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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 523 records · Page 29

A BLIND METHOD TO DETREND INSTRUMENTAL SYSTEMATICS IN EXOPLANETARY LIGHT CURVES

The study of the atmospheres of transiting exoplanets requires a photometric precision, and repeatability, of one part in ∼10{sup 4}. This is beyond the original calibration plans of current observatories, hence the necessity to disentangle the instrumental systematics from the astrophysical signals in raw data sets. Most methods used in the literature are based on an approximate instrument model. The choice of parameters of the model and their functional forms can sometimes be subjective, causing controversies in the literature. Recently, Morello et al. (2014, 2015) have developed a non-parametric detrending method that gave coherent and repeatable results when applied to Spitzer/IRAC data sets that were debated in the literature. Said method is based on independent component analysis (ICA) of individual pixel time-series, hereafter “pixel-ICA”. The main purpose of this paper is to investigate the limits and advantages of pixel-ICA on a series of simulated data sets with different instrument properties, and a range of jitter timescales and shapes, non-stationarity, sudden change points, etc. The performances of pixel-ICA are compared against the ones of other methods, in particular polynomial centroid division, and pixel-level decorrelation method. We find that in simulated cases pixel-ICA performs as well or better than other methods, and it also guarantees a higher degree of objectivity, because of its purely statistical foundation with no prior information on the instrument systematics. The results of this paper, together with previous analyses of Spitzer/IRAC data sets, suggest that photometric precision and repeatability of one part in 10{sup 4} can be achieved with current infrared space instruments.

79 ASTRONOMY AND ASTROPHYSICS↗

Acoustics Research of Propulsion Systems

The liftoff phase induces some of the highest acoustic loading over a broad frequency for a launch vehicle. These external acoustic environments are used in the prediction of the internal vibration responses of the vehicle and components. Thus, predicting these liftoff acoustic environments is critical to the design requirements of any launch vehicle but there are challenges. Present liftoff vehicle acoustic environment prediction methods utilize stationary data from previously conducted hold-down tests; i.e. static firings conducted in the 1960's, to generate 1/3 octave band Sound Pressure Level (SPL) spectra. These data sets are used to predict the liftoff acoustic environments for launch vehicles. To facilitate the accuracy and quality of acoustic loading, predictions at liftoff for future launch vehicles such as the Space Launch System (SLS), non-stationary flight data from the Ares I-X were processed in PC-Signal in two forms which included a simulated hold-down phase and the entire launch phase. In conjunction, the Prediction of Acoustic Vehicle Environments (PAVE) program was developed in MATLAB to allow for efficient predictions of sound pressure levels (SPLs) as a function of station number along the vehicle using semiempirical methods. This consisted, initially, of generating the Dimensionless Spectrum Function (DSF) and Dimensionless Source Location (DSL) curves from the Ares I-X flight data. These are then used in the MATLAB program to generate the 1/3 octave band SPL spectra. Concluding results show major differences in SPLs between the hold-down test data and the processed Ares IX flight data making the Ares I-X flight data more practical for future vehicle acoustic environment predictions.

Gao, Ximing↗

Ensemble Methodologies for Astronaut Cancer Risk Assessment in the face of Large Uncertainties

