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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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At least 1,747 records · Page 97

Radiation response of inorganic scintillators: Insights from Monte Carlo simulations

The spatial and temporal scales of hot particle thermalization in inorganic scintillators are critical factors determining the extent of second- and third-order nonlinear quenching in regions with high densities of electron-hole pairs, which, in turn, leads to the light yield nonproportionality observed, to some degree, for all inorganic scintillators. Therefore, kinetic Monte Carlo simulations were performed to calculate the distances traveled by hot electrons and holes as well as the time required for the particles to reach thermal energy following γ-ray irradiation. CsI, a common scintillator from the alkali halide class of materials, was used as a model system. Two models of quasi-particle dispersion were evaluated, namely, the effective mass approximation model and a model that relied on the group velocities of electrons and holes determined from band structure calculations. Both models predicted rapid electron-hole pair recombination over short distances (a few nanometers) as well as a significant extent of charge separation between electrons and holes that did not recombine and reached thermal energy. However, the effective mass approximation model predicted much longer electron thermalization distances and times than the group velocity model. Comparison with limited experimental data suggested that the group velocity model provided more accurate predictions. Nonetheless, both models indicated that hole thermalization is faster than electron thermalization and thus is likely to be an important factor determining the extent of third-order nonlinear quenching in high-density regions. The merits of different models of quasi-particle dispersion are also discussed.

Prange, Micah P.↗

Search for Higgs boson pair production in the $\mathrm{b}\overline{\mathrm{b}}\mathrm{WW}$ decay channel with two leptons in the final state using proton-proton collision data at $\sqrt{s}=13.6$ TeV

A search for Higgs boson pair production is presented, targeting final states where one Higgs boson decays to a bottom quark-antiquark pair and the other Higgs boson decays to two W bosons, both of which decay leptonically, to an electron or a muon, and a neutrino. For the first time, the search is conducted with proton-proton collision data from the LHC at $\sqrt{s}=13.6$ TeV, recorded with the CMS detector in 2022 and 2023 and corresponding to an integrated luminosity of 62 fb −1 . The results are consistent with the standard model predictions. An upper limit of 12.0 times the standard model prediction at 95% confidence level is set on the Higgs boson pair production cross section, with an expected limit of 18.5. The results are also used to constrain the strength of the trilinear self-coupling of the Higgs boson, as well as of the quartic coupling between two Higgs bosons and two vector bosons.

Hadron-Hadron Scattering↗

Thermodynamic and kinetic modeling of Mn-Ni-Si precipitates in low-Cu reactor pressure vessel steels

Formation of large volume fractions of Mn-Ni-Si precipitates (MNSPs) causes excess irradiation embrittlement of reactor pressure vessel (RPV) steels at high, extended-life fluences. Thus, a new and unique, semi-empirical cluster dynamics model was developed to study the evolution of MNSPs in low-Cu RPV steels. The model is based on CALPHAD thermodynamics and radiation enhanced diffusion kinetics. The thermodynamics dictates the compositional and temperature dependence of the free energy reductions that drive precipitation. The model treats both homogeneous and heterogeneous nucleation, where the latter occurs on cascade damage, like dislocation loops. The model has only four adjustable parameters that were fit to an atom probe tomography (APT) database. The model predictions are in semi-quantitative agreement with systematic Mn, Ni and Si composition variations in alloys characterized by APT, including a sensitivity to local tip-to-tip variations even in the same steel. The model predicts that heterogeneous nucleation plays a critical role in MNSP formation in lower alloy Ni contents. Single variable assessments of compositional effects show that Ni plays a dominant role, while even small variations in irradiation temperature can have a large effect on the MNSP evolution. Within typical RPV steel ranges, Mn and Si have smaller effects. Furthermore, the delayed but then rapid growth of MNSPs to large volume fractions at high fluence is well predicted by the model. For purposes of illustration, the effect of MNSPs on transition temperature shifts are presented based on well-established microstructure-property and property-property models.

