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DOE OSTI2025

Enhancing Gaussian Process Surrogates for Optimization and Posterior Approximation via Random Exploration

This paper proposes novel noise-free Bayesian optimization strategies that rely on a random exploration step to enhance the accuracy of Gaussian process surrogate models. The new algorithms retain the ease of implementation of the classical GP-UCB algorithm, but the additional random exploration step accelerates their convergence, nearly achieving the optimal convergence rate. Furthermore, to facilitate Bayesian inference with intractable likelihoods, we propose to utilize optimization iterates for maximum a posteriori estimation to build a Gaussian process surrogate model for the unnormalized log-posterior density. We provide bounds for the Hellinger distance between the true and the approximate posterior distributions in terms of the number of design points. We demonstrate the effectiveness of our Bayesian optimization algorithms in nonconvex benchmark objective functions, in a machine learning hyperparameter tuning problem, and in a black-box engineering design problem. The effectiveness of our posterior approximation approach is demonstrated in two Bayesian inference problems for parameters of dynamical systems.

Bayesian inference↗

DOE OSTI2016

Reconstruction of neuronal input through modeling single-neuron dynamics and computations

Mathematical models provide a mathematical description of neuron activity, which can better understand and quantify neural computations and corresponding biophysical mechanisms evoked by stimulus. In this paper, based on the output spike train evoked by the acupuncture mechanical stimulus, we present two different levels of models to describe the input-output system to achieve the reconstruction of neuronal input. The reconstruction process is divided into two steps: First, considering the neuronal spiking event as a Gamma stochastic process. The scale parameter and the shape parameter of Gamma process are, respectively, defined as two spiking characteristics, which are estimated by a state-space method. Then, leaky integrate-and-fire (LIF) model is used to mimic the response system and the estimated spiking characteristics are transformed into two temporal input parameters of LIF model, through two conversion formulas. We test this reconstruction method by three different groups of simulation data. All three groups of estimates reconstruct input parameters with fairly high accuracy. We then use this reconstruction method to estimate the non-measurable acupuncture input parameters. Results show that under three different frequencies of acupuncture stimulus conditions, estimated input parameters have an obvious difference. The higher the frequency of the acupuncture stimulus is, the higher the accuracy of reconstruction is.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2026

An Ab Initio Molecular Dynamics Study of Key Thermodynamic Input Parameters for Computer Simulation of U-6Nb Solidification

The key to metallic fuel development is the fabrication of uranium metal and alloys into fuel forms. U-Nb alloys are one of the best candidates for a metallic fuel alloy with high-temperature strength sufficient to support the core, acceptable nuclear properties, good fabricability, and compatibility with usable coolant media. Melt processing has been a key component of the metallic fuel cycle, and process models require thermophysical parameters at elevated temperatures, particularly above the melting temperatures, regarding which experimental data are scarce, for accurate simulations and process development. By means of ab initio density-functional theory (DFT) quantum molecular dynamics (QMD), we have calculated the main thermophysical parameters—the density, thermal expansion coefficient, specific heat, thermal conductivity, melting temperature, latent heat of fusion, and viscosity—used in the modeling of the U-6 wt.% Nb alloy casting. The melting temperature of the U-6 wt.% Nb alloy at ambient pressure is obtained by means of QMD simulations using the Z-method. The ambient volume change and latent heat of melting of U-6 wt.% Nb are also derived from QMD simulations in conjunction with analytical fitting for the energy and pressure. The thermal conductivity for the solid U-Nb alloy is calculated from the semi-classical Boltzmann transport equation combined with an estimate of the electron relaxation time obtained from DFT simulations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2019

A New Computational Method for Membrane Compressibility: Bilayer Mechanical Thickness Revisited

