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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 901 records · Page 50
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

The Shifting Role of mRUE for Regulating Ecosystem Production

To design a comprehensive view of ecosystem resource use, in this work we integrated parallel resource use efficiency observations into a multiple-resource use efficiency (mRUE) framework using a dynamic factor analysis model. Results from 56 site-years of eddy covariance data and mRUE factors for a site in the US Midwest show temporal dynamics and coherence (using Pearson’s R) among resources are associated with interannual variation in precipitation. Loading factors are derived from mRUE observations and quantify how strongly data are connected to the underlying ecosystem state. Water and light resource use loading factors are coherent at annual timescales (Pearson’s R of 0.86), whereas declining patterns of carbon use efficiency loading factors highlight the ecosystem’s trade-off between carbon uptake and respiration during the growing season. At annual and monthly timescales, influence decreases from ~85 to ~65% for loading factors for carbon use, while influence of light use loading factors peaks to ~60% at growing season timescales. Quantifying variation in ecosystem function provides novel insights into the temporal dynamics of changing significance of multiple resources to ecosystem function.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2011

Dynamic Loads Generation for Multi-Point Vibration Excitation Problems

A random-force method has been developed to predict dynamic loads produced by rocket-engine random vibrations for new rocket-engine designs. The method develops random forces at multiple excitation points based on random vibration environments scaled from accelerometer data obtained during hot-fire tests of existing rocket engines. This random-force method applies random forces to the model and creates expected dynamic response in a manner that simulates the way the operating engine applies self-generated random vibration forces (random pressure acting on an area) with the resulting responses that we measure with accelerometers. This innovation includes the methodology (implementation sequence), the computer code, two methods to generate the random-force vibration spectra, and two methods to reduce some of the inherent conservatism in the dynamic loads. This methodology would be implemented to generate the random-force spectra at excitation nodes without requiring the use of artificial boundary conditions in a finite element model. More accurate random dynamic loads than those predicted by current industry methods can then be generated using the random force spectra. The scaling method used to develop the initial power spectral density (PSD) environments for deriving the random forces for the rocket engine case is based on the Barrett Criteria developed at Marshall Space Flight Center in 1963. This invention approach can be applied in the aerospace, automotive, and other industries to obtain reliable dynamic loads and responses from a finite element model for any structure subject to multipoint random vibration excitations.

Shen, Lawrence↗
NASA NTRSDate not supplied

Impact of Canadian Wildfires on Mid Atlantic’s Region Air Quality: An Analysis Using ASDC Data

Wildfires pose a growing concern in North America due to their harmful impacts on air quality and public health, with increased wildfire activity in recent years leading to widespread smoke plumes that can transcend borders. The exposure of New York City (NYC), the most populous city in North America, to Canadian wildfire smoke highlights the substantial implications for public health and urban environments. To better understand the impact of Canadian wildfires on air quality in NYC, satellite data from the NASA Atmospheric Science Data Center (ASDC) at Langley Research Center, along with ground-based measurements and atmospheric modeling results, are analyzed. We examine concentrations of atmospheric aerosols—particularly PM2.5 particulate matter originating from Canadian wildfires—their dispersion patterns, and the duration and intensity of smoke events impacting NYC. Data from multiple satellites, such as those from the Earth Polychromatic Imaging Camera (EPIC), are synergistically used to identify regions affected by wildfires and estimate aerosol loading. Ground-based measurements, including data from air quality monitoring stations, provide localized information for validation and calibration purposes. The findings of this study contribute to our understanding of the impact of Canadian wildfires on NYC's air quality and emphasize the importance of monitoring and prediction of transboundary smoke events using data synthesized from multiple sources, such as those provided by the ASDC. This information is crucial for policymakers, public health officials, and residents in affected areas to develop effective strategies for mitigating the health risks associated with wildfire smoke and improving air quality during wildfire seasons. The utilization of ASDC data in this research highlights the critical role of atmospheric remote sensing in addressing the challenges posed by wildfires and their consequences on regional scales.