36 MATERIALS SCIENCE↗

Identification Approach to Alleviate Effects of Unmeasured Heat Gains for MIMO Building Thermal Systems

It is important to have practical methods for constructing a good mathematical model for a building's thermal system for energy audits, retrofit analysis and advanced building controls, e.g. model predictive control. Identification approaches based on semi-physical model structures are popular in building science for those purposes. However conventional gray box identification approaches applied to thermal networks would fail when significant unmeasured heat gains present in estimation data. Although this situation is very common and practical, there has been little research to tackle this issue in building science. This paper presents an overall identification approach to alleviate influences of unmeasured disturbances, and hence to obtain improved gray-box building models. The approach was applied to an existing open space building and the performance is demonstrated.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Measurements of supersonic jet aircraft wakes in the stratosphere

Progress is reported in an experimental program consisting of making supersonic aircraft wakes visible in the stratosphere so that photographs can be taken which yield wake dimensions vs time, and so that aircraft equipped with instruments which measure key exhaust species can find and penetrate the wakes. The object is to provide verification of fluid dynamic and chemical models. Three available models are summarized, and the experimental methods used are described. The Lockheed model predictions correspond in general most closely to experimental wake cross-sectional aerea. NO data are in reasonable agreement with NO predictions, but chemical models are relatively undeveloped, and additional measurements of exhaust products are needed before verification of chemical models becomes possible. However, the overall feasibility of wake visualization for model verification is substantiated. It is emphasized that significant model differences exist that must be resolved before reliable predictions can be made in the wake regimes studied.

Farlow, N. H.↗

Accelerated test modeling

Cycle life regression model, cycle life prediction model, and acceleration factors are discussed. A method was presented to: (1) select a mathematical model; (2) determine model coefficients using accelerated test data; (3) test model fit of the accelerated test data; and (4) predict normal packs.

Schwartz, D.↗

Reduced Pressure Cabin Testing of the Orion Atmosphere Revitalization Technology

An amine-based carbon dioxide (CO2) and water vapor sorbent in pressure-swing regenerable beds has been developed by Hamilton Sundstrand and baselined for the Atmosphere Revitalization System for moderate duration missions of the Orion Multipurpose Crew Vehicle. In previous years at this conference, reports were presented on extensive Johnson Space Center testing of this technology in a sea-level pressure environment with simulated and actual human metabolic loads in both open and closed-loop configurations. In 2011, the technology was tested in an open cabin-loop configuration at ambient and two sub-ambient pressures to compare the performance of the system to the results of previous tests at ambient pressure. The testing used a human metabolic simulator with a different type of water vapor generation than previously used, which added some unique challenges in the data analysis. This paper summarizes the results of: baseline and some matrix testing at all three cabin pressures, increased vacuum regeneration line pressure with a high metabolic load, a set of tests studying CO2 and water vapor co-adsorption effects relative to model-predicted performance, and validation tests of flight program computer model predictions with specific operating conditions.

Button, Amy↗

Reduced Pressure Cabin Testing of the Orion Atmosphere Revitalization Technology

An amine-based carbon dioxide (CO2) and water vapor sorbent in pressure-swing regenerable beds has been developed by Hamilton Sundstrand and baselined for the Atmosphere Revitalization System for moderate duration missions of the Orion Multipurpose Crew Vehicle. In previous years at this conference, reports were presented on extensive Johnson Space Center testing of this technology in a sea-level pressure environment with simulated and actual human metabolic loads in both open and closed-loop configurations. In 2011, the technology was tested in an open cabin-loop configuration at ambient and two sub-ambient pressures to compare the performance of the system to the results of previous tests at ambient pressure. The testing used a human metabolic simulator with a different type of water vapor generation than previously used, which added some unique challenges in the data analysis. This paper summarizes the results of: baseline and some matrix testing at all three cabin pressures, increased vacuum regeneration line pressure with a high metabolic load, a set of tests studying CO2 and water vapor co-adsorption effects relative to model-predicted performance, and validation tests of flight program computer model predictions with specific operating conditions.

Button, Amy↗

Reduced Pressure Cabin Testing of the Orion Atmosphere Revitalization Technology

An amine-based carbon dioxide (CO2) and water vapor sorbent in pressure-swing regenerable beds has been developed by United Technologies Corp. Aerospace Systems (UTAS, formerly Hamilton Sundstrand) and baselined for the Atmosphere Revitalization System for moderate duration missions of the Orion Multipurpose Crew Vehicle (MPCV). In previous years at this conference, reports were presented on extensive Johnson Space Center testing of this technology in a sea-level pressure environment with simulated and actual human metabolic loads in both open and closed-loop configurations. In 2011, the technology was tested in an open cabin-loop configuration at ambient and two sub-ambient pressures to compare the performance of the system to the results of previous tests at ambient pressure. The testing used a human metabolic simulator with a different type of water vapor generation than previously used, which added some unique challenges in the data analysis. This paper summarizes the results of: baseline and some matrix testing at all three cabin pressures, increased vacuum regeneration line pressure testing with a high metabolic load, a set of tests studying CO2 and water vapor co-adsorption effects relative to model-predicted performance, and validation tests of flight project computer model predictions with specific operating conditions.

