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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Evaluating the performance of WRF urban schemes and PBL schemes over Dallas-Fort Worth during a dry summer and a wet summer

This study evaluated the Weather Research and Forecasting (WRF) model sensitivity to different planetary boundary layer (PBL) schemes (the YSU and MYJ schemes) and urban schemes including the bulk scheme (BULK), single-layer urban canopy model (UCM), multi-layer building environment parameterization (BEP) model, and multi-layer building energy model (BEM). Daily reinitialization simulations were conducted over Dallas-Fort Worth during a dry summer month (July 2011) and a wet summer month (July 2015) with weaker (stronger) daytime (nocturnal) UHI in 2011 than 2015. All urban schemes overestimated the urban daytime 2m temperature in both summers, but BEP and BEM still reproduced the daytime urban cool island in dry summer. All urban schemes reproduced the nocturnal urban heat island, with BEP producing the weakest one due to its unrealistic urban cooling. BULK and UCM overestimated the urban canopy wind speed, while BEP and BEM underestimated it. The urban schemes showed prominent impact on daytime PBL profiles. UCM+MYJ showed a superior performance than other configurations. The relatively large (small) aspect ratio between building height and road width in UCM (BEM) was responsible for the overprediction (underprediction) of urban canopy temperature. The relatively low (high) building height in UCM (BEM) was responsible for the overprediction (underprediction) of urban canopy wind speed. Improving urban schemes and providing realistic urban parameters were critical for improving urban canopy simulation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Model America: Data and Models for every U.S. Building

The 5-year goal of the “Model America” concept was to generate a model of every building in the United States. This data repository delivers on that goal with "Model America v1". Oak Ridge National Laboratory (ORNL) has developed the Automatic Building Energy Modeling (AutoBEM) software suite to process multiple types of data, extract building-specific descriptors, generate building energy models, and simulate them on High Performance Computing (HPC) resources. For more information, see AutoBEM-related publications (bit.ly/AutoBEM). There were 125,715,609 buildings detected in the United States. Of this number, 122,146,671 (97.2%) buildings resulted in a successful generation and simulation of a building energy model. This dataset includes the full 125 million buildings. Future updates may include additional buildings, data improvements, or other algorithmic model enhancements in "Model America v2". This dataset contains OSM and IDF zip files for every U.S. county. Each zip file contains the generated buildings from that county. The .csv input data contains the following data fields: 1. ID - the Unique Building Identifier (UBID), generated using the Pacific Northwest National Laboratory (PNNL) BuildingID framework 2. Centroid - building center location in latitude/longitude (from Footprint2D) 3. Footprint2D - building polygon of 2D footprint (lat1/lon1_lat2/lon2_...) 4. State_abbr - state name 5. Area - estimate of total conditioned floor area (ft2) 6. Area2D - footprint area (ft2) 7. Height - building height (ft) 8. NumFloors - number of floors (above-grade) 9. WWR_surfaces - percent of each facade (pair of points from Footprint2D) covered by fenestration/windows (average 14.5% for residential, 40% for commercial buildings) 10. CZ - ASHRAE Climate Zone designation 11. BuildingType - DOE prototype building designation (IECC=residential) as implemented by OpenStudio-standards 12. Standard - building vintage This data is made free and openly available in hopes of stimulating any simulation-informed use case. Data is provided as-is with no warranties, express or implied, regarding fitness for a particular purpose. We wish to thank our sponsors which include Oak Ridge National Laboratory (ORNL) Laboratory Directed Research and Development (LDRD), U.S. Dept. of Energy’s (DOE) Building Technologies Office (BTO), Office of Electricity (OE), Biological and Environmental Research (BER), and National Nuclear Security Administration (NNSA). Update (September 23, 2025): We corrected the ID field in all state-level.csv input files to ensure one-to-one consistency with the corresponding .osm and .idf output files. The schema and file structure are unchanged; only the values in the ID column were modified. No files were added or removed, and the .zip bundles (containing .osm / .idf) are unchanged. The corrected .csv inputs were re-extracted in March 2025 from the original data generated ~ 2021 (Theta supercomputer runs), and published here to align input IDs with model outputs. Update (September 6, 2026): The Model America dataset was updated to replace the previous building ID field with the Unique Building Identifier (UBID), using the Pacific Northwest National Laboratory (PNNL) BuildingID framework. UBIDs provide standardized, location-based identifiers for individual building footprints and improve interoperability with other building and geospatial datasets. The data files containing the previous building identifiers were updated to include UBIDs. This update standardizes building identification; the underlying Model America building characteristics and energy simulation results were not recomputed as part of this update.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Aerial 3D Building Reconstruction from Drone Imagery (A3DBR) v1

