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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 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Thermal and Mechanical Energy Performance Analysis of Closed-loop Systems in Hot-Dry-Rock and Hot-Wet-Rock Reservoirs

To understand the potential and limitations for recovering thermal and mechanical energy from closed-loop geothermal systems a collaborative study is underway that will investigate an array of system configurations, working fluids, geothermal reservoir characteristics, operational periods, and heat transfer enhancements. Closed-loop geothermal systems are distinguished from hydrothermal or enhanced geothermal systems (EGS) in that the working fluid only circulates through drilled boreholes. Principal objectives of this study are to determine upper limits for thermal and mechanical energy recovery and optimal operational and configuration parameters for each scenario. Teams of scientists and engineers are applying a suite of numerical simulation and analytical tools to model the heat recovery from closed-loop geothermal systems, and then optimizing operational and configuration parameters to maximize the thermal and mechanical energy recovery. Results from the suite of numerical simulators and analytical tools, such as outlet and inlet states and temperature profiles in the geothermal reservoir over time are intercompared to increase confidence in the analysis. This paper documents the study findings for closed-loop systems in hot-dry-rock and hot-wet-rock reservoirs, where water is the working fluid. The characteristics of the hot-dry-rock reservoir were based on the U.S. Department of Energy's Utah Frontier Observatory for Research in Geothermal Energy (FORGE) site, near Milford Utah. Two objective functions are defined to optimize the operational and configuration parameters of the system, one each for the recovery of mechanical and thermal energy over the period of operation. For both objective functions, a surface plant thermal to mechanical energy conversion factor and an energy drilling cost is required. In keeping with the study objectives the surface plant conversion factor is determined from a second-law of thermodynamics analysis of a generic binary plant, and drilling costs are based on those from the Utah FORGE site and current national electrical costs.

closed-loop geothermal systems↗
DOE OSTI2021

Thermal and Mechanical Energy Performance Analysis of Closed-loop Systems in Hot-Dry-Rock and Hot-Wet-Rock Reservoirs

To understand the potential and limitations for recovering thermal and mechanical energy from closed-loop geothermal systems a collaborative study is underway that will investigate an array of system configurations, working fluids, geothermal reservoir characteristics, operational periods, and heat transfer enhancements. Closed-loop geothermal systems are distinguished from hydrothermal or enhanced geothermal systems (EGS) in that the working fluid only circulates through drilled boreholes. Principal objectives of this study are to determine upper limits for thermal and mechanical energy recovery and optimal operational and configuration parameters for each scenario. Teams of scientists and engineers are applying a suite of numerical simulation and analytical tools to model the heat recovery from closed-loop geothermal systems, and then optimizing operational and configuration parameters to maximize the thermal and mechanical energy recovery. Results from the suite of numerical simulators and analytical tools, such as outlet and inlet states and temperature profiles in the geothermal reservoir over time are intercompared to increase confidence in the analysis. This paper documents the study findings for closed-loop systems in hot-dry-rock and hot-wet-rock reservoirs, where water is the working fluid. The characteristics of the hot-dry-rock reservoir were based on the U.S. Department of Energy’s Utah Frontier Observatory for Research in Geothermal Energy (FORGE) site, near Milford Utah. Two objective functions are defined to optimize the operational and configuration parameters of the system, one each for the recovery of mechanical and thermal energy over the period of operation. For both objective functions, a surface plant thermal to mechanical energy conversion factor and an energy drilling cost is required. In keeping with the study objectives the surface plant conversion factor is determined from a second-law of thermodynamics analysis of a generic binary plant, and drilling costs are based on those from the Utah FORGE site and current national electrical costs.

