Results for “Advanced characterization” — Page 94

NASA NTRS1993

Characterization of fluid physics effects on cardiovascular response to microgravity (G-572)

The recognition and understanding of cardiovascular adaptation to spaceflight has experienced substantial advancement in the last several years. In-flight echocardiographic measurements of astronaut cardiac function on the Space Shuttle have documented a 15 percent reduction in both left ventricular volume index and stroke volume with a compensatory increase in heart rate to maintain cardiac output. To date, the reduced cardiac size and stroke volume have been presumed to be the consequence of the reduction in circulating fluid volume following diuresis and other physiological processes to reduce blood volume within a few days after orbital insertion. However, no specific mechanism for the reduced stroke volume has been elucidated. The following investigation proposes the use of a hydraulic model of the cardiovascular system to examine the possibility that the observed reduction in stroke volume may, in part, be related to fluid physics effects on heart function. The automated model is being prepared to fly as a GAS payload. The experimental apparatus consists of a pneumatically actuated, elliptical artificial ventricle connected to a closed-loop, hydraulic circuit with compliance and resistance elements to create physiologic pressure and flow conditions. The ventricle is instrumented with high-fidelity, acceleration-insensitive, catheter-tip pressure transducers (Millar Instruments) in the apex and base to determine the instantaneous ventricular pressures and (delta)P(sub LV) across the left ventricle (LVP(sub apex)-LVP(sub base). The ventricle is also instrumented with a flow probe and pressure transducers immediately upstream of the inflow valve and downstream of the outflow valve. The experiment will be microprocessor controlled with analog signals stored on the FM data tape recorder. By varying the circulating fluid volume, ventricular function can be determined for varying preload pressures with fixed afterload pressure. Pilot experiments on board the NASA KC-135 aircraft have demonstrated proof-of-concept and provided early support for the proposed hypothesis. A review of the pilot experiments and developmental progress on the GAS version of this experiment will be presented.

Pantalos, George M.↗

NASA NTRS1995

Bearing defect signature analysis using advanced nonlinear signal analysis in a controlled environment

Utilizing high-frequency data from a highly instrumented rotor assembly, seeded bearing defect signatures are characterized using both conventional linear approaches, such as power spectral density analysis, and recently developed nonlinear techniques such as bicoherence analysis. Traditional low-frequency (less than 20 kHz) analysis and high-frequency envelope analysis of both accelerometer and acoustic emission data are used to recover characteristic bearing distress information buried deeply in acquired data. The successful coupling of newly developed nonlinear signal analysis with recovered wideband envelope data from accelerometers and acoustic emission sensors is the innovative focus of this research.

Zoladz, T.↗

NASA NTRS2009

In-Situ NDE Characterization of Kevlar and Carbon Composite Micromechanics for Improved COPV Health Monitoring

This project is a subtask of a multi-center project to advance the state-of-the-art by developing NDE techniques that are capable of evaluating stress rupture (SR) degradation in Kevlar/epoxy (K/Ep) composite overwrapped pressure vessels (COPVs), and damage progression in carbon/epoxy (C/Ep) COPVs. In this subtask, acoustic emission (AE) data acquired during intermittent load hold tensile testing of K/Ep and C/Ep composite tow materials-of-construction used in COPV fabrication were analyzed to monitor progressive damage during the approach to tensile failure. Insight into the progressive damage of composite tow was gained by monitoring AE event rate, energy, source location, and frequency. Source location based on arrival time data was used to discern between significant AE attributable to microstructural damage and spurious AE attributable to background and grip noise. One of the significant findings was the observation of increasing violation of the Kaiser effect (Felicity ratio < 1.0) with damage accumulation.

