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NASA NTRS2026

A Summary of Test and Analysis Results from a Second Lift+Cruise Full-Scale Drop Test

The realization of advanced air mobility markets is enabling new forms of transportation to take shape in the United States and around the world. Though currently in development, as these markets mature, new types of vertical take-off and landing (VTOL) vehicles have been undergoing development for use. There are many factors which must be addressed prior to these types of vehicles becoming viable alternative forms of transportation in these markets. These factors include incorporation into the existing airspaces, the logistics of operating in urban environments, along with numerous factors associated with safety and reliability. To address some of the safety aspects associated with the development of these new types of vehicles, NASA has been conducting research into the performance of an example electric VTOL (eVTOL) aircraft as a part of the Revolutionary Vertical Lift Technology (RVLT) project. Over the course of this research, many aspects including the development of energy absorbing components, the evaluation of seating systems, the development of advanced finite element material model systems and the acquisition of full-scale vehicle impact data were investigated. The report will discuss aspects related to the acquisition of full-scale vehicle data which occurred in the form of a full-scale impact test conducted in the Summer of 2025. This test was on a NASA designed Lift+Cruise composite cabin test article and represented a partial capstone in the entirety of previous eVTOL research conducted for the project. In this test, a variety of experiments were included in order to investigate the effect of a full-scale environment on the experiment results. In parallel, the development of a computational impact model to simulate the full-scale test will be discussed in this report. A model of the Lift+Cruise test article was developed utilizing data collected from previous sub- and full-scale test data and then simulated in the current test environment. The model development, its use in pre-test predictions, and its use in post-test correlation will all be presented. This report will present the test data acquired from the Lift+Cruise test and document several of the results obtained. One intended result is to determine the effect of a complex full-scale crash impact on the identification of occupant injury risk within seat and vehicle designs. A second intended result is to determine whether high-fidelity models can be used with some confidence in the prediction of test events and can allow for additional test cases to be simulated without the need of having to conduct additional tests. The overall goal of the test is to provide the community with data that can be used for design, development or certification efforts, along with providing data on what an example eVTOL crash incident could entail.

energy storage systems↗

DOE OSTI2021

Capacity Investment under Bayesian Information Updates at Reporting Periods: Model and Application

We consider capacity addition decisions by a new product manufacturer faced with uncertain technology alternatives. The manufacturing capacity addition and technology development occurs in parallel, with preliminary results from a technology project's success providing valuable information to the manufacturer in adding capacity. We solve a stochastic dynamic program with Bayesian updates to obtain the manufacturer's expected profit‐maximizing capacity investment decision. Our model and applications are motivated by the Critical Materials Institute (CMI) (funded by the Department of Energy), which manages research projects focused on mitigating critical material constraints, vital to renewable energy technologies such as direct‐drive wind turbines, electric vehicles, and energy‐efficient lighting. We capture three unique aspects of the problem: first, the learning from project progress depends on task‐based stochastic outcomes and a project's percent‐done. Second, the underlying technology's profitability is based on a model of competition. Third, we evaluate the impact of progress across a portfolio of projects based on a manufacturer's capacity addition. We develop a heuristic that produces results that are close to optimal and can thus be used for large problem sizes. The managerial insights from an application of our model to CMI projects include: (i) technology projects that report the percent‐done of a project earlier increase expected manufacturer profit; (ii) careful choice of “safe bets,” that is, technologies with low profitability but a high probability of success, can increase expected manufacturer profit; (iii) a portfolio of projects can increase profits significantly over separate project evaluation; and (iv) dynamic management of project resources can increase overall profit.

