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At least 865 records · Page 48

Event generator tuning using Bayesian optimization

Monte Carlo event generators contain a large number of parameters that must be determined by comparing the output of the generator with experimental data. Generating enough events with a fixed set of parameter values to enable making such a comparison is extremely CPU intensive, which prohibits performing a simple brute-force grid-based tuning of the parameters. Bayesian optimization is a powerful method designed for such black-box tuning applications. In this article, we show that Monte Carlo event generator parameters can be accurately obtained using Bayesian optimization and minimal expert-level physics knowledge. A tune of the PYTHIA 8 event generator using $e^+e^-$ events, where 20 parameters are optimized, can be run on a modern laptop in just two days. Combining the Bayesian optimization approach with expert knowledge should enable producing better tunes in the future, by making it faster and easier to study discrepancies between Monte Carlo and experimental data.

47 OTHER INSTRUMENTATION↗

Ordering Unstructured Meshes for Sparse Matrix Computations on Leading Parallel Systems

The ability of computers to solve hitherto intractable problems and simulate complex processes using mathematical models makes them an indispensable part of modern science and engineering. Computer simulations of large-scale realistic applications usually require solving a set of non-linear partial differential equations (PDES) over a finite region. For example, one thrust area in the DOE Grand Challenge projects is to design future accelerators such as the SpaHation Neutron Source (SNS). Our colleagues at SLAC need to model complex RFQ cavities with large aspect ratios. Unstructured grids are currently used to resolve the small features in a large computational domain; dynamic mesh adaptation will be added in the future for additional efficiency. The PDEs for electromagnetics are discretized by the FEM method, which leads to a generalized eigenvalue problem Kx = AMx, where K and M are the stiffness and mass matrices, and are very sparse. In a typical cavity model, the number of degrees of freedom is about one million. For such large eigenproblems, direct solution techniques quickly reach the memory limits. Instead, the most widely-used methods are Krylov subspace methods, such as Lanczos or Jacobi-Davidson. In all the Krylov-based algorithms, sparse matrix-vector multiplication (SPMV) must be performed repeatedly. Therefore, the efficiency of SPMV usually determines the eigensolver speed. SPMV is also one of the most heavily used kernels in large-scale numerical simulations.

Oliker, Leonid↗

Use Of EOS-AURA Observation In The MERRA-2 Reanalysis

Meteorological reanalyses provide multi-year gridded datasets that describe the evolution of the atmosphere. Such products use a data assimilation system, comprising of an atmospheric model, a broad suite of observations, and an analysis system that optimally combines the model forecast with the observations, using an algorithm that includes information about model and data accuracy. The mixture of observations is of central importance to the quality of the assimilated datasets. The Modern-era Retrospective Analysis for Research and Applications (MERRA) included constraints on the thermal structure of the middle atmosphere from nadir sounders on the NOAA polar-orbiting platforms (Stratospheric Sounding Units and Advanced Microwave Sounding Units). These instruments have peak sensitivities that occur well below the stratopause. As such, the radiance measurements do not provide strong constraints on stratopause temperature. The new MERRA-2 reanalysis is using EOS-MLS temperature retrievals after they are available: it will be demonstrated that these data lead to a more realistic stratopause structure in MERRA-2 than in MERRA. Similarly, the work demonstrates the improvements in lower stratospheric ozone in MERRA-2 than in MERRA, for the period when EOS-MLS ozone data are assimilated. This improvement occurs because of the ozone profile information offered by MLS in the low stratosphere, in contrast to the SBUV/2 data used for the rest of MERRA-2. The impacts of choosing to use the EOS-MLS datasets are discussed in context of the continuity of the data record in MERRA- 2.

