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At least 415 records · Page 23

The Chemical Evolution of Cosmic Carbon: Laboratory Studies with the COSmIC Facility

Cosmic dust plays an essential role in our understanding of the chemical and physical evolution of the universe. Our understanding of cosmic dust relies on a combination of astronomical observations (either remote or on extraterrestrial dust samples), astrophysical modeling and laboratory studies of realistic analogs of cosmic dust grains. The COSmIC facility was developed at NASA Ames to study the evolution of cosmic carbon from circumstellar outflows to interstellar clouds to planetary atmospheres in the laboratory [1]. COSmIC stands for “Cosmic Simulation Chamber” and is dedicated to the study of neutral and ionized molecules and grain particles under the low temperature and density conditions that are required to simulate space environments. COSmIC integrates a variety of instruments that allow generating, processing, and monitoring simulated space conditions in the laboratory. It is composed of a Pulsed Discharge Nozzle (PDN) expansion that generates a plasma in a free supersonic jet expansion, coupled to high-sensitivity, complementary in situ diagnostic tools used for the detection and characterization of the species present in the expansion: Cavity Ring Down Spectroscopy (CRDS) and fluorescence spectroscopy systems for photonic detection and an orthogonal Reflectron Time-Of-Flight Mass Spectrometer (oReTOF-MS) for mass detection. Recent advances achieved in laboratory astrophysics using COSmIC’s laboratory data in synergy with observational data will be presented. These results include the formation of dust grains and aerosols from gas-phase molecular precursors in environments as varied as circumstellar outflows of late AGB stars [2] and planetary atmospheres [3] and the evolution of our understanding of the diffuse interstellar bands (DIBs) with applications to the ESO Diffuse Interstellar Bands Large Exploration Survey (EDIBLES [4, 5]). Plans for future laboratory developments and techniques to study the evolution of cosmic carbon molecules and grains (including NIR-MIR CRDS, laser induced fluorescence (LIF) and incandescence (LII)) will also be addressed as well as their astronomical applications.

Salama, F.↗

The Chemical Evolution of Cosmic Dust: From Gas-Phase Precursors to Solid Grains - Laboratory Studies with the COSmIC Facility

Cosmic dust in in its gas phase and solid phase components plays an essential role in the chemical and physical evolution of the universe. Our understanding of cosmic dust properties relies on a combination of astronomical observations, astrophysical modeling and laboratory studies of realistic analogs of cosmic dust being gas-phase molecules and/or solid grains. The COSmIC facility was developed at NASA Ames to study the evolution of cosmic carbon from circumstellar outflows to interstellar clouds to planetary atmospheres in the laboratory. COSmIC stands for “Cosmic Simulation Chamber” and is dedicated to the study of neutral and ionized molecules and grain particles under the low temperature and density conditions that are required to simulate space environments. It integrates a variety of instruments that allow generating, processing, and monitoring simulated space conditions in the laboratory. It is composed of a Pulsed Discharge Nozzle (PDN) expansion that generates a plasma in a free supersonic jet expansion, coupled to high-sensitivity, complementary in situ diagnostic tools used for the detection and characterization of the species present in the expansion: Cavity Ring Down Spectroscopy (CRDS) and fluorescence spectroscopy systems for photonic detection and an orthogonal Reflectron Time-Of-Flight Mass Spectrometer (oReTOF-MS) for mass detection. Recent advances achieved using COSmIC’s laboratory data in synergy with observational data will be presented. These results include the formation of dust grains and aerosols from gas-phase molecular precursors in environments as varied as circumstellar outflows of late AGB stars and planetary atmospheres [4] and the evolution of our understanding of the diffuse interstellar bands (DIBs) with applications to the ESO Diffuse Interstellar Bands Large Exploration Survey (EDIBLES). Plans for future laboratory developments and techniques to study the evolution of cosmic carbon molecules and grains (including NIR-MIR CRDS, laser induced fluorescence (LIF) and incandescence (LII)) will also be addressed as well as their astronomical applications.

