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Prototyping and Characterization of Advanced Environments for AI+HPC on Commodity Systems
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Evaluating Opportunities to Improve Material and Energy Impacts in Commodity Supply Chains.
When evaluated at the process level, next-generation technologies may be more energy and emissions intensive than current technology. However, many advanced technologies have the potential to reduce material and energy consumption in upstream or downstream processing stages. In order to fully understand the benefits and consequences of technology deployment, next-generation technologies should be evaluated in context, as part of a supply chain. This work presents the Material Flows through Industry (MFI) scenario modeling tool. The MFI tool is a cradle-to-gate linear network model of the U.S. industrial sector that can model a wide range of manufacturing scenarios, including changes in production technology, increases in industrial energy efficiency, and substitution between functionally equivalent materials. The MFI tool was developed to perform supply chain scale analyses in order to quantify the impacts and benefits of next-generation technologies and materials at that scale. For the analysis presented in this paper, the MFI tool is utilized to explore a case study comparing a steel supply chain to the supply chains of several functionally equivalent materials. Several of the alternatives to the baseline steel supply chain include next-generation production technologies and materials. Results of the case study show that aluminum production scenarios can out-perform the steel supply chain by using either an advanced smelting technology or an increased aluminum recycling rate. The next-generation material supply chains do not perform as well as either aluminum or steel, but may offer additional use phase reductions in energy and emissions that are outside the scope of the MFI tool. Future work will combine results from the MFI tool with a use phase analysis.
GPGPU Enabled Adaptive Volume Visualization Using Commodity Game Engines
The amount of data produced by researchers in fields like nuclear engineering, materials science, and medicine has dramatically increased in recent years. There is a growing need to analyze and visualize this data in order to derive new insights. However, creating a visualization of data that is many gigabytes in size in real time is a difficult task since most graphics processing units (GPUs) are unable to hold this much data at one time. In order to alleviate this issue, an adaptive volume visualizer has been developed that is capable of rendering large scale datasets with high levels of detail at interactive framerates.
Microalgae Commodities from Coal-Fired Power Plant Flue Gas CO 2 (Draft Final Report, October 1, 2015 to June 30, 2018)
The Orlando Utilities Commission (OUC) operates an approximately 900-MWe coal fired-power plant at Stanton Energy Center (SEC), which was the site for this project to develop an integrated process for microalgae utilization of flue gas CO 2 for the production of biofuels and animal feeds. Microalgae have both potentially high yields (tons biomass/acre-year) and can be used for biofuels or high value animal feeds. The high biomass yields of microalgae cultures allows efficient use of land and water resources. They can also use wastewaters, recycle fertilizers, and have lower overall greenhouse gas emissions than conventional biofuels or animal feeds. However, many technical issues and technology gaps related to large-scale algae biomass production still must be resolved before such a process can be scaled-up. In this project, techno-economic analyses (TEAs) and life cycle assessments (LCAs) were carried out, projecting the costs and impacts of large-scale algae biomass cultivation for production of biofuels and animal feeds using OUC-SEC flue gas CO 2 . In addition, 3.5-m 2 (~ 40-ft 2 ) experimental raceway ponds were used for the cultivation of microalgae at OUC-SEC and also at the University of Florida. A large-scale algae farm was designed for a 1,300-acre site (~500-ha) located near the OUC-SEC plant, consisting of 400 hectares (1,000 acres) of paddle wheel mixed raceway ponds (each 4 ha), receiving flue gas piped approximately 3 km (2 miles) from the SEC plant. In the first year of this project (Budget Period 1, BP1), the TEA and LCA studies focused on the production of biogas produced from algae biomass and its use to replace coal at the power plant. However, due to the resulting very high cost of CO 2 mitigation, the process was modified to produce compressed natural gas (‘renewable natural gas’, RNG) for transportation fuel from the biogas, in conjunction with wastewater treatment by the algae cultures. During Budget Period 2 (BP2), the TEA and LCA