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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 343 records · Page 19

The Development and Deployment of Machine Learning Models for Aircraft Engine Concept Assessment

In today's competitive landscape, the effective development and utilization of machine-learning (ML) applications have become crucial across diverse economic sectors. This study presents an outline of the procedure involved in creating and implementing ML models for conceptualizing and evaluating aircraft engines. These models leverage supervised deep-learning algorithms to analyze patterns within an open-source repository containing data on both production and research conventional turbofan engines. The main areas of focus encompass crucial engine parameters like thrust-specific fuel consumption (TSFC), engine weight, engine diameter, and turbomachinery stage counts. While the creation of ML models is fundamental for their utilization, ensuring their seamless deployment holds equal significance. To address this aspect, a conversational AI chatbot that specifically focuses on propulsion has been developed. Leveraging natural language processing (NLP) techniques, this chatbot simplifies the deployment of machine learning (ML) models. The comprehensive workflow encompasses several key stages: gathering and enhancing engine data, training and cross validating the ML models, testing and evaluating their performance, and finally, deploying, monitoring, and updating the ML models. By following this systematic approach, the aim is to streamline the development and deployment process of ML models tailored for aircraft engine assessment.

AI Chatbot↗

A model-independent analysis of the Fermi Large Area Telescope gamma-ray data from the Milky Way dwarf galaxies and halo to constrain dark matter scenarios

Here, we implemented a novel technique to perform the collective spectral analysis of sets of multiple gamma-ray point sources using the data collected by the Large Area Telescope onboard the Fermi satellite. The energy spectra of the sources are reconstructed starting from the photon counts and without assuming any spectral model for both the sources and the background. In case of faint sources, upper limits on their fluxes are evaluated with a Bayesian approach. Our analysis technique is very useful when several sources with similar spectral features are studied, such as sources of gamma rays from annihilation of dark matter particles. We also present the results obtained by applying this analysis to a sample of dwarf spheroidal galaxies and to the Milky Way dark matter halo. The analysis of dwarf spheroidal galaxies yields upper limits on the product of the dark matter pair annihilation cross section and the relative velocity of annihilating particles that are well below those predicted by the canonical thermal relic scenario in a mass range from a few GeV to a few tens of GeV for some annihilation channels.

79 ASTRONOMY AND ASTROPHYSICS↗

Developing Fault Models for Space Mission Software

A viewgraph presentation on the development of fault models for space mission software is shown. The topics include: 1) Goal: Improve Understanding of Technology Fault Generation Process; 2) Required Measurement; 3) Measuring Structural Evolution; 4) Module Attributes; 5) Principal Components of Raw Metrics; 6) The Measurement Process; 7) View of Structural Evolution at the System and Module Level; 8) Identifying and Counting Faults; 9) Fault Enumeration; 10) Modeling Fault Content; 11) Modeling Results; 12) Current and Future Work; and 13) Discussion and Conclusions.

