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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 1,711 records · Page 95
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Extended anharmonic collapse of phonon dispersions in SnS and SnSe

The lattice dynamics and high-temperature structural transition in SnS and SnSe are investigated via inelastic neutron scattering, high-resolution Raman spectroscopy and anharmonic first-principles simulations. We uncover a spectacular, extreme softening and reconstruction of an entire manifold of low-energy acoustic and optic branches across a structural transition, reflecting strong directionality in bonding strength and anharmonicity. Further, our results solve a prior controversy by revealing the soft-mode mechanism of the phase transition that impacts thermal transport and thermoelectric efficiency. Our simulations of anharmonic phonon renormalization go beyond low-order perturbation theory and capture these striking effects, showing that the large phonon shifts directly affect the thermal conductivity by altering both the phonon scattering phase space and the group velocities. These results provide a detailed microscopic understanding of phase stability and thermal transport in technologically important materials, providing further insights on ways to control phonon propagation in thermoelectrics, photovoltaics, and other materials requiring thermal management.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Tunable thermoelectric transport in nanomeshes via elastic strain engineering

Recent experimental explorations of silicon nanomeshes have shown that the unique metastructures exhibit reduced thermal conductivity while preserving bulk electrical conductivity via feature sizes between relevant phonon and electron mean free paths, aiding in the continued promise that nanometer-scale engineering may further enhance thermoelectric behavior. Here, we introduce a strategy for tuning thermoelectric transport phenomena in semiconductor nanomeshes via heterogeneous elastic strain engineering, using silicon as a model material for demonstration of the concept. By combining analytical models for electron mobility in uniformly stressed silicon with finite element analysis of strained silicon nanomeshes in a lumped physical model, we show that the nonuniform and multiaxial strain fields defined by the nanomesh geometry give rise to spatially varying band shifts and warping, which in aggregate accelerate electron transport along directions of applied stress. This allows for global electrical conductivity and Seebeck enhancements beyond those of homogenous samples under equivalent far-field stresses, ultimately increasing thermoelectric power factor nearly 50% over unstrained samples. The proposed concept and structures—generic to a wide class of materials with large dynamic ranges of elastic strain in nanoscale volumes—may enable a new pathway for active and tunable control of transport properties relevant to waste heat scavenging and thermal management.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Experimental Test Bed to Enable Realistic Evaluations for Direct Transfer Trip Relaying via Private Wireless LTE Communications

Increasing penetration levels of inverter-based distributed energy resources (DERs) in distribution systems are creating challenges in system operation. Currently, wired or proprietary wireless communications are used by advanced distribution management systems (ADMS) to detect the state of the system and control the DERs for optimal operation. Wireless communications are an alternative solution that can enable connectivity between the dispersed assets used in distribution system applications. This paper demonstrates an experimental test bed to enable the realistic evaluation of communications system characteristics for direct transfer trip (DTT) relaying of a photovoltaic inverter system using a private 900-MHz spectrum wireless LTE network. Private LTE network communications can be deployed to many remote DERs and other grid-edge devices to prevent costly infrastructure upgrades across distribution systems. In addition, this paper provides a framework for evaluating the impact of signal strength and network traffic in communications systems. The results shown develop a better understanding of the best practices for using LTE communications systems across multiple utility applications, such as protective relaying, voltage regulation, and supervisory control and data acquisition system messages.

900-MHz LTE network↗
DOE OSTI2020

Understanding Impacts of Data Integrity Attacks on Transactive Control Systems

With the rapid growth of internet-connected smart devices capable of exchanging energy price information and adaptively controlling energy consumption of connected loads, the role of transactive control is expected to become more prominent in the modern grid. Transactive control systems integrate the wholesale and retail energy markets, and enable active participation of end users, thereby playing a key role in managing the rising number of distributed assets in the smart grid. The use of internet for the communication of data between the controllers at the building, distribution, and transmission levels makes the system susceptible to cyber-attacks. A skilled adversary can potentially manipulate the exchanged data with the intention of inflicting damage to the system. In this paper, four categories of metrics are put forth for evaluating the performance of the system when under data integrity attacks. A model for scaling-based data integrity attack has been described, and co-simulations have been performed on a 240 bus WECC transmission system model with detailed modeling of distribution systems at specific buses. Our results show that scaling-based data integrity attacks can have non-trivial impacts on the operational, financial, and comfort aspects of the transactive control system.