Waller, Jess M.↗

DOE OSTI2022

Status of Research Activities on LVDTs: Modeling and Simulation Development and Performance Characterization of Commercial LVDTs

FY-22 research focused on two major areas. The first area was modeling and simulation with linked testing that will advance the Linear Variable Differential Transformers (LVDT) technology for use by stakeholders requiring LVDTs in upcoming irradiation tests. The second area focused on testing LVDTs purchased from U.S. suppliers that were investigated in FY-21. These cross-cutting development activities will ensure stakeholders have the current state-of-the-art LVDT-based technologies for deployment in future irradiation tests. Two stand-alone reports are included in the appendixes. The purpose of this report is to provide a convenient body of work to access the reports and to evaluate the data and conclusions provided. Appendix A, “Testing of the RDP Translation Transducer,” contains a complete evaluation of an RDP Electrosense linear transducer that has the capability of replicating the form, fit, and function of LVDTs currently being used at Idaho National Laboratory (INL). Appendix B is an extract from the report, “Advanced Sensors and Instrumentation Program at Boise State University (BSU), August 2022, Linear Variable Differential Transformers.” This report contains modeling and testing results conducted at BSU and INL.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

At-power subcritical multiplication in the advanced test reactor

The degree to which a given physical subdivision of a critical reactor acts as a neutron source for other lobes is not analytically characterized for general application. ATR and ATRC both operate at power, and individual power-producing lobes rely on each other as neutron sources in order to maintain constant power, which in general requires either exactly critical multiplication within a reactor or an external neutron source. Here, this work shows that lobe powers in ATR or ATRC can be related with subcritical multiplication theory, demonstrating that the lobes are not individually critical. This explanation is significant for ATR due to the desire to irradiate a large variety of experiments simultaneously, each having its impact on the core neutron population. This work also establishes the lack of relationship between experiment reactivity worth and cross-sections calculated from fundamental nuclear data. For any physical subdivision of any other critical reactor, it is likewise true that the subdivision undergoes only subcritical multiplication.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRS1994

The AEDC aerospace chamber 7V: An advanced test capability for infrared surveillance and seeker sensors

An advanced sensor test capability is now operational at the Air Force Arnold Engineering Development Center (AEDC) for calibration and performance characterization of infrared sensors. This facility, known as the 7V, is part of a broad range of test capabilities under development at AEDC to provide complete ground test support to the sensor community for large-aperture surveillance sensors and kinetic kill interceptors. The 7V is a state-of-the-art cryo/vacuum facility providing calibration and mission simulation against space backgrounds. Key features of the facility include high-fidelity scene simulation with precision track accuracy and in-situ target monitoring, diffraction limited optical system, NIST traceable broadband and spectral radiometric calibration, outstanding jitter control, environmental systems for 20 K, high-vacuum, low-background simulation, and an advanced data acquisition system.

Simpson, W. R.↗

NASA NTRSDate not supplied

Enhanced Quantification of 3D Woven Composites Via Fourier Analysis and Structure Tensors Applied to CT Scans

NASA's development of advanced 3D woven carbon composites, such as HEEET and 3MDCP, represents a significant leap in materials designed to endure extreme atmospheric entry conditions. However, the internal complexity of these materials introduces a variety of structures and novel defect types. Traditional characterization methods rely on labor-intensive, manual examination of X-ray CT scans, demanding considerable time and expertise. This process, while thorough, is not sustainable for large-scale analysis and defect tracking. Addressing this critical challenge, this presentation introduces an innovative suite of automated tools and analytical techniques, pioneered by the Mars Sample Return (MSR) Earth Entry System (EES) Thermal Protection System (TPS) project. These advancements offer a more efficient and accurate approach for quantifying CT data and characterizing the defects of 3D woven composites.

Magnus Haw↗

NASA NTRSDate not supplied

SelenITA: A dual-spacecraft lunar CubeSat mission to characterize the near-surface electromagnetic plasma environment

