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At least 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Leveraging M and S in Soft Skills Training for the DoD

Soft skills, also called "people skills," are typically hard to observe, quantify and measure. These skills have to do with how we relate to each other; communicating, listening, engaging in dialogue, giving feedback, cooperating as a team member, solving problems and resolving conflicts. Most of the soft skills training is scenario based, utilizing written or video-based scenarios. with limited or no branching, as well as quantitative feedback. This paper will outline a game-based approach to configurable, scenario-based, soft skills training. The paper will discuss the application of realistic visual behavior cues (e.g. body language, vocal inflection, facial expressions) and how these can benefit the learner. Using the concept of a "virtual vignette" this paper will discuss a prototype system intended to leach suicide prevention and provide qualitative feedback to the learner. The paper will also explore other soft skills training applications for this technology

Cimino, James D.↗
NASA NTRS2012

Disentangling AGN and Star Formation in Soft X-Rays

We have explored the interplay of star formation and active galactic nucleus (AGN) activity in soft X-rays (0.5-2 keV) in two samples of Seyfert 2 galaxies (Sy2s). Using a combination of low-resolution CCD spectra from Chandra and XMM-Newton, we modeled the soft emission of 34 Sy2s using power-law and thermal models. For the 11 sources with high signal-to-noise Chandra imaging of the diffuse host galaxy emission, we estimate the luminosity due to star formation by removing the AGN, fitting the residual emission. The AGN and star formation contributions to the soft X-ray luminosity (i.e., L(sub x,AGN) and L(sub x,SF)) for the remaining 24 Sy2s were estimated from the power-law and thermal luminosities derived from spectral fitting. These luminosities were scaled based on a template derived from XSINGS analysis of normal star-forming galaxies. To account for errors in the luminosities derived from spectral fitting and the spread in the scaling factor, we estimated L(sub x,AGN) and L(sub x,SF))from Monte Carlo simulations. These simulated luminosities agree with L(sub x,AGN) and L(sub x,SF) derived from Chandra imaging analysis within a 3sigma confidence level. Using the infrared [Ne ii]12.8 micron and [O iv]26 micron lines as a proxy of star formation and AGN activity, respectively, we independently disentangle the contributions of these two processes to the total soft X-ray emission. This decomposition generally agrees with L(sub x,SF) and L(sub x,AGN) at the 3 sigma level. In the absence of resolvable nuclear emission, our decomposition method provides a reasonable estimate of emission due to star formation in galaxies hosting type 2 AGNs.

Disentangling↗
NASA NTRS2016

A Soft X-Ray Spectral Episode for the Clocked Burster, GS 1826-24 as Measured by Swift and NuSTAR

We report on NuSTAR and Swift observations of a soft state of the neutron star low-mass X-ray binary GS 1826-24, commonly known as the "clocked" burster. The transition to the soft state was recorded in 2014 June through an increase of the 2-20 keV source intensity measured by MAXI, simultaneous with a decrease of the 15-50 keV intensity measured by Swift/BAT. The episode lasted approximately two months, after which the source returned to its usual hard state. We analyze the broadband spectrum measured by Swift/XRT and NuSTAR and estimate the accretion rate during the soft episode to be approximately equal to 13% m(sub Edd), within the range of previous observations. However, the best-fit spectral model, adopting the double Comptonization used previously, exhibits significantly softer components. We detect seven type-I X-ray bursts, all significantly weaker (and with shorter rise and decay times) than observed previously. The burst profiles and recurrence times vary significantly, ruling out the regular bursts that are typical for this source. One burst exhibited photospheric radius expansionand we estimate the source distance as (5.7 +/- 0.2) xi(sub b)(exp -1/2) kpc, where xi(sub b) parameterizes the possible anisotropy of the burst emission. The observed soft state may most likely be interpreted as a change in accretion geometry at about similar bolometric luminosity as in the hard state. The different burst behavior can therefore be attributed to this change in accretion flow geometry, but the fundamental cause and process for this effect remain unclear.