Closed-loop geothermal systems, hot-dry-rock, hot-↗
DOE OSTI2017

Report on the Economic Optimization of a Demonstration Case for a Static N-R HES Configuration using RAVEN

The synthetic time history generation algorithm in RAVEN has been extensively tested and used to perform qualitative assessments of the statistical characteristics of the net demand vs. demand for different values of the penetration of wind generation. Reported results highlight the need to consider the impact of variable renewable on the electricity net demand profile, due to the increase in its volatility with increased wind penetration. This analysis provides a strong foundation for the modeling and simulation needs expressed under the "Nuclear-Renewable Hybrid Energy Systems" (NRHES) project. Following this confirmative analysis the entire stochastic optimization framework has been tested in a demo case. The case chosen is an optimization driven by profitability for a system composed by a nuclear plant and a hydrogen production industrial process. This type of economical analysis is aimed to assess the capability of a hybrid system to penetrate the current energy market. In this sense it differs from the approach suggested under NRHES, where a cost minimization approach is suggested. This analysis is instead aimed to show the flexibility of the developed framework, e.g. for the evaluation of retrofitting projects of already existing plants. The system considered is subject to variable prices of electricity, which are simulated using the algorithm for the production of synthetic time histories. The physical system is considered without inertia so that it can be replaced by dispatching rules based on the highest marginal profit. Two optimization problems have been considered, for the first the size of the nuclear power plant is fixed and the optimization variable is the capacity of the hydrogen production plant. For the second, both plant sizes are optimization parameters while the overall capital expenditure is caped. The economical figures of merits considered are the Internal Rate of Return (IRR) and/or Profitability Index (PI) for the first one (since no cap is placed on the investment size) and Net Present Value (NPV) and/or IRR for the second one where the capital expenditure is constrained. Economic input data concerning capital costs, size-scaling factors, and operational costs for both plants have been collected from literature in order to achieve a simulation as realistic as possible. More work will be needed to obtain even more realistic numbers, possibly from industrial partners, and considering market elasticity for the hydrogen market. In order to perform the optimization of the cases described above, the economical external RAVEN module (CashFlow) for financial analysis has been improved in flexibility and generality. Some improvements have also been made to the optimization algorithm for a more efficient treatment of the boundary constrains. In conclusion three major results have been obtained: a) collection of the economical parameters characterizing the nuclear power plants and hydrogen production plants, b) extension of the financial analysis module (CashFlow) to drive the calculation of all needed cash flow streams and c) the testing of the full framework in a nearly final configuration.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Characterizing the Roles of Biogeochemical Cycling and Ocean Circulation in Regulating Marine Copper Distributions

Copper (Cu) is a key micronutrient for marine phytoplankton. Its oceanic biogeochemical cycle has elicited considerable attention due to dissolved Cu exhibiting a unique linear profile with depth. Several processes have been proposed for explaining this behavior. Here, in this study, we characterize the relationships between the observed Cu, PO 4 3– , and Si on a global scale. We find that the depth profiles of Cu resemble those of Si more than of PO 4 3– in the global ocean. To understand their relationships, we couple the biogeochemical and internal circulation processes in a model, fitting optimal Cu:PO 4 3– uptake ratios and remineralization length-scales to replicate the marine Cu distributions. The modeling results suggest that Cu uptake needs in the Southern Ocean are substantially higher than those in other oceanic regions. In addition, our modeling results indicate a deep Cu remineralization in the global ocean. We offer an alternative mechanism that relies on biogeochemical cycling and internal circulation to produce the linear depth profiles of dissolved Cu. Our results suggest that diatoms are likely the major phytoplankton dominating oceanic Cu cycling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Optimizing aluminum oxide passivation layers—Laser-induced plasmas for layer formation, real-time diagnostics, and layer evaluation

