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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Quandary

Quandary numerically simulates and optimizes the time-evolution of open quantum systems. The underlying dynamics are modelled by Lindblad's master equation, a linear ordinary differential equation (ODE) describing quantum systems interacting with the environment. Quandary solves this ODE numerically by applying a time-stepping integration scheme, and utilizes a gradient-based optimization approach to determine optimal control pulses that drive the quantum system to a desired target state. Two optimization objectives are considered: (a) Unitary gate optimization that finds controls to realize a unitary gate transformation, and (b) optimal reset that aims to drive the quantum system to the ground states. Gradient-based optimization schemes utilizing Petsc's Tao optimization package are applied to generate control pulses that minimize the respective measure. To evaluate the gradient of the objective function, the discrete adjoint method is used while leveraging techniques from Algorithmic Differentiation to produce exact and consistent gradients. To mitigate excessive execution run times, the software can be build together with the XBraid software library which provides a parallelization strategy to distribute the time-evolution of the underlying dynamics onto multiple processor.

Petersson, NilsA.↗
DOE OSTI2025

Superspin renormalization and slow relaxation in random spin systems

We develop an excited-state real-space renormalization group (RSRG-X) formalism to describe the dynamics of conserved densities in randomly interacting spin-12 systems. Our formalism is suitable for systems with U(1) and Z2 symmetries, and we apply it to chains of randomly positioned spins with dipolar XX+YY interactions, as arise in Rydberg quantum simulators and other platforms. The formalism generates a sequence of effective Hamiltonians that provide approximate descriptions for dynamics on successively smaller energy scales. These effective Hamiltonians involve “superspins”: two-level collective degrees of freedom constructed from (anti)aligned microscopic spins. Conserved densities can then be understood as relaxing via coherent collective spin flips. For the well-studied simpler case of randomly interacting nearest-neighbor XX+YY chains, the superspins reduce to single spins. Our formalism also leads to a numerical method capable of simulating the dynamics up to an otherwise inaccessible combination of large system size and late time. Focusing on disorder-averaged infinite-temperature autocorrelation functions, in particular the spin survival probability Sp¯(t), we demonstrate quantitative agreement between our algorithm and exact diagonalization (ED) at low but nonzero frequencies. Such agreement holds for chains with nearest-neighbor, next-nearest-neighbor, and long-range dipolar interactions. Our results indicate decay of Sp¯(t) slower than any power law and feature no significant deviation from the ∼1/ln2(t) asymptote expected from the infinite-randomness fixed-point of the nearest-neighbor model. We also apply the RSRG-X formalism to two-dimensional long-range systems of moderate size and find slow late-time decay of Sp¯(t).

Zhao, Yi J↗
DOE OSTI2021

Improving the performance of first- and last-mile mobility services through transit coordination, real-time demand prediction, advanced reservations, and trip prioritization

Socio-demographic trends and recent economic development patterns have resulted in travel behavior changes that call for more flexible and accessible public transit options. Because flexible transit services vary in scope, size, and service type, new data-informed methods are useful to optimize services based on the specific needs of local communities and riders. In this study, real-world demand and vehicle trajectory data were used to evaluate and optimize system performance for an existing first-mile–last-mile (FMLM) service in Robinson Township, PA. A general FMLM model for arbitrary demand and service supply was then developed to quantify system performance—both travel time costs and day-to-day reliability—for various operational polices considering spatio-temporal demand variation and transportation network dynamics. Heuristics were used for optimal real-time vehicle routing in sizable real-world networks accommodating various service types and scopes. In this case study, total user costs were reduced by 18.6% when rides were coordinated with mainline fixed-route transit. Predictive routing strategies were shown to marginally improve system performance under sparse and variable spatio-temporal demand. The case study also highlights potentially large travel time and user reliability improvements—reductions of 51% and 53.8%, respectively—when trip requests were made in advance of their desired pickup time. Finally, we show that travel time reliability can be improved for time-inflexible trips with trip prioritization without increasing total user costs. These results were stable to changes in demand density.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Optimized utilization of COMB3 reactive potentials in LAMMPS