accretion↗
NASA NTRS2020

Resolving the Soft X-Ray Ultrafast Outflow in PDS 456

Past X-ray observations of the nearby luminous quasar PDS 456 (at z = 0.184) have revealed a wide-angle accretion disk wind with an outflow velocity of ∼−0.25c, as observed through observations of its blueshifted iron K-shell absorption line profile. Here we present three new XMM-Newton observations of PDS 456: one in 2018 September where the quasar was bright and featureless and two in 2019 September, 22 days apart, occurring when the quasar was five times fainter and where strong blueshifted lines from the wind were present. During the second 2019 September observation, three broad (σ = 3000 km s(exp -1)) absorption lines were resolved in the high-resolution Reflection Grating Spectrometer spectrum that are identified with blueshifted O VIII Lyα, Ne IX Heα, and Ne X Lyα. The outflow velocity of this soft X-ray absorber was found to be v/c = -0.258 ± 0.003, fully consistent with an iron K absorber with v/c = -0.261 ± 0.007. The ionization parameter and column density of the soft X-ray component (log ξ = 3.4, N(sub H) = 2 × 10(exp 21) cm(exp -2)) outflow was lower by about 2 orders of magnitude when compared to the high-ionization wind at iron K (log ξ = 5, N(sub H) = 7 × 10(exp 23) cm(exp -2). Substantial variability was seen in the soft X-ray absorber between the 2019 observations, declining from N(sub H) = 10(exp 23) to 10(exp 21) cm(exp -2) over 20 days, while the iron K component was remarkably stable. We conclude that the soft X-ray wind may originate from an inhomogeneous wind streamline passing across the line of sight that, due to its lower ionization, is located further from the black hole, on parsec scales, than the innermost disk wind

Active galactic nuclei↗
NASA NTRSDate not supplied

Explaining Soft-Goal Conflicts through Constraint Relaxations

Recent work suggests to explain trade-offs between soft goals in terms of their conflicts, i. e., minimal unsolvable soft-goal subsets. But this does not explain the conflicts themselves: Why can a given set of soft-goals not be jointly achieved? Here we approach that question in terms of the underlying constraints on plans in the task at hand, namely resource availability and time windows. In this context, a natural form of explanation for a soft-goal conflict is a minimal constraint relaxation under which the conflict disappears (“if the deadline was 1 hour later, it would work”). We explore algorithms for computing such explanations. A baseline is to simply loop over all relaxed tasks and compute the conflicts for each separately. We improve over this by two algorithms that leverage information – conflicts, reachable states – across relaxed tasks. We show that these algorithms can exponentially outperform the baseline in theory, and we run experiments confirming that advantage in practice.

Planning↗
NASA NTRS2022

Learning-Based State-Dependent Coefficient Form Task Space Tracking Control of Soft Robot

n this paper, a data-driven modeling and control framework is developed for task space control of a soft robot gripper which consists of four individual soft fingers. Each of the four fingers is modeled as a manipulator with high degrees of freedom. The corresponding task space dynamics of the manipulator are derived using a rigid-link approximation of the continuum manipulator. A neural network approach is used to learn the derived dynamics in State Dependent Coefficient (SDC) form. Using the learned SDC matrices, an asymptotically stable optimal closed-loop tracking controller which is based on solving the State Dependent Riccati Equation (SDRE) is derived. The model learning and trajectory tracking controller is implemented on an open source Soft Motion (SoMo) platform simulating the soft gripper motion and corresponding tracking results are presented.

Rounak Bhattacharya↗
NASA NTRS2022

SoMoGym: A Toolkit for Developing and Evaluating Controllers and Reinforcement Learning Algorithms for Soft Robots

Soft robotsoffer a host of benefits over traditional rigid robots, including inherent compliance that lets them passively adapt to variable environments and operate safely around humans and fragile objects. However, that same compliance makes it hard to use model-based methods in planning tasks requiring high precision or complex actuation sequences. Reinforcement learning (RL) can potentially find effective control policies, but training RL using physical soft robots is often infeasible, and training using simulations has had a high barrier to adoption. To accelerate research in control and RL for soft robotic systems, we introduce SoMoGym ( So ft Mo tion Gym ), a software toolkit that facilitates training and evaluating controllers for continuum robots. SoMoGym provides a set of benchmark tasks in which soft robots interact with various objects and environments. It allows evaluation of performance on these tasks for controllers of interest, and enables the use of RL to generate new controllers. Custom environments and robots can likewise be added easily. We provide and evaluate baseline RL policies for each of the benchmark tasks. These results show that SoMoGym enables the use of RL for continuum robots, a class of robots not covered by existing benchmarks, giving them the capability to autonomously solve tasks that were previously unattainable.

