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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

RODeO (Revenue Operation and Device Optimization Model) [SWR 20-67]

The Revenue, Operation, and Device Optimization (RODeO) model explores optimal system design and operation considering different levels of grid integration, equipment cost, operating limitations, financing, and credits and incentives. RODeO is a price-taker model formulated as a mixed-integer linear programming (MILP) model in the GAMS modeling platform. The objective is to maximizes the net revenue for a collection of equipment at a given site. The equipment includes generators (e.g., gas turbine, steam turbine, solar, wind, hydro, fuel cells, etc.), storage systems (batteries, pumped hydro, gas-fired compressed air energy storage, long-duration systems, hydrogen), and flexible loads (e.g., electric vehicles, electrolyzers, flexible building loads). The input data required by RODeO can be classified into three bins: 1) utility service data, which refers to retail utility rate information (meter cost, energy and demand charges), 2) electricity market data, which include energy and reserve prices, 3) other inputs, which refer to additional electrical demand, product output demand, technological assumptions, financial properties, and operational parameters.

Guerra Fernandez, Omar Jose↗
DOE OSTI2022

Motility Analysis of T-Cell Histories in Activation (Matcha) v0.1.0

Despite advances in microscopy, imaging techniques only capture a very small spatial and temporal fraction of T cell activity within a tissue. For this reason, we have pursued the development of a virtual T cell model. Matcha's objective is to design virtual T cells that move like biological T cells. The virtual T cells will match the speed and turning angle distributions of biological cells. In addition, Matcha will also attempt to match the volume patrolled by the biological cells and the dependence on speed and turning angle on the previous speed.

Rouson, Damian↗
DOE OSTI2023

CCSI Toolset 3.19 Release

CCSI Toolset 3.19 Release Highlights A gradient generation tool was developed to support GENN models in FOQUS. Certain machine learning tools train gradient-enhanced neural network (GENN) models which can be more accurate for complex datasets given a priori knowledge of model derivatives. However, the derivatives must be known beforehand and are not often available for process data. This tool automatically predicts the gradients for a training dataset in a form usable by common GENN trainers, such as Surrogate Modeling Toolbox. Support was added for Surrogate Modeling Toolbox GENN models in FOQUS, including updates to the run methods, node properties, test framework, documentation and optional dependencies list. Users can train/save Surrogate Modeling Toolbox gradient-enhanced neural network (GENN) models with custom objects and produce .pkl files compatible with the Machine Learning/Artificial Intelligence Plugin in FOQUS. A simpler implementation of the ordering algorithm in the Sequential Design of Experiments (SDOE) module was included. The SDOE examples documentation was updated. The Optimality-Based Design of Experiments was updated to improve the error handling when the results are None.

AS↗
DOE OSTI2022

Dark Energy Survey Year 3 Results: Measuring the Survey Transfer Function with Balrog

Abstract We describe an updated calibration and diagnostic framework, Balrog , used to directly sample the selection and photometric biases of the Dark Energy Survey (DES) Year 3 (Y3) data set. We systematically inject onto the single-epoch images of a random 20% subset of the DES footprint an ensemble of nearly 30 million realistic galaxy models derived from DES Deep Field observations. These augmented images are analyzed in parallel with the original data to automatically inherit measurement systematics that are often too difficult to capture with generative models. The resulting object catalog is a Monte Carlo sampling of the DES transfer function and is used as a powerful diagnostic and calibration tool for a variety of DES Y3 science, particularly for the calibration of the photometric redshifts of distant “source” galaxies and magnification biases of nearer “lens” galaxies. The recovered Balrog injections are shown to closely match the photometric property distributions of the Y3 GOLD catalog, particularly in color, and capture the number density fluctuations from observing conditions of the real data within 1% for a typical galaxy sample. We find that Y3 colors are extremely well calibrated, typically within ∼1–8 mmag, but for a small subset of objects, we detect significant magnitude biases correlated with large overestimates of the injected object size due to proximity effects and blending. We discuss approaches to extend the current methodology to capture more aspects of the transfer function and reach full coverage of the survey footprint for future analyses.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Reviews and syntheses: Opportunities for robust use of peak intensities from high-resolution mass spectrometry in organic matter studies

