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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Advanced Ultrasupercritical (AUSC) Materials Thick-Walled Cycling Header Development for ComTest-AUSC (Final Report)

Alstom Power Inc., a wholly owned subsidiary of the General Electric Company (GE) recently completed “Advanced Ultrasupercritical (AUSC) Materials Thick-Walled Cycling Header Development for ComTest-AUSC” under Award No. DE-FE0026183 for the U.S. Department of Energy National Energy Technology Laboratory (DOE NETL). This project developed a design for testing of a high temperature nickel-based superalloy thick-walled header to simulate cycling and flexible plant operation in new and existing plants. The objective was to simulate the expected thermal stresses of a new AUSC plant or a retrofit header in an existing plant to improve flexible dynamic operation while maintaining component integrity and overall power plant reliability. The high performance superalloy materials that enable higher operating temperatures and pressures can support future transformational power technologies including new AUSC plants at 4250-5000 psi, 730°C/760°C or will serve as a replacement component in a repowered or retrofit USC coal powered cycling plant at 3600 psi, 600°C. These alloys can also enable supercritical CO2 cycles, nuclear power, solar power and more efficient natural gas combined cycle units as targeted by the U.S. DOE/NETL Cross-Cutting Research Technology Program Plan. Recently developed advanced nickel alloys such as Inconel 740H (740H) and Haynes 282 (H282) have been successfully tested on a pilot scale for fireside corrosion using steam loop tubing at AUSC temperatures of 760°C in actual operating coal fired boiler. These high strength materials have been demonstrated their adequacy for use in other high temperature boiler components such as superheater tubes. Thick-walled superheater outlet headers which operate at high temperatures and pressure under severe cycling condition are considered as one of the most critical component in the AUSC coal fired boiler. Over the design life of a plant, these headers are exposed to the most severe fatigue and creep damage accumulation and need to be properly designed for the expected cycling in an AUSC plant with flexible operation. These materials need to demonstrate adequate design life of 20 to 30 years for creep and fatigue conditions. The following tasks were performed: 1. A conceptual design was developed of a thick-walled component representative of typical headers with several tube connections and proper flow rates (~100,000 lbs/hr) suitable for Phase II test at 760°C operation. This was based on a process analysis of expected full scale new and component retrofit designs for AUSC; 2. A multi-physics flow and heat transfer computational fluid dynamics (CFD) analysis of the component for proper layout of the header configuration, number and geometry (size) of tubes required for bypass flow, flow rates through the tubing, and sectional pressure drops was performed. Steam to header metal heat transfer film coefficients in the header section and the tubes during the two stages (half load and full load) of the cycling operation were evaluated and used in the stress analysis; 3. Detailed analytical evaluation of the thick-walled pipe and tube connections for mechanical integrity under cycling conditions was performed. This included transient thermal stress analysis and fatigue usage estimation including the tube-to-pipe weld geometries and weld materials; 4. A layout and design of the thick-walled test component was developed and instrumentation required for a test was identified; 5. Continuum Damage Mechanics (CDM) creep prediction models were extended to 740H and H282 and validated with public data on 740H and H282 for use in creep analysis. In addition, detailed creep analyses were performed separately for the design life of the conceptual AUSC superheater outlet header using these General Electric (GE) creep constitutive models. GE was the prime contractor for the project, which was directed by Principal Investigator Robert Schrecengost and Lead Scientist Dr. B. Reddy Ganta. Other collaborative participants in this project included GE Global Research, GE Boiler Engineering, and a Technical Consultant from EPRI.

