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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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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Anoxic photogeochemical oxidation of manganese carbonate yields manganese oxide

The oxidation states of manganese minerals in the geological record have been interpreted as proxies for the evolution of molecular oxygen in the Archean eon. In this paper we report that an Archean manganese mineral, rhodochrosite (MnCO 3 ), can be photochemically oxidized by light under anoxic, abiotic conditions. Rhodochrosite has a calculated bandgap of about 5.4 eV, corresponding to light energy centering around 230 nm. Light at that wavelength would have been present on Earth’s surface in the Archean, prior to the formation of stratospheric ozone. We show experimentally that the photooxidation of rhodochrosite in suspension with light centered at 230 nm produced H 2 gas and manganite (γ-MnOOH) with an apparent quantum yield of 1.37 × 10 –3 moles hydrogen per moles incident photons. Our results suggest that manganese oxides could have formed abiotically on the surface in shallow waters and on continents during the Archean eon in the absence of molecular oxygen.

58 GEOSCIENCES↗
DOE OSTI2023

Automated remote sensing tools to counter illicit maritime activity: vessel detection, bathymetry and topography from WorldView imagery

Illicit maritime activity, such as piracy and smuggling, is a global issue that often occurs in areas where interdiction authorities are sparse, ground-based monitoring technologies like radar lack range and coverage, and dark vessels abound. Our objective was to assess vessel congregation patterns, identify likely beaching areas based on terrain maps, and use them to narrow the search for potential smuggling transfer and overland routes in a specific region along the Puntland coast of Somalia. To accomplish this goal, we developed automated protocols applied to WorldView satellite imagery for (1) vessel detection and size classification, (2) shallow-water bathymetric characterization, and (3) coastal topography mapping. Utilizing a single sensor for vessel detection and topographic and bathymetric extraction at high spatial resolution and at a high re-visit rate provides a simplification to near-shore characterization for monitoring purposes. The extracted topography and bathymetry are then presented as a single, comprehensive perspective of a coastal region. The vessel-detection algorithm identified all vessels larger than approximately 15 metres in length (35 of 35), but misidentified six artefacts (i.e. false positives), resulting in an overall accuracy of 85%. The combined vessel and terrain maps facilitated the identification of a potential beaching and overland transportation route location.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2023

Applications of physics informed neural operators

Abstract We present a critical analysis of physics-informed neural operators (PINOs) to solve partial differential equations (PDEs) that are ubiquitous in the study and modeling of physics phenomena using carefully curated datasets. Further, we provide a benchmarking suite which can be used to evaluate PINOs in solving such problems. We first demonstrate that our methods reproduce the accuracy and performance of other neural operators published elsewhere in the literature to learn the 1D wave equation and the 1D Burgers equation. Thereafter, we apply our PINOs to learn new types of equations, including the 2D Burgers equation in the scalar, inviscid and vector types. Finally, we show that our approach is also applicable to learn the physics of the 2D linear and nonlinear shallow water equations, which involve three coupled PDEs. We release our artificial intelligence surrogates and scientific software to produce initial data and boundary conditions to study a broad range of physically motivated scenarios. We provide the source code , an interactive website to visualize the predictions of our PINOs, and a tutorial for their use at the Data and Learning Hub for Science .

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Latent Twins

Over the past decade, scientific machine learning has transformed the development of mathematical and computational frameworks for analyzing, modeling, and predicting complex systems. From inverse problems to numerical partial differential equations (PDEs), dynamical systems, and model reduction, these advances have pushed the boundaries of what can be simulated. Yet they have often progressed in parallel, with representation learning and algorithmic solution methods evolving largely as separate pipelines. With Latent Twins, we propose a unifying mathematical framework that creates a hidden surrogate in latent space for the underlying equations. Whereas digital twins mirror physical systems in the digital world, Latent Twins mirror mathematical systems in a learned latent space governed by operators. Through this lens, classical modeling, inversion, model reduction, and operator approximation all emerge as special cases of a single principle. We establish the fundamental approximation properties of Latent Twins for both ordinary differential equations (ODEs) and PDEs and demonstrate the framework across three representative settings: (i) canonical ODEs, capturing diverse dynamical regimes; (ii) a PDE benchmark using the shallow-water equations, contrasting Latent Twin simulations with deep operator network and forecasts with a four-dimensional variational method baseline; and (iii) a challenging real-data geopotential reanalysis dataset, reconstructing and forecasting from sparse, noisy observations. Latent Twins provide a compact, interpretable surrogate for solution operators that evaluate across arbitrary time gaps in a single-shot, while remaining compatible with scientific pipelines such as assimilation, control, and uncertainty quantification. Looking forward, this framework offers scalable, theory-grounded surrogates that bridge data-driven representation learning and classical scientific modeling across disciplines.

