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Presentation to be given at the FY 2020 SDRD Annual Meeting, to be held Sept. 23-24, on WebEx. Dual Comb Spectroscopy for Definitive Identification of Gas at Speeds Faster than Turbulence Effects, STL-006-19, Year 2
Earthquake Early Warning (EEW) systems depend on the dense seismic network to make fast and accurate earthquake detections to issue useful early alerts. The recent development and implementation of the ShakeAlert system is relying on the west coast seismic network to detect and estimate the earthquake parameters in real-time. While working on making improvements on the current system, one potential approach is to include more seismic recordings from various sources, such as the low-cost smartphone seismic network, such as the MyShake network, or the Google Android smartphones, since these smartphone seismic networks have much more portable stations (phones) to potentially provide useful data to the system. This report summarizes the initial exploration of using a deep learning approach to combine the data from both traditional seismic stations and the smartphone data in California. Due to the heterogeneity nature of the data, we aggregate data from the phones (using simulation data), as well as that from traditional seismic stations to grid cells. By generating real-time triggering ratio grid cell maps, the designed deep learning algorithm can process the data from multiple sources and detect the earthquake faster than only using that from a traditional seismic network.
The US electric grid is facing operational, stability, and security challenges. Transmission system operators need some measure of visibility into distribution system renewable generation. Distribution system generation needs to support transmission system voltage. The grid is experiencing an expansion in measurement systems. How to take full advantage of this expansion and defend against attacks, both cyber and physical, poses additional challenges. The Faster-than-real-time Simulation with demonstration for Resilient DER Integration project set out to do the following: a. Flatten the voltage profile through the feeders and system for cost saving and voltage stabilization needs. b. Increase the amount of intermittent distributed energy resources (IDERs) that could be deployed on a utility feeder and provide 100% or more energy needed for the demands on that feeder, and c. based on an accurate model (Digital Twin) of the utilities system, be able to detect any abnormalities on the utilities distribution system. To manage the voltage and increase IDER penetration (a,b), Graph Trace Analysis is employed in a time-series, optimal power flow to coordinate the time-varying feedback control setpoints of a distribution feeder’s utility control devices. Under the coordinated control are a Load Tap Changing Transformer, a voltage regulator, and five switched capacitor banks. The feeder serves over 2000 customers, the feeder secondaries are modeled, and the feeder has 2.3 MW of PV generation, corresponding to a 17.4% penetration of PV generation. The feeder model has over 12,000 components, where every customer load bus and PV generator are modeled. The accuracy of the power flow solution is compared against historical meter voltage measurements, the improvement in conservation voltage reduction energy savings as a function of the coordinated control desired voltage profile is investigated, and the increase in PV penetration of the coordinated control over the existing control is presented. To achieve improved control performance while observing system operation constraints, bellwether Advanced Metering Infrastructure (AMI) voltage measurements are used to adjust the desired voltage profile used by the optimal power flow analysis. To detect and alleviate or negate attacks or failures on the distribution and transmission utility grids (c) the grid needs to be resilient and self-healing. In this project software was designed to do just that. At the center of the software is an Integrated System Model (ISM) that spans from transmission to secondary distribution. The ISM is employed in real-time abnormality detection, voltage stability forecasting, and multi-mode control. Testing results are presented for: 1—attacks on utility infrastructure; 2—energy savings from optimal control; 3—distribution system control response during a low voltage transmission system event; 4—cyber-attacks on PV inverters, where physical inverters are used in hard-ware-in-the-simulation-loop studies. Contributions of this work include real-time analysis that spans from three-phase transmission through secondary distribution; an approach for detecting abnormalities that employs measurements from three independent measurement systems; and a multi-mode distribution system control that responds to cyber-attacks, physical attacks, equipment failures, and transmission system needs.
Managing a large portfolio of buildings involves decisions on reuse, retrofit, renovation, rehabilitation, and new construction, influenced by trade-offs between performance metrics such as cost, time, and operational flexibility over the building's life cycle. Traditional life cycle assessment tools for evaluating these metrics can be labor- and compute-intensive, requiring extensive data and modeling for each building. Metamodels (or surrogate models) using machine learning have been explored as faster alternatives, but training these models has been hindered by the limited availability of comprehensive data on key life cycle metrics. Recent advancements in machine learning, particularly deep learning techniques like zero-shot and few-shot learning, allow models to learn from sparse or limited data. We propose a machine learning-based metamodel that leverages these techniques for rapid estimation of key building life cycle metrics. This presentation will cover the model architecture, data collection, training, and validation processes, along with an ongoing case study applied to a large portfolio of buildings. We will discuss the model's performance in terms of accuracy, compute time, limitations, and its potential for expanding to additional life cycle metrics. This data-driven approach offers a promising direction for the rapid evaluation of large building portfolios.
