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NASA NTRS1984

Optimum design sensitivity based on approximation concepts and dual methods

An optimum design sensitivity analysis capability is reported which exploits the approximation concepts-dual method formulation of the minimum weight structural sizing problem. An efficient iterative solution technique is used to facilitate determination of sensitivity derivatives for both primal and dual variables. Estimates on the useful range of parameter perturbations, over which the optimum design sensitivity projections can be expected to yield satisfactory revised optimum designs, are also obtained. Numerical results for several example problems will be presented to illustrate the effectiveness of the capability reported.

Schmit, L. A.↗

NASA NTRS1990

Dual-shaped offset reflector antenna designs from solutions of the geometrical optics first-order partial differential equations

In obtaining solutions to the first-order nonlinear partial differential equations (PDEs) for synthesizing offset dual-shaped reflectors, it is found that previously observed computational problems can be avoided if the integration of the PDEs is started from an inner projected perimeter and integrated outward rather than starting from an outer projected perimeter and integrating inward. This procedure, however, introduces a new parameter, the main reflector inner perimeter radius p(o), when given a subreflector inner angle 0(o). Furthermore, a desired outer projected perimeter (e.g., a circle) is no longer guaranteed. Stability of the integration is maintained if some of the initial parameters are determined first from an approximate solution to the PDEs. A one-, two-, or three-parameter optimization algorithm can then be used to obtain a best set of parameters yielding a close fit to the desired projected outer rim. Good low cross-polarization mapping functions are also obtained. These methods are illustrated by synthesis of a high-gain offset-shaped Cassegrainian antenna and a low-noise offset-shaped Gregorian antenna.

Galindo-Israel, V.↗

DOE OSTI2025

Robust Implicit Adaptive Low Rank Time-Stepping Methods for Matrix Differential Equations

In this work, we develop implicit rank-adaptive schemes for time-dependent matrix differential equations. The dynamic low rank approximation (DLRA) is a well-known technique to capture the dynamic low rank structure based on Dirac–Frenkel time-dependent variational principle. In recent years, it has attracted a lot of attention due to its wide applicability. Our schemes are inspired by the three-step procedure used in the rank adaptive version of the unconventional robust integrator (the so called BUG integrator) (Ceruti et al. in BIT Numer Math 62(4):1149–1174, 2022) for DLRA. First, a prediction (basis update) step is made computing the approximate column and row spaces at the next time level. Second, a Galerkin evolution step is invoked using an implicit solves for the small core matrix. Finally, a truncation is made according to a prescribed error threshold. Since the DLRA is evolving the differential equation projected on to the tangent space of the low rank manifold, the error estimate of the BUG integrator contains the tangent projection (modeling) error which cannot be easily controlled by mesh refinement. This can cause convergence issue for equations with cross terms. To address this issue, we propose a simple modification, consisting of merging the row and column spaces from the explicit step truncation method together with the BUG spaces in the prediction step. In addition, we propose an adaptive strategy where the BUG spaces are only computed if the residual for the solution obtained from the prediction space by explicit step truncation method, is too large. Here, we prove stability and estimate the local truncation error of the schemes under assumptions. We benchmark the schemes in several tests, such as anisotropic diffusion, solid body rotation and the combination of the two, to show robust convergence properties.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1996

Studies using IMP, Voyager and Pioneer cosmic ray data to determine the size of the heliosphere

The purpose of this project was to use the cosmic ray data from the IMP, Voyager and Pioneer spacecraft in the heliosphere out to approximately 65 AU to estimate the size of the heliosphere. We used several techniques to develop a consistent picture of the size of the heliosphere. The first method used a response function approach which determined the intensity as a function of time by scaling the modulation effect as they move outward and eventually reach the boundary of the heliosphere. In this model the effects of transient cosmic ray disturbances is included. A second approach using the perturbation method in which drifts are considered as a perturbation to the standard diffusion-convection modulation models was not fully developed. In a third approach the location of the modulation boundary beyond the termination shock was estimated using observations of the intensity and radial gradients between Voyager 2 and Pioneer 10 along with new estimates of the interstellar intensity of more than 70 MeV galactic cosmic rays. Using this method we found that for 7 years, from 1983 to 1990, the modulation boundary remained constant at 83 +/- 5 AU. We infer from these studies that a modulation boundary can be estimated only by extrapolating the observed radial gradients when the solar magnetic field polarity is such that cosmic-ray particles are drifting in the heliosphere inward toward the Earth along the neutral sheet. The boundary distance is larger than the estimates of the location of the termination shock at 67 +/- 5 AU using the same method. Two other studies partially supported by this grant are attached. The first deals with the recovery period of the greater than 70 MeV cosmic rays in the outer heliosphere from 1992-1995. In the second paper we compare the rigidity dependence of the 11-year cosmic ray variation at the Earth in two cycles of opposite solar magnetic field polarity.

