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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Safe Reinforcement Learning-Based Transient Stability Control for Islanded Microgrids With Topology Reconfiguration

This paper proposes a safe reinforcement learning (RL)-based transient stability emergency control (TSEC) method for islanded microgrids. RL requires extensive interaction with the environment to learn control strategies, hence, a data-driven approach is used as a substitute for time-consuming time-domain simulation calculations. Deep sigma point processes (DSPP), which is a Gaussian process model, is utilized to predict the normal distribution of transient stability of microgrids and to construct a transient stability chance constraint. Reward-constrained policy optimization (RCPO) can simultaneously achieve objective prediction, policy learning, and constraint cost coefficient update across multiple timescales. RCPO interacts with the DSPP-based microgrid environment through a multi-process parallel manner, greatly increasing the training speed. Case studies on a real islanded microgrid demonstrate that the proposed method can efficiently and quickly obtain the optimal emergency control strategy while adhering to all hard constraints.

14 SOLAR ENERGY↗
DOE OSTI2020

Scalable Open-Air Deposition of Compact ETL TiOx on Perovskite for Fullerene-Free Solar Cells

We report on a scalable, low-temperature TiOx electron transport layer (ETL) produced directly on top of perovskite in an inverted architecture device by an open-air chemical vapor deposition (OA-CVD) process. The OA-CVD pyrolysis of a titanium ethoxide precursor forms a fully inorganic, conformal, and compact TiOx film. The resultant film is mechanically robust and exhibits a fracture toughness 30-fold higher than commonly used fullerene-based ETL films. The TiOx is an effective barrier layer against environmental degradation—unencapsulated devices with the TiOx ETL retain 60% of their initial efficiency after 1000 hours in ambient aging conditions—compared to devices with a fullerene ETL which were inoperable after 144 hours. Inverted architecture devices with an optimized TiOx ETL thickness of 70nm exhibited high open-circuit voltages of 1.08V. We comment on the photocatalytic properties of TiOx and the influence of an amorphous film on maximum power point stability.

Chen, Justin↗
DOE OSTI2022

Fitting $\overline{\nu}$ for minor Pu isotopes

After successful fitting of prompt $\overline{\nu}$ for 235 U, 238 U, and 239 Pu(n,f) using CGMF, we will move on to the minor plutonium isotopes. Minor isotopes pose a greater challenge both because there is less data available and we do not, by default, have parametrizations in CGMF already. To mitigate these challenges— and provide consistency within CGMF—we will take a stepped approach to the optimization. Continuing from the 239 Pu work, we will then fit 241 Pu(n,f) $\overline{\nu}$, where there is also a number of experimental measurements, keeping consistency between the parameters that are included in the calculation for 239 Pu and 241 Pu. With these parametrizations settled, we can consistently optimize 240 Pu(n,f) $\overline{\nu}$. Following that step, we will move on to 242 Pu(n,f) (and increasing neutron number) and 238 Pu(n,f) (and decreasing neutron number). By including the fissioning systems in this manner, we should be able to minimize the unknown parameters in CGMF. We will possibly also be able to develop systematics for the CGMF input parameters along the Pu isotopic chain. This work can serve as a guide to broadening the reactions available in CGMF. In this short report, we first give an example of how we have updated CGMF to include 240 Pu(n,f) and 242 Pu(n,f), keeping consistency with the current 239 Pu and 241 Pu calculations, but without rigorous optimization (Sec. 2). Then, we will shown in Section 3 what experimental data exist for the various isotopes to provide some insight into why 241 Pu and 239 Pu are used as anchor points.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2023