This toolkit is composed of several modules for extracting buildings geometrical and thermal characteristics from RGB and thermal imagery captured using a drone. - Building 3D reconstruction module: leverage a photogrammetry software to construct a 3D point cloud from RGB drone imagery, which is then used in conjunction with image processing and geometric methods to extract building footprint and building height (i.e., 3D model of the building). - Windows to wall ratio estimation module: leverage deep learning semantic segmentation modeling to detect windows on 2D drone RGB images. The detected windows are then projected onto the extracted building 3D model (using building 3D reconstruction module) and their area is computed to obtain window to wall ratio estimation. - Thermal anomalies detection module: leverage image processing and machine learning algorithm to detect on 2D drone thermal images potential thermal anomalies within building's facades and roofs.

Granderson, Jessica↗
NASA NTRS1991

Improved disparity map analysis through the fusion of monocular image segmentations

The focus is to examine how estimates of three dimensional scene structure, as encoded in a scene disparity map, can be improved by the analysis of the original monocular imagery. The utilization of surface illumination information is provided by the segmentation of the monocular image into fine surface patches of nearly homogeneous intensity to remove mismatches generated during stereo matching. These patches are used to guide a statistical analysis of the disparity map based on the assumption that such patches correspond closely with physical surfaces in the scene. Such a technique is quite independent of whether the initial disparity map was generated by automated area-based or feature-based stereo matching. Stereo analysis results are presented on a complex urban scene containing various man-made and natural features. This scene contains a variety of problems including low building height with respect to the stereo baseline, buildings and roads in complex terrain, and highly textured buildings and terrain. The improvements are demonstrated due to monocular fusion with a set of different region-based image segmentations. The generality of this approach to stereo analysis and its utility in the development of general three dimensional scene interpretation systems are also discussed.

Perlant, Frederic P.↗
DOE OSTI2025

Demonstrating Advanced Sensors for In-Situ Monitoring Towards Qualification of Nuclear Relevant Components

The U.S. Department of Energy’s Office of Nuclear Energy Advanced Materials and Manufacturing Technologies (AMMT) program is pursuing qualification of laser powder bed fusion (LPBF) components for nuclear applications. A major focus of this effort is the use of in situ process monitoring and machine learning–based tools to establish real-time quality assurance. The primary objective of this report is to identify and evaluate the most relevant in situ sensor systems for LPBF, and to document the deployment of these systems across platforms critical to the AMMT program. This work demonstrates how in situ monitoring can detect process anomalies, track geometry-dependent flaws, and identify limiting combinations of processing parameters—particularly those related to energy density and complex geometries (e.g., overhanging structures). To support this goal, a diverse suite of sensor modalities was evaluated across LPBF platforms, including visible and near-infrared (NIR) imaging, fringe projection profilometry, long-wavelength infrared (LWIR) thermography, and high-speed photodiode/pyrometry systems. These sensor streams were integrated with Peregrine, a machine-agnostic software platform that, among other capabilities, can generate real-time process anomaly classification. This report documents sensor deployments on multiple AMMT flagship platforms, including the Concept Laser M2 and Renishaw AM400/AM250 systems. Calibration builds with complex, flaw-prone geometries such as unsupported overhangs, stepped features, and thin walls, were used to evaluate how well Peregrine and its associated sensors could detect process anomalies and other instabilities under varied energy densities. It will be shown how Peregrine reliably identifies common process anomalies such as recoater streaking, superelevation, etc., and can be used in post-build analysis for anomaly spatial distributions throughout the build height to better understand the impact of geometry and processing parameter choice on the build. This work demonstrates measurable progress toward the vision that components can be born-qualified by establishing a real-time monitoring framework, identifying limiting process conditions, and laying the foundation for sensor fusion–enabled prediction pipelines that are scalable across platforms and applicable to nuclear-relevant components.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Building Fraction and Mean Height for Los Angeles (2010 and 2020) at 30 m Resolution