Similarity solution for turbulent mixing between jet and faster moving coaxial stream
FASTER code for significantly reducing ducted reactor shield computation time for neutron number spectrum
FASTER computer program modified for tracking neutrons through reactor slabs penetrated by helical voided ducts
Searching for uncharged particles with spacelike four momentum traveling faster than light
The theory used in FASTER-III, a Monte Carlo computer program for the transport of neutrons and gamma rays in complex geometries, is outlined. The program includes the treatment of geometric regions bounded by quadratic and quadric surfaces with multiple radiation sources which have specified space, angle, and energy dependence. The program calculates, using importance sampling, the resulting number and energy fluxes at specified point, surface, and volume detectors. It can also calculate minimum weight shield configuration meeting a specified dose rate constraint. Results are presented for sample problems involving primary neutron, and primary and secondary photon, transport in a spherical reactor shield configuration.
A description of the FASTER-III program for Monte Carlo Carlo calculation of photon and neutron transport in complex geometries is presented. Major revisions include the capability of calculating minimum weight shield configurations for primary and secondary radiation and optimal importance sampling parameters. The program description includes a users manual describing the preparation of input data cards, the printout from a sample problem including the data card images, definitions of Fortran variables, the program logic, and the control cards required to run on the IBM 7094, IBM 360, UNIVAC 1108 and CDC 6600 computers.
Vacuum-assisted immersion test is much faster than conventional atmospheric immersion tests of cable seals. Vacuum speeds removal of air, allowing its replacement by conductive salt solution in leaking specimens. Previously, 24-hour immersion was necessary to assure displacement of trapped air. Improved method takes only 10 minutes.
Most simulation plots are heavily oversampled. Ignoring unnecessary data points dramatically reduces plot time with imperceptible effect on quality. The technique is suited to most plot devices. The departments laser printer's speed was tripled for large simulation plots by data thinning. This reduced printer delays without the expense of a faster laser printer. Surpisingly, it saved computer time as well. All plot data are now thinned, including PostScript and terminal plots. The problem, solution, and conclusions are described. The thinning algorithm is described and performance studies are presented. To obtain FORTRAN 77 or C source listings, mail a SASE to the author.
Improved algorithm yields faster numerical solutions of Navier-Stokes equations of steady or unsteady three-dimensional flow of incompressible fluid. In artificial-compressibility method, unsteady flow treated as incompressible in advancing from one time step to next, but at each time step (or in steady state), fluid treated as having variable compressibility enabling propagation of flow field, and subiterations performed in increments of pseudotime until effects of compressibility subside. Directly couples pressure and velocity fields at same time step and converts elliptic incompressible Navier-Stokes equations to hyperbolic form more amenable to numerical integration.
The NIR versus red 'infrared percentage vegetation index', NIR/(NIR + Red), is functionally and linearly equivalent to the normalized difference vegetation index, (NIR-Red)/(NIR + Red). Advantageously, it is both computationally faster and never negative.
Current-measuring circuit operates on Hall-effect-sensing and magnetic-field-nulling principles similar to those described in article, "Nulling Hall-Effect Current-Measuring Circuit" (LEW-15023), but simpler and responds faster. Designed without feedback loop, and analog pulse-width-modulated output indicates measured current. Circuit measures current at frequency higher than bandwidth of its Hall-effect sensor.
In faster, easier technique, material in weld zone fictitiously softened to negligibly low modulus of elasticity, and material considered deformed to specified offset. Displacements caused by deformation computed by analysis of static stresses and strains in fictitiously deformed material, using specified offset as displacement boundary condition. Resulting displacements added to coordinates of corresponding nodes of original (nonoffset) mathematical model of welded part. Technique used to modify large finite-element mathematical model to any desired weld offset configuration in short time.
In order to be consistent with current physical theories, any proposal of a faster-than light (FTL) transportation system must satisfy several critical conditions. It must predict the mass, space, and time dimensional changes predicted by relativity physics when velocity falls below the speed of light. It must also not violate causality, and remain consistent with quantum physics in the limit of microscopic systems. It is also essential that the proposal conserve energy.
Solar energy at the top of the atmosphere (solar constant), rotation rate, and carbon dioxide (CO2) may have varied significantly over Earth's history, especially during the earliest times. The sensitivity of a general circulation model to faster rotation, enhanced CO2 concentration, and reduced solar constant is presented. The control simulation of this study has a solar constant reduced by 10% the present amount, zero land fraction using a swamp ocean surface, CO2 concentrations of 330 ppmv, present-day rotation rate, and is integrated under mean diurnal and seasonal solar forcing. Four sensitivity test are performed under zero land fraction and reduced solar constant conditions by varying the earth's rotation rate atmospheric CO2 concentration and solar constant. The global mean sea surface temperatures (SSTs) compared to the control simulation: were 6.6 K to 12 K higher than the control's global mean temperature of 264.7 K. Sea ice is confined to higher latitudes in each experiment compared to the control, with ice-free areas equatorward of the subtropics. The warm SSTs are associated with a 20% reduction in clouds for the rotation rate experiments and higher CO2 concentrations in the other experiments. These results are in contrast to previous studies that have used energy balance and radiative convective models. Previous studies required a much larger atmospheric CO2 increase to prevent an ice-covered Earth. The results of the study, suggest that because of its possible feedback with clouds, the general circulation of the atmosphere should be taken into account in understanding the climate of early Earth. While higher CO2 concentrations are likely in view of the results, very large atmospheric CO2 concentrations may not be necessary to counterbalance the lower solar constant that existed early in Earth's history.