Fitting $\overline{ν}$ for Minor Pu Isotopes

After successful fitting of prompt ν for 235 U, 238 U, and 239 Pu(n,f) using CGMF, we have moved on to the minor plutonium isotopes. Minor isotopes pose a greater challenge both because there is less data available and we do not, by default, have parametrizations in CGMF already. Initially, we had planned to mitigate these challenges—and provide consistency within CGMF—by taking a stepped approach to the optimization. Continuing from the 239 Pu work, we would then fit 241Pu(n,f) $\overline{ν}$, where there is also a number of experimental measurements, keeping consistency between the parameters that are included in the calculation for 239 Pu and 241 Pu. With these parametrizations settled, we could consistently optimize 240 Pu(n,f) $\overline{ν}$. Following that step, we would move on to 242 Pu(n,f) (and increasing neutron number) and 238 Pu(n,f) (and decreasing neutron number). By including the fissioning systems in this manner, we should be able to minimize the unknown parameters in CGMF. We were also able to develop systematics for the CGMF input parameters along the Pu isotopic chain. However, after studies in the beginning of FY23, where we found reasonable agreement between CGMF and experimental prompt neutron multiplicities for 238−242 Pu, using a compound mass dependent parametrization from, and from discussions with I. Stetcu and P. Talou, we instead performed the evaluation of all five isotopes simultaneously. For all parameters in CGMF, they are either the same for each compound nucleus, or have a dependence on the compound mass. The details of these updates are given in. This report builds upon those details. In this short report, we first give an example of how we have updated CGMF to include 240 Pu(n,f) and 242 Pu(n,f), keeping consistency with the current 239 Pu and 241 Pu calculations, but without rigorous optimization (Sec. 2). Then, we will show in Section 3 what experimental data exist for the various isotopes to provide some insight into why 241 Pu and 239 Pu are used as anchor points. The evaluation is detailed in Section 4, and the comparison between CGMF calculations using the evaluated parameters and other prompt observables besides average neutron multiplicity are discussed in Section 2.2. Finally, we present conclusions and future work in Section 5.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2026

Multipoint Aerostructural Optimization of Wind Turbine Rotors Using a Coupled Blade‐Resolved Aerostructural Solver

Physics‐based design optimization workflows thread the needle between computational cost limitations and simulation complexity, often compromising between modeling detail and the range of operating design conditions. Multipoint aerostructural optimization of wind turbine rotors has so far been confined to low‐fidelity analyses or to high‐fidelity studies with simplified structural models, leaving the most complex design trade‐offs unexplored. We close this gap by performing the first tightly coupled gradient‐based multipoint aerostructural rotor optimization using 3D aerodynamic and structural solvers with discrete coupled adjoints. The optimizer simultaneously varies blade planform, airfoil shapes, and structural thickness through more than 270 design variables, minimizing a weighted combination of rotor mass and power across multiple wind speeds. Applied to a modified DTU 10‐MW benchmark under conservative structural and aerodynamic constraints, our multipoint optimization reduces rotor mass by up to 36% and increases power by 12%–15% across the main operating conditions; biasing the objective toward power yields power gains up to 18% and a 17% mass reduction. For a nominal wind distribution, 3‐point rotor designs accounting for low RPM and high thrust conditions capture dominant trade‐offs and outperform single‐point designs. Adding two off‐design points changes individual‐condition power by less than 3% but leaves the weighted average within 0.5%, and the mass‐power bias has a stronger effect on the final design than the operating‐point weighting itself. Our framework extends naturally to richer load cases and site‐specific wind distributions, providing a basis for high‐fidelity multipoint design earlier in industrial workflows.

17 WIND ENERGY↗
DOE OSTI2020

The effect of lighting environment on task performance in buildings – A review

The effects of indoor environmental conditions on human health, satisfaction, and performance have been the focal point of research for decades. This paper reviews and summarizes the impact of lighting environment on task performance, specifically for the built environment audience. Existing studies included a variety of performance tests on cognitive performance and perception, visual acuity and reaction, memory, reasoning, and labor productivity. Illuminance, luminance ratio and correlated color temperature were found to affect performance in different ways, reflecting the impact of experimental techniques, conditions, performance evaluation methods used and data analysis methods. These were reviewed and categorized, with discussion on limitations related to sample size, modeling approach, carryover effects and other factors affecting individual differences in performance, with recommendations for future improvement. Although no universal conclusions can be made, in general, task performance seems to improve with higher illuminances, contrast ratios in the range of 7–11:1 (while always making sure that glare will not occur in the space) and higher correlated color temperature, while spectral tuning in the red or blue wavelengths has also shown positive effects. To obtain more generic evidence, future studies should be more consistent in terms of experimental procedures and overall light conditions, and also consider the effects of vertical illuminance, daylight provision/control, and outside views on task performance. Finally, studying performance with multi-factorial designs in a human-centered optimized manner (such as deploying variable lighting scenarios optimized for various tasks) can lead to deeper understanding of lighting effects on task performance, and ultimately to improved lighting design and operation in buildings overall.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

