing ellipses for single dispersion sources as compared to the baseline aggregate of all dispersions. The figure shows that atmosphere winds alone dominate the size of the footprint ellipse (note: EES does not use a parachute unlike previous Earth-return missions and is in wind-driven free fall for ~5min). The significance of the wind led the EES flight mechanics team to pursue the development of a Custom Atmosphere Model [4], in lieu of EarthGRAM [1], built on actual radiosonde wind measurements around the UTTR-region. This decision was driven by the realism in the generated footprint ellipses and lessons-learned from Stardust [5]. These findings will be invaluable for future Earth-return missions in providing an early understanding of the key drivers affecting footprint size and modeling considerations for which to account. Another lesson learned is tied to the AEDL performance goal of achieving passive stability throughout all regions of flight. It is well understood that blunt-body aeroshells are less stable as they transition from supersonic to subsonic. Eliminating a backshell does help improvestability; however, other phenomena such as roll-induced instability during terminal descent can still arise. The EES flight mechanics team developed stability metrics as tools to better understand the causes of and better predict the onset of dynamic instability. These tools were built upon analytical models developed by Jaffe [3] and Murphy [2]. The tools were shown to both be very accurate in correlation with actual unstable cases and useful in developing stability margin policies based on the vehicle design and simulation considerations (e.g. sphere-cone angle change, mass change, wind turbulence). These tools allowed for the current EES design to demonstrate the ability to achieve passive stability and can be an invaluable tool for consideration in the design of parachute-less Earth-return vehicles.

Rohan Deshmukh↗
DOE OSTI2020

An Intelligent Adaptable Monitoring Package. Final Report

The “Intelligent Adaptable Monitoring Package” project was a four-year effort that demonstrated the feasibility of integrated sensing packages at tidal and wave energy sites. Such integration is generally required by the breadth of sensors required to understand environmental effects at marine energy sites and the operational difficulty of deploying, maintaining, and recovering such sensors. Over the course of the project, the Adaptable Monitoring Package (AMP) was deployed in multiple settings, each corresponding to a project budget period: - Budget Period 1: Demonstration of cabled deployment at Pacific Northwest National Laboratory’s Marine Science Laboratory. The deployment highlighted AMP hardware endurance over a 4-month deployment in a tidally-dominated environment and laid the groundwork for machine learning algorithms to detect and classify targets present in active sonar data. - Budget Period 2: Demonstration of an autonomous deployment at PacWave South off the coast of Newport, Oregon. The deployment highlighted the stability of AMP hardware and software, with the autonomous package collecting data on a duty cycle over a 1.5-month deployment. - Budget Period 3: Demonstration of an autonomous deployment powered by a wave energy converter at the U.S. Navy’s Wave Energy Test Site. The deployment highlighted the potential of wave energy to power ocean observatories and led to the development of machine learning algorithms to detect and classify targets in optical camera data. In aggregate, this project’s greatest success was demonstrating the AMP’s flexibility in a range of deployment scenarios. Each budget period represented a “first of a kind” demonstration of integrated instrumentation – cabled AMP, autonomous AMP, wave-energy powered AMP – and each deployment helped to identify and set goals for the next. Further, despite the exploratory nature of these deployments, each one achieved high system up-time and proved that flexible integration of multiple sensors in a single package represents a viable strategy for marine energy environmental monitoring. The key lessons learned from the project are: - Without continuous power, either from a shore cable or in situ source, many of the benefits of integration are lost (If continuous power is not available, the ability to detect rare events is lost, as is the ability to minimize the risk of behavioral changes through adaptive sensing. However, even on a duty cycle, there is still value in being able to acquire synchronous data from multiple sensors.); and - Observations from a moving platform present substantially greater data processing challenges than those from stationary platforms. Finally, these deployments also demonstrate an important truth: successful integration alone does not guarantee that relevant data are collected. To grow the knowledge base about environmental interactions with marine energy converters, integrated systems, like the AMP, need to include the right sensor mix and connect the data pipelines to effective processing algorithms. These deployments establish a strong foundation for future collaborations with the environmental research community: not only to understand the environmental effects of marine energy, but also to improve our general ability to study life in the sea.