Ingrid Garcia-Solera↗
NASA NTRSDate not supplied

Analyzing the Impact of Canadian Wildfires on Air Quality in the U.S. Mid-Atlantic: with Data and Tools from NASA’s Atmospheric Sciences Data Center

Wildfires pose a growing concern in North America due to their harmful impacts on air quality and public health, with increased wildfire activity in recent years leading to widespread smoke plumes that can transcend borders. The exposure of New York City (NYC), the most populous city in North America, to Canadian wildfire smoke highlights the substantial implications for public health and urban environments. To better understand the impact of Canadian wildfires on air quality in NYC, satellite data from the NASA Atmospheric Science Data Center (ASDC) at Langley Research Center, along with ground-based measurements and atmospheric modeling results, are analyzed. We examine concentrations of atmospheric aerosols—particularly PM2.5 particulate matter originating from Canadian wildfires—their dispersion patterns, and the duration and intensity of smoke events impacting NYC. Data from multiple satellites, such as those from the Earth Polychromatic Imaging Camera (EPIC), are synergistically used to identify regions affected by wildfires and estimate aerosol loading. Ground-based measurements, including data from air quality monitoring stations, provide localized information for validation and calibration purposes. The findings of this study contribute to our understanding of the impact of Canadian wildfires on NYC's air quality and emphasize the importance of monitoring and prediction of transboundary smoke events using data synthesized from multiple sources, such as those provided by the ASDC. This information is crucial for policymakers, public health officials, and residents in affected areas to develop effective strategies for mitigating the health risks associated with wildfire smoke and improving air quality during wildfire seasons. The utilization of ASDC data in this research highlights the critical role of atmospheric remote sensing in addressing the challenges posed by wildfires and their consequences on regional scales.

Ingrid Garcia-Solera↗
DOE OSTI2022

Consolidated Hydropower Data Repository: Value and Opportunities

Hydropower is one of several types of generating assets that provides energy, capacity, and services to electric power systems. It does so under rubrics and objectives—market driven and regulated, internal and external to asset and fleet owners—that address reliability, cost, price, and, increasingly, flexibility of output. The aggregation of data from multiple hydropower units can provide insights into asset operations and maintenance practices and needs and assist in meeting hydropower objectives. This paper examines the concept and potential benefits of aggregating hydropower asset data—primarily supervisory control and data acquisition (SCADA) information—with examples of insights developed from data aggregated by the Hydropower Research Institute (HRI). Data aggregation as discussed herein, and as implemented by the HRI, extends beyond multiple units in a powerhouse and beyond multiple hydropower facilities in an electric utility fleet or river system. Examples of research and analytics from such aggregated datasets range from unit load dependency analyses to modeling sensor measurements to detect and diagnose anomalies in assets. These examples showed the benefits of utilizing the entire dataset for insights into how the sensor layout of a single unit or set of units compares to the hydropower industry overall. Such insights include whether additional sensors are needed to complete analyses or to make decisions. In addition, utilizing multiple sensors of the same kind within a unit can provide an indication of possible current or upcoming problems with equipment. Although other analyses are possible, their use requires the development of complex models and, potentially, access to types of data that are currently not included with the example dataset used in this study. However, the examples studied herein confirmed the value of data aggregation in the fleet and unit contexts, and the value extends beyond multiple units in a powerhouse and beyond multiple hydropower facilities in an electric utility fleet or river system. The assessments also provided insights into potential extensions to the data aggregation concept that could further add to their value to the hydropower community, and these are included in this document as a set of recommendations.

13 HYDRO ENERGY↗
DOE OSTI2025

Compression–tension cell with sample manipulator for in situ X‐ray nanotomography experiments

In situ X-ray nanotomography experiments where tensile or compressive force is applied on the sample require specialized equipment. A compression-tension device with fluid flow-through capability has been designed for X-ray nanotomography beamlines. The compression-tension cell is equipped with a triaxial stage for sample alignment and a high sensitivity loadcell for measurement of applied force. To handle the <100 µm samples used for X-ray nanotomography imaging and for loading samples on the compression-tension cell a sample manipulator has been built. The sample manipulator is capable of selecting a single <100 µm particle for nanotomography scanning while viewing multiple samples under an optical microscope. To test the functionality of these two devices an initial compression experiment involving two glass beads was performed. To demonstrate instrument stability two spherical glass beads were compressed from a no load condition until one of the beads fractured. Nanotomography data were collected at each step of increasing compressive force. The experimentally observed contact area of the spherical glass beads was compared with the theoretical estimate using the Hertz analysis. To demonstrate the fluid flow capability, two calcite grains were compressed against each other under a calcite saturated solution. Surface topological changes were observed for the stressed grain contact area.