Lockwood, John A.↗

NASA NTRS1990

The semidiscrete Galerkin finite element modeling of compressible viscous flow past an airfoil

The primary project was the numerical simulation, by a finite element/finite difference method, of the viscous flow about an airfoil. The secondary project involved the numerical simulation of the three-dimensional separated and vortex-dominated flow about a hemispherically capped cylinder in the transonic regime. Preliminary calculations were started for the hemisphere-cylinder at 0 and 5 degree angle of attack. The solution of the flow field about airfoils and wings is required to determine the important parameters of lift, moment, and drag. Viscous effects must be accounted for if the drag is to be accurately calculated. At present there are basically two approaches to the numerical simulation of the flow field, the use of fully viscous models and the inviscid/viscous models. The fully viscous models require the solution of an approximation of the Navier-Stokes equations and therefore should simulate most of the physical mechanisms. A fast, accurate, and computationally efficient inviscid flow solver was recently developed by Hartwich. It is thought that Hartwich's program coupled to a fast, accurate, and computationally efficient boundary layer code, will make an excellent tool for airfoil design. The purpose of the primary project was to develop a compressible boundary layer code using the semidiscrete Galerkin finite element method. The numerical scheme employed used the combination of a Dorodnitsyn formulation of the boundary layer equations, with a finite difference/finite element procedure (semidiscrete Galerkin method), in the solution of the compressible two-dimensional boundary layer equations. A laminar compressible boundary layer code was developed and tested for a NACA 0012 airfoil at a Mach number of 0.5, a Reynolds number of 5000, and zero angle of attack. At present the boundary layer program solves up to, but not beyond, separation.

Meade, Andrew J.↗

DOE OSTI2023

Light Energy Transduction in Green Sulfur Bacteria

Green sulfur bacteria (GSB) are exquisitely adapted for growth at extraordinarily low light intensities. They are important primary producers of biomass in many anoxic environments, and they contribute significantly to the biogeochemical cycling of carbon, nitrogen, and sulfur on Earth. Green bacteria more generally share the property of using chlorosomes for light-harvesting, and these unusual organelles have many unique features. These include the presence of a monolayer lipid-protein envelope, self-assembling bacteriochlorophylls (BChl) in which pigment-pigment interactions predominate, and the presence of redox components ([2Fe-2S] ferredoxins and quinones) that play a role in regulating excitation energy transfer to the type-1 homodimeric reaction centers. The reaction centers of GSB are related to Photosystem I of cyanobacteria and higher plants but also exhibit several unique structural and functional features. The long-term objectives of this research program are to understand the structure, functions, and biogenesis of the chlorosomes, reaction centers, and electron transport chains that carry out the photochemical transduction of light energy into chemical energy in the model green sulfur bacterium, Chlorobaculum (formerly Chlorobium) tepidum. Over a period of 26 years, we characterized chlorosomes in detail. We identified the proteins in the chlorosome envelopes of diverse organisms, identified the nearest neighbors of those proteins, and characterized the chlorosomes of mutant strains lacking one to five of these proteins. After the genome sequence of Cba. tepidum became available, we identified all genes encoding enzymes for BChl a , BChl c/d/e/ƒ , and Chl a biosynthesis Cba. tepidum . We additionally identified all genes encoding enzymes for carotenoid biosynthesis. By constructing a bchQRU mutant strain that produces [Et, Me]-BChl d , together with collaborators who are specialists in solid-state NMR and cryo-electron microscopy, we solved the structure of the BChls in chlorosomes. Using similar methods and chlorosomes containing [Et, Me]-BChl c , we then showed that alternative structures were possible using the same syn-anti BChl dimer. The structures were refined by introducing spectroscopic data from single-chlorosome measurements. Over the course of this project, we sequenced the genomes of approximately twenty GSB strains, which provided important information for comparative analyses. Through analyses of metagenomic data from Mushroom and Octopus Springs in Yellowstone National Park, we identified a novel chlorophototroph belonging to the phylum Acidobacteriota. We successfully isolated an axenic culture of this organism. We characterized the photosynthetic apparatus of this bacterium, named Chloracidobacterium thermophilum, in significant detail, in particular its type-1, homodimeric reaction centers. Surprisingly, these reaction centers contain three types of Chls, BChl a , Chl a , and Zn-BChl a' . We showed that a dimer of Zn-BChl a' is the primary donor and Chl a the primary acceptor of electrons in this reaction center by using advanced spectroscopic techniques. We isolated eight additional strains of Chloracidobacterium spp. from Mushroom Spring and Rupite hot springs in Bulgaria. Comparative genomes showed that these represent three species, Cab. thermophilum , Cab. aggregatum , and Cab. validum . By applying comparative genomics, genetic, biochemical biophysical and physiological approaches to study green bacteria, we produced a wealth of new information about the remarkable light-harvesting and energy transduction capabilities of these poorly characterized microorganisms.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Development and Application of In Situ Nanocharacterization to Photocatalytic Materials for Solar Fuel Generation

