The Internet has changed the world in ways hitherto unknown. The international financial system, air, land and maritime transport systems are all digitally linked. Similarly most militaries are fully or partially networked. This has not only sped up the decision making processes at all levels, it has also rendered these systems vulnerable to cyber-attacks. Cyber-warfare is now recognized as the most potent form of non-kinetic war fighting. In order to prevent large scale network-attacks, cyber-powers are simultaneously spending a lot of time, money and effort to erect redundant cyber-defenses and enhancing their offensive cyber capabilities. Difficulties in creating a stable environment in information-space stem from differing national perceptions regarding the freedom of the Internet, application of international law and problems associated with attribution. This paper discusses a range of Confidence Building Measures that can be created between India and Pakistan in information-space to control malicious cyber behavior and avert an inadvertent war.
The development of advanced thermal barrier coatings (TBCs) of yttria stabilized zirconia (YSZ) that exhibit lower thermal conductivity through better control of electron beam - physical vapor deposition (EB-PVD) processing is of prime interest to both the aerospace and power industries. This report summarizes the work performed under a two-year Lab-Directed Research and Development (LDRD) project (38664) to produce lower thermal conductivity, graded-layer thermal barrier coatings for turbine blades in an effort to increase the efficiency of high temperature gas turbines. This project was sponsored by the Nuclear Fuel Cycle Investment Area. Therefore, particular importance was given to the processing of the large blades required for industrial gas turbines proposed for use in the Brayton cycle of nuclear plants powered by high temperature gas-cooled reactors (HTGRs). During this modest (~1 full-time equivalent (FTE)) project, the processing technology was developed to create graded TBCs by coupling ion beam-assisted deposition (IBAD) with substrate pivoting in the alumina-YSZ system. The Electron Beam - 1200 kW (EB-1200) PVD system was used to deposit a variety of TBC coatings with micron layered microstructures and reduced thermal conductivity below 1.5 W/m.K. The use of IBAD produced fully stoichiometric coatings at a reduced substrate temperature of 600°C and a reduced oxygen background pressure of 0.1 Pa. IBAD was also used to successfully demonstrate the transitioning of amorphous PVD-deposited alumina to the -phase alumina required as an oxygen diffusion barrier and for good adhesion to the substrate Ni2Al3 bondcoat. This process replaces the time consuming thermally grown oxide formation required before the YSZ deposition. In addition to the process technology, Direct Simulation Monte Carlo plume modeling and spectroscopic characterization of the PVD plumes were performed. The project consisted of five tasks. These included the production of layered periodic microstructures in the coating, the Direct Simulation Monte Carlo (DSMC) modeling of particle transport in the PVD plume, functional graded layer development, the deposition of all layers to form a complete coating, and materials characterization including thermal testing. Ion beam-assisted deposition, beam sharing through advanced digital rastering, substrate pivoting, hearth calorimetry, infrared imaging, fiber optic-enabled optical emission spectroscopy and careful thermal management were used to achieve all the milestones outlined in the FY02 LDRD proposal.
The impact of recent changes to the ASTM Standard E722 is investigated. The methodological changes in the production of the displacement kerma factors for silicon has significant impact for some energy regions of the 1-MeV(Si) equivalent fluence response function. When evaluating the integral over all neutrons energies in various spectra important to the SNL electronics testing community, the change in the response results in an increase in the total 1-MeV(Si) equivalent fluence of 2 7%. Response functions have been produced and are available for users of both the NuGET and MCNP codes.
Sandia National Laboratories, New Mexico (SNL/NM) is a government-owned/contractoroperated laboratory. Sandia Corporation (Sandia), a wholly owned subsidiary of Lockheed Martin Corporation, manages and operates SNL/NM for the U.S. Department of Energy (DOE), National Nuclear Security Administration (NNSA). The DOE/NNSA Sandia Field Office administers the contract and oversees contractor operations at the site. Sandia conducts two types of groundwater surveillance monitoring at SNL/NM: (1) on a site-wide basis as part of the SNL/NM Long-Term Stewardship (LTS) Program’s Groundwater Monitoring Program (GMP) Groundwater Surveillance Task and (2) as site-specific groundwater monitoring at LTS/Environmental Restoration (ER) Operations sites with ongoing groundwater investigations. This Annual Groundwater Monitoring Report documents the results of the groundwater monitoring activities at SNL/NM for Calendar Year (CY) 2013. This report has been prepared to meet the environmental reporting requirements for the CY 2013 Annual Site Environmental Report, providing an annual update of groundwater data to regulators, stakeholders, and outside agencies. In addition, it serves as a valuable tool to inform the public about the groundwater quality at SNL/NM. This report includes both water quality sampling results and water level measurements.