X-ray tomography↗
DOE OSTI2017

Sensitivity of polycrystal plasticity to slip system kinematic hardening laws for Al 7075-T6

The prediction of formation and early growth of microstructurally small fatigue cracks requires use of constitutive models that accurately estimate local states of stress, strain, and cyclic plastic strain. However, few research efforts have attempted to systematically consider the sensitivity of overall cyclic stress-strain hysteresis and higher order mean stress relaxation and plastic strain ratcheting responses introduced by the slip system back-stress formulation in crystal plasticity, even for face centered cubic (FCC) crystal systems. This paper explores the performance of two slip system level kinematic hardening models using a finite element crystal plasticity implementation as a User Material Subroutine (UMAT) within ABAQUS, with fully implicit numerical integration. The two kinematic hardening formulations aim to reproduce the cyclic deformation of polycrystalline Al 7075-T6 in terms of both macroscopic cyclic stress-strain hysteresis loop shape, as well as ratcheting and mean stress relaxation under strain- or stress-controlled loading with mean strain or stress, respectively. The first formulation is an Armstrong-Frederick type hardening-dynamic recovery law for evolution of the back stress. This approach is capable of reproducing observed deformation under completely reversed uniaxial loading conditions, but overpredicts the rate of cyclic ratcheting and associated mean stress relaxation. The second formulation corresponds to a multiple back stress Ohno-Wang type hardening law with nonlinear dynamic recovery. The adoption of this back stress evolution law greatly improves the capability to model experimental results for polycrystalline specimens subjected to cycling with mean stress or strain. As a result, the relation of such nonlinear dynamic recovery effects are related to slip system interactions with dislocation substructures.

36 MATERIALS SCIENCE↗
DOE OSTI2021

High‐efficiency adsorption of various heavy metals by tea residue biochar loaded with nanoscale zero‐valent iron

Abstract Nanoscale zero‐valent iron (nZVI) loaded on tea residue biochar activated with phosphoric acid composites was synthesized. This adsorbent can efficiently adsorb multiple heavy metal ions such as Pb (II), Cr (III), Cu (II), and Ni (II) simultaneously. The adsorption process was found to follow the pseudo‐second‐order kinetic model. Equilibrium adsorption capacities reached 288.18, 162.34, 242.72, and 267.22 mg·g −1 for Pb(II), Cr(III), Cu(II), and Ni(II), respectively. The common interfering ions exhibited lower influence on its adsorption capacity. The adsorption mechanism includes reduction, ion exchange, surface complexation and precipitation. Furthermore, the waste adsorbent was converted into a catalyst in situ, which could catalyze the degradation of Congo red by establishing an electron transfer pathway. This research provides a new concept for the sustainable utilization of industrial tea residues and the harmless treatment of waste nZVI composite adsorbents.

Liu, Shuang↗
DOE OSTI2015

Transmission Electron Microscope In Situ Straining Technique to Directly Observe Defects and Interfaces During Deformation in Magnesium

In-situ straining was used to study deformation behavior of hexagonal close-packed (hcp) metals.Twinning and dislocation motion, both essential to plasticity in hcp materials, were observed.Typically, these processes are characterized post-mortem by examining remnant microstructural features after straining has occurred. By imposing deformation during imaging, direct observation of active deformation mechanisms is possible. This work focuses on straining of structural metals in a transmission electron microscope (TEM), and a recently developed technique that utilizes familiar procedures and equipment to increase ease of experiments. In-situ straining in a TEM presents several advantages over conventional post-mortem characterization, most notably time-resolution of deformation and streamlined identification of active deformation mechanisms. Drawbacks to the technique and applicability to other studies are also addressed. In-situ straining is used to study twin boundary motion in hcp magnesium. A {101¯2} twin was observed during tensile and compressive loading. Twin-dislocation interactions are directly observed. Notably, dislocations are observed to remain mobile, even after multiple interactions with twin boundaries, a result which suggests that Basinki’s dislocation transformation mechanism by twinning is not present in hcp metals. The coupling of in-situ straining with traditional post-mortem characterization yields more detailed information about material behavior during deformation than either technique alone.

magnesium↗
DOE OSTI2018

Optimal allocation of series FACTS devices in large‐scale systems

Series flexible AC transmission systems devices, such as the variable series reactor, have the ability to continuously regulate the transmission line reactance so as to control power flow. This study presents a new approach to optimally locating such devices in the transmission network considering multiple operating states and contingencies. To investigate optimal investment, a single target year planning with three different load patterns is considered. The transmission contingencies may occur under any of the three load conditions and the coupling constraints between base case and contingencies are included. A reformulation technique transforms the original mixed integer non‐linear programming model into mixed integer linear programming model. To further relieve the computational burden and enable the planning model to be directly applied to practical large‐scale systems, a two‐phase decomposition algorithm is introduced. Detailed numerical simulation results on IEEE 118‐bus system and the Polish 2383‐bus system illustrate the efficient performance of the proposed algorithm.

