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Simulation Data Management - Requirements and Design Specification

Friedman-Hill, Ernest; Clay, Robert L.; Gibson, Marcus; Hoffman, Edward L.; Olson, Kevin H.

Simulation Data Management (SDM), the ability to securely organize, archive, and share analysis models and the artifacts used to create them, is a fundamental requirement for modern engineering analysis based on computational simulation. We have worked separately to provide secure, network SDM services to engineers and scientists at our respective laboratories for over a decade. We propose to leverage our experience and lessons learned to help develop and deploy a next-generation SDM service as part of a multi-laboratory team. This service will be portable across multiple sites and platforms, and will be accessible via a range of command-line tools and well-documented APIs. In this document, we’ll review our high-level and low-level requirements for such a system, review one existing system, and briefly discuss our proposed implementation.

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TYPE SAND Report YEAR 2017
DOIOSTI

DOE/DOT Crude Oil Characterization Research Study, Task 2 Test Report on Evaluating Crude Oil Sampling and Analysis Methods

Lord, David; Allen, Ray; Rudeen, David

The Crude Oil Characterization Research Study is designed to evaluate whether crude oils currently transported in North America, including those produced from "tight" formations, exhibit physical or chemical properties that are distinct from conventional crudes, and how these properties associate with combustion hazards with may be realized during transportation and handling.

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TYPE SAND Report YEAR 2017
DOIOSTI

Cure Schedule for Stycast 2651/Catalyst 11

Kropka, Jamie M.; Mccoy, John

The Henkel technical data sheet (TDS) for Stycast 2651/Catalyst 11 lists three alternate cure schedules for the material, each of which would result in a different state of reaction and different material properties. Here, a cure schedule that attains full reaction of the material is defined. The use of this cure schedule will eliminate variance in material properties due to changes in the cure state of the material, and the cure schedule will serve as the method to make material prior to characterizing properties. The following recommendation was motivated by (1) a desire to cure at a single temperature for ease of manufacture and (2) a desire to keep the cure temperature low (to minimize residual stress build-up associated with the cooldown from the cure temperature to room temperature) without excessively limiting the cure reaction due to vitrification (i.e., material glass transition temperature, Tg, exceeding cure temperature).

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TYPE Other Report YEAR 2017
DOIOSTI

Cure Schedule for Stycast 2651/Catalyst 9

Kropka, Jamie M.; Mccoy, John

The Emerson & Cuming technical data sheet (TDS) for Stycast 2651/Catalyst 9 lists three alternate cure schedules for the material, each of which would result in a different state of reaction and different material properties. Here, a cure schedule that attains full reaction of the material is defined. The use of this cure schedule will eliminate variance in material properties due to changes in the cure state of the material, and the cure schedule will serve as the method to make material prior to characterizing properties. The following recommendation uses one of the schedules within the TDS and adds a “post cure” to obtain full reaction.

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TYPE Other Report YEAR 2017
DOIOSTI

Measuring Plasma Formation Field Strength and Current Loss in Pulsed Power Diodes

Johnston, Mark D.; Patel, Sonal G.; Falcon, Ross E.; Cartwright, Keith L.; Kiefer, Mark L.; Cuneo, Michael E.; Maron, Yitzhak

This LDRD investigated plasma formation, field strength, and current loss in pulsed power diodes. In particular the Self-Magnetic Pinch (SMP) e-beam diode was studied on the RITS-6 accelerator. Magnetic fields of a few Tesla and electric fields of several MV/cm were measured using visible spectroscopy techniques. The magnetic field measurements were then used to determine the current distribution in the diode. This distribution showed that significant beam current extends radially beyond the few millimeter x-ray focal spot diameter. Additionally, shielding of the magnetic field due to dense electrode surface plasmas was observed, quantified, and found to be consistent with the calculated Spitzer resistivity. In addition to the work on RITS, measurements were also made on the Z-machine looking to quantify plasmas within the power flow regions. Measurements were taken in the post-hole convolute and final feed gap regions on Z. Dopants were applied to power flow surfaces and measured spectroscopically. These measurements gave species and density/temperature estimates. Preliminary B-field measurements in the load region were attempted as well. Finally, simulation work using the EMPHASIS, electromagnetic particle in cell code, was conducted using the Z MITL conditions. The purpose of these simulations was to investigate several surface plasma generations models under Z conditions for comparison with experimental data.

