Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “NETWORK ANALYSIS”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,639 records · Page 91

Framework for Adaptable Operating and Runtime Systems (Final Project Report)

In this grant, we examined a wide range of techniques for constructing high-performance con gurable system software for HPC systems and its application to DOE-relevant problems. Overall, research and development on this project focused in three specifc areas: (1) software frameworks for constructing and deploying con gurable system software, (2) applcation of these frameworks to HPC-oriented adaptable networking software, (3) performance analysis of HPC system software to understand opportunities for performance optimization.

97 MATHEMATICS AND COMPUTING↗

Integrated network design and scheduling problems :

We consider the class of integrated network design and scheduling problems. These problems focus on selecting and scheduling operations that will change the characteristics of a network, while being speci cally concerned with the performance of the network over time. Motivating applications of INDS problems include infrastructure restoration after extreme events and building humanitarian distribution supply chains. While similar models have been proposed, no one has performed an extensive review of INDS problems from their complexity, network and scheduling characteristics, information, and solution methods. We examine INDS problems under a parallel identical machine scheduling environment where the performance of the network is evaluated by solving classic network optimization problems. We classify that all considered INDS problems as NP-Hard and propose a novel heuristic dispatching rule algorithm that selects and schedules sets of arcs based on their interactions in the network. We present computational analysis based on realistic data sets representing the infrastructures of coastal New Hanover County, North Carolina, lower Manhattan, New York, and a realistic arti cial community CLARC County. These tests demonstrate the importance of a dispatching rule to arrive at near-optimal solutions during real-time decision making activities. We extend INDS problems to incorporate release dates which represent the earliest an operation can be performed and exible release dates through the introduction of specialized machine(s) that can perform work to move the release date earlier in time. An online optimization setting is explored where the release date of a component is not known.

Nurre, Sarah G.↗

Nested Narratives Final Report

In cybersecurity forensics and incident response, the story of what has happened is the most important artifact yet the one least supported by tools and techniques. Existing tools focus on gathering and manipulating low-level data to allow an analyst to investigate exactly what happened on a host system or a network. Higher-level analysis is usually left to whatever ad hoc tools and techniques an individual may have developed. We discuss visual representations of narrative in the context of cybersecurity incidents with an eye toward multi-scale illustration of actions and actors. We envision that this representation could smoothly encompass individual packets on a wire at the lowest level and nation-state-level actors at the highest. We present progress to date, discuss the impact of technical risk on this project and highlight opportunities for future work.

97 MATHEMATICS AND COMPUTING↗

PSB27: A thylakoid protein enabling Arabidopsis to adapt to changing light intensity

