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

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At least 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Power grid frequency prediction using spatiotemporal modeling

Understanding power system dynamics is essential for interarea oscillation analysis and the detection of grid instabilities. The FNET/GridEye is a GPS-synchronized wide-area frequency measurement network that provides an accurate picture of the normal real-time operational condition of the power system-dynamics, giving rise to new and intricate spatiotemporal patterns of power loads. We propose to model FNET/GridEye grid frequency data from the U.S. Eastern Interconnection with a spatiotemporal statistical model. We predict the frequency data at locations without observations, a critical need during disruption events where measurement data are inaccessible. Spatial information is accounted for either as neighboring measurements in the form of covariates or with a spatiotemporal correlation model captured by a latent Gaussian field. Finally, the proposed method is useful in estimating power system dynamic response from limited phasor measurements and holds promise for predicting instability that may lead to undesirable effects such as cascading outages.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Deformation Rate‐Adaptive Conducting Polymers and Composites

Abstract Materials are more easily damaged during accidents that involve rapid deformation. Here, a design strategy is described for electronic materials comprised of conducting polymers that defies this orthodox property, making their extensibility and toughness dynamically adaptive to deformation rates. This counterintuitive property is achieved through a morphology of interconnected nanoscopic core–shell micelles, where the chemical interactions are stronger within the shells than the cores. As a result, the interlinked shells retain material integrity under strain, while the rate of dissociation of the cores controls the extent of micelle elongation, which is a process that adapts to deformation rates. A prototype based on polyaniline shows a 7.5‐fold increase in ultimate elongation and a 163‐fold increase in toughness when deformed at increasing rates from 2.5 to 10 000% min −1 . This concept can be generalized to other conducting polymers and highly conductive composites to create “self‐protective” soft electronic materials with enhanced durability under dynamic movement or deformation.

Hernandez, Victor↗
DOE OSTI2025

Holistic Microstructure Control Strategies in Photopolymerization‐Induced Phase Separation of Acrylate Systems

Open porous materials, known for their large surface area and interconnected structures, are essential in various applications, including batteries, ion exchange, catalysis, filtration, and electronic waste recycling. A critical aspect of the functionality of porous membranes is the precise control of pore size and morphology. Photopolymerization-induced phase separation (photo-PIPS) offers a convenient and versatile methods for creating porous structures. However, controlling the porous morphology remains challenging due to the complex interplay between thermodynamics, polymerization kinetics, and monomer structures, which makes it difficult to establish the relationship between processing conditions and resulting morphology in photo-PIPS. Herein, a physics-based phase-field model capable of generating and characterizing the microstructures of porous materials based on both average and localized features is developed. Using the phase-field simulations as test bed, the effects of polarity, light intensity, and curing temperature, as well as the previously unexplored roles of chain transfer agents and substrates, on the morphology of the resulting porous microstructure are investigated. Experiments are performed to verify the results predicted by the simulations. This work lays out a comprehensive guide for designing PIPS-derived porous microstructures and offers practical engineering strategies for tailoring microstructure-level topology and size of pores for application-specific needs.

36 MATERIALS SCIENCE↗
DOE OSTI2024

The water–climate nexus: Intersections across sectors

Water security and climate change are important priorities for communities and regions worldwide. The intersections between water and climate change extend across many environmental and human activities. This Primer is intended as an introduction, grounded in examples, for students and others considering the interactions between climate, water, and society. In this Primer, we summarize key intersections between water and climate across four sectors: environment; drinking water, sanitation, and hygiene; food and agriculture; and energy. We begin with an overview of the fundamental water dynamics within each of these four sectors, and then discuss how climate change is impacting water and society within and across these sectors. Emphasizing the relationships and interconnectedness between water and climate change can encourage systems thinking, which can show how activities in one sector may influence activities or outcomes in other sectors. We argue that to achieve a resilient and sustainable water future under climate change, proposed solutions must consider the water–climate nexus to ensure the interconnected roles of water across sectors are not overlooked. Toward that end, we offer an initial set of guiding questions that can be used to inform the development of more holistic climate solutions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