Molten salts have beneficial thermophysical and electrolytic properties, but the aggressive nature of molten salts requires corrosion mitigation strategies, such as structural material surface treatment. In this study, a laser-induced breakdown spectroscopy (LIBS) system was used to simultaneously ablate and monitor de-excitation spectra to form and identify dense alumina passivation layers. Additionally, high-frequency (kHz) LIBS imaging allowed rapid elemental mapping and depth profiling for surface O/Al ratios via minimally destructive analysis. The paired t-test rejected the null hypothesis that air and Ar cover gases were equivalent (p = 0.00012), and the analysis of variance (ANOVA) showed that overlap between shots (p = 0.03112) and cover gas flow rate (p = 0.02729) were statistically significant. At 75% overlap, the O/Al ratio increased to 10% ± 2%, and 90% overlap rose further to 31% ± 2%. Regardless of overlap, tuning the gas flow from 0.5 to 2.5 L min −1 enhanced the O/Al ratio by 24% ± 4%. LIBS depth profiling showed a 3× increase in layer thickness from 75% to 90% overlap. Molecular band peaks of AlO, a precursor to Al 2 O 3 found during treatment, suggest that band intensity could be used for real-time Al 2 O 3 optimization. Ultimately, by adjusting laser spot overlap and cover gas flow rate, a 266 nm laser was shown to form Al 2 O 3 layers on an Al6061 sample, with cover gas flow rate primarily affecting the O/Al ratio and layer thickness correlating with laser spot overlap. This combination of molecular spectra collection, imaging, and depth profiling demonstrated the robust layer analysis capabilities of LIBS.

Corrosion↗
DOE OSTI2021

A Hybrid Energy System Workflow for Energy Portfolio Optimization

This manuscript develops a workflow, driven by data analytics algorithms, to support the optimization of the economic performance of an Integrated Energy System. The goal is to determine the optimum mix of capacities from a set of different energy producers (e.g., nuclear, gas, wind and solar). A stochastic-based optimizer is employed, based on Gaussian Process Modeling, which requires numerous samples for its training. Each sample represents a time series describing the demand, load, or other operational and economic profiles for various types of energy producers. These samples are synthetically generated using a reduced order modeling algorithm that reads a limited set of historical data, such as demand and load data from past years. Numerous data analysis methods are employed to construct the reduced order models, including, for example, the Auto Regressive Moving Average, Fourier series decomposition, and the peak detection algorithm. All these algorithms are designed to detrend the data and extract features that can be employed to generate synthetic time histories that preserve the statistical properties of the original limited historical data. The optimization cost function is based on an economic model that assesses the effective cost of energy based on two figures of merit: the specific cash flow stream for each energy producer and the total Net Present Value. An initial guess for the optimal capacities is obtained using the screening curve method. The results of the Gaussian Process model-based optimization are assessed using an exhaustive Monte Carlo search, with the results indicating reasonable optimization results. The workflow has been implemented inside the Idaho National Laboratory’s Risk Analysis and Virtual Environment (RAVEN) framework. The main contribution of this study addresses several challenges in the current optimization methods of the energy portfolios in IES: First, the feasibility of generating the synthetic time series of the periodic peak data; Second, the computational burden of the conventional stochastic optimization of the energy portfolio, associated with the need for repeated executions of system models; Third, the inadequacies of previous studies in terms of the comparisons of the impact of the economic parameters. The proposed workflow can provide a scientifically defendable strategy to support decision-making in the electricity market and to help energy distributors develop a better understanding of the performance of integrated energy systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

A single-cell Arabidopsis root atlas reveals developmental trajectories in wild-type and cell identity mutants

In all multicellular organisms, transcriptional networks orchestrate organ development. The Arabidopsis root, with its simple structure and indeterminate growth, is an ideal model to investigate the spatiotemporal transcriptional signatures underlying developmental trajectories. To map gene expression dynamics across root cell types and developmental time, we built a comprehensive, organ-scale atlas at single cell resolution. In addition to estimating developmental progressions in pseudotime, we employed the mathematical concept of optimal transport to infer developmental trajectories and identify their underlying regulators. To demonstrate the utility of the atlas to interpret new datasets, we profiled mutants for two key transcriptional regulators at single cell resolution, shortroot and scarecrow. We report transcriptomic and in vivo evidence for tissue trans-differentiation underlying a mixed cell identity phenotype in scarecrow. Our results support the atlas as a rich community resource for unraveling the transcriptional programs that specify and maintain cell identity to regulate spatiotemporal organ development.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Spatially-resolved study of the Meissner effect in superconductors using NV-centers-in-diamond optical magnetometry

