Search NASA⌕ Search

SEARCH · Search NASA

Results for “Hydros”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 541 records · Page 30

Assessing the Impact of Renewable Energy Sources to Achieve Net Zero Emissions

The mass generation of green energy through the pathway of Renewable Energy Sources (RES), is one of the major decisive components contributing to the concept of decarbonization. The energy sector assessment reveals that out of per kWh energy produced, renewable energy emits between 9 and 1000 gCO2 equivalent on a life-cycle basis. Contemplating the literature and the latest reports released by world-wide energy department(s), this study presents a comprehensive concept of carbon footprint, its causes and effects including major impact on biodiversity and human life. The study discusses the substantial steps taken by developing countries like India in leveraging RES for the production of energy and its progressive impact on ecology. The discussion would be inclusive of major change and transformation which has brought significant drop of 16% in the greenhouse gas (GHG) emissions by installation of 104.9 GW of RES excluding Hydro. The appropriate steps taken forward therefore align with the Sustainable Development Goals (SDGs) of the United Nation (UN) in achieving net zero emission (NZE).

decarbonization↗

Development of a Platform at the Matter in Extreme Conditions End Station for Characterization of Matter Heated by Intense Laser-Accelerated Protons

High intensity short-pulse lasers have made possible the generation of energetic proton beams, unlocking numerous applications in high energy density science. One such application is uniform and isochoric heating of materials to the warm dense matter (WDM) state. We have developed a new experimental platform to simultaneously create and probe warm dense matter at the Matter in Extreme Conditions (MEC) end station at the Linac Coherent Light Source (LCLS). The short pulse optical laser (delivering up to 1 J in 45 fs) and the ultra-bright LCLS x-ray laser with tunable frequency respectively deliver high power required to heat materials to WDM and precision-timed high-resolution x-rays to probe them. The laser-accelerated proton beam driven from a flat 1.5 μm Cu foil was first measured then directed to a secondary sample of Al or polypropylene, typically 300-400 μm away. The time evolution of the sample electron temperature was measured using streaked optical pyrometry, where we observed a peak temperature of 0.9 0.15 eV on the rear surface of an Al sample heated by the proton beam. Here, the simulations using the hybrid-PIC code LSP and the rad-hydro code HELIOS show that a measured proton beam can heat Al to approximately 4 eV and polypropylene to 1 eV if instead focused by a hemispherical Cu target. Through additional LSP simulations, we anticipate creating hotter warm dense matter states (20 eV) by increasing the laser energy to 10 J and keeping the other laser parameters fixed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Matrix Diffusion Controls Mountain Hillslope Groundwater Ages and Inferred Storage Dynamics

Groundwater age distributions provide fundamental insights on coupled water and biogeochemical processes in mountain watersheds. Field-based studies have found mixtures of young and old-aged groundwater in mountain catchments underlain by bedrock; yet, the processes that dictate these groundwater age distributions are poorly understood. In this work, we use the coupled ParFlow-CLM integrated hydrologic and EcoSLIM particle tracking models to simulate groundwater age distributions on a lower montane hillslope in the East River Watershed, Colorado (USA). We develop a convolution-based approach to propagate fracture-matrix diffusion processes to the EcoSLIM advection-dominated age distributions. We compare observed 3 H and 4 He concentrations from two groundwater wells against model predictions that have varying advective transport times and matrix diffusion magnitudes. Based on a Monte Carlo analysis that considers uncertain matrix and fracture parameters, we find that matrix diffusion is needed to jointly predict 3 H and 4 He observations at both wells. The advection-dominated age distributions lack adequate mixing of young and old-aged water to capture the observed co-occurrence of 3 H and 4 He. The model scenario that best matches the 3 H, 4 He, and water level observations when considering both advective flowpath and matrix diffusion mixing processes has a dynamic bedrock groundwater reservoir that is susceptible to considerable storage losses during low-snow periods. This dynamic groundwater system amplifies the need to assimilate deeper bedrock groundwater into watershed hydro-biogeochemical predictions. This work further highlights the importance of considering matrix diffusion when interpreting environmental tracers in bedrock groundwater systems.