Latent Twins↗
DOE OSTI2020

A new Devonian euthycarcinoid reveals the use of different respiratory strategies during the marine-to-terrestrial transition in the myriapod lineage

Myriapods were, together with arachnids, the earliest animals to occupy terrestrial ecosystems, by at least the Silurian. The origin of myriapods and their land colonization have long remained puzzling until euthycarcinoids, an extinct group of aquatic arthropods considered amphibious, were shown to be stem-group myriapods, extending the lineage to the Cambrian and evidencing a marine-to-terrestrial transition. Although possible respiratory structures comparable to the air-breathing tracheal system of myriapods are visible in several euthycarcinoids, little is known about the mechanism by which they respired. Here, we describe a new euthycarcinoid from Upper Devonian alluvio-lagoonal deposits of Belgium. Synchrotron-based elemental X-ray analyses were used to extract all available information from the only known specimen. Sulfur X-ray fluorescence (XRF) mapping and spectroscopy unveil sulfate evaporation stains, spread over the entire slab, suggestive of a very shallow-water to the terrestrial environment prior to burial consistent with an amphibious lifestyle. Trace metal XRF mapping reveals a pair of ventral spherical cavities or chambers on the second post-abdominal segment that do not compare to any known feature in aquatic arthropods, but might well play a part in air-breathing. Our data provide additional support for amphibious lifestyle in euthycarcinoids and show that different respiratory strategies were used during the marine-to-terrestrial transition in the myriapod lineage.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Self-assembled reconfigurable pump architectures via magnetic colloidal swarms

Self-assembled swarms of interactive active units, which are adaptive and dynamically reconfigurable to accommodate different functionalities, represent a promising platform for the development of next-generation robotics. Here, we utilize the emergent collective behavior of active magnetic colloids confined in quasi-two-dimensional arrays of overlapping wells to demonstrate the self-organization of a colloidal swarm into a dynamic pump architecture capable of controlled transport of passive cargo particles. This dynamic architecture provides a global unidirectional looping flow pattern along the entire length of the system. We show that the flow direction of the dynamic swarm-based pump can be externally controlled by a phase shift of a driving magnetic field energizing the swarm. The experimental observations are supported by computational modeling based on phenomenological coarse-grained particle dynamics coupled to shallow-water Navier-Stokes hydrodynamics. In conclusion, our findings demonstrate how the emergent collective behavior of a swarm can be orchestrated into a desired functionality by exploiting the interplay between activity and confinement potentials.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Probabilistic neural networks for fluid flow surrogate modeling and data recovery

We consider the use of probabilistic neural networks for fluid flow surrogate modeling and data recovery. This framework is constructed by assuming that the target variables are sampled from a Gaussian distribution conditioned on the inputs. Consequently, the overall formulation sets up a procedure to predict the hyperparameters of this distribution which are then used to compute an objective function given training data. We demonstrate that this framework has the ability to provide for prediction confidence intervals based on the assumption of a probabilistic posterior, given an appropriate model architecture and adequate training data. The applicability of the present framework to cases with noisy measurements and limited observations is also assessed. To demonstrate the capabilities of this framework, we consider canonical regression problems of fluid dynamics from the viewpoint of reduced-order modeling and spatial data recovery for four canonical data sets. The examples considered in this study arise from (i) the shallow-water equations, (ii) a two-dimensional cylinder flow, (iii) the wake of a NACA0012 airfoil with a Gurney flap, and (iv) the NOAA sea surface temperature data set. Furthermore, the present results indicate that the probabilistic neural network not only produces a machine-learning-based fluid flow surrogate model but also systematically quantifies the uncertainty therein to assist with model interpretability.