Meteorological↗

Impact of system parameters and geospatial variables on the reliability of residential systems with PV and energy storage

A reliable power supply is the foundation of modern society, enabling technologies used to function within a society. Residential systems are places where the end users directly consume power, enabling technologies to sustain life. With the emergence of behind-the-meter resources, the end-users have some control over power supply reliability. The intermittency and variability of these resources impact residential system reliability. In this work, we study the reliability performance of a grid-supplemented residential system with behind-the-meter Distributed Energy Resources(DER) subject to various system parameters and geospatial variables. We propose a multistate reliability model for the behind-the-meter microinverter-based Photo Voltaic (PV) system and integrated inverter-based energy storage (ES) system. A sequential Monte Carlo method is then presented to evaluate the reliability indices for the residential system with behind-the-meter DERs as the main supply and the grid as the backup. The sequential Monte Carlo method is used to analyze the reliability performance of the residential model at the top 100 populous counties of the United States, where actual load and solar irradiance data at the counties is used. In the analysis, the sensitivity of indices to system parameters such as DER size and the sensitivity of the indices to climate zone and gross horizontal irradiation (GHI), which affects the load conditions and the PV output of the residential system, is performed. The analysis results show that the system parameters and the geospatial variables significantly impact the residential system’s reliability. The insights from this analysis will be of immense value to the distribution system planners to provide zone-specific guidelines for DER system sizing and toward the evolution of utility business models. Finally, the methodology developed can be used to extend the analysis to other locations.

14 SOLAR ENERGY↗

Investigating the Impact of Wind Turbines on Distribution System Stability

Modern wind turbines utilize power electronic converters to regulate their output and optimize their performance. Their impact on the distribution system is not as well understood as for transmission system. The novelty of this work is in studying the impact of wind turbines given its proximity to faults or severe voltage events, and the influence on system stability given its location relative to the substation (representing the conventional grid). This paper presents the frequency and voltage swing plots for various study scenarios. The responses are analyzed two fold - Steady state operation, and performance given a fault or voltage events occurs in the system. The findings are presented, with crucial differences from transmission systems highlighted.

17 WIND ENERGY↗

Liquid Annular Seal CFD Analysis for Rotordynamic Force Prediction

A commercially available code is utilized to analyze a plain and grooved liquid annular seal. These type seals are commonly used in modern turbopumps and have a pronounced effect on the rotordynamic behavior of these systems. Accurate prediction of both leakage and dynamic reaction forces is vital to ensure good performance and sound mechanical operation. The code SCISEAL developed by CFDRC is a generic 3-D, finite volume based CFD code solving the 3-D Reynolds averaged Navier Stokes equations. The code allows body-fitted, multi-blocked structured grids, turbulence modeling, rotating coordinate frames, as well as integration of dynamic pressure and shear forces on the rotating journal. The code may be used with the commercially available pre-and post-processing codes from CFDRC as well.

Moore, Jeff↗

Performance Assessment of Pakistani Central Receiver Plant Case Study Using Aimpoint Strategy Optimization Tools

Pakistan has a high potential for both photovoltaic and Concentrated Solar Power (CSP) deployment to meet its energy requirements. Previous feasibility studies have shown that a variety of CSP technologies are both technically and economically viable in the Pakistani climate and can significantly mitigate the country's current lack of grid reliability. This work aims to enhance the performance of a previously designed Central Receiver System (CRS) plant for Pakistan using state-of-the-art aimpoint optimization methods. Results from our case study show that optimized aiming strategies have increased practicality due to their adherence to flux limitations on the receiver, and offer ~2.4% more thermal energy delivered to the receiver for the Pakistani case study compared to modern performance characterization software, translating to up to 149 additional hours of nameplate-capacity production to address the shortfall in an electricity-starved market.

central receiver system↗

Generation and Use of Thermal Energy in the U.S. Industrial Sector and Opportunities to Reduce its Carbon Emissions

