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Results for “HOLO methods”

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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14 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

A stable 1D multigroup high-order low-order method

The high-order low-order (HOLO) method is a recently developed moment-based acceleration scheme for solving time-dependent thermal radiative transfer problems, and has been shown to exhibit orders of magnitude speedups over traditional time-stepping schemes. However, a linear stability analysis by Haut et al. (2015 Haut, T. S., Lowrie, R. B., Park, H., Rauenzahn, R. M., Wollaber, A. B. (2015). A linear stability analysis of the multigroup High-Order Low-Order (HOLO) method. In Proceedings of the Joint International Conference on Mathematics and Computation (M&C), Supercomputing in Nuclear Applications (SNA) and the Monte Carlo (MC) Method; Nashville, TN, April 19–23, 2015. American Nuclear Society.) revealed that the current formulation of the multigroup HOLO method was unstable in certain parameter regions. Since then, we have replaced the intensity-weighted opacity in the first angular moment equation of the low-order (LO) system with the Rosseland opacity. Furthermore, this results in a modified HOLO method (HOLO-R) that is significantly more stable.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

On High-Order/Low-Order and Micro-Macro Methods for Implicit Time-Stepping of the BGK Model

In this paper, a high-order/low-order (HOLO) method is combined with a micro-macro (MM) decomposition to accelerate iterative solvers in fully implicit time-stepping of the Bhatnagar–Gross–Krook (BGK) equation for gas dynamics. The MM formulation represents a kinetic distribution as the sum of a local Maxwellian and a perturbation. In highly collisional regimes, the perturbation away from initial and boundary layers is small and can be compressed to reduce the overall storage cost of the distribution. The convergence behavior of the MM methods, the usual HOLO method, and the standard source iteration method is analyzed on a linear BGK model. Both the HOLO and MM methods are implemented using a discontinuous Galerkin (DG) discretization in phase space, which naturally preserves the consistency between high- and low-order models required by the HOLO approach. Furthermore, the accuracy and performance of these methods are compared on the Sod shock tube problem and a sudden wall heating boundary layer problem. Overall, the results demonstrate the robustness of the MM and HOLO approaches and illustrate the compression benefits enabled by the MM formulation when the kinetic distribution is near equilibrium.

BGK model↗
DOE OSTI2014

Applying Nonlinear Diffusion Acceleration to Fixed-Source Problems with Anisotropic Scattering - Paper 15

Work over the last several years has demonstrated the impressive performance gains that can be attained by using Moment-Based Acceleration (MBA), or High-Order/Low-Order (HOLO), methods in a variety of transport applications. In the field of neutronics, Nonlinear Diffusion Acceleration (NDA) has been used to accelerate the solution to the fixed-source problem and the k-eigenvalue problem. These methods efficiently move a major portion of the computational work out of the full phase-space (high-order (HO)) domain into a reduced phase-space (low-order (LO)) setting. In previous implementations, NDA has only been applied to isotropic scattering problems. In this paper, we will extend this methodology to anisotropic scattering. This initial work on anisotropic scattering will focus on the 1-D multi-group neutron transport equation. This summary focuses on a fixed-source problem, but the extension to criticality problems is straight-forward via NDA-NCA. Within this paper, we have described a method for extending Nonlinear Diffusion Acceleration to solve problems with anisotropic scattering. We demonstrated that a consistent low-order system, resembling the low-order system from, could be constructed. We demonstrated that the NDA method performed exceptionally in the presence of anisotropic scattering. NDA reduced the number of iterations required to meet the convergence tolerance by a factor of 500 over source iteration for a one fixed-source problem and by 3.5-50 x for the Henyey-Greenstein problems. This method is equally well-suited for eigenvalue problems. The NDA method allows us to transition the eigenvalue iteration to the low-order domain.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2015

High-Order/Low-Order methods for ocean modeling

We examine a High Order/Low Order (HOLO) approach for a z-level ocean model and show that the traditional semi-implicit and split-explicit methods, as well as a recent preconditioning strategy, can easily be cast in the framework of HOLO methods. The HOLO formulation admits an implicit-explicit method that is algorithmically scalable and second-order accurate, allowing timesteps much larger than the barotropic time scale. We demonstrate how HOLO approaches, in particular the implicit-explicit method, can provide a solid route for ocean simulation to heterogeneous computing and exascale environments.

