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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,423 records · Page 79
All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

Transmissive Diffractive Optical Element Solar Concentrators

Solar-thermal-radiation concentrators in the form of transmissive diffractive optical elements (DOEs) have been proposed as alternatives to mirror-type solar concentrators now in use. In comparison with functionally equivalent mirror-type solar concentrators, the transmissive, diffractive solar concentrators would weigh and cost less, and would be subject to relaxed mechanical tolerances. A DOE concentrator would be made from a thin, flat disk or membrane of a transmissive material having a suitable index of refraction. By virtue of its thinness, the DOE concentrator would have an areal mass density significantly less than that of a functionally equivalent conventional mirror. The DOE concentrator would have a relatively wide aperture--characterized by a focal-length/aperture-diameter ratio ('f number') on the order of 1. A kinoform (a surface-relief phase hologram) of high diffractive order would be microfabricated onto one face of the disk. The kinoform (see figure) would be designed to both diffract and refract incident solar radiation onto a desired focal region, without concern for forming an image of the Sun. The high diffractive order of this kinoform (in contradistinction to the low diffractive orders of some other kinoforms) would be necessary to obtain the desired f number of 1, which, in turn, would be necessary for obtaining a desired concentration ratio of 2,500 or greater. The design process of optimizing the concentration ratio of a proposed DOE solar concentrator includes computing convolutions of the optical bandwidth of the Sun with the optical transmission of the diffractive medium. Because, as in the cases of other non-imaging, light-concentrating optics, image quality is not a design requirement, the process also includes trading image quality against concentration ratio. A baseline design for one example calls for an aperture diameter of 1 m. This baseline design would be scalable to a diameter as large as 10 m, or to a smaller diameter for a laboratory test article. Initial calculations have indicated that the characteristics of the test article would be readily scalable to a full-size unit.

Baron, Richard↗
NASA NTRS1972

Development of termination and utilization concepts for flat conductor cables. Volume 3: Cost study comparison, flat versus round conductor cable

A cost study comparing flat conductor cable (FCC) with small-gage wire (SGW) and conventional round conductor cable (RCC) is presented. This study was based on a vehicle wiring system consisting of 110,000 ft of conventional RCC equally divided between AWG sizes 20,22, and 24 using MIL-W-81044-type wire and MIL-C-26500 circular connectors. Basic cost data were developed on a similar-sized commercial jet airplane wiring system on a previous company R&D program in which advanced wiring techniques were carried through equivalent installations on an airplane mockup; and on data developed on typical average bundles during this program. Various cost elements included were engineering labor, operations (manufacturing) labor, material costs, and cost impact on payload. Engineering labor includes design, wiring system integration, wiring diagrams and cable assembly drawings, wire installations, and other related supporting functions such as the electronic data processing for the wiring. Operations labor includes mockup, tooling and production planning, fabrication, assembly, installation, and quality control cost impact on payload is the conversion of wiring system weight variations through use of different wiring concepts to program payload benefits in terms of dollars.

Source record↗
DOE OSTI2025

Multi-fidelity learning for interatomic potentials: low-level forces and high-level energies are all you need

The promise of machine learning interatomic potentials (MLIPs) has led to an abundance of public quantum mechanical (QM) training datasets. The quality of an MLIP is directly limited by the accuracy of the energies and atomic forces in the training dataset. Unfortunately, most of these datasets are computed with relatively low-accuracy QM methods, e.g. density functional theory with a moderate basis set. Due to the increased computational cost of more accurate QM methods, e.g. coupled-cluster theory with a complete basis set (CBS) extrapolation, most high-accuracy datasets are much smaller and often do not contain atomic forces. The lack of high-accuracy atomic forces is quite troubling, as training with force data greatly improves the stability and quality of the MLIP compared to training to energy alone. Because most datasets are computed with a unique level of theory, traditional single-fidelity (SF) learning is not capable of leveraging the vast amounts of published QM data. In this study, we apply multi-fidelity learning (MFL) to train an MLIP to multiple QM datasets of different levels of accuracy, i.e. levels of fidelity. Specifically, we perform three test cases to demonstrate that MFL with both low-level forces and high-level energies yields an extremely accurate MLIP—far more accurate than a SF MLIP trained solely to high-level energies and almost as accurate as a SF MLIP trained directly to high-level energies and forces. Therefore, MFL greatly alleviates the need for generating large and expensive datasets containing high-accuracy atomic forces and allows for more effective training to existing high-accuracy energy-only datasets. Indeed, low-accuracy atomic forces and high-accuracy energies are all that are needed to achieve a high-accuracy MLIP with MFL.