SelenITA is an international interdisciplinary mission consisting of two CubeSats that will provide the first multi-point measurement in a sustained low lunar orbit. This mission will advance the understanding of spatiotemporal differentiation of the electromagnetic space environment at the Moon in support of Artemis crew and the geosciences. The mission science objectives are to: (1) further constrain the origins of crustal magnetic fields and their applications; (2) determine the nature of plasma interactions with crustal magnetic fields; (3) characterize plasma waves and turbulence at the Moon; (4) characterize the lunar surface potential in all plasma environments; (5) constrain the composition, thermal state, and structure of the lunar upper mantle and crust; (6) characterize the ionizing radiation in lunar orbit; (7) determine the density of the dust exosphere as a function of latitude, longitude, and altitude, including the lunar polar space environment. The measurement requirements include: 3-component vector magnetic field, plasma distribution (flux, energy, density, temperature), energetic particles (protons, electrons, gamma rays), and dust. SelenITA builds on a rich history of electromagnetic plasma observations of the near lunar surface and space environment, and it answers high level science questions with state of the art instruments in a small package. PLAIN LANGUAGE ABSTRACT – SelenITA comes from the greek word for Moon, selene, with the addition of “ITA” as a reference to the Brazilian teammate, Instituto Tecnológico de Aeronáutica. In addition, in Portuguese "ita" is a prefix similar to "ite" in English, used in naming minerals, so Selenita could be seen as a lunar gemstone. In Spanish, “ita” is a diminutive suffix for “little” which is appropriate for this CubeSat mission which consists of twin 12U CubeSats in low lunar orbit. The primary science goal of the mission is to distinguish time varying features within the electromagnetic plasma environment near the surface of the Moon. The science objectives include investigating the origins of crustal magnetic fields, plasma interactions with these fields, plasma waves, surface potential, and interior properties. This mission is also interested in the radiation environment at the Moon and the amount of dust at the lunar poles. This is important because it helps us understand how future astronauts will live and work on the lunar surface and identify hazards.

space weather↗

NASA NTRSDate not supplied

SelenITA: A Dual-Spacecraft Lunar Cubesat Mission to Characterize the Near-Surface Electromagnetic Plasma Environment

SelenITA is an international interdisciplinary mission consisting of two CubeSats that will provide the first multi-point measurement in a sustained low lunar orbit. This mission will advance the understanding of spatiotemporal differentiation of the electromagnetic space environment at the Moon in support of Artemis crew and the geosciences. The mission science objectives are to: (1) further constrain the origins of crustal magnetic fields and their applications; (2) determine the nature of plasma interactions with crustal magnetic fields; (3) characterize plasma waves and turbulence at the Moon; (4) characterize the lunar surface potential in all plasma environments; (5) constrain the composition, thermal state, and structure of the lunar upper mantle and crust; (6) characterize the ionizing radiation in lunar orbit; (7) determine the density of the dust exosphere as a function of latitude, longitude, and altitude, including the lunar polar space environment. The measurement requirements include: 3-component vector magnetic field, plasma distribution (flux, energy, density, temperature), energetic particles (protons, electrons, gamma rays), and dust. SelenITA builds on a rich history of electromagnetic plasma observations of the near lunar surface and space environment, and it answers high level science questions with state of the art instruments in a small package.

space weather↗

NASA NTRSDate not supplied

SelenITA: A Dual-Spacecraft Lunar CubeSat Mission to Characterize the Near-Surface Electromagnetic Plasma Environment

SelenITA is an international interdisciplinary mission consisting of two CubeSats that will provide the first multi-point measurement in a sustained low lunar orbit. This mission will advance the understanding of spatiotemporal differentiation of the electromagnetic space environment at the Moon in support of Artemis crew and the geosciences. The mission science objectives are to: (1) further constrain the origins of crustal magnetic fields and their applications; (2) determine the nature of plasma interactions with crustal magnetic fields; (3) characterize plasma waves and turbulence at the Moon; (4) characterize the lunar surface potential in all plasma environments; (5) constrain the composition, thermal state, and structure of the lunar upper mantle and crust; (6) characterize the ionizing radiation in lunar orbit; (7) determine the density of the dust exosphere as a function of latitude, longitude, and altitude, including the lunar polar space environment. The measurement requirements include: 3-component vector magnetic field, plasma distribution (flux, energy, density, temperature), energetic particles (protons, electrons, gamma rays), and dust. SelenITA builds on a rich history of electromagnetic plasma observations of the near lunar surface and space environment, and it answers high level science questions with state of the art instruments in a small package. PLAIN LANGUAGE ABSTRACT – SelenITA comes from the greek word for Moon, selene, with the addition of “ITA” as a reference to the Brazilian teammate, Instituto Tecnológico de Aeronáutica. In addition, in Portuguese "ita" is a prefix similar to "ite" in English, used in naming minerals, so Selenita could be seen as a lunar gemstone. In Spanish, “ita” is a diminutive suffix for “little” which is appropriate for this CubeSat mission which consists of twin 12U CubeSats in low lunar orbit. The primary science goal of the mission is to distinguish time varying features within the electromagnetic plasma environment near the surface of the Moon. The science objectives include investigating the origins of crustal magnetic fields, plasma interactions with these fields, plasma waves, surface potential, and interior properties. This mission is also interested in the radiation environment at the Moon and the amount of dust at the lunar poles. This is important because it helps us understand how future astronauts will live and work on the lunar surface and identify hazards.