Moritz A. Graule↗
NASA NTRS2023

Soft X-Ray Imaging of Earth's Dayside Magnetosheath and Cusps Using Hybrid Simulations

Interactions between solar wind ions and neutral hydrogen atoms in Earth's exosphere can lead to the emission of soft X-rays. Upcoming missions such as SMILE and LEXI aim to use soft X-ray imaging to study the global structure of the magnetosphere. Although the magnetosheath and dayside magnetopause can often be driven by kinetic physics, it has typically been omitted from fluid simulations used to predict X-ray emissions. We study the possible results of soft X-ray imaging using hybrid simulations under quasi-radial interplanetary magnetic fields, where ion-ion instabilities drive ultra-low frequency foreshock waves, leading to turbulence in the magnetosheath, affecting the dynamics of the cusp and magnetopause. We simulate soft X-ray emission to determine what may be seen by missions such as LEXI, and evaluate the possibility of identifying kinetic structures. While kinetic structures are visible in high-cadence imaging, current instruments may not have the time resolution to discern kinetic signals.

J Ng↗
NASA NTRS2023

Finding the magnetopause location using soft X-ray observations and a statistical inverse method

Variability in the location and shape of the dayside magnetopause is attributed to magnetic reconnection, a fundamental process that enables the transfer of mass, energy, and momentum from the solar wind into the magnetosphere. The spatial and temporal properties of the magnetopause, under varying solar and magnetospheric conditions, remain largely unknown because empirical studies using in-situ observations are challenging to interpret. Global wide field-of-view (FOV) imaging is the only means to simultaneously observe the spatial distribution of the plasma properties over the vast dayside magnetospheric region and, subsequently, quantify the energy transport from the interplanetary medium into the terrestrial magnetosphere. Two upcoming missions, ESA/CAS SMILE and NASA’s LEXI will provide wide-field imagery of the dayside magnetosheath in soft X-rays, an emission generated by charge exchange interactions between high charge-state heavy ions of solar wind origin and exospheric neutral atoms. High-cadence two-dimensional observations of the magnetosheath will allow the estimation of dynamic properties of its inner boundary, the magnetopause, and enable studies of its response to changes in the solar wind dynamic pressure and interplanetary magnetic field orientation. This work introduces a statistically-based estimation approach based on inverse theory to estimate the spatial distribution of magnetosheath soft X-ray emissivities and, with this, identify the location of the magnetopause over the Sun−Earth line. To do so, we simulate the magnetosheath structure using the MHD-based OpenGGCM model and generate synthetic soft X-ray images using LEXI’s orbit and attitude information. Our results show that 3-D estimations using the described statistically-based technique are robust against Poisson-distributed shot noise inherent to soft X-ray images. Also, our proposed methodology shows that the accuracy of both three-dimensional (3-D) estimation and the magnetopause standoff distance calculation highly depends on the observational point.

Gonzalo Cucho-Padin↗
NASA NTRS2023

Increasing the Payload Capacity of Soft Robot Arms by Localized Stiffening

Soft robot arms offer safety and adaptability due to their passive compliance, but this compliance typically limits their payload capacity and prevents them from performing many tasks. This paper presents a model-based design approach to effectively increase the payload capacity of soft robot arms. The proposed approach uses localized body stiffening to decrease the compliance at the end effector without sacrificing the robot’s range of motion. This approach is validated on both a simulated and a real soft robot arm, where experiments show that increasing the stiffness of localized regions of their bodies reduces the compliance at the end effector and increases the height to which the arm can lift a payload. By increasing the payload capacity of soft robot arms, this approach has the potential to improve their efficacy in a variety of tasks including object manipulation and exploration of cluttered environments.

