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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Tracking Community Building in Open Science

Open Science is enabled by a vibrant community of researchers who regularly engage with the data, from its production to its organization, curation, archiving, dissemination, analysis, and publication. This presentation will examine community building in open science. The NASA Open Science Data Repository (OSDR) makes data available to the public following the FAIR (Findability, Accessibility, Interoperability, and Reusability) principles. OSDR takes open science further with the OS Analysis Working Groups (AWGs) that facilitate community development and promotion. The primary activity of each AWG is to establish and validate analytical processes to generate higher-order data from data housed in OSDR. There are a number of these groups on various topics, including the Animal AWG, Plant AWG, Microbial AWG, Multi-Omics AWG, AI/ML AWG, and the Ames Life Sciences Data Archive (ALSDA) AWG. The international volunteers participating in these AWGs come from academia, citizen science initiatives, industry, and government. They include researchers, principal investigators, professors, trained hobbyists, and students from various domains and disciplines. Anyone may request to join the AWGs, and membership requests are vetted monthly by the group organizers before granting admission. Core to membership is demonstrated expertise through records of training, integrity, work in the professed domain(s), and good community standing. Regular virtual meetings are held for each AWG, with a varying cadence depending on the group's needs and goals. AWG communities share their expertise in research including cutting edge tools, software, frameworks, data formats, and libraries accelerating research collectively. This collaborative approach helps community members cross technology gaps and identify emerging challenges. These diverse communities encompass a wide range of individuals hailing from various sectors within the Science Mission Directorate and beyond. They serve as a means to promote and enhance transparency, accessibility, and inclusion. An annual AWG Symposium brings contributors together in person. Participation in AWGs can be synchronous or asynchronous, with some groups performing most of their work in off hours. Participants gain valuable skills and connections that allow them to add value to their communities and new organizations that they join, resulting in an expanded return on investment for the space life science community. Open science is increasingly a federal mandate and initiatives like NASA's Transform to Open Science and instruments like the Decadal Survey of Biological and Physical Sciences in Space demonstrate the need to carefully consider best practices in this domain. Here, we present greater detail about the makeup and participation metrics of the various AWGs affiliated with OSDR and details of successful peer-reviewed publication campaigns.

Christina M Johnson↗
NASA NTRSDate not supplied

LAVA Voronoi Mesher for Wall-Modeled Large-Eddy Simulations

The unstructured Voronoi mesher currently being developed within the Launch, Ascent, and Vehicle Aerodynamics (LAVA) software framework at NASA Ames Research Center is described in detail. The discussions include, but are not limited to, the strategies used in the seeding and smoothing phases to ensure a high-quality mesh for Wall-Modeled Large-Eddy Simulations (WMLES), the methods behind the cell clipping algorithm responsible for conforming the mesh to a complex geometry, and the approach to create a global mesh from the distinct Voronoi cells. Applications and benefits of the Voronoi meshing approach are also presented. The automated meshing paradigm introduced was able to significantly reduce the time necessary to create a high-quality mesh around a complex geometry when compared against the current LAVA curvilinear overset meshing standard. For example, the task of generating a single mesh around the high-lift common research model requires the full dedication of a mesh generation expert for a period between one and two months. A family of meshes with different refinement levels up to six hundred million cells can be generated by a single engineer in a day or two. This technology has the potential for decreasing the turnaround time for conducting WMLES around complex geometries, as well as facilitating comprehensive mesh refinement studies.

Victor C B Sousa↗
NASA NTRS2021

SoMo: Fast and Accurate Simulations of Continuum Robots in Complex Environments

Engineers and scientists often rely on their intuition and experience when designing soft robotic systems. The development of performant controllers and motion plans for these systems commonly requires time-consuming iterations on hardware. We present the SoMo (Soft Motion) toolkit, a software framework that makes it easy to instantiate and control typical continuum manipulators in an accurate physics simulator. SoMo introduces a standardized and human-readable description format for continuum manipulators. It leverages this description format and the Bullet physics engine to enable fast and accurate simulations of soft and soft-rigid hybrid robots in environments with complex contact interactions. This allows users to vary design and control parameters across simulations with minimal effort. We compare the capabilities of SoMo to other physics simulators and highlight the benefits and accuracy of SoMo by demonstrating the agreement between simulation and real-world experiments on several examples; these include an in-hand manipulation task with continuum fingers, an automated exploration of how to design soft fingers for precision grasping, and a brief snake locomotion study. Overall, SoMo provides an accessible way for designers of soft robotic hardware and control systems to gain access to a simulation-accelerated workflow.

