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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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At least 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Auto-Gopher-II – An Autonomous Wireline Rotary-Hammer Ultrasonic Drill

Developing technologies that would enable future NASA exploration missions to penetrate deeper into the subsurface of planetary bodies for sample collection is of great importance. Performing these tasks while using minimal mass/volume systems and with low energy consumption is another set of requirements imposed on such technologies. A deep drill, called Auto-Gopher II, is currently being developed as a joint effort between JPL’s NDEAA laboratory and Honeybee Robotics Corp. The Auto-Gopher II is a wireline rotary-hammer drill that combines formation breaking by hammering using an ultrasonic actuator and cuttings removal by rotating a fluted auger bit. The hammering mechanism is based on the Ultrasonic/Sonic Drill/Corer (USDC) mechanism that has been developed as an adaptable tool for many drilling and coring applications. The USDC uses an intermediate free-flying mass to transform high frequency vibrations of a piezoelectric transducer horn tip into sonic hammering of the drill bit. The USDC concept was used in a previous task to develop an Ultrasonic/Sonic Ice Gopher and then integrated into a rotary hammer device to develop the Auto-Gopher-I. The lessons learned from these developments are being integrated into the development of the Auto-Gopher-II, an autonomous deep wireline drill with integrated cuttings and sample management and drive electronics. Subsystems of the wireline drill are being developed in parallel at JPL and Honeybee Robotics Ltd. This paper presents the development efforts of the piezoelectric actuator, cuttings removal and retention flutes and drive electronics.

Badescu, Mircea↗
DOE OSTI2015

Investigation robot on cables - 15250

The Decontamination and Decommissioning (D and D) Operations take place in hostile environments to the human intervention. In this context, robotic systems are a solution to achieve these operations while minimizing human intervention. Among these operations, the monitoring of lengthwise plant has to be performed in places where the radioactive contaminations make hostile environments. These monitoring operations need to measure several physics parameters in several locations in a precise and safe manner. These repetitive tasks can be made by robots that are simple, small sized and easily adaptable. In this scope, a robotic system on cables has been designed to control and monitor the inside of lengthwise nuclear facilities. In lengthwise installations, the using of cables allows to increase the covered zone of the robots which is an essential quality in such places. Unlike cable-driven parallel robots used in workspaces of 2D or 3D controlled by redundant tensioning motors, the current robot moves in a 1D workspace. Thus a tractors cable controlled by one tensioning motor is used to drive the robot on carrier cables. In this paper, we will describe the first results of this work by bringing out the innovation of our system. Then, we will discuss the perspective to upgrade the actual system whose applications could be perfectly imagined outside the nuclear D and D industry. (authors)

42 ENGINEERING↗
DOE OSTI2020

FPDeep: Scalable Acceleration of CNN Training on Deeply-Pipelined FPGA Clusters

In this paper, we propose a framework called FPDeep, which uses a hybrid of model and layer paral- lelism to configure distributed reconfigurable clusters to train DNNs. This approach has numerous benefits. First, the design does not suffer from batch size growth. Second, novel workload and weight partitioning leads to balanced loads of both among nodes. And third, the entire system is fine-grained pipeline. This leads to high parallelism and utilization and also minimizes the time features need to be cached while waiting for back-propagation.

Wang, Tianqi↗
DOE OSTI2021

srMO-BO-3GP: A sequential regularized multi-objective Bayesian optimization for constrained design applications using an uncertain Pareto classifier

Bayesian optimization (BO) is an efficient and flexible global optimization framework that is applicable to a very wide range of engineering applications. To leverage the capability of the classical BO, many extensions, including multi-objective, multi-fidelity, parallelization, and latent-variable modeling, have been proposed to address the limitations of the classical BO framework. In this work, we propose a novel multi-objective BO formalism, called srMO-BO-3GP, to solve multi-objective optimization problems in a sequential setting. Three different Gaussian processes (GPs) are stacked together, where each of the GPs is assigned with a different task. The first GP is used to approximate a single-objective computed from the multi-objective definition, the second GP is used to learn the unknown constraints, and the third one is used to learn the uncertain Pareto frontier. At each iteration, a multi-objective augmented Tchebycheff function is adopted to convert multi-objective to single-objective, where the regularization with a regularized ridge term is also introduced to smooth the single-objective function. Finally, we couple the third GP along with the classical BO framework to explore the convergence and diversity of the Pareto frontier by the acquisition function for exploitation and exploration. The proposed framework is demonstrated using several numerical benchmark functions, as well as a thermomechanical finite element model for flip-chip package design optimization.