The industrial sector was the third-largest source of direct U.S. greenhouse gas (GHG) emissions in 2014 behind electricity generation and transportation and accounted for roughly 20% of total emissions (EPA 2016). The Energy Information Administration (EIA) projects that total U.S. energy consumption will grow to about 108 exajoules (1 EJ = 10 18 J) or 102 quads (1 quad = 10 15 British thermal units) in 2025, with nearly all of the growth coming from the industrial sector (DOE 2015b). Energy consumption in the industrial sector is forecast to increase to 39.5 EJ (37.4 quads)—a 22% increase, exceeding 36% of total energy consumption in the United States. Therefore, it is imperative that industrial GHG emissions be considered in any strategy intent on achieving deep decarbonization of the energy sector as a whole. It is important to note that unlike the transportation sector and electrical grid, energy use by industry often involves direct conversion of primary energy sources to thermal and electrical energy at the point of consumption. About 52% of U.S. industrial direct GHG emissions are the result of fuel combustion (EPA 2016) to produce hot gases and steam for process heating, process reactions, and process evaporation, concentration, and drying. The heterogeneity and variations in scale of U.S. industry and the complexity of modern industrial firms’ global supply chains are among the sector’s unique challenges to minimizing its GHG emissions. A combination of varied strategies—such as energy efficiency, material efficiency, and switching to low-carbon fuels—can help reduce absolute industrial GHG emissions. This report provides a complement to process-efficiency improvement to consider how clean energy delivery and use by industry could reduce GHG emissions. Specifically, it considers the possibility of replacing fossil-fuel combustion in industry with nuclear (specifically small modular reactors [SMRs]), solar thermal (referred to herein as solar industrial process heat [SIPH]), and geothermal energy sources. The possibility of applying electrical heating and greater use of hydrogen is also considered, although these opportunities are not discussed in as much detail.

08 HYDROGEN↗

Frequency domain identification for robust large space structure control design

A methodology is demonstrated for frequency domain identification of large space structures which systematically transforms experimental raw data into a form required for synthesizing H(infinity) controllers using modern robust control design software (e.g., Matlab Toolboxes). A unique feature of this approach is that the additive uncertainty is characterized to a specified statistic confidence rather than with hard bounds. In this study, the difference in robust performance is minimal between the two levels of confidence. In general cases, the present methodology provides a tool for performance/confidence level tradeoff studies. For simplicity, the additive uncertainty on a frequency grid is considered and the interpolation error in between grid points is neglected.

Yam, Y.↗

Three-Dimensional Nacelle Aeroacoustics Code With Application to Impedance Education

A three-dimensional nacelle acoustics code that accounts for uniform mean flow and variable surface impedance liners is developed. The code is linked to a commercial version of the NASA-developed General Purpose Solver (for solution of linear systems of equations) in order to obtain the capability to study high frequency waves that may require millions of grid points for resolution. Detailed, single-processor statistics for the performance of the solver in rigid and soft-wall ducts are presented. Over the range of frequencies of current interest in nacelle liner research, noise attenuation levels predicted from the code were in excellent agreement with those predicted from mode theory. The equation solver is memory efficient, requiring only a small fraction of the memory available on modern computers. As an application, the code is combined with an optimization algorithm and used to reduce the impedance spectrum of a ceramic liner. The primary problem with using the code to perform optimization studies at frequencies above I1kHz is the excessive CPU time (a major portion of which is matrix assembly). The research recommends that research be directed toward development of a rapid sparse assembler and exploitation of the multiprocessor capability of the solver to further reduce CPU time.

Watson, Willie R.↗

Change in Brooklyn and Queens: How New York?s Reforming the Energy Vision Program and Con Edison Are Reshaping Electric Distribution Planning

The New York City boroughs of Brooklyn and Queens are undergoing a period of gentrification, infrastructure rebuilding, new construction, and load growth not experienced in decades. Significant numbers of residents are moving in, and structures that had been abandoned or were in disrepair are being refurbished and modernized to accommodate the burgeoning population. Homes, businesses, and industries are reviving areas long in decline, and Brooklyn's growth has made it the nation's fourth most populous city, according to the U.S. Census Bureau.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Impedance Methods for Analyzing Stability Impacts of Inverter-Based Resources: Stability Analysis Tools for Modern Power Systems

