SEARCH · Engineering Papers

Results for “Base stations”

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.

SourceResearch connectionFrom yearThrough year

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

At least 559 records · Page 31

All sources NASA NTRS DOE OSTI

DOE OSTI2023

Fuel Cell Stack Model for Real-Time Simulation of Grid-Connected Applications

Fuel cell stacks coupled with electrolyzers and hydrogen storage sites can be a promising category of distributed energy resources for both grid-connected and stand-alone power systems. However, because of high costs, at-scale hardware testing of fuel cell stacks for grid-connected applications is not economically viable at present. A model-based system that can accurately captures the steady-state and dynamic response of fuel cell stacks over long time periods (hours), is needed. This paper demonstrate a real-time electromagnetic transient model of a megawatt-scale, grid-connected proton exchange membrane fuel cell stack, coupled with a mass-based hydrogen storage system. This model can emulate the electrical steady-state and dynamic response of grid-connected fuel cell stacks. We validate the model using the response of commercial hardware fuel cell stacks and analytical models in the literature - using a digital real-time simulator (RSCAD). The proposed real-time model is then used to simulate cases spanning different time horizons and to design controller-hardware-in-the-loop experiments to evaluate controllers for hydrogen stations.

activation potential↗

DOE OSTI2022

Scalable Predictive Control and Optimization for Grid Integration of Large-Scale Distributed Energy Resources

Integrating a large number of distributed energy resources (DERs) into the power grid needs a scalable power balancing method. We formulate the power balancing problem as a look-ahead optimization problem to be solved sequentially by a power distribution system aggregator based on a model predictive control (MPC) framework. Solving large-scale look-ahead control problems requires proper configuration of the control steps. In this paper, to solve large-scale control problems, we propose a variable time granularity where control time steps nearby the current control step have finer resolutions. The aggregator objective includes maximization of power production revenue and minimization of power purchasing expense, renewable power curtailment, and mileage costs for energy storage and electric vehicle (EV) charging stations while satisfying system capacity and operational constraints. The control problem is formulated as a mixed-integer linear program (MILP) and solved using the XpressMP solver. We perform simulations considering a copper plate representation of a large distribution network consisting of 2507 devices (control-lable DERs), including curtailable photovoltaics (PVs), energy storage batteries, EV charging stations, and buildings with heating, ventilation, and air conditioning units (HVACs). We show the effectiveness of the proposed approach in managing DERs interactively for maximum energy trading profit and local supply-demand power balancing. Finally, we demonstrate that the proposed method outperforms other benchmark controllers regarding computation time without compromising operational performance.

DER↗

DOE OSTI2024

Abatement Case Study

Radioxenon emissions from industrial sources such as fission based medical isotope production (MIP) facilities and nuclear reactors are generally known to be well below levels of public health and safety concern. However, the global background of radioxenon produced by MIP interferes with nuclear explosion monitoring by the International Monitoring System (IMS) developed for the Comprehensive Nuclear-Test-Ban Treaty (CTBT) (CTBTO, 2024). It was calculated that xenon emissions levels of 5×10 9 Bq/day 133 Xe were low enough to have minimal impact on International Monitoring System (IMS) stations (Bowyer et al, 2013). There are several technologies currently used to abate radioactive xenon emissions to meet regulatory release levels, and some alternative methods have been investigated to reduce xenon release levels well below required regulatory levels (Doll et al, 2014, Gueibe, et al, 2014). While MIP producers are sympathetic to the issue of radioxenon interference with IMS monitoring, the cost to implement and maintain additional abatement systems has resulted in limited implementation. Therefore, more cost-effective options for xenon abatement are needed to help reduce the impact of these emissions on nuclear explosion monitoring.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2022

Scalable Predictive Control and Optimization for Grid Integration of Large-Scale Distributed Energy Resources: Preprint

Integration of a large number of distributed energy resources (DERs) into the power grid needs a scalable power balancing method. We formulate the power balancing problem as a look-ahead optimization problem to be solved sequentially by a power distribution system aggregator based on a model predictive control (MPC) framework. Solving large-scale look-ahead control problem requires proper configuration of the control steps. In this paper, to solve large-scale control problems, we propose a variable time granularity where control time steps nearby the current control step have finer resolutions. The aggregator objective includes maximization of power production revenue and minimization of power purchasing expense, renewable power curtailment, and mileage costs for energy storage and electric vehicle (EV) charging stations while satisfying system capacity and operational constraints. The control problem is formulated as a mixed-integer linear program (MILP) and solved using the XpressMP solver. We perform simulations considering a copper plate representation of a large distribution network consisting of 2507 devices (controllable DERs) including curtailable photovoltaics (PVs), energy storage batteries, EV charging stations, and buildings with heating, ventilation, and air conditioning units (HVACs). We show the effectiveness of the proposed approach in managing DERs interactively for maximum energy trading profit and local supply-demand power balancing. Finally, we demonstrate that the proposed method outperformed other benchmark controllers regarding computation time without compromising operational performance.