Photocatalytic materials offer an attractive approach for converting solar energy into chemical energy but the performance of the current generation of materials is insufficient to make a technology viable. To address this deficiency, it is necessary to develop a fundamental atomic level understanding of the functioning of such materials so that strategies can be developed to improve performance. This project was undertaken to explore the fundamental structure and properties of photocatalytic materials using atomic resolution imaging and spectroscopy techniques available on advanced transmission electron microscopy. Specifically, there is a need to develop an understanding of how atomic structures/defects and nanoparticle configurations regulate electronic, optical, and catalytic properties to facilitate the design of next generation photocatalysts for solar fuel production. The work focused on fundamental materials information that can be gained from advanced transmission electron microscopy study on novel and existing photocatalytic systems with an emphasis on the hydrogen evolution reaction (HER). Throughout the project, new instrumentation and microscopy characterization tools were developed. Two focus areas were: developing in situ TEM methods and advanced electron energy-loss spectroscopic for nanoscale analysis of catalysts. The work spanned a period of 12 years and for convenience, the report is divided into four phases, approximately corresponding to the four funding periods of the program. Most of the significant results are reported in archival journal publications.

36 MATERIALS SCIENCE↗

NASA NTRS2001

Endoscopic surgery in weightlessness: the investigation of basic principles for surgery in space

BACKGROUND: Performing a surgical procedure in weightlessness, also called 0-gravity (0-g), has been shown to be no more difficult than in a 1-g environment if the requirements for the restraint of the patient, operator, surgical hardware, are observed. The performance of laparoscopic and thorascopic procedures in weightlessness, if feasible, would offer several advantages over the performance of an open operation. Concerns about the feasibility of performing minimally invasive procedures in weightlessness have included impaired visualization from the absence of gravitational retraction of the bowel (laparoscopy) or thoracic organs (thoracoscopy) as well as obstruction and interference from floating debris such as blood, pus, and irrigation fluid. The purpose of this study was to determine the feasibility of performing laparoscopic and thorascopic procedures and the degree of impaired surgical endoscopic visualization in weightlessness. METHODS: From 1993 to 2000, laparoscopic and thorascopic procedures were performed on 10 anesthetized adult pigs weighing approximately 50 kg in the National Aeronautics and Space Administration (NASA) Microgravity Program using a modified KC-135 airplane. The parabolic simulation system for advanced life support was used in this project, and 20 to 40 parabolas were used for laparoscopic or thorascopic investigation, each containing approximately 30 s of 0-g alternating with 2-g pullouts. The animal model was restrained in the supine position on a floor-level Crew Medical Restraint System, and the abdominal cavity was insufflated with carbon dioxide. The intraabdominal and intrathoracic anatomy was visualized in the 1-g, 0-g, and 2-g periods of parabolic flight. Bleeding was created in the animals, and the behavior of the blood in the abdominal and thoracic cavities was observed. In the thoracic cavity, gas insufflation and mechanical retraction was used at times unilaterally to decrease pulmonary ventilation enough to increase the thoracic domain. RESULTS: Visualization was improved in laparoscopy, from tethering of the bowel by the elastic mesentery, and from the strong tendency for debris and blood to adhere to the abdominal wall because of surface tension forces. The lack of adequate thoracic domain made thorascopy more difficult. Fluid in the thoracic cavity did not impair visualization because the fluid at 0-g does not loculate posteriorly, but disperses along the thoracic wall and mediastinal reflections. CONCLUSIONS: Performing minimally invasive procedures instead of open surgical procedures in a weightless environment has theoretical advantages, especially in the ability to prevent cabin atmosphere contamination from surgical fluids (blood, pus, irrigation). Visualization will become more important and practical as the endoscopic hardware is miniaturized from its current form, as endoscopic technology becomes more advanced, and as more surgically capable medical crew officers are present in future long-duration space exploration missions.