Farid Salama↗

The Chemical Evolution of Cosmic Dust: From Gas-Phase Precursors to Solid Grains - Laboratory Studies with the COSmIC Facility

Cosmic dust in in its gas phase and solid phase components plays an essential role in the chemical and physical evolution of the universe. Our understanding of cosmic dust properties relies on a combination of astronomical observations, astrophysical modeling and laboratory studies of realistic analogs of cosmic dust being gas-phase molecules and/or solid grains. The COSmIC facility was developed at NASA Ames to study the evolution of cosmic carbon from circumstellar outflows to interstellar clouds to planetary atmospheres in the laboratory [1]. COSmIC stands for “Cosmic Simulation Chamber” and is dedicated to the study of neutral and ionized molecules and grain particles under the low temperature and density conditions that are required to simulate space environments. It integrates a variety of instruments that allow generating, processing, and monitoring simulated space conditions in the laboratory. It is composed of a Pulsed Discharge Nozzle (PDN) expansion that generates a plasma in a free supersonic jet expansion, coupled to high-sensitivity, complementary in situ diagnostic tools used for the detection and characterization of the species present in the expansion: Cavity Ring Down Spectroscopy (CRDS) and fluorescence spectroscopy systems for photonic detection and an orthogonal Reflectron Time-Of-Flight Mass Spectrometer (oReTOF-MS) for mass detection. Recent advances achieved using COSmIC’s laboratory data in synergy with observational data will be presented. These results include the formation of dust grains and aerosols from gas-phase molecular precursors in environments as varied as circumstellar outflows of late AGB stars [2, 3] and planetary atmospheres [4] and the evolution of our understanding of the diffuse interstellar bands (DIBs) with applications to the ESO Diffuse Interstellar Bands Large Exploration Survey (EDIBLES [5, 6]). Plans for future laboratory developments and techniques to study the evolution of cosmic carbon molecules and grains (including NIR-MIR CRDS, laser induced fluorescence (LIF) and incandescence (LII)) will also be addressed as well as their astronomical applications.

Planetary↗

Improving Adhesive Bondline Time of Flight Predictions During Autoclave Cure Utilizing Machine Learning

Composite materials are increasingly being used in aerospace applications due to their superior strength-to-weight ratio compared to commonly used metals. A current limitation to widespread adoption is the certification of adhesively bonded joints. One approach to improving adhesive bonding in composites is accurately measuring the thickness of adhesive bondlines in composite laminates. Precise bondline thickness control is essential for aerospace applications where adhesive layer thickness directly affects joint fracture properties and structural performance. This study focused on implementing machine learning techniques to determine the ultrasonic time of flight (directly correlated to thickness) in adhesive bondlines throughout autoclave cure cycles. A high-temperature (use up to 180°C) ultrasonic scanning system was deployed in an autoclave to provide time of flight data through composite panels. Three experiments were conducted on the curing of 305 mm × 305 mm unidirectional composite panels. In the first experiment, a piecewise function was fit for the temperature correction factor to account for changing autoclave temperatures. Due to deficiencies in the first calibration experiment, a second experiment was run, and the results were used to train a machine learning model. The revised experiment, in combination with the machine learning model, significantly increased the accuracy of the bondline time of flight predictions (~14% error reduced to <1%). Data was processed using the Regression Learner Application in MATLAB®, with a Support Vector Machine selected for the model. The result was a machine learning algorithm capable of reliably quantifying ultrasonic time of flight through adhesive bondlines. The third experiment provided independent test data for the machine learning model, demonstrating that the model produces accurate predictions from data beyond its training set.

