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All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

DEPRECATED CSG-public (Connected and Automated Vehicles Scenario Generation Model) [SWR-13-31]

DEPRECATED This repository was archived by the owner on Jun 30, 2026. It is now read-only. The Connected and Automated Vehicles Scenario Generation (CSG) model is a system dynamics model. It was built by NREL and funded by the U.S. Department of Energy under the Systems and Modeling for Accelerated Research in Transportation (SMART) Mobility initiative. The purpose of the model is to simulate the "transitions from predominantly individual ownership of non-CAVs to various future scenarios of high connectivity/automation"(Bush, Vimmerstedt, and Gonder 2019).

Bush, Brian↗
DOE OSTI2020

Interseasonal Connections between the Timing of the Stratospheric Final Warming and Arctic Sea Ice

Connections across seasons in atmospheric circulation and sea ice have long been sought to advance seasonal prediction. This study presents a link between the springtime stratosphere and Arctic sea ice in summer through autumn. The polar stratospheric vortex dominates the winter stratosphere before breaking down each spring, which is called the stratospheric final warming, as solar radiation returns to the pole. Interannual variability of this breakdown is dynamically driven, leading to different springtime tropospheric and surface circulation patterns. To examine the different impacts of delayed and early final warmings, a multimodel composite was generated from selected CMIP5 models. Additionally, regressions were performed on JRA-55 against an index of springtime polar vortex strength. In both the multimodel composites and reanalysis regressions, significant anomalies in sea ice thickness persist several months following an anomalous timing of the final warming. A later final warming or stronger springtime polar stratospheric vortex leads to negative sea ice thickness anomalies in the East Siberian Sea and positive anomalies in the Beaufort Sea in comparison with an earlier final warming or weaker polar vortex. The spring polar stratospheric vortex is related to spring polar surface circulation patterns. The winds associated with this pattern induce anomalous sea ice motion, moving ice from the East Siberian Sea toward the Beaufort Sea. Reduced sea ice in the East Siberian Sea is linked to anomalous warmth over this region in autumn. Our results suggest that the timing of the stratospheric final warming exerts an influence on the tropospheric circulation and sea ice through autumn, which has implications for seasonal climate prediction.

Kelleher, Michael↗
DOE OSTI2014

Connections between Student Explanations and Arguments from Evidence about Plant Growth

We investigate how students connect explanations and arguments from evidence about plant growth and metabolism—two key practices described by the Next Generation Science Standards. This study reports analyses of interviews with 22 middle and high school students postinstruction, focusing on how their sense-making strategies led them to interpret—or misinterpret—scientific explanations and arguments from evidence. The principles of conservation of matter and energy can provide a framework for making sense of phenomena, but our results show that some students reasoned about plant growth as an action enabled by water, air, sunlight, and soil rather than a process of matter and energy transformation. These students reinterpreted the hypotheses and results of standard investigations of plant growth, such as van Helmont's experiment, to match their own understanding of how plants grow. Only the more advanced students consistently interpreted mass changes in plants or soil as evidence of movement of matter. We also observed that a higher degree of scaffolding during some of the interview questions allowed mid-level students to improve their responses. We describe our progress and challenges developing teaching materials with scaffolding to improve students’ understanding of plant growth and metabolism.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Network inference reveals novel connections in pathways regulating growth and defense in the yeast salt response

Cells respond to stressful conditions by coordinating a complex, multi-faceted response that spans many levels of physiology. Much of the response is coordinated by changes in protein phosphorylation. Although the regulators of transcriptome changes during stress are well characterized in Saccharomyces cerevisiae , the upstream regulatory network controlling protein phosphorylation is less well dissected. Here, we developed a computational approach to infer the signaling network that regulates phosphorylation changes in response to salt stress. We developed an approach to link predicted regulators to groups of likely co-regulated phospho-peptides responding to stress, thereby creating new edges in a background protein interaction network. We then use integer linear programming (ILP) to integrate wild type and mutant phospho-proteomic data and predict the network controlling stress-activated phospho-proteomic changes. The network we inferred predicted new regulatory connections between stress-activated and growth-regulating pathways and suggested mechanisms coordinating metabolism, cell-cycle progression, and growth during stress. We confirmed several network predictions with co-immunoprecipitations coupled with mass-spectrometry protein identification and mutant phospho-proteomic analysis. Results show that the cAMP-phosphodiesterase Pde2 physically interacts with many stress-regulated transcription factors targeted by PKA, and that reduced phosphorylation of those factors during stress requires the Rck2 kinase that we show physically interacts with Pde2. Conclusively, our work shows how a high-quality computational network model can facilitate discovery of new pathway interactions during osmotic stress.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Towards a more general understanding of the algorithmic utility of recurrent connections