space weather↗

NASA NTRS2017

A Comparison of the SOCIT and DebriSat Experiments

This paper explores the differences between, and shares the lessons learned from, two hypervelocity impact experiments critical to the update of orbital debris environment models. The procedures and processes of the fourth Satellite Orbital Debris Characterization Impact Test (SOCIT) were analyzed and related to the ongoing DebriSat experiment. SOCIT was the first hypervelocity impact test designed specifically for satellites in Low Earth Orbit (LEO). It targeted a 1960's U.S. Navy satellite, from which data was obtained to update pre-existing NASA and DOD breakup models. DebriSat is a comprehensive update to these satellite breakup models- necessary since the material composition and design of satellites have evolved from the time of SOCIT. Specifically, DebriSat utilized carbon fiber, a composite not commonly used in satellites during the construction of the US Navy Transit satellite used in SOCIT. Although DebriSat is an ongoing activity, multiple points of difference are drawn between the two projects. Significantly, the hypervelocity tests were conducted with two distinct satellite models and test configurations, including projectile and chamber layout. While both hypervelocity tests utilized soft catch systems to minimize fragment damage to its post-impact shape, SOCIT only covered 65% of the projected area surrounding the satellite, whereas, DebriSat was completely surrounded cross-range and downrange by the foam panels to more completely collect fragments. Furthermore, utilizing lessons learned from SOCIT, DebriSat's post-impact processing varies in methodology (i.e., fragment collection, measurement, and characterization). For example, fragment sizes were manually determined during the SOCIT experiment, while DebriSat utilizes automated imaging systems for measuring fragments, maximizing repeatability while minimizing the potential for human error. In addition to exploring these variations in methodologies and processes, this paper also presents the challenges DebriSat has encountered thus far and how they were addressed. Accomplishing DebriSat's goal of collecting 90% of the debris, which constitutes well over 100,000 fragments, required addressing many challenges stemming from the very large number of fragments. One of these challenges arose in identifying the foam-embedded fragments. DebriSat addressed this by X-raying all of the panels once the loose debris were removed, and applying a detection algorithm developed in-house to automate the embedded fragment identification process. It is easy to see how the amount of data being compiled would be outstanding. Creating an efficient way to catalog each fragment, as well as archiving the data for reproducibility also posed a great challenge for DebriSat. Barcodes to label each fragment were introduced with the foresight that once the characterization process began, the datasheet for each fragment would have to be accessed again quickly and efficiently. The DebriSat experiment has benefited significantly by leveraging lessons learned from the SOCIT experiment along with the technological advancements that have occurred during the time between the experiments. The two experiments represent two ages of satellite technology and, together, demonstrate the continuous efforts to improve the experimental techniques for fragmentation debris characterization.