01 COAL, LIGNITE, AND PEAT↗
NASA NTRS2004

Characterizing the effects of droplines on target acquisition performance on a 3-D perspective display

The present study investigated the effects of droplines on target acquisition performance on a 3-D perspective display in which participants were required to move a cursor into a target cube as quickly as possible. Participants' performance and coordination strategies were characterized using both Fitts' law and acquisition patterns of the 3 viewer-centered target display dimensions (azimuth, elevation, and range). Participants' movement trajectories were recorded and used to determine movement times for acquisitions of the entire target and of each of its display dimensions. The goodness of fit of the data to a modified Fitts function varied widely among participants, and the presence of droplines did not have observable impacts on the goodness of fit. However, droplines helped participants navigate via straighter paths and particularly benefited range dimension acquisition. A general preference for visually overlapping the target with the cursor prior to capturing the target was found. Potential applications of this research include the design of interactive 3-D perspective displays in which fast and accurate selection and manipulation of content residing at multiple ranges may be a challenge.

Time and Motion Studies↗
NASA NTRS2021

Verifying Mars 2020 Sampling and Caching Robotic Functions with Position Budgeting Process and Tool

The Mars 2020 Perseverance Rover was launched on July 30th, 2020 with one of the most complex robotic systems ever implemented on an interplanetary mission. Much of this robotic complexity resides in the Rover Sampling and Caching Subsystem (SCS) to enable collection of Martian samples for eventual return to earth and preparation of surfaces for close-up surface science observations. Two robotic arms are used by SCS: the large Robotic Arm (RA) positions the coring drill and science instruments mounted to the Turret for surface interactions, and the smaller Sample Handling Assembly (SHA) manipulates Sample Tube Assemblies (STA) within the Adaptive Caching Assembly (ACA) to prepare them for sample collection, processing, and hermetic sealing. The robotic arms interact with the Martian surface and other SCS components in many ways and in a variety of configurations, with positioning accuracy requirements ranging from tens of millimeters for some surface interactions down to sub-millimeter accuracy for some ACA interactions.This paper describes the process and tool used to calculate the SCS robotic interaction positioning budgets and verify the as-built hardware when delivered. To ensure that these robotic systems are able to perform their tasks, each robotic interaction with another element was broken down into its composite functions. To calculate a positioning budget margin for each function, an allowable was defined and then compared to the list of error sources that contribute to misalignment. Across the subsystem, over 250 functions were identified to be assessed, with almost 500 error sources feeding into their budget calculations. In addition to using as-built values in the budgets for SCS Verification and Validation (V&V) after the hardware was complete, these budgets were populated with design data during the design phase to identify areas of concern and guide hardware design to ensure positive position budget margins.Because of the size of the SCS team that had inputs to the positioning budgets and the sheer number of items in the budgets that needed to be created, updated, and verified, having a tool that would allow for simultaneous access and robust data integrity and processing was imperative. To accomplish this, a web-based MySQL database was created that allowed users to create function position budgets, link individual errors and allowables to them, and view function position budget margin reports. Each error and allowable records data for lateral, normal, angular, and clocking errors, with the ability to add as-built data for up to four different hardware builds. Margin reports can be generated for either design values alone or replacing design data with as-built data when available. These as-built reports are used for final verification of the SCS positioning requirements. Ultimately, the SCS positioning budget process and database tool led to successful interactions during test and an SCS robotic system that is ready to perform sample acquisition and caching on the surface of Mars.

Williams, Jeffrey↗
NASA NTRS2004

Summary of the key features of seven biomathematical models of human fatigue and performance