McCormick envelopes in mixed-integer PDE-constrained optimization

McCormick envelopes are a standard tool for deriving convex relaxations of optimization problems that involve polynomial terms. Such McCormick relaxations provide lower bounds, for example, in branch-and-bound procedures for mixed-integer nonlinear programs but have not gained much attention in PDE-constrained optimization so far. This lack of attention may be due to the distributed nature of such problems, which on the one hand leads to infinitely many linear constraints (generally state constraints that may be difficult to handle) in addition to the state equation for a pointwise formulation of the McCormick envelopes and renders bound-tightening procedures that successively improve the resulting convex relaxations computationally intractable. We analyze McCormick envelopes for a model problem class that is governed by a semilinear PDE involving a bilinearity and integrality constraints. We approximate the nonlinearity and in turn the McCormick envelopes by averaging the involved terms over the cells of a partition of the computational domain on which the PDE is defined. This yields convex relaxations that underestimate the original problem up to an a priori error estimate that depends on the mesh size of the discretization. These approximate McCormick relaxations can be improved by means of an optimization-based bound-tightening procedure. We show that their minimizers converge to minimizers to a limit problem with a pointwise formulation of the McCormick envelopes when driving the mesh size to zero. We provide a computational example, for which we certify all of our imposed assumptions. The results point to both the potential of the methodology and the gaps in the research that need to be closed. Our methodology provides a framework first for obtaining pointwise underestimators for nonconvexities and second for approximating them with finitely many linear inequalities in an infinite-dimensional setting.

Approximations and Expansions↗
DOE OSTI2021

Manifold Sampling for Optimizing Nonsmooth Nonconvex Compositions

Here we propose a manifold sampling algorithm for minimizing a nonsmooth composition $f= h\circ F$, where we assume $h$ is nonsmooth and may be inexpensively computed in closed form and $F$ is smooth but its Jacobian may not be available. We additionally assume that the composition $h\circ F$ defines a continuous selection. Manifold sampling algorithms can be classified as model-based derivative-free methods, in that models of $F$ are combined with particularly sampled information about $h$ to yield local models for use within a trust-region framework. We demonstrate that cluster points of the sequence of iterates generated by the manifold sampling algorithm are Clarke stationary. We consider the tractability of three particular subproblems generated by the manifold sampling algorithm and the extent to which inexact solutions to these subproblems may be tolerated. Numerical results demonstrate that manifold sampling as a derivative-free algorithm is competitive with state-of-the-art algorithms for nonsmooth optimization that utilize first-order information about $f$.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Use of Frit‐Disc Crucible Sets to Make Solution Growth More Quantitative and Versatile

The recent availability of step‐edge, frit‐disc crucible sets (generally sold as Canfield Crucible Sets or CCS) has led to multiple innovations associated with the group's use of solution growth. The use of CCS allows for the clean separation of liquid from solid phases during the growth process. This clean separation enables the reuse of the decanted liquid, either allowing for simple, economic, savings associated with recycling expensive precursor elements or allowing for the fractionation of a growth into multiple, small steps, revealing the progression of multiple solidifications. Clean separation of liquid from solid phases also allows for the determination of the liquidus line (or surface) and the creation, or correction, of composition–temperature phase diagrams. The reuse of clean decanted liquid has also allowed to prepare liquids ideally suited for the growth of large single crystals of specific phases by tuning the composition of the melt to the optimal composition for growth of the desired phase, often with reduced nucleation sites. Finally, it is discussed how solution growth and CCS use can be harnessed to provide a plethora of composition–temperature data points defining liquidus lines or surfaces with differing degrees of precision to either test or anchor artificial intelligence and/or machine‐learning‐based attempts to augment and extend the limited experimentally determined database.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Exploring the relationship between deposition method, microstructure, and performance of Nb/Si-based superconducting coplanar waveguide resonators

Superconducting quantum circuits (SQC) are one of the most promising hardware platforms for quantum computing, yet their performance is currently limited by the presence of various structural defects inside the circuit's structure. Despite impressive progress in the past decade, a precise understanding of the origin of these defects from various fabrication processes and their impact on coherence is still lacking. Here, in this study, we performed a comprehensive investigation on the microstructure, superconductivity, and resonator quality factor of Nb films deposited by high-power impulse magnetron sputtering (HiPIMS) and direct current (DC) magnetron sputtering. A suite of characterization techniques, including electron microscopy with spectroscopy, secondary ion mass spectrometry, magneto-optical microscopy, and pump-probe reflectivity spectroscopy is used. We reveal that niobium (Nb) resonators fabricated using HiPIMS exhibit a smaller average grain size, thicker surface oxide with larger thickness variations (rougher surface), and a thicker amorphous Nb/Si interface layer compared to samples deposited by DC sputtering. We identified that the amorphous Nb oxides (mainly located at the Nb surface and along the grain boundaries) and Nb-Si amorphous layers (at the Nb/Si interface) are major and potential sources of two-level system (TLS), while off-stochiometric oxides and suboxides of Nb close to the surface, crystalline defects (i.e., dislocations at grain boundary, point defects introduced during deposition) are main contributors of non-TLS sources. Our findings clarify the relationship between different defects and coherence loss mechanisms, highlighting the importance of material microstructure control on performance optimization in SQC.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A hybrid analytical and numerical model for cross-over and performance decay in a unit cell vanadium redox flow battery