software measurements↗

AERoBOND Project Summary

Under NASA’s Convergent Aeronautics Solutions (CAS) project, the Adhesive-Free Bonding of Complex Composites (AERoBOND) project investigated off-stoichiometric epoxy polymers for fast, reliable assembly of epoxy matrix composite structures. The project goal was to demonstrate feasibility of the AERoBOND joining method by demonstrating mechanical properties greater than 80% of conventional co-cured materials while reducing structure weight by 1%. The project consisted of three convergent research areas: material and process development, systems analysis, and material and process modeling. Material and process development was the largest component of AERoBOND with approximately 6 FTE and 1WYE of support to formulate and characterize new resins, prepare carbon fiber prepregs, fabricate laminates, measure mechanical properties, analyze failure results, and select material and process improvements. The systems analysis activity estimated the potential reduction in part count and aircraft weight by comparing models of composite wing boxes with no fasteners (co-cured structure), fasteners in major joints (co-cured stringers), and fasteners in all joints. The materials and process modeling activity included a molecular model of the AERoBOND materials system to predict mechanical properties of resins with offset stoichiometry and a process model to predict the effect of resin formulation and processing conditions on the extent of mixing and degree of cure in a finished joint. As the number of airline passenger trips doubles in the next 20 years (IATA/Tourism Economics Air Passenger Forecasts, April 2019), the increased demand for new commercial aircraft is now the single greatest technical challenge to the airframe manufacturing industry. To meet efficiency requirements, new aircraft must be fabricated primarily from high performance structural composites, but manufacturing processes are inherently slow with the largest bottleneck attributed to assembly and installation of fasteners (NASA/TM–2019-220428). Manufactures of commercial transport aircraft are compelled to install more than 100,000 redundant fasteners into bonded joints to prevent failures due to unpredictable weak bonds. In structural adhesive bonds, the interface between adherend and adhesive is nearly two-dimensional making it susceptible to minute quantities of contamination, which can cause weak bonds. Currently, bond strength assessment is only possible through destructive testing (i.e., breaking the joint). For these reasons, regulatory organizations such as the Federal Aviation Administration (FAA) often require redundant load paths in secondary-bonded, primary-structures to alleviate concerns with bond performance. The AERoBOND process enables reflow of matrix resin during assembly to eliminate the material discontinuity at the interface, thereby eliminating the dependence of mechanical performance on interfacial adhesion. The AERoBOND joint is equivalent to the interlaminar region obtained during a co-cure process, so joint performance depends on the cohesive properties of the matrix resin. Conventional co-cured structures, although too costly and complex for large-scale manufacturing, are trusted by manufacturers and regulators, and are certified for flight with few or no redundant fasteners.Systems analysis performed on a composite wing model at the scale of a single-aisle commercial transport aircraft indicated that >20,000 redundant fasteners per wing could be eliminated by implementing the AERoBOND joining method. A total weight reduction of 15% was predicted in a wing box by eliminating fasteners and thinning components that must no longer support localized fastener loads and accommodate fastener dimensions. Interlaminar shear fracture toughness measured by the end-notched flexure test was greater than 1 kJ/m2 (nearly 140% of the co-cured benchmark property), which is greatly in excess of the project goals for mechanical properties. Testing was planned to measure interlaminar tensile fracture toughness as well as interlaminar tensile and shear strengths using the same AERoBOND configuration, but was delayed due to closure of LaRC facilities during the COVID-19 pandemic. The AERoBOND process model is partially validated and available for experimental use. It allows the user to input AERoBOND process parameters such as material composition, laminate configuration, and cure cycle to predict the final cure state of the AERoBOND joint. A preliminary, multi-scale material model was developed to predict AERoBOND joint mechanical properties (stiffness and strength) based on the cure state of the joint provided by the process model. The timing for transition of this technology within NASA is excellent as NASA initiates new enduring projects to address composites manufacturing rate challenges. AERoBOND technology is well suited to AAVP/AATT objectives for rapid manufacturing of a composite wing. A minimal effort (1 FTE/$15k procurement/0 WYE) is proposed in FY21 to continue a minor mechanical testing effort and maintain a SAA with ASX composites to develop commercial quality prepreg material. An RFI with the composites industry is suggested to quantify the technology gap between the current TRL and the TRL needed for transition to industry. A moderate effort [3-4 FTE/$150k/1 WYE (~$115k)] is proposed in FY22 for the “high rate composites manufacturing” project currently in planning. The partnership with ASX Composites will be expanded to produce material for sub-element/element-scale “panel-off” activities. Industry partnerships with airframe manufacturers is an expected component to explore damage tolerance and environmental stability. Further development of multi-scale modeling tools (process model, meso-scale model, and molecular model) is planned to enhance and deliver tools for rapid manufacturing infusion.