Machine Learning↗

Sensor for Monitoring Nanodevice-Fabrication Plasmas

The term plasma process diagnostics (PPD) refers to a spectroscopic technique and sensing hardware that have been proposed for monitoring plasma processes used to fabricate electronic devices that feature sizes as small as several nanometers. Nanometer dimensions are characteristic of the quantum level of miniaturization, where single impurity atoms or molecules can drastically change the local properties of the nanostructures. Such changes may be purposely used in nanoscale design but may also be extremely damaging or cause improper operation of the fabricated devices. Determination of temperature and densities of reactants near the developing features is important, since the structural synthesis is affected by characteristics of the local microenvironment. Consequently, sensors capable of nonintrusive monitoring with high sensitivity and high resolution are essential for real-time atomistic control of reaction kinetics and minimizing trace contamination in plasma processes used to fabricate electronic nanodevices. Such process-monitoring sensors are required to be compact, multiparametric, and immune to the harsh environments of processing plasmas. PPD is intended to satisfy these requirements. The specific technique used to implement plasma diagnostics with a PPD sensor would be an advanced version of continuous-wave cavity-ringdown spectroscopy (CW-CRDS) capable of profiling spectral line broadenings in order to derive both Doppler and Stark components. CRDS is based on measurements of the rate of absorption of laser light in an optical resonator. The ultimate sensitivity results from a very long absorption path length within the cavity and immunity to variations in incident laser intensity. The proposed version of this technique would involve the use of multiplexing tunable laser diodes and an actively modulated high-reflectivity optical resonator, thus offering a synergistic combination of simplicity, compactness, high sensitivity, and high resolution. The multiplexing capabilities of diode lasers could be utilized to make the PPD sensor a single, simple, compact, and inexpensive tool for the acquisition of multiparametric data. A PPD sensor would be capable of continuous measurement of such physical parameters as gas temperature, gas velocity, electron number density, and absolute densities of reacting chemical species. A laser beam can be easily adjusted to analyze the immediate vicinity of the growing nanostructures (or features etched down) in real time. The absorption enhancement in an optical cavity would afford the sensitivity needed for measurement of the temperature and densities of species at concentrations significantly lower than measurable by other nonintrusive techniques. It is anticipated that fully developed PPD sensors would enable simultaneous measurement of local temperature and determination of plasma species responsible for the synthesis and functionalization of nanodevices. These sensors would also enable tracking the pathways and origins of damaging contaminants, thereby providing feedback for adjustment of processes to optimize them and reduce contamination. The PPD sensors should also be useful for optimization of conventional microelectronics manufacturing plasma processes. Going beyond plasma processes for fabrication of electronic devices, PPD sensors could be used for monitoring of atoms, molecules, ions, radicals, clusters, and particles in a variety of other settings, including outer space. Because of their high sensitivity, such sensors could also prove useful for detecting traces of illegal drugs and explosives.

Bolshakov, Alexander↗

Launch Commit Criteria Monitoring Agent

The Spaceport Processing Systems Branch at NASA Kennedy Space Center has developed and deployed a software agent to monitor the Space Shuttle's ground processing telemetry stream. The application, the Launch Commit Criteria Monitoring Agent, increases situational awareness for system and hardware engineers during Shuttle launch countdown. The agent provides autonomous monitoring of the telemetry stream, automatically alerts system engineers when predefined criteria have been met, identifies limit warnings and violations of launch commit criteria, aids Shuttle engineers through troubleshooting procedures, and provides additional insight to verify appropriate troubleshooting of problems by contractors. The agent has successfully detected launch commit criteria warnings and violations on a simulated playback data stream. Efficiency and safety are improved through increased automation.

Semmel, Glenn S.↗

Space Shuttle solid rocket motor exposure monitoring

During the processing of the Space Shuttle Solid Rocket Booster (SRB), segments at the Kennedy Space Center, an odor was detected around the solid propellant. An Industrial Hygiene survey was conducted to determine the chemical identity of the SRB offgassing constituents. Air samples were collected inside a forward SRB segment and analyzed to determine chemical composition. Specific chemical analysis for suspected offgassing constituents of the propellant indicated ammonia to be present. A gas chromatograph mass spectroscopy (GC/MS) analysis of the air samples detected numerous high molecular weight hydrocarbons.

