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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Design and Optimization of Processing Pathways for Rare Earth Element Recovery from End-of-Life Products

In this presentation, we first discuss the benefits of targeting end-of-life (EOL) products as a feedstock. We then discuss the problem statement of designing a processing facility for recovering rare earth elements (REEs) from EOL HDDs and motors from EOL EVs/HEVs. We then discuss the most profitable pathway, and then discuss the environmental impacts associated with the processing pathway, comparing it to a processing facility in China, and find it to have lower impacts overall. We also investigate the trade-off solutions for other pathways that are not as profitable, but have lower impacts by generating Pareto Fronts. In the next portion of the presentation, Critical Materials Recycling, Inc. is discussed. We discuss how their process was found to be the optimal pathway after performing superstructure optimization, and how we are currently working with them to further optimize their process to increase profits. Finally, we wrap up with conclusions summarizing the main takeaways of the presentation.

36 MATERIALS SCIENCE↗
DOE OSTI2022

High-Temperature Latent Heat Storage System using Transportable Heat Pipes for Versatile Integration with Emerging Microreactors

With the growing interest in the development of micro nuclear reactors and their application to microgrid, high-temperature thermal energy storage (TES) has also been receiving great attention as a technology to reinforce the energy utilization and profitability of this class of reactors. Given the importance and research needs of the TES technology, a research project is underway at Idaho National Laboratory (INL) to develop high-temperature TES that can be easily interfaced with emerging micro nuclear reactors. Currently under development is the Heat pipe-Integrated Thermal Battery (HITB), a novel latent heat storage design that enables flexible and robust integration with any design of currently considered micro nuclear reactors. The development of detailed design based on the proposed TES concept, HITB, requires not only development and validation of modeling and simulation capabilities, but also research that spans thermal performance analysis, component- and system-scale design optimization, and experimental demonstrations including high-temperature feasibility testing. The current research efforts (and plans) are divided into the following four areas: (i) Thermal and structural modeling and analysis at both system- and component-scales for evaluating performance and conducting design optimization, (ii) Small-scale experimental demonstrations for the key components of the proposed HITB design, (iii) Modelica-based dynamic model development for developing a control strategy under dynamic operation within integrated energy systems configuration, (iv) Integrated experimental testing and demonstration. This paper introduces the overall research efforts that have been and are being conducted to develop and demonstrate the novel design of the high-temperature latent heat storage device, HITB. The key design features, ongoing research efforts including the development of modeling and simulation capabilities, small-scale demonstrations of the HITB’s key functionalities prior to scaled-up experimental demonstration, are discussed. Then, this paper concludes with a remark on the future research plans for this project.

25 ENERGY STORAGE↗
DOE OSTI2021

Piston Bowl Geometry Effects on Gasoline Compression Ignition in a Heavy-Duty Diesel Engine

A design optimization campaign was conducted to search for improved combustion profiles that enhance gasoline compression ignition in a heavy-duty diesel engine with a geometric compression ratio of 17.3. A large-scale design of experiments approach was used for the optimization, employing three-dimensional computational fluid dynamics simulations. The main parameters explored include geometric features, injector specifications, and swirl motion. Both stepped-lip and re-entrant bowls were included in order to assess their respective performance implications. A total of 256 design candidates were prepared using the software package CAESES for automated and simultaneous geometry generation and combustion recipe perturbation. The design optimization was conducted for three engine loads representing light to medium load conditions. The design candidates were evaluated for fuel efficiency, emissions, fuel-air mixing, and global combustion behavior. Simulation results showed that the optimum designs were all stepped-lip bowls, due to improvements in fuel-air mixing, as well as reduced heat loss and emissions formation. Improvements in indicated specific fuel consumption of up to 3.2% were achieved while meeting engine-out NOx emission targets of 1-1.5 g/kW center dot h. Re-entrant bowls performed worse compared to the baseline design, and significant performance variations occurred across the load points. Specifically, the re-entrant bowls were on par with the stepped-lip bowls under light load conditions, but significant deteriorations occurred under higher load conditions. As a final task, selected optimized designs were then evaluated under full-load conditions.