Frank Louis Palmieri↗

Deadtime Calculations of Liquid Scintillator Neutron Detector Using Attenuation Law

Scientists have been working on deadtime problems for radiation detectors since 1940's. In detector systems, a minimum time must separate two different events before they can be measured individually. That minimum time interval is called to be deadtime of detector system. There are two commonly deadtime models: the paralyzing and the non-paralyzing models. Paralyzing model assumes that each event during the deadtime will reset the deadtime and deadtime extension will depend on the count rate. According to the non-paralyzing model, deadtime is fixed after each detected event and all events occurring during deadtime are lost. In this study, deadtime measurements have been obtained for an N-Probe fast neutron (NE-213 Liquid Scintillation) detector manufactured by BTI (Bubble Technology Industries) using a combination of the attenuation law and the assumption of ideal paralyzing and non-paralyzing method. Bubble Technology Industries (BTI) has manufactured a portable neutron scintillation spectrometer (N-Probe) with potential applications at nuclear reactor facilities, waste processing operations, and spent fuel storage areas. The deadtime of the N-Probe detector is not provided by the manufacturer; BTI, and there is no other study published on the N-Probe detector' deadtime. Since the detector will be used in future nuclear fuel investigations, it is important to determine the detector' deadtime for accurate nuclear fuel analysis. The deadtime of the BTI N-Probe was examined using different thicknesses of Plexiglas at the Missouri University of Science and Technology Reactor (MSTR) using attenuation law and average macroscopic cross-section of Plexiglas defined by both paralyzing and non-paralyzing model. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Forecasting distributed energy resources adoption for power systems

Failing to incorporate accurate distributed energy resource penetration forecasts into long-term resource and transmission planning can lead to cost inefficiencies at best and system failures at worst. We have developed an open-source tool that employs an advanced Bass specification to calibrate and forecast technology adoption. The advanced specification includes geographic clustering, exogenously estimated market size, and dynamic time steps. Training on historical adoption of rooftop photovoltaics at the U.S. county-level and using detailed techno-economic estimates, our model achieves a two-year average mean-absolute-percentage-error of 19% in predicting system counts at the county-level, weighted by population. Model error was negatively correlated with market maturity - the error was 12% for counties in states with at least 28 W-per-capita of installed capacity. The advanced specification significantly reduces unweighted forecasting percent error compared to a conventional Bass specification: from 196% to 25% for capacity and from 226% to 22% for system count.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Ecological analysis of associations between groundwater quality and hypertension and cardiovascular disease in rural Saskatchewan, Canada using Bayesian hierarchical models and administrative health data

Highlights: • Hardness and magnesium were associated with decreased risk of cardiovascular disease. • Arsenic concentrations were not associated with the risk of cardiovascular disease. • Summarized water health standards were not associated with cardiovascular disease. Associations between groundwater quality and the prevalence of hypertension and ischemic heart disease were investigated in rural areas of the Canadian province of Saskatchewan. The partially ecological study was analyzed using Bayesian hierarchical models to account for spatial variability in risk. Exposure measures and health outcomes were estimated based on previously collected water quality surveillance data from public water supplies and private wells and administrative health data. Water quality exposures for each study region were estimated by applying geostatistical techniques to arsenic concentrations and principal component (PC) scores. The PC scores summarized groups of parameters measuring either health standards or aesthetic objectives described by the province. Generalized linear mixed models with a log link assessed associations between water quality and observed count of health outcomes relative to the expected value. The Bayesian models contained uncorrelated and spatially correlated random effects for each geographic region. Effect estimates were controlled for sex and age by stratification of case and expected case counts, for smoking by inclusion of sex- and age-specific prevalence of chronic obstructive pulmonary disease as a surrogate covariate, and for education and income by use of census data. There was no evidence for associations between groundwater arsenic concentrations in public or private water supplies and increased risk of hypertension or cardiovascular disease. An increase in the second aesthetic objectives PC score from public supplies was associated with a protective effect against ischemic heart disease. This PC value summarized hardness and magnesium Similarly, an increase in the second aesthetic objectives PC in private supplies was associated with decreased prevalence of hypertension. The results of this study are consistent with others demonstrating a relationship between elevated hardness and magnesium concentrations in drinking water and reduced risk of hypertension and cardiovascular disease. Further investigation is warranted with individual exposure history, particularly with respect to the potential beneficial effect of hard water on the prevalence of hypertension and cardiovascular disease.

