Search NASA⌕ Search

SEARCH · Search NASA

Results for “measurement technology”

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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Cooperative Research and Development Agreement between National Energy Technology Laboratory and Gas Technology Institute (Abstract)

Hydrogen has the potential to play an important role in decarbonizing energy-intensive sectors, and credible and open-source protocols are needed to vet the environmental credibility of a specific production pathway, given the variability even among the same technologies. Stakeholders and markets lack consistent, transparent, technical tools and protocols to assess the carbon intensity of hydrogen production at the asset level. Gas Technology Institute (GTI) and S&P Global Platts have launched the Open Hydrogen Initiative (OHI), a new collaboration focused on brining industry within the hydrogen marketplace together to provide further transparency into the environmental greenhouse gas (GHG) impact of hydrogen production. As part of this initiative, GTI has invited NETL to participate in the effort because of NETL’s deep expertise and capabilities in Life Cycle Analysis. Therefore, NETL is joining forces with the Gas Technology Institute (GTI) to build a measurement tool, accompanying protocols, and confidence score of the quality of the measurement. This CRADA effort provides the technical research collaboration support with GTI that will be used in the broader Open Hydrogen Initiative that can provide stakeholders the technical tools and protocols to decarbonize energyintensive sectors.

08 HYDROGEN↗
DOE OSTI2025

The MAGIS-100 Experiment and a Future, Kilometer-scale Atom Interferometer

The dearth of signals unambiguously attributable to WIMP dark matter motivates exploring new parameter space, particularly the ultra-light dark matter (ULDM) regime, where the signal is not scattering events but wave phenomena. The proliferation of quantum technologies has enabled searches for ULDM at previously inaccessible sensitivity. One such technology is atom interferometry which can measure time-dependent fluctuations in the energy spacing of atoms as well as in the light-travel time across the apparatus, enabling searches for ULDM and gravitational waves, respectively. In this talk, I will review the science case for long baseline atom interferometers, such as MAGIS-100 at Fermilab, provide an update on the experiment’s status, and discuss the need for a future, kilometer-scale atom interferometer which would achieve unprecedented sensitivity to ULDM and gravitational waves in the “Mid-Band” region between LIGO and LISA.

Temples, Dylan J. [Fermilab] (ORCID:00000001601725↗
DOE OSTI2026

DER Cybersecurity Standards: Assessment and Gap Analysis

The purpose of this report is to share the comprehensive gap analysis of existing cybersecurity standards applicable to Distributed Energy Resources (DERs) within the electric power sector. This analysis aims to identify critical deficiencies in current standards, assess their alignment with industry needs, and provide actionable recommendations for enhancing cybersecurity measures. The scope encompasses various DER technologies, including solar, wind, energy storage, and hydrogen fuel cells, and emphasizes the significance of establishing robust cybersecurity frameworks and standards to safeguard these increasingly integrated systems. The report provides valuable insights for stakeholders in the DER ecosystem, including manufacturers, utilities, and regulators. It underscores the importance of continued development and refinement of cybersecurity standards to keep up with the technical advances in DERs and associated cybersecurity challenges. The analysis evaluated IEC, IEEE, ISA, ISO, and UL standards relevant to DER cybersecurity. Standards were assessed on their coverage of key requirements including data availability, integrity, confidentiality, access control, authentication, encryption, and system hardening. For each standard, the analysis assessed its alignment with current industry practices, regulatory compliance, effectiveness in addressing known risks, coverage of emerging risks, and how it promotes interoperability. The evaluation also considered potential integration challenges and barriers to adoption.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Distributed Temperature Monitoring of Tundish Refractory Lining Using Optical Fiber Sensors

Distributed temperature monitoring can provide useful insights into the thermal conditions in the continuous caster tundish that can affect operating stability and cast quality, such as preheat conditions, superheat uniformity, fill height, and refractory wear. In the current study, fiber optic sensors were embedded into the refractory lining of a lab-scale tundish to record the temperature profiles during dry-out, preheating, and direct molten steel exposure to demonstrate sensor performance. Additional trials were performed with fiber optic sensors embedded in an industrial tundish used in production. Furthermore, the results demonstrate that fiber optic sensors using Rayleigh technology can provide accurate distributed temperature measurements in refractory lined vessels and provide useful information about the process.