BACKGROUND: Biomathematical models that quantify the effects of circadian and sleep/wake processes on the regulation of alertness and performance have been developed in an effort to predict the magnitude and timing of fatigue-related responses in a variety of contexts (e.g., transmeridian travel, sustained operations, shift work). This paper summarizes key features of seven biomathematical models reviewed as part of the Fatigue and Performance Modeling Workshop held in Seattle, WA, on June 13-14, 2002. The Workshop was jointly sponsored by the National Aeronautics and Space Administration, U.S. Department of Defense, U.S. Army Medical Research and Materiel Command, Office of Naval Research, Air Force Office of Scientific Research, and U.S. Department of Transportation. METHODS: An invitation was sent to developers of seven biomathematical models that were commonly cited in scientific literature and/or supported by government funding. On acceptance of the invitation to attend the Workshop, developers were asked to complete a survey of the goals, capabilities, inputs, and outputs of their biomathematical models of alertness and performance. Data from the completed surveys were summarized and juxtaposed to provide a framework for comparing features of the seven models. RESULTS: Survey responses revealed that models varied greatly relative to their reported goals and capabilities. While all modelers reported that circadian factors were key components of their capabilities, they differed markedly with regard to the roles of sleep and work times as input factors for prediction: four of the seven models had work time as their sole input variable(s), while the other three models relied on various aspects of sleep timing for model input. Models also differed relative to outputs: five sought to predict results from laboratory experiments, field, and operational data, while two models were developed without regard to predicting laboratory experimental results. All modelers provided published papers describing their models, with three of the models being proprietary. CONCLUSIONS: Although all models appear to have been fundamentally influenced by the two-process model of sleep regulation by Borbely, there is considerable diversity among them in the number and type of input and output variables, and their stated goals and capabilities.

Fatigue/physiopathology↗
NASA NTRS2006

Assessment of Postflight Locomotor Performance Utilizing a Test of Functional Mobility: Strategic and Adaptive Responses

Space flight induces adaptive modification in sensorimotor function, allowing crewmembers to operate in the unique microgravity environment. This adaptive state, however, is inappropriate for a terrestrial environment. During a re-adaptation period upon their return to Earth, crewmembers experience alterations in sensorimotor function, causing various disturbances in perception, spatial orientation, posture, gait, and eye-head coordination. Following long duration space flight, sensorimotor dysfunction would prevent or extend the time required to make an emergency egress from the vehicle; compromising crew safety and mission objectives. We are investigating two types of motor learning that may interact with each other and influence a crewmember's ability to re-adapt to Earth's gravity environment. In strategic learning, crewmembers make rapid modifications in their motor control strategy emphasizing error reduction. This type of learning may be critical during the first minutes and hours after landing. In adaptive learning, long-term plastic transformations occur, involving morphological changes and synaptic modification. In recent literature these two behavioral components have been associated with separate brain structures that control the execution of motor strategies: the strategic component was linked to the posterior parietal cortex and the adaptive component was linked to the cerebellum (Pisella, et al. 2004). The goal of this paper was to demonstrate the relative contributions of the strategic and adaptive components to the re-adaptation process in locomotor control after long duration space flight missions on the International Space Station (ISS). The Functional Mobility Test (FMT) was developed to assess crewmember s ability to ambulate postflight from an operational and functional perspective. Sixteen crewmembers were tested preflight (3 sessions) and postflight (days 1, 2, 4, 7, 25) following a long duration space flight (approx 6 months) on the ISS. We have further analyzed the FMT data to characterize strategic and adaptive components during the postflight readaptation period. Crewmembers walked at a preferred pace through an obstacle course set up on a base of 10 cm thick medium density foam (Sunmate Foam, Dynamic Systems, Inc., Leicester, NC). The 6.0m X 4.0m course consisted of several pylons made of foam; a Styrofoam barrier 46.0cm high that crewmembers stepped over; and a portal constructed of two Styrofoam blocks, each 31cm high, with a horizontal bar covered by foam and suspended from the ceiling which was adjusted to the height of the crewmember s shoulder. The portal required crewmembers to bend at the waist and step over a barrier simultaneously. All obstacles were lightweight, soft and easily knocked over. Crewmembers were instructed to walk through the course as quickly and as safely as possible without touching any of the objects on the course. This task was performed three times in the clockwise direction and three times in the counterclockwise direction that was randomly chosen. The dependent measures for each trial were: time to complete the course (seconds) and the number of obstacles touched or knocked down. For each crewmember, the time to complete each FMT trial from postflight days 1, 2, 4, 7 and 25 were further analyzed. A single logarithmic curve using a least squares calculation was fit through these data to produce a single comprehensive curve (macro). This macro curve composed of data spanning 25 days, illustrates the re-adaptive learning function over the longer time scale term. Additionally, logarithmic curves were fit to the 6 data trials within each individual post flight test day to produce 5 separate daily curves. These micro curves, produced from data obtained over the course of minutes, illustrates the strategic learning function exhibited over a relative shorter time scale. The macro curve for all subjects exhibited adaptive motor learning patterns over the 25 day period. Howev, 9/16 crewmembers exhibited significant strategic motor learning patterns in their micro curves, as defined by m > 1 in the equation of the line y=m*LN(x) +b. These data indicate that postflight recovery in locomotor function involves both strategic and adaptive mechanisms. Future countermeasures will be designed to enhance both recovery processes.