CFD↗
DOE OSTI2021

Accelerating Multigrid-based Hierarchical Scientific Data Refactoring on GPUs

Rapid growth in scientific data and a widening gap between computational speed and I/O bandwidth make it increasingly infeasible to store and share all data produced by scientific simulations. Instead, we need methods for reducing data volumes: ideally, methods that can scale data volumes adaptively so as to enable negotiation of performance and fidelity tradeoffs in different situations. Multigrid-based hierarchical data representations hold promise as a solution to this problem, allowing for flexible conversion between different fidelities so that, for example, data can be created at high fidelity and then transferred or stored at lower fidelity via logically simple and mathematically sound operations. However, the effective use of such representations has been hindered until now by the relatively high costs of creating, accessing, reducing, and otherwise operating on such representations. We describe here highly optimized data refactoring kernels for GPU accelerators that enable efficient creation and manipulation of data in multigrid-based hierarchical forms. We demonstrate that our optimized design can achieve up to 250 TB/s aggregated data refactoring throughput—83% of theoretical peak—on 1024 nodes of the Summit supercomputer. We showcase our optimized design by applying it to a large-scale scientific visualization workflow and the MGARD lossy compression software.

Data refactoring↗
DOE OSTI2021

Accelerating Multigrid-based Hierarchical Scientific Data Refactoring on GPUs

Rapid growth in scientific data and a widening gap between computational speed and I/O bandwidth make it increasingly infeasible to store and share all data produced by scientific simulations. Instead, we need methods for reducing data volumes: ideally, methods that can scale data volumes adaptively so as to enable negotiation of performance and fidelity tradeoffs in different situations. Multigrid-based hierarchical data representations hold promise as a solution to this problem, allowing for flexible conversion between different fidelities so that, for example, data can be created at high fidelity and then transferred or stored at lower fidelity via logically simple and mathematically sound operations. However, the effective use of such representations has been hindered until now by the relatively high costs of creating, accessing, reducing, and otherwise operating on such representations. We describe here highly optimized data refactoring kernels for GPU accelerators that enable efficient creation and manipulation of data in multigrid-based hierarchical forms. We demonstrate that our optimized design can achieve up to 250 TB/s aggregated data refactoring throughput—83% of theoretical peak—on 1024 nodes of the Summit supercomputer. We showcase our optimized design by applying it to a large-scale scientific visualization workflow and the MGARD lossy compression software.

Chen, Jieyang↗
DOE OSTI2015

Application of Frequency of Detection Methods in Design and Optimization of the INL Site Ambient Air Monitoring Network

This report presents an evaluation of a hypothetical INL Site monitoring network and the existing INL air monitoring network using frequency of detection methods. The hypothetical network was designed to address the requirement in 40 CFR Part 61, Subpart H (2006) that “emissions of radionuclides to ambient air from U.S. DOE facilities shall not exceed those amounts that would cause any member of the public to receive in any year an effective dose equivalent exceeding 10 mrem/year.” To meet the requirement for monitoring only, “radionuclide releases that would result in an effective dose of 10% of the standard shall be readily detectable and distinguishable from background.” Thus, the hypothetical network consists of air samplers placed at residence locations that surround INL and at other locations where onsite livestock grazing takes place. Two exposure scenarios were used in this evaluation: a resident scenario and a shepherd/rancher scenario. The resident was assumed to be continuously present at their residence while the shepherd/rancher was assumed to be present 24-hours at a fixed location on the grazing allotment. Important radionuclides were identified from annual INL radionuclide National Emission Standards for Hazardous Pollutants reports. Important radionuclides were defined as those that potentially contribute 1% or greater to the annual total dose at the radionuclide National Emission Standards for Hazardous Pollutants maximally exposed individual location and include H-3, Am-241, Pu-238, Pu 239, Cs-137, Sr-90, and I-131. For this evaluation, the network performance objective was set at achieving a frequency of detection greater than or equal to 95%. Results indicated that the hypothetical network for the resident scenario met all performance objectives for H-3 and I-131 and most performance objectives for Cs-137 and Sr-90. However, all actinides failed to meet the performance objectives for most sources. The shepherd/rancher scenario showed that air samplers placed around the facilities every 22.5 degrees were very effective in detecting releases, but this arrangement is not practical or cost effective. However, it was shown that a few air samplers placed in the prevailing wind direction around each facility could achieve the performance objective of a frequency of detection greater than or equal to 95% for the shepherd/rancher scenario. The results also indicate some of the current sampler locations have little or no impact on the network frequency of detection and could be removed from the network with no appreciable deterioration of performance. Results show that with some slight modifications to the existing network (i.e., additional samplers added north and south of the Materials and Fuels Complex and ineffective samplers removed), the network would achieve performance objectives for all sources for both the resident and shepherd/rancher scenario.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