Project Title: Immunophilins in the assembly and maintenance of photosynthetic electron transport chain in Arabidopsis Applicant: The Regents of the University of California PI: Sheng Luan, University of California at Berkeley Photosynthetic light energy conversion entails coordinated function of complex molecular machines that capture and convert light energy into chemical forms through photosynthetic electron transport chain. Each molecular machine, such as photosystem II (PSII), may consist of dozens of protein subunits and small molecule cofactors. Despite advanced understanding of the structure and function of these complexes, little is known about “How individual proteins and cofactors assemble into a functional machine and how do these molecular machines maintain their structure and function under a highly hazardous lumenal environment.” Our studies on immunophilins have unexpectedly contributed to the understanding of this question. Originally defined as cellular receptors for immunosuppressants, immunophilins have been discovered in a wide range of organisms from bacteria, fungi, plants, to animals. Immunophilins function in protein folding processes as chaperones and foldases. Arabidopsis genome encodes ca. 50 immunophilins. The most striking finding is that 16 immunophilin members are targeted to chloroplast thylakoid lumen, by far the largest group in the lumenal proteome. What is the function of immunophilins in the thylakoid lumen? Our studies have demonstrated critical roles for several immunophilins in the biogenesis and maintenance of photosynthetic complexes such as PSII. These studies have made a critical link between immunophilins and the assembly of photosynthetic machines and thus opened up a new area of research in photosynthesis. Our goal is to dissect the roles of immunophilins and their partners in the assembly and maintenance of the photosynthetic electron transport chain. The specific objectives for this funding period will be: 1. To dissect the mechanism of action for CYP38. Our studies suggest an “autoinhibitory” model for CYP38 action. We plan to test this model and determine the mechanistic details for CYP38 function by biochemical and genetic procedures. 2. To determine the mechanism of action of FKBP20-2/FKBP16-3. Studies on FBKP16-3 and FKBP20-2 suggest that they may work together as a redox-dependent duo in PSII assembly. We will test this hypothesis using biochemical and genetic tools. 3. To determine the function of lumenal FKBPs by multi-gene mutagenesis approach. Using new genetic knockout (KO) procedures especially CRISPR/CAS9 system, we plan to generate multi-gene KO models that will likely provide vital information on those FKBPs with functional redundancy. 4. Functional analysis of thylakoid lumen network. We will focus our effort on objectives 1-3. Objective 4 represents a long-term goal to establish a more comprehensive network of proteins in the thylakoid lumen and their function in the assembly and maintenance of photosynthetic complexes. I hypothesize that the 16 immunophilin-type chaperones and foldases in the thylakoid lumen constitute an “assembly line” for the various components in the photosynthetic electron transport chain. Understanding this assembly line will enable further engineering of more efficient photosynthetic machines to capture more light energy and enhance plant productivity. Furthermore, it is envisioned that such molecular “assembly line” may be rebuilt to produce artificial photosynthesis in vitro or in non-photosynthetic organisms. These are highly relevant to the mission of “Photosynthetic Systems” and “Physical Biosciences” programs to “enhance our understanding of energy capture, conversion, and/or storage.” During the funding period, we have performed a number of experiments under the proposed objectives and obtained several new results. We have found in Objective 1 that CYP38 is associated to the thylokoid membrane with a larger complex that might be PSII supercomplex. Under objective 2, we have found that FKBP16-2 interacted with PSB27 that was further pursuited and published a research article in PNAS (attached). Under Objective 3, we have identified several mutants of other FKBPs in the thyalkoid lumen that should be further studied if future funding is available. Under Objective 4, we have started to build a network of lumenal proteins that play a number of roles in photosynthesis. For example, the CYP37 and CYP28 are linked to chloroplast signaling to nucleus, critical for controlling plant response to high light and adaptation to climate change. Unfortunately these studies have been terminated due to funding shortage.

59 BASIC BIOLOGICAL SCIENCES↗

Equation-free and variable free modeling for complex/multiscale systems. Coarse-grained computation in science and engineering using fine-grained models

The work explored the linking of modern developing machine learning techniques (manifold learning and in particular diffusion maps) with traditional PDE modeling/discretization/scientific computation techniques via the equation-free methodology developed by the PI. The result (in addition to several PhD degrees, two of them by CSGF Fellows) was a sequence of strong developments - in part on the algorithmic side, linking data mining with scientific computing, and in part on applications, ranging from PDE discretizations to molecular dynamics and complex network dynamics.

97 MATHEMATICS AND COMPUTING↗

Water Network Tool for Resilience (WNTR). User Manual, Version 0.2.3

The Water Network Tool for Resilience (WNTR, pronounced winter) is a Python package designed to simulate and analyze resilience of water distribution networks. Here, a network refers to the collection of pipes, pumps, valves, junctions, tanks, and reservoirs that make up a water distribution system. WNTR has an application programming interface (API) that is flexible and allows for changes to the network structure and operations, along with simulation of disruptive incidents and recovery actions. WNTR is based upon EPANET, which is a tool to simulate the movement and fate of drinking water constituents within distribution systems. Users are encouraged to be familiar with the use of EPANET and/or should have background knowledge in hydraulics and pressurized pipe network modeling before using WNTR. EPANET has a graphical user interface that might be a useful tool to facilitate the visualization of the network and the associated analysis results. Information on EPANET can be found at https://www.epa.gov/water-research/epanet. WNTR is compatible with EPANET 2.00.12 [Ross00]. In addition, users should have experience using Python, including the installation of additional Python packages. General information on Python can be found at https://www.python.org/.

