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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 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Monte Carlo study for optimal conditions in single-shot imaging with femtosecond x-ray laser pulses

Intense x-ray pulses from x-ray free electron lasers (XFELs) enable the unveiling of atomic structure in material and biological specimens via ultrafast single-shot exposures. As the radiation is intense enough to destroy the sample, a new sample must be provided for each x-ray pulse. These single-particle delivery schemes require careful optimization, though systematic study to find such optimal conditions is still lacking. We have investigated two major single-particle delivery methods: particle injection as flying objects and membrane-mount as fixed targets. The optimal experimental parameters were searched for via Monte Carlo simulations to discover that the maximum single-particle hit rate achievable is close to 40%.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Study on Electropolishing of N-Doped Niobium Surfaces and 650 MHz Cavity for High-Gradient Performance

This presentation provides an overview of the latest studies on electropolishing (EP) of nitrogen-doped niobium surfaces and 650 MHz cavities. The first study focuses on optimizing EP parameters to achieve a pit-free surface on N-doped niobium, highlighting the effects of process conditions on surface pitting and suggesting strategies for mitigation. The second study investigates the EP of 650 MHz cavities to achieve high-gradient performance comparable to that of 1.3 GHz niobium SRF cavities. Additionally, an example of a 650 MHz single-cell cavity is presented, demonstrating its record-high gradient achieved through optimized EP conditions.

43 PARTICLE ACCELERATORS↗
DOE OSTI2010

Protocol for high-fidelity readout in the photon-blockade regime of circuit QED

The driven-damped Jaynes-Cummings model in the regime of strong coupling is found to exhibit a coexistence between the quantum photon blockaded state and a quasicoherent bright state. We characterize the slow time scales and the basin of attraction of these metastable states using full quantum simulations. This form of bistability can be useful for implementing a qubit readout scheme that does not require additional circuit elements. We propose a coherent control sequence that makes use of a simple linear chirp of drive amplitude and frequency as well as qubit frequency. By optimizing the parameters of the system and the control pulse, we demonstrate theoretically very high readout fidelities (>98%) and high contrast with experimentally realistic parameters for qubits implemented in the circuit QED architecture.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Catalytic resonance theory for parametric uncertainty of programmable catalysis

Microkinetic models are useful tools for screening catalytic materials; however, errors in their input parameters can lead to significant uncertainty in model predictions of catalyst performance. Here, in this work, we investigate the impact of linear scaling and Brønsted-Evans-Polanyi relation parametric uncertainty on microkinetic predictions of programmable-catalyst performance. Two case studies are considered: a generic A-to-B prototype reaction and the oxygen evolution reaction (OER). The results show that error-unaware models can accurately predict trends and, for the prototype reaction, values of optimal waveform parameters. The specific model parameters driving output uncertainty are identified via variance-based global sensitivity analysis. However, predictions of dynamic rate enhancement can decrease when uncertainty is propagated into the models. In both cases, we identify operating conditions where the programmable catalyst achieves a rate enhancement of at least one order of magnitude despite parametric uncertainty in the model, supporting programmable catalysis as a viable strategy for exceeding the Sabatier limit.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

MODELING AND OPTIMIZATION OF A PCM-BASED OCEAN THERMAL ENERGY HARVESTER FOR POWERING UNMANNED UNDERWATER VEHICLES

As oceans cover over 70% of the planet’s surface, they represent a large reservoir of resources that remained vastly untapped. Uncrewed Underwater Vehicles (UUVs) are becoming key technology for ocean exploration. Ocean thermal gradient is a permanent and reliable energy source that can be used to power UUVs using phase change material (PCM)-based thermal engines. However, the main drawback of this technology is its low conversion efficiency. When using PCM-based thermal engines to power UUVs, there are different energy conversion stages, thermal-hydraulic, hydraulic-kinetic, kinetic-electrical, dependent of a wide variety of parameters. Thus, optimization of the overall energy conversion is still a challenge for powering the increasing energy demanding UUVs for long missions. The goal of this study is to propose a PCM-based ocean thermal energy harvesting system for powering the Solo II float. Using the ocean thermal energy reduces the cost for battery replacement and expands the float’s mission time. For this purpose, we developed a multiphysics model for a system consisting of thermal material, hydraulic, and electrical systems. This system is designed to provide the electrical power needed for the instruments aboard the underwater vehicle. The models of the hydraulic and the electric systems are implemented in MATLAB-Simulink/Simscape environment. The final model developed can provide 13.66 kJ of electrical energy, which is more than 1.5 times the energy requirement per cycle for the SOLO II float.