This dataset provides 30 m resolution spatial layers of building fraction and mean building height for the Los Angeles metropolitan region for 2010 and 2020. Derived from the Model America version 2 building dataset, it represents the distribution of total building footprint area and average building height across the metropolitan region, offering a consistent geospatial resource for urban analysis. The dataset is intended to support applications in urban climate studies, land-use assessment, city-scale modeling, and planning by enabling comparison of urban form characteristics over time. Additional dataset details including data processing details are provided in the Readme document (README_LA_BF_MeanHeight_2010_2020 1.txt).

geospatial↗
NASA NTRS2012

Estimation of the Relationship Between Remotely Sensed Anthropogenic Heat Discharge and Building Energy Use

This paper examined the relationship between remotely sensed anthropogenic heat discharge and energy use from residential and commercial buildings across multiple scales in the city of Indianapolis, Indiana, USA. The anthropogenic heat discharge was estimated with a remote sensing-based surface energy balance model, which was parameterized using land cover, land surface temperature, albedo, and meteorological data. The building energy use was estimated using a GIS-based building energy simulation model in conjunction with Department of Energy/Energy Information Administration survey data, the Assessor's parcel data, GIS floor areas data, and remote sensing-derived building height data. The spatial patterns of anthropogenic heat discharge and energy use from residential and commercial buildings were analyzed and compared. Quantitative relationships were evaluated across multiple scales from pixel aggregation to census block. The results indicate that anthropogenic heat discharge is consistent with building energy use in terms of the spatial pattern, and that building energy use accounts for a significant fraction of anthropogenic heat discharge. The research also implies that the relationship between anthropogenic heat discharge and building energy use is scale-dependent. The simultaneous estimation of anthropogenic heat discharge and building energy use via two independent methods improves the understanding of the surface energy balance in an urban landscape. The anthropogenic heat discharge derived from remote sensing and meteorological data may be able to serve as a spatial distribution proxy for spatially-resolved building energy use, and even for fossil-fuel CO2 emissions if additional factors are considered.

Multi-scale↗
DOE OSTI2026

NATURF: Urban Building Parameters for Chicago, Illinois, USA at a 100m resolution

132 Urban parameters based on building physical dimensions and location were generated for the city of Chicago at 100m resolution using the NATURF model. To use the binary file with WRF, the binary file and the index file must be placed in their own directory in WRF_GEOG and accessed in the same way NUDAPT44 would be accessed.

Vernon, Chris R [Pacific Northwest National Labora↗
DOE OSTI2020

Empirical Validation of Multi-Zone HVAC System Model: Evaluation of Existing Infiltration Models used in Building Energy Simulation

Infiltration can have a significant impact on building loads. Studies have shown that infiltration can account for 15-40% of annual space conditioning needs in commercial buildings (Emmerich et al. 2019; Younes et al. 2012). The driving force of infiltration is the pressure difference across the building envelope caused by wind, the stack effect (known as buoyancy effect), and the operation of ventilation equipment. Wind pressure is governed by wind direction, speed, building shape, and other structures around the building. The stack effect is a function of the building height and air density differences of ambient air (Han, 2015). The effect of wind is dominant in low-rise residential buildings, and the stack effect is dominant in highrise buildings (ASHRAE 2017). In building energy simulation programs (e.g., EnergyPlus), various empirical infiltration models (e.g., the effective leakage area model, the flow coefficient model) are available to simulate infiltration rates. To help users in selecting a proper infiltration model for modeling of the two-story Flexible Research Platform (FRP), the team evaluates the existing infiltration models in EnergyPlus based on field measurements from the FRP. The blower door and tracer gas decay tests were performed in the FRP. The blower door test result was used to estimate input parameters required in the infiltration models. The actual infiltration rates were estimated with the tracer gas decay test results.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Tool for Developing Integrated Strategies for Decontamination and Waste Management - 20291