A new approach to NASA space radiation risk modeling has successfully extended the current NASA probabilistic cancer risk model to an ensemble framework able to consider sub-model parameter uncertainty (e.g. uncertainty in a radiation quality parameter) as well as model-form uncertainty associated with differing theoretical or empirical formalisms (e.g. combined dose-rate and radiation quality effects). Ensemble methodologies are already widely used in weather prediction, modeling of infectious disease outbreaks, and certain terrestrial radiation protection applications to better understand how uncertainty may influence risk decision-making. Applying ensemble methodologies to space radiation risk projections offers the potential to efficiently incorporate emerging research results, allow for the incorporation of future (including international) models, improve uncertainty quantification for underlying sub-models developed against sparse experimental data, and reduce the impact of subjective bias on risk projections. Moreover, risk forecasting across an ensemble of multiple predictive models can provide stakeholders additional information on risk acceptance if current health/medical standards cannot be met or the level of knowledge doesn’t permit a specific risk or exposure limit to be developed for future space exploration missions. In this work, ensemble risk projections implementing multiple sub-models of radiation quality, dose and dose-rate effectiveness factors, excess risk, and latency as ensemble members are presented. Initial consensus methods for ensemble model weights and correlations to account for individual model bias are discussed. In these analyses, the ensemble forecast compares well to results from NASA's current operational cancer risk projection model used to assess permissible exposure limits and permissible mission durations for astronauts. However, a large range of projected risk values are obtained at the upper 95th confidence level where models must extrapolate beyond available biological data sets; closer agreement is seen at the median + one sigma due to the inherent similarities in available models. Future work, including the addition of new models and methods for statistical correlation between predictive members are discussed to define alternate ways of thinking about risk and ‘acceptable’ uncertainty with respect to NASA’s current permissible exposure limits.

space radiation↗

Ensemble Cancer Risk Model for Astronaut Risk Assessment

A new approach to NASA space radiation risk modeling has successfully extended the current NASA probabilistic cancer risk model to an ensemble framework able to consider sub-model parameter uncertainty (e.g. uncertainty in a radiation quality parameter) as well as model-form uncertainty associated with differing theoretical or empirical formalisms (e.g. combined dose-rate and radiation quality effects). Ensemble methodologies are already widely used in weather prediction, modeling of infectious disease outbreaks, and certain terrestrial radiation protection applications to better understand how uncertainty may influence risk decision-making. Applying ensemble methodologies to space radiation risk projections offers the potential to efficiently incorporate emerging research results, allow for the incorporation of future (including international) models, improve uncertainty quantification for underlying sub-models developed against sparse experimental data, and reduce the impact of subjective bias on risk projections. Moreover, risk forecasting across an ensemble of multiple predictive models can provide stakeholders additional information on risk acceptance if current health/medical standards cannot be met or the level of knowledge doesn’t permit a specific risk or exposure limit to be developed for future space exploration missions. In this work, ensemble risk projections implementing multiple sub-models of radiation quality, dose and dose-rate effectiveness factors, excess risk, and latency as ensemble members are presented. Initial consensus methods for ensemble model weights and correlations to account for individual model bias are discussed. In these analyses, the ensemble forecast compares well to results from NASA's current operational cancer risk projection model used to assess permissible exposure limits and permissible mission durations for astronauts. However, a large range of projected risk values are obtained at the upper 95th confidence level where models must extrapolate beyond available biological data sets; closer agreement is seen at the median + one sigma due to the inherent similarities in available models. Future work, including the addition of new models and methods for statistical correlation between predictive members are discussed to define alternate ways of thinking about risk and ‘acceptable’ uncertainty with respect to NASA’s current permissible exposure limits.

Lisa C Simonsen↗

Data Mining of Historical Human Data to Assess the Risk of Injury due to Dynamic Loads

