Search NASA⌕ Search

SEARCH · Search NASA

Results for “Flow meter”

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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Shear Assisted Processing and Extrusion of Aluminum Alloy 7075 Tubing at High Speed

Conventional extrusion of aluminum alloy 7075 is limited to 1-2 meters per minute in order to avoid surface tearing and cracking. An emerging technique called Shear Assisted Processing and Extrusion (ShAPE) was used to extrude aluminum alloy 7075 tubing at a speed of 7.4 meters per minute without inducing surface defects. The faster extrusion speed is attributed to the unique flow characteristics inherent to the ShAPE process compared to conventional extrusion. Tubes with an inner diameter of 10 mm, outer diameter of 12 mm, and length of 2 meters were extruded at temperatures ranging from 340°C to 466°C. Tensile testing was performed per ASTM B557-15 with strain measured using digital image correlation. An ultimate tensile strength of 565 ± 4.6 MPa, yield strength of 496 ± 8.7 MPa, and elongation of 16.4 ± 1.0 % were measured for extrusion made at 362°C and heat treated to the T6 condition.

Shear Assisted Processing and Extrusion, Friction ↗
DOE OSTI2023

A Novel Dew Point Meter: Application to the Measurement of the Sulfuric Acid Dew Point for Combustion Flue Gas

Accurate knowledge of acid dew point is essential for industrial and applied combustion. Sulfur in the fuel or raw materials is converted to sulfur dioxide (SO2) during combustion, and a portion of the SO2 is oxidized to sulfur trioxide (SO3). The SO3 will react to form H2SO4 vapor when in the presence of water vapor. Even with just trace levels of H2SO4 vapor in the gas phase (1-10 ppm), the dew point can reach 100°C and higher. To avoid acid condensation and the resulting corrosion on heat recovery equipment, plant engineers must ensure that surface temperatures are above the acid dew point, but this decreases the efficiency of the thermal energy recovery. Thus, there is a trade-off between minimizing equipment corrosion and maximizing thermal energy recovery efficiency, and the acid dew point is a key parameter for this optimization. In this work, we analyze and discuss the theory of the sulfuric acid condensation process and develop a novel dew point meter based on this analysis. The meter consists of a novel optical instrument that is designed to monitor the slightest appearance of condensation on a hydrophobic window surface, and the surface temperature of the window is slowly decreased until condensation is first observed, yielding an accurate measurement of the dew point. The basis of the instrument is that a collimated beam from a diode laser generates scattered light when encountering surface condensate, and a sophisticated array detector is used to sensitively monitor the light scattering. The measurement procedures are established to rapidly find the acid dew point, while minimizing error. Further, we propose a calibration system based on a liquid bubbler, which can generate a stable gas flow with known sulfuric acid dew point, to test the dew point meter. Test results show that the dew point meter can accurately measure the acid dew point over a wide range.

Cheng, Mao↗
DOE OSTI2022

Advanced Metering Infrastructure for Distribution Planning and Operation: Closing the Loop on Grid-Edge Visibility

In the recent history of electric utilities, the potential to have visibility of the grid edge is gaining significance for the reliable planning and operation of a clean energy smart grid. Before the recent large-scale customer adoption of distributed energy resources (DERs), distribution networks were planned with a simpler fit-and-forget philosophy. The importance of customer-sited DERs to achieve climate change goals marks a major shift for utility operations. Changes to traditional fit-and-forget planning paradigms require better availability of grid-edge data. Smart metering is an enterprise-wide tool that is enabling visibility when and where it has been most needed. As of 2020, the rollout of smart metering, or advanced metering infrastructure (AMI), had reached more than 100 million meters in the United States, and nearly half of all electricity customers are now equipped with a smart meter (Figure 1). Smart meters are quickly becoming a ubiquitous data capture feature of smart grids. AMI enables utilities to record and measure electricity usage and power-flow metrics at a minimum of hourly intervals and at least once a day. At a minimum, AMI enables interval metering, automatic meter reading enabling accurate and time-interval billing, and the ability to provide feedback on customer energy consumption.