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TYPE SAND Report YEAR 2017
DOIOSTI

Temporal Cyber Attack Detection

Ingram, Joe B.; Draelos, Timothy J.; Sahakian, Meghan A.; Doak, Justin E.

Rigorous characterization of the performance and generalization ability of cyber defense systems is extremely difficult, making it hard to gauge uncertainty, and thus, confidence. This difficulty largely stems from a lack of labeled attack data that fully explores the potential adversarial space. Currently, performance of cyber defense systems is typically evaluated in a qualitative manner by manually inspecting the results of the system on live data and adjusting as needed. Additionally, machine learning has shown promise in deriving models that automatically learn indicators of compromise that are more robust than analyst-derived detectors. However, to generate these models, most algorithms require large amounts of labeled data (i.e., examples of attacks). Algorithms that do not require annotated data to derive models are similarly at a disadvantage, because labeled data is still necessary when evaluating performance. In this work, we explore the use of temporal generative models to learn cyber attack graph representations and automatically generate data for experimentation and evaluation. Training and evaluating cyber systems and machine learning models requires significant, annotated data, which is typically collected and labeled by hand for one-off experiments. Automatically generating such data helps derive/evaluate detection models and ensures reproducibility of results. Experimentally, we demonstrate the efficacy of generative sequence analysis techniques on learning the structure of attack graphs, based on a realistic example. These derived models can then be used to generate more data. Additionally, we provide a roadmap for future research efforts in this area.

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TYPE Other Report YEAR 2017
DOIOSTI

Gasoline Combustion Fundamentals DOE FY17 Report

Ekoto, Isaac W.

Advanced automotive gasoline engines that leverage a combination of reduced heat transfer, throttling, and mechanical losses; shorter combustion durations; and higher compression and mixture specific heat ratios are needed to meet aggressive DOE VTP fuel economy and pollutant emission targets. Central challenges include poor combustion stability at low-power conditions when large amounts of charge dilution are introduced and high sensitivity of conventional inductive coil ignition systems to elevated charge motion and density for boosted high-load operation. For conventional spark ignited operation, novel low-temperature plasma (LTP) or pre-chamber based ignition systems can improve dilution tolerances while maintaining good performance characteristics at elevated charge densities. Moreover, these igniters can improve the control of advanced compression ignition (ACI) strategies for gasoline at low to moderate loads. The overarching research objective of the Gasoline Combustion Fundamentals project is to investigate phenomenological aspects related to enhanced ignition. The objective is accomplished through targeted experiments performed in a single-cylinder optically accessible research engine or an in-house developed optically accessible spark calorimeter (OASC). In situ optical diagnostics and ex situ gas sampling measurements are performed to elucidate important details of ignition and combustion processes. Measurements are further used to develop and validate complementary high-fidelity ignition simulations. The primary project audience is automotive manufacturers, Tier 1 suppliers, and technology startups—close cooperation has resulted in the development and execution of project objectives that address crucial mid- to long-range research challenges.

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TYPE Other Report YEAR 2017
DOIOSTI

Annual Report: DOE Advanced Combustion Systems & Fuels R&D; Light-Duty Diesel Combustion

Busch, Stephen

Despite compliance issues in previous years, automakers have demonstrated that the newest generation of diesel power trains are capable of meeting all federal and state regulations (EPA, 2016). Diesels continue to be a cost-effective, efficient, powerful propulsion source for many light- and medium-duty vehicle applications (Martec, 2016). Even modest reductions in the fuel consumption of light- and medium duty diesel vehicles in the U.S. will eliminate millions of tons of CO2 emissions per year. Continued improvement of diesel combustion systems will play an important role in reducing fleet fuel consumption, but these improvements will require an unprecedented scientific understanding of how changes in engine design and calibration affect the mixture preparation, combustion, and pollutant formation processes that take place inside the cylinder. The focus of this year’s research is to provide insight into the physical mechanisms responsible for improved thermal efficiency observed with a stepped-lip piston. Understanding how piston design can influence efficiency will help engineers develop and optimize new diesel combustion systems.