studies focused on the production of animal feeds by the algae farm, using fresh water and agricultural fertilizers. In this case, CO 2 mitigation costs would be entirely covered if the algal biomass could be sold at between a two to three-fold premium above soybean feed, based on a higher nutritional value for the algal biomass. In support of the above analyses, microalgae cultivation experiments were carried out for over two years during this project in small 3.5-m 2 ponds at both SEC and the University of Florida. The most important results were the demonstration at SEC of the cultivation, on flue gas CO 2 , of filamentous algae biomass, which can be harvested at much lower cost than processes required for the colloidal algae species, as currently used by almost all algal mass culture biofuels and animal feeds projects. The yield of biogas production from the algal biomass was investigated by the University of Florida, and the value of the algal biomass as animal feed was projected based on biochemical analysis of the SEC ad UF biomasses. The conclusion from TEA/LCA carried out for the biogas case in BP1 was that a 400-ha algae system producing biomethane for co-firing at OUC-SEC could generate 27,500 MWh/yr of renewable power, offsetting 28,400 Mg CO 2eq /yr, which amounted to less than 1% of the CO 2 emitted by the SEC plant. (Mg = metric ton = 1.10 short tons). The overall cost was projected at $820/Mg of CO 2eq reduction, making this process unfeasible under any possible scenario. More favorable economics were projected when the biogas was converted to higher value transportation fuel, RNG, which also would benefit from renewable fuel (RINs) and possibly other credits. However, only by combining RNG production with municipal wastewater treatment in the algal ponds would CO 2 utilization result in no net cost or even be economically beneficial (i.e., generate income to the power plant). However, in that case the amount of CO 2 utilization would be even lower than that in the biogas case, because a large fraction of the carbon required would be supplied from the wastewater and CO 2 recovered during biogas upgrading to RNG. In brief, use of power plant CO 2 emissions for algal biofuels production was not favorable, even with optimistic assumptions about biomass productivity and biogas yields. For the animal feed case, developed during BP2, algal biomass would replace soybean feeds. The same scale 400-ha algal production plant was projected to produce 26,280 Mg per year of animal feed with a utilization of 45,300 Mg flue gas CO 2 taken up by the algal biomass. However, the process would result in a projected reduction of 112,500 Mg CO 2eq emissions per year, or roughly 1.9% of OUC-SEC emissions, mainly due to the large CO 2eq emissions from conventional soybean production. A major factor in this analysis were greenhouse gas emissions from land use changes. The cost of CO 2 utilization was projected at $116/Mg if the biomass sold for the same price as soybean meal, but if sold as a premium feed (e.g., based on high omega-3 fatty acid and carotenoid content), the power plant could actually charge for the CO 2 utilized. These economic projections are sensitive to assumptions underlying the TEA and LCA models, including biomass composition and the financial models used to project CAPEX and OPEX. Further development of an algal animal feed production using coal-fired power plant flue gas CO 2 is recommended based on the TEA and LCA, as well as experimental results. The required research and development is detailed in a technology gap analysis (Section 11), which focuses on the demonstrations of the cultivation of higher value filamentous algal biomass at OUC-SEC.
Chemical looping combustion and gasification technologies for production of heat and valuable commodities
Presented by NETL at 2nd International Conference on Advances in Chemical Engineering and Technology, 11/17
Direct Conversion of Shale Gas Alkanes to Commodity Chemicals
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TOSS-2020: A Commodity Software Stack for High-Performance Computing
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Inspecting fast commodity RDMA network performance on production systems with LDMS.
Abstract not provided.
Synthesis of multiphase self-healing polymers from commodity monomers
A self-healing polymer material that includes a multiphase copolymer, and a method of making the copolymer, are provided. The multiphase copolymer includes one or more hydrogen bond-forming copolymer segments, each segment including a polymerized acrylamide monomer and a polymerized acrylic monomer. The polymerized acrylamide monomer includes functional groups that form hydrogen bonds in the multiphase copolymer, and is present in the one or more copolymer segments in an amount sufficient for self-healing of the multiphase copolymer.