Management of waste from chemical, biological, and radiological incidents is complicated by the fact that decontamination decisions have a profound impact on the characteristics of resulting waste streams. Wide-area biological and radiological incidents could produce massive quantities of waste that may need to be treated on-site and sent for subsequent disposal as non-contaminated materials, or else be directly disposed of as contaminated materials. The EPA has developed the Waste Estimation Support Tool (WEST) for characterizing and quantifying biological and radiological waste that may be generated from decontamination efforts. This paper focuses on the WEST's uses for radiological incidents. WEST combines Geographic Information System (GIS)-based analysis of externally-supplied plume data, infrastructure databases derived from the Federal Emergency Management Agency's (FEMA's) Hazus tool [1], and satellite imagery surface recognition algorithms to combine the composition and square footage of the buildings in the plume with estimates of the materials between the buildings in the plume. The resulting GIS data files are then imported into a Microsoft Access database application, where they are combined with information about the nature and concentration of contaminants, and then subjected to decontamination strategies for different contaminated surfaces. The tool provides estimates of the type and quantities of potential wastes resulting from simulated decontamination and/or demolition activities and includes estimates of the remaining contamination levels including residual contamination contained within each waste stream. Estimates are presented at several levels of detail, allowing users to obtain needed data at the desired resolution. These include estimates for the total affected area, estimates by contamination zone, estimates by decontamination method(s), and estimates by building type (occupancy classification). EPA is currently developing the next version of WEST which will include several substantial enhancements. The most significant improvement for the next version of WEST will include the ability for users to develop contamination scenarios and waste estimates based on previously developed, readily available, and geographically specific infrastructure data. Instead of using WEST's default infrastructure data based on FEMA's Hazus tool, users will be able to import their own building data specific to the geographically affected area. This capability may substantially decrease uncertainties in the resulting waste estimates because the results will be based on actual building data (numbers of each type, square footage, building height, etc.). Two other significant enhancements will be the ability to generate waste estimates for vehicles and biomass. In addition to building debris and building decontamination waste, vehicles and biomass will likely constitute a significant percentage of the total waste which may result from wide area contamination events. This presentation will present the most recent version of WEST, which includes such considerations as affected biomass (e.g., trees), vehicles, and the ability to replace the default Hazus infrastructure databases with custom infrastructure databases. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Methodology For Determining The Effective Aircraft Impact Area For Irregularly Shaped Facilities

This report presents a computational methodology for determining the effective aircraft impact area for irregularly shaped facilities, extending the approach in Department of Energy (DOE) Standard 3014 by decomposing “critical areas” into multiple rectangular nodes rather than relying on a single bounding cuboid. This method reduces unnecessary conservatism that can arise when non-critical space is enveloped by a single footprint. The facility’s critical areas are partitioned into nodes of constant height, a baseline aircraft impact trajectory is established, and the facility perspective is rotated to accommodate arbitrary heading angles. For each node, analytic expressions are provided to construct the node-specific effective impact polygon that accounts for skid distance, structural footprint, fly-in (shadow) region driven by building height and descent angle, and wingspan offsets capturing wing-only strikes.

42 ENGINEERING↗
DOE OSTI2024

Considering interplay between multiple physical phenomena to elucidate single crystal-like texture, phase transformations, and mechanical behavior of directed energy deposited SS316L

A widespread implementation of large scale additive manufacturing (AM) processes, such as wire arc-directed energy deposition (WA-DED) AM can transform the current manufacturing supply chain networks. Naturally, such implementation requires control of the microstructural attributes, such as texture and phase evolution in the processed alloys. Currently, the texture evolution in fusion-based AM (F-BAM) processes is majorly rationalized by the phenomena occurring only during solidification. However, such rationalization is insufficient for understanding the evolution of primary and secondary crystallographic orientations, and consequently, fails to offer a comprehensive understanding and control of overall texture in F-BAM processed alloys. To this end, we report a single crystal (SX)-like texture in WA-DED processed SS316L for the first time. Furthermore, we assess the physical phenomena that may lead to such unique microstructural evolution during WA-DED AM. Subsequently, using microstructural characterization spanning the build height and thermomechanical simulations we investigate the effect of competitive growth and epitaxial growth occurring during solidification and thermally induced plastic deformation occurring post solidification on the overall texture of WA-DED processed SS316L. A spatial variation in solidification pathway is also established and correlated with variation in undercoolings across the build. Tensile tests revealed a strong orientation dependence of deformation mechanisms with over 110% elongation to failure of specimens deformed along <011>. Such anisotropy is rationalized using Schmid's analysis of dislocation slip and deformation twinning. Importantly, overall, the mechanisms outlined in this work will facilitate an enhanced understanding and subsequent control of texture evolution, solidification behavior and mechanical behavior of WA-DED processed steels.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Upwind Buildings Effects on Test Section Performance of the NFAC 80- by 120-Foot Wind Tunnel