Vedantam, Aditya↗

DOE OSTI2024

The carbon challenge: Design, synthesis, and chemisorption behavior of solid sorbents in direct air capture of carbon dioxide

Direct air capture (DAC) of CO 2 is a promising solution for reducing the carbon footprint through "negative emission" technology. However, the low CO 2 concentration (~400 ppm) and the dynamic nature of DAC processes present challenges in designing effective sorbent systems. Recent advancements in material design and structural engineering have led to the development of high-performance solid sorbents, offering a more stable, safe, and energy-efficient alternative to traditional liquid CO 2 capture methods. This review highlights progress in solid sorbent-based DAC, focusing on amine-modified materials, hydrogen-bonded frameworks, and ionic liquid-engineered scaffolds. The discussion covers design principles, synthesis methodologies, and their impact on CO 2 chemisorption, comparing the advantages and limitations of each approach. Characterization techniques, especially operando methods and computational tools, are reviewed to understand sorbent behavior during CO 2 integration and release. The reaction pathways and interaction mechanisms of these sorbents with CO 2 are analyzed to guide future design. Additionally, the CO 2 chemisorption behaviors, including capacity, sorption kinetics, recyclability, and durability in the presence of gaseous impurities and under humid conditions will be evaluated and compared. Further, the review offers unique insights into the physical properties, chemical structures, and surface engineering effects of these sorbents, based on comprehensive characterization and evaluation techniques.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Challenging Common Assumptions of Thick-Wall Chamber Dynamics in Inertial Fusion Systems Using MOOSE-based Multiphysics Simulations

As an increasing number of companies look toward commercial Inertial Fusion Energy (IFE) designs, there is a pressing need to understand the physics of thick-wall chamber gas dynamics. The thick liquid wall approach implements a renewable wall to mitigate the fusion target emissions, thereby reducing the radiation damage rate and significantly extending the lifetime of chamber structures, leading to increased plant availability and reduced waste streams in comparison to dry wall chamber designs. It is necessary, however, to assess the critical performance and safety aspects of these systems. For example, it is crucial to predict (1) where the mass ablated from the liquid walls will vent, which determines the placement of condensing surfaces; (2) debris propagation up the beam lines, which provides essential information for design and protection requirements; (3) peak pressures and impulse on chamber walls, which affect chamber structural design; and (4) momentum transfer to the liquid jets, which constrains the shape and positioning of the jets. In turn, the chamber design and its liquid walls affect shielding requirements, material activation, and tritium fuel cycle. Currently available simulation tools, however, are unable to accurately capture key thick-wall chamber dynamics. Significant assumptions are often made to simplify the system and reduce computational cost and modeling capability needs, but the impact of these assumptions on simulation predictions has not been evaluated. For example, no three-dimensional simulations can be found in the open literature to evaluate gas venting and momentum transfer to the jets with simulations using two-dimensional domains to represent complex three-dimensional geometries. Moreover, limited studies have been dedicated to jet breakup due to both turbulence and neutron heating, and no studies have been found that evaluate how jet breakup can impact shock-jet interaction. Furthermore, effects of radiative heat transfer have rarely been included for the hydrodynamic phase of shock propagation, and integration of proper equations of state in shock dynamics codes has been mostly exploratory. In this study, we use the flexible, high-fidelity Multiphysics Object-Oriented Simulation Environment (MOOSE) to model these complex phenomena and inform design and safety studies. Capabilities to model thick-wall chamber gas dynamics are being developed, and the impact of the assumptions listed above (i.e., two-dimensional vs three-dimensional, absence of jet breakout, no radiative heat transfer, and ideal gas behavior) are being quantified.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Modelling the ejection of primary aerosols during the fast pyrolysis of biomass anisotropic particles

A model for the fast pyrolysis of anisotropic biomass particles is presented which considers bubbling dynamics within the liquid intermediate phase (metaplast) and aerosol ejection from this phase. The model employs the population balance equation and the method of moments to estimate the production rate and resultant size distribution of aerosol ejections, incorporating a detailed CRECK reaction mechanism, and considers the effect of anisotropic biomass microstructure on the intraparticle transport of mass and energy. Here, this study investigates the impact of particle size, heating rate (heat transfer coefficient), and lignocellulosic composition on aerosol ejection. The model predicts that, at high heating rates (convective heat transfer coefficient of 359 W/m 2 .K), aerosols can contribute over 20% to the heavy fraction yield in bio-oil for small particles (1 mm diameter, 4 mm length). The model can predict aerosol size distribution and surface area, indicating an average size of 20 μm for bubbles and 5 μm for aerosols during increased bubble production and aerosol ejection rates. These findings are consistent with prior experimental results and provide essential information for future modeling of extra-particle reactions of the aerosols as they progress through the reactor.

