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NASA NTRSDate not supplied

Database Design Strategies for Coordinated Simulation and Testing in Additive Manufacturing

The qualification and certification (Q&C) process presents a significant challenge for widespread adoption of additive manufacturing (AM) materials and processes for aerospace applications. A relational database framework will be presented as a tool for data curation of coordinated experimental and computational materials modeling research activities. A comparison of relational and hierarchical data structures in this domain will be emphasized through the evolution of a database design strategy. This framework’s mission is to support the advancement of computational materials-informed Q&C by providing the necessary data infrastructure to trace reliability and reproducibility measures through unified AM materials simulation and experimental testing. FAIR (findable, accessible, interoperable, and reusable) data will be highlighted as a necessary precursor for automation of specific actions, which ultimately reduces the time and expense burden for Q&C. The discussion will be mostly limited to back-end design elements, though a few front-end user experience examples will also be shared.

Qualification↗

NASA NTRS1981

Application of HCMM data to regional geologic analysis for mineral and energy resource evaluation

Experimentation with several potentially promising techniques led to the selection of a fairly simple scheme for registration of data from the HCMM using an affine transformation. A method based solely on remote sensing was developed to estimate those meteorological effects which are required for thermal inertia mapping. It assumes that the atmospheric fluxes are spatially invariant and that the solar, sky and sensible heat fluxes can be approximated by a simple mathematical form. Coefficients are determined from least squares method by fitting observational data to the thermal model.

Watson, K.↗

NASA NTRS1952

Experimental Investigation of Average Heat-Transfer and Friction Coefficients for Air Flowing in Circular Tubes Having Square-Thread-Type Roughness

An investigation of forced-convection heat transfer and associated pressure drops was conducted with air flowing through electrically heated Inconel tubes having various degrees of square-thread-type roughness, an inside diameter of 1/2 inch, and a length of 24 inches. were obtained for tubes having conventional roughness ratios (height of thread/radius of tube) of 0 (smooth tube), 0.016, 0.025, and 0.037 over ranges of bulk Reynolds numbers up to 350,000, average inside-tube-wall temperatures up to 1950deg R, and heat-flux densities up to 115,000 Btu per hour per square foot. Data The experimental data showed that both heat transfer and friction increased with increase in surface roughness, becoming more pronounced with increase in Reynolds number; for a given roughness, both heat transfer and friction were also influenced by the tube wall-to-bulk temperature ratio. Good correlation of the heat-transfer data for all the tubes investigated was obtained by use of a modification of the conventional Nusselt correlation parameters wherein the mass velocity in the Reynolds number was replaced by the product of air density evaluated at the average film temperature and the so-called friction velocity; in addition, the physical properties of air were evaluated at the average film temperature. The isothermal friction data for the rough tubes, when plotted in the conventional manner, resulted in curves similar to those obtained by other investigators; that is, the curve for a given roughness breaks away from the Blasius line (representing turbulent flow in smooth tubes) at some value of Reynolds number, which decreases with increase in surface roughness, and then becomes a horizontal line (friction coefficient independent of Reynolds number). A comparison of the friction data for the rough tubes used herein indicated that the conventional roughness ratio is not an adequate measure of relative roughness for tubes having a square-thread-type element. The present data, as well as those of other investigators, were used to isolate the influence of ratios of thread height to width, thread spacing to width, and the conventional roughness ratio on the friction coefficient. A fair correlation of the friction data was obtained for each tube with heat addition when the friction coefficient and Reynolds number were defined on the basis of film properties; however, the data for each tube retained the curve characteristic of that particular roughness. The friction data for all the rough tubes could be represented by a single line for the complete turbulence region by incorporating a roughness parameter in the film correlation. No correlation was obtained for the region of incomplete turbulence.

Sams, E. W.↗

NASA NTRS1999

Incorporating TRMM and Other High-Quality Estimates into the One-Degree Daily (1DD) Global Precipitation Product