Lateral and recurrent connections are ubiquitous in biological neural circuits. Yet while the strong computational abilities of feedforward networks have been extensively studied, our understanding of the role and advantages of recurrent computations that might explain their prevalence remains an important open challenge. Foundational studies by Minsky and Roelfsema argued that computations that require propagation of global information for local computation to take place would particularly benefit from the sequential, parallel nature of processing in recurrent networks. Such “tag propagation” algorithms perform repeated, local propagation of information and were originally introduced in the context of detecting connectedness, a task that is challenging for feedforward networks. Here, we advance the understanding of the utility of lateral and recurrent computation by first performing a large-scale empirical study of neural architectures for the computation of connectedness to explore feedforward solutions more fully and establish robustly the importance of recurrent architectures. In addition, we highlight a tradeoff between computation time and performance and construct hybrid feedforward/recurrent models that perform well even in the presence of varying computational time limitations. We then generalize tag propagation architectures to propagating multiple interacting tags and demonstrate that these are efficient computational substrates for more general computations of connectedness by introducing and solving an abstracted biologically inspired decision-making task. Our work thus clarifies and expands the set of computational tasks that can be solved efficiently by recurrent computation, yielding hypotheses for structure in population activity that may be present in such tasks.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Altered white matter connectivity in patients with schizophrenia: An investigation using public neuroimaging data from SchizConnect

Several studies have produced extensive evidence on white matter abnormalities in schizophrenia (SZ). However, optimum consistency and reproducibility have not been achieved, and reported low white matter tract integrity in patients with SZ varies between studies. A whole-brain imaging study with a large sample size is needed. This study aimed to investigate white matter integrity in the corpus callosum and connections between regions of interests (ROIs) in the same hemisphere in 122 patients with SZ and 129 healthy controls with public neuroimaging data from SchizConnect. For each diffusion-weighted image (DWI), two-tensor full-brain tractography was performed; DWIs were parcellated by processing and registering T1 images with FreeSurfer and Advanced Normalization Tools. White matter query language was used to extract white matter fiber tracts. We evaluated group differences in means of diffusion measures between the patients and controls, and correlations of diffusion measures with the severity of clinical symptoms and cognitive impairment in the patients using the Positive and Negative Syndrome Scale (PANSS), a letter-number sequencing (LNS) test, vocabulary test, letter fluency test, category fluency test, and trail-making test, part A. To correct for multiple comparisons, a false discovery rate of q < 0.05 was applied. In patients with SZ, we observed significant radial diffusivity (RD) and trace (TR) increases in left thalamo-occipital tracts and the right uncinate fascicle, and a significant RD increase in the right middle longitudinal fascicle (MDLF) and the right superior longitudinal fascicle ii. Correlations were present between TR of left thalamo-occipital tracts, and the letter fluency test and the LNS test, and RD in the right MDLF and PANSS positive subscale score. However, these correlations were not significant after correction for multiple comparisons. These results indicated widespread white matter fiber tract abnormalities in patients with SZ, contributing to SZ pathophysiology.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Spurious regulatory connections dictate the expression-fitness landscape of translation factors

During steady-state cell growth, individual enzymatic fluxes can be directly inferred from growth rate by mass conservation, but the inverse problem remains unsolved. Perturbing the flux and expression of a single enzyme could have pleiotropic effects that may or may not dominate the impact on cell fitness. Here, we quantitatively dissect the molecular and global responses to varied expression of translation termination factors (peptide release factors, RFs) in the bacterium Bacillus subtilis. While endogenous RF expression maximizes proliferation, deviations in expression lead to unexpected distal regulatory responses that dictate fitness reduction. Molecularly, RF depletion causes expression imbalance at specific operons, which activates master regulators and detrimentally overrides the transcriptome. Through these spurious connections, RF abundances are thus entrenched by focal points within the regulatory network, in one case located at a single stop codon. Such regulatory entrenchment suggests that predictive bottom-up models of expression-fitness landscapes will require near-exhaustive characterization of parts.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

The ABCs of phase retrieval: Connecting the acronyms of scanning transmission electron microscopy

