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At least 685 records · Page 38

Bridging material models across scales: An integrated approach to equation of state and molecular dynamics modeling of copper

New uncertainty-aware equation of state (EOS) and electrical conductivity (EC) models for copper have been developed. The multiphase EOS/EC models are fit to experimental solid/liquid EC isobar measurements as well as density-functional theory molecular dynamics (DFT-MD) EC calculations in both expanded and compressed regimes (0.1–16 g/ cm 3 ⁠). The liquid and solid EOS phases were fit to available experimental data along with additional DFT-MD data over the same range as the EC. Leveraging the DFT-MD data, a corresponding machine-learned interatomic potential (MLIAP) for copper was trained using genetic-algorithm optimization. The copper MLIAP was constrained by EOS shock points at high compressions. The final EOS bounded MLIAP proves to be stable over a large density range (approximately 0.1–20 g/ cm 3 ) with good agreement to an isothermal compression curve, shock Hugoniot, and liquid speed of sound measurements at high pressures (100s of GPa).

Acoustic measurements and instrumentation↗

The clustering of Lyman Alpha Emitting galaxies at 𝗓=2–3

Here, we measure the clustering of Lyman Alpha Emitting galaxies (LAEs) selected from the One-hundred-square-degree DECam Imaging in Narrowbands (ODIN) survey, with spectroscopic follow-up from Dark Energy Spectroscopic Instrument (DESI). We use DESI spectroscopy to optimize our selection and to constrain the interloper fraction and redshift distribution of our narrow-band selected sources. We select samples of 4000 LAEs at z = 2.45 and 3.1 in 9 sq. deg. centered on the COSMOS field with median Lyα fluxes of ≈ 10 -16 erg s -1 cm -2 . Covariances and cosmological inferences are obtained from a series of mock catalogs built upon high-resolution N-body simulations that match the footprint, number density, redshift distribution and observed clustering of the sample. We find that both samples have a correlation length of r 0 = 3.0 ± 0.2 h -1 Mpc. Within our fiducial cosmology these correspond to 3D number densities of ≈ 10 -3 h 3 Mpc -3 and, from our mock catalogs, biases of 1.7 and 2.0 at z= 2.45 and 3.1, respectively. We discuss the implications of these measurements for the use of LAEs as large-scale structure tracers for high-redshift cosmology.

79 ASTRONOMY AND ASTROPHYSICS↗

Gaming the beamlines—employing reinforcement learning to maximize scientific outcomes at large-scale user facilities

Abstract Beamline experiments at central facilities are increasingly demanding of remote, high-throughput, and adaptive operation conditions. To accommodate such needs, new approaches must be developed that enable on-the-fly decision making for data intensive challenges. Reinforcement learning (RL) is a domain of AI that holds the potential to enable autonomous operations in a feedback loop between beamline experiments and trained agents. Here, we outline the advanced data acquisition and control software of the Bluesky suite, and demonstrate its functionality with a canonical RL problem: cartpole. We then extend these methods to efficient use of beamline resources by using RL to develop an optimal measurement strategy for samples with different scattering characteristics. The RL agents converge on the empirically optimal policy when under-constrained with time. When resource limited, the agents outperform a naive or sequential measurement strategy, often by a factor of 100%. We interface these methods directly with the data storage and provenance technologies at the National Synchrotron Light Source II, thus demonstrating the potential for RL to increase the scientific output of beamlines, and layout the framework for how to achieve this impact.

36 MATERIALS SCIENCE↗

DiffLense: a conditional diffusion model for super-resolution of gravitational lensing data

Abstract Gravitational lensing data is frequently collected at low resolution due to instrumental limitations and observing conditions. Machine learning-based super-resolution techniques offer a method to enhance the resolution of these images, enabling more precise measurements of lensing effects and a better understanding of the matter distribution in the lensing system. This enhancement can significantly improve our knowledge of the distribution of mass within the lensing galaxy and its environment, as well as the properties of the background source being lensed. Traditional super-resolution techniques typically learn a mapping function from lower-resolution to higher-resolution samples. However, these methods are often constrained by their dependence on optimizing a fixed distance function, which can result in the loss of intricate details crucial for astrophysical analysis. In this work, we introduce DiffLense , a novel super-resolution pipeline based on a conditional diffusion model specifically designed to enhance the resolution of gravitational lensing images obtained from the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP). Our approach adopts a generative model, leveraging the detailed structural information present in Hubble space telescope (HST) counterparts. The diffusion model, trained to generate HST data, is conditioned on HSC data pre-processed with denoising techniques and thresholding to significantly reduce noise and background interference. This process leads to a more distinct and less overlapping conditional distribution during the model’s training phase. We demonstrate that DiffLense outperforms existing state-of-the-art single-image super-resolution techniques, particularly in retaining the fine details necessary for astrophysical analyses.