Because lipid bilayers can bend and stretch in ways similar to thin elastic sheets, physical models of bilayer deformation have utilized mechanical constants such as the moduli for bending rigidity (κ C ) and area compressibility (K A ). However, the use of these models to quantify the energetics of membrane deformation associated with protein-membrane interactions, and the membrane response to stress is often hampered by the shortage of experimental data suitable for the estimation of the mechanical constants of various lipid mixtures. Although computational tools such as molecular dynamics simulations can provide alternative means to estimate K A values, current approaches suffer significant technical limitations. Here, in this study, we present a novel, to our knowledge, computational framework that allows for a direct estimation of K A values for individual bilayer leaflets. The theory is based on the concept of elasticity and derives K A from real-space analysis of local thickness fluctuations sampled in molecular dynamics simulations. We explore and validate the model on a large set of single and multicomponent bilayers of different lipid compositions and sizes, simulated at different temperatures. The calculated bilayer compressibility moduli agree with values estimated previously from experiments and those obtained from a standard computational method based on a series of constrained tension simulations. We further validate our framework in a comparison with an existing polymer brush model and confirm the polymer brush model’s predicted linear relationship with proportionality coefficient of 24, using elastic parameters calculated from the simulation trajectories. The robustness of the results that emerge from the method allows us to revisit the origins of the bilayer mechanical (compressible) thickness and in particular its dependence on acyl-chain unsaturation and the presence of cholesterol.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Enhancement of detachment control with simplified real-time modelling on the KSTAR tokamak

Abstract Detachment control based on ion saturation current I sat measurements from Langmuir probes (LPs) is implemented in the KSTAR tokamak and shown to be capable of following dynamic and constant target trajectories with good accuracy, in H-mode, by moderating the flow rate of nitrogen or deuterium. I sat controllers normalize I sat in order to form attachment fraction ( A frac ) as their control parameter. The KSTAR implementation of A frac control differs from previous work in that it continuously calculates a model for attached I sat and uses that as the denominator in A frac , whereas prior implementations either record peak I sat at rollover as they pass it or take estimated I s a t , r o l l o v e r as a manual input prior to the shot. The KSTAR controller therefore does not need to keep track of rollover status and keep separate targets for pre- and post-rollover states, and it can automatically adapt to changes in scenario at any time. It is also less vulnerable to noise as it will not lock in an outlier as a rollover point.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2013

Effective perfect fluids in cosmology

We describe the cosmological dynamics of perfect fluids within the framework of effective field theories. The effective action is a derivative expansion whose terms are selected by the symmetry requirements on the relevant long-distance degrees of freedom, which are identified with comoving coordinates. The perfect fluid is defined by requiring invariance of the action under internal volume-preserving diffeomorphisms and general covariance. At lowest order in derivatives, the dynamics is encoded in a single function of the entropy density that characterizes the properties of the fluid, such as the equation of state and the speed of sound. This framework allows a neat simultaneous description of fluid and metric perturbations. Longitudinal fluid perturbations are closely related to the adiabatic modes, while the transverse modes mix with vector metric perturbations as a consequence of vorticity conservation. This formalism features a large flexibility which can be of practical use for higher order perturbation theory and cosmological parameter estimation.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Predictions of Cell-to-Cell Propagation and Vent Gas Production in the Thermal Runaway of Lithium-Ion Battery Stacks

This work presents the thermal runaway propagation model LIM1TR (Lithium-ion Modeling with 1-D Thermal Runaway) as an efficient tool to predict different cell-to-cell thermal runaway propagation scenarios. Here, we explored the vent gas volume production and reaction duration highlighting the relationship between these parameters and thermal runaway propagation due to convection by the vented gases. Two metrics based on gas production rate and heating rate are utilized as good indicators of the start and end of thermal runaway. LIM1TR results are compared with and validated by experiments from the literature for single-cell and multicell array experiments of 5 Ah and 10 Ah cells. By accounting for intraparticle diffusion of reacting species in the electrodes, we were able to capture the general dynamics of thermal runaway propagation and estimate acceptable reaction durations compared with the experimental values. Simulation results further demonstrated that varying heating modes lead to distinct reaction durations, consistent with experimental observations. Vent gas volume predictions indicate the need to consider both full and partial oxidation of the electrolyte. The outcomes of this work are building blocks for further investigations of module-to-module propagation by vented gases through convective heat transfer.

