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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 19 records

Adding Impacts and Mitigation Measures to OpenEI's RAPID Toolkit

The Open Energy Information platform hosts the Regulatory and Permitting Information Desktop (RAPID) Toolkit to provide renewable energy permitting information on federal and state regulatory processes. One of the RAPID Toolkit's functions is to help streamline the geothermal permitting processes outlined in the National Environmental Policy Act (NEPA). This is particularly important in the geothermal energy sector since each development phase requires separate land analysis to acquire exploration, well field drilling, and power plant construction permits. Using the Environmental Assessment documents included in RAPID's NEPA Database, the RAPID team identified 37 resource categories that a geothermal project may impact. Examples include impacts to geology and minerals, nearby endangered species, or water quality standards. To provide federal regulators, project developers, consultants, and the public with typical impacts and mitigation measures for geothermal projects, the RAPID team has provided overview webpages of each of these 37 resource categories with a sidebar query to reference related NEPA documents in the NEPA Database. This project is an expansion of a previous project that analyzed the time to complete NEPA environmental review for various geothermal activities. The NEPA review not only focused on geothermal projects within the Bureau of Land Management and U.S. Forest Service managed lands, but also projects funded by the Department of Energy. Timeline barriers found were: extensive public comments and involvement; content overlap in NEPA documents, and discovery of impacted resources such as endangered species or cultural sites.

15 GEOTHERMAL ENERGY↗

Hydropower Regulatory and Permitting Information Desktop (RAPID) Toolkit

Hydropower Regulatory and Permitting Information Desktop (RAPID) Toolkit presentation from the WPTO FY14-FY16 Peer Review. The toolkit is aimed at regulatory agencies, consultants, project developers, the public, and any other party interested in learning more about the hydropower regulatory process.

13 HYDRO ENERGY↗

Hydropower RAPID Toolkit

This fact sheet provides a brief overview of the U.S. Department of Energy (DOE) Hydropower Regulatory and Permitting Information Desktop (RAPID) Toolkit including its capabilities, features, and benefits.

13 HYDRO ENERGY↗

CRISPR-COPIES: Web Tool

CRISPR/Cas system has emerged as a powerful genome-editing tool for metabolic engineering and human gene therapy. However, the conundrum of where to integrate heterologous genes on the chromosome using the CRISPR/Cas system remains an open question. Selecting a site for gene integration requires incorporation of complex criteria such as factors involved in CRISPR/Cas-mediated integration, genetic stability, and gene expression and therefore, usually requires strenuous characterization of sites on particular or different chromosomal locations. To address these issues, we developed CRISPR-COPIES, a COmputational Pipeline for the Identification of CRISPR/Cas-facilitated intEgration Sites. The tool applies ScaNN, a state-of-the-art model on the embedding-based nearest neighbor search for fast and accurate off-target search and can identify genome-wide intergenic sites for most bacterial and fungal genomes within minutes. This submission contains the code we developed to create a user-friendly web interface for CRISPR-COPIES (https://biofoundry.web.illinois.edu/copies/). We anticipate CRISPR-COPIES will serve as a useful tool for targeted DNA integration and aid in the characterization of synthetic biology toolkits, rapid strain construction to produce valuable biochemicals, and human gene and cell therapy.

Bioinformatics↗

R3IT: Rapid, Rural, Resilient Interconnection Toolkit

R3IT is a free and open-source web application that allows utilities to automate the processing of solar interconnection requests. It handles request submission, request review workflows, payment collection, signature collection, email notifications for any status changes, and optionally an automated engineering screening and approval process.

Pinney, David↗

R3IT, Rapid Rural Resilient Interconnection Toolkit, Final Technical Report

Utilities nationwide are beginning to experience multiple solar interconnection requests per day. This request volume will soon overwhelm utility engineers, especially at smaller utilities which serve the majority of the landmass of the United States. In this project, we developed open-source software tool that automates the interconnection approval process and removes 80% of the time required to approve an interconnection and hence allow more solar to be quickly and safely integrated with the grid. This software is accompanied by a guidebook detailing interconnection best practices and utility lessons learned. Competing solar interconnection software is extremely expensive at ten times the cost of typical distribution engineering tools, it’s closed source which makes it hard to integrate into utility workflows, and it doesn’t address the hardest power flow modeling challenges of interconnection screening. Our solution was built built with our utility partners who are already experiencing multiple interconnection requests per day and integrates best practices from our past work with DOE and the cooperative community on solar integration. The resulting free and open-source solution has been disseminated through our media channels and conferences that engage over 1,900 utilities nationwide.