DER↗

DOE OSTI2022

Scalable Predictive Control and Optimization for Grid Integration of Large-Scale Distributed Energy Resources

Integrating a large number of distributed energy resources (DERs) into the power grid needs a scalable power balancing method. We formulate the power balancing problem as a look-ahead optimization problem to be solved sequentially by a power distribution system aggregator based on a model predictive control (MPC) framework. Solving large-scale look-ahead control problems requires proper configuration of the control steps. In this paper, to solve large-scale control problems, we propose a variable time granularity where control time steps nearby the current control step have finer resolutions. The aggregator objective includes maximization of power production revenue and minimization of power purchasing expense, renewable power curtailment, and mileage costs for energy storage and electric vehicle (EV) charging stations while satisfying system capacity and operational constraints. The control problem is formulated as a mixed-integer linear program (MILP) and solved using the XpressMP solver. We perform simulations considering a copper plate representation of a large distribution network consisting of 2507 devices (controllable DERs), including curtailable photovoltaics (PVs), energy storage batteries, EV charging stations, and buildings with heating, ventilation, and air conditioning units (HVACs). We show the effectiveness of the proposed approach in managing DERs interactively for maximum energy trading profit and local supply-demand power balancing. Finally, we demonstrate that the proposed method outperforms other benchmark controllers regarding computation time without compromising operational performance.

DER↗

DOE OSTI2021

Deep Learning Based Approach to Integrate MyShake's Trigger Data with ShakeAlert for Faster and Robust EEW Alerts

Earthquake Early Warning (EEW) systems depend on the dense seismic network to make fast and accurate earthquake detections to issue useful early alerts. The recent development and implementation of the ShakeAlert system is relying on the west coast seismic network to detect and estimate the earthquake parameters in real-time. While working on making improvements on the current system, one potential approach is to include more seismic recordings from various sources, such as the low-cost smartphone seismic network, such as the MyShake network, or the Google Android smartphones, since these smartphone seismic networks have much more portable stations (phones) to potentially provide useful data to the system. This report summarizes the initial exploration of using a deep learning approach to combine the data from both traditional seismic stations and the smartphone data in California. Due to the heterogeneity nature of the data, we aggregate data from the phones (using simulation data), as well as that from traditional seismic stations to grid cells. By generating real-time triggering ratio grid cell maps, the designed deep learning algorithm can process the data from multiple sources and detect the earthquake faster than only using that from a traditional seismic network.

58 GEOSCIENCES↗

DOE OSTI2022

Continuous Light Absorption Photometer (CLAP) Instrument Handbook

Reliable measurements of aerosol light absorption are crucial for quantifying the radiative forcing of climate. As a consequence, light absorption measurements are recommended for all stations in the Global Atmosphere Watch network, which is coordinated by the World Meteorological Organization. Aerosol light absorption is often dominated by soot-like particles produced by the incomplete combustion of carbonaceous fuels, commonly termed "black carbon", and optical methods are the primary way that equivalent black carbon concentrations are derived. Two basic approaches are used for determining the aerosol light absorption coefficient: in situ methods where the absorption is measured while the particles are suspended in air, and filter-based methods where the particles are deposited on a filter for real-time optical analysis. In situ methods are inherently more accurate because the physical state of the particles can be changed by the act of filtration. Unfortunately, currently available instruments for in situ measurements are more expensive and difficult to operate than filter-based methods, making them better suited for use in intensive field campaigns or as laboratory reference instruments. Filter-based instruments, because of their lower cost and simpler operation, have been the preferred choice for long-term measurements of aerosol light absorption in monitoring networks.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Continuous variable quantum secret sharing

Continuous variable quantum secret sharing (CV-QSS) technologies are described that use laser sources and homodyne detectors. Here, a Gaussian-modulated coherent state (GMCS) prepared by one device passes through secure stations of other devices sequentially on its way to a trusted device, and each of the other devices coherently adds a locally prepared, independent GMCS to the group of propagating GMCSs. Finally, the trusted device measures both the amplitude and the phase quadratures of the received group of coherent GMCSs using double homodyne detectors. The trusted device suitably uses the measurement results to establish a secure key for encoding secret messages to be broadcast to the other devices. The devices cooperatively estimate, based on signals corresponding to their respective Gaussian modulations, the trusted device's secure key, so that the cooperative devices can decode the broadcast secret messages with the secure key.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Site-Selective Modification of Lanthanum Oxychloride to Modulate Halide-Ion Conduction