42 ENGINEERING↗
NASA NTRS1992

Modeling, simulation, and high-autonomy control of a Martian oxygen production plant

Progress on a project for the development of a high-autonomy intelligent command and control architecture for process plants used to produce oxygen from local planetary resources is reported. A distributed command and control architecture is being developed and implemented so that an oxygen production plant, or other equipment, can be reliably commanded and controlled over an extended time period in a high-autonomy mode with high-level task-oriented teleoperation from one or several remote locations. During the reporting period, progress was made at all levels of the architecture. At the remote site, several remote observers can now participate in monitoring the plant. At the local site, a command and control center was introduced for increased flexibility, reliability, and robustness. The local control architecture was enhanced to control multiple tubes in parallel, and was refined for increased robustness. The simulation model was enhanced to full dynamics descriptions.

Schooley, L. C.↗
DOE OSTI2018

Modeling Large-Scale Slim Fly Networks Using Parallel Discrete-Event Simulation

As supercomputers approach exascale performance, the increased number of processors translates to an increased demand on the underlying network interconnect. We present that the slim fly network topology, a new low-diameter, low-latency, and low-cost interconnection network, is gaining interest as one possible solution for next-generation supercomputing interconnect systems. In this article, we present a high-fidelity slim fly packet-level model leveraging the Rensselaer Optimistic Simulation System (ROSS) and Co-Design of Exascale Storage (CODES) frameworks. We validate the model with published work before scaling the network size up to an unprecedented 1 million compute nodes and confirming that the slim fly observes peak network throughput at extreme scale. In addition to synthetic workloads, we evaluate large-scale slim fly models with real communication workloads from applications in the Design Forward program with over 110,000 MPI processes. We show strong scaling of the slim fly model on an Intel cluster achieving a peak network packet transfer rate of 2.3 million packets per second and processing over 7 billion discrete events using 128 MPI tasks. Enabled by the strong performance capabilities of the model, we perform a detailed application trace and routing protocol performance study. Lastly, through analysis of metrics such as packet latency, hop count, and congestion, we find that the slim fly network is able to leverage simple minimal routing and achieve the same performance as more complex adaptive routing for tested DOE benchmark applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

LANL/LLNL 240 Pu( n,f ) Prompt Fission Neutron Spectrum Measurement (Q4 FY2022 Progress Report)

The report details the joint LANL/LLNL measurement of the 240 Pu( n,f ) prompt fission neutron spectrum (PFNS) for incident neutron energies from 1–20 MeV. A summary of the experimental setup, including details of the parallel-plate avalanche counter (PPAC) used for this experiment, beam time awarded and received, and adaptations made for specifically for this experiment are described in Sec. II. Some preliminary results obtained with a portion of the total available statistics from the executed experiment are then described in Sec. III with a discussion of potential benefits and losses if more data were collected. Finally, some primary tasks remaining to convert these data to final results are discussed in Sec. IV.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1994

Integrating planning and reactive control

Our research is developing persistent agents that can achieve complex tasks in dynamic and uncertain environments. We refer to such agents as taskable, reactive agents. An agent of this type requires a number of capabilities. The ability to execute complex tasks necessitates the use of strategic plans for accomplishing tasks; hence, the agent must be able to synthesize new plans at run time. The dynamic nature of the environment requires that the agent be able to deal with unpredictable changes in its world. As such, agents must be able to react to unanticipated events by taking appropriate actions in a timely manner, while continuing activities that support current goals. The unpredictability of the world could lead to failure of plans generated for individual tasks. Agents must have the ability to recover from failures by adapting their activities to the new situation, or replanning if the world changes sufficiently. Finally, the agent should be able to perform in the face of uncertainty. The Cypress system, described here, provides a framework for creating taskable, reactive agents. Several features distinguish our approach: (1) the generation and execution of complex plans with parallel actions; (2) the integration of goal-driven and event driven activities during execution; (3) the use of evidential reasoning for dealing with uncertainty; and (4) the use of replanning to handle run-time execution problems. Our model for a taskable, reactive agent has two main intelligent components, an executor and a planner. The two components share a library of possible actions that the system can take. The library encompasses a full range of action representations, including plans, planning operators, and executable procedures such as predefined standard operating procedures (SOP's). These three classes of actions span multiple levels of abstraction.