Daniel Bruder↗
DOE OSTI2014

Synchronous motor with soft start element formed between the motor rotor and motor output shaft to successfully synchronize loads that have high inertia and/or high torque

A line-start synchronous motor has a housing, a rotor shaft, and an output shaft. A soft-start coupling portion is operatively coupled to the output shaft and the rotor shaft. The soft-start coupling portion is configurable to enable the synchronous motor to obtain synchronous operation and to drive, at least near synchronous speed during normal steady state operation of the motor, a load having characteristics sufficient to prevent obtaining normal synchronous operation of the motor when the motor is operatively connected to the load in the absence of the soft-start coupling. The synchronous motor is sufficiently rated to obtain synchronous operation and to drive, at least near synchronous speed during normal steady state operation of the motor, a load having characteristics sufficient to prevent obtaining normal synchronous operation of the motor when the motor is operatively connected to the load in the absence of the soft-start coupling.

42 ENGINEERING↗
DOE OSTI2020

Resilient, untethered soft robot

A pneumatically powered, fully untethered mobile soft robot is described. Composites consisting of silicone elastomer, polyaramid fabric, and hollow glass microspheres were used to fabricate a sufficiently large soft robot to carry the miniature air compressors, battery, valves, and controller needed for autonomous operation. Fabrication techniques were developed to mold a 0.65 meter long soft body with modified Pneumatic network actuators capable of operating at the elevated pressures (up to 138 kPa) required to actuate the legs of the robot and hold payloads of up to 8 kg. The soft robot is safe to handle, and its silicone body is innately resilient to a variety of adverse environmental conditions including snow, puddles of water, direct (albeit limited) exposure to flames, and the crushing force of being run over by an automobile.

42 ENGINEERING↗
DOE OSTI2023

Development of dual phase soft magnetic laminate for advanced electric machines

The development of dual phase soft magnetic laminate for advanced electric machines at General Electric is summarized, including alloy development, properties, manufacturing trials, prototype experience, potential applications, and future material development. Dual phase soft magnetic laminates provide the flexibility to tune magnetic/non-magnetic state at the desired locations, using solution nitriding treatment with protective mask/coating. This enabling material technology benefits electric machine performance by reducing flux leakage in the laminates. It also decouples the electromagnetic and mechanical design, which opens up the design space for advanced electric machines. Magnetic and mechanical properties of dual phase laminates were compared to commercial FeSi and FeCo soft magnetic laminates. Driven by the market needs for high power density and high-speed electric machines, a synchronous reluctance (SynRel) machine without PMs using dual phase soft magnetic laminates was assessed in machine electromagnetic performance as well as rotor stress analysis by finite element simulation. Successful prototype build and testing further retired manufacturing risks and advanced the technology maturity level. Future material development with higher mechanical strength, higher saturation magnetization, higher permeability, and lower loss are highly desired for ground and air transportation electrification.

Rallabandi, Vandana↗
DOE OSTI2015

Implementation and Analysis for APR1400 Soft Control System

Due to the rapid advancement of digital technology, the definite technical advantages of digital control system compared to analog control system are accelerating the implementation of advanced distributed digital control system in the nuclear power plant. One of the major advantages of digital control system is the capability of Soft Control System. The design of Soft Control System for Advanced Power Reactor 1400 (APR1400) plant of Man-Machine Interface System (MMIS) is based on full digital technologies to enhance reliability, operability and maintainability. Computer-based compact workstation has been adopted in the APR1400 Main Control Room (MCR) to provide convenient working environment. This paper introduces the approaches and methodologies of Soft Control System for the Advanced Control Room (ACR). This paper also explains major design features for operation and display of the Soft Control System and its implementation to cope with regulatory requirements. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Advanced silicone materials for soft actuator applications