09 BIOMASS FUELS↗

NASA NTRS1986

Dynamic delamination crack propagation in a graphite/epoxy laminate

The dynamic delamination crack propagation behavior during ballistic tests of (90/0)5s T-300/934 graphite/epoxy laminates with embedded interfacial cracks was investigated using high speed photography. The impact on the beam-like specimen was produced with a silicon rubber ball, and the crack propagation speeds and the threshold impact velocities required to initiate dynamic crack propagation were determined for several crack positions. The results suggest that the mode of crack propagation depends on the specimen geometry as well as the loading condition. A simplified finite element analysis of the experimental data obtained from one of the midplane-cracked specimens was used to estimate the critical strain energy release rate, which may determine the onset of unstable crack propagation.

Sun, C. T.↗

DOE OSTI2020

Modeling charging infrastructure impact on the electric vehicle market in China

The plug-in electric vehicle (PEV) is deemed as a critical technological revolution, and the governments are imposing various vehicle policies to promote its development. Meanwhile, the market success of PEVs depends on many aspects. The study reported herein integrates one’s use of charging infrastructure at home, public place and workplace into the market dynamics analysis tool, New Energy and Oil Consumption Credits (NEOCC) model, to systematically assess the charging infrastructure (home parking ratio, public charging opportunity, and charging costs) impact on PEV ownership costs and analyze how the PEV market shares may be affected by the attributes of the charging infrastructure. Compared to the charging infrastructure, the impact of battery costs is incontrovertibly decisive on PEV market shares, the charging infrastructure is still non-negligible in the PEV market dynamics. The simulation results find that the public charging infrastructure has more effectiveness on promoting the PEV sales in the PEV emerging market than it does in the PEV mature market. However, the improvement of charging infrastructure does not necessarily lead to a larger PEV market if the charging infrastructure incentives do not coordinate well with other PEV policies. Besides, the increase of public charging opportunities has limited motivations on the growth of public PEV fleets, which are highly correlated to the number of public fast charging stations or outlets. It also finds that more home parking spaces can stimulate more sales of personal plug-in hybrid electric vehicles instead of personal battery electric vehicles.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Potential Impacts of Dynamic Electricity Pricing in California: Load Shape and Customer Bill Impacts Under Elastic Customer Response

The increasing penetration of renewable energy in California has intensified grid management challenges, exemplified by the “duck curve” and the resulting need for steep ramping and curtailment of renewables. To address these issues, dynamic electricity tariffs that vary in near-real time are being considered to incentivize customers to shift demand and support the grid. This study extends previous work on the bill impacts of such tariffs in the absence of load response by quantifying the system-level and customer impacts of load response based on customer price elasticity. Customer-level load response modeling was conducted using meter data from 411,000 customers across residential, commercial, and industrial sectors. Customer demand elasticity was estimated using literature-based values, with scenarios ranging from low to high elasticity, including an automation-enhanced scenario. Results indicate that universal adoption of, and response to, dynamic tariffs can significantly reduce peak net load (by 15%) and maximum ramping requirements (by 20%) with moderate elasticity, delivering demand response resources comparable to or exceeding current programs at all elasticity levels. Bill analysis shows that, when responding elastically to dynamic prices, most non-PV customers experience modest savings, while PV customers may see higher effective rates due to lower compensation for exports during low-price periods. Emissions analysis reveals a reduction in per-kWh emissions system-wide, with a total absolute load increase of 2% accompanied by a negligible absolute emissions increase. The study concludes that while dynamic tariffs offer substantial grid benefits, customer bill savings under modeled response behaviors may be too modest to drive widespread adoption without additional incentives or enabling technologies. Future research should model flexible loads and advanced control technologies with greater fidelity to better represent the potential opportunities of dynamic tariffs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Direct implicit and explicit energy-conserving particle-in-cell methods for modeling of capacitively coupled plasma devices