54 ENVIRONMENTAL SCIENCES↗

Summary of NDC Capacity Building Workshop and Regional Seismic Travel Time (RSTT) in combination with Data Sharing and Integration Training

The NNSA Seismic Cooperation Program (SCP) sponsored Stephen Myers (LLNL), Michael Begnaud (LANL), Brian Young (SNL) and Istvan Bondar (Research Center for Astronomy and Earth Sciences, Hungary) to serve as a presenters/trainers at the “NDC Capacity Building Workshop and Regional Seismic Travel Time (RSTT) in combination with Data Sharing and Integration Training” September 4-8 2022 in Muscat, Oman (See Appendix A for the agenda). The workshop and training (workshop from here forward) was organized by the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO) Provisional Technical Secretariat (PTS). The first half of the week was devoted to NDC workshop activities, and the second half was devoted to RSTT training. Fifty-five participants from 27 countries and the CTBTO-PTS attended the 5-day workshop (See Appendix B for list of participants and countries of origin). Presentations from the PTS described the International Monitoring System (IMS), International Data Centre (IDC) products, and metrics of regional data utilization. Contributed presentations from each country’s scientists included descriptions of regional and national networks, methods of data analysis, and needs for material and technical assistance. Training included an overview of the RSTT method and instruction on how to locate seismic events with the iLoc program, which utilizes RSTT travel times to reduce bias in event location estimates. Methods of seismic tomography and the need for a high-quality tomographic set, including seismological “ground truth”, were emphasized. Seismological “ground truth” or “GT” is a term that has come to mean both events with known location and events with well-characterized locations that are estimated using seismological data, typically with epicenter accuracy of 5 km or better. Notably, the instructional platform has migrated from UNIX shell scripts to Jupyter Notebooks. Jupyter Notebooks have the advantage being more visually intuitive, including display of graphics within the notebook. Each notebook includes every processing step that participants need to reproduce the entire exercise.

58 GEOSCIENCES↗

Elucidating Mechanisms of Rust Pathogenesis for Engineering Resistance in Poplar

The overall objective of this research was to elucidate the molecular basis for the virulence of Melampsora larici-populina towards Populus spp. in order to address the formidable challenge of engineering durable resistance in poplar against leaf rust. Our original research plan was built on the technically innovative approach of using dual host systems and known host defense proteins and pathogen avirulent effectors along with genome-wide approaches to identify key pathogenesis effectors of Melampsora larici-populina that target poplar defense and nutrient acquisition. Our efforts focused on developing high-throughput experimental approaches and systems to enable us to address our overarching hypothesis that rust effectors with homology to other fungal effectors will either bypass the poplar immune system and/or suppress effector-triggered immunity through conserved mechanisms, and that an analysis of these interaction networks would provide for new approaches to develop rust-resistant poplar. Three main objectives were originally proposed: (1) mine key rust effectors that suppress host immunity; (2) elucidate interaction networks in poplar targeted by key rust effectors; (3) generate transgenic poplar resources for identification of genes involved in pathogen infection or host defense triggered by rust. Generally, we worked towards all three objectives by developing and applying complementary molecular, genomic, biochemical and plant transformation approaches.

54 ENVIRONMENTAL SCIENCES↗

Infrasound Detections of Low-Magnitude Earthquakes: Preliminary Results of the West Texas Acoustic Experiment

Infrasound observations have grown increasingly important for the monitoring of earthquakes. While large earthquakes generate infrasound that can be detected thousands of kilometers away, there are few near-field observations of infrasound generated by low-magnitude events. We describe preliminary results of the West Texas Acoustic Experiment, during which infrasound sensors collected continuous data in the Permian Basin for a six-month period spanning January—June 2023. During this time, more than 1000 earthquakes with magnitudes between 1.2 and 4.2 occurred within 50 km of the network. We used spectral analysis, array processing, and manual inspection of waveforms to evaluate arrivals of infrasound signals following 84 events with magnitudes between 2.5 and 4.2. Here, we describe eight such events and the infrasound signals associated with each. We find detections of seismic-to-acoustic infrasound signals associated with seven events. We also find strong evidence of a laterally-propagating, purely acoustic wave generated by an M2.9 earthquake.

