Search NASA⌕ Search

SEARCH · Search NASA

Results for “Linear interpolation”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

SU-G-201-05: Comparison of Different Methods for Output Verification of Eleckta Nucletron’s Valencia Skin Applicators

Purpose: The provided output factors for Elekta Nucletron’s skin applicators are based on Monte Carlo simulations. These outputs have not been independently verified, and there is no recognized method for output verification of the vendor’s applicators. The purpose of this work is to validate the outputs provided by the vendor experimentally. Methods: Using a Flexitron Ir-192 HDR unit, three experimental methods were employed to determine dose with the 30 mm diameter Valencia applicator: first a gradient method using extrapolation ionization chamber (Far West Technology, EIC-1) measurements in solid water phantom at 3 mm SCD was used. The dose was derived based on first principles. Secondly a combination of a parallel plate chamber (Exradin A-10) and the EIC-1 was used to determine air kerma at 3 mm SCD. The air kerma was converted to dose to water in line with TG-61 formalism by using a muen ratio and a scatter factor measured with the skin applicators. Similarly a combination of the A-10 parallel plate chamber and gafchromic film (EBT 3) was also used. The Nk factor for the A-10 chamber was obtained through linear interpolation between ADCL supplied Nk factors for Cs-137 and M250. Results: EIC-1 measurements in solid water defined the outputs factor at 3 mm as 0.1343 cGy/U hr. The combination of A-10/ EIC-1 and A-10/EBT3 lead to output factors of 0.1383 and 0.1568 cGy/U hr, respectively. For comparison the output recommended by the vendor is 0.1659 cGy/U hr. Conclusion: All determined dose rates were lower than the vendor supplied values. The observed discrepancy between extrapolation chamber and film methods can be ascribed to extracameral gradient effects that may not be fully accounted for by the former method.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

MO-DE-207A-10: One-Step CT Reconstruction for Metal Artifact Reduction by a Modification of Penalized Weighted Least-Squares (PWLS)

Purpose: Metal objects create severe artifacts in kilo-voltage (kV) CT image reconstructions due to the high attenuation coefficients of high atomic number objects. Most of the techniques devised to reduce this artifact utilize a two-step approach, which do not reliably yield the qualified reconstructed images. Thus, for accuracy and simplicity, this work presents a one-step reconstruction method based on a modified penalized weighted least-squares (PWLS) technique. Methods: Existing techniques for metal artifact reduction mostly adopt a two-step approach, which conduct additional reconstruction with the modified projection data from the initial reconstruction. This procedure does not consistently perform well due to the uncertainties in manipulating the metal-contaminated projection data by thresholding and linear interpolation. This study proposes a one-step reconstruction process using a new PWLS operation with total-variation (TV) minimization, while not manipulating the projection. The PWLS for CT reconstruction has been investigated using a pre-defined weight, based on the variance of the projection datum at each detector bin. It works well when reconstructing CT images from metal-free projection data, which does not appropriately penalize metal-contaminated projection data. The proposed work defines the weight at each projection element under the assumption of a Poisson random variable. This small modification using element-wise penalization has a large impact in reducing metal artifacts. For evaluation, the proposed technique was assessed with two noisy, metal-contaminated digital phantoms, against the existing PWLS with TV minimization and the two-step approach. Result: The proposed PWLS with TV minimization greatly improved the metal artifact reduction, relative to the other techniques, by watching the results. Numerically, the new approach lowered the normalized root-mean-square error about 30 and 60% for the two cases, respectively, compared to the two-step method. Conclusion: A new PWLS operation shows promise for improving metal artifact reduction in CT imaging, as well as simplifying the reconstructing procedure.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Measurements and analytics of wide-area file transfers over dedicated connections

Distributed scientific and big-data computations are becoming increasingly dependent on access to remote files. Wide-area file transfers are supported by two basic schemes: (i) application-level tools, such as GridFTP, that provide transport services between file systems housed at geographically separated sites, and (ii) file systems mounted over wide-area networks, using mechanisms such as LNet routers that make them transparently available. In both cases, the file transfer performance critically depends on the configuration consisting of host, file, IO, and disk subsystems, which are complex by themselves, as well as on their complex compositions implemented using buffers and IO-network data transitions. We present extensive file transfer rate measurements collected over dedicated 10 Gbps connections with 0-366 ms round-trip times, using GridFTP and XDD file transfer tools, and Lustre file system extended over wide-area networks using LNet routers. Our test configurations are composed of: three types of host systems; XFS, Lustre, and ext3 file systems; and Ethernet and SONET wide-area connections. We present analytics based on the convexity-concavity of throughput profiles which provide insights into throughput and its superior or inferior trend compared to linear interpolations. We propose the utilization-concavity coefficient, a scalar metric that characterizes the overall performance of any file transfer method consisting of specific configuration and scheme. Our results enable performance optimizations by highlighting the significant roles of (i) buffer sizes and parallelism in GridFTP and XDD, and (ii) buffer utilization and credit mechanism in LNet routers.