36 MATERIALS SCIENCE↗
NASA NTRS1992

Functional implications of component commonality in operational systems

The application of commonality in a system represents an attempt to reduce costs by reducing the number of unique components. Research in this area has primarily addressed a significant benefit of commonality, the reduction of parts inventories in assemble-to-order manufacturing systems. Likewise, in an operational system subject to component failures, spares inventories are reduced through the increased commonality of components. However, commonality tends to degrade system performance parameters, a degradation that can preclude commonality in resource-constrained systems such as spacecraft. The functional impacts of component commonality on a system is addressed in a manner that allows inclusion in a commonality analysis.

Thomas, Lawrence D.↗
DOE OSTI2021

Density Functional Theory Investigation of the NiO@Graphene Composite as a Urea Oxidation Catalyst in the Alkaline Electrolyte

Developing efficient and low-cost urea oxidation reaction (UOR) catalysts is a promising but still challenging task for environment and energy conversion technologies such as wastewater remediation and urea electrolysis. In this work, NiO nanoparticles that incorporated graphene as the NiO@Graphene composite were constructed to study the UOR process in terms of density functional theory. The single-atom model, which differed from the previous heterojunction model, was employed for the adsorption/desorption of urea and CO 2 in the alkaline media. As demonstrated from the calculated results, NiO@Graphene prefers to adsorb the hydroxyl group than urea in the initial stage due to the stronger adsorption energy of the hydroxyl group. After NiOOH@Graphene was formed in the alkaline electrolyte, it presents excellent desorption energy of CO 2 in the rate-determining step. Electronic density difference and the d band center diagram further confirmed that the Ni(III) species is the most favorable site for urea oxidation while facilitating charge transfer between urea and NiO@Graphene. Moreover, graphene provides a large surface for the incorporation of NiO nanoparticles, enhancing the electron transfer between NiOOH and graphene and promoting the mass transport in the alkaline electrolyte. Notably, this work provides theoretical guidance for the electrochemical urea oxidation work.

25 ENERGY STORAGE↗
DOE OSTI2020

Functional materials and devices by self-assembly

The field of self-assembly has moved far beyond early work, where the focus was primarily the resultant beautiful two- and three-dimensional structures, to a focus on forming materials and devices with important properties either otherwise not available, or only available at great cost. Over the last few years, materials with unprecedented electronic, photonic, energy-storage, and chemical separation functionalities were created with self-assembly, while at the same time, the ability to form even more complex structures in two and three dimensions has only continued to advance. Self-assembly crosscuts all areas of materials. Functional structures have now been realized in polymer, ceramic, metallic, and semiconducting systems, as well as composites containing multiple classes of materials. Finally, as the field of self-assembly continues to advance, the number of highly functional systems will only continue to grow and make increasingly greater impacts in both the consumer and industrial space.

Materials for Devices↗
NASA NTRS2014

Printable Spacecraft: Flexible Electronic Platforms for NASA Missions

Why printed electronics? Why should NASA use printed electronics to make a spacecraft? Three words provide the answer: universal, impactful, progressive. The technology is universal because the applications it can affect are broad and diverse from simple sensors to fully functional spacecraft. The impact of flexible, printed electronics range from straightforward mass, volume and cost savings all the way to enabling new mission concepts. The benefits of the technology will become progressively larger from what is achievable today so that investments will pay dividends tomorrow, next year and next decade. We started off three years ago asking the question can you build an entire spacecraft out of printed electronics? In other words, can you design and fabricate a fully integrated, electronic system that performs the same end-to-end functions of a spacecraft - take scientific measurements, perform data processing, provide data storage, transmit the data, powers itself, orients and propels itself - all out of thin flexible sheets of printed electronics? This "Printable Spacecraft" pushes the limits of printed flexible electronics performance. So the answer is yes, more or less. In our studies for the NIAC (NASA Innovative Advanced Concepts) program, we have explored this question further, to explain more completely what "more or less" means and to outline what is needed to make the answer a definitive "yes". Despite its appealing "Flat Stanley"-like (a book series by Jeff Brown) qualities, making a Printable Spacecraft is not as easy as flattening the Cassini spacecraft with a bulletin board, as was Stanley Lamchop's fate. But, if NASA invests in the design challenges, the materials challenges, the performance challenges of printed electronics, it might find itself with a spacecraft that can enable as many adventures and advantages as Flat Stanley including putting it in an envelope and mailing it to the planet of your choice. You just have to let your imagination take over. In this report we document the work of the Phase 2 Printable Spacecraft task conducted under the guidance and leadership of the NIAC program. In Phase One of the NIAC task entitled "Printable Spacecraft", we investigated the viability of printed electronics technologies for creating multi-functional spacecraft platforms. Mission concepts and architectures that could be enhanced or enabled with this technology were explored. In Phase 2 we tried to answer the more practical questions such as can you really build a multi-functional printed electronic spacecraft system? If you do, can it survive the space environment? Even if it can, what benefit does a printable system provide over a traditional implementation of a spacecraft?

