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DOE OSTI2026

Thermal Performance of Spandrel Assemblies in Glazed Wall Systems: Laboratory Test Design – Challenges and Test Results

Accurate thermal performance calculation procedures for opaque spandrel areas in curtain wall and window wall systems are essential for rating systems when comparing spandrel systems. However, there is a lack of consensus in thermal modeling needed for accurately characterizing heat transfer through spandrel assemblies due to the complex arrangement of materials and structural components. Several studies indicate that conventional 2D thermal simulations may overestimate R-values by 30% compared to physical testing and 3D simulations. Detailed simulations and well-curated laboratory test data are necessary to build confidence in simulation models, which will later be used to develop correlations to improve widely used conventional 2D thermal simulations. This study aims to experimentally test heat transfer through various spandrel assemblies to validate 3D simulation models. Also, the challenges of conducting a thorough testing design along with the solutions would be documented. The team developed a design for testing spandrel assemblies, making appropriate modifications to the existing heat, air, and moisture (HAM) chamber to accommodate the testing needs. Two moveable baffles were designed and fabricated to guide airflow direction parallel to the test article surface. The data acquisition capabilities in the chamber were upgraded to add more than two hundred sensors to the climate and indoor side of the chamber. The goal is to provide a quality dataset for validating complex 3D modeling simulations, which will be used to develop improved thermal simulation techniques that more accurately represent the thermal behavior of spandrel assemblies and their integration within the building envelope. This paper will summarize the results for the boundary conditions of the testing and the temperature variation across different locations of the spandrel assemblies.

Kunwar, Niraj [ORNL] (ORCID:0000000263457652)↗

NASA NTRS1995

Application of a Navier-Stokes Solver to the Analysis of Multielement Airfoils and Wings Using Multizonal Grid Techniques

A computational study was performed to determine the predictive capability of a Reynolds averaged Navier-Stokes code (CFL3D) for two-dimensional and three-dimensional multielement high-lift systems. Three configurations were analyzed: a three-element airfoil, a wing with a full span flap and a wing with a partial span flap. In order to accurately model these complex geometries, two different multizonal structured grid techniques were employed. For the airfoil and full span wing configurations, a chimera or overset grid technique was used. The results of the airfoil analysis illustrated that although the absolute values of lift were somewhat in error, the code was able to predict reasonably well the variation with Reynolds number and flap position. The full span flap analysis demonstrated good agreement with experimental surface pressure data over the wing and flap. Multiblock patched grids were used to model the partial span flap wing. A modification to an existing patched- grid algorithm was required to analyze the configuration as modeled. Comparisons with experimental data were very good, indicating the applicability of the patched-grid technique to analyses of these complex geometries.

Jones, Kenneth M.↗

NASA NTRS2018

Experimental Calibration of a Numerical Model of Prepreg Tack for Predicting AFP Process Related Defects

Wrinkles, puckers, and fiber bridging are among the major defects encountered in the Automated Fiber Placement (AFP) process, and are all different manifestations of fiber misalignment. The main driver for these defects are the residual stresses introduced in the tow during the deposition stage by the AFP head. In contrast, the tack between the deposited tape and the substrate is the resisting force against the formation of such defects. Tack may be defined as the ability of a material to form a bond immediately on contact with another surface. Tack is a very complex phenomenon that is influenced by a variety of process parameters including temperature, head pressure and speed, as well as degree of cure, moisture content, and surface roughness A physics-based modeling framework for simulation of tack was developed in this study that allows for prediction of tack response. The developed tack model is incorporated in the AFP placement modelling framework developed to simulate AFP defects.

Forghani, Alireza↗

DOE OSTI2020

Stochastic nucleation processes and substrate abundance explain time-dependent freezing in supercooled droplets

Atmospheric immersion freezing (IF), a heterogeneous ice nucleation process where an ice nucleating particle (INP) is immersed in supercooled water, is a dominant ice formation pathway impacting the hydrological cycle and climate. Implementation of IF derived from field and laboratory data in cloud and climate models is difficult due to the high variability in spatio-temporal scales, INP composition, and morphological complexity. We demonstrate that IF can be consistently described by a stochastic nucleation process accounting for uncertainties in the INP surface area. This approach accounts for time-dependent freezing, a wide range of surface areas and challenges phenomenological descriptions typically used to interpret IF. The results have an immediate impact on the current description, interpretation, and experiments of IF and its implementation in models. The findings are in accord with nucleation theory, and thus should hold for any supercooled liquid material that nucleates in contact with a substrate.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2010

