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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 sourcesNASA NTRSDOE OSTI
DOE OSTI2020

New Technologies for Power System Operation and Analysis, 1st Edition

New Technologies for Power System Operation and Analysis considers the very latest developments in renewable energy integration and system operation, including electricity markets and wide-area monitoring systems and forecasting. Helping readers quickly grasp the essential information needed to address renewable energy integration challenges, this new book looks at basic power system mathematical models, advanced renewable integration and system optimizations from transmission and distribution system sides. Sections cover wind, solar, gas and petroleum, making this a useful reference for all engineers interested in power system operation.

electricity markets↗
DOE OSTI2016

A Survey of Colormaps in Visualization

Colormaps are a vital method for users to gain insights into data in a visualization. With a good choice of colormaps, users are able to acquire information in the data more effectively and efficiently. In this survey, we attempt to provide readers with a comprehensive review of colormap generation techniques and provide readers a taxonomy which is helpful for finding appropriate techniques to use for their data and applications. Specifically, we first briefly introduce the basics of color spaces including color appearance models. In the core of our paper, we survey colormap generation techniques, including the latest advances in the field by grouping these techniques into four classes: procedural methods, user-study based methods, rule-based methods, and data-driven methods; we also include a section on methods that are beyond pure data comprehension purposes. We then classify colormapping techniques into a taxonomy for readers to quickly identify the appropriate techniques they might use. Furthermore, a representative set of visualization techniques that explicitly discuss the use of colormaps is reviewed and classified based on the nature of the data in these applications. Lastly, our paper is also intended to be a reference of colormap choices for readers when they are faced with similar data and/or tasks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

UV-filters and musk fragrances in seafood commercialized in Europe Union: Occurrence, risk and exposure assessment

Highlights: • Largest survey on UV-Fs and musks in seafood commercialized in Europe. • Farmed seabream showed the highest average concentration of UV-Fs. • Wild mackerel showed the highest average concentration of polycyclic musks. • UV-Fs and musks in raw samples were far below the estimated toxicological reference value. In the framework of the FP7 ECsafeSeafood project, 62 seafood samples commercialized in Europe Union from several representative species – mackerel, tuna, salmon, seabream, cod, monkfish, crab, shrimp, octopus, perch and plaice – were analysed for residues of 21 personal care products (PCPs), including 11 UV-filters (UV-Fs) and 10 musk fragrances (musks). PCPs analysis were performed by Quick, Easy, Cheap, Effective Rugged, Safe (QuEChERS), combined with liquid-liquid extraction (LLE) or dispersive solid-phase extraction (dSPE), followed by gas chromatography-tandem mass spectrometry (GC-MS/MS). The results showed the presence in a wide range of samples of nine out of eleven UV-Fs compounds analysed, namely 2-ethylhexyl salicylate (EHS), 2-ethylhexyl,4-methoxycinnamate (EHMC), 4-methylbenzylidenecamphor (4-MBC), benzophenone-1 (BP1), benzophenone-3 (BP3), isoamyl-4-methoxycinnamate (IMC), 2,2′-dihydroxy-4,4′-dimethoxybenzophenone (DHMB), homosalate (HS), and octocrylene (OC), whereas galaxolide (HHCB), galaxolide lactone (HHCB-lactone), and tonalide (AHTN) were the most found musks. The potential risks to human health associated with the exposure to eight of the more prevalent PCPs – EHS, EHMC, 4-MBC, BP1, BP3, IMC, HHCB, and AHTN - through seafood consumption were assessed for consumers from five European countries (Belgium, Ireland, Italy, Portugal and Spain). Results showed that the human exposure to UV-Fs and musks estimated from the concentration values found in seafood and the daily consumption of concerned seafood species, were far below toxicological reference values.

54 ENVIRONMENTAL SCIENCES↗
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 OSTI2022

Primer for OTERR Core Reloading Optimization

OTERR (Optimization of Test Reactor Reloading) is a software tool which assists in finding optimal fuel assembly reloading patterns for nuclear reactors. It was created specifically to support the Versatile Test Reactor (VTR) program, but its functionality is general enough to be applied to most fast spectrum reactors which use hexagonal prismatic fuel elements. This document is meant to be a primer for new users of OTERR to walk through example workflows for core reloading optimization cases. Simple cases are followed step-by-step to discuss what needs to be done to complete a reloading optimization sequence. Note that the intent of this document is to provide practical examples for users to follow along with so they can quickly start using OTERR and then make changes to fit their own modeling needs. Detail is limited in terms of addressing additional features not used in these examples and especially lacking in discussion of theory used in the code. To better address these points, users are highly encouraged to refer to the OTERR User Manual and the OTERR Theory Manual.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Approximate Inverse Chain Preconditioner: Iteration Count Case Study for Spectral Support Solvers