Ouro-Koura, Habilou↗
DOE OSTI2011

Beam Line Design and Beam Physics Study of Energy Recovery Linac Free Electron Laser at Peking University

Energy recovering linac (ERL) offers an attractive alternative for generating intense beams of charged particles by approaching the operational efficiency of a storage ring while maintaining the superior beam quality typical of a linear accelerator. In ERLs, the decelerated beam cancels the beam loading effects of the accelerated beam with high repetition rate. Therefore, ERLs can, in principle, accelerate very high average currents with only modest amounts of RF power. So the efficiency of RF power to beam is much higher. Furthermore, the energy of beam to dump is lower, so it will reduce dump radiation. With the successful experiments in large maximum-to-injection energy ratio up to 51:1 and high power FEL up to 14kW, the use of ERL, especially combining with superconducting RF technology, provides a potentially powerful new paradigm for generation of the charged particle beams used in MW FEL, synchrotron radiation sources, high-energy electron cooling devices and so on. The 3+1/2 DC-SC photo injector and two 9cell TESLA superconducting cavity for IR SASE FEL in PKU provides a good platform to achieve high average FEL with Energy Recovery. The work of this thesis is on Beam line design and Beam dynamics study of Energy Recovery Linac Free Electron Laser for Peking University. It is the upgrade of PKU facility, which is under construction. With ERL, this facility can work in CW mode, so it can operate high average beam current without RF power constraint in main linac and generate high average FEL power. Moreover, it provides a test facility to study the key technology in ERL. System parameters are optimized for PKU ERL-FEL. The oscillation FEL output power is studied with different bunch charge, transverse emittance, bunch length and energy spread. The theory of optimal RF power and Q{sub ext} with ERL and without ERL is analyzed and applied to PKU injector and linac including microphonic effect. pace charge effect in the injector and merger is studied for beam energy at ~5MeV. Simulation shows that in the 3+1/2 DC- C injector, there is a region the beam could be over focused by RF electromagnetic field and the transverse emittance in the transport line up to linac will increase instantly due to over focusing. In order to eliminate this effect on beam emittance, several solutions are investigated to avoid over focusing. This result is very important for beam loading experiment for low bunch charge operation. Meanwhile, different merger structures are compared in terms of error sensitivity and emittance increase with space charge effect. In recirculation beam line, a new symmetric 180{degree} arc structure is designed. It fulfills the achromatic condition and adjustable bunch compression. These two parameters are controlled by different Quads knob. With this novel structure, the recirculation lattice can achieve path length adjustment, bunch compression and decompression in a large range. With beamline error, the beam central orbit will deviate from the designed trajectory. An orbit correction system is optimized, which balances between cost and performance of orbit after correction at design level. Different methods are used to estimate its robustness. The BBU instability, especially multi-pass BBU imposed a potentially severe limitation to the average current that can be accelerated in an ERL. Simulation gives the harmful HOMs and predicts that the threshold average current in this machine is much higher than the possible operation current. This work is based on the existing facility in PKU, so it provides guidelines for the facility operation and upgrade in the future. The theoretical analysis of ERL requirement and FEL requirement on beam transport line and beam property paves the way for future ERL research.

43 PARTICLE ACCELERATORS↗
DOE OSTI2013

Note: Characteristic beam parameter for the line electron gun

We have optimized the beam parameters of line source electron gun using Stanford Linear Accelerator Centre electron beam trajectory program (EGUN), utilizing electrostatic focusing only. We measured minimum beam diameter as 0.5 mm that corresponds to power density of 68.9 kW/cm{sup 2} at 13.5 mm in the post-anode region which is more than two-fold (33 kW/cm{sup 2}), of the previously reported results. The gun was operated for the validation of the theoretical results and found in good agreement. The gun is now without any magnetic and electrostatic focusing thus much simpler and more powerful.

