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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sources NASA NTRS DOE OSTI

NASA NTRS2014

Design and Control of Modular Spine-Like Tensegrity Structures

We present a methodology enabled by the NASA Tensegrity Robotics Toolkit (NTRT) for the rapid structural design of tensegrity robots in simulation and an approach for developing control systems using central pattern generators, local impedance controllers, and parameter optimization techniques to determine effective locomotion strategies for the robot. Biomimetic tensegrity structures provide advantageous properties to robotic locomotion and manipulation tasks, such as their adaptability and force distribution properties, flexibility, energy efficiency, and access to extreme terrains. While strides have been made in designing insightful static biotensegrity structures, gaining a clear understanding of how a particular structure can efficiently move has been an open problem. The tools in the NTRT enable the rapid exploration of the dynamics of a given morphology, and the links between structure, controllability, and resulting gait efficiency. To highlight the effectiveness of the NTRT at this exploration of morphology and control, we will provide examples from the designs and locomotion of four different modular spine-like tensegrity robots.

Modular↗

DOE OSTI2016

acdc – Automated Contamination Detection and Confidence estimation for single-cell genome data

Abstract Background A major obstacle in single-cell sequencing is sample contamination with foreign DNA. To guarantee clean genome assemblies and to prevent the introduction of contamination into public databases, considerable quality control efforts are put into post-sequencing analysis. Contamination screening generally relies on reference-based methods such as database alignment or marker gene search, which limits the set of detectable contaminants to organisms with closely related reference species. As genomic coverage in the tree of life is highly fragmented, there is an urgent need for a reference-free methodology for contaminant identification in sequence data. Results We present acdc, a tool specifically developed to aid the quality control process of genomic sequence data. By combining supervised and unsupervised methods, it reliably detects both known and de novo contaminants. First, 16S rRNA gene prediction and the inclusion of ultrafast exact alignment techniques allow sequence classification using existing knowledge from databases. Second, reference-free inspection is enabled by the use of state-of-the-art machine learning techniques that include fast, non-linear dimensionality reduction of oligonucleotide signatures and subsequent clustering algorithms that automatically estimate the number of clusters. The latter also enables the removal of any contaminant, yielding a clean sample. Furthermore, given the data complexity and the ill-posedness of clustering, acdc employs bootstrapping techniques to provide statistically profound confidence values. Tested on a large number of samples from diverse sequencing projects, our software is able to quickly and accurately identify contamination. Results are displayed in an interactive user interface. Acdc can be run from the web as well as a dedicated command line application, which allows easy integration into large sequencing project analysis workflows. Conclusions Acdc can reliably detect contamination in single-cell genome data. In addition to database-driven detection, it complements existing tools by its unsupervised techniques, which allow for the detection of de novo contaminants. Our contribution has the potential to drastically reduce the amount of resources put into these processes, particularly in the context of limited availability of reference species. As single-cell genome data continues to grow rapidly, acdc adds to the toolkit of crucial quality assurance tools.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

A Suite of Constitutive Promoters for Tuning Gene Expression in Plants

The need for convenient tools to express transgenes over a large dynamic range is pervasive throughout plant synthetic biology; however, current efforts are largely limited by the heavy reliance on a small set of strong promoters, precluding more nuanced and refined engineering endeavors in planta . To address this technical gap, we characterize a suite of constitutive promoters that span a wide range of transcriptional levels and develop a GoldenGate-based plasmid toolkit named PCONS, optimized for versatile cloning and rapid testing of transgene expression at varying strengths. We demonstrate how easy access to a stepwise gradient of expression levels can be used for optimizing synthetic transcriptional systems and the production of small molecules in planta . We also systematically investigate the potential of using PCONS as an internal standard in plant biology experimental design, establishing the best practices for signal normalization in experiments. Although our library has primarily been developed for optimizing expression in N. benthamiana , we demonstrate the translatability of our promoters across distantly related species using a multiplexed reporter assay with barcoded transcripts. In conclusion, our findings showcase the advantages of the PCONS library as an invaluable toolkit for plant synthetic biology.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2017