Smart grid, transactive control system, Buildings-↗
DOE OSTI2021

Optimal Demand Response Incorporating Distribution LMP with PV Generation Uncertainty

The utilization of aggregated demand-side flexibility via demand response (DR) has become a promising pathway for the integration of renewable energy resources in power systems. Nowadays, there are several management strategies for DR such as the price-based transactive control strategies. However, many of such existing price-based control strategies neglect the physics and operational constraints of the underlying distribution networks when computing the price, raising concerns regarding their theoretical and practical values. This paper studies this issue and investigates optimal DR (ODR) by incorporating the distribution locational marginal price (DLMP). In particular, we discuss DR in connection with DLMPs and propose a multiperiod bilevel optimization problem to find the ODR strategy. Here, the objective is to minimize the peak load, load fluctuation, and payments of load aggregators. In addition, a robust bilevel ODR model is formulated to provide a robust ODR strategy while minimizing operating costs under the worst-case realization of uncertainties; this mitigates the impact of forecasting errors on renewable energy resources. Then, we propose an efficient solution approach by employing the Karush-Kuhn-Tucker conditions and strong duality. Simulation results are presented to illustrate the mutual impacts of the interaction between DR and DLMP and the benefits of the robust ODR strategy.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

The impacts of four potential bioenergy crops on soil carbon dynamics as shown by biomarker analyses and DRIFT spectroscopy

Abstract Perennial bioenergy crops accumulate carbon (C) in soils through minimally disturbing management practices and large root inputs, but the mechanisms of microbial control over C dynamics under bioenergy crops have not been clarified. Root‐derived C inputs affect both soil microbial contribution to and degradation of soil organic matter resulting in differing soil organic carbon ( SOC ) concentrations, storage, and stabilities under different vegetation regimes. Here, we measured biomarker amino sugars and neutral sugars and used diffuse reflectance mid‐infrared Fourier transform spectroscopy ( DRIFTS ) to explore microbial C contributions, degradation ability, and SOC stability, respectively, under four potential bioenergy crops, M .× giganteus ( Miscanthus × giganteus ), switchgrass ( Panicum virgatum L .), a mixed prairie, and a maize ( Zea mays L .)–maize–soybean ( Glycine max(L.) Merr .) ( MMS ) rotation over six growing seasons. Our results showed that SOC concentration (g/kg) increased by 10.6% in mixed prairie over the duration of this experiment and SOC storage (Mg/ha) increased by 17.0% and 15.6% in switchgrass and mixed prairie, respectively. Conversion of row crops to perennial grasses maintained SOC stability and increased bacterial residue contribution to SOC in M .× giganteus and switchgrass by 20.0% and 15.0%, respectively, after 6 years. Degradation of microbe‐derived labile SOC was increased in M .× giganteus, and degradation of both labile and stable SOC increased in MMS rotation. These results demonstrate that microbial communities under perennial grasses maintained SOC quality, while SOC quantity increased under switchgrass and mixed prairie. Annual MMS rotation displayed decreases in aspects of SOC quality without changes in SOC quantity. These findings have implications for understanding microbial control over soil C quantity and quality under land‐use shift from annual to perennial bioenergy cropping systems.

09 BIOMASS FUELS↗
DOE OSTI2022

A Tanks-in-Series Approach to Estimate Parameters for Lithium-Ion Battery Models

Advanced Battery Management Systems (BMS) play a vital role in monitoring, predicting, and controlling the performance of lithium-ion batteries. BMS employing sophisticated electrochemical models can help increase battery cycle life and minimize charging time. However, in order to realize the full potential of electrochemical model-based BMS, it is critical to ensure accurate predictions and proper model parameterization. The accuracy of the predictions of an electrochemical model is dependent on the accuracy of its parameters, the values of which might change with battery cycling and aging. Parameter estimation for an electrochemical model is generally challenging due to the nonlinear nature and computational complexity of the model equations. To this end, this work utilizes the recently proposed Tanks-in-Series model for Li-ion batteries (J.Electrochem. Soc., 167, 013534 (2020)) to perform parameter estimation. The Tanks-in-Series approach allows for substantially faster parameter estimation compared to the original pseudo two-dimensional (p2D) model. The objective of this work is thus to demonstrate the gain in computational efficiency from the Tanks-in-Series approach. A sensitivity analysis of model parameters is also performed to benchmark the fidelity of the Tanks-in-Series model.

25 ENERGY STORAGE↗
DOE OSTI2016

A real-time path rating calculation tool powered by HPC

If transmission path ratings are determined in real time and optimized control methods can be implemented, congestion problems can be more effectively managed using the existing transmission assets, reducing congestion costs, avoiding capital expenditures for new physical assets, increasing revenues from the existing system, and maintaining reliability. In just one illustrative case, a BPA study has shown that a 1000-MW rating increase for a transmission path generates $15M in annual revenue, even if only 25% of the increased margin can be tapped for just 25% of the year.