16 TIDAL AND WAVE POWER↗
DOE OSTI2019

A multi-dimensional, moment-accelerated deterministic particle method for time-dependent, multi-frequency thermal radiative transfer problems

Thermal Radiative Transfer (TRT) is the dominant energy transfer mechanism in high-energy density physics with applications in inertial confinement fusion and astrophysics. The stiff interactions between the material and radiation fields make TRT problems challenging to model. In this study, we propose a multi-dimensional extension of the deterministic particle (DP) method. The DP method combines aspects from both particle and deterministic methods. If the emission source is known a priori, and no physical scattering is present, the intensity of a particle can be integrated analytically. This introduces no statistical noise compared to Monte-Carlo methods, while maintaining the flexibility of particle methods. The method is closely related to the popular method of long characteristics. The combination of the DP-method with a discretely-consistent, nonlinear, gray low-order system enables an efficient solution algorithm for multi-frequency TRT problems. Here, we demonstrate with numerical examples that the use of a linear-source approximation based on spatial moments improves the behavior of our method in the thick diffusion limit significantly.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

A comparison of acceleration methods for solving the neutron transport k-eigenvalue problem

Over the past several years a number of papers have been written describing modern techniques for numerically computing the dominant eigenvalue of the neutron transport criticality problem. These methods fall into two distinct categories. The first category of methods rewrite the multi-group k-eigenvalue problem as a nonlinear system of equations and solve the resulting system using either a Jacobian-Free Newton–Krylov (JFNK) method or Nonlinear Krylov Acceleration (NKA), a variant of Anderson Acceleration. These methods are generally successful in significantly reducing the number of transport sweeps required to compute the dominant eigenvalue. The second category of methods utilize Moment-Based Acceleration (or High-Order/Low-Order (HOLO) Acceleration). These methods solve a sequence of modified diffusion eigenvalue problems whose solutions converge to the solution of the original transport eigenvalue problem. This second class of methods is, in our experience, always superior to the first, as most of the computational work is eliminated by the acceleration from the LO diffusion system. In this paper, we review each of these methods. Our computational results support our claim that the choice of which nonlinear solver to use, JFNK or NKA, should be secondary. The primary computational savings result from the implementation of a HOLO algorithm. We display computational results for a series of challenging multi-dimensional test problems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Ligand-Binding-Site Refinement to Generate Reliable Holo Protein Structure Conformations from Apo Structures

The first important step in a structure-based virtual screening is the judicious selection of a receptor protein. In cases where the holo protein receptor structure is unavailable, significant reduction in virtual screening performance has been reported. In this work, we present a robust method to generate reliable holo protein structure conformations from apo structures using molecular dynamics (MD) simulation with restraints derived from holo structure binding-site templates. We perform benchmark tests on two different datasets: 40 structures from a directory of useful decoy-enhanced (DUD-E) and 84 structures from the Gunasekaran dataset. Our results show successful refinement of apo binding-site structures toward holo conformations in 82% of the test cases. In addition, virtual screening performance of 40 DUD-E structures is significantly improved using our MD-refined structures as receptors with an average enrichment factor (EF), an EF1% value of 6.2 compared to apo structures with 3.5. Docking of native ligands to the refined structures shows an average ligand root mean square deviation (RMSD) of 1.97 Å (DUD-E dataset and Gunasekaran dataset) relative to ligands in the holo crystal structures, which is comparable to the self-docking (i.e., docking of the native ligand back to its crystal structure receptor) average, 1.34 Å (DUD-E dataset) and 1.36 Å (Gunasekaran dataset). On the other hand, docking to the apo structures yields an average ligand RMSD of 3.65 Å (DUD-E) and 2.90 Å (Gunasekaran). These results indicate that our method is robust and can be useful to improve virtual screening performance of apo structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Assessing the potential of deep learning for protein–ligand docking