Moritz A. Graule↗
NASA NTRSDate not supplied

Automated End-to-End Spacecraft Connectivity Across Diverse Links

An increasing variety of communications services are available to space missions. Yet varying standards between providers hinder adoption due to the complexity of managing many configurations. We present a software framework to automatically establish end-to-end communications during contacts with a provider by configuring spacecraft protocols at the physical, link, and network layers. Underlying protocols and routes are abstracted, allowing the user to simply send data to a destination with the framework ensuring its delivery. We evaluate a full implementation of the framework in laboratory experiments conducted on an emulated communications testbed. These tests demonstrate data delivery across three different services with rapid (<20s) reconfiguration as the spacecraft transitions between providers.

satellite communication↗
DOE OSTI2014

Simulating Microbial Community Patterning Using Biocellion

Mathematical modeling and computer simulation are important tools for understanding complex interactions between cells and their biotic and abiotic environment: similarities and differences between modeled and observed behavior provide the basis for hypothesis forma- tion. Momeni et al. [5] investigated pattern formation in communities of yeast strains engaging in different types of ecological interactions, comparing the predictions of mathematical modeling and simulation to actual patterns observed in wet-lab experiments. However, simu- lations of millions of cells in a three-dimensional community are ex- tremely time-consuming. One simulation run in MATLAB may take a week or longer, inhibiting exploration of the vast space of parameter combinations and assumptions. Improving the speed, scale, and accu- racy of such simulations facilitates hypothesis formation and expedites discovery. Biocellion is a high performance software framework for ac- celerating discrete agent-based simulation of biological systems with millions to trillions of cells. Simulations of comparable scale and accu- racy to those taking a week of computer time using MATLAB require just hours using Biocellion on a multicore workstation. Biocellion fur- ther accelerates large scale, high resolution simulations using cluster computers by partitioning the work to run on multiple compute nodes. Biocellion targets computational biologists who have mathematical modeling backgrounds and basic C++ programming skills. This chap- ter describes the necessary steps to adapt the original Momeni et al.'s model to the Biocellion framework as a case study.

metabolic interaction↗
DOE OSTI2014

Analysis of the Space Propulsion System Problem Using RAVEN

This paper presents the solution of the space propulsion problem using a PRA code currently under development at Idaho National Laboratory (INL). RAVEN (Reactor Analysis and Virtual control ENviroment) is a multi-purpose Probabilistic Risk Assessment (PRA) software framework that allows dispatching different functionalities. It is designed to derive and actuate the control logic required to simulate the plant control system and operator actions (guided procedures) and to perform both Monte- Carlo sampling of random distributed events and Event Tree based analysis. In order to facilitate the input/output handling, a Graphical User Interface (GUI) and a post-processing data-mining module are available. RAVEN allows also to interface with several numerical codes such as RELAP5 and RELAP-7 and ad-hoc system simulators. For the space propulsion system problem, an ad-hoc simulator has been developed and written in python language and then interfaced to RAVEN. Such simulator fully models both deterministic (e.g., system dynamics and interactions between system components) and stochastic behaviors (i.e., failures of components/systems such as distribution lines and thrusters). Stochastic analysis is performed using random sampling based methodologies (i.e., Monte-Carlo). Such analysis is accomplished to determine both the reliability of the space propulsion system and to propagate the uncertainties associated to a specific set of parameters. As also indicated in the scope of the benchmark problem, the results generated by the stochastic analysis are used to generate risk-informed insights such as conditions under witch different strategy can be followed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Beamline Insertions Manager at Jefferson Lab

The beam viewer system at Jefferson Lab provides operators and beam physicists with qualitative and quantitative information on the transverse electron beam properties. There are over 140 beam viewers installed on the 12 GeV CEBAF accelerator. This paper describes an upgrade consisting of replacing the EPICS-based system tasked with managing all viewers with a mixed system utilizing EPICS and high-level software. Most devices, particularly the beam viewers, cannot be safely inserted into the beam line during high-current beam operations. Software is partly responsible for protecting the machine from untimely insertions. The multiplicity of beam-blocking and beam-vulnerable devices motivates us to try a data-driven approach. The beamline insertions application components are centrally managed and configured through an object-oriented software framework created for this purpose. A rules-based engine tracks the configuration and status of every device, along with the beam status of the machine segment containing the device. The application uses this information to decide on which device actions are allowed at any given time.