Setaria Comes of Age: Meeting Report on the Second International Setaria Genetics Conference

Setaria viridis is an emerging model for cereal and bioenergy grasses because of its short stature, rapid life cycle and expanding genetic and genomic toolkits. Its close phylogenetic relationship with economically important crops such as maize and sorghum positions Setaria as an ideal model system for accelerating discovery and characterization of crop genes that control agronomically important traits. The Second International Setaria Genetics Conference was held on March 6–8, 2017 at the Donald Danforth Plant Science Center, St. Louis, MO, United States to discuss recent technological breakthroughs and research directions in Setaria (presentation abstracts can be downloaded at https://www.brutnelllab.org/setaria). Here, we highlight topics presented in the conference including inflorescence architecture, C 4 photosynthesis and abiotic stress. Genetic and genomic toolsets including germplasm, mutant populations, transformation and gene editing technologies are also discussed. Since the last meeting in 2014, the Setaria community has matured greatly in the quality of research being conducted. Outreach and increased communication with maize and other plant communities will allow broader adoption of Setaria as a model system to translate fundamental discovery research to crop improvement.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2011

Rapid ISS Power Availability Simulator

The ISS (International Space Station) Power Resource Officers (PROs) needed a tool to automate the calculation of thousands of ISS power availability simulations used to generate power constraint matrices. Each matrix contains 864 cells, and each cell represents a single power simulation that must be run. The tools available to the flight controllers were very operator intensive and not conducive to rapidly running the thousands of simulations necessary to generate the power constraint data. SOLAR is a Java-based tool that leverages commercial-off-the-shelf software (Satellite Toolkit) and an existing in-house ISS EPS model (SPEED) to rapidly perform thousands of power availability simulations. SOLAR has a very modular architecture and consists of a series of plug-ins that are loosely coupled. The modular architecture of the software allows for the easy replacement of the ISS power system model simulator, re-use of the Satellite Toolkit integration code, and separation of the user interface from the core logic. Satellite Toolkit (STK) is used to generate ISS eclipse and insulation times, solar beta angle, position of the solar arrays over time, and the amount of shadowing on the solar arrays, which is then provided to SPEED to calculate power generation forecasts. The power planning turn-around time is reduced from three months to two weeks (83-percent decrease) using SOLAR, and the amount of PRO power planning support effort is reduced by an estimated 30 percent.

Downing, Nicholas↗

DOE OSTI2015

Agile Components for Modeling Internal Flows

The purpose of this project was to rapidly demonstrate the capabilities of Sandia’s Agile Components toolkit by building a prototype simulator for modeling internal fluid flows and similar technologies of interest to GE Global Research. In doing so, this allowed the CRADA partner to learn about the Agile Components from the Sandia experts that designed and developed the toolkit. Sandia and DOE benefited from the application of Agile Components to another type of modeling and simulation application that helped to further generalize and harden the Agile Components software. As per the CRADA/PTS agreement, the resulting demonstration application can now be distributed under an open source license so that it can be made available for others to also learn from.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1997

Charon Toolkit for Parallel, Implicit Structured-Grid Computations: Functional Design

Charon is a software toolkit that enables engineers to develop high-performing message-passing programs in a convenient and piecemeal fashion. Emphasis is on rapid program development and prototyping. In this report a detailed description of the functional design of the toolkit is presented. It is illustrated by the stepwise parallelization of two representative code examples.

