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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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At least 1,495 records · Page 83
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Preliminary Conceptual Neutronic, Thermal, and Mechanical Design for {sup 238}Pu ATR Targets

Pu-238 is a valuable heat source material used to manufacture radioisotope power systems (RPSs), which are needed to provide electrical power for space exploration and other missions. Before 1989, the United States Department of Energy (DOE) produced Pu-238 at the Savannah River Site in South Carolina in nuclear reactors that are now decommissioned. From 1989 through 2009, existing DOE inventories of Pu- 238 were supplemented by quantities of Pu-238 purchased from Russia; however, supplies available for purchase from Russia are limited. DOE has restored domestic production to meet future demand; otherwise, NASA will be in danger of not being able to use RPSs in future missions. The Pu-238 Supply Program has the objective of reestablishing the domestic capability for producing Pu-238. In order to meet the quantities of Pu-238 needed to support NASA space mission and other federal users the ATR is being considered as an important asset to achieve the desired production of the radioisotope. In order to determine the constraints and parameters needed to maximize the production of Pu-238 at ATR a preliminary conceptual design target design was performed. The preliminary conceptual design had two principal goals: 1. Perform a trade study to determine an ATR target length that maximizes production as well as minimize the need to modify ORNL's target. 2. Evaluate the selected preliminary design from the standpoint of the ATR nuclear safety basis. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Value of Information in Fuel Cycle Decision-making

Transitions between nuclear fuel cycles with uncertain key parameters (e.g., SNF and HLW disposal costs, fast reactor capital costs) have been examined using a decision-making under uncertainty methodology. The methodology explicitly incorporates uncertainties in key parameters into the decision-making process by constructing a stochastic model and embedding uncertainties as bifurcations in the decision-tree. The framework of this methodology allows for interpretation using a real options valuation or game theoretic approach, reviewed in. The work presented here extends the decision-making under uncertainty framework to calculate the value of information, which may be used to inform a game against nature. These games against nature have been applied to resource allocation problems, where scarce resources are allocated to maximize expected payoffs. More broadly, the value of developing alternative technologies may be considered under the same framework, where an investment portfolio for technology deployment may be developed. Here, the value of information is taken as the value of reducing uncertainty in key parameters, and these values may be substituted for the traditional payoff matrix when considering allocating scarce resources. Games against nature may provide a unique perspective on R and D funding decisions when considering transitions between nuclear fuel cycles. By determining the value of reducing uncertainties (of gaining information on probability distributions) scarce resources may be allocated in such a way to maximize their utility. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Session 058 - Panel: Ensuring Strong Return on Investment for DOE EM Technology Development: DOE Views (1/2) (R1.26)

The panel represented the views of US DOE National Laboratories and DOE Contractors and focused on DOE Technology Development Projects discussing how they approach tech development to maximize return on investment. Successful examples were discussed. Panelists with presentations: Ensuring a Strong ROI for DOE EM Technology Development (Jud Virden); The DOE EM Technology Development Technical Assistance Program (Carol Eddy-Dilek); SRR Liquid Waste Technology Development Program: Encouraging Creativity Maximize Return on Investment (Vijay Jain); Ensuring Strong Return on Investment for DOE EM Technology Development: A Vendor Perspective (Martin Williams)

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

A Simple, Revolutionary Approach to Waste Packaging Utilizing Proven Technology - 20201