43 PARTICLE ACCELERATORS↗
DOE OSTI2016

Shear Alignment of Diblock Copolymers for Patterning Nanowire Meshes

Metallic nanowire meshes are useful as cheap, flexible alternatives to indium tin oxide – an expensive, brittle material used in transparent conductive electrodes. We have fabricated nanowire meshes over areas up to 2.5 cm 2 by: 1) mechanically aligning parallel rows of diblock copolymer (diBCP) microdomains; 2) selectively infiltrating those domains with metallic ions; 3) etching away the diBCP template; 4) sintering to reduce ions to metal nanowires; and, 5) repeating steps 1 – 4 on the same sample at a 90° offset. We aligned parallel rows of polystyrene-b-poly(2-vinylpyridine) [PS(48.5 kDa)-b-P2VP(14.5 kDa)] microdomains by heating above its glass transition temperature (T g ≈ 100°C), applying mechanical shear pressure (33 kPa) and normal force (13.7 N), and cooling below T g . DiBCP samples were submerged in aqueous solutions of metallic ions (15 – 40 mM ions; 0.1 – 0.5 M HCl) for 30 – 90 minutes, which coordinate to nitrogen in P2VP. Subsequent ozone-etching and sintering steps yielded parallel nanowires. We aimed to optimize alignment parameters (e.g. shear and normal pressures, alignment duration, and PDMS thickness) to improve the quality, reproducibility, and scalability of meshes. We also investigated metals other than Pt and Au that may be patterned using this technique (Cu, Ag).

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2023

Development of a Reactive Force Field for Simulating Photoinitiated Acrylate Polymerization

Light-driven and photo-curable polymer based additive manufacturing (AM) has enormous potential due to its excellent resolution and precision. Acrylated radical chain-growth polymerized resins are widely used in photopolymer AM due to their fast kinetics, and often serve as a departure point for developing other resin materials for photopolymer-based AM technologies. For successful control of the photopolymer resins, the molecular basis of the acrylate free-radical polymerization has to be understood in detail. We present an optimized reactive force field (ReaxFF) for molecular dynamics (MD) simulations of acrylate polymer resins that captures radical polymerization thermodynamics and kinetics. The force field is trained against an extensive training set including density functional theory (DFT) calculations of reaction pathways along the radical polymerization from methyl acrylate to methyl butyrate, bond dissociation energies, and structures and partial charges of several molecules and radicals. We also found that it was critical to train the force field against an incorrect, nonphysical reaction pathway observed in simulations that used parameters not optimized for acrylate polymerization. As a result, the parameterization process utilizes a parallelized search algorithm, and the resulting model can describe polymer resin formation, crosslinking density, conversion rate, and residual monomers of the complex acrylate mixtures.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Computer-aided diagnosis for classifying benign versus malignant thyroid nodules based on ultrasound images: A comparison with radiologist-based assessments

Purpose: To develop a semiautomated computer-aided diagnosis (CAD) system for thyroid cancer using two-dimensional ultrasound images that can be used to yield a second opinion in the clinic to differentiate malignant and benign lesions. Methods: A total of 118 ultrasound images that included axial and longitudinal images from patients with biopsy-confirmed malignant (n = 30) and benign (n = 29) nodules were collected. Thyroid CAD software was developed to extract quantitative features from these images based on thyroid nodule segmentation in which adaptive diffusion flow for active contours was used. Various features, including histogram, intensity differences, elliptical fit, gray-level co-occurrence matrixes, and gray-level run-length matrixes, were evaluated for each region imaged. Based on these imaging features, a support vector machine (SVM) classifier was used to differentiate benign and malignant nodules. Leave-one-out cross-validation with sequential forward feature selection was performed to evaluate the overall accuracy of this method. Additionally, analyses with contingency tables and receiver operating characteristic (ROC) curves were performed to compare the performance of CAD with visual inspection by expert radiologists based on established gold standards. Results: Most univariate features for this proposed CAD system attained accuracies that ranged from 78.0% to 83.1%. When optimal SVM parameters that were established using a grid search method with features that radiologists use for visual inspection were employed, the authors could attain rates of accuracy that ranged from 72.9% to 84.7%. Using leave-one-out cross-validation results in a multivariate analysis of various features, the highest accuracy achieved using the proposed CAD system was 98.3%, whereas visual inspection by radiologists reached 94.9% accuracy. To obtain the highest accuracies, “axial ratio” and “max probability” in axial images were most frequently included in the optimal feature sets for the authors’ proposed CAD system, while “shape” and “calcification” in longitudinal images were most frequently included in the optimal feature sets for visual inspection by radiologists. The computed areas under curves in the ROC analysis were 0.986 and 0.979 for the proposed CAD system and visual inspection by radiologists, respectively; no significant difference was detected between these groups. Conclusions: The use of thyroid CAD to differentiate malignant from benign lesions shows accuracy similar to that obtained via visual inspection by radiologists. Thyroid CAD might be considered a viable way to generate a second opinion for radiologists in clinical practice.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2024