short duration↗

DOE OSTI2023

A guide to the design of the virtual element methods for second- and fourth-order partial differential equations

Here we discuss the design and implementation details of two conforming virtual element methods for the numerical approximation of two partial differential equations that emerge in phase-field modeling of fracture propagation in elastic material. The two partial differential equations are: (i) a linear hyperbolic equation describing the momentum balance and (ii) a fourth-order elliptic equation modeling the damage of the material. Inspired by, we develop a new conforming VEM for the discretization of the two equations, which is implementation-friendly, i.e., different terms can be implemented by exploiting a single projection operator. We use C 0 and C 1 virtual elements for the second-and fourth-order partial differential equation, respectively. For both equations, we review the formulation of the virtual element approximation and discuss the details pertaining the implementation.

42 ENGINEERING↗

DOE OSTI2024

SUBTASK 1.6 – BASIN ELECTRIC CARBON STORAGE RESEARCH PROJECT: NOVEL MONITORING TECHNIQUES

The Energy & Environmental Research Center (EERC) conducted baseline activities associated with an applied research project at Basin Electric Power Cooperative’s (Basin’s) carbon capture and storage (CCS) site in Beulah, North Dakota, to establish novel carbon storage-monitoring techniques as commercial methods under Cooperative Agreement No. DE-FE0024233, Subtask 1.6. The following report summarizes the baseline activities performed and briefly describes the subsequent (operational monitoring) activities that have been proposed to the U.S. Department of Energy (DOE) as part of the overall project to develop and demonstrate novel monitoring techniques at North America’s largest permitted CCS operation. Dakota Gasification Company (DGC), a wholly owned subsidiary of Basin, owns and operates the Great Plains Synfuels Plant (GPSP) approximately 5 miles northwest of the town of Beulah, North Dakota (Figure 1). In 2023, DGC received approval from the North Dakota Industrial Commission (NDIC) to develop a storage facility on-site for injecting a stream of carbon dioxide (CO2) captured from GPSP. DGC will transport the captured CO2 stream with approximately 6.8 miles of transmission lines that extend north of GPSP and inject >1 million tonnes (MMt) of CO2 annually (>1 MMt/yr) over a 12-year period with up to six underground injection control (UIC) Class VI-compliant injection wells completed in the Broom Creek Formation, a predominantly sandstone reservoir and saline aquifer underlying GPSP. The Broom Creek Formation lies approximately 5900 feet (ft) below ground surface (bgs) at GPSP. The commercial scale (i.e., >1 MMt/yr) of DGC’s permitted carbon storage project is ideal for developing and testing the novel monitoring techniques included within Subtask 1.6. The goals of this project are to demonstrate 1) the cost-effectiveness of novel monitoring technologies included as part of this research, 2) technology capability for tracking the CO2 plume and/or associated pressure response in the subsurface and monitoring out-of-zone migration, and 3) compliance with UIC Class VI program requirements. The research activities proposed for the overall project include 1) design of an automated, integrated, modular (AIM) monitoring station; 2) time-lapse electromagnetic (EM) field surveys; 3) drone-based surveillance studies; 4) time-lapse monitoring with seismic methods; 5) advanced wellbore-monitoring methods; 6) deployment of an AIM monitoring network; 7) EM monitoring of CO2 with real-time data processing; 8) continued seasonal drone-based surveillance studies; 9) seismic monitoring with passive and active surveys; and 10) wellbore monitoring with nuclear magnetic resonance (NMR) for near-surface characterization. Completion of Activities 1.0–5.0 (baseline activities) are described in this report. Upon authorization of funding by DOE, the EERC will initiate Activities 6.0– 10.0 (operational monitoring activities). Current state-of-the-art (SOA) carbon storage-monitoring techniques require countless labor hours dedicated to the acquisition of data. Once data are gathered, these SOA techniques often rely on commercial facilities to process raw data from the field. However, it is anticipated that next-generation monitoring techniques, such as those being demonstrated, will lower acquisition footprints, be less operationally intensive, and improve data acquisition efficiencies. These new techniques are more conducive to the application of machine learning, artificial intelligence, and automation, thus providing a pathway for integration into active control systems, informing site operability, and improving the integration of data for future CCS projects across the United States. Additionally, reclaimed and active mining lands are present within the project site, creating a unique opportunity to demonstrate the effectiveness of remote sensing and surface-based geophysics monitoring techniques at similar project sites that may include disturbed, unconsolidated, or actively excavated near-surface environments. The efforts included in the overall project will produce necessary designs, learnings, and data acquired during the baseline and operational monitoring periods that are necessary for time-lapse demonstration and validation of the described monitoring techniques. In addition, it is anticipated that the monitoring technologies included in this study will be compliant with UIC Class VI requirements to enable the potential for implementation at other CCS sites across the United States.