16 TIDAL AND WAVE POWER↗
NASA NTRS1994

Evaluation of NASA's end-to-end data systems using DSDS+

The Data Systems Dynamic Simulator (DSDS+) is a software tool being developed by the authors to evaluate candidate architectures for NASA's end-to-end data systems. Via modeling and simulation, we are able to quickly predict the performance characteristics of each architecture, to evaluate 'what-if' scenarios, and to perform sensitivity analyses. As such, we are using modeling and simulation to help NASA select the optimal system configuration, and to quantify the performance characteristics of this system prior to its delivery. This paper is divided into the following six sections: (1) The role of modeling and simulation in the systems engineering process. In this section, we briefly describe the different types of results obtained by modeling each phase of the systems engineering life cycle, from concept definition through operations and maintenance; (2) Recent applications of DSDS+. In this section, we describe ongoing applications of DSDS+ in support of the Earth Observing System (EOS), and we present some of the simulation results generated of candidate system designs. So far, we have modeled individual EOS subsystems (e.g. the Solid State Recorders used onboard the spacecraft), and we have also developed an integrated model of the EOS end-to-end data processing and data communications systems (from the payloads onboard to the principle investigator facilities on the ground); (3) Overview of DSDS+. In this section we define what a discrete-event model is, and how it works. The discussion is presented relative to the DSDS+ simulation tool that we have developed, including it's run-time optimization algorithms that enables DSDS+ to execute substantially faster than comparable discrete-event simulation tools; (4) Summary. In this section, we summarize our findings and 'lessons learned' during the development and application of DSDS+ to model NASA's data systems; (5) Further Information; and (6) Acknowledgements.

Rouff, Christopher↗
NASA NTRS1999

Re-Design and Beat Testing of the Man-Machine Integration Design and Analysis System: MIDAS

The Man-machine Design and Analysis System (MIDAS) is a human factors design and analysis system that combines human cognitive models with 3D CAD models and rapid prototyping and simulation techniques. MIDAS allows designers to ask 'what if' types of questions early in concept exploration and development prior to actual hardware development. The system outputs predictions of operator workload, situational awareness and system performance as well as graphical visualization of the cockpit designs interacting with models of the human in a mission scenario. Recently, MIDAS was re-designed to enhance functionality and usability. The goals driving the redesign include more efficient processing, GUI interface, advances in the memory structures, implementation of external vision models and audition. These changes were detailed in an earlier paper. Two Beta test sites with diverse applications have been chosen. One Beta test site is investigating the development of a new airframe and its interaction with the air traffic management system. The second Beta test effort will investigate 3D auditory cueing in conjunction with traditional visual cueing strategies including panel-mounted and heads-up displays. The progress and lessons learned on each of these projects will be discussed.

Shively, R. Jay↗
NASA NTRS2010

Heritage Systems Engineering Lessons from NASA Deep Space Missions

In the design and development of complex spacecraft missions, project teams frequently assume the use of advanced technology systems or heritage systems to enable a mission or reduce the overall mission risk and cost. As projects proceed through the development life cycle, increasingly detailed knowledge of the advanced and heritage systems within the spacecraft and mission environment identifies unanticipated technical issues. Resolving these issues often results in cost overruns and schedule impacts. The National Aeronautics and Space Administration (NASA) Discovery & New Frontiers (D&NF) Program Office at Marshall Space Flight Center (MSFC) recently studied cost overruns and schedule delays for 5 missions. The goal was to identify the underlying causes for the overruns and delays, and to develop practical mitigations to assist the D&NF projects in identifying potential risks and controlling the associated impacts to proposed mission costs and schedules. The study found that optimistic hardware/software inheritance and technology readiness assumptions caused cost and schedule growth for all five missions studied. The cost and schedule growth was not found to be the result of technical hurdles requiring significant technology development. The projects institutional inheritance and technology readiness processes appear to adequately assess technology viability and prevent technical issues from impacting the final mission success. However, the processes do not appear to identify critical issues early enough in the design cycle to ensure project schedules and estimated costs address the inherent risks. In general, the overruns were traceable to: an inadequate understanding of the heritage system s behavior within the proposed spacecraft design and mission environment; an insufficient level of development experience with the heritage system; or an inadequate scoping of the systemwide impacts necessary to implement an advanced technology for space flight applications. The paper summarizes the study s lessons learned in more detail and offers suggestions for improving the project s ability to identify and manage the technology and heritage risks inherent in the design solution.

Barley, Bryan↗
NASA NTRSDate not supplied

Designing Autonomy into Interfaces for Long-Duration Missions

As NASA develops technologies for long-duration crewed missions, we must understand how communication between ground control teams and astronauts differs from the current dynamic to adapt new concepts for long-duration mission operations. Today, ground control teams support astronauts with immediate availability to answer questions, resolve issues, and manage activities. In the near future, however, extended communication delays during long-duration missions will require astronauts to become more autonomous. As many of the responsibilities shift from the ground control teams to the astronauts on-board, the concept of operations must also change from how it functions today. With increased astronaut autonomy, software tools must be developed that enable efficient completion of mission tasks without increased mental workload. Designing software tools to facilitate crew autonomy requires development teams to know which data will enhance quick decision making while providing necessary context for situational awareness of systems being managed on-board. NASA's Autonomous Systems and Operations (ASO) team is presently developing a software interface tool, EXPRESS (EXpedite the PRocessing of Experiments for Space Station) 2.5 to enable a long-duration crew to schedule activities for and operate autonomous systems. This paper describes details of the integrated human factors approach that drove the design of the elements of the software tool, including self-managed scheduling, constraint-driven planning, autonomous system fault recovery, and recommended troubleshooting actions. Additionally, this paper will chronicle ASO modifications of the user interface after the team's first flight demonstration, how it was based on lessons learned during software development, as well as from crew feedback in order to develop the current version which will be demonstrated on ISS in 2021. In the upcoming ISS demonstration, the astronaut crew will be given scenarios for scheduling and operating autonomous system activities, including off-nominal scenarios and autonomous system recoveries. The demonstration of the EXPRESS 2.5 tool is a step towards improved levels of autonomy as our new journeys take us farther into space.