In 2013, a new development began that would put multi-story buildings within the exclusion zone of the 80- by 120- Foot Wind Tunnel (80x120) inlet that exceeded the then existing building height restriction. This raised questions concerning whether the tunnel could operate within the acceptable turbulence limits of ≤ 0.5% in the axial direction over 75% area in the wind tunnel test section. The goal of this testing was to determine the validity of this hypothesis. Testing was performed using the 1/50th-scale model of the 80- by 120-FootWind Tunnel within the full-scale facility test section to characterize the model’s test section turbulence levels as a function of wind direction with the presence of the upwind buildings that are currently being constructed. This paper reports the first testing performed to date on the 80x120 inlet as-built under controlled test conditions for wind magnitude and wind onset direction for a variety of buildings in the inlet external flow field, including no buildings (the control case). This testing determined that, at rated operational conditions the upwind blockages caused no increase in turbulence intensity levels measured in the test section and, in some limited cases, caused the turbulence levels to decrease. Lastly, looking at generic rectangular blockages showed that, to have a discernible effect on test section turbulence levels, scaled 100-ft tall blockages need to be within 600 ft of the existing inlet.

Upwind Buildings Effects↗
DOE OSTI2025

Leveraging Open-Source Satellite-Derived Building Footprints for Height Inference

At a global scale, cities are growing and characterizing the built environment is essential for deeper understanding of human population patterns, urban development, energy usage, climate change impacts, among others. Buildings are a key component of the built environment and significant progress has been made in recent years to scale building footprint extractions from satellite datum and other remotely sensed products. Billions of building footprints have recently been released by companies such as Microsoft and Google at a global scale. However, research has shown that depending on the methods leveraged to produce a footprint dataset, discrepancies can arise in both the number and shape of footprints produced. Therefore, each footprint dataset should be examined and used on a case-by-case study. In this work, we find through two experiments on Oak Ridge National Laboratory and Microsoft footprints within the same geographic extent that our approach of inferring height from footprint morphology features is source agnostic. Regardless of the differences associated with the methods used to produce a building footprint dataset, our approach of inferring height was able to overcome these discrepancies between the products and generalize, as evidenced by 98% of our results being within 3m of the ground-truthed height. This signifies that our approach can be applied to the billions of open-source footprints which are freely available to infer height, a key building metric. This work impacts the broader domain of urban science in which building height is a key, and limiting factor.

Stipek, Clinton [ORNL] (ORCID:0000000280501096)↗
DOE OSTI2023

Areal interpolation of population projections consistent with different SSPs from 1-km resolution to block level based on USA Structures dataset

Population data are normally collected at various census administrative levels, and areal interpolation of population is often required to transform population to the desired spatial resolution. Building footprint datasets, such as Microsoft building footprints, have proven to be useful in estimating population distribution and can therefore be used for areal interpolation of population. In addition to Microsoft building footprints, the recently released USA Structures dataset provides additional information such as building type and building height for some regions, which may provide valuable information for a better depiction of population distribution and improved population areal interpolation accuracy. In this study, we have conducted areal interpolation of population projections consistent with three different Shared Socioeconomic Pathways (SSP2, SSP3, and SSP5) from 1-km grid cells to block level in Washington state for every ten years from 2020 to 2040 based on USA Structures. We assessed USA Structures-based population downscaling accuracy using U.S. decennial survey data in 2020 under three different downscaling schemes, including population downscaling from census tracts to block groups, from census tracts to blocks, and from block groups to blocks. The resulting accuracies were compared with those based on Microsoft building footprints. The comparison showed that USA Structures achieved higher accuracies across different population density regions and areas with different urbanization extent within our study area.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

Computationally inexpensive part-scale thermal history of additive friction-stir deposition

