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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

A data-driven approach to construct a quantitative relationship between microstructural features of fatigue cracks and contact acoustic nonlinearity

This study demonstrates the feasibility of a data-driven approach to construct a quantitative relationship between nonlinear acoustic parameters and microstructural features of contact interfaces. The near-surface nonlinearity is measured using dynamic acousto-elastic testing (DAET) with a surface wave probe, while the microstructural features are extracted from scanning electron microscopy (SEM) images of fatigue cracks. Four aluminum alloy samples, each having a fatigue crack are prepared. Six local nonlinearity parameters are measured at different locations along the crack propagation direction. A total of 40 local measurements are acquired. A principal component analysis (PCA) reveals that all six nonlinearity parameters are correlated and hence can be replaced by one principal component (PC). Fifteen crack micro-geometrical features at each measurement point were extracted from the SEM images. Regression analysis is used to relate the PC of the nonlinearity parameters to the microstructural features at the crack interface. We compare three regression models that take variable selection into account: stepwise multiple linear regression (MLR), stepwise principal component regression (PCR), and least absolute shrinkage and selection operator (LASSO). Despite having different principles, the three predictive models identify two features as the most significant in predicting the interface nonlinearity: the crack aperture (opening) distribution and the distance to the crack tip. The differences between the three models and the physical interpretation of the data-driven predictions are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Accelerating Large-Format Metal Additive Manufacturing: How Controls R&D is Driving Speed, Scale, and Efficiency

This article highlights work at Oak Ridge National Laboratory’s Manufacturing Demonstration Facility to develop closed-loop, feedback control for laser-wire based Directed Energy Deposition, a form of metal Big Area Additive Manufacturing (m-BAAM), a process being developed in partnership with GKN Aerospace specifically for the production of Ti-6Al-4V pre-forms for aerospace components. A large-scale structural demonstrator component is presented as a case-study in which not just control, but the entire 3D printing workflow for m-BAAM is discussed in detail, including design principles for large-format metal AM, toolpath generation, parameter development, process control, and system operation, as well as post-print net-shape geometric analysis and finish machining. In terms of control, a multi-sensor approach has been utilized to measure both layer height and melt pool size, and multiple modes of closed-loop control have been developed to manipulate process parameters (laser power, print speed, deposition rate) to control these variables. Layer height control and melt pool size control have yielded excellent local (intralayer) and global (component-level) geometry control, and the impact of melt pool size control in particular on thermal gradients and material properties is the subject of continuing research. Further, these modes of control have allowed the process to advance to higher deposition rates (exceeding 7.5 lb/hr), larger parts (1-meter scale), shorter build times, and higher overall efficiency. The control modes are examined individually, highlighting their development, demonstration, and lessons learned, and it is shown how they operate concurrently to enable the printing of a large-scale, near net shape Ti-6Al-4V component.

Gibson, Brian↗
DOE OSTI2018

Transactive System: Part II: Analysis of Two Pilot Transactive Systems using Foundational Theory and Metrics

This document is the second of a two-part report. Part 1 reviewed several demonstrations of transactive control and compared them in terms of their payoff functions, control decisions, information privacy, and mathematical solution concepts. It was suggested in Part 1 that these four listed components should be adopted for meaningful comparison and design of future transactive systems. Part 2 proposes qualitative and quantitative metrics that will be needed to compare alternative transactive systems. It then uses the analysis and design principles from Part 1 while conducting more in-depth analysis of two transactive demonstrations: the American Electric Power (AEP) gridSMART Demonstration, which used a double –auction market mechanism, and a consensus method like that used in the Pacific Northwest Smart Grid Demonstration. Ultimately, metrics must be devised and used to meaningfully compare alternative transactive systems. One significant contribution of this report is an observation that the decision function used for thermostat control in the AEP gridSMART Demonstration has superior performance if its decision function is recast to more accurately reflect the power that will be used under for thermostatic control under alternative market outcomes.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2017

Transactive System: Part II: Analysis of Two Pilot Transactive Systems using Foundational Theory and Metrics

This document is the second of a two-part report. Part 1 reviewed several demonstrations of transactive control and compared them in terms of their payoff functions, control decisions, information privacy, and mathematical solution concepts. It was suggested in Part 1 that these four listed components should be adopted for meaningful comparison and design of future transactive systems. Part 2 proposes qualitative and quantitative metrics that will be needed to compare alternative transactive systems. It then uses the analysis and design principles from Part 1 while conducting more in-depth analysis of two transactive demonstrations: the American Electric Power (AEP) gridSMART Demonstration, which used a double-auction market mechanism, and a consensus method like that used in the Pacific Northwest Smart Grid Demonstration. Ultimately, metrics must be devised and used to meaningfully compare alternative transactive systems. One significant contribution of this report is an observation that the decision function used for thermostat control in the AEP gridSMART Demonstration has superior performance if its decision function is recast to more accurately reflect the power that will be used under for thermostatic control under alternative market outcomes.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Commissioning of SRF Cavity Analyzer System