25 ENERGY STORAGE↗

DOE OSTI2012

Proton beam lifetime increase with 10- and 12-pole correctors in the Relativistic Heavy Ion Collider

10- and 12-pole correctors were installed in a number of machines and are also considered for future machines. In the Relativistic Heavy Ion Collider (RHIC) 10- and 12-pole correctors exist to correct for the detrimental effects of magnetic field errors in the interaction region magnets. These field errors in conjunction with beam-beam effects and parameter modulations dominate the beam lifetime in polarized proton operation. During the 2009 polarized proton run 10- and 12-pole correctors were set through an iterative procedure, and used for the first time operationally in one of the beams. We report on the procedure to set these high-order multipole correctors, compare the found values with calculated ones, estimate the effect of the new corrector settings on the integrated luminosity, and calculate the effect of both the calculated and experimentally found corrector strengths on the dynamic aperture.

43 PARTICLE ACCELERATORS↗

DOE OSTI2012

Proton beam lifetime increase with 10- and 12-pole correctors in the Relativistic Heavy Ion Collider

43 PARTICLE ACCELERATORS↗

DOE OSTI2020

Validation of the Community Land Model Version 5 over the Contiguous United States (CONUS) using in-situ and remote sensing datasets

The Community Land Model (CLM) is an effective tool to simulate the biophysical and biogeochemical processes and their interactions with the atmosphere. Although CLM Version 5 (CLM5) constitutes various updates in these processes, its performance in simulating energy, water and carbon cycles over the Contiguous United States (CONUS) at scales which land surface changes and hydrometeorological and hydroclimatological applications are more locally relevant is yet to be assessed. In this study, we conducted three simulations at 0.125? during 1979-2018 over the CONUS using different configurations of CLM, namely CLM5-biogeochemistry (CLM5BGC), CLM4.5BGC, and CLM5-satellite phenology (CLM5SP). We validated and compared their simulations against multiple remote-sensed and in-situ datasets. Overall, the parametric and structural updates (e.g., carbon cost for nitrogen uptake, variable soil thickness, dry surface layer) in CLM5 improve its ability in capturing terrestrial biogeochemical dynamics. The low evapotranspiration in CLM5BGC is associated with biases in simulating vegetation phenological characteristics rather than soil water limitations. The mismatch between CLM5BGC-simulated peak leaf area index and reference data can be attributed to CLM5BGC's inability in simulating phenology of trees and grasses. The differences between CLM-simulated irrigation and reference estimates can be attributed to differences between processes represented in models and in reality, and uncertainties in input and validation datasets. Evaluation against observations at small catchments suggest that hydrologic parameters needed to be calibrated to improve simulations of runoff, especially subsurface runoff. Additional efforts are needed to incorporate spatially-distributed plant phenology and physiology parameters and regional-specific agricultural management practices (e.g., planting, harvest).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2013

GALAXY HALO TRUNCATION AND GIANT ARC SURFACE BRIGHTNESS RECONSTRUCTION IN THE CLUSTER MACSJ1206.2-0847

In this work, we analyze the mass distribution of MACSJ1206.2-0847, particularly focusing on the halo properties of its cluster members. The cluster appears relaxed in its X-ray emission, but has a significant amount of intracluster light that is not centrally concentrated, suggesting that galaxy-scale interactions are still ongoing despite the overall relaxed state. The cluster lenses 12 background galaxies into multiple images and one galaxy at z = 1.033 into a giant arc and its counterimage. The multiple image positions and the surface brightness (SFB) distribution of the arc, which is bent around several cluster members, are sensitive to the cluster galaxy halo properties. We model the cluster mass distribution with a Navarro-Frenk-White profile and the galaxy halos with two parameters for the mass normalization and the extent of a reference halo assuming scalings with their observed near-infrared light. We match the multiple image positions at an rms level of 0.''85 and can reconstruct the SFB distribution of the arc in several filters to a remarkable accuracy based on this cluster model. The length scale where the enclosed galaxy halo mass is best constrained is about 5 effective radii-a scale in between those accessible to dynamical and field strong-lensing mass estimates on the one hand and galaxy-galaxy weak-lensing results on the other hand. The velocity dispersion and halo size of a galaxy with m{sub 160W,AB} = 19.2 and M{sub B,Vega} = -20.7 are {sigma} = 150 km s{sup -1} and r Almost-Equal-To 26 {+-} 6 kpc, respectively, indicating that the halos of the cluster galaxies are tidally stripped. We also reconstruct the unlensed source, which is smaller by a factor of {approx}5.8 in area, demonstrating the increase in morphological information due to lensing. We conclude that this galaxy likely has star-forming spiral arms with a red (older) central component.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2015

