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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 217 records · Page 12

Efficient Translation of LTL Formulae into Buchi Automata

Model checking is a fully automated technique for checking that a system satisfies a set of required properties. With explicit-state model checkers, properties are typically defined in linear-time temporal logic (LTL), and are translated into B chi automata in order to be checked. This report presents how we have combined and improved existing techniques to obtain an efficient LTL to B chi automata translator. In particular, we optimize the core of existing tableau-based approaches to generate significantly smaller automata. Our approach has been implemented and is being released as part of the Java PathFinder software (JPF), an explicit state model checker under development at the NASA Ames Research Center.

Giannakopoulou, Dimitra↗

Cloud Inhomogeneity from MODIS

Two full months (July 2003 and January 2004) of MODIS Atmosphere Level-3 data from the Terra and Aqua satellites are analyzed in order to characterize the horizontal variability of cloud optical thickness and water path at global scales. Various options to derive cloud variability parameters are discussed. The climatology of cloud inhomogeneity is built by first calculating daily parameter values at spatial scales of l degree x 1 degree, and then at zonal and global scales, followed by averaging over monthly time scales. Geographical, diurnal, and seasonal changes of inhomogeneity parameters are examined separately for the two cloud phases, and separately over land and ocean. We find that cloud inhomogeneity is weaker in summer than in winter, weaker over land than ocean for liquid clouds, weaker for local morning than local afternoon, about the same for liquid and ice clouds on a global scale, but with wider probability distribution functions (PDFs) and larger latitudinal variations for ice, and relatively insensitive to whether water path or optical thickness products are used. Typical mean values at hemispheric and global scales of the inhomogeneity parameter nu (roughly the mean over the standard deviation of water path or optical thickness), range from approximately 2.5 to 3, while for the inhomogeneity parameter chi (the ratio of the logarithmic to linear mean) from approximately 0.7 to 0.8. Values of chi for zonal averages can occasionally fall below 0.6 and for individual gridpoints below 0.5. Our results demonstrate that MODIS is capable of revealing significant fluctuations in cloud horizontal inhomogenity and stress the need to model their global radiative effect in future studies.

Oreopoulos, Lazaros↗

V3885 Sagittarius: A Comparison With a Range of Standard Model Accretion Disks

A chi-squared analysis of standard model accretion disk synthetic spectrum fits to combined Far Ultraviolet Spectroscopic Explorer and Space Telescope Imaging Spectrograph spectra of V3885 Sagittarius, on an absolute flux basis, selects a model that accurately represents the observed spectral energy distribution. Calculation of the synthetic spectrum requires the following system parameters. The cataclysmic variable secondary star period-mass relation calibrated by Knigge in 2006 and 2007 sets the secondary component mass. A mean white dwarf (WD) mass from the same study, which is consistent with an observationally determined mass ratio, sets the adopted WD mass of 0.7M(solar mass), and the WD radius follows from standard theoretical models. The adopted inclination, i = 65 deg, is a literature consensus, and is subsequently supported by chi-squared analysis. The mass transfer rate is the remaining parameter to set the accretion disk T(sub eff) profile, and the Hipparcos parallax constrains that parameter to mas transfer = (5.0 +/- 2.0) x 10(exp -9) M(solar mass)/yr by a comparison with observed spectra. The fit to the observed spectra adopts the contribution of a 57,000 +/- 5000 K WD. The model thus provides realistic constraints on mass transfer and T(sub eff) for a large mass transfer system above the period gap.

MASS TRANSFER RATE↗

Optimizing Medical Kits for Spaceflight

The Integrated Medical Model (IMM) is a probabilistic model that estimates medical event occurrences and mission outcomes for different mission profiles. IMM simulation outcomes describing the impact of medical events on the mission may be used to optimize the allocation of resources in medical kits. Efficient allocation of medical resources, subject to certain mass and volume constraints, is crucial to ensuring the best outcomes of in-flight medical events. We implement a new approach to this medical kit optimization problem. METHODS We frame medical kit optimization as a modified knapsack problem and implement an algorithm utilizing a dynamic programming technique. Using this algorithm, optimized medical kits were generated for 3 different mission scenarios with the goal of minimizing the probability of evacuation and maximizing the Crew Health Index (CHI) for each mission subject to mass and volume constraints. Simulation outcomes using these kits were also compared to outcomes using kits optimized..RESULTS The optimized medical kits generated by the algorithm described here resulted in predicted mission outcomes more closely approached the unlimited-resource scenario for Crew Health Index (CHI) than the implementation in under all optimization priorities. Furthermore, the approach described here improves upon in reducing evacuation when the optimization priority is minimizing the probability of evacuation. CONCLUSIONS This algorithm provides an efficient, effective means to objectively allocate medical resources for spaceflight missions using the Integrated Medical Model.