Materials↗
NASA NTRS1978

Continuous Czochralski Growth. Silicon Sheet Growth Development of the Large Area Silicon Sheet Task of the Low Cost Silicon Solar Array Project

The JPL Continuous Czochralski Growth Facility is now essentially complete and is functional. In this reporting period, a silicon lump recharging device was designed, and a prototype was built which performed well in simulated recharge tests. The large chamber (designed to accommodate a 14-inch hot zone) was put into operation initially with the standard hot zone in order to compare performance with previous experience. Some modifications were made to the hot zones in the larger chamber due to considerably larger radiative heat losses. Several short (one-ingot) runs were performed and four continuous runs were attempted. The largest continuous run lasted 64 hours and produced 57 kilograms of ingot.

Merz, F.↗
NASA NTRS1999

Advanced Life Support System Value Metric

The NASA Advanced Life Support (ALS) Program is required to provide a performance metric to measure its progress in system development. Extensive discussions within the ALS program have led to the following approach. The Equivalent System Mass (ESM) metric has been traditionally used and provides a good summary of the weight, size, and power cost factors of space life support equipment. But ESM assumes that all the systems being traded off exactly meet a fixed performance requirement, so that the value and benefit (readiness, performance, safety, etc.) of all the different systems designs are considered to be exactly equal. This is too simplistic. Actual system design concepts are selected using many cost and benefit factors and the system specification is defined after many trade-offs. The ALS program needs a multi-parameter metric including both the ESM and a System Value Metric (SVM). The SVM would include safety, maintainability, reliability, performance, use of cross cutting technology, and commercialization potential. Another major factor in system selection is technology readiness level (TRL), a familiar metric in ALS. The overall ALS system metric that is suggested is a benefit/cost ratio, SVM/[ESM + function (TRL)], with appropriate weighting and scaling. The total value is given by SVM. Cost is represented by higher ESM and lower TRL. The paper provides a detailed description and example application of a suggested System Value Metric and an overall ALS system metric.

Jones, Harry W.↗
DOE OSTI2022

Stochastic Learning Approach for Binary Optimization: Application to Bayesian Optimal Design of Experiments

Here, we present a novel stochastic approach to binary optimization suited for optimal experimental design (OED) for Bayesian inverse problems governed by mathematical models such as partial differential equations. The OED utility function, namely, the regularized optimality criterion, is cast into a stochastic objective function in the form of an expectation over a multivariate Bernoulli distribution. The probabilistic objective is then solved by using a stochastic optimization routine to find an optimal observational policy. This formulation (a) is generally applicable to binary optimization problems with soft constraints and is ideal for OED and sensor placement problems; (b) does not require differentiability of the original objective function (e.g., a utility function in OED applications) with respect to the design variable, and thus it enables direct employment of sparsity-enforcing penalty functions such as $\ell_0$, without needing to utilize a continuation procedure or apply a rounding technique; (c) exhibits much lower computational cost than traditional gradient-based relaxation approaches; and (d) can be applied to both linear and nonlinear OED problems with proper choice of the utility function. The proposed approach is analyzed from an optimization perspective with detailed convergence analysis of the optimization approach and is also analyzed from a machine learning perspective with correspondence to policy gradient reinforcement learning. The approach is demonstrated numerically by using an idealized two-dimensional Bayesian linear inverse problem and validated by extensive numerical experiments carried out for sensor placement in a parameter identification setup.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Multilevel Monte Carlo Estimators For Derivative-Free Optimization Under Uncertainty