advanced metering infrastructure↗
DOE OSTI2026

Transient Pulse-Response Time-of-Flight Mass Spectrometry for Complex, Deactivating Heterogeneous Catalytic Systems: Application to Ethane Dehydroaromatization

The study of complex, multistep bond-forming and -breaking reactions in heterogeneous catalytic systems often encounters challenges associated with the involvement of large numbers of intermediates among branching pathways. Kinetic information obtained from traditional steady-state measurements can be complemented with that from time-resolved methods to uncover details of the underlying chemistry. Herein, we describe an approach for tracking the complete time-resolved chemical composition (ca. 4–200 u) of a reactor effluent in response to a reactant pulse. We use a six-port rotary valve with a metered sampling loop to pulse reactants at ambient pressure into a flow reactor packed with a catalyst bed within the isothermal region of a heated furnace. The temporal evolution of effluent species is tracked using time-resolved molecular-beam time-of-flight mass spectrometry. We highlight the possibilities that this method has to offer by studying the complex bifunctional mechanism of ethane dehydroaromatization over an HZSM-5-supported platinum catalyst. We demonstrate that energy-tunable ionization sources, which facilitate isomer resolution, enable the measurement of the full mass spectral time-dependent system response. This includes the evolution of major products and mechanistically relevant reactive intermediates such as 1,3-butadiene and cyclopentadiene; these species have not previously been observed from this reaction. In additional studies, we also assess the role of platinum in the catalyst by examining temporal responses to ethane and ethylene feeds. Results show that two temporally distinct formation pathways exist for methane and benzene, and that their importance depends on both catalyst composition and reactant identity. Additionally, characteristics of catalyst deactivation are uniquely observable in the time-resolved mass spectral response, including the selective deactivation of a benzene formation pathway. The combination of time-of-flight mass spectrometry with tunable ionization enables the simultaneous observation of all effluents in a complex mixture of intermediates with isomer/isobar differentiation capabilities that can be applied to any complex reaction system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Experimental Investigation of Gaseous Mixtures of Ethane, Methane, and Carbon Dioxide as an Alternative to Conventional Fuel in Spark Ignition Engines

This study investigates the viability and performance of certain synthetic fuels in spark ignition internal combustion engine based stationary power generation wherein the fuel comprises a mixture of methane and ethane in high dilutions of carbon dioxide (CO 2 ). The fuel of concern is a byproduct of a novel method for producing ethylene from ethane. The byproduct gas mixture has a concentration of approximately 41% CO 2 , 40% ethane, and 5% methane by weight along with other minor compounds. Varying mixtures of ethane and methane combined with between 42% and 46% by weight CO 2 were used to evaluate the viability and efficiency of this fuel to operate in existing internal combustion engines as a means of reducing emissions and increasing industrial process efficiency. A 13 hp gasoline generator was repurposed as a test stand by incorporating a modified fuel induction system and instrumentation for data collection. A gas metering and mixing system was installed to precisely control the mass flow of gases induced into the engine. Various instrumentations were installed to monitor in-cylinder pressure, temperature at various locations, emissions, and fuel and airflow rates. Varying fuel mixtures and loads were tested and compared to gasoline. It was found that under a high load, the mixed gas was able to generate comparable thermal efficiency and power to gasoline. But under no load or a part load condition the indicated thermal efficiency was found to be about 21% lower than that of gasoline. Further, the mixed gas also resulted in up to 50% reduction in CO and NOx emissions when compared to gasoline.