libwfa: Wavefunction analysis tools for excited and open‐shell electronic states

Abstract An open‐source software library for wavefunction analysis, libwfa, provides a comprehensive and flexible toolbox for post‐processing excited‐state calculations, featuring a hierarchy of interconnected visual and quantitative analysis methods. These tools afford compact graphical representations of various excited‐state processes, provide detailed insight into electronic structure, and are suitable for automated processing of large data sets. The analysis is based on reduced quantities, such as state and transition density matrices (DMs), and allows one to distill simple molecular orbital pictures of physical phenomena from intricate correlated wavefunctions. The implemented descriptors provide a rigorous link between many‐body wavefunctions and intuitive physical and chemical models, for example, exciton binding, double excitations, orbital relaxation, and polyradical character. A broad range of quantum‐chemical methods is interfaced with libwfa via a uniform interface layer in the form of DMs. This contribution reviews the structure of libwfa and highlights its capabilities by several representative use cases. This article is categorized under: Software > Quantum Chemistry Theoretical and Physical Chemistry > Spectroscopy

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Characterization of demand response in the commercial, industrial, and residential sectors in the United States

The goal of our study is to provide an overview of demand response (DR) technologies, including standards and end uses, in the United States and describe resource characteristics and the attributes of 14 specific DR resources in the U.S. commercial, residential, and industrial sectors. The attributes reviewed for the end uses being considered are response frequency, response time, the need for and impacts of energy pre- or recharge, the cost of enabling a resource to respond to a load-curtailment signal, and the magnitude of load curtailment in a given resource. We also describe controls and communications technologies that can enable end uses to participate in DR programs. The characterization was initially developed as a foundational work to quantify hourly availability of DR resources from the selected end uses followed by a multi-laboratory effort that quantified DR's value within the Western Interconnection.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Estimating the impacts of natural gas power generation growth on solar electricity development: PJM's evolving resource mix and ramping capability

Abstract Expansion of distributed solar photovoltaic (PV) and natural gas‐fired generation capacity in the United States has put a renewed spotlight on methods and tools for power system planning and grid modernization. This article investigates the impact of increasing natural gas‐fired electricity generation assets on installed distributed solar PV systems in the Pennsylvania–New Jersey–Maryland (PJM) Interconnection in the United States over the period 2008–2018. We developed an empirical dynamic panel data model using the system‐generalized method of moments (system‐GMM) estimation approach. The model accounts for the impact of past and current technical, market and policy changes over time, forecasting errors, and business cycles by controlling for PJM jurisdictions‐level effects and year fixed effects. Using an instrumental variable to control for endogeneity, we concluded that natural gas does not crowd out renewables like solar PV in the PJM capacity market; however, we also found considerable heterogeneity. Such heterogeneity was displayed in the relationship between solar PV systems and electricity prices. More interestingly, we found no evidence suggesting any relationship between distributed solar PV development and nuclear, coal, hydro, or electricity consumption. In addition, considering policy effects of state renewable portfolio standards, net energy metering, differences in the PJM market structure, and other demand and cost‐related factors proved important in assessing their impacts on solar PV generation capacity, including energy storage as a non‐wire alternative policy technique. This article is categorized under: Photovoltaics > Economics and Policy Fossil Fuels > Climate and Environment Energy Systems Economics > Economics and Policy

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

Industrial IoT cross-layer forensic investigation

Cross-layer forensic investigation is addressed for Industrial Internet of Things (IIoT) device attacks in Critical Infrastructure (CI) applications. The operational motivation for cross-layer investigation is provided by the desire to directly correlate bit-level network anomaly detection with physical layer (PHY) device connectivity and/or status (normal, defective, attacked, etc.) at the time of attack. The technical motivation for developing cross-layer techniques is motivated by (a) having considerable capability in place for Higher-Layer Digital Forensic Information exploitation—real-time network cyberattack and postattack analysis, (b) having considerably less capability in place for Lowest-Layer PHY Forensic Information exploitation—the PHY domain remains largely under exploited, and (c) considering cyber-physical integration as a means to jointly exploit higher-layer digital and lowest-layer PHY forensic information to maximize investigative benefit in IIoT cyber forensics. A delineation of higher-layer digital and lowest-layer PHY elements is provided for the standard network Open Systems Interconnection model and the specific Perdue Enterprise Reference Architecture commonly used in IIoT Industrial Control System/Supervisory Control and Data Acquisition applications. Finally, a forensics work summary is provided for each delineated area based on selected representative publications and provides the basis for presenting the envisioned cross-layer forensic investigation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