VanderWijngaart, Rob F.↗

DOE OSTI2015

Invited Article: Single-shot THz detection techniques optimized for multidimensional THz spectroscopy

Multidimensional spectroscopy at visible and infrared frequencies has opened a window into the transfer of energy and quantum coherences at ultrafast time scales. For these measurements to be performed in a manageable amount of time, one spectral axis is typically recorded in a single laser shot. An analogous rapid-scanning capability for THz measurements will unlock the multidimensional toolkit in this frequency range. Here, we first review the merits of existing single-shot THz schemes and discuss their potential in multidimensional THz spectroscopy. We then introduce improved experimental designs and noise suppression techniques for the two most promising methods: frequency-to-time encoding with linear spectral interferometry and angle-to-time encoding with dual echelons. Both methods, each using electro-optic detection in the linear regime, were able to reproduce the THz temporal waveform acquired with a traditional scanning delay line. Although spectral interferometry had mediocre performance in terms of signal-to-noise, the dual echelon method was easily implemented and achieved the same level of signal-to-noise as the scanning delay line in only 4.5% of the laser pulses otherwise required (or 22 times faster). This reduction in acquisition time will compress day-long scans to hours and hence provides a practical technique for multidimensional THz measurements.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2023

An extensible vector toolkit and parts library for advanced engineering of plant genomes

Abstract Plant biotechnology is rife with new advances in transformation and genome engineering techniques. A common requirement for delivery and coordinated expression in plant cells, however, places the design and assembly of transformation constructs at a crucial juncture as desired reagent suites grow more complex. Modular cloning principles have simplified some aspects of vector design, yet many important components remain unavailable or poorly adapted for rapid implementation in biotechnology research. Here, we describe a universal Golden Gate cloning toolkit for vector construction. The toolkit chassis is compatible with the widely accepted Phytobrick standard for genetic parts, and supports assembly of arbitrarily complex T‐DNAs through improved capacity, positional flexibility, and extensibility in comparison to extant kits. We also provision a substantial library of newly adapted Phytobricks, including regulatory elements for monocot and dicot gene expression, and coding sequences for genes of interest such as reporters, developmental regulators, and site‐specific recombinases. Finally, we use a series of dual‐luciferase assays to measure contributions to expression from promoters, terminators, and from cross‐cassette interactions attributable to enhancer elements in certain promoters. Taken together, these publicly available cloning resources can greatly accelerate the testing and deployment of new tools for plant engineering.

42 ENGINEERING↗

DOE OSTI2014

A pervasive parallel framework for visualization: final report for FWP 10-014707

We are on the threshold of a transformative change in the basic architecture of highperformance computing. The use of accelerator processors, characterized by large core counts, shared but asymmetrical memory, and heavy thread loading, is quickly becoming the norm in high performance computing. These accelerators represent significant challenges in updating our existing base of software. An intrinsic problem with this transition is a fundamental programming shift from message passing processes to much more fine thread scheduling with memory sharing. Another problem is the lack of stability in accelerator implementation; processor and compiler technology is currently changing rapidly. This report documents the results of our three-year ASCR project to address these challenges. Our project includes the development of the Dax toolkit, which contains the beginnings of new algorithms for a new generation of computers and the underlying infrastructure to rapidly prototype and build further algorithms as necessary.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Fast correlation function calculator: A high-performance pair-counting toolkit

A novel high-performance exact pair-counting toolkit called fast correlation function calculator (FCFC) is presented. With the rapid growth of modern cosmological datasets, the evaluation of correlation functions with observational and simulation catalogues has become a challenge. High-efficiency pair-counting codes are thus in great demand. We introduce different data structures and algorithms that can be used for pair-counting problems, and perform comprehensive benchmarks to identify the most efficient algorithms for real-world cosmological applications. We then describe the three levels of parallelisms used by FCFC, SIMD, OpenMP, and MPI, and run extensive tests to investigate the scalabilities. Finally, we compare the efficiency of FCFC with alternative pair-counting codes. The data structures and histogram update algorithms implemented in FCFC are shown to outperform alternative methods. FCFC does not benefit greatly from SIMD because the bottleneck of our histogram update algorithm is mainly cache latency. Nevertheless, the efficiency of FCFC scales well with the numbers of OpenMP threads and MPI processes, even though speedups may be degraded with over a few thousand threads in total. FCFC is found to be faster than most (if not all) other public pair-counting codes for modern cosmological pair-counting applications.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2017