54 ENVIRONMENTAL SCIENCES↗

In-Situ Assays Using a New Advanced Mathematical Algorithm - 12400

Current mathematical efficiency modeling software for in-situ counting, such as the commercially available In-Situ Object Calibration Software (ISOCS), typically allows the description of measurement geometries via a list of well-defined templates which describe regular objects, such as boxes, cylinder, or spheres. While for many situations, these regular objects are sufficient to describe the measurement conditions, there are occasions in which a more detailed model is desired. We have developed a new all-purpose geometry template that can extend the flexibility of current ISOCS templates. This new template still utilizes the same advanced mathematical algorithms as current templates, but allows the extension to a multitude of shapes and objects that can be placed at any location and even combined. In addition, detectors can be placed anywhere and aimed at any location within the measurement scene. Several applications of this algorithm to in-situ waste assay measurements, as well as, validations of this template using Monte Carlo calculations and experimental measurements are studied. Presented in this paper is a new template of the mathematical algorithms for evaluating efficiencies. This new template combines all the advantages of the ISOCS and it allows the use of very complex geometries, it also allows stacking of geometries on one another in the same measurement scene and it allows the detector to be placed anywhere in the measurement scene and pointing in any direction. We have shown that the template compares well with the previous ISOCS software within the limit of convergence of the code, and also compare well with the MCNPX and measured data within the joint uncertainties for the code and the data. The new template agrees with ISOCS to within 1.5% at all energies. It agrees with the MCNPX to within 10% at all energies and it agrees with most geometries within 5%. It finally agrees with measured data to within 10%. This mathematical algorithm can now be used for quickly and accurately evaluating efficiencies for wider range of gamma-ray spectroscopy applications. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

A petabyte size electronic library using the N-Gram memory engine

A model library containing petabytes of data is proposed by Triada, Ltd., Ann Arbor, Michigan. The library uses the newly patented N-Gram Memory Engine (Neurex), for storage, compression, and retrieval. Neurex splits data into two parts: a hierarchical network of associative memories that store 'information' from data and a permutation operator that preserves sequence. Neurex is expected to offer four advantages in mass storage systems. Neurex representations are dense, fully reversible, hence less expensive to store. Neurex becomes exponentially more stable with increasing data flow; thus its contents and the inverting algorithm may be mass produced for low cost distribution. Only a small permutation operator would be recalled from the library to recover data. Neurex may be enhanced to recall patterns using a partial pattern. Neurex nodes are measures of their pattern. Researchers might use nodes in statistical models to avoid costly sorting and counting procedures. Neurex subsumes a theory of learning and memory that the author believes extends information theory. Its first axiom is a symmetry principle: learning creates memory and memory evidences learning. The theory treats an information store that evolves from a null state to stationarity. A Neurex extracts information data without a priori knowledge; i.e., unlike neural networks, neither feedback nor training is required. The model consists of an energetically conservative field of uniformly distributed events with variable spatial and temporal scale, and an observer walking randomly through this field. A bank of band limited transducers (an 'eye'), each transducer in a bank being tuned to a sub-band, outputs signals upon registering events. Output signals are 'observed' by another transducer bank (a mid-brain), except the band limit of the second bank is narrower than the band limit of the first bank. The banks are arrayed as n 'levels' or 'time domains, td.' The banks are the hierarchical network (a cortex) and transducers are (associative) memories. A model Neurex was built and studied. Data were 50 MB to 10 GB samples of text, data base, and images: black/white, grey scale, and high resolution in several spectral bands. Memories at td, S(m(sub td)), were plotted against outputs of memories at td-1. S(m(sub td)) was Boltzman distributed, and memory frequencies exhibited self-organized criticality (SOC); i.e., 'l/f(sup beta)' after long exposures to data. Whereas output signals from level n may be encoded with B(sub output) = O(-log(2)f(sup beta)) bits, and input data encoded with B(sub input) = O((S(td)/S(td-1))(sup n)), B(sup output)/B(sub input) is much less than 1 always, the Neurex determines a canonical code for data and it is a lossless data compressor. Further tests are underway to confirm these results with more data types and larger samples.