High-resolution scanning transmission electron microscopy (S/TEM) is an indispensable tool for characterizing the structure and properties of materials down to the atomic scale. Conventional S/TEM imaging, however, is limited by the phase problem, whereby the phase of the electron exit wave is lost upon detection. Recent advances in diffractive imaging and 4D-STEM have enabled a range of phase-retrieval techniques that computationally reconstruct the missing information encoded in the phase of the transmission function. These approaches offer improved dose efficiency and enhanced sensitivity to weakly scattering signals, extending quantitative imaging to beam-sensitive materials composed of light elements. In this work, we introduce the phase problem in electron microscopy and survey the diverse landscape of phase-retrieval techniques used in the field. Despite their many acronyms and algorithmic variations, these techniques share a common physical and mathematical foundation. We present a unified framework that connects these seemingly distinct methods, from parallax imaging and tilt-corrected bright-field (tcBF-STEM), to aberration-corrected bright-field (acBF-STEM), optimum bright-field (OBF-STEM) and single-sideband (SSB) ptychography, as well as first-moment integrated center of mass techniques (iCOM) and iterative ptychographic algorithms. Based on these insights, we discuss the opportunities and practical limitations of applying these methods across different materials systems, detector designs, and microscope configurations.Graphical abstractRepresentative electron microscopy configurations used for phase retrieval and diffractive imaging in S/TEM: (a) Zernike phase-contrast transmission electron microscopy (TEM), (b) small-convergence-angle four-dimensional scanning transmission electron microscopy (4D-STEM) for nanobeam-based phase reconstruction methods, and (c) large-convergence-angle 4D-STEM for ptychographic and related diffractive imaging techniques reviewed in this work.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Connectivity-enhanced route selection and adaptive control for the Chevrolet Volt

The National Renewable Energy Laboratory and General Motors evaluated connectivity-enabled efficiency enhancements for the Chevrolet Volt. A high-level model was developed to predict vehicle fuel and electricity consumption based on driving characteristics and vehicle state inputs. These techniques were leveraged to optimize energy efficiency via green routing and intelligent control mode scheduling, which were evaluated using prospective driving routes between tens of thousands of real-world origin/destination pairs. The overall energy savings potential of green routing and intelligent mode scheduling was estimated at 5% and 3%, respectively. Furthermore, these represent substantial opportunities considering that they only require software adjustments to implement.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2024

Carbon Management Projects (CONNECT) Database and Explorer

Overview The Carbon Management Projects (CONNECT) Toolkit is an online exploratory visualization tool developed by the U.S. Department of Energy's (DOE) Office of Fossil Energy and Carbon Management (FECM) with support from other federal agencies such as the U.S. Environmental Protection Agency (EPA) and the U.S. Department of Transportation (DOT). It provides a single point of access to authoritative information on federal agency investment in a portfolio of research, development, and demonstration (RD&D) projects that have been publicly announced to advance technologies for point source carbon capture, carbon dioxide removal, transport, storage, and conversion, collectively referred to as carbon management. The RD&D programs covered in this tool are authorized by annual congressional appropriations ("Base Program") and the 2021 Infrastructure Investment and Jobs Act (IIJA). The tool also incorporates public information on other federal initiatives, such as the Regional Clean Hydrogen Hubs, and public information released by other government agencies, such as the Environmental Protection Agency's (EPA) and Primacy States’ Underground Injection Control Class VI permits and EPA’s facility level greenhouse gas (GHG) emissions. Developed in a geographic information system, the tool organizes carbon management projects into five groups based on the primary technology that a project aims to advance, each visually represented as a digital layer ("carbon management project layer"). Only federally funded projects are included, which can be awarded projects that are completed or ongoing, or projects that have been selected but are currently under negotiation. Project information can be viewed in the map or in the attribute table below it when turned on. In the map view, each project is displayed at either its host site (for field work), where available, or its performer site (project lead's location, further explained in the table below). Host sites and performer sites are represented in distinct icons. Several reference layers offer additional public information on infrastructural and natural resource environment for carbon management. These reference layers, combined with multiple geographical basemaps, enable users to visualize the carbon management project layers in context. Carbon management project information will be updated monthly based on feedback and information availability. Carbon management project layers Point Source Carbon Capture (PSC) This layer contains DOE-funded projects focused on capturing carbon dioxide (CO2) from power plants or industrial facilities. Carbon Dioxide Removal (CDR) This layer contains DOE-funded projects focused on capturing CO2 from the atmosphere, including direct air capture (DAC) and DAC hubs, direct ocean capture, enhanced mineralization, and biomass carbon removal and storage. For projects with multiple host sites, each of the sites are displayed individually with the project cost and cost sharing information representing the total for the entire project. Carbon Transport This layer contains DOE- and DOT-funded projects focused on CO2 transport. The Transport Research and Development sublayer contains projects that do not involve physical infrastructure; the Proposed Transport Corridor sublayer contains projects for which either a route for the transport infrastructure has been proposed or a general area for the transport infrastructure has been identified. Carbon Storage This layer contains DOE-funded key projects focused on CO2 storage. For projects with multiple field-work sites, each of the sites are displayed individually on the map with the project cost and cost sharing information representing the overall total for the entire project. Carbon Conversion This layer contains DOE-funded projects focused on converting CO2 into economically valuable products. Reference layers The following layers provide additional information in the geographic proximity of carbon management projects. Users should reference the original sources for more details (weblinks provided below and in pop-up windows on the map). Regional Clean Hydrogen Hub and Facility These layers illustrate the approximate areas of the Regional Clean Hydrogen Hubs announced by DOE's Office of Clean Energy Demonstrations (OCED) and the approximate locations of individual facilities that constitute the hubs (see "Where are the H2Hubs located?" on the webpage linked above). EPA Facility Level GHG Emissions (direct emitter) This layer shows direct CO2 emissions from stationary sources in 2022, using data extracted from EPA's Facility Level Information on GreenHouse gases Tool (FLIGHT). Captured and injected CO2 are not deducted from direct emitters’ total emissions. Contact EPA for additional details. Underground Injection Control Class VI permit/permit application This layer shows the locations of CO2 injection wells that are granted or in the process of applying for an Underground Injection Control Class VI permit by EPA or a Primacy State (currently Louisiana, North Dakota, and Wyoming). The URLs for the permits or permit applications are provided in the pop-up windows associated with the well locations. Contact EPA for additional details. Carbon Storage Resource This layer contains information on prospective CO2 storage resources in saline formations and oil and gas reservoirs provided by the National Carbon Sequestration Database and Geographic Information System (NATCARB) spatial database. Contact NETL for additional details. Existing CO2 pipeline This layer shows active CO2 pipelines based on information digitized from the map issued by the Pipeline and Hazardous Materials Safety Administration (PHMSA). Contact PHMSA for additional details.

