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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 OSTI2023

Factors influencing mode choice of adults with travel-limiting disability

Introduction: Despite the plethora of research devoted to analyzing the impact of disability on travel behavior, not enough studies have investigated the varying impact of social and environmental factors on the mode choice of people with disabilities that restrict their ability to use transportation modes efficiently. This research gap can be addressed by investigating the factors influencing the mode choice behavior of people with travel-limiting disabilities, which can inform the development of accessible and sustainable transportation systems. Additionally, such studies can provide insights into the social and economic barriers faced by this population group, which can help policymakers to promote social inclusion and equity. Method: This study utilized a Random Parameters Logit model to identify the individual, trip, and environmental factors that influence mode selection among people with travel-limiting disabilities. Here, using the 2017 National Household Travel Survey data for New York State, which included information on respondents with travel-limiting disabilities, the analysis focused on a sample of 8,016 people. In addition, climate data from the National Oceanic and Atmospheric Administration were integrated as additional explanatory variables in the modeling process. Results: The results revealed that people with disabilities may be inclined to travel longer distances walking in the absence of suitable accommodation facilities for other transportation modes. Furthermore, people were less inclined to walk during summer and winter, indicating a need to consider weather conditions as a significant determinant of mode choice. Moreover, low-income people with disabilities were more likely to rely on public transport or walking. Conclusion: Based on this study’s findings, transportation agencies could design infrastructure and plan for future expansions that is more inclusive and accessible, thus catering to the mobility needs of people with travel-limiting disabilities.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

The Effect of Prosumer Duality on Power Market: The Effect of Market Regulation

Electricity prosumers are energy subsystems that not only consume, but also produce electricity. They are present in distribution level networks as traditional utility customers who have installed distributed energy resources. They are also present in transmission level networks as large conglomerates own both generation assets and large industrial loads. Previous work on the economics of prosumers has demonstrated that prosumers in a market have incentives to behave more competitively compared to producers and consumers in traditional markets. This paper further explores the behavior of prosumers and their response to market policies including the allocation of network losses and the impact of net metering. We extend a Cournot model of a dual prosumer and find that prosumers respond with higher supply quantities if network losses are allocated to demand base. They respond with lower supply quantities if network losses are allocated to supply base. Allocating network losses to demand base also causes equilibrium prices to decline. Markets where prosumers first satisfy their own load and then sell the balance of electricity to the grid have lower quantities and higher prices compared to markets where prosumers buy and sell at locational marginal price.

Tsybina, Eve↗
DOE OSTI2021

A Circular Economy for Lithium-Ion Batteries Used in Mobile and Stationary Energy Storage: Drivers, Barriers, Enablers, and U.S. Policy Considerations

As large-format battery energy storage (BES) capacity increases in the United States, so will the volume of spent lithium-ion batteries (LiBs) (Bade 2019). Estimates based on a 10-year lifetime assumption found that the volume of LiBs that have reached the end of their utility for electric vehicle (EV) applications could total two million units (four million metric tons) annually by 2040 in the United States (Richa et al. 2014; Ai and Borucki 2018). Although there is currently no publicly available decommissioning or end-of-life (EoL) projection for stationary BES systems, the U.S. energy storage market is expected to grow from an annual deployment of 523 megawatts in 2013 to 7.3 gigawatts in 2025 (Wood MacKenzie and ESA 2020; Wesoff 2020). Despite potential secondary market opportunities and the potential benefits associated with the reuse/recovery of LiB material, anecdotal evidence suggests that in the United States most decommissioned LiBs from EVs are landfilled or otherwise disposed of (Steward et al. 2019; Salim et al. 2019; CPUC 2019; DTSC 2019d; NREL 2019b; Jacoby 2019; DOE 2019). The reuse of large-format LiBs is not at commercial scale and to date consists of only a handful of U.S.-led pilot projects. Similarly, less than 5% of LiBs from EVs are sent to recycling facilities in the United States (Steward et al. 2019; Jacoby 2019; America Made 2019; Patel 2017). As awareness of current practices grows, and the demand for critical LiB materials increases, U.S. industry stakeholders, regulators, and policymakers are starting to (1) consider solutions to drive and enable environmentally sustainable materials management decisions and behaviors and (2) identify barriers to a circular economy for LiBs (Figure 1). Circular economy principles (Figure 1) attempt to transition from a “take-make-consume-dispose” linear economic system to a circular system that allows for the long life, high performance, and the reuse/recovery of products and materials (Ellen MacArthur Foundation 2016). We begin this report by summarizing drivers, barriers, and enablers to a circular economy for LiBs used in mobile and stationary BES systems in the United States. We then report on our analysis of federal and state regulatory considerations that may impact the reuse/recovery and disposal of LiBs, and potential civil and criminal liabilities associated with noncompliance. We conclude by highlighting state policies and initiatives in the United States that expressly address reuse/recovery and disposal of large-format LiBs. Our results are based on legal and literature-based research and interviews with mobile and stationary BES industry stakeholders, regulators, and policymakers. While this report addresses stationary BES, as well as mobile BES, much of the information and experience with LiB decommissioning and EoL material management is derived from the increasing management of spent EV LiBs in the United States.