An investigation to optimize the application of the third-generation charge optimized many-body (COMB3) interatomic potential and associated input parameters was carried out through the study of solid–liquid interactions in classical molecular dynamics simulations. The rates of these molecular interactions are understood through the wetting rates of water nano-droplets on a bare copper (111) surface. Implementing the Langevin thermostat, the influence of simulation time step, the number of atoms in the system, the frequency at which charge equilibration is performed, and the temperature relaxation rate are all examined. The results indicate that time steps of 0.4 fs are possible when using longer relaxation times for the system temperature, which is almost double the typical time step used for reactive potentials. Additionally, the use of the charge equilibration allows for a fewer atomic layers to be used in the Cu slab. In addition, charge equilibrium schemes do not need to be performed every time step to ensure accurate charge transfer. Interestingly, the rate of wetting for the nanodroplets is dominantly dependent on the temperature relaxation time, which is predicted to significantly change the viscosity of the water droplets. This work provides a pathway for optimizing simulations using the COMB3 reactive interatomic potential.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Apparatus for real-time size-distributed measurement of aerosol mass concentration

An impactor, system and method for performing real-time measurements of particles in aerosol gases. The impactor comprises a plurality of cascading stages having impaction plates, mass-measurement mechanisms retained on the impaction plates, and a nozzle plate. A signal line associated with each of the plurality of cascading stages is configured to relay signals from the mass-measurement mechanism of the associated stage to a computer-based system configured to receive the transmitted signals from the signal lines, and to correlate changes in the resonant frequencies to particle concentrations in real time.

Chen, Modi↗
DOE OSTI2021

Thermophysical Properties Experimentally Tested for NaCl-KCl-MgCl 2 Eutectic Molten Salt as a Next-Generation High-Temperature Heat Transfer Fluids in Concentrated Solar Power Systems

A new eutectic chloride molten salt, MgCl 2 -KCl-NaCl (wt% 45.98–38.91–15.11), has been recognized as one of the most promising high-temperature heat transfer fluids (HTF) for both heat transfer and thermal storage for the third-generation concentrated solar power (CSP) systems. For the first time, some essential thermophysical properties of this eutectic chloride molten salt needed for basic heat transfer and energy storage analysis in the application of concentrating solar power systems have been experimentally tested and provided as functions of temperature in the range from 450 °C to 700 °C. The studied properties include heat capacity, melting point, heat of fusion, viscosity, vapor pressure, density, and thermal conductivity. The property equations provide essential database for engineers to use to calculate convective heat transfer in concentrated solar receivers, heat exchangers, and thermal storage for concentrated solar power plants.

14 SOLAR ENERGY↗
DOE OSTI2020

Layer-Parallel Training of Deep Residual Neural Networks

Residual neural networks (ResNets) are a promising class of deep neural networks that have shown excellent performance for a number of learning tasks, e.g., image classification and recognition. Mathematically, ResNet architectures can be interpreted as forward Euler discretizations of a nonlinear initial value problem whose time-dependent control variables represent the weights of the neural network. Hence, training a ResNet can be cast as an optimal control problem of the associated dynamical system. For similar time-dependent optimal control problems arising in engineering applications, parallel-in-time methods have shown notable improvements in scalability. This paper demonstrates the use of those techniques for efficient and effective training of ResNets. The proposed algorithms replace the classical (sequential) forward and backward propagation through the network layers with a parallel nonlinear multigrid iteration applied to the layer domain. This adds a new dimension of parallelism across layers that is attractive when training very deep networks. From this basic idea, we derive multiple layer-parallel methods. The most efficient version employs a simultaneous optimization approach where updates to the network parameters are based on inexact gradient information in order to speed up the training process. Finally, using numerical examples from supervised classification, we demonstrate that the new approach achieves a training performance similar to that of traditional methods, but enables layer-parallelism and thus provides speedup over layer-serial methods through greater concurrency.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Hybrid EMT-TS Simulation Strategies to Study High Bandwidth MMC-Based HVdc Systems