The Case for Reducing Emissions from Heavy-Duty Off-Road Applications via Ducted Fuel Injection

Designers of heavy-duty diesel engines use a variety of techniques to improve efficiency and reduce pollutant emissions. Ducted fuel injection (DFI), high fuel injection pressures, optimized injection orifices, multiple injection sites, and oxygenated fuels are a few techniques used by designers to improve fuel/charge-gas mixtures within the combustion chamber to improve efficiency and emissions results. Ducted fuel injection (DFI) has been proven to substantially reduce soot for low- and mid-load conditions in heavy duty engines, without significantly increasing nitrogen oxides (NO x ). This study investigates the performance of DFI utilizing conventional diesel fuel and the potential the technique has for future research utilizing varieties of test fuels and operating parameter values. Optimization for high engine efficiency and low emissions will help facilitate DFI deployment for substantial environmental benefits in heavy-duty sectors where electrification and/or carbon-free fuels aren’t feasible.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Leverage modern artificial intelligence (AI) enabled systems for waste reduction

Manufacturing industries continue to face challenges in reducing waste, as upstream strategies such as source reduction and product redesign require a deeper understanding of processes compared to conventional recycling methods. Recent advancements in artificial intelligence (AI) and machine learning (ML) have opened new opportunities to integrate modern computational techniques with traditional waste minimization strategies. This paper explores AI-enabled approaches for product redesign, source reduction, and recycling that can significantly reduce waste generation while improving efficiency and sustainability. AI-driven material substitution and lightweighting in product design enable discovery of novel materials with optimized properties, reducing waste without compromising performance. Reinforcement learning models optimize process parameters, raw material specifications, and machine sequencing to minimize production losses, while Industrial Internet of Things (IIoT) systems paired with AI analytics enhance real-time waste tracking, predictive maintenance, and quality inspection. Furthermore, AI-based demand forecasting and production planning reduce overproduction and excess inventory, as demonstrated in industrial applications. In recycling, ML-powered pattern recognition and robotic sorting technologies achieve higher accuracy in waste segregation, directly improving recycling efficiency. Complementary solutions such as smart bins and AI-enabled waste pickup scheduling optimize collection logistics, reducing both costs and emissions. Although implementation requires upfront investment in infrastructure and training, the long-term benefits include higher material efficiency, reduced waste, improved product quality, and stronger sustainability outcomes across the supply chain. By leveraging AI-enabled systems, manufacturers can align waste minimization efforts with circular economy principles, creating scalable solutions for both industry and society.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Studies on Printability Methodologies and Directed-Energy-Deposition-Fabricated Iron Alloys for Nuclear Applications

This report provides results from a printability study of laser directed energy deposition (DED)-based additive manufacturing of nuclear-grade stainless steels as well as DED process parameter development for austenitic Alloy 709 (A709) and ferritic/martensitic Grade 91 (G91) and Grade 92 (G92) steels. The printability study includes the use of machine learning and physics-based modeling via commercial software such as FLOW-3D for insights into the impact of the alloy composition, particularly the carbon content, on the printability of stainless steels during the DED process. In the DED process development work, 1 cm 3 alloy blocks were deposited with broad ranges of laser powers, scan speeds, and hatch spacings to optimize the build quality, resulting in densities of more than 99.8% for all three alloys. The microstructure and mechanical properties were characterized using electron microscopy, X-ray diffraction, and Vickers hardness measurements. Further, tensile samples were extracted from DED-fabricated alloys utilizing the optimized process parameters. The present work provides guidance and progress towards the successful deployment of the DED process for the fabrication of structural components of nuclear reactors.

36 MATERIALS SCIENCE↗
DOE OSTI2010

Effect of Fuel Fraction on Small Modified CANDLE Burn-up Based Gas Cooled Fast Reactors

A conceptual design study of Gas Cooled Fast Reactors with Modified CANDLE Burn-up has been performed. The objective of this research is to get optimal design parameters of such type reactors. The parameters of nuclear design including the critical condition, conversion ratio, and burn-up level were compared. These parameters are calculated by variation in the fuel fraction 47.5% up to 70%. Two dimensional full core multi groups diffusion calculations was performed by CITATION code. Group constant preparations are performed by using SRAC code system with JENDL-3.2 nuclear data library. In this design the reactor cores with cylindrical cell two dimensional R-Z core models are subdivided into several parts with the same volume in the axial directions. The placement of fuel in core arranged so that the result of plutonium from natural uranium can be utilized optimally for 10 years reactor operation. Modified CANDLE burn-up was established successfully in a core radial width 1.4 m. Total thermal power output for reference core is 550 MW. Study on the effect of fuel to coolant ratio shows that effective multiplication factor (k{sub eff}) is in almost linear relations with the change of the fuel volume to coolant ratio.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2015