25 ENERGY STORAGE↗
NASA NTRS2003

Buoyancy Effects in Fully-Modulated, Turbulent Diffusion Flames

Pulsed combustion appears to have the potential to provide for rapid fuel/air mixing, compact and economical combustors, and reduced exhaust emissions. The objective of this experiment (PuFF, for Pulsed-Fully Flames) is to increase the fundamental understanding of the fuel/air mixing and combustion behavior of pulsed, turbulent diffusion flames by conducting experiments in microgravity. In this research the fuel jet is fully-modulated (i.e., completely shut off between pulses) by an externally controlled valve system. This gives rise to drastic modification of the combustion and flow characteristics of flames, leading to enhanced fuel/air mixing compared to acoustically excited or partially-modulated jets. Normal-gravity experiments suggest that the fully-modulated technique also has the potential for producing turbulent jet flames significantly more compact than steady flames with no increase in exhaust emissions. The technique also simplifies the combustion process by avoiding the acoustic forcing generally present in pulsed combustors. Fundamental issues addressed in this experiment include the impact of buoyancy on the structure and flame length, temperatures, radiation, and emissions of fully-modulated flames.

Hermanson, J. C.↗
NASA NTRS2020

Thermal Analysis, Compressibility, and Decomposition of Synthetic Bastnäsite-(La) to Lanthanum Oxyfluoride

Understanding basic material properties of rare earth element (REE) bearing minerals such as their phase stability and equations of state can assist in understanding how economically viable deposits might form. Bastnäsite is the most commonly mined REE bearing mineral. We synthesized the lanthanum-fluoride end member, bastnäsite-(La) (LaCO3F), and investigated its thermal behavior and decomposition products from 298 K to 1173 K under ambient pressure conditions through thermogravimetric analysis, differential scanning calorimetry, evolved gas analysis, and high temperature powder X-ray diffraction. We also investigated the compressibility of bastnäsite-(La) via single crystal X-ray diffraction in diamond anvil cells at an ambient temperature up to 11.3 GPa and from 4.9 GPa to 7.7 GPa up to 673 K. At ambient pressure, bastnäsite-(La) was stable up to 598 K in air, where it decomposed into CO2 and tetragonal γ-LaOF. Above 948 K, cubic α-LaOF is stable. High temperature X-ray diffraction data were used to fit the Fei thermal equation of state and the thermal expansion coefficient α(sub 298) for all three materials. Bastnäsite-(La) was fit from 298 K to 723 K with V(sub 0) = 439.82 Å(exp 3), α(sub 298) = 4.32 × 10(exp -5) K(exp -1), a(sub 0) = −1.68 × 10(exp -5) K(exp -1), a(sub 1) = 8.34 × 10(exp -8) K(exp -1), and a(sub 2) = 3.126 K(exp -1). Tetragonal γ-LaOF was fit from 723 K to 948 K with V(sub 0) = 96.51 Å(exp 3), α(sub 298) = 2.95×10(exp -4) K(exp -1), a(sub 0) = −2.41×10(exp -5) K(exp -1), a(sub 1) = 2.42×10(exp -7) K(exp -1), and a(sub 2) = 41.147 K(exp -1). Cubic α-LaOF was fit from 973 K to 1123 K with V(sub 0) = 190.71 Å(exp 3), α(sub 298) = −1.12×10(exp -5) K(exp -1), a(sub 0) = 2.36×10(exp -4) K(exp -1), a(sub 1) = −1.73 × 10(exp -7) K(exp -1), and a(sub 2) = −17.362 K(exp -1). An ambient temperature third order Birch–Murnaghan equation of state was fit with V(sub 0) = 439.82 Å(exp 3), K(sub 0) = 105 GPa, and K’ = 5.58.

