Online Voltage Control for Unbalanced Distribution Networks Using Projected Newton Method
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Engineering↗
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Results for “distributed method”
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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Accessing tens-to-hundreds femtoseconds nuclear state lifetimes with low-energy binary heavy-ion reactions
A novel Monte Carlo technique has been developed to determine lifetimes of excited states in the tens-to-hundreds femtoseconds range in products of low-energy heavy-ion binary reactions, with complex velocity distributions. The method is based on a detailed study of Doppler-broadened γ-ray lineshapes. Its relevance is demonstrated in connection with the 18 O(7.0MeV/u)+ 181 Ta experiment, performed at GANIL with the AGATA+VAMOS+PARIS setup, to study neutron-rich O, C, N, ... nuclei. Excited states in 17 O and 19 O, with known lifetimes, are used to validate the method over the ~20-400fs lifetime-sensitivity range. Emphasis is given to the unprecedented position resolution provided by γ-tracking arrays, which turns out to be essential for reaching the required accuracy in Doppler-shift correction. The technique is anticipated to be an important tool for lifetime investigations in exotic neutron-rich nuclei, produced with intense ISOL-type beams.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Performance of parallel FDTD method for shared- and distributed-memory architectures: Application tobioelectromagnetics
Not Available
Ruiz-Cabello N., Miguel (ORCID:0000000190396181)↗
EPMA-Based Mass Balance Method for Quantitative Fission Product Distribution Comparison between TRISO Particles
Two irradiated AGR-2 TRISO particles were chosen to demonstrate a recently developed mass balance technique in which EPMA-generated concentration data was used to determine fission product mass on a layer-by-layer basis in TRISO particles. EPMA-calculated fission product masses for most fission products in the two particles were within +/- 20% of their ORIGEN-modelled masses. Results show that Sr, Ba, and Eu accumulate preferentially in the carbon-rich kernel periphery on the particles’ side that lacks a gap between the buffer and IPyC. In addition, the more mobile elements--Cs, Sr, and Pd, accumulate in greater quantity in the outer layers of particle AGR2-223-RS34 compared to particle AGR2-223-RS06, which has relatively more of those elements’ mass located in the kernel and kernel periphery, suggesting enhanced fission product transport in particle AGR2-223-RS34. This model can be used better understand and test fission product transport in TRISO particles.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Radiation Safety Information Computational Center (RSICC) [Slides]
This presentation touches on the Radiation Safety Information Computational Center (RSICC). This Lecture provides general mission, statistics, and strategies. A general background is provided of the tool. Licensee agreements and export control agreements are discussed. The presentation finishes with a look at the most in demand and requested software packages.
97 MATHEMATICS AND COMPUTING↗
Adjoint Monte Carlo Method for the Multiplicity Moment Distributions of Subcritical Multiplying Systems [Poster]
Abstract not provided.
Nuclear Criticality Safety Program (NCSP)↗
Does Carrier Envelope Phase Affect the Ionization Site in a Neutral Diatomic Molecule?
A recent work shows how to extract the ionization site of a neutral diatomic molecule by comparing Quantum Trajectory Monte Carlo (QTMC) simulations with experimental measurements of the final electron momenta distribution. This method was applied to an experiment using a 40-femtosecond infrared pulse, finding that a downfield atom is roughly twice as likely to be ionized as an upfield atom in a neutral nitrogen molecule. However, an open question remains as to whether an assumption of the zero carrier envelope phase (CEP) used in the above work is still valid for short, few-cycle pulses where the CEP can play a large role. Given experimentalists’ limited control over the CEP and its dramatic effect on electron momenta after ionization, it is desirable to see what influence the CEP may have in determining the ionization site. In this paper, we employ QTMC techniques to simulate strong-field ionization and electron propagation from neutral N2 using an intense 6-cycle laser pulse with various CEP values. Comparing simulated electron momenta to experimental data indicates that the ratio of down-to-upfield ions remains roughly 2:1 regardless of the CEP. This confirms that the ionization site of a neutral molecule is determined predominantly by the laser frequency and intensity, as well as the ground-state molecular wavefunction, and is largely independent of the CEP.