Computer Science↗

From noise to information: The transfer function formalism for uncertainty quantification in reconstructing the nuclear density

The neutron distribution of neutron-rich nuclei provides critical information on the structure of finite nuclei and neutron stars. Parity violating experiments—such as PREX and CREX—provide a clean and largely model-independent determination of neutron densities. Such experiments, however, are challenging and expensive, which is why sound statistical arguments are required to maximize the information gained. We introduce a new framework, the “transfer function formalism,” aimed at uncertainty quantification, model selection, and experimental design in the context of neutron densities. The transfer functions (TFs) are built analytically by expressing the linear response of the objective function (e.g., χ2) to small perturbations of the data. Using the TF formalism, we are able to analyze the expected overall uncertainty—quantified in terms of bias and variance—of the mean square radius and interior density of 48 Ca and 208 Pb. Using relativistic mean field models as a proxy for the weak-charge density—and assuming that a total of five measurements could be performed on the weak form factor of 48 Ca and 208 Pb—we identify the optimal models and experimental locations that minimize the uncertainty in the extraction of the radius and interior density. We also explore the use of the TF formalism to understand the influence of prior distributions for the model parameters, as well as the optimization of model hyperparameters not constrained by the data. Here,we establish how the choice of experimental locations and the model that is used can have a significant impact on the final uncertainties of the extracted quantities of interest. For challenging experiments such as CREX and PREX, a proper quantification of such uncertainties is critical. We have demonstrated how the TF formalism provides several advantages for this type of analysis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Analog Systems for Edge Optimization

Over the past decade, analog computing has the subject of substantial research interest providing a path toward improved computational efficiency in the post-Dennard era. Analog matrix vector multiplication (MVM) accelerators provide a popular approach given the ubiquity of MVM operations in numerous applications. However, historically analog computing systems can struggle with applications requiring high precision due to the inherent susceptibility of these systems to analog non-idealities. Therefore, prior work on analog systems has focused either on applications known to be tolerant of limited precision (e.g., neural network inference), or using expensive techniques to emulate high-precision using many analog MVM operations. In this work, we propose an alternative approach. Motivated by recent advances in inexact nonlinear solvers and optimizers, we explore the potential of co-designing optimization algorithms which can take full advantage of the fundamentally inexact analog MVM operations. To enable these co-designed algorithms we also develop a general mathematical theory of the precision and energy efficiency of analog operations, and a new system architecture for tightly-coupled analog and digital computation. Finally, we examine the applicability of analog computing to a wider class of symmetric positive definite systems and find potential in using analog operations as a sparse approximate inverse preconditioner. With these core innovations, this project provides a path toward effectively implementing optimization algorithms on power-constrained autonomous and semi-autonomous systems.

97 MATHEMATICS AND COMPUTING↗

Dynamic Analysis of a Six-Cable Parallel Robot for Automated Panelized Building Retrofits

Cable-Driven Parallel Robots (CDPRs) are highly suitable for automated panelized building retrofits, thanks to their compact footprint and high payload-to-weight ratio. A common CDPR configuration featuring eight cables, where the anchors form a rectangular prism in front of the building facade, offers a large wrench feasible workspace and good control versatility. However, installing upper anchor points requires additional support structures, such as towers or beams, increasing setup complexity and posing logistical challenges in construction settings. To mitigate these challenges, we propose a six-cable CDPR model specifically designed for automated panelized building retrofits. Although the feasible workspace is limited, our analysis shows that the proposed CDPR adequately covers the critical areas required for panel installation. To validate that the six-cable system can effectively transport the end effector to the desired installation pose, we calculated optimal trajectories based on a constrained dynamic model. The simulation results of the six-cable CDPR demonstrate promising potential for automated panelized building retrofits, effectively balancing simplicity, cost-effectiveness, and functionality.