Bastnäsite↗
DOE OSTI2024

Important Role of Ion Flux Regulated by Separators in Lithium Metal Batteries

Abstract Polyolefin separators are the most common separators used in rechargeable lithium (Li)‐ion batteries. However, the influence of different polyolefin separators on the performance of Li metal batteries (LMBs) has not been well studied. By performing particle injection simulations on the reconstructed three‐dimensional pores of different polyethylene separators, it is revealed that the pore structure of the separator has a significant impact on the ion flux distribution, the Li deposition behavior, and consequently, the cycle life of LMBs. It is also discovered that the homogeneity factor of Li‐ion toward Li metal electrode is positively correlated to the longevity and reproducibility of LMBs. This work not only emphasizes the importance of the pore structure of polyolefin separators but also provides an economic and effective method to screen favorable separators for LMBs.

25 ENERGY STORAGE↗
DOE OSTI2020

Analyzing the Validity of Brazilian Testing Using Digital Image Correlation and Numerical Simulation Techniques

Characterizing the mechanical behavior of rocks plays a crucial role to optimize the fracturing process in unconventional reservoirs. However, due to the intrinsic anisotropy and heterogeneity in unconventional resources, fracture process prediction remains the most significant challenge for sustainable and economic hydrocarbon production. During the deformation tracking under compression, deploying conventional methods (strain gauge, extensometer, etc.) is insufficient to measure the deformation since the physical attachment of the device is restricted to the size of the sample, monitoring limited point-wise deformation, producing difficulties in data retrieval, and a tendency to lose track in failure points, etc. Where conventional methods are limited, the application of digital image correlation (DIC) provides detailed and additional information of strain evolution and fracture patterns under loading. DIC is an image-based optical method that records an object with a camera and monitors the random contrast speckle pattern painted on the facing surface of the specimen. To overcome the existing limitations, this paper presents numerical modeling of Brazilian disc tests under quasi-static conditions to understand the full-field deformation behaviors and finally, it is validated by DIC. As the direct tensile test has limitations in sample preparation and test execution, the Brazilian testing principle is commonly used to evaluate indirectly the tensile strength of rocks. The two-dimensional numerical model was built to predict the stress distribution and full-field deformation on Brazilian disc under compression based on the assumptions of a homogenous, isotropic and linear elastic material. The uniaxial compression test was conducted using the DIC technique to determine the elastic properties of Spider Berea sandstone, which were used as inputs for the simulation model. The model was verified by the analytical solution and compared with the digital image correlation. The numerical simulation results showed that the solutions matched reasonably with the analytical solutions where the maximum deviation of stress distribution was obtained as 14.59%. The strain evolution (normal and shear strains) and displacements along the central horizontal and vertical planes were investigated in three distinguishable percentages of peak loads (20%, 40%, and 90%) to understand the deformation behaviors in rock. The simulation results demonstrated that the strain evolution contours consistently matched with DIC generated contours with a reasonable agreement. The changes in displacement along the central horizontal and vertical planes showed that numerical simulation and DIC generated experimental results were repeatable and matched closely. In terms of validation, Brazilian testing to measure the indirect tensile strength of rocks is still an issue of debate. The numerical model of fracture propagation supported by digital image correlation from this study can be used to explain the fracturing process in the homogeneous material and can be extended to non-homogeneous cases by incorporating heterogeneity, which is essential for rock mechanics field applications.