As the growing availability of computational power slows, there has been an increasing reliance on algorithmic advances. However, faster algorithms alone will not necessarily bridge the gap in allowing computational scientists to study problems at the edge of scientific discovery in the next several decades. Often, it is necessary to simplify or precondition solvers to accelerate the study of large systems of linear equations commonly seen in a number of scientific fields. Preconditioning a problem to increase efficiency is often seen as the best approach; yet, preconditioners which are fast, smart, and efficient do not always exist. Following the progress of [1], we present a new preconditioner for symmetric diagonally dominant (SDD) systems of linear equations. These systems are common in certain PDEs, network science, and supervised learning among others. Based on spectral support graph theory, this new preconditioner builds off of the work of [2], computing and applying a V-cycle chain of approximate inverse matrices. This preconditioner approach is both algebraic in nature as well as hierarchically-constrained depending on the condition number of the system to be solved. Due to its generation of an Approximate Inverse Chain of matrices, we refer to this as the AIC preconditioner. We further accelerate the AIC preconditioner by utilizing precomputations to simplify setup and multiplications in the con-text of an iterative Krylov-subspace solver. While these iterative solvers can greatly reduce solution time, the number of iterations can grow large quickly in the absence of good preconditioners. Initial results for the AIC preconditioner have shown a very large reduction in iteration counts for SDD systems as compared to standard preconditioners such as Incomplete Cholesky (ICC) and Multigrid (MG). We further show significant reduction in iteration counts against the more advanced Combinatorial Multigrid (CMG) preconditioner. We have further developed no-fill sparsification techniques to ensure that the computational cost of applying the AIC preconditioner does not grow prohibitively large as the depth of the V-cycle grows for systems with larger condition numbers. Our numerical results have shown that these sparsifiers maintain the sparsity structure of our system while also displaying significant reductions in iteration counts.1 2

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Approximate Inverse Chain Preconditioner: Iteration Count Case Study for Spectral Support Solvers

As the growing availability of computational power slows, there has been an increasing reliance on algorithmic advances. However, faster algorithms alone will not necessarily bridge the gap in allowing computational scientists to study problems at the edge of scientific discovery in the next several decades. Often, it is necessary to simplify or precondition solvers to accelerate the study of large systems of linear equations commonly seen in a number of scientific fields. Preconditioning a problem to increase efficiency is often seen as the best approach; yet, preconditioners which are fast, smart, and efficient do not always exist. Following the progress of [1], we present a new preconditioner for symmetric diagonally dominant (SDD) systems of linear equations. These systems are common in certain PDEs, network science, and supervised learning among others. Based on spectral support graph theory, this new preconditioner builds off of the work of [2], computing and applying a V-cycle chain of approximate inverse matrices. This preconditioner approach is both algebraic in nature as well as hierarchically-constrained depending on the condition number of the system to be solved. Due to its generation of an Approximate Inverse Chain of matrices, we refer to this as the AIC preconditioner. We further accelerate the AIC preconditioner by utilizing precomputations to simplify setup and multiplications in the con-text of an iterative Krylov-subspace solver. While these iterative solvers can greatly reduce solution time, the number of iterations can grow large quickly in the absence of good preconditioners. Initial results for the AIC preconditioner have shown a very large reduction in iteration counts for SDD systems as compared to standard preconditioners such as Incomplete Cholesky (ICC) and Multigrid (MG). We further show significant reduction in iteration counts against the more advanced Combinatorial Multigrid (CMG) preconditioner. We have further developed no-fill sparsification techniques to ensure that the computational cost of applying the AIC preconditioner does not grow prohibitively large as the depth of the V-cycle grows for systems with larger condition numbers. Our numerical results have shown that these sparsifiers maintain the sparsity structure of our system while also displaying significant reductions in iteration counts.1 2

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

High-Throughput Directed Evolution of Marine Microalgae and Phototrophic Consortia for Improved Biomass Yields (Final Report)