Developing an accurate and efficient model for cross-over is critical for improving the long-term performance of redox flow batteries (RFBs). Here, this work presents a hybrid analytical and numerical model that combines a two-dimensional analytical solution to the active species, a one-dimensional analytical model for cross-over mechanisms, and a zero-dimensional numerical model for outlet concentrations of reactants. By comparing with experiment over 41 cycles (ca. 144 h), the model reported a mean voltage difference of 0.0089 V, mean time difference of 14 s per cycle (of 3.5 h), maximum relative difference for capacity and energy of 1.34% and 1.63%, respectively. The predicted mean concentrations for V 2+ , V 3+ , and VO$_{2}^{+}$ in membrane are 65%~77% of measured values from the literature. Upon validation, the model reproduced behaviors in electrolyte imbalance similar to those observed in experiments and numerical models, and revealed the control of cross-over, self-discharge, stoichiometry of side reactions, and Coulombic efficiency on electrolyte imbalance. The model also demonstrates excellent computational efficiency for simulating 41 cycles (around 37,000 points) within 3~4 s. The demonstrated efficiency and accuracy for predicting cross-over and its impacts on voltage, capacity&energy decay, membrane concentrations, and electrolyte imbalance makes it a reliable tool for optimizing RFBs’ long-term performance.

25 ENERGY STORAGE↗
DOE OSTI2021

Review of Dew Point Evaporative Cooling Technology for Air Conditioning Applications

Indirect evaporative cooling has the potential to significantly improve the natural environment. It follows from a significant reduction in electricity consumption in the hot period, and hence lower operating costs for cooling systems. This paper presents the current state of knowledge and research directions on dew point indirect evaporative cooling. It was found that researchers focus on the development of dew point indirect evaporative coolers (DPIEC) by improving its design, geometry, water distribution, and new porous materials implementation. To evaluate the performance of new types of DPIEC, different methods are used by the scientists. Finally, optimized devices are studied in terms of their performance in different systems, like hybrid and desiccant systems, considering different climate conditions. Potential directions of development of evaporative technologies were indicated, such as increasing the coefficient of performance of solid desiccant evaporative cooling systems, developing novel geometry, and efficient water distribution, including development of porous materials.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Considering Strain Variation and Non-Type Strains for Yeast Metabolic Engineering Applications

A variety of yeast species have been considered ideal hosts for metabolic engineering to produce value-added chemicals, including the model organism Saccharomyces cerevisiae, as well as non-conventional yeasts including Yarrowia lipolytica, Kluyveromyces marxianus, and Pichia pastoris. However, the metabolic capacity of these microbes is not simply dictated or implied by genus or species alone. Within the same species, yeast strains can display distinct variations in their phenotypes and metabolism, which affect the performance of introduced pathways and the production of interesting compounds. Moreover, it is unclear how this metabolic potential corresponds to function upon rewiring these organisms. These reports thus point out a new consideration for successful metabolic engineering, specifically: what are the best strains to utilize and how does one achieve effective metabolic engineering? Understanding such questions will accelerate the host selection and optimization process for generating yeast cell factories. In this review, we survey recent advances in studying yeast strain variations and utilizing non-type strains in pathway production and metabolic engineering applications. Additionally, we highlight the importance of employing portable methods for metabolic rewiring to best access this metabolic diversity. Finally, we conclude by highlighting the importance of considering strain diversity in metabolic engineering applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Power system load flexibility forecasting

The example embodiments are directed to a system and method for forecasting load flexibility of a power grid. In one example, the method includes receiving temperature values associated with temperature set points of a plurality of loads that are included on a power grid, forecasting a flexibility of the plurality of loads using a polynomial-time mixed-integer non-linear programming (MINLP) optimization based on the received temperature values for the plurality of loads, and outputting information about the forecasted flexibility for display to a display device. The MINLP optimization performs the forecasting of the load flexibility on a fine-grained basis in comparison to conventional methods and is still fast enough that it can be computed in real-time.