Modular multilevel converters (MMCs) are widely used in the design of modern high-voltage direct current (HVdc) transmission system. High-fidelity dynamic models of MMCs-based HVdc system require small simulation time step and can be accurately modeled in electro-magnetic transient (EMT) simulation programs. The EMT program exhibits slow simulation speed and limitation on the size of the model and brings certain challenges to test the high-fidelity HVdc model in system-level simulations. This paper presents the design and implementation of a hybrid simulation framework, which enables the co-simulation of the EMT model of Atlanta-Orlando HVdc line and the transient stability (TS) model of the entire Eastern Interconnection system. This paper also introduces the implementation of two high-fidelity HVdc line models simulated at different time steps and discusses a dedicated method for sizing the buffer areas on both sides of the HVdc line. The simulation results of the two HVdc models with different sizes of buffer areas are presented and compared.

Liu, Yuan↗
DOE OSTI2022

Effectiveness of Privacy Techniques in Smart Metering Systems

Smart grid technologies enable timely energy billing for residential homes. The ability to react to energy demands during peak hours allows energy providers to conserve power and operate efficiently. However, these data streams are also susceptible to privacy attacks within the energy company and from outside hackers. We implemented four different privacy models: k-anonymous, l-diversity, t-closeness, and ε-differential privacy. We demonstrate the models’ effectiveness using a real-world dataset composed of 15 different residential households with energy consumption data spanning over a year.

Peralta-Peterson, Martin↗
DOE OSTI2020

Rapid Sample Insertion/Extraction Systems for Gamma Irradiation

The Rapid Sample Insertion/Extraction System for Gamma Irradiation, otherwise known as the "rabbit" system, was a four-week long project which included many different aspects; from coding an Arduino to building PVC piping to 3-D printing the "rabbit" capsules. The "rabbit" system is a system of PVC piping that allows a quick and efficient transfer of materials into/out of one of the irradiation chambers in the Gamma Irradiation Facility (GIF) with the use of a 3-D printed "rabbit." This "rabbit" encapsulates material to be irradiated and carries it from a position outside of the irradiation chamber to the basket inside of the chamber. The main purpose of this system is to save time and provide more exact data without any delays that normally occur when a person has to enter the chamber, retrieve data, and then analyze the data. This system should take measurements and retrieve the data instantaneously. The way in which the "rabbit" is sent through the PVC piping is with an advanced bi-directional, high-throughput pneumatic system, or a shop vacuum cleaner. When the vacuum is set to blow or suck then the "rabbit" will be pulled through the PVC piping to its intended destination and will hit sensors along the sides of the tubing when it reaches the end of the piping. These sensors tell the Arduino that the "rabbit" is finished moving throughout the tubing and stops a timer. Another timer is used to see how long the "rabbit" is being irradiated so when the "rabbit" reaches the sensors in the basket in the irradiation chamber another timer is started and it ends when the sensors no longer detect the "rabbit," which means that it has begun its journey back to the starting point.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2023

Development of a pixelated BaF 2 test bed for timing applications [Slides]

BaF 2 one of the fastest known scintillators, emitting at 195 & 220 nm with sub-nanosecond decay constant. Fast emission only comprises ~13% of total light. The goal is to develop a prototype BaF 2 detector system with a practical form factor and variable geometry, and characterize system performance for various timing applications.

42 ENGINEERING↗
DOE OSTI2020

Introduction to the Minitrack on Monitoring, Control, and Protection.

This minitrack is on topics related to the monitoring, control, and protection of electric power systems for real-time operations and short-term operations planning. This year the emphasis has been on recent developments in the area of large-scale dynamic research for power systems and on hybrid and distributed control concepts for decentralized command and control of existing critical energy infrastructures.

Eto, Joseph H↗
DOE OSTI2020

Pulse-train drive system for electrostatic generators and motors

A novel motor drive system has been described for use in electrostatic generator/motor systems based on the time variation of capacity of a rotating condenser comprised of segmented rotor and stator elements. It takes advantage of the fact that the motor action of such a system depends only on the rms value of the drive pulses, which therefore can be formed simply by periodically interrupting a high-frequency ac wave train. This new circuitry simplifies the drive system and takes advantage of recent developments of devices used in the art of inversion of dc voltages to high-frequency (tens of kiloHz) ac.

