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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.

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33 records · Page 2

Modeling of delamination damage evolution in laminated composites subjected to low velocity impact

This study examines the delamination evolution, under quasi-static conditions, of laminated polymeric composites with mechanically nonlinear resin rich interfaces. The constitutive behavior of the interface is represented by two models developed by Needleman and Tvegaard. These models assumed that the interfacial tractions, a function of only the interfacial displacement, will behave similarly to the interatomic forces generated during the interatomic seperation. The interface material's parameters control the load at which the delamination growth initiates and the final delamination size. A wide range of damage accumulation responses have been obtained by varying the model parameters. These results show that Tvergaard's model has been found to be better suited of the two models in predicting damage evolution for the configurations examined.

Lo, David C.↗

A Maskless Gamma-Ray All-Sky Imager: BATSE/CGRO

The non-collimated detectors of BATSE (Burst And Transient Source Experiment) on the Compton Gamma Ray Observatory (CGRO) can be used as a high sensitivity hard X-ray and low energy gamma-ray all-sky imager in the energy range between 20 keV and 2 MeV. The fluxes from sources in the sky are modulated as the spacecraft orbits the Earth. The CGRO orbital precession further allows sampling of sky in strips corresponding to the limb of the earth at any given time. The modulation data are transformed into images by various reconstruction methods. High sensitivity images of location accuracy of about 0.1 deg and source seperation of about 1 deg are obtained.

Zhang, S. N.↗

A simple protocol for coordinating planning agents

This paper introduces a simple decentralized protocol that enables seperate planners to coordinate shared tasks and resolve conflicts over shared and private resources.

multiple agents coordination planning scheduling M↗

Design, tolerancing and alignment of pushbroom imaging spectrometers for high response uniformity

We present a design and tolerancing approach that permits the achievement of a high degree of spatial and spectral uniformity of response from a pushbroom imaging spectrometer. Such uniformity of response is crucial for the extraction of accurate spectroscopic information from remotely sensed data. The spectrometer system example comprises two independent spectrometer modules covering the 400-2500 nm range, seperated through a dichroic mirror.

imaging spectrometry optical design tolerancing↗

Experimental Results for Temporally Overlapping Pulses from Quantel EverGreen 200 Laser

This report will detail the experimental results and observations obtained while investigating the feasibility of temporally overlapping the two laser pulses from a Quantel EverGreen 200 Laser. This laser was specifically designed for Particle Imaging Velocimetry (PIV) applications and operate by emitting two 532 nm laser pulses that are seperated by an adjustable finite time (typically on the order of ten to hundreds of microseconds). However, the use of this model laser has found recent application for Pressure Sensitive Paint (PSP) testing, especially for rotorcraft research. For this testing, it is desired to only use one laser pulse. While this is easily done by only firing one of the laser heads, more excitation energy could conceivably be had if both laser heads are fired with zero pulse separation. In addition, recently large field-of-view PIV measurements have become possible and need ever increasing laser power to illuminate the larger areas. For this work, two different methods of timing the laser are investigated using both a traditional power meter to monitor laser power as well as a fast photodiode to determine pulse separation. The results are presented here as well as some simple implications for PIV experiments using these methods.

Watkins, A. Neal↗

Cassini / Huygens Science Instruments

The Cassini spacecraft will bring eighteen scientific instruments to Saturn. After it is inserted into Saturn orbit, it will seperate into a Saturn Orbiter and an atmospheric probe, called Huygens, which will descend to the surface of Titan.

Cassini↗

Physics-Based Machine Learning Methods for U-235 Forensics Signatures

Signatures of low-intensity U-235 sources have been recently studied by utilizing a variety of machine learning (ML) classifiers using features derived from gamma spectral measurements collectedunder structured campaigns. Several ML classifiers, such as ensemble of tress and classification trees, revealed misleadingly-optimistic training error due to over-fitting, and furthermore,their performance is not directly relatable to the physical properties due to their data-driven, opaque designs. We present a regression-based ML method that first estimates the inverse distanceto the source and then utilizes a threshold to infer its presence, by representing the background as a source located at an infinite distance. For the inverse distance estimation, we study the ensembleof trees and Gaussian process regression methods, and a hyper parameter auto-tuning and selection method that employs five regression estimators. These methods avoid the over-fittingobserved in several ML classifiers, while providing the classification error nearly comparable to them based on independent test data. Their error is directly related to estimates of the inversephysical distance to source, and the precision of error determines the seperability property that determines the false alarm and missed detection rates. The property of monotonic decrease of thesource strength with increasing detector distance combined with Poisson distribution of measurements is utilized to analytically validate these methods by deriving the generalization equations ofunderlying regression methods.

Rao, Nageswara↗

Physics-Based Machine Learning Methods for U-235 Forensics Signatures

Signatures of low-intensity U-235 sources have been recently studied by utilizing a variety of machine learning (ML) classifiers using features derived from gamma spectral measurements collected under structured campaigns. Several ML classifiers, such as ensemble of tress and classification trees, revealed misleadingly-optimistic training error due to over-fitting, and furthermore, their performance is not directly relatable to the physical properties due to their data-driven, opaque designs. We present a regression-based ML method that first estimates the inverse distance to the source and then utilizes a threshold to infer its presence, by representing the background as a source located at an infinite distance. For the inverse distance estimation, we study the ensemble of trees and Gaussian process regression methods, and a hyper parameter auto-tuning and selection method that employs five regression estimators. These methods avoid the over-fitting observed in several ML classifiers, while providing the classification error nearly comparable to them based on independent test data. Their error is directly related to estimates of the inverse physical distance to source, and the precision of error determines the seperability property that determines the false alarm and missed detection rates. The property of monotonic decrease of the source strength with increasing detector distance combined with Poisson distribution of measurements is utilized to analytically validate these methods by deriving the generalization equations of underlying regression methods.