Primary project achievements include using selective pressures (O 2 , light, temperature) and developing culturing regimes for the diatom Nitzschia inconspicua str. hildebrandi to attain enrichments with an ~90% increase in areal biomass productivity relative to the parental strain under pond-mimicking conditions with high O 2 stress in laboratory bioreactors. The resulting strain (GAI-337) was tested further for dilution time, culture density, CO 2 supplementation, pH, temperature, and dissolved O 2 concentration under outdoor pond-mimicking conditions to improve areal productivities. These experiments yielded an optimum harvest and dilution time just after sunset, ~0.45 g AFDW L -1 initial culture density for maximal productivities, no requirement for CO 2 supplementation or pH control, maximal performance under a diel temperature curve going from 24 °C at night to 36 °C during the day, and benefits from some O 2 removal from the culture by bubbling with air. Using pond-mimicking laboratory bioreactors, N. inconspicua GAI-337 achieved ~42 g AFDW m -2 d -1 . Nutrient limitation experiments resulted in a biomass composition that equated to ~160 Gallons of Gasoline Equivalent energy per ton AFDW, highlighting the potential of GAI-337 as a promising renewable fuel feedstock strain. Genome resequencing has revealed genome alterations potentially contributing to the improved growth of GAI-337 in the laboratory. Based on the comparative analyses of the GAI-337 and GAI-229 (reference) strains, we identified 144 single nucleotide substitutions that resulted in amino acid change, 7 single nucleotide substitutions that resulted in protein truncation; 5 deletions; and 1 frameshift mutation. From the mutations that potentially affect expression of functionally annotated genes, particular interest was noted for an interferon-induced 6-16 family protein that may be involved in the host immune response against microbe invasion; the chaperone protein DnaK, which may function to protect the folding of proteins within the cell; and SPRY domain protein that is found in many eukaryotic proteins important in cell signaling pathways. Transcriptome analysis revealed over 1000 genes with increased transcript levels. Many of these and many of the genes with mutations are not yet functionally annotated and an increased bioinformatics effort is necessary to more completely analyze the Nitzschia inconspicua genome. Adaptive laboratory evolution (ALE) was performed for over 300 days using consecutive 0.5°C temperature increases in a constant temperature incubator to attain greater thermal tolerance in Nitzschia inconspicua. The adapted strain was able to grow at a constant temperature of 37.5°C; whereas this constant temperature was lethal to the parental control, which had an upper temperature boundary of 35.5°C prior to adaptive evolution. Several high-temperature clonal isolates were obtained from the evolved population following ALE, and increased temperature tolerance was observed in clonal adapted cultures. The final temperature adaptation was maintained through cryopreservation and was observed in multiple clonal isolates, including multiple clonal isolates with significantly increased cell size, indicating the potential occurrence of a sexual cycle during the clonal isolation process. A survey of Nannochloropsis strains was conducted for tolerances to high pH and high bicarbonate media. Nannochloropsis granulata showed promising growth in diel bioreactors and was successfully grown at the GAI Kauai farm site in long-term growth campaigns. Co-culturing using Nitzschia inconspicua, Nannochloropsis and a cyanobacterium were assembled in the laboratory to determine if productivity synergies could be attained. Although all strains grew well in the laboratory high-bicarbonate media individually, the cyanobacterium quickly outgrew the other strains in the laboratory consortium pushing the co-culture away from a diverse (and potentially synergistic assemblage) phototroph culture towards a monoculture dominated by the cyanobacterium. Several outdoor growth campaigns were conducted, with productivities ranging between 10-20 g/m 2 /d of biomass. The best performing strain in the laboratory (GAI-337) did not outperform reference strains at the Kauai farm under the conditions used. Addition growth campaigns are necessary under conditions that result in higher biomass (>20 g/m 2 /d) and that attain higher O 2 levels are likely necessary. Initial data indicate that the thermally adapted strain did slightly better than the control strain at higher temperatures; however, additional campaigns are necessary to establish statistical significance. In summary, Nitzschia inconspicua is able to attain exemplary biomass and lipid yields in the laboratory bioreactors. Strain evolution to both O 2 and temperature resulted in targeted strain improvements. Additional outdoor campaigns are necessary to determine if laboratory improvements translate to the field.