The effects of ligand binding on protein structures and their in vivo functions carry numerous implications for modern biomedical research and biotechnology development efforts such as drug discovery. Although several deep learning (DL) methods and benchmarks designed for protein–ligand docking have recently been introduced, so far no previous works have systematically studied the behaviour of the latest docking and structure prediction methods within the broadly applicable context of: (1) using predicted (apo) protein structures for docking (for example, for applicability to new proteins); (2) binding multiple (cofactor) ligands concurrently to a given target protein (for example, for enzyme design); and (3) having no previous knowledge of binding pockets (for example, for generalization to unknown pockets). To enable a deeper understanding of the real-world utility of docking methods, we introduce PoseBench, a comprehensive benchmark for broadly applicable protein–ligand docking. PoseBench enables researchers to rigorously and systematically evaluate DL methods for apo-to-holo protein–ligand docking and protein–ligand structure prediction using both primary ligand and multiligand benchmark datasets, the latter of which we introduce to the DL community. Empirically, using PoseBench, we find that: (1) DL cofolding methods generally outperform comparable conventional and DL docking baseline algorithms, but popular methods such as AlphaFold 3 are still challenged by prediction targets with new protein–ligand binding poses; (2) certain DL cofolding methods are highly sensitive to their input multiple sequence alignments, whereas others are not; and (3) DL methods struggle to strike a balance between structural accuracy and chemical specificity when predicting new or multiligand protein targets.

Morehead, Alex [Lawrence Berkeley National Laborat↗
DOE OSTI2015

Crystallization and x-ray diffraction analysis of a putative bacterial class I labdane-related diterpene synthase [Crysallization and preliminary x-ray diffraction analysis of a bacterial class I labdane-related diterpene synthase]

Here, labdane-related diterpenoids are natural products with potential pharmaceutical applications that are rarely found in bacteria. Here, a putative class I labdane-related diterpene synthase (LrdC) identified by genome mining in a streptomycete was successfully crystallized using the microbatch method. Crystals of the LrdC enzyme were obtained in a holo form with its natural cofactor Mg 2+ (LrdC-Mg 2+ ) and in complex with inorganic pyrophosphate (PP i ) (LrdC-Mg 2+ –PP i ). Crystals of native LrdC-Mg 2+ diffracted to 2.50 Å resolution and belonged to the trigonal space group P3 2 21, with unit-cell parameters a = b = 107.1, c = 89.2 Å. Crystals of the LrdC-Mg 2+ –PP i complex grown in the same conditions as the native enzyme with PEG 8000 diffracted to 2.36 Å resolution and also belonged to the trigonal space group P3 2 21. Crystals of the LrdC-Mg 2+ –PP i complex grown in a second crystallization condition with PEG 3350 diffracted to 2.57 Å resolution and belonged to the monoclinic space group P2 1 , with unit-cell parameters a = 49.9, b = 104.1, c = 66.5 Å, β = 111.4°. The structure was determined by the single-wavelength anomalous dispersion (SAD) technique using the osmium signal from a potassium hexachloroosmate (IV) derivative.