Achieving large-scale kinetic modeling is a crucial task for the development and optimization of modern plasma devices. With the trend of decreasing pressure in applications, such as plasma etching, kinetic simulations are necessary to self-consistently capture the particle dynamics. The standard, explicit, electrostatic, momentum-conserving particle-in-cell method suffers from restrictive stability constraints on spatial cell size and temporal time step, requiring resolution of the electron Debye length and electron plasma period, respectively. This results in a very high computational cost, making the technique prohibitive for large volume device modeling. We investigate the direct implicit algorithm and the explicit energy conserving algorithm as alternatives to the standard approach, both of which can reduce computational cost with a minimal (or controllable) impact on results. These algorithms are implemented into the well-tested EDIPIC-2D and LTP-PIC codes, and their performance is evaluated via 2D capacitively coupled plasma discharge simulations. The investigation reveals that both approaches enable the utilization of cell sizes larger than the Debye length, resulting in a reduced runtime, while incurring only minor inaccuracies in plasma parameters. The direct implicit method also allows for time steps larger than the electron plasma period; however, care must be taken to avoid numerical heating or cooling. It is demonstrated that by appropriately adjusting the ratio of cell size to time step, it is possible to mitigate this effect to an acceptable level.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

An Overview of Electric Vehicle Load Modeling Strategies for Grid Integration Studies

The adoption of electric vehicles (EVs) has emerged as a solution to reduce greenhouse gas emissions in the transportation sector, which has motivated the implementation of public policies to promote their use in several countries. However, the high adoption of EVs poses challenges for the electricity sector, as it would imply an increase in energy demand and possible impacts on the power quality (PQ) of the power grid. Therefore, it is important to conduct EV integration studies in the power grid to determine the amount that can be incorporated without causing problems and identify the areas of the power sector that will require reinforcements. Accurate EV load patterns are required for this type of study that, through mathematical modeling, reflect both the dynamic behavior and the factors that influence the decision to recharge EVs. This article aims to present an overview of EVs, examine the different factors considered in the literature for modeling EV load patterns, and review modeling methods. EV load modeling methods are classified into deterministic, statistical, and machine learning. The article shows that each modeling method has its advantages, disadvantages, and data requirements, ranging from simple load modeling to more accurate models requiring large datasets.

Computer Science↗

DOE OSTI2024

Challenging Common Assumptions of Thick-Wall Chamber Dynamics in Inertial Fusion Systems using MOOSE

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Aggregation of Inverter-Based Resources for Modeling and Simulation

In order to conduct system dynamic studies, it is necessary to have dynamic models of both inverter and plant levels. Detailed and aggregated modeling approaches are two essential options. The detailed modeling method involves capturing the dynamic characteristics of each individual device (e.g., wind turbine or PV array), as well as their interconnections. However, as the scale of the IBR plant increases, the complexity and computation time required for detailed modeling also increase. On the other hand, aggregated modeling offers a more efficient way of representing large-scale IBRs in power system dynamic studies. This approach involves aggregating a large number of wind turbines, PV arrays, inverters, and/or plant controllers into one or a smaller number of equivalent models. In order to analyze the impact of a high-level IBR penetration in power systems, it is important to develop accurate and computationally efficient models for both the detailed and aggregated methods.

