SEARCH · Engineering Papers

Results for “Operator learning”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,459 records · Page 81

All sources NASA NTRS DOE OSTI

DOE OSTI2021

Prediction of DIII-D Pedestal Structure From Externally Controllable Parameters

The sharp increase of pressure at the edge of a high confinement mode (H-mode) plasma, the pedestal, strongly impacts overall plasma performance. Predicting the pedestal is a necessity to control and optimize tokamak operations. Here, an experimental data-driven machine learning (ML) approach is presented that predicts the pedestal heights and widths of electron density (n e ) and electron temperature (T e ) profiles as well as the separatrix ne from externally controllable parameters such as the plasma shape, heating method and power, and gas puff rate and integrated gas puff. The OMFIT framework was used with DIII-D data to efficiently, robustly, and automatically build a database of pedestal parameters to train machine learning models. Database creation was enabled by the search engine tool for DIII-D data, TokSearch, which parallelizes data fetching, enabling fast searches through basic signals of thousands of DIII-D shots and selection of relevant time intervals. Principal Component Analysis (PCA) separated the database into three clusters that represent classes of plasma shapes that are regularly used in DIII-D. The most important parameters for setting the pedestal structure were plasma current (I p ), toroidal magnetic field (B Φ ), neutral beam heating power (P NBI ) and shaping quantities. The Deep Jointly Informed Neural Networks (DJINN) algorithm was applied to identify suitable neural network (NN) architectures that appropriately capture the features of the pedestal database. Separate NNs were implemented for each pedestal parameter, and ensembling methods were used to improve the prediction accuracy and allowed estimation of the prediction uncertainty. The pedestal predictions of the test dataset lie within the measurement uncertainties of the pedestal parameters. The NN outperformed simple Linear Regression (LR) analysis, indicating non-linear dependencies in the pedestal structure. The presented achievements illustrate a promising path for future research, using feature extraction to infer experimental trends and thereby improve pedestal models as well as deploying NN for a fast pedestal prediction in DIII-D scenario development.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Branching Dueling Q-Network Based Online Scheduling of a Microgrid With Distributed Energy Storage Systems

This letter investigates a Branching Dueling Q-Network (BDQ) based online operation strategy for a microgrid with distributed battery energy storage systems (BESSs) operating under uncertainties. Additionally, the developed deep reinforcement learning (DRL) based microgrid online optimization strategy can achieve a linear increase in the number of neural network outputs with the number of distributed BESSs, which overcomes the curse of dimensionality caused by the charge and discharge decisions of multiple BESSs. Numerical simulations validate the effectiveness of the proposed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Bindee

Bindee is a clang tool that outputs a simple pybind11 template given a C++ file for efficient generation of C++-Python bindings. Bindee is intended to be a helper tool for minimizing initial user effort and safeguarding against common runtime errors. Bindee relies on two open-source software to produce bindings. Clang's LibTooling enables bindee to traverse a C++ file's AST to pick out bindable variables and functions, or "bindees." PyBind11 is templated, header-only library for generating C++-Python bindings for variables and functions. Operating purely in C++, bindee does not require learning any new API for accomplishing its task. Additionally, picking the correct pybind11 API for a given bindable element is handled without interaction from the user. Any user input is denoted by '@TEXT@' string substitution. Bindee is capable of generating modular bindings for public class methods, public class variables, enumerations, and free functions and variables. Bindings for templates are also supported. For those familiar with pybind11, bindee does not handle trampolines, C++ extensions through lambdas, or custom type casters.