36 MATERIALS SCIENCE↗
DOE OSTI2019

A multigroup moment-accelerated deterministic particle solver for 1-D time-dependent thermal radiative transfer problems

We introduce an efficient, robust, Lagrangian (characteristic-based) transport solver for 1-D time-dependent thermal radiative transfer (TRT) applications within the context of a moment-accelerated (High-Order/Low-Order, HOLO) algorithm. This novel transport algorithm inherits the best features of both particle methods (e.g., time accuracy, phase-space adaptivity, positivity) and deterministic, grid-based methods (e.g., no stochastic noise). Particles are adapted by the method of characteristics, with a time-dependent weight that accounts for stiff absorption and reemission process self-consistently. As a result, this approach is able to obtain accurate results while employing large time steps and a moderate number of particles (compared to Implicit Monte Carlo).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2013

DBSI: DNA-binding site identifier

In this study, we present the DNA-Binding Site Identifier (DBSI), a new structure-based method for predicting protein interaction sites for DNA binding. DBSI was trained and validated on a data set of 263 proteins (TRAIN-263), tested on an independent set of protein-DNA complexes (TEST-206) and data sets of 29 unbound (APO-29) and 30 bound (HOLO-30) protein structures distinct from the training data. We computed 480 candidate features for identifying protein residues that bind DNA, including new features that capture the electrostatic microenvironment within shells near the protein surface. Our iterative feature selection process identified features important in other models, as well as features unique to the DBSI model, such as a banded electrostatic feature with spatial separation comparable with the canonical width of the DNA minor groove. Validations and comparisons with established methods using a range of performance metrics clearly demonstrate the predictive advantage of DBSI, and its comparable performance on unbound (APO-29) and bound (HOLO-30) conformations demonstrates robustness to binding-induced protein conformational changes. Finally, we offer our feature data table to others for integration into their own models or for testing improved feature selection and model training strategies based on DBSI.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

DNA Origami Incorporated into Solid-State Nanopores Enables Enhanced Sensitivity for Precise Analysis of Protein Translocations

The rapidly advancing field of nanotechnology is driving the development of precise sensing methods at the nanoscale, with solid-state nanopores emerging as promising tools for biomolecular sensing. Here, this study investigates the increased sensitivity of solid-state nanopores achieved by integrating DNA origami structures, leading to the improved analysis of protein translocations. Using holo human serum transferrin (holo-hSTf) as a model protein, we compared hybrid nanopores incorporating DNA origami with open solid-state nanopores. Results show a significant enhancement in holo-hSTf detection sensitivity with DNA origami integration, suggesting a unique role of DNA interactions beyond confinement. This approach holds potential for ultrasensitive protein detection in biosensing applications, offering advancements in biomedical research and diagnostic tool development for diseases with low-abundance protein biomarkers. Further exploration of origami designs and nanopore configurations promises even greater sensitivity and versatility in the detection of a wider range of proteins, paving the way for advanced biosensing technologies.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2014

Factors correlating with significant differences between X-ray structures of myoglobin

Conformational differences between myoglobin structures are studied. Most structural differences in whale myoglobin beyond the uncertainty threshold can be correlated with a few specific structural factors. There are always exceptions and a search for additional factors is needed. The results might have serious implications for biological insights from conformational differences. Validation of general ideas about the origins of conformational differences in proteins is critical in order to arrive at meaningful functional insights. Here, principal component analysis (PCA) and distance difference matrices are used to validate some such ideas about the conformational differences between 291 myoglobin structures from sperm whale, horse and pig. Almost all of the horse and pig structures form compact PCA clusters with only minor coordinate differences and outliers that are easily explained. The 222 whale structures form a few dense clusters with multiple outliers. A few whale outliers with a prominent distortion of the GH loop are very similar to the cluster of horse structures, which all have a similar GH-loop distortion apparently owing to intermolecular crystal lattice hydrogen bonds to the GH loop from residues near the distal histidine His64. The variations of the GH-loop coordinates in the whale structures are likely to be owing to the observed alternative intermolecular crystal lattice bond, with the change to the GH loop distorting bonds correlated with the binding of specific ‘unusual’ ligands. Such an alternative intermolecular bond is not observed in horse myoglobins, obliterating any correlation with the ligands. Intermolecular bonds do not usually cause significant coordinate differences and cannot be validated as their universal cause. Most of the native-like whale myoglobin structure outliers can be correlated with a few specific factors. However, these factors do not always lead to coordinate differences beyond the previously determined uncertainty thresholds. The binding of unusual ligands by myoglobin, leading to crystal-induced distortions, suggests that some of the conformational differences between the apo and holo structures might not be ‘functionally important’ but rather artifacts caused by the binding of ‘unusual’ substrate analogs. The causes of P6 symmetry in myoglobin crystals and the relationship between crystal and solution structures are also discussed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Mechanistic Studies of a Primitive Homolog of Nitrogenase Involved in Coenzyme F430 Biosynthesis