Source record↗
DOE OSTI2024

Considerations for Introducing Artificial Intelligence into Nuclear Power Plants

Advanced computational tools and techniques such as artificial intelligence and machine learning (AI/ML) can transform the nuclear power industry. This is necessary given that the economic viability of the existing fleet is in jeopardy and its labor-centric approach to operations and maintenance. Currently, AI/ML research is being undertaken for reactor system design and analysis including fault and accident prognosis, nuclear risk analysis such as plant safety and security evaluation, and plant operations and maintenance including predictive maintenance. Applications include both existing and advanced reactor technologies with the aim of improving operational and business efficiencies. Most every aspect of the organization can benefit, from instrumentation and control, to work planning, to human-machine interactions and business management. AI/ML in nuclear can simplify complex problems and produce more effective decision-making. Nonetheless, careful consideration must be given to the implementation of an AI/ML initiative. The aims of this research are to 1) review barriers to AI/ML adoption within the nuclear power industry, and 2) suggest potential solutions. These barriers are organized along five distinct categories (Figure 1) that are interconnected. The first are historical barriers that track the industry’s development over the decades including worldwide nuclear events that shaped public perceptions. The resulting federal scrutiny and intense safety culture that emerged are discussed. Technical barriers to AI/ML adoption are considerable, and include data privacy concerns, data governance, and the current lack of AI/ML expert knowledge at the plants. The main business case barrier remains cost, but an absence of an industry-wide vision and wide-scale adoption also produces reluctance. Stakeholder readiness is reviewed with special attention given to regulatory readiness. The 5-year strategic plan for AI readiness recently published by the U.S. Nuclear Regulatory Commission is highlighted. Last, adoption barriers at the user level are addressed including the importance of user experience and explainable AI. The AI adoption barriers described here are inter-related and ideally should be addressed in a holistic fashion.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

New Software Architecture Options for the TCL Data Acquisition System

The Turbulent Combustion Laboratory (TCL) conducts research on combustion in turbulent flow environments. To conduct this research, the TCL utilizes several pulse lasers, a traversable wind tunnel, flow controllers, scientific grade CCD cameras, and numerous other components. Responsible for managing these different data-acquiring instruments and data processing components is the Data Acquisition (DAQ) software. However, the current system is constrained to running through VXI hardware—an instrument-computer interface—that is several years old, requiring the use of an outdated version of the visual programming language, LabVIEW. A new Acquisition System is being programmed which will borrow heavily from either a programming model known as the Current Value Table (CVT) System or another model known as the Server-Client System. The CVT System model is in essence, a giant spread sheet from which data or commands may be retrieved or written to, and the Server-Client System is based on network connections between a server and a client, very much like the Server-Client model of the Internet. Currently, the bare elements of a CVT DAQ Software have been implemented, consisting of client programs in addition to a server program that the CVT will run on. This system is being rigorously tested to evaluate the merits of pursuing the CVT System model and to uncover any potential flaws which may result in further implementation. If the CVT System is chosen, which is likely, then future work will consist of build up the system until enough client programs have been created to run the individual components of the lab. The advantages of such a System will be flexibility, portability, and polymorphism. Additionally, the new DAQ software will allow the Lab to replace the VXI with a newer instrument interface—the PXI—and take advantage of the capabilities of current and future versions of LabVIEW.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Light Material Interactions in Energy Conversion (Final Report)