Research and development in Superconducting Radio Frequency (SRF) cavities manufacturing, surface treatment, preparation, and doping techniques for the improvement of cavities performance necessitate reliable cavities’ intrinsic quality factor measurement with accurate and repeatable results. Fermilab Vertical Test Stand facility (VTS) performs ~270 cavities tests per year, including R&D cavities as well as production cavities at each step of their preparation for the placement in accelerator’s cryomodules. Current Fermilab VTS testing system is based on the scalar approach of power measurement, which neglects potential error factors of the RF networks with distributed parameters, hence the assessed measurement errors of such a system might be slightly underestimated. Alternative approach, utilizing a vector measurement (amplitude and phase) of RF signals in the setup with a cavity as a device under test, promises an enhanced accuracy and results traceability. New cavity an alyser system based on this approach (Vector VTS) was developed by D. Frolov et al. and currently undergoes a commissioning process. Basic underlying principles of the system will be presented with the methods of quality factor extraction from S-parameters measurement of multiport cavities and brief error analysis will be discussed. The system architecture will be shown with main components parameters and ensuing testing capabilities. Multiple tests results will be discussed with a cross-check comparison of the results obtained with a conventional testing method. System advantages such as automated calibration process and additional features as a built- in microphonics measurement capability will be presented.

Netepenko, A.↗
DOE OSTI2023

LDRD23-0730: Invoking Multilayer Networks to Develop a Paradigm for Security Science—Summary Report

Current approaches to securing high consequence facilities (HCF) and critical assets are linear and static and therefore struggle to adapt to emerging threats (e.g., unmanned aerial systems) and changing environmental conditions (e.g., decreasing operational control). The pace of change in technological, organizational, societal, and political dynamics necessitates a move toward codifying underlying scientific principles to better characterize the rich interactions observed between HCF security technology, infrastructure, digital assets, and human or organizational components. The promising results of Laboratory Directed Research and Development (LDRD) 20-0373—“Developing a Resilient, Adaptive, and Systematic Paradigm for Security Analysis”—suggest that when compared to traditional security analysis, invoking multilayer network (MLN) modeling for HCF security system components captures unexpected failure cases and unanticipated interactions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Symbolic pregression: Discovering physical laws from distorted video

In this work, we present a method for unsupervised learning of equations of motion for objects in raw and optionally distorted unlabeled synthetic video (or, more generally, for discovering and modeling predictable features in time-series data). We first train an autoencoder that maps each video frame into a low-dimensional latent space where the laws of motion are as simple as possible, by minimizing a combination of nonlinearity, acceleration, and prediction error. Differential equations describing the motion are then discovered using Pareto-optimal symbolic regression. We find that our pre-regression (“pregression”) step is able to rediscover Cartesian coordinates of unlabeled moving objects even when the video is distorted by a generalized lens. Using intuition from multidimensional knot theory, we find that the pregression step is facilitated by first adding extra latent space dimensions to avoid topological problems during training and then removing these extra dimensions via principal component analysis. An inertial frame is autodiscovered by minimizing the combined equation complexity for multiple experiments.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

A first principles framework to predict the transient performance of latent heat thermal energy storage

Thermal energy storage (TES) is increasingly recognized as an essential component of efficient Combined Heat and Power (CHP), Concentrated Solar Power (CSP), Heating Ventilation and Air Conditioning (HVAC), and refrigeration as it reduces peak demand while helping to manage intermittent availability of energy (e.g., from solar or wind). Latent Heat Thermal Energy Storage (LHTES) is a viable option because of its high energy storage density. Parametric analysis of LHTES in terms of dimensionless numbers is highly desired as a tool to model LHTES systems. One approach is to develop a model equation so as to minimize the error between the model and data obtained from experiments or simulations. While this approach can produce an accurate correlation applicable within the range of data used for its creation, it does not provide physical understanding of the rate-limiting process controlling the transient behavior of the device. In this paper we present an alternative approach whereby the potential rate-limiting processes are identified from first principles and then the key process is determined as a function of time as a LHTES device is charged. For example, in a simple geometry, the melt-fraction can be expected to vary linearly in time if the heat transfer rate is limited by natural convection of the phase changing material and we show it scales with the PCM Grashof number as $Gr^1_p$ and PCM Prandtl number as $Pr_p^{(1/3)}$. On the other hand, if surface area of solid PCM limits the heat transfer rate, the melt fraction increases asymptotically to reach full melting. The existence of these linear and asymptotic regions and the $Gr^1_pP r^{1/3}_p$ shape of the melt fraction curve is verified using our database of 64 simulations. Of practical importance in designing LHTES devices is the melt fraction at which the heat transfer rate ceases to be limited by convection, after which the heat storage rate deteriorates. For our geometry, this is found to be about 90%. This test case of our methodology shows the value of our approach, that predicting heat storage rate based on the rate-limiting physical phenomenon as a function of time is an effective approach to modeling LHTES devices.