AIST-NREL Concentrator Photovoltaic (CPV) Demonstration. Cooperative Research and Development Final Report, CRADA Number CRD-10-402

The purpose of the project is to demonstrate and quantitatively compare performance of CPV systems installed in Japan and in the United States. The deployment conditions (e.g. spectrum and temperature) are site dependent and the optimal design of the system may vary with location. The CPV systems will use multi-junction concentrator cells for the conversion of sunlight into electricity. The optimal design of the cell may depend on the location at which a CPV system is installed. Thus, the systems in Japan and in the U.S. will all use a combination of concentrator cells obtained from three different vendors. This CRADA pertains only to the equipment that will be installed in the U.S. This effort is a collaborative project between AIST and NREL.

14 SOLAR ENERGY↗
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 OSTI2026

Multi-Objective design of interlocking metasurfaces using conditional diffusion models

Unit cell design remains a major challenge for interlocking metasurfaces, a promising joining technology for dissimilar materials, due to the complex, competing, multivariate design space and the need for rapid adaptation to varying performance requirements. This study explores Conditional Diffusion Models as a design optimization tool for interlocking metasurfaces. Given the complex, competing, multivariate design space for interlocking metasurfaces, unit cell design remains a major challenge for this joining technology. We trained a conditional diffusion model on 25,000 finite element analysis-simulated interlocking metasurface unit cells to generate designs with tailored thermo-mechanical properties (tensile strength, shear strength, and thermal conductivity) based on specified performance criteria. The model demonstrated a success rate of approximately 72 % in producing designs that met specified property bounds. The conditional diffusion model generated both thermally resistive and conductive designs, revealing clear trends in design characteristics: taller, dendritic structures were advantageous for tensile loads, while shorter, robust designs excelled in shear applications. Our findings indicate that the model's performance is more influenced by the breadth of the design space than by the quantity of training data, highlighting the importance of expansive design domains for generating innovative solutions. This work establishes conditional diffusion models as a highly efficient and adaptable tool for rapid interlocking metasurface unit cell design, paving the way for advancements in multi-material joining technologies, as well as highlighting the justification to leverage conditional diffusion models as design tools across complex design domains.

Conditional diffusion models↗
DOE OSTI2016

Design and optimization of Artificial Neural Networks for the modelling of superconducting magnets operation in tokamak fusion reactors

In superconducting tokamaks, the cryoplant provides the helium needed to cool different clients, among which by far the most important one is the superconducting magnet system. The evaluation of the transient heat load from the magnets to the cryoplant is fundamental for the design of the latter and the assessment of suitable strategies to smooth the heat load pulses, induced by the intrinsically pulsed plasma scenarios characteristic of today's tokamaks, is crucial for both suitable sizing and stable operation of the cryoplant. For that evaluation, accurate but expensive system-level models, as implemented in e.g. the validated state-of-the-art 4C code, were developed in the past, including both the magnets and the respective external cryogenic cooling circuits. Here we show how these models can be successfully substituted with cheaper ones, where the magnets are described by suitably trained Artificial Neural Networks (ANNs) for the evaluation of the heat load to the cryoplant. First, two simplified thermal-hydraulic models for an ITER Toroidal Field (TF) magnet and for the ITER Central Solenoid (CS) are developed, based on ANNs, and a detailed analysis of the chosen networks' topology and parameters is presented and discussed. The ANNs are then inserted into the 4C model of the ITER TF and CS cooling circuits, which also includes active controls to achieve a smoothing of the variation of the heat load to the cryoplant. The training of the ANNs is achieved using the results of full 4C simulations (including detailed models of the magnets) for conventional sigmoid-like waveforms of the drivers and the predictive capabilities of the ANN-based models in the case of actual ITER operating scenarios are demonstrated by comparison with the results of full 4C runs, both with and without active smoothing, in terms of both accuracy and computational time. Exploiting the low computational effort requested by the ANN-based models, a demonstrative optimization study has been finally carried out, with the aim of choosing among different smoothing strategies for the standard ITER plasma operation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Dissimilar Material Joining via Interlocking Metasurfaces

