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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 145 records · Page 8

Metagenome-assembled genomes from topsoils along a hillslope water gradient across early snowmelt to late summer in East River, CO

Drought is changing the American Mountain West at unprecedented rates with unknown consequences to soil microbiome composition and function. As a part of LBNL Watershed Science Focus Area (SFA), we investigated shifts in microbial community and transcriptional activity on a subalpine conifer-meadow transition zone throughout the summer of 2023 as soil dried down. This work took place in Crested Butte, CO on Snodgrass mountain, using a proxy for drought conditions.Here we present metagenome assembled genomes (MAGs) for the bacterial and archaeal community at 0-10cm from three sites along a hillslope water gradient across five timepoints from early snowmelt to late summer. 42 metagenomes were sequenced at Joint Genome Institute (JGI) and can be found under the JGI GOLD (Genomes Online Database) sequencing project Gs0166660. Metagenomes were assembled through an inhouse pipeline (see methods), binned using four autobinners (concoct, maxbin2, metabat2, and vamb) and consolidated using dastool. The consolidated bins from all metagenomes were pooled, filtered by completeness (>70%) and contamination (<10%), and dereplicated at 95% ANI using drep. This dataset (1) a zip file of 157 MAGs (as fasta files, Gs0166660_bins_tar.gz), (2) sample metadata file with sample IGSNs (International Generic Sample Numbers) (samples.csv), (3) bounding box coordinates for the sampled locations (Gs0166660.kml), (4) metagenome assembly and coassembly metadata file listing IMG/M (Integrated Microbial Genomes/Metagenomes) metagenome accessions linking samples to metagenomes (EastRiver_Drought_ESSDive_Metadata.csv), (5) location metadata file (locations.csv), (6) file-level metadata file (flmd.csv) and (7) data dictionary (dd.csv) file.This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

54 ENVIRONMENTAL SCIENCES↗

Train Like a (Var)Pro: Efficient Training of Neural Networks with Variable Projection

Deep neural networks (DNNs) have achieved state-of-the-art performance across a variety of traditional machine learning tasks, e.g., speech recognition, image classification, and segmentation. The ability of DNNs to efficiently approximate high-dimensional functions has also motivated their use in scientific applications, e.g., to solve partial differential equations and to generate surrogate models. In this paper, we consider the supervised training of DNNs, which arises in many of the above applications. We focus on the central problem of optimizing the weights of the given DNN such that it accurately approximates the relation between observed input and target data. Devising effective solvers for this optimization problem is notoriously challenging due to the large number of weights, nonconvexity, data sparsity, and nontrivial choice of hyperparameters. To solve the optimization problem more efficiently, we propose the use of variable projection (VarPro), a method originally designed for separable nonlinear least-squares problems. Our main contribution is the Gauss--Newton VarPro method (GNvpro) that extends the reach of the VarPro idea to nonquadratic objective functions, most notably cross-entropy loss functions arising in classification. These extensions make GNvpro applicable to all training problems that involve a DNN whose last layer is an affine mapping, which is common in many state-of-the-art architectures. In our four numerical experiments from surrogate modeling, segmentation, and classification, GNvpro solves the optimization problem more efficiently than commonly used stochastic gradient descent (SGD) schemes. Finally, GNvpro finds solutions that generalize well, and in all but one example better than well-tuned SGD methods, to unseen data points.

97 MATHEMATICS AND COMPUTING↗

AMPPED LDRD: Advanced Models of the Physics & Phenomena of Electrical Discharge.