A state-of-the-art, grid-convergent simulation methodology was applied to three-dimensional calculations of a single-cylinder optical engine. A mesh resolution study on a sector-based version of the engine geometry further verified the RANS-based cell size recommendations previously presented by Senecal et al. (“Grid Convergent Spray Models for Internal Combustion Engine CFD Simulations,” ASME Paper No. ICEF2012-92043). Convergence of cylinder pressure, flame lift-off length, and emissions was achieved for an adaptive mesh refinement cell size of 0.35 mm. Furthermore, full geometry simulations, using mesh settings derived from the grid convergence study, resulted in excellent agreement with measurements of cylinder pressure, heat release rate, and NOx emissions. On the other hand, the full geometry simulations indicated that the flame lift-off length is not converged at 0.35 mm for jets not aligned with the computational mesh. Further simulations suggested that the flame lift-off lengths for both the nonaligned and aligned jets appear to be converged at 0.175 mm. With this increased mesh resolution, both the trends and magnitudes in flame lift-off length were well predicted with the current simulation methodology. Good agreement between the overall predicted flame behavior and the available chemiluminescence measurements was also achieved. Our present study indicates that cell size requirements for accurate prediction of full geometry flame lift-off lengths may be stricter than those for global combustion behavior. This may be important when accurate soot predictions are required.
The research we present in this article focuses on a 9-m CX-100 wind turbine blade, designed by a team led by Sandia National Laboratories and manufactured by TPI Composites Inc. The key difference between the 9-m blade and baseline CX-100 blades is that this blade contains fabric wave defects of controlled geometry inserted at specified locations along the blade length. The defect blade was tested at the National Wind Technology Center at the National Renewable Energy Laboratory using a schedule of cycles at increasing load level until failure was detected. Our researchers used digital image correlation, shearography, acoustic emission, fiber-optic strain sensing, thermal imaging, and piezoelectric sensing as structural health monitoring techniques. Furthermore, this article provides a comparison of the sensing results of these different structural health monitoring approaches to detect the defects and track the resultant damage from the initial fatigue cycle to final failure.
Metal organic frameworks (MOF) are a recently discovered class of nanoporous, defect-free crystalline materials that enable rational design and exploration of porous materials at the molecular level. MOFs have tunable monolithic pore sizes and cavity environments due to their crystalline nature, yielding properties exceeding those of most other porous materials. These include: the lowest known density (91% free space); highest surface area; tunable photoluminescence; selective molecular adsorption; and methane sorption rivaling gas cylinders. These properties are achieved by coupling inorganic metal complexes such as ZnO4 with tunable organic ligands that serve as struts, allowing facile manipulation of pore size and surface area through reactant selection. MOFs thus provide a discovery platform for generating both new understanding of chemistry in confined spaces and novel sensors and devices based on their unique properties. At the outset of this project in FY06, virtually nothing was known about how to couple MOFs to substrates and the science of MOF properties and how to tune them was in its infancy. An integrated approach was needed to establish the required knowledge base for nanoscale design and develop methodologies integrate MOFs with other materials. This report summarizes the key accomplishments of this project, which include creation of a new class of radiation detection materials based on MOFs, luminescent MOFs for chemical detection, use of MOFs as templates to create nanoparticles of hydrogen storage materials, MOF coatings for stress-based chemical detection using microcantilevers, and "flexible" force fields that account for structural changes in MOFs that occur upon molecular adsorption/desorption. Eight journal articles, twenty presentations at scientific conferences, and two patent applications resulted from the work. The project created a basis for continuing development of MOFs for many Sandia applications and succeeded in securing $\$$2.75 M in funding from outside agencies to continue the research.