Liu, Yifang [ORNL] (ORCID:0000000190817417)↗

A Design Method for Low-Pressure Venturi Nozzles

The purpose of this work is to provide empirical design models for low-pressure, subsonic Venturi nozzles. Experimentally validated simulations were used to determine the effect of nozzle geometry and operating conditions on the suction ratio (ratio of suction mass flow rate to motive mass flow rate) of low-pressure, subsonic Venturi nozzles, over a wide range of geometries and operating conditions, through a parametric study. The results of the parametric study were used to develop seven empirical models, each with a different range of applicability or calculating a different indicator of nozzle performance (i.e., suction ratio, momentum ratio, or dynamic pressure ratio), of the Venturi nozzles using a constrained multi-variable global optimization method. Of the seven empirical models, the best models were found to be those for low- (less than one) and high-suction ratios (greater than one), with mean absolute percentage errors of 5% and 18%, respectively. These empirical models provide a design tool for subsonic, low-pressure Venturi nozzles that is more than an order of magnitude more accurate than a governing equation approach or conventional flow head calculations. These newly-developed empirical models can be applied for initial nozzle design when precise suction ratios are required.

O’Hern, Hannah↗

Optimal output feedback control of linear systems in presence of forcing and measurement noise

The problem of obtaining an optimal control law, which is constrained to be a linear feedback of the available measurements, for both continuous and discrete time linear systems subjected to additive white process noise and measurement noise was Necessary conditions are obtained for minimizing a quadratic performance function for both finite and infinite terminal time cases. The feedback gains are constrained to be time invariant for the infinite terminal time cases. For all the cases considered, algorithms are derived for generating sequences of feedback gain matrices which successively improve the performance function. A continuous time numerical example is included for the purpose of demonstration.

Joshi, S. M.↗

Design of optimal partial state feedback controllers for linear systems in stochastic environments

The problem of obtaining an optimal control law, which is constrained to be a feedback of the available measurements, is considered for both continuous and discrete time linear systems subjected to additive white process noise and measurement noise. Necessary conditions are obtained for minimizing a quadratic performance function for both finite and infinite duration cases. The feedback gain matrices are constrained to be constant for the infinite duration cases. For all the cases considered, algorithms are derived for generating sequences of feedback gain matrices which successively improve the performance function. Computational aspects are discussed via application to two continuous time processes, including a helicopter/slung load system subjected to measurement noise and random wind gust input.

Joshi, S. M.↗

The aerodynamic design of an advanced rotor airfoil

An advanced rotor airfoil, designed utilizing supercritical airfoil technology and advanced design and analysis methodology is described. The airfoil was designed subject to stringent aerodynamic design criteria for improving the performance over the entire rotor operating regime. The design criteria are discussed. The design was accomplished using a physical plane, viscous, transonic inverse design procedure, and a constrained function minimization technique for optimizing the airfoil leading edge shape. The aerodynamic performance objectives of the airfoil are discussed.

Blackwell, J. A., Jr.↗

Simulation of time-control procedures for terminal area flow management

Simulations of a terminal area traffic-management system incorporating automated scheduling and time-control (four-dimensional) techniques conducted at NASA Ames Research Center jointly with the Federal Aviation Administration, have shown that efficient procedures can be developed for handling a mix of 4D-equipped and conventionally equipped aircraft. A crucial role in this system is played by an ATC host computer algorithm, referred to as a speed advisory, that allows controllers to maintain accurate time schedules of the conventionally equipped aircraft in the traffic mix. Results are of the most recent simulations in which two important special cases were investigated. First, the effects of a speed advisory on touchdown time scheduling are examined, when unequipped aircraft are constrained to follow fuel-optimized profiles in the near-terminal area, and rescheduling procedures are developed to handle missed approaches of 4D-equipped aircraft. Various performance measures, including controller opinion, are used to evaluate the effectiveness of the procedures.

Alcabin, M.↗

Interplanetary trajectory design for the Mariner Mark II Comet Rendezvous/Asteroid Flyby mission

The primary purpose of the first mission utilizing a Mariner Mark II spacecraft will be to rendezvous with the short-period comet Wild 2 and conduct a proximal examination during the comet's quiescent and active phases. The purpose of the present study is to elucidate, using an accurate dynamic model, some of the characteristics of the interplanetary trajectory that are relevant to the mission design. Optimal transfer trajectories are generated, constrained by the Shuttle/Centaur launch vehicle capability and the total spacecraft mass and performance. Asteroid flyby opportunities are examined, and the effects of selected asteroid encounters on mission performance are discussed.

Myers, M. R.↗

Computational architecture for integrated controls and structures design

To facilitate the development of control structure interaction (CSI) design methodology, a computational architecture for interdisciplinary design of active structures is presented. The emphasis of the computational procedure is to exploit existing sparse matrix structural analysis techniques, in-core data transfer with control synthesis programs, and versatility in the optimization methodology to avoid unnecessary structural or control calculations. The architecture is designed such that all required structure, control and optimization analyses are performed within one program. Hence, the optimization strategy is not unduly constrained by cold starts of existing structural analysis and control synthesis packages.