Button, Amy B.↗

"Traffic Control via Connected and Automated Vehicles: An Open-Road Field Experiment with 100 CAVs"

The CIRCLES project aims to reduce instabilities in traffic flow, which are naturally occurring phenomena due to human driving behavior. These "phantom jams" or "stop-and-go waves,"are a significant source of wasted energy. Toward this goal, the CIRCLES project designed a control system referred to as the MegaController by the CIRCLES team, that could be deployed in real traffic. Our field experiment leveraged a heterogeneous fleet of 100 longitudinally-controlled vehicles as Lagrangian traffic actuators, each of which ran a controller with the architecture described in this paper. The MegaController is a hierarchical control architecture, which consists of two main layers. The upper layer is called Speed Planner, and is a centralized optimal control algorithm. It assigns speed targets to the vehicles, conveyed through the LTE cellular network. The lower layer is a control layer, running on each vehicle. It performs local actuation by overriding the stock adaptive cruise controller, using the stock on-board sensors. The Speed Planner ingests live data feeds provided by third parties, as well as data from our own control vehicles, and uses both to perform the speed assignment. The architecture of the speed planner allows for modular use of standard control techniques, such as optimal control, model predictive control, kernel methods and others, including Deep RL, model predictive control and explicit controllers. Depending on the vehicle architecture, all onboard sensing data can be accessed by the local controllers, or only some. Control inputs vary across different automakers, with inputs ranging from torque or acceleration requests for some cars, and electronic selection of ACC set points in others. The proposed architecture allows for the combination of all possible settings proposed above. Most configurations were tested throughout the ramp up to the MegaVandertest.

Lee, Jonathan↗

Effects of natural zeolites on field-scale geologic noble gas transport

Improving predictive models for noble gas transport through natural materials at the field-scale is an essential component of improving US nuclear monitoring capabilities. Several field-scale experiments with a gas transport component have been conducted at the Nevada National Security Site (Non-Proliferation Experiment, Underground Nuclear Explosion Signatures Experiment). However, the models associated with these experiments have not treated zeolite minerals as gas adsorbing phases. This is significant as zeolites are a common alteration mineral with a high abundance at these field sites and are shown here to significantly fractionate noble gases during field-scale transport. This fractionation and associated retardation can complicate gas transport predictions by reducing the signal-to-noise ratio to the detector (e.g. mass spectrometers or radiation detectors) enough to mask the signal or make the data difficult to interpret. Omitting adsorption-related retardation data of noble gases in predictive gas transport models therefore results in systematic errors in model predictions where zeolites are present.Herein is presented noble gas adsorption data collected on zeolitized and non-zeolitized tuff. Experimental results were obtained using a unique piezometric adsorption system designed and built for this study. Data collected were then related to pure-phase mineral analyses conducted on clinoptilolite, mordenite, and quartz. These results quantify the adsorption capacity of materials present in field-scale systems, enabling the modeling of low-permeability rocks as significant sorption reservoirs vital to bulk transport predictions.

58 GEOSCIENCES↗

Ellicott City Disasters II - Building a Real-Time Predictive Flood Model for Improving Early Warning Systems in Ellicott City, Maryland

As flood events in the United States grow in frequency and intensity, the uses of applied remote sensing analyses are increasingly necessary for effective flood monitoring and warning systems. The NASA DEVELOP Ellicott City Disasters III project investigated the use of machine learning for applications in flood risk detection to support the improvement of early warning systems in Ellicott City, Maryland. To strengthen the efforts of the Howard County Office of Emergency Management (OEM) in building a more robust flood monitoring system, this term built on the predictive capability of the long-short term memory (LSTM) model created by the second term of this DEVELOP project to create a Sequentially Trained Real-time EstimAted Model (STREAM). Enhancements to the model included the integration of both real-time and predicted weather products from the National Weather Service to increase predictive capacity. These weather products were supplemented by stream gauge data from the OEM as well as real-time radar products. The resultant flood risk model was trained to evaluate input variables and predict stage height in Ellicott City in real time. The model, upgraded to predict stage height up to 8 hours in advance, was incorporated into an online dashboard in a user-friendly interface. The project demonstrated the potential for integration of open data and NASA Earth observations into a flood risk forecasting tool capable of informing real-time decision-making.