58 GEOSCIENCES↗
DOE OSTI2022

Uncertainty Analysis in Multi‐Sector Systems: Considerations for Risk Analysis, Projection, and Planning for Complex Systems

Abstract Simulation models of multi‐sector systems are increasingly used to understand societal resilience to climate and economic shocks and change. However, multi‐sector systems are also subject to numerous uncertainties that prevent the direct application of simulation models for prediction and planning, particularly when extrapolating past behavior to a nonstationary future. Recent studies have developed a combination of methods to characterize, attribute, and quantify these uncertainties for both single‐ and multi‐sector systems. Here, we review challenges and complications to the idealized goal of fully quantifying all uncertainties in a multi‐sector model and their interactions with policy design as they emerge at different stages of analysis: (a) inference and model calibration; (b) projecting future outcomes; and (c) scenario discovery and identification of risk regimes. We also identify potential methods and research opportunities to help navigate the tradeoffs inherent in uncertainty analyses for complex systems. During this discussion, we provide a classification of uncertainty types and discuss model coupling frameworks to support interdisciplinary collaboration on multi‐sector dynamics (MSD) research. Finally, we conclude with recommendations for best practices to ensure that MSD research can be properly contextualized with respect to the underlying uncertainties.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Micro-Transfer Printing of Repeaters on Passive Interposer

Silicon-based sensors are central to particle physics experiments and particle tracking detectors. New-generation Large Focal Plane Arrays (LFPAs) cover areas that extend beyond several square meters. Distributing power and transporting data across such areas while maintaining good signal integrity is a complicated challenge. Tiling the detector on an organic interposer would be far too expensive and take too much space while offering little to no advantage regarding signal integrity. Passive silicon interposers are much less expensive and more integrable but would worsen signal integrity because of their inherent higher dielectric constant. Active interposers are a good compromise from the economic and signal integrity standpoint; unfortunately, their yield trends to zero for areas greater than a reticle size, making this technology incompatible with our application. NHanced proposes to duplicate the behavior of a high-yield, low-cost active interposer by printing active microcomponents on a passive interposer with our die-to-wafer micro-transfer printing (MTP) technology. This resolves the signal integrity and power distribution limitations. In Phase I, we designed and simulated analog and digital repeaters to be MTPed onto a passive silicon interposer test wafer.

2.5D↗
DOE OSTI2025

Core design and performance of the Westinghouse lead fast reactor with UO 2 and MOX configurations

For this work, Westinghouse partnered with Argonne National Laboratory to design, model and optimize UO 2 - and MOX-fueled core designs for a medium size (950 MWt) Lead Fast Reactor that was pursued by Westinghouse. Using Argonne’s suite of reactor analysis codes together with Westinghouse fuel cost economic models, thousands of candidate cores were considered to achieve the economics-optimized cores presented in this paper. This optimization process considered detailed reactor physics, fuel performance, transient performance, and fuel economics models. The reactor performance of the resulting optimized UO 2 - and MOX-fueled core designs are described and compared in this paper. Both cores show fuel performance and transient behavior that is considered acceptable for the optimization presented herein, while further testing campaigns on material performance in high-temperature liquid lead will be required to confirm acceptability at the operating conditions chosen. A multi-batch strategy was selected for the UO 2 core for best fuel utilization with minimum fuel inventory costs. A single-batch fuel management was instead selected for the MOX core to maximize cycle length and minimize the impact of the longer refueling outage resulting from the higher decay heat of the discharged MOX fuel relative to the discharged UO 2 fuel, requiring a longer cooling time before dry-lift of discharged fuel could take place.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2026

Advancing Concentrating Solar Thermal Modeling Using System Advisor Model (SAM)