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TYPE Other Report YEAR 2017
DOIOSTI

Benefit Analysis of Energy Storage for Cordova Electric Cooperative

Schenkman, Benjamin L.; Vandermeer, Jeremy B.; Mueller-Stoffels, Marc; Koplin, Clay; Benson, Cole

This report is a follow on to a previous study performed by Sandia National Labs and Alaska Center for Energy and Power which investigated the use of an energy storage system (ESS) providing spinning reserve within the Cordova Electric Cooperative (CEC) grid. The study provided the savings using the ESS as spinning reserve through reduced fossil fuel consumption and runtime on the diesel generators. In this report, the saving values are used from the previous study to determine the benefit-to-cost ratio for various ratings of ESS performing spinning reserve and quantifying other applications that are applicable to CEC.

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TYPE SAND Report YEAR 2017
DOIOSTI

Heavy-Duty Low-Temperature and Diesel Combustion & Heavy-Duty Combustion Modeling

Musculus, Mark P.B.

Regulatory drivers and market demands for lower pollutant emissions, lower carbon dioxide emissions, and lower fuel consumption motivate the development of clean and fuel-efficient engine operating strategies. Most current production engines use a combination of both in-cylinder and exhaust emissions-control strategies to achieve these goals. The emissions and efficiency performance of in-cylinder strategies depend strongly on flow and mixing processes associated with fuel injection. Various diesel engine manufacturers have adopted close-coupled post-injection combustion strategies to both reduce pollutant emissions and to increase engine efficiency for heavy-duty applications, as well as for light- and medium-duty applications. Close-coupled post-injections are typically short injections that follow a larger main injection in the same cycle after a short dwell, such that the energy conversion efficiency of the post-injection is typical of diesel combustion. Of the various post-injection schedules that have been reported in the literature, effects on exhaust soot vary by roughly an order of magnitude in either direction of increasing or decreasing emissions relative to single injections (O’Connor et al., 2015). While several hypotheses have been offered in the literature to help explain these observations, no clear consensus has been established. For new engines to take full advantage of the benefits that post-injections can offer, the in-cylinder mechanisms that affect emissions and efficiency must be identified and described to provide guidance for engine design.

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TYPE Other Report YEAR 2017
DOIOSTI

Co-Optima Project E2.2.2: Accelerate Development of ACI/LTC Fuel Effects on RCCI Combustion

Musculus, Mark P.B.

Many advanced combustion approaches have demonstrated potential for achieving diesel-like thermal efficiency but with much lower pollutant emissions of particulate matter (PM) and nitrogen oxides (NOx). RCCI is one advanced combustion concept, which makes use of in-cylinder blending of two fuels with differing reactivity for improved control of the combustion phasing and rate (Reitz et al., 2015). Previous research and development at ORNL has demonstrated successful implementation of RCCI on a light-duty multi-cylinder engine over a wide range of operating conditions (Curran et al., 2015). Several challenges were encountered when extending the research to practical applications, including limits to the operating range, both for high and low loads. Co-optimizing the engine and fuel aspects of the RCCI approach might allow these operating limits to be overcome. The in-cylinder mechanisms by which fuel properties interact with engine operating condition variables is not well understood, however, in part because RCCI is a new combustion concept that is still being developed, and limited data have been acquired to date, especially using in-cylinder optical/imaging diagnostics. The objective of this work is to use in-cylinder diagnostics in a heavy-duty single-cylinder optical engine at SNL to understand the interplay between fuel properties and engine hardware and operating conditions for RCCI in general, and in particular for the light-duty multi-cylinder all-metal RCCI engine experiments at ORNL.

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TYPE Other Report YEAR 2017
DOIOSTI

Practical Application Limits of Fuel Cells and Batteries for Zero Emission Vessels

Pratt, Joseph W.; Minnehan, John J.