Schimmoller, Alex↗
The K2 M67 Study: Precise Mass for a Turnoff Star in the Old Open Cluster M67
We present a study of the bright detached eclipsing main-sequence binary WOCS 11028 (Sanders 617) in the open cluster M67. Although the binary has only one eclipse per orbital cycle, we show that the masses of the stars can be derived very precisely thanks to a strong constraint on the orbital inclination: M {sub A} = 1.222 ± 0.006M {sub ⊙} and M {sub B} = 0.909 ± 0.004M {sub ⊙}. We use a spectral energy distribution fitting method to derive characteristics of the component stars in lieu of the precise radii that would normally be derived from a doubly eclipsing binary. The deconvolution of the SEDs reveals that the brighter component of the binary is at the faint turnoff point for the cluster—a distinct evolutionary point that occurs after the convective core has been established and while the star is in the middle of its movement toward lower surface temperatures, before the so-called hook at the end of the main sequence. The measurements are in distinct disagreement with evolution models at solar metallicity: higher metal abundances are needed to reproduce the characteristics of WOCS 11028 A. We discuss the changes to model physics that are likely to be needed to address the discrepancies. The clearest conclusions are that diffusion is probably necessary to reconcile spectroscopic abundances of M67 stars with the need for higher metallicity models and that reduced strength convective overshooting is occurring for stars at the turnoff. At super-solar bulk metallicity, various indicators agree on a cluster age between about 3.5 and 4.0 Gyr.
36 MATERIALS SCIENCE↗
Quantum frequency processor for provable cybersecurity
Methods of quantum key distribution include receiving a frequency bin photon at a location, selecting a frequency bin photon quantum key distribution measurement basis, with a quantum frequency processor, performing a measurement basis transformation on the received frequency bin photon so that the frequency bin photon is measurable in the selected frequency bin photon quantum key distribution measurement basis, and detecting the frequency bin photon in the selected quantum key distribution measurement basis and assigning a quantum key distribution key value based on the detection to a portion of a quantum key distribution key. Apparatus and methods for encoding, decoding, transmitting, and receiving frequency bin photons are disclosed.
Lukens, Joseph M.↗
Quantum frequency processor for provable cybersecurity
Methods of quantum key distribution include receiving a frequency bin photon at a location, selecting a frequency bin photon quantum key distribution measurement basis, with a quantum frequency processor, performing a measurement basis transformation on the received frequency bin photon so that the frequency bin photon is measurable in the selected frequency bin photon quantum key distribution measurement basis, and detecting the frequency bin photon in the selected quantum key distribution measurement basis and assigning a quantum key distribution key value based on the detection to a portion of a quantum key distribution key. Apparatus and methods for encoding, decoding, transmitting, and receiving frequency bin photons are disclosed.
Lukens, Joseph M.↗
Optimization of Distribution Feeder Topology: A Differential Programming Learning Approach
This paper presents a gradient based method for optimizing distribution feeder network topology under load un- certainty. We recast the optimal network reconfiguration problem as a learning problem where edge weights of a graph are learned to produce an optimized spanning tree for a distribution network. Using recent methods published on differentiable programming, we provide a data driven method for learning these weights. We test our method on 100 variations of an IEEE 15-bus test system. Our results show that our method outperforms more traditional mathematical programming-based approaches.
differentiable programming↗
Deep Reinforcement Learning Based Volt-VAR Optimization in Smart Distribution Systems
This paper develops a model-free volt-VAR optimization (VVO) algorithm via multi-agent deep reinforcement learning (DRL) in unbalanced distribution systems. This method is novel since we cast the VVO problem in distribution networks to an intelligent deep Q-network (DQN) framework, which avoids solving a specific optimization model directly when facing time-varying operating conditions in the systems. We consider statuses/ratios of switchable capacitors, voltage regulators, and smart inverters installed at distributed generators as the action variables of the agents. A delicately designed reward function guides these agents to interact with the distribution system, in the direction of reinforcing voltage regulation and power loss reduction simultaneously. The forward-backward sweep method for radial three-phase distribution systems provides accurate power flow results within a few iterations to the DRL environment. The proposed method realizes the dual goals for VVO. We test this algorithm on the unbalanced IEEE 13-bus and 123-bus systems. Numerical simulations validate the excellent performance of this method in voltage regulation and power loss reduction.