Optimization↗

Mass and Volume Optimization of Space Flight Medical Kits

Resource allocation is a critical aspect of space mission planning. All resources, including medical resources, are subject to a number of mission constraints such a maximum mass and volume. However, unlike many resources, there is often limited understanding in how to optimize medical resources for a mission. The Integrated Medical Model (IMM) is a probabilistic model that estimates medical event occurrences and mission outcomes for different mission profiles. IMM simulates outcomes and describes the impact of medical events in terms of lost crew time, medical resource usage, and the potential for medically required evacuation. Previously published work describes an approach that uses the IMM to generate optimized medical kits that maximize benefit to the crew subject to mass and volume constraints. We improve upon the results obtained previously and extend our approach to minimize mass and volume while meeting some benefit threshold. METHODS We frame the medical kit optimization problem as a modified knapsack problem and implement an algorithm utilizing dynamic programming. Using this algorithm, optimized medical kits were generated for 3 mission scenarios with the goal of minimizing the medical kit mass and volume for a specified likelihood of evacuation or Crew Health Index (CHI) threshold. The algorithm was expanded to generate medical kits that maximize likelihood of evacuation or CHI subject to mass and volume constraints. RESULTS AND CONCLUSIONS In maximizing benefit to crew health subject to certain constraints, our algorithm generates medical kits that more closely resemble the unlimited-resource scenario than previous approaches which leverage medical risk information generated by the IMM. Our work here demonstrates that this algorithm provides an efficient and effective means to objectively allocate medical resources for spaceflight missions and provides an effective means of addressing tradeoffs in medical resource allocations and crew mission success parameters.

Monte Carlo Method↗

Integrated Medical Model (IMM) Optimization Version 4.0 Functional Improvements

The IMMs ability to assess mission outcome risk levels relative to available resources provides a unique capability to provide guidance on optimal operational medical kit and vehicle resources. Post-processing optimization allows IMM to optimize essential resources to improve a specific model outcome such as maximization of the Crew Health Index (CHI), or minimization of the probability of evacuation (EVAC) or the loss of crew life (LOCL). Mass and or volume constrain the optimized resource set. The IMMs probabilistic simulation uses input data on one hundred medical conditions to simulate medical events that may occur in spaceflight, the resources required to treat those events, and the resulting impact to the mission based on specific crew and mission characteristics. Because IMM version 4.0 provides for partial treatment for medical events, IMM Optimization 4.0 scores resources at the individual resource unit increment level as opposed to the full condition-specific treatment set level, as done in version 3.0. This allows the inclusion of as many resources as possible in the event that an entire set of resources called out for treatment cannot satisfy the constraints. IMM Optimization version 4.0 adds capabilities that increase efficiency by creating multiple resource sets based on differing constraints and priorities, CHI, EVAC, or LOCL. It also provides sets of resources that improve mission-related IMM v4.0 outputs with improved performance compared to the prior optimization. The new optimization represents much improved fidelity that will improve the utility of the IMM 4.0 for decision support.

risk assessment↗

First Search for Dark-Trident Processes Using the MicroBooNE Detector

This thesis presents a first search for dark-trident scattering in a neutrino beam using a data set corresponding to $7.2 \times 10^{20}$ protons on target taken with the MicroBooNE detector at Fermilab. Proton interactions in the neutrino target at the Main Injector produce $\pi^0$ and $\eta$ mesons, which could decay into dark matter (DM) particles via a dark photon $A^{\prime}$. A convolutional neural network is trained to identify interactions of the DM particles in the liquid-argon time projection chamber (LArTPC) exploiting its image-like reconstruction capability. In the absence of a DM signal, limits at the $90\%$ confidence level on the squared kinematic mixing parameter $\varepsilon^2$ as a function of the dark-photon mass in the range $10\le M_{A^\prime}\le 400$~MeV are provided. The limits cover previously unconstrained parameter space for the production of fermion or scalar DM particles $\chi$ for two benchmark models with mass ratios $M_{\chi}/M_{A^\prime}=0.6$ and $2$ and for dark fine-structure constants $0.1\le\alpha_D\le 1$.Date of Award1 Aug 2024Original languageEnglishAwarding InstitutionThe University of ManchesterSupervisorStefan Soldner-Rembold (Supervisor) & Justin Evans (Supervisor)