Warren, L. E.↗
NASA NTRS2001

Sensorimotor adaptations to microgravity in humans

Motor function is altered by microgravity, but little detail is available as to what these changes are and how changes in the individual components of the sensorimotor system affect the control of movement. Further, there is little information on whether the changes in motor performance reflect immediate or chronic adaptations to changing gravitational environments. To determine the effects of microgravity on the neural control properties of selected motor pools, four male astronauts from the NASA STS-78 mission performed motor tasks requiring the maintenance of either ankle dorsiflexor or plantarflexor torque. Torques of 10 or 50% of a maximal voluntary contraction (MVC) were requested of the subjects during 10 degrees peak-to-peak sinusoidal movements at 0.5 Hz. When 10% MVC of the plantarflexors was requested, the actual torques generated in-flight were similar to pre-flight values. Post-flight torques were higher than pre- and in-flight torques. The actual torques when 50% MVC was requested were higher in- and post-flight than pre-flight. Soleus (Sol) electromyographic (EMG) amplitudes during plantarflexion were higher in-flight than pre- or post-flight for both the 10 and 50% MVC tasks. No differences in medial gastrocnemius (MG) EMG amplitudes were observed for either the 10 or 50% MVC tasks. The EMG amplitudes of the tibialis anterior (TA), an antagonist to plantarflexion, were higher in- and post-flight than pre-flight for the 50% MVC task. During the dorsiflexion tasks, the torques generated in both the 10 and 50% MVC tasks did not differ pre-, in- and post-flight. TA EMG amplitudes were significantly higher in- than pre-flight for both the 10 or 50% MVC tasks, and remained elevated post-flight for the 50% MVC test. Both the Sol and MG EMG amplitudes were significantly higher in-flight than either pre- or post-flight for both the 10 and 50% MVC tests. These data suggest that the most consistent response to space flight was an elevation in the level of contractions of agonists and antagonists when attempting to maintain constant torques at a given level of MVC. Also, the chronic levels of EMG activity in selected ankle flexor and extensor muscles during space flight and during routine activities on Earth were recorded. Compared with pre- and post-flight values, there was a marked increase in the total EMG activity of the TA and the Sol and no change in the MG EMG activity in-flight. These data indicate that space flight, as occurs on shuttle missions, is a model of elevated activation of both flexor and extensor muscles, probably reflecting the effects of programmed work schedules in flight rather than a direct effect of microgravity.

NASA Experiment Number 284036↗
NASA NTRSDate not supplied

Modeling Deformable Linear Objects for Autonomous Robotic Outfitting of Lunar Surface Systems