RCC Plug Repair Thermal Tools for Shuttle Mission Support

A thermal math model for the Space Shuttle Reinforced Carbon-Carbon (RCC) Plug Repair was developed to increase the confidence in the repair entry performance and provide a real-time mission support tool. The thermal response of the plug cover plate, local RCC, and metallic attach hardware can be assessed with this model for any location on the wing leading edge. The geometry and spatial location of the thermal mesh also matches the structural mesh which allows for the direct mapping of temperature loads and computation of the thermoelastic stresses. The thermal model was correlated to a full scale plug repair radiant test. To utilize the thermal model for flight analyses, accurate predictions of protuberance heating were required. Wind tunnel testing was performed at CUBRC to characterize the heat flux in both the radial and angular directions. Due to the complexity of the implementation of the protuberance heating, an intermediate program was developed to output the heating per nodal location for all OML surfaces in SINDA format. Three Design Reference Cases (DRC) were evaluated with the correlated plug thermal math model to bound the environments which the plug repair would potentially be used.

Rodriguez, Alvaro C.↗

DOE OSTI2022

Multitask Machine Learning of Collective Variables for Enhanced Sampling of Rare Events

Computing accurate reaction rates is a central challenge in computational chemistry and biology because of the high cost of free energy estimation with unbiased molecular dynamics. In this work, a data-driven machine learning algorithm is devised to learn collective variables with a multitask neural network, where a common upstream part reduces the high dimensionality of atomic configurations to a low dimensional latent space and separate downstream parts map the latent space to predictions of basin class labels and potential energies. Here, the resulting latent space is shown to be an effective low-dimensional representation, capturing the reaction progress and guiding effective umbrella sampling to obtain accurate free energy landscapes. This approach is successfully applied to model systems including a 5D Müller Brown model, a 5D three-well model, the alanine dipeptide in vacuum, and an Au(110) surface reconstruction unit reaction. It enables automated dimensionality reduction for energy controlled reactions in complex systems, offers a unified and data-efficient framework that can be trained with limited data, and outperforms single-task learning approaches, including autoencoders.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

UAS remote sensing (3DR SOLO platform): multispectral reflectance and normalized difference vegetation index, Seward Peninsula, Alaska, 2022

Airborne remote sensing data collected using a Parrot Sequoia+ multispectral sensor installed on a 3DR SOLO unoccupied aerial system (UAS) – operated by the Terrestrial Ecosystem Science & Technology group https://www.bnl.gov/envsci/testgroup/ at Brookhaven National Laboratory. This package includes data from 19 flights flown over the NGEE-Arctic, Kougarok Mile Marker (MM) 80, Kougarok Fire Complex (KFC) and Teller MM 27 sites in July 2022. Derived image products include point cloud, ortho-mosaiced multispectral image, a digital surface model (DSM) using the structure from motion (SfM) technique, and a normalized difference vegetation index (NDVI) map. Unprocessed and processed data products are included in this package (processing levels 0-2). Data and metadata are provided as text (*.txt, *.json, *hdr,), tabular (*.dat, *.csv), point cloud (*.laz), Cloud Optimized GeoTIFF (COG, *.tif), and image (*.jpg, *.tif, *png) formats.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1985

Prediction of HiMAT RPRV component interference effects at transonic speeds

Detailed surface flow field analyses of the NASA Highly Maneuverable Aircraft Technology Remotely Piloted Research Vehicle (HiMAT RPRV) are described. Computational predictions are provided by a nonlinear finite difference transonic wing-body code. Component interference effects are obtained through modifications in lifting surface twist and camber boundary conditions. Complex aircraft interactions created by wing-tip fins, landing gear, and lower surface wing actuator fairings are included. Lifting surface viscous flow effects are modeled using a two-dimensional 'strip' boundary layer method. Correlations with flight test data presented demonstrate the high degree of accuracy achieved for this realistic aircraft configuration. This methodology and approach appears to be generally applicable to other multisurface configurations.

Laiosa, J.↗

NASA NTRS1989

Autocorrelation and regularization in digital images. II - Simple image models

The variogram function used in geostatistical analysis is a useful statistic in the analysis of remotely sensed images. Using the results derived by Jupp et al. (1988), the basic second-order, or covariance, properties of scenes modeled by simple disks of varying size and spacing after imaging into disk-shaped pixels are analyzed to explore the relationship betwee image variograms and discrete object scene structure. The models provide insight into the nature of real images of the earth's surface and the tools for a complete analysis of the more complex case of three-dimensional illuminated discrete-object images.