42 ENGINEERING↗
DOE OSTI2025

Wave ripples formed in ancient, ice-free lakes in Gale crater, Mars

Symmetrical wave ripples identified with NASA’s Curiosity rover in ancient lake deposits at Gale crater provide a key paleoclimate constraint for early Mars: At the time of ripple formation, climate conditions must have supported ice-free liquid water on the surface of Mars. These features are the most definitive examples of wave ripples on another planet. The ripples occur in two stratigraphic intervals within the orbitally defined Layered Sulfate Unit: a thin but laterally extensive unit at the base of the Amapari member of the Mirador formation, and a sandstone lens within the Contigo member of the Mirador formation. In both locations, the ripples have an average wavelength of ~4.5 centimeters. Internal laminae and ripple morphology show an architecture common in wave-influenced environments where wind-generated surface gravity waves mobilize bottom sediment in oscillatory flows. Their presence suggests formation in a shallow-water (<2 meters) setting that was open to the atmosphere, which requires atmospheric conditions that allow stable surface water.

Science & Technology - Other Topics↗
DOE OSTI2021

Real Time - Optimal Power Flow Based Distributed Energy Resources Management System (DERMS) (CRADA Number CRD-20-16909 Final Report)

The integration of behind-the-meter distributed energy resources (DERs) into distribution systems brings transformative changes to power systems. This requires operators and planners to find solutions to modernize electric grids and to effectively manage DERs for grid services. NREL developed novel DER management algorithms (referred to as Real-Time Optimal Power Flow, RT-OPF) through U.S. Department of Energy (DOE)-funded efforts, including Advanced Research Projects Agency–Energy (ARPA-E) Network Optimized Distributed Energy Systems (NODES) funding. This cutting-edge control technology aims to modernize distribution systems with large amounts of DER integration, which will help utilities solve issues brought by renewable integration and build resilient and renewable-based electric grids nationwide. Utilidata worked with NREL to investigate the commercialization opportunity of this RT-OPF-based distributed energy resource management system (DERMS). In this project, NREL performs the technology transfer of the RT-OPF to Utilidata to help them fully understand the RT-OPF solution, to identify potential engineering hurdles, and to assess the expected commercial value of various RT-OPF use cases and deployment. The technology transfer work includes two major tasks. First, NREL performs an in-depth knowledge transfer of the entire RT-OPF solution to Utilidata to help them gain an extensive and detailed understanding of the complete RT-OPF solution. In this task, NREL provides exhaustive information (e.g., documentation, code packages, laboratory and field trial data, performance results) while conducting in-depth training sessions to provide a thorough explanation of the entire solution. NREL hosts meetings to present different topics related to the RT-OPF solution, and question-and-answer sessions are included in each meeting to better explain the RT-OPF-related work. Second, the RT-OPF simulations are performed in a laboratory environment. The main objectives of this task are to walk through with Utilidata engineers how to set up a simulation of RT-OPF, identifying each RT-OPF code block/component in operation, learning how these components interact with each other, and eventually running RT-OPF simulations under various system conditions. This task helps Utilidata engineers understand performance limitations and constraints while also quantifying the commercial value of the RT-OPF for different use cases. Based on these two tasks, Utilidata engineers should be able to define and prioritize the next steps of RT-OPF implementation with an eye toward commercial success and scalability of the solution. The next steps are expected to be part of a new project following the conclusion of this project.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Cooperative Merging via Online Speed Replanning: A Model-Free Approach With Vehicle-to-Vehicle Communication Packet Drop Compensation

On-ramp merging is a critical bottleneck in freeway traffic flow, contributing to congestion, accidents, and excessive fuel consumption. Although traditional ramp metering provides macroscopic control, it lacks the granularity for optimizing an individual vehicle’s trajectory. Cooperative merging, enabled by connected and automated vehicles, can potentially enhance traffic efficiency, safety, and fuel economy. However, existing research often neglects the influence of heterogeneous vehicle dynamics, unreliable vehicle-to-vehicle (V2V) communication, and real-time implementation challenges. Here, this paper introduces novel model-free online speed planners for cooperative on-ramp merging. The planners address these limitations by being agnostic to vehicle dynamics, effectively compensating for V2V communication packet drops and incurring only a light computational burden. Comprehensive evaluation, conducted on a real-time traffic-vehicle-communication co-simulation platform integrating high-fidelity vehicle dynamics, a traffic simulator, and recorded V2V communication footprints, demonstrates the effectiveness of the proposed speed planners. Simulation results reveal that the proposed method yields accurate tracking of desired speed and inter-vehicle distance, maintaining low fuel consumption even under high packet drop ratios, and demonstrating real-time implementation efficiency.