Optimization is a key tool for scientific and engineering applications; however, in the presence of models affected by uncertainty, the optimization formulation needs to be extended to consider statistics of the quantity of interest. Optimization under uncertainty (OUU) deals with this endeavor and requires uncertainty quantification analyses at several design locations; i.e., its overall computational cost is proportional to the cost of performing a forward uncertainty analysis at each design location. An OUU workflow has two main components: an inner loop strategy for the computation of statistics of the quantity of interest, and an outer loop optimization strategy tasked with finding the optimal design, given a merit function based on the inner loop statistics. Here, in this work, we propose to alleviate the cost of the inner loop uncertainty analysis by leveraging the so-called multilevel Monte Carlo (MLMC) method, which is able to allocate resources over multiple models with varying accuracy and cost. The resource allocation problem in MLMC is formulated by minimizing the computational cost given a target variance for the estimator. We consider MLMC estimators for statistics usually employed in OUU workflows and solve the corresponding allocation problem. For the outer loop, we consider a derivative-free optimization strategy implemented in the SNOWPAC library; our novel strategy is implemented and released in the Dakota software toolkit. We discuss several numerical test cases to showcase the features and performance of our approach with respect to its Monte Carlo single fidelity counterpart.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1986

Dynamic remapping of parallel computations with varying resource demands

A large class of computational problems is characterized by frequent synchronization, and computational requirements which change as a function of time. When such a problem must be solved on a message passing multiprocessor machine, the combination of these characteristics lead to system performance which decreases in time. Performance can be improved with periodic redistribution of computational load; however, redistribution can exact a sometimes large delay cost. We study the issue of deciding when to invoke a global load remapping mechanism. Such a decision policy must effectively weigh the costs of remapping against the performance benefits. We treat this problem by constructing two analytic models which exhibit stochastically decreasing performance. One model is quite tractable; we are able to describe the optimal remapping algorithm, and the optimal decision policy governing when to invoke that algorithm. However, computational complexity prohibits the use of the optimal remapping decision policy. We then study the performance of a general remapping policy on both analytic models. This policy attempts to minimize a statistic W(n) which measures the system degradation (including the cost of remapping) per computation step over a period of n steps. We show that as a function of time, the expected value of W(n) has at most one minimum, and that when this minimum exists it defines the optimal fixed-interval remapping policy. Our decision policy appeals to this result by remapping when it estimates that W(n) is minimized. Our performance data suggests that this policy effectively finds the natural frequency of remapping. We also use the analytic models to express the relationship between performance and remapping cost, number of processors, and the computation's stochastic activity.

Nicol, D. M.↗
DOE OSTI2021

Chemiresistor sensor based on ion-imprinted polymer (IIP)-functionalized rGO for Cd(II) ions in water

This study reports the design and development of a novel chemiresistor (CR) sensor using ion imprinted polymer (IIP)-functionalized reduced graphene oxide (rGO) [IIP/rGO-CR] for cadmium ions (Cd(II)) determination in water. The sensor consisted of a CR transducer made of rGO channel bridging source and drain electrodes prepared by self-assembly and thermal reduction of graphene oxide (GO) on Au interdigitated electrodes chip fabricated on Si/SiO 2 substrate. The IIP was then grafted on rGO using surface-initiated reversible addition-fragmentation chain transfer (RAFT) polymerization with polyethylenimine (PEI) and methylacrylic acid (MAA) as dual functional monomers and Cd(II) ions as template through UV light-initiated copolymerization. The IIP functionalized on rGO acted as an effective recognition element that modulated the resistance of rGO-CR upon binding of Cd(II), enabling Cd(II) detection at ppb level in aqueous solutions. The prepared IIP/rGO-CR sensor worked effectively in the linear range of 2~200ppb and achieved a limit of detection (LOD) of 0.83 ppb, which is lower than the World Health Organization guidelines of 3ppb for drinking water quality. The developed sensor of IIP/rGO-CR showed a high selectivity against a variety of trace and heavy metal ions found in water and good stability for up to 60 days when stored at room temperature for Cd(II) determination in water. Further, the sensor was successfully applied to analyzing Cd(II) spiked in tap, lake and river waters with a 94.5%–113.5% recovery, demonstrating a high degree of accuracy even in complex water samples. Finally, our results illustrated that the CR sensor of IIP functionalized rGO provides a potential platform for sensitive, robust and low-cost environmental analysis of Cd(II) in water.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Metal–Organic Frameworks as Catalysts for (De)Hydrogenation: Progress, Challenges, and Perspectives