DOE SBIR Final Technical Report: Interactive Visualization of Multi-Terabyte Datasets on Commodity Hardware
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Production of carotenoids from aromatics and pretreated lignocellulosic biomass by Novosphingobium aromaticivorans
ABSTRACT Carotenoids are lipophilic compounds found in the membranes of various organisms. Individual carotenoids are also commodity chemicals, produced industrially for use as food additives, nutritional supplements, cosmetics, and pharmaceuticals. The alphaproteobacterium Novosphingobium aromaticivorans has previously been established as a potential platform microbe for converting aromatic compounds derived from lignocellulosic plant biomass into valuable extracellular products. Here, we show that N. aromaticivorans DSM 12444 cells naturally produce the carotenoid nostoxanthin, and we construct a set of gene deletion mutants that accumulate β-carotene, lycopene, or zeaxanthin, which are predicted intermediates in nostoxanthin biosynthesis as well as commodity chemicals. We also show that a mutant strain heterologously expressing a CrtW protein accumulates the carotenoid astaxanthin. When grown on vanillate as the carbon source, we find that the levels of carotenoids are not significantly affected by O 2 concentration in the tested range of 5% to 21% O 2 . We also show that these carotenoids are produced at comparable levels when strains are grown in liquor from alkaline pretreated sorghum biomass [sorghum alkaline pretreatment liquor (APL)], which contains a mixture of aromatics. Finally, we construct strains that produce zeaxanthin, β-carotene, or astaxanthin concurrently with 2-pyrone-4,6-dicarboxylic acid, a potential building block for biodegradable polymers, when grown in sorghum APL. Combined, our results show that N. aromaticivorans can simultaneously produce valuable intracellular and extracellular commodities when grown in the presence of either pure aromatics or pretreated lignocellulosic biomass. IMPORTANCE There is economic and environmental interest in generating commodity chemicals from renewable resources, such as lignocellulosic biomass, that can substitute for chemicals derived from fossil fuels. The bacterium Novosphingobium aromaticivorans is a promising microbial platform for producing commodity chemicals from lignocellulosic biomass because it can produce these from compounds in pretreated lignocellulosic biomass, which many industrial microbial catalysts cannot metabolize. Here, we show that N. aromaticivorans can be engineered to produce several valuable carotenoids. We also show that engineered N. aromaticivorans strains can produce these lipophilic chemicals concurrently with the extracellular commodity chemical 2-pyrone-4,6-dicarboxylic acid when grown in a complex liquor obtained from alkaline pretreated lignocellulosic biomass. Concurrent microbial production of valuable intra- and extracellular products can increase the economic value generated from the conversion of lignocellulosic biomass-derived compounds into commodity chemicals and facilitate the separation of water- and membrane-soluble products.
Understanding the Impact of the Secondary Market on Proliferation
Economic, technological, and social trends are changing the way consumers think about used commodities. Many consumers are now more willing to consider used or remanufactured goods. Simultaneously, new technological innovations are arising that make it more cost-effective to remanufacture these goods and easier to find buyers for them. Together, these changes have led to rapid growth in the secondary market and, along with it, a new threat: the potential export of used, listed weapons of mass destruction (WMD)-related commodities by secondary market resellers who are unaware of export control requirements. While the export of WMD-related commodities is regulated throughout the commodity’s lifetime, knowledge of those export control requirements is sometimes lost as commodities are sold and resold. As such, the secondary market for listed commodities pose proliferation risks and export control challenges that may not be well understood by the U.S. Government.