58 GEOSCIENCES↗

Emissions Characterization for Ammonia Fuel Blends in an Enclosed Swirl-Stabilized Diffusion Burner

This study investigates ammonia flames using the enclosed Sydney swirl burner (ESSB), focusing on detailed global emissions measurements. Emissions were measured via Fourier-transform-infrared (FTIR) spectrometer, utilizing a heated, long-path absorption cell. Hot, wet measurements of pertinent species were collected, and concentrations were determined via lineshape fitting in conjunction with the HITRAN database. Results show that partially cracked ammonia compositions yield lower emissions compared to pure NH3/H2, and small amounts of NH3 addition to CH4-containing fuel blends exhibit high levels of NOx and CO, with measurable HCN and unburnt CH4. Equilibrium calculations suggest trade-offs between chemical timescale, heat loss, and mixing. Future work will explore emissions sampling procedures and expand analysis using chemical reactor network modelling.

ammonia combustion↗

Reduced Models for Chemical Kinetics derived from Parallel Ensemble Simulations of Stirred Reactors

Detailed chemical kinetic models are essential to improve the predictive capability of computational fluid dynamics (CFD) simulations and to impact the development of next generation combustion technologies. However, such detailed kinetic models are beyond the reach of CFD codes due to the computational cost of transporting additional chemical degrees of freedom. Reduced order models for combustion kinetics exploit the presence of lower dimensional manifolds in the state space and require far fewer number of scalars to be transported as part of CFD simulations. In this paper, we describe the software infrastructure developed to allow large ensembles of stirred reactor configurations with detailed chemical kinetics. The canonical reactor simulations are incorporated in a workflow with sparse grid and data reduction methodologies aimed at development of reduced order models. We present results from analyzing the results of the stirred reactor calculations for syngas mixture using principal component analysis (PCA) and neural network methodologies. The results show that nonlinear autoencoder model can surpass PCA in representing the original dataset with far fewer degrees of freedom.

Zhang, Pei↗

A priori examination of reduced chemistry models derived from canonical stirred reactors using three-dimensional direct numerical simulation datasets

Data-driven approaches to construct reduced chemical kinetic models, that rely heavily on thermo-chemical datasets with full chemical kinetics, have been gaining popularity. Datasets from direct numerical simulations (DNS) under three-dimensional (3-D) realistic turbulent flow conditions are desirable but limited to carefully designed parametric conditions due to the computational cost. Constructing datasets from a large ensemble of zero-dimensional stirred reactors like perfectly stirred reactor (PSR) and partially stirred reactor (PaSR) is a computationally efficient solution to consider the turbulence-chemistry interactions and cover a broad range of parametric conditions. In this paper, we derive reduced chemistry models from solutions of a large number of PSR and PaSR reactors using autoencoder (AE) neural networks and principal component analysis (PCA), and conduct a priori examination of the reduced models in three temporally evolving 3-D DNS jet flames featuring local extinction and re-ignition. The results show that the reduced models derived from PaSR datasets, i.e., AE-PaSR and PCA-PaSR, generally show significant improvement over the ones derived from PSR datasets. Among all the reduced models, AE-PaSR shows the best agreement with DNS results on the reconstruction accuracy and the representation of temporally evolving local extinction and re-ignition events.