Ausay, Erick↗

DOE OSTI2026

Data for A Generalized Platform for Artificial Intelligence-powered Autonomous Protein Engineering

Proteins are the molecular machines of life with numerous applications in energy, health, and sustainability. However, engineering proteins with desired functions for practical applications remains slow, expensive, and specialist-dependent. Here we report a generally applicable platform for autonomous enzyme engineering that integrates machine learning and large language models with biofoundry automation to eliminate the need for human intervention, judgement, and domain expertise. Requiring only an input protein sequence and a quantifiable way to measure fitness, this automated platform can be applied to engineer a wide array of proteins. As a proof of concept, we engineer Arabidopsis thaliana halide methyltransferase (AtHMT) for a 90-foldimprovement in substrate preference and 16-fold improvement in ethyl-transferase activity, along with developing a Yersinia mollaretii phytase (YmPhytase) variant with 26-fold improvement in activity at neutral pH. This is accomplished in four rounds over 4 weeks, while requiring construction and characterization of fewer than 500 variants for each enzyme. This platform for autonomous experimentation paves the way for rapid advancements across diverse industries, from medicine and biotechnology to renewable energy and sustainable chemistry.

AI/ML↗

DOE OSTI2023

Alternative Energy Carriers: Unique Interfaces for Electrochemical Hydrogenic Transformations

Abstract The shift toward renewable energy generation sources, characterized by their non‐carbon emitting but variable nature, has spurred significant innovation in energy storage technologies. Advancements in foundational understanding from investments in basic science and clever engineering solutions, coupled with increasing industrial adoption, have resulted in a notable reduction in the cost of storing electricity from variable energy generation sources. These developments have paved the way for the exploration of new and innovative forms of energy storage that deviate from traditional technologies. In this perspective, it is posited that the progress made in energy storage research over recent years has opened the door to the development of energy carriers for technologies that are yet to be realized. To illustrate this concept, examples of alternative energy carriers are provided within the context of unique electrochemical interfaces for electrochemical hydrogenic transformations. The unique properties of these interfaces and electrochemical systems can be leveraged in ways not yet imagined, creating new possibilities for energy storage. A perspective on the progress and challenges for each interface as well as a general outlook for the advancement of energy carrier systems are provided.

25 ENERGY STORAGE↗

DOE OSTI2024

Infrared nanoimaging and nanospectroscopy of electrochemical energy storage materials and interfaces

Electrochemical interfaces are central to the function and performance of energy storage devices. Thus, the development of new methods to characterize these interfaces, in conjunction with electrochemical performance, is essential for bridging the existing knowledge gaps and accelerating the development of energy storage technologies. Of particular need is the ability to characterize surfaces or interfaces in a non-destructive way with adequate resolution to discern individual structural and chemical building blocks. To this end, sub-diffraction-limit low-energy infrared optical probes that exploit near-field interactions within atomic force microscopy platforms, such as pseudoheterodyne nanoimaging, photothermal nanoimaging and nanospectroscopy, and nanoscale Fourier transform infrared spectroscopy, are all powerful emerging techniques. These are capable of non-destructive surface probing and imaging at nanometer resolution. This review outlines recent efforts to characterize ex situ, in situ, and operando electrode materials and electrochemical interfaces in rechargeable batteries with these advanced infrared near-field probes.

25 ENERGY STORAGE↗

DOE OSTI2025

Resonant Tender X-ray Scattering for Disclosing the Backbone Conformation of Conjugated Polymers

The backbone conformation of conjugated polymers (CPs) is essential to their performance in electronic applications. Contrast-variation small-angle neutron scattering (CV-SANS) techniques were used to assess the CP’s backbone conformation, which relies on synthesis of deuterated polymers. Such a technique has been proven mature and effective. One drawback is that deuteration labeling might subtly alter polymer’s physical properties due to structural modifications. To address these challenges, we introduce a novel approach utilizing tender Xray scattering near the sulfur K-edge to distinctly evaluate the backbone versus whole chain conformation for a low-bandgap donor−acceptor CP, poly[(5,6-difluoro- 2,1,3-benzothiadiazol-4,7-diyl)-alt-(3,3‴-dialkyl-2,2′;5′,2″;5″,2‴-quaterthiophen-5,5‴- diyl)] (PffBT4T). For PffBT4T dissolved in trimethylbenzene (TMB), the sulfur K-edge is identified at approximately 2477 eV using near-edge X-ray absorption fine structure spectroscopy (NEXAFS). Tender X-ray scattering conducted at presulfur K-edge and on-sulfur K-edge at elevated temperatures facilitated the distinction between the backbone and whole chain conformations. The results demonstrate that for highly flexible polymer, the backbone’s persistence length could be lower than that of the whole chains, suggesting a more flexible backbone. This rapid, label-free method enhances our ability to characterize CP’s backbone conformation efficiently, offering significant implications for the design and optimization of CPs for advanced electronics.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Evidence for the utility of quantum computing before fault tolerance