Kimkno, JasonS.↗

DOE OSTI2016

Non-destructive Quantitative Phase Analysis and Microstructural Characterization of Zirconium Coated U-10Mo Fuel Foils via Neutron Diffraction

This report uses neutron diffraction to investigate the crystal phase composition of uranium-molybdenum alloy foils (U-10Mo) for the CONVERT MP-1 Reactor Conversion Project, and determines the effect on alpha-uranium contamination following the deposition of a Zr metal diffusion layer by various methods: plasma spray deposition of Zr powders at LANL and hot co-rolling with Zr foils at BWXT. In summary, there is minimal decomposition of the gamma phase U-10Mo foil to alpha phase contamination following both plasma spraying and hot co-rolling. The average unit cell volume, i.e. lattice spacing, of the Zr layer can be mathematically extracted from the diffraction data; co-rolled Zr matches well with literature values of bulk Zr, while plasma sprayed Zr shows a slight increase in the lattice spacing, indicative of interstitial oxygen in the lattice. Neutron diffraction is a beneficial alternative to conventional methods of phase composition, i.e. x ray diffraction (XRD) and destructive metallography. XRD has minimal penetration depth in high atomic number materials, particularly uranium, and can only probe the first few microns of the fuel plate; neutrons pass completely through the foil, allowing for bulk analysis of the foil composition and no issues with addition of cladding layers, as in the final, aluminum-clad reactor fuel plates. Destructive metallography requires skilled technicians, cutting of the foil into small sections, hazardous etching conditions, long polishing and microscopy times, etc.; the neutron diffraction system has an automated sample loader and can fit larger foils, so there is minimal analysis preparation; the total spectrum acquisition time is ~ 1 hour per sample. The neutron diffraction results are limited by spectra refinement/calculation times and the availability of the neutron beam source. In the case of LANSCE at Los Alamos, the beam operates ~50% of the year. Following the lessons learned from these preliminary results, optimizations to the process and analysis can be made, and neutron diffraction can become a viable and efficient technique for gamma/alpha phase composition determination for nuclear fuels.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2019

Underground Natural Gas Storage - Analog Studies to Geologic Storage of CO 2

The purpose of this report is to compile a stand-alone body of knowledge regarding historical and current underground natural gas storage operations that may be directly or indirectly relevant to carbon dioxide (CO 2 ) geologic storage in saline-bearing formations. This is the first of three planned documents that evaluate analog industries of CO 2 storage (the second focuses on wastewater disposal using United States [U.S.] Environmental Protection Agency [EPA] Underground Injection Control [UIC] Class I disposal wells, and the third on CO 2 enhanced oil recovery). Natural gas has been stored underground for over 100 years. This type of storage is necessary for meeting seasonal demand requirements as well as insuring against unforeseen supply disruptions. There are significant similarities that exist between natural gas storage and CO 2 geologic storage (and full-scale carbon capture and storage [CCS]) in terms of site selection and characterization, as well as operational procedures, and the equipment used. Therefore, the extensive operational history of underground natural gas storage operations provides a wealth of knowledge and lessons learned from which CO 2 storage stakeholders in industry, academia, and policy can benefit.

03 NATURAL GAS↗

DOE OSTI2021

Module 10 Reactor Physics

Students will gain a understanding of some basic reactor physics concepts, which will prepare them for learning more detailed concepts about the design and operations of the experiments performed using the NCERC critical assemblies.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2022

SMALE: Enhancing Scalability of Machine Learning Algorithms on Extreme-Scale Computing Platforms