Abstract. Earth's biogeochemical cycles are intimately tied to the biotic and abiotic processing of organic matter (OM). Spatial and temporal variations in OM chemistry are often studied using direct infusion, high-resolution Fourier transform mass spectrometry (FTMS). An increasingly common approach is to use ecological metrics (e.g., within-sample diversity) to summarize high-dimensional FTMS data, notably Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). However, problems can arise when FTMS peak-intensity data are used in a way that is analogous to abundances in ecological analyses (e.g., species abundance distributions). Using peak-intensity data in this way requires the assumption that intensities act as direct proxies for concentrations. Here, we show that comparisons of the same peak across samples (within-peak) may carry information regarding variations in relative concentration, but comparing different peaks (between-peak) within or between samples does not. We further developed a simulation model to study the quantitative implications of using peak intensities to compute ecological metrics (e.g., intensity-weighted mean properties and diversity) that rely on information about both within-peak and between-peak shifts in relative abundance. We found that, despite analytical limitations in linking concentration to intensity, ecological metrics often perform well in terms of providing robust qualitative inferences and sometimes quantitatively accurate estimates of diversity and mean molecular characteristics. We conclude with recommendations for the robust use of peak intensities for natural organic matter studies. A primary recommendation is the use and extension of the simulation model to provide objective guidance on the degree to which conceptual and quantitative inferences can be made for a given analysis of a given dataset. Broad use of this approach can help ensure rigorous scientific outcomes from the use of FTMS peak intensities in environmental applications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A new metrics framework for quantifying and intercomparing atmospheric rivers in observations, reanalyses, and climate models

We present a new atmospheric river (AR) analysis and benchmarking tool, namely Atmospheric River Metrics Package (ARMP). It includes a suite of new AR metrics that are designed for quick analysis of AR characteristics via statistics in gridded climate datasets such as model output and reanalysis. This package can be used for climate model evaluation in comparison with reanalysis and observational products. Integrated metrics such as mean bias and spatial pattern correlation are efficient for diagnosing systematic AR biases in climate models. For example, the package identifies the fact that, in CMIP5 and CMIP6 (Coupled Model Intercomparison Project Phases 5 and 6) models, AR tracks in the South Atlantic are positioned farther poleward compared to ERA5 reanalysis, while in the South Pacific, tracks are generally biased towards the Equator. For the landfalling AR peak season, we find that most climate models simulate a completely opposite seasonal cycle over western Africa. This tool can also be used for identifying and characterizing structural differences among different AR detectors (ARDTs). For example, ARs detected with the Mundhenk algorithm exhibit systematically larger size, width, and length compared to the TempestExtremes (TE) method. The AR metrics developed from this work can be routinely applied for model benchmarking and during the development cycle to trace performance evolution across model versions or generations and set objective targets for the improvement of models. They can also be used by operational centers to perform near-real-time climate and extreme event impact assessments as part of their forecast cycle.

58 GEOSCIENCES↗
DOE OSTI2025

Model-based analysis of solute transport and potential carbon mineralization in the active layer of a hillslope underlain by permafrost with seasonal variability and climate change