25 ENERGY STORAGE↗
DOE OSTI2019

Structural and electronic properties of the spin-filter material CrVTiAl with disorder

The effects of chemical disorder on the electronic properties of the spin-filter material CrVTiAl are investigated experimentally and theoretically. Synchrotron X-ray diffraction experiments on bulk CrVTiAl and the associated Rietveld analysis indicate that the crystal structure consists primarily of a mixture of a partially ordered B2 phase, a fully disordered A2 phase, and a small component of an ordered L2 1 or Y phase. High temperature resistivity measurements confirm the existence of a bandgap. First-principles, all-electron, self-consistent electronic structure computations show that the chemically disordered A2 and B2 phases are metallic, while the spin-filter properties of the ideal Y-type phase are preserved in the presence of L2 1 disorder (Cr and V mixing). The Hall coefficient is found to decrease with increasing temperature, similar to the measured increase in the conductivity, indicating the presence of thermally activated semiconductor-like carriers.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Evaluating Water Assets Using Water Efficiency Framework for Infrastructure Intensive Agency

Water infrastructure-intensive organizations should incorporate sustainability principles when making decisions on infrastructure investments to ensure the long-term resilience of mission-critical equipment and components. A water efficiency evaluation framework to inform infrastructure investments is discussed and applied to three federal campuses. The methodology considered emphasizes the iterative process between data analysis and decision-making; evaluates cost-sharing solution alternatives when making final recommendations; considers both internal and external stakeholder perceptions of project outcomes and future planning; and makes explicit government and community preferences when evaluating projects. Case study findings underscore condition evaluations for infrastructure that are critical to setting a baseline for system performance and determining desired potential upgrades and sustainment strategies. Such a holistic approach has demonstrated effectiveness for understanding, classifying, and recommending innovative water asset solutions that are necessary for the public sector to consider in today’s complex, modern planning environment.

Asset Management, Alternative Water, evaluation, P↗
DOE OSTI2019

Particle Flow Solarthermal Redox Process to Split Water

The aim of this project is to develop novel solarthermal water splitting (STWS) materials and a STWS reactor capable of producing hydrogen gas in an economic (<2/gge H 2 ) and efficient manner (>26% solar to hydrogen efficiency) at commercial scales (>50,000 kg of H 2 /day). To meet these targets, new materials must be developed with high intrinsic STWS efficiencies and then fabricated into a robust, long-lived “reactor ready” form. Additionally, scalable novel reactors are necessary to efficiently deliver the solar heat to the reacting materials while minimizing parasitic efficiency losses such as unnecessary heating and cooling, electrical work and heat losses from the reactor (such as radiation, or conduction). In this project we will: 1) develop new materials capable of meeting the targets outlined above; 2) develop particle formulation capable of producing attrition resistant, long lived, “reactor ready” particles; 3) evaluate and refine the individual reactor components of our Particle Flow Solarthermal Reactor design; 4) develop an overall system model to be used for reactor design improvement and economic analysis; and 5) produce at least three liters of H 2 on-sun in an eight hour day using our developed materials and reactor design principles. Overall, we will move our STWS process from Technology Readiness Level (TRL) 2 to TRL3.