Carbon Conversion↗
DOE OSTI2021

Pore-Scale Oil Connectivity and Displacement by Controlled-Ionic-Composition Waterflooding Using Synchrotron X-Ray Microtomography

Controlled-ionic-composition waterflooding is an economic and effective method to improve oil recovery in carbonate oil reservoirs. Recent studies show controlling the salinity and ionic composition of injection water can alter the wettability of carbonate mineral surfaces. The pore-scale oil connectivity and displacement by controlled-ionic-composition waterflooding in heterogeneous carbonate reservoirs, especially at the early stage, is still unclear. The goal of this study is to examine the role of ion concentrations and types in the oil displacement efficiency and investigate the impact of the waterflooding on the pore-scale oil displacement using the national synchrotron facility. A carbonate rock sample was flooded with synthetic high-salinity water and other water solutions with different sulfate concentrations. The waterflooding processes were visualized with synchrotron X-ray microtomography to follow the evolution of pore-scale oil/brine interactions at typical field flow rates. Experimental results show that the water with lower sulfate concentration and higher salinity did not change the wettability of the pore surfaces. Higher sulfate ion concentrations in the water, in contrast, altered the wettability of carbonate pore surfaces from oil-wet to neutral-wet within the first few minutes of waterflooding. Finally, novel insight was gained on the ability of water with high-sulfate concentration to displace oil in the small pores and through abundant oil channels, which could consequently lead to higher oil recovery from the carbonate rock.

04 OIL SHALES AND TAR SANDS↗
DOE OSTI2020

Connecting quasinormal modes and heat kernels in 1-loop determinants

We connect two different approaches for calculating functional determinants on quotients of hyperbolic spacetime: the heat kernel method and the quasinormal mode method. For the example of a rotating BTZ background, we show how the image sum in the heat kernel method builds up the logarithms in the quasinormal mode method, while the thermal sum in the quasinormal mode method builds up the integrand of the heat kernel. More formally, we demonstrate how the heat kernel and quasinormal mode methods are linked via the Selberg zeta function. We show that a 1-loop partition function computed using the heat kernel method may be cast as a Selberg zeta function whose zeros encode quasinormal modes. We discuss how our work may be used to predict quasinormal modes on more complicated spacetimes.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2013

TSA Radiation Portal Monitor SC-770 Telnet Connection Using Tera Term

Tera Term is open-source telnet communications software, available from and other websites. This software provides a simple way to connect a computer to the Ethernet output of the SC-770 in a TSA radiation portal monitor (RPM). Streaming the data output can be useful for monitoring the status of an RPM, performing diagnostics, and recordkeeping.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2013

RECOVERY ACT - Robust Optimization for Connectivity and Flows in Dynamic Complex Networks