Brown, S. W.↗

Optics-Only Calibration of a Neural-Net Based Optical NDE Method for Structural Health Monitoring

A calibration process is presented that uses optical measurements alone to calibrate a neural-net based NDE method. The method itself detects small changes in the vibration mode shapes of structures. The optics-only calibration process confirms previous work that the sensitivity to vibration-amplitude changes can be as small as 10 nanometers. A more practical value in an NDE service laboratory is shown to be 50 nanometers. Both model-generated and experimental calibrations are demonstrated using two implementations of the calibration technique. The implementations are based on previously published demonstrations of the NDE method and an alternative calibration procedure that depends on comparing neural-net and point sensor measurements. The optics-only calibration method, unlike the alternative method, does not require modifications of the structure being tested or the creation of calibration objects. The calibration process can be used to test improvements in the NDE process and to develop a vibration-mode-independence of damagedetection sensitivity. The calibration effort was intended to support NASA s objective to promote safety in the operations of ground test facilities or aviation safety, in general, by allowing the detection of the gradual onset of structural changes and damage.

Decker, Arthur J.↗

Reshaping the Quantum Arrow of Time

While the microscopic laws of physics are often symmetric under time reversal, most natural processes that we observe are not. The emergent asymmetry between typical and time-reversed processes is referred to as the arrow of time. In quantum physics, an arrow of time emerges when a sequence of measurements is performed on a system. We introduce quantum control tools that can yield dynamics more consistent with time flowing backward than forward. The control tools are based on the explicit construction of a Hamiltonian that can replicate the stochastic trajectories of a monitored quantum system. Such a Hamiltonian can reverse the effect of monitoring and, via a feedback process, generate trajectories consistent with a reversed arrow of time. It can also be used to simulate the backward-in-time dynamics of an open quantum system. Finally, we design a feedback-driven continuous measurement engine powered by the energy pumped into the system by the monitoring process. We show that the engine can operate under experimentally realizable conditions with feedback delay and finite-efficiency measurements.

Entropy production↗

Signal processing methodologies for an acoustic fetal heart rate monitor

Research and development is presented of real time signal processing methodologies for the detection of fetal heart tones within a noise-contaminated signal from a passive acoustic sensor. A linear predictor algorithm is utilized for detection of the heart tone event and additional processing derives heart rate. The linear predictor is adaptively 'trained' in a least mean square error sense on generic fetal heart tones recorded from patients. A real time monitor system is described which outputs to a strip chart recorder for plotting the time history of the fetal heart rate. The system is validated in the context of the fetal nonstress test. Comparisons are made with ultrasonic nonstress tests on a series of patients. Comparative data provides favorable indications of the feasibility of the acoustic monitor for clinical use.

Pretlow, Robert A., III↗

Development of an ERT‐Based Framework for Bentonite Buffers Monitoring From Laboratory Tests: 1. Characterizing Thermal–Hydrological–Mechanical Processes