This Laboratory Directed Research and Development (LDRD) project aimed at addressing an unmet need for physics-based models that enable prediction of electrical breakdown in the presence of high voltage gradients and real-world environments. This project focused on understanding coupled plasma-surface feedback phenomena critical to electrical discharge processes and design of breakdown voltages, breakdown times, and breakdown paths. New secondary electron emission and coupled plasma-surface measurement methods and models were developed. Highly reproducible discharge experiments were developed to provide current-voltage data as a function of time, and methods were developed to condition electrodes for predictable discharge. To assess plasma-surface feedback mechanisms, new surface physics capabilities, including measurement systems for local and global photoemission yield and ion-induced secondary electron emission yield were developed. Discharge models were developed to incorporate these yields for predicting discharge behavior to understand influence of surface physics on discharge current and time evolution, and methods to accelerate these simulations were demonstrated. A key finding was that the initiation process of a non-vacuum discharge appears highly dependent on photoemission at the cathode. Advanced diagnostics were developed, including spatial electrical field imaging, spectroscopy of plasmas, and high-speed imaging of discharge event s in metal and dielectric environments. These diagnostics and improved electrical models are a step toward enabling quantitative design margins, assurance of safety architectures, and implementation of novel materials and technologies for wide ranging energy and electronics applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Optimal active control for Burgers equations

A method for active fluid flow control based on control theory is discussed. Dynamic programming and fixed point successive approximations are used to accommodate the nonlinear control problem. The long-term goal of this project is to establish an effective method applicable to complex flows such as turbulence and jets. However, in this report, the method is applied to stochastic Burgers equation as an intermediate step towards this goal. Numerical results are compared with those obtained by gradient search methods.

Ikeda, Yutaka↗

On convergent finite difference schemes for variational–PDE-based image processing

We study an adaptive anisotropic Huber functional-based image restoration scheme. Using a combination of L2–L1 regularization functions, an adaptive Huber functional-based energy minimization model provides denoising with edge preservation in noisy digital images. We study a convergent finite difference scheme based on continuous piecewise linear functions and use a variable splitting scheme, namely the Split Bregman (In: Goldstein and Osher, SIAM J Imaging Sci 2(2):323–343, 2009) algorithm, to obtain the discrete minimizer. Experimental results are given in image denoising and comparison with additive operator splitting, dual fixed point, and projected gradient schemes illustrates that the best convergence rates are obtained for our algorithm.

97 MATHEMATICS AND COMPUTING↗

Design of robust state feedback controllers via eigenvalue/eigenvector assignment

A new method of selecting a multivariable state feedback controller is presented. The resulting controller simultaneously realizes arbitrary closed-loop eigenvalues, approximates specified modal behavior and achieves low eigensystem sensitivity with respect to plant parameter variations. The method characterizes a vector space slightly larger than the null space of the closed-loop system matrix and projects a desired modal matrix onto this space. Sensitivity of eigenvalues and eigenvectors is then minimized local to the desired modal matrix using a gradient search technique. A tutorial example to illustrate the design procedure is given.

Mielke, R. R.↗

NASA-UVA Light Aerospace Alloy and Structures Technology Program: LA(2)ST

The NASA-UVA Light Aerospace Alloy and Structures Technology (LA(2)ST) Program continues a high level of activity, with projects being conducted by graduate students and faculty advisors in the Departments of Materials Science and Engineering, Civil Engineering and Applied Mechanics, and Mechanical and Aerospace Engineering at the University of Virginia. This work is funded by the NASA-Langley Research Center under Grant NAG-1-745. We report on progress achieved between July 1 and December 31, 1992. The objective of the LA(2)ST Program is to conduct interdisciplinary graduate student research on the performance of next generation, light weight aerospace alloys, composites and thermal gradient structures in collaboration with NASA-Langley researchers. Specific technical objectives are presented for each research project. We generally aim to produce relevant data and basic understanding of material mechanical response, corrosion behavior, and microstructure; new monolithic and composite alloys; advanced processing methods; new solid and fluid mechanics analyses; measurement advances; and critically, a pool of educated graduate students for aerospace technologies.