Multicaloric effect in bi-layer multiferroic composites

The multicaloric effect was theoretically proposed in 2012 and, despite numerous follow up studies, the effect still awaits experimental confirmation. The main limitation is the fact that the multicaloric effect is only observed at a temperature equal to the transition temperature of the magnetic and electric phases coexisting within a multiferroic (MF) (i.e., T ≈ T{sub c}{sup m} ≈ T{sub c}{sup e}). Such condition is hard to fulfill in single phase MFs and a solution is to develop suitable composite MF materials. Here, we examine the multicaloric effect in a bi-layer laminated composite MF in order to determine the optimal design parameters for best caloric response. We show that magnetically induced multicaloric effect requires magnetic component of heat capacity smaller than that of the electric phase, while the layer thickness of the magnetic phase must be at least 5 times the thickness of the electric phase. The electrically induced multicaloric effect requires the magnetic layer to be 10% of the electric phase thickness, while its heat capacity must be larger than that of the electric phase. These selection rules are generally applicable to bulk as well as thin film MF composites for optimal multicaloric effect.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Removal of Congo Red from Aqueous Solution by Hydroxyapatite Nanoparticles Loaded on Zein as an Efficient and Green Adsorbent: Response Surface Methodology and Artificial Neural Network-Genetic Algorithm

This study is based on the application of hydroxyapatite nanoparticles loaded on Zein (Zein/nHAp) as an efficient adsorbent for the removal of Congo red from aqueous solutions. The properties of the adsorbent were characterized using various techniques including FT-IR, XRD, FE-SEM, and BET. The influence of five parameters such as pH, temperature, contact time, initial dye concentration, and adsorbent dosage on the removal percentage of the dye was investigated. The optimum conditions of 5.83, 34.32 °C, 5.20 min, 392.10 ppm, and 0.007 g were achieved for pH, temperature, contact time, initial dye concentration, and adsorbent dosage, respectively. The maximum removal percentage of 99.48% was obtained under the optimum condition that exhibited high adsorption potential of the used adsorbent. Central composite design (CCD) under response surface methodology and artificial neural network-genetic algorithm (ANN-GA) were utilized for optimization of parameters. Comparison of the results of the two models in terms of coefficient of determination (R{sup 2}) and mean absolute percentage error confirmed the prediction potential of CCD and ANN-GA. Higher ability and accuracy of ANN-GA in prediction was found based on given results. The experimental equilibrium data were studied by Langmuir, Freundlich, Temkin and Dubinin-Radushkevic isotherm models and explored that the data well presented by Langmuir model with maximum adsorption capacity of 416.66 mg/g. The adsorption kinetic was well-fitted by the pseudo-second-order model. The thermodynamics of the adsorption displayed spontaneous and endothermic nature of the process. Regeneration investigation showed that Zein/nHAp can impressively be reused, indicating that the adsorbent was a promising one for the removal of Congo red from aqueous solution. Graphical Abstract: .

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2017

Estimation of LOCA break size using cascaded support vector regression - 334

A failure of emergency core cooling system (ECCS) during a certain small break loss of coolant accident (SBLOCA) can cause a severe core uncovery and fuel failure. The safety injection systems (SISs) might not function properly in case of a SBLOCA, due to the slight change of pressure in the pipes. Early trend of the major parameters has to be observed and the accurate information has to be given to the nuclear power plant (NPP) operators by precisely identifying the break size to effectively manage accidents. In this study, the objective is to provide to operators the information on the break size in a short time by considering the accident situations such as hot-leg LOCA, cold-leg LOCA, steam generator tube rupture (SGTR). A cascaded support vector regression (CSVR) is used in order to estimate the break size. The simulation data set was obtained from the optimized power plant reactor 1000 (OPR1000) using modular accident analysis program (MAAP) code. And genetic algorithm (GA) was used to select the input variables of the CSVR model and optimize its parameters. As a result of this study, the CSVR model estimate very well the break size of LOCAs. If the operators can predict the break size in the LOCA, they can response quickly and properly to LOCA circumstances to prevent the core uncovery and fuel failure. Also, it will be possible to more efficiently manage beyond design basis accidents. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