Climate Services for Agriculture: Tools for Informing Decisions Relating to Climate Change and Climate Variability in the Wine Industry
Australia’s changing climate is already impacting the agriculture sector and will continue to do so in the future. To help respond to these impacts, the Climate Services for Agriculture (CSA) platform presents readily accessible climate data, including future climate projections, relevant to specific agricultural commodities. This wine industry example aims to demonstrate the functionality and utility of the CSA for national use across a broad range of commodities. Methods and Results. The platform includes commodity-relevant climate indices designed in consultation with experts to ensure that they are as salient to producers as possible; the wine-grape specific indices include measures of growing season temperature, rainfall, extreme heat, and frost. Here, we describe the research behind the wine-grape specific indices and present sample outputs from the CSA platform for a site within a selected winegrowing region. We note the CSA platform has been developed through an extensive and continuing user engagement initiative, ensuring it meets the needs of the agriculture community as they grapple with how to make decisions based on longer term climate projections. Conclusions. Provision of past, seasonal outlook, and future climate information for Australia and for a range of important agricultural commodities can help improve on-farm planning and decision-making to respond to climate risks. The wine industry provides a leading example of how to use these data for decision-making, noting ongoing adjustments will be needed. Significance of the Study. The CSA platform brings together historical climate data, seasonal climate outlooks, and future climate projections to assist agricultural producers to better manage climate variability and climate change. It aims to nationalise this information for all major agricultural commodities in Australia. We use wine production as a demonstration case here.
Data Fusion for the Development of a Multimodal Freight Transload Facilities Dataset in the U.S.
To withstand the growing demand of commodity volume and its strain on the transportation infrastructure, it is necessary to identify the flow of commodities by route and mode. However, a national multimodal freight routing model does not exist for the U.S. The development of such model requires multiple building blocks, such as virtual representations of roadway, railway, and waterway networks, transload facilities (TFs), and access/egress links. Most of these blocks have a robust database in the U.S., except for the TFs. Here, this paper presents the fusion of dispersed and heterogeneous representations of multimodal TFs into a single, comprehensive, geospatial freight TF dataset. The TF dataset is derived from several sources, including the U.S. Army Corps of Engineers Master Docks Plus, the National Transportation Atlas Database, the Intermodal Association of North America, industry publications, and other public information. First, individual datasets were queried and reconciled. A geocoding/reverse geocoding process was applied to get the best street address and latitude/longitude location for each terminal. Then, duplicate terminals were identified by a fuzzy match algorithm based on terminal name and location, and removed. Validation was performed by visual inspection of random facilities. The main contributions of this work are: a publicly available version of the TF dataset, including facility location and multimodal transfer capability of 9,003 facilities, and an enterprise-version with the same facilities but including commodity handling capabilities. The main purpose of developing the TF dataset is to inform multimodal routing algorithms. The proposed TF dataset allows for credibly modeling the multimodal transfer of commodities within shipment routes.
Large-scale fire suppression modeling of corrugated cardboard boxes on wood pallets in rack-storage configurations
In this study, the fire growth and suppression models in FireFOAM were validated for rack-storage commodities consisting of two solid fuels, namely corrugated cardboard boxes and hardwood pallets, which are referred to as Class 2 commodity. Validation experiments included two fire-growth and two fire-suppression configurations with different rack-storage array heights (3 and 5 tiers). In the suppression study, standard-response upright ceiling sprinklers (K-factor of 160 lpm/bar1/2) were used. The time-resolved chemical heat release rates obtained from the experiments were used to validate the fire growth model. The observed sprinkler activations and fire-spread patterns were used to validate the suppression model. This study identified that lateral flame spread is primarily enabled by flames impinging on the commodity's bottom surfaces. This study also showed that obstructions, such as wood pallets, can significantly impede convective and radiative heat transfer to the underside of the commodity, reducing the lateral flame spread rate. Fire-suppression modeling revealed that both surface water transport and lateral flame spread rates are important when predicting fire-suppression behavior. Therefore, as the rack-storage array height increases, so does the water transport time, which results in the fire becoming more difficult to control. Likewise, as the lateral spread rate increases, e.g., as occurs in the absence of wood pallets, fire-suppression also becomes more difficult.