A Real-Time Big Data Control-Theoretical Framework for Cyber-Physical-Human Systems [Book Chapter]

It is known that cyber-physical-human systems naturally arise from interdependent infrastructure systems and smart connected communities. Such applications require ubiquitous information sensing and processing, intelligent machine-to-machine communication for a seamless coordination, as well as intelligent interactions between humans and machines. This chapter presents a control-theoretical framework to model heterogeneous physical dynamic systems, information and communication, as well as cooperative controls and/or distributed optimization of such interconnected systems. It is shown that efficient analytical and computational algorithms can be modularly designed and hierarchically implemented to operate and optimize cyber-physical-human systems, first to quantify individually the input–output relationship of nonlinear dynamic behaviors of every physical subsystem, then to coordinate locally both cyber-physical interactions of neighboring agents as well as physical-human interactions, and finally to dynamically model and optimize the overall networked system. The hierarchical structure makes the overall optimization and control problem scalable and solvable. Moreover, the three levels integrate individual designs and optimization, distributed cooperative optimization, and decision-making through real-time, data-driven, model-based learning and control. Specifically, one of the contributions of the chapter is to demonstrate how the combination of dissipativity theory and cooperative control serves as a natural framework and promising tools to analyze, optimize, and control such large-scale system. Application to digital grid is investigated as an illustrative example.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Extending OpenSHMEM with Aggregation Support for Improved Message Rate Performance

OpenSHMEM is a highly efficient one-sided communication API that implements the PGAS parallel programming model, and is known for its low latency communication operations that can be mapped efficiently to RDMA capabilities of network interconnects. However, applications that use OpenSHMEM can be sensitive to point-to-point message rates, as many-to-many communication patterns can generate large amounts of small messages which tend to overwhelm network hardware that has predominantly been optimised for bandwidth over message rate. Additionally, many important emerging classes of problems such as data analytics are similarly troublesome for the irregular access patterns they employ. Message aggregation strategies have been proven to significantly enhance network performance, but their implementation often involves complex restructuring of user code, making them unwieldy. This paper shows how to combine the best qualities of message aggregation within the communication model of OpenSHMEM such that applications with small and irregular access patterns can improve network performance while maintaining their algorithmic simplicity. We do this by providing a path to a message aggregation framework called conveyors through a minimally intrusive OpenSHMEM extension introducing aggregation contexts that fit more naturally to the OpenSHMEM atomics, gets, and puts model. We test these extensions using four of the bale 3.0 applications which contain essential many-to-many access patterns to show how they can produce performance improvements of up to 65×.

Welch, Aaron↗
DOE OSTI2015

Accelerating k-NN Algorithm with Hybrid MPI and OpenSHMEM

Machine Learning algorithms are benefiting from the continuous improvement of programming models, including MPI, MapReduce and PGAS. k-Nearest Neighbors (k-NN) algorithm is a widely used machine learning algorithm, applied to supervised learning tasks such as classification. Several parallel implementations of k-NN have been proposed in the literature and practice. However, on high-performance computing systems with high-speed interconnects, it is important to further accelerate existing designs of the k-NN algorithm through taking advantage of scalable programming models. To improve the performance of k-NN on large-scale environment with InfiniBand network, this paper proposes several alternative hybrid MPI+OpenSHMEM designs and performs a systemic evaluation and analysis on typical workloads. The hybrid designs leverage the one-sided memory access to better overlap communication with computation than the existing pure MPI design, and propose better schemes for efficient buffer management. The implementation based on k-NN program from MaTEx with MVAPICH2-X (Unified MPI+PGAS Communication Runtime over InfiniBand) shows up to 9.0% time reduction for training KDD Cup 2010 workload over 512 cores, and 27.6% time reduction for small workload with balanced communication and computation. Experiments of running with varied number of cores show that our design can maintain good scalability.