Concentrating solar thermal (CST) technologies play a critical role in enabling dispatchable power and high-temperature industrial heat applications. Accurate and flexible modeling tools are essential for evaluating system performance, guiding technology research and development, and informing investment decisions. The National Laboratory of the Rockies's System Advisor Model (SAM) is a widely used techno-economic simulation platform for CST systems, providing detailed performance and financial modeling capabilities for multiple CST system configurations. SAM integrates physics-based performance models with financial analysis to simulate the behavior of complex energy systems under realistic operating conditions. For CST technologies (including tower, parabolic trough, and linear Fresnel), SAM enables hourly simulations using site-specific weather data that ensure feasible operating conditions and convergence of mass and energy between core system components (i.e., solar field, receiver, thermal energy storage, and power cycle). These capabilities allow researchers and developers to evaluate annual energy production, capacity factors, levelized cost of energy (LCOE), and system dispatch strategies. A key advantage of SAM lies in its flexibility for parametric analysis and large-scale computational studies. Users can vary system design parameters such as heliostat field layout, receiver dimensions, thermal energy storage capacity, power block sizing, and installation cost assumptions to investigate their impact on system performance and financial metrics. When combined with automated scripting through LK, SDKTool, or Python interfaces, SAM enables high-throughput simulation workflows that support sensitivity analysis, technology benchmarking, and optimization studies. These approaches are particularly valuable for next-generation CST concepts, where design spaces are large and system interactions are complex. Another important capability of SAM is its support for dispatch optimization and thermal energy storage modeling, which are central to the value proposition of CST technologies. The ability to simulate integrated storage and flexible power generation allows researchers to explore strategies that maximize grid value, improve capacity utilization, and enhance integration with variable resources such as photovoltaic and wind generation. This poster will present an overview of SAM's thermal system modeling capabilities including concentrating solar. Additionally, we will highlight new feature developments including: 1) implementing Google's OR-Tools optimization platform for faster and more robust dispatch optimization, 2) developing a new power load following controller for modeling behind-the-meter applications, 3) enabling direct modeling of CSP-PV hybrid systems with the inclusion of battery storage, and 4) developing a multi-receiver falling particle Gen3 system model.

14 SOLAR ENERGY↗
NASA NTRS1980

Air cargo market outlook and impact via the NASA CLASS project

An overview is given of the Cargo/Logistics Airlift Systems Study (CLASS) project which was a 10 man-year effort carried out by two contractor teams, aimed at defining factors impacting future system growth and obtaining market requirements and design guidelines for future air freighters. Growth projection was estimated by two approaches: one, an optimal systems approach with a more efficient and cost effective system considered as being available in 1990; and the other, an evolutionary approach with an econometric behavior model used to predict long term evolution from the present system. Both approaches predict significant growth in demand for international air freighter services and less growth for U.S. domestic services. Economic analysis of air freighter fleet options indicate very strong market appeal of derivative widebody transports in 1990 with little incentive to develop all new dedicated air freighters utilizing the 1990's technology until sometime beyond the year 2000. Advanced air freighters would be economically attractive for a wide range of payload sizes (to 500 metric tons), however, if a government would share in the RD and T costs by virtue of its needs for a slightly modified version of a civil air freighter design (a.g. military airlifter).

Winston, M. M.↗
NASA NTRS2001

Improving Simulated Annealing by Replacing Its Variables with Game-Theoretic Utility Maximizers

The game-theory field of Collective INtelligence (COIN) concerns the design of computer-based players engaged in a non-cooperative game so that as those players pursue their self-interests, a pre-specified global goal for the collective computational system is achieved as a side-effect. Previous implementations of COIN algorithms have outperformed conventional techniques by up to several orders of magnitude, on domains ranging from telecommunications control to optimization in congestion problems. Recent mathematical developments have revealed that these previously developed algorithms were based on only two of the three factors determining performance. Consideration of only the third factor would instead lead to conventional optimization techniques like simulated annealing that have little to do with non-cooperative games. In this paper we present an algorithm based on all three terms at once. This algorithm can be viewed as a way to modify simulated annealing by recasting it as a non-cooperative game, with each variable replaced by a player. This recasting allows us to leverage the intelligent behavior of the individual players to substantially improve the exploration step of the simulated annealing. Experiments are presented demonstrating that this recasting significantly improves simulated annealing for a model of an economic process run over an underlying small-worlds topology. Furthermore, these experiments reveal novel small-worlds phenomena, and highlight the shortcomings of conventional mechanism design in bounded rationality domains.