Rao, Nageswara↗
DOE OSTI2012

Simple Coupling of Reactor Physics Effects and Uncertain Nuances

The "Simple Coupling of Reactor Physics Effects and Uncertain Nuances" (SCORPEUN) code is a simple r-z 1-group neutron diffusion code where each r-mesh is coupled to a single-flow-channel model that represents all flow-channels in that r-mesh. This 1-D model assesses q=m*Cp*deltaT for each z-mesh in that channel. This flow channel model is then coupled to a simple 1-D heat conduction model for ascertaining the peak center-line fuel temperature in a hypothetical pin assigned to that flow channel. The code has property lookup capability for water, Na, Zirc, HT9, metallic fuel, oxide fuel, etc. It has linear interpolation features for microscopic cross-sections with respect to coolant density and fuel temperature. ***This last feature has not been fully tested and may need development***. The interpolated microscopic cross-sections are then combined (using the water density from the T/H calculation) to generate macroscopic diffusion coefficient, removal cross-section and nu-sigmaF for each r-z mesh of the neutron diffusion code.

Bays, Samuel↗
DOE OSTI2021

EKAT v.1.0

E3SM Kokkos Application Toolkit (EKAT) is a collection of C++, Fortran, and CMake utilities for providing a single implementation of common kernels based on the Kokkos programming model. The library contains utilities for vectorization, tridiagonal linear system solvers, and linear interpolation as well as some general-purpose utilities such as testing utilities, parameter lists, representation of physical units, and additional interfaces. The goal is to provide a centralized implementation for high-performance computing structures and common utilities that reduce code duplication and streamline maintenance efforts. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525. SAND2022-1327 O

Bertagna, Luca↗
DOE OSTI2022

WORM (Write One, Read Many)

WORM (Write One, Run Many) is an easy to use, cross platform, embedded and extensible, functional programming language designed to facilitate the creation of input-decks for computer codes that use standard ASCII text files for input. WORM makes it easy to create generic (yet, complex and powerful) reusable models. Additionally its nature allows for complex calculations and routines to be coded once and easily reused, further simplifying the creation of input decks. WORM (Write One, Run Many) is a powerful and versatile tool designed to improve the efficiency of today’s criticality safety analyst by allowing: + input decks for parametric studies to be created quickly and easily, + calculations and variables to be imbedded into any input deck, thus allowing for meaningful parameter specifications, + problems to be specified using any combination of units, and + complex mathematically defined models to be created. A very simple syntax is employed, and therefore the WORM is easy to learn. A WORM model is essentially a standard input deck with some of its numerical values replaced by WORM code. WORM code may include and evaluate the following mathematical operators and functions: addition, subtraction, multiplication, division, exponentiation, modulus, sine, cosine, tangent, arcsine, arccosine, arctangent, the natural logarithm, logarithm base 10, integer truncation, absolute value, and random number. Several common constants, e.g., pi, e, and Avogadros’s Number (both as 6.022e23 and 0.6022), are predefined in WORM. Additionally, many unit conversion factors are also predefined: millimeters, meters, inches, feet, yards, and mils to centimeters; kilograms, pounds, and ounces to grams; liters, milliliters, gallons, and fluid ounces to cubic centimeters; and angular degrees to radians. For parametric studies, WORM supports various shorthand list specifications: the explicit step size, linear interpolation, and logarithmic interpolation. The list notation sequentially assigns multiple values to a name. WORM creates an input deck for each value of the name. If multiple lists are used, WORM steps through each list individually, i.e., WORM creates input decks corresponding to each and every permutation of the list values. Additionally, a library of standard material definitions and Perl subroutines are included. Any one of these files can be incorporated into the subject model with a simple WORM read command. WORM is completely written in Perl, the Practical Extraction and Reporting Language. Perl is one of the most portable programming languages available today. As such, the WORM works on practically any computer platform.