Exascale data environments are fast approaching, driven by diverse structured and unstructured data such as system and application telemetry streams, open-source information capture, and on-demand simulation output. Storage costs having plummeted, the question is now one of converting vast stores of data to actionable information. Complicating this problem are the low degrees of awareness across domain boundaries about what potentially useful data may exist, and write-once-read- never issues (data generation/collection rates outpacing data analysis and integration rates). Increasingly, technologists and researchers need to correlate previously unrelated data sources and artifacts to produce fused data views for domain-specific purposes. New tools and approaches for creating such views from vast amounts of data are vitally important to maintaining research and operational momentum. We propose to research and develop tools and services to assist in the creation, refinement, discovery and reuse of fused data views over large, diverse collections of heterogeneously structured data. We innovate in the following ways. First, we enable and encourage end-users to introduce customized index methods selected for local benefit rather than for global interaction (flexible multi-indexing). We envision rich combinations of such views on application data: views that span backing stores with different semantics, that introduce analytic methods of indexing, and that define multiple views on individual data items. We specifically decline to build a big fused database of everything providing a centralized index over all data, or to export a rigid schema to all comers as in federated query approaches. Second, we proactively advertise these application-specific views so that they may be programmatically reused and extended (data proactivity). Through this mechanism, both changes in state (new data in existing view collected) and changes in structure (new or derived view exists) are made known. Lastly, we embrace found data heterogeneity by coupling multi-indexing to backing stores with appropriate semantics (as opposed to a single store or schema).
A hybrid fs/ps pure-rotational coherent anti-Stokes Raman scattering (CARS) scheme is systematically evaluated over a wide range of flame conditions in the product gases of two canonical flat-flame burners. Near-transform-limited, broadband femtosecond pump and Stokes pulses impulsively prepare a rotational Raman coherence, which is later probed using a high-energy, frequency-narrow picosecond beam generated by the second-harmonic bandwidth compression scheme that has recently been demonstrated for rotational CARS generation in H2/air flat flames. The measured spectra are free of collision effects and nonresonant background and can be obtained on a single-shot basis at 1kHz. The technique is evaluated for temperature/oxygen measurements in near-adiabatic H2/air flames stabilized on the Hencken burner for equivalence ratios of ϕ=0.20-1.20. Thermometry is demonstrated in hydrocarbon/air products for ϕ=0.75-3.14 in premixed C2H4/air flat flames on the McKenna burner. Reliable spectral fitting is demonstrated for both shot-averaged and single-laser-shot data using a simple phenomenological model. Measurement accuracy is benchmarked by comparison to adiabatic-equilibrium calculations for the H2/air flames, and by comparison with nanosecond CARS measurements for the C2H4/air flames. Quantitative accuracy comparable to nanosecond rotational CARS measurements is observed, while the observed precision in both the temperature and oxygen data is extraordinarily high, exceeding nanosecond CARS, and on par with the best published thermometric precision by femtosecond vibrational CARS in flames, and rotational femtosecond CARS at low temperature. Threshold levels of signal-to-noise ratio to achieve 1-2% precision in temperature and O2/N2 ratio are identified. The results show that pure-rotational fs/ps CARS is a robust and quantitative tool when applied across a wide range of flame conditions spanning lean H2/air combustion to fuel-rich sooting hydrocarbon flames.
The objective of this project was to characterize the performance and chemistry of a siliconebased replicating compound. Some silicone replicating compounds are useful for critical inspection of surface features. Common applications are for examining micro-cracks, surface pitting, scratching, and other surface defects. Materials characterization techniques were used: FTIR, XPS, ToF-SIMS, AFM, and Confocal Microscopy to evaluate the replicating compound. These techniques allowed for the characterization and verification of the resolution capabilities and surface contamination that may be a result of using the compound. FTIR showed the compound is entirely made from silicone constituents. The AFM and Confocal Microscopy results showed the compound does accurately replicate the surface features to the claimed resolution. XPS and ToF-SIMS showed there is a silicone contaminant layer left behind when a cured replica is peeled off a surface. Attempts to clean off the contamination could not completely remove all silicone residues.
