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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Novel geometries for air-cooled condensation of ammonia-water mixtures

An analytical and experimental investigation of air-cooled condensers for small-scale ammonia-water absorption heat pumps is presented. Conventional round-tube corrugated fin design and a novel multi-pass tube array design are considered for a condenser operating at severe ambient conditions within a compact footprint. Segmental heat and mass transfer models are developed to gain a deeper understanding of the characteristics of each design. Predicted heat duties are within 5% of the measured values. The limitations of correlations to predict air-side pressure drop in corrugated fins are identified. The performance of the novel multi-pass tube array condenser was comparable to that of conventional condensers, but is determined to be air-side limited throughout length of the heat exchanger. An improved multi-pass condenser design with fins for increased air-side area is proposed using the insights gained from the modeling and experiments. In closing this design meets the heat duty requirements at severe ambient conditions, while decreasing the size of the heat exchanger by 33%.

42 ENGINEERING↗
DOE OSTI2021

Analysis of Post-Deposition Recrystallization Processing via Indium Bromide of Cu(In,Ga)Se2 Thin Films

Cu(In,Ga)Se2 (CIGS) thin films were deposited at low temperature (350 °C) and high rate (10 µm/h) by a single stage process. The effect of post-deposition treatments at 400 °C and 500 °C by indium bromide vapor were studied and compared to the effect of a simple annealing under selenium. Structural, electrical, and chemical analyses demonstrate that there is a drastic difference between the different types of annealing, with the ones under indium bromide leading to much larger grains and higher conductivity. These properties are associated with a modification of the elemental profiles, specifically for gallium and sodium.

14 SOLAR ENERGY↗
DOE OSTI2025

A split ribozyme system for in vivo plant RNA imaging and genetic engineering

RNA plays a central role in plants, governing various cellular and physiological processes. Monitoring its dynamic abundance provides a discerning understanding of molecular mechanisms underlying plant responses to internal (developmental) and external (environmental) stimuli, paving the way for advances in plant biotechnology to engineer crops with improved resilience, quality and productivity. In general, traditional methods for analysis of RNA abundance in plants require destructive, labour-intensive and time-consuming assays. To overcome these limitations, we developed a transformative innovation for in vivo RNA imaging in plants. Specifically, we established a synthetic split ribozyme system that converts various RNA signals to orthogonal protein outputs, enabling in vivo visualisation of various RNA signals in plants. We demonstrated the utility of this system in transient expression experiments (i.e., leaf infiltration in Nicotiana benthamiana ) to detect RNAs derived from transgenes and tobacco rattle virus, respectively. Also, we successfully engineered a split ribozyme-based biosensor in Arabidopsis thaliana for in vivo visualisation of endogenous gene expression at the cellular level, demonstrating the feasibility of multi-scale (e.g., cellular and tissue level) RNA imaging in plants. Furthermore, we developed a platform for easy incorporation of different protein outputs, allowing for flexible choice of reporters to optimise the detection of target RNAs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI1968

Nuclear Physics Made Very, Very Easy

The fundamental approach to nuclear physics was prepared to introduce basic reactor principles to various groups of non-nuclear technical personnel associated with NERVA Test Operations. NERVA Test Operations functions as the field test group for the Nuclear Rocket Engine Program. Nuclear Engine for Rocket Vehicle Application (NERVA) program is the combined efforts of Aerojet-General Corporation as prime contractor, and Westinghouse Astronuclear Laboratory as the major subcontractor, for the assembly and testing of nuclear rocket engines. Development of the NERVA Program is under the direction of the Space Nuclear Propulsion Office, a joint agency of the U. S. Atomic Energy Commission and the National Aeronautics and Space Administration. This report is being reprinted for use in the U. S. Atomic Energy Commission and National Aeronautics and Space Administration educational and technology utilization programs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Universal finite-time thermodynamics of many-body quantum machines from Kibble-Zurek scaling