Abstract Bentonite clay is widely used in engineered barrier systems for the permanent disposal of high‐level radioactive waste due to its low permeability, high swelling capacity, and thermal stability. However, the complex thermal‐hydrological‐mechanical (THM) processes induced by heating from decaying radioactive waste and hydration from surrounding rock can lead to heterogeneous changes that are difficult to measure and predict. This study develops an Electrical Resistivity Tomography (ERT)‐based framework for monitoring THM processes, progressing from sample‐scale to bench‐scale tests, to inform field‐scale applications. Sample‐scale tests analyzed small bentonite samples under controlled variations in water content, temperature, and porosity to establish fundamental resistivity relationships. Bench‐scale tests involved larger bentonite columns subjected to heating (up to 200°C) and hydration under controlled pressure, simulating repository conditions. ERT measurements, complemented by X‐ray CT imaging, temperature monitoring, and tracing sensors, revealed coupled THM processes, such as hydration‐induced compression, swelling, and thermal gradients, leading to complex resistivity patterns. The results demonstrate the potential of ERT for capturing THM‐induced resistivity changes, though challenges remain in upscaling and quantitative analysis. This study evaluates laboratory test capabilities and proposes future improvements for understanding THM‐induced resistivity responses. A conceptual framework for ERT implementation in field‐scale monitoring is presented, synthesizing findings from both scales and exploring how ERT data can inform long‐term modeling and reduce prediction uncertainties. Overall, this ERT‐based framework offers a robust method for monitoring bentonite buffers, aiding in early issue detection and supporting the safe long‐term disposal of radioactive waste in geological repositories, while highlighting the need for future development. Plain Language Summary Bentonite clay is crucial in engineered barrier systems (EBS) for containing high‐level radioactive waste due to its ability to absorb water, swell, seal and remain stable under high temperatures. When bentonite absorbs water and heats up from radioactive decay, it experiences complex changes in its physical and mechanical properties. Understanding these changes is important for ensuring the long‐term safety and effectiveness of EBS. This study used Electrical Resistivity Tomography (ERT), a non‐invasive method that measures electrical conductivity to monitor these changes during laboratory experiments. The ERT data revealed significant variations in resistivity corresponding to changes in water content, temperature, and density, providing detailed spatial and temporal insights into the behavior of bentonite. These findings enhance our ability to predict the long‐term performance of bentonite barriers, ensuring the safe containment of radioactive waste. By improving our understanding of bentonite's behavior, this research supports the development of more reliable and effective barrier systems for radioactive waste disposal, protecting the environment and public health. Key Points ERT monitoring was employed to capture resistivity changes in bentonite during controlled heating and hydration experiments, providing insights into THM processes ERT data reveal significant resistivity changes correlated with water content, temperature, and mechanical effects, enhancing the understanding of THM dynamics in bentonite This study explores the potential of the framework for application in field‐scale EBS monitoring, emphasizing the need for integrating additional geophysical methods for comprehensive subsurface imaging

Chen, Hang↗

Non-Traditional Displays for Mission Monitoring

Advances in automation capability and reliability have changed the role of humans from operating and controlling processes to simply monitoring them for anomalies. However, humans are traditionally bad monitors of highly reliable systems over time. Thus, the human is assigned a task for which he is ill equipped. We believe that this has led to the dominance of human error in process control activities such as operating transportation systems (aircraft and trains), monitoring patient health in the medical industry, and controlling plant operations. Research has shown, though, that an automated monitor can assist humans in recognizing and dealing with failures. One possible solution to this predicament is to use a polar-star display that will show deviations from normal states based on parameters that are most indicative of mission health.

Trujillo, Anna C.↗

The meteorological monitoring system for the Kennedy Space Center/Cape Canaveral Air Station

The Kennedy Space Center (KSC) and Cape Canaveral Air Station (CCAS) are involved in many weather-sensitive operations. Manned and unmanned vehicle launches, which occur several times each year, are obvious example of operations whose success and safety are dependent upon favorable meteorological conditions. Other operations involving NASA, Air Force, and contractor personnel, including daily operations to maintain facilities, refurbish launch structures, prepare vehicles for launch, and handle hazardous materials, are less publicized but are no less weather-sensitive. The Meteorological Monitoring System (MMS) is a computer network which acquires, processes, disseminates, and monitors near real-time and forecast meteorological information to assist operational personnel and weather forecasters with the task of minimizing the risk to personnel, materials, and the surrounding population. CLIPS has been integrated into the MMS to provide quality control analysis and data monitoring. This paper describes aspects of the MMS relevant to CLIPS including requirements, actual implementation details, and results of performance testing.

Dianic, Allan V.↗