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Precise Modeling of a Complex Solenoidal Magnetic Field Using a Combination of Analytic Functions and a PINN

We demonstrate an iterative approach to modeling a sparsely measured magnetic field in a large-bore solenoid. This approach uses a hybrid of traditional and machine learning techniques. The traditional technique is a linear least-squares fit using a series solution to Laplace's equation, while the machine learning technique involves the training of a physics-informed neural network (PINN) on the least-squares fit residuals. We use a newly defined activation function "DELTAsnake," a modification to the snake activation function proposed by Ziyin et al. that allows for stronger curvature and non-monotonicity. The combined model approximately obeys Maxwell's equations to a level sufficient for producing high quality physics simulations and analysis. Our approach is applied to a highly realistic calculation of the expected magnetic field in the Mu2e experiment's Detector Solenoid which includes a simple model for the expected statistical measurement uncertainties. Using ten toy measurement simulations, we demonstrate the capabilities of our model in comparison to the least-squares method alone; the least-squares method alone results in a reduced chi-squared statistic of ${2.15 \pm 0.01}$, while our approach improves the reduced chi-square to ${1.034 \pm 0.005}$. Furthermore, for an average toy simulation, we show that the range of the RMS of the three field component residuals reduces from ${0.07-0.37}$ Gauss to ${0.05-0.07}$ Gauss. We find that this novel method is robust against a realistic systematic uncertainty deriving from Hall probe calibration bias and can be used to significantly reduce the number of measurements required to achieve an accurate model.

Kampa, Cole [Caltech] (ORCID:0000000192972920)↗

Measurement of the 239 Pu$(n, f$) prompt fission neutron spectrum from 10 keV to 10 MeV induced by neutrons of energy 1–20 MeV

Although the prompt fission neutron spectrum (PFNS) is an essential component of neutron-driven systems that has been measured for decades, there are still multiple glaring unknowns regarding the PFNS of major actinides in the fission neutron incident energy range, specifically with regard to multichance fission and pre-equilibrium neutron emission processes. The only impactful experimental 239 Pu PFNS measurements included in recent nuclear data evaluations were measured over a limited outgoing neutron energy range at thermal and 1.5-MeV average incident neutron energy, while other potentially impactful measurements have been shown to contain errors that resulted in either large uncertainty increases or in complete exclusion from nuclear data evaluation. Here, we report a measurement of the 239 Pu PFNS over a wide range of incident neutron energy (1–20 MeV) and three orders of magnitude in outgoing neutron energy (0.01–10 MeV) resulting from the Chi-Nu experiment at the Los Alamos Neutron Science Center. These results are the combination of separate PFNS measurements in the same experimental area, one using a Li-glass and the other a liquid scintillator detector array. Covariances between all PFNS data points from each detector and within each incident energy range were generated between all other data in both detector arrays and within all other incident neutron energy bins, yielding a single covariance matrix for all 1300 PFNS data points reported here. These covariances are based on a thorough assessment of systematic bias and uncertainties associated with the measurement, PFNS extraction technique, combination of data from each detector type, and other aspects of the analysis. The existence of covariances between PFNS data points in different incident neutron energy ranges yielded covariances between average PFNS energy values at each incident energy to be reported here as well, which allowed for firm statements to be made regarding a shape of a purely experimental mean PFNS energy trend for the first time. Although minor PFNS shape differences exist between the results reported here and recent nuclear data evaluations, the ENDF/B-VIII.0 and JEFF-3.3 PFNS evaluations agree reasonably well with the present results from 1-to 10-MeV incident neutron energy, which spans the well-measured 1.5-MeV incident neutron energy PFNS from Lestone and Shores as well as the onset of second-chance fission. However, while the pre-equilibrium component of the PFNS above 12-MeV incident neutron energy roughly agrees in position and magnitude with ENDF/B-VIII.0 and JEFF-3.3, clear differences relating to the relative magnitude of third-chance fission PFNS features are present in the PFNS shape and in the mean PFNS energy trends.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Joint Inversion of Regional Waveform, First-Motion Polarity, and Synthetic Aperture Radar Surface Displacement for the Fourth and Sixth North Korean Declared Nuclear Explosions