Power systems around the world are undergoing a major transformation because of the increasing shares of renewable energy, growing deployment of energy storage systems, proliferation of distributed energy resources, electrification of other sectors, and so on. In the United States, wind and solar provided almost 10% of electricity in 2019. The U.S. Energy Information Administration, in its 2020 Annual Energy Outlook, forecasted that the share of electricity from renewables will reach 38% by 2050, of which more than 80% will come from wind and solar. Wind and solar, along with battery energy storage systems, interface with the grid using power electronic inverters; hence, they are collectively referred to as inverter-based resources (IBRs). The increasing annual share of electricity from IBRs in a power system means that during more times of the year, the system will operate at a much higher concentration of IBRs. Figure 1 presents the hourly share of wind and solar generation in the Electric Reliability Council of Texas (ERCOT) system in Texas in 2019. While the annual wind share was at 20%, the instantaneous percentage share was much higher. Moments of high shares of IBRs (>50%) will continue to grow as more IBRs will be deployed in a power system.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A Digital Twin for an Inverter-Based Resource Power Plant: Real-time data streaming unlocks situation awareness

Here, this study presents the development and successful implementation of a digital twin specifically designed for a grid-connected IBR power plant. By integrating a reduced-order model of the IBR system and dynamically updating the grid impedance with real-time data, the digital twin effectively captures and replicates the behavior of the physical system. Its accuracy and reliability are validated through critical test scenarios, including a three-phase fault and a line-tripping event. The results confirm that the digital twin closely emulates its physical counterpart, demonstrating its strong potential for real-time analysis, system monitoring, and predictive decision making in modern power systems.

Digital twins↗

MPI-AMRVAC FOR SOLAR AND ASTROPHYSICS

In this paper, we present an update to the open source MPI-AMRVAC simulation toolkit where we focus on solar and non-relativistic astrophysical magnetofluid dynamics. We highlight recent developments in terms of physics modules, such as hydrodynamics with dust coupling and the conservative implementation of Hall magnetohydrodynamics. A simple conservative high-order finite difference scheme that works in combination with all available physics modules is introduced and demonstrated with the example of monotonicity-preserving fifth-order reconstruction. Strong stability-preserving high-order Runge-Kutta time steppers are used to obtain stable evolutions in multi-dimensional applications, realizing up to fourth-order accuracy in space and time. With the new distinction between active and passive grid cells, MPI-AMRVAC is ideally suited to simulate evolutions where parts of the solution are controlled analytically or have a tendency to progress into or out of a stationary state. Typical test problems and representative applications are discussed with an outlook toward follow-up research. Finally, we discuss the parallel scaling of the code and demonstrate excellent weak scaling up to 30, 000 processors, allowing us to exploit modern peta-scale infrastructure.

79 ASTRONOMY AND ASTROPHYSICS↗

Intelligent Buildings of the Future: Cyberaware, Deep Learning Powered, and Human Interacting

This study discuss, intelligent buildings are quickly becoming cohesive and integral entities of cyber-physical ecosystems. Modern buildings adapt to internal and external elements and thrive on ever increasing data sources such as ubiquitous smart devices and sensors while mimicking various approaches previously known in software, hardware, and bio inspired systems. This article provides an overview of intelligent buildings of the future from a range of perspectives. First, a brief overview of prospects of U.S. and world energy consumption, concepts of smart buildings as integral entities of smart grids is presented. This is followed by a discussion of the role of connectivity and interoperability as well as current issues and solutions in the areas of security, resilience, and humans in realm of intelligent buildings. The article dives into detail about the intelligence aspect of intelligent buildings of the future. The learning and predictive Artificial Intelligence (AI) techniques behind many of the concepts of intelligent buildings are reviewed, including the latest techniques such as deep learning. As a concrete application of AI in the realm of intelligent buildings, prediction of energy consumption/load/demand, which is a much researched application of AI in the realm of intelligent buildings, is elaborated. The discussion is focused on most recent advancements of AI based demand prediction and the overview consists of existing research and a case study conducted by the authors for deep learning based demand prediction. Then, the article discusses the role of humans in intelligent buildings. Different types of human-building interactions are identified. Further, the article presents how each type of human-building interaction can benefit the overall control of intelligent buildings. The section is concluded by elaborating a case study conducted by the authors to achieve effective and efficient human-building interaction. The article is concluded with compilation of future insights based on latest technological advancements in U.S. industry and government.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Thermal energy storage heat exchanger: Molten salt heat exchanger design for utility power plants