Non-invasive magnetic field sensing using optically-detected magnetic resonance of nitrogen-vacancy centers in diamond was used to study spatial distribution of the magnetic induction upon penetration and expulsion of weak magnetic fields in several representative superconductors. Vector magnetic fields were measured on the surface of conventional, elemental Pb and Nb, and compound LuNi 2 B 2 C and unconventional iron-based superconductors Ba 1-x K x Fe 2 As 2 (x = 0.34 optimal hole doping), Ba(Fe 1-x Co x )2As2 (x = 0.07 optimal electron doping), and stoichiometric CaKFe 4 As 4 , using variable-temperature confocal system with diffraction-limited spatial resolution. Magnetic induction profiles across the crystal edges were measured in zero-field-cooled and field-cooled conditions. While all superconductors show nearly perfect screening of magnetic fields applied after cooling to temperatures well below the superconducting transition, T c , a range of very different behaviors was observed for Meissner expulsion upon cooling in static magnetic field from above T c . Substantial conventional Meissner expulsion is found in LuNi 2 B 2 C, paramagnetic Meissner effect is found in Nb, and virtually no expulsion is observed in iron-based superconductors. In all cases, good correlation with macroscopic measurements of total magnetic moment is found.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Coordination of Energy Storage and Distributed Generation for Voltage Control and Peak-valley Filling

The increasing penetration of distributed energy resources (DERs) in distribution network (DN) poses challenges on voltage control. In addition, the growing integration of DERs also reshapes the traditional load profile. To comprehensively address the voltage control and peak-valley filling in DN, this paper proposes a model predictive control (MPC) based optimization framework. The proposed method can achieve coordinated voltage control and peak-valley filling by adjusting the reactive power output from distributed generations (DGs) and the charging/discharging of energy storage systems (ESS). The performance of the proposed method is demonstrated by simulations on a modified IEEE-123 bus system.

Zhang, Zhengfa [University of Tennessee, Knoxville↗
DOE OSTI2021

Quantifying Uncertainty in Tortuosity Estimates for Porous Electrodes

Measuring tortuosity in porous electrodes is important for understanding rate capability and optimizing design. Here, we describe an approach to determine electrode tortuosities and quantify the associated uncertainties by fitting a P2D model to discharge profiles from a standard rate capability test. A dimensionless current is identified as a design-of-experiment parameter that can be used to identify experiments that return confident estimates of tortuosity, even when other model parameters are not known with certainty. This approach is applied to analysis of L i x V 3 O 8 (LVO) electrodes and L i x N i 0.33 M n 0.33 C o 0.33 O 2 (NMC) electrodes. The details of the assumptions made in these measurements and their impact on the reported uncertainties are discussed. We also perform an uncertainty analysis on the standard method for quantifying tortuosity in the literature: electrochemical impedance spectroscopy collected under blocking electrolyte conditions. We find that confident estimates can be obtained using this approach even when uncertainties in equivalent circuit model parameters are considered.

25 ENERGY STORAGE↗
DOE OSTI2023

Autonomous Controls For Reactor Technologies (acorn)

ACORN (Autonomous Controls fOr Reactor techNologies) software utilizes data, obtained from an experimental test bed and/or simulation, to implement a control command for microreactor operation. Command examples include a change to the temperature profile, power profiles, heat fluxes, etc. The control command recommended by the code is derived based on future predicted states of a microreactor, allowing proactive optimal and autonomous microreactor operation. The software is written in Python languages. The current software supports autonomous temperature controls of heat pipe simulator and autonomous heat flux controls of a 37 heat pipe non-nuclear testbed simulator (or its surrogate models).