Wilkins, David E.↗
NASA NTRS1994

Robotic Vehicle

A commercially available ANDROS Mark V-A robot was used by Jet Propulsion Laboratory (JPL) as the departure point in the development of the HAZBOT III, a prototype teleoperated mobile robot designed for response to emergencies. Teleoperated robots contribute significantly to reducing human injury levels by performing tasks too hazardous for humans. ANDROS' manufacturer, REMOTEC, Inc., in turn, adopted some of the JPL concepts, particularly the control panel. HAZBOT III has exceptional mobility, employs solid state electronics and brushless DC motors for safer operation, and is designed so combustible gases cannot penetrate areas containing electronics and motors. Other features include the six-degree-of-freedom manipulator, the 30-pound squeeze force parallel jaw gripper and two video cameras, one for general viewing and navigation and the other for manipulation/grasping.

Source record↗
DOE OSTI2019

Lazy Shadowing: An Adaptive, Power-Aware, Resiliency Framework for Extreme Scale Computing

The inherent instability of extreme-scale computing systems puts into question the viability of traditional fault-tolerance methods and calls for a reconsideration of the fault-tolerance and power-awareness problem, at scale. This project explores a novel paradigm, Lazy Shadowing, to achieve high resiliency in future extreme-scale systems. The basic tenet of Lazy Shadowing is the association of a shadow with each process which runs in parallel, but on a different node and at a reduced execution rate, than its associated process. The successful completion of the main process causes the immediate termination of the shadow, resulting in significant energy savings. Upon failure of the main process, however, the shadow’s execution rate is increased so that it completes by the expected completion time without significantly impacting the progress of the remaining tasks. Different approaches can be used to control execution rate, including co-locating multiple shadows on a single computing node and/or using Dynamic Voltage and Frequency Scaling.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

User Manual - HydraGNN v5.0: Distributed Implementation of Multi-Tasking Graph Neural Networks

This document serves as the user manual for HydraGNN v5.0, a scalable graph neural network (GNN) architecture for simultaneous prediction of multiple target properties using multi-task learning (MTL). This version of HydraGNN has been developed primarily to support the development, training, and deployment of predictive graph-based deep learning (DL) models for atomistic materials modeling. HydraGNN is templated over 13 message-passing policies, including invariant models (GIN, PNA, PNAPlus, GAT, MFC, CGCNN, SAGE, SchNet, DimeNet) and equivariant models (EGNN, PNAEq, PAINN, MACE), and supports distributed training via distributed data parallelism (DDP), DeepSpeed, and Fully Sharded Data Parallelism (FSDP) on leadership-class supercomputers. Although HydraGNN can be applied to problems beyond atomistic materials modeling, its current use is confined to homogeneous graphs. Additional capabilities include machine-learned interatomic potentials with energy-conserving forces, General, Powerful, and Scalable Graph Transformer (GraphGPS) global attention, periodic boundary conditions, hyperparameter optimization, mixed-precision training, and uncertainty quantification.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1986

Two-dimensional nonsteady viscous flow simulation on the Navier-Stokes computer miniNode

The needs of large-scale scientific computation are outpacing the growth in performance of mainframe supercomputers. In particular, problems in fluid mechanics involving complex flow simulations require far more speed and capacity than that provided by current and proposed Class VI supercomputers. To address this concern, the Navier-Stokes Computer (NSC) was developed. The NSC is a parallel-processing machine, comprised of individual Nodes, each comparable in performance to current supercomputers. The global architecture is that of a hypercube, and a 128-Node NSC has been designed. New architectural features, such as a reconfigurable many-function ALU pipeline and a multifunction memory-ALU switch, have provided the capability to efficiently implement a wide range of algorithms. Efficient algorithms typically involve numerically intensive tasks, which often include conditional operations. These operations may be efficiently implemented on the NSC without, in general, sacrificing vector-processing speed. To illustrate the architecture, programming, and several of the capabilities of the NSC, the simulation of two-dimensional, nonsteady viscous flows on a prototype Node, called the miniNode, is presented.

Nosenchuck, Daniel M.↗
NASA NTRS1989

Concurrent processing simulation of the space station

The development of a new capability for the time-domain simulation of multibody dynamic systems and its application to the study of a large angle rotational maneuvers of the Space Station is described. The effort was divided into three sequential tasks, which required significant advancements of the state-of-the art to accomplish. These were: (1) the development of an explicit mathematical model via symbol manipulation of a flexible, multibody dynamic system; (2) the development of a methodology for balancing the computational load of an explicit mathematical model for concurrent processing; and (3) the implementation and successful simulation of the above on a prototype Custom Architectured Parallel Processing System (CAPPS) containing eight processors. The throughput rate achieved by the CAPPS operating at only 70 percent efficiency, was 3.9 times greater than that obtained sequentially by the IBM 3090 supercomputer simulating the same problem. More significantly, analysis of the results leads to the conclusion that the relative cost effectiveness of concurrent vs. sequential digital computation will grow substantially as the computational load is increased. This is a welcomed development in an era when very complex and cumbersome mathematical models of large space vehicles must be used as substitutes for full scale testing which has become impractical.