This study presents an analytical model for steady-state power generation and tool heat loss in additive friction-stir deposition (AFSD), developed to enable part-scale thermal simulation while remaining computationally inexpensive. The model predicts total generated power, yielding 3.7–4.7 kW across deposition temperature setpoints of 400–460 °C for the deposition of AA6061 with a Be-Cu tool. This corresponds to 90–95% of the reported spindle power. Tool heat loss is experimentally determined by calibrating a steady-state energy balance between the generated power, the substrate-deposition thermal gradient, and a temperature dependent tool heat loss term: q tool (T) = a + b (T - 400°C) with a = 2.7 x 10 6 Wm -2 and b = 9.5 x 10 3 Wm -2 K -1 . The calibration indicates that about 69% of the generated heat is conducted into the tool for this configuration, which is much higher than previously reported. The calibrated heat-source is implemented in finite element software (Adamantine) to simulate the transient thermal history of a 100 cm 3 representative build in 8 min on a standard desktop (at 0.635 mm build-height resolution). For the first three layers, the substrate temperatures between simulation and experiment are within 10% mean absolute percentage error. Sensitivity analysis indicates that uncertainties in average deposition temperature and deformation localization (stir-zone geometry, depth, and spatial dependance of strain-rate and flow stress) dominate model variance, motivating additional experimental verification.

Additive Friction-Stir Deposition↗
DOE OSTI2022

Numerical and experimental investigation of the geometry dependent layer-wise evolution of temperature during laser powder bed fusion of Ti–6Al–4V

Abstract Laser powder bed fusion (L-PBF) is currently the additive manufacturing process with the widest industrial use for metal parts. Yet some hurdles persist on the way to a widespread industrial serial production, with reproducibility of the process and the resulting part properties being a major concern. As the geometry changes, so do the local boundary conditions for heat dissipation. Consequently, the use of global, geometry-independent processing parameters, which are today’s state of the art, may result in varying part properties or even defects. This paper presents a numerical simulation as a method to predict the geometry-dependent temperature evolution during the build. For demonstration, an overhang structure with varying angles towards the build platform was manufactured using Ti–6Al–4V. A calibrated infrared camera was integrated into a commercial L-PBF system to measure the temperature evolution over time for a total build height of 10 mm, and the results are used for validation of the simulation. It is shown that the simulation is capable of predicting the temperature between layers. The deviations between simulation and measurement remain in single digit range for smaller overhang structures (90°, 60° and 45°). For large overhang structures (30°), the simulation tends to over-predict the temperatures up to 15 °C. Experiments with varying process parameters showed the feasibility of energy reduction as compensation of the heat accumulation produced by overhang structures.

Li, Gefei (ORCID:0000000174837952)↗
DOE OSTI2026

Nondestructive ultrasonic characterization of a triple-weld-bead wire arc additively manufactured ER70S-6 S-curved wall

Understanding build-scale microstructural variation in wire arc additive manufacturing (WAAM) of low-carbon steels is essential for ensuring consistent structure–property relationships throughout large components. Conventional destructive characterization techniques, such as scanning electron microscopy (SEM) and electron backscatter diffraction (EBSD), are time-intensive and limited to localized regions, making comprehensive evaluation of large WAAM structures challenging. In this study, a nondestructive ultrasonic approach was employed to characterize a 252 mm tall ER70S-6 S-curved WAAM wall produced using a triple-bead deposition strategy. Optical and SEM analysis revealed a repeating dual-region microstructure consisting of uniform polygonal ferrite at melt pool centers and heterogeneous ferrite with coarse and fine grains near melt pool boundaries, attributed to cyclic thermal conditions. Longitudinal ultrasonic backscatter imaging was used to evaluate the continuity of this periodicity along the full build height. The ultrasonic response exhibited a consistent repeating pattern that correlated with the observed layer-wise microstructural variation. X-ray computed tomography confirmed the absence of detectable porosity, indicating that ultrasonic contrast is primarily governed by grain morphology. Overall, the results indicate that longitudinal backscatter ultrasound is a promising nondestructive characterization technique for validating microstructural variations along the s-curved WAAM wall, with significant potential for microstructure optimization and process control.

36 MATERIALS SCIENCE↗