We demonstrate the existence of universal features in the finite-time thermodynamics of quantum machines by considering a many-body quantum Otto cycle in which the working medium is driven across quantum critical points during the unitary strokes. Specifically, we consider a quantum engine powered by dissipative energizing and relaxing baths. We show that under very generic conditions, the output work is governed by the Kibble-Zurek mechanism; i.e., it exhibits a universal power-law scaling with the driving speed through the critical points. We also optimize the finite-time thermodynamics as a function of the driving speed. The maximum power and the corresponding efficiency take a universal form, and are reached for an optimal speed that is governed by the critical exponents. We exemplify our results by considering a transverse-field Ising spin chain as the working medium. For this model, we also show how the efficiency and power vary as the engine becomes critical.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Towards a Robust Sampling Approach: A Computational Review and Design

As pointed out in several other works, the estimation of the reliability of the electrical grid can not be conducted without the estimation of the stochastic phenomena of electicity demand and electricity production by variable renewable sources. Therefore, sampling procedures have become integral in the design of engineering structures and analysis. Commonly referred to as Monte Carlo uncertainty analysis or integration, the general objective of these procedures is to establish specifics about the uncertainty of an output characteristic of such an engineering system, given uncertainty about its input characteristics. These sampling procedures are applied in a context in which establishing such specifics cannot be performed through other means. Variance-reduction techniques are designed to lessen the variability among estimators to estimate statistics of those output uncertainties. Importance-sampling techniques, on the other hand, are designed to reduce the number of samples needed to estimate a particular statistic—e.g., a tail probability. The combination of these approaches can reduce the computational burden considerably for a particular estimator and statistic. Importance sampling—geared and designed as it is toward improving a particular estimator—suffers, unfortunately, from the unintended consequence of reducing the performance of other estimators in terms of their variance. The objective of this paper is to offer an alternative sampling procedure where this variance does not grow unacceptably large for a suite of estimators. Moreover, it is anticipated that, with additional knowledge of how an engineering output characteristic responds to its input characteristics, tuning parameters of the input’s sampling procedure can be set to improve the output characteristic’s estimation. This work proves the effectiveness of the suggested alternative approach. Such positive outcome will lead to a decrease of the computational burden of performing stochastic optimization of integrated energy systems (e.g., components dispatch, and portfolio composition). In particular, capturing the contribution to the overall system cost of rare and unlikely events and patterns of the electricity demand and production will become less computationally expensive. This is due to the fact that the approach demonstrated here will allow the sampling of those rare occurrences more frequently without misrepresenting their probabilistic impacts.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Safeguards by Design Projects (Final Report FY2021)

This University Engagement project challenged engineering students at universities, that do not have Bachelor degrees in nuclear engineering but do have research reactors and some nuclear engineering coursework, to incorporate Safeguards by Design concepts into their Senior Capstone Design Project. This University Engagement project was part of the U. S. Department of Energy’s (DOE) National Nuclear Security Administration (NNSA), Office of Defense Nuclear Nonproliferation, Office of International Nuclear Safeguards, Next Generation Safeguards Initiative, Human Capital Development: University Engagement Program. This program exposed university students with Mechanical Engineering majors and Nuclear Engineering minors to the concepts of international nuclear safeguards.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Calibration of RAFM Micromechanical Model for Creep Using Bayesian Optimization for Functional Output

A Bayesian optimization procedure is presented for calibrating a multimechanism micromechanical model for creep to experimental data of F82H steel. Reduced activation ferritic martensitic (RAFM) steels based on Fe(8–9)%Cr are the most promising candidates for some fusion reactor structures. Although there are indications that RAFM steel could be viable for fusion applications at temperatures up to 600°C, the maximum operating temperature will be determined by the creep properties of the structural material and the breeder material compatibility with the structural material. Due to the relative paucity of available creep data on F82H steel compared to other alloys such as Grade 91 steel, micromechanical models are sought for simulating creep based on relevant deformation mechanisms. As a point of departure, this work recalibrates a model form that was previously proposed for Grade 91 steel to match creep curves for F82H steel. Due to the large number of parameters (9) and cost of the nonlinear simulations, an automated approach for tuning the parameters is pursued using a recently developed Bayesian optimization for functional output (BOFO) framework (Huang et al., 2021, “Bayesian optimization of functional output in inverse problems,” Optim. Eng., 22, pp. 2553–2574). Incorporating extensions such as batch sequencing and weighted experimental load cases into BOFO, a reasonably small error between experimental and simulated creep curves at two load levels is achieved in a reasonable number of iterations. In conclusion, validation with an additional creep curve provides confidence in the fitted parameters obtained from the automated calibration procedure to describe the creep behavior of F82H steel.