Jupp, David L. B.↗

NASA NTRS1995

Chromatic Image Analysis For Quantitative Thermal Mapping

Chromatic image analysis system (CIAS) developed for use in noncontact measurements of temperatures on aerothermodynamic models in hypersonic wind tunnels. Based on concept of temperature coupled to shift in color spectrum for optical measurement. Video camera images fluorescence emitted by phosphor-coated model at two wavelengths. Temperature map of model then computed from relative brightnesses in video images of model at those wavelengths. Eliminates need for intrusive, time-consuming, contact temperature measurements by gauges, making it possible to map temperatures on complex surfaces in timely manner and at reduced cost.

Buck, Gregory M.↗

NASA NTRS1999

Martian Polar Impact Craters: A Preliminary Assessment Using Mars Orbiter Laser Altimeter (MOLA)

Our knowledge of the age of the layered polar deposits and their activity in the volatile cycling and climate history of Mars is based to a large extent on their apparent ages as determined from crater counts. Interpretation of the polar stratigraphy (in terms of climate change) is complicated by reported differences in the ages of the northern and southern layered deposits. The north polar residual ice deposits are thought to be relatively young, based on the reported lack of any fresh impact craters in Viking Orbiter Images. Herkenhoff et al., report no craters at all on the North polar layered deposits or ice cap, and placed an upper bound on the surface age (or, alternatively, the vertical resurfacing rate) of 100 thousand years to 10 million years, suggesting that the north polar region is an active resurfacing site. In contrast, the southern polar region was found to have at least 15 impact craters in the layered deposits and cap. Plaut et al, concluded that the surface was less than or = 120 million years old. This reported age difference factor of 100 to 1000 increases complexity in climate and volatile modeling. Recent MOLA results for the topography of the northern polar cap document a handful or more of possible craters, which could result in revised age or resurfacing estimates for the northern cap. This study is a preliminary look at putative craters in both polar caps. Additional information is contained in the original extended abstract.

Sakimoto, S. E. H.↗

NASA NTRS2020

The Pliocene Model Intercomparison Project Phase 2: Large-scale Climate Features and Climate Sensitivity

The Pliocene epoch has great potential to improve our understanding of the long-term climatic and environmental consequences of an atmospheric CO2 concentration near ∼400 parts per million by volume. Here we present the large-scale features of Pliocene climate as simulated by a new ensemble of climate models of varying complexity and spatial resolution based on new reconstructions of boundary conditions (the Pliocene Model Intercomparison Project Phase 2; PlioMIP2). As a global annual average, modelled surface air temperatures increase by between 1.7 and 5.2 ∘C relative to the pre-industrial era with a multi-model mean value of 3.2 ∘C. Annual mean total precipitation rates increase by 7 % (range: 2 %–13 %). On average, surface air temperature (SAT) increases by 4.3 ∘C over land and 2.8 ∘C over the oceans. There is a clear pattern of polar amplification with warming polewards of 60∘ N and 60∘ S exceeding the global mean warming by a factor of 2.3. In the Atlantic and Pacific oceans, meridional temperature gradients are reduced, while tropical zonal gradients remain largely unchanged. There is a statistically significant relationship between a model's climate response associated with a doubling in CO2 (equilibrium climate sensitivity; ECS) and its simulated Pliocene surface temperature response. The mean ensemble Earth system response to a doubling of CO2 (including ice sheet feedbacks) is 67 % greater than ECS; this is larger than the increase of 47 % obtained from the PlioMIP1 ensemble. Proxy-derived estimates of Pliocene sea surface temperatures are used to assess model estimates of ECS and give an ECS range of 2.6–4.8 ∘C. This result is in general accord with the ECS range presented by previous Intergovernmental Panel on Climate Change (IPCC) Assessment Reports.