41 EE - Solar Energy Technologies Office (EE-4S)↗
Rigid stiffener-reinforced flexible neural probes, and methods of fabrication using wicking channel-distributed adhesives and tissue insertion and extraction
A stiffener-reinforced microelectrode array probe and fabrication method using wicking channel-distributed adhesives which temporarily adheres a flexible device onto a rigid stiffener for insertion and extraction. Assembly is by dispensing a liquid adhesive into a narrow open groove wicking channel formed on the stiffener so that the adhesive is wicked along and fills the channel by capillary action, and adhering the adhesive-filled bonding side of the elongated section of the rigid substrate to a flexible device.
Shah, Kedar G.↗
Prediction for Pressure Differential Across HEPA Filter Media Based on Media Characteristics and Particle Size Distribution
A new method for predicting the pressure drop across High Efficiency Particulate Air (HEPA) filter media is proposed based upon mass deposited onto the filter and known physical characteristics of the filter media. Detailed are the methods used in conjunction with current filter loading models to predict the pressure drop, as well as tests conducted to validate the methods. The benefit of a prediction model for practical use lies in the manufacturing and service life of nuclear grade HEPA filters. HEPA filters for use in nuclear facilities have a prescribed expiration date and a maximum allowable operating pressure drop. Therefore, the ability to predict the pressure drop across a filter and relate it to an expected length of service time can enable a reduction in wasted filters. This will allow for more informed decisions to be made based upon the dictated life cycle of the filters. Also, understanding and predicting how the pressure drop of HEPA filter media behaves as a function of physical characteristics and loaded mass can assist in future design and manufacturing of filter media. Currently, most existing pressure drop models are either computationally based or analytical methods relying on data gathered during tests. Neither are practical for prediction; the computational methods are difficult to implement, and the current analytical methods are more useful as tools for analysis. The current analytical model developed by Bergman et al. is based upon the pressure drop from each media fiber and modeling the deposited particles as newly formed fibers. Using Bergman's model and the media properties, air properties, and known aerosol particle size distribution, a pressure drop curve as a function of loaded mass can be created. This curve implies initial loading in the depth of the filter media with a transition to pure surface loading on the filter face, and a sensitivity to an evolving particle size distribution as mass continues to load onto the filter. To implement the predictive model, knowledge of the mean filter fiber diameter and porosity of the filter media is required. Traditionally, the mean fiber diameter is calculated as an effective diameter from prior media testing, however, in this study a Scanning Electron Microscope (SEM) technique is used to acquire this variable. Validation of the predictive model is provided by flat sheet media tests under a controlled environment with a measured particle size distribution of the challenge aerosol and shows reasonable preliminary agreement.