42 ENGINEERING↗
DOE OSTI2022

Suppressing Charged Cation Antisites via Se Vapor Annealing Enables p-Type Dopability in AgBiSe 2 –SnSe Thermoelectrics

Cation disordering is commonly found in multinary cubic compounds, but its effect on electronic properties has been neglected because of difficulties in determining the ordered structure and defect energetics. An absence of rational understanding of the point defects present has led to poor reproducibility and uncontrolled conduction type. AgBiSe 2 is a representative compound that suffers from poor reproducibility of thermoelectric properties, while the origins of its intrinsic n-type conductivity remain speculative. Here, it is demonstrated that cation disordering is facilitated by Bi Ag charged antisite defects in cubic AgBiSe 2 which also act as a principal donor defect that greatly controls the electronic properties. Using density functional theory calculations and in situ Raman spectroscopy, how saturation annealing with selenium vapor can stabilize p-type conductivity in cubic AgBiSe 2 alloyed with SnSe at high temperatures is elucidated. With stable and controlled hole concentration, a peak is observed in the weighted mobility and the density-of-states effective mass in AgBiSnSe 3 , implying an increased valley degeneracy in this system. These findings corroborate the importance of considering the defect energetics for exploring the dopability of ternary thermoelectric chalcogenides and engineering electronic bands by controlling self-doping.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Dynamic Species Reduction for Multi-Cycle CFD Simulations (Final Technical Report)

This project primarily sought to address some of the computational cost concerns of detailed simulations by developing improved methods of handling species transport, and chemical kinetics evaluation in a commercial 3D Computational Fluid Dynamics (CFD) environment. Secondary goals were to apply these techniques to fuels and conditions of interest to better understand the key species and reactions required to adequately capture cycle to cycle coupling. Improved modeling will lead to better understanding of these combustion modes and their dependence on fuel composition, which can then enable more clean and efficient engines, ultimately benefiting the consumer as well as the general public. Two approaches were used to address the computational cost. A “Dynamic Species Reduction” (DSR) procedure was developed to remove chemical species from the simulation during periods when chemical reactions were not expected to be important, particularly during gas exchange when temperatures are low and little fuel remains. This modelling procedure automatically detects relevant species to retain in the simulation domain based on their local concentration, removes species below a specified concentration threshold, and then adjusts the remaining species mass to conserve not only the number of H, C, and O atoms in each cell, but also the relative proportions between species and the heating value of the mixture in every cell. The second procedure was a “Product Directed Remapping” (PDR) updates the algorithm used to group individual computational cells for chemical kinetics evaluation to account for non-uniform temperature distributions and the CO to CO 2 ratio in the cells. The model techniques developed in this work successfully demonstrated computational performance improvements for a range of conditions relevant for Highly Dilute SI and HCCI engine operation. Runtime reductions of 10% were observed for small mechanisms, with further reductions of up to 36% observed for larger mechanisms. Improvements were primarily related to reducing the number of chemical species tracked during the gas exchange process using the Dynamic Species Reduction method. With smaller benefits observed from changes to the kinetics binning and evaluation strategy in the post combustion region using the PDR method. The results of this work show the potential for improved computational runtime for complicated simulations. They can and should be extended to additional conditions and new bio-derived and renewable fuels as they are developed and new kinetic mechanisms become available.