Historically, removing hazardous waste from gloveboxes involves the use of bags as the primary containment method. This method can prove tedious, repetitive, and time consuming to ensure the process follows all safeguards required to contain the waste and mitigate any breach of containment. Layers of bags, yards of tape, and multiple filters are added to the waste stream in order to transfer the hazardous waste from the glovebox safely into the drum package. Then, finally, it can be shipped and disposed of. The process to cut, tie, and tape each bag for disposal involves manual effort by multiple operators. Following Administrative Safety Controls, good operators are able to safely perform those tasks; but, since the bag is the only confinement layer, incidents can occur. Operators, in some cases, are also at close proximity to this waste which may increase the risk of radiation exposure. Once the waste is transferred out through these bags, it is nearly impossible to remove packaged waste that may contain higher dosage levels, thus increasing drum disposal costs incurred by the facility. Exceeding the allowable radiation levels, and drums not fully filled, both contribute significantly to excess disposal costs. Central Research Laboratories (CRL), based in Red Wing Minnesota, has developed the Waste Drum Transfer System (WDTS) building upon the proven technology and containment of the Rapid Transfer Port (RTP) as an alternate, more efficient method of waste transfer. This solution consists of an RTP Alpha port mounted inside a glovebox and Beta assembly unit composed of a drum liner fitted inside a standard 55 gallon drum. The use of the Beta drum liner bypasses the typical use of bags, sleeves or tape to provide leak tight containment. The process to connect and disconnect a drum from the glovebox is achieved by the self-docking and rotating system controls of the RTP Alpha, all done with only one operator standing in an upright ergonomic position. This system also allows for greater flexibility in available Beta connection options, expanding the overall functionality of the system. This system can be disconnected and reconnected multiple times to maximize volume containment. This will minimize drum disposal costs and reduce the overall volume of waste output by more efficiently filling the drums. Radiation levels inside each drum can be monitored and adjusted more efficiently by operators utilizing the reconnect option. Minimal As Low As Reasonably Achievable (ALARA) levels are also achievable with this system. This paper will show how highly efficient packaging and disposal of hazardous waste can be accomplished in a cost-effective manner utilizing the proven RTP technology. Maximized operator productivity and safety, as well as minimized radiation dose exposure, are all attainable through the system's engineered controls. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Conceptual System Design of a Supercritical CO{sub 2} cooled Micro Modular Reactor - 18492

Small modular reactor (SMR) concepts proposed in the past have compact size and a longer life reactor core than the conventional nuclear power plants. However, previous concepts based on the water-cooled technologies with a steam Rankine cycle have shown that the complete modularization is still technically challenging. This study suggests an innovative concept of a reactor directly cooled by supercritical carbon dioxide (S-CO{sub 2}) with S-CO{sub 2} Brayton cycle as a power conversion system, namely KAIST MMR (Micro Modular Reactor). To enhance neutron economy and maximize the fuel volume fraction of the core, a uranium carbide fuel controlled by drum type control rods was used in the fast-spectrum MMR. The core has long life (20 years) without refueling or reshuffling as well as inherent safety features. The reactor can be used as a distributed power source, and replace outdated fossil fuel power plants for small cities. Moreover, we propose a S-CO{sub 2} Brayton cycle as a power conversion system to achieve small, high performance and lightweight module. Thanks to the compact core and power conversion system, the entire system can be contained in a single module. The target of the system is to achieve small and compact system that can be transported via ground transportation of a single module containing the core and the power conversion system altogether. In order to meet this target single module s total weight is minimized in the order of 150 tons. The external size of a module is less than 7 m in length and 4 m in diameter. It produces 12 MWe electricity from 36 MWt reactor core. The S-CO{sub 2} Brayton cycle was optimized, and the cycle components were designed while maximizing the performance and minimizing the weight. A passive decay heat removal system utilizing shell and tube heat exchangers was also developed, and examined its performance with transient analysis code. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2016

Base-load high-temperature reactors with variable electricity to the grid using Brayton cycles to match low-carbon electricity markets - 18622