Zhang, Pei↗

The direct and indirect drivers shaping RNA viral communities in grassland soil

Recent studies have revealed diverse RNA viral communities in soils. Yet, how environmental factors influence soil RNA viruses remains largely unknown. Here, we recovered RNA viral communities from 24 metatranscriptomes sequenced from grassland soils managed under a range of environmental conditions including 1) water content: 100% and 25% water holding capacity, 2) plant presence: planted with tall wheatgrass (Thinopyrum ponticum) and bare soil, 3) cultivar type: Alkar and Jose, and 4) soil depth: 0-5 cm and 15-25 cm. The recovered RNA viral communities were novel with nearly one-third of the RNA viral contigs uniquely detected in the studied grassland. The classified RNA viral contigs are mostly known as eukaryotic RNA viruses (74.7%) belonging to Phyla Duplornaviricota, Kitrinoviricota, Lenarviricota, and Pisuviricota. Eukaryotic RNA viruses of Family Mitoviridae as well as their natural hosts, Fungi, are one of the most dominant taxa. Consistent with the results of nonmetric multidimensional scaling analysis, the four environmental conditions (water content, plant presence, cultivar, and soil depth) significantly influence the assemblages of soil RNA viral communities as suggested by the correlation analysis and the random forest algorithm. The modularity analysis of the factor network and the structural equation modeling further support the hierarchical associations among the four environmental factors and the community factors representing the co-existing eukaryotic, prokaryotic, and RNA viral communities. The soil water content, plant presence, and type of cultivar demonstrate a significant positive impact on eukaryotic RNA viral richness directly as well as indirectly on eukaryotic RNA viral abundance via influencing the co-existing eukaryotic members in this soil. Our data also provide statistical support for the negative influence of soil depth on soil eukaryotic richness and abundances resulting in its indirect impact on soil eukaryotic RNA viral communities. This study provides field-relevant information on how environmental and community factors collectively shape soil RNA communities and contribute to ecological understanding of RNA viral survival under various environmental conditions and virus-host interactions in soil.

Wu, Ruonan↗

Nramp: Deprive and conquer?

Solute carriers 11 (Slc11) evolved from bacterial permease (MntH) to eukaryotic antibacterial defense (Nramp) while continuously mediating proton (H+)-dependent manganese (Mn2+) import. Also, Nramp horizontal gene transfer (HGT) toward bacteria led to mntH polyphyly. Prior demonstration that evolutionary rate-shifts distinguishing Slc11 from outgroup carriers dictate catalytic specificity suggested that resolving Slc11 family tree may provide a function-aware phylogenetic framework. Hence, MntH C (MC) subgroups resulted from HGTs of prototype Nramp (pNs) parologs while archetype Nramp (aNs) correlated with phagocytosis. PHI-Blast based taxonomic profiling confirmed MntH B phylogroup is confined to anaerobic bacteria vs. MntH A (MA)’s broad distribution; suggested niche-related spread of MC subgroups; established that MA-variant MH, which carries ‘eukaryotic signature’ marks, predominates in archaea. Slc11 phylogeny shows MH is sister to Nramp. Site-specific analysis of Slc11 charge network known to interact with the protonmotive force demonstrates sequential rate-shifts that recapitulate Slc11 evolution. 3D mapping of similarly coevolved sites across Slc11 hydrophobic core revealed successive targeting of discrete areas. The data imply that pN HGT could advantage recipient bacteria for H+-dependent Mn2+ acquisition and Alphafold 3D models suggest conformational divergence among MC subgroups. It is proposed that Slc11 originated as a bacterial stress resistance function allowing Mn2+-dependent persistence in conditions adverse for growth, and that archaeal MH could contribute to eukaryogenesis as a Mn2+ sequestering defense perhaps favoring intracellular growth-competent bacteria.

59 BASIC BIOLOGICAL SCIENCES↗

Linking Associations of Rare Low-Abundance Species to Their Environments by Association Networks

Studies of microbial communities by targeted sequencing of rRNA genes lead to recovering numerous rare low-abundance taxa with unknown biological roles. We propose to study associations of such rare organisms with their environments by a computational framework based on transformation of the data into qualitative variables. Namely, we analyze the sparse table of putative species or OTUs (operational taxonomic units) and samples generated in such studies, also known as an OTU table, by collecting statistics on co-occurrences of the species and on shared species richness across samples. Based on the statistics we built two association networks, of the rare putative species and of the samples respectively, using a known computational technique, Association networks (Anets) developed for analysis of qualitative data. Clusters of samples and clusters of OTUs are then integrated and combined with metadata of the study to produce a map of associated putative species in their environments. We tested and validated the framework on two types of microbiomes, of human body sites and that of the Populus tree root systems. We show that in both studies the associations of OTUs can separate samples according to environmental or physiological characteristics of the studied systems.