The NASA Occupant Protection Group is charged with ensuring crewmembers are protected during all dynamic phases of spaceflight. Previous work with outside experts has led to the development of a definition of acceptable risk (DAR) for space capsule vehicles. The DAR defines allowable probability rates for various categories of injuries. An important question is how to validate these probabilities for a given vehicle. One approach is to impact test human volunteers under projected nominal landing loads. The main drawback is the large number of subject tests required to attain a reasonable level of confidence that the injury probability rates would meet those outlined in the DAR. An alternative is to mine existing databases containing human responses to impact. Testing an anthropomorphic test device (ATD) at the same human‐exposure levels could yield a range of ATD responses that would meet DAR. As one aspect of future vehicle validation, the ATD could be tested in the vehicle's seat and suit configuration at nominal landing loads and compared with the ATD responses supported by the human data set. This approach could reduce the number of human‐volunteer tests NASA would need to conduct to validate that a vehicle meets occupant protection standards. METHODS: The U.S. Air Force has recorded hundreds of human responses to frontal, lateral, and spinal impacts at many acceleration levels and pulse durations. All of this data are stored on the Collaborative Biomechanics Data Network (CBDN), which is maintained by the Wright Patterson Air Force Base (WPAFB). The test device for human occupant restraint (THOR) ATD was impact tested on WPAFB's horizontal impulse accelerator (HIA) matching human‐volunteer exposures on the HIA to 5 frontal and 3 spinal loading conditions. No human injuries occurred as a result of these impact conditions. Peak THOR response variables for neck axial tension and compression, and thoracic‐spine axial compression were collected. Maximal chest deflection was determined from motion capture video of the impact test. HIC‐ 15 and BRIC were calculated from head acceleration responses. Given the number of human subjects for each test condition a confidence interval of injury probability will be obtained. RESULTS: Results will be discussed in terms of injury‐risk probability estimates based on the human data set evaluated. Also, gaps in the data set will be identified. These gaps could be one of two types. One is areas where additional THOR testing would increase the comparable human data set, thereby improving confidence in the injury probability rate. The other is where additional human testing would assist in obtaining information on other acceleration levels or directions. DISCUSSION: The historical human data showed validity of the THOR ATD for supplemental testing. The historical human data are limited in scope, however. Further data are needed to characterize the effects of sex, age, anthropometry, and deconditioning due to spaceflight on risk of injury

Wells, Jesica↗

Energy Distribution among Reaction Products. III: The Method of Measured Relaxation Applied to H + Cl2

The method of measured relaxation is described for the determination of initial vibrational energy distribution in the products of exothermic reaction. Hydrogen atoms coming from an orifice were diffused into flowing chlorine gas. Measurements were made of the resultant ir chemiluminescence at successive points along the line of flow. The concurrent processes of reaction, diffusion, flow, radiation, and deactivation were analyzed in some detail on a computer. A variety of relaxation models were used in an attempt to place limits on k(nu prime), the rate constant for reaction to form HCl in specified vibrational energy levels: H+Cl2 yields (sup K(nu prime) HCl(sub nu prime) + Cl. The set of k(?) obtained from this work is in satisfactory agreement with those obtained by another experimental method (the method of arrested relaxation described in Parts IV and V of the present series.

Pacey, P. D.↗

Structure of Offshore Low-Level Jet Turbulence and Implications to Mesoscale-to-Microscale Coupling

This paper explores realistic nonstationary atmospheric boundary layer (ABL) turbulence arising from nonstationarity at the mesoscale, particularly within offshore low-level jets with implications to offshore wind farms, using high-fidelity multiscale large-eddy simulations (LES). To this end, we analyzed the single-point turbulence statistical structure of a North-Atlantic offshore LLJ event simulated using high-resolution LES (AMR-Wind). The nonstationary LLJ is simulated using a mesoscale-to-microscale coupled (MMC) simulation procedure involving data assimilation of mesoscale velocity and temperature data from the Weather Research and Forecasting (WRF) model. Unlike the assimilation of mesoscale velocity data into the LES, the direct assimilation of temperature profiles had a strong impact on turbulence stratification, thereby causing erroneous predictions of turbulence both above and within the jet layer. Various approaches to mitigate this effect have resulted in multiple (four) variants of this MMC strategy. Outcomes from this work clearly show that the turbulence within the low-level jet is a strong function of the MMC approach as the turbulence structure within the low-level jet is dependent on the flux of residual turbulence from outside the jet, which in turn depends on the temperature forcing history. Additionally, the turbulence predicted by all these different methods (as well as the observation data) show similar deviations from equilibrium as evidenced by comparisons with idealized atmospheric turbulence structure obtained using the same numerical method. In general, we observe that the predicted LLJ turbulence tends to differ from canonical ABL turbulence with comparable shear. Particularly, the combination of shear and turbulence observed in such nonstationary low-level turbulence cannot be matched using equilibrium settings and therefore, represents a critical use-case for both testing and leveraging meso–micro coupling strategies.