54 ENVIRONMENTAL SCIENCES↗

Future climate doubles the risk of hydraulic failure in a wet tropical forest

Summary Future climate presents conflicting implications for forest biomass. We evaluate how plant hydraulic traits, elevated CO 2 levels, warming, and changes in precipitation affect forest primary productivity, evapotranspiration, and the risk of hydraulic failure. We used a dynamic vegetation model with plant hydrodynamics (FATES‐HYDRO) to simulate the stand‐level responses to future climate changes in a wet tropical forest in Barro Colorado Island, Panama. We calibrated the model by selecting plant trait assemblages that performed well against observations. These assemblages were run with temperature and precipitation changes for two greenhouse gas emission scenarios (2086–2100: SSP2‐45, SSP5‐85) and two CO 2 levels (contemporary, anticipated). The risk of hydraulic failure is projected to increase from a contemporary rate of 5.7% to 10.1–11.3% under future climate scenarios, and, crucially, elevated CO 2 provided only slight amelioration. By contrast, elevated CO 2 mitigated GPP reductions. We attribute a greater variation in hydraulic failure risk to trait assemblages than to either CO 2 or climate. Our results project forests with both faster growth (through productivity increases) and higher mortality rates (through increasing rates of hydraulic failure) in the neo‐tropics accompanied by certain trait plant assemblages becoming nonviable.

54 ENVIRONMENTAL SCIENCES↗

Recovery of Oxpure 612C-50 Coconut Carbon Particles Using Bump Arrays

Cyanide is used to leach gold from crushed ore (solid matrix) into a gold cyanide solution. The gold is extracted from the cyanide solution by adsorption onto activated carbon. The gold extraction process occurs when the activated coconut carbon is placed into tanks that contain the gold cyanide solution either in a batch process or into a continuous flow circuit. The coconut carbon is then removed from the solution for gold recovery. The use of the mesofluidic separation system (a deterministic lateral displacement system) can significantly reduce costs and waste generated from the process of removing the coconut carbon from the solution. In the coconut carbon recovery process used at many gold mines in Nevada, the gold is attached to carbon particles that are still in the cyanide liquor. The mesofluidic system can rapidly remove the gold bearing carbon particles from the cyanide liquor quickly and with no operating costs. The benefits include: • Reduce operational costs related to filtration and hydro-cyclones • Reduced acid usage for the elution gold stripping phase as only 25% of the fluids will follow the carbon particles to the final express lane when two mesofluidic systems are used in series This alternative particle removal techniques would be advantageous. A promising technique for removing larger particles from slurries is mesofluidic separation, similar to deterministic lateral displacement arrays or “bump” arrays [1] but operates at much larger flow rates. As described by Pease, et al. [2], “Bump arrays in deterministic lateral displacement devices separate large particles from small particles using arrays of staggered posts. Large particles, defined as those with radii larger than the distance between the edge of a post and the stagnation streamline from the next downstream post, must bump toward one side of the device, whereas particles smaller than this distance slalom from entrance to exit without net lateral displacement.” Unlike filters or sieves, the posts in the arrays that cause separation do not block or occlude particle flow but work because particles go around the posts. Unlike hydrocyclones separation, separation is not driven by particle density, because gravitational forces are unimportant to mesofluidic separation. Burns, et al., and Pease, et al., have shown that particles may be separated from complex suspensions, under turbulent flow conditions, and at industrially important flow rates [3-5]. They have also recently shown that mesofluidic devices may be arranged in series to increase separation performance [6]. In this paper, we evaluate the mesofluidic system for the separation of commercial OxPure GR 612 Charred Coconut shell particles as a proof of principle test for the rapid separation using the 1500 micron cut mesofluidic separator. We first describe the experimental system and conditions. We then present the experimental results. [1] Huang, L.R., E.C. Cox, R.H. Austin, J.C. Sturm. 2004. Continuous particle separation through deterministic lateral displacement. Science, 304, 987–990. https://doi.org/10.1126/science.1094567. [2] Pease L.F., J.A. Bamberger, C.A. Burns, and M.J. Minette. 2021. Large Particle Separation from Non-Newtonian Slurries using Bump Arrays. In Proceedings of the ASME 2021 Fluids Engineering Division Summer Meeting FEDSM2021-65904, V003T08A023. New York, New York: ASME. doi:10.1115/FEDSM2021-65904 [3] Burns C.A., T.G. Veldman, J. Serkowski, R.C. Daniel, X.-Y. Yu, M.J. Minette, L.F. Pease. 2021. Mesofluidic separation versus dead-end filtration. Separation and Purification Technology, 254, 117256. https://doi.org/10.1016/j.seppur.2020.117256. [4] Pease L.F., J.E. Serkowski, T.G. Veldman, J. Williams, X.-Y. Yu, M.J. Minette, J.A. Bamberger, C.A. Burns. 2021. Can Bump Arrays Separate Particles from Turbulent Flows?. In Proceedings of the ASME 2021 Fluids Engineering Division Summer Meeting FEDSM2021-67696, V003T08A024. New York, New York: ASME. doi:10.11