The electricity markets are changing because of (1) the transition to a low-carbon electricity grid and (2) addition of solar and wind. The large-scale addition of wind or solar results in low-electricity prices at times of high wind or solar output. It also results in higher electricity prices at times of low wind and solar input. This changing market in the United States favors natural gas plants with low capital costs and high operating costs where it is economic to shut down the gas turbine at times of low electricity prices. Such markets are less favorable to base-load nuclear plants. The change in the markets requires rethinking high-temperature reactor (HTR) power systems to enable base-load reactor operations with variable electricity to the grid. Base-load reactor operation is required to minimize costs but electricity output to the grid must be maximized at times of high prices to maximize total revenue. This can be accomplished by HTR open or closed Brayton power cycles coupled to high-temperature heat storage systems such as Firebrick Resistance-Heated Energy Storage (FIRES) or using auxiliary natural gas if coupled to an open Brayton power cycle. The temperature limits of HTRs are far below gas turbine temperature limits. This characteristic allows the power cycle to operate at base-load on nuclear heat with the option of added peak power by increasing compressed gas temperatures after nuclear heating but before the power turbine with other heat sources (natural gas, FIRES). For the case we have studied, the incremental heat to electricity efficiency is above 66%. The high efficiency is because it is a thermodynamic topping cycle. Because incremental heat-to-electricity efficiency is greater than a stand-alone natural gas plant (60%), such plants can directly compete against natural gas. At times of low electricity prices, electricity from the HTR and purchased from the grid is used to charge FIRES that can provide high-temperature heat as a substitute for natural gas for peak electricity production. Such nuclear Brayton cycles can replace fossil fuels in providing variable electricity on demand to the grid. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Modeling Advanced Strippers for CO2 Capture from Gas-Fired Power Plants using Aqueous Piperazine

Energy performance of 5 m piperazine was evaluated with an advanced stripper at the pilot scale, accounting for heat loss. Modeling studies indicated that heat loss at locations other than the heat source impacted the heat duty. For strippers with excess packing, the column was the most important source of heat loss, and values as low as 0.03 GJ/hr can cause pinch and reabsorption of CO2. Solvents like 5 m PZ are more affected by heat loss in the column due to a top-side temperature pinch at high lean loading. Heat loss impacts NGCC CO2 capture more than coal-based CO2 capture. Surface temperature measurements pilot plants showed that heat loss was 50-75% controlled by natural convection. Measured heat loss was correlated with steam flowrate and wind speed and ranged from 8126 to 219668 Btu/hr, representing 35% of the measured heat rate on average. Net heat duty linearly varied with CO2 removal at low lean loading and was similar for coal and NGCC conditions at fixed removal. At 90% removal, net heat duty was about 2.5 GJ/t with 4 and 12% CO2 in the flue gas. 7 At NGCC conditions, strippers with finite packing can benefit from a flashing feed to the top of the column by using a hot bypass. A flashing feed was linked to a reduction in irreversibility of the stripper from temperature driving forces. It also reduces heat duty by up to 6% at fixed packing height and reduces packing requirement for a fixed steam heater size compared to a warm bypass. Lean loading and lean solvent rate were effective handles to maximize profitability of a fixed stripper design at low gas price. High ambient temperature operation can benefit from low pressure stripping to about 0.18 lean loading at 150 ℃ to maintain the cyclic capacity at reduced rich loading. At low gas price, the capture plant was able to maximize profitability even with a high heat duty of 2.7-3.1 GJ/t at a lean loading of 0.2-0.22 mol/mol. Heat recovery by partial water vapor condensation in a gas-liquid exchanger can be replaced by a direct contact condenser (DCC). The DCC improved gas cooling and reduced heat duty compared to the CO2 exchanger at 0.2 lean loading. The DCC when used with a 150 ℃/5.5 bar stripper can reduce the cost of capture compared to the base case by $3- 4/tonne at 15 ft of packing (optimum) but increases cost of capture by $6/tonne with a 120 ℃/2 bar stripper and 10 ft of packing (optimum). The DCC can work effectively with a solvent with a high heat of absorption and thermal stability.

Suresh Babu, Athreya↗
DOE OSTI2024

Analysis and Optimization of the Recompression Cycle with High Temperature Recuperator Bypass for Concentrating Solar Power Applications