This paper presents structural models of deformable linear objects (DLOs). DLOs are a subclass of deformable objects that encompasses common outfitting elements such as cables and ropes. Models are validated through hardware experiments, and integration in a robotic autonomy architecture for space environments is discussed. A persistent human presence on the lunar surface is one of the next major milestones in space exploration. This requires the development of robust extraplanetary construction technologies including structures and materials modeling and robotic systems. Previous robotic construction technology development has primarily focused on structural assembly, with significantly less focus on robotically performed outfitting tasks to instantiate subsystems providing power, data, life support, etc. These tasks involve manipulation of highly flexible elements, which are difficult to model, such as cable harnesses, ropes, and hoses. Robotic manipulation of DLOs, especially cable harnesses, is an active area of research as cable harnesses are essential for providing power and data to space assets. DLO models that can be used for robot manipulator trajectory generation are necessary for autonomous operation of lunar infrastructure. There are many proposed methods for modeling DLOs, and they primarily fall into three types: 1) discrete model-based, 2) continuum model-based, and 3) Neural Network-based. These types each have pros and cons, and the tradeoff between model accuracy and computational speed informs which type should be used. An understanding of this trade-off is imperative for real-time control of autonomous systems. High computational requirements reduce the speed of the model, making real-time control difficult, while accuracy is critical to preventing collisions. Discrete models, such as a mass-spring multibody representation, require relatively few calculations, and accuracy is directly tied to the step size of the discretization. Continuum models, such as a B-spline representation or a Cosserat rod model (a mix of continuous and discrete), are more informed of the structural properties of the cable and are much more accurate than a rigid body mass-spring model, but at significant computational cost. A Neural Network approach can provide an online solution with very few computational steps, but properly generating training data can be difficult and validation for an in-space application is not trivial. This paper explores the trade-off between different modeling approaches and compares accuracy and computational speed/complexity of the three types mentioned above. Model accuracy is evaluated using a cable in a static configuration. True cable shape is obtained using a depth camera for RGB images and point-cloud segmentation. The purpose of this experiment is to evaluate the trade-offs of different approaches to the DLO modeling problem. Understanding the tradeoffs between different cable modeling techniques paves the way for developing robotic control and planning architectures necessary for real-time manipulation of DLOs for lunar infrastructure outfitting. Real-time control is required for robotic systems to be able to actively manipulate a cable in a harsh environment where model and sensor errors compound, and environmental conditions can cause significant disturbances. Cable routing must be performed in areas with high density of objects/obstacles: through truss structures, near solar panels or mirror arrays, next to bundles of electrical equipment. Understanding the best way to plan and manipulate a cable without disrupting the environment or damaging the cable is imperative to robotic outfitting operations on the lunar surface.

Amy M Quartaro↗
NASA NTRS1990

The JPL telerobot operator control station: Operational experiences

The Operator Control Station of the JPL/NASA Telerobot Demonstration System provides an efficient man-machine interface for the performance of telerobot tasks. Its hardware and software have been designed with high flexibility. It provides a feedback-rich interactive environment in which the Operator performs teleoperation tasks, robotic tasks, and telerobotic tasks with ease. The to-date operational experiences of this system, particularly related to the Object Designate Process and the Voice Input/Output Process are discussed.

Kan, Edwin P.↗
NASA NTRS2012

EVA Development and Verification Testing at NASA's Neutral Buoyancy Laboratory

As an early step in the preparation for future Extravehicular Activities (EVAs), astronauts perform neutral buoyancy testing to develop and verify EVA hardware and operations. Neutral buoyancy demonstrations at NASA Johnson Space Center's Sonny Carter Training Facility to date have primarily evaluated assembly and maintenance tasks associated with several elements of the International Space Station (ISS). With the retirement of the Shuttle, completion of ISS assembly, and introduction of commercial players for human transportation to space, evaluations at the Neutral Buoyancy Laboratory (NBL) will take on a new focus. Test objectives are selected for their criticality, lack of previous testing, or design changes that justify retesting. Assembly tasks investigated are performed using procedures developed by the flight hardware providers and the Mission Operations Directorate (MOD). Orbital Replacement Unit (ORU) maintenance tasks are performed using a more systematic set of procedures, EVA Concept of Operations for the International Space Station (JSC-33408), also developed by the MOD. This paper describes the requirements and process for performing a neutral buoyancy test, including typical hardware and support equipment requirements, personnel and administrative resource requirements, examples of ISS systems and operations that are evaluated, and typical operational objectives that are evaluated.