Pliocene Model Intercomparison Project↗

NASA NTRS2021

Planetary Boundary Layer Height Estimates From ICESat-2 and CATS Backscatter Measurements

The lowest layer of the atmosphere in which all human activity occurs is called the Planetary Boundary Layer (PBL). All physical interactions with the surface, such as heat and moisture transport, pollution dispersion and transport happen in this relatively shallow layer. The ability to understand and model the complex interactions that occur in the PBL is very important to air quality, weather prediction and climate modeling. A fundamental and physically important property of the PBL is its thickness or height. This work presents two methods to obtain global PBL height using satellite lidar data from the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) and the Cloud-Aerosol Transport System (CATS). The first method is a straightforward backscatter threshold technique and the second is a machine learning approach known as a Convolutional Neural Network. The PBL height retrievals from the two methods are compared with each other and with PBL height from the NASA GEOS MERRA-2 reanalysis. The lidar-retrieved PBL heights have a high degree of spatial correlation with the model heights but are generally higher over ocean (∼400 m) and over northern hemisphere high latitude regions (∼1,000 m). Over mid-latitude and tropical land areas, the satellite estimated PBL heights agree well with model mid-day estimates. This work demonstrates the feasibility of using satellite lidar backscatter measurements to obtain global PBL height estimates, as well as determining seasonal and regional variability of PBL height.

Stephen P Palm↗

DOE OSTI2025

Reactive Transport Modeling of Hydrogen Production from Serpentinization of Olivine

Hydrogen production from serpentinization of ultramafic rocks represents a promising natural pathway for generating carbon-free energy, yet its kinetics and controlling factors remain incompletely understood. A key challenge in advancing serpentinization research lies in the heterogeneity of porosity and permeability in rocks, which leads to nonuniform fluid velocity fields, as well as uncertainties in estimating reactive surface area and identifying appropriate mineral reaction equilibria. Additional complexities arise from the role of dissolved SiO 2 , Fe 2+ /Fe 3+ partitioning, and the limited effect of pH variations within the strongly alkaline regime on hydrogen yields. These challenges hinder straightforward extrapolation from laboratory tests to practical applications of hydrogen production from natural rocks. Here, in this work, we address these questions using a simulation-based reactive transport modeling framework calibrated against controlled laboratory experiments reported elsewhere. The model couples geochemical kinetics, multiphase flow, and mineralogical feedbacks, enabling systematic evaluation of how surface area, dissolved silica concentration, Fe redox state, temperature, and pressure govern serpentinization and H2 generation. We find that surface area exerts the strongest control on reaction rates and hydrogen yields, while Fe 2+ /Fe 3+ ratios act as secondary modulators. Elevated dissolved silica concentrations suppress hydrogen production but accelerate serpentine precipitation, whereas increasing pH beyond 12 within the strongly alkaline regime produces only marginal gains. Finally, we demonstrate that integrating targeted experiments with calibrated simulations offers a powerful and efficient approach for predicting hydrogen yields and assessing parameter trade-offs in industrial-scale applications. This integration can substantially reduce the experimental burden while improving predictive capability, thereby enhancing both the mechanistic understanding and the practical feasibility of hydrogen production from serpentinization.

08 HYDROGEN↗

DOE OSTI2024

Dynamic embedding of effective harmonic normal mode vibrations in all-atomistic energy gap fluctuations: Case study of light harvesting 2 complex

Environmental effects in excitation energy transfer have mostly been modeled by baths of harmonic oscillators, but to what extent such modeling provides a reliable description of actual interactions between molecular systems and environments remains an open issue. Here, we address this issue by investigating fluctuations in the excitation energies of the light harvesting 2 complex using a realistic all-atomistic simulation of the potential energy surface. Our analyses reveal that molecular motions exhibit significant anharmonic features, even for underdamped intramolecular vibrations. In particular, we find that the anharmonicity contributes to the broadening of spectral densities and substantial overlaps between neighboring peaks, which complicates the meaning of mode frequencies constituting a bath model. Thus, we develop a strategy to construct a minimally underdamped harmonic bath that has a clear connection to all-atomistic dynamics by utilizing actual normal modes of molecules but optimizing their frequencies such that the resulting bath model can best reproduce the all-atomistic simulation results. By subtracting the underdamped contribution from the entire fluctuations, we also show that identifying a residual spectral density representing all other contributions with overdamped behavior is possible. We find that this can be fitted well with a well-established analytic form of a spectral density function or, alternatively, modeled as explicit time dependent fluctuations with muti-exponential or power law type correlation functions. We provide an assessment and the implications of these possibilities. The approach presented here can also serve as a general strategy to construct a simplified bath model that can effectively represent the underlying all-atomistic bath dynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2023

Investigating the Response of Land-Atmosphere Interactions and Feedbacks to Spatial Representation of Irrigation in a Coupled Modeling Framework