The One-Degree Daily (1DD) precipitation dataset was recently developed for the Global Precipitation Climatology Project (GPCP). The IDD provides a globally-complete, observation-only estimate of precipitation on a daily 1 deg x 1 deg grid for the period 1997 through late 1999 (by the time of the conference). In the latitude band 40 N - 40 S the IDD uses the Threshold-Matched Precipitation Index (TMPI), a GPI-like IR product with the T(sub b) threshold and (single) conditional rain rate determined locally for each month by the frequency of precipitation in the GPROF SSNU product and by the precipitation amount in the GPCP satellite-gauge (SG) combination. Outside 40 N - 40 S the 1DD uses a scaled TOVS precipitation estimate that has adjustments based on the TMPI and the SG. This first-generation 1DD has been in beta test preparatory to release as an official GPCP product. In this paper we discuss further development of the 1DD framework to allow the direct incorporation of TRMM and other high-quality precipitation estimates. First, these data are generally sparse (typically from low-orbit satellites), so a fair amount of work was devoted to data boundaries. Second, these data are not the same as the original 1DD estimates, so we had to give careful consideration to the best scheme for forcing the 1DD to sum to the SG for the month. Finally, the non-sun-synchronous, low-inclination orbit occupied by TRMM creates interesting variations against the sun-synchronous, high-inclination orbits occupied by the Defense Meteorological Satellite Program satellites that carry the SSM/I. Examples will be given of each of the development issues, then comparisons will be made to daily raingauge analyses.

Huffman, George J.↗

NASA NTRS2011

Effects of Data Quality on the Characterization of Aerosol Properties from Multiple Sensors

Cross-comparison of aerosol properties between ground-based and spaceborne measurements is an important validation technique that helps to investigate the uncertainties of aerosol products acquired using spaceborne sensors. However, it has been shown that even minor differences in the cross-characterization procedure may significantly impact the results of such validation. Of particular consideration is the quality assurance I quality control (QA/QC) information - an auxiliary data indicating a "confidence" level (e.g., Bad, Fair, Good, Excellent, etc.) conferred by the retrieval algorithms on the produced data. Depending on the treatment of available QA/QC information, a cross-characterization procedure has the potential of filtering out invalid data points, such as uncertain or erroneous retrievals, which tend to reduce the credibility of such comparisons. However, under certain circumstances, even high QA/QC values may not fully guarantee the quality of the data. For example, retrievals in proximity of a cloud might be particularly perplexing for an aerosol retrieval algorithm, resulting in an invalid data that, nonetheless, could be assigned a high QA/QC confidence. In this presentation, we will study the effects of several QA/QC parameters on cross-characterization of aerosol properties between the data acquired by multiple spaceborne sensors. We will utilize the Multi-sensor Aerosol Products Sampling System (MAPSS) that provides a consistent platform for multi-sensor comparison, including collocation with measurements acquired by the ground-based Aerosol Robotic Network (AERONET), The multi-sensor spaceborne data analyzed include those acquired by the Terra-MODIS, Aqua-MODIS, Terra-MISR, Aura-OMI, Parasol-POLDER, and CalipsoCALIOP satellite instruments.

Petrenko, Maksym↗

NASA NTRS1987

Reduction of hub- and pylon-fairing drag

A wind tunnel test was conducted to obtain data on several drag reduction methods for rotorcraft hubs. The objective of the test was to use small-scale models to develop the technology to substantially reduce hub drag. A helicopter test model, which did not incorporate a rotor, was used to study single-rotor fairing configurations. The rotor shaft assembly was modeled with nonrotating hardware. Drag trend data was obtained for the following fairing configuration changes: hub-fairing camber, hub-fairing thickness ratio, hub-fairing surface curvature, hub-fairing height with respect to the fuselage, inclusion of blade shanks in the hub fairings, hub- and pylon-fairing gaps, pylon-fairing cross-sectional geometry, pylon-fairing thickness ratio and camber. Substantial drag reductions could potentially result from application of the test results to helicopter hub- and pylon-fairing design.

Young, Larry A.↗

NASA NTRSDate not supplied

NASA biological and physical sciences databases: who’s the FAIRest of them all?

Conceptual models are a key part of the foundation of scientific study. Scientific data discovery and retrieval are often inaccurate and incomplete because these models are not sufficiently well-incorporated into data retrieval systems. Systems often don’t provide the necessary tools to those producing scientific data to fully and unambiguously annotate them and the result is consumers of the data cannot find them efficiently. The capability of data archives to provide these tools to link data to underlying conceptual models is one of dimensions of the recently developed “FAIR” principles (https://www.go-fair.org/fair-principles/ ), and is key to many automated processes being able to operate on these data, particularly analytics involving artificial intelligence. We used an open-source web service to measure the FAIR compliance of the three data archives operated by NASA for the biological and physical sciences: the Life Sciences Data Archive, the Physical Sciences Informatics database, and GeneLab. The service ingests references to data sets in these archives, and then executes domain-non-specific examinations of these data and metadata that test compliance to the FAIR principles. Of the 22 metrics tested, GeneLab passed 11 (50%), and PSI and LSDA each passed 7 (32%). These data were gathered using only one representative data set from each archive and we anticipate variability in results as we continue to apply these metrics to other data. A preliminary study of the failure traces for each metric suggests there is a wide range of effort and complexity in the enhancements required for each system to elevate FAIR compliance, and this is the subject of continued investigation. This information has been and will likely continue to be important information in planning these enhancements, with the goal of increased readiness of the data for automated processes.