14 SOLAR ENERGY↗

DOE OSTI2022

The Critical Need for Innovations in Instruments and Techniques to Enable In-Situ Cold Ion and Cold Electron Measurements within the Magnetosphere

Relatively few studies have focused on the cold plasma populations of the magnetosphere due to difficulties associated with obtaining measurements. The cold particle populations are defined here as those with total energy approximately <100 eV which is an energy range for which measurements are difficult (regardless of species), but which often make up the bulk of the plasma density. These populations have known and suspected impacts on the structure and dynamics of the magnetosphere. Unfortunately, the lack of accurate measurements of the cold ion and cold electron populations through the magnetosphere makes closure of these science questions extremely difficult if not impossible. In a complex system of interconnected parts like the Earth’s magnetosphere, a lack of understanding of one part of the system (the cold electron and ion populations) is disabling. Hence, until cold electron and cold ion measurements are obtained robustly with every mission, the magnetospheric plasma environment cannot be completely understood. This will require innovations in plasma spectrometers and associated techniques required to obtain high-fidelity in-situ measurements of the cold ion and cold electron populations in the magnetosphere. This paper seeks to review the instruments and techniques that have been used to date and present possible options for future missions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2020

Photoexcited energy relaxation and vibronic couplings in π-conjugated carbon nanorings

Conjugated carbon nanorings exhibit unique photophysical properties that, combined with their tunable sizes and conformations, make them suitable for a variety of practical applications. These properties are intimately associated to their strained, bent and sterically hindered cyclic structures. Herein we perform a comparative analysis of the photoinduced dynamics in carbon nanorings composed of nine phenyl units([9]CPP) and nine naphthyl units ([9]CN) respectively. The sterically demanding naphthyl units lead to large dihedral angles between neighboring units. Nevertheless, the ultrafast electronic and vibrational energy relaxation and redistribution is found to be similar for both systems. We observe that vibronic couplings, introduced by nonadiabatic energy transfer between electronic excited states, ensure the intramolecular vibrational energy redistribution through specific vibrational modes. The comparative impact of the internal conversion process on the exciton spatial localization and intra-ring migration indicates that naphthyl units in [9]CN achieve more efficient but less dynamical self-trapping compared to that of phenyl units in [9]CPP. That is, during the photoinduced process, the exciton in [9]CN is more static and localized than the exciton in [9]CPP. Furthermore, the internal conversion processes take place through a specific set of middle- to high-frequency normal modes, which directly influence the spatial exciton redistribution during the internal conversion, self-trapping and intra-ring migration.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Assessing VQLS for Fluid Dynamics on a Hybrid Quantum-HPC Stack

Recent advances in quantum linear solvers offer a promising direction for accelerating extreme scientific computations such as fluid dynamics. However, the deep and complex circuits required by many quantum algorithms limit their practical use on current quantum hardware. The Variational Quantum Linear Solver (VQLS) presents a viable alternative for near-term quantum devices (NISQ), and initial efforts have explored its application to select fluid dynamics problems. In this work, we evaluate the use of VQLS for canonical fluid dynamics problems, aiming to identify pathways for generalizing its implementation across a broader class of systems. We analyze the impact of various circuit ansatz and classical optimizers on solution quality and convergence behavior. Furthermore, we assess the algorithm's feasibility within a hybrid quantum–high-performance computing (HPC) framework by porting it to QFw, a state-of-the-art quantum-HPC software stack. 11This manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan. This research used resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the US DOE under Contract No. DE-AC05-00OR22725.