This work analyzes the sCO2 recompression with high temperature recuperator (HTR) bypass power cycle for use in concentrating solar power (CSP) systems. CSP operation differs from other thermal power plants in that CSP must balance between maximizing the heat transfer fluid (HTF) temperature difference and maximizing the cycle thermal efficiency, which typically are inversely related. Large HTF temperature differences reduce the size and cost of thermal energy storage (TES), improve the solar receiver efficiency, and require lower mass flow rates that reduce pumping power required to elevate the HTF to the receiver. The recompression cycle with HTR bypass potentially offers improved thermal efficiency with larger HTF temperature differences as compared to the recompression cycle, and it has fewer turbomachinery components than the partial cooling cycle. The recompression with HTR bypass cycle adds a second lower temperature primary heat exchanger which transfers heat from the HTF to the fraction of sCO2 flow that bypasses the HTR. We developed a model to compare the recompression with HTR bypass cycle to the recompression and partial cooling cycles. A sweep of design parameters including bypass fraction, recompression fraction, recuperator conductance, and pressure ratio is used to form a pareto-optimal front with the cycle thermal efficiency and HTF temperature difference as objectives. An optimization routine has also been developed to find optimal design point parameters for a target HTF temperature difference. The performance of the recompression with HTR bypass cycle is compared with recompression and partial cooling cycles.

concentrating solar power↗
DOE OSTI2023

Design optimization of an ethanol heavy-duty engine using design of experiments and bayesian optimization

Diesel-fueled engines still hold a large market share in the medium and heavy-duty transportation sector. However, the increase in fossil fuel prices and the strict emission regulations are leading engine manufacturers to seek cleaner alternatives without a compromise in performance. Alcohol-based fuels, such as ethanol, offer a promising alternative to diesel fuel in meeting regulatory demands. Ethanol provides cleaner combustion and lower levels of soot due to its chemical properties, in particular its lower level of carbon content. In addition, the stoichiometric operating conditions of alcohol fueled engines enable the mitigation of NOx emissions in aftertreatment stage. With the promise of retrofitting diesel engines to run on ethanol to reduce emissions, the thermal efficiency of these engines remains the primary optimization target. In order to find the optimal ethanol-fueled engine design that maximizes the thermal efficiency, a large design space needs to be investigated using engineering tools. In this study, previous research by the authors on optimizing the design of a single-cylinder ethanol-fueled engine was extended to explore the design space for a heavy-duty multi-cylinder engine configuration. A heavy-duty engine setup with multiple operating conditions at different engine speeds and loads were considered. A design optimization analysis was performed to identify the potential designs that maximize the indicated thermal efficiency in an ethanol-fueled compression ignition engine. First, a computational fluid dynamics (CFD) model of the engine was validated using experimental data for four drive cycle points. Using a design of experiments (DoE) approach and a parameterized piston bowl geometry, the model was then exercised to explore the relationship among geometric features of the piston bowl and spray targeting angle and indicated thermal efficiency across all tested operating conditions. After evaluating 165~candidate designs, a piston bowl geometry was identified that yielded an increase between 1.3 to 2.2 percentage points in indicated thermal efficiency for all tested conditions, while satisfying the operational design constraints for peak pressure and maximum pressure rise rate. The increased performance was attributed to enhanced mixing that led to the formation of a more homogeneous distribution of in-cylinder temperature and equivalence ratio, higher combustion temperatures, and shorter combustion duration. Finally, a Bayesian optimization (BOpt) analysis was employed to find the optimal piston bowl geometry with a fixed spray injector angle for one of the operating conditions. Using BOpt, a piston candidate was identified that resulted in a 1.9~percentage point increase in thermal efficiency from the baseline design, yet only required 65\% of the design samples investigated using the DoE approach.

Tekgul, Bulut↗
DOE OSTI2024

Accelerated CO2 Storage Optimization Using Multi-Resolution Fourier Neural Operator at the Illinois Basin Decatur Project (IBDP)

This paper presents a deep learning-based approach for optimizing CO2 injection in carbon capture and storage (CCS) operations. We developed a multi-resolution machine learning model to significantly reduce data generation costs. Utilizing this proxy model, we implemented a multi-objective genetic algorithm to optimize well control during the CO2 injection process. The proposed approach was applied to the Illinois Basin Decatur Project (IBDP), successfully optimizing the CO2 injection schedule based on three key objectives: maximizing the amount of CO2 stored, maximizing sweep efficiency, and minimizing pressure increase. The use of the proxy model accelerated the optimization workflow by two orders of magnitude, while the cost of data generation for the proxy model was reduced by 90% by utilizing a coarse-scale model.