Sartor, Raymond↗
DOE OSTI2012

Reconstructing the South Pacific Convergence Zone Position during the Presatellite Era: A La Niña Case Study

Sixty-four southwest Pacific island meteorological stations were utilized to develop ENSO-related austral warm season (November–April) rainfall climatologies for 1961–90. Historical data for the same station set were then examined for 1955/56, one of the strongest La Niñas of the twentieth century. The pattern for that event was typical of a well-coupled protracted La Niña, with above-normal rainfall (>150%) observed for 17 stations in the case study. Tropical cyclone tracks were also used to illustrate the proximal effects of historical storms on station rainfall. Several stations that were located along the northern edge of the tropical cyclone swarm, but south of a region of anomalously low rainfall, were selected as possible candidates having been close to the mean South Pacific convergence zone (SPCZ) location. Linear interpolations between those stations highlighted a likely SPCZ position for the 1955/56 event. The reconstructed SPCZ location suggested a position southwest of normal, consistent with many La Niñas observed during the satellite era. The 1955/56 SPCZ reconstruction compared favorably with NOAA Cooperative Institute for Research in Environmental Sciences (CIRES) twentieth-century reanalysis (20CR) positions of maximum atmospheric water content and omega (time derivative of pressure that illustrates vertical velocity, and a proxy for convection and SPCZ location) at 500 hPa. Comparisons between Global Precipitation Climatology Project (GPCP) warm season rainfall composite plots for several satellite era La Niñas and one well-coupled La Niña event that occurred during 2010/11 to omega at 500 hPa and maximum rainfall amounts suggest that the 1955/56 reconstruction from in situ rainfall measurements captured the SPCZ location. Our results suggest that use of the 20CR could help to identify hemispheric-scale atmospheric circulation features like the SPCZ and improve understanding of ENSO dynamics prior to the satellite era.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Methodology and Software for Gross Defect Detection of Spent Nuclear Fuel at the Atucha-I Reactor [Novel Methodology and Software for Spent Fuel Gross Defect Detection at the Atucha-I Reactor]

Here, fuel assemblies in the spent fuel pool are stored by suspending them in two vertically stacked layers at the Atucha Unit 1 nuclear power plant (Atucha-I). This introduces the unique problem of verifying the presence of fuel in either layer without physically moving the fuel assemblies. Given that the facility uses both natural uranium and slightly enriched uranium at 0.85 wt% 235 U and has been in operation since 1974, a wide range of burnups and cooling times can exist in any given pool. A gross defect detection tool, the spent fuel neutron counter (SFNC), has been used at the site to verify the presence of fuel up to burnups of 8000 MWd/t. At higher discharge burnups, the existing signal processing software of the tool was found to fail due to nonlinearity of the source term with burnup.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Closed Loop Geothermal Working Group: GeoCLUSTER App, Subsurface Simulation Results, and Publications

To better understand the heat production, electricity generation performance, and economic viability of closed-loop geothermal systems in hot-dry rock, the Closed-Loop Geothermal Working Group -- a consortium of several national labs and academic institutions has tabulated time-dependent numerical solutions and levelized cost results of two popular closed-loop heat exchanger designs (u-tube and co-axial). The heat exchanger designs were evaluated for two working fluids (water and supercritical CO2) while varying seven continuous independent parameters of interest (mass flow rate, vertical depth, horizontal extent, borehole diameter, formation gradient, formation conductivity, and injection temperature). The corresponding numerical solutions (approximately 1.2 million per heat exchanger design) are stored as multi-dimensional HDF5 datasets and can be queried at off-grid points using multi-dimensional linear interpolation. A Python script was developed to query this database and estimate time-dependent electricity generation using an organic Rankine cycle (for water) or direct turbine expansion cycle (for CO2) and perform a cost assessment. This document aims to give an overview of the HDF5 database file and highlights how to read, visualize, and query quantities of interest (e.g., levelized cost of electricity, levelized cost of heat) using the accompanying Python scripts. Details regarding the capital, operation, and maintenance and levelized cost calculation using the techno-economic analysis script are provided. This data submission will contain results from the Closed Loop Geothermal Working Group study that are within the public domain, including publications, simulation results, databases, and computer codes. GeoCLUSTER is a Python-based web application created using Dash, an open-source framework built on top of Flask that streamlines the building of data dashboards. GeoCLUSTER provides users with a collection of interactive methods for streamlining the exploration and visualization of an HDF5 dataset. The GeoCluster app and database are contained in the compressed file geocluster_vx.zip, where the "x" refers to the version number. For example, geocluster_v1.zip is Version 1 of the app. This zip file also contains installation instructions. **To use the GeoCLUSTER app in the cloud, click the link to "GeoCLUSTER on AWS" in the Resources section below. To use the GeoCLUSTER app locally, download the geocluster_vx.zip to your computer and uncompress this file. When uncompressed this file comprises two directories and the geocluster_installation.pdf file. The geo-data app contains the HDF5 database in condensed format, and the GeoCLUSTER directory contains the GeoCLUSTER app in the subdirectory dash_app, as app.py. The geocluster_installation.pdf file provides instructions on installing Python, the needed Python modules, and then executing the app.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Observed and Imputed Volumetric Soil Water Content Timeseries for the New Mexico Elevation Gradient