For synthetic aperture radar image products interference can degrade the quality of the images while techniques to mitigate the interference also reduce the image quality. Usually the radar system designer will try to balance the amount of mitigation for the amount of interference to optimize the image quality. This may work well for many situations, but coherent data products derived from the image products are more sensitive than the human eye to distortions caused by interference and mitigation of interference. This dissertation examines the e ect that interference and mitigation of interference has upon coherent data products. An improvement to the standard notch mitigation is introduced, called the equalization notch. Other methods are suggested to mitigation interference while improving the quality of coherent data products over existing methods.
The purpose of this study is to characterize the technical performance of the PNM Prosperity electricity storage project, and to identify lessons learned that can be used to improve similar projects in the future. The PNM Prosperity electricity storage project consists of a 500 kW/350 kWh advanced lead-acid battery with integrated supercapacitor (for energy smoothing) and a 250 kW/1 MWh advanced lead-acid battery (for energy shifting), and is co-located with a 500 kW solar photovoltaic (PV) resource. The project received American Reinvestment and Recovery Act (ARRA) funding. The smoothing system is e ective in smoothing intermittent PV output. The shifting system exhibits good round-trip efficiencies, though the AC-to-AC annual average efficiency is lower than one might hope. Given the current utilization of the smoothing system, there is an opportunity to incorporate additional control algorithms in order to increase the value of the energy storage system.
A reduction in cost of energy from wind is anticipated when maximum allowable tip velocity is allowed to increase. Rotor torque decreases as tip velocity increases and rotor size and power rating are held constant. Reduction in rotor torque yields a lighter weight gearbox, a decrease in the turbine cost, and an increase in the capacity for the turbine to deliver cost competitive electricity. The high speed rotor incurs costs attributable to rotor aero-acoustics and system loads. The increased loads of high speed rotors drive the sizing and cost of other components in the system. Rotor, drivetrain, and tower designs at 80 m/s maximum tip velocity and 100 m/s maximum tip velocity are created to quantify these effects. Component costs, annualized energy production, and cost of energy are computed for each design to quantify the change in overall cost of energy resulting from the increase in turbine tip velocity. High fidelity physics based models rather than cost and scaling models are used to perform the work. Results provide a quantitative assessment of anticipated costs and benefits for high speed rotors. Finally, important lessons regarding full system optimization of wind turbines are documented.
Isotope identification algorithms that are contained in the Gamma Detector Response and Analysis Software (GADRAS) can be used for real-time stationary measurement and search applications on platforms operating under Linux or Android operating sys-tems. Since the background radiation can vary considerably due to variations in natu-rally-occurring radioactive materials (NORM), spectral algorithms can be substantial-ly more sensitive to threat materials than search algorithms based strictly on count rate. Specific isotopes or interest can be designated for the search algorithm, which permits suppression of alarms for non-threatening sources, such as such as medical radionuclides. The same isotope identification algorithms that are used for search ap-plications can also be used to process static measurements. The isotope identification algorithms follow the same protocols as those used by the Windows version of GADRAS, so files that are created under the Windows interface can be copied direct-ly to processors on fielded sensors. The analysis algorithms contain provisions for gain adjustment and energy lineariza-tion, which enables direct processing of spectra as they are recorded by multichannel analyzers. Gain compensation is performed by utilizing photopeaks in background spectra. Incorporation of this energy calibration tasks into the analysis algorithm also eliminates one of the more difficult challenges associated with development of radia-tion detection equipment.
This report demonstrates versatile and practical model validation and uncertainty quantification techniques applied to the accuracy assessment of a computational model of heated steel pipes pressurized to failure. The Real Space validation methodology segregates aleatory and epistemic uncertainties to form straightforward model validation metrics especially suited for assessing models to be used in the analysis of performance and safety margins. The methodology handles difficulties associated with representing and propagating interval and/or probabilistic uncertainties from multiple correlated and uncorrelated sources in the experiments and simulations including: material variability characterized by non-parametric random functions (discrete temperature dependent stress-strain curves); very limited (sparse) experimental data at the coupon testing level for material characterization and at the pipe-test validation level; boundary condition reconstruction uncertainties from spatially sparse sensor data; normalization of pipe experimental responses for measured input-condition differences among tests and for random and systematic uncertainties in measurement/processing/inference of experimental inputs and outputs; numerical solution uncertainty from model discretization and solver effects.