Background The integration of dissimilar materials poses a significant challenge in engineering, necessitating innovative solutions for robust and reliable joining. Interlocking metasurfaces (ILMs) are a new joining technology comprising arrays of autogenous features patterned across two surfaces that interlock to form robust structural joints. Objective Here, this study elucidates the factors influencing the tensile performance of ILM joints formed between dissimilar materials. Methods We employed parametric optimization to identify optimal unit cell geometries for maximal yield strength based on the hypothesis that the elastic tensile properties of the materials are the primary determinants of tensile performance. Experimental validation was performed by mechanically testing the theorized optimal ILM geometry and a range of ILM geometries to capture the overall behavior trends of joints between two additively manufactured polymers, VeroPureWhite (VW) and RGDA8430-DM (8430). Results Experimental validation of optimized designs revealed that additional factors, e.g. flexural strength and localized plasticity, also strongly influenced the tensile performance of T-slot ILMs joining dissimilar materials. The proposed optimal design remained the best performer. Conclusions This study demonstrates the viability of ILMs as a joining method for dissimilar materials. ILMs can join dissimilar materials with no loss in joint yield strength compared to joints composed solely of the weaker of the two constitutive materials. ILMs demonstrated their potential as a versatile and effective joining technology in diverse engineering applications.

Elbrecht, Benjamin James [Sandia National Laborato↗
DOE OSTI2015

Magnetized retarding field energy analyzer measuring the particle flux and ion energy distribution of both positive and negative ions

This paper presents the development of a magnetized retarding field energy analyzer (MRFEA) used for positive and negative ion analysis. The two-stage analyzer combines a magnetic electron barrier and an electrostatic ion energy barrier allowing both positive and negative ions to be analyzed without the influence of electrons (co-extracted or created downstream). An optimal design of the MRFEA for ion-ion beams has been achieved by a comparative study of three different MRFEA configurations, and from this, scaling laws of an optimal magnetic field strength and topology have been deduced. The optimal design consists of a uniform magnetic field barrier created in a rectangular channel and an electrostatic barrier consisting of a single grid and a collector placed behind the magnetic field. The magnetic barrier alone provides an electron suppression ratio inside the analyzer of up to 6000, while keeping the ion energy resolution below 5 eV. The effective ion transparency combining the magnetic and electrostatic sections of the MRFEA is measured as a function of the ion energy. It is found that the ion transparency of the magnetic barrier increases almost linearly with increasing ion energy in the low-energy range (below 200 eV) and saturates at high ion energies. The ion transparency of the electrostatic section is almost constant and close to the optical transparency of the entrance grid. We show here that the MRFEA can provide both accurate ion flux and ion energy distribution measurements in various experimental setups with ion beams or plasmas run at low pressure and with ion energies above 10 eV.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Integrated Sustainable Product Design With Warranty and End-of-Use Considerations

The concept of integrated sustainable product design has recently emerged, aiming to incorporate downstream life cycle performance into the initial product design to enhance sustainability. Various sustainable product design tools based on life cycle assessment or quality function deployment have been established while the impact of reliability on circular practices has received limited attention. Recognizing the critical role of product reliability in post-design performance, this paper develops a product design optimization model that considers the warranty performance and the effect of end-of-use options. The model takes into account the effect of uncertain operating conditions on product reliability. Two optimization goals including the minimization of expected unit life cycle cost and environmental impact are achieved by the model. To demonstrate the benefits of the integrated approach, the model is applied to an electric motor design problem. The results highlight that integrating end-of-use options in the early design phase leads to adjustments in component selection and reliability design. Moreover, the circular utilization of used products enables cost savings throughout the product’s life cycle and contributes to environmental impact reduction. Finally, the study analyzes the effects of operating conditions, warranty policies, and take-back prices for used products on design decisions, providing valuable insights for product designers.