43 PARTICLE ACCELERATORS↗
DOE OSTI2015

A Comprehensive Validation Approach Using The RAVEN Code

The RAVEN computer code , developed at the Idaho National Laboratory, is a generic software framework to perform parametric and probabilistic analysis based on the response of complex system codes. RAVEN is a multi-purpose probabilistic and uncertainty quantification platform, capable to communicate with any system code. A natural extension of the RAVEN capabilities is the imple- mentation of an integrated validation methodology, involving several different metrics, that represent an evolution of the methods currently used in the field. The state-of-art vali- dation approaches use neither exploration of the input space through sampling strategies, nor a comprehensive variety of metrics needed to interpret the code responses, with respect experimental data. The RAVEN code allows to address both these lacks. In the following sections, the employed methodology, and its application to the newer developed thermal-hydraulic code RELAP-7, is reported.The validation approach has been applied on an integral effect experiment, representing natu- ral circulation, based on the activities performed by EG&G Idaho. Four different experiment configurations have been considered and nodalized.

PRA↗
DOE OSTI2014

DGM Version .1.2

Software framework for forward modeling and optimization of partial differential equations using the discontinuous Galerkin method (DGM). Examples are provided for solution to generic Navier-Stokes (with and without subgrid-scale turbulence models), Euler, Burgers, Poisson, Helmholtz, Darcy, linear transport, and advection-diffusion equations.

Source record↗
DOE OSTI2014

Rplexos

rplexos is a R (statistical software framework; more? details below) package that processes and facilitates analysis of solution from PLEXOS. PLEXOS is a production cost model that is utilize to simulate the behavior of the power.systems and is developed and commercialized by Energy Exomplar. The intention is to make rptexos open-source so other PLEXOS users can utilize it.

Ibanez, Eduardo↗
DOE OSTI2016

Tusas, Version 1.0

Tusas is a general / flexible software framework for solving coupled systems of onlinear partial differential equations. Tusas was originally developed for phase-field simulation of solidification. In order for Tusas to be effective, the PDEs must be compatible with structured or unstructured Lagrange (nodal) finite element discretizations and explicit (Euler) or implicit (Euler, Trapezoid, BDF2) temporal discretizations.

Newman, Christopher K.↗
DOE OSTI2017

Demand Response Resource Quantification with Detailed Building Energy Models

Demand response is a broad suite of technologies that enables changes in electrical load operations in support of power system reliability and efficiency. Although demand response is not a new concept, there is new appetite for comprehensively evaluating its technical potential in the context of renewable energy integration. The complexity of demand response makes this task difficult -- we present new methods for capturing the heterogeneity of potential responses from buildings, their time-varying nature, and metrics such as thermal comfort that help quantify likely acceptability of specific demand response actions. Computed with an automated software framework, the methods are scalable.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Correlated Synthetic Time Series Generation using Fourier and ARMA

As the contribution of renewable energy grows in electricity markets, the complexity nuclear’s place within the energy mix increases, and likewise the need for robust simulation techniques. While decades of wind, solar, and demand pro- files can sometimes be obtained, this is too few samples to provide a statistically meaningful analysis of a system with baseload, peaker, and renewable generation. Synthetic time series generation presents itself as a suitable methodology to meet this need. One approach for synthetic series generation is training a model using Fourier series decomposition for seasonal patterns and Auto-Regressive Moving Average models (ARMA) to describe time-correlated statistical noise about the seasonal patterns. When combined, the Fourier plus ARMA (FARMA) model has been shown to provide an infinite set of independent, identically-distributed sample time series with the same statistical properties as the original data [1]. When considering an energy mix with renewable electricity production, several time series of energy, grid, and weather measurements are needed for each synthetic year modeled to statistically comprehend the efficiency of any given energy mix. These cannot be considered independent series in a given synthetic year. To capture and reproduce the correlations that might exist in the measured histories, the ARMA can further be extended as a Vector ARMA (VARMA). In the VARMA algorithm, covariance in statistical noise is captured both within a history as part of the autoregressive moving average, and with respect to the other variables in the time series. In this work the implementation of the Fourier VARMA in the RAVEN uncertainty quantification and risk analysis software framework [2] is presented, along with examples of correlated synthetic history generation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Data Analysis Approach for Large Data Volumes in a Connected Community