An Open Source Extensible Smart Energy Framework
Aggregated distributed energy resources are the subject of much interest in the energy industry and are expected to play an important role in meeting our future energy needs by changing how we use, distribute and generate electricity. This energy future includes an increased amount of energy from renewable resources, load management techniques to improve resiliency and reliability, and distributed energy storage and generation capabilities that can be managed to meet the needs of the grid as well as individual customers. These energy assets are commonly referred to as Distributed Energy Resources (DER). DERs rely on a means to communicate information between an energy provider and multitudes of devices. Today DER control systems are typically vendor-specific, using custom hardware and software solutions. As a result, customers are locked into communication transport protocols, applications, tools, and data formats. Today’s systems are often difficult to extend to meet new application requirements, resulting in stranded assets when business requirements or energy management models evolve. By partnering with industry advisors and researchers, an implementation DER research platform was developed called the Smart Energy Framework (SEF). The hypothesis of this research was that an open source Internet of Things (IoT) framework could play a role in creating a commodity-based eco-system for DER assets that would reduce costs and provide interoperable products. SEF is based on the AllJoynTM IoT open source framework. The demonstration system incorporated DER assets, specifically batteries and smart water heaters. To verify the behavior of the distributed system, models of water heaters and batteries were also developed. An IoT interface for communicating between the assets and a control server was defined. This interface supports a series of “events” and telemetry reporting, similar to those defined by current smart grid communication standards. The results of this effort demonstrated the feasibility and application potential of using IoT frameworks for the creation of commodity-based DER systems. All of the identified commodity-based system requirements were met by the AllJoyn framework. By having commodity solutions, small vendors can enter the market and the cost of implementation for all parties is reduced. Utilities and aggregators can choose from multiple interoperable products reducing the risk of stranded assets. Based on this research it is recommended that interfaces based on existing smart grid communication protocol standards be created for these emerging IoT frameworks. These interfaces should be standardized as part of the IoT framework allowing for interoperability testing and certification. Similarly, IoT frameworks are introducing application level security. This type of security is needed for protecting application and platforms and will be important moving forward. Recommendations are that along with DER-based data model interfaces, platform and application security requirements also be prescribed when IoT devices support DER applications.
A Visual Atlas on Strategic Trade
Strategic trade concerns global trade flows of items with strategic military value. Items include goods with exclusive military use, but also dual-use items that can have both military and civil uses. Many countries require licenses for trade in strategic items as a measure of non-proliferation. For example, items listed for trade control by multilateral export control arrangements, such as the Nuclear Suppliers Group (NSG), typically are considered strategic goods. Analysts and officials involved in strategic trade control often lack quantitative global understanding of relevant trade patterns that would help them focus control and enforcement efforts, select companies for outreach and audit, target transactions for verification and inspection, and assess the potential economic impact of trade control policies. Many are unaware of available open source data on international trade that can inform these issues. Many do not know how to make use of such data or lack the tools necessary to do so. A book of charts dubbed a ‘Strategic Trade Atlas’ was developed to illustrate global trade flows of strategic goods and raise awareness of the availability and utility of open source trade data. The Atlas was prepared for the World Customs Organization (WCO) and its Member States to support their planning and execution of Strategic Trade Control Enforcement (STCE) operations. It offers macroscopic graphical representations of global trade flows classified under Harmonized System (HS) codes associated by the WCO with commodities described in its STCE Implementation Guide. While these HS codes are understood to also encompass many non-strategic items, they nevertheless provide a good overview of potentially strategic trade flows. These include HS codes covering nuclear and nuclear-related commodities listed by the NSG, such as uranium, heavy water, graphite, carbon fiber, nickel powder, beryllium, aluminum tubes, vacuum pumps, valves, machine tools, cameras, and many others. The Atlas uses trade data from the Base pour l’Analyse du Commerce International (BACI), a statistical elaboration of public UN Comtrade data. BACI data reconciles trade flows, taking into account asymmetries in import and export trade valuation. The data visualization approach facilitates rapid sense making, pattern recognition, and anomaly detection. Country-based profiles summarize vast amounts of data into readily understandable graphical representations of each country’s primary strategic imports and exports and their main trading partners. Commodity-based profiles provide a global view of major exporters, importers, and trade patterns for each commodity. These insights can inform the risk management approach employed by customs to allocate enforcement and compliance efforts.