Gopalakrishnan Meena, Murali [ORNL] (ORCID:0000000↗

DOE OSTI2021

Grand Challenges of Hydrologic Modeling for Food-Energy-Water Nexus Security in High Mountain Asia

Climate-influenced changes in hydrology affect water-food-energy security that may impact up to two billion people downstream of the High Mountain Asia (HMA) region. Changes in water supply affect energy, industry, transportation, and ecosystems (agriculture, fisheries) and as a result, also affect the region's social, environmental, and economic fabrics. Sustaining the highly interconnected food-energy-water nexus (FEWN) will be a fundamental and increasing challenge under a changing climate regime. High variability in topography and distribution of glaciated and snow-covered areas in the HMA region, and scarcity of high resolution (in-situ) data make it difficult to model and project climate change impacts on individual watersheds. We lack basic understanding of the spatial and temporal variations in climate, surface impurities in snow and ice such as black carbon and dust that alter surface albedo, and glacier mass balance and dynamics. These knowledge gaps create challenges in predicting where and when the impact of changes in river flow will be the most significant economically and ecologically. In response to these challenges, the United States National Aeronautics and Space Administration (NASA) established the High Mountain Asia Team (HiMAT) in 2016 to conduct research to address knowledge gaps. This paper summarizes some of the advances HiMAT made over the past 5 years, highlights the scientific challenges in improving our understanding of the hydrology of the HMA region, and introduces an integrated assessment framework to assess the impacts of climate changes on the FEWN for the HMA region. The framework, developed under a NASA HMA project, links climate models, hydrology, hydropower, fish biology, and economic analysis. The framework could be applied to develop scientific understanding of spatio-temporal variability in water availability and the resultant downstream impacts on the FEWN to support water resource management under a changing climate regime.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

High strain rate deformation of aged TRIP Ti-10V-2Fe-3Al (wt.%) examined by in-situ synchrotron X-ray diffraction

Transformation Induced Plasticity (TRIP) is a promising avenue for tailoring the work hardening response of metastable $β$ titanium (Ti) alloys. Here we show that aged TRIP Ti-10V-2Fe-3Al (wt.%) maintains higher elongations and flow stresses as strain rate increases, if phase stability and microstructural characteristics are tuned. Low temperature aging influences the matrix $β$ phase stability by $ω$ phase precipitation, which affords a promising way to impact the TRIP effect and obtain desirable mechanical properties, ranging from high damping capacity to good strength/ductility combinations. Although TRIP is active during quasi-static and dynamic testing up to 2000 s –1 , increasing aging time and/or strain rate reduces the overall propensity for the TRIP effect and extent of transformation, which occurs rapidly just at the onset of yielding. Importantly, TRIP with $ω$ phase precipitation provides interesting alloying, microstructure, and property design strategies for engineering applications like lightweight protective structures, where high strains and the need for energy absorption are encountered.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Modeling ash deposition and shedding during oxy-combustion of coal/rice husk blends at 70% inlet O2

Abstract Co-firing rice husk (RH) and coal with carbon capture using oxy-combustion presents a net carbon negative energy production opportunity. In addition, the high fusion temperature of the non-sticky, silica rich, RH can mitigate ash deposition as well as promote shedding of deposits. To identify the optimum operating conditions, fuel particle sizes, and blend ratios that minimize ash deposition, a Computational Fluid Dynamic methodology with add-on ash deposition and shedding models were employed to predict outer ash deposition and shedding rates during co-combustion of coal/RH in AIR and O 2 /CO 2 (70/30 vol%, OXY70) oxidizer compositions. After ensuring that the fly-ash particle size distributions and particle Stokes numbers near the deposition surface were accurately represented (to model impaction), appropriate models for coal ash and RH ash viscosities that were accurate in the temperature region (1200–1300 K) of interest in this study were identified. A particle viscosity and kinetic energy (PKE) based capture criterion was enforced to model the ash capture. An erosion/shedding criterion that takes the deposit melt fraction and the energy consumed during particle impact into account was also implemented. Deposition rate predictions as well as the deposition rate enhancement (OXY70/AIR) were in good agreement with measured values. While the OXY70 scenario was associated with a significant reduction (60%–70%) in flue gas velocities, it also resulted in larger fly-ash particles. As a result, the PKE distributions of the erosive RH ash were similar in both scenarios and resulted in similar shedding rates.

Energy & Fuels↗