Reliable soil water content (SWC) data are essential for understanding dryland ecosystem dynamics, but high-frequency SWC sensors often fail, creating gaps in critical datasets. To address this, we developed a Bayesian mixture model that imputes missing SWC using both linear interpolation and an ecosystem water balance model (SOILWAT2), tested across six AmeriFlux eddy covariance tower sites in the New Mexico Elevation Gradient, demonstrating its effectiveness in reconstructing SWC patterns while providing insights into the factors driving SWC variability. Daily volumetric soil water content (SWC) data are provided as csv-formatted spreadsheets for the six AmeriFlux sites (US-Seg, US-Ses, US-Wjs, US-Mpi, US-Vcp, and US-Vcs). For each site there is an observed SWC file (site_SWC_gapfill.csv) and a file that contains imputed SWC (imputed_SWC_site.csv). The observed SWC files contain temperature corrected sensor values, tower precipitation data, as well as outputs from SOILWAT2 simulations that were used to impute SWC. The imputed files contain the original observed SWC values and the imputed missing SWC values. When SWC was missing from the original data, the missing value was imputed based on the Bayesian imputation mixture model. The posterior mean of all imputed values is reported as "mean_X". When the observed SWC was NOT missing, mean_X = observed SWC value (original data). The standard deviation, 2.5th percentile and the 97.5th percentile for the imputed values are also reported in the imputed files. There are readme text files for each file type explaining the contents of each column.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2011

POINT 2011: ENDF/B-VII.1 Beta2 Temperature Dependent Cross Section Library

This report is one in the series of 'POINT' reports that over the years have presented temperature dependent cross sections for the then current version of ENDF/B. In each case I have used my personal computer at home and publicly available data and codes. I have used these in combination to produce the temperature dependent cross sections used in applications and presented in this report. I should mention that today anyone with a personal computer can produce these results. The latest ENDF/B-VII.1 beta2 data library was recently and is now freely available through the National Nuclear Data Center (NNDC), Brookhaven National Laboratory. This release completely supersedes all preceding releases of ENDF/B. As distributed the ENDF/B-VII.1 data includes cross sections represented in the form of a combination of resonance parameters and/or tabulated energy dependent cross sections, nominally at 0 Kelvin temperature. For use in our applications the ENDF/B-VII.1 library has been processed into cross sections at eight neutron reactor like temperatures, between 0 and 2100 Kelvin, in steps of 300 Kelvin (the exception being 293.6 Kelvin, for exact room temperature at 20 Celsius). It has also been processed to five astrophysics like temperatures, 1, 10, 100 eV, 1 and 10 keV. For reference purposes, 300 Kelvin is approximately 1/40 eV, so that 1 eV is approximately 12,000 Kelvin. At each temperature the cross sections are tabulated and linearly interpolable in energy. All results are in the computer independent ENDF-6 character format [R2], which allows the data to be easily transported between computers. In its processed form the POINT 2011 library is approximately 16 gigabyte in size and is distributed on one compressed DVDs (see, below for the details of the contents of each DVD).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2014

Computer Spreadsheet Representation of the Groeneveld Et Al.: 2006 Critical Heat Flux Look-Up Table

The Groeneveld, et al. 2006 Critical Heat Flux Look-Up Table provides values of Critical Heat Flux (CHF) in kW/m 2 for a vertical 8 mm water-cooled tube. The CHF values are a function of pressure, P (100 ≤ P ≤ 21000 kPa), mass flux, G (0≤ G ≤8000 kg/m 2 -s), and quality, X (-0.50 ≤ X ≤ 1.00). Typically, obtaining a value of CHF for a particular triad of P, G, and X within the domain of the table requires looking up eight values of CHF in the table and performing linear interpolation. The purpose of this brief technical memo is to describe and formally transmit a Microsoft Excel ® computer spreadsheet that has been developed to enable one to enter a triad of P, G, and X and obtain the corresponding value of CHF.