17 WIND ENERGY↗

Communication: Unambiguous comparison of many-electron wavefunctions through their overlaps

A simple and powerful method for comparing many-electron wavefunctions constructed at different levels of theory is presented. By using wavefunction overlaps, it is possible to analyze the effects of varying wavefunction models, molecular orbitals, and one-electron basis sets. The computation of wavefunction overlaps eliminates the inherent ambiguity connected to more rudimentary wavefunction analysis protocols, such as visualization of orbitals or comparing selected physical observables. Instead, wavefunction overlaps allow processing the many-electron wavefunctions in their full inherent complexity. The presented method is particularly effective for excited state calculations as it allows for automatic monitoring of changes in the ordering of the excited states. A numerical demonstration based on multireference computations of two test systems, the selenoacrolein molecule and an iridium complex, is presented.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Method for the Quantification of Model Form Error Associated with Physical Systems

In the process of model validation, models are often declared valid when the differences between model predictions and experimental data sets are satisfactorily small. However, little consideration is given to the effectiveness of a model using parameters that deviate slightly from those that were fitted to data, such as a higher load level. Furthermore, few means exist to compare and choose between two or more models that reproduce data equally well. These issues can be addressed by analyzing model form error, which is the error associated with the differences between the physical phenomena captured by models and that of the real system. This report presents a new quantitative method for model form error analysis and applies it to data taken from experiments on tape joint bending vibrations. Two models for the tape joint system are compared, and suggestions for future improvements to the method are given. As the available data set is too small to draw any statistical conclusions, the focus of this paper is the development of a methodology that can be applied to general problems.

97 MATHEMATICS AND COMPUTING↗

Best practices for building energy codes compliance

Building energy codes are a proven policy mechanism to achieve economy-wide energy savings in buildings. In 2021, the International Energy Agency Energy in Buildings and Communities Programme (IEA EBC) Building Energy Codes Working Group (BECWG) set out to survey the diverse codes compliance practices across BECWG member countries. While codes vary in format and approach, attaining the energy reduction potential of building energy codes requires effective implementation and compliance. This is a large undertaking for countries, as effective compliance checking requires adequate resources, technical knowledge, capacity, and strong institutions. Many nations face the same compliance issues, such as requiring faster and easier methods to verify codes and coordinating among numerous stakeholders and levels of government. This paper explores the need for stronger institutional approaches to enforce building energy codes that will lead to code compliance. Specifically, this report sets out to address the question of what practices result in effective building energy code compliance in selected BECWG member countries.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Orbital breathing effects in the computation of x-ray d -ion spectra in solids by ab initio wave-function-based methods

In existing theoretical approaches to core-level excitations of transition-metal ions in solids relaxation and polarization effects due to the inner core hole are often ignored or described phenomenologically. Here, we set up an ab initio computational scheme that explicitly accounts for such physics in the calculation of x-ray absorption and resonant inelastic x-ray scattering spectra. Good agreement is found with experimental transition-metal L-edge data for the strongly correlated d 9 cuprate Li 2 CuO 2 , for which we also determine the absolute scattering intensities. The newly developed methodology opens the way for the investigation of even more complex d n electronic structures of group VI B to VIII B correlated oxide compounds.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Investigation of dose reduction in cardiac perfusion SPECT via optimization and choice of the image reconstruction strategy