Continuous Caster↗
DOE OSTI2022

Comparing Calibration Algorithms for the Rapid Characterization of Pretreated Corn Stover Using Near-Infrared Spectroscopy

Rapid characterization of biomass composition is a key enabling technology for biorefineries—the ability to measure the chemical composition of biomass materials entering the biorefinery as well as the composition of key process intermediate streams would allow real-time process control and the development of robust models to predict process performance. The utility of near-infrared (NIR) spectroscopy for rapid characterization requires multivariate algorithms for building calibration models. The most prevalent algorithm used for building calibration models using NIR spectra is the linear modeling algorithm Partial Least Squares Regression (PLS). Nonlinear regression algorithms (which are typically more computationally intensive than linear modeling approaches) have gained popularity in recent years due to their ability to solve a wide variety of classification and regression problems and the dramatic increase in available computational resources. In this work, we demonstrate that a calibration model can predict the composition of corn stover process intermediate samples pretreated with three different treatments—hot water (HW), dilute acid (DA), and deacetylation followed by dilute acid (DDA). We quantitatively compare three different algorithms for building prediction models based on near-infrared spectroscopy—partial least squares (PLS), support vector machines (SVM), and random forests (RF). We demonstrate the utility of improving model performance by accounting for instrument performance variability using repeated measurements of standard materials (e.g., the “repeatability file” strategy) and investigate its performance with nonlinear regression techniques, and we discuss methods for quantifying the uncertainties of specific predictions among the three methods.

09 BIOMASS FUELS↗
DOE OSTI2024

Recent Progress on Surface Water Quality Models Utilizing Machine Learning Techniques

Surface waterbodies are heavily exposed to pollutants caused by natural disasters and human activities. Empowering sensor technologies in water quality monitoring, sufficient measurements have become available to develop machine learning (ML) models. Numerous ML models have quickly been adopted to predict water quality indicators in various surface waterbodies. This paper reviews 78 recent articles from 2022 to October 2024, categorizing water quality models utilizing ML into three groups: Point-to-Point (P2P), which estimates the current target value based on other measurements at the same time point; Sequence-to-Point (S2P), which utilizes previous time series data to predict the target value at one time point ahead; and Sequence-to-Sequence (S2S), which uses previous time series data to forecast sequential target values in the future. The ML models used in each group are classified and compared according to water quality indicators, data availability, and model performance. Widely used strategies for improving performance, including feature engineering, hyperparameter tuning, and transfer learning, are recognized and described to enhance model effectiveness. The interpretability limitations of ML applications are discussed. This review provides a perspective on emerging ML for surface water quality models.

machine learning (ML)↗
DOE OSTI2021

Aerosol-Based Method Seals the Deal for Tighter New Homes

What if an aerosol-based sealing method could tighten new home envelopes more quickly and effectively than traditional sealing methods? The method involves pressurizing an entire building while dispersing an aerosol sealant "fog" to the building interior. As air escapes the building through leaks in the envelope, sealant particles are carried to the leaks where they make contact and stick, sealing the leaks. A standard blower door and connected laptop facilitate the sealing process and provide real-time feedback and a permanent record of the sealing. The technology is thus capable of simultaneously measuring, locating, and automatically sealing leaks in a building. In fact, hundreds of linear feet of narrow leaks can be sealed simultaneously, reducing the time needed for manual inspection and sealing. To investigate the use of this method in new homes, the Center for Energy and Environment and partners worked with builders who performed the technique on 11 homes in California and 15 homes in Minnesota.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2023

Counting Calories: Light Yield Studies with ADRIANO2 Calorimeter Prototype

Precision in measuring particle energies is crucial to understand the intricacies of high-energy physics beyond the standard model. For the REDTOP experiment to detect η/η´ mesons potentially decaying into dark-matter particles not yetdiscovered, it is essential to have accurate measurements through sophisticated and innovative detector technology built with special properties. The ADRIANO2 (A Dual Readout Integrally Active Non-segmented Option) Calorimeter Prototype plays a pivotal role in advancing detection capabilities, offering the potential to enhance the particle identification procedure. This study delves into the characterization of the ADRIANO2 prototype’s light yield with the ultimate goal of contributing to broader high-energy physics objectives. To estimate the light yield for the ADRIANO2 prototype, we must calibrate the light sensors as well as collect data from beams of known properties. Several prototypes of the ADRIANO2 detector have been tested at the Mtest Facility at Fermi National Accelerator Laboratory in the last few years. This paper attempts to summarize the calibration of one such ADRIANO2 prototype to estimate its experimental performance.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Paths Forward: Approaches to Achieve Plug and Process Load Efficiency and Control in Commercial Buildings: Preprint