09 BIOMASS FUELS↗
DOE OSTI2014

SU-E-J-20: Adaptive Aperture Morphing for Online Correction for Prostate Cancer Radiotherapy

Purpose: Online adaptive aperture morphing is desirable over translational couch shifts to accommodate not only the target position variation but also anatomic changes (rotation, deformation, and relation of target to organ-atrisks). We proposed quick and reliable method for adapting segment aperture leaves for IMRT treatment of prostate. Methods: The proposed method consists of following steps: (1) delineate the contours of prostate, SV, bladder and rectum on kV-CBCT; (2) determine prostate displacement from the rigid body registration of the contoured prostate manifested on the reference CT and the CBCT; (3) adapt the MLC segment apertures obtained from the pre-treatment IMRT planning to accommodate the shifts as well as anatomic changes. The MLC aperture adaptive algorithm involves two steps; first move the whole aperture according to prostate translational/rotational shifts, and secondly fine-tune the aperture shape to maintain the spatial relationship between the planning target contour and the MLC aperture to the daily target contour. Feasibility of this method was evaluated retrospectively on a seven-field IMRT treatment of prostate cancer patient by comparing dose volume histograms of the original plan and the aperture-adjusted plan, with/without additional segments weight optimization (SWO), on two daily treatment CBCTs selected with relative large motion and rotation. Results: For first daily treatment, the prostate rotation was significant (12degree around lateral-axis). With apertureadjusted plan, the D95 to the target was improved 25% and rectum dose (D30, D40) was reduced 20% relative to original plan on daily volumes. For second treatment-fraction, (lateral shift = 6.7mm), after adjustment target D95 improved by 3% and bladder dose (D30, maximum dose) was reduced by 1%. For both cases, extra SWO did not provide significant improvement. Conclusion: The proposed method of adapting segment apertures is promising in treatment position correction, including target translational displacement, rotation and deformation. Additional SWO could improve ROIs dose distribution.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Thermal Energy Storage for Dispatchable Geothermal Power

Dispatchable generation refers to sources of electricity that can be turned on or off, or can adjust their power output accordingly to an order. Geothermal plants are usually used for base-load power rather than dispatchable power. Flexibility is a challenge for a geothermal plant because the heat source does not naturally respond quickly to changes in demand. The current state-of-the-art approach to address this challenge is to maintain the geothermal fluid flows at relatively steady rates while providing a bypass around the generation equipment as needed. Under part load, some of the geothermal fluid is pumped to the surface, bypasses the generation equipment, and is re-injected to the ground without extracting any useful enthalpy. This approach is robust but necessarily incurs high parasitic power draws at part load due to the constant, full-flow pumping power requirements. There are even more challenges and unknowns for steam and flash geothermal plants, which were the focus for this project. As a process improvement to this existing configuration of a dispatchable geothermal plant, we examined the use of a phase-change thermal-energy storage (TES) unit that will provide some “inertia” against temperature fluctuations. The TES phase change material (PCM) could be in the form of eutectic molten nitrate salts, organic sugar alcohols, or the like based on the required temperature. This configuration allowed the power plant to meet the ramp rate requirements while allowing the geothermal resource to drawn down at the duty-cycle-averaged extraction rate rather than the full-rated-output extraction rate. The project team performed an experimental and computational evaluation of a peak shaving technical approach that used thermal storage to switch between two nominal operating points: full rated power and 50% power. In the initial requirements definition phase, the team decided to examine the PCM/TES-enhanced geothermal plant in the context of a 40-MW two-stage flash plant operating in mid-Southern California. Steady-state process simulations were used to understand the equipment sizing and the energetics. Dynamic process simulations were used to understand the response rate of the system to changes in requested power output from the utility. The technical approach was also guided by a techno-economic analysis (TEA) and a high-level analysis of the reservoir. Recognizing that performance of the thermal storage was a key risk element, high-fidelity finite-element simulations of the PCM-TES heat exchanger were performed to better understand its performance and temporal response. These simulations were validated with a subscale PCM-TES experimental apparatus that mimicked the geometry of the full-scale system. The key outcomes of this Phase I project were that: 1) the PCM-TES heat exchanger met the target for gravimetric energy storage density, 2) the dispatchable geothermal plant met its target for response rate, 3) the peak shaving approach reduces the number of production wells and does not disturb the wellfield, and 4) the incentives for properly remunerating dispatchable operation were identified.