Gluck, R.↗
NASA NTRS1989

Multitasking a three-dimensional Navier-Stokes algorithm on the Cray-2

A three-dimensional computational aerodynamics algorithm has been multitasked for efficient parallel execution on the Cray-2. It provides a means for examining the multitasking performance of a complete CFD application code. An embedded zonal multigrid scheme is used to solve the Reynolds-averaged Navier-Stokes equations for an internal flow model problem. The explicit nature of each component of the method allows a spatial partitioning of the computational domain to achieve a well-balanced task load for MIMD computers with vector-processing capability. Experiments have been conducted with both two- and three-dimensional multitasked cases. The best speedup attained by an individual task group was 3.54 on four processors of the Cray-2, while the entire solver yielded a speedup of 2.67 on four processors for the three-dimensional case. The multiprocessing efficiency of various types of computational tasks is examined, performance on two Cray-2s with different memory access speeds is compared, and extrapolation to larger problems is discussed.

Swisshelm, Julie M.↗
NASA NTRS1992

Domain specific software design for decision aiding

McDonnell Aircraft Company (MCAIR) is involved in many large multi-discipline design and development efforts of tactical aircraft. These involve a number of design disciplines that must be coordinated to produce an integrated design and a successful product. Our interpretation of a domain specific software design (DSSD) is that of a representation or framework that is specialized to support a limited problem domain. A DSSD is an abstract software design that is shaped by the problem characteristics. This parallels the theme of object-oriented analysis and design of letting the problem model directly drive the design. The DSSD concept extends the notion of software reusability to include representations or frameworks. It supports the entire software life cycle and specifically leads to improved prototyping capability, supports system integration, and promotes reuse of software designs and supporting frameworks. The example presented in this paper is the task network architecture or design which was developed for the MCAIR Pilot's Associate program. The task network concept supported both module development and system integration within the domain of operator decision aiding. It is presented as an instance where a software design exhibited many of the attributes associated with DSSD concept.

Keller, Kirby↗
NASA NTRS1992

On the transmission of partial information: inferences from movement-related brain potentials

Results are reported from a new paradigm that uses movement-related brain potentials to detect response preparation based on partial information. The paradigm uses a hybrid choice-reaction go/nogo procedure in which decisions about response hand and whether to respond are based on separate stimulus attributes. A lateral asymmetry in the movement-related brain potential was found on nogo trials without overt movement. The direction of this asymmetry depended primarily on the signaled response hand rather than on properties of the stimulus. When the asymmetry first appeared was influenced by the time required to select the signaled hand, and when it began to differ on go and nogo trials was influenced by the time to decide whether to respond. These findings indicate that both stimulus attributes were processed in parallel and that the asymmetry reflected preparation of the response hand that began before the go/nogo decision was completed.

NASA Discipline Space Human Factors↗
NASA NTRS2007

Radiation Hardened Electronics for Extreme Environments

The Radiation Hardened Electronics for Space Environments (RHESE) project consists of a series of tasks designed to develop and mature a broad spectrum of radiation hardened and low temperature electronics technologies. Three approaches are being taken to address radiation hardening: improved material hardness, design techniques to improve radiation tolerance, and software methods to improve radiation tolerance. Within these approaches various technology products are being addressed including Field Programmable Gate Arrays (FPGA), Field Programmable Analog Arrays (FPAA), MEMS Serial Processors, Reconfigurable Processors, and Parallel Processors. In addition to radiation hardening, low temperature extremes are addressed with a focus on material and design approaches.

Keys, Andrew S.↗
NASA NTRS2008

Technology Developments in Radiation-Hardened Electronics for Space Environments

The Radiation Hardened Electronics for Space Environments (RHESE) project consists of a series of tasks designed to develop and mature a broad spectrum of radiation hardened and low temperature electronics technologies. Three approaches are being taken to address radiation hardening: improved material hardness, design techniques to improve radiation tolerance, and software methods to improve radiation tolerance. Within these approaches various technology products are being addressed including Field Programmable Gate Arrays (FPGA), Field Programmable Analog Arrays (FPAA), MEMS, Serial Processors, Reconfigurable Processors, and Parallel Processors. In addition to radiation hardening, low temperature extremes are addressed with a focus on material and design approaches. System level applications for the RHESE technology products are discussed.

Keys, Andrew S.↗