artdaq : DAQ software development made simple

For a few years now, the artdaq data acquisition software toolkit has provided numerous experiments with ready-to-use components which allow for rapid development and deployment of DAQ systems. Developed within the Fermilab Scientific Computing Division, artdaq provides data transfer, event building, run control, and event analysis functionality. This latter feature includes built-in support for the art event analysis framework, allowing experiments to run art modules for real-time filtering, compression, disk writing and online monitoring; as art, also developed at Fermilab, is also used for online analysis, a major advantage of artdaq is that it allows developers to easily switch between developing online and online software. artdaq continues to be improved. Support for an alternate mode of running whereby data from some subdetector components are only streamed if requested has been added; this option will reduce unnecessary DAQ throughput. Real-time reporting of DAQ metrics has been implemented, along with the flexibility to choose the format through which experiments receive the reports; these formats include the Ganglia, Graphite and syslog software packages, along with at ASCII files. Additionally, work has been performed investigating more flexible modes of online monitoring, including the capability of being able to run multiple online monitoring processes on different hosts, each running its own set of art modules. Finally, a web-based GUI interface through which users can configure details of their DAQ system has been implemented, increasing the ease of use of the system. Already successfully deployed on the LArIAT, DarkSide-50, DUNE 35ton and Mu2e experiments, artdaq will be employed for SBND and is a strong candidate for use on ICARUS and protoDUNE. With each experiment comes new ideas for how artdaq can be made more flexible and powerful; the above improvements will be described, along with potential ideas for the future.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

Green AI: Insights Into Deep Learning's Looming Energy Efficiency Crisis

As demands grow to integrate artificial intelligence into every aspect of industry, commerce, and life, deep learning's exploding energy cost has become a looming crisis, making AI systems a salient energy-efficiency challenge. One might expect that doubling a neural network's size would halve its error rate, or at least allow it to achieve greater performance given the same amount of time and energy. I will present clear and substantial scientific evidence which indicates that not only is this intuition wildly wrong, but that neural networks scale so poorly that to increase deep learning performance by only a small fraction can easily require an order of magnitude or more increase in computational resources and energy. Further, the marginal trade-off price of to increase model performance rapidly explodes as performance targets are increased. To address this challenge, I will provide a toolkit of techniques that can be applied today to mitigate the inefficiency of modern deep learning. And, I will conclude by illuminating a practical path forward towards efficient, Green AI.

artificial intelligence↗

NASA NTRS1995

Machine learning for a Toolkit for Image Mining

A prototype user environment is described that enables a user with very limited computer skills to collaborate with a computer algorithm to develop search tools (agents) that can be used for image analysis, creating metadata for tagging images, searching for images in an image database on the basis of image content, or as a component of computer vision algorithms. Agents are learned in an ongoing, two-way dialogue between the user and the algorithm. The user points to mistakes made in classification. The algorithm, in response, attempts to discover which image attributes are discriminating between objects of interest and clutter. It then builds a candidate agent and applies it to an input image, producing an 'interest' image highlighting features that are consistent with the set of objects and clutter indicated by the user. The dialogue repeats until the user is satisfied. The prototype environment, called the Toolkit for Image Mining (TIM) is currently capable of learning spectral and textural patterns. Learning exhibits rapid convergence to reasonable levels of performance and, when thoroughly trained, Fo appears to be competitive in discrimination accuracy with other classification techniques.