Gangloff, Richard P.↗

NASA-UVA light aerospace alloy and structures technology program (LA2ST)

The NASA-UVA Light Aerospace Alloy and Structures Technology (LA2ST) Program was initiated in 1986, and continues a high level of activity, with projects being conducted by graduate students and faculty advisors in the Departments of Materials Science and Engineering, and Mechanical and Aerospace Engineering at the University of Virginia. This work is funded by the NASA-Langley Research Center under Grant NAG-1-745. Here, we report on progress achieved between July 1 and December 31, 1993. The objective of the LA2ST Program is to conduct interdisciplinary graduate student research on the performance of next generation, light weight aerospace alloys, composites and thermal gradient structures in collaboration with NASA-Langley researchers. Specific technical objectives are presented for each research project. We generally aim to produce relevant data and basic understanding of material mechanical response, environmental/corrosion behavior, and microstructure; new monolithic and composite alloys; advanced processing methods; new solid and fluid mechanics analyses; measurement and modeling advances; and critically, a pool of educated graduate students for aerospace technologies.

Gangloff, Richard P.↗

NASA-UVA Light Aerospace Alloy and Structures Technology Program (LA2ST)

The NASA-UVA Light Aerospace Alloy and Structures Technology (LA2ST) Program was initiated in 1986 and continues with a high level of activity. Projects are being conducted by graduate students and faculty advisors in the Department of Materials Science and Engineering, as well as in the Department of Civil Engineering and Applied Mechanics, at the University of Virginia. This work is funded by the NASA-Langley Research Center under Grant NAG-1-745. Here, we report on progress achieved between January 1 and June 30, 1994. These results were presented at the Fifth Annual NASA LA2ST Grant Review Meeting held at the Langley Research Center in July of 1994. The objective of the LA2ST Program is to conduct interdisciplinary graduate student research on the performance of next generation, lightweight aerospace alloys, composites, and thermal gradient structures in collaboration with NASA-Langley researchers. Specific technical objectives are presented for each research project. We generally aim to produce relevant data and basic understanding of material mechanical response, environmental/corrosion behavior, and microstructure; new monolithic and composite alloys; advanced processing methods; new solid and fluid mechanics analyses; measurement and modeling advances; and a pool of educated graduate students for aerospace technologies.

Gangloff, Richard P.↗

NASA-UVA light aerospace alloy and structures technology program (LA2ST)

The NASA-UVa Light Aerospace Alloy and Structures Technology (LA2ST) Program was initiated in 1986 and continues with a high level of activity. Projects are being conducted by graduate students and faculty advisors in the Department of Materials Science and Engineering, as well as in the Department of Civil Engineering and Applied Mechanics, at the University of Virginia. Here, we report on progress achieved between July 1 and December 31, 1994. The objective of the LA2ST Program is to conduct interdisciplinary graduate student research on the performance of next generation, light-weight aerospace alloys, composites and thermal gradient structures in collaboration with NASA-Langley researchers. Specific technical objectives are presented for each research project. We generally aim to produce relevant data and basic understanding of material mechanical response, environmental/corrosion behavior, and microstructure; new monolithic and composite alloys; advanced processing methods; new solid and fluid mechanics analyses; measurement and modeling advances; and a pool of educated graduate students for aerospace technologies.

Starke, Edgar A., Jr.↗

NASA-UVA Light Aerospace Alloy and Structures Technology Program (LA2ST)

The NASA-UVA Light Aerospace Alloy and Structures Technology (LA2ST) Program was initiated in 1986 and continues with a high level of activity. The objective of the LA2ST Program is to conduct interdisciplinary graduate student research on the performance of next generation, light-weight aerospace alloys, composites and thermal gradient structures in collaboration with NASA-Langley researchers. Specific technical objectives are presented for each research project. We generally aim to produce relevant data and basic understanding of material mechanical response, environmental/corrosion behavior, and microstructure; new monolithic and composite alloys; advanced processing methods; new solid and fluid mechanics analyses; measurement and modeling advances; and a pool of educated graduate students for aerospace technologies. Three research areas are being actively investigated, including: (1) Mechanical and environmental degradation mechanisms in advanced light metals, (2) Aerospace materials science, and (3) Mechanics of materials for light aerospace structures.