accelerated CO2 storage optimization↗
DOE OSTI2025

DEVELOPMENT AND APPLICATION OF RISK ANALYSIS TOOLKIT FOR PLANT RESOURCE OPTIMIZATION

This paper presents the development of methods and tools that are being designed to optimize plant operations (e.g., maintenance/replacement schedules and optimal maintenance postures for plant components) in a manner that is more cost effective than current approaches and makes better use of available component health and cost data. These methods include both data- and model-based optimization methods. Model-based optimization methods directly include reliability and cost models to determine an optimal plant operational strategy. We consider gradient-based and evolutionary (based on genetic algorithms) optimization methods. The second class of methods target more specific use cases (e.g., project schedule optimization) and are not based on reliability models directly, but they require specific component reliability and cost data. This class of methods is based on variants of the knapsack problem with an aim to determine an optimal project schedule that maximizes the overall NPV. This paper also presents multi-objective methods designed to identify an optimal maintenance posture based on a Pareto frontier analysis. Rather than dictating the “right” tradeoff (i.e., identify the absolute best posture), we show how it is possible to perform a trade space exploration approach (i.e., identify value and costs of several postures and let the analysis account for desired value and cost metrics). This is performed by identifying maintenance postures that maximize value (e.g., system availability) and minimize operational costs, i.e., the Pareto frontier in a value-cost trade space. For all these methods we present detailed applicative examples that show their validity from a decision-making perspective.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Biconjugate Impedance Matching Control of the HERO WEC: Preprint

Effective control strategies are essential for maximizing the power output of wave energy converters (WECs). In this study, we explore the methodology of port-based modelling which can be used for bi-conjugate impedance matching, a type of reactive control that involves maximizing power transfer by setting the load (PTO) impedance to be the complex conjugate of the source impedance (WEC). Despite its foundational role in electrical engineering, this method has seen limited application in wave energy and has not yet been demonstrated in wave-powered desalination systems. We represent our complex multidisciplinary system as an equivalent circuit to explore frequency-based relations. The HERO WEC, a small-scale, modular point absorber (PA) designed for reverse osmosis desalination is used as a case study to demonstrate port-based modelling for control applications. Improving the performance of wave-powered water desalination systems could play a critical role in addressing freshwater scarcity for coastal communities, especially those in remote or disaster-prone regions.

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

Optimization for Bioenergy Systems

The Sustainable Aviation Fuel (SAF) Grand Challenge (Langholtz, 2024 ) seeks to generate 35 billion gallons of SAF each year by 2050, with corn stover, an agricultural byproduct, playing a key role as a feedstock. This study develops an optimization framework to enhance the quality and quantity of corn stover while ensuring economic and environmental viability. Using the Decision Support System for Agrotechnology Transfer (DSSAT) crop model, we simulate the effects of cover crops on rotation yield, soil moisture balance, and nitrogen cycling across diverse climates and soils. The model outputs, including yield data and soil quality changes, inform a Mixed-Integer Linear Programming (MILP) optimization model. This model aims to maximize economic and environmental returns by incorporating production costs, direct and indirect income, and environmental incentives. The optimization model evaluates 280 agriculture management plans composed of various crop management strategies, including corn stover removal rates, cover crop adoption, and fertilization practices. It seeks to identify the optimal combination of crop and tillage decisions for each subfield, maximizing profits while enhancing soil carbon sequestration and reducing greenhouse gas emissions. Outputs include detailed subfield locations, optimal management plans, and profits per hectare and per acre, allowing for comparison with literature values on farm profits. This study provides a robust optimization framework supporting the SAF Grand Challenge by proposing economically viable and environmentally sustainable strategies for corn stover utilization. The findings highlight corn stover's potential as a sustainable feedstock for SAF production, offering practical solutions to enhance its quality and quantity while maintaining soil health. Idaho is used as a case study to demonstrate the framework's applicability and effectiveness in real-world scenarios. Langholtz, M. H., Davis, M., Hellwinckel, C., De La Torre Ugarte, D., Efroymson, R., Jacobson, R., Milbrandt, A., Coleman, A., Davis, R., Kline, K. L., Badgett, A., Curran, S., Schmidt, E., Theiss, T., Fried, J., English, B., Lambert, L., Cook, H., Field, J., ... Walker, L. (2024). 2023 Billion-Ton Report: An Assessment of U.S. Renewable Carbon Resources. https://doi.org/10.2172/2441098 DSSAT Foundation. (2025). Decision Support System for Agrotechnology Transfer (DSSAT). Retrieved from https://dssat.net/