10 SYNTHETIC FUELS↗
DOE OSTI2021

Report on Properties and Microstructure of 3D Printed Inc-718

The report presents the microstructure and mechanical properties of 3D printed Inconel 718 to assess its potential use as a structural material for the Transformation Challenge Reactor (TCR). The structural components near the outlet of the core will experience significant neutron fluxes and outlet coolant temperatures from the hot standby temperature of 300°C to nearly 550°C at the center of the part. These components must support the core in appropriate loading conditions and require structural analysis at relevant temperatures. Strong spatial and chemical heterogeneity was found in as-built (ASB) Inconel 718. Three heat treatments were designed and conducted to simplify the microstructure and determine how each precipitating phase contributed to the overall strength. Baseline mechanical properties were measured from uniaxial tensile tests on subsize SS-J2 specimens at room temperature and at elevated temperatures of 300, 450, and 600°C. Microstructure electron microscopy was performed on ASB Inconel 718 and heat treated to correlate the observed mechanical properties with nanoscale features. Homogenization of the microstructure led to a highly ductile Inconel with lower strength compared with wrought Inconel 718. The tensile properties of additively manufactured 718 using a standard ASTMrecommended heat treatment were consistent with literature and with the ASTM for the properties of this alloy. A higher fraction of the δ phase led to shorter uniform elongation without altering other engineering properties.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Toward engineering lattice structures with the material point method (MPM)

This study examines the potential of two variants of the material point method—the generalized interpolation material point (GIMP) and dual domain material point (DDMP) methods—in developing a robust computational framework for engineering lattice structures under different loading conditions. The study begins with assessing the ability of the two methods in predicting elastic buckling phenomena using column geometries with and without initial geometric imperfections. The results indicate that both methods effectively capture buckling phenomena when initial geometric imperfections are introduced. After this verification step, we create several models of tetrahedral lattice structures with varying strut diameter and orientation and subject them to quasi-static loading. We then validate the numerical results using laboratory test results. The results show that, while both methods accurately predict load–displacement curves in the pre-buckling regime, their predictive capabilities diminish in the post-buckling regime. Through visual comparison between the numerical and experimental deformed shapes, it appears that the discrepancies between model and experimental results are attributed to initial geometric imperfections in the lattices that occurred during 3D printing. We then establish a second set of lattice models where different types of initial geometric imperfections are considered. The results from these models show that imperfections have a negligible influence in the pre-buckling regime but affect the behavior considerably in the post-buckling regime. As a final step in this work, we subject the lattice models to impact loading and employ hypothetical soft and stiff materials. These results show that the lattice stiffness, which depends on material stiffness, strut diameter, and orientation, significantly influences the ability of a lattice structure to resist impact. In particular, we find that a stiffer lattice (i.e., one made with a stiff material and thicker struts) is capable of absorbing more energy than a softer one during impact. Although material nonlinearities, inelasticity, and detailed contact formulations are not considered in this study, the findings obtained herein lay the groundwork for engineering lattice structures under extreme loading conditions through a simulation-driven framework based on particle-based methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

NucMesh: nuclear reactor geometry creation and mesh generation module in NEMoSys

NucMesh is a parameterized geometry and mesh generator for nuclear reactors developed within the Nuclear Energy Modeling System NEMoSys at Illinois Rocstar. NEMoSys is a platform developed for mesh generation, adaptive refinement, and solution verification. NucMesh is implemented to be generalized and extensible with a robust computer aided design engine and multiple mesh generation algorithms for unstructured triangular, quad-dominant, and structured quadrilateral meshing. In this paper, we present the geometric and meshing features of NucMesh. Geometrically objects are constructed bottom-to-top and overlaps are addressed automatically. A sophisticated object tracking algorithm prevents data from being lost for segmented objects. We discuss the primitive objects of circle and polygons that constitute the module and show how they are used with example inputs. Arrays of primitives and arrays of arrays are utilized to build large assemblies of objects. The concept of saved objects is discussed to demonstrate how repetitive objects can be reused easily and augmented in place. Three dimensional meshes can be obtained through mesh extrusion where all materials and side sets are extended to three dimensions. We show that side sets can be defined nearly anywhere within the geometry and can then be applied to the mesh. Finally, example reactor meshes are demonstrated for the Idaho National Laboratory Advanced Test Reactor and Los Alamos National Lab Empire reactor, both of which use control drums that NucMesh handles easily. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Parameter uncertainties for imperfect surrogate models in the low-noise regime