Delanoy, Richard L.↗

NASA NTRSDate not supplied

Development of an Extended Reality (XR) Tool for Earth Science Visualization

In this presentation, we will discuss our work in adapting the NASA open source XR software, the Mixed Reality Exploration Toolkit (MRET), to an earth science domain. MRET is a NASA open source XR software for rapidly building extended reality (XR) environments for NASA domain problems, e.g., pulling in CAD models of thermal vac chamber and Roman Space Telescope to do fit checks. Primarily used for hardware integration & test, we have been adapting and extending MRET for science problems. Traditionally, scientists view and analyze the result of calculated or measured observables with static 1-D, 2-D or 3-D plots. It can be difficult to identify, track and understand the evolution of key features due to poor viewing angles and the nature of flat computer screens. Additionally, numerical models, such as the NASA GEOS climate model, are almost exclusively formulated and analyzed on Eulerian grids with points fixed in space and time. However, atmospheric phenomena such as convective clouds, hurricanes and wildfire smoke plumes move with the 3-D flow field, and it is often difficult and unnatural to understand these phenomena in an Eulerian reference frame as opposed to the Lagrangian reference frame in which nature operates. As part of an Earth Science Technology Office (ESTO) proposal, we have been adapting MRET to be a scientific exploration and analysis XR tool with integrated Lagrangian Dynamics (LD) for the Goddard Earth Observing System (GEOS) numerical weather prediction model. We believe this will help scientists identify, track, and understand the evolution of Earth Science phenomena. This presentation will discuss current results in our work in developing this XR tool for Earth Science.

Thomas G Grubb↗

NASA NTRSDate not supplied

Development of an Extended Reality (XR) Tool for Earth Science Visualization

Thomas Grubb↗

DOE OSTI2026

PyJMAK: An Open-Source Python Toolkit for Modeling Solid-State Metallurgical Phase Transformations

Accurate prediction of metallurgical phase transformations is an essential basis for autonomous optimization and rapid part qualification. Several methods can be used to estimate the evolution of phase fractions such as JMAK kinetics-based models, phase-field models, thermodynamic models, and data-driven machine learning models. Thermodynamic and phase-field-based methodologies solve multiphysics equations requiring numerous calibration parameters and significant computational resources. As a result, the computation domain is limited to a point or on order of micron-meters. The data-driven models rely on large datasets from experiments and simulations. While the JMAK model only provides information about phase fraction evolution, it can predict this evolution in near real-time using thermal history and thermodynamic data without restriction on the domain. JMAK models have been popularly used by researchers to model phase transformations occuring during additive manufacturing or over arbitrary temperature profiles. Commercial proprietary software such as Abaqus and Ansys or closed-source in-house implementations offer the ability to model JMAK based kinetics to predict phase transformation. However, these software packages are not open-source or freely available for use and development in conjunction with manufacturing machines, sensors, and machine learning algorithms. In addition, the use of the model is restricted by a license token. In contrast, given temperature profiles at multiple points in the domain, this Python-based PyJMAK model can compute phase evolution in parallel due to its stand-alone modular, voxel-based structure, and it can be executed on high-performance computing resources without any license restrictions.

Prabhune, Bhagya [Oak Ridge National Laboratory (O↗

DOE OSTI2013

Multiphysics Application Coupling Toolkit

This particular consortium implementation of the software integration infrastructure will, in large part, refactor portions of the Rocstar multiphysics infrastructure. Development of this infrastructure originated at the University of Illinois DOE ASCI Center for Simulation of Advanced Rockets (CSAR) to support the center's massively parallel multiphysics simulation application, Rocstar, and has continued at IllinoisRocstar, a small company formed near the end of the University-based program. IllinoisRocstar is now licensing these new developments as free, open source, in hopes to help improve their own and others' access to infrastructure which can be readily utilized in developing coupled or composite software systems; with particular attention to more rapid production and utilization of multiphysics applications in the HPC environment. There are two major pieces to the consortium implementation, the Application Component Toolkit (ACT), and the Multiphysics Application Coupling Toolkit (MPACT). The current development focus is the ACT, which is (will be) the substrate for MPACT. The ACT itself is built up from the components described in the technical approach. In particular, the ACT has the following major components: 1.The Component Object Manager (COM): The COM package provides encapsulation of user applications, and their data. COM also provides the inter-component function call mechanism. 2.The System Integration Manager (SIM): The SIM package provides constructs and mechanisms for orchestrating composite systems of multiply integrated pieces.

Campbell, MichaelT.↗