Distance-Based Configurational Entropy of Proteins from Molecular Dynamics Simulations

Estimation of configurational entropy from molecular dynamics trajectories is a difficult task which is often performed using quasi-harmonic or histogram analysis. An entirely different approach, proposed recently, estimates local density distribution around each conformational sample by measuring the distance from its nearest neighbors. In this work we show this theoretically well grounded the method can be easily applied to estimate the entropy from conformational sampling. We consider a set of systems that are representative of important biomolecular processes. In particular: i. reference entropies for amino acids in unfolded proteins are obtained from a database of residues not participating in secondary structure elements; ii. the conformational entropy of folding of β 2-microglobulin is computed from molecular dynamics simulations using reference entropies for the unfolded state; iii. backbone conformational entropy is computed from molecular dynamics simulations of four different states of the EPAC protein and compared with order parameters (often used as a measure of entropy); iv. the conformational and rototranslational entropy of binding is computed from simulations of 20 tripeptides bound to the peptide binding protein OppA and of β 2-microglobulin bound to a citrate coated gold surface. This work shows the potential of the method in the most representative biological processes involving proteins, and provides a valuable alternative, principally in the shown cases, where other approaches are problematic.

Science & Technology - Other Topics↗

DOE OSTI2020

Influence of Vegetation Canopy Architecture on Dynamics of Spatiotemporal Light Distribution and its Effect on Land-Biosphere-Atmosphere Fluxes of Energy, Carbon, and Water

The dynamic spatiotemporal distribution of light and micro climatic variables (wind speed, atmospheric CO 2 concentration, humidity, pressure, and air temperature) within the plant canopy as determined by the canopy architecture play a critical role in land-biosphere-atmosphere (LBA) photosynthetic carbon uptake, transpiratory water loss and energy partitioning. Vegetation models that include effects of sun and shade flecks, leaf temperature and energy balance partitioning between sensible and latent heat fluxes, and reduced turbulent mixing in dense vegetation canopies can accurately predict canopy performance, particularly its shaded leaves, which can constitute 80% of leaf area and contribute up to 50% of carbon update and 65% of water loss. However, current vegetation models with their bulk characterization of shaded leaves poorly represent the complex three dimensional (3D) canopy architecture are insufficient to capture the spatiotemporal dynamics of shaded leaves. Here, we propose to employ an x-ray computed tomography (XCT) imaging technique in combination with an automated, high throughput, image processing pipeline (3DArch, to be developed) to obtain an explicit 3D triangulated surface mesh of a plant canopy (Fig 1). 3DArch would provide a much needed technological jump in 3D LBA modeling where computer generated artificial 3D models suffer from lack of high resolution detailed canopy architecture parameters. The 3D canopy surface mesh output from 3DArch is coupled with an explicit 3D forward ray tracing model (fastTracer) to obtain a high resolution representation of the dynamic spatiotemporal light environment within the canopy over the course of a day (Fig 1). The results from the light attenuation model are then coupled with a process based multi-scale bio-physical canopy and leaf model of photosynthesis (PlantGro) to get fluxes of carbon, water and energy at the leaf and canopy scale, in addition to estimating whole plant carbon uptake, and water loss. Our proposed model framework would be the first of its kind to provide a breakthrough capability in the field of process-based plant modeling that bridges the key technological gap in shaded leaf modeling through explicit representation of 3D canopy architecture. Computer generated artificial 3D model canopy simulations on grasses show that the canopy light distribution does not follow an exponential behavior as assumed in most 1D vegetation models, but rather exhibits a heterogeneous behavior, with a small but significant portion of interior canopy leaves experiencing peak light levels due to sun flecks while the rest of the canopy receives substantially lower light levels. These results indicate a bias in traditional models that overestimates shaded leaf contribution towards whole canopy photosynthesis by up to 15% and underestimate transpiration by up to 12% with an associated increase in sensible heat fluxes since photosynthesis, transpiration and energy partitioning are tightly coupled processes. However, these test results need to be validated using the 3D architecture obtained from a real plant imaged in 3D using 3DArch, rather than an artificial model plant. Our proposed model framework would allow us to identify inefficiencies in canopy light distribution and prescribe optimal canopy architectures (leaf optical properties, leaf area, leaf angles, row spacing, planting density, etc.) to traditional and genetic engineering based crop breeders, for maximizing target functions such as light use efficiency, water use efficiency, drought tolerance, crop yield, crop resilience etc., with important applications in biofuel crops such as sorghum, and switchgrass. Our model can also be applied for designing optimal canopy architecture that increase surface albedo as a mitigation strategy for global warming and projections of crop yield for future food and water security under climate change.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2017