Lin, Linyu [Idaho National Laboratory (INL), Idaho↗
DOE OSTI2022

MemLeap GPU Memory Profiler

MemLeap is a GPU Memory Profiler built atop Nvbit (NVidia Binary Instrumentation Tool) framework. It analyzes memory accesses to memory objects in GPU memory, including Unified Memory, to optimize memory usage and reveal performance bottlenecks.

Peng, Bo↗
DOE OSTI2019

A Moment-Based Polarimetric Radar Forward Operator for Rain Microphysics

There is growing interest in combining microphysical models and polarimetric radar observations to improve our understanding of storms and precipitation. Mapping model-predicted variables into the radar observational space necessitates a forward operator, which requires assumptions that introduce uncertainties into model–observation comparisons. These include uncertainties arising from the microphysics scheme a priori assumptions of a fixed drop size distribution (DSD) functional form, whereas natural DSDs display far greater variability. To address this concern, this study presents a moment-based polarimetric radar forward operator with no fundamental restrictions on the DSD form by linking radar observables to integrated DSD moments. The forward operator is built upon a dataset of >200 million realistic DSDs from one-dimensional bin microphysical rain-shaft simulations, and surface disdrometer measurements from around the world. This allows for a robust statistical assessment of forward operator uncertainty and quantification of the relationship between polarimetric radar observables and DSD moments. Comparison of “truth” and forward-simulated vertical profiles of the polarimetric radar variables are shown for bin simulations using a variety of moment combinations. Higher-order moments (especially those optimized for use with the polarimetric radar variables: the sixth and ninth) perform better than the lower-order moments (zeroth and third) typically predicted by many bulk microphysics schemes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Measurement techniques using the electron beam profile scanner at the Fermilab Main Injector

This work presents techniques for non-invasive transverse profile measurements of high-intensity proton beams using an Electron Beam Profile Scanner (EBPS). The EBPS utilizes low-energy electrons as a probe to analyze the transverse size of proton beams, allowing for potential analysis on a single-bunch basis. Recent upgrades to the Fermilab Main Injector have enhanced beam power on target to 1 MW, with future developments targeting 2 MW. The higher beam power has increased the demand for non-invasive diagnostics, as invasive methods can disrupt operations.The techniques presented include 1) the slow scan technique, which serves as a proof of concept for the probe beam, 2) the one-shot scan technique for measuring horizontal beam profiles, and 3) the raster scan technique for analyzing horizontal beam profiles as a function of the longitudinal distribution of the beam. The profiles obtained will be crucial for studying and understanding instabilities in high-power, high-intensity proton beams. This will contribute to optimizing the operation of high-power proton accelerators by minimizing beam loss, activation, and damage to both the diagnostics and the accelerator components.

Mwaniki, Matilda [IIT, Chicago]↗
DOE OSTI2025

Optimizing 4d Emittance Measurements Using the Pinhole Scan Technique

Accurate measurement of electron beam emittance is essential for optimizing high-brightness electron sources. The Pinhole Scan Technique measures the 4D phase space and hence the emittance by measuring the beam profile after clipping the beam using a pinhole followed by a drift section and then scanning the beam over the pinhole. This technique has been implemented in low energy (< 200 keV) beamlines at both Cornell University and Arizona State University. However, the technique poses several practical challenges. In this work, we analyze and address key issues affecting the 4D phase space and emittance measurements using this technique. We identify and investigate sources of inaccuracies like the pinhole aspect ratio, beam divergence, position-momentum correlations in the phase space, and the point-spread-function of the detector and suggest techniques to minimize them. Our findings offer a pathway to more accurate 4D phase space characterization in advanced electron beam systems.