Zhang, Xiaohu↗
DOE OSTI2021

Field validation of an actuated convergent-beam acoustic Doppler profiler for high resolution flow mapping

Abstract Energetic river and tidal flow environments feature complex hydrodynamic conditions. Conventional acoustic Doppler profiling instrumentation typically requires assumptions of flow homogeneity over the spatial scales of the divergent beam separation. This removes the ability to measure spatio-temporal variability within the flow. However, velocity variability within these spatial scales is often important in the design of structures and devices exposed to such flow, informing dynamic and peak hydrodynamic load predictions. The research presented outlines the development and testing of a flow measurement instrument consisting of multiple spatially-separated single beam acoustic Doppler profilers converging on a remote focal point, the location of which can be programmatically adjusted through actuation. This increases the spatial resolution at which remote field measurements can be made in energetic flow environments. Field testing of the instrument was conducted in a tidal channel at Sequim Bay Inlet, WA, USA. Results are compared with independent reference measurements made by a co-located, motion-corrected acoustic Doppler velocimeter. This comparison, across tidal velocities of 0.4–0.7 m s −1 , showed a mean velocity error of 0.5%–13.2% across nine sample locations within a 3.00 m × 2.25 m plane. To the authors’ knowledge, this is the first publication of flow velocity results from non-intrusive acoustic measurements at an off-axis, focal point location that features 3D positional control.

13 HYDRO ENERGY↗
DOE OSTI2025

Computing virtual dark-field X-ray microscopy images of complex discrete dislocation structures from large-scale molecular dynamics simulations

Dark-field X-ray microscopy (DFXM) is a novel diffraction-based imaging technique that non-destructively maps the local deformation from crystalline defects in bulk materials. While studies have demonstrated that DFXM can spatially map 3D defect geometries, it is still challenging to interpret DFXM images of the high-dislocation-density systems relevant to macroscopic crystal plasticity. This work develops a scalable forward model to calculate virtual DFXM images for complex discrete dislocation structure(s) (DDS) obtained from atomistic simulations. Our new DDS-DFXM model integrates a non-singular formulation for calculating the local strain from the DDS and an efficient geometrical optics algorithm for computing the DFXM image from the strain field. We apply the model to complex DDS obtained from a large-scale mol­ecular dynamics simulation of compressive loading on single-crystal silicon. Simulated DFXM images exhibit prominent contrast for dislocation features between the multiple slip systems, demonstrating the potential of DFXM to resolve features from dislocation multiplication. In conclusion, the integrated DDS-DFXM model provides a toolbox for DFXM experimental design and image interpretation in the context of bulk crystal plasticity for a range of measurements across shock plasticity and the broader materials science community.

X-ray imaging↗
DOE OSTI2017

Generating Performance Models for Irregular Applications

Many applications have irregular behavior --- non-uniform input data, input-dependent solvers, irregular memory accesses, unbiased branches --- that cannot be captured using today's automated performance modeling techniques. We describe new hierarchical critical path analyses for the \Palm model generation tool. To create a model's structure, we capture tasks along representative MPI critical paths. We create a histogram of critical tasks with parameterized task arguments and instance counts. To model each task, we identify hot instruction-level sub-paths and model each sub-path based on data flow, instruction scheduling, and data locality. We describe application models that generate accurate predictions for strong scaling when varying CPU speed, cache speed, memory speed, and architecture. We present results for the Sweep3D neutron transport benchmark; Page Rank on multiple graphs; Support Vector Machine with pruning; and PFLOTRAN's reactive flow/transport solver with domain-induced load imbalance.

analytical performance models↗
DOE OSTI2024

1 kV 150 A Bidirectional Isolated DC/DC Converter With Full Range ZVS For Charger Application

This paper focusses on the development of a bidirectional DC/DC converter based on dual active bridge (DAB) converter for 1 kV class fast charger applications. A novel modulation technique is proposed to achieve zero voltage switching across the entire operating range of a vehicle battery system. The topology includes a tap changer to support multiple class of vehicles. The full range ZVS operation will allow high efficiency operation even at light load, reduced dv/dt to improve transformer insulation lifetime and mitigate EMI impact. A 1 kV class, 150 A prototype was developed to validate the proposed concepts.