autonomy↗
DOE OSTI2021

Large scale multi-node simulations of $\mathbb{Z}_2$ gauge theory quantum circuits using Google Cloud Platform

Simulating quantum field theories on a quantum computer is one of the most exciting fundamental physics applications of quantum information science. Dynamical time evolution of quantum fields is a challenge that is beyond the capabilities of classical computing, but it can teach us important lessons about the fundamental fabric of space and time. Whether we may answer scientific questions of interest using near-term quantum computing hardware is an open question that requires a detailed simulation study of quantum noise. Here we present a large scale simulation study powered by a multi-node implementation of qsim using the Google Cloud Platform. We additionally employ newly-developed GPU capabilities in qsim and show how Tensor Processing Units -- Application-specific Integrated Circuits (ASICs) specialized for Machine Learning -- may be used to dramatically speed up the simulation of large quantum circuits. We demonstrate the use of high performance cloud computing for simulating $\mathbb{Z}_2$ quantum field theories on system sizes up to 36 qubits. We find this lattice size is not able to simulate our problem and observable combination with sufficient accuracy, implying more challenging observables of interest for this theory are likely beyond the reach of classical computation using exact circuit simulation.

Gustafson, Erik↗
DOE OSTI2025

Demonstration of and future perspective on scaling ultrafast-laser-ablation microstructuring of Li-ion battery electrodes to roll-to-roll production and large-format cells

This work demonstrates integration of an ultrafast laser onto a roll-to-roll machine, the laser structuring of a double-sided, 700 m long roll of graphite battery anode and its subsequent manufacture into 27 Ah prismatic cells. The electrode was ablated with a novel hybrid-microstructure composed of both hexagonally arranged pores for enhanced rate performance and channels for fast electrolyte wetting. Subsequently, this anode and a non-ablated baseline anode are paired with an NMC111 cathode for cell building and electrochemical characterization. Compared to the baseline, laser ablated cells demonstrated a reduction in soaking time of at least 60%, an improvement in fast charge capability with >30% more capacity accepted during 6C charging, and an extension of cycle life of >40% during 0.5C cycling. Further, a perspective is provided on scaling ultrafast laser ablation of battery electrodes to industrial throughputs. Additionally, lessons learned from this pilot-scale demonstration are provided in regards to optical architecture, debris removal, and system control. A techno-economic analysis is used to demonstrate that laser ablation can be integrated into existing electrode manufacturing facilities with only ≈$\$$1.3 per kWh increase (≈2%) in manufacturing cost. Preemptive electrode design for laser ablation is discussed as a further method for enhancing performance. Finally, an analysis of available laser systems and beam-scanning architectures is used to determine design requirements to scale process throughput to a state-of-the-art speed of 50 m min −1 . This analysis demonstrates that laser ablating Li-ion battery electrodes has multiple benefits to manufacturing and battery performance, that the technology already exists to achieve high laser-ablation throughputs, and that integrating ultrafast laser ablation to electrode manufacturing will not create a cost or processing bottleneck.

25 ENERGY STORAGE↗
DOE OSTI2023

The Challenges and Solutions of Meeting the Assembly Specifications for the 4.5 m Long MQXFA Magnets for the Hi-Luminosity LHC

The U.S. High-Luminosity LHC Accelerator Upgrade Project (HL-LHC AUP) has, in the recent years, developed assembly specifications for the 4.5 m long MQXFA magnets, which are 150 mm aperture high-field Nb 3 Sn low-β quadrupole magnets that are being built for the CERN Hi-Luminosity LHC (HL-LHC) upgrade. While the specifications were based on lessons learned from the LHC Accelerator Research Program (LARP) effort and the MQXFS and MQXFA prototype magnets, the experience gained from having both MQXFA07 and MQXFA08 magnets not meeting performance specifications during cold testing actually catalyzed a better understanding of the impact of the target assembly specifications and a subsequent refinement of the same. This paper summarizes a body of assembly data from the Pre-Series (MQXFA03-MQXFA07) and Series magnets (MQXFA08-MQXFA11) that have been built to date, and discusses the processes employed to successfully face the challenge of ensuring that the assembly specifications are met for the duration of the project.