Wang, Zejiang [Univ. of Texas at Dallas, Richardso↗
DOE OSTI2025

High-Fidelity Analysis of EV Integration on Real Utility Feeders in Colorado

Residential electric vehicle (EV) charging has the potential to alter long-held assumptions on load characteristics impacting distribution grid planning, operations, and design standards. This study identifies analysis and control methods to increase the affordability of residential EV charging both for Xcel Energy and their customers. The project also provides solutions for more reliable grid interconnection that can support a reliable utility business model prepared for increasing EV charging load in the coming years. For this project, we referenced Level 2 alternating current (AC) onboard charging profiles for various vehicle models and high-fidelity charging data collected at the experimental setup established at the EV Research Infrastructure Laboratory at the National Renewable Energy Laboratory (NREL). Next, we developed EV adoption models for 2030 and 2040 for the Boulder and Aurora regions in Colorado. Moreover, we evaluated different smart charging control algorithms and compared their performance. We developed time-of-use (TOU)-based and grid-aware active EV charging control methods and integrated them within the study region to understand field impacts. Diving deeper, we selected 10 feeders in Boulder and Aurora for high-fidelity grid modeling down to the house level. We executed detailed grid analysis comparing the smart charge management (SCM) algorithms we developed. Finally, we created a novel tool, Electric Vehicle Infrastructure--Distribution System Integration Tool (EVI-DiST), to integrate all the approaches in a single software environment to provide easy integration, fast simulation, and detailed evaluation capability for utility engineers and other stakeholders.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Validation of strongly coupled geomechanics and gas hydrate reservoir simulation with multiscale laboratory tests

In this work, we validate a coupled flow-geomechanics simulator for gas hydrate deposits, named T+M AM , performing two meter-scale laboratory experiments of gas hydrates for production by depressurization, replicating the gas hydrate deposit in the Ulleung Basin, East Sea, South Korea. The first experiment with a sand-only specimen is a 1D 1 m-scale depressurization test based on the excess gas method, which represents the grain coating hydrate growth. On the other hand, the second is a 3D 1.5 m-scale test with the excess water method for a sand-mud alternating layer system, representing the pore filling hydrate growth. We measure production and displacement at the top with different depressurization levels. In particular, the 3D test exhibits high coupling strength of substantial deformation induced by incompressibility of water and high deformability of the specimen. For validation, we match pressure, flow rate, and displacement between the experimental data and numerical results. Thus, we identify that T+M AM is a reliable simulator, which can be applied to fields in both permafrost and deep oceanic hydrate deposits of strongly coupled flow and geomechanics systems. This validation also implies that other coupled simulators based on the same coupling formulation as T+M AM can be validated when individual flow and geomechanics simulators are stable and reliable.

02 PETROLEUM↗
DOE OSTI2021

National Renewable Energy Laboratory, South Table Mountain Campus, Golden, Colorado

The National Renewable Energy Laboratory (NREL) South Table Mountain campus, located in Golden, Colorado, has multiyear datasets from buildings with approximately 1,100,000 sq ft of floor area. These 16 buildings include a large office, nine laboratories, and other education or public assembly facilities such as an education center, a warehouse, quick service restaurants, two site entrance security buildings, and a parking garage—all constructed and improved from 1982 to 2014. These datasets are also available from the NREL data storage and management platform SkySparks. The datasets contain electricity meter data (poser, voltage, and current) with 1-minute resolution and building automation system (BAS) data with resolutions of 5 or 15 minutes. Some subsystems (e.g., lighting) or equipment electricity data have the same intervals as above. Some mechanical equipment state or condition data, such as flow and temperature, are captured with 5- to 15-minute intervals. The types of measurement points (i.e., electrical meter power and zone temperature) and associated data quality across the campus are typical, which helps reduce the unreliability of data quality.