Bugajski, Joseph M.↗

LandScan mosaic enables high-resolution gridded population estimates with explicit uncertainty

Gridded population datasets represent high-resolution distributions of human occupancy, enabling informed decision-making across a broad range of fields. These data products are valuable for assessing environmental risk, urban development, disaster preparedness and resource allocation—areas where accurate population estimates directly enhance policy effectiveness and optimize resource distribution. Despite the importance of gridded population datasets, traditional population modeling approaches often overlook inherent uncertainties in the estimation process. This limitation can create a false sense of certainty in population estimates, potentially leading to flawed decisions by those who rely on the data. To address this methodological gap, we introduce a probabilistic machine learning modeling framework, LandScan Mosaic, that explicitly incorporates uncertainty into the population modeling process. Our approach systematically quantifies uncertainty in three key modeling parameters of the LandScan HD gridded population dataset: building use types, floor counts, and occupancy rates. By employing Monte Carlo simulations, we propagate these uncertainties through the modeling process, yielding probability distributions of population counts in place of deterministic point estimates. We demonstrate the practical application of this framework in Iloilo City, Philippines, using structured decision-making techniques and our probabilistic estimates to identify and prioritize areas most affected by projected flooding, supporting targeted interventions that address both economic and social risks. In doing so, we propose a population-specific approach for incorporating confidence into structured decision making processes. Through a comparative analysis with conventional deterministic approaches and point estimate approaches, including LandScan HD and WorldPop, we evaluate how the incorporation of machine learning and uncertainty influences decision rankings. This research advances population distribution modeling by offering a robust, quantitative approach that explicitly accounts for uncertainty in the underlying data, along with guidance for how users can apply uncertainty in their decision-making.

Environmental sciences↗

Determination of plasma temperatures and luminosities using multiple extreme-ultraviolet and X-ray filters

We carefully examine the techniques used to infer temperatures of stellar coronal plasmas from the count rates of several broadband instruments in the X-ray and extreme-ultraviolet spectral ranges. In particular, we determine to what extent temperatures can be constrained and the corresponding uncertainties in the luminosities and emission measures lowered by fitting simultaneously count rates from the Einstein imaging proportional counter (IPC), the ROSAT Position Sensitive Proportional Counter (PSPC), the ROSAT Wide Field Camera (WFC) (both filters), and the EXOSAT Low Energy Telescope (LET) with the 3-Lex filter. We use published plasma emissivities with solar photospheric abundances. Since it has been found that single-temperature plasmas do not fit IPC data well, we assume a two-temperature plasma model. We find that, even with count rates from all of the above filters and overly optimistic error estimates, it is still not possible to determine a unique two-temperature solution. However, since the use of count rates from many filters can reduce substantially the number of possible solutions, temperature solutions determined by other means can be tested. We carry out such an analysis on a set of 18 nearby late-type stars to determine possible two-temperature solutions using multifilter photometry, and we compare these results with the temperature solutions derived by Schmitt et al. (1990) using IPC spectral data. In general, the two-temperature fits derived from the IPC spectral data are inconsistent with our results, with our data implying that, for many stars, the two temperatures derived by the IPC may be too low by about a factor of 2. The EXOSAT transmission grating Spectrometer (TGS) spectra of capella and sigma(exp 2) CrB support this conclusion. For Procyon and 70 Oph, though, the presence of a temperature component cooler than a million degress (not detected by the IPC) is deduced. While our analysis suggests the existence of more than one temperature in the coronae of late-type stars, in many instances our WFC data appear to be inconsistent with the presence of significant emission measure over a broad temperature distribution. This, together with the success of two-temperature plasmas in fitting IPC and TGS data, implies that for many stars, the coronal emission measure distribution may in fact be dominated by two distinct temperature regimes.