Rao, Nageswara↗

Beartooth - Digital Twin Framework Enabling AI

Digital twin was designed as a core part of this testbed. This presentation will discuss the digital twin framework that will enable AI for nuclear aqueous seperations.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Amine functionalized supported ionic liquid membranes (SILMs) for CO 2 /N 2 separation

Supported ionic liquid membranes (SILMs), containing aprotic N-heterocyclic anion ionic liquids (AHA ILs) in an inorganic inert support, exhibit CO 2 /N 2 permselectivity values as high as 640 at 35.0 °C and 0.03 bar CO 2 , which represents conditions similar to post-combustion carbon capture (PCCC) from a natural gas power plant. A Fickian model fit to the experimental data estimates CO 2 permeability at direct air capture (DAC) conditions of 10,400 barrer and a CO 2 /N 2 permselectivity of 4000 for the best performing IL, triethyl(octyl)phosphonium 4-bromopyrazolide ([P 2228 ][4-BrPyra]). The most important criterion for high selectivity is a large equilibrium constant for binding between the IL and CO 2 , which results in high CO 2 solubility. ILs with smaller molar volumes and with no fluoroalkyl chains enhance N 2 rejection. As a result, low viscosity and high IL molar density also enhance CO 2 /N 2 permselectivity and CO 2 permeance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Controlling Catalyst–Semiconductor Contacts: Interfacial Charge Separation in p-InP Photocathodes

Charge-carrier-selective interfaces between electrocatalyst particles and semiconductor light absorbers are critical for solar photochemistry but controlling their properties is challenging. Using thin films and nanoparticle arrays of Pt hydrogen-evolution catalysts on p-InP (a high-performance photocathode material), along with macroscopic and nanoscopic electrical and chemical analysis, we show how hydrogen alloying, the pinch-off effect for nanoscale contacts, and the formation of a native surface oxides all play different roles in creating charge-carrier-selective junctions. As a result, the new insights can be broadly applied to photocathodes, photoanodes, and overall water-splitting systems to control charge-carrier selectivity and improve performance.

14 SOLAR ENERGY↗

Adaptive Trajectory Prediction Algorithm for Climbing Flights

Aircraft climb trajectories are difficult to predict, and large errors in these predictions reduce the potential operational benefits of some advanced features for NextGen. The algorithm described in this paper improves climb trajectory prediction accuracy by adjusting trajectory predictions based on observed track data. It utilizes rate-of-climb and airspeed measurements derived from position data to dynamically adjust the aircraft weight modeled for trajectory predictions. In simulations with weight uncertainty, the algorithm is able to adapt to within 3 percent of the actual gross weight within two minutes of the initial adaptation. The root-mean-square of altitude errors for five-minute predictions was reduced by 73 percent. Conflict detection performance also improved, with a 15 percent reduction in missed alerts and a 10 percent reduction in false alerts. In a simulation with climb speed capture intent and weight uncertainty, the algorithm improved climb trajectory prediction accuracy by up to 30 percent and conflict detection performance, reducing missed and false alerts by up to 10 percent.

Seperation Assurance↗

Investigating the Impacts of a Separation Standard for UAS Operations in Enroute and Transition Airspace

Unmanned aircraft systems will be required to equip with a detect and avoid system in order to satisfy the federal aviation regulations to remain well clear of other aircraft. To comply with regulations in today’s operations manned aircraft must “see and avoid” other aircraft and use subjective judgment to determine whether those aircraft are well clear. For a detect-and- avoid (DAA) system to satisfy the requirement to stay well clear, a quantitative definition of well clear needs to be defined and evaluated. Definitions for the boundary of well clear have been proposed by the Unmanned Aircraft System (UAS) Executive Committee Science and Research Panel (SaRP) and the Radio Technical Commission for Aeronautics (RTCA) Special Committee 228 on Detect and Avoid Systems. This study investigates the interoperability implications of UAS using proposed well clear definitions as a separation standard for conducting operations in the national airspace system. The first analysis in the study focuses on the effect of variations in well clear definition parameters on the rate of losses of well clear per flight hour. The second analysis considers three well clear definitions and presents the relative state conditions of intruder aircraft as they encroach upon the well clear boundary. The third analysis focuses on the definition of the alerting criteria needed to inform the UAS operator of a potential loss of well clear. All three analyses are conducted in a NAS-wide fast-time simulation environment using UAS aircraft models, proposed UAS missions, and historical air defense radar data to populate the background traffic operating under visual flight rules. The results from the three analyses presented in this study inform the safety case, requirements development, and the operational environment for the DAA minimum operational performance standards.

UAS Seperation Standard↗

High Pressure DME-Driven Fractional Crystallizations

Rare Earth Elements (REEs), include the 15 lanthanides plus yttrium and scandium and are crucial for various technologies and applications. Their low concentrations in the earth's crust require alternative sources. This study explores antisolvent fractional crystallization (FC) using dimethyl ether (DME) under high pressures to extract REEs from secondary sources such as mining waste, coal byproducts, and e-waste. DME's properties, including its solubility in water, small molecular size, and high vapor pressure, make it an effective antisolvent that can be easily recovered and reused. The method involves pressurizing DME to 1000-2000 psi in a reaction chamber with the test solution, followed by sample collection and analysis using ICP-MS and ICP-OES. This approach aims to address the limitations of current extraction methods, such as high energy consumption, chemical usage, and waste production, offering a potentially more efficient and sustainable solution for REE extraction.

37 - INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL C↗