09 - BIOMASS FUELS↗
DOE OSTI2022

Bayesian optimization to design a novel x-ray shaping device

In radiation therapy, x-ray dose must be precisely sculpted to the tumor, while simultaneously avoiding surrounding organs at risk. This requires modulation of x-ray intensity in space and/or time. Typically, this is achieved using a multi leaf collimator (MLC) - a complex mechatronic device comprising over one hundred individually powered tungsten ‘leaves’ that move in or out of the radiation field as required. Here, an all-electronic x-ray collimation concept with no moving parts is presented, termed “SPHINX”: Scanning Pencil-beam High-speed Intensity-modulated X-ray source. SPHINX utilizes a spatially distributed bremsstrahlung target and collimator array in conjunction with magnetic scanning of a high energy electron beam to generate a plurality of small x-ray “beamlets.” A simulation framework was developed in Topas Monte Carlo incorporating a phase space electron source, transport through user defined magnetic fields, bremsstrahlung x-ray production, transport through a SPHINX collimator, and dose in water. This framework was completely parametric, meaning a simulation could be built and run for any supplied geometric parameters. This functionality was coupled with Bayesian optimization to find the best parameter set based on an objective function which included terms to maximize dose rate for a user defined beamlet width while constraining inter-channel cross talk and electron contamination. Designs for beamlet widths of 5, 7, and 10 mm 2 were generated. Each optimization was run for 300 iterations and took approximately 40 h on a 24-core computer. For the optimized 7-mm model, a simulation of all beamlets in water was carried out including a linear scanning magnet calibration simulation. Finally, a back-of-envelope dose rate formalism was developed and used to estimate dose rate under various conditions. The optimized 5–, 7–, and 10-mm models had beamlet widths of 5.1 , 7.2 , and 10.1 mm 2 and dose rates of 3574, 6351, and 10 015 Gy/C, respectively. The reduction in dose rate for smaller beamlet widths is a result of both increased collimation and source occlusion. For the simulation of all beamlets in water, the scanning magnet calibration reduced the offset between the collimator channels and beam centroids from 2.9 ±1.9 mm to 0.01 ±0.03 mm. A slight reduction in dose rate of approximately 2% per degree of scanning angle was observed. Based on a back-of-envelope dose rate formalism, SPHINX in conjunction with next-generation linear accelerators has the potential to achieve substantially higher dose rates than conventional MLC-based delivery, with delivery of an intensity modulated 100 x 100 mm 2 field achievable in 0.9 to 10.6 s depending on the beamlet widths used. Bayesian optimization was coupled with Monte Carlo modeling to generate SPHINX geometries for various beamlet widths. A complete Monte Carlo simulation for one of these designs was developed, including electron beam transport of all beamlets through scanning magnets, x-ray production and collimation, and dose in water. These results demonstrate that SPHINX is a promising candidate for sculpting radiation dose with no moving parts, and has the potential to vastly improve both the speed and robustness of radiotherapy delivery. A multi-beam SPHINX system may be a candidate for delivering magavoltage FLASH RT in humans.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

Plastic work constrained elastoplastic topology optimization

An elastoplastic topology optimization framework for limiting plastic work generation while maximizing stiffness is presented. The kinematics and constitutive model are based on finite strain linear isotropic hardening plasticity, and the balance laws are solved using a total Lagrangian finite element formulation. Aggregation of the specific plastic work combined with an adaptive normalization scheme efficiently constrains the maximum specific plastic work. The optimization problem is regularized using an augmented partial differential equation filter, and is solved by the method of moving asymptotes where path-dependent sensitivities are derived using the adjoint method. The numerical examples show a clear dependence on the optimized maximum stiffness structures for different levels of constrained specific plastic work. It is also shown that due to the history dependency of the plasticity, the load path significantly influences the structural performance and optimized topology.