15 GEOTHERMAL ENERGY↗
DOE OSTI2017

Quicklook overview of model changes in Melcor 2.2: Rev 6342 to Rev 9496

MELCOR 2.2 is a significant official release of the MELCOR code with many new models and model improvements. This report provides the code user with a quick review and characterization of new models added, changes to existing models, the effect of code changes during this code development cycle (rev 6342 to rev 9496), a preview of validation results with this code version. More detailed information is found in the code Subversion logs as well as the User Guide and Reference Manuals.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Quick Urban and Industrial Complex (QUIC) CBR Plume Modeling System: Validation-Study Document

This document contains information on QUIC validation studies that have been performed to evaluate the wind, pressure, and concentration solutions produced by QUIC. Tests of QUIC's source term models and specialized transport mechanisms (e.g., buoyancy algorithms, particle settling and deposition, liquid pool growth, droplet and pool evaporation) are also provided. A brief description of the experiment, a few example validation results, and references to journal articles, reports, and/or presentations are given. Both LANL and non-LANL sources are provided.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Hourly land-use regression models based on low-cost PM monitor data

Highlights: • A network of 23 low-cost PM monitors was deployed across an urban area. • Land use regression models predict the hourly intra-urban PM variations. • Coefficients of determination for hourly PM predictions ranged 0.66–0.76. • Low-cost PM monitor data need to be carefully evaluated before use. • The combination of low-cost monitors and modeling provides useful PM estimates. Land-use regression (LUR) models provide location and time specific estimates of exposure to air pollution and thereby improve the sensitivity of health effects models. However, they require pollutant concentrations at multiple locations along with land-use variables. Often, monitoring is performed over short durations using mobile monitoring with research-grade instruments. Low-cost PM monitors provide an alternative approach that increases the spatial and temporal resolution of the air quality data. LUR models were developed to predict hourly PM concentrations across a metropolitan area using PM concentrations measured simultaneously at multiple locations with low-cost monitors. Monitors were placed at 23 sites during the 2015/16 heating season. Monitors were externally calibrated using co-located measurements including a reference instrument (GRIMM particle spectrometer). LUR models for each hour of the day and weekdays/weekend days were developed using the deletion/substitution/addition algorithm. Coefficients of determination for hourly PM predictions ranged from 0.66 and 0.76 (average 0.7). The hourly-resolved LUR model results will be used in epidemiological studies to examine if and how quickly, increases in ambient PM concentrations trigger adverse health events by reducing the exposure misclassification that arises from using less time resolved exposure estimates.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Design Guidelines for Deployable Wind Turbines for Military Operational Energy Applications

This document aims to provide guidance on the design and operation of deployable wind systems that provide maximum value to missions in defense and disaster relief. Common characteristics of these missions are shorter planning and execution time horizons and a global scope of potential locations. Compared to conventional wind turbine applications, defense and disaster response applications place a premium on rapid shipping and installation, short-duration operation (days to months), and quick teardown upon mission completion. Furthermore, defense and disaster response applications are less concerned with cost of energy than conventional wind turbine applications. These factors impart design drivers that depart from the features found in conventional distributed wind turbines, thus necessitating unique design guidance. The supporting information for this guidance comes from available relevant references, technical analyses, and input from industry and military stakeholders. This document is not intended to be a comprehensive, prescriptive design specification. This document is intended to serve as a written record of an ongoing discussion of stakeholders about the best currently available design guidance for deployable wind turbines to help facilitate the effective development and acquisition of technology solutions to support mission success. The document is generally organized to provide high-level, focused guidance in the main body, with more extensive supporting details available in the referenced appendices. Section 2 begins with a brief qualitative description of the design guidelines being considered for the deployable wind turbines. Section 3 provides an overview of the characteristics of the mobile power systems commonly used in U.S. military missions. Section 4 covers current military and industry standards and specifications that are relevant to a deployable wind turbine design. Section 5 presents the deployable turbine design guidelines for the application cases.

17 WIND ENERGY↗
DOE OSTI2016

Contingency Contractor Optimization Phase 3 Sustainment Platform Requirements - Contingency Contractor Optimization Tool - Prototype

Sandia National Laboratories (Sandia) is in Phase 3 Sustainment of development of a prototype tool, currently referred to as the Contingency Contractor Optimization Tool - Prototype (CCOTP), under the direction of OSD Program Support. CCOT-P is intended to help provide senior Department of Defense (DoD) leaders with comprehensive insight into the global availability, readiness and capabilities of the Total Force Mix. The CCOT-P will allow senior decision makers to quickly and accurately assess the impacts, risks and mitigating strategies for proposed changes to force/capabilities assignments, apportionments and allocations options, focusing specifically on contingency contractor planning. During Phase 2 of the program, conducted during fiscal year 2012, Sandia developed an electronic storyboard prototype of the Contingency Contractor Optimization Tool that can be used for communication with senior decision makers and other Operational Contract Support (OCS) stakeholders. Phase 3 used feedback from demonstrations of the electronic storyboard prototype to develop an engineering prototype for planners to evaluate. Sandia worked with the DoD and Joint Chiefs of Staff strategic planning community to get feedback and input to ensure that the engineering prototype was developed to closely align with future planning needs. The intended deployment environment was also a key consideration as this prototype was developed. Initial release of the engineering prototype was done on servers at Sandia in the middle of Phase 3. In 2013, the tool was installed on a production pilot server managed by the OUSD(AT&L) eBusiness Center. The purpose of this document is to specify the CCOT-P engineering prototype platform requirements as of May 2016. Sandia developed the CCOT-P engineering prototype using common technologies to minimize the likelihood of deployment issues. CCOT-P engineering prototype was architected and designed to be as independent as possible of the major deployment components such as the server hardware, the server operating system, the database, and the web server. This document describes the platform requirements, the architecture, and the implementation details of the CCOT-P engineering prototype.