42 ENGINEERING↗
DOE OSTI2018

Analysis of Favorable Process Conditions for the Manufacturing of Thin-Wall Pieces of Mild Steel Obtained by Wire and Arc Additive Manufacturing (WAAM)

Here, one of the challenges in additive manufacturing (AM) of metallic materials is to obtain workpieces free of defects with excellent physical, mechanical, and metallurgical properties. In wire and arc additive manufacturing (WAAM) the influences of process conditions on thermal history, microstructure and resultant mechanical and surface properties of parts must be analyzed. In this work, 3D metallic parts of mild steel wire (American Welding Society-AWS ER70S-6) are built with a WAAM process by depositing layers of material on a substrate of a S235 JR steel sheet of 3 mm thickness under different process conditions, using as welding process the gas metal arc welding (GMAW) with cold metal transfer (CMT) technology, combined with a positioning system such as a computer numerical controlled (CNC) milling machine. Considering the hardness profiles, the estimated ultimate tensile strengths (UTS) derived from the hardness measurements and the microstructure findings, it can be concluded that the most favorable process conditions are the ones provided by CMT, with homogeneous hardness profiles, good mechanical strengths in accordance to conditions defined by standard, and without formation of a decohesionated external layer; CMT Continuous is the optimal option as the mechanical properties are better than single CMT.

36 MATERIALS SCIENCE↗
DOE OSTI2018

On Concavity and Utilization Analytics of Wide-Area Network Transport Protocols

Wide-area data transfers in high-performance computing infrastructures and big data applications are increasingly carried over dynamically provisioned dedicated network connections, which provide high capacities with no competing traffic. Throughput of TCP and UDT over wide-area connections depends, often in a complex non-linear way, on the congestion control mechanism, buffer sizes, and the number of parallel streams. In addition, our extensive TCP and UDT throughput measurements and time traces over a suite of physical and emulated 10 Gbps connections with 0-366 ms round-trip times (RTTs) show significant statistical and temporal variations. Consequently, parameter selection and optimization for transport methods require data analytics to complement analytical throughput models. We present analytics based on the concavity-convexity of throughput profiles which provide insights into peak throughput and superior/inferior trend compared to linear interpolations based on RTT. In particular, we propose the utilization-concavity coefficient, a scalar metric that incorporates both utilization and concavity profile to characterize the overall performance of a transport protocol. These measurements-based anaytics enable us to select a transport protocol and its parameters for a given host and connection configuration to achieve high throughput with statistical guarantees.

Rao, Nageswara↗
DOE OSTI2017

RISK MONITORING CAPABILITES FROM DYNAMIC PRA DATA

Risk Monitors (RMs) are software tools that are employed in nuclear power plants to monitor the safety properties of the plant itself during operation. These safety properties are generated using classical PRA methods which are typically based on static Boolean structures such as Fault-Trees (FTs) and Event-Trees (ETs). The outcomes of these methods are Core Damage Frequency (CDF) and risk importance values of plant components (e.g., valves and pumps). Examples of Risk Importance Measures (RIMs) commonly used are: Risk Achievement Worth (RAW), Risk Reduction Worth (RRW), Birnbaum (B) and Fussell-Vesely (FV) [1,2]. In a RM these values are updated in real time once plant components status is updated (e.g., under maintenance, off-line, testing). In addition, RMs can be used to optimize maintenance schedules so those safety features of the plant are below plant standard values. This paper presents an approach to create temporal profiles of RIMs (i.e., RM capabilities) given a temporal change of the plant configuration. Instead of employing data generated by ETs and FTs, the proposed approach will employ data generated by Dynamic PRA methods. In contrast to classical PRA methods, Dynamic PRA methods couple stochastic methods with safety analysis codes to determine risk associate to complex systems such as nuclear plants. Compared to classical PRA methods, they can evaluate with higher resolution the safety impact of timing and sequencing of events on the accident progression. We will describe how classical RIMs can be generated by Dynamic PRA data and then we will show how the temporal profiles of the RIMs can be generated given a temporal profile of the system configuration.

97 MATHEMATICS AND COMPUTING↗