The scientific vision of the “Light-Material Interactions in Energy Conversion” Energy Frontier Research Center (LMI-EFRC) is embodied in our mission statement: ‘to tailor the morphology, complex dielectric structure, and electronic properties of matter so as to sculpt the flow of sunlight and heat, enabling light conversion to electrical energy with unprecedented efficiency’. Founded in 2009, the LMI-EFRC has become a national resource for fundamental optical principles and phenomena relevant to solar energy conversion, addressing new scientific opportunities that enable efficient utilization of the entire visible and infrared solar resource. The LMI-EFRC is directed by Prof. Ralph Nuzzo and centered at its lead institution, the California Institute of Technology. The Center is an integrated and collaborative partnership of research leaders in photonics and photonic materials, comprising 14 faculty investigators that span six academic departments at five institutions, including Profs. Harry Atwater, Andrei Faraon, Nathan Lewis, and Austin Minnich at Caltech; Profs. Ralph Nuzzo, Paul Braun and John Rogers at the University of Illinois at Urbana-Champaign; Prof. Jennifer Lewis at Harvard University; Profs. Mark Brongersma, Jennifer Dionne, and Shanhui Fan at Stanford University; and Profs. Paul Alivisatos, Eli Yablonovitch, and Xiang Zhang at Lawrence Berkeley National Laboratory. The Center is organized into four research groups (RGs) that address scientific themes related to light-matter interactions, with each team spanning multiple institutional partners and designed to meet our scientific objectives. Notable project outcomes that address the LMI Mission and 2014-2018 goals include: (1) RG1 “New Light Management Mechanisms” demonstrated tunable and active nanostructured patterned surfaces (‘metasurfaces’) for control of light absorption, reflection, and propagation. (2) RG2 “Solar Spectrum Control and Conversion” developed colloidal nanocrystals with designer optical properties for fundamental studies of solar spectrum control and conversion. (3) RG3 “Thermal Photon Harvesting” established photonic design principles to harness and control thermal photons in novel conversion systems. (4) RG4 “Programmable Assembly of Photonic and Electronic Architectures” developed powerful new methods for light- and matter-based additive fabrication of electronic and photonic architectures.

14 SOLAR ENERGY↗
DOE OSTI2022

Characterizing Plug Load Energy Use and Savings Potential in Army Buildings

The Assistant Secretary of the Army (Installations, Energy and Environment) tasked the Pacific Northwest National Laboratory to examine plug loads in typical Army buildings. Plug loads (also known as miscellaneous electric loads (MELs)) represent the electricity used by appliances and devices that are plugged in or hardwired and serve functions outside of a building’s core end uses. Common plug loads include computers, printers, copiers, networking devices, refrigerators, and vending machines. They also include personal electronic devices such as televisions, smart phones, tablets, and gaming systems. Examples of hardwired MELs include elevators, air compressors, and fire and security systems. The findings from this study confirm that significant energy is consumed within Army buildings by plug load devices and hardwired MEL equipment. A number of opportunities are identified for reducing unnecessary energy use that could save the Army over $5 million per year when broadly applied. Army regulations clearly spell out expectations for the purchase and operation of information technology equipment (computers, laptops, monitors, printers, and multi-function devices). However, the policies regarding the shutdown or activation of sleep and other lower power modes after 30 minutes of inactivity (15 minutes for monitors) do not appear to be consistently followed. There are many effective approaches and pathways for impacting change as it relates to improving awareness, implementing measures, and adjusting behaviors to identify and reduce plug load energy use. The Army should prioritize and consider deploying all of these to better understand and manage plug load equipment to save energy and enhance resilience across their facilities. Engaging the building occupants who use these devices daily via outreach and education should be a strong component of the strategy. The focus should be on reducing waste without sacrificing productivity or the benefits that many of these devices provide. Continued evaluation of plug loads beyond that performed here is important to gather lessons from additional building and equipment types, and to stay aware of evolving device technology and management options. This will highlight additional needs for policies, best practices, control technologies, and education of personnel to achieve real reductions in energy waste from plug load equipment. It is recommended that this study may serve as the foundation for a broader and sustained focus on plug loads and MELs, towards simultaneously enhancing the productivity, readiness, and resilience of the Army while reducing energy use and demand, and freeing up resources to better support the mission.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Security Constrained Economic Optimization of Photovoltaic and Other Distributed Assets

The rapid growth of distributed energy resources (DERs), especially photovoltaic (PV) systems, has introduced new complexities in maintaining grid reliability, stability, and cost-effective operation. This project addresses these challenges by developing and demonstrating a scalable GridOS Distributed Energy Resource Management System (DERMS) that enables secure, real-time optimization and control of DERs at the distribution feeder level.

14 SOLAR ENERGY↗
DOE OSTI2025

A comprehensive method on black-legged tick larvae and nymph feeding on mice to study Lyme disease transmission and acquisition

Tick-borne diseases are a growing public health concern in the United States, with cases rising steadily each year. Lyme borreliosis, or Lyme disease, remains the most prevalent, affecting approximately 476,000 individuals annually. Human-driven changes in climate and ecosystems have expanded the habitat of pathogen-carrying ticks, facilitating the spread of these infections. Additionally, increased instances of tick-borne diseases transmission through human tissues have been reported. Despite ongoing efforts to manage these infections, their incidence continues to rise. To develop effective control measures against these diseases and prevent the transmission of tick-borne infections through human and animal tissues, it is very important to develop detection assays and understand the transmission mechanisms of tick-borne infections. In this study, we provide detailed descriptions and visual references for larval and nymphal tick feeding on mice, focusing on the transmission and acquisition ofBorrelia burgdorferi(sensu stricto). These methodologies can be applied to study other tick-borne diseases, tick vectorial capacity, and tick biology, aiding in the development of detection strategies to combat these infections.