08 HYDROGEN↗
DOE OSTI2017

A parts list for fungal cellulosomes revealed by comparative genomics

Here, cellulosomes are large, multiprotein complexes that tether plant biomass-degrading enzymes together for improved hydrolysis. These complexes were first described in anaerobic bacteria, where species-specific dockerin domains mediate the assembly of enzymes onto cohesin motifs interspersed within protein scaffolds. The versatile protein assembly mechanism conferred by the bacterial cohesin–dockerin interaction is now a standard design principle for synthetic biology. For decades, analogous structures have been reported in anaerobic fungi, which are known to assemble by sequence-divergent non-catalytic dockerin domains (NCDDs). However, the components, modular assembly mechanism and functional role of fungal cellulosomes remain unknown. Here, we describe a comprehensive set of proteins critical to fungal cellulosome assembly, including conserved scaffolding proteins unique to the Neocallimastigomycota. High-quality genomes of the anaerobic fungi Anaeromyces robustus , Neocallimastix californiae and Piromyces finnis were assembled with long-read, single-molecule technology. Genomic analysis coupled with proteomic validation revealed an average of 312 NCDD-containing proteins per fungal strain, which were overwhelmingly carbohydrate active enzymes (CAZymes), with 95 large fungal scaffoldins identified across four genera that bind to NCDDs. Fungal dockerin and scaffoldin domains have no similarity to their bacterial counterparts, yet several catalytic domains originated via horizontal gene transfer with gut bacteria. However, the biocatalytic activity of anaerobic fungal cellulosomes is expanded by the inclusion of GH3, GH6 and GH45 enzymes. These findings suggest that the fungal cellulosome is an evolutionarily chimaeric structure—an independently evolved fungal complex that co-opted useful activities from bacterial neighbours within the gut microbiome.

09 BIOMASS FUELS↗
DOE OSTI2020

New method for fitting coefficients in standard model effective theory

We present an alternative method for carrying out a principal-component analysis of Wilson coefficients in standard model effective field theory (SMEFT). The method is based on singular-value decomposition (SVD). The SVD method provides information about the sensitivity of experimental observables to physics beyond the standard model that is not accessible in the Fisher-information method. In principle, the SVD method can also have computational advantages over diagonalization of the Fisher information matrix. We demonstrate the SVD method by applying it to the dimension-6 coefficients for the process of top-quark decay to a b quark and a W boson and use this example to illustrate some pitfalls in widely used fitting procedures. We also outline an iterative procedure for applying the SVD method to dimension-8 SMEFT coefficients.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Phylogenetic diversity of 200+ isolates of the ectomycorrhizal fungus Cenococcum geophilum associated with Populus trichocarpa soils in the Pacific Northwest, USA and comparison to globally distributed representatives

The ectomycorrhizal fungal symbiont Cenococcum geophilum is of high interest as it is globally distributed, associates with many plant species, and has resistance to multiple environmental stressors. C . geophilum is only known from asexual states but is often considered a cryptic species complex, since extreme phylogenetic divergence is often observed within nearly morphologically identical strains. Alternatively, C . geophilum may represent a highly diverse single species, which would suggest cryptic but frequent recombination. Here we describe a new isolate collection of 229 C . geophilum isolates from soils under Populus trichocarpa at 123 collection sites spanning a ~283 mile north-south transect in Western Washington and Oregon, USA (PNW). To further understanding of the phylogenetic relationships within C . geophilum , we performed maximum likelihood and Bayesian phylogenetic analyses to assess divergence within the PNW isolate collection, as well as a global phylogenetic analysis of 789 isolates with publicly available data from the United States, Japan, and European countries. Phylogenetic analyses of the PNW isolates revealed three distinct phylogenetic groups, with 15 clades that strongly resolved at >80% bootstrap support based on a GAPDH phylogeny and one clade segregating strongly in two principle component analyses. The abundance and representation of PNW isolate clades varied greatly across the North-South range, including a monophyletic group of isolates that spanned nearly the entire gradient at ~250 miles. A direct comparison between the GAPDH and ITS rRNA gene region phylogenies, combined with additional analyses revealed stark incongruence between the ITS and GAPDH gene regions, consistent with intra-species recombination between PNW isolates. In the global isolate collection phylogeny, 34 clades were strongly resolved using Maximum Likelihood and Bayesian approaches (at >80% MLBS and >0.90 BPP respectively), with some clades having intra- and intercontinental distributions. Together these data are highly suggestive of divergence within multiple cryptic species, however additional analyses such as higher resolution genotype-by-sequencing approaches are needed to distinguish potential species boundaries and the mode and tempo of recombination patterns.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

First-Cycle Simulation for Li-Rich Layered Oxide Cathode Material x Li 2 MnO 3 • (1- x )Li M O 2 ( x = 0.4)