Design principles for solid-state halide-ion conduction remain poorly defined despite the increasing importance of halide ions as charge carriers in a variety of energy storage and electrochemical computing technologies. Here, we employ a siteselective modification strategy in which aliovalent cations are preferentially introduced at the La 3+ crystallographic site of LaOCl in the 2c Wyckoff position, enabling controlled generation of chloride vacancies and modification of lattice dynamics to enhance chloride-ion conductivity. Aliovalent substitution of La 3+ with Mg 2+ , Ca 2+ , and Sr 2+ generates charge-compensating Cl vacancies while preserving the matlockite crystal structure. X-ray excited optical luminescence measurements with Dy 3+ as a reporter chromophore evidence vacancy-derived midgap electronic states and an extended energy range of radiation-less Auger electron emission corresponding to substantial modification of electronic structure and local electrostatic potentials. Ca alloying at 8−10 at. % increases the chloride-ion conductivity by three- to 4 orders of magnitude as compared to unalloyed LaOCl, whereas comparable amounts of Sr- and Mg-alloying in LaOCl imbue less pronounced conductivity enhancements. Temperature-dependent Raman spectroscopy measurements reveal that Ca- and Sr-alloying substantially soften the La−Cl sublattice and yield a more compliant crystal lattice that can deform to accommodate Cl-ion migration. Structure solutions derived from Rietveld refinements to powder Xray diffraction reveal larger O−La−Cl bond-angle deviations and enhanced out-of-plane cation displacements for Ca- and Sr-alloyed compositions as compared to Mg-alloyed LaOCl. Such local distortions enhance chloride-ion mobility by reshaping and flattening vacancy migration energy landscapes and by modulating lattice dynamics governing anion conduction. We further illustrate that coalloying of Ca with Mg and Sr induces a nonmonotonic conductivity−defect stoichiometry relationship that can be rationalized based on cooperative interactions. Together, these results establish site-selective aliovalent alloying of LaOCl as an effective route to halide-ion solid electrolytes and provide broadly generalizable design principles for site-selective modification to induce vacancy formation and lattice softening to engender facile anion transport

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Trace explosives sampling for security applications (TESSA) study: Evaluation of procedures and methodology for contact sampling efficiency

We report the detection of trace amounts of explosive materials is critical to the security at mass transit centers (e.g., airports and railway stations). In a typical screening process, a trap is used to probe a surface of interest to collect and transfer particulate residue to a detector for analysis. The collection of residues from the surface being probed is widely viewed as the limiting step in this process. A multi-institutional study was performed to establish a methodology for the evaluation of sampling media collection efficiencies. Dry deposited residues of 1,3,5-trinitroperhydro-1,3,5-triazine (RDX), C-4 (an RDX-based explosive), and pentaerythritol tetranitrate (PETN) were harvested from acrylonitrile butadiene styrene (ABS) plastic, ballistic nylon (NYL), and uncoated aluminum surfaces using muslin, Texwipe cotton, and stainless-steel mesh traps. Transfer and collection efficiencies of the sample media were calculated based on liquid chromatography-mass spectrometry analysis. Dry transfer efficiencies (DTE%) to all tested surfaces were greater than 75%, with transfer to ABS plastic being the lowest. Collection efficiency (CE%) varied significantly across the traps and the surfaces, yet some conclusions can be drawn; nylon had the lowest CE% for all cases (~10%), and the stainless steel mesh had the lowest CE% for the evaluated traps (~20%). Though the testing parameters have been standardized among the participants to establish a framework for an independent comparison of contact sampling media and surfaces, substantial variations in the DTE% and the CE% were observed, suggesting that other variables can affect contact sampling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Dynamic Simulation Technoeconomic Model for Power Generation

Sandia National Laboratories has built and successfully tested a dynamic simulation technoeconomic model of the Palo Verde Generating Station that is now being updated to help other US power plants improve operations. Palo Verde, located west of Phoenix, Arizona, is the largest electricity generator in the US at 4 GW. Palo Verde uses — 60 million gallons per day of treated wastewater from Phoenix to cool reactors, and disposes of blowdown in evaporation ponds. The model built for Palo Verde numerically evaluates the economic impact of changing, for example, alternative cooling technologies, water usage and treatment, and influent water chemistry, and is based on detailed accounting of mass, energy, and cash flows.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Bolide Infrasound Signal Morphology and Yield Estimates: A Case Study of Two Events Detected by a Dense Acoustic Sensor Network