Deployment and execution of machine learning tasks on extreme-scale computing platforms face several significant technical challenges: 1) High computing cost incurred by dense networks – The computing workload of deep networks with densely-connected topology increases rapidly with the network size, imposing a non-scalable computing model of extreme-scale computing platforms; 2) Non-optimized workload distribution – Many advanced deep learning algorithms, e.g., sparsification and irregular net-work topology, produce very unbalanced workload distribution on extreme-scale computing platforms. The computation efficiency is greatly hindered by the incurred data and computation redundancies as well as long tails of the node with extensive workload; 3) Constraints in data movement and I/O bottle-neck – Inter-node data movement in extreme-scale computing platforms are associated with high energy and latency costs, and subject to the constraints of I/O bandwidth; and 4) Generalization of algorithm realization and acceleration on computing platforms – The large varieties of machine learning algorithms and structures of extreme-scale computing platforms make the derivation of a generalized algorithm realization and acceleration method very challenging, which, however, is the requirement by domain scientists and interested users. We call the above challenges Smale’s Problems in Machine Learning and Understanding for High-Performance Computing Scientific Discovery. The objective of our three-year research project is to develop a holistic innovation set at structure, assembly, and acceleration layers of machine learning algorithms to address the above challenges in algorithm deployment and execution. Three tasks are particularly performed, including: At the algorithm structure level, we investigate the techniques that can structurally sparsify on the topology of deep networks for computing workload reduction. We also study clustering and pruning techniques that can optimize the workload distributions over the extreme-scale computing platforms; At the algorithm assembly level, we derive a unified learning framework for unsupervised transfer learning and dynamic growing capabilities. Novel training methods are also exploited to enhance the training efficiency of the proposed framework; At the algorithm acceleration level, we will develop a series of techniques that can accelerate the computation of sparse matrix operations, which are one of the core executions in deep learning and optimize memory access of the concerned platforms. Our proposed techniques attack the fundamental problems in machine learning algorithms running on extreme-scale computing platforms by vertically integrating the solutions at three closely entangled layers, paving the long-term scaling path of machine learning applications under DOE context. Three tasks corresponding to the above respective research orientations are performed during the three-year project period with our collaborators at ORNL. The outcome of the proposed project is anticipated to form a holistic solution set of novel algorithms and network topologies, efficient training techniques, and fast acceleration methods to promote the computing scalability of the machine learning applications of particular interest to DOE.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

BETO Visit: Investigating Large-Scale Cultivation Processes [Slides]

Questions: How important is density management in a scaled system?; What processes are currently proposed/used, and how are they deployed?; What sort of information (tools/experimentation) would be helpful?; What can be learned that can inform better strain, cultivation systems, operations and tools development for increased productivities?; Beginning with the end in mind?

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Development and Validation of Home Comfort System for Total Performance Deficiency/Fault Detection and Optimal Comfort Control

In this project, we developed and tested a learning-based home thermal model that facilitates the operation of a model predictive control (MPC)-based optimization agent and an automated fault detection and diagnosis (AFDD) agent. The home thermal model was constructed using a two-node resistor-capacitor model. Moreover, two accompanying parameter identification methods were introduced, least-squares and optimization. Based on the home thermal model, the MPC-based optimization agent was developed to optimize residential HVAC operation. Using two FDD methods, the AFDD agent was constructed to detect and diagnose two prevalent residential AC faults, airflow reduction and refrigerant undercharge. The home thermal model, along with the MPC-based optimization agent and AFDD agent, were tested at the Norman Test House, Miami Test House, Pacific Northwest National Laboratory (PNNL) Test House A, and PNNL Test House B. Finally, they were also field tested in nine demonstration homes with real occupants.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS1963

NASA Facility for the Study of Space Radiation Effects

Space particulate radiation from the Van Allen belts, solar flares, galactic cosmic, and manmade sources have energies and fluxes which are capable of producing damage in space mission payloads. NASA - Langley Research Center, Hampton, Virginia, has initiated the construction of a ground-based Space Radiation Effects Laboratory which simulates most of the space particulate energy spectrum and which can be used in a radiation research program for minimizing or eliminating deleterious radiation effects. A 600-megaelectronvolt synchrocyclotron of variable energy and electron accelerators from 1 to 10 megaelectronvolts will be included in the laboratory for accelerated testing. The plan of the proposed test areas reflects the latest advances in the state of the art as it pertains to the engineering and basic experimental requirements in flexibility, radiation background levels, shielding, and isolation. The laboratory operational plan permits three Virginia institutions of higher learning to cooperate with the Langley Research Center in carrying out radiation programs.