STM, Systems and equipment operational, Energy use↗
DOE OSTI2022

INGENIOUS - Great Basin Regional Dataset Compilation

This is the regional dataset compilation for the INnovative Geothermal Exploration through Novel Investigations Of Undiscovered Systems (INGENIOUS) project. The primary goal of this project is to accelerate discoveries of new, commercially viable hidden geothermal systems while reducing the exploration and development risks for all geothermal resources. These datasets will be used in INGENIOUS as input features for predicting geothermal favorability throughout the Great Basin study area. Datasets consist of shapefiles, geotiffs, tabular spreadsheets, and metadata that describe: 2-meter temperature probe surveys, quaternary faults and volcanic features, geodetic shear and dilation models, heat flow, magnetotellurics (conductance), magnetics, gravity, paleogeothermal features (such as sinter and tufa deposits), seismicity, spring and well temperatures, spring and well aqueous geochemistry analyses, thermal conductivity, and fault slip and dilation tendency. For additional project information, see the INGENIOUS project site linked in the submission. Terms of use: These datasets are provided "as is", and the contributors assume no responsibility for any errors or omissions. The user assumes the entire risk associated with their use of these data and bears all responsibility in determining whether these data are fit for their intended use. These datasets may be redistributed with attribution (see citation information below). Please refer to the license information on this page for full licensing terms and conditions.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Machine Learning Based Network Parameter Estimation Using AMI Data

The expansion of distribution power system and the growing penetration of distributed energy resources present new challenges for situational awareness. Calibrating the extended system model with sensor measurements and maintaining the usability is critical for utilities. This paper presents a distribution network parameter estimation (DNPE) approach using machine learning (ML) and metering data that improve the quality of extended distribution power system modeling. The reliability model can improve the ability of endpoint data to be translated into network-level situational awareness in real time and help distribution system operators (DSOs) solve branch flow and voltage problems. In addition, a data analytic and automate processing scheme is proposed to improve the sensor data quality and prevent misleading information. The effectiveness of the proposed method is verified with actual advanced metering infrastructure (AMI) data on a real utility feeder model, while considering the higher penetration of photovoltaic power generation. The test of DNPE and study results are demonstrated in this paper.

Parameter estimation, machine learning, power dist↗
DOE OSTI2023

Learning Distribution Grid Topologies: A Tutorial

Unveiling feeder topologies from data is of paramount importance to advance situational awareness and proper utilization of smart resources in power distribution grids. This tutorial summarizes, contrasts, and establishes useful links between recent works on topology identification and detection schemes that have been proposed for power distribution grids. The primary focus is to highlight methods that overcome the limited availability of measurement devices in distribution grids, while enhancing topology estimates using conservation laws of power-flow physics and structural properties of feeders. Grid data from phasor measurement units or smart meters can be collected either passively in the traditional way, or actively, upon actuating grid resources and measuring the feeder's voltage response. Analytical claims on feeder identifiability and detectability are reviewed under disparate meter placement scenarios. Such topology learning claims can be attained exactly or approximately so via algorithmic solutions with various levels of computational complexity, ranging from least-squares fits to convex optimization problems, and from polynomial-time searches over graphs to mixed-integer programs. Although the emphasis is on radial single-phase feeders, extensions to meshed and/or multiphase circuits are sometimes possible and discussed. Here this tutorial aspires to provide researchers and engineers with knowledge of the current state-of-the-art in tractable distribution grid learning and insights into future directions of work.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Standoff trace explosives vapor detection at meter distances