Jairala, Juniper C.↗
DOE OSTI2024

Embedded Fluidic Sensing and Control with Soft Open‐Cell Foams

Abstract The synthesis of soft matter intelligence with circuit‐driven logic has enabled a new class of robots that perform complex tasks or conform to specialized form factors in unique ways that cannot be realized through conventional designs. Translating this hybrid approach to fluidic systems, the present work addresses the need for sheet‐based circuit materials by leveraging the innate porosity of foam—a soft material—to develop pneumatic components that support digital logic, mixed‐signal control, and analog force sensing in wearables and soft robots. Analytical tools and experimental techniques developed in this work serve to elucidate compressible gas flow through porous sheets, and to inform the design of centimeter‐sized foam resistors with fluidic resistances on the order of 10 9 Pa s m −3 . When embedded inside soft robots and wearables, these resistors facilitate diverse functionalities spanning both sensing and control domains, including digital logic using textile logic gates, digital‐to‐analog signal conversion using ladder networks, and analog sensing of forces up to 40 N via compression‐induced changes in resistance. By combining features of both circuit‐based and materials‐based approaches, foam‐enabled fluidic circuits serve as a useful paradigm for future hybrid robotic architectures that fully embody the sensing and computing capabilities of soft fluidic materials.

Rajappan, Anoop↗
DOE OSTI2021

Graphitic Aza-Fused π-Conjugated Networks: Construction, Engineering, and Task-Specific Applications

2D π-conjugated networks linked by aza-fused units represent a pivotal category of graphitic materials with stacked nanosheet architectures. Extensive efforts have been directed at their fabrication and application since the discovery of covalent triazine frameworks (CTFs). Besides the triazine cores, tricycloquinazoline and hexaazatriphenylene linkages are further introduced to tailor the structures and properties. Diverse related materials have been developed rapidly, and a thorough outlook is necessitated to unveil the structure–property–application relationships across multiple subcategories, which is pivotal to guide the design and fabrication toward enhanced task-specific performance. Herein, the structure types and development of related materials including CTFs, covalent quinazoline networks, and hexaazatriphenylene networks, are introduced. Advanced synthetic strategies coupled with characterization techniques provide powerful tools to engineer the properties and tune the associated behaviors in corresponding applications. Case studies in the areas of gas adsorption, membrane-based separation, thermo-/electro-/photocatalysis, and energy storage are then addressed, focusing on the correlation between structure/property engineering and optimization of the corresponding performance, particularly the preferred features and strategies in each specific field. In the last section, the underlying challenges and opportunities in construction and application of this emerging and promising material category are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Reward Driven Workflows for Unsupervised Explainable Analysis of Phases and Ferroic Variants From Atomically Resolved Imaging Data

Rapid progress in aberration corrected electron microscopy necessitates development of robust methods for the identification of phases, ferroic variants, and other pertinent aspects of materials structure from imaging data. While unsupervised methods for clustering and classification are widely used for these tasks, their performance can be sensitive to hyperparameter selection in the analysis workflow. In this study, the effects of descriptors and hyperparameters are explored on the capability of unsupervised ML methods to distill local structural information, exemplified by the discovery of polarization and lattice distortion in Sm − dopped BiFeO 3 (BFO) thin films. It is demonstrated that a reward-driven approach can be used to optimize these key hyperparameters across the full workflow, where rewards are designed to reflect domain wall continuity and straightness, ensuring that the analysis aligns with the material's physical behavior. This approach allows the discovery of local descriptors that are best aligned with the specific physical behavior, providing insight into the fundamental physics of materials. The reward driven workflow is further extended to disentangle structural factors of variation via an optimized variational autoencoder (VAE). Lastly, the importance of well-defined rewards is explored as a quantifiable measure of the success of the workflow.