42 ENGINEERING↗

DOE OSTI2024

Simplified projection on total spin zero for state preparation on quantum computers

Here, we introduce a simple algorithm for projecting on J = 0 states of a many-body system by performing a series of rotations to remove states with angular momentum projections greater than zero. Existing methods rely on unitary evolution with the two-body operator J 2 , which when expressed in the computational basis contains many complicated Pauli strings requiring Trotterization and leading to very deep quantum circuits. Our approach performs the necessary projections using the one-body operators J x and J z . By leveraging the method of Cartan decomposition, the unitary transformations that perform the projection can be parametrized as a product of a small number of two-qubit rotations, with angles determined by an efficient classical optimization. Given the reduced complexity in terms of gates, this approach can be used to prepare approximate ground states of even-even nuclei by projecting onto the J = 0 component of deformed Hartree-Fock states. We estimate the resource requirements in terms of the universal gate set {H,S, CNOT ,T} and briefly discuss a variant of the algorithm that projects onto J = 1/2 states of a system with an odd number of fermions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS2004

Bayesian Vision for Shape Recovery

We present a new Bayesian vision technique that aims at recovering a shape from two or more noisy observations taken under similar lighting conditions. The shape is parametrized by a piecewise linear height field, textured by a piecewise linear irradiance field, and we assume Gaussian Markovian priors for both shape vertices and irradiance variables. The observation process. also known as rendering, is modeled by a non-affine projection (e.g. perspective projection) followed by a convolution with a piecewise linear point spread function. and contamination by additive Gaussian noise. We assume that the observation parameters are calibrated beforehand. The major novelty of the proposed method consists of marginalizing out the irradiances considered as nuisance parameters, which is achieved by Laplace approximations. This reduces the inference to minimizing an energy that only depends on the shape vertices, and therefore allows an efficient Iterated Conditional Mode (ICM) optimization scheme to be implemented. A Gaussian approximation of the posterior shape density is computed, thus providing estimates both the geometry and its uncertainty. We illustrate the effectiveness of the new method by shape reconstruction results in a 2D case. A 3D version is currently under development and aims at recovering a surface from multiple images, reconstructing the topography by marginalizing out both albedo and shading.