Quantum computing promises to offer substantial speed-ups over its classical counterpart for certain problems. However, the greatest impediment to realizing its full potential is noise that is inherent to these systems. The widely accepted solution to this challenge is the implementation of fault-tolerant quantum circuits, which is out of reach for current processors. Here we report experiments on a noisy 127-qubit processor and demonstrate the measurement of accurate expectation values for circuit volumes at a scale beyond brute-force classical computation. We argue that this represents evidence for the utility of quantum computing in a pre-fault-tolerant era. These experimental results are enabled by advances in the coherence and calibration of a superconducting processor at this scale and the ability to characterize and controllably manipulate noise across such a large device. We establish the accuracy of the measured expectation values by comparing them with the output of exactly verifiable circuits. In the regime of strong entanglement, the quantum computer provides correct results for which leading classical approximations such as pure-state-based 1D (matrix product states, MPS) and 2D (isometric tensor network states, isoTNS) tensor network methods break down. These experiments demonstrate a foundational tool for the realization of near-term quantum applications.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Deciphering decomposition pathways of high explosives with cryogenic X-ray Raman spectroscopy

We employed cryogenic X-ray Raman spectroscopy to investigate the early-stage decomposition of the high explosive molecule hexanitrohexaazaisowurtzitane (CL-20). By systematically varying the radiation dose under cryogenic conditions, we induced the decomposition of the molecule using ionizing radiation and observed the evolution of spectral features at the carbon, nitrogen, and oxygen K edges. Through extensive first-principles calculations, we identified key intermediates in the early stages of the decomposition process, resulting from C–C and C–N bond cleavage which leads to the opening of the internal cage structure. A detailed analysis of spectral trends and fingerprints provided evidence supporting N–NO 2 homolytic cleavage as the primary initial decomposition pathway. The combination of advanced core-level spectroscopy methods and state-of-the-art theoretical calculations enabled a comprehensive characterization of the molecular changes induced by controlled radiation dose exposures. In conclusion, our findings establish a benchmark for understanding the decomposition chemistry of high-explosive materials, offering important insights into their stability and reactivity under extreme conditions.

X-ray Raman spectroscopy↗

DOE OSTI2022

Deep Neural Network High Spatiotemporal Resolution Precipitation Estimation (Deep-STEP) Using Passive Microwave and Infrared Data

Recent developments in “headline-making” deep neural networks (DNNs), specifically convolutional neural networks (CNNs), along with advancements in computational power, open great opportunities to integrate massive amounts of real-time observations to characterize spatiotemporal structures of surface precipitation. This study aims to develop a CNN algorithm, named Deep Neural Network High Spatiotemporal Resolution Precipitation Estimation (Deep-STEP), that ingests direct satellite passive microwave (PMW) brightness temperatures (Tbs) at emission and scattering frequencies combined with infrared (IR) Tbs from geostationary satellites and surface information to automatically extract geospatial features related to the precipitable clouds. These features allow the end-to-end Deep-STEP algorithm to instantaneously map surface precipitation intensities with a spatial resolution of 4 km. The main advantages of Deep-STEP, as compared to current state-of-the-art techniques, are 1) it learns and estimates complex precipitation systems directly from raw measurements in near–real time, 2) it uses the automatic spatial neighborhood feature extraction approach, and 3) it fuses coarse-resolution PMW footprints with IR images to reliably retrieve surface precipitation at a high spatial resolution. We anticipate our proposed DNN algorithm to be a starting point for more sophisticated and efficient precipitation retrieval systems in terms of accuracy, fine spatial pattern detection skills, and computational costs.

54 ENVIRONMENTAL SCIENCES↗