42 ENGINEERING↗
DOE OSTI2017

Echo

This document is a white paper marketing proposal for Echo™ is a data analysis platform designed for efficient, robust, and scalable creation and execution of complex workflows. Echo’s analysis management system refers to the ability to track, understand, and reproduce workflows used for arriving at results and decisions. Echo improves on traditional scripted data analysis in MATLAB, Python, R, and other languages to allow analysts to make better use of their time. Additionally, the Echo platform provides a powerful data management and curation solution allowing analysts to quickly find, access, and consume datasets. After two years of development and a first release in early 2016, Echo is now available for use with many data types in a wide range of application domains. Echo provides tools that allow users to focus on data analysis and decisions with confidence that results are reported accurately.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

ENERGY INVESTMENTS UNDER CLIMATE POLICY: A COMPARISON OF GLOBAL MODELS

The levels of investment needed to mobilize an energy system transformation and mitigate climate change are not known with certainty. This paper aims to inform the ongoing dialogue and in so doing to guide public policy and strategic corporate decision making. Within the framework of the LIMITS integrated assessment model comparison exercise, we analyze a multi-IAM ensemble of long-term energy and greenhouse gas emissions scenarios. Our study provides insight into several critical but uncertain areas related to the future investment environment, for example in terms of where capital expenditures may need to flow regionally, into which sectors they might be concentrated, and what policies could be helpful in spurring these financial resources. We find that stringent climate policies consistent with a 2°C climate change target would require a considerable upscaling of investments into low-carbon energy and energy efficiency, reaching approximately $45 trillion (range: $30–$75 trillion) cumulative between 2010 and 2050, or about $1.1 trillion annually. This represents an increase of some $30 trillion ($10–$55 trillion), or $0.8 trillion per year, beyond what investments might otherwise be in a reference scenario that assumes the continuation of present and planned emissions-reducing policies throughout the world. In other words, a substantial "clean-energy investment gap" of some $800 billion/yr exists — notably on the same order of magnitude as present-day subsidies for fossil energy and electricity worldwide ($523 billion). Unless the gap is filled rather quickly, the 2°C target could potentially become out of reach.

carbon financing↗
DOE OSTI2018

Camelina sativa , an oilseed at the nexus between model system and commercial crop

The rapid assessment of metabolic engineering strategies in plants is aided by crops that provide simple, high throughput transformation systems, a sequenced genome, and the ability to evaluate the resulting plants in field trials. Camelina sativa provides all of these attributes in a robust oilseed platform. The ability to perform field evaluation of Camelina is a useful, and in some studies essential benefit that allows researchers to evaluate how traits perform outside the strictly controlled conditions of a greenhouse. In the field the plants are subjected to higher light intensities, seasonal diurnal variations in temperature and light, competition for nutrients, and watering regimes dictated by natural weather patterns, all which may affect trait performance. There are difficulties associated with the use of Camelina . The current genetic resources available for Camelina pale in comparison to those developed for the model plant Arabidopsis thaliana; however, the sequence similarity of the Arabidopsis and Camelina genomes often allows the use of Arabidopsis as a reference when additional information is needed. Camelina ’s genome, an allohexaploid, is more complex than other model crops, but the diploid inheritance of its three subgenomes is straightforward. The need to navigate three copies of each gene in genome editing or mutagenesis experiments adds some complexity but also provides advantages for gene dosage experiments. In conclusion, the ability to quickly engineer Camelina with novel traits, advance generations, and bulk up homozygous lines for small-scale field tests in less than a year, in our opinion, far outweighs the complexities associated with the crop.

59 BASIC BIOLOGICAL SCIENCES↗