database↗

DOE OSTI2025

Alaska's Rural Building Stock: a Validation Study Using ResStock and Field Data

The availability of accurate national data on demographics, building stock, and energy use is vital for modeling residential buildings and evaluating decarbonization strategies. However, rural and Indigenous populations, including those in rural Alaska, are typically underrepresented in these datasets. These communities face unique challenges due to their remote locations, severe weather conditions, and limited access to resources, resulting in high energy burden. This report examines how rural Alaskan communities are underrepresented in the ResStock housing model and highlights the need for improved data to address their unique housing and energy challenges. Thus, this report examines the representation of rural Alaskan communities within the national housing stock model, ResStock. A validation study was conducted, considering ResStock, Field Data and Aerial and 3D-view data collection (A3DDC) datasets. The validation process started by using the down selecting approach on the ResStock building stock dataset. For the purpose of this study, only the rural Alaska Boroughs and Census areas located in ASHRAE IECC Climate Zone 8 were considered to ensure a more accurate and fair comparison with the field data, which was collected in rural areas located in climate zone 8, specifically within the Nome Census area. While ResStock may accurately represent several characteristics of the building stock for rural Alaska, some differences between modeled, field data, and aerial and 3D-view data collection datasets were identified. The following building characteristics have a high impact on modeled energy consumption and demonstrated large differences: Revisit heating setpoints and consider a substantially higher setpoint distribution, it could potentially address "missing loads" if this is the case. Develop and include Toyo heating in future modeling for ResStock and EnergyPlus. Remove natural gas as a water heater fuel type outside of North Slope County. Foundation type updated to have more crawlspaces rather than basements. Infiltration rates need reexamination for a larger distribution toward higher infiltration rates. Include more vinyl and less brick in exterior wall type and revise wall color for greater proportion of light rather than dark color. Roof material revised from majority shingles to majority metal. Update number of occupants to higher number of occupant count. Building orientation represents a higher proportion of south facing buildings rather than relatively equal. The findings suggest that updating ResStock's probability logic could better represent rural Alaskan buildings. ResStock can be utilized to identify the best upgrades or energy efficiency and energy efficiency improvements, helping community leaders in making more informed decisions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS2018

Steps Toward Improved Integration, Search, and Analysis of Heterogeneous Data in the Astrobiology Habitable Environments Database

The Astrobiology Habitable Environments Database (AHED) is a new data system being developed as a long-term, open-access repository for astrobiology data. AHED is intended to store user-contributed results from NASA or externally-funded research in astrobiology, and to encourage sharing and synergy within the astrobiology community. However, the interdisciplinary nature of astrobiology presents some specific challenges to data management, integration, and analysis within AHED. In some disciplines (e.g., genomics), open databases thrive because the contributed products are fairly uniform and standardized (e.g., sequence data). In astrobiology, each investigation produces a unique set of data products; this makes it difficult to search across different datasets to find similar data, or to combine results from separate investigations. With AHED, we are taking steps to ensure there is adequate metadata - both at the dataset and record levels - to facilitate search, integration, and analysis. At the dataset level, we are developing a new metadata standard for describing astrobiology datasets, with detailed information about content, funding source, and scientific relevance, along with a set of topical keywords for characterizing datasets. At the record level, we are encouraging users to provide more structured content and finer-grained metadata. In many user-contributed science data repositories, few restrictions are placed on the uploaded data format, and minimal or no record-level metadata is required; thus users are unburdened when it comes to data preparation. The tradeoff is that deep integration and search across datasets is almost impossible without standardized structures and metadata. Although AHED users are free to upload minimally-described datasets, they will be encouraged to use database authoring tools (supplied by the underlying platform - Open Data Repository's Data Publisher) plus a set of customizable astrobiology-specific templates to help structure their data and provide standardized metadata. In reward for their extra effort, AHED will be able to deliver enhanced search, discovery, and analysis capabilities.

astrobiology↗

NASA NTRSDate not supplied

Open Science for Plants in Space: Improvements in NASA's Open Science Data Repository