Jalobeanu, Andre↗

DOE OSTI2021

Train Like a (Var)Pro: Efficient Training of Neural Networks with Variable Projection

Deep neural networks (DNNs) have achieved state-of-the-art performance across a variety of traditional machine learning tasks, e.g., speech recognition, image classification, and segmentation. The ability of DNNs to efficiently approximate high-dimensional functions has also motivated their use in scientific applications, e.g., to solve partial differential equations and to generate surrogate models. In this paper, we consider the supervised training of DNNs, which arises in many of the above applications. We focus on the central problem of optimizing the weights of the given DNN such that it accurately approximates the relation between observed input and target data. Devising effective solvers for this optimization problem is notoriously challenging due to the large number of weights, nonconvexity, data sparsity, and nontrivial choice of hyperparameters. To solve the optimization problem more efficiently, we propose the use of variable projection (VarPro), a method originally designed for separable nonlinear least-squares problems. Our main contribution is the Gauss--Newton VarPro method (GNvpro) that extends the reach of the VarPro idea to nonquadratic objective functions, most notably cross-entropy loss functions arising in classification. These extensions make GNvpro applicable to all training problems that involve a DNN whose last layer is an affine mapping, which is common in many state-of-the-art architectures. In our four numerical experiments from surrogate modeling, segmentation, and classification, GNvpro solves the optimization problem more efficiently than commonly used stochastic gradient descent (SGD) schemes. Finally, GNvpro finds solutions that generalize well, and in all but one example better than well-tuned SGD methods, to unseen data points.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Sodium-Cooled Fast Reactor Reference Plant Model

This report details the progress of Idaho National Laboratory (INL) in creating a reference plant multiphysics model for the Advanced Burner Test Reactor (ABTR). This model was developed under Task 13 of the U.S. Nuclear Regulatory Commission project “Development and Modeling Support for Advanced Non-Light Water Reactors,” and is an extension of the reference plant model developed in Task 4b, which was improved upon in the following ways. (1) The discrete ordinates method was used in lieu of the super-homogenization (SPH)-corrected diffusion approximation in order to better capture the anisotropic scattering contribution and the neutron leakage change due to thermal expansion. (2) The novel neutronic spatial discretization approach, termed the ring-heterogeneous (RH) approximation, was conceptualized and introduced to capture the differential expansion of the materials in the core. This new technique proved capable of preserving fission rates and maintaining the eigenvalue within 2.5% and 266 pcm with 9 neutron energy groups, respectively. Separating the different materials in the core enables the differential expansion of materials to be explicitly accounted for, eliminating the need for problem-specific cross-section functionalization techniques. (3) The SAM model for the core and system thermal-hydraulics analysis was updated to include 61 channels instead of just four representative ones. This enables users to obtain improved spatial resolution for sodium temperature and density scalar fields. (4) All the mesh files were created via the Multiphysics Object-Oriented Simulation Environment (MOOSE) Reactor module, eliminating all reliance on external tools for mesh creation. (5) Finally, the fuel axial expansion now leverages the HT9 and UPuZr material properties that have been validated against experimental data. The reference plant model was used to perform a full-core unprotected loss of flow (ULOF) transient calculation, including neutronics, thermal and mechanical feedback mechanisms. Future work will be devoted to further enhancements of the model. Potential improvements to the model include the addition of the control rod driveline expansion feedback and the upgrading of the support plate model so as to explicitly include 3D effects. Additionally, a Nuclear Energy Advanced Modeling and Simulation funded parallel effort has completely automated the creation of the ring-heterogeneous (RH) mesh from the fully heterogeneous (FH) geometry, thus maximizing user friendliness for the sodium fast reactor sodium-cooled fast reactor (SFR) workflow and will be incorporated in future work.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

Leverage Score Sampling for Parametric PDEs (Final Technical Report)

This final technical report summarizes the accomplishments of work performed under DOE Office of Science Award DE-SC0022266, which is titled “Leverage Score Sampling for Parametric PDEs”. The goal of the project was to extend methods from Randomized Numerical Linear Algebra (RandNLA) to tackle central computational challenges in model order reduction and uncertainty quantification (UQ) for parametric partial differential equations (PDEs). In particular, we sought to use importance sampling methods originally developed for RandNLA to develop sample efficient active learning algorithms for approximating high-dimensional scalar functions, e.g. by polynomials, Gaussian process models, and simple neural networks. Such methods can be immediately applied to developing surrogate models or to approximating quantity of interest (QoI) surfaces. In the context of PDEs, each sample used for learning equates to the solution of the differential equation for a particular set of parameters, so sample efficiency translates to improved computational efficiency for a variety of downstream tasks.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

A Kaczmarz-inspired approach to accelerate the optimization of neural network wavefunctions