RADIATION EFFECT↗

NASA NTRS1984

Solar Total Energy Project (STEP) Performance Analysis of High Temperature Energy Storage Subsystem

The 1982 milestones and lessons learned; performance in 1983; a typical day's operation; collector field performance and thermal losses; and formal testing are highlighted. An initial test that involves characterizing the high temperature storage (hts) subsystem is emphasized. The primary element is on 11,000 gallon storage tank that provides energy to the steam generator during transient solar conditions or extends operating time. Overnight, thermal losses were analyzed. The length of time the system is operated at various levels of cogeneration using stored energy is reviewed.

Moore, D. M.↗

NASA NTRS1987

The desktop interface in intelligent tutoring systems

The interface between an Intelligent Tutoring System (ITS) and the person being tutored is critical to the success of the learning process. If the interface to the ITS is confusing or non-supportive of the tutored domain, the effectiveness of the instruction will be diminished or lost entirely. Consequently, the interface to an ITS should be highly integrated with the domain to provide a robust and semantically rich learning environment. In building an ITS for ZetaLISP on a LISP Machine, a Desktop Interface was designed to support a programming learning environment. Using the bitmapped display, windows, and mouse, three desktops were designed to support self-study and tutoring of ZetaLISP. Through organization, well-defined boundaries, and domain support facilities, the desktops provide substantial flexibility and power for the student and facilitate learning ZetaLISP programming while screening the student from the complex LISP Machine environment. The student can concentrate on learning ZetaLISP programming and not on how to operate the interface or a LISP Machine.

Baudendistel, Stephen↗

NASA NTRS1991

An Intelligent Computer-aided Training System (CAT) for Diagnosing Adult Illiterates: Integrating NASA Technology into Workplace Literacy

Yaden, David B., Jr.↗

NASA NTRS1992

The adult literacy evaluator: An intelligent computer-aided training system for diagnosing adult illiterates

An important part of NASA's mission involves the secondary application of its technologies in the public and private sectors. One current application being developed is The Adult Literacy Evaluator, a simulation-based diagnostic tool designed to assess the operant literacy abilities of adults having difficulties in learning to read and write. Using ICAT system technology in addition to speech recognition, closed-captioned television (CCTV), live video and other state-of-the art graphics and storage capabilities, this project attempts to overcome the negative effects of adult literacy assessment by allowing the client to interact with an intelligent computer system which simulates real-life literacy activities and materials and which measures literacy performance in the actual context of its use. The specific objectives of the project are as follows: (1) To develop a simulation-based diagnostic tool to assess adults' prior knowledge about reading and writing processes in actual contexts of application; (2) to provide a profile of readers' strengths and weaknesses; and (3) to suggest instructional strategies and materials which can be used as a beginning point for remediation. In the first and developmental phase of the project, descriptions of literacy events and environments are being written and functional literacy documents analyzed for their components. Examples of literacy events and situations being considered included interactions with environmental print (e.g., billboards, street signs, commercial marquees, storefront logos, etc.), functional literacy materials (e.g., newspapers, magazines, telephone books, bills, receipts, etc.) and employment related communication (i.e., job descriptions, application forms, technical manuals, memorandums, newsletters, etc.). Each of these situations and materials is being analyzed for its literacy requirements in terms of written display (i.e., knowledge of printed forms and conventions), meaning demands (i.e., comprehension and word knowledge) and social situation. From these descriptions, scripts are being generated which define the interaction between the student, an on-screen guide and the simulated literacy environment. The proposed outcome of the Evaluator is a diagnostic profile which will present broad classifications of literacy behaviors across the major areas of metacognitive abilities, word recognition, vocabulary knowledge, comprehension and writing. From these classifications, suggestions for materials and strategies for instruction with which to begin corrective action will be made. The focus of the Literacy Evaluator will be essentially to provide an expert diagnosis and an interpretation of that assessment which then can be used by a human tutor to further design and individualize a remedial program as needed through the use of an authoring system.