42 ENGINEERING↗
DOE OSTI2022

3D LiMn 2 O 4 nThin Film Deposited by ALD: A Road toward High-Capacity Electrode for 3D Li-Ion Microbatteries

Miniaturized electronics suffer from a lack of energy autonomy. In that context, the fabrication of lithium-ion solid-state microbatteries with high performance is mandatory for powering the next generation of portable electronic devices. Here, the fabrication of a thin film positive electrode for 3D Li-ion microbatteries made by the atomic layer deposition (ALD) method and in situ lithiation step is demonstrated. The 3D electrodes based on spinel LiMn 2 O 4 films operate at high working potential (4.1 V vs Li/Li + ) and are capable of delivering a remarkable surface capacity (approximate to 180 mu Ah cm -2 ) at low C-rate while maintaining more than 40 mu Ah cm -2 at C/2 (time constant = 2 h). Both the thickness of the electrode material and the 3D gain of the template are carefully tuned to maximize the electrode performance. Further, advanced characterization techniques such as transmission electron and X-ray transmission microscopies are proposed as perfect tools to study the conformality of the deposited films and the interfaces between each layer: no interdiffusion or segregation are observed. This work represents a major issue towards the fabrication of 3D-lithiated electrode by ALD-without any prelithiation step by electrochemical technique-making it an attractive solution for the fabrication of 3D Li-ion solid-state microbatteries with semiconductor processing methods.

3D Li-ion micro-batteries↗
DOE OSTI2019

An alternative approach for MLE calculation in nonlinear continuous dynamic systems

As an important metric to tell if a nonlinear dynamic system has a singular attractor or divergent trajectory, the maximal Lyapunov exponent (MLE) can be calculated from either system models or time series of state variable measurement. However, in the real world, due to inaccurate models, measurement noise, and the fact that sometimes state variables cannot be measured directly, it is very difficult to get an accurate MLE, which limits its application in, for example, in prediction of a nonlinear physical system (e. g. power systems, etc.) behavior. To overcome these factors, this paper proposed a trajectory-estimation-based MLE calculation approach. The proposed approach addressed how to calculate the MLE when state variables cannot be accessed directly, and uncertainties in system models, as well as noise in measurements. The simulation results shows that the proposed approach is able to handle well the nonlinear measurement functions between state variables and measurements, and get better results than pure model-based approaches or measurement-based approaches in front of measurement noise and model uncertainties.

maximal Lyapunov exponents, nonlinear differential↗
DOE OSTI2026

Re-evaluating probable maximum precipitation estimates: sensitivity to transposition domains and storm rotation using modern datasets

This study examines the sensitivity of Probable Maximum Precipitation (PMP) estimates to key methodological decisions embedded in the legacy approach adopted in the U.S. National Weather Service Hydrometeorological Reports No. 51 and No. 52. Although widely used for infrastructure design and risk regulation, fundamental aspects of PMP estimation—such as storm sample size, transposition domain, maximization procedures, and storm rotation—remain poorly constrained and lack formal guidance. Using the Red Rock watershed in Iowa as a case study, and leveraging the 2002–2023 NOAA Analysis of Record for Calibration (AORC) precipitation dataset, we systematically evaluate how each methodological choice, individually and in combination, influences PMP estimates. Our findings demonstrate that PMP is not a fixed physical upper bound but rather a modeling construct shaped heavily by user-defined assumptions. Notably, PMP values derived from modern gridded rainfall datasets can be substantially higher than the legacy estimate used in the original spillway design for Red Rock Dam. Decisions regarding storm sample size, domain extent, climatological window, and particularly storm rotation all contributed to higher PMP estimates. Storm rotation alone—a loosely constrained element in the current PMP practice—can amplify PMP by more than 25%. These results reveal the lack of standardized bounds in current PMP workflows and the need for systematic sensitivity and uncertainty analysis. As PMP estimation shifts toward probabilistic approaches, incorporating physically meaningful storm attributes will be key to developing more transparent, defensible methods for dam safety and climate-resilient infrastructure.

Probable maximum precipitation↗