Permafrost carbon, stored in frozen organic matter across vast Arctic and sub-Arctic regions, represents a substantial and increasingly vulnerable carbon reservoir. As global temperatures rise, the accelerated thawing of permafrost releases greenhouse gases, exacerbating climate change. However, freshly thawed permafrost carbon may also experience lateral transport by groundwater flow to surface water recipients such as rivers and lakes, increasing the terrestrial-to-aquatic transfer of permafrost carbon. Mobilization and subsurface transport mechanisms are poorly understood and not accounted for in global climate models, leading to high uncertainties in the predictions of the permafrost carbon feedback. Here, we focus on a hillslope in Endalen Valley, Svalbard, as a representative example of a high-Arctic hillslope underlain by continuous permafrost. We analyze solute transport in the form of a non-reactive tracer representing dissolved organic carbon (DOC) using a physics-based numerical model with the objective to study governing cryotic and hydrodynamic transport mechanisms relevant for warming permafrost regions. We first analyze transport times for DOC pools at different locations within the active layer under present-day climatic conditions and proceed to study susceptibility for deeper ancient carbon release in the upper permafrost due to thaw under different warming scenarios. Results suggest that DOC in the active layer near the permafrost table experiences rapid lateral transport upon thaw due to saturated conditions and lateral flow, while DOC close to the ground surface experiences slower transport due to flow in unsaturated soil. Deeper permafrost carbon release exhibits vastly different transport behaviors depending on warming and thaw rate. Gradual warming leads to small fractions of DOC being mobilized every year, while the majority moves vertically through percolation and cryosuction. Abrupt thaw resulting from a single very warm year leads to faster lateral transport times, similar to active layer DOC released in saturated conditions. Lastly, we analyze the potential susceptibility of DOC to mineralization to CO 2 prior to export due to soil moisture and temperature conditions. We find that high liquid saturation during transport coincides with very low mineralization rates and potentially inhibits mineralization into CO 2 before export. Overall, the results highlight the importance of subsurface hydrologic and thermal conditions for the retention and lateral export of permafrost carbon by subsurface flow.

Hamm, Alexandra [Stockholm Univ. (Sweden)] (ORCID:↗
DOE OSTI2021

No Galaxy Left Behind: Measuring the Transfer Function of the Dark Energy Survey with Balrog

In this dissertation, we describe a calibration and diagnostic framework called Balrog which was used to directly sample the selection and photometric biases of the Dark Energy Survey (DES) Year 3 (Y3) dataset. We systematically inject onto the single-epoch images of a random 20% subset of the DES footprint an ensemble of nearly 30 million realistic galaxy models derived from DES Deep Field observations. These augmented images are analyzed in parallel with the original data to automatically inherit measurement systematics that are often too difficult to capture with traditional generative models. The resulting object catalog is a Monte Carlo sampling of the DES transfer function and is used as a powerful diagnostic and calibration tool for a variety of DES Y3 science, particularly for the calibration of the photometric redshifts of distant "source" galaxies and magnification biases of nearer "lens" galaxies. The recovered Balrog injections are shown to closely match the photometric property distributions of the fiducial Y3 GOLD catalog, particularly in color, and capture the number density fluctuations from observing conditions of the real data within 1% for a typical galaxy sample. We find that Y3 colors are extremely well calibrated, typically within ~1-8 millimagnitudes, but for a small subset of objects we detect significant magnitude biases correlated with large overestimates of the injected object size due to proximity effects and blending. Finally, we discuss approaches to extend the current methodology to capture more aspects of the transfer function for future analyses.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Design and Performance Evaluation of a Resistive Control Using a Hydraulic PTO System for the TALOS Wave Energy Converter

This study is focused on developing a numerical model to evaluate the performance of a hydraulic PTO system for the TALOS Wave Energy Converter. The WEC device is described and the architecture of the hydraulic PTO system is presented with detail. The WEC is modeled using WEC-Sim, and the PTO is modeled using the Simscape Fluids library from Simulink. The hydraulic PTO is based on a constant pressure configuration that is suitable for WEC passive control. The hydraulic system is composed by a set of rectifying valves and two hydraulic accumulators that reduce the stiffness of the system and also serve as energy storage devices. One of the advantages of this hydraulic PTO architecture is the possibility of controlling the electric generator to operate around the optimal efficiency operating point. The main components of the hydraulic PTO are off-the-shelf devices that are commercially available, which will facility a future deployment of the designed system. The design variables used for this study are the accumulator size, the maximum pressure in the accumulators, the hydraulic motor maximum displacement, and the shaft speed in the electric generator. The performance of the system is evaluated individually, using sinusoidal inputs that replicates regular wave conditions. In addition to this, the numerical model of the PTO is coupled to a WEC-Sim simulation of the TALOS Wave Energy Converter with six PTOs to generate a wave-to-wire model. The main objective of this work is to present a comprehensive design methodology that could serve as a guideline for future research efforts focused on implementing control algorithms on multi degree of freedom WECs.