Scully, John R.↗

NASA-UVA Light Aerospace Alloy and Structures Technology Program (LA2ST)

The NASA-UVA Light Aerospace Alloy and Structures Technology (LA2ST) Program was initiated in 1986 and continues with a high level of activity. Here, we report on progress achieved between July I and December 31, 1996. The objective of the LA2ST Program is to conduct interdisciplinary graduate student research on the performance of next generation, light-weight aerospace alloys, composites and thermal gradient structures in collaboration with NASA-Langley researchers. Specific technical objectives are presented for each research project. We generally aim to produce relevant data and basic understanding of material mechanical response, environmental/corrosion behavior, and microstructure; new monolithic and composite alloys; advanced processing methods; new solid and fluid mechanics analyses; measurement and modeling advances; and a pool of educated graduate students for aerospace technologies. The accomplishments presented in this report are summarized as follows. Three research areas are being actively investigated, including: (1) Mechanical and Environmental Degradation Mechanisms in Advanced Light Metals, (2) Aerospace Materials Science, and (3) Mechanics of Materials for Light Aerospace Structures.

Gangloff, Richard P.↗

The development of two-dimensional object identification techniques

This report marks the end of the first year of an anticipated three year effort to study methods for numerically identifying objects according to shape in two dimensions. The method is based upon comparing the unit gradient of an observed object and the unit gradient of a standard object over a specified range of points. The manner in which the gradients are compared forms the basis of a shape recognition scheme, which is then applied to simple closed plane figures. The gradient based method is calibrated by using various distorted objects in comparison with a set of standard reference objects. The use of pattern recognition techniques for computer identification of two-dimensional figures will be investigated during the second and third years of this project.

Lebby, Gary↗

Design of a lunar transportation system

The development of a good transportation infrastructure is a major requirement for the establishment of a permanent lunar base. Transportation is characterized by the technology available in a specific time frame and the need to transport personnel and cargo between Earth and Moon, and between lunar bases. In our study, attention was first focused on developing a transportation system for the first generation lunar base. As a first step, a tracked-type multipurpose lunar transportation vehicle was considered as a possible mode of transportation and a detailed study was conducted on the various aspects of the vehicle. Since the vehicle is composed of many moving parts, exposing it to the environment of the Moon, where fine dust particles are prevalent, can cause problems associated with lubrication and friction. The vehicle also posed problems concerning weight and power. Hence, several modifications were made to the above design ideas conceptually, and a Lunar Articulated Remote Transportation System (Lunar ARTS) is proposed as a more effective alternative with the following objectives: (1) minimizing the transportation of construction material and fuel from Earth or maximizing the use of the lunar material; (2) use of novel materials and light-weight structures; (3) use of new manufacturing methods and technology such as magnetic levitation using superconducting materials; and (4) innovative concepts of effectively utilizing the exotic lunar conditions, i.e., high thermal gradients, lack of atmosphere, lower gravity, etc. To achieve the above objectives of designing transportation systems from concept to operation, the project was planned in three phases: (1) conceptual design; (2) detailed analysis and synthesis; and (3) construction, testing, evaluation, and operation. In this project, both phases 1 and 2 have been carried out and work on phase 3 is in progress. In this paper, the details of the Lunar ARTS are discussed and the future work on the vehicle are also outlined.

Sankaravelu, A.↗

Prevention of Dual-Mode Excitation in 9-Cell Cavities for LCLSII-HE

Dual-Mode Excitation, also referred to as mode-mixing, is a superposition of two fundamental pi modes in an SRF cavity. In 9-cell TESLA cavities used for the LCLSII-HE project, the two modes that are commonly excited are the pi mode (1300.2 MHz), and the 7/9 pi mode (1297.8 MHz). During vertical cavity qualification testing, only the pi mode is driven by the RF system. However, at high gradients, emitted power at the frequency of the 7/9 pi mode grows despite the RF system only powering the pi mode. When this happens, the RF power measurement system is unable to differentiate between the superimposed modes, and any data taken is invalid. The previous method of dealing with mode-mixing was to turn off power to the cavity, let both modes decay fully, then restore power. Because of the time-sensitive nature of this testing, this leads to underestimates of Q0 or any radiant field emission present in the cavity. The novel RF control solution prevents the 7/9 pi mode from being excited while not interfering with measurements of the fundamental pi mode. A second RF control system is connected to the cavity which drives the 7/9 pi mode. The loop phase for driving the 7/9 pi mode in self excited loop mode is determined then shifted by 180 degrees, thus providing a negative feedback to the undesired mode. Because this off-resonance power can be very small, on the order of milliwatts, it does not interfere with the high-power measurements of the fundamental pi mode. At Jefferson Lab, we are now able to test a cavity for the LCLSII-HE project with no problems from mode-mixing, which allows for CW processing of high-gradient multipacting and field emission.