The transport of water, heat, and momentum from the surface to the atmosphere is dependent in part on the 10 characteristics of the land surface. Together with the model physics, parameterization schemes, and parameters employed, land datasets determine the spatial variability in land surface states (i.e., soil moisture and temperature) and fluxes. Despite the importance of these datasets, they are often chosen out of convenience or regional limitations without due assessment of their impacts on model results. Irrigation is an anthropogenic form of land heterogeneity that has been shown to alter the land surface energy balance, ambient weather, and local circulations. As such, irrigation schemes are becoming more 15 prevalent in weather and climate models with rapid developments in dataset availability and parameterization scheme complexity. Thus, to address pragmatic issues related to modeling irrigation, this study uses a high-resolution, regional coupled modeling system to investigate the impacts of irrigation dataset selection on land-atmosphere (L-A) coupling using a case study from the Great Plains Irrigation Experiment (GRAINEX) field campaign. The simulations are assessed in the context of irrigated versus non-irrigated regions, subregions across the irrigation gradient, and sub-grid scale process 20 representation in coarser scale models. The results show that L-A coupling is sensitive to the choice of irrigation dataset and resolution and that the irrigation impact on surface fluxes and near surface meteorology can be dominant, conditioned on the details of the irrigation map (i.e., boundaries, heterogeneity, etc), or minimal. A consistent finding across several analyses was that even a low percentage of irrigation fraction (i.e., 4-16%) can have significant local and downstream atmospheric impacts (e.g., lower PBL height), suggesting that representation of boundaries and heterogeneous areas within irrigated 25 regions is particularly important for the modeling of irrigation impacts on the atmosphere in this model. When viewing the simulations presented here as a proxy for ‘ideal’ tiling in a Earth System Model scale gridbox, the results show that some ‘tiles’ will reach critical nonlinear moisture and planetary boundary layer (PBL) thresholds that could be important for clouds and convection, implying that heterogeneity resulting from irrigation should be taken into consideration in new sub-grid land-atmosphere exchange parameterizations.

Patricia Lawston-Parker↗

NASA NTRS2012

Overcoming the Critical Shortage of STEM - Prepared Secondary Students Through Modeling and Simulation

In developing understanding of technological systems - modeling and simulation tools aid significantly in the learning and visualization processes. In design courses we sketch , extrude, shape, refine and animate with virtual tools in 3D. Final designs are built using a 3D printer. Aspiring architects create spaces with realistic materials and lighting schemes rendered on model surfaces to create breathtaking walk-throughs of virtual spaces. Digital Electronics students design systems that address real-world needs. Designs are simulated in virtual circuits to provide proof of concept before physical construction. This vastly increases students' ability to design and build complex systems. We find students using modeling and simulation in the learning process, assimilate information at a much faster pace and engage more deeply in learning. As Pre-Engineering educators within the Career and Technical Education program at our school division's Technology Academy our task is to help learners in their quest to develop deep understanding of complex technological systems in a variety of engineering disciplines. Today's young learners have vast opportunities to learn with tools that many of us only dreamed about a decade or so ago when we were engaged in engineering and other technical studies. Today's learner paints with a virtual brush - scenes that can aid significantly in the learning and visualization processes. Modeling and simulation systems have become the new standard tool set in the technical classroom [1-5]. Modeling and simulation systems are now applied as feedback loops in the learning environment. Much of the study of behavior change through the use of feedback loops can be attributed to Stanford Psychologist Alfred Bandura. "Drawing on several education experiments involving children, Bandura observed that giving individuals a clear goal and a means to evaluate their progress toward that goal greatly increased the likelihood that they would achieve it."

Spencer, Thomas↗

NASA NTRSDate not supplied

Design of a Subscale, Inert Gas Test for Plume-Surface Interactions in a Reduced Pressure Environment

Rocket plume-surface interaction is a multi-phase, complex discipline characterized by plume flow physics, erosion physics, and ejecta dynamics. To provide critical data for the validation of predictive modeling capabilities, an inert-gas, subscale ground test has been designed, with one test phase focused on cratering and ejecta and another test phase focused on plume structure and behavior. Using a supersonic, heated N2 jet impinging onto six different mechanical regolith simulants, visual data on the temporal evolution of cratering and ejecta are collected in a vacuum chamber at ambient pressures ranging from 600 Pa down to approximately 7 Pa. Using the same N2 jet impinging onto an instrumented plate, NO planar laser-induced fluorescence data are obtained at lower ambient pressures for the validation of both continuum and rarefied gas-phase physics. This paper discusses the design of this test and data products, with emphasis on the cratering and ejecta experiments, along with the physical scaling, challenges, and relevance of these data to the maturation of the plume-surface interaction discipline.

Ashley M Korzun↗