Lin, Jian↗
DOE OSTI2022

-Omics potential of in vitro skin models for radiation exposure

There is a growing need to uncover biomarkers of ionizing radiation exposure that leads to a better understanding of how exposures take place, including dose type, rate, and time since exposure. As one of the first organs to be exposed to external sources of ionizing radiation, skin is uniquely positioned in terms of model systems for radiation exposure study. The simultaneous evolution of both MS-based -omics studies, as well as in vitro 3D skin models, has created the ability to develop a far more holistic understanding of how ionizing radiation affects the many interconnected biomolecular processes that occur in human skin. However, there are a limited number of studies describing the biomolecular consequences of low-dose ionizing radiation to the skin. As a result, this review will seek to explore the current state-of-the-art technology in terms of in vitro 3D skin models, as well as track the trajectory of MS-based -omics techniques and their application to ionizing radiation research, specifically, the search for biomarkers within the low-dose range.

3D tissue model↗
DOE OSTI2016

Possible role of interference, protein noise, and sink effects in nonphotochemical quenching in photosynthetic complexes

Here, we analyze theoretically a simple and consistent quantum mechanical model that reveals the possible role of quantum interference, protein noise, and sink effects in the nonphotochemical quenching (NPQ) in light-harvesting complexes (LHCs). The model consists of a network of five interconnected sites (excitonic states of light-sensitive molecules) responsible for the NPQ mechanism. The model also includes the “damaging” and the dissipative channels. The damaging channel is responsible for production of singlet oxygen and other destructive outcomes. In this model, both damaging and “dissipative” charge transfer channels are described by discrete electron energy levels attached to their sinks, that mimic the continuum part of electron energy spectrum. All five excitonic sites interact with the protein environment that is modeled using a stochastic process. Our approach allowed us to derive the exact and closed system of linear ordinary differential equations for the reduced density matrix and its first momentums. Moreover, these equations are solved numerically including for strong interactions between the light-sensitive molecules and protein environment. As an example, we apply our model to demonstrate possible contributions of quantum interference, protein noise, and sink effects in the NPQ mechanism in the CP29 minor LHC. The numerical simulations show that using proper combination of quantum interference effects, properties of noise, and sinks, one can significantly suppress the damaging channel. Finally, our findings demonstrate the possible role of interference, protein noise, and sink effects for modeling, engineering, and optimizing the performance of the NPQ processes in both natural and artificial light-harvesting complexes.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Quantifying the influence of natural climate variability on in situ measurements of seasonal total and extreme daily precipitation

Abstract While various studies explore the relationship between individual sources of climate variability and extreme precipitation, there is a need for improved understanding of how these physical phenomena simultaneously influence precipitation in the observational record across the contiguous United States. In this work, we introduce a single framework for characterizing the historical signal (anthropogenic forcing) and noise (natural variability) in seasonal mean and extreme precipitation. An important aspect of our analysis is that we simultaneously isolate the individual effects of seven modes of variability while explicitly controlling for joint inter-mode relationships. Our method utilizes a spatial statistical component that uses in situ measurements to resolve relationships to their native scales; furthermore, we use a data-driven procedure to robustly determine statistical significance. In Part I of this work we focus on natural climate variability: detection is mostly limited to DJF and SON for the modes of variability considered, with the El Niño/Southern Oscillation, the Pacific–North American pattern, and the North Atlantic Oscillation exhibiting the largest influence. Across all climate indices considered, the signals are larger and can be detected more clearly for seasonal total versus extreme precipitation. We are able to detect at least some significant relationships in all seasons in spite of extremely large (> 95%) background variability in both mean and extreme precipitation. Furthermore, we specifically quantify how the spatial aspect of our analysis reduces uncertainty and increases detection of statistical significance while also discovering results that quantify the complex interconnected relationships between climate drivers and seasonal precipitation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

The Tunisian Jurassic aquifer in the North African Sahara aquifer system: information derived from two-dimensional seismic reflection and well logs