Owen, Peter↗

Electrically Driven Ion Separations in Permeable Membranes

Membranes are attractive for a wide range of separations due to their low energy costs and continuous operation. To achieve practical fluxes, most membranes consist of a thin, selective skin on a highly permeable substrate that provides mechanical strength. Thus, this project focused on creating new methods for forming highly selective ultrathin skins as well as modeling transport through these coatings to better understand their unprecedented selectivities. The research explored both gas and ion separations, and the latter included transport due to concentration, pressure and electrical potential gradients. This report describes a series of highlights of the research and then provides a complete list of publications supported by the grant. These publications have been cited more than 4000 times. Perhaps the most stunning finding is the recent discovery of monovalent/divalent cation and anion selectivities around 1000 when modifying cation- and anion-exchange membranes with polyelectrolyte multilayers (PEMs). This discovery builds on many years of exciting research. (Citation numbers refer to the journal articles in the bibliography.)

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Real space iterative reconstruction for vector tomography (RESIRE-V)

Tomography has had an important impact on the physical, biological, and medical sciences. To date, most tomographic applications have been focused on 3D scalar reconstructions. However, in some crucial applications, vector tomography is required to reconstruct 3D vector fields such as the electric and magnetic fields. Over the years, several vector tomography methods have been developed. Here, we present the mathematical foundation and algorithmic implementation of REal Space Iterative REconstruction for Vector tomography, termed RESIRE-V. RESIRE-V uses multiple tilt series of projections and iterates between the projections and a 3D reconstruction. Each iteration consists of a forward step using the Radon transform and a backward step using its transpose, then updates the object via gradient descent. Incorporating with a 3D support constraint, the algorithm iteratively minimizes an error metric, defined as the difference between the measured and calculated projections. The algorithm can also be used to refine the tilt angles and further improve the 3D reconstruction. To validate RESIRE-V, we first apply it to a simulated data set of the 3D magnetization vector field, consisting of two orthogonal tilt series, each with a missing wedge. Our quantitative analysis shows that the three components of the reconstructed magnetization vector field agree well with the ground-truth counterparts. We then use RESIRE-V to reconstruct the 3D magnetization vector field of a ferromagnetic meta-lattice consisting of three tilt series. Our 3D vector reconstruction reveals the existence of topological magnetic defects with positive and negative charges. We expect that RESIRE-V can be incorporated into different imaging modalities as a general vector tomography method. To make the algorithm accessible to a broad user community, we have made our RESIRE-V MATLAB source codes and the data freely available at https://github.com/minhpham0309/RESIRE-V.

47 OTHER INSTRUMENTATION↗

An Incremental Gradient Method for Optimization Problems With Variational Inequality Constraints

We consider minimizing a sum of agent-specific nondifferentiable merely convex functions over the solution set of a variational inequality (VI) problem in that each agent is associated with a local monotone mapping. This problem finds an application in computation of the best equilibrium in nonlinear complementarity problems arising in transportation networks. We develop an iteratively regularized incremental gradient method where at each iteration, agents communicate over a directed cycle graph to update their solution iterates using their local information about the objective and the mapping. The proposed method is single-timescale in the sense that it does not involve any excessive hard-to-project computation per iteration. We derive nonasymptotic agent-wise convergence rates for the suboptimality of the global objective function and infeasibility of the VI constraints measured by a suitably defined dual gap function. Finally, the proposed method appears to be the first fully iterative scheme equipped with iteration complexity that can address distributed optimization problems with VI constraints over cycle graphs.

convergence↗