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Intersection-distribution-based remapping between arbitrary meshes for staggered multi-material arbitrary Lagrangian-Eulerian hydrodynamics
In this paper, we present a new intersection-distribution-based remapping method between arbitrary polygonal meshes for indirect staggered multi-material arbitrary Lagrangian-Eulerian hydrodynamics. All cell-centered material quantities are conservatively remapped using intersections between the Lagrangian (old, source) mesh and the rezoned (new, target) mesh. The new nodal masses are obtained by conservative distribution of all material masses in each new cell to the cell's corners and then collecting those corner masses at new nodes. This distribution is done using a local constrained optimization approach for each cell in the new mesh. In order to remap nodal momentum we first define cell-centered momentum for each cell in the old mesh, conservatively remap this to the new mesh and then conservatively distribute the new zonal momentum to each cell's bounding nodes, again using local constrained optimization. Our method also conserves total energy by applying a new nodal kinetic energy correction that relies on a process similar to that used for remapping nodal mass and momentum. Cell-centered kinetic energy is computed, conservatively remapped and then distributed to nodes. The discrepancy between this conservatively remapped and actual nodal kinetic energy is then conservatively distributed to the internal energies of the materials in the cells surrounding each node. Unlike conventional cell-based corrections of this type, this new nodal kinetic energy correction has not been observed to drive material internal energy negative in any of our testing. Unlike flux based remapping, our new intersection-distribution method can be applied to remapping between source and target meshes that are arbitrarily different, which provides superior flexibility in the rezoning strategy. Our method is accurate, essentially conservative and essentially bounds preserving.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Taylor-Expansion-Based Robust Power Flow in Unbalanced Distribution Systems: A Hybrid Data-Aided Method
Traditional power flow methods often adopt certain assumptions designed for passive balanced distribution systems, thus lacking practicality for unbalanced operation. moreover, their computation accuracy and efficiency are heavily subject to unknown errors and bad data in measurements or prediction data of distributed energy resources (ders). to address these issues, this paper proposes a hybrid data-aided robust power flow algorithm in unbalanced distribution systems, which combines taylor series expansion knowledge with a data-driven regression technique. the proposed method initiates a linearization power flow model to derive an explicitly analytical solution by modified taylor expansion. to mitigate the approximation loss that surges due to the der integration and bad data, we further develop a data-aided robust support vector regression approach to estimate the errors efficiently. comparative analysis in the 13-bus and 123-bus ieee unbalanced feeders shows that the proposed hybrid algorithm achieves superior computational efficiency, with guaranteed accuracy and robustness against outliers.
data-driven↗
Predicting Volume of Distribution in Humans: Performance of In Silico Methods for a Large Set of Structurally Diverse Clinical Compounds
Volume of distribution at steady state (V D,ss ) is one of the key pharmacokinetic parameters estimated during the drug discovery process. Despite considerable efforts to predict V D,ss , accuracy and choice of prediction methods remain a challenge, with evaluations constrained to a small set (<150) of compounds. To address these issues, a series of in silico methods for predicting human V D,ss directly from structure were evaluated using a large set of clinical compounds. Machine learning (ML) models were built to predict V D,ss directly and to predict input parameters required for mechanistic and empirical V D,ss predictions. In addition, log D, fraction unbound in plasma (fup), and blood-to-plasma partition ratio (BPR) were measured on 254 compounds to estimate the impact of measured data on predictive performance of mechanistic models. Furthermore, the impact of novel methodologies such as measuring partition (Kp) in adipocytes and myocytes (n = 189) on V D,ss predictions was also investigated. In predicting V D,ss directly from chemical structures, both mechanistic and empirical scaling using a combination of predicted rat and dog V D,ss demonstrated comparable performance (62%–71% within 3-fold). The direct ML model outperformed other in silico methods (75% within 3-fold, r 2 = 0.5, AAFE = 2.2) when built from a larger data set. Scaling to human from predicted V D,ss of either rat or dog yielded poor results (<47% within 3-fold). Measured fup and BPR improved performance of mechanistic V D,ss predictions significantly (81% within 3-fold, r 2 = 0.6, AAFE = 2.0). Adipocyte intracellular Kp showed good correlation to the V D,ss but was limited in estimating the compounds with low V D,ss .
59 BASIC BIOLOGICAL SCIENCES↗
Controlling radioisotope proportions when randomly sampling from Dirichlet distributions in PyRIID
As machine learning models for radioisotope quantification become more powerful, likewise the need for high-quality synthetic training data grows as well. For problem spaces that involve estimating the relative isotopic proportions of various sources in gamma spectra it is necessary to generate training data that accurately represents the variance of proportions encountered. In this report, we aim to provide guidance on how to target a desired variance of proportions which are randomly when using the PyRIID Seed Mixer, which samples from a Dirichlet distribution. We provide a method for properly parameterizing the Dirichlet distribution in order to maintain a constant variance across an arbitrary number of dimensions, where each dimension represents a distinct source template being mixed. We demonstrate that our method successfully parameterizes the Dirichlet distribution to target a specific variance of proportions, provided that several conditions are met. This allows us to follow a principled technique for controlling how random mixture proportions are generated which are then used downstream in the synthesis process to produce the final, noisy gamma spectra.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