54 ENVIRONMENTAL SCIENCES↗

Transcriptional responses of Arabidopsis thaliana to chewing and sucking insect herbivores

We tested the hypothesis that Arabidopsis can recognize and respond differentially to insect species at the transcriptional level using a genome wide microarray. Transcriptional reprogramming was characterized using co-expression analysis in damaged and undamaged leaves at two times in response to mechanical wounding and four insect species. In all, 2778 (10.6%) of annotated genes on the array were differentially expressed in at least one treatment. Responses differed mainly between aphid and caterpillar and sampling times. Responses to aphids and caterpillars shared only 10% of up-regulated and 8% of down-regulated genes. Responses to two caterpillars shared 21 and 12% of up- and down-regulated genes, whereas responses to the two aphids shared only 7 and 4% of up-regulated and down-regulated genes. Overlap in genes expressed between 6 and 24 h was 3–15%, and depended on the insect species. Responses in attacked and unattacked leaves differed at 6 h but converged by 24 h. Genes responding to the insects are also responsive to many stressors and included primary metabolism. Aphids down-regulated amino acid catabolism; caterpillars stimulated production of amino acids involved in glucosinolate synthesis. Co-expression analysis revealed 17 response networks. Transcription factors were a major portion of differentially expressed genes throughout and responsive genes shared most of the known or postulated binding sites. However, cis-element composition of genes down regulated by the aphid M. persicae was unique, as were those of genes down-regulated by caterpillars. As many as 20 cis-elements were over-represented in one or more treatments, including some from well-characterized classes and others as yet uncharacterized. We suggest that transcriptional changes elicited by wounding and insects are heavily influenced by transcription factors and involve both enrichment of a common set of cis-elements and a unique enrichment of a few cis-elements in responding genes.

60 APPLIED LIFE SCIENCES↗

Fractal Characterization of Multimodal, Multiscale Images of Shale Rock Fracture Networks

An array of multimodal and multiscale images of fractured shale rock samples and analogs was collected with the aim of improving the numerical representation of fracture networks. 2D and 3D reconstructions of fractures and matrices span from 10 –6 to 100 m. The origin of the fracture networks ranged from natural to thermal maturation to hydraulically induced maturation. Images were segmented to improve fracture identification. Then, the fractal dimension and length distribution of the fracture networks were calculated for each image dataset. The resulting network connectivity and scaling associations are discussed at length on the basis of scale, sample and order of magnitude. Fracture network origin plays an important role in the resulting fracture systems and their scaling. Rock analogs are also evaluated using these descriptive tools and are found to be faithful depictions of maturation-induced fracture networks.

58 GEOSCIENCES↗

Lithium Metal Battery Quality Control via Transformer–CNN Segmentation

Lithium metal battery (LMB) has the potential to be the next-generation battery system because of its high theoretical energy density. However, defects known as dendrites are formed by heterogeneous lithium (Li) plating, which hinders the development and utilization of LMBs. Non-destructive techniques to observe the dendrite morphology often use X-ray computed tomography (XCT) to provide cross-sectional views. To retrieve three-dimensional structures inside a battery, image segmentation becomes essential to quantitatively analyze XCT images. This work proposes a new semantic segmentation approach using a transformer-based neural network called TransforCNN that is capable of segmenting out dendrites from XCT data. In addition, we compare the performance of the proposed TransforCNN with three other algorithms, U-Net, Y-Net, and E-Net, consisting of an ensemble network model for XCT analysis. Our results show the advantages of using TransforCNN when evaluating over-segmentation metrics, such as mean intersection over union (mIoU) and mean Dice similarity coefficient (mDSC), as well as through several qualitatively comparative visualizations.

Quenum, Jerome (ORCID:0000000271265853)↗