Soft actuators are at the forefront of the innovation tide in medicine, manufacturing, and aerospace because they are able to mimic the behavior of biological tissue and adapt to complex, unstructured environments. Of all the materials used, silicone-based elastomers have drawn enormous attention since they offer a superb combination of mechanical flexibility, biocompatibility, thermal stability, and long-term durability. In the past few years, there has also been a rapid pace of material evolution, additive manufacturing, and biointegration that has enhanced the performance and applications of silicone-based soft actuators. However, there is no focused and timely review compiling these advances. This review seeks to address that need by critically discussing recent advancements in advanced silicone materials, exploring new fabrication methodologies, and discussing emerging applications that range from wearable devices to implantable robotics. We also present suggestions for directions and the problems which must be addressed in order to further develop the performance and potential of silicone-based soft actuators, justifying the relevance and urgency of this effort.

biocompatibility↗
DOE OSTI2019

Ground-Truth Prediction to Accelerate Soft-Error Impact Analysis for Iterative Methods

Understanding the impact of soft errors on applications can be expensive. Often, it requires an extensive error injection campaign involving numerous runs of the full application in the presence of errors. In this paper, we present a novel approach to arriving at the ground truth--the true impact of an error on the final output--for iterative methods by observing a small number of iterations to learn deviations between normal and error-impacted execution. We develop a machine learning based predictor for three iterative methods to generate ground-truth results without running them to completion for every error injected. We demonstrate that this approach achieves greater accuracy than alternative prediction strategies, including three existing soft error detection strategies. We demonstrate the effectiveness of the ground truth prediction model in evaluating vulnerability and the effectiveness of soft error detection strategies in the context of iterative methods.

iterative methods, failure prediction, Soft error ↗
DOE OSTI2021

Decoupling Complex Multi–Length–Scale Morphology in Non–Fullerene Photovoltaics with Nitrogen K–Edge Resonant Soft X–ray Scattering

Complex morphology in organic photovoltaics (OPVs) and other functional soft materials commonly dictates performance. Such complexity in OPVs originates from the mesoscale kinetically trapped non-equilibrium state, which governs device charge generation and transport. Resonant soft X-ray scattering (RSoXS) has been revolutionary in the exploration of OPV morphology in the past decade due to its chemical and orientation sensitivity. However, for non-fullerene OPVs, RSoXS analysis near the carbon K-edge is challenging, due to the chemical similarity of the materials used in active layers. Here, an innovative approach is provided by nitrogen K-edge RSoXS (NK-RSoXS), utilizing the spatial and orientational contrasts from the cyano groups in the acceptor materials, which allows for determination of phase separation. NK-RSoXS clearly visualizes the combined feature sizes in PM6:Y6 blends from crystallization and liquid-liquid demixing, while PM6:Y6:Y6-BO ternary blends with reduced phase-separation size and enhanced material crystallization can lead to current amplification in devices. Nitrogen is common in organic semiconductors and other soft materials, and the strong and directional N 1s → π* resonances make NK-RSoXS a powerful tool to uncover the mesoscale complexity and open opportunities to understand heterogeneous systems.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Near-Edge Soft X-ray Absorption Mass Spectrometry of Protonated Melittin

We have investigated the photoionization and photofragmentation yields of gas-phase multiply protonated melittin cations for photon energies at the K-shell absorption edges of carbon, nitrogen, and oxygen. Two similar experimental approaches were employed. In both experiments, mass selected [melittin+qH]{sup q+} (q=2–4) ions were accumulated in radiofrequency ion traps. The trap content was exposed to intense beams of monochromatic soft X-ray photons from synchrotron beamlines and photoproducts were analyzed by means of time-of-flight mass spectrometry. Mass spectra were recorded for fixed photon energies, and partial ion yield spectra were recorded as a function of photon energy. The combination of mass spectrometry and soft X-ray spectroscopy allows for a direct correlation of protein electronic structure with various photoionization channels. Non-dissociative single and double ionization are used as a reference. The contribution of both channels to various backbone scission channels is quantified and related to activation energies and protonation sites. Soft X-ray absorption mass spectrometry combines fast energy deposition with single and double ionization and could complement established activation techniques. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