The Formation and Physical Origin of Highly Ionized Cooling Gas

We present a simple model that explains the origin of warm, diffuse gas seen primarily as highly ionized absorption-line systems in the spectra of background sources. We predict the observed column densities of several highly ionized transitions such as O vi, O vii, Ne viii, N v, and Mg x, and we present a unified comparison of the model predictions with absorption lines seen in the Milky Way disk, Milky Way halo, starburst galaxies, the circumgalactic medium, and the intergalactic medium at low and high redshifts. We show that diffuse gas seen in such diverse environments can be simultaneously explained by a simple model of radiatively cooling gas. We show that most such absorption-line systems are consistent with being collisionally ionized, and we estimate the maximum-likelihood temperature of the gas in each observation. This model satisfactorily explains why O vi is regularly observed around star-forming low- z L* galaxies, and why N v is rarely seen around the same galaxies. We further present some consequences of this model in quantifying the dynamics of the cooling gas around galaxies and predict the shock velocities associated with such flows. A unique strength of this model is that while it has only one free (but physically well-constrained) parameter, it nevertheless successfully reproduces the available data on O vi absorbers in the interstellar, circumgalactic, intragroup, and intergalactic media, as well as the available data on other absorption lines from highly ionized species.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Feasibility of Vascular Parameter Estimation for Assessing Hypertensive Pregnancy Disorders

Abstract Hypertensive pregnancy disorders (HPDs), such as pre-eclampsia, are leading sources of both maternal and fetal morbidity in pregnancy. Noninvasive imaging, such as ultrasound (US) and magnetic resonance imaging (MRI), is an important tool for predicting and monitoring these high risk pregnancies. While imaging can measure hemodynamic parameters, such as uterine artery pulsatility and resistivity indices (PI and RI), the interpretation of such metrics for disease assessment relies on ad hoc standards, which provide limited insight to the physical mechanisms underlying the emergence of hypertensive pregnancy disorders. To provide meaningful interpretation of measured hemodynamic data in patients, advances in computational fluid dynamics can be brought to bear. In this work, we develop a patient-specific computational framework that combines Bayesian inference with a reduced-order fluid dynamics model to infer parameters, such as vascular resistance, compliance, and vessel cross-sectional area, known to be related to the development of hypertension. The proposed framework enables the prediction of hemodynamic quantities of interest, such as pressure and velocity, directly from sparse and noisy MRI measurements. We illustrate the effectiveness of this approach in two systemic arterial network geometries: an aorta with branching carotid artery and a maternal pelvic arterial network. For both cases, the model can reconstruct the provided measurements and infer parameters of interest. In the case of the maternal pelvic arteries, the model can make a distinction between the pregnancies destined to develop hypertension and those that remain normotensive, expressed through the value range of the predicted absolute pressure.