Background: We investigated the extent to which the administered dose (activity) level can be reduced without sacrificing diagnostic accuracy for three reconstruction strategies for SPECT-myocardial perfusion imaging (MPI). Methods: We optimized the parameters of the three reconstruction strategies for perfusion-defect detection over a range of simulated administered dose levels using a set of hybrid studies (derived from 190 subjects) consisting of clinical SPECT-MPI data modified to contain realistic simulated lesions. The optimized strategies we considered are filtered backprojection (FBP) with no correction for degradations, ordered-subsets expectation-maximization (OS-EM) with attenuation correction (AC), scatter correction (SC), and resolution correction (RC), and OS-EM with scatter and resolution correction only. Each study was evaluated using a total perfusion deficit (TPD) score computed by the Quantitative Perfusion SPECT (QPS) software package. We conducted a receiver operating characteristics (ROC) study based on the TPD scores for each dose level and reconstruction strategy. Results: For FBP, the achieved optimum values of the area under the ROC curve (AUC) at 100%, 50%, 25%, and 12.5% of standard dose were 0.75, 0.74, 0.72, and 0.70, respectively, compared to 0.81, 0.79, 0.76, and 0.74 for OS-EM with AC–SC–RC and 0.78, 0.77, 0.74, 0.72 for OS-EM with SC–RC. Conclusions: Our results suggest that studies reconstructed by OS-EM with AC–SC–RC could possibly be reduced, on average, to 25% of the originally administered dose without causing diagnostic accuracy (AUC) to decrease below that of FBP.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

SIRT1-mediated deacetylation of PGC1α attributes to the protection of curcumin against glutamate excitotoxicity in cortical neurons

It is widely accepted that accumulation of extracellular glutamate mediates neuronal injuries in a number of neurological disorders via binding glutamate receptors. However, usage of the glutamate receptor antagonists aimed to prevent glutamate excitotoxicity is still controversial. As a polyphenol natural product, curcumin, has been implied multiple bioactivities. In this study, we explored whether the silent information regulator 1 (SIRT1)-peroxisome proliferator-activated receptor-coactivator 1α (PGC1α) pathway participated in the protection of curcumin against glutamate excitotoxicity. The cultured primary cortical neurons were treated with glutamate to set up a neuronal excitotoxicity model. The MTT and TUNEL methods were employed to measure cell viability and apoptosis, respectively. The mitochondrial function, the expression levels of SIRT1, PGC1α and acetylated PGC1α (ac-PGC1α) were measured to explore the mechanism of curcumin against glutamate excitotoxicity. The results showed that glutamate significantly induced cell death and apoptosis, which was blocked by pretreatment with curcumin. Meanwhile, curcumin preserved mitochondrial function, increased the expression level of SIRT1 and reduced the level of ac-PGC1α in the presence of glutamate. These results suggest that SIRT1-mediated deacetylation of PGC1α attributes to the neuroprotection of curcumin against glutamate excitotoxicity. - Highlights: • Curcumin attenuates glutamate induced cell death and apoptosis in cultured neurons. • Curcumin preserves mitochondrial function in the presence of glutamate. • Curcumin enhanced the expression of SIRT1 in the glutamate rich environment. • SIRT1-mediated deacetylation of PGC1α attributes to the neuroprotection of curcumin.

60 APPLIED LIFE SCIENCES↗

Highly polarized photoluminescence and its dynamics in semipolar (202{sup ¯}1{sup ¯}) InGaN/GaN quantum well

Very high polarization degree of 0.98, considerably larger than theoretical predictions, has been measured in (202{sup ¯}1{sup ¯}) In{sub 0.24}Ga{sub 0.76}N/GaN quantum well by low temperature photoluminescence. With increasing temperature, the polarization degree decreases due to thermal population of the excited valence band level. This effect suggests an accurate method to determine the interlevel energy, which, for the studied well, is 32 meV. Time-resolved photoluminescence measurements set radiative recombination times between 2 and 12 ns for temperatures from 3 to 300 K. Nonradiative recombination was found to be slow, over 2 ns at 300 K, taking place via traps with activation energy of 0.19 eV.