The use of thermal energy storage (TES) in the latent heat of molten salts as a means of conserving fossil fuels and lowering the cost of electric power was evaluated. Public utility systems provided electric power on demand. This demand is generally maximum during late weekday afternoons, with considerably lower overnight and weekend loads. Typically, the average demand is only 60% to 80% of peak load. As peak load increases, the present practice is to purchase power from other grid facilities or to bring older less efficient fossil-fuel plants on line which increase the cost of electric power. The widespread use of oil-fired boilers, gas turbine and diesel equipment to meet peaking loads depletes our oil-based energy resources. Heat exchangers utilizing molten salts can be used to level the energy consumption curve. The study begins with a demand analysis and the consideration of several existing modern fossil-fuel and nuclear power plants for use as models. Salts are evaluated for thermodynamic, economic, corrosive, and safety characteristics. Heat exchanger concepts are explored and heat exchanger designs are conceived. Finally, the economics of TES conversions in existing plants and new construction is analyzed. The study concluded that TES is feasible in electric power generation. Substantial data are presented for TES design, and reference material for further investigation of techniques is included.

Ferarra, A.↗

Study of Near-Stall Flow Behavior in a Modern Transonic Fan with Composite Sweep

Detailed flow behavior in a modern transonic fan with a composite sweep is investigated in this paper. Both unsteady Reynolds-averaged Navier-Stokes (URANS) and Large Eddy Simulation (LES) methods are applied to investigate the flow field over a wide operating range. The calculated flow fields are compared with the data from an array of high-frequency response pressure transducers embedded in the fan casing. The current study shows that a relatively fine computational grid is required to resolve the flow field adequately and to calculate the pressure rise across the fan correctly. The calculated flow field shows detailed flow structure near the fan rotor tip region. Due to the introduction of composite sweep toward the rotor tip, the flow structure at the rotor tip is much more stable compared to that of the conventional blade design. The passage shock stays very close to the leading edge at the rotor tip even at the throttle limit. On the other hand, the passage shock becomes stronger and detaches earlier from the blade passage at the radius where the blade sweep is in the opposite direction. The interaction between the tip clearance vortex and the passage shock becomes intense as the fan operates toward the stall limit, and tip clearance vortex breakdown occurs at near-stall operation. URANS calculates the time-averaged flow field fairly well. Details of measured RMS static pressure are not calculated with sufficient accuracy with URANS. On the other hand, LES calculates details of the measured unsteady flow features in the current transonic fan with composite sweep fairly well and reveals the flow mechanism behind the measured unsteady flow field.

Hah, Chunill↗

A Real-Time Testbed for Smart Inverter Cyber Security Studies

Distributed energy resources (DER) have become a popular solution to modern-day issues surrounding the efficiency and reliability of power generation, as well as climate change concerns. Energy centers are shifting towards incorporating smart inverters with embedded functionalities such as high voltage ride through (HVRT), low voltage ride through (LVRT), active and reactive power compensation. However, the integration of smart inverters leave DER systems highly vulnerable to cybersecurity threats. The distributed network protocol 3 (DNP3) is a common method of communication between grid-tied hardware. Despite its popularity, the level of security leaves all hardware connected to the grid at risk of severe cyber-attacks. Thus, it is important to study any potential cybersecurity threats towards grid-tied smart inverters to mitigate cybersecurity vulnerabilities and refine existing cyber-security protections. This report describes the proposed testbed design to study cybersecurity threats to smart inverters. The testbed utilizes a real-time simulation case in RSCAD that includes a grid-tied wind turbine (WT) topology featuring two back-to-back two-level voltage source converters (BTB,2L-VSCs) and a permanent magnet synchronous machine (PMSM). The simulated case runs within the NovaCor real time digital simulator (RTDS). This report focuses on the design and implementation of a single module of the GTNETx2 card as a distributed network protocol and the configuration of an IEEE 1518 DNP database file that includes input and output variables mapped to different connection points in the grid that transmit and receive discrete, analog, and binary signals on command. This allows realistic emulation of the communication between the smart inverter and the grid for cybersecurity studies.

97 MATHEMATICS AND COMPUTING↗