Storing hydrogen through chemical bonding in liquid-organic hydrogen carriers (LOHCs) offers a safer and more practical approach for hydrogen transportation compared to physical liquefaction, which is limited by low volumetric efficiency and gas release. The efficiency of LOHC systems is highly dependent on effective catalysts, which are typically composed of transition metals supported on metal oxides. However, these materials often rely upon costly noble metals, and their nonuniform nature limits mechanistic insights and structure–function relationships that could improve catalyst design. Metal–organic frameworks (MOFs) are promising alternatives to existing catalysts due to their crystalline, tunable, and porous nature. However, their use as catalysts for (de)hydrogenation reactions remains largely underexplored. Related to this, we identify two general classes of MOFs reported as catalysts for (de)hydrogenation reactions: MOFs as scaffolds for catalytically active species and MOFs that function as reactive materials themselves. MOF composites anchor reactive nanoparticles or homogeneous species, imparting reactivity to the framework. The confinement effects experienced by the affixed species, combined with favorable substrate adsorption interactions or acid sites provided by the MOF, enhance the stability, selectivity, and activity of these catalysts for (de)hydrogenation reactions. Additionally, catalytically active MOFs often feature open metal sites at the node or undergo postsynthetic modification at either node or linker to impart reactivity. Here, taking inspiration from these materials, we outline the current state and key challenges of utilizing MOFs as (de)hydrogenation catalysts and propose research pathways to advance materials in this field for energy applications.

Catalysts↗
DOE OSTI2024

Robust wind farm layout optimization

Wake interactions in wind farms cause losses in annual energy production (AEP) on the order of 10%. Wind farm designers optimize the layout of the farm to mitigate wake losses, especially in the dominant site-specific wind directions. As wind turbines and wind farms grow in scale, optimization becomes more complex. Offshore wind farms regularly comprise more than 100 wind turbines and are characterized by complex boundaries due to shipping lanes, neighboring wind farms, and other constraints. Layout optimization methods are broadly split between gradient-based and gradient-free approaches. Gradient-based approaches can converge quickly and perform well for smaller, academic problems but are often sensitive to initial conditions and tuning parameters and require expert knowledge to use. On the other hand, gradient-free approaches can be more robust to problem complexities. We present a robust layout optimization approach based on a random search algorithm. The algorithm is intended for those who are not optimization experts and has few tuning parameters that need specification to achieve satisfactory results. Unlike off-the-shelf methods, which use generally available, non-domain-specific optimization routines that accept as inputs an optimization function and constraint definitions, this approach takes advantage of the relative computational costs of the different evaluations by evaluating cheaper computations first (boundary and minimum distance constraints) and running expensive AEP evaluations only if all other checks pass. Moreover, an outer genetic algorithm allows multiple solutions to evolve in parallel, enabling rapid solution development on high-performance computers. We discuss the relative ease of selecting necessary tuning parameters and demonstrate the efficacy of the genetic random search on a complex layout problem consisting of placing 70 turbines in a nonconvex and unconnected boundary region.

17 WIND ENERGY↗
DOE OSTI2023

Modified Virtual Oscillator Based Operation of Grid Forming Converters with Single Voltage Sensor

Virtual oscillator based control architecture for grid forming converter with inner current control loop for additional objective accomplishments is proposed in this paper. In general, virtual oscillator is based on Lienard type of oscillator equation with a cubic nonlinearity. Virtual oscillator alone cannot accommodate unbalanced or harmonic mitigation while operating converters in grid forming mode. Therefore, to accomplish better tracking performance, incorporating the provision for nonlinear and/or unbalanced loads, an inner current control loop is utilized which is based upon Lyapunov energy function type control architecture due to its advantages. To reduce the overall cost of implementation and ensure proper phase difference in the generated voltages, the implemented virtual oscillator operates with only one voltage feedback from the point of common coupling as presented in this paper. To verify the effectiveness of the proposed approach, the overall system has been modeled in MATTLAB/Simulink and PLECS domain and case studies showing the successful production of low harmonic load voltages under nonideal loading condition along with other important results are presented in this paper.

dual second order generalized integrator↗
DOE OSTI2023

Direct conversion of syngas to lower olefins precursors of jet fuel and chemicals

This study investigates the direct conversion of syngas to olefins as a pathway to produce sustainable aviation fuels. This approach combines methanol/ dimethyl ether synthesis with methanol-to-olefins into one unit operation to avoid the equilibrium limitation of methanol synthesis and the Anderson–Schulz–Flory distribution limitations from the Fischer Tropsch process. The ability to combine reactor functionalities into a single step are also projected to significantly lower capital costs over current synthesis approaches for the syngas to olefins process.

10 SYNTHETIC FUELS↗