14 SOLAR ENERGY↗

Development of programmable logic in a rapid, automated, and repeatable fashion for safety-related applications - 385

Digital safety platform considerations for power plant modernization or new build efforts involve a burdensome task of implementing a large number of software-based functions onto a designated platform to match the plant's architecture. This problem is not unique to any particular safety-related platform solution, but is prevalent across the landscape of current Qualified and Licensed Safety-related Instrumentation and Control (I and C) Solutions. As an example when implementing a RG 1.97 compliant Post Accident Monitoring System (PAMS) solution with the Lockheed Martin Nuclear Protection and Control (NuPAC) safety platform, 72 unique software loads are needed to configure the Qualified Display System (QDS). Large scale development and customization efforts to upgrade existing plant functions or systems require the licensee to assume the cost and technical risk necessary to undergo a digital based upgrade. Often the cost, schedule, and technical risk outweighed the benefit of modernization efforts due to the unknown hurdles and past projects that overran cost and schedule projections. Lockheed Martin's Engineering Production Suite (EPS) minimizes the licensee risk and expense associated with modernization efforts through a developer's toolkit for rapid, automated, and repeatable development of Programmable Logic used to implement plant functions and architectures for use on the Lockheed Martin NuPAC platform. This paper describes a use case where by EPS can create system level representations, simulate system functions, partition logic designs to accommodate hardware constraints through logic partitioning, automate the assembly of Application Specific Programmable Logic (ASPL), generate system test cases, program the NuPAC hardware, and perform testing throughout the design workflow. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

CRISPR-COPIES: an in silico platform for discovery of neutral integration sites for CRISPR/Cas-facilitated gene integration

Abstract The CRISPR/Cas system has emerged as a powerful tool for genome editing in metabolic engineering and human gene therapy. However, locating the optimal site on the chromosome to integrate heterologous genes using the CRISPR/Cas system remains an open question. Selecting a suitable site for gene integration involves considering multiple complex criteria, including factors related to CRISPR/Cas-mediated integration, genetic stability, and gene expression. Consequently, identifying such sites on specific or different chromosomal locations typically requires extensive characterization efforts. To address these challenges, we have developed CRISPR-COPIES, a COmputational Pipeline for the Identification of CRISPR/Cas-facilitated intEgration Sites. This tool leverages ScaNN, a state-of-the-art model on the embedding-based nearest neighbor search for fast and accurate off-target search, and can identify genome-wide intergenic sites for most bacterial and fungal genomes within minutes. As a proof of concept, we utilized CRISPR-COPIES to characterize neutral integration sites in three diverse species: Saccharomyces cerevisiae, Cupriavidus necator, and HEK293T cells. In addition, we developed a user-friendly web interface for CRISPR-COPIES (https://biofoundry.web.illinois.edu/copies/). We anticipate that CRISPR-COPIES will serve as a valuable tool for targeted DNA integration and aid in the characterization of synthetic biology toolkits, enable rapid strain construction to produce valuable biochemicals, and support human gene and cell therapy applications.

59 BASIC BIOLOGICAL SCIENCES↗

Development of a high efficiency integration system and promoter library for rapid modification of Pseudomonas putida KT2440

Pseudomonas putida strains are highly robust bacteria known for their ability to efficiently utilize a variety of carbon sources, including aliphatic and aromatic hydrocarbons. Recently, P. putida has been engineered to valorize the lignin stream of a lignocellulosic biomass pretreatment process. Nonetheless, when compared to platform organisms such as Escherichia coli, the toolkit for engineering P. putida is underdeveloped. Heterologous gene expression in particular is problematic. Plasmid instability and copy number variance provide challenges for replicative plasmids, while use of homologous recombination for insertion of DNA into the chromosome is slow and laborious. Furthermore, heterologous expression efforts to date typically rely on overexpression of exogenous pathways using a handful of poorly characterized promoters. In order to improve the P. putida toolkit, we developed a rapid genome integration system using the site-specific recombinase from bacteriophage Bxb1 to enable rapid, high efficiency integration of DNA into the P. putida chromosome. We also developed a library of synthetic promoters with various UP elements, -35 sequences, and -10 sequences, as well as different ribosomal binding sites. We tested these promoters using a fluorescent reporter gene, mNeonGreen, to characterize the strength of each promoter, and identified UP-element-promoter-ribosomal binding sites combinations capable of driving a ~150-fold range of protein expression levels. One additional integrating vector was developed that confers more robust kanamycin resistance when integrated at single copy into the chromosome. This genome integration and reporter systems are extensible for testing other genetic parts, such as examining terminator strength, and will allow rapid integration of heterologous pathways for metabolic engineering.

59 BASIC BIOLOGICAL SCIENCES↗

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↗

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↗

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↗

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↗

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↗

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 ↗

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↗

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↗