Abstract Bayesian regression determines model parameters by minimizing the expected loss, an upper bound to the true generalization error. However, this loss ignores model form error, or misspecification, meaning parameter uncertainties are significantly underestimated and vanish in the large data limit. As misspecification is the main source of uncertainty for surrogate models of low-noise calculations, such as those arising in atomistic simulation, predictive uncertainties are systematically underestimated. We analyze the true generalization error of misspecified, near-deterministic surrogate models, a regime of broad relevance in science and engineering. We show that posterior parameter distributions must cover every training point to avoid a divergence in the generalization error and design a compatible ansatz which incurs minimal overhead for linear models. The approach is demonstrated on model problems before application to thousand-dimensional datasets in atomistic machine learning. Our efficient misspecification-aware scheme gives accurate prediction and bounding of test errors in terms of parameter uncertainties, allowing this important source of uncertainty to be incorporated in multi-scale computational workflows.

Swinburne, Thomas D. (ORCID:0000000232554257)↗
DOE OSTI2022

INL Digital Engineering: Model-Based Design, Digital Threads, Digital Twins, Artificial Intelligence, and Extended Reality for Complex Energy Systems

This presentation showcases digital transformation efforts carried by the Idaho National Laboratory (INL) Digital Innovation Center of Excellence (DICE). Digital Engineering technologies are described, including Model-Based Systems Engineering, Digital Thread, Digital Twins, Artificial Intelligence, and Extended Reality. Selected projects across the laboratory that have used or are currently using a digital engineering design approach are presented.

08 HYDROGEN↗
DOE OSTI2022

Effects of stratification and charge cooling on combustion in a gasoline direct-injection compression ignition (GDCI) engine

With the development of low temperature engine combustion strategies, performance of gasoline-type fuels under compression ignition conditions has attracted extensive research interest. Meanwhile, for the sake of co-optimization of engines and fuels for future ground transportation, identification and evaluation of general fuel properties should be a core research priority instead of endless testing of specific fuels. In this study, the roles of fuel octane sensitivity in characterizing the ignition performance of gasoline surrogates have been systematically investigated under typical gasoline direct ignition compression ignition (GDCI) engine conditions using 3D combustion CFD simulation, especially considering the subsequent in-cylinder charge stratification and charge cooling. Two different operating conditions, high boost pressure low boost temperature (beyond-RON) case and low boost pressure high boost temperature (beyond-MON) case, were considered. By comparing with our previous zero-dimensional chemical kinetic study of gasoline surrogates in advanced compression ignition (ACI) engines, the effects of stratification and charge cooling on the combustion processes are investigated. It is found that different fuel octane sensitivities lead to slight difference in equivalence ratio stratification and charge cooling due to differences in volatility. However, fuel reactivity is still the more dominant factor than the stratification and charge cooling effects in determining combustion phasing. The present results help to justify the P-T domain framework for engine autoignition analysis of overlapping pressure-temperature trajectory with ignition delay iso-contour. Here, the results also provide useful guidance to the understanding of GCI combustion process, and to the evaluation of controlling fuel properties and the selection of alternative fuels in GCI engines.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Topological alloy engineering and locally linearized gap dependence on concentration

Alloy engineering is a well-established approach to tune various materials’ properties, but its application to topological alloys remains rudimentary. Of special interest is the band gap, the most defining property of topological materials; however, the concentration dependence of energy gaps in topological alloys remains unknown. Here we systematically investigate the band gap evolution of a topological alloy as a function of alloy concentration, using KZnSb 1-x Bi x as a prototype, based on first-principles calculations. In contrast to the well-established smooth bowing curve for a trivial gap in semiconductor alloys, we found that the topological gap evolves generally with a complex fragmented pattern due to topological phase transitions, and most strikingly a linear dependence on concentration locally in each distinct phase. Such gap linearization is fundamentally rooted in the linear dependence on alloy concentration of spin-orbit coupling (SOC) that predominantly determines a topological gap. Furthermore, we demonstrate topological alloy engineering as a general approach to tune the topological order by modulating the band edge composition and degeneracy through the alloying-induced interplay of SOC and atomic orbital on-site energy, while the linear gap dependence on alloy concentration remains independent of the degree of topological order.

36 MATERIALS SCIENCE↗