Methyl-coenzyme M reductase (MCR) is the key enzyme in the biological formation and anaerobic oxidation of methane (AOM). Methane is a potent greenhouse gas and the major component of natural gas. Given the abundance of natural gas reserves in remote areas, there is great current interest in a scalable bio-based process for the conversion of methane to liquid fuel or other high-value commodity chemicals. MCR holds much promise for use in such a methane bioconversion strategy. However, MCR cannot currently be produced in an active form in a heterologous host, due in large part to the lack of genetic and biochemical information about the production of holo MCR. In an effort to overcome this deficiency, our laboratory elucidated the biosynthetic pathway of the unique nickel-containing coenzyme of MCR, F430. The key step in coenzyme F430 biosynthesis (Cfb) was found to involve an unprecedented reductive cyclization reaction that converts Ni-sirohydrochlorin a , c -diamide to 15,17 3 -seco-F430-17 3 -acid. This remarkable transformation, which involves a 6-electron reduction of the isobacteriochlorin ring system, cyclization of the c -acetamide side chain to form a γ-lactam ring, and the formation of 7 stereocenters, is catalyzed by a primitive homolog of nitrogenase (CfbCD). Nitrogenase is a two-component metalloenzyme that catalyzes the ATP-dependent reduction of dinitrogen to ammonia (nitrogen fixation). Homologs of nitrogenase are also involved in the biosynthesis of the photosynthetic pigments chlorophyll and bacteriochlorophyll. Phylogenetic analysis of the CfbCD complex suggests that it is representative of a more ancient lineage of the nitrogenase superfamily, and a thorough investigation of its structure and function is likely to shed light on the mechanisms and evolution of these important metalloenzymes that catalyze multi-electron redox reactions. Moreover, a detailed understanding of the mechanism of the CfbCD complex may aid in the development of specific inhibitors to help reduce natural greenhouse gas emissions and can be exploited for the heterologous production of MCR for methane bioconversion. Towards these goals, the following Specific Aims will be pursued to determine the: 1) Identity of the CfbCD reaction product. The exact reaction catalyzed by CfbCD, including the number of electrons transferred and whether it involves enzymatic cyclization, is unclear. Several approaches, including reaction stoichiometry measurements, spectroelectrochemistry, and magnetic resonance spectroscopy will be applied to elucidate the structure of the reaction product and establish whether CfbCD is a reductase or reductive cyclase. 2) Structure, conformational dynamics, and oligomerization state changes of CfbCD. Significant insight into the mechanism and allosteric regulation of CfbCD can be obtained by assessing changes in the structure and dynamics of the complex during the catalytic cycle. To accomplish this, a combination of size-exclusion chromatography, hydrogen-deuterium exchange mass spectrometry, molecular dynamics simulations, and high-resolution structural methods will be employed. 3) Source, order, and stereochemistry of proton additions during CfbCD catalysis. Details regarding the order and stereochemistry of proton additions during the CfbCD reaction will be uncovered using a combined spectroscopic and computational approach. Complementary mechanistic studies employing site-directed mutagenesis and substrate analogs will establish the identity of active site acid residues and the possible involvement of substrate-assisted catalysis during the CfbCD reaction.

09 BIOMASS FUELS↗