Two bolides (2016 June 2 and 2019 April 4) were detected at multiple regional infrasound stations, with many of the locations receiving multiple detections. Analysis of the received signals was used to estimate the yield, location, and trajectory, as well as the type of shock that produced the received signal. The results from the infrasound analysis were compared with ground-truth information that was collected through other sensing modalities. This multimodal framework offers an expanded perspective on the processes governing bolide shock generation and propagation. The majority of signal features showed reasonable agreement between the infrasound-based interpretation and the other observational modalities, though the yield estimate from the 2019 bolide was significantly lower using the infrasound detections. There was also evidence suggesting that one of the detections was from a cylindrical shock that was initially propagating upward, which is unusual though not impossible.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

H2@Scale - Validating an Electrolysis System with High Output Pressure: Cooperative Research and Development Final Report, CRADA Number CRD-18-00741

Electrolysis has been a commercially available product for a while and electrolyzers have been a proven capability to provide additional benefits (e.g. controllable load for grid services) in addition to production of hydrogen. The hydrogen output is typically compressed for storage and dispensing. Compression adds cost and decreases system reliability. Honda’s electrolyzer systems have been developed to include electrochemical compression to leverage the production system itself for at least partial compression. In this project, the team will evaluate Honda’s PEM based electrochemical compression system. The system is capable of compressing hydrogen up to 70 MPa electrochemically. Validation testing is the next step to accelerate this technology into the marketplace, as the validation will provide needed data under a variety of operation conditions and controls. These operating conditions and controls are based on over a decade of NLR research and development with low-temperature electrolysis. The validation testing will include preparing NLR’s site for third party evaluation, benchmark testing of Honda’s stack and system, and simulating operation connected to renewables or in a grid service profile. NLR’s Energy System Integration Lab will be the location for the electrolyzer validation research and integrated into the Hydrogen Infrastructure Test & Research Facility (HITRF). This will build into the existing retail style hydrogen fueling station for a fully integrated experimental setup.

08 HYDROGEN↗

DOE OSTI2025

Investigation of Arctic Cloud Properties and Surface Radiation Based on MOSAiC Shipborne Observations

The Arctic is rapidly changing due to changes of the Earth system. This study investigates cloud fraction, phase partition, cloud type, and their relationships with surface radiation based on yearlong shipborne observations in the Arctic regions. The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) campaign provided lidar and radar observations of cloud microphysical properties and surface shortwave (SW) and longwave (LW) radiation. Cloud and radiative properties were examined at daily and monthly resolutions in four seasons. Low clouds were found to be most prevalent throughout the year, followed by deep clouds. The ice phase is the dominant phase except for summer (June–August). Liquid and mixed phases show more significant monthly and annual mean radiative effects in SW and LW than the ice phase. The clouds show net warming effects due to LW heating in most months, while the SW cooling effects of clouds become more dominant for July and August. The cloud and radiation observations from MOSAiC were used to evaluate simulations of the atmospheric component of the Energy Exascale Earth System Model version 2. The simulations show large overestimations of the liquid and mixed phases in the Arctic regions from February to September. The simulations also underestimate the percentages of low clouds and overestimate the percentages of deep clouds throughout the year. Altogether, this work provides a unique analysis of cloud and radiation properties based on high-resolution shipborne observations, which can be used to assist future model evaluation and development.

58 GEOSCIENCES↗

DOE OSTI2024

Fitness-for-Service Analysis of Reactor Components under Flexible Load-Following Operating Conditions