Recent advancements within smart neighborhoods where utilities are enabling automatic control of appliances such as heating, ventilation, and air conditioning (HVAC) and water heater (WH) systems are providing new opportunities to minimize energy costs through reduced peak load. This requires systematic collection, storage, management, and in-memory processing of large volumes of streaming data for fast performance. In this paper, we propose a multi-tier layered IoT software framework that enables effective descriptive and predictive data analysis for understanding live operation of the neighborhood, fault identification, and future opportunities for further optimization of load curves. We then demonstrate how we achieve live situational awareness of the connected neighborhood through a suite of visualization components. Finally, we discuss a few analytic dashboards that address questions such as peak load reductions obtained due to optimization, customer preference for automatic control of appliances (do they override the automatic control of HVAC?, etc.). 1 1 This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a nonexclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).

Chinthavali, Supriya↗
DOE OSTI2021

DUNE Software and Computing Challenges

The DUNE experiment will begin running in the late 2020's. The goals of the experiment include 1) studying neutrino oscillations using a beam of neutrinos from Fermilab in Illinois to the Sanford Underground Research Facility, 2) studying astrophysical neutrino sources and rare processes and 3) understanding the physics of neutrino interactions in matter. The DUNE Far Detector, consisting of four 17 kt LArTPC modules, will produce "events" rang-ing in size from 6 GBs to more than 100 TBs, posing unique challenges for DUNE software and computing. The data processing algorithms, particularly for raw data, drive the requirements for the future DUNE software framework documented here.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

MFIX-Exa: Performance prediction of multiphase energy conversion devices

MFIX-Exa targets the high-fidelity CFD-DEM model in which particles are unresolved by the fluid grid (typically using a fluid mesh approximately twice the particle diameter) but discrete particle dynamics including collisions are resolved with a simple linear-spring dashpot model. The fluid field is solved with a modern low Mach number formation of a cell-centered, nodal-pressure approximate projection method using a Godunov scheme . Physics capabilities include: complex geometries via embedded boundaries (EBs), open and closed system ideal gas equations of state, species transport and heterogeneous chemi- cal reactions. MFIX-Exa is built on the AMReX software framework, the ECP Block-Structured Adaptive Mesh Refinement (AMR) Co-Design Center, which allows the code to be portable and performant.Further integration into the ECP ecosystem includes HYPRE linear solvers and Ascent for in situ visualization. Current project efforts focus on scaling up realistic simulations to the KPP of the challenge problem: NETs 50kW chemical looping reactor, shakedown and scaling on JSLE and OLCF TDS systems and reaching for any remaining performance improvements.

Musser, Jordan↗
DOE OSTI2022

2021 Component Innovation Awardee: Windurance, LLC

Distributed wind turbine manufacturers seeking to enter the market are often hampered by two challenges: not enough capital and no specific expertise in developing certified electronic equipment. A harsh reality is that off-the-shelf power electronics are neither certified nor cost-effective. This lack of certified controller equipment in the distributed wind energy industry adds expense and impedes market penetration related to certification for individual wind turbines, wind system projects, and installations. Normally, these certification costs would be borne repeatedly by individual turbine manufacturers or developers on a model-by-model or project-by-project basis, resulting in cost and time delays as well as uncertainty and risk for project developers and prospective owners. Windurance seeks to eliminate these challenges by developing and obtaining third-party certification of a standardized wind turbine controller. This will facilitate development, certification, and production while supporting efficiencies not easily achievable by individual manufacturers. Windurance's Distributed Wind Industry Turbine Controller will enable manufacturers to apply proprietary turbine- specific configurations and functionality. When applicable, manufacturers can expand on a Windurance-provided software framework to add unique or proprietary functionality.

CIP↗