42 ENGINEERING↗
DOE OSTI2022

Methods and apparatus for calibration and response time testing of level sensors

Systems and methods of diagnosing performance of a level sensor of a fluid test chamber, including a data acquisition and processing unit configured to receive output signals of one or more level sensors that are installed to a fluid chamber, the data acquisition and processing unit being configured to connect to the one or more level sensors to record and process the output signals to test operation of the one or more level sensors.

Hashemian, Alexander Hashem↗
DOE OSTI2021

A Real-time Agent Based Optimization and Control Approach for Residential Building Heating Ventilation and Air Conditioning Systems

The prevalence of the loT (Internet of Things) is fostering the development of new control options and decision making that was not previously available. This is creating a wealth of opportunities for real-time control approaches and systems that can optimize for a common goal. This paper presents a smart residential neighborhood with optimization at the residential level utilizing a system of agents. The optimization utilizes information and modeling to optimize variable speed HVAC real-time operation in actual residential buildings. Data is presented showing the performance of the optimization and conclusions are drawn on next steps for development.

Hall, Joni↗
DOE OSTI2022

Quantum simulation of nonequilibrium dynamics and thermalization in the Schwinger model

In this work, we present simulations of nonequilibrium dynamics of quantum field theories on digital quantum computers. As a representative example, we consider the Schwinger model, a (1+1)-dimensional U(1) gauge theory, coupled through a Yukawa-type interaction to a thermal environment described by a scalar field theory. We use the Hamiltonian formulation of the Schwinger model discretized on a spatial lattice. With the thermal scalar fields traced out, the Schwinger model can be treated as an open quantum system and its real-time dynamics are governed by a Lindblad equation in the Markovian limit. The interaction with the environment ultimately drives the system to thermal equilibrium. In the quantum Brownian motion limit, the Lindblad equation is related to a field theoretical Caldeira-Leggett equation. By using the Stinespring dilation theorem with ancillary qubits, we perform studies of both the nonequilibrium dynamics and the preparation of a thermal state in the Schwinger model using IBM's simulator and quantum devices. The real-time dynamics of field theories as open quantum systems and the thermal state preparation studied here are relevant for a variety of applications in nuclear and particle physics, quantum information and cosmology.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Accelerating Simulation for High-Fidelity PV Inverter System Reliability Assessment with High-Performance Computing

The overall cost of photovoltaic (PV) systems has shown a downward trend during the last decade; however, PV inverter failures account for the highest cost of operation and maintenance. To address this, reliability tools with powerful computation and better accuracy are required for the lifetime prediction and degradation evaluation of PV inverters. This paper proposes an event-driven parallel computing-based simulator. The proposed simulator applies high-performance computing techniques and other accessory optimization techniques-including cluster merging, adaptive model updates, and steady-state identification-to make reliability assessments for PV inverters under given input mission profiles and operating conditions with high efficiency and high fidelity. The main idea of the simulator and its workflow are introduced. Then, a demo PV inverter system simulator is implemented, and the speedup of the total simulations of the switching model reaches 123.03 times.

high-performance computing↗
DOE OSTI2024

An Efficient Numerical Algorithm for Solving Coupled Time-Dependent Ginzburg-Landau Equation for Superconductivity and Elasticity

A decoupled finite element algorithm is developed for simulating the vortex dynamics on an elastic superconductor which couples the time-dependent Ginzburg- Landau equation with the complex-valued superconducting order parameter and the vector-valued magnetic potential, and the elasticity equation. We present an iterative algorithm for the decoupled system arising from the time and spatial discretization using a combination of preconditioner, algebraic multigrid method (AMG) and preconditioned conjugate gradient method (PCG). The iterative algorithm allows us to perform large-scale three-dimensional simulations of mesoscale pattern formation during superconducting phase transitions with arbitrary elastic boundary conditions. Here, the performance and efficiency of the algorithm are numerically verified by several benchmark problems, exhibiting up to two orders of magnitude improvement depending on the scale of discrete system compared to the exact solver.

Efficiency↗