36 MATERIALS SCIENCE↗

Full-dimensional global potential energy surfaces describing abstraction and exchange for the H + H{sub 2}S reaction

For the H + H{sub 2}S system, ∼34 000 data points are sampled over a large configuration space including both abstraction and exchange channels, and calculated at the level of explicitly correlated unrestricted coupled cluster method with singles, doubles, and perturbative triples excitations with the augmented correlation-consistent polarized triple zeta basis set (UCCSD(T)-F12a/aug-cc-pVTZ). The data set was fit using the newly proposed permutation invariant polynomial-neural network (PIP-NN) method with three different vectors as the input: two redundant sets of PIPs, one with the maximum order four (PES-I) and one with the maximum order three (PES-II), and nine non-redundant PIPs (PES-III). All these PESs show small fitting errors and essentially the same performance in representing the title system. Various kinetics and dynamical properties are calculated using the tunneling corrected transition state theory and quasi-classical trajectory, and compared with available experimental results. At a collision energy of 10 kcal/mol, both the H{sub 2} and SH products are found to be internally cold, with ∼20% of H{sub 2} at its first vibrational excited state, while SH is essentially a spectator. The angular distributions of the products are mainly in backward with considerable contributions from sideway direction. In addition, analytical partial derivatives of any PIP-NN PES with respect to the coordinates of atoms are derived by making use of the monomial symmetrization algorithm [Z. Xie and J. M. Bowman, J. Chem. Theory Comput. 6, 26–34 (2010)]. It can not only accelerate the evaluation of the derivatives, but also improve the energy convergence significantly.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Automated experimental design of safe rampdowns via probabilistic machine learning

Abstract Typically the rampdown phase of a shot consists of a decrease in current and injected power and optionally a change in shape, but there is considerable flexibility in the rate, sequencing, and duration of these changes. On the next generation of tokamaks it is essential that this is done safely as the device could be damaged by the stored thermal and electromagnetic energy present in the plasma. This works presents a procedure for automatically choosing experimental rampdown designs to rapidly converge to an effective rampdown trajectory. This procedure uses probabilistic machine learning methods paired with acquisition functions taken from Bayesian optimization. In a set of 2022 experiments at DIII-D, the rampdown designs produced by our method maintained plasma control down to substantially lower current and energy levels than are typically observed. The actions predicted by the model significantly improved as the model was able to explore over the course of the experimental campaign.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Conditional deep generative models for simultaneous simulation and reconstruction of entire events

We extend the particle-flow neural assisted simulations (arnassus) framework of fast simulation and reconstruction to entire collider events. In particular, we use two generative artificial intelligence tools, continuous normalizing flows and diffusion models, to create a set of reconstructed particle-flow objects conditioned on truth-level particles from CMS Open Simulations. While previous work focused on jets, our updated methods now can accommodate all particle-flow objects in an event along with particle-level attributes like particle type and production vertex coordinates. This approach is fully automated, entirely written in Python, and GPU-compatible. Using a variety of physics processes at the LHC, we show that the extended arnassus is able to generalize beyond the training dataset and outperforms the standard, public tool elphes.

Dreyer, Etienne [Weizmann Institute of Science, Re↗

Model-independent Higgs coupling measurements at the LHC using the H{yields}ZZ{yields}4l lineshape

We show that combining a direct measurement of the Higgs total width from the H{yields}ZZ{yields}4l lineshape with Higgs signal rate measurements allows Higgs couplings to be extracted in a model-independent way from CERN LHC data. Using existing experimental studies with 30 fb{sup -1} at one detector of the 14 TeV LHC, we show that the couplings squared of a 190 GeV Higgs to WW, ZZ, and gg can be extracted with statistical precisions of about 10%, and a 95% confidence level upper limit on an unobserved component of the Higgs decay width of about 22% of the standard model Higgs width can be set. The method can also be applied for heavier Higgs masses.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