42 ENGINEERING↗
DOE OSTI2024

Control of Floating Offshore Wind Energy Systems: An Introduction to the Special Issue

As the global demand for renewable energy sources intensifies amid the urgent fight against climate change [1] , offshore wind energy has emerged as a promising and crucial component of the sustainable energy portfolio. Fixed-bottom offshore wind farms have already demonstrated their potential; however, they are limited to relatively shallow waters, typically no deeper than 60 m.

climate change↗
DOE OSTI2020

Local Truncation Error-Informed Code Verification

The method of manufactured solutions (MMS) has become increasingly popular in conducting code verification studies on predictive codes, such as nuclear power system codes and computational fluid dynamic codes. The reason for the popularity of this approach is that it can be used when an analytical solution is not available. Using MMS, code developers are able to verify that their code is free of coding errors that impact the observed order of accuracy. While MMS is still an excellent tool for code verification, it does not identify coding errors that are of the same order as the numerical method. This paper presents a method that combines MMS with modified equation analysis (MEA), which calculates the local truncation error (LTE) to identify coding error up to and including the order of the numerical method. This method is referred to as modified equation analysis methd of manufactured solutions (MEAMMS). MEAMMS is then applied to a custom-built code, which solves the shallow water equations, to test the performance of the code verification method. MEAMMS is able to detect all coding errors that impact the implementation of the numerical scheme. To show how MEAMMS is different than MMS, they are both applied to the same first-order numerical method test problem with a first-order coding error. When there are first-order coding errors, only MEAMMS is able to identify them. Finally, this shows that MEAMMS is able to identify a larger set of coding errors while still being able to identify the coding errors MMS is able to identify.

42 ENGINEERING↗
DOE OSTI2025

DOE-ICoM/RIFT

Rapid Infrastructure Flood Tool (RIFT) is a two-dimensional hydrodynamic model based on the complete shallow water equations. RIFT has specifically been designed with rapid simulation in mind by utilizing commodity high performance computing technology and best-available nation-wide data. RIFT is used to predict the movement of water over land and resolve the spatial and temporal variability of flood depths, extent, and velocity. RIFT can be applied to many flood situations and has primarily been used to quantify flood extents from dam/levee failure or inland rainfall flooding.

Perkins, Bill [Pacific Northwest National Laborato↗
DOE OSTI2026

swe-python

Python shallow water equations solver.

Lilly, Jeremy [Los Alamos National Lab]↗
DOE OSTI2021

Two-Day Westward-Propagating Inertio-Gravity Waves during GoAmazon

The dynamical and thermodynamical features of Amazonian 2-day westward-propagating inertia–gravity (WIG) waves are examined. On the basis of a linear regression analysis of satellite brightness temperature and data from the 2014–15 Observations and Modeling of the Green Ocean Amazon (GoAmazon) field campaign, it is shown that Amazonian WIG waves exhibit structure and propagation characteristics consistent with the n = 1 WIG waves from shallow water theory. These WIG waves exhibit a pronounced seasonality, with peak activity occurring from March to May and a minimum occurring from June to September. Evidence is shown that mesoscale convective systems over the Amazon are frequently organized in 2-day WIG waves. Results suggest that many of the Amazonian WIG waves come from preexisting 2-day waves over the Atlantic, which slow down when coupled with the deeper, more intense convection over tropical South America. In contrast to WIG waves that occur over the ocean, Amazonian 2-day WIG waves exhibit a pronounced signature in surface temperature, moisture, and heat fluxes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Semi-Implicit Computation of Fast Modes in a Scheme Integrating Slow Modes by a Leapfrog Method Based on a Selective Implicit Time Filter

Abstract A scheme for integration of atmospheric equations containing terms with differing time scales is developed. The method employs a filtered leapfrog scheme utilizing a fourth-order implicit time filter with one function evaluation per time step to compute slow-propagating phenomena such as advection and rotation. The terms involving fast-propagating modes are handled implicitly with an unconditionally stable method that permits application of larger time steps and faster computations compared to fully explicit treatment. Implementation using explicit and recurrent formulation is provided. Stability analysis demonstrates that the method is conditionally stable for any combination of frequencies involved in the slow and fast terms as they approach the origin. The implicit filter used in the method damps the computational modes without noticeably sacrificing the accuracy of the physical mode. TheO[(Δt 4 )] accuracy for amplitude errors achieved by the implicitly filtered leapfrog is preserved in applications where terms responsible for fast propagation are integrated with a semi-implicit method. Detailed formulation of the method for soundproof nonhydrostatic anelastic equations is provided. Procedures for implementation in global spectral shallow-water models are also given. Examples comparing numerical and analytical solutions for linear gravity waves demonstrate the accuracy of the scheme. The performance is also shown in more practical nonlinear applications, where numerical solutions accomplished by the method are evaluated against those computed from a scheme where the slow terms are handled by the third-order Runge–Kutta scheme. It demonstrates that the method is able to accurately resolve fine-scale dynamics of Kelvin–Helmholtz shear instabilities, the evolution of density current, and nonlinear drifts of twin tropical cyclones.