Kandula, Prasad↗
DOE OSTI2024

Newton-Raphson AC Power Flow Convergence Based on Deep Learning Initialization and Homotopy Continuation

Power flow forms the basis of many power system studies. With the increased penetration of renewable energy, grid planners tend to perform multiple power flow simulations under various operating conditions and not just selected snapshots at peak or light load conditions. Getting a converged AC power flow (ACPF) case remains a significant challenge for grid planners especially in large power grid networks. This paper proposes a two-stage approach to improve Newton-Raphson ACPF convergence and was applied to a 6102 bus Electric Reliability Council of Texas (ERCOT) system. The first stage utilizes a deep learning-based initializer with data re-training. Here a deep neural network (DNN) initializer is developed to provide better initial voltage magnitude and angle guesses to aid in power flow convergence. This is because Newton-Raphson ACPF is quite sensitive to the initial conditions and bad initialization could lead to divergence. The DNN initializer includes a data re-training framework that improves the initializer's performance when faced with limited training data. The DNN initializer successfully solved 3,285 cases out of 3,899 non-converging dispatch and performed better than random forest and DC power flow initialization methods. ACPF cases not solved in this first stage are then passed through a hot-starting algorithm based on homotopy continuation with switched shunt control. The hot-starting algorithm successfully converged 416 cases out of the remaining 614 non-converging ACPF dispatch. In conclusion, the combined two-stage approach achieved a 94.9% success rate, by converging a total of 3,701 cases out of the initial 3,899 unsolved cases.

Deep learning↗
DOE OSTI2022

K-anonymity applied to the energy grid of things distributed energy resource management system

Smart grid infrastructure relies on information exchange between multiple actors in order to ensure system reliability. These actors include but are not limited to smart loads, grid control, and energy management technologies. As information exchange between these actors is susceptible to cyber-attacks, security and privacy issues are indispensable to ensure a reliable and stable grid. This position paper proposes a privacypreserving, trust-augmented secure scheme for a smart grid implementation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

Building Energy Management Open Source Software

This is the repository for Building Energy Management Open Source Software (BEMOSS), which is an open source operating system that is engineered to improve sensing and control of equipment in small- and medium-sized commercial buildings. BEMOSS offers the following key features: (1) Open source, open architecture – BEMOSS is an open source operating system that is built upon VOLTTRON – a distributed agent platform developed by Pacific Northwest National Laboratory (PNNL). BEMOSS was designed to make it easy for hardware manufacturers to seamlessly interface their devices with BEMOSS. Software developers can also contribute to adding additional BEMOSS functionalities and applications. (2) Plug & play – BEMOSS was designed to automatically discover supported load controllers (including smart thermostats, VAV/RTUs, lighting load controllers and plug load controllers) in commercial buildings. (3) Interoperability – BEMOSS was designed to work with load control devices form different manufacturers that operate on different communication technologies and data exchange protocols. (4) Cost effectiveness – Implementation of BEMOSS deemed to be cost-effective as it was built upon a robust open source platform that can operate on a low-cost single-board computer, such as Odroid. This feature could contribute to its rapid deployment in small- or medium-sized commercial buildings. (5) Scalability and ease of deployment – With its multi-node architecture, BEMOSS provides a distributed architecture where load controllers in a multi-floor and high occupancy building could be monitored and controlled by multiple single-board computers hosting BEMOSS. This makes it possible for a building engineer to deploy BEMOSS in one zone of a building, be comfortable with its operation, and later on expand the deployment to the entire building to make it more energy efficient. (6) Ability to provide local and remote monitoring – BEMOSS provides both local and remote monitoring ability with role-based access control. (7) Security – In addition to built-in security features provided by VOLTTRON, BEMOSS provides enhanced security features, including BEMOSS discovery approval process, encrypted core-to-node communication, thermostat anti-tampering feature and many more. (8) Support from the Advisory Committee – BEMOSS was developed in consultation with an advisory committee from the beginning of the project. BEMOSS advisory committee comprises representatives from 22 organizations from government and industry.

Source record↗
DOE OSTI2020

Concurrent Relaxation through Accelerated Deep Learning

CRADL captures performance metrics of machine learning algorithms operating on mesh data from multiphysics codes This proxy application is a tool to explore scalability of inference on HPC platforms, and also gather performance metrics for inference on new machine learning specific hardware. CRADL is designed to give users as fine a control as possible over an inference simulation. Users may select the number of cycles, amount of data, and batch size to pass to the accelerator of choice. Additionally the user may select a number of performance optimization libraries and flags. CRADL comes packaged with a repository of anonymized multi-physics simulation data, as well as a pretrained model for inference. The code allows a user to load their own pre-trained model and data if they wish. The code can operate in multiple parallelization schemes, with performance enhancing options such as half-precision libraries, PyTorch benchmarking, and pinned memory with non-blocking data transfers.

Zieb, KristoferJ.↗