Upcoming deep space missions will rely on plants for crew and ecosystem health. Open access space biology data enables scientists to examine the biological responses of plants to ionizing radiation, altered gravity, elevated CO2, and many other abiotic stressors. NASA has declared 2023 as the ‘Year of Open Science’ and created a 5-year Transform to Open Science (TOPS) initiative designed to rapidly transform the agency toward an inclusive culture of open science. NASA’s Open Science Data Repository (OSDR) combines two databases, GeneLab and Ames Life Sciences Data Archive (ALSDA) to maximize access to standardized ‘omics (e.g., transcriptomics, proteomics) and phenotypic data (e.g., microscopy, biomass), respectively. Current OSDR standards include the ISA (Investigation-Study-Assay) experiment model, assay metadata configurations, and standardized terminology and ontologies. In 2024 OSDR will include a new suite of features for improved FAIR compliance including downloadable plant metadata templates, data submission tools and overall improved AI-readiness of plant datasets. AI/ML methods can be helpful tools to overcome the inherent challenges of space biology research (small sample size, sparse and heterogeneous data etc.). However these methods are built on an assumption of normalized and well-curated data. OSDR’s new curation tools will improve users ability to leverage ML and AI methods to model space biology data and better understand the complex effects of spaceflight on living systems across hierarchical biological levels. We look forward to sharing our advances with the spaceflight community.

FAIR↗

NASA NTRS2004

[Analysis of Multiplatform CO (Carbon Monoxide) Measurements During Trace-P Mission]

Carbon monoxide is considered mission critical (TRACE-P NRA) because it is one of the gases involved in controlling the oxidizing power of the atmosphere and, as a tracer gas, is valuable in interpreting mission data sets. Carbon monoxide exhibits interannual differences, suggesting relatively short-term imbalances in sources and sinks. Sources of CO are dominated by fossil fuel combustion, biomass burning, and the photochemical oxidation of CH4 and nonmethane hydrocarbons while reaction with OH is believed to be the major sink for atmospheric CO, with additional losses due to soil uptake. Uncertainties in the magnitude and distribution of both sources and sinks remain fairly large however, and additional data are required to refine the global budget. Seasonal changes and a northern hemispheric latitudinal gradient have been described for a variety of Pacific basin sites through long-term monitoring of surface background levels. Latitudinal variations have also recently been described at upper tropospheric altitudes over a multi-year period by. TRACE-P will provide an aircraft survey of CO over the northern Pacific in the northern spring when CO concentrations are at their seasonal maximum in the northern hemisphere (NH) and at their seasonal minimum in the southern hemisphere (SH). Previous GTE missions, Le., PEM West-B and PEM Tropics-B, ground-based, and satellite observations (MAPS, April 1994) give us a general picture of the distribution of CO over the northern Pacific during this season. Based on these measurements, background CO levels over remote ocean areas are anticipated to be in the range of 110 - 180 ppbv, while those closer to the Asian continent may rise as high as 600 ppbv. These measurements also reveal high spatial variability (both horizontal and vertical) as well as temporal variations in CO over the area planned for the TRACE-P mission. This variability is a result of multiple CO sources, the meteorological complexity of transport processes, and the photochemical aging of air masses. The influence of biomass burning in the southern Pacific should be relatively small since the mission coincides with the southern tropical wet season when agricultural burning is at its seasonal low. The proposed CO measurements taken during TRACE-P should therefore largely be a function of the impact of various NH sources, primarily Asian and predominantly fossil fuel combustion and biomass burning. These processes are also major sources of many other atmospheric pollutants, consequently making accurate and precise CO measurements is one of the highest TRACE-P priorities [TRACE-P NRA]. The TRACE-P mission emphasizes the dual objectives of assessing the magnitude of the transport of chemically and radiatively important gases such as CO from Asia to the western Pacific, and determining how emissions change and are modified during this transport.

Pougatchev, Nikita S.↗

NASA NTRS2002

Summary of Data from the First AIAA CFD Drag Prediction Workshop

The results from the first AIAA CFD Drag Prediction Workshop are summarized. The workshop was designed specifically to assess the state-of-the-art of computational fluid dynamics methods for force and moment prediction. An impartial forum was provided to evaluate the effectiveness of existing computer codes and modeling techniques, and to identify areas needing additional research and development. The subject of the study was the DLR-F4 wing-body configuration, which is representative of transport aircraft designed for transonic flight. Specific test cases were required so that valid comparisons could be made. Optional test cases included constant-C(sub L) drag-rise predictions typically used in airplane design by industry. Results are compared to experimental data from three wind tunnel tests. A total of 18 international participants using 14 different codes submitted data to the workshop. No particular grid type or turbulence model was more accurate, when compared to each other, or to wind tunnel data. Most of the results overpredicted C(sub Lo) and C(sub Do), but induced drag (dC(sub D)/dC(sub L)(exp 2)) agreed fairly well. Drag rise at high Mach number was underpredicted, however, especially at high C(sub L). On average, the drag data were fairly accurate, but the scatter was greater than desired. The results show that well-validated Reynolds-Averaged Navier-Stokes CFD methods are sufficiently accurate to make design decisions based on predicted drag.