hydraulic systems↗
DOE OSTI2025

Structural uncertainty assessment for fire-engulfed objects in crosswind: Establishing credibility for a multiphysics wall-modeled large-eddy simulation paradigm

A structural uncertainty validation study for a large-scale, fire-engulfed, elevated object subjected to crosswind is presented to establish the credibility of a high-fidelity, low-Mach, turbulent reacting flow wall-modeled large-eddy simulation (WMLES) approach that includes multiphysics coupling to participating media radiation and conjugate heat transfer. To establish that WMLES can accurately predict surface quantities including drag and pressure coefficient in the low-Mach crosswind regime, a foundational elevated isothermal cylinder validation case is presented at a similar gap-to-diameter ratio of 0.25, spanning the subcritical to supercritical drag regime (Re 𝐷 = 1.1 × 10 5 and 4.3 × 10 5 , respectively). Here, this study exercised both static and dynamic coefficient LES (Smagorinsky and 𝑘 sgs ) with both local and exchange-based velocity sampling. Results showcase that the drag crisis (or the sudden drop in drag coefficient at increased Re 𝐷 ) is well captured when using an exchange-based dynamic coefficient WMLES methodology, while noting lack of mesh convergence and overall drag and pressure coefficient predictively when using a static coefficient, local velocity sampling WMLES. For the 𝒪⁡(10) m JP-8 liquid pool fire crosswind validation study presented, two experimental crosswind configurations (2 m/s and 9.5 m/s) are showcased for a fire-engulfed mock fuselage roughly 4 m in diameter. Using the best model-form practices identified in the isothermal study, dynamic coefficient 𝑘 sgs exchange-based WMLES fire validation findings demonstrate accurate peak irradiation and skin temperature predictions as a function of crosswind magnitude. Excessive yaw in the low-crosswind fuselage configuration, consistent with experimental findings, captured a significant predicted asymmetry in flame attachment and heat flux toward the downwind cylindrical cap—indicative of axial vortex structures transporting the flame along the upper and lower fuselage leeward surface. All fire mesh resolution simulations captured the experimental finding that as crosswind increased, predicted flame shape and peak irradiation magnitude onto the fuselage transitioned from a windward to a leeward cylinder location due to the migration of the upper- to lower-shear fuel/air mixing layer thereby demonstrating the novelty, significance, and credibility of this high-fidelity WMLES reacting flow framework.

Domino, Stefan Paul [Sandia National Laboratories ↗
DOE OSTI2022

Environmental design of low-head run-of-river hydropower in the United States: A review of facility design models

We state that the goal of run-of-river hydropower is to produce cost-competitive renewable electricity with minimal disruption of the natural riverine ecosystem. Modeling and feasibility analysis of alternative design options are crucial for developing new run-of-river hydropower projects. Our review shows that existing run-of-river hydropower design models focus on maximizing economic potential at high-head diversion schemes with limited consideration of environmental outcomes. Since nearly three-quarters of new hydropower potential in the United States is found at low-head sites and environmental performance standards are imperative to project success, new models are needed to address the multi-dimensional design challenges at these sites. To aid in formulating holistic models, we synthesize the performance objectives and design variables related to early-stage run-of-river facility design. The objectives span six potential impact areas, including hydrologic alteration, sediment continuity, water quality, aquatic species passage, social, and economic. Based on these reviews, we identify three key areas to enhance the capabilities of run-of-river hydropower design models. These are 1) expanded model formulations, 2) assessment of barrier effects, and 3) explicit environmental objectives. The resulting modeling improvements would accelerate the identification of run-of-river hydropower designs that minimize environmental impacts, promote economic competitiveness, and incorporate the value of non-power benefits.