Genc, Sahika↗
DOE OSTI2022

Prediction and compression of lattice QCD data using machine learning algorithms on quantum annealer

We present regression and compression algorithms for lattice QCD data utilizing the efficient binary optimization ability of quantum annealers. In the regression algorithm, we encode the correlation between the input and output variables into a sparse coding machine learning algorithm. The trained correlation pattern is used to predict lattice QCD observables of unseen lattice configurations from other observables measured on the lattice. In the compression algorithm, we define a mapping from lattice QCD data of floating-point numbers to the binary coefficients that closely reconstruct the input data from a set of basis vectors. Since the reconstruction is not exact, the mapping defines a lossy compression, but, a reasonably small number of binary coefficients are able to reconstruct the input vector of lattice QCD data with the reconstruction error much smaller than the statistical fluctuation. In both applications, we use D-Wave quantum annealers to solve the NP-hard binary optimization problems of the machine learning algorithms.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Electric vehicle supply equipment location and capacity allocation for fixed-route networks

Electric vehicle (EV) supply equipment location and allocation (EVSELCA) problems for freight vehicles are becoming more important because of the trending electrification shift. Some previous works address EV charger location and vehicle routing problems simultaneously by generating vehicle routes from scratch. Although such routes can be efficient, introducing new routes may violate practical constraints, such as drive schedules, and satisfying electrification requirements can require dramatically altering existing routes. To address the challenges in the prevailing adoption scheme, we approach the problem from a fixed -route perspective. We develop a mixed -integer linear program, a clustering approach, and a metaheuristic solution method using a genetic algorithm (GA) to solve the EVSELCA problem. The clustering approach simplifies the problem by grouping customers into clusters, while the GA generates solutions that are shown to be nearly optimal for small problem cases. A case study examines how charger costs, energy costs, the value of time (VOT), and battery capacity impact the cost of the EVSELCA. Charger equipment costs were found to be the most significant component in the objective function, leading to a substantial reduction in cost when decreased. VOT costs exhibited a significant decrease with rising energy costs. Further, an increase in VOT resulted in a notable rise in the number of fast chargers. Longer EV ranges decrease total costs up to a certain point, beyond which the decrease in total costs is negligible.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Reduced-order CFD modeling of cryogenic hydrogen isotope extrusion for pellet fueling

This study presents a reduced-order model (ROM) for computational fluid dynamics (CFD) simulations of cryogenic hydrogen isotope extrusions, focusing on protium (H₂) and deuterium (D₂) piston extruders. Using a 2D axisymmetric ROM in ANSYS-Polyflow, significant computational savings were achieved (runtime reduced from 9∼24 h to 3∼5 min), with extrusion force discrepancies between the 2D ROM and 3D models being on the order of 1%. Parametric studies identified optimal cutoff shear rates in the viscosity model (0.01/s for H₂ and 0.001/s for D₂), providing recommendations for future simulations. Finally, a comprehensive comparison of ROM results with experimental data was performed across varying geometries, cryogenic materials, temperatures, extrusion lengths, and piston velocities. Predictions at low extrusion temperatures met the objective of providing quick and efficient solutions with an acceptable extrusion force error of approximately 10% or less, validating the effectiveness of the 2D ROM approach. However, at high temperatures closer to the triple point, extrusion force error grows, which necessitates developing an improved model that accounts for temperature effects, e.g. melting. Nevertheless, the findings still represent a significant improvement in efficiency of CFD modeling of cryogenic hydrogenic extrusion. The ROM framework can also be extended to tritium (T2) and screw extruders, which will ultimately provide a fast and effective tool for optimizing pellet injector design for ITER and future reactor systems.

Fan, Joy [ORNL] (ORCID:0000000229751735)↗
DOE OSTI2020

A novel triple power cycle featuring a gas turbine cycle with supercritical carbon dioxide and organic Rankine cycles: Thermoeconomic analysis and optimization

In this study, a novel triple power cycle is proposed where waste heat from a gas turbine cycle is utilized to drive a supercritical carbon dioxide (s-CO 2 ) recompression cycle and a recuperative organic Rankine cycle (ORC) in sequence. A detailed thermoeconomic model is developed and implemented in MATLAB to evaluate the performance of the proposed cycle under different operating conditions. Optimization using a particle swarm optimization (PSO) algorithm is performed to minimize the levelized cost of electricity (LCOE) and determine the optimum design conditions of the cycle. The optimization results show that for a 100 MW cycle, the overall thermal efficiency and LCOE are 0.521 and $\$52.819$/MWh, respectively. The turbine inlet temperature of the gas turbine and s-CO 2 cycles are found as the most influential parameters on the thermoeconomic performance of the triple cycle. The proposed triple cycle shows an excellent waste energy recovery potential and superiority over a very thermodynamically efficient cycle from the literature, which included a gas turbine topping cycle and a complex cascade s-CO 2 power cycle used a bottoming cycle. As a result, the proposed triple cycle shows up to 0.9% points higher efficiency while it has fewer heat exchangers and turbomachinery than the cycle from the literature.

30 DIRECT ENERGY CONVERSION↗