Microbiology↗
DOE OSTI2025

MMMnet: A Neural Network Surrogate for Real-Time Transport Prediction Based on the Updated Multi-Mode Model

The Multi-Mode Model (MMM) is a physics-based anomalous transport model integrated into TRANSP for predicting electron and ion thermal transport, electron and impurity particle transport, and toroidal and poloidal momentum transport. While MMM provides valuable predictive capabilities, its computational cost, although manageable for standard simulations, is too high for real-time control applications. MMMnet, a neural network-based surrogate model, is developed to address this challenge by significantly reducing computation time while maintaining high accuracy. Trained on TRANSP simulations of DIII-D discharges, MMMnet incorporates an updated version of MMM (9.0.10) with enhanced physics, including isotopic effects, plasma shaping via effective magnetic shear, unified correlation lengths for ion-scale modes, and a new physics-based model for the electromagnetic electron temperature gradient mode. A key advancement is MMMnet’s ability to predict all six transport coefficients, providing a comprehensive representation of plasma transport dynamics. MMMnet achieves a two-order-of-magnitude speed improvement while maintaining strong correlation with MMM diffusivities, making it well-suited for real-time tokamak control and scenario optimization.

DIII-D↗
DOE OSTI2013

LED lamp power management system and method

An LED lamp power management system and method including an LED lamp having an LED controller 58; a plurality of LED channels 60 operably connected to the LED controller 58, each of the plurality of LED channels 60 having a channel switch 62 in series with at least one shunted LED circuit 83, the shunted LED circuit 83 having a shunt switch 68 in parallel with an LED source 80. The LED controller 58 reduces power loss in one of the channel switch 62 and the shunt switch 68 when LED lamp electronics power loss (P.sub.loss) exceeds an LED lamp electronics power loss limit (P.sub.lim); and each of the channel switches 62 receives a channel switch control signal 63 from the LED controller 58 and each of the shunt switches 68 receives a shunt switch control signal 69 from the LED controller 58.

42 ENGINEERING↗
DOE OSTI2020

Experimental Test Bed to Enable Realistic Evaluations for Direct Transfer Trip Relaying via Private Wireless LTE Communications: Preprint

Increasing penetration levels of inverter-based distributed energy resources (DERs) in distribution systems are creating challenges in system operation. Currently, wired or proprietary wireless communications are used by advanced distribution management systems (ADMS) to detect the state of the system and control the DERs for optimal operation. Wireless communications are an alternative solution that can enable connectivity between the dispersed assets used in distribution system applications. This paper demonstrates an experimental test bed to enable the realistic evaluation of communications system characteristics for direct transfer trip (DTT) relaying of a photovoltaic inverter system using a private 900-MHz spectrum wireless LTE network. Private LTE network communications can be deployed to many remote DERs and other grid-edge devices to prevent costly infrastructure upgrades across distribution systems. In addition, this paper provides a framework for evaluating the impact of signal strength and network traffic in communications systems. The results shown develop a better understanding of the best practices for using LTE communications systems across multiple utility applications, such as protective relaying, voltage regulation, and supervisory control and data acquisition system messages.

900 MHz LTE network↗
DOE OSTI2021

Experimental Test Bed to Enable Realistic Evaluations for Direct Transfer Trip Relaying via Private Wireless LTE Communications

Increasing penetration levels of inverter-based distributed energy resources (DERs) in distribution systems are creating challenges in system operation. Currently, wired or proprietary wireless communications are used by advanced distribution management systems (ADMS) to detect the state of the system and control the DERs for optimal operation. Wireless communications are an alternative solution that can enable connectivity between the dispersed assets used in distribution system applications. This paper demonstrates an experimental test bed to enable the realistic evaluation of communications system characteristics for direct transfer trip (DTT) relaying of a photovoltaic inverter system using a private 900-MHz spectrum wireless LTE network. Private LTE network communications can be deployed to many remote DERs and other grid-edge devices to prevent costly infrastructure upgrades across distribution systems. In addition, this paper provides a framework for evaluating the impact of signal strength and network traffic in communications systems. The results shown develop a better understanding of the best practices for using LTE communications systems across multiple utility applications, such as protective relaying, voltage regulation, and supervisory control and data acquisition system messages.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