Vapor detection is a noncontact sampling method, which is a less invasive means of explosives screening than physical swiping. Explosive vapor detection is a challenge due to the low levels of vapors available for detection. This study demonstrates that the parts-per-quadrillion sensitivity of atmospheric flow tube-mass spectrometry (AFT-MS) combined with a high-volume air sampler enables standoff detection of trace explosives vapor at distances of centimeters to meters. Standoff detection of explosives vapor was possible both upstream and downstream of the vapor source relative to room air currents. RDX vapor from a saturated source was detected at up to 2.5 m. Vapors from RDX residue and nitroglycerin residue were detected at distances up to 0.5 m. The sampling can be optimized by accounting for air movement in the room or environment, which could further extend standoff detection distances. In conclusion, using AFT-MS with a high-volume sampler could also be effective for standoff vapor detection of drugs and additional chemical threats and could be useful for security screening applications such as at mail facilities, border crossings, and security checkpoints.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

SWIFT - Shaped-Waveform Interrogation of Fluids Technique

Researchers at Los Alamos have developed the Shaped-Waveform Interrogation of Fluids Technique (SWIFT), a technology enabling unprecedented process control capability. This technology provides important composition, flow rate, and pipe thickness measurements in real-time, at an extremely low cost and maintenance cycle. By utilizing a specialized shaped-waveform, as well as state-of-the-art signal processing, this information can be gathered without any frequency-domain signal processing, allowing for simplified electronics compared to nearly any other meter on the market. Since this technology is in expensive and non-invasive, with the capability of measuring liquids in both flow pipes and sealed containers, it is perfect for several industrial applications in the oil and gas, beverage, chemical, and pharmaceutical spaces. We are seeking a commercialization partner to license the technology or fund us through a Cooperative Research and Development Agreement (CRADA) to a further develop a usable product for commercial purposes.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Network-Aware and Welfare-Maximizing Dynamic Pricing for Energy Sharing

The proliferation of behind-the-meter (BTM) distributed energy resources (DER) within the electrical distribution network presents significant supply and demand flexibilities, but also introduces operational challenges such as voltage spikes and reverse power flows. In response, this paper proposes a network-aware dynamic pricing framework tailored for energy-sharing coalitions that aggregate small, but ubiquitous, BTM DER downstream of a distribution system operator's (DSO) revenue meter that adopts a generic net energy metering (NEM) tariff. By formulating a Stackelberg game between the energy-sharing market leader and its prosumers, we show that the dynamic pricing policy induces the prosumers toward a network-safe operation and decentrally maximizes the energysharing social welfare. The dynamic pricing mechanism involves a combination of a locational ex-ante dynamic price and an ex-post allocation, both of which are functions of the energy sharing's BTM DER. The ex-post allocation is proportionate to the price differential between the DSO NEM price and the energy-sharing locational price. Simulation results using real DER data and the IEEE 13-bus test systems illustrate the dynamic nature of network-aware pricing at each bus, and its impact on voltage.

aggregates↗
DOE OSTI2024

Network-Aware and Welfare-Maximizing Dynamic Pricing for Energy Sharing: Preprint

The proliferation of behind-the-meter (BTM) distributed energy resources (DER) within the electrical distribution network presents significant supply and demand flexibilities, but also introduces operational challenges such as voltage spikes and reverse power flows. In response, this paper proposes a network-aware dynamic pricing framework tailored for energy-sharing coalitions that aggregate small, but ubiquitous, BTM DER downstream of a distribution system operator's (DSO) revenue meter that adopts a generic net energy metering (NEM) tariff. By formulating a Stackelberg game between the energy-sharing market leader and its prosumers, we show that the dynamic pricing policy induces the prosumers toward a network-safe operation and decentrally maximizes the energysharing social welfare. The dynamic pricing mechanism involves a combination of a locational ex-ante dynamic price and an ex-post allocation, both of which are functions of the energy sharing's BTM DER. The ex-post allocation is proportionate to the price differential between the DSO NEM price and the energy sharing locational price. Simulation results using real DER data and the IEEE 13-bus test systems illustrate the dynamic nature of network-aware pricing at each bus, and its impact on voltage.

energy communities↗