mesofluidic separation, slurry, bump array↗

New Developments and Capabilities Within WEC-Sim

WEC-Sim is an open-source software for simulating wave energy converters and has been actively developed and applied since its initial release in 2014 to simulate a wide variety of device archetypes. WEC-Sim is developed jointly by the National Renewable Energy Laboratory and Sandia National Laboratories within the MATLAB/SIMULINK environment. A general wave-to-wire model begins with a deployment site resource characterization, which is used to complete the hydrodynamic simulation of wave energy converters (WEC), with the power generation profile imported to a grid simulator to understand the influence on the local electrical network. While modeling the entire wave-to-wire is difficult and encompasses multiple time scales and physics, WEC-Sim is focused on the hydrodynamics simulation to predict, analyze, and optimize WEC dynamics and power performance. WEC-Sim simulations are performed in the time domain based on the radiation and diffraction method using hydrodynamics coefficients derived from boundary element method (BEM)-based frequency-domain potential flow solvers (e.g., WAMIT, NEMOH, Capytaine, or ANSYS-AQWA). With this level of modeling fidelity, WEC-Sim can handle floating body hydrodynamics, mechanical and electrical power generation methods, advanced control implementation, mooring systems, and other unique applications such as desalination. Additional WEC-Sim functionalities include pre-built Simulink blocks and MATLAB scripts that can simulate a wide range of floating systems and the corresponding auxiliary subsystems. The developers of WEC-Sim continue to release new versions of the software, at least annually, with the latest release in September 2022. These releases include bug fixes, updates to software documentation, as well as new features to expand WEC-Sim's capabilities to model a wide range of WEC concepts. This publication will highlight the new features added to WEC-Sim between versions 4.1.0 to 5.0.1, which spans a 2-year period from June 2020 to September 2022. New features described here include topics such as continuous integration checks, revised Morison Element and nonlinear hydro implementations, run directly from Simulink (required for hardware-in-the-loop execution), BEMIO updates to import Capytaine BEM hydrodynamics, addition of cable blocks, and new wave visualization features.

TIDAL AND WAVE POWER↗

Computer Model Calibration with Time Series Data Using Deep Learning and Quantile Regression

Computer models play a key role in many scientific and engineering problems. One major source of uncertainty in computer model experiments is input parameter uncertainty. Computer model calibration is a formal statistical procedure to infer input parameters by combining information from model runs and observational data. The existing standard calibration framework suffers from inferential issues when the model output and observational data are high-dimensional dependent data, such as large time series, due to the difficulty in building an emulator and the nonidentifiability between effects from input parameters and data-model discrepancy. To overcome these challenges, we, in this work, propose a new calibration framework based on a deep neural network (DNN) with long short-term memory layers that directly emulates the inverse relationship between the model output and input parameters. Adopting the “learning with noise” idea, we train our DNN model to filter out the effects from data-model discrepancy on input parameter inference. We also formulate a new way to construct interval predictions for DNN using quantile regression to quantify the uncertainty in input parameter estimates. Through a simulation study and real data application with the Weather Research and Forecasting Model Hydrological modeling system (WRF-Hydro), we show our approach can yield accurate point estimates and well-calibrated interval estimates for input parameters.

97 MATHEMATICS AND COMPUTING↗

GEOS-DEV/FORGE

This dataset is a repository that provides the input deck for numerical models associated with two Utah FORGE research projects: "Closing the Loop Between In situ Stress Complexity and EGS Fracture Compexity" (Project Number: 2-2446) and "Coupled Investigation of Fracture Permeability Impact on Reservoir Stress and Seismic Slip Behavior" (Project Number: 5-2428). Three kinds of simulation decks are included: (i) hydraulic fracturing simulation (HydroFrac folder), (ii) phase-field simulation (PhaseField folder), and (iii) thermo-hydro-mechanical simulation (ThermoHydroMech folder).