13 HYDRO ENERGY↗
DOE OSTI2026

MONet/1000 Soils metagenome pathway modelling narrative w/ auto batch import

This narrative performs metabolic modeling and flux balance analysis (FBA) using metagenome-assembled genomes (MAGs) from the 1000 Soils samples, as described by Song et al. (2026, accepted). The set of MAGs (in FASTA format) is converted into a set of assembly objects compatible with functional annotation via RASTtk, yielding a set of genome objects that undergo metabolic modeling via OMEGGA. These genome objects are then used to conduct FBA, generating tables of metabolite uptake rates across the MAGs under investigation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Numerical Simulation of Infrasound Resonance in Underground Tunnel Structures

Remote observation of infrasound resonant signals emanating from underground tunnel structures could potentially allow the remote quantification of the geometry of the underground structures in which the signals were generated. However, the sensitivity of these observations to tunnel geometry and changes in that geometry are unknown. In this report we outline a numerical simulation study with the following three objectives: 1. Can we model infrasound resonance using numerical simulations? 2. What is the sensitivity of the modeled observations to changes in tunnel geometry or boundary conditions? And 3. Can we accurately model resonant observations of explosions occurring in Redmond Salt Mine in Central Utah. In this report we outline affirmative answers to the first two objectives, but we were unable to accurately model the Redmond Explosions due to numerical instability in the model of the complex structure of the mine. Recommendations for future work emphasize the need to acquire additional datasets and to explore a more data-based approach in which changes in data signatures are detected as a first step towards developing a method which inverts resonant infrasound signals for tunnel geometry.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Toward Improving the Generation Quality of Autoregressive Slot VAEs

Unconditional scene inference and generation are challenging to learn jointly with a single compositional model. Despite encouraging progress on models that extract object-centric representations (“slots”) from images, unconditional generation of scenes from slots has received less attention. This is primarily because learning the multiobject relations necessary to imagine coherent scenes is difficult. We hypothesize that most existing slot-based models have a limited ability to learn object correlations. We propose two improvements that strengthen object correlation learning. The first is to condition the slots on a global, scene-level variable that captures higher-order correlations between slots. Second, we address the fundamental lack of a canonical order for objects in images by proposing to learn a consistent order to use for the autoregressive generation of scene objects. Specifically, we train an autoregressive slot prior to sequentially generate scene objects following a learned order. Ordered slot inference entails first estimating a randomly ordered set of slots using existing approaches for extracting slots from images, then aligning those slots to ordered slots generated autoregressively with the slot prior. Our experiments across three multiobject environments demonstrate clear gains in unconditional scene generation quality. Detailed ablation studies are also provided that validate the two proposed improvements.

MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Development of a Conditioned System-Level Groundwater Model to Evaluate Long-Term Groundwater Impacts within a Performance Assessment - 20115