43 PARTICLE ACCELERATORS↗
NASA NTRS1994

Operations on Graphical Models with Plates

This paper explains how graphical models, for instance Bayesian or Markov networks, can be extended to model problems in data analysis and learning. This provides a unified framework that combines lessons learned from the artificial intelligence, statistical and connectionist communities. This also offers a set of principles for developing a software generator for data analysis, whereby a learning or discovery system can be compiled from specifications. Many of the popular learning algorithms can be compiled in this way from graphical specifications. While in a sense this paper is a multidisciplinary review of learning, the main contribution here is the presentation of the material within the unifying framework of graphical models, and the observation that, as a result, the process of developing learning algorithms can be partly automated.

Buntine, Wray L.↗
NASA NTRS2016

Evolution of the JPSS Ground Project Calibration and Validation System

The Joint Polar Satellite System (JPSS) is the National Oceanic and Atmospheric Administration's (NOAA) next-generation operational Earth observation Program that acquires and distributes global environmental data from multiple polar-orbiting satellites. The JPSS Program plays a critical role to NOAA's mission to understand and predict changes in weather, climate, oceans, coasts, and space environments, which supports the Nation's economy and protection of lives and property. The National Aeronautics and Space Administration (NASA) is acquiring and implementing the JPSS, comprised of flight and ground systems, on behalf of NOAA. The JPSS satellites are planned to fly in the afternoon orbit and will provide operational continuity of satellite-based observations and products for NOAA Polar-orbiting Operational Environmental Satellites (POES) and the Suomi National Polar-orbiting Partnership (SNPP) satellite. To support the JPSS Calibration and Validation (CalVal) node Government Resource for Algorithm Verification, Independent Test, and Evaluation (GRAVITE) services facilitate: Algorithm Integration and Checkout, Algorithm and Product Operational Tuning, Instrument Calibration, Product Validation, Algorithm Investigation, and Data Quality Support and Monitoring. GRAVITE is a mature, deployed system that currently supports the SNPP Mission and has been in operations since SNPP launch. This paper discusses the major re-architecture for Block 2.0 that incorporates SNPP lessons learned, architecture of the system, and demonstrates how GRAVITE has evolved as a system with increased performance. It is now a robust, stable, reliable, maintainable, scalable, and secure system that supports development, test, and production strings, replaces proprietary and custom software, uses open source software, and is compliant with NASA and NOAA standards.

Next-Generation↗
NASA NTRS2018

Lessons Learned and Cost Analysis of Hosting a Full Stack Open Data Cube (ODC) Application on the Amazon Web Services (AWS)

The Open Data Cube (ODC) initiative, with support from the Committee on Earth Observation Satellites (CEOS) System Engineering Office (SEO) has developed a state-of-the-art suite of software tools and products to facilitate the analysis of Earth Observation data. This paper presents a short summary and cost analysis of our experience using Amazon Web Services (AWS) to host one such software product, the CEOS Data Cube (CDC) web-based User Interface (UI). In order to provide adaptability, flexibility, scalability, and robustness, we leverage widely-adopted and well-supported technologies such as the Django web framework and the AWS Cloud platform. The UI has empowered users by providing features that assist with streamlining data preparation, data processing, data visualization, and the sub-setting of Analysis Ready Data (ARD) products in order to achieve a wide variety of Earth imaging objectives.

Rizvi, Syed R.↗
DOE OSTI2021

Risk Assessment and Management Workflow—An Example of the Southwest Regional Partnership

This paper summarizes the risk assessment and management workflow developed and applied to the Southwest Regional Partnership on Carbon Sequestration (SWP) Phase III Demonstration Project. The risk assessment and management workflow consists of six primary tasks, including management planning, identification, qualitative analysis, quantitative analysis, response planning, and monitoring. Within the workflow, the SWP assembled and iteratively updated a risk registry that identifies risks for all major activities of the project. Risk elements were ranked with respect to the potential impact to the project and the likelihood of occurrence. Both qualitative and quantitative risk analyses were performed. To graphically depict the interactions among risk elements and help building risk scenarios, process influence diagrams were used to represent the interactions. The SWP employed quantitative methods of risk analysis including Response Surface Method (RSM), Polynomial Chaos Expansion (PCE), and the National Risk Assessment Partnership (NRAP) toolset. The SWP also developed risk response planning and performed risk control and monitoring to prevent the risks from affecting the project and ensure the effectiveness of risk management. As part of risk control and monitoring, existing and new risks have been tracked and the response plan was subsequently evaluated. Findings and lessons learned from the SWP’s risk assessment and management efforts will provide valuable information for other commercial geological CO2 storage projects.

Lee, Si-Yong↗