Conventional power-generation plants, including nuclear plants, have been traditionally designed to provide a steady baseload energy capacity, optimizing output efficiency while minimizing variable costs. However, the growing adoption of large-scale renewable energy-generation systems, which rely on intermittent sources such as solar and wind, has introduced more variability into the energy supply in interconnected electricity grids. As a result, the next generation of power plants needs to operate in what is known as the load-following mode, requiring flexible adjustments in electricity production to align with the energy demand on the grid. This transition from the steady baseload operation to load-following operating conditions can significantly increase the number of times various plant components are exposed to transient stresses. This increased thermo-mechanical cycling can lead to accelerated material degradation, thereby elevating the risk of premature failure of a component. It becomes imperative to conduct a comprehensive analysis of fatigue, creep-fatigue, and stress corrosion cracking life, to assess the resilience of the various engineering components under these flexible load-following operating conditions. This study aims to develop a comprehensive numerical model of a light-water reactor pressure vessel (RPV) to investigate its degradation under various operating scenarios. This coupled thermo-mechanical finite element analysis evaluated the stress response of the RPV caused by considering fluctuations in thermal and mechanical loads caused by the varying pressure and temperature occurring during the load-following operation. Critical locations on the RPV are subsequently identified based on the stress response. The stress intensity factors for the postulated flaws at those locations are then calculated, followed by an evaluation of the reactor's life in accordance with the ASME Boiler and Pressure Vessel Code Section XI. This comprehensive life assessment covers a number of transients expected during the flexible load-following operation, providing invaluable insights into the RPV's structural integrity. Moreover, the development methodology can be adapted to other reactor components, as well as components of conventional power stations that are affected by varying operating conditions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2021

Thermodynamic modeling of hydrogen fueling process from high-pressure storage tank to vehicle tank

This study develops a hydrogen fueling station (HFS) thermodynamic model that simulates the actual fueling process in which hydrogen is supplied from a high-pressure (HP) storage tank into a fuel cell electric vehicle (FCEV) tank. To make the model as accurate as possible, we use the same components and specifications as in actual HFSs, such as a pressure control valve, a pre-cooling system, and an FCEV tank. After the components and their specifications are set, pressure and temperature profiles are set as the HP tank supply conditions. Based on the pressure and temperature profiles, the model solves for the temperature, pressure, and mass flow rate of hydrogen at each downstream position, including the inside of the vehicle tank. The values predicted by the model are compared with experimental data, and we show that the developed model makes it possible to accurately simulate those values at any position during the fueling process.

08 HYDROGEN↗

DOE OSTI2020

Modeling of hydrogen liquefaction using magnetocaloric cycles with permanent magnets

Hydrogen (H 2 ) is promising alternative to replace fossil fuels, but its transport and storage has been challenging. As H 2 fuel cell vehicles are gaining traction, the infrastructure for storing large amounts of liquid H 2 is needed. However, liquid H 2 would suffer from boil-off loss, and traditional vapor compression refrigeration systems would not be able to economically recover the lost H 2 due to the low efficiencies at cryogenic temperature. Magnetocaloric (MC) refrigeration systems could possess much higher coefficient of performance (COP) at cryogenic temperature compared to the vapor compression ones. Previous work on cryogenic MC systems, however, have only focused on large scale applications which use superconducting magnets to provide a large magnetic field but are prohibitively expensive to operate for small scale applications, such as that of a H 2 refilling station. In this work, we model the performance of a MC refrigeration cycle using 1-Tesla permanent magnets for H 2 liquefaction, with the objective of cooling H 2 from 80 K (using liquid nitrogen as the heat sink) to 20 K (boiling point of hydrogen). We evaluate main performance metrics including the total work input to the refrigeration system, COP, total MCM mass in the system, and total volume of the permanent magnets, etc. Our modeling results indicate that such a permanent magnet-based MC cooling system is feasible for small-scale H 2 liquefaction, with projected COP values significantly higher than those of vapor compression systems. In conclusion, this work provides design guidelines for future experimental efforts on permanent magnet MC cooling systems for cryogenic cooling.

08 HYDROGEN↗

DOE OSTI2021

Robotic sample changers for macromolecular X-ray crystallography and biological small-angle X-ray scattering at the National Synchrotron Light Source II

In this work, we present two robotic sample changers integrated into the experimental stations for the macromolecular crystallography (MX) beamlines AMX and FMX, and the biological small-angle scattering (bioSAXS) beamline LiX. They enable fully automated unattended data collection and remote access to the beamlines. The system designs incorporate high-throughput, versatility, high-capacity, resource sharing and robustness. All systems are centered around a six-axis industrial robotic arm coupled with a force torque sensor and in-house end effectors (grippers). They have the same software architecture and the facility standard EPICS-based BEAST alarm system. The MX system is compatible with SPINE bases and Unipucks. It comprises a liquid nitrogen dewar holding 384 samples (24 Unipucks) and a stay-cold gripper, and utilizes machine vision software to track the sample during operations and to calculate the final mount position on the goniometer. The bioSAXS system has an in-house engineered sample storage unit that can hold up to 360 samples (20 sample holders) which keeps samples at a user-set temperature (277 K to 300 K). The MX systems were deployed in early 2017 and the bioSAXS system in early 2019.

36 MATERIALS SCIENCE↗