The goal of this project was to study robust connectivity and flow patterns of complex multi-scale systems modeled as networks. Networks provide effective ways to study global, system level properties, as well as local, multi-scale interactions at a component level. Numerous applications from power systems, telecommunication, transportation, biology, social science, and other areas have benefited from novel network-based models and their analysis. Modeling and optimization techniques that employ appropriate measures of risk for identifying robust clusters and resilient network designs in networks subject to uncertain failures were investigated in this collaborative multi-university project. In many practical situations one has to deal with uncertainties associated with possible failures of network components, thereby affecting the overall efficiency and performance of the system (e.g., every node/connection has a probability of partial or complete failure). Some extreme examples include power grid component failures, airline hub failures due to weather, or freeway closures due to emergencies. These are also situations in which people, materials, or other resources need to be managed efficiently. Important practical examples include rerouting flow through power grids, adjusting flight plans, and identifying routes for emergency services and supplies, in the event network elements fail unexpectedly. Solutions that are robust under uncertainty, in addition to being economically efficient, are needed. This project has led to the development of novel models and methodologies that can tackle the optimization problems arising in such situations. A number of new concepts, which have not been previously applied in this setting, were investigated in the framework of the project. The results can potentially help decision-makers to better control and identify robust or risk-averse decisions in such situations. Formulations and optimal solutions of the considered problems need to capture uncertainty and risk using appropriate probabilistic, statistical and optimization concepts. The main difficulty arising in addressing these issues is the dramatic increase in the computational complexity of the resulting optimization problems. This project studied novel models and methodologies for risk-averse network optimization- specifically, network design, network flows and cluster detection problems under uncertainty. The approach taken was to incorporate a quantitative risk measure known as conditional value-at-risk that is widely used in financial applications. This approach presents a viable alternate modeling and optimization framework to chance-constrained optimization and mean-variance optimization, one that also facilitates the detection of risk-averse solutions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Connecting Performance Analysis and Visualization to Advance Extreme Scale Computing

In the first week of January 2014 Dagstuhl hosted a Perspectives Workshop on “Connecting Performance Analysis and Visualization to Advance Extreme Scale Computing”. The event brought together two previously separate communities – from Visualization and HPC Performance Analysis – to discuss a long term joined research agenda. The goal was to identify and address the challenges in using visual representations to understand and optimize the performance of extreme-scale applications running on today’s most powerful computing systems like climate modeling, combustion, material science or astro-physics simulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Connectivity Enhanced Energy Management and Control for EREVs: Cooperative Research and Development Final Report, CRADA Number CRD-11-457

The projected trend in personal mobility is the use of range extended electric vehicles (EREVs) and plug in hybrids (PHEVs). Although batteries with high power density and compact high power electric machines provide appreciable 'all electric' range, there still exists the need for an onboard range extender. The use of connectivity information such as route, elevation/curvature, traffic etc. enables substantial real world improvement in system efficiency and fuel economy of EREVs and plug-in hybrids through efficient use of stored electrical energy.

25 ENERGY STORAGE↗
DOE OSTI2015

Connecting Organic Aerosol Climate-Relevant Properties to Chemical Mechanisms of Sources and Processing

The research conducted on this project aimed to improve our understanding of secondary organic aerosol (SOA) formation in the atmosphere, and how the properties of the SOA impact climate through its size, phase state, and optical properties. The goal of this project was to demonstrate that the use of molecular composition information to mechanistically connect source apportionment and climate properties can improve the physical basis for simulation of SOA formation and properties in climate models. The research involved developing and improving methods to provide online measurements of the molecular composition of SOA under atmospherically relevant conditions and to apply this technology to controlled simulation chamber experiments and field measurements. The science we have completed with the methodology will impact the simulation of aerosol particles in climate models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Magnitude and Variability of Controllable Charge Capacity Provided by Grid Connected Plug-in Electric Vehicles

As market penetration of plug-in electric vehicles (PEV) increases over time, the number of PEVs charging on the electric grid will also increase. As the number of PEVs increases, their ability to collectively impact the grid increases. The idea of a large body of PEVs connected to the grid presents an intriguing possibility. If utilities can control PEV charging, it is possible that PEVs could act as a distributed resource to provide grid services. The technology required to control charging is available for modern PEVs. However, a system for wide-spread implementation of controllable charging, including robust communication between vehicles and utilities, is not currently present. Therefore, the value of controllable charging must be assessed and weighed against the cost of building and operating such as system. In order to grasp the value of PEV charge control to the utility, the following must be understood: 1. The amount of controllable energy and power capacity available to the utility 2. The variability of the controllable capacity from day to day and as the number of PEVs in the market increases.

33 ADVANCED PROPULSION SYSTEMS↗