Biophysics↗

DOE OSTI2021

Probing Quantum Speed Limits with Ultracold Gases

Here, quantum speed limits (QSLs) rule the minimum time for a quantum state to evolve into a distinguishable state in an arbitrary physical process. These fundamental results constrain a notion of distance traveled by the quantum state, known as the Bures angle, in terms of the speed of evolution set by nonadiabatic energy fluctuations. I theoretically propose how to measure QSLs in an ultracold quantum gas confined in a time-dependent harmonic trap. In this highly-dimensional system of continuous variables, quantum tomography is prohibited. Yet, QSLs can be probed whenever the dynamics is self-similar by measuring as a function of time the cloud size of the ultracold gas. This makes it possible to determine the Bures angle and energy fluctuations, as I discuss for various ultracold atomic systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

SIF-based GPP modeling for evergreen forests considering the seasonal variation in maximum photochemical efficiency

Solar-induced chlorophyll fluorescence (SIF) has shown great potential in estimating gross primary production (GPP). However, their quantitative relationship is not invariant, which undermines the reliability of empirical SIF-based GPP estimation at fine spatiotemporal scales, especially under extreme conditions. In this study, we developed a parsimonious mechanistic model for SIF-based GPP estimation in evergreen needle forests (ENF) by employing the Mechanistic Light Response framework and Eco-Evolutionary theory to describe the light and dark reactions during photosynthesis, respectively. Specifically, we found that considering the seasonal variation in a key parameter of the MLR framework, the maximum photochemical efficiency of photosystem II (Φ PSIImax ), can avoid the GPP overestimation in winter and early spring due to the relatively low environmental sensitivity of SIF. Compared to the estimates from other benchmark models, our GPP estimates were closer to the 1: 1 line and had higher accuracy (average R 2 = 0.86, RMSE=1.99 μmol m -2 s -1 ) across sites. Furthermore, the changes in the relationship between SIF and J (refers to the electron transport rate) contribute a lot to the dynamic SIF–GPP relationship in this study, while the J–GPP relationship is less variant when the temperature drops. Further, the seasonal variation in the SIF–J relationship, especially the reduction in its slope at low temperatures, is found largely explained by the Φ PSIImax . These results indicate the importance of the uncertainty caused by the variation in the SIF–J relationship for SIF-based GPP estimation, and the consideration of changes in Φ PSIImax under extreme conditions (such as severe winter in this study) is crucial for the improvement of GPP estimation via SIF.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Onset of cavitation and vapor bubble development over hydrophilic and hydrophobic surfaces

Cavitation, the formation of vapor bubbles as the liquid pressure is reduced below the saturated vapor pressure, often requires a substantial negative relative pressure in a pure liquid. Classical nucleation theory (CNT) provides an estimate for the rate of cavitation but there is often a disconnect between the predictions at the molecular scale compared to observations at the macroscale. We report on mesoscale simulations of cavitation based on many-body dissipative particle dynamics (mDPD), a coarse-grained molecular dynamics (MD), which bridges the two scales. A liquid layer is confined between smooth planar walls at a constant temperature, while the pressure is reduced slowly by expanding the wall-bounded domain. The wetting properties of the liquid are determined by the parameters of the interaction potentials. With hydrophilic walls, homogeneous nucleation is observed in the liquid bulk. As a bubble forms and grows, it creates a strong pressure pulse and oscillations that cause other bubbles that may have formed slightly later to collapse. For a nearly neutral wall with a contact angle close to 90 ° , heterogeneous nucleation occurs at the walls at a smaller negative pressure and generates weaker pressure oscillations. With hydrophobic walls or seed particles, heterogeneous nucleation readily occurs, where fluctuations and the merger of transient surface bubbles are significant.

Science & Technology - Other Topics↗