Wolpert, David H.↗
DOE OSTI2026

EXERGETIC: De-Risking Next-Generation Resilient Geothermal Hybrids via At-Scale Evaluation Using Virtual Emulation Digital Twin Environment for Efficient Operation

The DOE-GTO-funded project, award number 5.1.2.12, entitled "EXERGETIC - De-risking Next Generation Resilient Geothermal Hybrids via at-Scale Evaluation Using a Virtual Emulation Digital Twin Environment for Efficient Operation," advances the solution to these challenges by developing and validating a geothermal co-emulation environment implemented at the National Laboratory of the Rockies (NLR)'s Advanced Research on Integrated Energy Systems (ARIES) platform. This framework enables the de-risking of next-generation geothermal and geothermal hybrid systems through high-fidelity modeling, real-time digital emulation, advanced control strategies, and techno-economic assessment. The project focused on geothermal hybrid configurations that integrate geothermal power plants with concentrated solar power and underground thermal energy storage, enabling enhanced efficiency, flexibility, and grid support capabilities. The main goal of this project was the development of a geothermal digital co-emulation environment to demonstrate the technical and economic value of geothermal hybrid systems and their contribution to grid stability and flexibility. The EXERGETIC framework combined physics-based models, controls, and real assets at ARIES, including digital real-time simulators (DRTS), a 20-MW-scale controllable grid interface (CGI), and a 2-MW conventional generator. Detailed transient models were developed for the key subsystems of a hybrid geothermal plant, including parabolic trough solar collectors, reservoir thermal energy storage (RTES), and a binary Organic Rankine Cycle (ORC) power plant. The ORC model explicitly captured thermal inertia and off-design operation and integrated control strategies to dynamically respond to electric load profiles. The models were validated against published experimental and numerical studies, demonstrating strong agreement and confirming the accuracy and robustness of the modeling approach. The resulting digital twin represents geothermal-solar-storage systems at multiple scales (1 MW to 100 MW) and enables realistic emulation of grid-connected operation. The control architecture allows the geothermal resource to provide stable baseload generation, while solar and stored thermal energy supply flexible, dispatchable support during periods of high demand or variable grid conditions. A key contribution of the EXERGETIC project is the demonstration that geothermal hybrid systems can be designed to be active grid assets rather than passive baseload generators. Using the ARIES platform, the digital twin was evaluated under multiple grid scenarios, including load following, voltage support at the distribution level, and frequency response at the transmission level. Results show that hybrid geothermal systems can respond effectively to dynamic grid conditions, providing inertia-like behavior, primary frequency support, and voltage regulation through coordinated control. In addition to the performance and grid services capability analysis of geothermal and hybrid geothermal systems, the EXERGETIC project also focused on scalability and techno-economic analysis of geothermal hybrid plants. In particular, for the scalability analysis, machine-learning (ML)-based surrogate models were trained using data generated from the geothermal digital twin under different grid-connected scenarios and plant capacities. These ML models demonstrated strong interpolation and extrapolation capabilities across plant sizes, accurately reproducing both steady-state and transient responses with very low errors. Regarding the techno-economic analysis, plant performance results were integrated with cost models for hybrid geothermal systems, and the levelized cost of electricity (LCOE) was used as the main economic metric to evaluate system performance across a range of system capacities, solar shares, solar multiples, and storage durations. Results indicate that economies of scale significantly reduce geothermal LCOE as plant capacity increases, with large-scale systems (25-100 MW) achieving substantially lower costs than small plants. Hybridization with solar thermal energy and storage further improves economic performance by increasing capacity utilization and enabling flexible dispatch. In addition, thermal storage plays a critical role in reducing LCOE by maximizing geothermal, solar, and stored energy resources. In summary, the results from this project demonstrate that geothermal hybrid systems represent a promising alternative for increasing the energy conversion efficiency of geothermal technologies, contributing to the preservation of geothermal resources, and supporting the transition of geothermal plants from traditional baseload resources into flexible, resilient, and cost-competitive energy conversion technologies.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

A control oriented comprehensive degradation model for battery energy storage system life prediction

In order to ensure that stationary battery energy storage systems (BESSs) provide reliable energy buffering, both for power quality and economic purposes, the degradation must be considered. Cell degradation involves various side reactions and is highly dependent on its operating conditions. To accurately track cell degradation and predict its impact on battery behavior, a comprehensive physics-based degradation model based on an electrolyte phase-enhanced single particle (SP) model is developed. Key degradation physics, namely solid electrolyte interphase (SEI) layer formation and growth, Li plating on the graphite anode, and Mn dissolution on cathode of nickel-cobalt-manganese oxide (NMC622) are considered. The model is validated against experimental capacity data. The results reveal that the deposition rate of both SEI layer and Li metal increase as the charge voltage increases. At the cathode side, the solvent oxidation rate determines the Mn dissolution rate. As a result, the volume fraction of NMC622 in the cathode continually decreases at a gradually increasing rate.