To accomplish net-zero carbon in the built environment by 2050, we must equitably decarbonize commercial buildings, which includes reducing plug and process loads (PPLs). PPLs are plug-in or hardwired electric and gas loads that are not directly associated with major building end uses like lighting and heating, ventilating, and air conditioning. PPLs account for a growing portion of U.S. commercial building energy consumption. Although commercial building PPL strategies and technologies are available today, they have not been adopted at a level sufficient to achieve significant savings and load flexibility across the building stock. In our "Pathways to Plug and Process Load Efficiency and Control" study, we investigated why these technologies and strategies have not seen widespread adoption and identified five behavior and technology pathways to increase PPL reduction in commercial buildings. In this paper, we expand beyond identifying the pathways and discuss approaches for achieving them. We discuss the importance of collecting and sharing data and case studies on PPL energy consumption and savings from control technology implementation, including code-required measures, for increasing adoption. Centralizing case studies and data, engaging industry organizations, and promoting awareness of PPL efficiency benefits to relevant groups are also key approaches. Additionally, funding, incentives, and rebate programs play important roles in driving PPL efficiency and control adoption. Finally, we discuss integrating PPL efficiency into broader company goals, such as environmental, social and governance (ESG) strategies and green building certifications, to further drive adoption.

adoption pathways↗
DOE OSTI2022

In-Use Passenger Vessel Emission Rates of Black Carbon and Nitrogen Oxides

This study quantified emission factors of black carbon (BC) and nitrogen oxides (NO x ) from 21 engines on in-use excursion vessels and ferries operating in California's San Francisco Bay, including EPA uncertified and Tier 1-4 engines and across engine operating modes. On average, ~60 fuel-based emission factors per engine were measured using a novel combination of exhaust plume capture combined with GPS location and speed data that can be more readily deployed than common portable emissions measurement systems. Here, BC and NO x emission factors (g kg -1 ) were lowest and least variable during fast cruising and highest during maneuvering and docked operation. Selective catalytic reduction (SCR) reduced NO x emissions by ~80% when functional. However, elevated NO x emissions that exceeded corresponding exhaust standards were measured on most Tier 3 and Tier 4 engines sampled, which can be attributed to inactive SCR during frequent low engine load operation. In contrast, BC emissions exceeded the PM emission standard for only one engine, and SCR systems employed as a NO x reduction technology also reduced emitted BC. Using these measured emission factors to compare commuting options, we show that the CO 2 -equivalent emissions per passenger-kilometer are comparable when commuting by car and ferry, but BC and NO x emissions can be several to more than ten times larger when commuting by ferry.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Attosecond control and measurement of chiral photoionization dynamics

Many chirality-sensitive light–matter interactions are governed by chiral electron dynamics. Therefore, the development of advanced technologies making use of chiral phenomena would critically benefit from measuring and controlling chiral electron dynamics on their natural attosecond timescales. Such endeavours have so far been hampered by the lack of characterized circularly polarized attosecond pulses, an obstacle that has recently been overcome. Here we introduce chiroptical spectroscopy with attosecond pulses and demonstrate attosecond coherent control over photoelectron circular dichroism (PECD), as well as the measurement of chiral asymmetries in the forward–backward and angle-resolved photoionization delays of chiral molecules. We show that co-rotating attosecond and near-infrared (IR) pulses can nearly double the PECD and even change its sign compared with single-photon ionization. We demonstrate that chiral photoionization delays depend on both polar and azimuthal angles of photoemission in the light-propagation frame, requiring 3D momentum resolution. We measure forward–backward chiral-sensitive delays of up to 60 as and polar-angle-resolved photoionization delays of up to 240 as, which include an asymmetry of about 60 as originating from chirality in the continuum–continuum transitions. Attosecond chiroptical spectroscopy opens the door to quantitatively understanding and controlling the dynamics of chiral molecules on the electronic timescale.

Atomic and molecular interactions with photons↗
DOE OSTI2024

R&D for LAr + Xe + photosensitive dopants

LArTPCs are the technology of choice for current and future neutrino experiments, including those expected to make eagerly awaited measurements of accelerator neutrino oscillations in the coming decade. This technology provides a large active volume and sensitivity to GeV signals like accelerator neutrinos all the way down to 10s of MeV, covering part of the supernova neutrino spectrum.Expanding the reach of LArTPCs to below the 10 MeV range would substantially enhance the flagship analyses of experiments like DUNE, while potentially enabling the physics of solar neutrinos, dark matter searches, and neutrinoless double beta decay searches.We outline the R&D pathway for photosensitive dopants, whose introduction into the LAr active medium, has the potential to substantially increase ionization yields of LAr detectors and enable the detection of low energy signals in large LArTPCs. This R&D program will demonstrate the feasibility and impacts of introducing doped LAr into current and future neutrino detectors at the kTon scale including the Xenon + photosensitive doping strategy.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Newberry SHR Demonstration Project – Bipartisan Infrastructure Law Enhanced Geothermal (EGS) Pilot Demonstration (Abstract)