Here, this study analyzed the Democratic People’s Republic of Korea’s (DPRK) fourth (DPRK4, 6 January 2016 M w 4.49) and sixth (DPRK6, 7 September 2017 M w 5.2) declared nuclear tests, employing a joint seismic and Interferometric Synthetic Aperture Radar (InSAR) inversion to improve understanding of these events and enhance moment tensor (MT) inversion capabilities. The recent efforts have focused on employing seismic waveform and InSAR geodetic deformation data separately to analyze these and the previous nuclear tests (e.g., Chiang et al., 2018; Myers et al., 2018; Wang et al., 2018). Building upon our previous work (Chi-Durán et al., 2021), we performed a joint regional waveform, first-motion (FM) polarity, and surface displacement inversion, which demonstrated improved source-type discrimination, a revised MT solution with reduced scalar moment uncertainty, and an independently constrained location. In this article, we build on the previous results for DPRK6 by including an analysis using a four-layered velocity model with free-surface topography to compute the near-source static deformation Green’s functions. The model consists of a 50 m basalt layer (⁠V P = 2.07 km/s, V S = 1.2 km/s⁠), a 250 m stratified volcanic deposit layer (⁠V P = 1.73 km/s, V S = 1.0 km/s⁠), a 700 m weathered granodiorite layer (⁠V P = 2.5 km/s, V S = 1.3 km/s⁠⁠), and a granodiorite half-space (⁠V P = 5.35 km/s, V S = 3.09 km/s⁠⁠). The half-space shares the velocity of the regional MDJ2 velocity model (Ford et al., 2010), which has proven effective for waveform inversion in the region. This model considers the range of reported values for various lithologies and weathering effects. Our findings show that using the layered velocity model enhances the recovery of source location and depth for both the explosions by improving fits and reducing uncertainties. The joint inversion also improves source-type discrimination and better constrains the scalar seismic moment necessary for downstream yield estimation.

58 GEOSCIENCES↗

Variable thickness shear layer aerodynamics revisited

The constant boundary-layer thickness (BLT) figuring in the Ventres (1975) Kernel function can be replaced by a slowly varying BLT, in the case of shear layers of slowly varying thickness. A simplification of the extension by Chi (1976) of Ventres' solution is put forward. The Kernel function in this instance relates pressure on the lifting surface to downwash over the surface. The results should also apply, formally, to three-dimensional compressible unsteady flows, but the accuracy in assuming slowly varying shear BLT remains to be determined. All variants of the shear layer model fail when the shear layer thickness varies rapidly.

Dowell, E. H.↗

Roundoff noise analysis for digital signal power processors using Welch's power spectrum estimation

The noise due to finite-word-length effects is analyzed for digital-signal power processors using Welch's power-spectrum estimation technique to measure the power of Gaussian random signals over a frequency band of interest. The input of the digital signal processor contains a finite-length time interval in which the true Gaussian signal is contaminated by Gaussian noise. The roundoff noise-to-signal ratio in the measurement of the signal power is derived, and computer simulations which validate the analytical results are presented. These results can be used in tradeoff studies of hardware design, such as the number of bits required at each processing stage. The results presented in this paper are currently being used in the design of a digital Doppler processor (Chi et al., 1986) for a radar scatterometer.

Chi, Chong-Yung↗

A further analysis for the minimum-variance deconvolution filter performance

Chi and Mendel (1984) analyzed the performance of minimum-variance deconvolution (MVD). In this correspondence, a further analysis of the performance of the MVD filter is presented. It is shown that the MVD filter performs like an inverse filter and a whitening filter as SNR goes to infinity, and like a matched filter as SNR goes to zero. The estimation error of the MVD filter is colored noise, but it becomes white when SNR goes to zero. This analysis also conects the error power-spectral density of the MVD filter with the spectrum of the causal-prediction error filter.

Chi, Chong-Yung↗

A search for the decays of stopped long-lived particles at $ \sqrt{\mathrm{s}} $ = 13 TeV with the ATLAS detector

A search for long-lived particles, which have come to rest within the ATLAS detector, is presented. The subsequent decays of these particles can produce high-momentum jets, resulting in large out-of-time energy deposits in the ATLAS calorimeters. These de- cays are detected using data collected during periods in the LHC bunch structure when collisions are absent. The analysed dataset is composed of events from proton-proton collisions produced by the Large Hadron Collider at a centre-of-mass energy of s = 13 TeV and recorded by the ATLAS experiment during 2017 and 2018. The dataset used for this search corresponds to a total live time of 579 hours. The results of this search are used to derive lower limits on the mass of gluino R -hadrons, assuming a branching fraction $ \mathcal{B}\left(\overset{\sim }{g}\to q\overline{q}{\chi}_1^0\right) $ B g ~ → q q ¯ χ 1 0 = 100%, with masses of up to 1 . 4 TeV excluded for gluino lifetimes of 10 - 5 to 10 3 s.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Scattering equations in AdS: scalar correlators in arbitrary dimensions