Levy, David W.↗

DOE OSTI2025

Confronting Large‐Eddy Simulations With Stereo Camera Data by Means of Reconstructed Hemispheric Cloud Size Distributions

High-resolution hemispheric camera images at a meteorological site in western Germany are used to analyze the multi-dimensional spatial characteristics of continental cumulus cloud fields, and to evaluate Large-Eddy Simulations on this aspect. Traditional non-hemispheric cloud-detecting instruments provide additional reference data. The main model-observation comparison focuses on cloud size distributions (CSDs), employing two methods: (a) directly using three-dimensional model fields, direct CSDs, and (b) using rendered hemispheric images of the model fields as produced by a camera simulator based on path-tracing. In the latter method, both the real and rendered images are used to three-dimensionally reconstruct the cloud fields, yielding hemispheric CSDs. Advantages of hemispheric comparisons over more classic approaches include (a) fair comparisons between model and data, and (b) full use of the enhanced resolutions and hemispheric spatial coverage of the camera imagery. Basic evaluation of the simulations demonstrates good agreement on thermodynamic structure and its diurnal cycle. Cloud heights and cloud cover are intercompared between the model, camera data and other instrumentation, providing insight into their structural differences. A consistent alignment is found between the hemispheric CSDs from both the model and the cameras. Power law fits reveal structurally lower exponents in hemispheric CSDs compared to non-hemispheric CSDs, which particularly caution against directly comparing hemispheric CSDs to non-hemispheric distributions. This result is robust for sample size and fitting method. These findings inform future use of hemispheric camera systems for studying cumulus cloud field morphology and model evaluation.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRSDate not supplied

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge, reduce risk, and support safe, productive human space missions. Through the powerful emerging approaches of artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in biomedical science and engineered astronaut health systems, to enable Earth independence and autonomy of mission operations. Here we present an overview of AI/ML architecture to support deep space mission goals, developed with leaders in the field. First, we focus on the fundamental biological research that supports our understanding of physiological responses to spaceflight, and we describe current efforts to support AI/ML research including data standardization and data engineering through maximally open and FAIR (findable, accessible, interoperable, reusable) databases and the generation of AI-ready datasets for reuse and analysis. We also discuss remote data management frameworks for research data as well as environmental and health data that are generated during deep space missions. We highlight several research projects that leverage data standardization and management for fundamental biological discovery to uncover the complex effects of space travel on living systems. Next, we provide an overview of cutting-edge AI/ML approaches that can be integrated to support remote monitoring and analysis during deep space missions, including generative models and large language models to learn the underlying biomedical patterns and predict outcomes or answer questions during off world medical scenarios. We also describe current AI/ML methods to support this research and monitoring through automated cloud-based labs which enable limited human intervention and closed-loop experimentation in remote settings. These labs could support mission autonomy by analyzing environmental data streams, and would be facilitated through in situ analytics capabilities to avoid sending large raw data files through low bandwidth communications. Finally, in the context of deep space missions with limited communications or access to medical advice from Earth, we describe a solution for integrated, real-time mission biomonitoring across hierarchical levels from continuous environmental monitoring, to wearables and point-of-care devices, to molecular and physiological monitoring. We introduce a precision space health system that will ensure that the future of space health is predictive, preventative, participatory and personalized.

artificial intelligence↗

NASA NTRS1978

Quiet-time plasma irregularities at 1400 km in the cleft region

The quiet north polar cleft at 1400 km was studied by Isis-2 instruments, and data from the retarding potential analyzer and the cylindrical electrostatic probe show that thermal plasma density fluctuations are distributed in a region between 75 deg and 82 deg invariant latitude and approximately dawn to dusk. Cleft shape and shape variations are described. Thermal ions and thermal electrons usually fluctuated together, but suprathermal electrons fluctuated independently. Data on thermal plasma patterns correlates fairly well with observations of soft particles and auroral optical emissions and not as well with measurements of high-energy particles. The data suggest that the energy source for the thermal irregularities is associated with soft particles and that precipitating high-energy particles do not drive the thermal plasma at these altitudes.