Batteries and hydrogen fuel cells provide zero emission power at the point of use. They are studied as an alternative powerplant for maritime vessels by considering 14 case studies of various ship sizes and routes varying from small passenger vessels to the largest cargo ships. The method used was to compare the mass and volume of the required zero emission solution to the available mass and volume on an existing vessel considering its current engine and fuel storage systems. The results show that it is practically feasible to consider these zero emission technologies for most vessels in the world's fleet. Hydrogen fuel cells proved to be the most capable while battery systems showed an advantage for high power, short duration missions. The results provide a guide to ship designers to determine the most suitable types of zero emission powerplants to fit a ship based on its size and energy requirements.

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TYPE SAND Report YEAR 2017
DOIOSTI

Emulation Platform for Cyber Analysis of Wireless Communication Network Protocols

Van Leeuwen, Brian P.; Eldridge, John M.

Wireless networking and mobile communications is increasing around the world and in all sectors of our lives. With increasing use, the density and complexity of the systems increase with more base stations and advanced protocols to enable higher data throughputs. The security of data transported over wireless networks must also evolve with the advances in technologies enabling more capable wireless networks. However, means for analysis of the effectiveness of security approaches and implementations used on wireless networks are lacking. More specifically a capability to analyze the lower-layer protocols (i.e., Link and Physical layers) is a major challenge. An analysis approach that incorporates protocol implementations without the need for RF emissions is necessary. In this research paper several emulation tools and custom extensions that enable an analysis platform to perform cyber security analysis of lower layer wireless networks is presented. A use case of a published exploit in the 802.11 (i.e., WiFi) protocol family is provided to demonstrate the effectiveness of the described emulation platform.

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TYPE SAND Report YEAR 2017
DOIOSTIDOIOSTI

Assessment of the Available Drawdowns for Oil Storage Caverns at the Bayou Choctaw SPR Site

Park, Byoung

The Department of Energy, in response to requests from the U.S. Congress, wishes to maintain an up-to-date table documenting the number of available full drawdowns of each of the caverns owned by the Strategic Petroleum Reserve. This information is important for assessing the SPR's ability to deliver oil to domestic oil companies expeditiously if national or world events dictate a rapid sale and deployment of the oil reserves. The evaluation of drawdown risks require the consideration of several factors regarding cavern and wellbore integrity and stability, including stress states caused by cavern geometry and operations, salt damage caused by dilatant and tensile stresses, the effect on enhanced creep on wellbore integrity, the sympathetic stress effect of operations on neighboring caverns. Based on the work over the past several years, a consensus has been built regarding the assessment of drawdown capabilities and risks for the SPR caverns. This report draws upon the recently Bayou Choctaw model upgrade and analyses to reevaluate and update the available drawdowns for each of those caverns. BC-18, 19, 101 and 102 are predicted to have conditional five available drawdowns remaining BC-15 and 17 have only one remaining drawdowns due to their proximity.

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TYPE SAND Report YEAR 2017
DOIOSTIDOIOSTI

CPHASE gate with Rydberg atoms (CPHAR)

Biedermann, Grant; Martin, Michael J.

We demonstrate a controlled phase gate approach to entangling neutral atoms using a tunable, Rydberg-dressed interaction. Previous approaches utilize a “dipole blockade” or a “spin-flip blockade” and thereby lack arbitrary phase control, and are less extensible to simultaneous entangling operations in many-atom systems. We systematically study major error mechanisms that limit the fidelity of the entangling interaction and find the dominant error mechanism to be phase noise in the coherent control of the single spins. Our work charts a definitive path to high fidelity entanglement using Rydberg-state-mediated interactions in neutral atoms.

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TYPE Other Report YEAR 2017
DOIOSTIDOIOSTI

Hardware Acceleration of Adaptive Neural Algorithms

James, Conrad D.

As tradit ional numerical computing has faced challenges, researchers have turned towards alternative computing approaches to reduce power - per - computation metrics and improve algorithm performance. Here, we describe an approach towards non - conventional computing that strengthens the connection between machine learning and neuroscience concepts. The Hardware Acceleration of Adaptive Neural Algorithms (HAANA) project ha s develop ed neural machine learning algorithms and hardware for applications in image processing and cybersecurity. While machine learning methods are effective at extracting relevant features from many types of data, the effectiveness of these algorithms degrades when subjected to real - world conditions. Our team has generated novel neural - inspired approa ches to improve the resiliency and adaptability of machine learning algorithms. In addition, we have also designed and fabricated hardware architectures and microelectronic devices specifically tuned towards the training and inference operations of neural - inspired algorithms. Finally, our multi - scale simulation framework allows us to assess the impact of microelectronic device properties on algorithm performance.