Meteorology & Atmospheric Sciences↗
DOE OSTI2022

AmeriFlux FLUXNET-1F US-Hn3 Hanford 100H sagebrush

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-Hn3 Hanford 100H sagebrush. This is the FLUXNET version of the carbon flux data for the site US-Hn3 Hanford 100H sagebrush produced by applying the standard ONEFlux (1F) software. Site Description - The site is a riparian sagebrush-steppe ecosystem characterized by a shallow water table.

Liu, Heping↗
DOE OSTI2022

AmeriFlux FLUXNET-1F US-Hn2 Hanford 100H grassland

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-Hn2 Hanford 100H grassland. This is the FLUXNET version of the carbon flux data for the site US-Hn2 Hanford 100H grassland produced by applying the standard ONEFlux (1F) software. Site Description - The site is a riparian grassland ecosystem characterized by a shallow water table.

Liu, Heping↗
DOE OSTI2026

AmeriFlux CA-BCW Big Creek Watershed

This is the AmeriFlux version of the carbon flux data for the site CA-BCW Big Creek Watershed. Site Description - This flux tower is located in the Lower Big Creek Watershed on agricultural land restored by the Nature Conservancy of Canada. The tower is monitoring a 0.88 ha marsh dominated by rushes and open shallow water. This wetland was created in 2012.

Barreto, Carlos [Ontario Ministry of Natural Resou↗
DOE OSTI2020

Sequim Bay Underwater UXO (SBU2) Prototype Demonstration Site: Field Operations Summary, 2019

The U.S. Department of Defense (DoD) has identified more than 400 underwater sites that are potentially contaminated with munitions. Many of these sites are in shallow water (0–35 m deep) where the munitions pose a threat to human health and the environmental. To address this challenge, the Strategic Environmental Research and Development Program (SERDP) and Environmental Security Technology Certification Program (ESTCP) held a workshop in 2018 to establish the requirements and framework for developing a series of underwater unexploded ordnance (UXO) Standardized Demonstration sites (“test beds”) to support the evaluation of sensors, equipment, and technologies to detect UXO. Sequim Bay in Washington State was evaluated as a potential test bed and was determined to meet initial qualifying criteria with respect to environmental setting, and operational, logistical, and facilities support provided by the Pacific Northwest National Laboratory (PNNL).

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2021

Structure-preserving numerical discretizations for domains with boundaries

This SAND report documents Exploratory Express LDRD Project 223790, "Structure-preserving numerical discretizations for domains with boundaries", which developed a method to incorporate consistent treatment of domain boundaries and arbitrary boundary conditions in discrete exterior calculus (DEC) for arbitrary polygonal (2D) and tensor-product structure prism (3D) grids. The new DEC required the development of novel discrete exterior derivatives, boundary operators, wedge products and Hodge stars. This was accomplished through the use of boundary extension and the blending of known 2D operators on the interior with 1D operators on the boundary. The Hodge star was based on the Voronoi Hodge star, and retained the limitation of a triangular circumcentric primal or dual grid along with low-order accuracy. In addition to the new DEC, two related software packages were written: one for the study of DEC operators on arbitrary polygonal and polyhedral grids using both symbolic and numerical approaches and one for a (thermal) shallow water testbed using TRiSK-type numerics. Immediately relevant (already funded, through CANGA) followup work is the development of a high-order, geometrically flexible Hodge star and structure-preserving, high-order, oscillation-limiting transport operators (using WENO) for n-forms on arbitrary 2D and 3D grids. This will provide all of the machinery required for a high-order version of TRiSK with boundaries on arbitrary 2D and tensor-product 3D grids, which is applicable to both the atmospheric (CRM in E3SM-MMF) and oceanic (MPAS-O) components of E3SM.

97 MATHEMATICS AND COMPUTING↗