Southern Tunisia is an arid area where socio-economic activities are dependent on groundwater resources. The presented study aims to better characterize the Jurassic aquifer based on geological and geophysical data, with a view to develop a rational exploitation program. Well logs are used to precisely determine the position and composition of the known Jurassic aquifer layers and to identify others able to produce good quality water. The logs show that limestones, sandstones and dolomites of the Krachoua, Techout and Foum Tataouine formations are the main Jurassic aquifers. Sixty-eight seismic-reflection sections are integrated within this study. The interpolation between the interpreted sections leads to the construction of isochronous isopach maps and geoseismic sections, and their analysis finds that compressive and extensive tectonic deformations have influenced the Jurassic aquifer geometry. The Hercynian orogeny phase manifestation is remarkable in that there are several stratigraphic gaps in the Jurassic sequence. The E–W, NW–SE, and NNW–SSE accidents, reactivated in normal faults since the Permian to Lower Cretaceous epochs, have generated the structures found in the Jurassic series, such as subsided and raised blocks. Their syn-sedimentary activity has controlled the thickness and facies of these series. The Cretaceous, Tortonian and Post-Villafranchian compressions are responsible for the Jurassic-deposits folding in some localities. The highlighted tectonic and sedimentary events have an important impact on the Jurassic aquifer function by favoring the Jurassic aquifer interconnections and their connections with the Triassic and Cretaceous permeable series.

58 GEOSCIENCES↗
DOE OSTI2018

Modeling groundwater/surface-water interactions in an Alpine valley (the Aosta Plain, NW Italy): the effect of groundwater abstraction on surface-water resources

A groundwater flow model of the Alpine valley aquifer in the Aosta Plain (NW Italy) showed that well pumping can induce river streamflow depletions as a function of well location. Analysis of the water budget showed that ∼80% of the water pumped during 2 years by a selected well in the downstream area comes from the baseflow of the main river discharge. Alluvial aquifers hosted in Alpine valleys fall within a particular hydrogeological context where groundwater/surface-water relationships change from upstream to downstream as well as seasonally. A transient groundwater model using MODFLOW2005 and the Streamflow-Routing (SFR2) Package is here presented, aimed at investigating water exchanges between the main regional river (Dora Baltea River, a left-hand tributary of the Po River), its tributaries and the underlying shallow aquifer, which is affected by seasonal oscillations. The three-dimensional distribution of the hydraulic conductivity of the aquifer was obtained by means of a specific coding system within the database TANGRAM. Both head and flux targets were used to perform the model calibration using PEST. Results showed that the fluctuations of the water table play an important role in groundwater/surface-water interconnections. In upstream areas, groundwater is recharged by water leaking through the riverbed and the well abstraction component of the water budget changes as a function of the hydraulic conditions of the aquifer. In downstream areas, groundwater is drained by the river and most of the water pumped by wells comes from the base flow component of the river discharge.

58 GEOSCIENCES↗
DOE OSTI2021

Integrated energy-water-land nexus planning in the Colorado River Basin (Argentina)

Integrated energy-water-land (EWL) planning promotes synergies and avoids conflicts in ways that sector-specific planning approaches cannot. Many important decisions that influence emerging EWL nexus issues are implemented at regional (e.g., large river basin, electricity grid) and sub-regional (e.g., small river basin, irrigation district) scales. However, actual implementation of integrated planning at these scales has been limited. Simply collecting and visualizing data and interconnections across multiple sectors and sub-regions in a single modeling platform is a unique endeavor in many regions. This study introduces and applies a novel approach to linking together multiple sub-regions in a single platform to characterize and visualize EWL resource use, EWL system linkages within and among sub-regions, and the EWL nexus implications of future policies and investments. This integrated planning methodology is applied in the water-stressed Colorado River Basin in Argentina, which is facing increasing demands for agricultural and fossil fuel commodities. Guided by stakeholders, this study seeks to inform basin planning activities by characterizing and visualizing (1) the basin’s current state of EWL resources, (2) the linkages between sectors within and among basin sub-regions, and (3) the EWL nexus implications of planned future agricultural development activities. Results show that water scarcity, driven in part by human demands that have historically reached 60% of total surface water supply, poses a substantial constraint to economic development in the basin. The Colorado basin has the potential to serve as a testbed for crafting novel and generalizable sub-regional EWL planning approaches capable of informing the EWL planning dialogue globally.

54 ENVIRONMENTAL SCIENCES↗