We introduce a bosonic ambitwistor string theory in AdS space. Even though the theory is anomalous at the quantum level, one can nevertheless use it in the classical limit to derive a novel formula for correlation functions of boundary CFT operators in arbitrary space-time dimensions. The resulting construction can be treated as a natural extension of the CHY formalism for the flat-space S-matrix, as it similarly expresses tree-level amplitudes in AdS as integrals over the moduli space of Riemann spheres with punctures. These integrals localize on an operator-valued version of scattering equations, which we derive directly from the ambitwistor string action on a coset manifold. As a testing ground for this formalism we focus on the simplest case of ambitwistor string coupled to two cur- rent algebras, which gives bi-adjoint scalar correlators in AdS. In order to evaluate them directly, we make use of a series of contour deformations on the moduli space of punctured Riemann spheres and check that the result agrees with tree level Witten diagram computations to all multiplicity. We also initiate the study of eigenfunctions of scattering equations in AdS, which interpolate between conformal partial waves in different OPE channels, and point out a connection to an elliptic deformation of the Calogero-Sutherland model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

High bias machine learning for antineutrino-based safeguards for small reactors

The statistical methods used for antineutrino detection will need to be improved to effectively monitor the inventory of next-generation nuclear reactors. In this sensitivity study, we evaluate machine learning models compared to previously used statistical approaches to identify diversion scenarios in a simulated Advanced Fast Reactor (AFR)-100. A chi-square goodness-of-fit technique, which individually compares the simulated antineutrino yields to the expected antineutrino yield, resulted in precise but low diversion detection probability. Various support vector machine (SVM) models were applied with diverse training datasets to evaluate the robustness of the method towards unexpected or “unseen” diversion scenarios. Furthermore, our results indicate that while the SVM models significantly improved the detection probability of near-field antineutrino-based safeguards, up to a probability of ~0.04, for the simulated small reactor, the detection system still needs improvements to reach the 0.2 detection limit established by the International Atomic Energy Agency.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Dietary uptake of geosmin in rainbow trout ( Oncorhynchus mykiss )

Geosmin is a primary source of muddy/earthy ‘off-flavors’ in farmed fish, which may render their organoleptic quality unacceptable to consumers. Model systems of geosmin uptake typically comprise exposure to waterborne geosmin that is absorbed via the gills. The present research demonstrates dietary exposure as an alternative route of geosmin uptake in Rainbow Trout (Oncorhynchus mykiss) fillets. Trout (average initial weight of 355 g) were stocked in quadruplicate compartmentalized raceways (N = 4 compartments per treatment, n = 50 fish per compartment) supplied with first-use, flow-through water (4.5 complete turnovers per hour). Fish were fed diets containing 0 (control dose), 0.005 (low dose), 0.05 (medium dose), or 0.5 (high dose) mg geosmin/kg feed at 1% body weight/day for four weeks. Fillets (12 fillets/diet/week plus 12 pre-trial fillet samples) and weekly feed and water samples were analyzed via GC–MS to determine geosmin concentrations. Feeding behavior was documented daily according to a four-point scale. ANOVA with post-hoc Tukey tests and polynomial contrast, regression, correlation, and chi-squared statistical analyses were applied to data (α = 0.05 significance level). Palatability of feed did not hinder consumption of the geosmin-spiked feeds: although fish responded positively to all feeds, the most aggressive feeding behavior was observed among those fed medium and high dose feed. Geosmin was effectively imparted into fillets after one week, and no significant temporal effect was found after four weeks. Mean geosmin concentrations significantly increased in fillets from low (mean of 26 ng/kg geosmin) to medium (202 ng/kg) to high (441 ng/kg) dose feed groups during the trial. Polynomial contrasts and regression modeling validated this significant positive effect of dose on geosmin uptake, with an estimated 166 ng/kg rise in fillet-geosmin for every log 10 increase in feed concentration. Waterborne geosmin levels immediately post-feeding were conditionally independent of concentrations in feed and fillets, therefore dietary uptake was affirmed as the predominant mechanism of absorption in the present experimental system. Finally, based on these findings, geosmin-spiked feeds may be used to induce predictable, repeatable levels of this off-flavor compound in fillets and serve as a model system for further investigation of sensory quality and off-flavor mitigation strategies for farm-raised fish.

59 BASIC BIOLOGICAL SCIENCES↗