Wood, Brian E.↗

Protogalactic mergers and cosmochronology

We construct schematic models for chemical evolution and cosmochronology within the expanding and collapsing protogalactic halo followed by formation of the local disk. Star formation is associated with both the rate of protogalactic mergers and the intrinsic gas density of protogalactic clouds and the disk. This leads naturally to a scenario in which star formation in the disk can be delayed by several billion years relative to the formation of the oldest globular clusters. We analyze various cosmochronometers in the context of this model and show that the apparent differences between the maximum globular-cluster ages, the white-dwarf cooling age, and nuclear chronometric ages can be understood. The merger models which satisfy the age constraints imply a relatively late forming peak in luminosity and therefore may be consistent with the observed peak in galaxy number counts at intermediate redshifts. Versions of the model with and without nonbaryonic dark matters can yield significant dark baryonic halos.

Mathews, G. J.↗

CFD-Informed Spacer Grid Models in the Subchannel Code CTF

Data from computational fluid dynamics (CFD) simulations can be utilized to improve the predictive capabilities of the subchannel code CTF. Past work incorporating CFD results into CTF has included accounting for directed crossflow and turbulent mixing between adjacent subchannels. Spacer grids impact fluid flow in various ways, and this work focuses on four spacer grid effects, namely: 1. Directed crossflow; 2. Turbulent mixing; 3. Enhanced downstream heat transfer; 4. Pressure drop correlation. Heat transfer augmentation occurs partially due to the disturbances in the developed flow and from the additional turbulence generated by the presence of obstructions in the fluid flow's path. The boundary layer disruption is caused in part by the newly-directed flow just downstream of the spacer grid vanes. This effect lessens as the distance from the grid increases and the flow returns to its developed state, closer to what would be expected in a bare subchannel. Current plans of this work are to develop a method for incorporating the effects of spacer grids on the heat transfer calculation within CTF. Proposed techniques include the addition of an enhancement factor to the local heat transfer coefficient. The inclusion of CFD data from properly-designed simulations will allow CTF to better predict parameters such as fluid temperatures near spacer grids. Improved pressure loss coefficients for each grid can also be generated using CFD simulations. The heat transfer modification has been studied, with other authors noting correlations which are dependent on grid properties such as the blockage ratio. Parameters considered in this study are the turbulent kinetic energy (TKE) and vorticity. There are currently no models to calculate or store either of these parameters within CTF. When accounting for spacer grid effects in CTF, it is important to not double-count the effects towards two different CTF models. This requires carefully designing CFD simulations around capturing specific phenomena from the grids and being able to apply these CFD results to all appropriate flow conditions. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Spatial distribution of Compton-produced X-ray flux from rich and regular clusters of galaxies

The spatial distribution of radio and X-ray fluxes from rich and regular clusters of galaxies is discussed. A diffusion model is investigated in which high-energy electrons are ejected from a point source at the center of the cluster. While diffusing out, the electrons lose energy by Compton scattering with the universal blackbody photons, thus producing the X-ray emission. Traversing intracluster magnetic fields, the electrons emit synchrotron radio emission. For the Coma cluster of galaxies good agreement is found between the observed and predicted X-ray counting-rate distribution for the Compton model. From the observed radio data a value of about 3 by 10 to the -8th power gauss is deduced for the average magnetic-field strength in the central region of Coma.