Erika Munshi↗

Using Direct Numerical Simulation of Pore-Level Events to Improve Pore-Network Models for Prediction of Residual Trapping of CO2

Direct numerical simulation and pore-network modeling are common approaches to study the physics of two-phase flow through natural rocks. For assessment of the long-term performance of geological sequestration of CO 2 , it is important to model the full drainage-imbibition cycle to provide an accurate estimate of the trapped CO 2 . While direct numerical simulation using pore geometry from micro-CT rock images accurately models two-phase flow physics, it is computationally prohibitive for large rock volumes. On the other hand, pore-network modeling on networks extracted from micro-CT rock images is computationally efficient but utilizes simplified physics in idealized geometric pore elements. This study uses the lattice-Boltzmann method for direct numerical simulation of CO 2 -brine flow in idealized pore elements to develop a new set of pore-level flow models for the pore-body filling and snap-off events in pore-network modeling of imbibition. Lattice-Boltzmann simulations are conducted on typical idealized pore-network configurations, and the interface evolution and local capillary pressure are evaluated to develop modified equations of local threshold capillary pressure of pore elements as a function of shape factor and other geometrical parameters. The modified equations are then incorporated into a quasi-static pore-network flow solver. The modified model is applied on extracted pore-network of sandstone samples, and saturation of residual trapped CO 2 is computed for a drainage-imbibition cycle. The modified model yields different statistics of pore-level events compared with the original model; in particular, the occurrence of snap-off in pore-throats is reduced resulting in a more frontal displacement pattern along the main injection direction. Compared to the original model, the modified model is in closer agreement with the residual trapped CO 2 obtained from core flow experiments and direct numerical simulation.

Kohanpur, Amir H.↗

A model for prediction of ride quality in a multifactor environment

Recently a ride quality comfort model has been proposed which accounts for the effect of both multifrequency and multiaxes vibratory inputs, as well as nonvibratory inputs such as noise, on human comfort response. The proposed NASA ride quality model is described in general terms and selected results of several experimental investigations are presented that have contributed to the development of the model and to a more comprehensive understanding of human comfort response to vibration. Human subjective response to vertical vibration, combined vertical-lateral vibrations, and roll vibrations are discussed, and a set of vertical discomfort curves is presented.

Leatherwood, J. D.↗

The modeling and prediction of multiple jet VTOL aircraft flow fields in ground effect

An engineering methodology based on an empirical data base and analytical fluid dynamic models was developed for the prediction of propulsive lift system induced aerodynamic effects for multiple lift jet VTOL aircraft operating in the hover mode in and out of ground effect. The effects of aircraft geometry, aircraft orientation (pitch, roll) as well as height above ground are considered. Lift jet vector and splay directions fit the airframe, lift jet exit flow conditions, and both axisymmetric and rectangular nozzle exit geometry are also accommodated. The induced suckdown flows are computed from the potential flowfield induced by the turbulent entrainment of both the free jets and wall jets in ground effect and from the free jets alone out of ground effect. The methodology emphasized geometric considerations, computation of stagnation lines and fountain upwash inclination, fountain upwash formation and development, and fountain impingement on the airframe.

Kotansky, D. R.↗

Response Surface Energy Modeling of an Electric Vehicle over a Reduced Composite Drive Cycle

Response surface methodology (RSM) techniques were applied to develop a predictive model of electric vehicle (EV) energy consumption over the Environmental Protection Agency's (EPA) standardized drive cycles. The model is based on measurements from a synthetic composite drive cycle. The synthetic drive cycle is a minimized statistical composite of the standardized urban (UDDS), highway (HWFET), and US06 cycles. The composite synthetic drive cycle is 20 minutes in length thereby reducing testing time of the three standard EPA cycles by over 55%. Vehicle speed and acceleration were used as model inputs for a third order least squared regression model predicting vehicle battery power output as a function of the drive cycle. The approach reduced three cycles and 46 minutes of drive time to a single test of 20 minutes. Application of response surface modeling to the synthetic drive cycle is shown to predict energy consumption of the three EPA cycles within 2.6% of the actual measured values. Additionally, the response model may be used to predict energy consumption of any cycle within the speed/acceleration envelope of the synthetic cycle. This technique results in reducing test time, which additionally provides a model that may be used to expand the analysis and understanding of the vehicle under consideration.

33 ADVANCED PROPULSION SYSTEMS↗