Belvin, W. Keith↗

Predicting thunderstorm evolution using ground-based lightning detection networks

Lightning measurements acquired principally by a ground-based network of magnetic direction finders are used to diagnose and predict the existence, temporal evolution, and decay of thunderstorms over a wide range of space and time scales extending over four orders of magnitude. The non-linear growth and decay of thunderstorms and their accompanying cloud-to-ground lightning activity is described by the three parameter logistic growth model. The growth rate is shown to be a function of the storm size and duration, and the limiting value of the total lightning activity is related to the available energy in the environment. A new technique is described for removing systematic bearing errors from direction finder data where radar echoes are used to constrain site error correction and optimization (best point estimate) algorithms. A nearest neighbor pattern recognition algorithm is employed to cluster the discrete lightning discharges into storm cells and the advantages and limitations of different clustering strategies for storm identification and tracking are examined.

Goodman, Steven J.↗

Development of homotopy algorithms for fixed-order mixed H2/H(infinity) controller synthesis

A major difficulty associated with H-infinity and mu-synthesis methods is the order of the resulting compensator. Whereas model and/or controller reduction techniques are sometimes applied, performance and robustness properties are not preserved. By directly constraining compensator order during the optimization process, these properties are better preserved, albeit at the expense of computational complexity. This paper presents a novel homotopy algorithm to synthesize fixed-order mixed H2/H-infinity compensators. Numerical results are presented for a four-disk flexible structure to evaluate the efficiency of the algorithm.

Whorton, M.↗

Impact of Surface Emissions to the Zonal Variability of Tropical Tropospheric Ozone and Carbon Monoxide for November 2004

The chemical and dynamical processes governing the zonal variability of tropical tropospheric ozone and carbon monoxide are investigated for November 2004 using satellite observations, in-situ measurements, and chemical transport models in conjunction with inverse-estimated surface emissions. Vertical ozone profile estimates from the Tropospheric Emission Spectrometer (TES) and ozone sonde measurements from the Southern Hemisphere Additional Ozonesondes (SHADOZ) network show the so called zonal 'wave-one' pattern, which is characterized by peak ozone concentrations (70-80 ppb) centered over the Atlantic, as well as elevated concentrations of ozone over Indonesia and Australia (60-70 ppb) in the lower troposphere. Observational evidence from TES CO vertical profiles and Ozone Monitoring Instrument (OMI) NO2 columns point to regional surface emissions as an important contributor to the elevated ozone over Indonesia. This contribution is investigated with the GEOS-Chem chemistry and transport model using surface emission estimates derived from an optimal inverse model, which was constrained by TES and Measurements Of Pollution In The Troposphere (MOPITT) CO profiles (Jones et al., 2007). These a posteriori estimates, which were over a factor of 2 greater than climatological emissions, reduced differences between GEOS-Chem and TES ozone observations by 30-40% and led to changes in GEOS-Chem upper tropospheric ozone of up to 40% over Indonesia. The remaining residual differences can be explained in part by upper tropospheric ozone produced from lightning NOx in the South Atlantic. Furthermore, model simulations from GEOS-Chem indicate that ozone over Indonesian/Australian is more sensitive to changes in surface emissions of NOx than ozone over the tropical Atlantic.

tropical tropospheric ozone↗

Instrumentation and Performance Analysis Plans for the HIFiRE Flight 2 Experiment

Supersonic combustion performance of a bi-component gaseous hydrocarbon fuel mixture is one of the primary aspects under investigation in the HIFiRE Flight 2 experiment. In-flight instrumentation and post-test analyses will be two key elements used to determine the combustion performance. Pre-flight computational fluid dynamics (CFD) analyses provide valuable information that can be used to optimize the placement of a constrained set of wall pressure instrumentation in the experiment. The simulations also allow pre-flight assessments of performance sensitivities leading to estimates of overall uncertainty in the determination of combustion efficiency. Based on the pre-flight CFD results, 128 wall pressure sensors have been located throughout the isolator/combustor flowpath to minimize the error in determining the wall pressure force at Mach 8 flight conditions. Also, sensitivity analyses show that mass capture and combustor exit stream thrust are the two primary contributors to uncertainty in combustion efficiency.

Gruber, Mark↗