Feldman, Earl E.↗
DOE OSTI2017

Method for modeling the gradual physical degradation of a porous material

Cementitious and other engineered porous materials encountered in waste disposals may degrade over time due to one or more mechanisms. Physical degradation may take the form of cracking (fracturing) and/or altered (e.g. increased) porosity, depending on the material and underlying degradation mechanism. In most cases, the hydraulic properties of degrading materials are expected to evolve due to physical changes occurring over roughly the pore to decimeter scale, which is conducive to calculating equivalent or effective material properties. The exact morphology of a degrading material in its end-state may or may not be known. In the latter case, the fully-degraded condition can be assumed to be similar to a more-permeable material in the surrounding environment, such as backfill soil. Then the fully-degraded waste form or barrier material is hydraulically neutral with respect to its surroundings, constituting neither a barrier to nor conduit for moisture flow and solute transport. Unless the degradation mechanism is abrupt, a gradual transition between the intact initial and fully-degraded final states is desired. Linear interpolation through time is one method for smoothly blending hydraulic properties between those of an intact matrix and those of a soil or other surrogate for the end-state.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Development of a Novel Accelerator for Neutron Transport Solution Using the Galerkin Spectral Element Methods (Final Report)

This report summarizes the results of a three-year research project sponsored by the U.S. Department of Energy (DOE) Nuclear Energy University Program (NEUP) to develop and implement advanced acceleration schemes for the DOE NEAMS neutronics code PROTEUSSN. The project team included the University of Massachusetts Lowell, The Ohio State University, University of Michigan, and Argonne National Laboratory. The PROTEUS code is a high-fidelity capable deterministic neutron transport code based on unstructured finite element meshes, which solves the steady-state and transient neutron transport problem using the 2nd-order discrete ordinate method (SN2ND), the method of characteristics (MOC), and the advanced nodal transport method (NODAL). The DSA scheme has been implemented in PROTEUS to speed up SN transport calculations. The existing DSA scheme employs a consistent finite element formulation on the same fine mesh structure as the SN solution While the use of consistent discretizations makes the DSA method effective, it does not necessarily make it efficient because the numerical solution of a discretized elliptic diffusion problem itself can be costly, particularly when the problem size becomes large. We developed a new discontinuous Galerkin (DG) discretization of the diffusion equation, called DG-DSA, which can effectively and efficiently accelerate the SN transport iterations. As compared with the previous work, the novelty of our method is that the diffusion equation is solved on a coarse-mesh grid using the DG methods, and the DG diffusion discretization incorporates local hp adaptation, i.e., local adaptation of mesh size and/or polynomial degree, based on local total cross section (or optical thickness). Therefore, the resulting number of degrees of freedom (DOF) of the DG discretization is much less than the conventional consistent DSA discretizations, and thus DG-DSA can achieve significant improvement in computational efficiency. We implemented this scheme in PROTEUS-SN. In addition, we developed a new stabilization scheme named linear prolongation CMFD (lpCMFD). A novel feature of this scheme is that the conventional flat flux ratio–based scaling approach is replaced with a linear interpolation of the scalar flux differences at the coarse-mesh cell edges between the neutron transport and CMFD calculations. Fourier convergence analysis and numerical results show that lpCMFD is unconditionally stable and more effective than other CMFD based on acceleration schemes such as pCMFD, odCMFD. We also developed a new nonlinear diffusion acceleration scheme for solving neutron transport equations. This scheme, called LR-NDA, employs a local refinement approach on the framework of CMFD by solving a local boundary value problem of the scalar flux on the coarse-mesh structure to replace the piecewise constant scalar flux obtained by CMFD. The refined flux is then used to update the scalar flux in the neutron transport source iteration. It has been demonstrated that that LR-NDA is much more effective and stable than CMFD for a wide range of optical thicknesses. LR-NDA is a local adaptive method, which means LR-NDA does not necessarily require local refinement for all the coarse-mesh cells on the problem domain, i.e., it can be used only for relatively optically thick regions where the standard CMFD scheme would encounter the convergence problem.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Bearing Fault Detection and Wear Estimation Using Machine Learning

Unpredicted bearings failures can be costly and dangerous. Current methods have been examining the use of machine learning algorithms to automatically detect bearing faults. Vibration specialists must react daily, as the sheer number of bearings and the machines they operate are critical and any downtime will result in loss of productivity and endanger personal. The method presented in this paper utilizes a novel approach to detect and determine bearings fault diameters. The detection algorithm uses the cubic support vector machine (SVM) for high accuracy inner and outer race fault detection. After detecting the type of fault, the data is then passed through a second layer that uses a modified K-means clustering and a linear interpolation to accurately estimate the diameter of the fault that was detected.