Here, lithium-rich layered oxides (LRLO) x Li 2 MnO 3 • (1- x )Li M O 2 continue to attract attention owing to their promise of high capacity and energy density as lithium-ion battery cathodes, despite the degradation of atomic structure and energy density (voltage fade) with cycling. First-principles DFT calculations for the model systems M = Co and M = Mn 0.5 Ni 0.5 provide insights into the atomic-scale transformations in the bulk during the first charge and discharge of LRLO. The simulations were performed with the VASP code at the GGA+ U level. Molecular dynamics simulations were conducted at T = 1000 K (charge) and 2000 K (discharge) to accelerate the dynamics. Considerable Co migration to the Li layer occurs during the first charge for the system with M = Co, but the Li M O 2 component remains substantially intact for the system with M = Mn 0.5 Ni 0.5 . First-charge oxygen dimerization in the M = Co system occurs in both the Li M O 2 and the Li 2 MnO 3 components of the material, and exceeds than for M = Mn 0.5 Ni 0.5 , where dimerization is essentially confined to the Li 2 MnO 3 component. About half of the oxygen dimers created during the voltage plateau dissociate during the first discharge. Analysis of the redox suggests that some Mn 3+ is generated during the first charge for the system M = Co.

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

A review on recent machine learning applications for imaging mass spectrometry studies

Imaging mass spectrometry (IMS) is a powerful analytical technique widely used in biology, chemistry, and materials science fields that continue to expand. IMS provides a qualitative compositional analysis and spatial mapping with high chemical specificity. The spatial mapping information can be 2D or 3D depending on the analysis technique employed. Due to the combination of complex mass spectra coupled with spatial information, large high-dimensional datasets (hyperspectral) are often produced. Therefore, the use of automated computational methods for an exploratory analysis is highly beneficial. The fast-paced development of artificial intelligence (AI) and machine learning (ML) tools has received significant attention in recent years. These tools, in principle, can enable the unification of data collection and analysis into a single pipeline to make sampling and analysis decisions on the go. There are various ML approaches that have been applied to IMS data over the last decade. Here, in this review, we discuss recent examples of the common unsupervised (principal component analysis, non-negative matrix factorization, k-means clustering, uniform manifold approximation and projection), supervised (random forest, logistic regression, XGboost, support vector machine), and other methods applied to various IMS datasets in the past five years. The information from this review will be useful for specialists from both IMS and ML fields since it summarizes current and representative studies of computational ML-based exploratory methods for IMS.

47 OTHER INSTRUMENTATION↗
DOE OSTI2018

A Hyperthermophilic Phage Decoration Protein Suggests Common Evolutionary Origin with Herpesvirus Triplex Proteins and an Anti-CRISPR Protein

Virus capsids are protein shells that protect the viral genome from environmental assaults, while maintaining the high internal pressure of the tightly packaged genome. To elucidate how capsids maintain stability under harsh conditions, we investigated the capsid components of the hyperthermophilic phage P74-26. We determined the structure of capsid protein gp87 and show that it has the same fold as decoration proteins in many other phages, despite lacking significant sequence homology. Interestingly, we also find that gp87 is significantly more stable than mesophilic homologs. Our analysis of the gp87 structure reveals that the core “β tulip” domain is conserved in trimeric capsid components across numerous double-stranded DNA viruses, including Herpesviruses. Moreover, this β barrel domain is found in anti-CRISPR protein AcrIIC1, suggesting a mechanism for the evolution of this Cas9 inhibitor. Our work illustrates the principles for increased stability of gp87, and extends the evolutionary reach of the β tulip domain.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Inhomogeneity of Cellulose Microfibril Assembly in Plant Cell Walls Revealed with Sum Frequency Generation Microscopy

Sum frequency generation (SFG) vibrational spectroscopy can selectively detect and analyze noncentrosymmetric components interspersed in amorphous matrices; this principle has been used for studies of nanoscale structure and mesoscale assembly of cellulose in plant cell walls. However, the spectral information averaged over a large area or volume cannot provide regiospecific or tissue-specific information of different cells in plants. Here, we demonstrate spatially resolved SFG analysis and imaging by combining a broad-band SFG spectroscopy system with an optical microscope. The system was designed to irradiate both narrow-band 800 nm and broad-band tunable IR beams through a single reflective objective lens, but from opposite sides of the surface normal direction of the sample. The developed technique was used to reveal inhomogeneous distributions of cellulose microfibrils within single cell walls, such as cotton fibers and onion epidermis as well as among different tissues in Arabidopsis inflorescence stems and bamboo culms. SFG microscopy can be used for vibrational spectroscopic imaging of other biological systems in complement to conventional Fourier transform infrared spectroscopy and confocal Raman microscopy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