This project will create an Engineered Geothermal System (EGS) comprising two or more wells drilled to a depth of 4.25 km into superhot rock (SHR) with a temperature of 425 °C at Newberry Volcano in Central Oregon. An EGS is a manufactured heat exchanger in which water is injected in a deep injection well, or injector, to extract heat from the hot rock at depth and steam is returned to the surface in a production well, or producer, to generate electricity. In this project, the SHR EGS will be made using new methods and technologies to stimulate and connect hydraulic and natural fractures to enable multiple flow pathways between wells, allowing for optimal heat mining from the reservoir rock. The new technologies are designed to operate at rock temperatures much higher than those encountered in traditional geothermal. Following EGS completion, water will be injected into the injector well and steam extracted from the producer well in a long-term connectivity flow test demonstrating SHR reservoir evolution with time and use. Success will be measured by demonstrating the efficacy of new technologies and by producing economic quantities of steam (>40 MWth).

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Autonomous Wireless Technology Detection in Seamless IoT Applications

The ever-increasing use of Internet of Things (IoT) devices results in the implementation of multiple wireless technologies that would not only cater their data rate requirements but also support various applications. To optimize the energy efficiency and security of the wireless transmission, it is imperative to identify the wireless technologies in various IoT implementations. Many of the existing approaches are based on measuring only the receiving signal strength indicator (RSSI). However, such approaches may not work well because of transmit power control and complex channel variations among different wireless technologies. In this article, we propose an autonomous wireless detection scheme that considers multiple distinguishable physical (PHY)-layer settings for real-time identification of wireless technologies for real-time applications. Specifically, the proposed scheme relies on the PHY-layer measurements of the targeted spectrum. Transmission settings, such as bandwidth, carrier frequency, and RSSI are estimated from the raw in-phase and quadrature-phase (I/Q) measurements. In addition, a symbol-level extraction scheme is implemented to extract unique features of modulation settings. These aforementioned features are applied to a machine learning process to identify the received wireless technologies. Compared with raw I/Q measurements, the extracted features are much simplified and, thus, the machine learning classifier can be designed with a simple structure for fast processing on IoT nodes. Finally, the proposed schemes are primarily evaluated theoretically, followed by implementing them on a USRP software-defined radio (SDR)-based hardware testbed. The evaluation results demonstrate high accuracy in the real-time detection of different wireless technologies for seamless IoT applications.

42 ENGINEERING↗
DOE OSTI2022

Measurement of Resistance, Porosity, and Water Contact Angle of Porous Transport Layers for Low-Temperature Electrolysis Technologies

The porous transport layer is an important component of low-temperature electrolysis devices, such as proton exchange membrane water electrolyzers or anion exchange membrane water electrolyzers. PTLs have significant influence on the cell performance as their bulk resistance can impact the ohmic resistance, their contact resistance can impact electrode performance, and their structure can impact the liquid flow to the cell, which could cause mass-transport losses. In order to improve cell performance, optimization of the PTL is critical. Standardized protocols should be utilized to adequately compare PTLs being developed from different institutions. This method will detail a standardized protocol for measuring the resistance of the PTL using a four-wire setup and will also detail a process for measuring the porosity and water contact angle of the PTL using capillary flow porometry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Characterizing the Electromagnetic Response of the NOvA Detectors

The NOvA Test Beam Program was commissioned to complement the full-scale NOvA experiment in its goal of measuring neutrino oscillations. The NOvA Experiment consists of a 300-ton Near Detector and a 14-kton Far Detector, both exposed to the same beam, which can be operated in neutrino or antineutrino mode from Fermilab at an off-axis angle of 14.6~mrad. These detectors can discriminate between $\nu_\mu$-CC and $\nu_e$-CC neutrino (or corresponding antineutrino) events, enabling appearance and disappearance measurements of these flavors across the \SI{810}{\kilo\meter} near-to-far detector baseline. From these measurements, the underlying parameters of the three-flavor PMNS oscillations framework are measured. The NOvA Test Beam uses identical technology to the full-scale detectors, but scaled down to 30~tons. It is exposed to a beam of charged particles closely matched to the daughter products of NOvA (anti)neutrino interactions in both energy and species. An instrumented beamline determines both particle momentum and species upstream of the NOvA detector, allowing for a crisp measurement of the NOvA detector response to these known inputs. This dissertation presents an analysis of the electromagnetic response of the NOvA hardware and establishes a framework for incorporating these results to enhance the physics reach of the experiment. Prior to this work, the electromagnetic energy response of the NOvA detector relied primarily on simulation-driven calibration together with a globally applied energy scale uncertainty. The measurements presented here provide direct test beam constraints on the detector response, enabling particle-dependent and potentially energy-dependent uncertainty models derived from controlled electromagnetic inputs.

Myers, Dalton Grant [U. Texas, Austin (main)] (ORC↗