25 ENERGY STORAGE↗
DOE OSTI2023

Multi–length scale characterization of point defects in thermally oxidized, proton irradiated iron oxides

A key for the success of safe nuclear power generation system is to consider structural materials that are economical, meet mechanical property needs, possess good corrosion resistance, and are radiation tolerant. Nevertheless, fundamental insights that elucidate the details of radiation damage on materials corrosion performance are lacking. This includes the behavior of surface oxides which often regulate corrosion. For example, it is unclear how non-equilibrium point defects, oxide structure, mass transport in oxides, and subsequent oxidation behavior are altered by the radiation. Here, in this work, some of the effects of proton irradiation on the attributes of point defects, iron oxide microstructures, and the physical nature of the oxidation product were correlated with corrosion behavior. Iron oxides, fabricated by thermal oxidation in air at 400°C and 800°C for 1 h, were subjected to 200 keV, 0.03 dpa (displacements per atom) of proton irradiation, and subjected to corrosion reactivity assessment using AC and DC electrochemical methods. Experimental methods that target materials information at different length scales, such as positron annihilation spectroscopy (atomistic), transmission electron microscopy (mesoscopic), and electrochemical methods (macroscopic), were coupled to shed light on the impact of radiation-induced defect modifications and structural changes in oxides on corrosion reactivity which ultimately affects durability in harsh environments.

36 MATERIALS SCIENCE↗
NASA NTRS2001

An Investigation of Fully Modulated, Turbulent Diffusion Flames in Reduced Gravity

Pulsed combustion appears to have the potential to provide for rapid fuel/air mixing, compact and economical combustors, and reduced exhaust emissions. The objective of this Flight-Definition experiment (PuFF, for Pulsed-Fully Flames) is to increase the fundamental understanding of the fuel/air mixing and combustion behavior of pulsed, turbulent diffusion flames by conducting experiments in microgravity. In this research the fuel jet is fully modulated (i.e., completely shut off between pulses) by an externally controlled valve system. This gives rise to drastic modification of the combustion and flow characteristics of flames, leading to enhanced fuel/air mixing mechanisms not operative for the case of acoustically excited or partially-modulated jets. The fully-modulated injection approach also simplifies the combustion process by avoiding the acoustic forcing generally present in pulsed combustors. Relatively little is known about the behavior of turbulent flames in reduced-gravity conditions, even in the absence of pulsing. Fundamental issues addressed in this experiment include the impact of buoyancy on the fuel/air mixing and combustion characteristics of fully-modulated flames. It is also important for the planned space experiments to establish the effects of confinement and oxidizer co-flow on these flames.

Hermanson, J. C.↗
NASA NTRS1993

Undecidability in macroeconomics

In this paper we study the difficulty of solving problems in economics. For this purpose, we adopt the notion of undecidability from recursion theory. We show that certain problems in economics are undecidable, i.e., cannot be solved by a Turing Machine, a device that is at least as powerful as any computational device that can be constructed. In particular, we prove that even in finite closed economies subject to a variable initial condition, in which a social planner knows the behavior of every agent in the economy, certain important social planning problems are undecidable. Thus, it may be impossible to make effective policy decisions. Philosophically, this result formally brings into question the Rational Expectations Hypothesis which assumes that each agent is able to determine what it should do if it wishes to maximize its utility. We show that even when an optimal rational forecast exists for each agency (based on the information currently available to it), agents may lack the ability to make these forecasts. For example, Lucas describes economic models as 'mechanical, artificial world(s), populated by ... interacting robots'. Since any mechanical robot can be at most as computationally powerful as a Turing Machine, such economies are vulnerable to the phenomenon of undecidability.

Chandra, Siddharth↗