Neural network wavefunctions optimized using the variational Monte Carlo method have been shown to produce highly accurate results for the electronic structure of atoms and small molecules, but the high cost of optimizing such wavefunctions prevents their application to larger systems. We propose the Subsampled Projected-Increment Natural Gradient Descent (SPRING) optimizer to reduce this bottleneck. SPRING combines ideas from the recently introduced minimum-step stochastic reconfiguration optimizer (MinSR) and the classical randomized Kaczmarz method for solving linear least-squares problems. We demonstrate that SPRING outperforms both MinSR and the popular Kronecker-Factored Approximate Curvature method (KFAC) across a number of small atoms and molecules, given that the learning rates of all methods are optimally tuned. For example, on the oxygen atom, SPRING attains chemical accuracy after forty thousand training iterations, whereas both MinSR and KFAC fail to do so even after one hundred thousand iterations.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2012

The Agricultural Model Intercomparison and Improvement Project (AgMIP): Protocols and Pilot Studies

The Agricultural Model Intercomparison and Improvement Project (AgMIP) is a major international effort linking the climate, crop, and economic modeling communities with cutting-edge information technology to produce improved crop and economic models and the next generation of climate impact projections for the agricultural sector. The goals of AgMIP are to improve substantially the characterization of world food security due to climate change and to enhance adaptation capacity in both developing and developed countries. Analyses of the agricultural impacts of climate variability and change require a transdisciplinary effort to consistently link state-of-the-art climate scenarios to crop and economic models. Crop model outputs are aggregated as inputs to regional and global economic models to determine regional vulnerabilities, changes in comparative advantage, price effects, and potential adaptation strategies in the agricultural sector. Climate, Crop Modeling, Economics, and Information Technology Team Protocols are presented to guide coordinated climate, crop modeling, economics, and information technology research activities around the world, along with AgMIP Cross-Cutting Themes that address uncertainty, aggregation and scaling, and the development of Representative Agricultural Pathways (RAPs) to enable testing of climate change adaptations in the context of other regional and global trends. The organization of research activities by geographic region and specific crops is described, along with project milestones. Pilot results demonstrate AgMIP's role in assessing climate impacts with explicit representation of uncertainties in climate scenarios and simulations using crop and economic models. An intercomparison of wheat model simulations near Obregón, Mexico reveals inter-model differences in yield sensitivity to [CO2] with model uncertainty holding approximately steady as concentrations rise, while uncertainty related to choice of crop model increases with rising temperatures. Wheat model simulations with midcentury climate scenarios project a slight decline in absolute yields that is more sensitive to selection of crop model than to global climate model, emissions scenario, or climate scenario downscaling method. A comparison of regional and national-scale economic simulations finds a large sensitivity of projected yield changes to the simulations' resolved scales. Finally, a global economic model intercomparison example demonstrates that improvements in the understanding of agriculture futures arise from integration of the range of uncertainty in crop, climate, and economic modeling results in multi-model assessments.

Rosenzweig, C.↗

NASA NTRS2024

Substantial Cooling Effect From Aerosol-Induced Increase in Tropical Marine Cloud Cover

With global warming currently standing at approximately +1.2 °C since preindustrial times, climate change is a pressing global issue. Marine cloud brightening is one proposed method to tackle warming through injecting aerosols into marine clouds to enhance their reflectivity and thereby planetary albedo. However, because it is unclear how aerosols influence clouds, especially cloud cover, both climate projections and the effectiveness of marine cloud brightening remain uncertain. Here, we use satellite observations of volcanic eruptions in Hawaii to quantify the aerosol fingerprint on tropical marine clouds. We observe a large enhancement in reflected sunlight, mainly due to an aerosol-induced increase in cloud cover. This observed strong negative aerosol forcing suggests that the current level of global warming is driven by a weaker net radiative forcing than previously thought, arising from the competing effects of greenhouse gases and aerosols. This implies a greater sensitivity of Earth’s climate to radiative forcing and therefore a larger warming response to both rising greenhouse gas concentrations and reductions in atmospheric aerosols due to air quality measures. However, our findings also indicate that mitigation of global warming via marine cloud brightening is plausible and is most effective in humid and stable conditions in the tropics where solar radiation is strong.

Atmospheric science↗