Kayser, S. E.↗

NASA NTRS2003

Computations of Internal and External Axisymmetric Nozzle Aerodynamics at Transonic Speeds

Computational Fluid Dynamics (CFD) analyses of axisymmetric circular-arc boattail nozzles have been completed in support of NASA's Next Generation Launch Technology Program to investigate the effects of high-speed nozzle geometries on the nozzle internal flow and the surrounding boattail regions. These computations span the very difficult transonic flight regime, with shock-induced separations and strong adverse pressure gradients. External afterbody and internal nozzle pressure distributions computed with the Wind code are compared with experimental data. A range of turbulence models were examined in Wind, including an Explicit Algebraic Stress model (EASM). Computations on two nozzle geometries have been completed at freestream Mach numbers ranging from 0.6 to 0.9, driven by nozzle pressure ratios (NPR) ranging from 2.9 to 5. Results obtained on converging-only geometry indicate reasonable agreement to experimental data, with the EASM and Shear Stress Transport (SST) turbulence models providing the best agreement. Calculations completed on a converging-diverging geometry involving large-scale internal flow separation did not converge to a true steady-state solution when run with variable timestepping (steady-state). Calculations obtained using constant timestepping (time-accurate) indicate less variations in flow properties compared with steady-state solutions. This failure to converge to a steady-state solution was found to be the result of difficulties in using variable time-stepping with large-scale separations present in the flow. Nevertheless, time-averaged boattail surface pressure coefficient and internal nozzle pressures show fairly good agreement with experimental data. The SST turbulence model demonstrates the best over-all agreement with experimental data.

Dalbello, Teryn↗

NASA NTRS1994

The dilemma of the new-comet flux

The question of the constancy of the flux rate of 'new' comets from the Oort cloud is critical in studies of the origin of comets. The large numbers may be explained by our being in a 'comet shower' or else by a loss of intrinsic brightness by new comets during their first passage through the inner solar system-hence the dilemma. Improvements in the quality and quantity of reliable orbits now make possible fairly precise evaluation of the data involved in the dilemma and a realistic comparison of the two alternatives. If we are in a comet shower, the increase with respect to the last several tens of thousands of years is not more than a factor of 1.8 nor a magnitude loss during first passage of more than 0.85 mag. This applies if new comets are defined as those with periods greater than 10(exp 6) yr. If the limit is set at 2.8 x 10(exp 6) yr, we may not be really in a comet shower and a good fraction of the comets with periods in the range P greater than 10(exp 6) and less than 2.8 x 10(exp 6) yr may be returning comets. The Oort cloud would then be fairly stable to nearly 40,000 AU. If we assume the reality of comet fading in the sense that few new comets are observable on their returns when more distant than 3.0 AU from the Sun, and if we then limit the discussion to comets with perihelion distance q less than 3.0 AU, there is no evidence for a shower.

Whipple, F. L.↗

NASA NTRS2025

Mind the Gap: Addressing Data Gaps and Assessing Noise Mismodeling in LISA

Due to the sheer complexity of the Laser Interferometer Space Antenna (LISA) space mission, data gaps arising from instrumental irregularities and/or scheduled maintenance are unavoidable. Focusing on merger-dominated massive black hole binary signals, we test the appropriateness of the Whittle-likelihood on gapped data in a variety of cases. From first principles, we derive the likelihood valid for gapped data in both the time and frequency domains. Cheap-to-evaluate proxies to p-p plots are derived based on a Fisher-based formalism, and verified through Bayesian techniques. Our tools allow to predict the altered variance in the parameter estimates that arises from noise mismodeling, as well as the information loss represented by the broadening of the posteriors. The result of noise mismodeling with gaps is sensitive to the characteristics of the noise model, with strong low-frequency (red) noise and strong high-frequency (blue) noise giving statistically significant fluctuations in recovered parameters. We demonstrate that the introduction of a tapering window reduces statistical inconsistency errors, at the cost of less precise parameter estimates. We also show that the assumption of independence between inter-gap segments appears to be a fair approximation even if the data set is inherently coherent. However, if one instead assumes fictitious correlations in the data stream, when the data segments are actually independent, then the resultant parameter recoveries could be inconsistent with the true parameters. The theoretical and numerical practices that are presented in this work could readily be incorporated into global-fit pipelines operating on gapped data.

LISA↗