Cusini, Matteo [Lawrence Livermore National Labora↗

NRWAL (NLR formerly known as NREL Wind Analysis Library) [SWR-21-26]

NRWAL (NLR (National Laboratory of the Rockies) formerly known as NREL (National Renewable Energy Laboratory) Wind Analysis Library: A library of offshore wind cost equations (plus new energy technologies like marine hydro!) Easy equation manipulation without editing source code Full continental-scale integration with the NREL Renewable Energy Potential Model (reV) https://nrel.github.io/reV/ Ready-to-use configs for basic users Dynamic python tools for intuitive equation handling One seriously badass sea unicorn To get started with NRWAL, check out the NRWAL Config documentation or the NRWAL example notebook. You can also launch the notebook in an interactive jupyter shell right in your browser without any downloads or software using binder. Ready to build a model with NRWAL but don't want to contribute to the library? No problem! Check out the example getting started project here. Here is the important stuff: The NRWAL Equation Library. Default NRWAL Configs

Nunemaker, Jacob↗

inp2cjw

inp2cjw is a utility program for hierarchical finite element analysis which converts Abaqus formatted (inp) model output from CUBIT to a format (cjw) for HFEM and HFEM-Hydro modeling codes while introducing volume, facet, and edge material properties into the model. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-4551 O

Weiss, ChesterJ↗

Offshore Wind ENergy Simulation Toolkit (OWENS)

SAND2021-2751 O The Offshore Wind ENergy Simulation Toolkit (OWENS) is a collection of aerodynamic, structural, hydrodynamic, drivetrain, controls, composite structure and mesh preprocessing, and data postprocessing. OWENS is primarily an ontology, or glue code, pulling together many open-source and Sandia-developed libraries to model the aero-servo-hydro-elastic physics of wind and marine energy turbines. The toolkit’s intended use is for arbitrary aeroelastic rotor configurations analysis including vertical-axis wind turbines, horizontal-axis wind turbines, and analogous marine energy applications for fixed-bottom and floating configurations. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525

Owens, Brian↗

Hydroboost

HydroBoost is the most realistic revenue optimization tool for the hybridization of hydropower and battery energy storage systems to date. The innovative representation of how operators actually schedule hydropower in practice results in more realistic predictions of revenue and operations. Unlike other optimization tools, HydroBoost generates forecast energy prices with uncertainty to use in the optimization. This allows HydroBoost to give users a range of potential revenue with an upper bound using the perfect foresight pricing and a lower bound using a naive persistence forecast model. Additional forecast can be generated and used in the optimization, such as additive models, random forest, and neural networks to give further insight into potential revenue. HydroBoost has been designed to be applicable for both run-of-river and reservoir storage sites. The primary focus is on the day-ahead market and requires year-long data with an hour time-step. All time-series input and constraints are contained in an Excel worksheet for convince. The user will run the forecasting generation first with a Python script to give the optimization model the necessary requirements. Next the optimization is ran using Julia and results are generated and stored into a directory as csv files. HydroBoost includes an additional module to generate figures based on the results of the optimization simulation. The results help analyze the results and users to draw insights into how the hydro and battery systems are operated and the revenue each is producing. Additionally, the difference between the perfect foresight model and models that include forecast can easily be inspected.

Phillips, TylerB. [Idaho National Laboratory (INL)↗

FuelLib (Fuel Library) [SWR-25-26]

FuelLib is a library that utilizes the group contribution method (GCM) for calculating thermodynamic properties of hydro-carbon jet fuels. FuelLib utilizes the tables and functions of the GCM as proposed by Constantinou and Gani (1994) and Constantinou, Gani and O'Connel (1995), with additional physical properties discussed in Govindaraju & Ihme (2016). The code is based on Pavan B. Govindaraju's Matlab implementation of the GCM, and has been expanded to include additional thermodynamic properties and mixture properties. The fuel library contains gas chromatography (GC x GC) data for a variety of fuels ranging from simple single component fuels to complex jet fuels. The GC x GC data for POSF jet fuels comes from Edwards (2020).

Montgomery, David [National Renewable Energy Labor↗

A deformation-dependent coupled Lagrangian/semi-Lagrangian meshfree hydromechanical formulation for landslide modeling