Integrated design↗
DOE OSTI2022

Cylindrical battery design app

Software that delivers optimal design parameters and performance predictions for cylindrical cells, which can range in size from microbatteries to EV batteries, is developed. The software utilizes machine learning and includes a graphical user interface to enable rapid prototyping and to accelerate energy storage research, development, and manufacturing. The Cylindrical battery design V1.0 comprises of three types of cylindrical batteries, Microbattery (Primary), Microbattery (Secondary) and 18650/21700/xxxxx Cylindrical battery. The software was developed in MATLAB. The software has the capability to output the cell design with the capacity ranges from several mAh to several million Ah.

Xiao, Jie↗
DOE OSTI2018

Design and Optimization of Amorphous Based on Highly Efficient HIT Solar Cell

The objective of this paper is to improve the power conversion efficiency of HIT solar cell using amorphous materials. A high efficiency amorphous material based on two dimensional heterojunction solar cell with thin intrinsic layer is designed and simulated at the research level using Synopsys/RSOFT-Solar Cell utility. The HIT structure composed of TCO/a-Si:H(p)/a-Si:H(i)/c-Si(n)/a-Si:H(i)/a-Si:H(n{sup +})/Ag is created by using of RSOFT CAD. Optical characterization of the cell is performed by Diffract MOD model based on RCWA (rigorous coupled wave analysis) algorithm. Electrical characterization of the cell is done by Solar cell utility using based on Ideal diode method. In addition, optimization of the different layer thickness in the HIT structure is executed to improve the absorption and thereby the photocurrent density. The proposed HIT solar cell structure resulted in an open circuit voltage of 0.751 V, a short circuit current density of 36.37 mA/cm{sup 2} and fill factor of 85.37% contributing to the total power conversion efficiency of 25.91% under AM1.5G. Simulation results showed that the power conversion efficiency is improved by 1.21% as compared to the reference HIT solar cell. This improvement in high efficiency is due to reduction of resistive losses, recombination losses at the hetero junction interface between intrinsic a-Si and c-Si, and optimization of the thicknesses in a-Si and c-Si layers.

14 SOLAR ENERGY↗
DOE OSTI2016

Design and optimization of a modular setup for measurements of three-dimensional spin polarization with ultrafast pulsed sources

ULTRASPIN is an apparatus devoted to the measurement of the spin polarization (SP) of electrons ejected from solid surfaces in a UHV environment. It is designed to exploit ultrafast light sources (free electron laser or laser high harmonic generation) and to perform (photo)electron spin analysis by an arrangement of Mott scattering polarimeters that measure the full SP vector. The system consists of two interconnected UHV vessels: one for surface science sample cleaning treatments, e-beam deposition of ultrathin films, and low energy electron diffraction/AES characterization. The sample environment in the polarimeter allows for cryogenic cooling and in-operando application of electric and magnetic fields. The photoelectrons are collected by an electrostatic accelerator and transport lens that form a periaxial beam that is subsequently directed by a Y-shaped electrostatic deflector to either one of the two orthogonal Mott polarimeters. The apparatus has been designed to operate in the extreme conditions of ultraintense single-X-ray pulses as originated by free electron lasers (up to 1 kHz), but it allows also for the single electron counting mode suitable when using statistical sources such as synchrotron radiation, cw-laser, or e-gun beams (up to 150 kcps).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Design and optimization of a modular hydrogen-based integrated energy system to maximize revenue via nuclear-renewable sources

Here, this paper demonstrates a novel modular distributed framework that uses optimal energy-dispatching strategies to enable greater flexibility and profitability in nuclear-renewable integrated energy systems (NR-IES). Hydrogen is used as a commodity in this framework since its production can improve grid stability and system operational flexibility, decarbonize heavy industry, and create an additional revenue stream for electricity generators, particularly nuclear power plants with high operational expenses. The proposed solution addresses the challenges associated with merging multiple software and services from various domains by using functional mock-up units (FMU) to co-simulate diverse subsystems designed in various platforms. The tightly coupled integrated energy system (IES) is optimized to maximize revenue by utilizing the deep reinforcement learning (DRL) technique to make smart dispatching decisions based on variable electricity prices and the availability of renewable energy. Proximal policy optimization (PPO) algorithm is used in training and testing the DRL agent. Over a period of 120 days, the proposed hydrogen-based IES framework showed about 10% revenue boost compared to a non-hydrogen generating baseline IES while also providing an easily-adoptable framework which can help to improve the flexibility of future generation nuclear power plants.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