Yaden, David B., Jr.↗

NASA NTRS1994

Software interface verifier

A Telos study of 40 recent subsystem deliveries into the DSN at JPL found software interface testing to be the single most expensive and error-prone activity, and the study team suggested creating an automated software interface test tool. The resulting Software Interface Verifier (SIV), which was funded by NASA/JPL and created by Telos, employed 92 percent software reuse to quickly create an initial version which incorporated early user feedback. SIV is now successfully used by developers for interface prototyping and unit testing, by test engineers for formal testing, and by end users for non-intrusive data flow tests in the operational environment. Metrics, including cost, are included. Lessons learned include the need for early user training. SIV is ported to many platforms and can be successfully used or tailored by other NASA groups.

Soderstrom, Tomas J.↗

NASA NTRS1998

Simple Automatic File Exchange (SAFE) to Support Low-Cost Spacecraft Operation via the Internet

Various issues associated with Simple Automatic File Exchange (SAFE) are presented in viewgraph form. Specific topics include: 1) Packet telemetry, Internet IP networks and cost reduction; 2) Basic functions and technical features of SAFE; 3) Project goals, including low-cost satellite transmission to data centers to be distributed via an Internet; 4) Operations with a replicated file protocol; 5) File exchange operation; 6) Ground stations as gateways; 7) Lessons learned from demonstrations and tests with SAFE; and 8) Feedback and future initiatives.

Baker, Paul↗

NASA NTRS1998

X-34 Main Propulsion System Design and Operation

The X-34 program is a joint industry/government program to develop, test, and operate a small, fully-reusable hypersonic flight vehicle, utilizing technologies and operating concepts applicable to future Reusable Launch Vehicle (RLV) systems. The vehicle will be capable of Mach 8 flight to 250,000 feet altitude and will demonstrate an all composite structure, composite RP-1 tank, the Marshall Space Flight Center (MSFC) developed Fastrac engine, and the operability of an advanced thermal protection systems. The vehicle will also be capable of carrying flight experiments. MSFC is supporting the X-34 program in three ways: Program Management, the Fastrac engine as Government Furnished Equipment (GFE), and the design of the Main Propulsion System (MPS). The MPS Product Development Team (PDT) at MSFC is responsible for supplying the MPS design, analysis, and drawings to Orbital. The MPS consists of the LOX and RP-1 Fill, Drain, Feed, Vent, & Dump systems and the Helium & Nitrogen Purge, Pressurization, and Pneumatics systems. The Reaction Control System (RCS) design was done by Orbital. Orbital is the prime contractor and has responsibility for integration, procurement, and construction of all subsystems. The paper also discusses the design, operation, management, requirements, trades studies, schedule, and lessons learning with the MPS and RCS designs.

Champion, R. J., Jr.↗

NASA NTRS2003

Development and Utility of a Piloted Flight Simulator for Icing Effects Training

A piloted flight simulator called the Ice Contamination Effects Flight Training Device (ICEFTD), which uses low cost desktop components and a generic cockpit replication is being developed. The purpose of this device is to demonstrate the effectiveness of its use for training pilots to recognize and recover from aircraft handling anomalies that result from airframe ice formations. High-fidelity flight simulation models for various baseline (non-iced) and iced configurations were developed from wind tunnel tests of a subscale DeHavilland DHC-6 Twin Otter aircraft model. These simulation models were validated with flight test data from the NASA Twin Otter Icing Research Aircraft, which included the effects of ice on wing and tail stall characteristics. These simulation models are being implemented into an ICEFTD that will provide representative aircraft characteristics due to airframe icing. Scenario-based exercises are being constructed to give an operational-flavor to the simulation. Training pilots will learn to recognize iced aircraft characteristics from the baseline, and will practice and apply appropriate recovery procedures to a handling event.

Ratvasky, Thomas P.↗