42 ENGINEERING↗
DOE OSTI2024

Improving Grid Awareness by Empowering Utilities with Machine Learning and Artificial Intelligence

Gap filling time series data typically depends on linear interpolation. More recently gap filling advancements include machine learning techniques. However, none leverage advanced learning approach that uses cohort training or a neighborhood informed approach, which is described in this report. The report also describes a physics informed approach using Reduced Order Models (ROM). There are several methods to capture the nature of the detailed system in aggregated models, however there is a trade-off for these methods developed for multiple applications. These methods have specific requirements and applications that includes consideration of dynamics or covering a larger range of operating conditions, etc. The various methods of aggregation are: 1) Thevenin equivalents for downstream networks 2) Equivalent feeder representation to capture downstream network losses accurately 3) Structured reduced order models for dynamics 4) System identification-based ROM (abstract dynamical model) Methods described in items 1 and 2 above are ideal for steady-state models and useful for this application. Of these two methods, based on the data availability, the targeted application, the reduced order model that is proposed to be developed is the equivalent feeder model representation. This includes a structure of the reduced order model whose parameters can be determined by the system load and losses with the meter measurements.

14 SOLAR ENERGY↗
DOE OSTI2026

LandCast Mosaic: Reconstructing Global Population Distributions, 1975-2025

LandCast Mosaic (LCM) provides a global, high-resolution gridded population dataset spanning 1975–2025, representing annual, scenario-consistent estimates of daytime, nighttime, and ambient population distributions. LCM builds on the 2025 LandScan Mosaic (LSM) population data by backcasting to earlier years using historical changes in built-surface area derived from the Global Human Settlement Layer (GHSL) and authoritative population counts from international datasets. The workflow scales 2025 building-informed gridded population estimates according to observed changes in built surface, applies linear interpolation for intermediate years, and normalizes estimates to match administrative- and country-level totals. The resulting dataset offers consistent, globally gridded population estimates over fifty years, suitable for temporal analyses of population dynamics, disaster risk modeling, and urban planning applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

A Centralized AI Lakehouse Framework for Brain Tumor MRI Classification and Segmentation, University KPI Forecasting, and Water Potability Prediction

In many university and healthcare projects, models are built for very different data types such as tables, institutional time series, and medical images, but they are deployed as separate applications. In this work, that separation made testing and maintenance difficult because each module had its own pipeline and runtime requirements. This paper presents an integrated AI lakehouse-style implementation that runs three model pipelines inside one containerized backend. For medical imaging, we used MRI datasets from IEEE DataPort: a four-class classification set with 7012 images (5708 train/1304 test) and a segmentation set with 3063 image–mask pairs. The classification model (ResNet50 transfer learning) is evaluated using a proper train–validation–test protocol across multiple splits (80/10/10, 70/10/20, 60/10/30, and 10/30/60), achieving a test accuracy of 99.00% under the standard 80/10/10 split. Additionally, a patient-level evaluation is conducted using an external glioma dataset to provide a more realistic assessment without data leakage. The segmentation model (DeepLabV3-ResNet50) achieved 83.09% validation mIoU and 88.79% Dice score. For university KPI forecasting, we used annual IPEDS and NSF HERD data from 2010 to 2023 for three universities (BSU, EOU, and UAB). To examine the effect of preprocessing on forecasting performance, two case studies are conducted. In the first case, linear interpolation is applied to generate semester-level data. In the second case, the original annual data is used directly without interpolation. Random Forest regression and ARIMA models are evaluated using MAE, RMSE, MAPE, and R 2 . The results showed that interpolation improved apparent forecasting performance due to smoothing, while evaluation on the original annual data provided a more realistic assessment of model behavior. To further validate the framework on a larger dataset, an additional case study is conducted using a student dropout dataset. For water potability, we trained and compared multiple tabular classifiers on a large dataset (1,048,575 samples). A Random Forest model (100 trees, max depth 10) achieved 85.86% test accuracy and high recall for unsafe samples (0.8447). All modules are served via FastAPI and deployed together using Docker, with workflow automation routing requests to the correct endpoint. System-level benchmarking indicates that the backend maintains stable throughput and latency under concurrent requests.

97 MATHEMATICS AND COMPUTING↗