A preliminary performance assessment (PA) of single-shell tank Waste Management Area (WMA) A-AX located at the U.S. Department of Energy (DOE)'s Hanford Site in southeastern Washington is being conducted to satisfy the requirements of DOE Order 435.1 [1] as it relates to closure of the single-shell radioactive waste tanks in the WMA A-AX tank farms. A PA assesses the fate, transport, and impacts of radionuclides within a low-level radioactive waste disposal facility in its assumed closure configuration and the subsequent potential doses to humans over a 1,000-year compliance period and a 10,000-year performance evaluation period. The WMA A-AX preliminary PA evaluation is structured around the complementary use of process-level and system-level models to calculate the facility performance against established DOE Order 435.1 [1] performance objectives. Process-level models are those that represent a detailed phenomenological representation of processes of concern in the PA. Process models typically only represent one or a few of the components of the PA, such as groundwater flow and transport, and must be integrated with other modeling elements to perform PA calculations. System-level models are those that are abstracted from the process models, retaining the essential features of the process model, while allowing integration of all aspects of the PA in a single modeling framework. System-level models are often characterized by coarser numerical discretization, lower dimensionality, or other similar simplifications compared to the process-level model. Traditionally, a three-dimensional (3-D) process-level model is utilized primarily to evaluate the long-term impact on groundwater and the potential doses to individuals who consume contaminated groundwater. System-level models are also utilized to evaluate the groundwater pathway in PAs. These models typically have reduced dimensionality (1-D) and are conditioned utilizing flow fields (Darcy fluxes) and moisture content distributions that are abstracted from the process level models. The abstraction approach assures that the flow field in both models is consistent for a specific set of input parameters for flow, differing only in the discretization and dimensionality of the two models. The preliminary WMA A-AX PA incorporates a detailed representation of the geological system and hydraulic properties within the 3-D model STOMP{sup C} numerical code so that the effects of relevant features and processes on water flow and radionuclide transport in the subsurface can be evaluated. The complementary system-level model is developed utilizing the GoldSim{sup C} code to implement a simplified, 1-D equivalent model to represent the groundwater pathway. Contaminant transport through the vadose zone and unconfined aquifer for Tc-99 and I-129 were evaluated in each of the models. Adjustments to the saturated portion of the GoldSim{sup C} 1-D model were required to mimic the dispersion effect captured with the 3-D STOMP{sup C} model. Once this conditioning was conducted, highly similar results for the transport of Tc-99 and I-129 were achieved at the point of calculation, located 100 m downgradient from the WMA A-AX fenceline. These radionuclides represent elements that are regarded as primary dose drivers in the PA groundwater pathway analysis. The high degree of conformance between the two models suggests that the use of the equivalent 1-D system model is suitable for evaluating the full suite of radionuclides that will be released from the tank sources within WMA A-AX over the 1,000-year compliance period and over the 10,000-year evaluation period. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

How to form a wormhole

Abstract We provide a simple but very useful description of the process of wormhole formation. We place two massive objects in two parallel universes (modeled by two branes). Gravitational attraction between the objects competes with the resistance coming from the brane tension. For sufficiently strong attraction, the branes are deformed, objects touch and a wormhole is formed. Our calculations show that more massive and compact objects are more likely to fulfill the conditions for wormhole formation. This implies that we should be looking for wormholes either in the background of black holes and compact stars, or massive microscopic relics. Our formation mechanism applies equally well for a wormhole connecting two objects in the same universe.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Fast and accurate influenza forecasting in the United States with Inferno

Infectious disease forecasting is an emerging field and has the potential to improve public health through anticipatory resource allocation, situational awareness, and mitigation planning. By way of exploring and operationalizing disease forecasting, the U.S. Centers for Disease Control and Prevention (CDC) has hosted FluSight since the 2013/14 flu season, an annual flu forecasting challenge. Since FluSight’s onset, forecasters have developed and improved forecasting models in an effort to provide more timely, reliable, and accurate information about the likely progression of the outbreak. While improving the predictive performance of these forecasting models is often the primary objective, it is also important for a forecasting model to run quickly, facilitating further model development and improvement while providing flexibility when deployed in a real-time setting. In this vein I introduce Inferno, a fast and accurate flu forecasting model inspired by Dante, the top performing model in the 2018/19 FluSight challenge. When pseudoprospectively compared to all models that participated in FluSight 2018/19, Inferno would have placed 2nd in the national and regional challenge as well as the state challenge, behind only Dante. Inferno, however, runs in minutes and is trivially parallelizable, while Dante takes hours to run, representing a significant operational improvement with minimal impact to performance. Forecasting challenges like FluSight should continue to monitor and evaluate how they can be modified and expanded to incentivize the development of forecasting models that benefit public health.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