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TYPE SAND Report YEAR 2017
DOIOSTI

Fundamental Understanding of Methane-Carbon Dioxide-Water (CH4-CO2-H2O) Interactions in Shale Nanopores under Reservoir Conditions: Quarterly Report

Wang, Yifeng

Shale is characterized by the predominant presence of nanometer-scale (1-100 nm) pores. The behavior of fluids in those pores directly controls shale gas storage and release in shale matrix and ultimately the wellbore production in unconventional reservoirs. Recently, it has been recognized that a fluid confined in nanopores can behave dramatically differently from the corresponding bulk phase due to nanopore confinement (Wang, 2014). CO2 and H2O, either preexisting or introduced, are two major components that coexist with shale gas (predominately CH4) during hydrofracturing and gas extraction. Note that liquid or supercritical CO2 has been suggested as an alternative fluid for subsurface fracturing such that CO2 enhanced gas recovery can also serve as a CO2 sequestration process. Limited data indicate that CO2 may preferentially adsorb in nanopores (particularly those in kerogen) and therefore displace CH4 in shale. Similarly, the presence of water moisture seems able to displace or trap CH4 in shale matrix. Therefore, fundamental understanding of CH4-CO2-H2O behavior and their interactions in shale nanopores is of great importance for gas production and the related CO2 sequestration. This project focuses on the systematic study of CH4-CO2-H2O interactions in shale nanopores under high-pressure and high temperature reservoir conditions. The proposed work will help to develop new stimulation strategies to enable efficient resource recovery from fewer and less environmentally impactful wells.

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TYPE Other Report YEAR 2017
DOIOSTI

Fuel Cell Electric Vehicles: Drivers and Impacts of Adoption

Levinson, Rebecca S.; West, Todd H.; Manley, Dawn K.

We present scenario and parametric analyses of the US light duty vehicle (LDV) stock, sim- ulating the evolution of the stock in order to assess the potential role and impacts of fuel cell electric vehicles (FCEVs). The analysis probes the competition of FCEVs with other LDVs and the effects of FCEV adoption on LDV fuel use and emissions. We parameterize commodity and technology prices in order to explore the sensitivities of FCEV sales and emissions to oil, natural gas, battery technology, fuel cell technology, and hydrogen produc- tion prices. We additionally explore the effects of vehicle purchasing incentives for FCEVs, identifying potential impacts and tipping points. Our analyses lead to the following conclu- sions: (1) In the business as usual scenario, FCEVs comprise 7% of all new LDV sales by 2050. (2) FCEV adoption will not substantially impact green house gas emissions without either policy intervention, significant increases in natural gas prices, or technology improve- ments that motivate low carbon hydrogen production. (3) FCEV technology cost reductions have a much greater potential for impact on FCEV sales than hydrogen fuel cost reductions. (4) FCEV purchasing incentives must be both substantial and sustained in order to motivate lasting changes to FCEV adoption.

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TYPE SAND Report YEAR 2017
DOIOSTI

Exploiting Social Media Sensor Networks through Novel Data Fusion Techniques

Kouri, Tina; Pinar, Ali P.

Unprecedented amounts of data are continuously being generated by sensors (“hard” data) and by humans (“soft” data), and this data needs to be exploited to its full potential. The first step in exploiting this data is determine how the hard and soft data are related to each other. In this project we fuse hard and soft data, using the attributes of each (e.g., time and space), to gain more information about interesting events. Next, we attempt to use social networking textual data to predict the present (i.e., predict that an interesting event is occurring and details about the event) using data mining, machine learning, natural language processing, and text analysis techniques.

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TYPE SAND Report YEAR 2017
DOIOSTI
Results 34401–34600 of 101,000
Results 34401–34600 of 101,000
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