Abstract The numerical modelling of natural disasters such as landslides presents several challenges for conventional mesh-based methods such as the finite element method (FEM) due to the presence of numerically challenging phenomena such as severe material deformation and fragmentation. In contrast, meshfree methods such as the reproducing kernel particle method (RKPM) possess unique features conducive to modelling extreme events such as the absence of a structured mesh and the ease of adaptive refinement, among others. While the semi-Lagrangian reproducing kernel (SL-RK) shape functions of RKPM defined in the current configuration have proven to be effective in extreme event modelling, the computational cost for the re-evaluation of the shape functions at every time step is costly. In this work, a deformation-dependent coupling of the Lagrangian reproducing kernel (L-RK) and SL-RK approximations is proposed for the solution of a hydro-mechanical formulation for effective simulations of landslides. The ramp function is constructed based on an equivalent plastic strain as a deformation-dependent transition from L-RK shape functions to SL-RK ones as the deformation progresses. The particular focus of the paper will be on modelling seepage-induced landslides with a mixed $$u$$ u – $$p$$ p formulation to couple the solid and fluid phases. Examples are presented to examine the effectiveness of this coupled Lagrangian/semi-Lagrangian reproducing kernel (L–SL RK) formulation and to highlight its performance in landslide modelling.

Baek, Jonghyuk↗

Optimization Formulations for Storage Devices with Disjoint Operating Modes

Optimizing State of Charge for Storage Resources Storage of generated energy has existed as a contributing resource within the power sector for more than a century in the case of pumped hydro storage. Even though most regional transmission organizations/independent system operators do not currently optimize state of charge (SOC) for storage, the SOC is an essential aspect of the operating characteristics of storage. This paper investigates the impact on computational performance of optimizing storage with explicit representation of SOC. To investigate the model, the paper considers two contexts, stand-alone and large-scale. Analysis of the stand-alone context helps to explain why the combination of features in the storage model results in a difficult problem. Numerical results for large-scale test cases verify that new tighter valid inequalities can improve the computation compared with the standard model in the literature.

Business & Economics↗

High-Resolution Fire Weather Index Data for the Conterminous US (1980–2099), Version 1

This dataset presents a suite of high-resolution fire weather index datasets calculated from observation (gridMet, Livneh, Daymet V4), reanalysis (AgERA5), downscaled hydro-climate projections over the conterminous United States (CONUS) based on multiple selected Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6). Aside from the daily FWI datasets, we also include a set of FWI extreme indicators at annual, seasonal, and monthly scales, including 1) fwixx: maximum FWI; 2) fwisa: mean FWI. For annual fwisa, it refers to the season with the maximum seasonal average; 3) fwils: Length of fire season over a specified period, where fire season is defined as the days exceeding the median value of the normalized FWI during the reference period (1980-1984); 4) fwixd: Number of extreme fire weather days over a specified period, where extreme day is defined as the day with FWI > the 95th percentile of the FWI during the reference period (1980-1984). All FWI datasets cover 1980-2020 baseline and the model simulated products including the downscaled products additionally include 2021-2099 near-future periods under the high-end (SSP585) emission scenario.

54 ENVIRONMENTAL SCIENCES↗

Cholla Galactic OutfLow Simulations (CGOLS)

These datasets contain full hydro-field snapshots from the galactic outflow simulations in the CGOLS suite, models I-V. The datasets were generated using the Cholla hydrodynamics code (https://github.com/cholla-hydro/cholla); descriptions of the models are in the associated publications (Schneider & Robertson 2018, ApJ; Schneider et al. 2018, ApJ; Schneider et al. 2020, ApJ; and Schneider & Mao, 2024, ApJ). Each hdf5 dataset is numbered according to the simulation time of the snapshot, in Myr. Fields include density, x momentum, y momentum, z momentum, total energy, and thermal energy (for models I - III), as well as a passive scalar field (models IV and V). 2 dimensional density and temperature projections, as well as slices along each midplane are also included if they exist.

79 ASTRONOMY AND ASTROPHYSICS↗

Utah FORGE 3-2417: Fiber-Optic Geophysical Monitoring of Reservoir Evolution - Workshop Presentation

This is a presentation on the Fiber-Optic Geophysical Monitoring of Reservoir Evolution at the Utah FORGE Milford Site project by Rice University, presented by Prof. Jonathan Ajo-Franklin. The project's objective was to develop an end-to-end fiber-optic sensing approach for EGS to track the initial zone of fracture creation, zones of connected mechanically compliant fractures, and zones of flowing fractures linking the injection/production well pair. This approach would also be used to integrate data into an improved thermo-hydro-mechanical model (THM). This presentation was featured in the Utah FORGE R&D Annual Workshop on September 8, 2023. The workshop provided a valuable opportunity to explore the progress made in each of the 17 Research and Development projects funded under Solicitation 2020-1 which aim to enhance our understanding of the crucial factors influencing the development of Enhanced Geothermal Systems (EGS) reservoirs and resources.

15 GEOTHERMAL ENERGY↗