Barakati, Kamyar [University of Tennessee, Knoxvil↗
DOE OSTI2024

Autonomous Output‐Oriented Aerosol Jet Printing Enabled by Hybrid Machine Learning

Additive manufacturing (AM) is rapidly revolutionizing modern manufacturing with recent progress in advanced printing methods and improved properties of printed materials. However, traditional AM methods are limited by their input‐oriented nature, which demands tedious trial‐and‐error tuning of printing parameters to achieve desired output properties. Here, in this work, an output‐oriented artificial intelligence‐integrated AM (AIAM) method is reported that enables an user to specify desired output properties while the printer autonomously discovers the optimal input printing parameters by integrating hybrid machine learning models and in situ measurements. Based on a predictive mapping between the input printing parameters and the output properties of interests established with <20 experiments designed by active learning, inverse design tasks are performed to intelligently generate the printing parameter settings that lead to desired outcomes using reinforcement learning. This method is demonstrated by autonomous aerosol jet printing (AJP) of conductive polymer films and achieving user‐defined electrical resistances with an ultralow error of 3.7%. The AIAM method, with its output‐oriented nature, holds the potential to significantly improve the autonomy, predictability, efficiency, and accessibility of the AM processes, which will unlock new possibilities in the autonomous and intelligent printing of a broad range of functional materials and devices.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Solving Large‐Scale Linear Systems of Equations by a Quantum Hybrid Algorithm

Abstract Today's intermediate‐scale quantum computers, although imperfect, already perform computational tasks that are manifestly beyond the capabilities of modern classical supercomputers. However, so far, quantum‐enabled large‐scale solutions have been realized only for limited set of problems. Here a hybrid algorithm based on phase estimation and classical optimization of the circuit width and depth is employed for solving a specific class of large linear systems of equations ubiquitous to many areas of science and engineering. A classification of linear systems based on the entanglement properties of the associated phase‐estimation unitary operation is introduced, enabling a highly efficient search for solutions that is facilitated by a straightforward matrix‐to‐circuit map. A 2 17 ‐dimensional problem is implemented on several IBM quantum computer superconducting quantum processors, a record‐breaking result for a linear system solved by a quantum computer. Demonstrated realisation sets a clear benchmark in the quest for the future quantum speedup in the linear systems of equations solution.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Oak Ridge OpenSHMEM Benchmark Suite

The assessment of application performance is a fundamental task in high-performance computing (HPC). The OpenSHMEM Benchmark (OSB) suite is a collection of micro-benchmarks and mini-applications/compute kernels that have been ported to use OpenSHMEM. Some, like the NPB OpenSHMEM benchmarks, have been published before while most others have been used for evaluations but never formally introduced or discussed. This suite puts them together and is useful for assessing the performance of different use cases of OpenSHMEM. This offers system implementers a useful means of measuring performance and assessing the effects of new features as well as implementation strategies. The suite is also useful for application developers to assess the performance of the growing number of OpenSHMEM implementations that are emerging. In this paper, we describe the current set of codes available within the OSB suite, how they are intended to be used, and, where possible, a snapshot of their behavior on one of the OpenSHMEM implementations available to us. We also include detailed descriptions of every benchmark and kernel, focusing on how OpenSHMEM was used. This includes details on the enhancements we made to the benchmarks to support multithreaded variants. We encourage the OpenSHMEM community to use, review, and provide feedback on the benchmarks.

Naughton III, Thomas↗
DOE OSTI2017

Performance Analysis of OpenSHMEM Applications with TAU Commander

The TAU Performance System® (TAU) is a powerful and highly versatile profiling and tracing tool ecosystem for performance engineering of parallel programs. Developed over the last twenty years, TAU has evolved with each new generation of HPC systems and scales efficiently to hundreds of thousands of cores. TAU’s organic growth has resulted in a loosely coupled software toolbox such that novice users first encountering TAU’s complexity and vast array of features are often intimidated and easily frustrated. To lower the barrier to entry for novice TAU users, ParaTools and the US Department of Energy have developed “TAU Commander,” a performance engineering workflow manager that facilitates a systematic approach to performance engineering, guides users through common profiling and tracing workflows, and offers constructive feedback in case of error. This work compares TAU and TAU Commander workflows for common performance engineering tasks in OpenSHMEM applications and demonstrates workflows targeting two different SHMEM implementations, Intel Xeon “Haswell” and “Knights Landing” processors, direct and indirect measurement methods, callsite, profiles, and traces.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Online transfer learning strategy for enhancing the scalability and deployment of deep reinforcement learning control in smart buildings