Rephaeli, Y.↗

Leveraging Fine-Grained Occupancy Estimation Patterns for Effective HVAC Control

As occupancy sensing technologies become mature, various occupancy sensors are increasingly deployed in commercial buildings for pervasive occupancy monitoring. These sensors provide occupant-count data, which contains rich spatiotemporal information about occupancy patterns. With long-term occupant-count data collected from a commercial building, we design three different predictive models that capture the occupancy dynamics and examine how a model predictive control of the HVAC system benefits from actual occupancy count prediction. Our analysis reveals that mispredictions of occupancy states, especially false positives and false negatives, may introduce inefficient control that leads to energy waste or user discomfort. To address this issue, we take a step further to design an adaptive model predictive controller that minimizes inefficient control actions according to misprediction types and distributions. A comprehensive evaluation is performed in OpenBuild and EnergyPlus simulators to study the effectiveness of the proposed end-to-end control strategy. The evaluation shows that the proposed solution reduces energy consumption by 29.5% while improving the average weighted occupants comfort by 86.7% in Predicted Mean Vote (PMV) over the fixed schedule strategy.

97 MATHEMATICS AND COMPUTING↗

The NuSTAR Extragalactic Surveys: The Number Counts Of Active Galactic Nuclei And The Resolved Fraction Of The Cosmic X-ray Background

We present the 3-8 kiloelectronvolts and 8-24 kiloelectronvolts number counts of active galactic nuclei (AGNs) identified in the Nuclear Spectroscopic Telescope Array (NuSTAR) extragalactic surveys. NuSTAR has now resolved 33 percent -39 percent of the X-ray background in the 8-24 kiloelectronvolts band, directly identifying AGNs with obscuring columns up to approximately 10 (exp 25) per square centimeter. In the softer 3-8 kiloelectronvolts band the number counts are in general agreement with those measured by XMM-Newton and Chandra over the flux range 5 times 10 (exp -15) less than or approximately equal to S (3-8 kiloelectronvolts) divided by ergs per second per square centimeter less than or approximately equal to 10 (exp -12) probed by NuSTAR. In the hard 8-24 kiloelectronvolts band NuSTAR probes fluxes over the range 2 times 10 (exp -14) less than or approximately equal to S (8-24 kiloelectronvolts) divided by ergs per second per square centimeter less than or approximately equal to 10 (exp -12), a factor approximately 100 times fainter than previous measurements. The 8-24 kiloelectronvolts number counts match predictions from AGN population synthesis models, directly confirming the existence of a population of obscured and/or hard X-ray sources inferred from the shape of the integrated cosmic X-ray background. The measured NuSTAR counts lie significantly above simple extrapolation with a Euclidian slope to low flux of the Swift/BAT15-55 kiloelectronvolts number counts measured at higher fluxes (S (15-55 kiloelectronvolts) less than or approximately equal to 10 (exp -11) ergs per second per square centimeter), reflecting the evolution of the AGN population between the Swift/BAT local (redshift is less than 0.1) sample and NuSTAR's redshift approximately equal to 1 sample. CXB (Cosmic X-ray Background) synthesis models, which account for AGN evolution, lie above the Swift/BAT measurements, suggesting that they do not fully capture the evolution of obscured AGNs at low redshifts

nucle↗

Enhancing Adaptive Physics Refinement Simulations Through the Addition of Realistic Red Blood Cell Counts

Simulations of cancer cell transport require accurately modeling mm-scale and longer trajectories through a circulatory system containing trillions of deformable red blood cells, whose intercellular interactions require submicron fidelity. Using a hybrid CPU-GPU approach, we extend the advanced physics refinement (APR) method to couple a finely-resolved region of explicitly-modeled red blood cells to a coarsely-resolved bulk fluid domain. We further develop algorithms that: capture the dynamics at the interface of differing viscosities, maintain hematocrit within the cell-filled volume, and move the finely-resolved region and encapsulated cells while tracking an individual cancer cell. Comparison to a fully-resolved fluid-structure interaction model is presented for verification. Finally, we use the advanced APR method to simulate cancer cell transport over a mm-scale distance while maintaining a local region of RBCs, using a fraction of the computational power required to run a fully-resolved model.

Roychowdhury, Sayan↗