In recent years, advanced control strategies based on Deep Reinforcement Learning (DRL) proved to be effective in optimizing the management of integrated energy systems in buildings, reducing energy costs and improving indoor comfort conditions when compared to traditional reactive controllers. However, the scalability and implementation of DRL controllers are still limited since they require a considerable amount of time before converging to a near-optimal solution. This issue is currently addressed in literature through the offline pre-training of the DRL agent. However this solution results in two main critical issues: (1) the need to develop a building surrogate model to perform the training task, and (2) the need to perform a fine-tuning process over several training episodes to obtain a near-optimal control policy. In this context, this paper introduces an Online Transfer Learning (OTL) strategy that exploits two knowledge-sharing techniques, weight-initialization and imitation learning, to transfer a DRL control policy from a source office building to various target buildings in a simulation environment coupling EnergyPlus and Python. A DRL controller based on discrete Soft Actor–Critic (SAC) is trained on the source building to manage the operation of a cooling system consisting of a chiller and a thermal storage. Several target buildings are defined to benchmark the performance of the OTL strategy with that of a Rule-Based Controller (RBC) and two DRL-based control strategies, deployed in offline and online fashion. The strategy adopted for OTL emulates the real world implementation with a simulation process by implementing the transferred DRL agent for a single episode in the target buildings. Target buildings have the same geometrical features and are served by the same energy system as the source building, but differ in terms of weather conditions, electricity price schedules, occupancy patterns, and building envelope efficiency levels. The results show that the OTL strategy can reduce the cumulated sum of temperature violations on average by 50% and 80% respectively when compared to RBC and online DRL while enhancing the energy system operation with electricity cost savings ranging between 20% and 40%. Furthermore, the OTL agent performs slightly worse than the offline DRL controller but it does not require any modeling effort and can be implemented directly on target buildings emulating a real-world implementation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Differential effects of voluntary wheel running and toy rotation on the mRNA expression of neurotrophic factors and FKBP5 in a post-traumatic stress disorder rat model with the shuttle-box task

Highlights: • Running wheel or toy rotation produces almost the same behavioral effects. • The running wheel might alter PTSD-like behaviors via neurotrophic factors. • Toy rotation might alter PTSD-like behaviors via the HPA system. Life-threatening experiences can result in the development of post-traumatic stress disorder. We have developed an animal model for post-traumatic stress disorder (PTSD) using a shuttle box in rats. In this paradigm, the rats were exposed to inescapable foot-shock stress (IS) in a shuttle box, and then an avoidance/escape task was performed in the same box 2 weeks after IS. A previous study using this paradigm revealed that environmental enrichment (EE) ameliorated avoidance/numbing-like behaviors, but not hyperarousal-like behaviors, and EE also elevated hippocampal brain-derived neurotrophic factor (BDNF) expression. However, the differential effects of EE components, i.e., running wheel (RW) or toy rotation, on PTSD-like behaviors has remained unclear. In this experiment, we demonstrated that RW, toy rotation, and EE (containing RW and toy rotation) ameliorated avoidance/numbing-like behaviors, induced learning of avoidance responses, and improved depressive-like behaviors in traumatized rats. The RW increased the hippocampal mRNA expression of neurotrophic factors, especially BDNF and glial-cell derived neurotrophic factor. Toy rotation influenced FK506 binding protein 5 mRNA expression, which is believed to be a regulator of the hypothalamic-pituitary-adrenal (HPA)-axis system, in the hippocampus and amygdala. This is the first report to elucidate the differential mechanistic effects of RW and toy rotation. The former appears to exert its effects via neurotrophic factors, while the latter exerts its effects via the HPA axis. Further studies will lead to a better understanding of the influence of environmental factors on PTSD.

60 APPLIED LIFE SCIENCES↗